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Tenax

Q: What are the key properties of Tenax that make it a useful material?

Tenax is a synthetic polymer known for its high thermal and chemical stability, as well as its abrasion resistance. These properties make it a versatile material for use in a variety of applications, such as sorbents, membranes, and reinforcing agents in fields like environmental monitoring, gas chromatography, and composite manufacturing.

Tenax is a synthetic polymer material commonly used in various applications, such as sorbents, membranes, and reinforcing agents.
It is known for its high thermal and chemical stability, as well as its abrasion resistance.
Tenax products are often utilized in fields like environmental monitoring, gas chromatography, and composite manufacturing.
Researchers can leverag AI-driven comparison tools, like those provided by PubCompare.ai, to identify the optimal Tenax products for their specific needs and maximize the reproducibility and accuracy of their studies.

Most cited protocols related to «Tenax»

Construction of Archaeal Clusters of Orthologous Genes

Cited 29 times

Protein sets for 40 completely sequenced genomes of Archaea were downloaded from the NCBI FTP site [55 ] or from the RefSeq section of GenBank (Caldivirga maquilingensis IC-167, Cenarchaeum symbiosum and Uncultured methanogenic archaeon). Protein sequences of Thermoproteus tenax were kindly provided by Bettina Siebers with permission from the sequencing consortium. The procedure of COG construction involved the following steps.
1. All-against-all BLAST [56 (link)] search was used to establish the similarity relationships between the archaeal proteins. Lineage-specific expansions of paralogs were identified essentially as described previously [57 (link),58 (link)]. Initial clusters based on triangles of symmetrical best hits were constructed using a modified COG algorithm [11 (link),13 (link)]; the major difference in the current implementation was the strict symmetry requirement for the "best hit" relationship between proteins. This constraint lowers the number of false-positives but, in the presence of paralogs, leads to substantial underclustering [11 (link)]; this was rectified on the subsequent steps.
2. Multiple alignments of the initial cluster members were constructed using the MUSCLE program [59 (link)]; alignments were used to construct PSSMs for a PSI-BLAST search [56 (link)] against the database of Archaea proteins with the e-value threshold of 0.01; proteins (domains) were added to the corresponding best-scoring original clusters resulting in a set of expanded clusters.
3. Sequences of expanded cluster members were aligned using MUSCLE, and the PSSMs constructed from these alignment were used for a second round of PSI-BLAST search against the database of archaeal proteins. The search results were used to construct a similarity graph for the relationships between the expanded clusters. Formally, all statistically significant (e<0.01) hits in a search with the PSSM for a particular cluster were classified according to the cluster they belong to; clusters in the hit list were ranked according to the mean score across their members (members missing from the hit list were assigned an arbitrary score 2 bits below the significance threshold). An edge between the i-th and the j-th clusters was given weight equal to the lowest rank among the i→j and j→i relationships (i.e., if cluster j is the top-ranking hit when cluster i is the query but cluster i is the third-ranking hit for cluster j, then the edge connecting i and j is given the rank of 3). Connected components were extracted from the graph; pairs of nodes within a connected component were assigned an edge with a rank of infinity if they were not connected directly. A minimum-linkage clustering procedure was applied to the connected sets of clusters (if cluster i and j are merged, the edge between cluster k and the node, representing the merged clusters, is given the rank equal to the lowest rank of k-i and k-j edges), resulting in a rooted dendrogram of relationships between the clusters. Then each node on on the tree was labeled with the number of species that were present in all descendant clusters. Two rules were used to determine if the descendant clusters should be merged: i) if species-coverage of the node is at least 50% greater than that of any of the descendant nodes and ii) if, among the descendants of a node, one is species-rich and the other one is species-poor (formally, if s_i>20s_j/(10-s_j) where s_iand s_jstand for the species-coverage of the species-rich and species-poor descendant nodes, respectively).
4. In parallel to the above procedures, a BLAST search against the COG 2003 database was performed, followed by using a modified COGNITOR program [11 (link),13 (link)] to assign archaeal proteins to prokaryotic COGs. Merged clusters with proteins assigned to different COGs were split into COG-specific clusters to avoid clustering of paralogous proteins that previously have been assigned to different curated COGs.

Makarova K.S., Sorokin A.V., Novichkov P.S., Wolf Y.I, & Koonin E.V. (2007). Clusters of orthologous genes for 41 archaeal genomes and implications for evolutionary genomics of archaea. Biology Direct, 2, 33.

Publication 2007

Amino Acid Sequence Archaea Archaeal Proteins Genome, Archaeal Methanobacteria Muscle Tissue Prokaryotic Cells Proteins Species Specificity tenax Thermoproteus Trees

Purge and Trap ICP-MS Analysis

Cited 11 times

The purge and trap apparatus including a Hg gold trap for scrubbing the He purging gas, gas flowmeter, glass reaction vessels and spargers and Tenax traps and the trap desorption module were purchased from Brooks Rand (Seattle, WA). The GC column was made in-house from a 60 cm quartz tube (6 mm OD) that was heated and shaped to fit in a GC laboratory oven (Model 20, Quincy Lab. Inc., Chicago, IL); the column was silanized and packed with 15% OV3 on Chromosorb. The voltage output from trap desorption module was set to heat the Tenax trap to 200°C within 30 sec, confirmed by thermocouple readout. The GC oven was set at 85-90°C. Either He or He with 100 ppm Xe was used as the carrier gas for the GC at a flow rate of 70 ml min^-1. This set-up is essentially the same as that described initially by Liang et al.(1 (link)). The outflow from the GC was mixed with an Ar stream (using the nebulizer gas supply of the ICP-MS) and then introduced directly into the ICP-MS. The use of a mixed gas (Xe in He) allows certain ICP-MS conditions (XYZ stage position and ‘nebulizer’ gas flow) to be optimized daily with the GC on-line. The ICP-MS was an Element 2 sector field instrument (Thermo Electron, Bremen, Germany) operated in low resolution mode. Instrument operating conditions are given in Table 1. Deadtime correction was performed according to Nelms et al.(11 ) Element specific chromatograms were exported in ASCII format and data processed in Microsoft XL.

Jackson B., Taylor V., Baker R.A, & Miller E. (2009). Low level mercury speciation in freshwaters by isotope dilution GC-ICP-MS. Environmental science & technology, 43(7), 2463-2469.

Publication 2009

Blood Vessel Electrons Flowmeters Gold Nebulizers Quartz tenax

Phoma Phylogeny and Identification Protocol

Cited 7 times

Genomic DNA extraction was performed using the Ultraclean Microbial DNA
isolation kit (Mo Bio Laboratories, Carlsbad, CA, U.S.A.), according to the
instructions of the manufacturer. All DNA extracts were diluted 10 × in
milliQ water and stored at 4 °C before their use as PCR templates.
For nucleotide sequence comparisons fragments of four loci were analysed:
LSU, SSU, ITS, and TUB. Amplification of LSU and SSU was conducted utilising
the primer combination LR0R (Rehner &
Samuels 1994) and LR7
(Vilgalys & Hester 1990 (link))
for LSU sequencing and the primer pair NS1 and NS4
(White et al. 1990 )
for SSU. The PCRs were performed in a 2720 Thermal Cycler (Applied Biosystems,
Foster City, California) in a total volume of 12.5 μL. The PCR mixture
contained 0.5 μL 10 × diluted genomic DNA, 0.2 μM of each primer,
0.5 Unit Taq polymerase E (Genaxxon Bioscience, Germany), 0.04 mM (SSU) or
0.06 mM (LSU) of each of the dNTP, 2 mM MgCl₂ and 1 × PCR
buffer E incomplete (Genaxxon Bioscience). Conditions for amplification for
both regions were an initial denaturation step of 5 min at 94 °C, followed
by 35 cycles of denaturation, annealing and elongation and a final elongation
step of 7 min at 72 °C. For the SSU amplification, the 35 cycles consisted
of 30 s at 94 °C, 50 s at 48 °C and 90 s at 72 °C; for the LSU 45
s at 94 °C, 45 s at 48 °C and 2 min at 72 °C. The loci ITS and TUB
were amplified as described by Aveskamp et al.
(2009a (link)), using the primer
pairs V9G (De Hoog & Gerrits van den
Ende 1998) and ITS4 (White
et al. 1990) for ITS sequencing and the BT2Fw and BT4Rd
primer pair (Aveskamp et al. 2009a) for sequencing of the TUB locus. PCR products were analysed
by electrophoresis in a 1.0 % (w/v) agarose gel containing 0.1 ug/mL ethidium
bromide in 1 × TAE buffer (0.4 M Tris, 0.05 M glacial acetetic acid 0.01
M ethylenediamine tetraacetic acid [EDTA], pH 7.85). The amplicons were
visualised under UV light. Hyperladder I (Bioline, Luckenwalde, Germany) was
applied as size standard.
The obtained amplicons were sequenced in both directions using the same
primer combinations, except for LSU, where an additional primer, LR5
(White et al. 1990 )
was further required to assure complete coverage of the locus. Sequencing
reactions were prepared with the BigDye terminator chemistry v. 3.1 (Applied
Biosystems) according to the manufacturer's recommendations. Sequence products
were purified with Sephadex G-50 Fine (Amersham Biosciences, Roosendaal, the
Netherlands) and subsequently separated and analysed on an ABI Prism 3730 DNA
Sequencer (Applied Biosystems). Consensus sequences were computed from the
forward and reverse sequences using the BioNumerics v. 4.61 software package
(Applied Maths, St-Martens-Latem, Belgium). The consensus sequences are
deposited in GenBank (For GenBank accession numbers see Tables
2,
3).

Table 2.

Isolates of Phoma and related genera used for DNA analyses. The
GenBank accession numbers in bold have been obtained from other studies.

Strain no.¹	Holomorph²	GenBank no.		Original substrate	Locality
		SSU	LSU
CBS 129.79	Ampelomyces quisqualis	EU754029	EU754128	Mildew on Cucumis sativus	Canada
CBS 543.70	Aposphaeria populina	EU754031	EU754130	Populus canadensis	Netherlands
CBS 246.79; PD 77/655	Ascochyta caulina T	EU754032	EU754131	Atriplex hastata	Germany
CBS 544.74	Ascochyta hordei var. hordei	EU754035	EU754134	Triticum aevestum	South Africa
CBS 117477	Ascochyta sp.	GU238202	GU237926	Salicornia australis	New Zealand
CBS 265.94	Asteromella tiliae	EU754040	EU754139	Tilia platyphilos	Austria
CBS 431.74; PD 74/2447	Boeremia exigua var. exigua B	EU754084	EU754183	Solanum tuberosum	Netherlands
CBS 341.67; CECT 20055; IMI 331912	Boeremia foveata B	GU238203	GU237947	Solanum tuberosum	U.K.
CBS 148.94	Chaetasbolisia erysiphoides	EU754041	EU754140	Unknown	Unknown
CBS 216.75; PD 71/1030	Chaetosphaeronema hispidulum	EU754045	EU754144	Anthyllis vulneraria	Germany
CBS 589.79	Coniothyrium concentricum	EU754053	EU754152	Yucca sp.	Netherlands
CBS 797.95	Coniothyrium fuckelii	GU238204	GU237960	Rubus sp.	Denmark
CBS 400.71	Coniothyrium palmarum	EU754054	EU754153	Chamaerops humilis	Italy
CBS 122787; PD 03486691	Coniothyrium sp.	EU754052	EU754151	Unknown	Germany
CBS 183.55	Didymella exigua T	EU754056	EU754155	Rumex arifolius	France
CBS 524.77	Didymella fabae	EU754034	EU754133	Phaseolus vulgaris	Belgium
CBS 581.83A	Didymella rabiei	GU238205	GU237970	Cicer arietinum	Syria
CBS 173.73; ATCC 24428; IMI 164070	Epicoccum nigrum T	GU238206	GU237975	Dactylis glomerata	U.S.A.
CBS 298.36	Leptosphaeria biglobosa	GU238207	GU237980	Brassica napus var. napobrassica	Unknown
CBS 127.23; MUCL 9930	Leptosphaeria maculans	EU754090	EU754189	Brassica sp.	Netherlands
CBS 939.69	Leptosphaerulina australis	EU754068	EU754167	Soil	Netherlands
CBS 525.71	Macroventuria anomochaeta T	GU238208	GU237984	Decayed canvas	South Africa
CBS 442.83	Microsphaeropsis olivacea	EU754072	EU754171	Taxus baccata	Netherlands
CBS 331.37	Neottiosporina paspali	EU754073	EU754172	Paspalum notatum	U.S.A.
CBS 122786; PD 99/1064-1	Paraconiothyrium minitans	EU754075	EU754174	Unknown	Unknown
CBS 626.68; IMI 108771	Peyronellaea gardeniae T	GQ387534	GQ387595	Gardenia jasminoides	India
CBS 528.66; PD 63/590	Peyronellaea glomerata B	EU754085	EU754184	Chrysanthemum sp.	Netherlands
CBS 531.66	Peyronellaea pinodella B	GU238209	GU238017	Trifolium pratense	U.S.A.
CBS 235.55	Peyronellaea pinodes	GU238210	GU238021	Unknown	Netherlands
CBS 588.69	Peyronellaea zeae-maydis T	EU754093	EU754192	Zea mays	U.S.A.
CBS 110110	Phaeosphaeria oryzae	GQ387530	GQ387591	Oryza sativa	South Korea
CBS 297.74	Phialophorophoma litoralis	EU754078	EU754177	Sea water	Montenegro
CBS 285.72	Phoma apiicola B	GU238211	GU238040	Apium graveolens var. rapaceum	Germany
CBS 337.65; ATCC 16195; IMI 113693	Phoma capitulum B	GU238212	GU238054	Soil	India
CBS 522.66	Phoma chrysanthemicola T	GQ387521	GQ387582	Chrysanthemum morifolium	U.K.
CBS 100311	Phoma complanata	EU754082	EU754181	Heracleum sphondylium	Netherlands
CBS 345.78; PD 76/1015	Phoma dimorphospora	GU238213	GU238069	Chenopodium quinoa	Peru
CBS 527.66	Phoma eupyrena B	GU238214	GU238072	Soil	Germany
CBS 161.78	Phoma fallens B	GU238215	GU238074	Olea europaea	New Zealand
CBS 170.70; ATCC 22707; CECT 20011; IMI 163514; PD 70/Alk	Phoma fimeti T	GQ387523	GQ387584	Apium graveolens	Netherlands
CBS 178.93; PD 82/1062	Phoma flavescens T	GU238216	GU238075	Soil	Netherlands
CBS 314.80	Phoma flavigena T	GU238217	GU238076	Water	Romania
CBS 633.92; ATCC 36786; VKM MF-325	Phoma fungicola	EU754028	EU754127	Microsphaera alphitoides on Quercus sp.	Ukraine
CBS 284.70	Phoma glaucispora B	GU238218	GU238078	Nerium oleander	Italy
CBS 175.93; PD 92/370	Phoma haematocycla T	GU238219	GU238080	Phormium tenax	New Zealand
CBS 615.75; PD 73/665, IMI 199779	Phoma herbarum B	EU754087	EU754186	Rosa multiflora	Netherlands
CBS 448.68	Phoma heteromorphospora B	EU754088	EU754187	Chenopodium album	Netherlands
CBS 467.76	Phoma incompta B	GU238220	GU238087	Olea europaea	Greece
CBS 253.92; PD 70/998	Phoma lini B	GU238221	GU238093	Water	U.S.A.
CBS 529.66; PD 66/521	Phoma macrostoma var. macrostoma B	GU238222	GU238098	Malus sylvestris	Netherlands
CBS 316.90	Phoma medicaginis var. medicaginis	GU238223	GU238103	Medicago sativa	Czech Republic
CBS 509.91; PD 77/920	Phoma minutispora	GU238224	GU238108	Saline soil	India
CBS 501.91; PD 83/888	Phoma multipora B	GU238225	GU238109	Unknown	Egypt
CBS 376.91; CBS 328.78, PD 77/1177	Phoma opuntiae B	GU238226	GU238123	Opuntia ficus-indica.	Peru
CBS 560.81; PD 92/1569; PDDCC 6614	Phoma paspali T	GU238227	GU238124	Paspalum dilatatum	New Zealand
CBS 445.81; PDDCC 7049	Phoma pratorum T	GU238228	GU238136	Lolium perenne	New Zealand
CBS 111.79; PD 76/437; IMI 386094	Phoma radicina B	EU754092	EU754191	Malus sylvestris	Netherlands
CBS 138.96; PD 82/653	Phoma samarorum B	GQ387517	GQ387578	Phlox paniculata	Netherlands
CBS 343.85; IMI 386097	Phoma terricola T	GQ387563	GQ387624	Globodera pallida	Netherlands
CBS 630.68; PD 68/141	Phoma valerianae B	GU238229	GU238150	Valeriana phu	Netherlands
CBS 539.63	Phoma vasinfecta T	GU238230	GU238151	Chrysanthemum sp.	Greece
CBS 306.68	Phoma violicola B	GU238231	GU238156	Viola tricolor	Unknown
CBS 523.66; PD 66/270	Pleospora betae B	EU754080	EU754179	Beta vulgaris	Netherlands
CBS 191.86; IMI 276975	Pleospora herbarum T	GU238232	GU238160	Medicago sativa	India
CBS 257.68; IMI 331911	Pleurophoma cava	EU754100	EU754199	Soil	Germany
CBS 398.61; IMI 070678	Pseudorobillarda phragmitis T	EU754104	EU754203	Phragmites australis	U.K.
CBS 122789; PD 03486800	Pyrenochaeta acicola	EU754105	EU754204	Hordeum vulgare	Unknown
CBS 306.65	Pyrenochaeta lycopersici T	EU754106	EU754205	Lycopersicon esculentum	Germany
CBS 407.76	Pyrenochaeta nobilis T	EU754107	EU754206	Laurus nobilis	Italy
CBS 252.60; ATCC 13735	Pyrenochaeta romeroi T	EU754108	EU754209	Man	Venezuela
CBS 524.50	Sporormiella minima	DQ678003	DQ678056	Goat dung	Panama
CBS 343.86	Stagonospora neglecta var. colorata	EU754119	EU754218	Phragmites australis	France
CBS 101.80; PD 75/909; IMI 386090	Stagonosporopsis andigena B	GU238233	GU238169	Solanum sp.	Peru
CBS 133.96; PD 79/127	Stagonosporopsis cucurbitacearum	GU238234	GU238181	Cucurbita sp.	New Zealand
CBS 631.68; PD 68/147	Stagonosporopsis dennisii B	GU238235	GU238182	Solidago floribunda	Netherlands
CBS 164.31	Stenocarpella macrospora	EU754121	EU754220	Zea mays	Unknown

ATCC: American Type Culture Collection, Virginia, U.S.A.; CBS:
Centraalbureau voor Schimmelcultures, Utrecht, The Netherlands; CECT:
Colección Española de Cultivos Tipo, Valencia University, Spain;
IMI: International Mycological Institute, CABI-Bioscience, Egham, Bakeham
Lane, U.K.; MUCL: Mycotheque de l'Universite catholique de Louvain,
Louvain-la-Neuve, Belgium; PD: Plant Protection Service, Wageningen, the
Netherlands; PDDCC: Plant Diseases Division Culture Collection, Auckland, New
Zealand; VKM: All-Russian Collection of Microorganisms, Pushchino, Russia.

T: Ex-type strain; B: Reference strain according to Boerema et al. (2004 ).

Table 3.

Strains from the Didymellaceae used for DNA analyses. The GenBank
accession numbers in bold have been obtained from other studies.

Strain no.1	Holomorph2	GenBank no.			Original substrate	Locality
		LSU	ITS	TUB
CBS 544.74	Ascochyta hordei var. hordei	EU754134	GU237887	GU237488	Triticum aevestum	South Africa
CBS 109.79; PD 77/747	Boeremia crinicola B	GU237927	GU237737	GU237489	Crinum powellii	Netherlands
CBS 118.93; PD 70/195	Boeremia crinicola	GU237928	GU237758	GU237490	Crinum sp.	Netherlands
CBS 101194; PD 79/687; IMI 373349	Boeremia diversispora	GU237929	GU237716	GU237491	Phaseolus vulgaris	Netherlands
CBS 102.80; PD 79/61; CECT 20049; IMI 331907	Boeremia diversispora B	GU237930	GU237725	GU237492	Phaseolus vulgaris	Kenya
CBS 119730	Boeremia exigua var. coffeae	GU237942	GU237759	GU237504	Coffea arabica	Brazil
CBS 109183; IMI 300060; PD 2000/10506	Boeremia exigua var. coffeae B	GU237943	GU237748	GU237505	Coffea arabica	Cameroon
CBS 431.74; PD 74/2447	Boeremia exigua var. exigua B	EU754183	FJ427001	FJ427112	Solanum tuberosum	Netherlands
CBS 101150; PD 79/118	Boeremia exigua var. exigua	GU237933	GU237715	GU237495	Cichorium intybus	Netherlands
CBS 101197; PD 95/721	Boeremia exigua var. forsythiae	GU237931	GU237718	GU237493	Forsythia sp.	Netherlands
CBS 101213; PD 92/959	Boeremia exigua var. forsythiae B	GU237932	GU237723	GU237494	Forsythia sp.	Netherlands
CBS 101196; PD 79/176	Boeremia exigua var. heteromorpha	GU237934	GU237717	GU237496	Nerium oleander	France
CBS 443.94	Boeremia exigua var. heteromorpha B	GU237935	GU237866	GU237497	Nerium oleander	Italy
CBS 569.79; PD 72/741	Boeremia exigua var. lilacis B	GU237936	GU237892	GU237498	Syringa vulgaris	Netherlands
CBS 114.28	Boeremia exigua var. linicola	GU237937	GU237752	GU237499	Linum usitatissimum	Netherlands
CBS 116.76; ATCC 32332; CECT 20022; CECT 20023; IMI 197074	Boeremia exigua var. linicola B	GU237938	GU237754	GU237500	Linum usitatissimum	Netherlands
CBS 100167; PD 93/217	Boeremia exigua var. populi T	GU237939	GU237707	GU237501	Populus (x) euramericana	Netherlands
CBS 101202; PD 82/942	Boeremia exigua var. populi	GU237940	GU237719	GU237502	Salix sp.	Netherlands
CBS 101207; PD 94/614	Boeremia exigua var. pseudolilacis T	GU237941	GU237721	GU237503	Syringa vulgaris	Netherlands
CBS 100354; PD 84/448	Boeremia exigua var. viburni B	GU237944	GU237711	GU237506	Viburnum opulus	Netherlands
CBS 101211; PD 93/838	Boeremia exigua var. viburni	GU237945	GU237722	GU237507	Viburnum sp.	Netherlands
CBS 109176; CECT 2828; PD 94/1394	Boeremia foveata B	GU237946	GU237742	GU237508	Solanum tuberosum	Bulgaria
CBS 341.67; CECT 20055; IMI 331912	Boeremia foveata B	GU237947	GU237834	GU237509	Solanum tuberosum	U.K.
CBS 366.91; PD 70/811	Boeremia hedericola	GU237948	GU237841	GU237510	Hedera helix	Netherlands
CBS 367.91; PD 87/229	Boeremia hedericola B	GU237949	GU237842	GU237511	Hedera helix	Netherlands
CBS 378.67; PD 76/276	Boeremia lycopersici B	GU237950	GU237848	GU237512	Lycopersicon esculentum	Netherlands
CBS 109172; PD 84/143	Boeremia lycopersici	GU237951	GU237739	GU237513	Lycopersicon esculentum	Netherlands
CBS 100353; PD 87/718	Boeremia noackiana B	GU237952	GU237710	GU237514	Phaseolus vulgaris	Guatemala
CBS 101203; PD 79/1114	Boeremia noackiana	GU237953	GU237720	GU237515	Phaseolus vulgaris	Colombia
CBS 109170; PD 75/796	Boeremia sambuci-nigrae	GU237954	GU237738	GU237516	Sambucus nigra	Netherlands
CBS 629.68; CECT 20048; IMI 331913; PD 67/753	Boeremia sambuci-nigrae T	GU237955	GU237897	GU237517	Sambucus nigra	Netherlands
CBS 126.93; PD 73/642	Boeremia strasseri	GU237956	GU237773	GU237518	Mentha sp.	Netherlands
CBS 261.92; ATCC 244146; PD 92/318	Boeremia strasseri	GU237957	GU237812	GU237519	Mentha piperita	U.S.A.
CBS 109175; PD 79/524	Boeremia telephii B	GU237958	GU237741	GU237520	Sedum spectabile	Netherlands
CBS 760.73; PD 71/1616	Boeremia telephii B	GU237959	GU237905	GU237521	Sedum spectabile	Netherlands
CBS 148.94	Chaetasbolisia erysiphoides	EU754140	GU237785	GU237522	Unknown	Unknown
CBS 187.83; PD 82/128	Didymella adianticola B	GU238035	GU237796	GU237576	Polystichum adiantiforme	U.S.A.
CBS 258.92; PD 89/1887	Didymella adianticola	GU238036	GU237811	GU237577	Polystichum adiantiforme	Costa Rica
CBS 102634; PD 75/248	Didymella applanata	GU237997	GU237726	GU237555	Rubus idaeus	Netherlands
CBS 205.63	Didymella applanata T	GU237998	GU237798	GU237556	Rubus idaeus	Netherlands
CBS 234.37	Didymella cannabis	GU237961	GU237804	GU237523	Cannabis sativa	Unknown
CBS 102635; PD 77/1131	Didymella catariae	GU237962	GU237727	GU237524	Nepeta catenaria	Netherlands
CBS 183.55	Didymella exigua T	EU754155	GU237794	GU237525	Rumex arifolius	France
CBS 524.77	Didymella fabae	GU237963	GU237880	GU237526	Phaseolus vulgrais	Belgium
CBS 649.71	Didymella fabae	GU237964	GU237902	GU237527	Vicia faba	Netherlands
PD 83/492	Didymella fabae	GU237965	GU237917	GU237528	Phaseolus vulgaris	Netherlands
PD 84/512	Didymella macropodii	GU237966	GU237919	GU237529	Crucifer	Unknown
CBS 100190; PD 82/736	Didymella macropodii	GU237967	GU237708	GU237530	Brassica napus	Germany
CBS 126.54	Didymella pisi	GU237968	GU237772	GU237531	Pisum sativum	Netherlands
CBS 122785; PD 78/517	Didymella pisi	GU237969	GU237763	GU237532	Pisum sativum	Netherlands
CBS 534.65	Didymella rabiei	GU237970	GU237886	GU237533	Cicer arietinum	India
CBS 581.83a	Didymella rabiei	GU237971	GU237894	GU237534	Cicer arietinum	Syria
CBS 121.75; ATCC 32164; IHEM 3403; IMI 194767; PD 73/584	Didymella urticicola T	GU237972	GU237761	GU237535	Urtica dioica	Netherlands
PD 73/570	Didymella urticicola	GU237973	GU237914	GU237536	Urtica dioica	Netherlands
CBS 454.64	Didymella vitalbina	FJ515646	FJ515605	FJ515623	Clematis vitalba	France
CBS 138.25	Diplodina coloradensis	EU754158	GU237784	GU237537	Senecio sp.	Unknown
CBS 172.34	“Dothiorella ulmi”	EU754160	GU237789	GU237538	Ulmus sp.	U.S.A.
CBS 125.82; IMI 1331914; CECT 20044	Epicoccum nigrum	GU237974	FJ426995	FJ427106	Human	Netherlands
CBS 173.73; ATCC 24428; IMI 164070	Epicoccum nigrum T	GU237975	FJ426996	FJ427107	Dactylis glomerata	U.S.A.
CBS 246.60; ATCC 22237; ATCC 16652; IMI 081601	Epicoccum pimprinum T	GU237976	FJ427049	FJ427159	Soil	India
PD 77/1028	Epicoccum pimprinum	GU237977	FJ427050	FJ427160	Unknown	Unknown
CBS 179.80; PD 76/1018	Epicoccum sorghi	GU237978	FJ427067	FJ427173	Sorghum vulgare	Puerto Rico
CBS 627.68; PD 66/926	Epicoccum sorghi	GU237979	FJ427072	FJ427178	Citrus sp.	France
CBS 213.55	Leptosphaerulina americana	GU237981	GU237799	GU237539	Trifolium pretense	U.S.A.
CBS 275.59; ATCC 13446	Leptosphaerulina arachidicola	GU237983	GU237820	GU237543	Arachis hypochea	Taiwan
CBS 317.83	Leptosphaerulina australis	EU754166	GU237829	GU237540	Eugenia aromatica	Indonesia
CBS 939.69	Leptosphaerulina australis	EU754167	GU237911	GU237541	Soil	Netherlands
CBS 235.58	Leptosphaerulina trifolii	GU237982	GU237806	GU237542	Trifolium sp.	Netherlands
CBS 525.71	Macroventuria anomochaeta T	GU237984	GU237881	GU237544	decayed canvas	South Africa
CBS 502.72	Macroventuria anomochaeta	GU237985	GU237873	GU237545	Medicago sativa	South Africa
CBS 526.71	Macroventuria wentii	GU237986	GU237881	GU237546	Unidentified plant material	U.S.A.
CBS 432.71	Microsphaeropsis olivacea	GU237987	GU237863	GU237548	Sorothamus sp.	Netherlands
CBS 233.77	Microsphaeropsis olivacea	GU237988	GU237803	GU237549	Pinus laricio	France
CBS 442.83	Microsphaeropsis olivacea	EU754171	GU237865	GU237547	Taxus baccata	Netherlands
CBS 132.96; PD 93/853	Peyronellaea alectorolophi T	GU237989	GU237778	GU237550	Rhinanthus major	Netherlands
CBS 185.85; PD 80/1191	Peyronellaea americana B	GU237990	FJ426972	FJ427088	Zea mays	U.S.A.
CBS 568.97; PD 94/1544; ATCC 44494	Peyronellaea americana	GU237991	FJ426974	FJ427090	Glycine max	U.S.A.
PD 82/1059	Peyronellaea americana	GU237992	FJ426980	FJ427096	Nematode cyst	Unknown
CBS 360.84	Peyronellaea anserina B	GU237993	GU237839	GU237551	Potatoflour	Netherlands
CBS 363.91; PD 79/712	Peyronellaea anserina	GU237994	GU237840	GU237552	Pisum sativum	Netherlands
CBS 315.90; PD 80/1190	Peyronellaea arachidicola	GU237995	GU237827	GU237553	Arachis hypogaea	Zimbabwe
CBS 333.75; ATCC 28333; IMI 386092; PREM 44889	Peyronellaea arachidicola T	GU237996	GU237833	GU237554	Arachis hypogaea	South Africa
CBS 269.93; PD 78/1087	Peyronellaea aurea B	GU237999	GU237818	GU237557	Medicago polymorpha	New Zealand
CBS 444.81; PDDCC 6546	Peyronellaea australis T	GU238000	GU237867	GU237558	Actinidia chinensis	New Zealand
PD 77/919	Peyronellaea australis	GU238001	GU237915	GU237559	Actinidea chinensis	Unknown
CBS 109.92; PD 73/1405	Peyronellaea calorpreferens T	GU238002	FJ426983	FJ427098	Undefined food material	Netherlands
CBS 630.97; ATCC 96683; IMI 361196; PD 96/2022	Peyronellaea calorpreferens	GU238004	GU237925	GU237560	Heterodera glycines	U.S.A.
CBS 875.97; PD 93/1503	Peyronellaea calorpreferens	GU238003	GU237908	GU237561	Indoor environment	U.S.A.
CBS 123380; PD 84/1013	Peyronellaea coffeae-arabicae T	GU238005	FJ426993	FJ427104	Coffea arabica	Ethiopia
CBS 123398; PD 84/1014	Peyronellaea coffeae-arabicae	GU238006	FJ426994	FJ427105	Coffea arabica	Ethiopia
PD 92/1460	Peyronellaea curtisii	GU238012	FJ427041	FJ427151	Sprekelia	Netherlands
CBS 251.92; PD 86/1145	Peyronellaea curtisii B	GU238013	FJ427038	FJ427148	Nerine sp.	Netherlands
CBS 377.91; PD 79/210	Peyronellaea eucalyptica B	GU238007	GU237846	GU237562	Eucalyptus sp.	Australia
CBS 508.91; PD 73/1413	Peyronellaea eucalyptica	GU238008	GU237878	GU237563	Water	Croatia
CBS 302.79; PD 79/1156	Peyronellaea gardeniae	GQ387596	FJ427002	FJ427113	Air	Netherlands Antilles
CBS 626.68; IMI 108771	Peyronellaea gardeniae T	GQ387595	FJ427003	FJ427114	Gardenia jasminoides	India
CBS 464.97; MUCL 9882	Peyronellaea glomerata	GU238009	FJ427012	FJ427123	Indoor environment	Netherlands
CBS 528.66; PD 63/590	Peyronellaea glomerata B	EU754184	FJ427013	FJ427124	Chrysanthemum sp.	Netherlands
CBS 103.25	Peyronellaea lethalis	GU238010	GU237729	GU237564	Unknown	Unknown
CBS 463.69	Peyronellaea musae B	GU238011	FJ427026	FJ427136	Mangifera indica	India
CBS 377.93; PD 80/976	Peyronellaea obtusa B	GU238014	GU237847	GU237565	Daucus carota	Netherlands
CBS 391.93; PD 80/87	Peyronellaea obtusa B	GU238015	GU237858	GU237566	Spinacia oleracea	Netherlands
CBS 318.90; PD 81/729	Peyronellaea pinodella	GU238016	FJ427051	FJ427161	Pisum sativum	Netherlands
CBS 531.66	Peyronellaea pinodella B	GU238017	FJ427052	FJ427162	Trifolium pratense	U.S.A.
CBS 100580; PD 98/1135	Peyronellaea pinodella	GU238018	GU237713	GU237567	Glycine max	Hungary
CBS 567.97; PD 97/2160	Peyronellaea pinodella	GU238019	GU237891	GU237568	Glycine max	Hungary
CBS 159.78b	Peyronellaea pinodes	GU238020	GU237786	GU237569	Pisum sativum	Iraq
CBS 285.49	Peyronellaea pinodes	GU238022	GU237823	GU237571	Primula auricula	Switzerland
CBS 235.55	Peyronellaea pinodes	GU238021	GU237805	GU237570	Unknown	Netherlands
CBS 525.77	Peyronellaea pinodes	GU238023	GU237883	GU237572	Pisum sativum	Belgium
CBS 525.77a	Peyronellaea pinodes	GU238024	GU237882	GU237573	Pisum sativum	Belgium
CBS 539.66; ATCC 16791; IMI 122266; PD 64/914	Peyronellaea pomorum var. pomorum B	GU238028	FJ427056	FJ427166	Polygonum tataricum	Netherlands
CBS 285.76; ATCC 26241; IMI 176742; VKM F-1843	Peyronellaea pomorum var. circinata T	GU238025	FJ427053	FJ427163	Heracleum dissectum	Russia
CBS 286.76; ATCC 26242; IMI 176743; VKM F-1844	Peyronellaea pomorum var. circinata	GU238026	FJ427054	FJ427164	Allium nutans	Russia
CBS 388.80; PREM 45736	Peyronellaea pomorum var. cyanea T	GU238027	FJ427055	FJ427165	Triticum sp.	South Africa
CBS 381.96; PD 71/706	Peyronellaea protuberans B	GU238029	GU237853	GU237574	Lycium halifolium	Netherlands
CBS 281.83	Peyronellaea sancta T	GU238030	FJ427063	FJ427170	Ailanthus altissima	South Africa
LEV 15292	Peyronellaea sancta	GU238031	FJ427065	FJ427172	Gleditsia triacantha	Unknown
CBS 110.92; PD 76/1010	Peyronellaea subglomerata B	GU238032	FJ427080	FJ427186	Triticum sp.	U.S.A.
PD 78/1090	Peyronellaea subglomerata	GU238033	FJ427081	FJ427187	Zea mays	Unknown
CBS 588.69	Peyronellaea zeae-maydis T	EU754186	FJ427086	FJ427190	Zea mays	U.S.A.
CBS 179.97	Phoma acetosellae	GU238034	GU237793	GU237575	Rumex hydrolapathum	Netherlands
CBS 379.93; PD 82/945	Phoma aliena	GU238037	GU237851	GU237578	Berberis sp.	Netherlands
CBS 877.97; PD 94/1401	Phoma aliena	GU238038	GU237910	GU237579	Buxus sempervirens	Netherlands
CBS 381.91; PD 79/1110	Phoma anigozanthi B	GU238039	GU237852	GU237580	Anigozanthus maugleisii	Netherlands
CBS 107.96; PD 73/598	Phoma aquilegiicola B	GU238041	GU237735	GU237582	Aconitum pyramidale	Netherlands
CBS 108.96; PD 79/611	Phoma aquilegiicola B	GU238042	GU237736	GU237583	Aquilegia sp.	Netherlands
CBS 125.93; PD 77/1029	Phoma arachidis-hypogaeae B	GU238043	GU237771	GU237584	Arachis hypogaea	India
CBS 383.67; PD 65/223	Phoma aubrietiae B	GU238044	GU237854	GU237585	Aubrietia hybrida cv. Superbissima	Netherlands
CBS 627.97; PD 70/714	Phoma aubrietiae B	GU238045	GU237895	GU237586	Aubrietia sp.	Netherlands
CBS 714.85; PD 74/265	Phoma bellidis B	GU238046	GU237904	GU237587	Bellis perennis	Netherlands
PD 94/886	Phoma bellidis	GU238047	GU237923	GU237581	Bellis sp.	Netherlands
CBS 109942; PD 84/402	Phoma boeremae T	GU238048	FJ426982	FJ427097	Medicago littoralis cv. Harbinger	Australia
CBS 120105	Phoma brasiliensis T	GU238049	GU237760	GU237588	Amaranthus sp.	Brazil
CBS 357.84	Phoma bulgarica T	GU238050	GU237837	GU237589	Trachystemon orientale	Bulgaria
CBS 124515; PD 82/1058	Phoma bulgarica	GU238051	GU237768	GU237590	Trachystemon orientale	Bulgaria
CBS 448.83	Phoma calidophila T	GU238052	FJ427059	FJ427168	Soil	Egypt
PD 84/109	Phoma calidophila	GU238053	FJ427060	FJ427169	Cucumis sativus	Europe
CBS 128.93; PD 79/140	Phoma chenopodiicola B	GU238055	GU237775	GU237591	Chenopodium quinoa cv. Sajana	Peru
CBS 129.93; PD 89/803	Phoma chenopodiicola	GU238056	GU237776	GU237592	Chenopodium quinoa cv. Sajana	Peru
CBS 102.66	Phoma clematidina	FJ515630	FJ426988	FJ427099	Clematis sp.	U.K.
CBS 108.79; PD 78/522	Phoma clematidina T	FJ515632	FJ426989	FJ427100	Clematis sp.	Netherlands
CBS 507.63; MUCL 9574; PD 07/03486747	Phoma clematidis-rectae T	FJ515647	FJ515606	FJ515624	Clematis sp.	Netherlands
PD 95/1958	Phoma clematidis-rectae	FJ515648	FJ515607	FJ515625	Clematis sp.	Netherlands
CBS 100409	Phoma commelinicicola B	GU238057	GU237712	GU237593	Tradescantia sp.	New Zealand
CBS 100311	Phoma complanata	EU754181	GU237709	GU237594	Heracleum sphondylium	Netherlands
CBS 268.92; PD 75/3	Phoma complanata	EU754180	GU237815	GU237595	Angelica sylvestris	Netherlands
CBS 506.91; IMI 215229; PD 91/876	Phoma costarricensis B	GU238058	GU237876	GU237596	Coffea sp.	Nicaragua
CBS 497.91; PD 79/209	Phoma costarricensis	GU238059	GU237870	GU237597	Coffea arabica	Unknown
CBS 193.82	Phoma crystallifera T	GU238060	GU237797	GU237598	Chamaespartium sagittale	Austria
CBS 124513; PD 73/1414	Phoma dactylidis T	GU238061	GU237766	GU237599	Dactylis glomerata	U.S.A.
CBS 133.93; PD 88/961; IMI 173142	Phoma destructiva var. destructiva	GU238064	GU237779	GU237602	Solanum lycopersicum	Guadeloupe
CBS 378.73; CECT 2877	Phoma destructiva var. destructiva B	GU238063	GU237849	GU237601	Lycopersicon esculentum	Tonga
CBS 162.78; PD 77/725	Phoma destructiva var. diversispora	GU238062	GU237788	GU237600	Lycopersicon esculentum	Netherlands
CBS 507.91; PD 74/148	Phoma dictamnicola B	GU238065	GU237877	GU237603	Dictamnus albus	Netherlands
CBS 109179; PD 90/835-1	Phoma digitalis	GU238066	GU237744	GU237604	Digitalis sp.	Netherlands
CBS 229.79; LEV 7660	Phoma digitalis B	GU238067	GU237802	GU237605	Digitalis purpurea	New Zealand
CBS 346.82	Phoma dimorpha T	GU238068	GU237835	GU237606	Opuntiae sp.	Spain
CBS 186.83; PD 82/47	Phoma draconis B	GU238070	GU237795	GU237607	Dracaena sp.	Rwanda
CBS 123.93; PD 77/1148	Phoma eupatorii B	GU238071	GU237764	GU237608	Eupatorium cannabinum	Netherlands
CBS 374.91; PD 78/391	Phoma eupyrena B	GU238072	FJ426999	FJ427110	Solanum tuberosum	Netherlands
CBS 527.66; ATCC 22238	Phoma eupyrena B	GU238073	FJ427000	FJ427111	Soil	Germany
CBS 633.92; ATCC 36786; VKM MF-325	Phoma fungicola	EU754127	GU237900	GU237609	Microsphaera alphitoides on Quercus sp.	Ukraine
CBS 112.96	Phoma glaucii	GU238077	GU237750	GU237610	Dicentra sp.	Netherlands
CBS 114.96; PD 94/888	Phoma glaucii B	FJ515649	FJ515609	FJ515627	Chelidonium majus	Netherlands
CBS 377.67	Phoma gossypiicola B	GU238079	GU237845	GU237611	Gossypium hirsutum	U.S.A.
CBS 104.80; PD 74/1017	Phoma henningsii B	GU238081	GU237731	GU237612	Acacia mearnesii	Kenya
CBS 502.91; PD 86/276	Phoma herbarum	GU238082	GU237874	GU237613	Nerium sp.	Netherlands
CBS 615.75; PD 73/665; IMI 199779	Phoma herbarum B	EU880896	FJ427022	FJ427133	Rosa multiflora	Netherlands
CBS 629.97; PD 76/1017	Phoma herbicola B	GU238083	GU237898	GU237614	Water	U.S.A.
CBS 105.80; PD 75/908	Phoma huancayensis T	GU238084	GU237732	GU237615	Solanum sp.	Peru
CBS 390.93; PD 77/1173	Phoma huancayensis	GU238085	GU237857	GU237616	Chenopodium quinoa	Peru
CBS 220.85	Phoma humicola B	GU238086	GU237800	GU237617	Franseria sp.	U.S.A.
CBS 123394	Phoma infossa	GU238088	FJ427024	FJ427134	Fraxinus pennsylvanica	Argentina
CBS 123395	Phoma infossa T	GU238089	FJ427025	FJ427135	Fraxinus pennsylvanica	Argentina
CBS 252.92; PD 80/1144	Phoma insulana B	GU238090	GU237810	GU237618	Olea europaea	Greece
CBS 124.93; PD 87/269	Phoma labilis B	GU238091	GU237765	GU237619	Solanum lycopersicum	Netherlands
CBS 479.93; PD 70/93	Phoma labilis	GU238092	GU237868	GU237620	Rosa sp.	Israel
CBS 347.82	Phoma longicolla	GU238094	GU237836	GU237621	Opuntiae sp.	Spain
CBS 124514; PD 80/1189; VPRI 1239	Phoma longicolla T	GU238095	GU237767	GU237622	Opuntiae sp.	Spain
CBS 223.69	Phoma macrostoma var. incolorata B	GU238096	GU237801	GU237623	Acer pseudoplatanus	Switzerland
CBS 109173; PD 83/908	Phoma macrostoma var. incolorata B	GU238097	GU237740	GU237624	Malus sylvestris	Netherlands
CBS 529.66; PD 66/521	Phoma macrostoma var. macrostoma B	GU238098	GU237885	GU237625	Malus sylvestris	Netherlands
CBS 482.95	Phoma macrostoma var. macrostoma	GU238099	GU237869	GU237626	Larix decidua	Germany
CBS 259.92; IMI 286996; PD 91/272	Phoma matteuciicola B	GU238100	GU237812	GU237627	Matteuccia struthiopteris	Canada
CBS 112.53	Phoma medicaginis var. macrospora B	GU238101	GU237749	GU237628	Medicago sativa	U.S.A.
CBS 404.65; IMI 116999	Phoma medicaginis var. macrospora B	GU238102	GU237859	GU237629	Medicago sativa	Canada
CBS 316.90	Phoma medicaginis var. medicaginis	GU238103	GU237828	GU237630	Medicago sativa	Czech Republic
CBS 105.95	Phoma microchlamydospora T	GU238104	FJ427028	FJ427138	Eucalyptus sp.	U.K.
CBS 491.90	Phoma microchlamydospora	GU238105	FJ427029	FJ427139	Unidentified vegetable	U.K.
CBS 315.83	Phoma minor	GU238106	GU237826	GU237631	Syzygium aromaticum	Indonesia
CBS 325.82	Phoma minor T	GU238107	GU237831	GU237632	Syzygium aromaticum	Indonesia
CBS 110.79; PD 65/8875; MUCL 8247	Phoma multirostrata	GU238110	FJ427030	FJ427140	Cucumis sativus	Netherlands
CBS 274.60; IMI 081598	Phoma multirostrata T	GU238111	FJ427031	FJ427141	Soil	India
CBS 368.65; PD 92/1757; HACC 154	Phoma multirostrata	GU238112	FJ427033	FJ427143	Soil	India
PD 83/48	Phoma multirostrata	GU238113	FJ427037	FJ427147	Cucumis sativus	Unknown
CBS 117.93; PD 83/90	Phoma nebulosa	GU238114	GU237757	GU237633	Mercurialis perennis	Netherlands
CBS 503.75; ATCC 32163; DSM 63391; IMI 194766; PD 75/4	Phoma nebulosa B	GU238115	GU237875	GU237634	Urtica dioica	Austria
CBS 358.71	Phoma negriana B	GU238116	GU237838	GU237635	Vitis vinifera	Germany
PD 79/74	Phoma negriana	GU238117	GU237916	GU237636	Vitis vinifera	Netherlands
CBS 116.96; PD 95/7930	Phoma nigripycnidia B	GU238118	GU237756	GU237637	Vicia cracca	Russia
CBS 114.93; PD 74/228	Phoma novae- verbascicola	GU238119	GU237753	GU237638	Verbascum sp.	Netherlands
CBS 127.93; PD 92/347	Phoma novae-verbascicola B	GU238120	GU237774	GU237639	Verbascum densiflorum	Netherlands
CBS 654.77	Phoma omnivirens	GU238122	FJ427043	FJ427153	Unknown	India
CBS 991.95	Phoma omnivirens	GU238121	FJ427044	FJ427154	Soil	Papua New Guinea
CBS 560.81; PD 92/1569; PDDCC 6614	Phoma paspali T	GU238124	FJ427048	FJ427158	Paspalum dilatatum	New Zealand
CBS 561.81; PDDCC 6615	Phoma paspali	GU238125	GU237889	GU237640	Lolium perenne	New Zealand
CBS 124516; PD 84/453	Phoma pedeiae	GU238126	GU237769	GU237641	Orchidaceae	Netherlands
CBS 124517; PD 92/612A	Phoma pedeiae T	GU238127	GU237770	GU237642	Schefflera elegantissima	Netherlands
CBS 267.92; PD 76/1014	Phoma pereupyrena T	GU238128	GU237814	GU237643	Coffea arabica	India
CBS 268.93; CBS 108.93; PD 88/720	Phoma piperis B	GU238129	GU237816	GU237644	Peperomia pereskifolia	Netherlands
PD 90/2011	Phoma piperis	GU238130	GU237921	GU237645	Peperomia sp.	Netherlands
CBS 284.93; PD 75/907	Phoma plurivora	GU238131	GU237822	GU237646	Medicago sativa	Australia
CBS 558.81; PDDCC 6873	Phoma plurivora T	GU238132	GU237888	GU237647	Setaria sp.	New Zealand
CBS 109181; PD 83/757	Phoma polemonii B	GU238133	GU237746	GU237648	Polemonium caeruleum	Netherlands
CBS 116.93; PD 71/884	Phoma poolensis B	GU238134	GU237755	GU237649	Antirrhinum majus	Netherlands
CBS 113.20; PD 92/774	Phoma poolensis	GU238135	GU237751	GU237650	Unknown	Unknown
CBS 372.91; PD 75/690	Phoma putaminum B	GU238137	GU237843	GU237651	Ulmus sp.	Netherlands
CBS 130.69; CECT 20054; IMI 331916	Phoma putaminum B	GU238138	GU237777	GU237652	Malus sylvestris	Denmark
CBS 109177; LEV 15165; PD 2000/9941	Phoma rhei B	GU238139	GU237743	GU237653	Rheum rhaponticum	New Zealand
CBS 298.89	Phoma saxea	GU238140	GU237824	GU237654	Limestone	Germany
CBS 419.92	Phoma saxea T	GU238141	GU237860	GU237655	Corroded mediterranean marble	Germany
CBS 122.93; PD 77/1049	Phoma selaginellicola B	GU238142	GU237762	GU237656	Selaginella sp.	Netherlands
CBS 160.78; LEV 11451	Phoma senecionis B	GU238143	GU237787	GU237657	Senecio jacobaea	New Zealand
CBS 249.92; PD 78/1088	Phoma subherbarum	GU238144	GU237808	GU237658	Solanum sp.	Peru
CBS 250.92; DAOM 171914; PD 92/371	Phoma subherbarum B	GU238145	GU237809	GU237659	Solanum sp.	Peru
CBS 305.79A; DAOM 170848	Phoma subherbarum	GU238146	GU237825	GU237660	Zea mays	Peru
CBS 135.93; PD 83/87	Phoma sylvatica B	GU238147	GU237781	GU237661	Melampyrum pratense	Netherlands
CBS 874.97; PD 93/764	Phoma sylvatica B	GU238148	GU237907	GU237662	Melampyrum pratense	Netherlands
CBS 436.75	Phoma tropica T	GU238149	GU237864	GU237663	Saintpaulia ionantha	Germany
CBS 876.97; PD 82/1008	Phoma versabilis B	GU238152	GU237909	GU237664	Silene sp.	Netherlands
PD 2000/1379	Phoma versabilis	GU238153	GU237913	GU237665	Stellaria media	Netherlands
CBS 500.91; PD 83/322	Phoma viburnicola B	GU238154	GU237871	GU237666	Ilex aquifolium	Netherlands
CBS 523.73; PD 69/800	Phoma viburnicola B	GU238155	GU237879	GU237667	Viburnum cassioides	Netherlands
CBS 383.68	Phoma xanthina B	GU238157	GU237855	GU237668	Delphinium sp.	Netherlands
PD 84/407	Phoma xanthina	GU238158	GU237918	GU237669	Delphinium sp.	Netherlands
CBS 131.93; PD 69/140	Phoma zantedeschiae	GU238159	FJ427084	FJ427188	Calla sp.	Netherlands
CBS 105.96; PD 74/230	Stagonosporopsis actaeae B	GU238165	GU237733	GU237670	Cimicifuga simplex	Netherlands
CBS 106.96; PD 94/1318	Stagonosporopsis actaeae T	GU238166	GU237734	GU237671	Actaea spicata	Netherlands
CBS 176.93; PD 86/547	Stagonosporopsis ajacis	GU238167	GU237790	GU237672	Delphinium sp.	Netherlands
CBS 177.93; PD 90/115	Stagonosporopsis ajacis T	GU238168	GU237791	GU237673	Delphinium sp.	Kenya
CBS 101.80; PD 75/909; IMI 386090	Stagonosporopsis andigena B	GU238169	GU237714	GU237674	Solanum sp.	Peru
CBS 269.80; PD 75/914	Stagonosporopsis andigena	GU238170	GU237817	GU237675	Solanum sp.	Peru
CBS 102636; PD 73/1409	Stagonosporopsis artemisiicola B	GU238171	GU237728	GU237676	Artemisia dracunculus	France
CBS 178.25; MUCL 9915	Stagonosporopsis astragali B	GU238172	GU237792	GU237677	Astragalus sp.	Unknown
CBS 248.90	Stagonosporopsis caricae	GU238175	GU237807	GU237680	Carica papaya	Chile
PD 06/03082531	Stagonosporopsis caricae	GU238176	GU237912	GU237681	Carica papaya	Brazil
CBS 282.76	Stagonosporopsis caricae	GU238177	GU237821	GU237682	Brassica sp.	Indonesia
CBS 713.85; ATCC 76027; PD 83/826	Stagonosporopsis crystalliniformis T	GU238178	GU237903	GU237683	Lycopersicon esculentum	Colombia
CBS 771.85; IMI 386091; PD 85/772	Stagonosporopsis crystalliniformis	GU238179	GU237906	GU237684	Solanum tuberosum	Colombia
CBS 109171; PD 91/310; PDDCC 272	Stagonosporopsis cucurbitacearum	GU238180	GU237922	GU237685	Cucurbita sp.	Netherlands
CBS 133.96; PD 79/127	Stagonosporopsis cucurbitacearum	GU238181	GU237780	GU237686	Cucurbita sp.	New Zealand
CBS 631.68; PD 68/147	Stagonosporopsis dennisii B	GU238182	GU237899	GU237687	Solidago floribunda	Netherlands
CBS 135.96; IMI 19337; PD 95/4756	Stagonosporopsis dennisii	GU238183	GU237782	GU237688	Solidago canadensis	Canada
CBS 320.90; PD 86/932	Stagonosporopsis dorenboschii B	GU238184	GU237830	GU237689	Physostegia virginiana	Netherlands
CBS 426.90; IMI 386093; PD 86/551	Stagonosporopsis dorenboschii T	GU238185	GU237862	GU237690	Physostegia virginiana	Netherlands
CBS 109182; PD 74/231	Stagonosporopsis heliopsidis B	GU238186	GU237747	GU237691	Heliopsis patula	Netherlands
PD 95/6189; DAOM 221138	Stagonosporopsis heliopsidis	GU238187	GU237924	GU237692	Ambrosia artemisiifolia	Canada
CBS 104.42	Stagonosporopsis hortensis B	GU238198	GU237730	GU237703	Unknown	Netherlands
CBS 572.85; PD 79/269	Stagonosporopsis hortensis B	GU238199	GU237893	GU237704	Phaseolus vulgaris	Netherlands
CBS 425.90; PD 81/520	Stagonosporopsis ligulicola var. inoxydabilis T	GU238188	GU237861	GU237693	Chrysanthemum parthenii	Netherlands
PD 85/259	Stagonosporopsis ligulicola var. inoxydabilis	GU238189	GU237920	GU237694	Matricaria sp.	Netherlands
CBS 500.63; MUCL 8090	Stagonosporopsis ligulicola var. ligulicola B	GU238190	GU237872	GU237695	Chrysanthemum indicum	Germany
CBS 137.96; PD 84/75	Stagonosporopsis ligulicola var. ligulicola B	GU238191	GU237783	GU237696	Chrysanthemum indicum	Netherlands
CBS 562.81; PDDCC 6884	Stagonosporopsis loticola T	GU238192	GU237890	GU237697	Lotus pedunculatus	New Zealand
CBS 628.97; PD 79/72; PDDCC 3870	Stagonosporopsis loticola	GU238193	GU237896	GU237698	Lotus tenuis	New Zealand
CBS 101494; PD 98/5247	Stagonosporopsis lupini B	GU238194	GU237724	GU237699	Lupinus albus	U.K.
CBS 375.84; PD 80/1250	Stagonosporopsis lupini	GU238195	GU237844	GU237700	Lupinus mutabilis	Peru
CBS 634.92; IMI 193307	Stagonosporopsis oculo-hominis T	GU238196	GU237901	GU237701	Human	U.S.A.
CBS 109180; PD 79/175	Stagonosporopsis rudbeckiae B	GU238197	GU237745	GU237702	Rudbeckia bicolor	Netherlands
CBS 379.91; PD 77/675	Stagonosporopsis trachelii B	GU238173	GU237850	GU237678	Campanula isophylla	Netherlands
CBS 384.68	Stagonosporopsis trachelii B	GU238174	GU237856	GU237679	Campanula isophylla	Sweden
CBS 273.92; PD 76/1019	Stagonosporopsis valerianellae	GU238200	GU237819	GU237705	Valerianella locusta	Netherlands
CBS 329.67; PD 66/302	Stagonosporopsis valerianellae B	GU238201	GU237832	GU237706	Valerianella locusta var. oleracea	Netherlands

ATCC: American Type Culture Collection, Virginia, U.S.A.; CBS:
Centraalbureau voor Schimmelcultures, Utrecht, The Netherlands; CECT:
Colección Española de Cultivos Tipo, Valencia University, Spain;
DAOM: Canadian Collection of Fungal Cultures, Ottawa, Canada; DSM: Deutsche
Sammlung von Mikroorganismen und Zellkulturen GmbH, Braunschweig, Germany;
HACC: Research Laboratory, Hindustan Antibiotics Ltd., Pimpri Poona, India;
IMI: International Mycological Institute, CABI-Bioscience, Egham, Bakeham
Lane, U.K.; LEV: Plant Health and Diagnostic Station, Auckland, New Zealand;
MUCL: Mycotheque de l'Universite catholique de Louvain, Louvain-la-Neuve,
Belgium; PD: Plant Protection Service, Wageningen, the Netherlands; PDDCC:
Plant Diseases Division Culture Collection, Auckland, New Zealand; PREM:
National Collection of Fungi: Culture Collection, Pretoria, South Africa; VKM:
All-Russian Collection of Microorganisms, Pushchino, Russia; VPRI: Victorian
Plant Disease Herbarium, Victoria, Australia.

T: Ex-type strain; B: Reference strain according to Boerema et al. (2004 ).

Obtained consensus sequences were assembled and aligned using the same
BioNumerics software and adjusted manually where necessary. As SSU was highly
conserved in deeper node phylogenies, revealing almost no phylogenetic
informative nuclear polymorphisms, and as ITS and TUB proved to be unalignable
due to a high level of polymorphism if all taxa studied would be taken into
account, it was decided to conduct two separate analyses. The first analysis
comprised SSU and LSU loci, and was applied to 76 taxa of which most species
included belonged to genera that were often confused with Phoma (Sutton 1980 ,
De Gruyter et al. 2009). A second set of analyses was conducted on 274 taxa, and
focussed on the species that had proven to be related to the
Didymellaceae from preliminary studies.
Each of the phylogenetic analyses consisted of two methods: Bayesian
Interference (BI) and Maximum Likelihood (ML). For BI analysis, the nucleotide
substitution models were determined for each locus separately with MrModeltest
v. 2.2 (Nylander 2004 ).
According to this software, the General Time Reversible substitution was
determined to be the best model for SSU, TUB and LSU in both data sets, with
inverse gamma rates and dirichlet base frequencies (GTR + I + G). For the ITS
dataset, the software suggested the Symmetrical Model as the best model for
substitution of nucleotides. Also in this locus, the inverse gamma rates and
dirichlet base frequencies were used (SYM + I + G). The actual Bayesian
calculations were performed in MrBayes v. 3.1.2
(Huelsenbeck & Ronquist
2001). One tree was saved per 100 generations, and the run was
automatically ended when the standard deviation of split frequencies was below
0.01. The temperature value of the Bayesian run was set at 0.2. To avoid
suboptimal trees being taking into account for the consensus tree, a burn-in
of 25 % of the saved trees was used. The resulting “50 % majority rule
consensus” trees were visualised with TreeView v. 1.6.6
(Page 1996 (link)).
A second measure of branch support was obtained by conducting a ML analysis
using RAxML software (Stamatakis et
al. 2005) through the CIPRES Website
(www.phylo.org).
The same partitions were used as in the BI analyses, but because RAxML
implements only the GTR substitution model, the symmetrical model for the ITS
partition was waived. The robustness of trees in the ML analyses was evaluated
by bootstrapping the datasets. The number of bootstrap replicates was
automatically determined by the RAxML software
(Stamatakis et al. 2008). The obtained trees in both analyses are lodged with
TreeBASE
(www.treebase.org).

Aveskamp M.M., de Gruyter J., Woudenberg J.H., Verkley G.J, & Crous P.W. (2010). Highlights of the Didymellaceae: A polyphasic approach to characterise Phoma and related pleosporalean genera. Studies in Mycology, 65, 1-60.

Publication 2010

Analysis of Chlorinated Solvents and Gases

Cited 5 times

Concentrations of TCE, cis-DCE and VC were measured using 8610GC instrument with purge-trap system (SRI, USA), photoionization detector and MXT-VOL stationary column. The purge-trap autosampler was equipped with carbon-sieve trap and Tenax^™ trap, allowing the detection of highly volatile VC. 50 μL of water sample was injected in 5 mL deionized water in glass tubes, and loaded into the 10-port autosampler. The GC was programmed at 40°C for 6 minutes, then ramped to 60°C in 2 minutes, held at 60°C for 10 minutes. Hydrocarbon gases (methane, ethene, ethane and acetylene) in headspace of electrolytic cell were analyzed through a Model 310 GC (SRI, USA) with flame ionization detector and Haysep-T column. 100 μL of headspace gas was sampled and injected from an on-column port. The temperature program applied was: heat column from 40 to 140°C at a rate of 15°C min⁻¹, hold 140°C for 1 minute, and cool to 40°C at a rate of 20°C min⁻¹. Chloride ion concentration was analyzed by Dionex DX-120 ion chromatograph. After each experiment, an aliquot 0.2 to 0.5 ml of supernatant was transferred into 5 mL vials which had been pre-filled with de-ionized water (> 18 M3), then filtered by 0.45μm pore size filter paper prior to final analysis. pH, conductivity and oxidation-reduction potential (ORP) of the electrolyte were measured by pH meter, conductivity meter and ORP meter with corresponding microprobes (Microelectro, USA). The microprobes allow the measurement on these parameters using small amount of liquid (≈0.2 mL).

Mao X., Ciblak A., Amiri M, & Alshawabkeh A.N. (2011). Redox control for electrochemical dechlorination of trichloroethylene in bicarbonate aqueous media. Environmental science & technology, 45(15), 6517-6523.

Publication 2011

Acetylene ARID1A protein, human Carbon Cells Chlorides Chromatography Electric Conductivity Electrolytes Ethane ethylene Flame Ionization Hydrocarbons Methane Oxidation-Reduction Strains tenax

Measuring BVOC Emissions in Vegetation

Cited 5 times

BVOC emissions were sampled 8 times in 2010 and 4 times in 2012 during the growing season in the same area as used for vegetation analysis. Samplings were made using transparent polycarbonate chambers (thickness 1.5 mm, 220 × 220 mm, height 200 mm; Vink Finland, Kerava, Finland) placed on an aluminum collar permanently installed in each plot in 1999. Collar grooves were filled with water before placing the chamber to create an airtight headspace inside the chamber. Before the 30-min-long sampling, the chamber was flushed for 10 min with a flow rate of 1000 ml min⁻¹ to replace the headspace with filtered air (Ortega & Helmig, 2008 (link)). During the sampling, the air was circulated through the chambers using battery-operated pumps (12V; Rietschle Thomas, Puchheim, Germany) at 200 ml min⁻¹ for both inflow and outflow and the chambers were equipped with fans to ensure well-mixed headspace. Incoming air was purified using a charcoal filter (Wilkerson F03-C2-100, Mexico) to remove particles and volatile impurities and a MnO₂ scrubber (Ozone Scrubber Cartridge, Environnement S.A. France) to remove ozone (Fig. S1).
The BVOCs released from the plots were trapped in stainless steel adsorbent tubes (150 mg Tenax TA, 200 mg Carbograph 1TD, Markes International Limited, Llantrisant, UK). After the collection, the tubes were sealed with Teflon-coated brass caps and stored at 5 °C until analysis.
Temperature and relative humidity inside the chamber were recorded (Hygrochron DS 1923-F5 iButton, Maxim Integrated Products Inc., CA, USA) once a minute during the sampling. PAR was recorded every 10 s using PAR sensors (S-LIA-M003, Onset Computer Corporation, Bourne, MA, USA) coupled to a Hobo Micro Station (Onset Computer Corporation); see Table S1 for chamber temperature and PAR during measurements.

Valolahti H., Kivimäenpää M., Faubert P., Michelsen A, & Rinnan R. (2015). Climate change-induced vegetation change as a driver of increased subarctic biogenic volatile organic compound emissions. Global Change Biology, 21(9), 3478-3488.

Publication 2015

Aluminum brass Charcoal Humidity Ozone polycarbonate Stainless Steel Teflon tenax

Most recents protocols related to «Tenax»

Exploring Trichomonas tenax Role in Periodontal Diseases

Not available on PMC !

Several reviews and original articles in the Scopus, PubMed and ScienceDirect databases were examined. The articles had a publication period up to July 2023. We used the "Advanced search" extension and the following keywords: "Trichomonas tenax" and "periodontal diseases". Only full texts were included.

Stoyanov S.N., Tasinov O., Dimitrova T., & Yaneva G. (2024). Prevalence of Trichomonas tenax in the Population Affected by Periodontal Disease—A Review. Applied Sciences, 14(6), 2666-2666.

Publication 2024

Comprehensive VOC Analysis via TD-GC-MS

Not available on PMC !

Collected VOCs were analysed by thermal desorption gas chromatography coupled to mass spectrometry (TD-GC-MS) as described elsewhere (Marco and Grimalt 2015) (link). Briefly, VOCs were thermo-desorbed at 300°C for 5 min with a desorption flow of 40 mL min -1 and reconcentrated in a general purpose hydrophobic cold trap at -20°C (U-T2GPH-2S, Markes International). Then, an uncoated and deactivated fused-silica transfer line carried the analytes within a split ratio of 1:5 into a Gas Chromatograph 7890 (GC; Agilent Technologies Inc., Santa Clara, CA, USA) coupled to a mass spectrometer (MS; 5975C Inert XL MSD, Agilent) with an electron impact (EI) ionization source. GC was fitted with a DB-5 MS UI capillary column (60 m × 320 μm × 1 μm; Agilent J&W GC Columns) where compounds were separated at a helium flow rate of 1 mL min -1 . The oven was programmed to start at 40°C (holding for 10 min), rising to 150°C at 5°C min -1 , subsequently to 210°C at 15°C min -1 and finishing with 10 min of holding time. MS spectra were obtained at 70 eV, being 230ºC and 150°C the temperatures of the ion source and the quadrupole, respectively. EI detector operated in full scan mode and acquired data over a mass range from 30 to 380 a.m.u.
The identification of VOCs was accomplished based on retention times, the ratios of quantifier and qualifier ions and the mass spectra from target compounds in standard solutions. Quantification of the target compounds was carried out by the external standard method. In order to determine linear range and limits of detection, three different calibration solutions with concentrations between 0.25 and 200 μg/mL were prepared in methanol (Merck, Darmstadt, Germany) from the following commercial standards: 8260B MegaMix Calibration Mix (2000 μg mL -1 in methanol; Restek, Bellefonte, PA, USA), Cannabis Terpenes Standard #1 (2500 μg mL -1 in isopropanol, Restek), 8260B Acetates Mix (2000 μg mL -1 in methanol; Restek), FIA Paraffin Standard (Accustandard Inc., New Haven, CT, USA). Each calibration solution was injected (1 μL) into conditioned cartridges through a calibration Solution Ring (CSLRTM, Markes International Ltd, Llantrisant, UK) with N 2 as carrier gas (flow rate of 50 mL min -1 ) and then was analyzed by TD-GC-MS. The coefficients of determination (R 2 ) of the calibration curves for target compounds were always >0.99. The instrumental limits of detection (LOD) were determined by multiplying the standard deviation of the response of the calibration curve by 3 and subsequently dividing the result by the slope of the same curve. Method detection limits (MDLs) were obtained by dividing LOD by the sampling volume of each sample. Overall, the MDLs ranged from 0.003 to 0.08 μg m -3 . To enable comparable and statistically significant analysis, VOC species were chosen if their calculated concentrations in ambient air exceeded the MDLs in more than 75% of the ground samples. Consequently, the final dataset comprised 40 VOCs from various chemical groups. The selected compounds were also found in over 75% of the balloon samples, with the exceptions of ethyl methacrylate and naphthalene, present at 63% of the samples, isopropylbenzene and n-decane at 50%, n-butylbenzene at 38%, and n-octane and isopropyl acetate at only 25%.

Díez-Palet I., Jaén C., Marco E., Van Drooge B.L., Fernández P, & Grimalt J.O. (2024). Measurement of volatile organic compounds using tethered balloons in a polluted industrial site in Catalonia (Spain). Environmental science and pollution research international.

Publication 2024

Periodontal Disease and Oral Flagellates

Not available on PMC !

All studies involving individuals diagnosed with periodontal disease, with or without concomitant systemic disorders, were included. There were no geographical restrictions on selection. Other inclusion criteria included considering articles that contained information about the year of publication, country, reported detection methods, total number of samples tested, and the percentage of patients infected with the flagellate microorganism.
Duplicate articles from all three databases were excluded. In addition, articles were excluded if they were not relevant to the aims of the study, such as those involving animal studies or analyzing Trichomonas tenax in a site other than the oral cavity.

Stoyanov S.N., Tasinov O., Dimitrova T., & Yaneva G. (2024). Prevalence of Trichomonas tenax in the Population Affected by Periodontal Disease—A Review. Applied Sciences, 14(6), 2666-2666.

Publication 2024

Rhizosphere Volatiles Profiling during Herbivory Stress

Rhizosphere volatiles were trapped through passive diffusion by placing one Tenax® (Markes International, Llantrisant, United Kingdom) trap containing 200 mg Tenax/tube type TA 60/80trap inside a metal holder in each pot, reaching an approximate depth of 5 cm. Metal holders were stainless steel cylinders with perforations allowing the air entrance while protecting the trap from soil contamination. Tenax traps were placed before the onset of the herbivory stress for 24 h (T0). Upon the leaf-herbivory stress induced by S. exigua, new Tenax traps were placed in the same pots where T0 was measured. Traps were placed 24 h after the onset of the herbivory stress for a 24 h period, thus collecting the volatiles during the initial 24–48 h herbivory stress induction period (T1). Traps were tightly closed and stored at room temperature until measurement. Before utilization, Tenax traps were preconditioned by heating at 300°C for 45 min under helium flow (5 l/min).
Full details of Tenax measurement regarding thermal desorption, GC/Q-TOF measuring conditions, calibration, data analysis, and compound identification are described by Lee Díaz et al. (2022 (link)). Briefly, volatiles was thermo-desorbed from Tenax traps at 240°C for 8 min and then transferred to an ultra-inter column (122–5532 UI, Agilent Technologies, Inc., Santa Clara, CA, USA) of the GC/Q-TOF (model Agilent 7890B GC and the Agilent 7200A Q-TOF). An n-alkane (C8–C20) standard solution was spiked at the beginning of the run for calibration. Mass spectra of compounds were acquired in full-scan-mode and GC/Q-TOF raw data was translated to .cdf format and analyzed with MzMine v2.53 (Pluskal et al. 2010 , 2020 ) for mass feature detection and peak intensity quantification. Parameters used for GC-MS peak intensity tables (Du et al. 2020 ) are available in Table S3 (Supporting Information). Peak intensity tables were used in combination with chromatogram data (Mass Hunter Qualitative v10, Agilent Technologies) for manual identification of volatile compounds comparing the mass spectrum of target compounds with the NIST 2020 database (V2.20, National Institute of Standards and Technology, USA).

Lee Díaz A.S., Minchev Z., Raaijmakers J.M., Pozo M.J, & Garbeva P. (2024). Impact of bacterial and fungal inoculants on the resident rhizosphere microbiome and the volatilome of tomato plants under leaf herbivory stress. FEMS Microbiology Ecology, 100(2), fiad160.

Publication 2024

Thermal Desorption and GC-MS Analysis of Volatile Compounds

A flow of 0.4 NL/min was diverted from the exposure chamber and forced through a Tenax TA 60/80 tube. The Tenax tubes were thermally desorbed and analyzed using a multimode inlet (OPTIC-4, GL Sciences, Eindhoven, The Netherlands) coupled to a GC–MS (an Agilent Technologies 7890A GC-system in combination with an Agilent Technologies 5975 inert XL MSD, Santa Clara, US). The injector was flash heated from 10 to 250 °C at a flow rate of 8 mL He/min. After a desorbing time of 90 s the column flow was reduced to 1.5 mL/min.

Durán Jiménez D., Venema T., de Bruin-Hoegée M., Alkema D.P., Busker R.W, & van Wuijckhuijse A.L. (2024). CHART: a novel system for detector evaluation against toxic chemical aerosols. Scientific Reports, 14, 1050.

Publication 2024

Top products related to «Tenax»

Tenax ta by Merck Group

Sourced in United States, Germany

Tenax TA is a porous polymer adsorbent material used in various analytical techniques. It is designed to trap and concentrate volatile organic compounds (VOCs) from gas samples. Tenax TA provides a high surface area and good thermal stability, making it suitable for a wide range of applications in analytical chemistry and environmental monitoring.

Tenax ta by Markes International

Sourced in United Kingdom

Tenax TA is an adsorbent material designed for the collection and analysis of volatile organic compounds (VOCs) in air, water, and soil samples. It is a porous polymer with a high surface area, providing efficient trapping and subsequent desorption of a wide range of organic compounds.

Tenax ta by Gerstel

Sourced in United States

Tenax TA is an adsorbent material commonly used in analytical techniques for trapping and concentrating volatile organic compounds (VOCs) from various sample matrices. It is a porous polymer material with a high surface area, providing efficient adsorption capabilities. Tenax TA can be used in a variety of applications, including environmental monitoring, indoor air quality assessments, and industrial process analysis.

Labchart 7 pro software by ADInstruments

Sourced in Australia, United Kingdom, United States

LabChart 7 Pro is a powerful data acquisition and analysis software for life science research. It provides a flexible and intuitive interface to record, visualize, and analyze physiological data from various instruments.

Tenax ta by PerkinElmer

Sourced in United States

Tenax TA is a solid adsorbent material used for the collection and analysis of volatile organic compounds (VOCs) in air samples. It is a porous polymer with a high surface area, which enables it to effectively trap and concentrate VOCs for subsequent analytical testing.

Dam50 differential amplifier by World Precision Instruments

Sourced in United States, Canada

The DAM50 is a differential amplifier that amplifies the difference between two input signals. It features a gain range of 0.1 to 5000 and a bandwidth of 0.1 Hz to 100 kHz. The DAM50 is designed to provide precise amplification of small, differential signals.

Carbopack b by Markes International

Sourced in United Kingdom

Carbopack B is a porous polymer-based adsorbent material used in gas chromatography and thermal desorption applications. It is specifically designed for the collection and analysis of volatile organic compounds (VOCs) and other trace-level analytes in air samples.

Turbomatrix 350 by PerkinElmer

Sourced in United States

The TurboMatrix 350 is a thermal desorption unit designed for the analysis of volatile and semi-volatile organic compounds. It is capable of thermally desorbing samples from a variety of media, including air, water, and soil, and transferring the desorbed compounds to a gas chromatography system for further analysis.

Powerlab 4 30 by ADInstruments

Sourced in Australia, United States, United Kingdom

The PowerLab 4/30 is a data acquisition system designed for laboratory research. It features four input channels for recording physiological signals such as biopotentials, pressure, and force. The device digitizes and processes the incoming signals, enabling researchers to analyze and display the data on a connected computer.

Atd 400 by PerkinElmer

Sourced in United States, United Kingdom

The ATD 400 is a thermal desorption instrument designed for the analysis of volatile organic compounds (VOCs) and semi-volatile organic compounds (SVOCs) in various sample matrices. It provides automated thermal desorption and transfer of analytes to a gas chromatography (GC) or liquid chromatography (LC) system for separation and detection.

What are the key properties of Tenax that make it a useful material?

What are some common applications of Tenax?

Tenax is widely used in environmental monitoring to collect and analyze air, water, and soil samples. It is also a popular stationary phase material in gas chromatography, where its stability and selectivity help improve the accuracy and reproducibility of analyses. Additionally, Tenax is used as a reinforcing agent in composite materials, leveraging its strength and durability.

Are there different types or variations of Tenax?

Yes, there are several variations of Tenax, each with its own unique properties and characteristics. For example, Tenax TA and Tenax GR differ in their surface area, pore size, and adsorption capacities, making them suited for different applications. Researchers should carefull yconsider the specific requirements of their project when selecting the appropriate Tenax product.

How can PubCompare.ai help researchers find the best Tenax products?

PubCompare.ai's AI-driven comparison tools can be invaluable for researchers looking to identify the optimal Tenax products for their studies. The platform allows you to efficiently screen protocol literature, leveraging artificial intelligence to pinpoint critical insights that can help you choose the most effective Tenax-based protocols for your specific research goals. This can improve the reproducibility and accuracy of your work by ensuring you use the best-suited Tenax materials.

More about "Tenax"

Tenax is a versatile synthetic polymer material with a wide range of applications.
This high-performance thermoplastic is known for its exceptional thermal and chemical stability, as well as its remarkable abrasion resistance.
Tenax products are commonly used as sorbents, membranes, and reinforcing agents in various industries, including environmental monitoring, gas chromatography, and composite manufacturing.
Researchers can leverage advanced AI-driven comparison tools, like those provided by PubCompare.ai, to identify the optimal Tenax products for their specific needs.
These intelligent tools help maximize the reproducibility and accuracy of research studies by enabling researchers to locate the best protocols from literature, preprints, and patents.
Tenax TA, a widely used Tenax product, is a versatile adsorbent material with a high surface area and strong affinity for volatile organic compounds (VOCs).
It is commonly employed in applications such as thermal desorption (ATD 400) and gas chromatography (LabChart 7 Pro software, TurboMatrix 350).
The DAM50 differential amplifier is another useful tool that can be used in conjunction with Tenax-based systems to enhance signal detection and analysis.
Carbopack B, another member of the Tenax family, is a graphitized carbon black adsorbent material often used in environmental monitoring and air quality assessment applications.
The PowerLab 4/30 is a data acquisition system that can be utilized to capture and analyze data from Tenax-based studies.
By leveraging the insights and capabilities offered by these Tenax-related products and software, researchers can maximize the efficiency, reproducibility, and accuracy of their investigations, leading to more robust and reliable research outcomes.