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Abstract Magnetic resonance (MR) images are commonly used to diagnose prolapsed lumbar intervertebral disc (PLID). However, for a computer-aided diagnostic (CAD) system, distinguishing between pathological abnormalities of PLID in MR images is a challenging and intricate task. Here, we propose a comprehensive model for the automatic detection and cropping of regions of interest (ROI) from sagittal MR images using the YOLOv8 framework to solve this challenge. We also propose weighted average ensemble (WAE) classification and segmentation models for the classification and the segmentation, respectively. YOLOv8 has good detection accuracy for both the lumbar region (mAP50 = 99.50%) and the vertebral disc (mAP50 = 99.40%). The use of ROI approaches enhances the accuracy of individual models. Specifically, the classification accuracy of the WAE classification model reaches 97.64%, while the segmentation model achieves a Dice value of 95.72%. This automatic technique would improve the diagnostic process by offering enhanced accuracy and efficiency in the assessment of PLID.

The land use transition plays an important role for terrestrial environmental services, which had a mixed impact of positive and negative on the groundwater and terrestrial water resource. The health of ecological systems and groundwater depends on the mapping and management of land use. The Ganga basin is one of the most densely populated and agriculture-intensive river systems in the South Asia and the world. The multi-temporal spatial database includes land use (ESA-CCI), satellite-based gravity anomaly (GRACE/GRACE-FO), and well log (CGWB) adopted in this study for assessment of the impact of land use transition on groundwater depth, groundwater drought, and terrestrial water storage. The methodology includes the computation of land use transition, trend magnitude by Sen's slope, Innovative Trend Analysis (ITA) for graphical visualization, clustering techniques employ to identify pattern & structure, and finally space-time transformation was assessed based on multi-dimensional scaling using Alternating Least Squares Scaling (ALSCAL). The land use transition over two decades shows an increase in forest (2.23%), wetland (2.2%), settlement (208.4%), bare area (3.18%), water (5.18%), and a decrease in agriculture (-1.16%), grassland (-4.5%), & vegetation (-2.8%). The non-parametric climatological trend of groundwater depth, drought, and terrestrial water loss was maximally observed during the post-monsoon season in the Ganga basin. The seasonal climatological trend statistics shows that, the upper Ganga and northern (left) of the Ganga basin shows an alarming rate of groundwater depletion, with increased in the severity of groundwater drought in near future with the loss in terrestrial water storage. The ITA shows the monotonic decreasing trend depicting loss of groundwater and terrestrial water resources. Bi-dimensional regression, ALSCAL shows that the model is efficient based on the input data having stress value and RSQ (proportion of variance) of 0.09 and 0.97 with excellent linear fit. The impact assessment of land use transition was obtained in low dimensional space showing that the conversion from sparse vegetation, agriculture, grassland, wetland and forest to settlement has the maximum impact on groundwater and TWSA loss, although the persistent settlement area is also responsible. The results are extremely useful for the policymakers, scientists, concern Govt. section, and local communities must work together to manage groundwater sustainably. Water resource management can also help to lessen the effects of climate change on groundwater and terrestrial water loss by focusing on the environmental, economic, social, and institutional dimensions of UN-SDG., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Reformulating the physical processes associated with the evolution of different ailments in accordance with globally shared objectives is crucial for deeper comprehension. This study aims to investigate the mechanism by which the HB virus induces harmful inflammation of the liver, with a focus on early detection and therapy using corticosteroids or chemotherapy. Based on the developed hypothesis, a new mathematical model has been created for this purpose. The recently developed system for HBV is S E I 1 I 2 R , which is examined both quantitatively and qualitatively to determine its actual effect on stability. Reliable conclusions are ensured by examining the system's boundedness, positivity, existence, uniqueness, and conducting local and global stability analysis-all crucial components of epidemic models. Global stability is tested using Lyapunov first derivative functions to assess the overall impact of asymptomatic persons and chemotherapy treatment. Additionally, the Lipschitz condition is used to confirm the unique solutions for the newly built HBV model using methods from fixed point theory, thus meeting the requirements for uniqueness and existence. Since the population must maintain this property, positivity is confirmed using global derivatives and Lipschitz criteria to calculate the rate of change in each sub-compartment. Applying the Mittag-Leffler kernel with a fractal-fractional operator to continuously monitor the HBV virus for liver cirrhosis infection yields dependable results. Furthermore, the current situation regarding the HBV outbreak pertaining to liver cirrhosis infection, along with the control measures implemented following early diagnosis through asymptomatic measures and chemotherapy treatment under constant observation, are established to prevent chronic stage infections. Simulations have been used to study the true behavior and impact of HBV in asymptomatic persons receiving chemotherapy for liver cirrhosis infection in the community. This research is essential for understanding the spread of viruses and developing control strategies based on our validated findings to mitigate the risk factors associated with liver cirrhosis., Competing Interests: Ethical Approval Not applicable. Competing interests The authors declare no conflict of interest., (© 2024. The Author(s).)

Solitary wave solutions are of great interest to bio-mathematicians and other scientists because they provide a basic description of nonlinear phenomena with many practical applications. They provide a strong foundation for the development of novel biological and medical models and therapies because of their remarkable behavior and persistence. They have the potential to improve our comprehension of intricate biological systems and help us create novel therapeutic approaches, which is something that researchers are actively investigating. In this study, solitary wave solutions of the nonlinear Murray equation will be discovered using a modified extended direct algebraic method. These solutions represent a uniform variation in blood vessel shape and diameter that can be used to stimulate blood flow in patients with cardiovascular disease. These solutions are newly in the literature, and give researchers an important tool for grasping complex biological systems. To see how the solitary wave solutions behave, graphs are displayed using Matlab., (© 2024. The Author(s).)

Salmonella Typhi, a bacteria, is responsible for typhoid fever, a potentially dangerous infection. Typhoid fever affects a large number of people each year, estimated to be between 11 and 20 million, resulting in a high mortality rate of 128,000 to 161,000 deaths. This research investigates a robust numerical analytic strategy for typhoid fever that takes infection protection into consideration and incorporates fuzzy parameters. The use of fuzzy parameters acknowledges the variation in parameter values among individuals in the population, which leads to uncertainties. Because of their diverse histories, different age groups within this community may exhibit distinct customs, habits, and levels of resistance. Fuzzy theory appears as the most appropriate instrument for dealing with these uncertainty. With this in mind, a model of typhoid fever featuring fuzzy parameters is thoroughly examined. Two numerical techniques are developed within a fuzzy framework to address this model. We employ the non-standard finite difference (NSFD) scheme, which ensures the preservation of essential properties like dynamic consistency and positivity. Additionally, we conduct numerical simulations to illustrate the practical applicability of the developed technique. In contrast to many classical methods commonly found in the literature, the proposed approach exhibits unconditional convergence, solidifying its status as a dependable tool for investigating the dynamics of typhoid disease., (© 2023. The Author(s).)

Elucidation of the genetic basis of drought tolerance is vital for genomics-assisted breeding of drought tolerant crop varieties. Here, we used genotyping-by-sequencing (GBS) to identify single nucleotide polymorphisms (SNPs) in recombinant inbred lines (RILs) derived from a cross between a drought tolerant chickpea variety, Pusa 362 and a drought sensitive variety, SBD 377. The GBS identified a total of 35,502 SNPs and subsequent filtering of these resulted in 3237 high-quality SNPs included in the eight linkage groups. Fifty-one percent of these SNPs were located in the genic regions distributed throughout the genome. The high density linkage map has total map length of 1069 cm with an average marker interval of 0.33 cm. The linkage map was used to identify 9 robust and consistent QTLs for four drought related traits viz. membrane stability index, relative water content, seed weight and yield under drought, with percent variance explained within the range of 6.29%-90.68% and LOD scores of 2.64 to 6.38, which were located on five of the eight linkage groups. A genomic region on LG 7 harbors quantitative trait loci (QTLs) explaining > 90% phenotypic variance for membrane stability index, and > 10% PVE for yield. This study also provides the first report of major QTLs for physiological traits such as membrane stability index and relative water content for drought stress in chickpea. A total of 369 putative candidate genes were identified in the 6.6 Mb genomic region spanning these QTLs. In-silico expression profiling based on the available transcriptome data revealed that 326 of these genes were differentially expressed under drought stress. KEGG analysis resulted in reduction of candidate genes from 369 to 99, revealing enrichment in various signaling pathways. Haplotype analysis confirmed 5 QTLs among the initially identified 9 QTLs. Two QTLs, qRWC1.1 and qYLD7.1, were chosen based on high SNP density. Candidate gene-based analysis revealed distinct haplotypes in qYLD7.1 associated with significant phenotypic differences, potentially linked to pathways for secondary metabolite biosynthesis. These identified candidate genes bolster defenses through flavonoids and phenylalanine-derived compounds, aiding UV protection, pathogen resistance, and plant structure.The study provides novel genomic regions and candidate genes which can be utilized in genomics-assisted breeding of superior drought tolerant chickpea cultivars., (© 2023. Springer Nature Limited.)

Coastal hazard vulnerability assessment has been centered around the multi-variate analysis of geo-physical and hydroclimate data. The representation of coupled socio-environmental factors has often been ignored in vulnerability assessment. This study develops an integrated socio-environmental Coastal Vulnerability Index (CVI), which simultaneously combines information from five vulnerability groups: biophysical, hydroclimate, socio-economic, ecological, and shoreline. Using the Multi-Criteria Decision Making (MCDM) approach, two CVI (CVI-50 and CVI-90) have been developed based on average and extreme conditions of the factors. Each CVI is then compared to a data-driven CVI, which is formed based on Probabilistic Principal Component Analysis (PPCA). Both MCDM and PPCA have been tied into geospatial analysis to assess the natural hazard vulnerability of six coastal counties in South Carolina. Despite traditional MCDM-based vulnerability assessments, where the final index is estimated based on subjective weighting methods or equal weights, this study employs an entropy weighting technique to reduce the individuals' biases in weight assignment. Considering the multivariate nature of the coastal vulnerability, the validation results show both CVI-90 and PPCA preserve the vulnerability results from biophysical and socio-economic factors reasonably, while the CVI-50 methods underestimate the biophysical vulnerability of coastal hazards. Sensitivity analysis of CVIs shows that Charleston County is more sensitive to socio-economic factors, whereas in Horry County the physical factors contribute to a higher degree of vulnerability. Findings from this study suggest that the PPCA technique facilitates the high-dimensional vulnerability assessment, while the MCDM approach accounts more for decision-makers' opinions., (© 2022. The Author(s).)

Dyslipidemia, a major contributor to cardiovascular diseases, is rapidly increasing in Asian countries including Bangladesh. In addition to the cardiovascular system, abnormal lipid levels are also known to cause complications in renal and hepatic systems. The data regarding dyslipidemia and its relationship with liver enzymes are scarce for the Bangladeshi population. Therefore, this study was conducted to estimate the prevalence of dyslipidemia and determine the relationship between lipid profile and liver enzymes in Bangladeshi adults. A total of 405 participants (318 males and 87 females) were enrolled in the study. Serum levels of TG, TC, LDL, HDL and liver enzymes including ALT, AST, GGT and ALP were analyzed using standard methods. Dyslipidemia and liver function tests abnormalities were defined according to the international standard guidelines. The association between elevated lipid profile markers and liver enzyme abnormalities was assessed by logistic regression analysis. Overall, the prevalence of elevated TG, TC, LDL and low HDL were 30.9%, 23.7%, 26.2% and 78.8%, respectively. On the other hand, the prevalence of elevated liver enzymes ALT, AST, GGT and ALP were 18.8%, 21.6%, 12.9% and 21.9%, respectively. Dyslipidemia and liver enzyme abnormalities were higher in diabetic and hypertensive participants than in the healthy participants. About 61% of participants with dyslipidemia had at least one or more elevated liver enzymes. In regression analysis, an independent association was observed between serum GGT and all lipid components. In conclusion, a high prevalence of dyslipidemia and liver enzyme abnormalities were observed among the study participants. Of the four liver enzymes, the serum levels of GGT showed an independent association with all lipid components. Moreover, this study indicates that subjects with dyslipidemia often have a higher chance of having liver diseases than subjects with no dyslipidemia. However, large-scale prospective studies are needed to understand the underlying mechanisms of lipid-induced hepatic dysfunction in the Bangladeshi population., (© 2022. The Author(s).)

Our study aimed to describe the root and canal morphology of mandibular second molars in Emirati population and to study the prevalence and types of morphological change in C-shaped canal configuration along the root length in an effort to describe C-shaped molars as a unit. Cone beam computed tomography (CBCT) scans of Emirati patients were analyzed in multiple plans and root and canal configuration of mandibular second molars were evaluated. Moreover, specific types of morphological change in C-shaped canal configuration along root length were studied and reconstructed using 3D reconstruction software. A total of 508 mandibular second molars were evaluated. Among the non-C-shaped mandibular second molars, two separate roots were the most prevalent root morphology (78.3%). The mesial root's most common root canal configuration was Vertucci Type II (46.5%), and in the distal root, Vertucci Type I (90.5%). The prevalence of C-shaped mandibular second molars was 17.9% and was significantly prevalent (P < 0.001) in females. Specific types of morphological change in C-shaped molars along the root length were observed and described for the first time, in which the most common types of morphological change were C1-C2-C3d (18%), C1-C3c-C3d (15.4%), C4-C3c-C3d (7.7%), and C3c-C3c-C3d (7.7%). This study showed wide variations in the root and canal morphology in mandibular second molars in Emirati population with a relatively high prevalence of C-shaped canal configuration (17.9%). Moreover, specific types of morphological change in C-shaped configuration were detected and described for the first time in this population., (© 2021. The Author(s).)

Serum uric acid (SUA) level has been suggested to be associated with cardiovascular disease, diabetes and metabolic syndrome. However, little is known about the relationship between SUA and liver enzymes activity in the general population. The present study aimed to assess the relationship between SUA and serum liver enzymes in an adult population in Bangladesh. In this cross-sectional study, a total of 410 blood samples were collected from apparently healthy adults aged > 18 years. SUA, liver enzymes, lipid profile and other biochemical markers were measured in the collected samples by using standard methods. Multinomial logistic regression model was used to assess the relationship between SUA and elevated levels of liver enzymes among the participants. Overall, the prevalence of hyperuricemia was 30.1% with 32.2% in male and 18.6% in female participants. About 33% of the participants had at least one or more elevated levels of liver enzymes. The mean level of SUA was significantly higher in males (389.3 ± 96.9 µmol/L) than in the female (290.4 ± 89.8 µmol/L) subjects (p < 0.001). There was a significant difference in the mean levels of serum ALT and GGT between the male (34.5 ± 16.0 U/L and 26.7 ± 19.5 U/L, respectively) and female (25.0 ± 13.0 U/L and 19.5 ± 13.2 U/L, respectively) participants (p < 0.001 and p < 0.01, respectively). An increasing trend was observed in the mean levels of serum ALT and GGT across the SUA quartile groups (p < 0.001 and p < 0.01, respectively). SUA showed a positive and significant correlation with serum ALT (p < 0.001) and GGT (p < 0.01). In further statistical analysis after adjustment for potential confounders, SUA showed an independent and significant association with serum ALT and GGT in all regression models. In conclusion, SUA was strongly associated with serum levels of ALT and GGT after adjustment for potential confounders. More prospective studies are needed to clarify the complex relationship between SUA and liver enzymes in the general population., (© 2021. The Author(s).)

Obesity is a global health concern because of its increasing trend both in developed and developing countries. A limited number of studies have evaluated the association of liver enzymes with both general and abdominal obesity in the general population; data for the Bangladeshi population are not available yet. This study aimed to assess the relationship of serum liver enzymes activity with both general and abdominal obesity in Bangladeshi adults. In total, 540 blood samples were obtained from the participants (388 males and 152 females) and analyzed for serum levels of ALT, AST, GGT, and ALP using standard methods. General obesity was defined as body mass index (BMI) ≥ 27.5 kg/m 2 and abdominal obesity was defined as waist circumference (WC) ≥ 90 cm in males and ≥ 80 cm in females. The relationship between liver enzymes and obesity was evaluated by multivariate logistic regression models. Overall, 58% of participants in the general obesity group and 55% of the participants in the abdominal obesity group had at least one or more elevated levels of liver enzymes. The prevalence of elevated liver enzymes was significantly higher in the obesity group compared to the normal BMI and WC groups (p < 0.05 for all cases). The mean level of serum ALT, AST and GGT were significantly higher in the obesity group than the normal BMI group (p < 0.05). In the WC groups, mean AST and GGT were significantly higher in the obesity group compared to the normal group (p < 0.05). In regression analysis, serum levels of ALT showed an independent and significant association with general obesity, whereas, serum GGT showed a significant association with both general and abdominal obesity. In conclusion, a high prevalence of elevated liver enzymes was observed among participants included in the present study. Of the four enzymes, serum GGT was independently associated with both general and abdominal obesity. Further studies are required to understand the complex relationship between liver enzymes and obesity in the general population.

A novel, highly sensitive and selective safrole sensor has been developed using quartz crystal microbalance (QCM) coated with polyvinyl acetate (PVAc) nanofibers. The nanofibers were collected on the QCM sensing surface using an electrospinning method with an average diameter ranging from 612 nm to 698 nm and relatively high Q-factors (rigid coating). Scanning electron microscopy (SEM) and atomic force microscopy (AFM) were used to analyze the PVAc nanofiber surface morphology, confirming its high surface area and roughness, which are beneficial in improving the sensor sensitivity compared to its thin-film counterpart. The as-spun PVAc nanofiber sensor could demonstrate a safrole limit of detection (LOD) of down to 0.7 ppm with a response time of 171 s and a sensitivity of 1.866 Hz/ppm. It also showed good reproducibility, rapid response time, and excellent recovery. Moreover, cross-interference of the QCM sensor response to non-target gases was investigated, yielding very low cross-sensitivity and high selectivity of the safrole sensor. Owing to its high robustness and low fabrication cost, this proposed sensing device is expected to be a promising alternative to classical instrumental analytical methods for monitoring safrole-based drug precursors.