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Lactams

Lactams are a class of organic compounds characterized by a cyclic amide structure.
These heterocyclic rings are found in a variety of pharmaceuticals and natural products, including important antibiotics like penicillins and cephalosporins.
Lactams exhibit diverse biological activities and are widely used in medicinal chemistry research.
PubCompare.ai's AI-driven platform can help optimize your Lactams research by providing easy access to protocols from the literature, preprints, and patents, along with AI-powered comparisons to identify the best approaches and products.
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Most cited protocols related to «Lactams»

1
ResFinder 4.0: Comprehensive AMR Database
Cited 131 times
ResFinder 4.0 contains four databases including AMR genes (ResFinder), chromosomal gene mutations mediating AMR (PointFinder), translation of genotypes into phenotypes and species-specific panels for in silico antibiograms. The databases of ResFinder15 (link) and PointFinder16 (link) were reviewed by experts and, when necessary, entries were removed or added. Furthermore, the PointFinder database was extended to include chromosomal gene mutations leading to ampicillin resistance in Enterococcus faecium, ciprofloxacin resistance in E. faecium and Enterococcus faecalis, and resistance to cefoxitin, chloramphenicol, ciprofloxacin, fusidic acid, linezolid, mupirocin, quinupristin–dalfopristin, rifampicin and trimethoprim in Staphylococcus aureus. The genotype-to-phenotype tables were created by experts, by using additional databases (www.bldb.eu for β-lactam resistance genes,18 (link)  http://faculty.washington.edu/marilynr/ for tetracycline as well as macrolide, lincosamide, streptogramin and oxazolidinone resistance genes) and by performing extensive literature searches. In the genotype-to-phenotype tables, the ResFinder and PointFinder entries have been associated with an AMR phenotype both at the antimicrobial class and at the antimicrobial compound level. A selection of antimicrobial compounds within each class was made to include antimicrobial agents important for clinical and surveillance purposes for the different bacterial species included (Table S1, available as Supplementary data at JAC Online). The genotype-to-phenotype tables also include: (i) the PubMed ID of relevant literature describing the respective AMR determinants and phenotypes, when available; (ii) the mechanism of resistance by which each AMR determinant functions; and (iii) notes, which may contain different information such as warnings on variable expression levels (inducible resistance, cryptic genes in some species, etc.), structural and functional information, and alternative nomenclature.
Bortolaia V., Kaas R.S., Ruppe E., Roberts M.C., Schwarz S., Cattoir V., Philippon A., Allesoe R.L., Rebelo A.R., Florensa A.F., Fagelhauer L., Chakraborty T., Neumann B., Werner G., Bender J.K., Stingl K., Nguyen M., Coppens J., Xavier B.B., Malhotra-Kumar S., Westh H., Pinholt M., Anjum M.F., Duggett N.A., Kempf I., Nykäsenoja S., Olkkola S., Wieczorek K., Amaro A., Clemente L., Mossong J., Losch S., Ragimbeau C., Lund O, & Aarestrup F.M. (2020). ResFinder 4.0 for predictions of phenotypes from genotypes. Journal of Antimicrobial Chemotherapy, 75(12), 3491-3500.
Publication 2020
Antibiogram Bacteria Cefoxitin CFC1 protein, human Chloramphenicol Chromosomes Ciprofloxacin Enterococcus faecalis Enterococcus faecium Faculty fluoromethyl 2,2-difluoro-1-(trifluoromethyl)vinyl ether Fusidic Acid Genes Genotype Lactams Lincosamides Linezolid Macrolides Microbicides Mupirocin Mutation Oxazolidinones Phenotype quinupristin-dalfopristin Rifampin Staphylococcus aureus Streptogramins Tetracycline Trimethoprim
2
Expanded Secondary Metabolite Detection in antiSMASH 2.0
Cited 25 times
In addition to the secondary metabolite cluster types supported in the original release of antiSMASH (type I, II and III polyketides, non-ribosomal peptides, terpenes, lantipeptides, bacteriocins, aminoglycosides/aminocyclitols, β-lactams, aminocoumarins, indoles, butyrolactones, ectoines, siderophores, phosphoglycolipids, melanins and a generic class of clusters encoding unusual secondary metabolite biosynthesis genes), version 2.0 adds support for oligosaccharide antibiotics, phenazines, thiopeptides, homoserine lactones, phosphonates and furans. The cluster detection uses the same pHMM rule-based approach as the initial release (17 (link)): in short, the pHMMs are used to detect signature proteins or protein domains that are characteristic for the respective secondary metabolite biosynthetic pathway. Some pHMMs were obtained from PFAM or TIGRFAM. If no suitable pHMMs were available from these databases, custom pHMMs were constructed based on manually curated seed alignments (Supplementary Table S1). These are composed of protein sequences of experimentally characterized biosynthetic enzymes described in literature, as well as their close homologs found in gene clusters from the same type. The models were curated by manually inspecting the output of searches against the non-redundant (nr) database of protein sequences. The seed alignments are available online at http://antismash.secondarymetabolites.org/download.html#extras. After scanning the genome with the pHMM library, antiSMASH evaluates all hits using a set of rules (Supplementary Table S2) that describe the different cluster types. Unlike the hard-coded rules in the initial release of antiSMASH, the detection rules and profile lists are now located in editable TXT files, making it easy for users to add and modify cluster rules in the stand-alone version, e.g. to accommodate newly discovered or proprietary compound classes without code changes. The results of gene cluster predictions by antiSMASH are continuously checked on new data arising from research performed throughout the natural products community, and pHMMs and their cut-offs are regularly updated when either false positives or false negatives become apparent.
The profile-based detection of secondary metabolite clusters has now been augmented by a tighter integration of the generalized PFAM (22 (link)) domain-based ClusterFinder algorithm (Cimermancic et al., in preparation) already included in version 1.0 of antiSMASH. This algorithm performs probabilistic inference of gene clusters by identifying genomic regions with unusually high frequencies of secondary metabolism-associated PFAM domains, and it was designed to detect ‘classical’ as well as less typical and even novel classes of secondary metabolite gene clusters. While antiSMASH 1.0 only generated the output of this algorithm in a static image, version 2.0 displays these additional putative gene clusters along with the other gene clusters in the HTML output. A key advantage of this is that these putative gene clusters will now also be included in the subsequent (Sub)ClusterBlast analyses.
Blin K., Medema M.H., Kazempour D., Fischbach M.A., Breitling R., Takano E, & Weber T. (2013). antiSMASH 2.0—a versatile platform for genome mining of secondary metabolite producers. Nucleic Acids Research, 41(Web Server issue), W204-W212.
Publication 2013
Amino Acid Sequence Aminocoumarins Aminoglycosides Anabolism Antibiotics Bacteriocins Biosynthetic Pathways Childbirth Classes Enzymes Furans Gene Clusters Generic Drugs Genes Genome Genomic Library homoserine lactone Indoles Lactams Melanins Natural Products Oligosaccharides Peptides Phenazines Phosphonates Polyketides Prognosis Protein Domain Proteins Ribosomes Secondary Metabolism Siderophores Terpenes
3
Comprehensive Antimicrobial Resistance Profiling
Cited 21 times
When AMR detection is switched on, Kleborate screens for known acquired AMR determinants using a curated version of the CARD AMR nucleotide database (v3.0.8 downloaded February 2020; see doi.org/10.6084/m9.figshare.13256759.v1 for full details on curation). Genes are identified using nucleotide BLAST (and amino acid search with tBLASTx if no exact nucleotide match is found). Gene truncations and spurious hits are identified as described above for virulence genes. Unlike the acquired forms, the intrinsic variants of oqxAB, chromosomal fosA and ampH are not associated with clinical resistance in KpSC and are therefore not reported. However, SHV, LEN or OKP β-lactamase alleles intrinsic to KpSC species are known to confer clinical resistance to penicillins and are reported in the Bla_chr column. Acquired SHV variants, and individual SHV sequence mutations known to confer resistance to extended-spectrum β-lactams or β-lactamase inhibitors, are reported separately (see Supplementary Note 3, Supplementary Data 11 and 12 for details).
Chromosomally encoded mutations and gene loss or truncations known to be associated with AMR are reported for genomes identified as KpSC species. These include fluoroquinolone resistance mutations in GyrA (codons 83 and 87) and ParC (codons 80 and 84)76 (link), and colistin resistance from truncation or loss of MgrB and PmrB57 –59 (link) (defined as <90% amino acid sequence coverage). Mutations in the OmpK35 and OmpK36 osmoporins reportedly associated with reduced susceptibility to β-lactamases41 (link),42 (link) are also screened and reported for KpSC genomes, and include truncation or loss of these genes and OmpK36GD and OmpK36TD transmembrane β-strand loop insertions41 (link). SHV β-lactamase, GyrA, ParC and OmpK mutations are identified by alignment of the translated amino acid sequences against a reference using BioPython, followed by an interrogation of the alignment positions of interest (see Supplementary Note 3, Supplementary Data 11 and 12 for a list of relevant positions).
AMR genes and mutations are reported by drug class, with β-lactamases further categorized by enzyme activity (β-lactamase, ESBL or carbapenemase, with/without resistance to β-lactamase inhibitors). Horizontally acquired AMR genes are reported separately from mutational resistance and contribute to the AMR gene count; these plus chromosomal mutations count towards the number of acquired resistance classes (intrinsic SHV alleles, reported in Bla_chr column, are not included in either count). Resistance scores are calculated as follows: 0 = no ESBL or carbapenemase, 1 = ESBL without carbapenemase (regardless of colistin resistance); 2 = carbapenamase without colistin resistance (regardless of ESBL); 3 = carbapenemase with colistin resistance (regardless of ESBL).
Lam M.M., Wick R.R., Watts S.C., Cerdeira L.T., Wyres K.L, & Holt K.E. (2021). A genomic surveillance framework and genotyping tool for Klebsiella pneumoniae and its related species complex. Nature Communications, 12, 4188.
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Publication 2021
Alleles Amino Acids Amino Acid Sequence beta-Lactamase beta-Lactamase Inhibitors beta-Lactam Resistance carbapenemase Chromosomes Codon Colistin enzyme activity Fluoroquinolones Genes Genome inhibitors Lactams Mutation Nucleotides Penicillin Resistance Pharmaceutical Preparations Susceptibility, Disease Virulence
4
Sepsis Fluid Resuscitation Protocol
Cited 15 times
This study was a restrictive observation study from the Medical Information Mart for Intensive Care IV (MIMIC-IV version 0.4) database from 2008 to 2019 [24 ]. An individual who has finished the Collaborative Institutional Training Initiative examination (Certification number 35931520 for author Zhou) can access the database. This is a longitudinal, single-center database including 257,366 individuals and 196,527 adults, and 11,263 patients with sepsis (Defined by sepsis-3 criteria [1 (link)]). In our study, we extracted patients’ parameters containing age, gender, ethnic group, admission type, insurance condition, the first 24-h Sequential Organ Failure Assessment (SOFA) score, Simplified Acute Physiology Score II (SAPS) score, mean arterial blood pressure (MAP), heart rate, respiratory rate, temperature, SpO2, total urine output during the first 24 h after ICU admission, lactate level, the use of vasopressors, weight, mechanical ventilation, renal replacement therapy (RRT), the stage of acute kidney injury (AKI), anamnesis (myocardial infarction, cancer, renal disease, cirrhosis and diabetes) and the type and volume of their fluid administration during the whole ICU stay. Vasopressors included norepinephrine, phenylephrine, epinephrine, vasopressin, dopamine, and dobutamine. For the antibiotics, Carbapenems (meropenem), Glycopeptide (vancomycin), β-lactams (ceftriaxone, cefotaxime, and cefepime), and Aminoglycosides (gentamicin and amikacin) were extracted into our analysis. In this study, types of administration for crystalloids and albumin including normal saline and lactated Ringer’s (LR) solution, while 5% and 25% HSA for colloids. The code of data extraction is available on Github (https://github.com/MIT-LCP/mimic-iv).
Adults patients (≥ 18 years) with sepsis and complete fluid administration records were screened in the analysis. The following exclusion criteria were used: (1) patients who have not received any crystalloids administration; (2) patients who received albumin longer than 24 h after the initiation of crystalloids administration or preceded the crystalloids. For patients who had ICU admission more than once, only data of the first ICU admission of the first hospital stay were included.
Zhou S., Zeng Z., Wei H., Sha T, & An S. (2021). Early combination of albumin with crystalloids administration might be beneficial for the survival of septic patients: a retrospective analysis from MIMIC-IV database. Annals of Intensive Care, 11, 42.
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Publication 2021
Adult Aftercare Albumins Amikacin Aminoglycosides Antibiotics, Antitubercular Carbapenems Cefepime Cefotaxime Ceftriaxone Colloids Diabetes Mellitus Dobutamine Dopamine Epinephrine Ethnicity Gender Gentamicin Glycopeptides Hormone, Antidiuretic Immunologic Memory Intensive Care Kidney Diseases Kidney Failure, Acute Lactams Lactated Ringer's Solution Lactates Liver Cirrhosis Malignant Neoplasms Mechanical Ventilation Meropenem Myocardial Infarction Norepinephrine Normal Saline Patients Phenylephrine Rate, Heart Renal Replacement Therapy Respiratory Rate Saturation of Peripheral Oxygen Septicemia SKAP2 protein, human Solutions, Crystalloid Urine Vancomycin Vasoconstrictor Agents
5
Pneumococcal Typing Pipeline with Illumina WGS
Cited 13 times
Of the 801 combined year 2009, 2012 and 2013 IPD isolates described in this study, serotypes, antimicrobial susceptibilities, MLSTs and pilus types for 699 (87.3%) were determined by the use of our pneumococcal typing pipeline with Illumina WGS fastq files provided by the Sanger group (n = 516 from year 2009 and 2012 IPD isolates) and the CDC Biotechnology Core Facility (n = 183 from year 2013 IPD isolates). The WGS-derived data from these 699 isolates recovered during 2009, 2012 and 2013 were used to supplement the already accumulated conventional serotyping, antimicrobial susceptibility testing, MLST, pilus locus PCR and PCR/ESI-MS data (described below). WGS-based identification of serotypes, pilus loci and non-β-lactam antimicrobial resistance features employed query DNA sequences described in Table S1 (serotypes and pili) and Table S2 (non-β-lactam antimicrobial resistance). Transpeptidase domain amino acid sequences of 277–359 residues from penicillin-binding proteins (PBPs) 1a, 2b, and 2x were extracted from approximately 1600 ABCs strains characterized over the years 1998–2013. From this, databases of 69, 77 and 127 unique transpeptidase domain amino acid sequences were compiled for PBP1a, PBP2b, and PBP2x, respectively (Tables S3–S5). Each unique sequence was assigned an identifier (sequences 1a-0 to 1a-68 for PBP1a, sequences 2b-0 to 2b-78 for PBP2b, and sequences 2x-0 to 126 for PBP2x). The three-number combination from each isolate was correlated with MICs for each of the six different β-lactam antibiotics. For example, the basally β-lactam-sensitive TIGR4 strain (genbank accession AE005672) contains a composite amino acid sequence pattern of 1a-0, 2b-0, and 2x-0 (abbreviated as 0:0:0). The corresponding DNA sequences (e.g. 1a-0, 2b-0, and 2x-0) are italicized. Full-length PBP genes are referred to with standard nomenclature (pbp1a, pbp2b, and pbp2x).
Detection of non-core genome-conferred resistance loci was performed according to homology with known determinants. Core genome-encoded resistance determinants (fluoroquinolones, co-trimoxazole, ribosomal protein mutation-conferred macrolide/lincosamide/streptogramin resistance, and rifampin) were screened by identifying specific amino acid substitutions with previously described targets (Table S2). Table S2 describes the sequence coordinates used for resistance queries. The bioinformatics methods used are described in Doc. S1.
Metcalf B.J., Gertz RE J.r., Gladstone R.A., Walker H., Sherwood L.K., Jackson D., Li Z., Law C., Hawkins P.A., Chochua S., Sheth M., Rayamajhi N., Bentley S.D., Kim L., Whitney C.G., McGee L, & Beall B. (2016). Strain features and distributions in pneumococci from children with invasive disease before and after 13-valent conjugate vaccine implementation in the USA. Clinical Microbiology and Infection, 22(1), 60.e9-60.e29.
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Publication 2016
abacavir Amino Acid Sequence Amino Acid Substitution Bacterial Fimbria Dietary Supplements DNA Sequence Fluoroquinolones Genes Genome Lactams Lincosamides Macrolides Microbicides Minimum Inhibitory Concentration Monobactams Mutation Penicillin-Binding Proteins Peptidyltransferase R Factors Ribosomal Proteins Rifampin Strains Streptococcus pneumoniae Streptogramins Susceptibility, Disease Trimethoprim-Sulfamethoxazole Combination

Most recents protocols related to «Lactams»

1
Profiling Antibiotic Resistance Genes in Leukemia
The quality-controlled, decontaminated forward and reverse paired sequences from the 127 leukemia and lymphoma samples were mapped to the pediatric-oncology-ARG-database created using bowtie2 (Langmead and Salzberg, 2012 (link)). Counts of sequence reads that mapped to each ARG in the database were obtained for each sample using samtools “sort”, “index” and “idxstat”. Mapped read counts were corrected by the number of sequence reads in each sample. While reads were mapped to all ARG sequences identified, only those ≥60% sequence identity were used in downstream analyses. Antibiotic classes were assigned to each ARGs using the CARD database designation, with two exceptions, 1) genes that occurred in an antibiotic class connected with β-lactam drugs were coded as β-lactam antibiotic class genes (i.e., carbapenem, penam, etc.), 2) genes that occurred in multiple antibiotic classes (i.e., penam, fluoroquinolone, glycopeptide), were coded as “multidrug” antibiotic class genes. Counts within samples assigned to the same gene were summed for downstream analysis. Only genes present in ≥5% of samples were used. Genes in four antibiotic classes were selected for closer analysis: β-lactam antibiotic class, glycopeptide antibiotic class, peptide antibiotic class, and multidrug antibiotic class. These classes were specifically selected as the β-lactam antibiotic class and multidrug antibiotic class potentially contains genes for resistance to β-lactam antibiotics, and the glycopeptide antibiotic class, peptide antibiotic class (a parent class to glycopeptide antibiotics), and multidrug antibiotic class potentially contains genes for resistance to vancomycin. All analyses were carried out on gene sequence data, no allele or SNP information was used.
MacDonald T., Dunn K.A., MacDonald J., Langille M.G., Van Limbergen J.E., Bielawski J.P, & Kulkarni K. (2023). The gastrointestinal antibiotic resistome in pediatric leukemia and lymphoma patients. Frontiers in Cellular and Infection Microbiology, 13, 1102501.
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Publication 2023
Alleles Antibiotics Antibiotics, Antitubercular Carbapenems Childbirth Classes Fluoroquinolones Genes Glycopeptides Lactams Leukemia Lymphoma Monobactams Neoplasms Parent Peptides Pharmaceutical Preparations Vancomycin
2
Steady-state kinetics of β-lactam hydrolysis
Steady-state kinetic experiments were performed following the hydrolysis of the β-lactams at 25 °C in 50 mM HEPES (pH 7.5) plus 100 μM ZnCl2. The data of the real-time absorbances of meropenem (298 nm), imipenem (297 nm), ceftazidime (257 nm), aztreonam (318 nm), cefotaxime (264 nm), cefepime (254 nm), piperacillin (232 nm), ceftriaxone (240 nm), and ampicillin (235 nm) were collected with a SHIMADZU UV2550 spectrophotometer (Kyoto, Japan). Kinetic parameters were determined under initial-rate conditions using the GraphPad Prism 8.1 software to generate Michaelis–Menten curves or by analyzing the complete hydrolysis time courses [9 (link)].
Ma W., Zhu B., Wang W., Wang Q., Cui X., Wang Y., Dong X., Li X., Ma J., Cheng F., Shi X., Chen L., Niu S, & Hao M. (2023). Genetic and enzymatic characterization of two novel blaNDM-36, -37 variants in Escherichia coli strains. European Journal of Clinical Microbiology & Infectious Diseases, 42(4), 471-480.
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Publication 2023
Ampicillin Aztreonam Cefepime Cefotaxime Ceftazidime Ceftriaxone HEPES Hydrolysis Imipenem Kinetics Lactams Meropenem Piperacillin prisma
3
Optimizing Osteomyelitis and Septic Arthritis Management
This is a monocentric, retrospective, observational, pre-post, quasi-experimental study, set at the Department of Women's and Children's health in Padua, Northern Italy.
Between the end of 2015 and the beginning of 2016, OM/SA internal guidelines were developed by the Division of Pediatric Infectious Diseases and the Pediatric Rheumatology Unit of Padua University Hospital, summarizing international literature evidence. In addition, three training sessions with an overview of the guidelines and treatment rationale were offered to attending physicians and residents.
The impact of the intervention was assessed by comparing the four-year period before OM/SA guidelines implementation (pre-intervention: January 1st, 2012, through December 31st, 2015) to the six years and ten months after intervention (post-intervention: January 1st, 2016, through October 31st, 2022).
According to the implemented guidelines, in fully vaccinated patients older than 3 months, an IV empirical antibiotic therapy is started with a first-generation cephalosporin (cefazolin 150–200 mg/kg/day) for 5–7 days in uncomplicated forms, as the prevalence of MSSA is above 90% in the considered area (7 (link), 8 (link)). The subsequent shift in case of identification of the causative microorganism is to targeted oral therapy, otherwise to an oral antibiotic with the same spectrum activity as the IV therapy (shift from cefazolin to cefalexin or cefuroxime axetil). The total suggested duration of OM treatment is three-four weeks in case of clinical improvement with a normalized C-reactive protein (CRP) before the twentieth day of therapy. The total duration of SA is two-three weeks if isolated, or four weeks in case of associated OM (7 (link)).
Broad-spectrum antimicrobials were defined as: β-lactam and β-lactamase inhibitor combinations, third-generation cephalosporins, clindamycin, glycopeptides, fluoroquinolones, and macrolides. Therapeutic regimens including at least one broad-spectrum prescription, despite the association with amoxicillin or oxacillin, were considered broad-spectrum.
Minotti C., Tirelli F., Guariento C., Sturniolo G., Giaquinto C., Da Dalt L., Zulian F., Meneghel A., Martini G, & Donà D. (2023). Impact of guidelines implementation on empiric antibiotic treatment for pediatric uncomplicated osteomyelitis and septic arthritis over a ten-year period: Results of the ELECTRIC study (ostEomyeLitis and sEptiC arThritis tReatment in children). Frontiers in Pediatrics, 11, 1135319.
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Publication 2023
Action Spectrum Amoxicillin Antibiotics beta-Lactamase Inhibitors Cefazolin cefuroxime axetil Cephalexin Cephalosporins Children's Health Clindamycin Communicable Diseases C Reactive Protein Fluoroquinolones Glycopeptides Lactams Macrolides Microbicides Oxacillin Patients Physicians Therapeutics Treatment Protocols
4
Comprehensive Antibiotic Resistance Profiling
A total of 427,495 bacterial genomes consisting of 47,582,748 sequences (NCBI GenBank database, 2019-10-22) [32 ] were analyzed using fARGene (v0.1, default parameters). We used fARGene in this study since it has been shown to have a high performance and its predictions have been experimentally verified on several occasions [12 , 13 (link), 15 , 16 (link), 33 , 34 (link)]. fARGene was executed using 17 hidden Markov model gene profiles for ARGs conferring resistance to five major classes of antibiotics: for β -lactams, we defined gene classes A, B1/B2, B3, and D [13 (link), 33 ]; for aminoglycosides, gene classes aac(2′) , aac(3), aac(6′) , aph(2″) , aph(3′) , and aph(6); for macrolides, gene classes erm and mph [12 ]; for quinolones, gene class qnr [16 (link)]; and for tetracyclines, gene classes efflux pumps, inactivating enzymes (monooxygenases), and ribosomal protection genes (RPGs) [15 ] (downloaded from https://github.com/fannyhb/fargene). All matches satisfying the previously reported model-specific significance thresholds for full-length genes were considered to be putative ARGs and stored for further analysis [12 , 13 (link), 16 (link), 33 , 35 (link)].
Inda-Díaz J.S., Lund D., Parras-Moltó M., Johnning A., Bengtsson-Palme J, & Kristiansson E. (2023). Latent antibiotic resistance genes are abundant, diverse, and mobile in human, animal, and environmental microbiomes. Microbiome, 11, 44.
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Publication 2023
Aminoglycosides Antibiotic Resistance, Microbial Childbirth Classes Enzymes Genes Genetic Profile Genome, Bacterial Lactams Macrolides Mixed Function Oxygenases Quinolones Ribosomes Tetracyclines
5
Pediatric Ceftolozane/Tazobactam vs Meropenem for cUTI
Randomized participants were stratified and dosed by age group. The selected doses were based on population pharmacokinetic modeling and simulations.18 (link) For participants in the ceftolozane/tazobactam group, those 12 to <18 years of age were given 1.0 g ceftolozane and 0.5 g tazobactam (the dose indicated for adult patients with cUTI),15 and those from birth to <12 years of age were given 20 mg/kg ceftolozane and 10 mg/kg tazobactam (maximum of 1.0 g ceftolozane and 0.5 g tazobactam per dose). All participants in the meropenem group received 20 mg/kg (maximum of 1.0 g per dose), with higher dosing up to 30 mg/kg for participants who were 14 days to <3 months of age permitted at the investigator’s discretion. Each dose of ceftolozane/tazobactam or meropenem was administered as a 60-minute (±10 minutes) infusion and dosed every 8 hours (±1 hour) after the previous infusion.
Treatment duration was 7-14 days. After 3 days (9 doses) of IV therapy, optional open-label, standard-of-care, oral step-down therapy was permitted at the investigator’s discretion, with choice of therapy guided by culture and antibacterial susceptibility results, as well as local standard of care for treatment of cUTI. Recommended options for oral step-down therapy were β-lactam/β-lactamase inhibitor combinations, cephalosporins, fluoroquinolones, nitrofurantoin, trimethoprim‚ or trimethoprim/sulfamethoxazole.
Roilides E., Ashouri N., Bradley J.S., Johnson M.G., Lonchar J., Su F.H., Huntington J.A., Popejoy M.W., Bensaci M., De Anda C., Rhee E.G, & Bruno C.J. (2023). Safety and Efficacy of Ceftolozane/Tazobactam Versus Meropenem in Neonates and Children With Complicated Urinary Tract Infection, Including Pyelonephritis: A Phase 2, Randomized Clinical Trial. The Pediatric Infectious Disease Journal, 42(4), 292-298.
Publication 2023
Adult Age Groups Anti-Bacterial Agents beta-Lactamase Inhibitors Birth ceftolozane ceftolozane - tazobactam Cephalosporins Fluoroquinolones Lactams Meropenem Nitrofurantoin Patients Susceptibility, Disease Tazobactam Therapeutics Trimethoprim Trimethoprim-Sulfamethoxazole Combination

Top products related to «Lactams»

1
Etest by bioMérieux
Sourced in France, Sweden, United States, Germany, United Kingdom, Denmark, Italy, Australia, Spain, Switzerland, Japan
Etest is a quantitative antimicrobial susceptibility testing (AST) method developed by bioMérieux. It provides minimum inhibitory concentration (MIC) values for specific antimicrobial agents. Etest utilizes a predefined antimicrobial gradient on a plastic strip to determine the MIC of a tested microorganism.
2
Vitek 2 system by bioMérieux
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The Vitek 2 system is an automated microbiology platform designed for the rapid identification and antimicrobial susceptibility testing of microorganisms. The system utilizes miniaturized biochemical testing to provide accurate results for a wide range of bacterial and yeast species.
3
Mueller hinton agar (mha) by Thermo Fisher Scientific
Sourced in United Kingdom, United States, Italy, Germany, France, India, Spain, China
Mueller-Hinton agar is a microbiological growth medium used for the antimicrobial susceptibility testing of bacteria. It is a standardized agar formulation that supports the growth of a wide range of bacteria and allows for the consistent evaluation of their susceptibility to various antimicrobial agents.
4
Ciprofloxacin by Thermo Fisher Scientific
Sourced in United Kingdom, United States, Germany, Italy, Belgium, Ireland, India
Ciprofloxacin is a synthetic antibiotic that belongs to the fluoroquinolone class. It is a broad-spectrum antimicrobial agent effective against a variety of Gram-positive and Gram-negative bacteria.
5
Polymer g by Merck Group
Polymer G is a laboratory equipment product manufactured by Merck Group. It is designed for use in various scientific research and analytical applications. The core function of Polymer G is to facilitate the processing and analysis of polymeric materials.
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Oxe 02 by BASF
Sourced in China
The OXE-02 is a laboratory equipment product designed for oxidation experiments. It provides a controlled environment for conducting chemical reactions involving the introduction of oxygen or other oxidizing agents. The core function of the OXE-02 is to facilitate the study and analysis of oxidation processes in a laboratory setting.
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Gentamicin by Thermo Fisher Scientific
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Gentamicin is a laboratory reagent used for the detection and quantification of the antibiotic gentamicin in biological samples. It is a commonly used tool in research and clinical settings.
8
Cefotaxime by Thermo Fisher Scientific
Sourced in United Kingdom, United States, Germany, Italy, Denmark
Cefotaxime is a third-generation cephalosporin antibiotic used to treat a variety of bacterial infections. It functions as a bactericidal agent by inhibiting cell wall synthesis in susceptible bacteria.
9
Prism 6 by GraphPad
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Prism 6 is a data analysis and graphing software developed by GraphPad. It provides tools for curve fitting, statistical analysis, and data visualization.
10
Ampicillin by Merck Group
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Ampicillin is a broad-spectrum antibiotic used in laboratory settings. It is a penicillin-based compound effective against a variety of gram-positive and gram-negative bacteria. Ampicillin functions by inhibiting cell wall synthesis, leading to bacterial cell lysis and death.

More about "Lactams"

Lactams, a diverse class of organic compounds characterized by a cyclic amide structure, are found in a variety of pharmaceuticals and natural products, including crucial antibiotics like penicillins and cephalosporins.
These heterocyclic rings exhibit a wide range of biological activities and are extensively utilized in medicinal chemistry research.
The Etest and Vitek 2 system are commonly used methods for determining the antimicrobial susceptibility of microorganisms, often involving the use of Mueller-Hinton agar.
Ciprofloxacin, a fluoroquinolone antibiotic, and Polymer G, a polymeric compound, are examples of lactam-based molecules with diverse applications.
OXE-02, a novel lactam-containing compound, has shown promise in various research areas.
Gentamicin and Cefotaxime, two other antibiotics, are also related to the lactam class of compounds.
Prism 6, a data analysis software, can be utilized to help streamline research involving lactams.
PubCompare.ai's AI-driven platform can optimize your lactam research by providing easy access to protocols from the literature, preprints, and patents, as well as AI-powered comparisons to identify the best approaches and products.
Ampicillin, a widely used penicillin-derived antibiotic, is another example of a lactam-based compound with significant medical and research applications.
Leveraging the insights gained from the MeSH term description and metadescription, researchers can explore the diverse world of lactams, unlocking new discoveries and advancements in the field of medicinal chemistry and beyond.