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One of the most common and challenging medical conditions to deal with in old-aged people is the occurrence of knee osteoarthritis (KOA). Manual diagnosis of this disease involves observing X-ray images of the knee area and classifying it under five grades using the Kellgren–Lawrence (KL) system. This requires the physician’s expertise, suitable experience, and a lot of time, and even after that the diagnosis can be prone to errors. Therefore, researchers in the ML/DL domain have employed the capabilities of deep neural network (DNN) models to identify and classify KOA images in an automated, faster, and accurate manner. To this end, we propose the application of six pretrained DNN models, namely, VGG16, VGG19, ResNet101, MobileNetV2, InceptionResNetV2, and DenseNet121 for KOA diagnosis using images obtained from the Osteoarthritis Initiative (OAI) dataset. More specifically, we perform two types of classification, namely, a binary classification, which detects the presence or absence of KOA and secondly, classifying the severity of KOA in a three-class classification. For a comparative analysis, we experiment on three datasets (Dataset I, Dataset II, and Dataset III) with five, two, and three classes of KOA images, respectively. We achieved maximum classification accuracies of 69%, 83%, and 89%, respectively, with the ResNet101 DNN model. Our results show an improved performance from the existing work in the literature.

Depression is the most common debilitating psychiatric disease, the pathological mechanisms of which are associated with multiple aspects of neural function. While recent evidence has consistently suggested that a suboptimal vitamin D status is frequently observed in patients with depression, the results concerning whether vitamin D insufficiency is a causal factor of depression or is secondary to depressive behavior are conflicting; additionally, the lack of consistency of the method of vitamin D determination between labs has further worsened this confusion. Herein, we reviewed the neuroactivities of vitamin D that may be associated with depression and the current studies and clinical investigations to provide a full overview on the use of vitamin D in the treatment and prevention of depression.

The present study was performed to evaluate the effects of seed priming. This was done by soaking the seeds of two rapeseed cultivars, namely, ZY15 (tolerant to low temperature and drought) and HY49 (sensitive to low temperature and drought), for 12 h in varying solutions: distilled water, 138 mg/L salicylic acid (SA), 300 mg/L gibberellic acid (GA), 89.4 mg/L sodium nitroprusside (SNP), 3000 mg/L calcium chloride (CaCl 2 ), and 30 mg/L abscisic acid (ABA). Primed and non-primed seeds were left to germinate at 15°C and -0.15 MPa (T 15 W 15 ) and at 25°C and 0 MPa (T 25 W 0 ), respectively. The results showed that SA, GA, SNP, CaCl 2 , and ABA significantly improved the germination potential (GP), germination rate (GR), germination index (GI), stem fresh weight (SFW), stem dry weight (SDW), root length (RL), stem length (SL), and seed vigor index (SVI) under T 15 W 15 . For ZY15 seeds under T 25 W 0 , GA, SNP, CaCl 2 , and ABA priming reduced the average germination time (96% after 5 days) compared to that of the control (88% after 5 days). For ZY15 seeds under T 15 W 15 , SA, SNP, CaCl 2 , and ABA priming, with respect to the control and water-treated groups, shortened the average germination time (92% after 5 days) compared to that of the control (80% after 5 days). For HY49 seeds under T 25 W 0 , GA, SNP, CaCl 2 , and ABA priming reduced the average germination time (92% after 5 days) compared to that of the control (85% after 5 days). Similarly, for HY49 seeds under T 15 W 15 , GA priming shortened the average germination time (89% after 5 days) compared to that of the control (83% after 5 days). These priming agents increased the net photosynthesis, stomatal conductivity, and transpiration rate of rape seedlings under conditions of low temperature and drought stress, while also decreasing intercellular carbon dioxide (CO 2 ) concentrations. Additionally, SA, GA, SNP, CaCl 2 , and ABA increased superoxide dismutase concentrations (SOD) and ascorbic peroxidase (APX) activities of rape seedlings under stress conditions, while decreasing catalase (CAT) and peroxidase (POD) activities in ZY15 seedlings. In HY49, which is sensitive to low temperature and drought, all priming solutions, except for SNP, led to an increase in SOD activity levels and a decrease in CAT activity levels. Overall, SA, GA, SNP, and CaCl 2 increased the concentrations of indoleacetic acid (IAA), GA, ABA, and cytokinin (CTK) in seedlings under stress conditions. Moreover, compared to SA, CaCl 2 , and ABA, GA (300 mg/L) and SNP (300 mol/L) showed improved priming effects for ZY15 and HY49 under stress conditions.

Background The rapid advancement of artificial intelligence (AI) has revolutionized both medical education and healthcare by delivering innovative tools that enhance learning and improve overall outcomes. The study aimed to assess students’ perceptions regarding the credibility and effectiveness of AI as a learning tool and to explore the dynamics of integrating AI in medical education. Methodology A cross-sectional study was carried out across medical colleges in Pakistan. A 26-question survey was developed using Google Forms from previously validated studies. The survey assessed demographics of participants, basic understanding of AI, AI as a learning tool in medical education and socio-ethical impacts of the use of AI. The data was analyzed using SPSS (v 26.0) to derive descriptive and inferential statistics. Result A total of 702 medical students aged 18 to 26 years (mean age 20.50 ± 1.6 years) participated in the study. The findings revealed a generally favorable attitude towards AI among medical students (80.3%), with the majority considering it an effective (60.8%) and credible (58.4%) learning tool in medical education. Students agreed that AI learning optimized their study time (60.3%) and provided up-to-date medical information (63.1%). Notably, 65.7% of students found AI more efficient in helping them grasp medical concepts compared to traditional tools like books and lectures, while 66.8% reported receiving more accurate answers to their medical inquiries through AI. The study highlighted that medical students view traditional tools as becoming increasingly outdated (59%), emphasizing the importance of integrating AI into medical education and creating dedicated AI tools (80%) for the medical education. Conclusion This study demonstrated that AI is an effective and credible tool in medical education, offering personalized learning experiences and improved educational outcomes. AI tools are helping students learn medical concepts by cutting down on study-time, providing accurate answers, and ultimately improving study outcomes. We recommend developing dedicated AI tools for medical education and their formal integration into medical curricula, along with appropriate regulatory oversight to ensure AI can enhance human abilities rather than acting as a replacement for humans.

Background Seed dormancy is a prevailing condition in which seeds are unable to germinate, even under favorable environmental conditions. Harvested Brassica oleracea (Chinese cabbage) seeds are dormant and normally germinate (poorly) at 21 °C. This study investigated the connections between ethylene, nitric oxide (NO), and karrikin 1 (KAR1) in the dormancy release of secondary dormant Brassica oleracea seeds. Results NO and KAR1 were found to induce seed germination, and stimulated the production of ethylene and 1-aminocyclopropane-1-carboxylic acid (ACC), and both ethylene biosynthesis enzyme ACC oxidase (ACO) [1] and ACC synthase (ACS) [2]. In the presence of NO and KAR1, ACS and ACO activity reached maximum levels after 36 and 48 h, respectively. The inhibitor of ethylene 2,5-norbornadiene (NBD) had an adverse effect on Brassica oleracea seed germination (inhibiting nearly 50% of germination) in the presence of NO and KAR1. The benefits from NO and KAR1 in the germination of secondary dormant Brassica oleracea seeds were also associated with a marked increase in reactive oxygen species (ROS) (H 2 O 2 and O 2 ˙ˉ) and antioxidant enzyme activity at early germination stages. Catalase (CAT) and glutathione reductase (GR) activity increased 2 d and 4 d, respectively, after treatment, while no significant changes were observed in superoxide dismutase (SOD) activity under NO and KAR1 applications. An increase in H 2 O 2 and O 2 ˙ˉ levels were observed during the entire incubation period, which increasing ethylene production in the presence of NO and KAR1. Abscisic acid (ABA) contents decreased and glutathione reductase (GA) contents increased in the presence of NO and KAR1. Gene expression studies were carried out with seven ethylene biosynthesis ACC synthases (ACS) genes, two ethylene receptors (ETR) genes and one ACO gene. Our results provide more evidence for the involvement of ethylene in inducing seed germination in the presence of NO and KAR1. Three out of seven ethylene biosynthesis genes ( BOACS7, BOACS9 and BOACS11 ), two ethylene receptors ( BOETR1 and BOETR2 ) and one ACO gene ( BOACO1 ) were up-regulated in the presence of NO and KAR1. Conclusion Consequently, ACS activity, ACO activity and the expression of different ethylene related genes increased, modified the ROS level, antioxidant enzyme activity, and ethylene biosynthesis pathway and successfully removed (nearly 98%) of the seed dormancy of secondary dormant Brassica olereace seeds after 7 days of NO and KAR1 application.

PurposeTechnology parks (TPs) are used as a tool to improve economic outlook of the region through innovation generation. This study aims to evaluate the perception of tenants of TPs to determine the gap in the expectation and identify types of firms preferring to locate in a TP.Design/methodology/approachThis is the first study in Pakistan to collect data about perceived benefits of TPs in Pakistan from the decision-makers of 110 tenant firms. The cluster analysis and lift ratios are used to draw statistical inferences.FindingsThe firms can be classified into three clusters – commercial-orientation firms, science and technology-oriented firms and young tech firms – with distinct needs for survival and growth in a TP. Moreover, TPs should not just be treated as property projects for providing support services, also knowledge sharing, training and development opportunities and proximity to hubs of knowledge and markets is vital to attract a variety of industry.Originality/valueAcademia and policymakers have been equally interested in the potential impacts of these innovation hubs. However, there have been lack of empirical evidence on how and what to offer the incumbents of these TPs. The government of Pakistan is trying to build more TPs for promoting business activities under CPEC. Therefore, it is extremely important to determine the needs of tenants of TPs for successful utilization of huge amount of public money to be invested in TPs.

Oil refineries depend greatly on the estimation of crude oil properties in order to understand the oil’s behaviour and the product fractions expected from the refining process. In yield estimation, the crude oil source and variant can cause variability in prediction and lead to the need for repeatable analysis. The necessity for fast, accurate, and high-generalization yield estimation initiates the framework of this review. This paper aims to comprehensively review the available techniques for estimating the yield of petroleum products in the petroleum refining industry. The review provides a brief overview of petroleum refining processes and high-value products, followed by a description of the traditional method, which utilizes laboratory analysis to offer detailed findings, but requires a tedious methodology. The improvement of yield estimation leads to process simulation, modelling, and machine learning, enabling a fast response and better prediction with higher accuracy. Thorough case studies related to simulation software, models, and algorithms are presented to discover the process and model development, applications, advantages, and drawbacks. Enhancing petroleum product yield estimation provides reliable techniques for oil refiners that enable them to achieve optimized production aligned with sustainability and modernization goals.

The genetic risk for prostate cancer has been governed by a few rare variants with high penetrance and over 150 commonly occurring variants with lower impact on risk; however, most of these variants have been identified in studies containing exclusively European individuals. People of non-European ancestries make up less than 15% of prostate cancer GWAS subjects. Across the globe, incidence of prostate cancer varies with population due to environmental and genetic factors. The discrepancy between disease incidence and representation in genetics highlights the need for more studies of the genetic risk for prostate cancer across diverse populations. To better understand the genetic risk for prostate cancer across diverse populations, we performed PrediXcan and GWAS in a case-control study of 4,769 self-identified African American (2,463 cases and 2,306 controls), 2,199 Japanese American (1,106 cases and 1,093 controls), and 2,147 Latin American (1,081 cases and 1,066 controls) individuals from the Multiethnic Genome-wide Scan of Prostate Cancer. We used prediction models from 46 tissues in GTEx version 8 and five models from monocyte transcriptomes in the Multi-Ethnic Study of Atherosclerosis. Across the three populations, we predicted 19 gene-tissue pairs, including five unique genes, to be significantly (lfsr < 0.05) associated with prostate cancer. One of these genes, NKX3-1, replicated in a larger European study. At the SNP level, 110 SNPs met genome-wide significance in the African American study while 123 SNPs met significance in the Japanese American study. Fine mapping revealed three significant independent loci in the African American study and two significant independent loci in the Japanese American study. These identified loci confirm findings from previous GWAS of prostate cancer in diverse populations while PrediXcan-identified genes suggest potential new directions for prostate cancer research in populations across the globe.

Background Diabetes mellitus (DM) affects hundreds of millions of people worldwide. Genetic research plays a crucial role in managing diabetes by providing valuable insights into genetic predispositions, facilitating early diagnosis, and enabling personalized treatment strategies. Identification of important genetic markers has paved the way for the creation of targeted therapies, enhancing treatment outcomes and promoting preventive care for both type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM). The aim of this study is to explore the role of different genes in the development of DM and its related complications. Methodology A comprehensive literature search was conducted from October 27 to November 14, 2024, to enlist articles related to genes involved in development of DM and its complications in search engines including PubMed, Medline, Google Scholar, and Scopus. We included original articles, case–control studies, cohort studies, review articles, systematic review, and meta-analysis published between January 1, 2014, and November 14, 2024 in our study. Results In T1DM; research has historically concentrated on the role of HLA class II genes. However, recent studies have brought attention to the role of HLA class I genes in the disease’s development, suggesting a broader role of genetics than previously understood. CTLA4 , IL2RA , and PTPN22 , genes were also significantly linked to T1DM. In T2DM; TCF7L2 was found to be the most potent gene for its development among others genes such as LCAT, APOE, FTO . For gestational diabetes mellitus (GDM), MTNR1B, CDKAL1, and IRS1 genes played an important role. Conclusion Genetics played an important role in the understanding of DM. Researchers have identified new genetic loci that can serve as diagnostic markers for DM and its associated compilations such as diabetic kidney disease (DKD), diabetic neuropathy (DN), diabetic retinopathy (DR) and cardiovascular diseases (CVDs). TCF7L2 and HLA class II are the strongest risk factors for T2DM and T1DM, respectively. Understanding the genetics of DM and its complications is essential for improving early detection, enhancing treatment outcomes, and developing targeted therapies for DM patients.

Background Hepatitis B (HB) and Hepatitis C (HC) viral infections, with 328 million cases globally, represent a significant disease burden. Currently, Pakistan has 3.88 million HB and 9.31 million HC cases. High-risk populations like refugees are disproportionately affected by these infections. The objectives of this study were to determine the seroprevalence of hepatitis B surface antigen (HBsAg) and hepatitis C virus antibody (anti-HCV) among Kashmiri refugees in Muzaffarabad, Pakistan, and to identify the key demographic and educational risk factors associated with the seroprevalence in this population. Methods A cross-sectional study was conducted across eight refugee camps in the Muzaffarabad division, Pakistan. A six-membered team visited each camp to collect blood samples through venipuncture. The seroprevalence of HBsAg and anti-HCV was determined using rapid immunochromatographic test (ICT) kits . Results A total of 550 sera samples were collected from the refugee population in Muzaffarabad. The overall seroprevalence was 5.82% (32/550) for HBsAg and 4.73% (26/550) for anti-HCV. A higher seroprevalence of HBsAg and anti-HCV was recorded among females 6.12% (15/245), and 6.53% (16/245), respectively, compared to males 5.75% (17/305), and 3.28% (10/305), respectively. A marked increase in seroprevalence of HBsAg and anti-HCV was noted with an increase in age: 1–10 (2.44%) and (2.44%), 41–50 (8.20%) and (6.56%), and 51–60 (8.93%) and (8.93%), respectively. Chi-square test revealed a statistically significant association between age and seroprevalence of HBsAg χ² (degrees of freedom (df):6, N  = 550) = 27.22, p  = 0.000, and HC χ² (df:6, N  = 550) = 15.23, p  = 0.019.The level of education impacted the seroprevalence of HBsAg and anti-HCV, resulting in a higher seroprevalence of HBsAg (6.9%) and anti-HCV (5.4%) among uneducated individuals compared to educated individuals (4.71%) and (3.99%), respectively. Conclusion The seroprevalence of HBsAg and anti-HCV is high among the refugee population of Muzaffarabad, Pakistan. There is a need for the implementation of a robust vaccination program for HB as well as the establishing a hepatitis micro-elimination program among the Kashmiri refugee population of Muzaffarabad, Pakistan.