The effect of a mindfulness-based cognitive therapy program on the spiritual health of mothers of infants admitted to the neonatal intensive care unit.

Introduction: The birth and admission of a premature infant to the NICU is often an unexpected experience and a mental and spiritual challenge for families. Spiritual health is an influential factor affecting how a mother faces and endures a stressful situation. Improving the mother's spiritual health requires cognitive therapy approaches, including mindfulness techniques.

Predictive modeling of air quality in the Tehran megacity via deep learning techniques.

Air pollution is a significant challenge in metropolitan areas, where increasing amounts of air pollutants threaten public health and environmental safety. The present study aims to forecast the concentrations of various air pollutants, including CO, O, NO, SO, PM, and PM, from 2013 to 2023 in the Tehran megacity, Iran, via deep learning (DL) models and evaluate their effectiveness over conventional machine learning (ML) methods. Key driving variables, including temperature, relative humidity, dew point, wind speed, and air pressure, were considered.

Myrtenol-loaded niosomes can prevent lung ischemia-reperfusion injury model in rats by balancing the Nrf2/Keap1 and NF-κB signaling pathways.

Lung Ischemia-reperfusion injury (LIRI) is a risk during lung transplantation that can cause acute lung injury and organ failure. In LIRI, the NF-E2-related factor 2(Nrf2)/ Kelch-like ECH-associated protein 1 (Keap1) signaling pathway and the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling pathway are two major pathways involved in regulating oxidative stress and inflammation, respectively. Myrtenol, a natural compound with anti-inflammatory and antioxidant properties, has potential protective effects against IRI.

Application of the Lasso regularisation technique in mitigating overfitting in air quality prediction models.

As a significant global concern, air pollution triggers enormous challenges in public health and ecological sustainability, necessitating the development of precise algorithms to forecast and mitigate its impacts, which has led to the development of many machine learning (ML)-based models for predicting air quality. Meanwhile, overfitting is a prevalent issue with ML algorithms that decreases their efficacy and generalizability. The present investigation, using an extensive collection of data from 16 sensors in Tehran, Iran, from 2013 to 2023, focuses on applying the Least Absolute Shrinkage and Selection Operator (Lasso) regularisation technique to enhance the forecasting precision of ambient air pollutants concentration models, including particulate matter (PM and PM), CO, NO, SO, and O while decreasing overfitting.

The activation of the G-protein-coupled estrogen receptor promotes the aggressiveness of MDA-MB231 cells by targeting the IRE1α/TXNIP pathway.

Background And Purpose: This study investigated modulating the G protein-coupled estrogen receptor (GPER) on the IRElα/TXNIP pathway and its role in drug resistance in MDA-MB231 cells.

Experimental Approach: To determine the optimal concentrations of G and 4-hydroxytamoxifen (TAM), GPER expression and ERK1/2 phosphorylation were analyzed using qRT-PCR and western blotting, respectively. Cells were treated with individual concentrations of G (1000 nM), G (1000 nM), and TAM (2000 nM), as well as combinations of these treatments (G + G, TAM + G, and G + TAM) for 24 and 48 h.

Comparing machine learning approaches for estimating soil saturated hydraulic conductivity.

Characterization of near (field) saturated hydraulic conductivity (Kfs) of the soil environment is among the crucial components of hydrological modeling frameworks. Since the associated laboratory/field experiments are time-consuming and labor-intensive, pedotransfer functions (PTFs) that rely on statistical predictors are usually integrated with the existing measurements to predict Kfs in other areas of the field. In this study some of the most appropriate machine learning approaches, including variants of artificial neural networks (ANNs) were used for predicting Kfs by some easily measurable soil attributes.

The Effect of Spirulina Supplementation on Blood Pressure in Adults: A GRADE-Assessed Systematic Review and Meta-Analysis of Randomized Clinical Trials.

Previous studies have yielded controversial results regarding the effect of spirulina on blood pressure (BP), which need updating. So, this updated systematic review and meta-analysis of randomized controlled trials (RCTs) carry out a more accurate estimation of the effect of spirulina on BP in adults. This systematic searches (in PubMed/Medline, Scopus, and ISI Web of Science) until April 1, 2024, to identify related RCTs based on PICOS guidelines (population (individuals > 18 years old), the intervention (spirulina), the comparison (control or placebo group), the outcomes (systolic BP (SBP) and diastolic BP (DBP)), the study design (RCTs)), and PRISMA-checklist (Supporting Information, data S2).

Managing Select Immune-Related Adverse Events in Patients Treated with Immune Checkpoint Inhibitors.

The increased use of immune checkpoint inhibitors (ICIs) across cancer programs has created the need for standardized monitoring and management of immune-related adverse events (irAEs). Delayed recognition without appropriate treatment can have serious and life-threatening consequences. The management of irAEs presents a unique set of challenges that must be addressed at a multidisciplinary level.

Nursing educators' experiences of cultural competence in the nursing education program: A qualitative descriptive study.

Background: To meet the population's increasing diversity and the health system's needs, it is necessary to prepare nursing schools to produce culturally qualified students.

Purpose: This study aimed to extract the experiences of nursing educators about the cultural competence of nursing students.

Method: In this qualitative descriptive study, data were collected through in-depth, semi-structured interviews with 15 nursing educators affiliated with three medical sciences universities in southeastern Iran.

Effect of Virtual Education on Knowledge and Practice of Critical Care Nurses Regarding the Administration of Drugs Through Enteral Feeding Tubes: A Prospective Randomized Pre-Post Intervention Study.

A study was conducted to evaluate the effect of virtual education on knowledge and practice of nurses regarding administration of drugs through enteral feeding tubes (EFTs). Sixty nurses working in 4 intensive care units were enrolled. A questionnaire evaluating knowledge and practice of nurses regarding drug administration through EFTs was used.

LPBF Processability of NiTiHf Alloys: Systematic Modeling and Single-Track Studies.

Research into the processability of NiTiHf high-temperature shape memory alloys (HTSMAs) via laser powder bed fusion (LPBF) is limited; nevertheless, these alloys show promise for applications in extreme environments. This study aims to address this limitation by investigating the printability of four NiTiHf alloys with varying Hf content (1, 2, 15, and 20 at. %) to assess their suitability for LPBF applications.

Cross-Linked Starch as Media for Crystal Violet Elimination from Water: Modeling Batch Adsorption with Fuzzy Regression.

A scalable and cost-effective solution for removing pollutants from water is to use biodegradable and eco-friendly sorbents that are readily available such as starch. The current research explored the removal of crystal violet (CV) dye from water using chemically modified potato starch. The adsorbent was prepared by cross-linking potato starch with sodium trimetaphosphate (STMP).

The barriers and challenges of using health information technology in medication administration process for pediatrics and neonates: A qualitative study.

Background And Aims: Children and neonates are more susceptible to diseases and are a vulnerable group in medication administration (MA). Nurses interact directly with patients, ensuring safety and preventing unintended outcomes. Health Information Technology (HIT) has transformed health care, aiding nurses in decision-making and treatment responses.

A cohort study on the predictive capability of body composition for diabetes mellitus using machine learning.

Purpose: We applied machine learning to study associations between regional body fat distribution and diabetes mellitus in a population of community adults in order to investigate the predictive capability. We retrospectively analyzed a subset of data from the published Fasa cohort study using individual standard classifiers as well as ensemble learning algorithms.

Methods: We measured segmental body composition using the Tanita Analyzer BC-418 MA (Tanita Corp, Japan).

Can internship programs affect nursing students' critical thinking disposition, caring behaviors, and professional commitment?

Background: Nursing students are given opportunities to develop critical thinking disposition, caring behaviors, and professional commitment through clinical training. Therefore, nurse educators should move away from traditional methods toward new ones, such as internship programs in clinical training. This study assessed the effect of nursing internship programs on senior undergraduate nursing students' critical thinking disposition, caring behaviors, and professional commitment.

The effect of polyethylene cover intervention on ocular surface disorder of intensive care unit patients: a systematic review and meta-analysis.

Background: Polyethylene covers have been proven to be effective in protecting the eyes in patients with decreased or disappeared blink reflexes, but their advantages compared to other conventional methods are still unclear. This systematic review and meta-analysis study aimed to elucidate the impact of polyethylene covers in the prevention of ocular surface disease (OSD) in patients admitted to the intensive care unit (ICU).

Methods: We searched the Scopus, PubMed, Web of Science, and Cochrane Central Register of Controlled Trials (CENTRAL) databases to identify randomized controlled trial studies.

Rheum khorasanicum. Hydroalcoholic root extract induces cell death in human colorectal adenocarcinoma: An in vitro and in silico study.

Colorectal cancer (CRC) is the second greatest cause of cancer-related death in the world and chemotherapy, as an important part of CRC treatment, has some drawbacks, including systemic toxicity. Therefore, it is crucial to discover new and more effective CRC treatment plans. Rheum khorasanicum (R.

Predicting saturated and near-saturated hydraulic conductivity using artificial neural networks and multiple linear regression in calcareous soils.

Hydraulic conductivity (Kψ) is one of the most important soil properties that influences water and chemical movement within the soil and is a vital factor in various management practices, like drainage, irrigation, erosion control, and flood protection. Therefore, it is an essential component in soil monitoring and managerial practices. The importance of Kψ in soil-water relationship, difficulties for its measurement in the field, and its high variability led us to evaluate the potential of stepwise multiple linear regression (SMLR), and multilayer perceptron (MLPNNs) and radial-basis function (RBFNNs) neural networks approaches to predict Kψ at tensions of 15, 10, 5, and 0 cm (K15, K10, K5, and K0, respectively) using easily measurable attributes in calcareous soils.

Structure-Based Drug Design for Targeting IRE1: An in Silico Approach for Treatment of Cancer.

Background: Endoplasmic Reticulum (ER) stress and Unfolded Protein Response (UPR) play a key role in cancer progression. The aggregation of incorrectly folded proteins in the ER generates ER stress, which in turn activates the UPR as an adaptive mechanism to fix ER proteostasis. Inositol-requiring enzyme 1 (IRE1) is the most evolutionary conserved ER stress sensor, which plays a pro-tumoral role in various cancers.

The effect of scenario-based training on the Core competencies of nursing students: a semi-experimental study.

Introduction: Competency is defined as the variety of skills and knowledge required to perform a specific task. Due to the specificity of pediatric nursing, students face some challenges in acquiring core competencies. Therefore, the use of new training methods in pediatric nursing is necessary.

Impact of a 50bp insertion/deletion polymorphism of the superoxide dismutase-1 on oxidative stress status and risk of keratoconus.

Keratoconus (KC) is characterized by the predominant primary ectatic disease, affecting the cornea, necessitating corneal transplants in some cases. While some loci associated with KC risk have been identified, the understanding of the disease remains limited. Superoxide dismutase (SOD) enzymes play a crucial role in countering the reactive oxygen species and providing protection against oxidative stress (OS).

Lithium and zinc levels along with oxidative status in myocardial infarction: A case-control study.

Background: Coronary artery disease (CAD) and myocardial infarction (MI) are the most prevalent diseases globally. While several risk factors for MI are well assessed, the influence of trace elements on MI has not been thoroughly studied. This study aimed to evaluate lithium (Li) and zinc (Zn) levels in MI patients and healthy control and assess their relationship with oxidative stress (OS) parameters, such as nitric oxide (NO) and total antioxidant capacity (TAC).

Preparation and Evaluation of Preventive Effects of Inhalational and Intraperitoneal Injection of Myrtenol Loaded Nano-Niosomes on Lung Ischemia-Reperfusion Injury in Rats.

Introduction: Ischemia-reperfusion injury (IRI) is directly related to forming reactive oxygen species, endothelial cell injury, increased vascular permeability, and the activation of neutrophils and cytokines. Niosomes are nanocarriers and an essential part of drug delivery systems. We aimed to investigate the effects of myrtenol's inhaled and intraperitoneal niosomal form, compared to its simple form, on lung ischemia reperfusion injury (LIRI).