Clinical and translational advances in primary brain tumor therapy with a focus on glioblastoma-A comprehensive review of the literature.

This comprehensive review paper examines the most updated state of research on glioblastoma, an aggressive brain tumor with limited treatment options. By analyzing 76 recent studies, from translational and basic sciences, to clinical trials, we highlight various aspects of glioblastoma and shed light on potential therapeutic strategies. The interplay between tumor cells, neural progenitor cells, and the tumor microenvironment is explored. Targeting the PI3K-Akt-mTOR pathway through extracellular-vesicle (EV)-mediated signaling emerges as a potential therapeutic strategy. Personalized modeling approaches utilizing patient-specific MRI data offer promise for optimizing treatment strategies. The response of glioblastoma stem cells (GSCs) to different treatment modalities is examined, emphasizing the need to inhibit the transformation of proneural (PN) GSCs into resistant mesenchymal (MES) GSCs. Metabolic therapy and combination therapies show potential in reversing treatment resistance and inhibiting both PN and MES GSCs. Immunotherapy, targeted approaches, and molecular dynamics in gliomas are discussed, providing insights into early-stage diagnosis and treatment. Additionally, the potential use of Zika virus as an oncolytic agent is explored. Analysis of phase 0 to 3 clinical trials reveal promising outcomes for various experimental treatments, highlighting the importance of combination therapies, predictive signatures, and patient selection strategies. Specific compounds demonstrate potential therapeutic benefits and tolerability. Phase 3 trials indicate the efficacy of DCVax-L in improving survival rates and depatux-m in prolonging progression-free survival. These findings emphasize the importance of personalized treatment approaches and continued exploration of targeted therapies, immunotherapies, and tumor biology understanding in shaping the future of glioblastoma treatment.

Green synthesis of NiO and NiO@graphene oxide nanomaterials using Elettaria cardamomum leaves: Structural and electrochemical studies.

An eco-friendly synthetic route was developed for the formation of nickel oxide (NiOaq and NiOet) nanoparticles (NPs) by treating Ni(NO3)2.6H2O with aqueous/ethanolic extracts of Elettaria cardamomum leaves; the same reaction was performed in the presence of graphene oxide (GO) to produce NiOaq@GO and NiOet@GO nanocomposites (NCs), respectively. The NMs were characterized by XRD, FT-IR, SEM, EDX, UV-visible spectroscopy, and TGA-DSC analysis. They were also subjected to electrochemical investigations and photocatalytic degradation of crystal violet (CV) dye. XRD analysis revealed the average crystallite sizes of 8.84-14.07 nm with a face-centered cubic form of NiO NPs and a hexagonal structure of their nanocomposites with GO. FT-IR spectroscopy confirmed the presence of Ni-O vibrations at 443-436 cm-1. SEM images confirmed the spherical morphology of NiO NPs while NiOaq@GO NCs contained randomly aggregated, thin, and wrinkled graphene sheets. NiOaq and NiOet have shown particle sizes of 27.7-30.63 nm which were decreased to 19.33-26.39 nm in their respective NiOaq@GO and NiOet@GO NCs. EDX spectra verified the homogeneous distribution of elements (Ni, O, C) on the surface of the particles. The synthesized NCs have shown smaller band gaps (NiOaq@GO = 3.74 eV; NiOet@GO = 3.34 eV) as compared to their respective NPs (NiOaq = 5.0 eV; NiOet = 3.89 eV). TGA/DSC data was used to find the thermal stabilities, glass transition temperatures, and enthalpies. Cyclic voltammetry measurements exhibited distinct oxidation and reduction peaks. NCs exhibited better potential as electrode materials for supercapacitor applications as compared to their respective NPs. NiOet@GO exhibited the best electrochemical performance and photocatalytic degradation efficiency of CV dye. After 120 min exposure to sunlight, the degradation coefficient of CV was observed to be 82.93, 86.34, 89.99, 90.27 and 81.65 % in the presence of NiOaq, NiOet, NiOaq@GO, NiOet@GO and GO, respectively.

Calcium oxide nanoparticles ameliorate cadmium toxicity in alfalfa seedlings by depriving its bioaccumulation, enhancing photosystem II functionality and antioxidant gene expression.

Cadmium (Cd) is a highly toxic and carcinogenic pollutant that poses significant risks to living organisms and the environment, as it is absorbed by the plant roots and accumulates in different parts of crop during its production. A promising sustainable strategy to counteract these threats to use calcium oxide nanoparticles (CaO-NPs) as soil supplements in fodder crops. This approach has shown notable morpho-physiological and biochemical improvements under metal toxicity conditions. However, the specific mechanisms driving Cd tolerance, particularly at physio-biochemical level and antioxidant related genes expression in fodder crops including alfalfa remain unexplored. CaO-NPs supplementation can trigger various signaling pathways that lead to enhance the photosynthetic pigments formation, stomatal conductance, CO2 assimilation rate and quantum yield of photosystem II. In this study, we evaluated various doses of CaO-NPs (0, 25, 50, and 100 mg kg-1) for their efficacy in reducing Cd bioavailability and toxicity in alfalfa plants. Our results demonstrated that Ca2+ and Cd2+, which share the same ionic radius, compete for ion transport through channels. The small size and high availability of CaO-NPs facilitate their rapid translocation within plant tissues, reducing metal uptake by 61 % in shoots and 30 % in roots. Notably, application of CaO-NPs at 100 mg kg-1 significantly increased shoot length (44 %) and root length (35 %) as compared to Cd-treated control plants. The highest dose of CaO-NPs also improved photosynthetic efficiency and gas exchange attributes including gs, Tr, Pn and Ci by 66 %, 27 %, 33 % and Ci 21 %, respectively, compared with the Cd treated control. Moreover, CaO-NPs (at 100 mg kg-1) alleviated metal-induced oxidative stress by boosting antioxidant enzyme activities like superoxide dismutase (25 %) peroxidase (42 %), catalase (72 %) and ascorbate peroxidase (87 %) and diminishing reactive oxygen species (ROS) production when compared with sole Cd treatment. Scanning and transmission electron microscopy revealed that CaO-NPs positively impacted stomatal conductance and mitigated Cd toxicity in leaf ultrastructure. Additionally, the highest dose of CaO-NPs markedly upregulated the expression of antioxidant-related genes, MsCu/Zn SOD, MtPOD, MtCAT, and MtAPX in roots and shoots by 0.67 and 1.03 fold-change (FC), 0.61 and 0.53 FC, 0.54 and 0.88 FC, and 0.46 and 0.66 FC, respectively. In conclusion, CaO-NPs demonstrate significant potential for environmentally friendly mitigation of Cd stress in alfalfa by reducing its uptake, thereby supporting sustainable agriculture.

The Factors Associated With Mutant Epidermal Growth Factor Receptor Positivity in Patients With Lung Cancer: A Study From a Tertiary Care Center in Pakistan.

Objective In this study, we sought to elucidate the relationship between demographic and clinical factors and epidermal growth factor receptor tyrosine kinase (EGFR-TK) positivity in patients with advanced-stage lung cancer at a tertiary care center in Pakistan. Methods This analytical cross-sectional study was conducted from February 2020 to July 2023 at Shaikh Zayed Hospital, Lahore, Pakistan, in collaboration with the Centre of Excellence in Molecular Biology (CEMB), University of the Punjab. The study included 70 consecutive patients with advanced-stage lung cancer, and aimed to identify common EGFR mutations (Exon 19 deletion and Exon 21 L858R mutation), determine their frequency, and correlate EGFR-TK mutation positivity with clinical and non-clinical factors. Tissue acquisition and processing involved bronchoscopy, pleuroscopy, or percutaneous ultrasound-guided lung mass biopsy, followed by molecular analysis using polymerase chain reaction (PCR) extraction, amplification, and sequencing. The study employed convenient sampling and included adults aged over 18 years with histologically confirmed lung cancer. Results We enrolled 70 lung cancer patients, with a mean age of 60.87 years, and a male-to-female ratio of 1.4:1. The majority (61.4%) had adenocarcinoma, and 34.3% harbored a mutant EGFR-TK. EGFR mutations were more common in adenocarcinoma (91.7%) and associated with female non-smokers. Binary logistic regression analysis revealed that age <50 years and adenocarcinoma type were significant predictors of EGFR mutations. We found no significant associations with gender, smoking status, or other variables. These findings have implications for personalized treatment approaches in lung cancer patients. Conclusions Our study reveals a high frequency of occult EGFR mutations (Exon 19 deletion and Exon 21 L858R mutation) in non-small cell lung cancer (NSCLC) patients, particularly among male smokers and female non-smokers. These findings emphasize the importance of routine EGFR mutation testing to identify patients who may benefit from targeted therapies, ultimately improving treatment outcomes.

Genetic variation and population structure of Taenia multiceps (Coenurus cerebralis) based on mitochondrial cox1 gene: A comprehensive global analysis.

Taenia multiceps is a neglected parasite having veterinary and public health importance. The predilection sites of the parasite larva (Coenurus cerebralis) are brain (cerebral coenurosis) and subcutaneous (non-cerebral coenurosis). There is a dearth of data regarding molecular characterization of T. multiceps and even fewer population structure-based studies on T. multiceps. The current study was conducted to provide epidemiological information regarding the global population structure of the parasite. The NCBI GenBank database was accessed to download the sequences of cox1 gene, which were further subjected to PopArt software to construct median-joining networks. The DnaSp software was used to compute neutrality and diversity indices. Host and region-wise indices of neutrality and diversity were also computed. There were 166 gene sequences found in the NCBI database. Followed by removal of short gene sequences, 143 were considered to perform bioinformatic analyses. A total of 30 haplotypes with 46 mutations and 23 parsimony informative sites were found. High diversity (Hd = 0.889, π = 0.01186) and negative but statistically insignificant neutrality indices (Tajima's D = -1.57659, Fu's Fs = -10.552) were found. Region-wise results revealed highest haplotype diversities in isolates from KSA (Hd = 1.00) followed by Greece and Italy (Hd = 0.962), and China (Hd = 0.931). Host-wise data analysis showed an overall negative Tajima's D value and there exists highest haplotype diversity in cattle (Hd = 1.00) followed by dogs (Hd = 0.833), sheep (Hd = 0.795) and goats (Hd = 0.788). The findings of the study indicate that the population diversity of T. multiceps will increase worldwide as shown by high diversity and negative neutrality indices. The findings of the study significantly add-in to the existing bank of knowledge about population structure of T. multiceps. We recommend conducting more studies employing different genetic markers to better comprehend the epidemiology of the parasite.

Artificial intelligence-driven transformations in diabetes care: a comprehensive literature review.

Artificial intelligence (AI) has been applied in healthcare for diagnosis, treatments, disease management, and for studying underlying mechanisms and disease complications in diseases like diabetes and metabolic disorders. This review is a comprehensive overview of various applications of AI in the healthcare system for managing diabetes. A literature search was conducted on PubMed to locate studies integrating AI in the diagnosis, treatment, management and prevention of diabetes. As diabetes is now considered a pandemic now so employing AI and machine learning approaches can be applied to limit diabetes in areas with higher prevalence. Machine learning algorithms can visualize big datasets, and make predictions. AI-powered mobile apps and the closed-loop system automated glucose monitoring and insulin delivery can lower the burden on insulin. AI can help identify disease markers and potential risk factors as well. While promising, AI's integration in the medical field is still challenging due to privacy, data security, bias, and transparency. Overall, AI's potential can be harnessed for better patient outcomes through personalized treatment.

Artificial intelligence: revolutionizing robotic surgery: review.

Robotic surgery, known for its minimally invasive techniques and computer-controlled robotic arms, has revolutionized modern medicine by providing improved dexterity, visualization, and tremor reduction compared to traditional methods. The integration of artificial intelligence (AI) into robotic surgery has further advanced surgical precision, efficiency, and accessibility. This paper examines the current landscape of AI-driven robotic surgical systems, detailing their benefits, limitations, and future prospects. Initially, AI applications in robotic surgery focused on automating tasks like suturing and tissue dissection to enhance consistency and reduce surgeon workload. Present AI-driven systems incorporate functionalities such as image recognition, motion control, and haptic feedback, allowing real-time analysis of surgical field images and optimizing instrument movements for surgeons. The advantages of AI integration include enhanced precision, reduced surgeon fatigue, and improved safety. However, challenges such as high development costs, reliance on data quality, and ethical concerns about autonomy and liability hinder widespread adoption. Regulatory hurdles and workflow integration also present obstacles. Future directions for AI integration in robotic surgery include enhancing autonomy, personalizing surgical approaches, and refining surgical training through AI-powered simulations and virtual reality. Overall, AI integration holds promise for advancing surgical care, with potential benefits including improved patient outcomes and increased access to specialized expertise. Addressing challenges and promoting responsible adoption are essential for realizing the full potential of AI-driven robotic surgery.

Bile acid modulation by gut microbiota: a bridge to understanding cognitive health.

The gut microbiota plays an important role in regulating the body's physiological system, and more recently its impact on bile acid metabolism and cognitive function has been investigated by many studies. In addition to their conventional function in fat digestion and absorption, bile acids are now considered crucial signaling molecules that control several metabolic processes and immunological responses. For this purpose, the authors conducted comprehensive research using relevant terms in an attempt to understand more about the gut microbiota and its impact on bile acid metabolism and cognitive health. The gut-brain axis refers to the network of routes through which gut bacteria communicate with the brain. Through its capacity to bio-transform primary bile acids into secondary bile acids, the gut microbiota plays a significant role in bile acid metabolism. Bile acids function as signaling molecules and act on the brain through nuclear and membrane-bound receptors, influencing neurotransmitter production, neuroinflammation, and neuroplasticity to modify this communication. Any dysregulation in this axis can result in cognitive dysfunction. The link between gut microbiota, bile acids, and cognitive health cannot be ignored. It is imperative to explore this link further by conducting large-scale trials to improve the cognitive health of patients with multiple comorbidities, especially those involving the gastrointestinal tract and nervous system.

Dynamics and control of two-dimensional discrete-time biological model incorporating weak Allee's effect.

Incorporating a weak Allee effect in a two-dimensional biological model in ℜ2, the study delves into the application of bifurcation theory, including center manifold and Ljapunov-Schmidt reduction, normal form theory, and universal unfolding, to analyze nonlinear stability issues across various engineering domains. The focus lies on the qualitative dynamics of a discrete-time system describing the interaction between prey and predator. Unlike its continuous counterpart, the discrete-time model exhibits heightened chaotic behavior. By exploring a biological Mmdel with linear functional prey response, the research elucidates the local asymptotic properties of equilibria. Additionally, employing bifurcation theory and the center manifold theorem, the analysis reveals that, for all α1 (i.e., intrinsic growth rate of prey), ð1˙ (i.e., parameter that scales the terms yn), and m (i.e., Allee effect constant), the model exhibits boundary fixed points A1 and A2, along with the unique positive fixed point A∗, given that the all parameters are positive. Additionally, stability theory is employed to explore the local dynamic characteristics, along with topological classifications, for the fixed points A1, A2, and A∗, considering the impact of the weak Allee effect on prey dynamics. A flip bifurcation is identified for the boundary fixed point A2, and a Neimark-Sacker bifurcation is observed in a small parameter neighborhood around the unique positive fixed point A∗=(mð1˙-1,α1-1-α1mð1˙-1). Furthermore, it implements two chaos control strategies, namely, state feedback and a hybrid approach. The effectiveness of these methods is demonstrated through numerical simulations, providing concrete illustrations of the theoretical findings. The model incorporates essential elements of population dynamics, considering interactions such as predation, competition, and environmental factors, along with a weak Allee effect influencing the prey population.

Genetic diversity and population structure of Echinococcus multilocularis: An in-silico global analysis.

Objective: Alveolar echinococcosis is caused by Echinococcus multilocularis, a parasite of zoonotic significance with a wide range of intermediate and final hosts, and the parasite survives successfully in diversified conditions. Plentiful studies have been done to study the genetic structure of the population of the parasite and the level of intimate kinship using mitochondrial (mt) DNA. The present study was conducted to investigate the population structure, genetic variation, and phylogenetic relationship of various isolates of E. multiocularis submitted to GenBank worldwide. Sequences of mt genes (mt-cytochrome c oxidase (cox1), mt-NADH dehydrogenase (nad1)) of E. multilocularis were analyzed to achieve the set goals. Materials and Methods: A total of 275 and 124 gene sequences of mt-cox1 and mt-nad1 belonging to E. multilocularis, respectively, were retrieved from the National Center for Biotechnology Information GenBank. The retrieved sequences were subjected to alignment with respective reference sequences using MEGA software. The PopArt software was used to establish median-joining networks, while DnaSp was used to calculate neutrality and diversity indices. MrBayes software was used to investigate the phylogenetic association between haplotypes based on Bayesian phylogeny. Results: Approximately 13 and 20 distinctive haplotypes of nad1 and cox1 genes, respectively, were observed in the present study. In both of the mt genes, diversity indices indicated low haplotype (mt-cox1 = 0.140; mt-nad1 = 0.374) and nucleotide (mt-cox1 = 0.00111; mt-nad1 = 0.00287) diversities. The values of Tajima's D and Fu Fs for a population of both of the genes under study were found to be negative. Conclusion: This study is a maiden attempt to provide insights into the population structure and genetic variation of E. multilocularis on a global scale. However, it is suggested that to better understand the population structure and genetic diversity of E. multilocularis, more geographical locations and amplifications of full-length gene sequences should be considered, which could be helpful in widening the insights into the genetic diversity of E. multilocularis.

A large, locally aggressive giant cell tumour arising from the laryngeal cartilage: A Rare Case Report.

Giant cell tumour is a growth predominantly found in long bones of the body. Giant cell tumour has a rare occurrence in the head and neck. A case of a 31 year old male with no known comorbidities at the ENT Department, Shifa International Hospital, Islamabad presented with anterior neck swelling and hoarseness of voice. Patient was diagnosed as having Giant Cell Tumour of Larynx (GTCL) proven on FNA cytology and post-operative biopsy. GCTL is an uncommon entity with only 45 reported cases in the world.

Phylogenomic analyses and comparative genomic studies of Thermus strains isolated from Tengchong and Tibet Hot Springs, China.

Genus Thermus is the main focus of researcher among the thermophiles. Members of this genus are the inhabitants of both natural and artificial thermal environments. We performed phylogenomic analyses and comparative genomic studies to unravel the genomic diversity among the strains belonging to the genus Thermus in geographically different thermal springs. Sixteen Thermus strains were isolated and sequenced from hot springs, Qucai hot springs in Tibet and Tengchong hot springs in Yunnan, China. 16S rRNA gene based phylogeny and phylogenomic analyses based on concatenated set of 971 Orthologous Protein Families (supermatrix and gene content methods) revealed a mixed distribution of the Thermus strains. Whole genome based phylogenetic analysis showed, all 16 Thermus strains belong to five species; Thermus oshimai (YIM QC-2-109, YIM 1640, YIM 1627, 77359, 77923, 77838), Thermus antranikianii (YIM 73052, 77412, 77311, 71206), Thermus brokianus (YIM 73518, 71318, 72351), Thermus hydrothermalis (YIM 730264 and 77927) and one potential novel species 77420 forming clade with Thermus thalpophilus SYSU G00506T. Although the genomes of different strains of Thermus of same species were highly similar in their metabolic pathways, but subtle differences were found. CRISPR loci were detected through genome-wide screening, which showed that Thermus isolates from two different thermal locations had well developed defense system against viruses and adopt similar strategy for survival. Additionally, comparative genome analysis screened competence loci across all the Thermus genomes which could be helpful to acquire DNA from environment. In the present study it was found that Thermus isolates use two mechanism of incomplete denitrification pathway, some Thermus strains produces nitric oxide while others nitrious oxide (dinitrogen oxide), which show the heterotrophic lifestyle of Thermus genus. All isolated organisms encoded complete pathways for glycolysis, tricarboxylic acid and pentose phosphate. Calvin Benson Bassham cycle genes were identified in genomes of T. oshimai and T. antranikianii strains, while genomes of all T. brokianus strains and organism 77420 were lacking. Arsenic, cadmium and cobalt-zinc-cadmium resistant genes were detected in genomes of all sequenced Thermus strains. Strains 77,420, 77,311, 73,518, 77,412 and 72,351 genomes were found harboring genes for siderophores production. Sox gene clusters were identified in all sequenced genomes, except strain YIM 730264, suggesting a mode of chemolithotrophy. Through the comparative genomic analysis, we also identified 77420 as the genome type species and its validity as novel organism was confirmed by whole genome sequences comparison. Although isolate 77420 had 99.0% 16S rRNA gene sequence similarity with T. thalpophilus SYSU G00506T but based on ANI 95.86% (Jspecies) and digital DDH 68.80% (GGDC) values differentiate it as a potential novel species. Similarly, in the phylogenomic tree, the novel isolate 77,420 forming a separate branch with their closest reference type strain T. thalpophilus SYSU G00506T.

Biocompatible Janus microparticle synthesis in a microfluidic device.

Janus particles are popular in recent years due to their anisotropic physical and chemical properties. Even though there are several established synthesis methods for Janus particles, microfluidics-based methods are convenient and reliable due to low reagent consumption, monodispersity of the resultant particles and efficient control over reaction conditions. In this work a simple droplet-based microfluidic technique is utilized to synthesize magnetically anisotropic TiO2-Fe2O3 Janus microparticles. Two droplets containing reagents for Janus particle were merged by using an asymmetric device such that the resulting droplet contained the constituents within its two hemispheres distinct from each other. The synthesized Janus particles were observed under the optical microscope and the scanning electron microscope. Moreover, a detailed in vitro characterization of these particles was completed, and it was shown that these particles have a potential use for biomedical applications.

Fractional order cancer model infection in human with CD8+ T cells and anti-PD-L1 therapy: simulations and control strategy.

In order to comprehend the dynamics of disease propagation within a society, mathematical formulations are essential. The purpose of this work is to investigate the diagnosis and treatment of lung cancer in persons with weakened immune systems by introducing cytokines ( I L 2 & I L 12 ) and anti-PD-L1 inhibitors. To find the stable position of a recently built system TCD I L 2 I L 12 Z, a qualitative and quantitative analysis are taken under sensitive parameters. Reliable bounded findings are ensured by examining the generated system's boundedness, positivity, uniqueness, and local stability analysis, which are the crucial characteristics of epidemic models. The positive solutions with linear growth are shown to be verified by the global derivative, and the rate of impact across every sub-compartment is determined using Lipschitz criteria. Using Lyapunov functions with first derivative, the system's global stability is examined in order to evaluate the combined effects of cytokines and anti-PD-L1 inhibitors on people with weakened immune systems. Reliability is achieved by employing the Mittag-Leffler kernel in conjunction with a fractal-fractional operator because FFO provide continuous monitoring of lung cancer in multidimensional way. The symptomatic and asymptomatic effects of lung cancer sickness are investigated using simulations in order to validate the relationship between anti-PD-L1 inhibitors, cytokines, and the immune system. Also, identify the actual state of lung cancer control with early diagnosis and therapy by introducing cytokines and anti-PD-L1 inhibitors, which aid in the patients' production of anti-cancer cells. Investigating the transmission of illness and creating control methods based on our validated results will both benefit from this kind of research.

Machine learning in heart failure diagnosis, prediction, and prognosis: review.

Globally, cardiovascular diseases take the lives of over 17 million people each year, mostly through myocardial infarction, or MI, and heart failure (HF). This comprehensive literature review examines various aspects related to the diagnosis, prediction, and prognosis of HF in the context of machine learning (ML). The review covers an array of topics, including the diagnosis of HF with preserved ejection fraction (HFpEF) and the identification of high-risk patients with HF with reduced ejection fraction (HFrEF). The prediction of mortality in different HF populations using different ML approaches is explored, encompassing patients in the ICU, and HFpEF patients using biomarkers and gene expression. The review also delves into the prediction of mortality and hospitalization rates in HF patients with mid-range ejection fraction (HFmrEF) using ML methods. The findings highlight the significance of a multidimensional approach that encompasses clinical evaluation, laboratory assessments, and comprehensive research to improve our understanding and management of HF. Promising predictive models incorporating biomarkers, gene expression, and consideration of epigenetics demonstrate potential in estimating mortality and identifying high-risk HFpEF patients. This literature review serves as a valuable resource for researchers, clinicians, and healthcare professionals seeking a comprehensive and updated understanding of the role of ML diagnosis, prediction, and prognosis of HF across different subtypes and patient populations.

Primary leiomyosarcoma of thyroid with pulmonary metastasis: A diagnostic odyssey.

The presented primary thyroid leiomyosarcoma (TL) case report underscores the importance of recognizing and addressing the diagnostic challenges and management complexities associated with this exceedingly rare malignancy. Given the limited effective therapeutic strategies available, timely intervention, thorough diagnostics, and vigilant follow-up are paramount in managing such intricate tumors. Further research focusing on molecular-based treatment modalities is imperative to improve patient outcomes in cases of primary TL.

Smoking behaviour in post-acute myocardial infarction patients: cross-sectional study.

Introduction: Heart disease remains the leading cause of death in developed countries, and cigarette smoking contributes to a significant proportion of cardiovascular-related deaths. Abstaining from tobacco use is associated with a significant reduction in the risk of recurrent myocardial infarctions. Methodology: In this cross-sectional study, 384 participants post-acute myocardial infarction (MI) were recruited through random sampling to explore the associations between smoking status and intention to quit smoking. Data collection took place over a 6-month period at a tertiary care hospital, Islamabad, Pakistan. Results: The majority of participants were male (59.9%) and fell into the age category of 46-50 years (37.5%). Heavy daily smokers comprised the largest smoking group (41.6%), and non-ST-elevated MI was the most common subtype (40.1%). Intention to quit smoking varied among participants, with the pre-contemplation stage having the highest representation (19.3%), followed by contemplation (25.8%). Notably, a significant proportion of participants expressed no intention to quit smoking (35.4%). Conclusion: Multinomial logistic regression analysis identified current smoking as a significant predictor of intention to quit in the preparation and contemplation stages. Overall, this study underscores the importance of considering smoking behaviour when evaluating the intention to quit smoking post-MI and highlights the need for tailored interventions and support strategies to address smoking cessation in this population. These findings offer valuable insights for the development of effective strategies aimed at reducing persistent smoking following MI and improving patient outcomes.

Changes in Metabolite Profiles of Chinese Soy Sauce at Different Time Durations of Fermentation Studied by 1H-NMR-Based Metabolomics.

Fermentation parameters, especially the duration, are important in imparting a peculiar taste and flavor to soy sauce. The main purpose of this research was to monitor metabolic changes occurring during the various time intervals of the fermentation process. NMR-based metabolomics was used to monitor the compositional changes in soy sauce during fermentation. The 1H-NMR spectra of the soy sauce samples taken from the fermentation tanks at 0 to 8 months were analyzed using 1H-NMR spectroscopy, and the obtained spectra were analyzed by multivariate statistical analysis. The Principal Component Analysis (PCA) and Partial Least Square Discriminate analysis (PLSDA) revealed the separation of samples fermented for various time durations under identical conditions. Key metabolites shown by corresponding loading plots exhibited variations in amino acids (lysine, threonine, isoleucine, etc.), acetate, glucose, fructose, sucrose, ethanol, glycerol, and others. The levels of ethanol in soy sauce increased with longer fermentation durations, which can be influenced by both natural fermentation and the intentional addition of ethanol as a preservative. The study shows that the variation in metabolite can be very efficiently monitored using 1H-NMR-based metabolomics, thus suggestion to optimize the time duration to get the soy sauce product with the desired taste and flavor.

Risk of infection with arboviruses in a healthy population in Pakistan based on seroprevalence.

Infectious diseases caused by arboviruses are a public health concern in Pakistan. However, studies on data prevalence and threats posed by arboviruses are limited. This study investigated the seroprevalence of arboviruses in a healthy population in Pakistan, including severe fever with thrombocytopenia syndrome virus (SFTSV), Crimean-Congo hemorrhagic fever virus (CCHFV), Tamdy virus (TAMV), and Karshi virus (KSIV) based on a newly established luciferase immunoprecipitation system (LIPS) assays, and Zika virus (ZIKV) by enzyme-linked immunosorbent assays (ELISA). Neutralizing activities against these arboviruses were further examined from the antibody positive samples. The results showed that the seroprevalence of SFTSV, CCHFV, TAMV, KSIV, and ZIKV was 17.37%, 7.58%, 4.41%, 1.10%, and 6.48%, respectively, and neutralizing to SFTSV (1.79%), CCHFV (2.62%), and ZIKV (0.69%) were identified, as well as to the SFTSV-related Guertu virus (GTV, 0.83%). Risk factors associated with the incidence of exposure and levels of antibody response were analyzed. Moreover, co-exposure to different arboviruses was demonstrated, as thirty-seven individuals were having antibodies against multiple viruses and thirteen showed neutralizing activity. Males, individuals aged ≤40 years, and outdoor workers had a high risk of exposure to arboviruses. All these results reveal the substantial risks of infection with arboviruses in Pakistan, and indicate the threat from co-exposure to multiple arboviruses. The findings raise the need for further epidemiologic investigation in expanded regions and populations and the necessity to improve health surveillance in Pakistan.

Self-Powered Humidity Sensor Driven by Triboelectric Nanogenerator Composed of Bio-Wasted Peanut Skin Powder.

The increasing number of IoT devices has led to more electronic waste production, which harms the environment and human health. Self-powered sensor systems are a solution, but they often use toxic materials. We propose using biocompatible peanut skin as the active material for a self-powered humidity sensor (PSP-SPHS) through integration with a peanut-skin-based triboelectric nanogenerator (PSP-TENG). The PSP-TENG was characterized electrically and showed promising results, including an open circuit voltage (162 V), short circuit current (0.2 µA), and instantaneous power (2.2 mW) at a loading resistance of 20 MΩ. Peanut skin is a great choice for the sensor due to its porous surface, large surface area, eco-friendliness, and affordability. PSP-TENG was further used as a power source for the PSP-humidity sensor. PSP-SPHS worked as a humidity-dependent resistor, whose resistance decreased with increasing relative humidity (%RH), which further resulted in decreasing voltage across the humidity sensor. This proposed PSP-SPHS exhibited a good sensitivity (0.8 V/RH%), fast response/recovery time (4/10 s), along with excellent stability and repeatability, making it a potential candidate for self-powered humidity sensor technology.