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Background: Non-fatal overdoses frequently precede fatal overdoses, thus identifying risk factors for non-fatal overdoses could help develop strategies to prevent substance related deaths., Aim: This study aimed to identify patterns, circumstances and risk factors leading to non-fatal substance overdose in people experiencing homelessness., Method: All recorded cases of non-fatal substance overdose from a population of people experiencing homelessness registered at a specialist homelessness primary care centre in England were identified using electronic medical records. Overdose details and patient characteristics were extracted. The heterogeneity between variables in people with and without a recorded non-fatal overdose were tested and multivariable logistic regressions were used to identify the risk factors of non-fatal overdoses., Results: From the 1221 registered patients, 194(16%) were identified as having had a non-fatal overdose with 428 overdoses between them. Half were polypharmacy events with the main substances of overdose being: heroin, paracetamol, benzodiazepines, cocaine, antipsychotics, SSRIs and synthetic cannabinoids. Risk of non-fatal overdose was greater in females, white ethnicity, ages 36-45, and in those with a recorded use of tobacco, alcohol or illicit substance use. Chronic physical and mental health conditions increased the risk of non-fatal overdose including respiratory conditions, blood borne viruses, migraines, anxiety and depression., Conclusion: With a high number of non-fatal overdoses within this population, identifying individuals at risk based on the factors identified in this research could enable primary care providers to apply prevention actions such as overdose awareness and naloxone provision to avoid drug harm and deaths. Future work should explore the role of chronic physical conditions and their treatment on non-fatal overdose risks., Competing Interests: Conflicts of interest Vibhu Paudyal is an Associate editor of the International Journal of Clinical Pharmacy. He had no role in handling the manuscript, specifically the processes of editorial review, peer review and decision making., (© 2024. The Author(s).)

Streptococcus pneumoniae (pneumococcus) is a multidrug-resistant pathogen associated with pneumonia, otitis media, meningitis and other severe complications that are currently a global threat to human health. The World Health Organization listed Pneumococcus as the fourth of twelve globally prioritized pathogens. Identifying alternatives to antibiotic therapies is urgently needed to combat Pneumococcus . Bacteriophage-derived endolysins can be used as alternative therapeutics due to their bacterial cell wall hydrolyzing capability. In this study, S. pneumoniae phage genomes were screened to create a database of endolysins for molecular modelling and diversity analysis of these lytic proteins. A total of 89 lytic proteins were curated from 81 phage genomes and categorized into eight groups corresponding to their different enzymatically active (EAD) domains and cell wall binding (CBDs) domains. We then constructed three-dimensional structures that provided insights into these endolysins. Group I, II, III, V, and VI endolysins showed conserved catalytic and ion-binding residues similar to existing endolysins available in the Protein Data Bank. While performing structural and sequence analysis with template lysin, an additional cell wall binding repeat was observed in Group II lysin, which was not previously known. Molecular docking performed with choline confirmed the existence of this additional repeat. Group III endolysins showed 99.16 % similarity to LysME-EF1, a lysin derived from Enterococcus faecalis . Furthermore, the comparative computational analysis revealed the existence of CBDs in Group III lysin. This study provides the first insight into the molecular and diversity analysis of S. pneumoniae phage endolysins that could be valuable for developing novel lysin-based therapeutics., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

The accurate characterisation of centreline segregation requires precise measurements of composition variations over large length scales (10 - 1 $^{-1}$ m ${\rm {m}}$ ) across the centreline of the cast product, while having high resolution, sufficient to quantify the significant composition variations between dendrites due to microsegregation at very small length scales (10 - 5 m $^{-5}{\rm {m}}$ ). This study investigates the potential of a novel microscopy technique, named Synchrotron Micro X-ray Flurorescence (SMXRF), to generate large-scale high-resolution segregation maps from a steel sample taken from a thin slab caster. Two methods, Point Analysis and Regression Analysis, are proposed for SMXRF data calibration. By comparing with the traditional Laser-Induced Breakdown Spectroscopy (LIBS), and Electron Probe Micro Analyser (EPMA) techniques, we show that SMXRF is successful in quantitative characterisation of centreline segregation. Over large areas (e.g. 12 × $\times$ 16 mm 2 ${\rm {mm}}^2$ ) and at high resolution (10-50 μ m $\mu\text{m}$ pixel size) various techniques yield comparable outcomes in terms of composition maps and solute profiles. The findings also highlight the importance of both high spatial resolution and large field of view to have a quantitative, accurate, and efficient measurement tool to investigate segregation phenomena., (© 2024 The Authors. Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.)

Background and Objective: Hypertension is a potentially dangerous health condition that can be detected by measuring blood pressure (BP). Blood pressure monitoring and measurement are essential for preventing and treating cardiovascular diseases. Cuff-based devices, on the other hand, are uncomfortable and prevent continuous BP measurement., Methods: In this study, a new non-invasive and cuff-less method for estimating Systolic Blood Pressure (SBP), Mean Arterial Pressure (MAP), and Diastolic Blood Pressure (DBP) has been proposed using characteristic features of photoplethysmogram (PPG) signals and nonlinear regression algorithms. PPG signals were collected from 219 participants, which were then subjected to preprocessing and feature extraction steps. Analyzing PPG and its derivative signals, a total of 46 time, frequency, and time-frequency domain features were extracted. In addition, the age and gender of each subject were also included as features. Further, correlation-based feature selection (CFS) and Relief F feature selection (ReliefF) techniques were used to select the relevant features and reduce the possibility of over-fitting the models. Finally, support vector regression (SVR), K-nearest neighbour regression (KNR), decision tree regression (DTR), and random forest regression (RFR) were established to develop the BP estimation model. Regression models were trained and evaluated on all features as well as selected features. The best regression models for SBP, MAP, and DBP estimations were selected separately., Results: The SVR model, along with the ReliefF-based feature selection algorithm, outperforms other algorithms in estimating the SBP, MAP, and DBP with the mean absolute error of 2.49, 1.62 and 1.43 mmHg, respectively. The proposed method meets the Advancement of Medical Instrumentation standard for BP estimations. Based on the British Hypertension Society standard, the results also fall within Grade A for SBP, MAP, and DBP., Conclusion: The findings show that the method can be used to estimate blood pressure non-invasively, without using a cuff or calibration, and only by utilizing the PPG signal characteristic features., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: S. M. Taslim Uddin Raju reports was provided by Khulna University of Engineering and Technology. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author(s).)

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis, one of the most deadly infections in humans. The emergence of multidrug-resistant and extensively drug-resistant Mtb strains presents a global challenge. Mtb has shown resistance to many frontline antibiotics, including rifampicin, kanamycin, isoniazid, and capreomycin. The only licensed vaccine, Bacille Calmette-Guerin, does not efficiently protect against adult pulmonary tuberculosis. Therefore, it is urgently necessary to develop new vaccines to prevent infections caused by these strains. We used a subtractive proteomics approach on 23 virulent Mtb strains and identified a conserved membrane protein (MmpL4, NP_214964.1) as both a potential drug target and vaccine candidate. MmpL4 is a non-homologous essential protein in the host and is involved in the pathogen-specific pathway. Furthermore, MmpL4 shows no homology with anti-targets and has limited homology to human gut microflora, potentially reducing the likelihood of adverse effects and cross-reactivity if therapeutics specific to this protein are developed. Subsequently, we constructed a highly soluble, safe, antigenic, and stable multi-subunit vaccine from the MmpL4 protein using immunoinformatics. Molecular dynamics simulations revealed the stability of the vaccine-bound Toll-like receptor-4 complex on a nanosecond scale, and immune simulations indicated strong primary and secondary immune responses in the host. Therefore, our study identifies a new target that could expedite the design of effective therapeutics, and the designed vaccine should be validated. Future directions include an extensive molecular interaction analysis, in silico cloning, wet-lab experiments, and evaluation and comparison of the designed candidate as both a DNA vaccine and protein vaccine.

The need for fast detection of etiological agents outside the narrow target range of pathogens that may cause an event of an infectious disease epidemic necessitates rapid sequencing technologies to be implemented in routine diagnostic procedures. We tested the performance of a PCR-free rapid nanopore barcoding assay to detect microbial species by analyzing genomic contents extracted from acute diarrheal case specimens. Sequenced reads were processed in an automated analysis module for species identification, whereas pathogenic subspecies detection was aided by a sequence similarity search against a gene-specific database. Evaluation of assay and analysis parameters (e.g., run-time, sequence length, and species hit abundance level) was carried out using a standard bacterial community for assessing detection accuracy. It was observed that longer sequence length (≥500 nucleotides) along with higher species abundance level (≥1%) can be critical for exclusion of false-negative outcomes, while increased sequencing run-time can affect the proportional abundance of true-positive species. Under optimal parameters, the sensitivity of the rapid assay remained 100% for the detection of a target species in a background of nontarget fecal (diarrheal) DNA that weighed up to 64 times the DNA of the target species. The method was applied to acute diarrheal samples. Among these, 62.5% (5/8) were in agreement with target-specific traditional diagnosis methods for the presence/absence of pathogenic agent(s), 12.5% (1/8) were in disagreement, and pathogenic agents that were not targeted by the traditional methods were revealed by sequencing for 25% (2/8) of samples. These observations suggest that further optimization and evaluation of the rapid nanopore sequencing method could potentiate the widening of the range of pathogens that can be detected in acute diarrheal samples in the context of regular diagnostic needs as well as epidemics.

Multi-resistant pathogenic strains of non-lactose fermenting Escherichia coli (NLF E. coli ) are responsible for various intestinal and extraintestinal infections. Although several studies have characterised such strains using conventional methods, they have not been comprehensively studied at the genomic level. To address this gap, we used whole-genome sequencing (WGS) coupled with detailed microbiological and biochemical testing to investigate 17 NLF E. coli from a diagnostic centre (icddr,b) in Dhaka, Bangladesh. The prevalence of NLF E. coli was 10%, of which 47% (8/17) exhibited multi-drug resistant (MDR) phenotypes. All isolates (17/17) were confirmed as E. coli and could not ferment lactose sugar. WGS data analysis revealed international high-risk clonal lineages. The most prevalent sequence types (STs) were ST131 (23%), ST1193 (18%), ST12 (18%), ST501 (12%), ST167 (6%), ST73 (6%) and ST12 (6%). Phylogenetic analysis corroborated a striking clonal population amongst the studied NLF E. coli isolates. The predominant phylogroup detected was B2 (65%). The bla CTX-M-15 extended-spectrum beta-lactamase gene was present in 53% of isolates (9/17), whilst 64.7% (11/17) isolates were affiliated with pathogenic pathotypes. All extraintestinal pathogenic E. coli pathotypes demonstrated β-hemolysis. Our study underscores the presence of critical pathogens and MDR clones amongst non-lactose fermenting E. coli. be considered equally capable as lactose fermenting forms in causing intestinal and extraintestinal infections. Further, there is a need to undertake systematic, unbiased monitoring of predominant lineages amongst non-lactose fermenting E. coli be considered equally capable as lactose fermenting forms in causing intestinal and extraintestinal infections. Further, there is a need to undertake systematic, unbiased monitoring of predominant lineages amongst non-lactose fermenting E. coli that would help in better treatment and prevention strategies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Mazumder, Hussain, Phelan, Campino, Haider, Mahmud, Ahmed, Asadulghani, Clark and Mondal.)

Legionella pneumophila is the causative agent of a severe type of pneumonia (lung infection) called Legionnaires' disease. It is emerging as an antibiotic-resistant strain day by day. Hence, identifying novel drug targets and vaccine candidates is essential to fight against this pathogen. Here, attempts were taken through a subtractive genomics approach on the complete proteome of L. pneumophila to address the challenges of multidrug resistance. A total of 2,930 proteins from L. pneumophila proteome were investigated through diverse subtractive proteomics approaches, e.g., identification of human nonhomologous and pathogen-specific essential proteins, druggability and "anti-target" analysis, subcellular localization prediction, human microbiome nonhomology screening, and protein-protein interaction studies to find out effective drug and vaccine targets. Only three fulfilled these criteria and were proposed as novel drug targets against L. pneumophila. Furthermore, outer membrane protein TolB was identified as a potential vaccine target with a better antigenicity score. Antigenicity and transmembrane topology screening, allergenicity and toxicity assessment, population coverage analysis, and a molecular docking approach were adopted to generate the most potent epitopes. The final vaccine was constructed by the combination of highly immunogenic epitopes, along with suitable adjuvant and linkers. The designed vaccine construct showed higher binding interaction with different major histocompatibility complex (MHC) molecules and human immune TLR-2 receptors with minimum deformability at the molecular level. The present study aids the development of novel therapeutics and vaccine candidates for efficient treatment and prevention of L. pneumophila infections. However, further wet-lab-based phenotypic and genomic investigations and in vivo trials are highly recommended to validate our prediction experimentally. IMPORTANCE Legionella pneumophila is a human pathogen distributed worldwide, causing Legionnaires' disease (LD), a severe form of pneumonia and respiratory tract infection. L. pneumophila is emerging as an antibiotic-resistant strain, and controlling LD is now difficult. Hence, developing novel drugs and vaccines against L. pneumophila is a major research priority. Here, the complete proteome of L. pneumophila was considered for subtractive genomics approaches to address the challenge of antimicrobial resistance. Our subtractive proteomics approach identified three potential drug targets that are promising for future application. Furthermore, a possible vaccine candidate, "outer membrane protein TolB," was proposed using reverse vaccinology analysis. The constructed vaccine candidate showed higher binding interaction with MHC molecules and human immune TLR-2 receptors at the molecular level. Overall, the present study aids in developing novel therapeutics and vaccine candidates for efficient treatment of the infections caused by L. pneumophila.

The Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) became a pandemic, resulting in an exponentially increased mortality globally and scientists all over the world are struggling to find suitable solutions to combat it. Multiple repurposed drugs have already been in several clinical trials or recently completed. However, none of them shows any promising effect in combating COVID-19. Therefore, developing an effective drug is an unmet global need. RdRp (RNA dependent RNA polymerase) plays a pivotal role in viral replication. Therefore, it is considered as a prime target of drugs that may treat COVID-19. In this study, we have screened a library of compounds, containing approved RdRp inhibitor drugs that were or in use to treat other viruses (favipiravir, sofosbuvir, ribavirin, lopinavir, tenofovir, ritonavir, galidesivir and remdesivir) and their structural analogues, in order to identify potential inhibitors of SARS-CoV-2 RdRp. Extensive screening, molecular docking and molecular dynamics show that five structural analogues have notable inhibitory effects against RdRp of SARS-CoV-2. Importantly, comparative protein-antagonists interaction revealed that these compounds fit well in the pocket of RdRp. ADMET analysis of these compounds suggests their potency as drug candidates. Our identified compounds may serve as potential therapeutics for COVID-19., Competing Interests: The authors declare no conflict of interest., (© 2021 Published by Elsevier Ltd.)

Purpose: To investigate the in situ rehardening effect by white or whole-meal bread on softened enamel., Materials and Methods: Twelve volunteers wearing orthodontic removable appliances participated in this study. The intraoral test was chosen for measuring microhardness of enamel slabs inserted into the dental appliance. Average microhardness of enamel was calculated at three stages: At start (baseline), after exposing the enamel slabs to a citrus beverage (pH 3.4) for 30 minutes in vitro as a softening agent, followed by intraoral exposure for a duration of 5 minutes to stimulated secreted saliva by parafilm chewing (control), or to 15g white- and wholemeal-bread mastication respectively (experimental)., Results: A significant rehardening of the softened enamel surfaces took place following mastication of the two bread samples and salivary secretion. The differences in the rehardening potentials of the bread samples as compared to that of saliva were not significant. From the conditions chosen for the experiment, there was no sufficient evidence to support the hypothesis that bread eating with calcium and phosphate concentrations at the existent levels will afford a significant greater rehardening than saliva alone.