Exploring rice tolerance to salinity and drought stresses through inoculation: understanding physiological and metabolic adaptations.

Drought and salinity are significant challenges to global food security. This study investigated the interactive impacts of inoculation with salinity and drought stresses on rice. Two greenhouse experiments were conducted.

A modified U-Net to detect real sperms in videos of human sperm cell.

Background: This study delves into the crucial domain of sperm segmentation, a pivotal component of male infertility diagnosis. It explores the efficacy of diverse architectural configurations coupled with various encoders, leveraging frames from the VISEM dataset for evaluation.

Methods: The pursuit of automated sperm segmentation led to the examination of multiple deep learning architectures, each paired with distinct encoders.

Therapeutic potential of endometrial stem cells encapsulated in alginate/gelatin hydrogel to treat of polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder in women, often leading to infertility due to anovulation. Recent advances suggest that endometrial stem cells (EnSCs) hold considerable promise for tissue regeneration, which could be pivotal in treating PCOS. To enhance the survival and stabilization of EnSCs within the ovary, the EnSCs were encapsulated in an injectable alginate/gelatin hydrogel (SC-H), which has excellent biocompatibility to support the survival of EnSCs.

Advancements in Melanoma Therapies: From Surgery to Immunotherapy.

Melanoma is defined as the most aggressive and deadly form of skin cancer. The treatment of melanoma depends on the disease stage, tumor location, and extent of its spread from its point of origin. Melanoma treatment has made significant advances, notably in the context of targeted and immunotherapies.

An artificial intelligence algorithm to select most viable embryos considering current process in IVF labs.

Background: The most common Assisted Reproductive Technology is Fertilization (IVF). During IVF, embryologists commonly perform a morphological assessment to evaluate embryo quality and choose the best embryo for transferring to the uterus. However, embryo selection through morphological assessment is subjective, so various embryologists obtain different conclusions.

Enhancing bladder cancer diagnosis through transitional cell carcinoma polyp detection and segmentation: an artificial intelligence powered deep learning solution.

Background: Bladder cancer, specifically transitional cell carcinoma (TCC) polyps, presents a significant healthcare challenge worldwide. Accurate segmentation of TCC polyps in cystoscopy images is crucial for early diagnosis and urgent treatment. Deep learning models have shown promise in addressing this challenge.

Isolation and Characterization of the Vascular Endothelial Growth Factor Receptor Targeting ScFv Antibody Fragments Derived from Phage Display Technology.

Angiogenesis, as a tumor hallmark, plays an important role in the growth and development of the tumor vasculature system. There is a huge amount of evidence suggesting that the vascular endothelial growth factor receptor (VEGFR-2)/VEGF-A axis is one of the main contributors to tumor angiogenesis and metastasis. Thus, inhibition of the VEGFR-2 signaling pathway by anti-VEGFR-2 mAb can retard tumor growth.

A novel approach toward optimal workflow selection for DNA methylation biomarker discovery.

DNA methylation is a major epigenetic modification involved in many physiological processes. Normal methylation patterns are disrupted in many diseases and methylation-based biomarkers have shown promise in several contexts. Marker discovery typically involves the analysis of publicly available DNA methylation data from high-throughput assays.

Arbuscular mycorrhizal fungi and nitric oxide alleviate cadmium phytotoxicity by improving internal detoxification mechanisms of corn plants.

Plants develop several external and internal mechanisms to increase their tolerance to heavy metals (HMs) toxicity including cadmium (Cd). Symbiosis with arbuscular mycorrhizae fungi (AMF) is one of the plants' strategies to tolerate HMs toxicity. Nitric oxide (NO), as a signaling molecule, is also involved in physiological responses of plants to various stresses.

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In this case report, a 62-year-old woman was diagnosed with lymph node metastasis from melanoma in the groin. Initially the primary tumour was unknown. The entire skin was examined without any suspicious moles.

Sex-specific association of exposure to air pollutants and Nrf2 gene expression and inflammatory biomarkers in exhaled breath of healthy adolescents.

Studies investigating the nuclear factor erythroid 2-related factor 2 (Nrf2) expression levels in the respiratory system of healthy subjects are scarce. Moreover, separate studies on the health-related outcomes of air pollution for each sex are limited. The current panel study investigated sex-specific Nrf2 expression levels and related oxidative stress and inflammatory responses among healthy adolescents exposed to PM, PM, O, and PM-bounded metals in a high traffic region.

Co-application of ACC deaminase-producing rhizobial bacteria and melatonin improves salt tolerance in common bean (Phaseolus vulgaris L.) through ion homeostasis.

A comprehensive body of scientific evidence indicates that rhizobial bacteria and melatonin enhance salt tolerance of crop plants. The overall goal of this research was to evaluate the ability of Rhizobium leguminoserum bv phaseoli to suppress salinity stress impacts in common bean treated with melatonin. Treatments included bacterial inoculations (inoculated (RI) and non-inoculated (NI)), different salinity levels (non-saline (NS), 4 (S1) and 8 (S2) dS m of NaCl) and priming (dry (PD), melatonin (PM100) and hydro (PH) priming) with six replications in growing media containing sterile sand and perlite (1:1).

Quantifying Asymmetry and Performance of Lower Limb Mechanical Muscle Function in Varsity Athletes-Using Non-Countermovement Jumps.

Stadnyk, M, Sepehri, M, Cook, M, Adeeb, S, and Westover, L. Quantifying asymmetry and performance of lower limb mechanical muscle function in varsity athletes-using non-countermovement jumps. J Strength Cond Res 37(1): 98-106, 2023-The ability to automatically quantify jump performance and lower limb muscle function in athletes would be beneficial for both training and rehabilitation purposes.

Improving vascular access creation among hemodialysis patients: An agent-based modeling and simulation approach.

Chronic kidney disease is a worldwide public health problem, and vascular access is known as hemodialysis patients' lifeline. Hemodialysis is the most common treatment for kidney replacement. The choice of vascular access should be "patient-centered.

A review on targeting tumor microenvironment: The main paradigm shift in the mAb-based immunotherapy of solid tumors.

Monoclonal antibodies (mAbs) as biological macromolecules have been remarked the large and growing pipline of the pharmaceutical market and also the most promising tool in modern medicine for cancer therapy. These therapeutic entities, which consist of whole mAbs, armed mAbs (i.e.

A Regionalization Model to Increase Equity of Access to Maternal and Neonatal Care Services in Iran.

Objectives: Access to maternal and neonatal care services (MNCS) is an important goal of health policy in developing countries. In this study, we proposed a 3-level hierarchical location-allocation model to maximize the coverage of MNCS providers in Iran.

Methods: First, the necessary criteria for designing an MNCS network were explored.

Ranking patients on the kidney transplant waiting list based on fuzzy inference system.

Background: Kidney transplantation is the best treatment for people with End-Stage Renal Disease (ESRD). Kidney allocation is the most important challenge in kidney transplantation process. In this study, a Fuzzy Inference System (FIS) was developed to rank the patients based on kidney allocation factors.

A novel approach to educate hospitalized cardiovascular disease patients about lifestyle and behavior modifications.

Background: Cardiovascular diseases (CVDs) are always considered by healthcare specialists for different reasons, including extensive prevalence, increased costs, chronicity, and high risk of death. The control of CVDs is highly influenced by behavior and lifestyle and it seems necessary to train special abilities about lifestyle and behavior modification to improve self-care skills for patients, and their caregivers. As a result, the development of effective training systems should be considered by healthcare specialists.

A comparison between the function of Serendipita indica and Sinorhizobium meliloti in modulating the toxicity of zinc oxide nanoparticles in alfalfa (Medicago sativa L.).

Zinc oxide nanoparticles (ZnO-NPs) are among the most commonly used nano-fertilizers (NF). However, elevated levels of ZnO-NPs in soil may affect plant growth and development due to its potential toxicity when accumulated in large amounts in plant tissues. This research was conducted using an in situ rhizobox system with the aims of evaluating zinc uptake from nano-zinc oxide amended rhizosphere soil by alfalfa plant and the effect of plant growth-promoting microorganisms on alleviating the phytotoxicity of ZnO-NPs.

A Comparative Overview of Epigenomic Profiling Methods.

In the past decade, assays that profile different aspects of the epigenome have grown exponentially in number and variation. However, standard guidelines for researchers to choose between available tools depending on their needs are lacking. Here, we introduce a comprehensive collection of the most commonly used bulk and single-cell epigenomic assays and compare and contrast their strengths and weaknesses.

Acute responses of airway oxidative stress, inflammation, and hemodynamic markers to ambient PM and their trace metal contents among healthy adolescences: A panel study in highly polluted versus low polluted regions.

Particulate air pollutants are known contributors to global cardiorespiratory mortality through several pathways. We examined the effects of varied exposure to PM and trace metals on biological markers of airway inflammation, oxidative stress, and hemodynamic function of young individuals living in two different exposure settings. We enrolled and followed a panel of 97 healthy nonsmoking participants aged 15-18 years living in a highly polluted metropolitan city of Tabriz (TBZ) and a much less polluted semi-urban town of Hadishahr (HDS).

A predictive framework in healthcare: Case study on cardiac arrest prediction.

Data-driven healthcare uses predictive analytics to enhance decision-making and personalized healthcare. Developing prognostic models is one of the applications of predictive analytics in medical environments. Various studies have used machine learning techniques for this purpose.

Impact of roof rain water harvesting of runoff capture and household consumption.

In recent years, the occurrence of floods is one of the most important challenges facing in Hamadan city. In the absence/inefficiency of urban drainage systems, rainwater harvesting (RWH) systems as low-impact development (LID) methods can be considered as a measure to reduce the floods. In this study, three scenarios concerning the RWH from the roof surfaces are studied to evaluate the type of the harvested water on reducing flooding.

The association of vitamin-D level with catheter-related-thrombosis in hemodialysis patients: A data mining model.

Purpose: This study aims to investigate the association of different risk factors including vitamin-D level with catheter-related-thrombosis in hemodialysis patients by applying data mining techniques.

Methods: This study used the retrospectively approach and was done based on the CRISP-DM framework. The data of 1048 hemodialysis patients of Hasheminejad Kidney Center whose first catheterization was between 2014 and 2019 was used for analysis.

Proposing a machine-learning based method to predict stillbirth before and during delivery and ranking the features: nationwide retrospective cross-sectional study.

Background: Stillbirth is defined as fetal loss in pregnancy beyond 28 weeks by WHO. In this study, a machine-learning based method is proposed to predict stillbirth from livebirth and discriminate stillbirth before and during delivery and rank the features.

Method: A two-step stack ensemble classifier is proposed for classifying the instances into stillbirth and livebirth at the first step and then, classifying stillbirth before delivery from stillbirth during the labor at the second step.