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Sensation

Sensation refers to the immediate and direct awareness of a stimulus, such as touch, taste, smell, or sound, which is processed by the sensory organs and transmitted to the brain.
This term encompasses the physiological and psychological processes involved in the detection and interpretation of various environmental stimuli.
Sensation plays a crucial role in our understanding and interaction with the world around us, allowing us to perceive and respond to various physical and chemical cues.
Teh study of sensation is a fundamental aspect of neuroscience and psychology, providing insights into the mechanisms of perception, cognition, and behavior.

Most cited protocols related to «Sensation»

Current gene annotations for S. pombe were downloaded as file ‘pombe_290110.gff’ from GeneDB (http://old.genedb.org/genedb/pombe/). RefSeq transcript gene annotations were downloaded for mouse at the UCSC mouse genome browser gateway (http://genome.ucsc.edu/cgi-bin/hgGateway?db=mm9) in BED format. Protein coding nucleotide sequences were extracted from the genome sequences based on the gene annotations using custom PERL scripts. The mouse reference coding sequences were further distilled to remove entirely identical sequences corresponding to isoforms encoding identical proteins and paralogous sequences: the original 19,947 genes encoding 23,881 transcripts were reduced to 19,857 genes encoding 22,717 on-identical coding transcripts.
Reconstructed transcript sequences (via de novo assembly, Scripture, or Cufflinks) were mapped to the reference coding sequences using BLAT35 (link). Full-length reference annotation mappings were defined as having at least 95% sequence identity covering the entire reference coding sequence and containing at most 5% insertions or deletions (cumulative gap content). In evaluating methods that leverage the strand-specific data (Trinity and Cufflinks), proper sense-strand mapping of sequences was required. Transcripts reconstructed by the alternative methods (Scripture, ABySS, and SOAPdenovo) were allowed to map to either strand. Fusion transcripts were identified as individual reconstructed transcripts that mapped as full-length to multiple reference coding sequences and lacked overlap among the matching regions within the reconstructed transcript. One-to-one mappings were required between reconstructed transcripts and reference transcripts, including alternatively spliced isoforms, with the exception of fusion transcripts.
Publication 2011
Exons Gene Annotation Gene Deletion Genes Genome Insertion Mutation Mus Open Reading Frames Protein Isoforms Proteins
Current gene annotations for S. pombe were downloaded as file ‘pombe_290110.gff’ from GeneDB (http://old.genedb.org/genedb/pombe/). RefSeq transcript gene annotations were downloaded for mouse at the UCSC mouse genome browser gateway (http://genome.ucsc.edu/cgi-bin/hgGateway?db=mm9) in BED format. Protein coding nucleotide sequences were extracted from the genome sequences based on the gene annotations using custom PERL scripts. The mouse reference coding sequences were further distilled to remove entirely identical sequences corresponding to isoforms encoding identical proteins and paralogous sequences: the original 19,947 genes encoding 23,881 transcripts were reduced to 19,857 genes encoding 22,717 on-identical coding transcripts.
Reconstructed transcript sequences (via de novo assembly, Scripture, or Cufflinks) were mapped to the reference coding sequences using BLAT35 (link). Full-length reference annotation mappings were defined as having at least 95% sequence identity covering the entire reference coding sequence and containing at most 5% insertions or deletions (cumulative gap content). In evaluating methods that leverage the strand-specific data (Trinity and Cufflinks), proper sense-strand mapping of sequences was required. Transcripts reconstructed by the alternative methods (Scripture, ABySS, and SOAPdenovo) were allowed to map to either strand. Fusion transcripts were identified as individual reconstructed transcripts that mapped as full-length to multiple reference coding sequences and lacked overlap among the matching regions within the reconstructed transcript. One-to-one mappings were required between reconstructed transcripts and reference transcripts, including alternatively spliced isoforms, with the exception of fusion transcripts.
Publication 2011
Exons Gene Annotation Gene Deletion Genes Genome Insertion Mutation Mus Open Reading Frames Protein Isoforms Proteins
Human gene annotations were acquired from GENCODE v17 (31 (link)). Protein-coding transcripts were defined as those with ‘protein_coding’ gene biotype and ‘protein_coding’ transcript biotype. The lncRNAs transcripts were defined as those with ‘processed_transcript’, ‘lincRNA’, ‘3prime_overlapping_ncrna’, ‘antisense’, ‘non_coding’, ‘sense_intronic’ or ‘sense_overlapping’ gene biotype. Small non-coding RNA (sncRNA) transcripts were defined as those with ‘snRNA’, ‘snoRNA’, ‘rRNA’, ‘Mt_tRNA’, ‘Mt_rRNA’, ‘misc_RNA’ or ‘miRNA’ gene biotype. Pseudogene transcripts were defined as those with ‘polymorphic_pseudogene’, ‘pseudogene’, ‘IG_C_pseudogene’, ‘IG_J_pseudogene’, ‘IG_V_pseudogene’, ‘TR_V_pseudogene’ or ‘TR_J_pseudogene’ gene biotype.
Mouse and Caenorhabditis elegans gene annotations were extracted from Ensembl Gene Release 72 and LiftOver to mm9/mm10 and ce6/ce10, respectively. Protein-coding, lncRNAs, sncRNAs and pseudogenes were classified using a similar method. Human, mouse and C. elegans circRNA annotations were downloaded from circBase v0.1 (6 (link)).
These transcripts were scanned to find conserved miRNAs target sites using miRanda v3.3a with the ‘-strict’ parameter. The target sites that overlap with any entry of the aforementioned AGO CLIP clusters were considered as the CLIP-supported target sites.
Publication 2013
Caenorhabditis elegans Clip Gene Annotation Gene Products, Protein Genes Genes, Overlapping Homo sapiens Introns Long Intergenic Non-Protein Coding RNA MicroRNAs Mus Neutrophil Proteins Pseudogenes Ribosomal RNA RNA, Circular RNA, Long Untranslated RNA, Small Untranslated RNA, Untranslated Small Nuclear RNA Small Nucleolar RNA Transfer RNA
AUGUSTUS is based on a generalized hidden Markov model (GHMM), which defines probability distributions for the various sections of genomic sequences. Introns, exons, intergenic regions, etc. correspond to states in the model and each state is thought to create DNA sequences with certain pre-defined emission probabilities. Similar to other HMM-based gene finders, AUGUSTUS finds an optimal parse of a given genomic sequence, i.e. a segmentation of the sequences into states that is most likely according to the underlying statistical model. We probabilistically model the sequence around the splice sites, the sequence of the branch point region, the bases before the translation start, the coding regions and non-coding regions, the first coding bases of a gene, the length distribution of single exons, initial exons, internal exons, terminal exons, intergenic regions, the distribution of the number of exons per gene and the length distribution of introns.
The performance of AUGUSTUS has been extensively evaluated on sequence data from human and Drosophila (7 ,8 (link)) (). These studies showed that, especially for long input sequences, the accuracy of our program is superior to that of existing ab initio gene finding approaches. To make our tool available to the research community, we have set up a WWW server at GOBICS (Göttingen Bioinformatics Compute Server) (9 (link)).
AUGUSTUS may be forced to predict an exon, an intron, a splice site, a translation start or a translation end point at a certain position in the sequence. An arbitrary number of such constraints is allowed and supported types of constraints are given in Table 1.
With the term gene structure, we refer to a segmentation of the input sequence into any meaningful sequence of exons, introns and intergenic regions. This includes the possibility of having no genes at all or of having multiple genes. AUGUSTUS tries to predict a gene structure that

is (biologically) consistent in the following sense:

No exon contains an in-frame stop codon.

The splice sites obey the gt–ag consensus. All complete genes start with atg and end with a stop codon.

Each gene ends before the next gene starts.

The lengths of single exons and introns exceed a species-dependent minimal length.

That obeys all given constraints.

Among all gene structures that are consistent and that obey all constraints, AUGUSTUS finds the most likely gene structure. A constraint may contradict the biological consistency. For example, an exonpart constraint may be impossible to realize because there is no containing open reading frame with allowed exon boundaries. If no consistent gene structure is possible, which obeys all constraints, then some constraints are ignored. Also, if two or more constraints contradict each other, then AUGUSTUS obeys only that constraint that fits better to the model. Figure 1 illustrates the concept. Further examples are on the page .
Publication 2005
Biopharmaceuticals Codon, Terminator Drosophila Exons Genes Genetic Structures Genome Homo sapiens Intergenic Region Introns Multiple Birth Offspring Reading Frames Seizures
Based on the hypothesis that genes with high frequency of non-sense (stop-gain) mutations in population are unlikely to be causal for rare Mendelian diseases, we compiled a list of such ‘dispensable’ genes using data from the 1000 Genomes Project. For the CEU, YRI and JPT+CHB population separately, we identify genes that have non-sense mutations with combined minor allele frequency (MAF) >1%. For example, if two nonsense mutations in the same gene have MAF of 0.5 and 0.8% in CEU populations, this gene will be regarded as a dispensable gene. This analysis resulted in the identification of a total of 2064 genes from the 1000 Genomes Project. We caution that genes may fall within this list due to sequencing errors or alignment errors; for example, if the gene has many pseudogenes or if it is present within a segmental duplication. This list (∼10% of all annotated human genes) is useful as a filtering step to further trim down potential candidate genes for Mendelian diseases.
Publication 2010
Genes Genes, vif Genome Mutation Mutation, Nonsense Population Group Pseudogenes Segmental Duplications, Genomic Strains

Most recents protocols related to «Sensation»

Example 6

Ceres cDNA 12723147 encodes an Arabidopsis putative aldo/keto reductase. Ectopic expression of Ceres cDNA 12723147 under the control of the CaMV35S promoter induces the following phenotypes:

    • Germination on high concentrations of polyethylene glycol (PEG), mannitol and abscissic acid (ABA).
    • Continued growth on high concentration of PEG, mannitol and ABA.
      Generation and Phenotypic Evaluation of T1 Lines Containing 35S::cDNA 12723147.

Wild-type Arabidopsis Wassilewskija (WS) plants were transformed with a Ti plasmid containing cDNA 12723147 in the sense orientation relative to the CaMV35S constitutive promoter. The Ti plasmid vector used for this construct, CRS338, contains PAT and confers herbicide resistance to transformed plants. Ten independently transformed events were selected and evaluated for their qualitative phenotype in the T1 generation. No positive or negative phenotypes were observed in the T1 plants.

Screens of Superpools on High PEG, Mannitol, and ABA as Surrogate Screens for Drought Tolerance.

Seeds from 13 superpools (1,200 T2 seeds from each superpool) from the CaMV35S or 32449 over-expression lines were tested on 3 drought surrogate screens (high concentrations of PEG, mannitol, and ABA) as described above. T3 seeds were collected from the resistant plants and analyzed for resistance on all three surrogate drought screens.

Once cDNA 12723147 was identified in resistant plants from each of the three surrogate drought screens, the five individual T2 events containing this cDNA (SR01013) were screened on high PEG, mannitol, and ABA to identify events with the resistance phenotype.

Superpools (SP) are referred to as SP1, SP2 and so on. The letter following the hyphen refers to the screen (P=PEG, M=mannitol, and A=ABA) and the number following the letter refers to a number assigned to each plant obtained from that screen on that superpool. For example, SP1-M18 is the 18th plant isolated from a mannitol screen of Superpool 1.

Qualitative and Quantitative Analysis of 2 Independent Events Representing 35S::cDNA 12659859 (SR01010) on PEG, Mannitol and ABA

To identify two independent events of 35S::cDNA 12659859 showing PEG, mannitol, and ABA resistance, 36 seedlings from each of two events, SR01013-01 and -02 were screened as previously described. BastaR segregation was assessed to verify that the lines contained a single insert segregating in a 3:1 (R:S) ratio as calculated by a chi-square test (Table 6-1). Both lines (01 and 02) segregated for a single insert in the T2 generation (Table 1)

TABLE 6-1
BastaR segregation for SR01013 individual events
Probability
EventResistantSensitiveTotalof Chi-test*
SR01013-01305350.14323
SR01013-02306360.24821
SR01013-01-3341360.00248**
SR01013-02-2320320.00109**
*Chi-test to determine whether actual ratio of resistant to sensitive differs form the expected 3:1 ratio.
**Significantly different than a 3:1 (R:S) ratio

Lines SR01013-01 and -02 were chosen as the two events because they had a strong and consistent resistance to PEG, mannitol and ABA. The controls were sown the same day and in the same plate as the individual lines. The PEG (Tables 6-2 and 6-3), mannitol (Tables 6-4 and 6-5) and ABA (Tables 6-6 and 6-7) segregation ratios observed for SR01013-01 and -02 are consistent with the presence of single insert as demonstrated by chi-square, similar to what we observed for BastaR resistance (Table 6-1).

The progeny from one resistant T2 plant from each of these two events were tested in the same manner as the T2. Resistance to PEG, mannitol and ABA was also observed in the T3 generation. Taken together, the segregation of resistant seedlings containing cDNA 12723147 from two events on all three drought surrogate screens and the inheritance of this resistance in a subsequent generation, provide strong evidence that cDNA 12723147 when over-expressed can provide tolerance to drought.

TABLE 6-2
Chi-square analysis assuming a 3:1 (R:S) ratio for progeny of
SR01013-01T2 containing 35S::cDNA 12723147 on PEG.
Probability
EventObservedExpectedχ2of Chi-Test
PEG Resistant22270.9260.054
PEG Sensitive1492.778
36363.704

TABLE 6-3
Chi-square analysis assuming a 3:1 (R:S) ratio for progeny of
SR01013-02 T2 containing 35S::cDNA 12723147 on PEG.
Probability
EventObservedExpectedχ2of Chi-Test
PEG Resistant26270.037.700
PEG Sensitive109.111
3636.148

TABLE 6-4
Chi-square analysis assuming a 3:1 (R:S) ratio for progeny of
SR01013-01 T2 containing 35S::cDNA 12723147 on mannitol.
Probability
EventObservedExpectedχ2of Chi-Test
Mannitol Resistant2827.037.700
Mannitol Sensitive89.111
3636.148

TABLE 6-5
Chi-square analysis assuming a 3:1 (R:S) ratio for progeny of
SR01013-02 T2 containing 35S::cDNA 12723147 on mannitol.
Probability
EventObservedExpectedχ2of Chi-Test
Mannitol Resistant18273.0005
Mannitol Sensitive1899
363612

TABLE 6-6
Chi-square analysis assuming a 3:1 (R:S) ratio for progeny of
SR01013-02 T2 containing 35S::cDNA 12723147 on ABA.
EventObservedExpectedχ2Probability
ABA Resistant1324 5.0427.098
ABA Sensitive19 815.125
323220.167

TABLE 6-7
Chi-square analysis assuming a 3:1 (R:S) ratio for progeny of
SR01013-02 T2 containing 35S::cDNA 12723147 on ABA.
EventObservedExpectedχ2Probability
ABA Resistant1324 5.0427.098
ABA Sensitive19 815.125
323220.167
FIG. 5 provides the results of the consensus sequence (SEQ ID NOs: 178-200) analysis based on Ceres cDNA 12723147.

Patent 2024
14-3-3 Proteins Abscisic Acid Aldo-Keto Reductase Arabidopsis CERE Cloning Vectors Consensus Sequence DNA, Complementary Droughts Drought Tolerance Ectopic Gene Expression Germination Herbicide Resistance Mannitol Pattern, Inheritance Phenotype Plant Embryos Plants Plant Tumor-Inducing Plasmids Polyethylene Glycols Seedlings

Example 17

To further validate the activity of the DMPK siRNAs, many of the sequences that showed the best activity in the initial screen were selected for a follow-up evaluation in dose response format. Once again, two human cell lines were used to assess the in vitro activity of the DMPK siRNAs: first, SJCRH30 human rhabdomyosarcoma cell line; and second, Myotonic Dystrophy Type 1 (DM1) patient-derived immortalized human skeletal myoblasts. The selected siRNAs were transfected in a 10-fold dose response at 100, 10, 1, 0.1, 0.01, 0,001, and 0.0001 nM final concentrations or in a 9-fold dose response at 50, 5.55556, 0.617284, 0.068587, 0.007621, 0.000847, and 0.000094 nM final concentrations. The siRNAs were formulated with transfection reagent Lipofectamine RNAiMAX (Life Technologies) according to the manufacturer's “forward transfection” instructions. Cells were plated 24 h prior to transfection in triplicate on 96-well tissue culture plates, with 8500 cells per well for SJCRH30 and 4000 cells per well for DM1 myoblasts. At 48 h (SJCRH30) or 72 h (DM1 myoblasts) post-transfection cells were washed with PBS and harvested with TRIzol® reagent (Life Technologies). RNA was isolated using the Direct-zol-96 RNA Kit (Zymo Research) according to the manufacturer's instructions. 10 μl of RNA was reverse transcribed to cDNA using the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems) according to the manufacturer's instructions. cDNA samples were evaluated by qPCR with DMPK-specific and PPIB-specific TaqMan human gene expression probes (Thermo Fisher) using TaqMan® Fast Advanced Master Mix (Applied Biosystems). DMPK values were normalized within each sample to PPIB gene expression. The quantification of DMPK downregulation was performed using the standard 2−ΔΔCt a method. All experiments were performed in triplicate, with Tables 16A-B, 17A-B, and 18A-B presenting the mean values of the triplicates as well as the calculated IC50 values determined from fitting curves to the dose-response data by non-linear regression.

TABLE 16A
sense strandSEQantisense strandSEQ
sequence (5′-3′)IDsequence (5′-3′)ID
ID #1Passenger Strand (PS)NO:Guide Strand (GS)NO:
535GGGCGAGGUGUCGUGCUUA9349UAAGCACGACACCUCGCCC12053
584GACCGGCGGUGGAUCACGA9398UCGUGAUCCACCGCCGGUC12102
716AUGGCGCGCUUCUACCUGA9530UCAGGUAGAAGCGCGCCAU12234
1028CAGACGCCCUUCUACGCGA9842UCGCGUAGAAGGGCGUCUG12546
1276UUUCGAAGGUGCCACCGAA10090UUCGGUGGCACCUUCGAAA12794
1825UGCUCCUGUUCGCCGUUGA10639UCAACGGCGAACAGGAGCA13343
1945CCCUAGAACUGUCUUCGAA10759UUCGAAGACAGUUCUAGGG13463
2529CUUCGGCGGUUUGGAUAUA11343UAUAUCCAAACCGCCGAAG14047
2558GUCCUCCGACUCGCUGACA11372UGUCAGCGAGUCGGAGGAC14076
2628CCGACAUUCCUCGGUAUUA11442UAAUACCGAGGAAUGUCGG14146
2636CCUCGGUAUUUAUUGUCUA11450UAGACAAUAAAUACCGAGG14154
119mer position in NM_001288766.1

TABLE 16B
IC50
ID #1qPCR2qPCR3qPCR4qPCR5qPCR6qPCR7qPCR8(nM)
535111.9105.4106.382.436.729.535.70.165
58490.590.284.767.838.025.828.30.190
71688.985.281.962.032.619.320.30.181
102888.581.883.061.332.727.331.50.127
127687.085.084.066.140.534.036.40.150
182585.185.983.769.136.225.225.00.259
194585.081.774.444.922.917.717.20.070
252983.381.875.350.624.617.517.70.103
255884.381.174.345.423.413.311.80.088
262885.384.079.559.830.323.525.10.140
263686.386.974.344.019.812.413.00.070
2SJCRH30; 0.0001 nM; % DMPK mRNA
3SJCRH30; 0.001 nM; % DMPK mRNA
4SJCRH30; 0.01 nM; % DMPK mRNA
5SJCRH30; 0.1 nM; % DMPK mRNA
6SJCRH30; 1 nM; % DMPK mRNA
7SJCRH30; 10 nM; % DMPK mRNA
8SJCRH30; 100 nM; % DMPK mRNA

TABLE 17A
sense strandSEQantisense strandSEQ
sequence (5′-3′)IDsequence (5′-3′)ID
ID #1Passenger Strand (PS)NO:Guide Strand (GS)NO:
2600CAAUCCACGUUUUGGAUGA11414UCAUCCAAAACGUGGAUUG14118
2636CCUCGGUAUUUAUUGUCUA11450UAGACAAUAAAUACCGAGG14154
2675CCCCGACCCUCGCGAAUAA11489UUAUUCGCGAGGGUCGGGG14193
2676CCCGACCCUCGCGAAUAAA11490UUUAUUCGCGAGGGUCGGG14194
2679GACCCUCGCGAAUAAAAGA11493UCUUUUAUUCGCGAGGGUC14197
2680ACCCUCGCGAAUAAAAGGA11494UCCUUUUAUUCGCGAGGGU14198
2681CCCUCGCGAAUAAAAGGCA11495UGCCUUUUAUUCGCGAGGG14199
2682CCUCGCGAAUAAAAGGCCA11496UGGCCUUUUAUUCGCGAGG14200
119mer position in NM_001288766.1

TABLE 17B
IC50
ID #1qPCR2qPCR3qPCR4qPCR5qPCR6qPCR7(nM)
2600107.5107.6108.1106.3103.172.731.31
263681.181.174.047.225.711.50.073
267588.188.384.364.638.120.70.151
267688.978.984.472.744.935.60.204
267984.087.382.753.331.413.50.091
268087.485.385.168.544.539.60.110
268187.085.477.649.626.516.00.061
268282.483.977.150.827.331.10.047
2SJCRH30; 0.000094 nM; % DMPK mRNA
3SJCRH30; 0.000847 nM; % DMPK mRNA
4SJCRH30; 0.007621 nM; % DMPK mRNA
5SJCRH30; 0.068587 nM; % DMPK mRNA
6SJCRH30; 0.617284 nM; % DMPK mRNA
7SJCRH30; 5.55556 nM; % DMPK mRNA

TABLE 18A
sense strandSEQantisense strandSEQ
sequence (5′-3′)IDsequence (5′-3′)ID
ID #1Passenger Strand (PS)NO:Guide Strand (GS)NO:
584GACCGGCGGUGGAUCACGA9398UCGUGAUCCACCGCCGGUC12102
716AUGGCGCGCUUCUACCUGA9530UCAGGUAGAAGCGCGCCAU12234
1265UUUACACCGGAUUUCGAAA10079UUUCGAAAUCCGGUGUAAA12783
1297AUGCAACUUCGACUUGGUA10111UACCAAGUCGAAGUUGCAU12815
1945CCCUAGAACUGUCUUCGAA10759UUCGAAGACAGUUCUAGGG13463
1960CGACUCCGGGGCCCCGUUA10774UAACGGGGCCCCGGAGUCG13478
2529CUUCGGCGGUUUGGAUAUA11343UAUAUCCAAACCGCCGAAG14047
2530UUCGGCGGUUUGGAUAUUA11344UAAUAUCCAAACCGCCGAA14048
2531UCGGCGGUUUGGAUAUUUA11345UAAAUAUCCAAACCGCCGA14049
2554CCUCGUCCUCCGACUCGCA11368UGCGAGUCGGAGGACGAGG14072
2628CCGACAUUCCUCGGUAUUA11442UAAUACCGAGGAAUGUCGG14146
2629CGACAUUCCUCGGUAUUUA11443UAAAUACCGAGGAAUGUCG14147
2681CCCUCGCGAAUAAAAGGCA11495UGCCUUUUAUUCGCGAGGG14199
119mer position in NM_001288766.1

TABLE 18B
IC50
ID #1qPCR2qPCR3qPCR4qPCR5qPCR6qPCR7(nM)
58490.877.097.771.945.029.70.228
71696.582.577.064.643.333.90.080
126568.580.968.057.137.525.70.146
129771.467.269.453.540.525.40.171
194571.862.341.729.822.415.30.006
196063.065.462.145.831.128.30.068
252963.558.749.231.122.921.90.017
253069.366.753.143.238.824.50.016
253169.972.457.340.235.425.60.018
255468.270.151.243.032.117.30.043
262869.767.962.538.431.617.10.042
262972.165.669.042.134.413.70.078
268182.491.587.655.529.319.60.084
2DM1 myoblasts; 0.000094 nM; % DMPK mRNA
3DM1 myoblasts; 0.000847 nM; % DMPK mRNA
4DM1 myoblasts; 0.007621 nM; % DMPK mRNA
5DM1 myoblasts; 0.068587 nM; % DMPK mRNA
6DM1 myoblasts; 0.617284 nM; % DMPK mRNA
7DM1 myoblasts; 5.55556 nM; % DMPK mRNA

Patent 2024
Cell Lines Cells DNA, Complementary Down-Regulation Gene Expression Homo sapiens Lipofectamine Myoblasts Myoblasts, Skeletal Myotonic Dystrophy NM-107 Patients PPIB protein, human Reverse Transcription Rhabdomyosarcoma RNA, Messenger RNA, Small Interfering Tissues Transfection trizol
Not available on PMC !

Example 18

A non-transitory computer readable medium storing computer readable instructions which, when executed, causes a machine to: control the operation of a plurality of illumination sources of a tissue sample wherein each illumination source is configured to emit light having a specified central wavelength; receive data from the light sensor when the tissue sample is illuminated by each of the plurality of illumination sources; calculate structural data related to a characteristic of a structure within the tissue sample based on the data received by the light sensor when the tissue sample is illuminated by each of the illumination sources; and transmit the structural data related to the characteristic of the structure to be received by a smart surgical device, wherein the characteristic of the structure is a surface characteristic or a structure composition.

While several forms have been illustrated and described, it is not the intention of the applicant to restrict or limit the scope of the appended claims to such detail. Numerous modifications, variations, changes, substitutions, combinations, and equivalents to those forms may be implemented and will occur to those skilled in the art without departing from the scope of the present disclosure. Moreover, the structure of each element associated with the described forms can be alternatively described as a means for providing the function performed by the element. Also, where materials are disclosed for certain components, other materials may be used. It is therefore to be understood that the foregoing description and the appended claims are intended to cover all such modifications, combinations, and variations as falling within the scope of the disclosed forms. The appended claims are intended to cover all such modifications, variations, changes, substitutions, modifications, and equivalents.

The foregoing detailed description has set forth various forms of the devices and/or processes via the use of block diagrams, flowcharts, and/or examples. Insofar as such block diagrams, flowcharts, and/or examples contain one or more functions and/or operations, it will be understood by those within the art that each function and/or operation within such block diagrams, flowcharts, and/or examples can be implemented, individually and/or collectively, by a wide range of hardware, software, firmware, or virtually any combination thereof. Those skilled in the art will recognize that some aspects of the forms disclosed herein, in whole or in part, can be equivalently implemented in integrated circuits, as one or more computer programs running on one or more computers (e.g., as one or more programs running on one or more computer systems), as one or more programs running on one or more processors (e.g., as one or more programs running on one or more microprocessors), as firmware, or as virtually any combination thereof, and that designing the circuitry and/or writing the code for the software and or firmware would be well within the skill of one of skill in the art in light of this disclosure. In addition, those skilled in the art will appreciate that the mechanisms of the subject matter described herein are capable of being distributed as one or more program products in a variety of forms, and that an illustrative form of the subject matter described herein applies regardless of the particular type of signal bearing medium used to actually carry out the distribution.

Instructions used to program logic to perform various disclosed aspects can be stored within a memory in the system, such as dynamic random access memory (DRAM), cache, flash memory, or other storage. Furthermore, the instructions can be distributed via a network or by way of other computer readable media. Thus a machine-readable medium may include any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computer), but is not limited to, floppy diskettes, optical disks, compact disc, read-only memory (CD-ROMs), and magneto-optical disks, read-only memory (ROMs), random access memory (RAM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic or optical cards, flash memory, or a tangible, machine-readable storage used in the transmission of information over the Internet via electrical, optical, acoustical or other forms of propagated signals (e.g., carrier waves, infrared signals, digital signals, etc.). Accordingly, the non-transitory computer-readable medium includes any type of tangible machine-readable medium suitable for storing or transmitting electronic instructions or information in a form readable by a machine (e.g., a computer).

As used in any aspect herein, the term “control circuit” may refer to, for example, hardwired circuitry, programmable circuitry (e.g., a computer processor comprising one or more individual instruction processing cores, processing unit, processor, microcontroller, microcontroller unit, controller, digital signal processor (DSP), programmable logic device (PLD), programmable logic array (PLA), or field programmable gate array (FPGA)), state machine circuitry, firmware that stores instructions executed by programmable circuitry, and any combination thereof. The control circuit may, collectively or individually, be embodied as circuitry that forms part of a larger system, for example, an integrated circuit (IC), an application-specific integrated circuit (ASIC), a system on-chip (SoC), desktop computers, laptop computers, tablet computers, servers, smart phones, etc. Accordingly, as used herein “control circuit” includes, but is not limited to, electrical circuitry having at least one discrete electrical circuit, electrical circuitry having at least one integrated circuit, electrical circuitry having at least one application specific integrated circuit, electrical circuitry forming a general purpose computing device configured by a computer program (e.g., a general purpose computer configured by a computer program which at least partially carries out processes and/or devices described herein, or a microprocessor configured by a computer program which at least partially carries out processes and/or devices described herein), electrical circuitry forming a memory device (e.g., forms of random access memory), and/or electrical circuitry forming a communications device (e.g., a modem, communications switch, or optical-electrical equipment). Those having skill in the art will recognize that the subject matter described herein may be implemented in an analog or digital fashion or some combination thereof.

As used in any aspect herein, the term “logic” may refer to an app, software, firmware and/or circuitry configured to perform any of the aforementioned operations. Software may be embodied as a software package, code, instructions, instruction sets and/or data recorded on non-transitory computer readable storage medium. Firmware may be embodied as code, instructions or instruction sets and/or data that are hard-coded (e.g., nonvolatile) in memory devices.

As used in any aspect herein, the terms “component,” “system,” “module” and the like can refer to a computer-related entity, either hardware, a combination of hardware and software, software, or software in execution.

As used in any aspect herein, an “algorithm” refers to a self-consistent sequence of steps leading to a desired result, where a “step” refers to a manipulation of physical quantities and/or logic states which may, though need not necessarily, take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated. It is common usage to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, or the like. These and similar terms may be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities and/or states.

A network may include a packet switched network. The communication devices may be capable of communicating with each other using a selected packet switched network communications protocol. One example communications protocol may include an Ethernet communications protocol which may be capable permitting communication using a Transmission Control Protocol/Internet Protocol (TCP/IP). The Ethernet protocol may comply or be compatible with the Ethernet standard published by the Institute of Electrical and Electronics Engineers (IEEE) titled “IEEE 802.3 Standard”, published in December, 2008 and/or later versions of this standard. Alternatively or additionally, the communication devices may be capable of communicating with each other using an X.25 communications protocol. The X.25 communications protocol may comply or be compatible with a standard promulgated by the International Telecommunication Union-Telecommunication Standardization Sector (ITU-T). Alternatively or additionally, the communication devices may be capable of communicating with each other using a frame relay communications protocol. The frame relay communications protocol may comply or be compatible with a standard promulgated by Consultative Committee for International Telegraph and Telephone (CCITT) and/or the American National Standards Institute (ANSI). Alternatively or additionally, the transceivers may be capable of communicating with each other using an Asynchronous Transfer Mode (ATM) communications protocol. The ATM communications protocol may comply or be compatible with an ATM standard published by the ATM Forum titled “ATM-MPLS Network Interworking 2.0” published August 2001, and/or later versions of this standard. Of course, different and/or after-developed connection-oriented network communication protocols are equally contemplated herein.

Unless specifically stated otherwise as apparent from the foregoing disclosure, it is appreciated that, throughout the foregoing disclosure, discussions using terms such as “processing,” “computing,” “calculating,” “determining,” “displaying,” or the like, refer to the action and processes of a computer system, or similar electronic computing device, that manipulates and transforms data represented as physical (electronic) quantities within the computer system's registers and memories into other data similarly represented as physical quantities within the computer system memories or registers or other such information storage, transmission or display devices.

One or more components may be referred to herein as “configured to,” “configurable to,” “operable/operative to,” “adapted/adaptable,” “able to,” “conformable/conformed to,” etc. Those skilled in the art will recognize that “configured to” can generally encompass active-state components and/or inactive-state components and/or standby-state components, unless context requires otherwise.

The terms “proximal” and “distal” are used herein with reference to a clinician manipulating the handle portion of the surgical instrument. The term “proximal” refers to the portion closest to the clinician and the term “distal” refers to the portion located away from the clinician. It will be further appreciated that, for convenience and clarity, spatial terms such as “vertical”, “horizontal”, “up”, and “down” may be used herein with respect to the drawings. However, surgical instruments are used in many orientations and positions, and these terms are not intended to be limiting and/or absolute.

Those skilled in the art will recognize that, in general, terms used herein, and especially in the appended claims (e.g., bodies of the appended claims) are generally intended as “open” terms (e.g., the term “including” should be interpreted as “including but not limited to,” the term “having” should be interpreted as “having at least,” the term “includes” should be interpreted as “includes but is not limited to,” etc.). It will be further understood by those within the art that if a specific number of an introduced claim recitation is intended, such an intent will be explicitly recited in the claim, and in the absence of such recitation no such intent is present. For example, as an aid to understanding, the following appended claims may contain usage of the introductory phrases “at least one” and “one or more” to introduce claim recitations. However, the use of such phrases should not be construed to imply that the introduction of a claim recitation by the indefinite articles “a” or “an” limits any particular claim containing such introduced claim recitation to claims containing only one such recitation, even when the same claim includes the introductory phrases “one or more” or “at least one” and indefinite articles such as “a” or “an” (e.g., “a” and/or “an” should typically be interpreted to mean “at least one” or “one or more”); the same holds true for the use of definite articles used to introduce claim recitations.

In addition, even if a specific number of an introduced claim recitation is explicitly recited, those skilled in the art will recognize that such recitation should typically be interpreted to mean at least the recited number (e.g., the bare recitation of “two recitations,” without other modifiers, typically means at least two recitations, or two or more recitations). Furthermore, in those instances where a convention analogous to “at least one of A, B, and C, etc.” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., “a system having at least one of A, B, and C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). In those instances where a convention analogous to “at least one of A, B, or C, etc.” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., “a system having at least one of A, B, or C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). It will be further understood by those within the art that typically a disjunctive word and/or phrase presenting two or more alternative terms, whether in the description, claims, or drawings, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms unless context dictates otherwise. For example, the phrase “A or B” will be typically understood to include the possibilities of “A” or “B” or “A and B.”

With respect to the appended claims, those skilled in the art will appreciate that recited operations therein may generally be performed in any order. Also, although various operational flow diagrams are presented in a sequence(s), it should be understood that the various operations may be performed in other orders than those which are illustrated, or may be performed concurrently. Examples of such alternate orderings may include overlapping, interleaved, interrupted, reordered, incremental, preparatory, supplemental, simultaneous, reverse, or other variant orderings, unless context dictates otherwise. Furthermore, terms like “responsive to,” “related to,” or other past-tense adjectives are generally not intended to exclude such variants, unless context dictates otherwise.

It is worthy to note that any reference to “one aspect,” “an aspect,” “an exemplification,” “one exemplification,” and the like means that a particular feature, structure, or characteristic described in connection with the aspect is included in at least one aspect. Thus, appearances of the phrases “in one aspect,” “in an aspect,” “in an exemplification,” and “in one exemplification” in various places throughout the specification are not necessarily all referring to the same aspect. Furthermore, the particular features, structures or characteristics may be combined in any suitable manner in one or more aspects.

Any patent application, patent, non-patent publication, or other disclosure material referred to in this specification and/or listed in any Application Data Sheet is incorporated by reference herein, to the extent that the incorporated materials is not inconsistent herewith. As such, and to the extent necessary, the disclosure as explicitly set forth herein supersedes any conflicting material incorporated herein by reference. Any material, or portion thereof, that is said to be incorporated by reference herein, but which conflicts with existing definitions, statements, or other disclosure material set forth herein will only be incorporated to the extent that no conflict arises between that incorporated material and the existing disclosure material.

In summary, numerous benefits have been described which result from employing the concepts described herein. The foregoing description of the one or more forms has been presented for purposes of illustration and description. It is not intended to be exhaustive or limiting to the precise form disclosed. Modifications or variations are possible in light of the above teachings. The one or more forms were chosen and described in order to illustrate principles and practical application to thereby enable one of ordinary skill in the art to utilize the various forms and with various modifications as are suited to the particular use contemplated. It is intended that the claims submitted herewith define the overall scope.

Patent 2024
Acoustics Character Conferences DNA Chips Electricity Enzyme Multiplied Immunoassay Technique Fingers Human Body Light Medical Devices Memory Mental Orientation Ocular Refraction Physical Examination Reading Frames Surgical Instruments Teaching Tissues Transmission, Communicable Disease Vision

Example 3

With reference to FIG. 1, the sensor 120 senses vasopressin, and the sensor 124 senses Na+, which is an indicator of sweat generation rate. The sensor 124 could therefore provide a leading warning of possible dehydration before dehydration occurs as recorded by sensor 220, which measures changes in levels of vasopressin.

Patent 2024
AVP protein, human Companions Dehydration Medical Devices Sweat

EXAMPLE 8

Diet Cookies

Flour (50.0%), margarine (30.0%) fructose (10.0%), maltitol (8.0%), whole milk (1.0%), salt (0.2%), baking powder (0.15%), vanillin (0.1%) and different glucosyl Stevia compositions (0.03%) were kneaded well in dough-mixing machine. The obtained dough was molded and baked in oven at 200° C. for 15 minutes. Glucosyl Stevia compositions were by represented by Samples 1a, 2a, and 3, obtained according to EXAMPLES 3, 4, and 5, respectively; with Sample 4 being a commercial β-amylase treated product (containing only mono- and di-α-1,4-glucosyl-derivatives of steviol glycosides).

The sensory properties were evaluated by 20 panelists. The best results were obtained in samples prepared by high purity short-chain glucosyl Stevia compositions (containing four or less α-1,4-glucosyl residues) derivatives (Samples 1a and 2a). The panelists noted rounded and complete flavor profile and mouthfeel in cookies prepared with Samples 1a and 2a.

Patent 2024
Amylase baking powder derivatives Flavor Enhancers Flour Fructose maltitol Margarine Milk, Cow's Sodium Chloride Stevia stevioside Therapy, Diet vanillin

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Lipofectamine 2000 is a cationic lipid-based transfection reagent designed for efficient and reliable delivery of nucleic acids, such as plasmid DNA and small interfering RNA (siRNA), into a wide range of eukaryotic cell types. It facilitates the formation of complexes between the nucleic acid and the lipid components, which can then be introduced into cells to enable gene expression or gene silencing studies.
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TRIzol is a monophasic solution of phenol and guanidine isothiocyanate that is used for the isolation of total RNA from various biological samples. It is a reagent designed to facilitate the disruption of cells and the subsequent isolation of RNA.
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More about "Sensation"

Sensation refers to the immediate and direct awareness of various stimuli, such as touch, taste, smell, or sound, which are processed by the sensory organs and transmitted to the brain.
This physiological and psychological process plays a crucial role in our understanding and interaction with the world around us, allowing us to perceive and respond to physical and chemical cues.
The study of sensation is a fundamental aspect of neuroscience and psychology, providing insights into the mechanisms of perception, cognition, and behavior.
Sensory stimuli can be detected and interpreted through a variety of methods, including the use of specialized reagents and kits.
For example, TRIzol reagent is commonly used for RNA extraction, while Lipofectamine 2000 and Lipofectamine RNAiMAX are transfection reagents used for introducing nucleic acids into cells.
The RNeasy Mini Kit is another tool for purifying RNA, and PrimeScript RT reagent kit is used for reverse transcription.
Opti-MEM and FBS are also commonly used in cell culture experiments.
The study of sensation encompasses a wide range of subtopics, including sensory receptors, sensory transduction, sensory processing, and sensory perception.
These processes involve the detection of various stimuli, the conversion of these stimuli into electrical signals, and the interpretation of those signals by the brain.
Understanding the mechanisms of sensation is crucial for research in fields such as neuroscience, psychology, and medicine.
Overall, the study of sensation is a fasinating and complex area of science, with numerous applications in various fields of research and development.
By leveraging the power of AI-driven protocol optimization tools like PubCompare.ai, researchers can more easily discover and optimize the protocols and products necessary for their sensory-related studies, ultimately leading to more efficient and effective research outcomes.