bluuebunny/crossref_metadata_2025_split huggingface dataset:
Partitioning of dense RBC suspensions in single microfluidic bifurcations: role of cell deformability and bifurcation angle
Authors: Stathoulopoulos Antonios , Passos Andreas , Kaliviotis Efstathios , Balabani Stavroula 
Published: January 2024

AbstractRed blood cells (RBCs) are a key determinant of human physiology and their behaviour becomes extremely heterogeneous as they navigate in narrow, bifurcating vessels in the microvasculature, affecting local haemodynamics. This is due to partitioning in bifurcations which is dependent on the biomechanical properties of RBCs, especially deformability. We examine the effect of deformability on the haematocrit distributions of dense RBC suspensions flowing in a single, asymmetric Y-shaped bifurcation, experimentally. Human RBC suspensions (healthy and artificially hardened) at 20% haematocrit (Ht) were perfused through the microchannels at different flow ratios between the outlet branches, and negligible inertia, and imaged to infer cell distributions. Notable differences in the shape of the haematocrit distributions were observed between healthy and hardened RBCs near the bifurcation apex. These lead to more asymmetric distributions for healthy RBCs in the daughter and outlet branches with cells accumulating near the inner channel walls, exhibiting distinct hematocrit peaks which are sharper for healthy RBCs. Although the hematocrit distributions differed locally, similar partitioning characteristics were observed for both suspensions. Comparisons with RBC distributions measured in a T-shaped bifurcation showed that the bifurcation angle affects the haematocrit characteristics of the healthy RBCs and not the hardened ones. The extent of RBC partitioning was found similar in both geometries and suspensions. The study highlights the differences between local and global characteristics which impact RBC distribution in more complex, multi-bifurcation networks.
Cracking the code: uncovering the factors that drive COVID-19 standard operating procedures compliance among school management in Malaysia
Authors: Ahmad Noor Sakinah , Karuppiah Karmegam , Praveena Sarva Mangala , Ali Nina Fatma , Ramdas Murugadas , Mohammad Yusof Nur Athirah Diyana 
Published: January 2024

AbstractMalaysia's government's decision to reopen schools during the COVID-19 outbreak, especially for students taking important exams, has alarmed the public. However, the Ministry of Education has implemented a COVID-19 Standard Operating Procedure (SOP) for educational institutions. The school management’s ability to protect children from COVID-19 rests on their understanding, attitudes, and practices regarding COVID-19 SOP compliance. This study investigated Selangor, Kuala Lumpur, and Putrajaya school management’s COVID-19 SOP compliance determinants. Multistage sampling was used to sample 740 school management from Kuala Lumpur, Putrajaya, and Selangor. A self-administered questionnaire collected sociodemographic, occupational, and lifestyle data, knowledge, attitude, and practice of COVID-19 SOP compliance. The school management had good knowledge, attitude, and practice toward COVID-19 SOP. Monthly income, school location, smoking status, and physical activity differed significantly from KAP (p < 0.05). The correlation between KAP showed a significant relationship with the values (r = 0.348, p < 0.001) and (r = 0.358, p = 0.003). Nine independent variables strongly predicted SOPs compliance practice in multiple linear regression: knowledge, attitude, age, source of knowledge; Ministry of Health, physical activities, type of infectious disease exposed; Tuberculosis and Measles (p < 0.05). The data indicate that school management exhibits good knowledge, attitude, and compliance with SOPs during the pandemic. School management oversees SOPs, and to keep schools safe, management must analyse hazards and take action. Therefore, knowledge and attitude are expected to determine factors of practice toward COVID-19 SOP compliance.
High expression of Trop2 is associated with aggressive localized prostate cancer and is a candidate urinary biomarker
Authors: Liu Shiqin , Hawley Sarah J. , Kunder Christian A. , Hsu En-Chi , Shen Michelle , Westphalen Lennart , Auman Heidi , Newcomb Lisa F. , Lin Daniel W. , Nelson Peter S. , Feng Ziding , Tretiakova Maria S. , True Lawrence D. , Vakar-Lopez Funda , Carroll Peter R. , Simko Jeffry , Gleave Martin E. , Troyer Dean A. , McKenney Jesse K. , Brooks James D. , Liss Michael A. , Stoyanova Tanya 
Published: January 2024

AbstractDistinguishing indolent from clinically significant localized prostate cancer is a major clinical challenge and influences clinical decision-making between treatment and active surveillance. The development of novel predictive biomarkers will help with risk stratification, and clinical decision-making, leading to a decrease in over or under-treatment of patients with prostate cancer. Here, we report that Trop2 is a prognostic tissue biomarker for clinically significant prostate cancer by utilizing the Canary Prostate Cancer Tissue Microarray (CPCTA) cohort composed of over 1100 patients from a multi-institutional study. We demonstrate that elevated Trop2 expression is correlated with worse clinical features including Gleason score, age, and pre-operative PSA levels. More importantly, we demonstrate that elevated Trop2 expression at radical prostatectomy predicts worse overall survival in men undergoing radical prostatectomy. Additionally, we detect shed Trop2 in urine from men with clinically significant prostate cancer. Our study identifies Trop2 as a novel tissue prognostic biomarker and a candidate non-invasive marker for prostate cancer.
A novel few shot learning derived architecture for long-term HbA1c prediction
Authors: Qaraqe Marwa , Elzein Almiqdad , Belhaouari Samir , Ilam Md Shafiq , Petrovski Goran 
Published: January 2024

AbstractRegular monitoring of glycated hemoglobin (HbA1c) levels is important for the proper management of diabetes. Studies demonstrated that lower levels of HbA1c play an essential role in reducing or delaying microvascular difficulties that arise from diabetes. In addition, there is an association between elevated HbA1c levels and the development of diabetes-related comorbidities. The advanced prediction of HbA1c enables patients and physicians to make changes to treatment plans and lifestyle to avoid elevated HbA1c levels, which can consequently lead to irreversible health complications. Despite the impact of such prediction capabilities, no work in the literature or industry has investigated the futuristic prediction of HbA1c using current blood glucose (BG) measurements. For the first time in the literature, this work proposes a novel FSL-derived algorithm for the long-term prediction of clinical HbA1c measures. More importantly, the study specifically targeted the pediatric Type-1 diabetic population, as an early prediction of elevated HbA1c levels could help avert severe life-threatening complications in these young children. Short-term CGM time-series data are processed using both novel image transformation approaches, as well as using conventional signal processing methods. The derived images are then fed into a convolutional neural network (CNN) adapted from a few-shot learning (FSL) model for feature extraction, and all the derived features are fused together. A novel normalized FSL-distance (FSLD) metric is proposed for accurately separating the features of different HbA1c levels. Finally, a K-nearest neighbor (KNN) model with majority voting is implemented for the final classification task. The proposed FSL-derived algorithm provides a prediction accuracy of 93.2%.
Elevated circulating adiponectin levels do not prevent anxiety-like behavior in a PCOS-like mouse model
Authors: Samad Manisha , Ek Joakim , Börchers Stina , Krieger Jean-Philippe , Stener-Victorin Elisabet , Skibicka Karolina P. , Asterholm Ingrid Wernstedt , Benrick Anna 
Published: January 2024

AbstractPolycystic ovary syndrome (PCOS) is associated with symptoms of moderate to severe anxiety and depression. Hyperandrogenism is a key feature together with lower levels of the adipocyte hormone adiponectin. Androgen exposure leads to anxiety-like behavior in female offspring while adiponectin is reported to be anxiolytic. Here we test the hypothesis that elevated adiponectin levels protect against the development of androgen-induced anxiety-like behavior. Pregnant mice overexpressing adiponectin (APNtg) and wildtypes were injected with vehicle or dihydrotestosterone to induce prenatal androgenization (PNA) in the offspring. Metabolic profiling and behavioral tests were performed in 4-month-old female offspring. PNA offspring spent more time in the closed arms of the elevated plus maze, indicating anxiety-like behavior. Intriguingly, neither maternal nor offspring adiponectin overexpression prevented an anxiety-like behavior in PNA-exposed offspring. However, adiponectin overexpression in dams had metabolic imprinting effects, shown as lower fat mass and glucose levels in their offspring. While serum adiponectin levels were elevated in APNtg mice, cerebrospinal fluid levels were similar between genotypes. Adiponectin overexpression improved metabolic functions but did not elicit anxiolytic effects in PNA-exposed offspring. These observations might be attributed to increased circulating but unchanged cerebrospinal fluid adiponectin levels in APNtg mice. Thus, increased adiponectin levels in the brain are likely needed to stimulate anxiolytic effects.
Hematologic parameters in female alpacas during age progression: a retrospective study
Authors: Wagener Matthias Gerhard , Kornblum Max , Kiene Frederik , Ganter Martin , Teichmann Ulrike 
Published: January 2024

AbstractAlpacas, like all camelids, have elliptical red blood cells (RBCs) in contrast to other mammals. This particular shape is important for increased osmotic resistance and stability. Age-related changes in the RBC count are known in other species, with alterations in both red and white blood cells being described. In alpacas, there are few data on age-related changes, and only a comparison of crias with adult animals. We characterized age-related hematologic changes in a study of 21 female alpacas from a research herd. A total of 87 records of clinically healthy alpacas of different ages were statistically analyzed retrospectively from the hematologic records over a nine-year period. Significant positive correlations of age with hemoglobin (Hb), HCT, MCV, MCH, neutrophils, platelet-to-lymphocyte ratio (PLR), and neutrophil-to-lymphocyte ratio (NLR) were found as well as significant negative correlations of age with lymphocytes in addition to lymphocyte-to-monocyte ratio (LMR). A paired comparison of eight older animals in the herd at three different ages also showed significant differences in the parameters Hb, HCT, MCV, MCH, MCHC, lymphocytes, eosinophils and neutrophils. Similar changes in hematologic parameters have been reported in other species and should be taken into account when interpreting hematologic results in alpacas.
Synthesis, in vitro potency of inhibition, enzyme kinetics and in silico studies of quinoline-based α-glucosidase inhibitors
Authors: Ghomi Minoo Khalili , Dastyafteh Navid , Montazer Mohammad Nazari , Noori Milad , Mojtabavi Somayeh , Faramarzi Mohammad Ali , Hashemi Seyedeh Mahdieh , Mahdavi Mohammad 
Published: January 2024

AbstractDiabetes mellitus is a multifactorial global health disorder that is rising at an alarming rate. One effective therapeutic approach for controlling hyperglycemia associated with type-2 diabetes is to target α-glucosidase, which catalyzes starch hydrolysis in the intestine. In an attempt to find potential α-glucosidase inhibitors, a series of twenty new quinoline linked benzothiazole hybrids (8a–t) were synthesized in good yields from suitable reaction procedures and their chemical structures were analyzed by 1HNMR, 13CNMR, IR, and ESI–MS analysis. The synthesized derivatives further screened for their activity against α-glucosidase. Among them, compounds 8b, 8h, 8n and 8o exhibited remarkable α-glucosidase inhibitory activity with IC50 values ranging from 38.2 ± 0.3 to 79.9 ± 1.2 µM compared with standard drug acarbose (IC50 = 750.0 ± 2.0 µM). Enzyme kinetic studies of the most active compound (8h) indicated a non-competitive inhibition with Ki value of 38.2 µM. Moreover, the homology modeling, molecular docking and molecular dynamics simulation studies were conducted to reveal key interactions between the most active compound 8h and the targeted enzyme. These results are complementary to the experimental observations. In order to predict the druggability of the novel derivatives, the pharmacokinetic properties were also applied. These findings could be useful for the design and development of new α-glucosidase inhibitors.
Divorce prediction using machine learning algorithms in Ha’il region, KSA
Authors: Moumen Abdelkader , Shafqat Ayesha , Alraqad Tariq , Alshawarbeh Etaf Saleh , Saber Hicham , Shafqat Ramsha 
Published: January 2024

AbstractThe application of artificial intelligence (AI) in predictive analytics is growing in popularity. It has the power to offer ground-breaking solutions for a range of social problems and real world societal difficulties. It is helpful in addressing some of the social issues that today’s world seems incapable of solving. One of the most significant phenomena affecting people’s lives is divorce. The goal of this paper is to study the use of machine learning algorithms to determine the effectiveness of divorce predictor scale (DPS) and identify the reasons that usually lead to divorce in the scenario of Hail region, KSA. For this purpose, in this study, the DPS, based on Gottman couples therapy, was used to predict divorce by applying different machine learning algorithms. There were 54 items of the DPS used as features or attributes for data collection. In addition to the DPS, a personal information form was utilized to gather participants’ personal data in order to conduct this study in a more structured and traditional manner. Out of 148 participants 116 participants were married whereas 32 were divorced. With the use of algorithms artificial neural network (ANN), naïve bayes (NB), and random forest (RF), the effectiveness of DPS was examined in this study. The correlation based feature selection method was used to identify the top six features from the same dataset and the highest accuracy rate was 91.66% with RF. The results show that DPS can predict divorce. This scale can help family counselors and therapists in case formulation and intervention plan development process. Additionally, it may be argued that the Hail region, KSA sampling confirmed the Gottman couples treatment predictors.
Electro osmotically interactive biological study of thermally stratified micropolar nanofluid flow for Copper and Silver nanoparticles in a microchannel
Authors: Akbar Noreen Sher , Rafiq Maimona , Muhammad Taseer , Alghamdi Metib 
Published: January 2024

AbstractA novel mathematical analysis is established that summits the key features of peristaltic propulsion for a non-Newtonian micropolar fluid with the electroosmosis and heat transfer enhancement using nanoparticles. In such physiological models, the channel have a symmetric configuration in accordance with the biological problem. Being mindful of this fact, we have disclosed an integrated analysis on symmetric channel that incorporates major physiological applications. The creeping flow inference is reviewed to model this realistic problem. Flow equations are model using cartesian coordinates and simplified using long wave length and low Reynolds number approximation. Nonlinear linear couple equations are solving numerically. We have studied the variation in the properties of nanofluid developed by two different types of nanoparticles (i.e. Cu and Ag nanoparticles). Graphical illustrations are unveiled to highlight the physical aspects of nanoparticles and flow parameters. The exploration demonstrates that the micro-rotation of the nano-liquid elements enhances the thermal conductivity of the fluid movement. The effect of micropolar fluid parameters on mean flow and pressure variables is also presented.
Development of an ammonia-biodiesel dual fuel combustion engine's injection strategy map using response surface optimization and artificial neural network prediction
Authors: Elumalai R. , Ravi K. , Elumalai P. V. , Sreenivasa Reddy M. , Prakash E. , Sekar Prabhakar 
Published: January 2024

AbstractThe study intends to calibrate the compression ignition (CI) engine split injection parameters as efficiently. The goal of the study is to find the best split injection parameters for a dual-fuel engine that runs on 40% ammonia and 60% biodiesel at 80% load and a constant speed of 1500 rpm with the CRDi system. To optimize and forecast split injection settings, the RSM and an ANN model are created. Based on the experimental findings, the RSM optimization research recommends a per-injection timing of 54 °CA bTDC, a main injection angle of 19 °CA bTDC, and a pilot mass of 42%. As a result, in comparison to the unoptimized map, the split injection optimized calibration map increases BTE by 12.33% and decreases BSEC by 6.60%, and the optimized map reduces HC, CO, smoke, and EGT emissions by 15.68%, 21.40%, 18.82, and 17.24%, while increasing NOx emissions by 15.62%. RSM optimization with the most desirable level was selected for map development, and three trials were carried out to predict the calibrated map using ANN. According to the findings, the ANN predicted all responses with R > 0.99, demonstrating the real-time reproducibility of engine variables in contrast to the RSM responses. The experimental validation of the predicted data has an error range of 1.03–2.86%, which is acceptable.
Psychrophiles to control ice-water phase changes in frost-susceptible soils
Authors: Rahman Rashed , Bheemasetti Tejo V. , Govil Tanvi , Sani Rajesh 
Published: January 2024

AbstractThe phase changes of soil water or porous media have a crucial influence on the performance of natural and man-made infrastructures in cold regions. While various methods have been explored to address the impacts of frost-action arising from these phase changes, conventional approaches often rely on chemicals, mechanical techniques, and the reuse of waste materials, which often exhibit certain limitations and environmental concerns. In contrast, certain organisms produce ice-binding proteins (IBPs) or antifreeze proteins (AFPs) to adapt to low temperatures, which can inhibit ice crystal growth by lowering the freezing point and preventing ice crystallization without the need for external intervention. This study explores the potential of three psychrophilic microbes: Sporosarcina psychrophile, Sporosarcina globispora, and Polaromonas hydrogenivorans, to induce non-equilibrium freezing point depression and thermal hysteresis in order to control ice lens growth in frost-susceptible soils. We hypothesize that the AFPs produced by psychrophiles will alter the phase changes of porous media in frost-susceptible soils. The growth profiles of the microbes, the concentration of released proteins in the extracellular solution, and the thermal properties of the protein-mixed soils are monitored at an interval of three days. The controlled soil showed a freezing point of − 4.59 °C and thermal hysteresis of 4.62 °C, whereas protein-treated soil showed a maximum freezing point depression of − 8.54 °C and thermal hysteresis of 7.71 °C. Interestingly, except for the controlled sample, all the protein-treated soil samples were thawed at a negative temperature (minimum recorded at − 0.85 °C). Further analysis showed that the treated soils compared to porous media mixed soil freeze (1.25 °C vs. 0.51 °C) and thaw (2.75 °C vs. 1.72 °C) at extensive temperature gap. This freezing and thawing temperature gap is the temperature difference between the beginning of ice core formation and completed frozen, and the beginning of ice core thawing and completed thawed for the treated soil samples selected from different incubation days. Overall, this study presents a novel bio-mediated approach using psychrophilic microbes to control ice formation in frost-susceptible soils.
Genome-wide in-silico analysis of ethylene biosynthesis gene family in Musa acuminata L. and their response under nutrient stress
Authors: Tabassum Nosheen , Shafiq Muhammad , Fatima Sameen , Tahir Sana , Tabassum Bushra , Ali Qurban , Javed Muhammad Arshad 
Published: January 2024

AbstractEthylene is a gaseous phytohormone involved in plants’ growth and developmental processes, including seed germination, root initiation, fruit ripening, flower and leaf senescence, abscission, and stress responses. Ethylene biosynthesis (EB) gene analysis in response to nitrogen (N) and potassium (K) stress has not yet been conducted in Musa acuminata (banana) roots. The genome mining of banana (Musa acuminata L.) revealed 14 putative 1-aminocyclopropane-1-carboxylate synthase (ACS), 10 1-aminocyclopropane-1-carboxylate oxidase (ACO), and 3 Ethylene overproducer 1 (ETO1) genes. ACS, ACO, and ETO1 proteins possessed amino acid residues ranging from 422–684, 636–2670, and 893–969, respectively, with molecular weight (Mw) ranging from 4.93–7.55 kD, 10.1–8.3 kD and 10.1–10.78 kD. The number of introns present in ACS, ACO, and ETO1 gene sequences ranges from 0–14, 1–6, and 0–6, respectively. The cis-regulatory element analysis revealed the presence of light-responsive, abscisic acid, seed regulation, auxin-responsive, gibberellin element, endosperm-specific, anoxic inducibility, low-temperature responsiveness, salicylic acid responsiveness, meristem-specific and stress-responsive elements. Comprehensive phylogenetic analyses ACS, ACO, and ETO1 genes of Banana with Arabidopsis thaliana revealed several orthologs and paralogs assisting in understanding the putative functions of these genes. The expression profile of Musa acuminata genes in root under normal and low levels of nitrogen and potassium shows that MaACS14 and MaACO6 expressed highly at normal nitrogen supply. MaACS1 expression was significantly upregulated at low potassium levels, whereas, MaACO6 gene expression was significantly downregulated. The functional divergence and site-specific selective pressures on specific gene sequences of banana have been investigated. The bioinformatics-based genome-wide assessment of the family of banana attempted in the present study could be a significant step for deciphering novel ACS, ACO, and ETO1 genes based on genome-wide expression profiling.