Acceptability, cost-effectiveness, and capacity of a facility-based seasonal influenza vaccination among high-risk groups: a study protocol in selected tertiary care hospitals of Bangladesh.

BACKGROUND: In Bangladesh, seasonal influenza imposes considerable disease and economic burden, especially for those at high-risk of severe disease. The most successful approach for influenza prevention is the administration of a vaccine. Many poor and middle-income nations, including Bangladesh, do not have a national strategy or program in place for seasonal influenza vaccines, despite the World Health Organization's (WHO) advice to prioritize high-risk populations. Additionally, there is a scarcity of substantial data on the cost-effectiveness of seasonal influenza vaccination in these countries. The aim of our study is to determine acceptability, health beliefs, barriers, and intention of receiving influenza vaccine among high-risk populations, assess the cost-effectiveness of implementing a facility-based seasonal influenza vaccination programme, and investigate the required capacity for a potential seasonal influenza vaccination programme. METHODS: We will undertake this study following STROBE guidelines. We will conduct the study in inpatient and outpatient departments of three selected tertiary-level hospitals leveraging the ongoing hospital-based influenza surveillance (HBIS) platform. The study population will include the WHO-defined four high-risk groups excluding healthcare workers: children six months to eight years, pregnant women, elderly ≥ 60 years, and adults with chronic diseases. We will collect quantitative data on participants' acceptability, health beliefs, barriers, and vaccination intentions using the health belief model (HBM) from patients meeting the criteria for high-risk populations attending two public tertiary-level hospitals. In one of the two public tertiary-level hospitals, we will arrange an influenza vaccination campaign before the influenza season, where the vaccine will be offered free of cost to high-risk patients, and in the second hospital, vaccination will not be offered. Both the vaccinated and unvaccinated participants will then be followed-up once a month for one year to record any influenza-like illness, hospitalization, and death. Additional data for objective two will be collected from patients with symptoms of influenza-like illness (ILI) and severe acute respiratory infection (SARI) at one public and one private hospital to determine both direct and indirect costs associated with influenza illness. We will estimate the required number of influenza vaccines, safe injections, and total storage volume utilizing secondary data. We will use a deterministic Markov decision-analytic model to estimate the cost-effectiveness of facility-based influenza vaccination in Bangladesh. DISCUSSION: The results of this study will enable the National Immunization Technical Advisory Group and the Ministry of Health & Family Welfare of Bangladesh to decide what steps to take to develop and implement an influenza vaccination strategy targeting high-risk populations. TRIAL REGISTRATION: The Clinicaltrials.gov registration number is NCT05996549. The registration for the protocol version 2.0 took place in August 2023, with the initial participant being enrolled in March 2022.

Isolation and Characterization of One New Natural Compound with Other Potential Bioactive Secondary Metabolites from Glycosmis cyanocarpa (Blume) Spreng. (Family: Rutaceae).

Glycosmis cyanocarpa (Blume) Spreng is a plant in the Rutaceae family and a species in the Glycosmis genus that has received little attention. Therefore, this research aimed to report the chemical and biological analysis of Glycosmis cyanocarpa (Blume) Spreng. The chemical analysis involved the isolation and characterization of secondary metabolites through an extensive chromatographic study, and the structures of these metabolites were elucidated on the basis of a detailed analysis of NMR and HRESIMS spectroscopic data and by comparison with those of related compounds reported in the literature. Different partitions of the crude ethyl acetate (EtOAc) extract were evaluated for antioxidant, cytotoxic, and thrombolytic potentials. In chemical analysis, one new phenyl acetate derivative, namely 3,7,11,15-tetramethylhexadec-2-en-1-yl 2-phenylacetate (1), along with four known compounds N-methyl-3-(methylthio)-N-(2-phenylacetyl) acrylamide (2), penangin (3), ß-Caryophyllene oxide (4), and acyclic diterpene-phytol (5) were isolated for the first time from the stem and leaf of the plant. The ethyl acetate fraction showed significant free radical scavenging activity with an IC50 value of 11.536 µg/mL compared to standard ascorbic acid (4.816 µg/mL). In the thrombolytic assay, the dichloromethane fraction showed the maximum thrombolytic activity of 16.42% but was still insignificant compared to the standard streptokinase (65.98%). Finally, in a brine shrimp lethality bioassay, the LC50 values of dichloromethane, ethyl acetate, and aqueous fractions were found to be 0.687 µg/mL, 0.805 µg/mL, and 0.982 µg/mL which are significant compared to the standard vincristine sulfate of 0.272 µg/mL.

Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer.

Background and Objectives: Breast cancer (BC) is one of the major causes of cancer-related death in women globally. Proper identification of BC-causing hub genes (HubGs) for prognosis, diagnosis, and therapies at an earlier stage may reduce such death rates. However, most of the previous studies detected HubGs through non-robust statistical approaches that are sensitive to outlying observations. Therefore, the main objectives of this study were to explore BC-causing potential HubGs from robustness viewpoints, highlighting their early prognostic, diagnostic, and therapeutic performance. Materials and Methods: Integrated robust statistics and bioinformatics methods and databases were used to obtain the required results. Results: We robustly identified 46 common differentially expressed genes (cDEGs) between BC and control samples from three microarrays (GSE26910, GSE42568, and GSE65194) and one scRNA-seq (GSE235168) dataset. Then, we identified eight cDEGs (COL11A1, COL10A1, CD36, ACACB, CD24, PLK1, UBE2C, and PDK4) as the BC-causing HubGs by the protein-protein interaction (PPI) network analysis of cDEGs. The performance of BC and survival probability prediction models with the expressions of HubGs from two independent datasets (GSE45827 and GSE54002) and the TCGA (The Cancer Genome Atlas) database showed that our proposed HubGs might be considered as diagnostic and prognostic biomarkers, where two genes, COL11A1 and CD24, exhibit better performance. The expression analysis of HubGs by Box plots with the TCGA database in different stages of BC progression indicated their early diagnosis and prognosis ability. The HubGs set enrichment analysis with GO (Gene ontology) terms and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways disclosed some BC-causing biological processes, molecular functions, and pathways. Finally, we suggested the top-ranked six drug molecules (Suramin, Rifaximin, Telmisartan, Tukysa Tucatinib, Lynparza Olaparib, and TG.02) for the treatment of BC by molecular docking analysis with the proposed HubGs-mediated receptors. Molecular docking analysis results also showed that these drug molecules may inhibit cancer-related post-translational modification (PTM) sites (Succinylation, phosphorylation, and ubiquitination) of hub proteins. Conclusions: This study's findings might be valuable resources for diagnosis, prognosis, and therapies at an earlier stage of BC.

Dysfunction of NMDA receptors in neuronal models of an autism spectrum disorder patient with a DSCAM mutation and in Dscam-knockout mice.

Heterogeneity in the etiopathology of autism spectrum disorders (ASD) limits the development of generic remedies, requires individualistic and patient-specific research. Recent progress in human-induced pluripotent stem cell (iPSC) technology provides a novel platform for modeling ASDs for studying complex neuronal phenotypes. In this study, we generated telencephalic induced neuronal (iN) cells from iPSCs derived from an ASD patient with a heterozygous point mutation in the DSCAM gene. The mRNA of DSCAM and the density of DSCAM in dendrites were significantly decreased in ASD compared to control iN cells. RNA sequencing analysis revealed that several synaptic function-related genes including NMDA receptor subunits were downregulated in ASD iN cells. Moreover, NMDA receptor (R)-mediated currents were significantly reduced in ASD compared to control iN cells. Normal NMDA-R-mediated current levels were rescued by expressing wild-type DSCAM in ASD iN cells, and reduced currents were observed by truncated DSCAM expression in control iN cells. shRNA-mediated DSCAM knockdown in control iN cells resulted in the downregulation of an NMDA-R subunit, which was rescued by the overexpression of shRNA-resistant DSCAM. Furthermore, DSCAM was co-localized with NMDA-R components in the dendritic spines of iN cells whereas their co-localizations were significantly reduced in ASD iN cells. Levels of phospho-ERK1/2 were significantly lower in ASD iN cells, suggesting a potential mechanism. A neural stem cell-specific Dscam heterozygous knockout mouse model, showing deficits in social interaction and social memory with reduced NMDA-R currents. These data suggest that DSCAM mutation causes pathological symptoms of ASD by dysregulating NMDA-R function.

Insight rifampicin-resistant (rpoB) mutation in Pseudomonas stutzeri leads to enhance the biosynthesis of secondary metabolites to survive against harsh environments.

In this study, a wild-type and five distinct rifampicin-resistant (Rifr) rpoB mutants of Pseudomonas stutzeri (i.e., Q518R, D521Y, D521V, H531R and I614T) ability were investigated against harsh environments (particularly nutritional complexity). Among these, the robust Rifr phenotype of P. Stutzeri was associated only with base replacements of the amino deposits. The use of carboxylic and amino acids significantly increased in various Rifr mutants than that of wild type of P. stutzeri. The assimilation of carbon and nitrogen (N) sources of Rifr mutants' confirmed that the organism maintains the adaptation in nutritionally complex environments. Acetylene reduction assay at different times also found the variability for N-fixation in all strains. Among them, the highest nitrogenase activity was determined in mutant 'D521V'. The assimilation of carbon and nitrogen sources of P. stutzeri and its Rifr mutants ensures that the organism maintains the adaptability in nutritionally complex environments through fixing more nitrogen.

Seasonal influenza vaccine uptake among healthcare workers in tertiary care hospitals, Bangladesh: Study protocol for influenza vaccine supply and awareness intervention.

BACKGROUND: Healthcare workers (HCWs), such as doctors, nurses, and support staffs involved in direct or indirect patient care, are at increased risk of influenza virus infections due to occupational exposures. Vaccination is the most effective way to prevent influenza. Despite the World Health Organization (WHO) recommendations, Bangladesh lacks a seasonal influenza vaccination policy for HCWs, and thus vaccination rates remain low. The current project aims to investigate the effect of interventions on influenza vaccine awareness and availability of vaccine supply, explore HCWs' knowledge and perceptions about influenza vaccination, understand the barriers and motivators for influenza vaccine uptake, and understand policymakers' views on the practicality of influenza vaccination among HCWs. METHOD: We will conduct the study at four tertiary care teaching hospitals in Bangladesh, using a cluster randomized controlled trial approach, with the hospital as the unit of randomization and intervention. The study population will include all types of HCWs.The four different types of intervention will be randomly allocated and implemented in four study hospitals separately. The four interventions will be: i) ensuring the availability of influenza vaccine supply; ii) developing influenza vaccine awareness; iii) both ensuring influenza vaccine supply and developing influenza vaccine awareness and iv) control arm with no intervention. Both quantitative and qualitative approaches will be applied to assess the intervention effect. We will estimate the Difference in Differences (DID) with 95% CI of the proportion of vaccine uptake between each intervention and control (non-intervention) arm, adjusting for the clustering effect. The qualitative data will be summarised using a framework matrix method. DISCUSSION: The results of this study will inform the development and implementation of a context-specific strategy to enhance influenza vaccination rates among Bangladeshi HCWs. TRIAL REGISTRATION: Clinicaltrials.gov NCT05521763. Version 2.0 was registered in September 2022, and the first participant enrolled in March 2022. Retrospectively registered.

Trappc9 Deficiency Impairs the Plasticity of Stem Cells.

Genetic mutations of trappc9 cause intellectual disability with the atrophy of brain structures and variable obesity by poorly understood mechanisms. Trappc9-deficient mice develop phenotypes resembling pathological changes in humans and appear overweight shortly after weaning, and thus are useful for studying the pathogenesis of obesity. Here, we investigated the effects of trappc9 deficiency on the proliferation and differentiation capacity of adipose-derived stem cells (ASCs). We isolated ASCs from mice before overweight was developed and found that trappc9-null ASCs exhibited signs of premature senescence and cell death. While the lineage commitment was retained, trappc9-null ASCs preferred adipogenic differentiation. We observed a profound accumulation of lipid droplets in adipogenic cells derived from trappc9-deficient ASCs and marked differences in the distribution patterns and levels of calcium deposited in osteoblasts obtained from trappc9-null ASCs. Biochemical studies revealed that trappc9 deficiency resulted in an upregulated expression of rab1, rab11, and rab18, and agitated autophagy in ASCs. Moreover, we found that the content of neural stem cells in both the subventricular zone of the lateral ventricle and the subgranular zone of the dentate gyrus vastly declined in trappc9-null mice. Collectively, our results suggest that obesity, as well as brain structure hypoplasia induced by the deficiency of trappc9, involves an impairment in the plasticity of stem cells.

Bioinformatics Screening of Potential Biomarkers from mRNA Expression Profiles to Discover Drug Targets and Agents for Cervical Cancer.

Bioinformatics analysis has been playing a vital role in identifying potential genomic biomarkers more accurately from an enormous number of candidates by reducing time and cost compared to the wet-lab-based experimental procedures for disease diagnosis, prognosis, and therapies. Cervical cancer (CC) is one of the most malignant diseases seen in women worldwide. This study aimed at identifying potential key genes (KGs), highlighting their functions, signaling pathways, and candidate drugs for CC diagnosis and targeting therapies. Four publicly available microarray datasets of CC were analyzed for identifying differentially expressed genes (DEGs) by the LIMMA approach through GEO2R online tool. We identified 116 common DEGs (cDEGs) that were utilized to identify seven KGs (AURKA, BRCA1, CCNB1, CDK1, MCM2, NCAPG2, and TOP2A) by the protein-protein interaction (PPI) network analysis. The GO functional and KEGG pathway enrichment analyses of KGs revealed some important functions and signaling pathways that were significantly associated with CC infections. The interaction network analysis identified four TFs proteins and two miRNAs as the key transcriptional and post-transcriptional regulators of KGs. Considering seven KGs-based proteins, four key TFs proteins, and already published top-ranked seven KGs-based proteins (where five KGs were common with our proposed seven KGs) as drug target receptors, we performed their docking analysis with the 80 meta-drug agents that were already published by different reputed journals as CC drugs. We found Paclitaxel, Vinorelbine, Vincristine, Docetaxel, Everolimus, Temsirolimus, and Cabazitaxel as the top-ranked seven candidate drugs. Finally, we investigated the binding stability of the top-ranked three drugs (Paclitaxel, Vincristine, Vinorelbine) by using 100 ns MD-based MM-PBSA simulations with the three top-ranked proposed receptors (AURKA, CDK1, TOP2A) and observed their stable performance. Therefore, the proposed drugs might play a vital role in the treatment against CC.

Diphtheria Antitoxin Administration, Outcomes, and Safety: Response to a Diphtheria Outbreak in Cox's Bazar, Bangladesh.

BACKGROUND: Diphtheria has re-emerged over the past several years. There is a paucity of data on the administration and safety of diphtheria antitoxin (DAT), the standard treatment for diphtheria. The 2017-2018 outbreak among Rohingya refugees in Bangladesh was the largest in decades. We determined the outcomes of DAT-treated patients and describe the occurrence and risk factors associated with adverse reactions to DAT. METHODS: We conducted a retrospective study at the Médecins Sans Frontières Rubber Garden Diphtheria Treatment Center from December 2017-September 2018. Diphtheria was diagnosed based on the World Health Organization clinical case criteria. High-acuity patients were eligible for DAT. Safety precautions were meticulously maintained. We calculated the presence of adverse events by age, duration of illness, and DAT dosage using bivariate comparisons. RESULTS: We treated 709 patients with DAT; 98% (n = 696) recovered and were discharged. One-fourth (n = 170) had at least 1 adverse reaction. Common reactions included cough (n = 115, 16%), rash (n = 66, 9%), and itching (n = 37, 5%). Three percent (n = 18) had severe hypersensitivity reactions. Five patients died during their DAT infusion or soon afterwards, but no deaths were attributed to DAT. CONCLUSIONS: Outcomes for DAT-treated patients were excellent; mortality was <1%. Adverse reactions occurred in one-quarter of all patients, but most reactions were mild and resolved quickly. DAT can be safely administered in a setting with basic critical care, provided there is continuous patient monitoring during the infusion, staff training on management of adverse effects, and attention to safety precautions.

Different reactivity of Sp and Rp isomers of phosphorothioate-modified oligonucleotides in a duplex structure.

The presence of a stereoisomeric center at the phosphorus atom in phosphorothioate-modified oligonucleotides (PS-ONs) has been recognized as an important feature since the early stages of their development. Therefore, several studies have been conducted on the chirality of PS-ONs. In this study, we evaluated the stereo-biased chemistry of PS-ON duplexes. Depending on their absolute configurations, PS-ON duplexes were found to have significantly different and stereospecific reactivities towards simple alkylating reagent.

N-Acetyl-D-Glucosamine Kinase Interacts with NudC and Lis1 in Dynein Motor Complex and Promotes Cell Migration.

Recently, we showed that N-acetylglucosamine kinase (NAGK), an enzyme of amino sugar metabolism, interacts with dynein light chain roadblock type 1 (DYNLRB1) and promotes the functions of dynein motor. Here, we report that NAGK interacts with nuclear distribution protein C (NudC) and lissencephaly 1 (Lis1) in the dynein complex. Yeast two-hybrid assays, pull-down assays, immunocytochemistry, and proximity ligation assays revealed NAGK-NudC-Lis1-dynein complexes around nuclei, at the leading poles of migrating HEK293T cells, and at the tips of migratory processes of cultured rat neuroblast cells. The exogenous expression of red fluorescent protein (RFP)-tagged NAGK accelerated HEK293T cell migration during in vitro wound-healing assays and of neurons during in vitro neurosphere migration and in utero electroporation assays, whereas NAGK knockdown by short hairpin RNA (shRNA) delayed migration. Finally, a small NAGK peptide derived from the NudC interacting domain in in silico molecular docking analysis retarded the migrations of HEK293T and SH-SY5Y cells. These data indicate a functional interaction between NAGK and dynein-NudC-Lis1 complex at the nuclear envelope is required for the regulation of cell migration.

Synthesis and biophysical properties of 5'-thio-2',4'-BNA/LNA oligonucleotide.

Phosphorothioate modification of oligonucleotides is one of the most promising chemical modifications in nucleic acid therapeutics. Structurally similar 5'-thio or phosphorothiolate-modified nucleotides, in which the 5'-bridging oxygen atom is replaced with a sulfur atom, are attracting attention and gaining importance in oligonucleotide-based research. In our present study, we synthesized 5'-thio-2',4'-BNA/LNA monomers bearing thymine or 5-methylcytosine nucleobase. The 5'-thio-2',4'-BNA/LNA monomers were successfully incorporated into target oligonucleotides, and their nuclease stability and binding affinity with complementary strands were evaluated.

Autophagic Regulation of p62 is Critical for Cancer Therapy.

Sequestosome1 (p62/SQSTM 1) is a multidomain protein that interacts with the autophagy machinery as a key adaptor of target cargo. It interacts with phagophores through the LC3-interacting (LIR) domain and with the ubiquitinated protein aggregates through the ubiquitin-associated domain (UBA) domain. It sequesters the target cargo into inclusion bodies by its PB1 domain. This protein is further the central hub that interacts with several key signaling proteins. Emerging evidence implicates p62 in the induction of multiple cellular oncogenic transformations. Indeed, p62 upregulation and/or reduced degradation have been implicated in tumor formation, cancer promotion as well as in resistance to therapy. It has been established that the process of autophagy regulates the levels of p62. Autophagy-dependent apoptotic activity of p62 is recently being reported. It is evident that p62 plays a critical role in both autophagy and apoptosis. Therefore in this review we discuss the role of p62 in autophagy, apoptosis and cancer through its different domains and outline the importance of modulating cellular levels of p62 in cancer therapeutics.

Aspect of thrombolytic therapy: a review.

Thrombolytic therapy, also known as clot busting drug, is a breakthrough treatment which has saved untold lives. It has been used in the clinical area to treat venous and arterial thromboembolic complaints which are a foremost cause of death. In 1761, Morgagni lead the way of thrombolytic therapy. Now day's different types of thrombolytic drugs are currently available in market: alteplase, anistreplase, urokinase, streptokinase, tenecteplase, and so forth. Thrombolytic therapy should be given with maintaining proper care in order to minimize the risk of clinically important bleeding as well as enhance the chances of successfully thrombolysis of clot. These cares include preinfusion care, during the infusion care, and postinfusion care. Besides proper knowledge of contraindication, evolutionary factor, and combination of drug is essential for successful thrombolytic therapy. In these review we discussed about these aspect of thrombolytic therapy.

Unraveling the complexity of human brain: Structure, function in healthy and disease states.

The human brain stands as an intricate organ, embodying a nexus of structure, function, development, and diversity. This review delves into the multifaceted landscape of the brain, spanning its anatomical intricacies, diverse functional capacities, dynamic developmental trajectories, and inherent variability across individuals. The dynamic process of brain development, from early embryonic stages to adulthood, highlights the nuanced changes that occur throughout the lifespan. The brain, a remarkably complex organ, is composed of various anatomical regions, each contributing uniquely to its overall functionality. Through an exploration of neuroanatomy, neurophysiology, and electrophysiology, this review elucidates how different brain structures interact to support a wide array of cognitive processes, sensory perception, motor control, and emotional regulation. Moreover, it addresses the impact of age, sex, and ethnic background on brain structure and function, and gender differences profoundly influence the onset, progression, and manifestation of brain disorders shaped by genetic, hormonal, environmental, and social factors. Delving into the complexities of the human brain, it investigates how variations in anatomical configuration correspond to diverse functional capacities across individuals. Furthermore, it examines the impact of neurodegenerative diseases on the structural and functional integrity of the brain. Specifically, our article explores the pathological processes underlying neurodegenerative diseases, such as Alzheimer's, Parkinson's, and Huntington's diseases, shedding light on the structural alterations and functional impairments that accompany these conditions. We will also explore the current research trends in neurodegenerative diseases and identify the existing gaps in the literature. Overall, this article deepens our understanding of the fundamental principles governing brain structure and function and paves the way for a deeper understanding of individual differences and tailored approaches in neuroscience and clinical practice-additionally, a comprehensive understanding of structural and functional changes that manifest in neurodegenerative diseases.

Precision healthcare: A deep dive into machine learning algorithms and feature selection strategies for accurate heart disease prediction.

This paper presents a comprehensive exploration of machine learning algorithms (MLAs) and feature selection techniques for accurate heart disease prediction (HDP) in modern healthcare. By focusing on diverse datasets encompassing various challenges, the research sheds light on optimal strategies for early detection. MLAs such as Decision Trees (DT), Random Forests (RF), Support Vector Machines (SVM), Gaussian Naive Bayes (NB), and others were studied, with precision and recall metrics emphasized for robust predictions. Our study addresses challenges in real-world data through data cleaning and one-hot encoding, enhancing the integrity of our predictive models. Feature extraction techniques-Recursive Feature Extraction (RFE), Principal Component Analysis (PCA), and univariate feature selection-play a crucial role in identifying relevant features and reducing data dimensionality. Our findings showcase the impact of these techniques on improving prediction accuracy. Optimized models for each dataset have been achieved through grid search hyperparameter tuning, with configurations meticulously outlined. Notably, a remarkable 99.12 % accuracy was achieved on the first Kaggle dataset, showcasing the potential for accurate HDP. Model robustness across diverse datasets was highlighted, with caution against overfitting. The study emphasizes the need for validation of unseen data and encourages ongoing research for generalizability. Serving as a practical guide, this research aids researchers and practitioners in HDP model development, influencing clinical decisions and healthcare resource allocation. By providing insights into effective algorithms and techniques, the paper contributes to reducing heart disease-related morbidity and mortality, supporting the healthcare community's ongoing efforts.

Respiratory Syncytial Virus-Associated Deaths among Children under Five before and during the COVID-19 Pandemic in Bangladesh.

Respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory infections in young children worldwide. RSV-associated deaths in children are underreported in Bangladesh. We analyzed hospital-based surveillance data on severe acute respiratory infections (SARIs) in under-five children before (August 2009-February 2020) and during the COVID-19 pandemic (March 2020-March 2022). Using the World Health Organization definition, we identified SARI cases in 14 tertiary-level hospitals. Nasopharyngeal and oropharyngeal swabs were collected for real-time reverse-transcriptase-polymerase chain reaction (rRT-PCR) testing of six respiratory viruses, including RSV. SARI deaths during the pandemic (2.6%, 66) were higher than pre-pandemic (1.8%, 159; p < 0.001). Nearly half of pandemic deaths (47%) had underlying respiratory viruses, similar to the pre-pandemic rate (45%). RSV detection in deaths was consistent pre-pandemic (13%, 20/159) and during the pandemic (12%, 8/66). Children aged < 6 months constituted 57% (16) of RSV-related deaths. Evaluating interventions like maternal vaccination and infant monoclonal antibody prophylaxis is crucial to address RSV, a major contributor to under-five SARI deaths.

Structural, functional, molecular docking analysis of a hypothetical protein from Talaromyces marneffei and its molecular dynamic simulation: an in-silico approach.

Telaromyces marneffei (formerly Penicillium marneffei) is an endemic pathogenic fungus in Southern China and Southeast Asia. It can cause disease in patients with travel-related exposure to this organism and high morbidity and mortality in acquired immune deficiency syndrome (AIDS). In this study, we analyzed the structure and function of a hypothetical protein from T. marneffei using several bioinformatics tools and servers to unveil novel pharmacological targets and design a peptide vaccine against specific epitopes. A total of seven functional epitopes were screened on the protein, and 'STGVDMWSV' was the most antigenic, non-allergenic and non-toxic. Molecular docking showed stronger affinity between the CTL epitope 'STGVDMWSV' and the MHC I allele HLA-A*02:01, a higher docking score -234.98 kcal/mol, revealed stable interactions during a 100 ns molecular dynamic simulation. Overall, the results of this study revealed that this hypothetical protein is crucial for comprehending biochemical, physiological pathways and identifying novel therapeutic targets for human health. Communicated by Ramaswamy H. Sarma.

Radiation recall dermatitis in HER 2 positive breast cancer patients triggered by trastuzumab: A rare case report and review of literature.

INTRODUCTION AND IMPORTANCE: Radiation recall dermatitis (RRD) is a localized drug-induced inflammatory skin reaction occurring exclusively in a previously irradiated site months to years after discontinuation of ionizing radiation. The symptoms of RRD can range from mild redness to extensive dermatitis. Antineoplastic drugs such as doxorubicin, docetaxel, paclitaxel, and gemcitabine are most commonly associated with radiation recall reactions. These reactions can also occur with antibiotics and anti-tubercular drugs. CASE PRESENTATION: A 38-years-old woman with hormone receptor-negative, HER2-positive inflammatory breast cancer (right), clinical stage cT4dN1Mx, received neoadjuvant chemotherapy with AC > TH protocol at 3 weeks intervals (Anthracycline-Doxorubicin plus Cyclophosphamide X 4 cycles, then docetaxel plus Trastuzumab X 4 cycles) followed by modified radical mastectomy followed by adjuvant locoregional radiotherapy. She received the 5th cycle and 6th cycle trastuzumab monotherapy just before the start of surgery and radiotherapy, respectively. After 1 month of completion of radiotherapy, during her seventh cycle of Trastuzumab monotherapy, she developed mild edema with erythematous change over the previously irradiated area with fever. A skin biopsy was taken to exclude any recurrence; however, no evidence of malignancy was found. CLINICAL DISCUSSION: We diagnosed it as a case of RRD. We managed her conservatively. Later, she was rechallenged with the same dose in subsequent cycles with systemic steroid coverage, which she tolerated very well, except for the reappearance of mild erythema following each cycle of maintenance dose of Trastuzumab. CONCLUSION: Radiation recall dermatitis is an extremely rare phenomenon; hence, an acquaintance of clinicians with this rare entity is essential for timely diagnosis and appropriate management.

A review of machine learning and deep learning algorithms for Parkinson's disease detection using handwriting and voice datasets.

Parkinson's Disease (PD) is a prevalent neurodegenerative disorder with significant clinical implications. Early and accurate diagnosis of PD is crucial for timely intervention and personalized treatment. In recent years, Machine Learning (ML) and Deep Learning (DL) techniques have emerged as promis-ing tools for improving PD diagnosis. This review paper presents a detailed analysis of the current state of ML and DL-based PD diagnosis, focusing on voice, handwriting, and wave spiral datasets. The study also evaluates the effectiveness of various ML and DL algorithms, including classifiers, on these datasets and highlights their potential in enhancing diagnostic accuracy and aiding clinical decision-making. Additionally, the paper explores the identifi-cation of biomarkers using these techniques, offering insights into improving the diagnostic process. The discussion encompasses different data formats and commonly employed ML and DL methods in PD diagnosis, providing a comprehensive overview of the field. This review serves as a roadmap for future research, guiding the development of ML and DL-based tools for PD detection. It is expected to benefit both the scientific community and medical practitioners by advancing our understanding of PD diagnosis and ultimately improving patient outcomes.