Mobile game addiction and its association with musculoskeletal pain among students: A cross-sectional study.

BACKGROUND: The purpose of this study was to ascertain whether there is a difference in musculoskeletal pain between those who are addicted to mobile games and those who are not, to ascertain the association between mobile game addiction and socio-demographic variables, and to ascertain the pain predictor for mobile game addiction on different musculoskeletal regions. METHODS: There were 840 students in all, both males and females, in this cross-sectional survey from three distinct Bangladeshi institutions. The Nordic Musculoskeletal Discomfort Questionnaire, the Gaming Addiction Scale, and the demographic data form were distributed to the participants. The data were analyzed using the Chi-square test and descriptive statistics. Binary logistic regression was used to find the predicted risk factor for mobile gaming addiction. RESULTS: Musculoskeletal pain affects 52.1% of participants in some part of the body. Males have a 2.01-fold higher likelihood of developing gaming addiction compared to females. Those who are addicted to mobile games experience a higher occurrence of pain in the neck, upper back, elbows, and wrist and hands with a odds ratio of (OR 2.84, 95% CI: 1.49-5.36; p = 0.016), (OR 3.75, 95% CI 1.97-7.12; p = <0.001), (OR 3.38, 95% CI 1.34-8.50; p = 0.010), and (OR 2.14, 95% CI 1.00-4.57; p = 0.049) respectively. CONCLUSION: These results demonstrate that mobile gaming addiction raises students' risk of musculoskeletal discomfort. Two-three times higher risk of developing pain in the neck, upper back, elbows, and wrist and hands among mobile game addicts.

Characterization of the dominant strain (G-VII) of Newcastle disease viruses isolated from commercial chickens in Bangladesh during recent outbreaks.

Objective: Newcastle disease virus genotype VII (NDV-GVII), an extremely infectious pathogen, has been causing severe economic consequences for the chicken industry. The current study aimed to isolate and characterize NDV-GVII from commercial chickens in Bangladesh during a recent outbreak. Materials and Methods: From clinically suspected chickens from 70 commercial poultry farms, a total of 420 samples (trachea, lungs, and brain tissue) were collected. The samples were cultivated in 9-10 day-old seronegative embryonated chicken eggs (ECEs) after evaluating them using the rapid Newcastle disease virus (NDV) antigen detection kit. The hemagglutination (HA) inhibition test, agar gel immune diffusion (AGID) test, molecular detection by reverse transcription-polymerase chain reaction (RT-PCR), and phylogenetic studies using gene sequences of fusion (F) protein. The HA pattern of isolated NDV was determined using different avian and mammalian red blood cells (RBCs). The pathogenicity of the isolated virus was evaluated using mean death time (MDT), intravenous pathogenicity index (IVPI), and intracerebral pathogenicity index (ICPI). Results: The study found 87 NDV samples positive using the rapid NDV Ag detection kit and then 60 positives for virus isolation in ECEs. All 60 isolates were positive for NDV by HI, AGID, and RT-PCR. Phylogenetic tree analysis indicated that recent NDV isolates belong to genotype VII and exhibit a similarity of 99.7%-98.5% with isolates from Bangladesh, Iran, and India. The new isolates, identified as velogenic strains of NDV, possess an F protein cleavage site with 112-R-T-K-R-F-117 amino acid motifs. The isolated NDV showed diversified HA activity while using RBCs from birds and mammals. The results of ICPI, IVPI, and MDT indicated that the recent NDV isolates were very virulent. Conclusion: This study concluded that NDV-GVII is prevalent in commercial poultry farms in Bangladesh.

Characterization of infectious laryngotracheitis virus isolated from commercial layer chickens in Bangladesh during the year 2021-2022.

Objective: Infectious laryngotracheitis virus (ILTV) is responsible for causing infectious laryngotracheitis (ILT), which is a rapidly spreading and extremely transmissible disease in chickens. The current research aims to isolate and characterize ILTV from layer chickens in Bangladesh. Materials and Methods: A total of 345 samples (trachea, larynx, and lungs) were collected from ILT-suspected dead and sick layer chickens of 32 ILT-suspected farms in three different outbreak districts (Gazipur, Tangail, and Mymensingh) of Bangladesh during the outbreak year 2021-2022. Rapid detection kits examined the samples for avian influenza virus (AIV) and Newcastle disease virus (NDV). ILTV-specific primers were used to screen 72 NDV- and AIV-negative samples by polymerase chain reaction (PCR). Using chorioallantoic membrane (CAM), the study isolated the ILT virus from 9 to 10-day-old seronegative embryonated chicken eggs (ECEs) using selected PCR-positive samples. The virus was confirmed using nucleotide sequencing, agar gel immunodiffusion test (AGIDT), viral neutralization test (VNT), and pathogenicity evaluations using mortality index for chicken embryos (MICEs) and intra-tracheal pathogenicity index (ITPI). Results: The results indicated that among the PCR-positive 10 samples, only two (Alim_ILT_1001 and Alim_ILT_1,000) were found positive using ECEs. There were two field isolates of ILTVs, as shown by the amplicon size of the ICP4 gene-based PCR. A phylogenetic study of the ICP4 gene revealed that the recent isolates have a close similarity with the ILTV isolates of Turkey, Bangladesh, and Australia. AGIDT revealed strong precipitation lines due to ILTV-specific antibodies reacting with field viruses, while VNT neutralized both isolates with conventional ILTV antibodies. The pathogenicity testing indicated that Alim_ILT_1001 had MICE and ITPI values of 0.77 and 0.63, whereas Alim_ILT_1,000 had 0.71 and 0.57. Conclusion: Both the ILTV isolates have similarities with the isolates of Turkey, Bangladesh, and Australia, and they are highly virulent for chickens.

An in-depth analysis of COVID-19 treatment: Present situation and prospects.

Coronavirus disease 2019 (COVID-19) the most contagious infection caused by the unique type of coronavirus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), produced a global pandemic that wreaked havoc on the health-care system, resulting in high morbidity and mortality. Several methods were implemented to tackle the virus, including the repurposing of existing medications and the development of vaccinations. The purpose of this article is to provide a complete summary of the current state and future possibilities for COVID-19 therapies. We describe the many treatment classes, such as antivirals, immunomodulators, and monoclonal antibodies, that have been repurposed or developed to treat COVID-19. We also looked at the clinical evidence for these treatments, including findings from observational studies and randomized-controlled clinical trials, and highlighted the problems and limitations of the available evidence. Furthermore, we reviewed existing clinical trials and prospective COVID-19 therapeutic options, such as novel medication candidates and combination therapies. Finally, we discussed the long-term consequences of COVID-19 and the importance of ongoing research into the development of viable treatments. This review will help physicians, researchers, and policymakers to understand the prevention and mitigation of COVID-19.

MicroRNA-455-3P as a peripheral biomarker and therapeutic target for mild cognitive impairment and Alzheimer's disease.

MicroRNAs are small non-coding RNAs evolutionary conserved molecules. They regulate cellular processes, including RNA silencing, post-translational gene expression and neurodegeneration. MicroRNAs are involved with human diseases such as cancer, Alzheimer's disease (AD) and others. Interestingly, cerebrospinal fluids (CSF) and the blood of AD patients have altered expressions of many RNAs, which may serve as potential peripheral biomarkers. The intensive investigation from our lab revealed that microRNA-455-3 P (miR-455-3p) is a strong candidate as a potential biomarker and therapeutic target for AD. Several genes implicated in the pathogenesis of AD are directly targeted by miR-455-3p. Several years of our lab research revealed that miR-455-3p regulates important physiological processes associated with AD, such as the processing of the amyloid precursor protein (APP), TGF-ß signaling, the regulation of oxidative stress, mitochondrial biogenesis, and synaptic damages. The expression of miR-455-3p in mild cognitive impaired subjects and AD patients pointed out its involvement in AD progression. Recently, our lab generated both transgenic and knockout mice for miR-455-3p. Interestingly miR-455-3p transgenic mice showed superior cognitive learning, improved memory and extended lifespan compared to age matched wild-type mice, whereas miR-455-3-p knockout mice showed cognitive decline and reduced lifespan. Information derived from mouse models further demonstrated the advantageous impact of miR-455-3p on dendritic growth, synaptogenesis, and mitochondrial biogenesis in preventing the onset and progression of AD. The identification of miR-455-3p as a biomarker was suggested by its presence in postmortem AD brains, B-lymphocytes, and fibroblasts. Our hypothesis that miR-455-3p could be a peripheral biomarker and therapeutic target for AD.

XRCC1 and XPD polymorphisms: clinical outcomes and risk of prostate cancer in Bangladeshi population.

BACKGROUND: In Bangladesh, only a fraction of prostate cancer patients are diagnosed annually due to lack of symptom awareness and screening challenges, resulting in high mortality. Aiming to improve screening methods, we evaluated X-ray cross-complementing gene 1 (XRCC1) Arg194Gln and Xeroderma pigmentosum group D (XPD) Lys751Gln polymorphisms to determine their relevance as potential markers for predicting prostate cancer risk, severity and clinical parameters in Bangladeshi population. METHODS AND RESULTS: This study included 132 prostate cancer patients and 135 healthy controls. Genotype analysis was done from blood samples by the PCR-RFLP method. The XRCC1 Trp/Trp genotype was associated with prostate cancer (ORadj = 5.51; 95% CI = 1.13-26.78; p-value = 0.03) compared to Arg/Arg genotype. No significant association was found between the XPD variants and prostate cancer risk. The XRCC1 Trp/Trp genotype increased prostate cancer risk in smokers and non-smokers but was statistically non-significant. In individuals without a family history of cancer, the XRCC1 Trp/Trp genotype had a non-significant 4.64-fold higher risk (ORadj=4.64; 95% CI = 0.88-24.36; p-value = 0.07), while the XPD Gln/Gln had a 2.66-fold non-significant higher risk (ORadj=2.66; 95% CI = 0.88-8.10; p-value = 0.09). The XRCC1 Trp/Trp variant was associated with hematuria risk, higher mean serum creatinine, and mean prostate-specific antigen (PSA) levels in prostate cancer patients. The XPD Gln/Gln variant was only associated with higher mean serum creatinine levels. CONCLUSION: Our findings suggest that XRCC1 screening may be used as a biomarker for prostate cancer to improve early diagnosis in Bangladesh.

Post-discharge mortality among patients hospitalised with severe acute respiratory infection, Bangladesh, 2012-2019: a prospective observational study.

Background: Enhancing outcomes post-hospitalisation requires an understanding of predictive factors for adverse events. This study aimed to estimate post-discharge mortality rates among patients with severe acute respiratory infection (SARI) in Bangladesh, identify associated factors, and document reported causes of death. Methods: From January 2012 to December 2019, we conducted follow-up calls to patients or their families 30 days after discharge to assess the status of patients with SARI. Proportions of deaths within 30 days of discharge were estimated, and a comparative analysis of demographics, clinical characteristics, and influenza illness between decedents and survivors was performed using multivariable Cox regression models. Findings: Among 23,360 patients with SARI (median age: 20 years, IQR: 1.5-48, 65% male), 351 (1.5%) died during hospitalisation. Of 23,009 patients alive at discharge, 20,044 (87%) were followed, with 633 (3.2%) deaths within 30 days of discharge. In children (<18 years), difficulty breathing (adjusted hazard ratio [aHR] 1.8; 95% CI 1.1-3.0), longer hospital stay (aHR 1.1; 95% CI 1.1-1.1), and heart diseases (aHR 8.5; 95% CI 3.2-23.1) were associated with higher post-discharge death risk. Among adults (≥18 years), difficulty breathing (aHR 2.3; 95% CI 1.7-3.0), chronic obstructive pulmonary disease (aHR 1.7; 95% CI 1.4-2.2), and intensive care unit admission (aHR 5.2; 95% CI 1.9-14.0) were linked to elevated post-discharge death risk. Influenza virus was detected in 13% (46/351) of in-hospital SARI deaths and 10% (65/633) of post-discharge SARI deaths. Interpretation: Nearly one in twenty patients with SARI died during hospitalisation or within 1 month of discharge, with two-thirds of deaths occurring post-discharge. Seasonal influenza vaccination is recommended to mitigate influenza-associated mortality. To enhance post-discharge outcomes, hospitals should consider developing safe-discharge algorithms, reinforcing post-discharge care plans, and establishing outpatient monitoring for recently discharged patients. Funding: Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA [U01GH002259].

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.

Incidence of Hospitalization due to Influenza-Associated Severe Acute Respiratory Infection During 2010-2019 in Bangladesh.

BACKGROUND: Global influenza-associated acute respiratory infections contribute to 3-5 million severe illnesses requiring hospitalization annually, with 90% of hospitalizations occurring among children < 5 years in developing countries. In Bangladesh, the inadequate availability of nationally representative, robust estimates of influenza-associated hospitalizations limits allocation of resources for prevention and control measures. METHODS: This study used data from the hospital-based influenza surveillance (HBIS) system in Bangladesh from 2010 to 2019 and healthcare utilization surveys to determine hospital utilization patterns in the catchment area. We estimated annual influenza-associated hospitalization numbers and rates for all age groups in Bangladesh using WHO methods, adjusted for a 6-day-a-week enrollment schedule, selective testing of specimens from children under five, and healthcare-seeking behavior, based on the proportion of symptomatic community participants seeking healthcare within the past week. We then estimated national hospitalization rates by multiplying age-specific hospitalization rates with the corresponding annual national census population. RESULTS: Annual influenza-associated hospitalization rates per 100,000 population for all ages ranged from 31 (95% CI: 27-36) in 2011 to 139 (95% CI: 130-149) in 2019. Children < 5 years old had the highest rates of influenza-associated hospitalization, ranging from 114 (95% CI: 90-138) in 2011 to 529 (95% CI: 481-578) in 2019, followed by adults aged ≥ 65 years with rates ranging from 46 (95% CI: 34-57) in 2012 to 252 (95% CI: 213-292) in 2019. The national hospitalization estimates for all ages during 2010-2019 ranged from 47,891 to 236,380 per year. CONCLUSIONS: The impact of influenza-associated hospitalizations in Bangladesh may be considerable, particularly for young children and older adults. Targeted interventions, such as influenza vaccination for these age groups, should be prioritized and evaluated.

Resolving the Current Controversy of Use and Reuse of Housekeeping Proteins in Ageing Research: Focus on Saving People's Tax Dollars.

The use of housekeeping genes and proteins to normalize mRNA and protein levels in biomedical research has faced growing scrutiny. Researchers encounter challenges in determining the optimal frequency for running housekeeping proteins such as ß-actin, Tubulin, and GAPDH for nuclear-encoded proteins, and Porin, HSP60, and TOM20 for mitochondrial proteins alongside experimental proteins. The regulation of these proteins varies with age, gender, disease progression, epitope nature, gel running conditions, and their reported sizes can differ among antibody suppliers. Additionally, anonymous readers have raised concerns about peer-reviewed and published articles, creating confusion and concern within the research and academic institutions. To clarify these matters, this minireview discusses the role of reference housekeeping proteins in Western blot analysis and outlines key considerations for their use as normalization controls. Instead of Western blotting of housekeeping proteins, staining of total proteins, using Amido Black and Coomassie Blue can be visualized the total protein content on a membrane. The reducing repeated Western blotting analysis of housekeeping proteins, will save resources, time and efforts and in turn increase the number of competitive grants from NIH and funding agencies. We also discussed the use of dot blots over traditional Western blots, when protein levels are low in rare tissues/specimens and cell lines. We sincerely hope that the facts, figures, and discussions presented in this article will clarify the current controversy regarding housekeeping protein(s) use, reuse, and functional aspects of housekeeping proteins. The contents presented in our article will be useful to students, scholars and researchers of all levels in cell biology, protein chemistry and mitochondrial research.

Yield stability among potato varieties suitable for different agroecological regions of Bangladesh.

Multilocation trials are usually performed in breeding and variety evaluation programs to identify stable genotype(s) with similar crop performance in various environments. The present study evaluated the stability of six selected potato varieties (BARI Alu-7, BARI Alu-8, BARI Alu-25, BARI Alu-28, BARI Alu-36, and BARI Alu-41) suitable for multiple locations (Barishal, Bogura, Cumilla, Jamalpur, Jashore, Munshiganj, Mymensingh, and Rajshahi) in Bangladesh from 2014 to 2019. The study considered genotype and environment as treatments, year as replications and used a randomized complete block design (RCBD) with to construct the genotype plus genotype-vs-environment interaction (GGE) model. The joint analysis of variance revealed significant differences among the genotypes and environments (GE). The scores of PC1 (principal component 1) and PC2 (principal component 2) cumulatively explained approximately 63 % of the total variation in GE interactions and were used to construct the GGE biplot. BARI Alu-8 and BARI Alu-28 were the best genotypes, with high average yields and high stability across the locations. Jamalpur and Munshiganj was identified as the desired locations among the tested environments for growing all the genotypes. This study will help potato growers select highly stable high-performance varieties for a particular environment to achieve maximum tuber production.

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.

Trastuzumab-induced toxic epidermal necrolysis in a Her-2-positive metastatic breast cancer patient-A rare case report.

Toxic Epidermal Necrolysis (TEN) is a rare, but potentially fatal mucocutaneous reaction, that may occur due to an immunologic response to certain medications. However, TEN triggered by Trastuzumab is extremely rare. Early diagnosis, recognition, and prompt cessation of the offending drugs and initiation of steroid therapy with supportive management are the most important actions for managing TEN. Although rare, it is important to be vigilant about this potential adverse reactions associated with trastuzumab to ensure patient safety and contribute to better outcomes.

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.

Amyloid-ß and Phosphorylated Tau are the Key Biomarkers and Predictors of Alzheimer's Disease.

Alzheimer's disease (AD) is a age-related neurodegenerative disease and is a major public health concern both in Texas, US and Worldwide. This neurodegenerative disease is mainly characterized by amyloid-beta (Aß) and phosphorylated Tau (p-Tau) accumulation in the brains of patients with AD and increasing evidence suggests that these are key biomarkers in AD. Both Aß and p-tau can be detected through various imaging techniques (such as positron emission tomography, PET) and cerebrospinal fluid (CSF) analysis. The presence of these biomarkers in individuals, who are asymptomatic or have mild cognitive impairment can indicate an increased risk of developing AD in the future. Furthermore, the combination of Aß and p-tau biomarkers is often used for more accurate diagnosis and prediction of AD progression. Along with AD being a neurodegenerative disease, it is associated with other chronic conditions such as cardiovascular disease, obesity, depression, and diabetes because studies have shown that these comorbid conditions make people more vulnerable to AD. In the first part of this review, we discuss that biofluid-based biomarkers such as Aß, p-Tau in cerebrospinal fluid (CSF) and Aß & p-Tau in plasma could be used as an alternative sensitive technique to diagnose AD. In the second part, we discuss the underlying molecular mechanisms of chronic conditions linked with AD and how they affect the patients in clinical care.

Discovery of Bacterial Key Genes from 16S rRNA-Seq Profiles That Are Associated with the Complications of SARS-CoV-2 Infections and Provide Therapeutic Indications.

SARS-CoV-2 infections, commonly referred to as COVID-19, remain a critical risk to both human life and global economies. Particularly, COVID-19 patients with weak immunity may suffer from different complications due to the bacterial co-infections/super-infections/secondary infections. Therefore, different variants of alternative antibacterial therapeutic agents are required to inhibit those infection-causing drug-resistant pathogenic bacteria. This study attempted to explore these bacterial pathogens and their inhibitors by using integrated statistical and bioinformatics approaches. By analyzing bacterial 16S rRNA sequence profiles, at first, we detected five bacterial genera and taxa (Bacteroides, Parabacteroides, Prevotella Clostridium, Atopobium, and Peptostreptococcus) based on differentially abundant bacteria between SARS-CoV-2 infection and control samples that are significantly enriched in 23 metabolic pathways. A total of 183 bacterial genes were found in the enriched pathways. Then, the top-ranked 10 bacterial genes (accB, ftsB, glyQ, hldD, lpxC, lptD, mlaA, ppsA, ppc, and tamB) were selected as the pathogenic bacterial key genes (bKGs) by their protein-protein interaction (PPI) network analysis. Then, we detected bKG-guided top-ranked eight drug molecules (Bemcentinib, Ledipasvir, Velpatasvir, Tirilazad, Acetyldigitoxin, Entreatinib, Digitoxin, and Elbasvir) by molecular docking. Finally, the binding stability of the top-ranked three drug molecules (Bemcentinib, Ledipasvir, and Velpatasvir) against three receptors (hldD, mlaA, and lptD) was investigated by computing their binding free energies with molecular dynamic (MD) simulation-based MM-PBSA techniques, respectively, and was found to be stable. Therefore, the findings of this study could be useful resources for developing a proper treatment plan against bacterial co-/super-/secondary-infection in SARS-CoV-2 infections.

SuperAgers and centenarians, dynamics of healthy ageing with cognitive resilience.

Graceful healthy ageing and extended longevity is the most desired goal for human race. The process of ageing is inevitable and has a profound impact on the gradual deterioration of our physiology and health since it triggers the onset of many chronic conditions like dementia, osteoporosis, diabetes, arthritis, cancer, and cardiovascular disease. However, some people who lived/live more than 100 years called 'Centenarians" and how do they achieve their extended lifespans are not completely understood. Studying these unknown factors of longevity is important not only to establish a longer human lifespan but also to manage and treat people with shortened lifespans suffering from age-related morbidities. Furthermore, older adults who maintain strong cognitive function are referred to as "SuperAgers" and may be resistant to risk factors linked to cognitive decline. Investigating the mechanisms underlying their cognitive resilience may contribute to the development of therapeutic strategies that support the preservation of cognitive function as people age. The key to a long, physically, and cognitively healthy life has been a mystery to scientists for ages. Developments in the medical sciences helps us to a better understanding of human physiological function and greater access to medical care has led us to an increase in life expectancy. Moreover, inheriting favorable genetic traits and adopting a healthy lifestyle play pivotal roles in promoting longer and healthier lives. Engaging in regular physical activity, maintaining a balanced diet, and avoiding harmful habits such as smoking contribute to overall well-being. The synergy between positive lifestyle choices, access to education, socio-economic factors, environmental determinants and genetic supremacy enhances the potential for a longer and healthier life. Our article aims to examine the factors associated with healthy ageing, particularly focusing on cognitive health in centenarians. We will also be discussing different aspects of ageing including genomic instability, metabolic burden, oxidative stress and inflammation, mitochondrial dysfunction, cellular senescence, immunosenescence, and sarcopenia.

Nanomedicine: A New Frontier in Alzheimer's Disease Drug Targeting.

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder affecting elderly individuals, characterized by progressive cognitive decline leading to dementia. This review examines the challenges posed by anatomical and biochemical barriers such as the blood-brain barrier (BBB), blood-cerebrospinal fluid barrier (BCSFB), and p-glycoproteins in delivering effective therapeutic agents to the central nervous system (CNS) for AD treatment. This article outlines the fundamental role of acetylcholinesterase inhibitors (AChEIs) and NMDA(N-Methyl-D-Aspartate) receptor antagonists in conventional AD therapy and highlights their limitations in terms of brain-specific delivery. It delves into the intricacies of BBB and pglycoprotein-mediated efflux mechanisms that impede drug transport to the CNS. The review further discusses cutting-edge nanomedicine-based strategies, detailing their composition and mechanisms that enable effective bypassing of BBB and enhancing drug accumulation in brain tissues. Conventional therapies, namely AChEIs and NMDA receptor antagonists, have shown limited efficacy and are hindered by suboptimal brain penetration. The advent of nanotechnology-driven therapeutic delivery systems offers promising strategies to enhance CNS targeting and bioavailability, thereby addressing the shortcomings of conventional treatments. Various nanomedicines, encompassing polymeric and metallic nanoparticles (MNPs), solid lipid nanoparticles (SLNs), liposomes, micelles, dendrimers, nanoemulsions, and carbon nanotubes, have been investigated for their potential in delivering anti-AD agents like AChEIs, polyphenols, curcumin, and resveratrol. These nanocarriers exhibit the ability to traverse the BBB and deliver therapeutic payloads to the brain, thereby holding immense potential for effective AD treatment and early diagnostic approaches. Notably, nanocarriers loaded with AChEIs have shown promising results in preclinical studies, exhibiting improved therapeutic efficacy and sustained release profiles. This review underscores the urgency of innovative drug delivery approaches to overcome barriers in AD therapy. Nanomedicine-based solutions offer a promising avenue for achieving effective CNS targeting, enabling enhanced bioavailability and sustained therapeutic effects. As ongoing research continues to elucidate the complexities of CNS drug delivery, these advancements hold great potential for revolutionizing AD treatment and diagnosis.

Red ginseng ameliorates lipotoxicity-induced renal fibrosis in hyperuricemia mice.

ETHNOPHARMACOLOGICAL RELEVANCE: Chronic kidney disease can be caused by numerous diseases including obesity and hyperuricemia (HUA). Obesity may exacerbate the renal injury caused by HUA. Red ginseng, a steamed products of Panax ginseng Meyer root, is known for its remarkable efficacy in improving metabolic syndrome, such as maintaining lipid metabolic balance. However, the role of red ginseng on hyperuricemia-induced renal injury in obese cases remains unclear. AIM OF THE STUDY: This study aimed to investigate the action of red ginseng extract (RGE) on lipotoxicity-induced renal injury in HUA mice. MATERIALS AND METHODS: A high-fat diet (HFD)-induced obesity model was employed to initially investigate the effects of RGE on body weight, TC, OGTT, renal lipid droplets, and renal function indices such as uric acid, creatinine, and urea nitrogen. Renal structural improvement was demonstrated by H&E staining. Subsequently, an animal model combining obesity and HUA was established to further study the impact of RGE on OAT1 and ACC1 expression levels. The mechanisms underlying renal injury regulation by RGE were postulated on the basis of RNA sequencing, which was verified by immunohistochemical (including F4/80, Ki67, TGF-ß1, α-SMA, and E-cadherin), Masson, and Sirius red staining. RESULTS: RGE modulated HFD-induced weight gain, glucose metabolism, and abnormalities of uric acid, urea nitrogen, and creatinine. RGE alleviated the more severe renal histopathological changes induced by obesity combined with HUA, with down-regulated the protein levels of ACC1, F4/80, Ki67, TGF-ß1, and α-SMA, and up-regulated OAT1 and E-cadherin. CONCLUSIONS: RGE has ameliorative effects on chronic kidney disease caused by obesity combined with HUA by maintaining lipid balance and reducing renal inflammation and fibrosis.

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.