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This paper presents comparisons between flow fields for turbulent flow over square cylinder with two different angles of incidence in free stream at Reynolds number of Re = 3400. The present numerical results were obtained using a two-dimensional finite-volume code which solves governing equations. The pressure field was obtained with well known SIMPLE algorithm. The central difference scheme was employed for the discretization of convection and diffusion terms. The v2f and standard k-ε model were used for simulation of turbulent flow. Time averaged velocity, root mean square velocities and streamlines in the downstream of square cylinders are presented. A number of quantities such as Strouhal number, drag coefficient and the length of the wake are calculated for the case of angle of incidence α=0°, 45° with two turbulent models. Strouhal number and the length of the wake are larger for the case ofα=45° because of the sharp corners in it which results in more diffusion of turbulence in the downstream of the cylinder. On the other hand, with comparison of results obtained by v2f and standard k-εmodels with experiment, it is obvious that v2f leads to much more accurate results. [ABSTRACT FROM AUTHOR]

The highly plastic nature of Alveolar Macrophage (AM) plays a crucial role in the defense against inhaled particulates and pathogens in the lungs. Depending on the signal, AM acquires either the classically activated M1 phenotype or the alternatively activated M2 phenotype. In this study, we investigate the metabolic shift in the activated phases of AM (M1 and M2 phases) by reconstructing context specific Genome-Scale Metabolic (GSM) models. Metabolic pathways such as pyruvate metabolism, arachidonic acid metabolism, chondroitin/heparan sulfate biosynthesis, and heparan sulfate degradation are found to be important driving forces in the development of the M1/M2 phenotypes. Additionally, we formulated a bilevel optimization framework named MetaShiftOptimizer to identify minimal modifications that shift one activated state (M1/M2) to the other. The identified reactions involve metabolites such as glycogenin, L-carnitine, 5-hydroperoxy eicosatetraenoic acid, and leukotriene B4, which show potential to be further investigated as significant factors for developing efficient therapy targets for severe respiratory disorders in the future. Overall, our study contributes to the understanding of the metabolic capabilities of the M1 and M2 phenotype of AM and identifies pathways and reactions that can be potential targets for polarization shift and also be used as therapeutic strategies against respiratory diseases. [ABSTRACT FROM AUTHOR]

Cerebral vascular malformations (CVMs), particularly cerebral cavernous malformations and cerebral arteriovenous malformations, pose significant neurological challenges due to their complex etiologies and clinical implications. Traditionally viewed as congenital conditions with structural abnormalities, CVMs have been treated primarily through resection, embolization, and stereotactic radiosurgery. While these approaches offer some efficacy, they often pose risks to neurological integrity due to their invasive nature. Advances in next‐generation sequencing, particularly high‐depth whole‐exome sequencing and bioinformatics, have facilitated the identification of gene variants from neurosurgically resected CVMs samples. These advancements have deepened our understanding of CVM pathogenesis. Somatic mutations in key mechanistic pathways have been identified as causative factors, leading to a paradigm shift in CVM treatment. Additionally, recent progress in noninvasive and minimally invasive techniques, including gene imaging genomics, liquid biopsy, or endovascular biopsies (endovascular sampling of blood vessel lumens), has enabled the identification of gene variants associated with CVMs. These methods, in conjunction with clinical data, offer potential for early detection, dynamic monitoring, and targeted therapies that could be used as monotherapy or adjuncts to surgery. This review highlights advancements in CVM pathogenesis and precision therapies, outlining the future potential of precision medicine in CVM management. [ABSTRACT FROM AUTHOR]

Radiogenomics is an emerging field that links imaging features with molecular characteristics of diseases. In clear cell renal cell carcinoma (ccRCC), metabolic reprogramming leads to lipid accumulation, influenced by the adipose differentiation-related protein (ADFP). This study aimed to investigate whether hepatic and tumoral Hounsfield Unit (HU) values could serve as noninvasive radiogenomic biomarkers for ADFP expression in ccRCC. We analyzed CT images of 185 ccRCC patients, comparing lipid-associated HU values in the liver and tumor across ADFP expression statuses. Patients with low-grade ccRCC expressing ADFP showed significantly lower minimum HU values in both liver and tumor tissue, indicating greater lipid accumulation. Additionally, ADFP expression correlated negatively with abdominal adipose tissue compartments and positively with minimum tumoral HU values, linking systemic lipid metabolism to tumor biology. These findings suggest that hepatic and tumoral HU measurements may serve as noninvasive markers of lipid accumulation related to ADFP, providing insight into metabolic alterations in ccRCC. While promising, these results require validation in larger, controlled studies due to sample size and variability limitations. This approach could enhance the radiogenomic assessment of ccRCC, supporting noninvasive insights into tumor metabolism and progression. [ABSTRACT FROM AUTHOR]

Featured Application: The research results described in the article will find applications in modern systems that integrate electronic devices with textiles in the form of e-textiles and intelligent clothing. This paper introduces a novel approach to fabricating textile microwave transmission lines through knitting techniques. These textile-based transmission lines, capable of transmitting high-frequency signals between wearable transceivers and antennas, offer significant potential for the development of advanced wearable electronics. By leveraging a single technological process, our proposed method enables the creation of flexible and wearable devices. To demonstrate the feasibility of this approach, we present the design and numerical modeling of a microstrip line operating within the gigahertz frequency range. A prototype structure was fabricated and experimentally characterized, revealing moderate attenuation of less than 5 dB for frequencies below 2.5 GHz. However, a major challenge in the field of wearable electronics is the real-time applicability of such devices. Our work aims to address this challenge by providing a flexible and scalable solution for integrating wireless communication capabilities into wearable systems. Future research will focus on further optimizing the design and fabrication processes to enhance performance and minimize signal loss, ultimately enabling the realization of practical and user-friendly wearable devices. [ABSTRACT FROM AUTHOR]

There are several important challenges in radiomics research; one of them is feature selection. Since many quantitative features are non-informative, feature selection becomes essential. Feature selection methods have been mixed with filter, wrapper, and embedded methods without a rule of thumb. This study aims to develop a framework for optimal feature selection in radiomics research. We developed the framework that the optimal features were selected to quickly through controlling relevance and redundancy among features. A ‘FeatureMap’ was generated containing information for each step and used as a platform. Through this framework, we can explore the optimal combination of radiomics features and evaluate the predictive performance using only selected features. We assessed the framework using four real datasets. The FeatureMap generated 6 combinations, with the number of features selected varying for each combination. The predictive models obtained high performances; the highest test area under the curves (AUCs) were 0.792, 0.820, 0.846 and 0.738 in the cross-validation method, respectively. We developed a flexible framework for feature selection methods in radiomics research and assessed its usefulness using various real-world data. Our framework can assist clinicians in efficiently developing predictive models based on radiomics. [ABSTRACT FROM AUTHOR]

Based on high-throughput metabolomics data, the recently introduced inverse differential Jacobian algorithm can infer regulatory factors and molecular causality within metabolic networks close to steady-state. However, these studies assumed perturbations acting independently on each metabolite, corresponding to metabolic system fluctuations. In contrast, emerging evidence puts forward internal network fluctuations, particularly from gene expression fluctuations, leading to correlated perturbations on metabolites. Here, we propose a novel approach that exploits these correlations to quantify relevant metabolic interactions. By integrating enzyme-related fluctuations in the construction of an appropriate fluctuation matrix, we are able to exploit the underlying reaction network structure for the inverse Jacobian algorithm. We applied this approach to a model-based artificial dataset for validation, and to an experimental breast cancer dataset with two different cell lines. By highlighting metabolic interactions with significantly changed interaction strengths, the inverse Jacobian approach identified critical dynamic regulation points which are confirming previous breast cancer studies. [ABSTRACT FROM AUTHOR]

Vitiligo is a skin condition characterized by the loss of pigment, resulting in white patches on various parts of the body. It occurs when melanocytes, the cells that are responsible for producing skin pigment, are destroyed or stop functioning. This study aimed to investigate the melanogenic potential of various 4-methylcoumarin (4MC) derivatives, including 6-methoxy-4-methylcoumarin (6M-4MC), 7-methoxy-4-methylcoumarin (7M-4MC), 7-amino-4-methylcoumarin (7A-4MC), 6,7-dihydroxy-4-methylcoumarin (6,7DH-4MC), 7,8-dihydroxy-4-methylcoumarin (7,8DH-4MC), and 6,7-dimethoxy-4-methylcoumarin (6,7DM-4MC), in B16F10 melanoma cells. Our findings revealed that, while 4MC, 7A-4MC, 6,7DH-4MC, and 7,8DH-4MC did not exhibit any effect on melanin production, significant stimulation of melanogenesis was observed with 6M-4MC, 7M-4MC, and 6,7DM-4MC, with 6M-4MC demonstrating the most pronounced effect. 6M-4MC significantly stimulated melanin production and tyrosinase activity in a concentration-dependent manner in B16F10 cells. A Western blot analysis revealed that 6M-4MC increased the expression levels of microphthalmia-associated transcription factor (MITF), tyrosinase, tyrosinase-related protein-1 (TRP-1), and tyrosinase-related protein-2 (TRP-2). Further mechanistic studies showed that 6M-4MC inhibited extracellular signal-regulated kinase (ERK) and protein kinase B (AKT), which led to the upregulation of MITF and TRP proteins and subsequent activation of melanin synthesis. Additionally, 6M-4MC activated GSK3β phosphorylation, reduced β-catenin phosphorylation, and stimulated melanogenesis via the GSK3β/β-catenin pathway. Moreover, a primary skin irritation test was conducted on the upper backs of 32 healthy female volunteers to assess the potential irritation or sensitization from 6M-4MC when applied topically at concentrations of 50 µM and 100 µM. The test results showed no adverse effects on the skin. Collectively, these findings suggest that 6M-4MC may be a promising pigmentation stimulator for use in cosmetics and in the medical treatment of hypopigmentation disorders, particularly in the treatment of skin conditions such as vitiligo. [ABSTRACT FROM AUTHOR]

Bacterial blight (BB) of rice caused by Xanthomonas oryzae pathovar oryzae (Xoo) is a serious global rice disease. Due to increasing bactericide resistance, developing new inhibitors is urgent. Drug repositioning offers a potential strategy to address this issue. In this study, we integrated transcriptional data into a genome-scale metabolic model (GSMM) to screen novel anti-Xoo targets. Two RNA-seq datasets (before and after bismerthiazol treatment) were used to constrain the GSMM and simulate metabolic processes. Metabolic fluxes were calculated using parsimonious flux balance analysis (pFBA) identifying reactions with significant changes for target screening. Glutathione oxidoreductase (GSR) was selected as a potential anti-Xoo target and validated through antibacterial experiments. Virtual screening based on the target identified DB12411 as a lead compound with the potential for new antibacterial agents. This approach demonstrates that integrating metabolic networks and transcriptional data can aid in both understanding antibacterial mechanisms and discovering novel drug targets. [ABSTRACT FROM AUTHOR]

Background: Psoriasis is characterized by accelerated proliferation of epidermal keratinocytes. IL-27 is relevant to psoriasis pathogenesis. We previously found that IL-27 stimulates the proliferation of keratinocytes. However, the mRNAs involved in the process have not been fully studied. This study aims to identify potential pathways and hub genes associated with proliferation in keratinocytes with IL-27 intervention by bioinformatics analysis. Methods: The mRNA expression profiles from HaCaT cells with or without IL-27 treated were analyzed by bioinformatics tools. The protein–protein interaction (PPI) network was constructed to screen gene clusters and hub genes associated with proliferation. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were used to identify the function of the mRNAs. The GEO database and quantitative real-time PCR (qPCR) were used to verify the expression levels of hub genes in psoriatic skin lesions and IL-27-treated psoriasiform keratinocytes, respectively. Results: We found 1257 differentially expressed genes and screened 2 crucial gene clusters. GO analysis revealed that Cluster 1 was mainly enriched in "Mitotic sister chromatid segregation" and "Spindle". Cluster 2 was mainly enriched in the "Pyruvate metabolic process" and "Oxidoreductase complex". KEGG analysis showed that Cluster 1 and Cluster 2 were mainly enriched in "Cell cycle" and "Glycolysis/Gluconeogenesis", respectively. We then identified 6 hub genes enriched in the two pathways, including CCNB1, PTTG1, CDC20, PLK1, PKM, and LDHA. GSEA complemented the role of the mitochondrial "Oxidative phosphorylation" pathway. Moreover, we found that 6 hub genes were upregulated in psoriasis skin lesions and IL-27 elevated the hub genes expression in M5-induced psoriasiform keratinocytes. Conclusion: IL-27 possibly promotes glycolysis, mitochondrial oxidative phosphorylation, and cell cycle progression in keratinocytes. Additionally, we identified CCNB1, PTTG1, CDC20, PLK1, PKM, and LDHA as hub genes that may be involved in the mechanism of IL-27 facilitating keratinocyte proliferation in psoriasis. [ABSTRACT FROM AUTHOR]

Mutations of KRAS, CDKN2A, TP53, and SMAD4 are the four major driver genes for pancreatic ductal adenocarcinoma (PDAC), of which mutations of KRAS and TP53 are the most frequently recognized. However, molecular‐targeted therapies for mutations of KRAS and TP53 have not yet been developed. To identify novel molecular targets, we newly established organoids with the Kras mutation (KrasmuOR) and Trp53 loss of function using Cre transduction and CRISPR/Cas9 (Krasmu/p53muOR) from murine epithelia of the pancreatic duct in KrasLSL‐G12D mice, and then analyzed the proteomic and metabolomic profiles in both organoids by mass spectrometry. Hyperfunction of the glycolysis pathway was recognized in Krasmu/p53muOR compared with KrasmuOR. Loss of function of triosephosphate isomerase (TPI1), which is involved in glycolysis, induced a reduction of cell proliferation in human PDAC cell lines with the TP53 mutation, but not in PDAC or in human fibroblasts without TP53 mutation. The TP53 mutation is clinically recognized in 70% of patients with PDAC. In the present study, protein expression of TPI1 and nuclear accumulation of p53 were recognized in the same patients with PDAC. TPI1 is a potential candidate therapeutic target for PDAC with the TP53 mutation. [ABSTRACT FROM AUTHOR]

Purpose: To examine the influence of learning adjustment dimensions (motivation, attitude, ability, teaching pattern, and environment) on depressive symptoms in Chinese nursing freshmen, and the mediating role of psychological capital. Methods: A cross-sectional survey was conducted among 471 nursing freshmen at a university in May 2024. The anonymous self-reported questionnaire included the Patient Health Questionnaire, the Learning Adjustment Questionnaire, and the Psychological Capital Questionnaire. Data were analyzed using SPSS v25.0 and PROCESS v4.1 macro, including correlation and mediation analysis. Results: Learning adjustment had a significant direct effect on depressive symptoms among nursing freshmen (β = − 0.565, p < 0.001), and psychological capital partially mediated this relationship (β= − 0.156, 95% Boot CI [− 0.107, − 0.135]), suggesting psychological capital explains part of the link between poor learning adjustment and depressive symptoms. Conclusion: More attention should be paid to the mental health issues of freshmen. Addressing learning adjustment issues and fostering psychological capital among nursing freshmen may alleviate depressive symptoms, which will require relevant educational interventions and mental health support from university educators and counselors. [ABSTRACT FROM AUTHOR]

The sense of school belonging plays an important role in students' academic, behavioural, and psychological outcomes. Based on a systematic review, following the PRISMA 2020 guidelines and examining 86 studies conducted between 1990 and February 2023, the article addresses two research questions: (a) what are the predictors of the sense of school belonging at the individual, micro, meso, exo, macro, and chrono levels of the bioecological model of human development; (b) do these predictors differ based on students' individual characteristics, and if so, how. The findings reveal individual factors as important predictors of school belonging and indicate the lack of studies that take into consideration the interplay of different (micro, meso, exo, macro, chrono) levels in addressing the sense of school belonging. Considering the complexity and multi-factorial nature of the sense of school belonging, it calls upon further research, which would support the development of evidence-based interventions for fostering school belonging among different groups of students, particularly those who are at risk of feeling alienated from school, and thus promote equity in education. [ABSTRACT FROM AUTHOR]

Concerns about a sustainable environment are increasing and have attained significant attention among policy experts worldwide. Therefore, the current research investigated to what extent financial innovations, green energy, and economic growth impacted Indian transport-based carbon (TCO2) emissions from 1990 to 2018. This research applied quantile autoregressive distributed lag (QARDL) model and the Wald test for parameter consistency. The QARDL approach proves valuable as it illustrates the causal patterns across different quantiles of financial innovations, green energy, economic growth, and environmental degradation. It offers a more comprehensive understanding of the overall relationships among these variables, which conventional methods such as ARDL and OLS often overlook. The outcomes reveal that financial innovation and green energy negatively affect TCO2 emissions, suggesting that transportation sector emissions will likely decline because of a rise in green energy and financial innovation. In contrast, GDP positively affects TCO2 emissions which deteriorate the environment. Furthermore, the findings of GDP2 found significant and negative effects on TCO2 for all quantiles, affirming the inverse U-shaped curve for the Indian economy. Overall, the study suggests that Indian governments should promote the development of green financial innovation and focus their priorities on sustainable energy to attain carbon neutrality and sustainable development goals. [ABSTRACT FROM AUTHOR]

Background: The nursing education sector has felt the impact of the shortage of nursing clinical instructors (CI) or faculty members. This phenomenon became more profound with the pandemic experience along with the global shortage of nurses in the hospitals. Objective: The study was conducted to explore the lived experiences on learning among undergraduate nursing students in a higher education institution amidst the nursing faculty shortage. Methods: The study was undertaken using a descriptive phenomenological design with seven informants, using Colaizzi's approach for data analysis. Findings: The findings of the study generated three main themes: disruptions in the learning process and platforms, responses to learning disruptions, and learners' call to action. It uncovered substantial disruptions in scheduled lectures, activities, and clinical rotations due to the nursing faculty shortage. Conclusion: The findings underscore the critical need for immediate and comprehensive measures to address the nursing faculty shortage. Despite compensatory efforts by the institution, the impact on learning experience remains significant. This study calls for prompt and effective strategies to rectify the nursing faculty shortage, ensuring optimal learning experiences for student nurses. [ABSTRACT FROM AUTHOR]

Genome-scale metabolic models (GEMs) cover the entire list of metabolic genes in an organism and associated reactions, in a tissue/condition non-specific manner. RNA-seq provides crucial information to make the GEMs condition-specific. Integrative Metabolic Analysis Tool (iMAT) and Integrative Network Inference for Tissues (INIT) are the two most popular algorithms to create condition-specific GEMs from human transcriptome data. The normalization method of choice for raw RNA-seq count data affects the model content produced by these algorithms and their predictive accuracy. However, a benchmark of the RNA-seq normalization methods on the performance of iMAT and INIT algorithms is missing in the literature. Another important phenomenon is covariates such as age and gender in a dataset, and they can affect the predictivity of analysis. In this study, we aimed to compare five different RNA-seq data normalization methods (TPM, FPKM, TMM, GeTMM, and RLE) and covariate adjusted versions of the normalized data by mapping them on a human GEM using the iMAT and INIT algorithms to generate personalized metabolic models. We used RNA-seq data for Alzheimer's disease (AD) and lung adenocarcinoma (LUAD) patients. The results demonstrated that RNA-seq data normalized by the RLE, TMM, or GeTMM methods enabled the production of condition-specific metabolic models with considerably low variability in terms of the number of active reactions compared to the within-sample normalization methods (FPKM, TPM). Using these models, we could more accurately capture the disease-associated genes (average accuracy of ~0.80 for AD and ~0.67 for LUAD) for the RLE, TMM, and GeTMM normalization methods. An increase in the accuracies was observed for all the methods when covariate adjustment was applied. We found a similar accuracy trend when we compared the metabolites of perturbed reactions to metabolome data for AD. Together, our benchmark study shows that the between-sample RNA-seq normalization methods reduce false positive predictions at the expense of missing some true positive genes when mapped on GEMs. [ABSTRACT FROM AUTHOR]

Introduction: This study examined the interplay between perceived feedback (PF), subjective wellbeing (SWB), and students’ sense of belonging to school (SBS). School belonging is a key factor for decisions regarding academic studies, and is usually impacted by PF. The current study explored whether SWB mediates the established relationship between PF and SBS. Method: This was achieved by applying a mediation model to PISA 2018 data from 12,058 students in four areas of China. Results: Perceived feedback positively affected students’ SBS (β  =  0.26, p  <  0.01); and that SWB partially mediated this relationship between PF and SBS (β  =  0.47, p  <  0.01). Discussion: The findings of this study have the potential to contribute to the existing literature on educational psychology and well-being. By shedding light on the mediating role of SWB, the research offers practical implications for educators and policymakers seeking to enhance students’ school belonging and other implications for their academic success. Further research can contribute to this promising area, by focusing on subjective wellbeing and its impact on a range of decisions being made by students during a critical phase of their personal and academic development. [ABSTRACT FROM AUTHOR]

Ocimum tenuiflorum, commonly known as Tulsi, is revered in Ayurveda for its extensive medicinal properties. However, there is a need to consolidate current knowledge on its phytochemical constituents and their pharmacological activities to identify potential areas for further research and drug development. This review aims to bridge this gap by providing a comprehensive analysis of the bioactive secondary metabolites found in O. tenuiflorum, such as rosmarinic acid, oleanolic acid, luteolin, ursolic acid, and limonene, and their associated therapeutic effects. The review will highlight the pharmacological importance of these metabolites, which exhibit antioxidant, neuroprotective, anticancer, and anti‐inflammatory properties. Additionally, this study will explore the plant's wide range of beneficial qualities, including anti‐inflammatory, antioxidant, anticholinergic, pain‐relieving, antimicrobial, stress‐reducing, antidiabetic, anticancer, liver‐protective, ulcer‐inhibiting, antifungal, and wound‐healing attributes. Furthermore, this review focuses on the plant's potential in treating conditions such as asthma, persistent fever, tuberculosis, malaria, skin discoloration, itching, digestive issues, hemorrhoids, bone fractures, gout, urinary tract infection, and diabetes. By reviewing the current literature, the aim is to identify the gaps in the existing research and propose directions for future studies. This comprehensive review will serve as a valuable resource for researchers in the development and investigation of novel drugs derived from O. tenuiflorum. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, represents a significant global health challenge due to its rising incidence, complex management, as well as recurrence rates of up to 70% or more. Early and accurate imaging diagnosis, through modalities such as ultrasound, CT, and MRI, is crucial for effective treatment. Minimally invasive therapies, including thermal ablation methods such as radiofrequency ablation, microwave ablation, laser ablation, high-intensity focused ultrasound, and cryoablation, as well as non-thermal methods like percutaneous ethanol injection and irreversible electroporation, have shown promise in treating early and intermediate stages of HCC. Some studies have reported complete response in more than 90% of nodules and survival rates of up to 60–85% at 5 years after the procedure. These therapies are increasingly employed and induce specific morphological and physiological changes in the tumor and surrounding liver tissue, which are critical to monitor for assessing treatment efficacy and detecting recurrence. This review highlights the imaging characteristics of HCC following non-surgical treatments, focusing on the common features, challenges in post-treatment evaluation, and the importance of standardized imaging protocols such as the Liver Imaging Reporting and Data System. Understanding these imaging features is essential for radiologists to accurately assess tumor viability and guide further therapeutic decisions, ultimately improving patient outcomes. [ABSTRACT FROM AUTHOR]

Background: The clinical readiness of newly graduated nurses is crucial in meeting the growing demand for health services. Consequently, it is essential to develop a scale that accurately evaluates the clinical readiness of these novice nurses. Aim: This study aimed to translate and psychometrically evaluate the Persian version of the Nursing Practice Readiness Scale (NPRS) for new graduate nurses. Methods: This methodological and cross-sectional study was conducted on new graduate nurses from June to November 2023 in Kermanshah City, Iran. The translation of the scale was performed using the forward–backward translation method. Construct validity was assessed using Exploratory Factor Analysis (EFA) with a sample of 180 participants and Confirmatory Factor Analysis (CFA) with a sample of 318 participants, both employing the convenience sampling method. The internal consistency of the tool was measured using Cronbach's alpha coefficient. Additionally, the tool's reliability was evaluated using the intraclass correlation coefficient (ICC). The analyses were conducted using SPSS version 27 and LISREL version 8 software. Results: The results of EFA and CFA confirmed the tool's structure, comprising five factors and 35 items. The CFA results showed a well-fitting model (CFI = 0.96, NNFI = 0.96, GFI = 0.893, RMSEA = 0.062, SRMR = 0.049). Pearson's correlation coefficient indicated a significant relationship between the items, subscales, and the main scale. Additionally, the Cronbach's alpha coefficient of the tool was 0.932, and the intraclass correlation coefficient (ICC) was 0.891(0.724–0.957). Conclusion: The Persian version of the Nursing Practice Readiness Scale (NPRS) is a valid and reliable tool, comprising 35 items and five factors. This scale can be effectively used to evaluate the clinical readiness of newly graduated nurses within the Iranian community. [ABSTRACT FROM AUTHOR]

Background: Assessing the clinical level of competency in nursing students is crucial as it represents the ultimate goal of nursing education. Poor competency result in low performance and can be affected by various factors. Thus, the aim of this study was to identify level of clinical competency and associated factors of nursing students in Ethiopia. Methods: systematic review and meta-analysis was employed. Searching strategy was conducted from January up to march 2024 from Web of Science, PubMed and Google Scholar. The quality of studies was assessed using PRISMA checklist. A meta-analysis was performed using R Studio with the meta package Version 1.4.1106. Results: in total, 145 studies were identified through database search, and only 7 studies were included in the meta-analysis representing 1937 nursing students. The pooled effect size of clinical competency of nursing students was 28%. Three factors were found to be associated with clinical competency: a positive clinical learning environment, student confidence in performing procedures, and effective staff-student interaction. The effect sizes of these factors were 6.30, 2.23, and 7.76, respectively. Conclusion and recommendation: The clinical competency of nursing students was 28%, and it was associated with clinical learning environment, student confidence in performing procedures, and staff-student interaction. Nursing education programs should focus on enhancing students' competency levels by addressing specific factors. (PROSPERO) International prospective register of systematic reviews: CRD42022367057. [ABSTRACT FROM AUTHOR]

The gustatory system is responsible for detecting and evaluating the palatability of the various chemicals present in food and beverages. Taste bud cells, located primarily on the tongue, communicate with the gustatory sensory neurons by means of neurochemical signals, transmitting taste information to the brain. It has also been found that the endocannabinoid system (ECS) may modulate food intake and palatability, and that taste bud cells express cannabinoid receptors. The purpose of this study was to investigate the expression of cannabinoid and cannabinoid-related receptors in the gustatory cells of the papillae vallatae and foliatae of ten piglets. Specific antibodies against the cannabinoid receptors (CB1R and CB2R), G protein-coupled receptor 55 (GPR55), transient receptor potential vanilloid 1 (TRPV1) and ankyrin 1 (TRPA1) were applied on cryosections of lingual tissue; the lingual tissue was also processed using Western blot analysis. Cannabinoid and cannabinoid-related receptors were found to be expressed in the taste bud cells and the surrounding epithelial cells. The extra-papillary epithelium also showed strong immunolabeling for these receptors. The results showed that these receptors were present in both the taste bud cells and the extra-gustatory epithelial cells, indicating their potential role in taste perception and chemesthesis. These findings contributed to understanding the complex interactions between cannabinoids and the gustatory system, highlighting the role of the ECS within taste perception and its potential use in animal production in order to enhance food intake. [ABSTRACT FROM AUTHOR]

The intricate relationship between cancer and bacteria has garnered increasing attention in recent years. While traditional cancer research has primarily focused on tumor cells and genetic mutations, emerging evidence highlights the significant role of microbial communities within the tumor microenvironment in cancer development and progression. This review aims to provide a comprehensive overview of the current understanding of the complex interplay between cancer and bacteria. We explore the diverse ways in which bacteria influence tumorigenesis and tumor behavior, discussing direct interactions between bacteria and tumor cells, their impact on tumor immunity, and the potential modulation of the tumor microenvironment. Additionally, we delve into the mechanisms through which bacterial metabolites and extracellular products May affect cancer pathways. By conducting a thorough analysis of the existing literature, we underscore the multifaceted and intricate relationship between bacteria and cancer. Understanding this complex interplay could pave the way for novel therapeutic approaches and preventive strategies in cancer treatment. [ABSTRACT FROM AUTHOR]

In parallel to the legalization of cannabis for both medicinal and recreational purposes, cannabinoid use has steadily increased over the last decade in the United States. Cannabinoids, such as tetrahydrocannabinol and anandamide, bind to the central cannabinoid‐1 (CB1) receptor to impact several physiological processes relevant for body weight regulation, including appetite and energy expenditure. The hypothalamus integrates peripheral signals related to energy balance, houses several nuclei that orchestrate eating, and expresses the CB1 receptor. Herein we review literature to date concerning cannabinergic action in the hypothalamus with a specific focus on eating behaviors. We highlight hypothalamic areas wherein researchers have focused their attention, including the lateral, arcuate, paraventricular, and ventromedial hypothalamic nuclei, and interactions with the hormone leptin. This review serves as a comprehensive analysis of what is known about cannabinoid signaling in the hypothalamus, highlights gaps in the literature, and suggests future directions. [ABSTRACT FROM AUTHOR]

Transcriptional enhancers orchestrate cell type- and time point-specific gene expression programs. Genetic variation within enhancer sequences is an important contributor to phenotypic variation including evolutionary adaptations and human disease. Certain genes and pathways may be more prone to regulatory evolution than others, with different patterns across diverse organisms, but whether such patterns exist has not been investigated at a sufficient scale. To address this question, we identified signatures of accelerated sequence evolution in conserved enhancer elements throughout the mammalian phylogeny at an unprecedented scale. While different genes and pathways were enriched for regulatory evolution in different parts of the tree, we found a striking overall pattern of pleiotropic genes involved in gene regulatory and developmental processes being enriched for accelerated enhancer evolution. These genes were connected to more enhancers than other genes, which was the basis for having an increased amount of sequence acceleration over all their enhancers combined. We provide evidence that sequence acceleration is associated with turnover of regulatory function. Detailed study of one acceleration event in an enhancer of HES1 revealed that sequence evolution led to a new activity domain in the developing limb that emerged concurrently with the evolution of digit reduction in hoofed mammals. Our results provide evidence that enhancer evolution has been a frequent contributor to regulatory innovation at conserved developmental signaling genes in mammals. [ABSTRACT FROM AUTHOR]

Fungi are diverse organisms with various characteristics and functions. Some play a role in recycling essential elements, such as nitrogen and carbon, while others are utilized in the food and drink production industry. Some others are known to cause diseases in various organisms, including humans. Fungal pathogens cause superficial, subcutaneous, and systemic infections. Consequently, many scientists have focused on studying the factors contributing to the development of human diseases. Therefore, multiple approaches have been assessed to examine the biology of these intriguing organisms. The genome-scale metabolic models (GEMs) have demonstrated many advantages to microbial metabolism studies and the ability to propose novel therapeutic alternatives. Despite significant advancements, much remains to be elucidated regarding the use of this tool for investigating fungal metabolism. This review aims to compile the data provided by the published GEMs of human fungal pathogens. It gives specific examples of the most significant contributions made by these models, examines the advantages and difficulties associated with using such models, and explores the novel approaches suggested to enhance and refine their development. [ABSTRACT FROM AUTHOR]

The present study investigates the potential medicinal and health benefits of the Middle Eastern and North African herb Pistacia atlantica. Research shows that its compounds, such as flavonoids, phenolic compounds, and oils, could be beneficial. It can help with heart disease, sugar sickness, and brain illness because of its antioxidant and anti -inflammatory attributes. Also, P. atlantica can kill bacteria and help heal cuts. It might help fight cancer too. But we need to study more to know all its uses, enhance extraction techniques, and make sure it's safe and works well in tests with people. The review will focus on the pharmacological properties, constituents, and mechanisms of action of P. atlantica, discussing its traditional use in medicine, effects on inflammatory diseases, antibacterial properties, promise in cancer treatment, and potential for treating diabetes and other metabolic issues. The review aims to comprehensively understand P. atlantica's potential as a therapeutic agent and identify areas for further research. [ABSTRACT FROM AUTHOR]

Hepatocellular Carcinoma (HCC), the most common primary liver cancer, is a significant contributor to worldwide cancer-related deaths. Various medical imaging techniques, including computed tomography, magnetic resonance imaging, and ultrasound, play a crucial role in accurately evaluating HCC and formulating effective treatment plans. Artificial Intelligence (AI) technologies have demonstrated potential in supporting physicians by providing more accurate and consistent medical diagnoses. Recent advancements have led to the development of AI-based multi-modal prediction systems. These systems integrate medical imaging with other modalities, such as electronic health record reports and clinical parameters, to enhance the accuracy of predicting biological characteristics and prognosis, including those associated with HCC. These multi-modal prediction systems pave the way for predicting the response to transarterial chemoembolization and microvascular invasion treatments and can assist clinicians in identifying the optimal patients with HCC who could benefit from interventional therapy. This paper provides an overview of the latest AI-based medical imaging models developed for diagnosing and predicting HCC. It also explores the challenges and potential future directions related to the clinical application of AI techniques. [ABSTRACT FROM AUTHOR]

Simple Summary: This research aims to explore how specific imaging features on computed tomography (CT) scans, related to lipid metabolism, can be linked to a protein called adipose differentiation-related protein (ADFP) in clear cell renal cell carcinoma. This study suggests that tumors with higher lipid content, which can be seen as lower values on a CT scan, are associated with lower-grade, less aggressive cancers that express ADFP. This finding is significant because it could lead to non-invasive methods for evaluating tumor characteristics, potentially helping better understand the nature of the cancer and tailor treatment plans without needing invasive procedures. This study aimed to investigate the association between metabolic lipid computed tomography (CT) features and adipose differentiation-related protein (ADFP) expression in clear cell renal cell carcinoma (ccRCC), providing insights into non-invasive methods for assessing ADFP expression and tumor characteristics. This study utilized data from The Cancer Genome Atlas and the Cancer Imaging Archive to analyze genetic alterations and imaging characteristics in ccRCC patients. Tumoral Hounsfield units (HU) analysis and quantification of abdominal adipose tissue compartments were performed using CT images. Statistical analyses were conducted to compare tumoral HU values according to ADFP gene expression and World Health Organization/International Society of Urological Pathology (WHO/ISUP) tumor grade, as well as to explore correlations between tumoral HU values and adipose tissue quantification. Among the 174 identified patients, those with ADFP gene expression showed significantly lower minimum tumoral HU values in low-grade cancers compared to high-grade cancers. Similarly, patients with low-grade cancers expressing ADFP exhibited lower minimum tumoral HU values compared to those without ADFP expression. Negative correlations were observed between minimum tumoral HU values and visceral adipose tissue, subcutaneous adipose tissue, and total adipose tissue in both ccRCC patients with and without ADFP expression. This study reveals a significant association between metabolic lipid CT features and ADFP expression in ccRCC patients. Lower minimum tumoral HU values, suggestive of higher intracellular lipid accumulation, were observed in tumors with low WHO/ISUP grade and ADFP expression. [ABSTRACT FROM AUTHOR]

Background and Aims: COVID‐19 patients might be admitted to the hospital based on their clinical manifestations or to the intensive care unit (ICU) due to the severity of their symptoms or critical situation. Our main objective was to investigate clinical and demographic factors influencing COVID‐19 patients' admission to the ICU and length of stay (LOS) using extracted data from the hospital information systems in Iran. Methods: The data of hospitalized patients with confirmed COVID‐19 were retrieved from the health information system of Imam Khomeini Hospital Complex, Tehran, Iran between March 2020 and February 2022. The primary outcome was the ICU admission, and the secondary outcome was the LOS. The correlation analysis between laboratory findings and demographic data with ICU admission and LOS was done using SPSS 21.0, and p < 0.05 was considered significant. Results: Of all the 4156 patients, 2391 (57.5%) were male and the mean age was 58.69 ± 8.19 years. Of these, 9.5% of patients were admitted to ICU at any time point during their hospital stay. Age and laboratory variables such as neutrophil‐to‐lymphocyte ratio (NLR), ALT (U/L), albumin (g/dL), plasma glucose (mg/dL), ferritin levels (ng/mL), and phosphorous levels (mg/dL) shown the significant relationship with ICU admission. Also, being a smoker and having hypoxemia had a significant relationship with longer stays in the hospital. In this study, we validated a cut‐off value of 4.819 for NLR, calculated at hospitalization, as a useful predictor of disease progression and occurrence of serious clinical outcomes, such as ICU admission. Conclusion: The study examined various clinical factors associated with ICU admission in COVID‐19 patients. The findings suggest that certain factors can increase the risk of ICU admission and influence the length of hospital stay which should be focused in future studies. [ABSTRACT FROM AUTHOR]

Frailty and cardiovascular diseases are increasingly prevalent in aging populations, sharing common pathological mechanisms, such as oxidative stress. The evidence shows that these factors predispose frail individuals to cardiovascular diseases but also increase the risk of thrombosis. Considering this background, this review aims to explore advances regarding the relationship between oxidative stress, platelet alterations, and cardiovascular diseases in frailty, examining the role of reactive oxygen species overproduction in platelet activation and thrombosis. The current evidence shows a bidirectional relationship between frailty and cardiovascular diseases, emphasizing how frailty not only predisposes individuals to cardiovascular diseases but also accelerates disease progression through oxidative damage and increased platelet function. Thus, oxidative stress is the central axis in the increase in platelet activation and secretion and the inadequate response to acetylsalicylic acid observed in frail people by mitochondrial mechanisms. Also, key biomarkers of oxidative stress, such as isoprostanes and derivate reactive oxygen metabolites, can be optimal predictors of cardiovascular risk and potential targets for therapeutic intervention. The potential of antioxidant therapies in mitigating oxidative stress and improving cardiovascular clinical outcomes such as platelet function is promising in frailty, although further research is necessary to establish the efficacy of these therapies. Understanding these mechanisms could prove essential in improving the health and quality of life of an aging population faced with the dual burden of frailty and cardiovascular diseases. [ABSTRACT FROM AUTHOR]

The use of low-carbon energy in power grids is essential for minimizing negative effects on the environment. Energy consumption causes environmental damage to the OECD's economy. This study aims to investigate the effect of energy consumption, population, and GDP on CO2 emissions using panel data from 17 OECD countries over the period 2000–2023. We use regression approaches, such as partial least squares and principal components, to study the effects of GDP, urban and total population, oil and nuclear use, renewable energy, and industrialization on CO2 emissions. The regression process in this study reduces the data to a two-dimensional representation using a stochastic model and estimation techniques. The findings of this empirical investigation indicate that the United States, Canada, France, Germany, Italy, Korea, Mexico, and the United Kingdom exhibit higher levels of primary energy consumption in comparison to value-added sectors, renewable–geothermal energy, and nuclear energy. We determined the effects of CO2 emissions, GDP, and energy consumption by considering these as the most significant elements. This has made it possible to reduce CO2 emissions by focusing one's attention and energy on the development of novel technologies, the use of renewable energy sources, and the execution of strategic plans. Attracting increasing attention are technological shifts that deliver enormous quantities of clean energy to combat climate change. Findings from this study can help environmentalists and policymakers better understand the role of structural change and energy consumption processes in the globalization process. [ABSTRACT FROM AUTHOR]

In orthopedics, bone drilling is a crucial part of a surgical method commonly carried out for internal fixation in bone fracture treatment. The primary purpose of bone drilling is the creation of holes for screw insertion to immobilize fractured parts. The bone drilling task depends on the orthopedist and surgeon's high level of skill and experience. This paper aimed to provide a summary of previously published review studies in the field of bone drilling. This review paper also presents a comprehensive review of the application of machine learning for bone drilling and as a future direction for automation systems. This review can also help medical surgeons and bone drillers understand the latest improvements through parameter selection and optimization strategies to reduce bone damage in bone drilling procedures. Apart from the review, bone drilling vibration data collected in a university laboratory experiment is also presented in this study. The vibration data consist of three different layers of femur cow bone, which are processed and classified using several deep learning (DL) methods such as long short-term memory (LSTM), convolutional neural network (CNN), and recurrent neural network (RNN). These DL methods are used in the bone drilling lab case study to prove that the layers of bone drilling are associated with the vibration signal and that they can be classified and predicted using DL methods. The result shows that LSTM is outperformed by CNN and RNN. [ABSTRACT FROM AUTHOR]

Hypercholesterolemia forms the background of several cardiovascular pathologies. LDL receptor-knockout (LDLR-KO) mice kept on a high-fat diet (HFD) develop high cholesterol levels and atherosclerosis (AS). Cannabinoid type 1 receptors (CB1Rs) induce vasodilation, although their role in cardiovascular pathologies is still controversial. We aimed to reveal the effects of CB1Rs on vascular function and remodeling in hypercholesterolemic AS-prone LDLR-KO mice. Experiments were performed on a newly established LDLR and CB1R double-knockout (KO) mouse model, in which KO and wild-type (WT) mice were kept on an HFD or a control diet (CD) for 5 months. The vascular functions of abdominal aorta rings were tested with wire myography. The vasorelaxation effects of acetylcholine (Ach, 1 nM–1 µM) were obtained after phenylephrine precontraction, which was repeated with inhibitors of nitric oxide synthase (NOS) and cyclooxygenase (COX), Nω-nitro-L-arginine (LNA), and indomethacin (INDO), respectively. Blood pressure was measured with the tail-cuff method. Immunostaining of endothelial NOS (eNOS) was carried out. An HFD significantly elevated the cholesterol levels in the LDLR-KO mice more than in the corresponding WT mice (mean values: 1039 ± 162 mg/dL vs. 91 ± 18 mg/dL), and they were not influenced by the presence of the CB1R gene. However, with the defect of the CB1R gene, damage to the Ach relaxation ability was moderated. The blood pressure was higher in the LDLR-KO mice compared to their WT counterparts (systolic/diastolic values: 110/84 ± 5.8/6.8 vs. 102/80 ± 3.3/2.5 mmHg), which was significantly elevated with an HFD (118/96 ± 1.9/2 vs. 100/77 ± 3.4/3.1 mmHg, p < 0.05) but attenuated in the CB1R-KO HFD mice. The expression of eNOS was depressed in the HFD WT mice compared to those on the CD, but it was augmented if CB1R was knocked out. This newly established double-knockout mouse model provides a tool for studying the involvement of CB1Rs in the development of hypercholesterolemia and atherosclerosis. Our results indicate that knocking out the CB1R gene significantly attenuates vascular damage in hypercholesterolemic mice. [ABSTRACT FROM AUTHOR]

The goal of farmers operating in a market economy is to maximize profit. In view of the changing political situation, the main social interest, in addition to food security, should be energy security. Here is a refined version of that sentence: This article examines the production efficiency of selected crops grown in the EU and how well their production can ensure both the economic security of the producers, i.e., the farmers, and Europe's energy security. In addition, it aims to determine which costs incurred in the production process have the greatest impact on productivity. The paper uses data obtained from the Cash Crop agricultural benchmarking database, covering 19 crops and 39 cost categories for each crop. The data (averaged for 2019–2021) came from 30 farms located in 11 EU member states. The DEA method and stepwise multiple regression were used. Research has shown that crops are already being grown in Europe that provide high energy efficiency in production without compromising farm performance (including oats, peas, and winter rye). Moreover, improving the involvement of certain inputs results in improved production efficiency (e.g., through spending on agricultural consulting services). In addition, crop economic efficiency, as assessed by profit with and without subsidies, was found to be strongly correlated with production efficiency. This could indicate that subsidies do not play a key role in farm efficiency within the EU. Crop productivity remains a key factor in achieving economic and energy efficiency. The significance of the findings presented in connection with the recent COVID-19 pandemic and the escalation of the armed conflict in Ukraine has led to renewed interest in EU energy security, i.e., generating as much EU energy as possible for food and non-food production. [ABSTRACT FROM AUTHOR]

Triple-negative breast cancer (TNBC) accounts for about 10-20% of all breast cancer cases and is associated with an unfavorable prognosis. Until recently, treatment options for TNBC were limited to chemotherapy. A new successful systemic treatment is immunotherapy with immune checkpoint inhibitors, but new tumor-specific biomarkers are needed to improve patient outcomes. Cannabinoids show antitumor activity in most preclinical studies in TNBC models and do not appear to have adverse effects on chemotherapy. Clinical data are needed to evaluate efficacy and safety in humans. Importantly, the endocannabinoid system is linked to the immune system and immunosuppression. Therefore, cannabinoid receptors could be a potential biomarker for immune checkpoint inhibitor therapy or a novel mechanism to reverse resistance to immunotherapy. In this article, we provide an overview of the currently available information on how cannabinoids may influence standard therapy in TNBC. [ABSTRACT FROM AUTHOR]

Workplace bullying is a critical and prevalent issue that causes serious problems in healthcare settings. However, there is little research on the factors affecting nursing students' perception of workplace bullying despite their forthcoming transition into the nursing profession. Therefore, this study aimed to identify the factors related to nursing students' perception of workplace bullying in Korea. A cross-sectional study was conducted among 242 nursing students who had experienced clinical practice. The survey questionnaire included general characteristics, perceived susceptibility and severity of bullying, and perception of workplace bullying. Data were analyzed using multiple regression analysis. In this study, the significant factors affecting nursing students' perception of workplace bullying included bullying experience in clinical practice and the perceived severity of bullying. Therefore, it is crucial for nursing managers and instructors to have a clear understanding of the bullying situations experienced by nursing students during clinical practice. We should promote the perception of workplace bullying through indirect experiences such as systematic education about workplace bullying for nursing students, which may prevent workplace bullying in clinical practice and work environments. Furthermore, a comprehensive and multifaceted approach is necessary to effectively prevent workplace bullying in clinical practice and work environments. This study reveals that systemic and persistent education and intervention to bullying may improve nursing students' perception of workplace bullying and prevent workplace bullying in clinical practice and work environments. Furthermore, this study provides basic data on the prevention and management of bullying in nursing students' clinical practice. [ABSTRACT FROM AUTHOR]

Background: Ethical competence is a key competence in nursing and the development of the competence is a central part in nursing education. During clinical studies, nursing students face ethical problems that require them to apply and develop their ethical knowledge and skills. Little is known about how ethical competence evolves during students' initial clinical placements. This study explored the development of ethical competence in first-year nursing students during their first clinical placements in nursing homes. Methods: This exploratory-descriptive qualitative study used focus group interviews to collect data and a phenomenological hermeneutical method for analysis. Twenty-eight first-year nursing students participated in six focus groups. The data were collected between March and April 2024 at Oslo Metropolitan University in Norway. Results: The naïve reading of the data involved an awareness of the students applying their prior knowledge, modifying their prior knowledge and developing skills that allowed them to manoeuvre ethical practices that, in some cases, appeared excellent and, in other cases, grim. The structural analysis identified three themes: (i) ethical competence forges in practice, (ii) ethical competence evolves at the intersection of knowledge and skills and (iii) ethical competence unfolds through meaningful discussions. A comprehensive understanding of the data was formulated as 'Being on a journey towards ethical competence'. This presents a metaphor illustrating that nursing students embark on a journey towards ethical competence; from their point of departure, their clinical experiences forge the essential waypoints along their path, knowledge and skills fuelling their navigation in rugged terrain towards their destination. Conclusions: Nursing students' ethical competence evolved in intricate ways during their initial clinical period. Being informed bystanders or participants in the care of nursing home residents in situations of ethical tension may be a unique position enabling students to evaluate care options differently from those immersed in the ward culture. The findings indicate that organised professional development in nursing homes needs to focus on more reflexively driven ways of supervising students in their first clinical study period. Educational institutions need to continue and further develop reflection-based learning activities and meeting points with students and their peers during their clinical placement periods. [ABSTRACT FROM AUTHOR]

Inflammatory bowel disease is a chronic inflammatory disease that encompasses entities such as Crohn's disease and ulcerative colitis. Its incidence has risen in newly industrialised countries over time, turning it into a global disease. Lately, studies on inflammatory bowel disease have focused on finding non-invasive and specific biomarkers. Long non-coding RNAs may play a role in the pathophysiology of inflammatory bowel disease and therefore they may be considered as potential biomarkers for this disease. In the present article, we review information in the literature on the relationship between long non-coding RNAs and inflammatory bowel disease. We especially focus on understanding the potential function of these RNAs as non-invasive biomarkers, providing information that may be helpful for future studies in the field. [ABSTRACT FROM AUTHOR]

Agricultural machinery services are an important guaranteed way to promote Conservation Agriculture. It is of great significance to study how to encourage farmers to choose agricultural machinery services to promote the standard implementation of Conservation Agriculture technology. In order to promote the implementation of Conservation Agriculture and improve the supply of agricultural machinery services, this paper identifies the stakeholders of normative Conservation Agriculture technology adoption behavior and the relationship between agricultural machinery service organizations, farmers and agriculture-related governments. An evolutionary game model was established to evaluate the decision-making characteristics of tripartite behavior and simulate the evolution trend of stakeholder behavior. The results show that agriculture-related governments, agricultural machinery service organizations and farmers can achieve evolutionarily stable strategies. The punishments and subsidies of agriculture-related governments and the supervision cost of all links of agricultural machinery social service organizations can significantly affect the behavior strategies of the three parties. The government set up reasonable subsidy and punishment mechanisms, and the agricultural machinery service organization controls the supervision cost of all links to ensure the stability of the three-party behavior strategy. This study provides theoretical guidance for scientific decision making and active cooperative development of the government, farmers and agricultural machinery service organizations and lays a foundation for countermeasures and suggestions to further promote farmers' implementation of Conservation Agriculture technology. [ABSTRACT FROM AUTHOR]

Weightlifting requires explosive strength, high speed, and flexibility. The aim of this research is to present a method based on barbell trajectory and on an anthropometric model comprised of six links for dynamic analysis and optimization of snatch lift. First, snatch lift is divided into nine stages based on barbell trajectory, velocity, and acceleration, while evaluating dynamic characteristics. Then, an anthropometric model of weightlifter which is comprised of six segments: shin, thigh, trunk, upper arm, forearm, and head is developed. Since the head accounts for more or less than 10% of body weight, it should be considered as one link of one degree of freedom. Physical properties such as mass and center of mass of each link are not given by statistical data, but by anthropometry and calculation in Solidworks program. Finally, for barbell trajectory as one of the most important performance indices in weightlifting, an optimal control problem is formulated to minimize a criterion function defined as the sum of work done by lifter during snatch lift and solved by using Pontryagin Maximum Principle (PMP). The proposed method is illustrated with case study, showing results in good agreement with ones by analysis of lifter's actual performances. It can help coach or weightlifter to improve the snatch technique. [ABSTRACT FROM AUTHOR]

The gastrointestinal (GI) tract, home to the largest microbial population in the human body, plays a crucial role in overall health through various mechanisms. Recent advancements in research have revealed the potential implications of gut-brain and vice-versa communication mediated by gut-microbiota and their microbial products in various diseases including type-2 diabetes and Alzheimer's disease (AD). AD is the most common type of dementia where most of cases are sporadic with no clearly identified cause. However, multiple factors are implicated in the progression of sporadic AD which can be classified as non-modifiable (e.g., genetic) and modifiable (e.g. Type-2 diabetes, diet etc.). Present review focusses on key players particularly the modifiable factors such as Type-2 diabetes (T2D) and diet and their implications in microbiota-gut-brain (MGB) and brain-gut (BG) communication and cognitive functions of healthy brain and their dysfunction in Alzheimer's Disease. Special emphasis has been given on elucidation of the mechanistic aspects of the impact of diet on gut-microbiota and the implications of some of the gut-microbial products in T2D and AD pathology. For example, mechanistically, HFD induces gut dysbiosis with driven metabolites that in turn cause loss of integrity of intestinal barrier with concomitant colonic and systemic chronic low-grade inflammation, associated with obesity and T2D. HFD-induced obesity and T2D parallel neuroinflammation, deposition of Amyloid β (Aβ), and ultimately cognitive impairment. The review also provides a new perspective of the impact of diet on brain-gut and microbiota-gut-brain communication in terms of transcription factors as a commonly spoken language that may facilitates the interaction between gut and brain of obese diabetic patients who are at a higher risk of developing cognitive impairment and AD. Other commonality such as tyrosine kinase expression and functions maintaining intestinal integrity on one hand and the phagocytic clarence by migratory microglial functions in brain are also discussed. Lastly, the characterization of the key players future research that might shed lights on novel potential pharmacological target to impede AD progression are also discussed. [ABSTRACT FROM AUTHOR]

Liver segmentation technologies play vital roles in clinical diagnosis, disease monitoring, and surgical planning due to the complex anatomical structure and physiological functions of the liver. This paper provides a comprehensive review of the developments, challenges, and future directions in liver segmentation technology. We systematically analyzed high-quality research published between 2014 and 2024, focusing on liver segmentation methods, public datasets, and evaluation metrics. This review highlights the transition from manual to semi-automatic and fully automatic segmentation methods, describes the capabilities and limitations of available technologies, and provides future outlooks. [ABSTRACT FROM AUTHOR]

Macrophages are phagocytic innate immune cells capable of phenotypical switching in response to the local microenvironment. Studies often use either primary macrophages or immortalized cell lines for hypothesis testing, therapeutic assessment, and biomaterial evaluation without carefully considering the potential effects of cell source and tissue of origin, which strongly influence macrophage response. Surprisingly, limited information is available about how, under similar stimuli, immortalized cell lines and primary cells respond in both phenotypical and functional changes. To address this need, in this work, we cultured immortalized macrophage cell lines derived from different origins (i.e., blood, lung, peritoneal) to understand and compare macrophage phenotypical responses, including polarization and plasticity, morphological changes, and phagocytic functionalities, as well as compared primary macrophages extracted from peritoneal and bone marrow to their immortalized cell line counterparts. We found significant differences in baseline expression of different markers (e.g., CD86, MHCII, CD206, and EGR2) amongst different cell lines, which further influence both polarization and repolarization of the cells, in addition to their phagocytic functionality. Additionally, we observed that, while RAW 264.7 cells behave similarly to the primary bone marrow-derived macrophages, there are noticeable phenotypical and functional differences in cell line (IC-21) and primary peritoneal macrophages, highlighting tissue-specific differences in macrophage response amongst cell lines and primary cells. Moving to three-dimensional (3D) culture in well-defined biomaterials, blood-derived primary and cell line macrophages were encapsulated within hydrogel-based synthetic extracellular matrices and their polarization profiles and cell morphologies were compared. Macrophages exhibited less pronounced polarization during 3D culture in these compliant, soft materials compared to two-dimensional (2D) culture on rigid, tissue culture plastic plates. Overall, our findings highlight origin-specific differences in macrophage response, and therefore, careful considerations must be made to identify the appropriate cell source for the application of interest. [ABSTRACT FROM AUTHOR]