Risk prediction models for ovarian hyperstimulation syndrome: a systematic review and meta-analysis.

Background: Ovarian hyperstimulation syndrome (OHSS) is a serious complication of controlled ovarian stimulation (COS). The main clinical manifestation of OHSS is increased ovarian volume. OHSS can cause local and systemic tissue oedema, electrolyte disturbances, cardiorespiratory dysfunction, coagulation dysfunction, and other symptoms.

Risk Prediction Models for Perioperative Hypothermia: A Systematic Review.

Background: Perioperative hypothermia is a frequent complication causing patient discomfort and increasing risks like surgical site infection, coagulation dysfunction, slow drug metabolism, cardiovascular events, and prolonged hospitalization, which severely affect prognosis. Due to its significant impact, this study systematically reviews and evaluates existing risk prediction models for perioperative hypothermia. The aim is to provide clinical staff with a reference for selecting or developing an appropriate prediction model.

Guard-cell expression of abscisic acid receptors for engineering water-use-efficient plants without trade-offs in growth.

Abscisic acid (ABA) induces stomatal closure, reducing transpirational water loss, a critical adaptation for agriculture under drought. However, ABA is often viewed cautiously as stomatal closure limits CO uptake for photosynthesis and growth. We have demonstrated that ectopic expression of selected ABA receptors in Arabidopsis reduces transpiration without growth penalty, thus achieving high water use efficiency (WUE).

PLK1-mediated PDHA1 phosphorylation drives mitochondrial dysfunction, mitophagy, and cancer progression in Cr(VI)-associated lung cancer.

Hexavalent chromium (Cr(VI)) is a class I environmental carcinogen that induces lung epithelial cell transformation and promotes lung cancer progression by altering cell cycle regulation and cellular energy metabolism. In this study, we investigated the role of polo-like kinase 1 (PLK1) in Cr(VI)-transformed (CrT) bronchial epithelial cells (BEAS-2B) and found that PLK1 expression was significantly upregulated in these cells, leading to impaired mitochondrial function and enhanced mitophagy, which in turn stimulated cell proliferation both in vitro and in vivo. Mechanistically, we demonstrated that PLK1 directly phosphorylates the pyruvate dehydrogenase E1 subunit alpha 1 (PDHA1) at Thr57, leading to its destabilization and disruption of pyruvate dehydrogenase complex (PDHc) integrity.

Comparing Text-Based Clinical Risk Prediction in Critical Care: A Note-Specific Hierarchical Network and Large Language Models.

Clinical predictive analysis is a crucial task with numerous applications and has been extensively studied using machine learning approaches. Clinical notes, a vital data source, have been employed to develop natural language processing (NLP) models for risk prediction in healthcare with robust performance. However, clinical notes vary considerably in text composition-written by diverse healthcare providers for different purposes-and the impact of these variations on NLP modeling is also underexplored.

Effects of preservatives and drying methods on the nutrient composition and mould counts of hay and pellet processing of Oats.

The aim of this study was to investigate the effects of different preservatives and drying methods on the nutrient composition and mould counts of oat hay and oat pellets. Oat hay and oat pellets were divided into 5 groups: CON (without additives, control), CAP (with 5% calcium propionate), CUR (with 5% curcumin), SKU (with 5% Scutellaria baicalensis) and KC (with 2% potassium carbonate). The nutrients and mould counts of each group were determined after air drying, drying at 50 °C and drying at 50 °C with forced air for 48 h and 96 h, respectively.

Therapeutic targeting of the p300/CBP bromodomain enhances the efficacy of immune checkpoint blockade therapy.

Blockade of immune checkpoints, such as programmed death-ligand 1 (PD-L1), has shown promise in cancer treatment; however, clinical response remains limited in many cancer types. Our previous research demonstrated that p300/CBP mediates the acetylation of the PD-L1 promoter, regulating PD-L1 expression. In this study, we further investigated the role of the p300/CBP bromodomain in regulating PD-L1 expression using CCS1477, a selective bromodomain inhibitor developed by our team.

Diagnostic Value of PET Tracers in Differentiating Glioma Tumor Recurrence from Treatment-Related Changes: A Systematic Review and Meta-Analysis.

Background: It is often difficult to identify treatment-related changes (TRC) from tumor progression (TP) in patients with glioma, and the current application of PET scanning is expected to improve the diagnosis.

Purpose: We used a systematic review and meta-analysis to reveal diagnostically more promising tracers by comparing the diagnostic accuracy of different PET tracers in identifying TRC and TP in patients with glioma.

Data Sources: We searched PubMed, Web of Science, and EMBASE databases, and we selected studies that used PET scans to identify TP and TRC in patients with glioma.

Artesunate enhances the efficacy of enzalutamide in advanced prostate cancer.

Prostate cancer (PCa) is one of the leading causes of death among men worldwide. Treatments targeting the androgen receptor pathway remain the standard therapy for PCa patients. Enzalutamide (ENZ), a second-generation androgen receptor inhibitor, was developed to treat castration-resistant prostate cancer.

Label-Free Proteomics Reveals the Response of Oat ( L.) Seedling Root Respiratory Metabolism to Salt Stress.

Soil salinity is among the crucial factors influencing agricultural productivity of crops, including oat. The respiratory metabolic pathways are of great significance for plants to adapt to salt stress, but current research is limited and there are few reports on salt-tolerant crops such as oat, which is necessary to conduct in-depth research. In this study, we conducted a pot experiment to determine the effects of salt stress on oat root growth and respiratory metabolism.

Pharmacodynamics, pharmacokinetics, and toxicology of Fc-growth hormone fusion protein in macaques.

Purpose: Growth hormone (GH) therapy for GH deficiency is used to treat multiple conditions. However, the short half-life of GH necessitates frequent dosing, which limits patient adherence. Fc fusion proteins, created by binding an active peptide to the Fc portion of IgG, are known to prolong the plasma half-life of the peptide.

The kinase PLK1 promotes Hedgehog signaling-dependent resistance to the antiandrogen enzalutamide in metastatic prostate cancer.

Enzalutamide, a second-generation androgen receptor inhibitor (also known as an antiandrogen), is used to treat patients with metastatic castration-resistant prostate cancer (CRPC). Tumors often acquire resistance to enzalutamide. Tumor progression and enzalutamide resistance are associated with decreased abundance of the tumor suppressor PDCD4.

Utilizing Multi-Omics Analysis to Elucidate the Molecular Mechanisms of Oat Responses to Drought Stress.

The oat is a crop and forage species with rich nutritional value, capable of adapting to various harsh growing environments, including dry and poor soils. It plays an important role in agricultural production and sustainable development. However, the molecular mechanisms underlying the responses of oat to drought stress remain unclear, warranting further research.

Emerging translocator protein-positron emission tomographic imaging improves detection of focal cortical dysplasia.

Objective: The identification of epileptic lesions is crucial for improving surgical outcomes. Nevertheless, substantial focal cortical dysplasia (FCD) may be invisible on magnetic resonance imaging (MRI). We aimed to characterize the expression pattern of 18-kDa translocator protein (TSPO) in FCD and to evaluate the effectiveness of this inflammation-reflective molecular imaging technique for detecting FCD.

Flood vulnerability assessment in the Ili River Basin based on the comprehensive symmetric Kullback-Leibler distance.

In vulnerability assessments, accurately determining the indicator weights is essential to ensure the results' precision and reliability. This paper proposes an optimized comprehensive symmetric Kullback-Leibler (K-L) distance weighting method, in which the comprehensive symmetric K-L distance for each indicator is calculated using a grid-based approach, and the normalized distance serves as the weight for each indicator. ArcGIS software was employed to assess the Ili River Basin flood vulnerability as a case study.

Predictive value of the neutrophil-to-lymphocyte ratio for epidural labor analgesia-associated intrapartum fever: a retrospective single-center study.

Background: Studies have indicated that epidural analgesia increases the risk of maternal fever during labor, possibly due to non-infectious inflammation. The neutrophil-to-lymphocyte ratio (NLR) is a crucial indicator of inflammation, with a higher NLR potentially signaling worse patient adverse outcomes. The present study explores whether NLR has clinical predictive value for epidural analgesia-related maternal fever (ERMF).

Generating synthetic clinical text with local large language models to identify misdiagnosed limb fractures in radiology reports.

Large language models (LLMs) demonstrate impressive capabilities in generating human-like content and have much potential to improve the performance and efficiency of healthcare. An important application of LLMs is to generate synthetic clinical reports that could alleviate the burden of annotating and collecting real-world data in training AI models. Meanwhile, there could be concerns and limitations in using commercial LLMs to handle sensitive clinical data.

Development and validation of a deep learning-based survival prediction model for pediatric glioma patients: A retrospective study using the SEER database and Chinese data.

Objective: Develop a time-dependent deep learning model to accurately predict the prognosis of pediatric glioma patients, which can assist clinicians in making precise treatment decisions and reducing patient risk.

Study Design: The study involved pediatric glioma patients from the Surveillance, Epidemiology, and End Results (SEER) Registry (2000-2018) and Tangdu Hospital in China (2010-2018) within specific time frames. For training, we selected two neural network-based algorithms (DeepSurv, neural multi-task logistic regression [N-MTLR]) and one ensemble learning-based algorithm (random survival forest [RSF]).

Prognostic Factors for Patients with Primary Gliosarcoma: A Single-Center Retrospective Study.

Background: Primary gliosarcoma is a rare form of malignant central nervous system tumor, with limited understanding regarding its prognostic determinants and effective therapeutic interventions.

Methods: The medical records of patients diagnosed with gliosarcoma at Tangdu Hospital between March 2011 and June 2023 were retrospectively analyzed in this study. Patients with a prior history of glioma or those who received preoperative chemoradiotherapy were excluded.

Predicting the Risk of In-Hospital Mortality in Traumatic Brain Injury Patients on Invasive Mechanical Ventilation in the Intensive Care Unit: Construction and Validation of an Online Nomogram.

Objective: To explore mortality risk factors and to construct an online nomogram for predicting in-hospital mortality in traumatic brain injury (TBI) patients receiving invasive mechanical ventilation (IMV) in intensive care unit (ICU).

Methods: We retrospectively analyzed TBI patients on IMV in ICU from Medical Information Mart for Intensive Care IV database and 2 hospitals. Least absolute shrinkage and selection operation regression and multiple logistic regression were used to detect predictors of in-hospital mortality and to construct an online nomogram.

Risk Factors and Predictive Nomogram for Survival in Elderly Patients with Brain Glioma.

Objective: To determine the factors that contribute to the survival of elderly individuals diagnosed with brain glioma and develop a prognostic nomogram.

Methods: Data from elderly individuals (age ≥65 years) histologically diagnosed with brain glioma were sourced from the Surveillance, Epidemiology, and End Results (SEER) database. The dataset was randomly divided into a training cohort and an internal validation cohort at a 6:4 ratio.