Antibiotics

Co-administration of phages and antibiotics has been proposed as a therapeutic approach against antibiotic-resistant bacteria. The relationship, however, between antibiotic resistance and phage resistance in clinical isolates is unclear. Here, we examine associations between phage and antibiotic resistance profiles across a panel of Pseudomonas aeruginosa clinical isolates from the Centers for Disease Control (CDC) and Food and Drug Administration (FDA) Antimicrobial Resistance Isolate (ARI) Bank comprising 55 clinical strains with full genome sequences and antibiotic susceptibility testing (AST) data for 11 clinically relevant antibiotics. As phages in this study, we use three well-characterized, morphologically distinct phages, OMKO1, Luz19, and PAML31-1. We screen for phage resistance using a growth suppression assay, then conduct statistical analysis against antibiotic MIC (Minimum Inhibitory Concentration) data provided by the CDC to define association patterns across this dataset. We find multiple significant susceptibility correlations between pairs of antibiotics and phages, and a positive overall association between average phage resistance and antibiotic resistance across the 55 strains, even controlling for phylogenetic associations (=0.358, p<0.005). We conclude that phage and antibiotic resistance are positively associated across this clinical isolate collection, suggesting that the two resistance phenotypes are not independent in P. aeruginosa. These findings have implications for the development of phage-antibiotic cocktails.

Shigella flexneri is an enteric pathogen responsible for causing shigellosis, a type of bacillary dysentery of significant global health concern. The increasing prevalence of antibiotic resistance has driven the search for alternative treatments, including bacteriophage (phage) therapy. However, the effectiveness of orally administered phages for enteric pathogens depends on their ability to survive passage through the gastrointestinal tract. In this study, the ability of bacteriophage Sf14 to maintain infectivity was evaluated under simulated gastrointestinal conditions using a modified INFOGEST 2.0 in vitro digestion model. This model includes salivary, gastric, and intestinal fluids with physiologically relevant compositions of electrolytes, bile salts, and enzymes. Phages were incubated in each simulated phase at standard physiological temperature, then tested for infectivity using quantitative plaque assays. Results show that Sf14 remained stable during the short duration of the oral phase and for the duration of the intestinal phase. By contrast, survival in simulated gastric fluid required a pH of 2.75 or higher, with rapid and substantial loss of infectivity at pH 2.5 and below. These findings demonstrate that while Sf14 is stable in oral and intestinal environments, the gastric phase poses a critical barrier to phage survival. With in vivo fasting gastric pH ranging from 1.5 to 3, encapsulation would enable the most flexible oral phage therapy against enteric pathogens, but ingestion after eating or alongside antacids may be sufficient.

Urinary tract infections (UTIs) are frequently caused by Escherichia coli and are increasingly associated with antimicrobial resistance, highlighting the need for alternative therapies. Although phage therapy is a promising approach, the rational selection of phages and phage cocktails remains challenging, particularly when detailed genomic information on the infecting strain is unavailable. In this study, we isolated 18 phages from environmental samples collected in Sherbrooke, Quebec, Canada. Genome sequencing identified 15 pure lytic phages representing diverse taxonomic groups and revealed prophage-derived contaminants in three isolates, underscoring the importance of genomic validation during phage discovery. Host range was determined using efficiency-of-plating (EOP) assays against UTI-associated E. coli isolates. Based on host-range overlap and cumulative EOP values, we developed a phenotype-based framework for phage cocktail design and classified combinations as redundant or complementary. Complementary cocktails composed of phages with distinct host ranges and high infection effectiveness consistently outperformed redundant combinations in time-kill assays, demonstrating that host-range diversity and lytic effectiveness are independent properties that should be considered separately during cocktail design. To evaluate cocktail performance under physiologically relevant conditions, the most effective combinations were tested in artificial urine. Both cocktails exhibited reduced activity compared with standard laboratory media, indicating that environmental conditions strongly influence phage-host interactions. Together, our results demonstrate that host-range overlap and cumulative infection effectiveness provide a practical framework for identifying effective phage combinations in the absence of detailed bacterial genomic information and may facilitate the rational development of phage therapies for UTIs.

Inflammatory bowel disease challenges modern gastroenterology due to high relapse rates. This study evaluated the effects of medicinal fungal sclerotium Fu Ling (Wolfiporia cocos), its derived {beta}-1,3-1,6-Glucan, Bacillus coagulans GBI-30, 6086, and their combinations in dextran sulfate sodium-induced colitis in male BALB/c mice. The {beta}-glucan-B. coagulans combination significantly improved body weight, disease activity index, colon length and architecture, mucus secretion, and cecal fermentation over single ingredient. Consistently, this combination increased total short-chain fatty acids production, particularly acetate, improved gut tight-junction organization and reduced myeloperoxidase accumulation. Shotgun metagenomic sequencing indicated that this combination reshaped the gut microbiota, notably enriching Anaeromassilibacillus sp., which associated with improved clinical feature. These findings highlight the potential of fungal-derived {beta}-glucan and probiotic combinations as functional food ingredients for mitigating intestinal inflammation and supporting barrier repair.

Background: Bovine respiratory disease (BRD) is a major cause of antimicrobial use in cattle, raising concerns about antimicrobial resistance (AMR). This systematic review estimated pooled AMR proportions in BRD pathogens: Mannheimia haemolytica, Pasteurella multocida, and Histophilus somni, and assessed temporal and geographic trends in resistance. Methods: Five antimicrobials commonly used for BRD treatment were evaluated: penicillin G (PEN), tetracycline (TET), florfenicol (FLO), tulathromycin (TUL), and enrofloxacin (ENR). Following PRISMA guidelines, 1,097 records were screened and 24 studies met inclusion criteria. Study quality and risk of bias were assessed, and random-effects meta-analyses estimated pooled proportions of resistant isolates by antimicrobial, continent and period. Results: A total of 13,949 bacterial isolates were analysed including P. multocida (5,615), M. haemolytica (5,585), and H. somni (2,749). TET resistance was highest across all pathogens (12-30%), followed by TUL (6-11%), PEN (4-12%), FLO (0.5-1.6%) and ENR (0.2-1.1%). TET resistance in M. haemolytica and P. multocida, and FLO resistance in P. multocida were significantly more frequent in North America than in Europe (p[&le;]0.05). TUL resistance increased significantly in P. multocida after 2013 (p=0.038), with similar non significant trends in M. haemolytica and H. somni. FLO resistance decreased significantly in H. somni after 2013 (p=0.013). Egger's test identified significant funnel plot asymmetry for ENR resistance in H. somni and PEN resistance in M. haemolytica, suggesting possible small study effects. Conclusion: These results offer insights into distribution of phenotypic resistance across pathogens and regions, informing BRD antimicrobial treatment guidelines and One-Health antimicrobial stewardship aimed at preserving the effectiveness of medically important antimicrobials.

Antimicrobial resistance is a global One Health threat connecting antimicrobial use in human health, animal husbandry, and companion animal health with concern for persistence in environmental reservoirs. Complicating this threat is the gap that exists in our understanding of the intersection of antimicrobial resistance among humans and our companion and food production animals. This study applies a visual and statistical approach to further understand antimicrobial resistance characteristics and relatedness of Escherichia coli found in humans, dogs and cattle. The primary study collection included third-generation cephem resistant (3GCR) E. coli isolates recovered from human, dog, and cattle gastrointestinal specimens and secondarily human and dog isolates recovered from infection sources, primarily urinary tract infections. We previously reported on the transferable gene targets encoding for 3GCR in colonizing isolates and here further identified the familial-like clonal group of each resistant isolate using a novel clonotype diagnostic (septatyping). Together, this approach identified distinct genetic signatures among these 3GCR isolates, many of which are peculiar to their respective host species. We found that the overlap measured by the correlation in abundance of shared clonotypes of resistant E. coli among hosts revealed statistically greater similarity between dogs and humans than between cattle and humans. Yet, the reservoir of AMR genes was highest in cattle and secondarily dogs. While these findings demonstrate that clonotypes of 3GCR E. coli in humans, dogs and cattle display significant host specificity, transient colonization from a host enriched with resistant strains may still pose considerable risk of horizontal transfer of resistance genes between hosts living in proximity to each other.

BackgroundMethicillin-resistant Staphylococcus aureus (MRSA) is one the most common cause of post-surgical infections in Malawi and poses a significant public health challenge due to resistance to commonly used antibiotics. We isolated and evaluated the stability and lytic activity of a MRSA-specific bacteriophage (Staphylophage) from Mzuzu Central hospital (MZCH) sewage against MRSA strains isolated from surgical wards. MethodsA prospective in vitro experimental study was conducted using 56 pus swabs collected from post-surgical patients at Mzuzu Central Hospital (MZCH), Malawi. Standard microbiological methods and VITEK analysis were used for bacterial isolation, identification and antimicrobial susceptibility testing of Staphylococcus aureus and MRSA according to the 2024 EUCAST guidelines. A lytic Staphylophage was isolated and purified from sewage wastewater using filtration, enrichment, and double-layer agar techniques. The purified Staphylophage was evaluated for its lytic activity through host range testing and stability under ultraviolet (UV) exposure (up to 60 minutes), different pH levels (2-12), and temperatures (4{degrees}C, -20{degrees}C, and -80{degrees}C). ResultsOut of 56 bacterial isolates, 18 (32.1%) were S. aureus, of which 11 (61.1%) were MRSA. The isolated Staphylophage showed lytic activity against 87% of Staphylococcus species tested. The phage remained stable at temperatures between -80{degrees}C and 4{degrees}C and across a pH range of 2- 12. It also retained viability after UV exposure for up to 15 minutes, although a reduction in phage titre was observed after 30 minutes. ConclusionsA lytic Staphylophage isolated from hospital sewage at MZCH demonstrated activity against Staphylococcus species, including MRSA strains from post-surgical wound infections. These findings illustrate the feasibility of generating candidate phages for alternative therapeutic approaches in a central hospital setting in Malawi.

Methicillin-resistant Staphylococcus aureus (MRSA) is non-susceptible to beta-lactams. Blockade of cell wall biosynthesis is a potential target for beta-lactam enhancement but requires further investigation. A butyrolactone derivative enhanced beta-lactams against MRSA strains by reducing the availability of D-Ala-D-Ala. Unlike D-cycloserine, it did not inhibit D-Ala-D-Ala ligase (Ddl). Nor did it show an additive or synergistic effect when combined with cycloserine, indicating a unique mechanism for blocking cell wall precursor production that does not involve the traditional Lipid II pathway. Notably, beta-lactam potentiation by our chemical or D-cycloserine was highly dependent on the intrinsic autolytic ability of the tested MRSA strains. Strains that resisted lysis upon Triton X-100 exposure showed a minimal increase in beta-lactam susceptibility, whereas highly autolytic strains showed significant changes in their beta-lactam MICs. We have thus identified autolytic ability as the Achilles Heel in the strategy of targeting cell wall biosynthesis for beta-lactam potentiation.

Modern clinical medicine depends on reducing complex human realities into forms that support knowledge, judgment, and action. Such reduction is indispensable to scientific medicine, but necessarily selective. A medical framing may therefore remain well warranted within medicine while becoming insufficient in relation to the reality of a particular patient. What happens clinically when the adequacy of such a framing itself becomes uncertain remains insufficiently understood. We conducted an abductive, theory-generating qualitative study of 44 patients who attended a supplementary Dialogue-Based Outpatient Clinic within a breast oncology service in Japan between 2021 and 2023, comprising 111 consultations. The clinic had no predefined clinical agenda, allowing patients to raise concerns that mattered to them. Through iterative comparison within and across cases, we examined how patients' concerns were understood and responded to clinically. Across cases, a recurrent clinical process became apparent when patient reality called the adequacy of existing medical framing into question. Exploration of patients' concerns could expose a consequential mismatch between their reality and the framing through which medicine understands and represents clinical reality. Such mismatches prompted inquiry into medical framing to identify what required reopening. Reopening occurred when the identified framing, previously treated as provisionally settled, became reconsiderable in relation to the patient's reality. Reconsideration involved examining what had been reopened and exploring clinical responses through dialogue between clinician and patient, followed by a clinical response and provisional closure. We describe this recurrent process as Clinical Epistemic Reopening (CER). CER identifies a clinical process through which the framing produced by medicine's necessary selectivity in making complex reality clinically knowable and actionable can itself become reconsiderable when patient reality reveals its limits. CER can thereby reverse the usual direction of clinical scrutiny: aspects of medicine that ordinarily function as means of understanding and acting upon the patient can themselves become objects of clinical inquiry. CER thus allows medicine to remain open to patient reality beyond the limits of its existing framings.

Purpose: Vancomycin-resistant Gram-positive organisms represent a potential therapeutic challenge in endophthalmitis. To evaluate alternative treatment options, the FDA-approved oxazolidinones linezolid (LZD) and tedizolid (TZD) were tested against a collection of Gram-positive bacterial endophthalmitis isolates. Methods: Minimum inhibitory concentrations (MICs) were determined using epsilometers (Etest strips) for coagulase negative staphylococci (CoNS, n=20), Staphylococcus aureus (n=18), Bacillus species (n=10), Enterococcus species (n=5), and Streptococcus pneumoniae (n=1). Available CLSI and EUCAST breakpoints were applied to determine susceptibility. Results: TZD exhibited a >5-fold reduction in median MIC compared with LZD across all organisms tested (p<0.0001). MIC90 values for CoNS were 2.0 /ml for LZD and 0.25 /ml for TZD. For S. aureus, MIC90 values were 1.5 /ml (LZD) and 0.19 /ml (TZD). For Bacillus spp., MIC90 values were 1.0 /ml (LZD) and 0.25 /ml (TZD). Among Enterococcus species, the MIC range was 0.5-4.0 /ml (LZD) and 0.064-0.75 /ml (TDZ). The single S. pneumoniae strain had a MIC of 0.5 for LZD and 0.064 for TZD. All isolates were susceptible to TZD. One Enterococcus isolate was non-susceptible to LZD; the remaining isolates were susceptible. Conclusions: LZD and TZD demonstrated in vitro activity against Gram-positive bacterial endophthalmitis isolates, with TZD displaying consistently lower MICs than LZD. These findings suggest that oxazolidinones may represent potential alternatives when vancomycin cannot be used, including infections caused by vancomycin-resistant Gram-positive organisms. Given their excellent oral bioavailability, favorable safety profile, and reported anti-virulence effects in certain pathogens, further evaluation of oxazolidinones for the treatment of intraocular infections is warranted.

Objective: To determine outcomes by referral route (any Advice and Guidance [A&G] versus elective referrals only) for patients with inflammatory bowel disease (IBD), Parkinson's disease, and systemic lupus erythematosus (SLE). Design: Population-based retrospective cohort study. Setting: Linked Clinical Practice Research Datalink (CPRD) Aurum primary care records, 2015-2022. Participants: Patients with incident diagnosis of IBD, Parkinson's disease, or SLE. Main Outcome Measures: Time from the earliest recorded A&G or elective referral to diagnosis, first recorded definitive treatment and first attended outpatient appointment. Secondary outcomes included counts of primary care consultations, prescriptions, referrals, and outpatient appointments. Propensity score weighted flexible parametric survival analyses accounted for differences between exposure groups. Results: Among 71,145 eligible patients, A&G was recorded for 1,137 (3.0%) with IBD, 971 (3.4%) with Parkinson's, and 243 (4.9%) patients with SLE. Compared with elective referral only, A&G was associated with slower time to diagnosis for IBD (adjusted median difference 15.9 weeks; hazard ratio 0.58, 95% confidence interval 0.52 to 0.66), Parkinson's disease (11.4 weeks; 0.57, 0.51 to 0.64), and SLE (6.3 weeks; 0.82, 0.73 to 0.91). However, A&G was not associated with a longer time to treatment or first attended outpatient appointment. An increase in primary care consultations following A&G was observed in patients later diagnosed with IBD and SLE. Conclusion: A&G was associated with a longer diagnostic interval than elective referral only. These findings do not establish that A&G caused diagnostic delay. A&G might be used at an earlier stage of more complex diagnostic pathways.

This study aims to identify potential inhibitors of the Ag85C enzyme from Mycobacterium tuberculosis through primary docking, pharmacophore modelling, and ADME/pharmacokinetics analysis. Delamanid and Pretomanid emerged as the top hits in primary docking, demonstrating strong binding affinities and interactions with key active site residues. A robust pharmacophore model was developed, identifying essential features for binding and used to screen 4254 antituberculotic compounds, yielding three promising candidates: F0314-0040, F0398-0505, and F0349-2716. These compounds exhibited high binding affinities in major docking studies. ADME and pharmacokinetics analysis revealed favorable Drug likeness and absorption profiles, supporting their potential as effective antituberculotic agents. The integration of computational methods provided a comprehensive approach for rational drug design.

Carbohydrate inducible promoters on expression plasmids are widely used for biotechnology and basic science research. However, using carbohydrates for inducers has drawbacks including influencing bacterial metabolism, the inducer being used as a carbon source by the bacteria, high background expression, and only a subset of cells experiencing promoter activation. Furthermore, some bacteria including the pathogen Acinetobacter baumannii currently lack good carbohydrate-inducible promoters. To address this issue, a tetracycline-inducible promoter, PtetB, isolated from A. baumannii was cloned and evaluated in a number of important bacteria: Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Pseudomonas fluorescens, and Serratia marcescens. A highly sensitive luxCDABE reporter was used to evaluate promoter activity. S. marcescens strains with elevated and reduced cyclic-AMP levels were used to evaluate the impact of cAMP on PtetB function. The PtetB promoter was induced over 800-fold in A. baumannii and 10-750-fold inducible in the other tested species. Background expression was lower from PtetB in the pseudomonads than previously described carbohydrate inducible promoters. Data indicated that the PtetB promoter system may be a useful tool for future basic science research with the tested bacteria.

Aims Honey represents a distinct microbial habitat, imposing physicochemical stresses on its resident microbiota while also serving as a potential source of beneficial microorganisms. This study aimed to isolate lactic acid bacteria (LAB) from Korean wildflower honey and characterize their gastrointestinal (GI) and physiological stress tolerance, adhesion-related properties, functional characteristics, and safety to evaluate their potential as probiotic candidates. Methods and Results Two Streptococcus salivarius strains, DOW-5A and DOW-10, were isolated from Korean wildflower honey and identified by phenotypic and molecular analyses. Both strains survived in sequential exposure to simulated GI conditions and showed tolerance to physiological stresses. DOW-5A maintained higher viability during the simulated gastric phase, whereas DOW-10 showed an initial decrease in viable counts followed by an increase during the simulated intestinal phase. The two strains also exhibited various probiotic characteristics, including mucin adhesion and antioxidant activity. Atypical, crystalline colony morphologies associated with EPS production were observed when sucrose was supplied as a carbon source. Both strains formed biofilms, while DOW-5A showed a marked increase in biofilm formation upon sucrose supplementation. Neither strain showed gelatinase or hemolytic activity or significant cytotoxicity toward Caco-2 cells. Impact Statement In this study, we isolated two honey-derived S. salivarius strains with high probiotic potential. Our findings highlight wildflower honey as a potential reservoir of LAB with traits relevant to survival under GI and physiological stresses, as well as various probiotic traits.

Introduction: In vivo, temporal, and personalized data on immunological-antibiotic interactions may provide richer, earlier information that improves infection treatment. To test this hypothesis, we applied a proof-of-concept approach to evaluate a non-reductionist methodology. Methods: A non-reductionist, data-driven, pattern recognition-based combinatorial method that captures relationships was evaluated with blood leukocyte data collected from 401 individuals from Greece [n=331] and the US [n=70] who experienced sepsis, pneumonia, endocarditis, tuberculosis, syphilis, skin and soft tissue, intra-abdominal, or urinary tract infections associated with meningitis. Results: While ambiguity was observed when variables were measured in isolation by a reductionist alternative, ambiguity was prevented and hidden information was uncovered when complex dynamics were assessed by the non-reductionist method. The combinatorial approach grouped together observations that displayed similar immune profiles, distinguished those with different mortality risks, identified antibiotics that modulated specific leukocytes, differentiated two types of non-responsiveness (associated or not associated with antibiotics), and facilitated earlier and personalized evaluation of therapies. For instance, in tuberculosis, blood monocytes were modulated by isoniazid-related antimicrobials. Discussion: Across numerous syndromes, the non-reductionist method extracted more information from the same data than the reductionist alternative. If corroborated, non-reductionist methodologies may promote research and support personalized medicine.

In 1998 we predicted percent human intestinal absorption (HIA) for 86 drug and drug-like compounds from six molecular descriptors chosen by a genetic algorithm with a small neural network serving as the fitness function. That result rested on one division of the compounds into three sets: training, cross-validation and external prediction. Repeating the division shows it was a rather fortunate one. An extraction is one random draw from a wide distribution, so we repeat every experiment 250 times and report the result as a distribution. Across 250 stratified extractions, 14 match the published cross-validation error and only one matches the published external prediction error. Reconstructed this way, the published six descriptors give a mean extraction error roughly twice the external prediction value we reported in 1998 (Table 1). We then applied the same six descriptors to a larger set of 780 compounds from a public compilation. Under the 1998 network they give 22.50 %HIA units on training compounds against 25.77 on extracted compounds, whereas on the 86 they give 13.43 against 30.39. More compounds close the gap between fitting and prediction. Four datasets are modeled here: 780 small molecules with HIA measured in man, 3,771 small molecules and 1,281 cyclic peptides measured across Caco-2 cell monolayers, and 7,298 cyclic peptides measured across artificial membranes. Each is its own prediction problem, and one procedure is applied to all four. A genetic algorithm chooses which descriptors to use and how many, and a random forest grades each choice on compounds its own trees never saw. The descriptors chosen most often across the 250 extractions form one consensus set for each dataset. For absorption, 25 consensus descriptors under a random forest reach an extraction rms of 20.47 %HIA units at R 0.76. On the same compounds and the same extractions, the six 1998 descriptors under the 1998 network reach 25.77 at R 0.59. The four models are served at predicthia.ai, where a structure can be drawn or pasted, scored against its training set for similarity, and the training data with fitted models downloaded. Each model served is its fixed consensus set fitted on every compound in its dataset; the accuracy quoted beside a prediction comes from evaluating that same set across 250 extractions (Table 3). The fixed sets hold 25 descriptors for absorption, 55 for Caco-2 small-molecule permeability, 50 for Caco-2 peptide permeability and 25 for artificial-membrane permeability. Keywords: human intestinal absorption; QSPR; genetic algorithm; descriptor selection; cyclic peptides; membrane permeability; oral bioavailability; repeated extraction

Background: Surveillance tells laboratories which antimicrobial resistance genes are circulating now, but not which will change next. We built a model that forecasts, for each resistance gene and year, whether the following year brings a previously unseen allele (sequence variant), called emergence, or a change in the most common allele, called turnover. We tested it separately in Klebsiella pneumoniae and Acinetobacter baumannii. Results: We used genomes annotated with AMRFinderPlus: 2,385 gene-years across 331 genes for K.pneumoniae and 1,059 across 216 for A. baumannii. To remove the effect of sequencing effort, each gene-year was sampled to 10 records and the analysis repeated 25 times. Models were trained on earlier years and tested on later ones, and on genes held out of training. On later years every model ranked genes by risk better than simple baselines in both organisms, and results for held-out genes were close. In K.pneumoniae, turnover was predicted better than emergence (best area under the ROC curve, AUROC, 0.909 versus 0.819). In A. baumannii the order reversed (emergence 0.789, turnover 0.722). The two events also relied on different features. Emergence depended mainly on how many alleles a gene had already accumulated, in both organisms. Turnover in K. pneumoniae depended mainly on how dominant the leading allele already was, and a stability index added a small gain. In A. baumannii it was spread across many weaker features. There, 56% of changes in the leading allele involved only alleles already seen, against 23% in K. pneumoniae, which may make them harder to predict. Conclusions: Changes in resistance genes can be forecast a year ahead from routine genomic surveillance data, including for genes the model has not seen. How well it works, and what it depends on, differs between organisms, so models should be built and validated for each organism, not assumed to transfer. Such models could help laboratories decide which resistance genes to monitor most closely. Keywords: antimicrobial resistance; genomic surveillance; forecasting; machine learning; allele dynamics; Klebsiella pneumoniae; Acinetobacter baumannii

Sepsis is a global health problem. Patients in the Intensive Care Unit (ICU) are at risk of having sepsis because of their vulnerability and use of invasive medical devices. Emerging antimicrobial-resistance complicates treatment. Understanding bacterial profiles and antibiotic sensitivity patterns in the ICU plays an important role in managing sepsis, optimizing antimicrobial use, and improving patient outcomes. The aim of this study was to show bacterial profiles and antibiotic sensitivity patterns among patients who were admitted to the ICU at Mbeya Zonal Referral Hospital for 12 months. This was a prospective cross-sectional study among 187 sepsis-suspected patients. Data analysis was performed using SPSS Version 27. Categorical data were summarized by frequency and percentage. Fishers exact test, chi-square test, and modified Poisson regression were used to show the association between patients clinical variables and culture positivity at a 95% CI. Statistical significance was set at a p-value < 0.05. Out of 187 samples, 41.7% were culture positive. Gram-negative bacteria were commonly isolated (65.4%, with Klebsiella pneumoniae and Escherichia coli being commonly isolated. Commonly isolated Gram-positive bacteria were Coagulase-negative Staphylococcus species (19%). 100% of gram-positive bacteria and 96% of gram-negative bacteria were Multi-Drug Resistant (MDR), respectively. In multivariable analysis, patients who were intubated and mechanically ventilated (aPR = 2.208, 95% CI: 1.133-4.305, p = 0.020) and post-laparotomy patients (aPR = 3.241,95% CI: 1.320-7.958, p = 0.010) independently had a higher proportion of Gram-negative bacteria. The study reveals a high level of resistance to commonly used antimicrobials in our setting, necessitating strengthening of the antimicrobial stewardship program and routine surveillance of antimicrobial resistance patterns.

Background: Clinical decision support (CDS) systems may improve chronic pain management by providing guideline-based recommendations within clinical workflows. However, low clinician use can limit their effectiveness. Understanding the association between CDS use and guideline-recommended care may help distinguish implementation challenges from limitations in CDS functionality. Objective: To estimate the association of OneSheet, a CDS system for chronic pain management, and guideline-recommended care when the system was used during patient encounters. Methods: We conducted a per-protocol secondary data analysis of data from a pragmatic randomized clinical trial conducted from October 2020 to May 2022 across 25 primary care clinics at 2 academic health systems in Indiana and North Carolina. The parent trial enrolled 137 primary care clinicians. This analysis included 145511 eligible chronic pain encounters and 15480 long term opioid therapy (LTOT) encounters that occurred after OneSheet implementation. OneSheet use at a patient encounter was the exposure of interest. Propensity score matching was used to create comparable groups of encounters with and without OneSheet use. Outcomes included documentation of pain-related goals, documentation of pain and function using the Pain, Enjoyment of Life and General Activity (PEG) scale, prescription drug monitoring (PDMP) review, urine drug screening (UDS) orders, and naloxone orders. Results: OneSheet was used in 959 of 145511 chronic pain encounters (0.7%) and 582 of 15480 LTOT encounters (4.0%). In matched analyses, OneSheet use was associated with increased documentation of pain-related goals (relative risk (RR)=11.70 (95% CI 4.25-32.50) and PEG score documentation (RR=9.70 (95% CI 4.14-22.31). Among LTOT encounters, OneSheet use was associated with increased UDS ordering (RR=1.52 (95% CI 1.40-1.65) and PDMP review (RR=1.06 (95% CI 1.03-1.09), but decreased naloxone ordering (RR=0.13 (95% CI, 0.02-0.90). Conclusions: OneSheet use was associated with several guideline-recommended chronic pain management actions, suggesting that they system may support care quality when clinicians use it. However, use was rare, indicating that increasing routine use through better workflow integration may be necessary to achieve population-level improvements in chronic pain care.

Ensuring the safety and suitability of proteins considered for food and biotechnology applications is an important challenge. Computational approaches can facilitate the prioritisation of candidate proteins for further investigation, particularly given the rapid growth of genomic and metagenomic sequence datasets. In this study, we developed computational models to distinguish edible plant tissue-associated (EPTA) proteins from non-EPTA proteins. The positive class comprised 939 proteins with experimentally validated evidence of expression in plant tissues commonly consumed by humans, hereafter referred to as EPTA proteins. The negative class comprised 939 proteins annotated in UniProt as toxic, allergenic, or antinutritional, hereafter referred to as non-EPTA proteins. Models were evaluated using five-fold cross-validation with a cluster-based partitioning strategy, ensuring that no protein in the validation set shared more than 40% sequence identity with proteins in the corresponding training set. First, composition-based sequence features were evaluated to establish a baseline for EPTA or non-EPTA classification, with the Extra Trees (ET) classifier achieving a validation AUROC of 0.848. To incorporate evolutionary information beyond amino acid composition, PSSM profiles were subsequently evaluated, yielding an AUROC of 0.842 with an SVM classifier. Finally, to capture richer sequence patterns and contextual information using protein language modelling, we evaluated ESM2-based models. The fine-tuned ESM2-T33 model achieved the highest validation AUROC of 0.925 and was selected as the final predictive model. The resulting approach was implemented as the EdiProPred web server (https://webs.iiitd.edu.in/raghava/edipropred/) and standalone software for computational classification of plant proteins. The EdiProPred framework provides a useful computational tool for prioritising candidate plant proteins and facilitating the exploration of novel protein resources for food and biotechnology applications.