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The COVID-19 pandemic has caused havoc all around the world. The causative agent of COVID-19 is the novel form of the coronavirus (CoV) named SARS-CoV-2, which results in immune system disruption, increased inflammation, and acute respiratory distress syndrome (ARDS). T cells have been important components of the immune system, which decide the fate of the COVID-19 disease. Recent studies have reported an important subset of T cells known as regulatory T cells (Tregs), which possess immunosuppressive and immunoregulatory properties and play a crucial role in the prognosis of COVID-19 disease. Recent studies have shown that COVID-19 patients have considerably fewer Tregs than the general population. Such a decrement may have an impact on COVID-19 patients in a number of ways, including diminishing the effect of inflammatory inhibition, creating an inequality in the Treg/Th17 percentage, and raising the chance of respiratory failure. Having fewer Tregs may enhance the likelihood of long COVID development in addition to contributing to the disease’s poor prognosis. Additionally, tissue-resident Tregs provide tissue repair in addition to immunosuppressive and immunoregulatory activities, which may aid in the recovery of COVID-19 patients. The severity of the illness is also linked to abnormalities in the Tregs’ phenotype, such as reduced expression of FoxP3 and other immunosuppressive cytokines, including IL-10 and TGF-beta. Hence, in this review, we summarize the immunosuppressive mechanisms and their possible roles in the prognosis of COVID-19 disease. Furthermore, the perturbations in Tregs have been associated with disease severity. The roles of Tregs are also explained in the long COVID. This review also discusses the potential therapeutic roles of Tregs in the management of patients with COVID-19.

Artificial intelligence (AI) is a branch of science and engineering that focuses on the computational understanding of intelligent behavior. Many human professions, including clinical diagnosis and prognosis, are greatly useful from AI. Antimicrobial resistance (AMR) is among the most critical challenges facing Pakistan and the rest of the world. The rising incidence of AMR has become a significant issue, and authorities must take measures to combat the overuse and incorrect use of antibiotics in order to combat rising resistance rates. The widespread use of antibiotics in clinical practice has not only resulted in drug resistance but has also increased the threat of super-resistant bacteria emergence. As AMR rises, clinicians find it more difficult to treat many bacterial infections in a timely manner, and therapy becomes prohibitively costly for patients. To combat the rise in AMR rates, it is critical to implement an institutional antibiotic stewardship program that monitors correct antibiotic use, controls antibiotics, and generates antibiograms. Furthermore, these types of tools may aid in the treatment of patients in the event of a medical emergency in which a physician is unable to wait for bacterial culture results. AI’s applications in healthcare might be unlimited, reducing the time it takes to discover new antimicrobial drugs, improving diagnostic and treatment accuracy, and lowering expenses at the same time. The majority of suggested AI solutions for AMR are meant to supplement rather than replace a doctor’s prescription or opinion, but rather to serve as a valuable tool for making their work easier. When it comes to infectious diseases, AI has the potential to be a game-changer in the battle against antibiotic resistance. Finally, when selecting antibiotic therapy for infections, data from local antibiotic stewardship programs are critical to ensuring that these bacteria are treated quickly and effectively. Furthermore, organizations such as the World Health Organization (WHO) have underlined the necessity of selecting the appropriate antibiotic and treating for the shortest time feasible to minimize the spread of resistant and invasive resistant bacterial strains.

Background In Al-Baha viral hepatitis in clinical settings has not been adequately investigated. This study examined chronic HBV and HCV infections and their treatment outcomes among patients at King Fahd Hospital in Al-Baha. Methods Patients records were retrieved anonymously for clinical, demographic, virological and biochemical data from January 2019 to December 2022. Results Of 148 patients (mean age was 49.6 ± 13.2; 56.8% males) 80.4% had HBV, 18.2% had HCV while 1.4% had dual infection. HBV viral loads correlated with ALT levels ( r  = 0.317, p  = 0.001) while HCV viral loads did not. ( r  = 0.246, p  = 0.23). Among the 148 cases, 144 were clinically classified as chronic HBV infections ( n  = 117), chronic HCV infections ( n  = 25), acute HCV infection ( n  = 1). The remaining cases were unclassified HCV infections ( n  = 4) or dual HBV/HCV infection ( n  = 1). Cirrhosis was observed in 6% of HBV cases and 18.5% of HCV cases. Viral load suppression with ALT levels either maintained at baseline or normalized in most cases occurred in 93.3% of HBV patients ( n  = 15) treated with tenofovir alafenamide and in all those ( n  = 8) treated with entecavir with generally unchanging ALT levels. All HCV patients ( n  = 16) achieved viral clearance after 12 weeks treatment course; sofosbuvir–daclatasvir ( n  = 14) was highly effective though 2 showed elevated post-treatment ALT. Conclusions Chronic HBV and HCV infections remain clinical challenge in Al-Baha. Current antivirals showed strong efficacy. Cirrhosis and post- treatment liver abnormalities underscores the need for continuing monitoring, improved prevention and broadened hepatitis health care.

Streptococcus pneumoniae (S. pneumoniae) is responsible for a wide range of infections. The aim of this study was to investigate the clonal diversity of S. pneumoniae in thirteen Arab countries. Multi-Locus Sequence Typing (MLST) data were extracted from PubMLST database. Genetic analysis was performed using DnaSP software version 6.0. A Minimum Spanning Tree (MST) analysis was conducted to evaluate the population structure of S. pneumoniae strains. Genetic data from 1008 Arab S. pneumoniae strains, collected over 22 years (1996–2018), were analyzed. MLST analysis identified a highly diverse population comprising 600 sequence types grouped into 87 clonal complexes and 295 singletons. Both internationally disseminated clones (e.g., ST156) and country-specific lineages (e.g., ST2307, Saudi Arabia) were observed, indicating substantial geographic structuring. Significant associations were detected between sequence types and geographical origin, decade of isolation, patient age, disease type, and serotype (p < 0.05). Although recombination events were presented, the population retained a predominantly clonal structure over time (ISA = 0.0715, p < 0.001). Overall, these findings demonstrated extensive genetic heterogeneity and spatiotemporal structuring of S. pneumoniae in the Arab region, providing valuable insights for regional surveillance and vaccine-related strategies.

Background Tuberculosis (TB) remains a significant health concern in India, especially among households with children and young adolescents aged 6–17 years. Despite ongoing research, there is a knowledge gap regarding specific risk factors for TB within this demographic. This study aims to bridge this gap by examining the association between TB and various socio-demographic factors, including socioeconomic status, nutritional status, and environmental conditions. Data and methods Utilizing data from the National Family Health Survey (NFHS) 4th and 5th round (2015-16 and 2019-21), this study conducted a comprehensive cross-sectional analysis. Unadjusted and Adjusted Logistic regression is utilized to identify key factors influencing TB. Furthermore, Wagstaff decomposition analysis is applied, to quantifying the factors that contributes to the inequalities in social determinants on the wealth-related inequality observed in the prevalence of TB. Results The study observed a notable decline in TB prevalence from 1.7 to 1.2% among individuals from households having children and young adolescents aged 6–17 years. Additionally, factors like the use of unclean cooking fuel, lack of electricity, and unimproved toilet facilities were associated with increased TB prevalence. Wealth-based inequality in TB prevalence was also evident, with the burden falling disproportionately on poorer households. Unclean fuel is the most significant determinant of wealth-based inequality in TB, contributing to nearly 2/5th (18.5% in NFHS-4) of the observed inequality. Notably, gender did not significantly influence TB prevalence. Conclusion The decline in TB prevalence in India correlates with improvements in socio-economic and living conditions, as evidenced by increased access to better housing, clean fuel, and sanitation facilities. The study underscores the need for integrated public health strategies that address both medical and socio-environmental determinants of TB. Improving socio-economic conditions, alongside targeted healthcare interventions, appears vital in reducing the TB burden in high-prevalence settings like India. This research emphasizes the importance of comprehensive approaches to combat pediatric TB, combining clinical care with enhancements in living standards and access to basic amenities.

Background: Among gram-negative bacteria, Klebsiella pneumoniae is one of the most common causes of healthcare-related infection. Bloodstream infections (BSIs) caused by Klebsiella pneumoniae are notorious for being difficult to treat due to resistance to commonly used antimicrobials. Klebsiella pneumoniae isolates from bloodstream infections are becoming increasingly resistant to carbapenems. In the fight against carbapenem-resistant Klebsiella pneumoniae, colistin [polymyxin E] is the antimicrobial of choice and is thus widely used. Objective: This study aimed to determine the global prevalence of colistin resistance amongst Klebsiella pneumoniae isolates from bloodstream infections. Methods: PubMed, Medline, Scopus, and the Cochrane Library were searched for published articles without restricting the search period. Studies meeting the predefined inclusion and exclusion criteria were included, and quality was assessed using Joanna Briggs Institute Checklist. We used a statistical random effect model to analyze data with substantial heterogeneity (I2 > 50%) in the meta-analysis. Results: A total of 10 studies out of 2873 search results that met the inclusion criteria were included in the final synthesis for this study. A pooled prevalence of colistin resistance was 3.1%, 95% CI (1.5–4.7%). The highest colistin resistance pooled prevalence was recorded in isolates studied in 2020 and beyond 12.90% (4/31), while Klebsiella pneumoniae isolates studied in 2015 and before and in 2016–2019 showed a pooled colistin resistance rate of 2.89% (48/1661) and 2.95% (28/948), respectively. The highest colistin resistance was found in Klebsiella pneumoniae isolates from Thailand (19.2%), while the least pooled resistance was in Klebsiella pneumoniae from South Korea (0.8%). The pooled prevalence of the multidrug-resistant (MDR) of Klebsiella pneumoniae from bloodstream infection ranged from 80.1%, 95% CI (65.0–95.2%), and the resistance prevalence of other antibiotics by Klebsiella pneumoniae from bloodstream infections were as follows; ciprofloxacin (45.3%), ertapenem (44.4%), meropenem (36.1%), imipenem (35.2%), gentamicin (33.3%), amikacin (25.4%) and tigecycline (5.1%). Klebsiella pneumoniae recovered from the intensive care unit (ICU) showed higher colistin resistance, 11.5% (9/781%), while non-ICU patients showed 3.03% (80/2604) pooled colistin resistance. Conclusion: This study showed low colistin resistance in Klebsiella pneumoniae isolates from global bloodstream infections. However, significant colistin resistance was observed in isolates collected from 2020 and beyond. Significant colistin resistance was also observed in Klebsiella pneumoniae isolates in bloodstream infections from the intensive care unit (ICU) compared to those from non-ICUs. As a result, there is a need to institute colistin administration stewardship in the ICU in clinical settings.

Tuberculosis (TB) is a global burden to humanity due to its adverse effects on health and society since time is not clearly defined. The existence of drug-resistant strains and the potential threat posed by latent tuberculosis act as strong impetuses for developing novel anti-tuberculosis drugs. In this study, various flavonoids were tested against the Mycobacterium tuberculosis (Mtb) Isocitrate Lyase (ICL), which has been identified as an authorised therapeutic target for treating Mtb infection. Using in silico drug discovery approach, a library of 241 flavonoid compounds was virtually screened against the binding pocket of the crystalline ligand, the VGX inhibitor, in the Mtb ICL protein. As a result, the top four flavonoids were selected based on binding score and were further considered for redocking and intermolecular contact profiling analysis. The global and local fluctuations in the protein and ligand structure were analysed using their root mean square deviation (RMSD) and root mean square fluctuation (RMSF) values obtained from the GROMACS generated 100 ns molecular dynamics (MD) simulation trajectories. The end-state binding free energy was also calculated using the MMPBSA approach for all the respective docked complexes. All four selected compounds exhibited considerable stability and affinity compared to control ligands, i.e. VGX inhibitor; however, Vaccarin showed the highest stability and affinity against the Mtb ICL protein active site, followed by the Genistin, Glabridin, and Corylin. Therefore, this study recommends selected flavonoids for in vitro and in vivo experimental studies to check their potency and efficacy against Mtb.

Human Parainfluenza Virus (HPIV) Type-1, which is an anti-sense ribonucleic acid (RNA) virus belonging to the paramyxoviridae family, induces upper and lower respiratory tract infections. The infections caused by the HPIV Type-1 virus are usually confined to northwestern regions of America. HPIV-1 causes infections through the virulence of the hemagglutinin-neuraminidase (HN) protein, which plays a key role in the attachment of the viral particle with the host’s receptor cells. To the best of our knowledge, there is no effective antiviral drugs or vaccines being developed to combat the infection caused by HPIV-1. In the current study, a multiple epitope-based vaccine was designed against HPIV-1 by taking the viral HN protein as a probable vaccine candidate. The multiple epitopes were selected in accordance with their allergenicity, antigenicity and toxicity scoring. The determined epitopes of the HN protein were connected simultaneously using specific conjugates along with an adjuvant to construct the subunit vaccine, with an antigenicity score of 0.6406. The constructed vaccine model was docked with various Toll-like Receptors (TLRs) and was computationally cloned in a pET28a (+) vector to analyze the expression of vaccine sequence in the biological system. Immune stimulations carried out by the C-ImmSim Server showed an excellent result of the body’s defense system against the constructed vaccine model. The AllerTop tool predicted that the construct was non-allergen with and without the adjuvant sequence, and the VaxiJen 2.0 with 0.4 threshold predicted that the construct was antigenic, while the Toxinpred predicted that the construct was non-toxic. Protparam results showed that the selected protein was stable with 36.48 instability index (II) scores. The Grand average of Hydropathicity or GRAVY score indicated that the constructed protein was hydrophilic in nature. Aliphatic index values (93.53) confirmed that the construct was thermostable. This integrated computational approach shows that the constructed vaccine model has a potential to combat laryngotracheobronchitis infections caused by HPIV-I.

Marburg virus disease (MVD) is caused by the Marburg virus, a one-of-a-kind zoonotic RNA virus from the genus Filovirus. Thus, this current study employed AI-based QSAR and molecular docking-based virtual screening for identifying potential binders against the target protein (nucleoprotein (NP)) of the Marburg virus. A total of 2727 phytochemicals were used for screening, out of which the top three compounds (74977521, 90470472, and 11953909) were identified based on their predicted bioactivity (pIC50) and binding score (< − 7.4 kcal/mol). Later, MD simulation in triplicates and trajectory analysis were performed which showed that 11953909 and 74977521 had the most stable and consistent complex formations and had the most significant interactions with the highest number of hydrogen bonds. PCA (principal component analysis) and FEL (free energy landscape) analysis indicated that these compounds had favourable energy states for most of the conformations. The total binding free energy of the compounds using the MM/GBSA technique showed that 11953909 (ΔGTOTAL = − 30.78 kcal/mol) and 74977521 (ΔGTOTAL = − 30 kcal/mol) had the highest binding affinity with the protein. Overall, this in silico pipeline proposed that the phytochemicals 11953909 and 74977521 could be the possible binders of NP. This study aimed to find phytochemicals inhibiting the protein's function and potentially treating MVD.

Enterobacteriaceae have been classified as severely drug resistant bacteria by the World Health Organization due to their extensive production and dissemination of carbapenemases (CPs) and extended-spectrum β-lactamases (ESBL). The current study was conducted with the aim to determine the prevalence of CP- and ESBL-producing Enterobacteriaceae, as well as their antibiotic susceptibility profiles. For this, a hospital-based study was conducted which included 384 participants with bacterial infections. The collection and processing of specimens was conducted per standard microbiological protocol. The samples were inoculated on agar media plates to obtain the bacterial growths, and if they were positive for any bacterial growth, the antibiotic susceptibility testing was performed using disk diffusion method to check their antibiotic susceptibility patterns. The double disc diffusion as well as carbapenem inhibition techniques were used to examine the CP enzymes. Multiplex real-time PCR technique was performed to identify three distinct genetic types of CPs that have been identified in the Enterobacteriaceae (KPC, NDM, and OXA-48). A majority of participants (58.3%) in the current study were living in urban areas. A total of 227 (59.1%) patients were hospitalized. Furthermore, 26.04% of the patients were determined to be suffering from infections with Enterobacteriaceae. Escherichia coli was the most prevalent (9.1%) isolate overall, followed by Klebsiella pneumoniae (8.07%), Acinetobacter baumannii (2.6%), Pseudomonas aeruginosa (3.1%), Enterobacter cloacae (1.3%), Proteus spp. (1.3%), and Morganella spp. (0.5%). The studied patients were suffering from urinary tract infections (48.6%), blood stream infections (32.2%), wounds infection (11.9%), and respiratory infections (7.03%), confirmed with bacterial cultures. The resistance against carbapenems was seen in 31.4% of E. coli isolates, 25.8% in K. pneumoniae, 50% in P. aeruginosa, 25% in A. baumannii, and 20% in E. cloacae isolates. Such high rates of CP- and ESBL-producing Enterobacteriaceae are alarming, suggesting high spread in the study area. It is advised to implement better infection prevention and control strategies and conduct further nationwide screening of the carriers of these pathogens. This might help in reducing the burden of highly resistant bugs.