Evaluation of TRPM2 Channel-Mediated Autophagic Signaling Pathway in Hippocampus and Cortex Tissues of Rat Offspring Following Prenatal Exposure to Elevated Alcohol Levels.

Fetal alcohol syndrome (FAS) can occur because of high amount of alcohol intake during pregnancy and is characterized by both physical and neurological problems. Children diagnosed with FAS have difficulties in learning, memory, and coordination. Hippocampus has a major role in memory and learning.

Detecting Cerebral Ischemia From Electroencephalography During Carotid Endarterectomy Using Machine Learning.

Monitoring cerebral neuronal activity via electroencephalography (EEG) during surgery can detect ischemia, a precursor to stroke. However, current neurophysiologist-based monitoring is prone to error. In this study, we evaluated machine learning (ML) for efficient and accurate ischemia detection.

A Bayesian System to Detect and Track Outbreaks of Influenza-Like Illnesses Including Novel Diseases: Algorithm Development and Validation.

Background:  The early identification of outbreaks of both known and novel influenza-like illnesses (ILIs) is an important public health problem.

Objective:  This study aimed to describe the design and testing of a tool that detects and tracks outbreaks of both known and novel ILIs, such as the SARS-CoV-2 worldwide pandemic, accurately and early.

Methods:  This paper describes the ILI Tracker algorithm that first models the daily occurrence of a set of known ILIs in hospital emergency departments in a monitored region using findings extracted from patient care reports using natural language processing.

Time-Series Aware Metrics for the Evaluation of Intraoperative Electroencephalography-Based Ischemia Detection.

Continuous intraoperative monitoring with electroencephalo2 graphy (EEG) is commonly used to detect cerebral ischemia in high-risk surgical procedures such as carotid endarterectomy. Machine learning (ML) models that detect ischemia in real time can form the basis of automated intraoperative EEG monitoring. In this study, we describe and compare two time-series aware precision and recall metrics to the classical precision and recall metrics for evaluating the performance of ML models that detect ischemia.

Melatonin Derivative-Conjugated Formulations of Pd(II) and Pt(II) Thiazoline Complexes on Mesoporous Silica to Enhance Cytotoxicity and Apoptosis against HeLa Cells.

The search for alternatives to cisplatin has led to the development of new metal complexes where thiazoline derivatives based on platinum(II) and palladium(II) stand out. In this sense, the Pt(II) and Pd(II) complexes coordinated with the thiazoline derivative ligand 2-(3,4-dichlorophenyl)imino-N-(2-thiazolin-2-yl)thiazolidine (TdTn), with formula [PtCl(TdTn)] and [PdCl(TdTn)], have previously shown good results against several cancer lines; however, in this work, we have managed to improve their activity by supporting them on mesoporous silica nanoparticles (MSN). The incorporation of metal compounds with a melatonin derivative (5-methoxytryptamine, 5MT), which is a well-known antioxidant and apoptosis inducer in different types of cancer, has been able to increase the cytotoxic activity of both MSN-supported and isolated complexes with only a very low amount (0.

The US COVID-19 and Influenza Scenario Modeling Hubs: Delivering long-term projections to guide policy.

Between December 2020 and April 2023, the COVID-19 Scenario Modeling Hub (SMH) generated operational multi-month projections of COVID-19 burden in the US to guide pandemic planning and decision-making in the context of high uncertainty. This effort was born out of an attempt to coordinate, synthesize and effectively use the unprecedented amount of predictive modeling that emerged throughout the COVID-19 pandemic. Here we describe the history of this massive collective research effort, the process of convening and maintaining an open modeling hub active over multiple years, and attempt to provide a blueprint for future efforts.

Antioxidant potential of nanomaterials.

Background/aim: The novel field of nanomaterials allows infinite possibilities in order to create antioxidant therapies. The present review is aimed to describe the state of art concerning on nanomaterials and their effects on reactive oxygen species (ROS) production. A wide range of nanoparticles has been designed for this purpose, and each one possesses some particular characteristics which allow these significant antioxidant results.

Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty.

Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.

Efficient Analysis of Proteome-Wide FPOP Data by FragPipe.

Monitoring protein structure before and after environmental alterations (e.g., different cell states) can give insights into the role and function of proteins.

Selenium Protects ARPE-19 and ACBRI 181 Cells against High Glucose-Induced Oxidative Stress.

Diabetic retinopathy (DR), a complication of diabetes mellitus (DM), can cause severe visual loss. The retinal pigment epithelium (RPE) plays a crucial role in retinal physiology but is vulnerable to oxidative damage. We investigated the protective effects of selenium (Se) on retinal pigment epithelium (ARPE-19) and primary human retinal microvascular endothelial (ACBRI 181) cells against high glucose (HG)-induced oxidative stress and apoptotic cascade.

Informing pandemic response in the face of uncertainty. .

Our ability to forecast epidemics more than a few weeks into the future is constrained by the complexity of disease systems, our limited ability to measure the current state of an epidemic, and uncertainties in how human action will affect transmission. Realistic longer-term projections (spanning more than a few weeks) may, however, be possible under defined scenarios that specify the future state of critical epidemic drivers, with the additional benefit that such scenarios can be used to anticipate the comparative effect of control measures. Since December 2020, the U.

Efficient Analysis of Proteome-wide FPOP Data by FragPipe.

Monitoring protein structure before and after perturbations can give insights into the role and function of proteins. Fast photochemical oxidation of proteins (FPOP) coupled with mass spectrometry (MS) allows monitoring of structural rearrangements by exposing proteins to OH radicals that oxidize solvent accessible residues, indicating protein regions undergoing movement. Some of the benefits of FPOP include high throughput and lack of scrambling due to label irreversibility.

A Bayesian System to Track Outbreaks of Influenza-Like Illnesses Including Novel Diseases.

It would be highly desirable to have a tool that detects the outbreak of a new influenza-like illness, such as COVID-19, accurately and early. This paper describes the algorithm that first models the daily occurrence of a set of known influenza-like illnesses in a hospital emergency department using findings extracted from patient-care reports using natural language processing. We include results based on modeling the diseases influenza, respiratory syncytial virus, human metapneumovirus, and parainfluenza for five emergency departments in Allegheny County Pennsylvania from June 1, 2010 through May 31, 2015.

Cytotoxic Effects of New Palladium(II) Complexes with Thiazine or Thiazoline Derivative Ligands in Tumor Cell Lines.

The synthesis of analogs of cisplatin, which is a widely used chemotherapeutic agent, using other metal centers could be an alternative for cancer treatment. Pd(II) could be a substitute for Pt(II) due to its coordination chemistry similarity. For that reason, six squared-planar Pd(II) complexes with thiazine and thiazoline ligands and formula [PdCl(L)] were synthesized and characterized in this work.

Coping with Oxidative Stress in Reproductive Pathophysiology and Assisted Reproduction: Melatonin as an Emerging Therapeutical Tool.

Infertility is an increasing global public health concern with socio-psychological implications for affected couples. Remarkable advances in reproductive medicine have led to successful treatments such as assisted reproductive techniques (ART). However, the search for new therapeutic tools to improve ART success rates has become a research hotspot.

Pro-Apoptotic and Anti-Migration Properties of a Thiazoline-Containing Platinum(II) Complex in MDA-MB-231 Breast Cancer Cells: The Role of Melatonin as a Synergistic Agent.

Triple-negative breast cancer (TNBC) is an aggressive cancer insensitive to hormonal and human epidermal growth factor receptor 2 (HER2)-targeted therapies and has a poor prognosis. Therefore, there is a need for the development of convenient anticancer strategies for the management of TNBC. In this paper, we evaluate the antitumoral potential of a platinum(II) complex coordinated with the ligand 2-(3,5-diphenylpyrazol-1-yl)-2-thiazoline (DPhPzTn), hereafter PtDPhPzTn, against the TNBC cell line MDA-MB-231, and compared its effect with both cisplatin and its less lipophilic counterpart PtPzTn, the latter containing the ligand 2-(pyrazol-1-yl)-2-thiazoline (PzTn).

Impact of SARS-CoV-2 vaccination of children ages 5-11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021-March 2022: a multi-model study.

Background: SARS-CoV-2 vaccination of persons aged 12 years and older has reduced disease burden in the United States. The COVID-19 Scenario Modeling Hub convened multiple modeling teams in September 2021 to project the impact of expanding vaccine administration to children 5-11 years old on anticipated COVID-19 burden and resilience against variant strains.

Methods: Nine modeling teams contributed state- and national-level projections for weekly counts of cases, hospitalizations, and deaths in the United States for the period September 12, 2021 to March 12, 2022.

Influence of ligand lipophilicity in Pt(II) complexes on their antiproliferative and apoptotic activities in tumour cell lines.

One of the most widely used strategies for drug development is the coordination of bioactive ligands to transition metals, which could improve biological activity. Moreover, the incorporation of aromatic groups to ligands may allow an enhanced lipophilicity that can influence the cellular uptake and accumulation of the metallodrugs, thus increasing their activity. Herein, we have reported the synthesis and characterization of four Pt(II) complexes [PtCl(L)], where L = 2-(1-pyrazolyl)-2-thiazoline (PzTn), 2-(1-pyrazolyl)-1,3-thiazine (PzTz), 2-(3,5-diphenyl-1-pyrazolyl)-2-thiazoline (DPhPzTn) or 2-(3,5-diphenyl-1-pyrazolyl)-1,3-thiazine (DPhPzTz).

Bayesian multitrait kernel methods improve multienvironment genome-based prediction.

When multitrait data are available, the preferred models are those that are able to account for correlations between phenotypic traits because when the degree of correlation is moderate or large, this increases the genomic prediction accuracy. For this reason, in this article, we explore Bayesian multitrait kernel methods for genomic prediction and we illustrate the power of these models with three-real datasets. The kernels under study were the linear, Gaussian, polynomial, and sigmoid kernels; they were compared with the conventional Ridge regression and GBLUP multitrait models.