Altered Mechanobiology of PDAC Cells with Acquired Chemoresistance to Gemcitabine and Paclitaxel.

: Pancreatic ductal adenocarcinoma acquired resistance to chemotherapy poses a major limitation to patient survival. Despite understanding some biological mechanisms of chemoresistance, much about those mechanisms remains to be uncovered. Mechanobiology, which studies the physical properties of cells, holds promise as a potential target for addressing the challenges of chemoresistance in PDAC.

A spatial analysis of power-dependent medical equipment and extreme weather risk in the southeastern United States.

Extreme weather events endanger critical health infrastructure, and many individuals rely on infrastructure to meet their basic needs, such as heat, water, and medical devices. The purpose of this study is to identify spatially explicit at-risk populations for power outages due to these extreme weather events. To accomplish this, we used the HHS emPOWER Emergency Planning Dataset, which was created to help public health authorities plan for and address the needs of communities.

Do Chemformers Dream of Organic Matter? Evaluating a Transformer Model for Multistep Retrosynthesis.

Synthesis planning of new pharmaceutical compounds is a well-known bottleneck in modern drug design. Template-free methods, such as transformers, have recently been proposed as an alternative to template-based methods for single-step retrosynthetic predictions. Here, we trained and evaluated a transformer model, called the Chemformer, for retrosynthesis predictions within drug discovery.

Frailty in severe COVID-19 survivors after ICU admission. A prospective and multicenter study in Mexico.

Objective: To analyze the presence of frailty in survivors of severe COVID-19 admitted in the Intensive Care Unit (ICU) and followed six months after discharge.

Design: An observational, prospective and multicenter, nation-wide study.

Setting: Eight adult ICU across eight academic acute care hospitals in Mexico.

Cohort profile: evaluation of immune response and household transmission of SARS-CoV-2 in Costa Rica: the RESPIRA study.

Purpose: The RESPIRA cohort aims to describe the nature, magnitude, time course and efficacy of the immune response to SARS-CoV-2 infection and vaccination, population prevalence, and household transmission of COVID-19.

Participants: From November 2020, we selected age-stratified random samples of COVID-19 cases from Costa Rica confirmed by PCR. For each case, two population-based controls, matched on age, sex and census tract were recruited, supplemented with hospitalised cases and household contacts.

Effectiveness of Cannabidiol to Manage Chronic Pain: A Systematic Review.

Objectives: Cannabidiol (CBD), a component in Cannabis, is used to treat seizures, anxiety, and pain. Little is known about how effectively CBD works in managing chronic pain, a condition characterized by discomfort that persists beyond 3-6 months or beyond expected normal healing. Therefore, this systematic review aimed to synthesize evidence on the effectiveness of CBD in chronic pain management.

Outbreak of Locally Acquired Mosquito-Transmitted (Autochthonous) Malaria - Florida and Texas, May-July 2023.

Eight cases of locally acquired, mosquito-transmitted (i.e., autochthonous) Plasmodium vivax malaria, which has not been reported in the United States since 2003, were reported to CDC from state health departments in Florida and Texas during May 18-July 17, 2023.

Data Sharing in Chemistry: Lessons Learned and a Case for Mandating Structured Reaction Data.

The past decade has seen a number of impressive developments in predictive chemistry and reaction informatics driven by machine learning applications to computer-aided synthesis planning. While many of these developments have been made even with relatively small, bespoke data sets, in order to advance the role of AI in the field at scale, there must be significant improvements in the reporting of reaction data. Currently, the majority of publicly available data is reported in an unstructured format and heavily imbalanced toward high-yielding reactions, which influences the types of models that can be successfully trained.

Optimized quantification of intra-host viral diversity in SARS-CoV-2 and influenza virus sequence data.

High error rates of viral RNA-dependent RNA polymerases lead to diverse intra-host viral populations during infection. Errors made during replication that are not strongly deleterious to the virus can lead to the generation of minority variants. However, accurate detection of minority variants in viral sequence data is complicated by errors introduced during sample preparation and data analysis.

Genetic characterization of Dibothriocephalus latus and Dibothriocephalus dendriticus (Cestoda: Diphyllobothriidae) from Chile based on haplotype analysis using mitochondrial DNA markers.

Dibothriocephalus latus and Dibothriocephalus dendriticus are found throughout the temperate and sub-arctic zones of the northern hemisphere, but they are also found in the southern core countries of South America, Chile and Argentina. Genetic characteristics of D. latus and D.

Silica Nanoparticles in Xanthan Gum Solutions: Oil Recovery Efficiency in Core Flooding Tests.

Polymer flooding is one of the enhanced oil recovery (EOR) methods that increase the macroscopic efficiency of the flooding process and enhanced crude oil recovery. In this study, the effect of silica nanoparticles (NP-SiO) in xanthan gum (XG) solutions was investigated through the analysis of efficiency in core flooding tests. First, the viscosity profiles of two polymer solutions, XG biopolymer and synthetic hydrolyzed polyacrylamide (HPAM) polymer, were characterized individually through rheological measurements, with and without salt (NaCl).

Optimized Quantification of Intrahost Viral Diversity in SARS-CoV-2 and Influenza Virus Sequence Data.

Unlabelled: High error rates of viral RNA-dependent RNA polymerases lead to diverse intra-host viral populations during infection. Errors made during replication that are not strongly deleterious to the virus can lead to the generation of minority variants. However, accurate detection of minority variants in viral sequence data is complicated by errors introduced during sample preparation and data analysis.

Using a stakeholder-engaged, iterative, and systematic approach to adapting collaborative decision skills training for implementation in VA psychosocial rehabilitation and recovery centers.

Background: Adaptation of interventions is inevitable during translation to new populations or settings. Systematic approach to adaptation can ensure that fidelity to core functions of the intervention are preserved while optimizing implementation feasibility and effectiveness for the local context. In this study, we used an iterative, mixed methods, and stakeholder-engaged process to systematically adapt Collaborative Decision Skills Training for Veterans with psychosis currently participating in VA Psychosocial Rehabilitation and Recovery Centers.

Stable Cuprous Hydroxide Nanostructures by Organic Ligand Functionalization.

Copper compounds have been extensively investigated for diverse applications. However, studies of cuprous hydroxide (CuOH) have been scarce due to structural metastability. Herein, a facile, wet-chemistry procedure is reported for the preparation of stable CuOH nanostructures via deliberate functionalization with select organic ligands, such as acetylene and mercapto derivatives.

Drug Design Using Reinforcement Learning with Graph-Based Deep Generative Models.

Machine learning provides effective computational tools for exploring the chemical space via deep generative models. Here, we propose a new reinforcement learning scheme to fine-tune graph-based deep generative models for molecular design tasks. We show how our computational framework can successfully guide a pretrained generative model toward the generation of molecules with a specific property profile, even when such molecules are not present in the training set and unlikely to be generated by the pretrained model.

Impacts of ruthenium valence state on the electrocatalytic activity of ruthenium ion-complexed graphitic carbon nitride/reduced graphene oxide nanosheets towards hydrogen evolution reaction.

Design and engineering of effective electrode catalysts represents a critical first step for hydrogen production by electrochemical water splitting. Nanocomposites based on ruthenium atomically dispersed within a carbon scaffold have emerged as viable candidates. In the present study, ruthenium metal centers are atomically embedded within graphitic carbon nitride/reduced graphene oxide nanosheets by thermal refluxing.

Leishmania (Viannia) guyanensis Causing Localized Cutaneous Leishmaniasis in a Traveler.

We report on a 66-year-old male who presented for evaluation of rapidly expanding lesions on his lower extremities. He first noticed these lesions following a trip to Costa Rica, in which he was bitten by several unidentified bugs. He was initially treated empirically with antibiotics in the outpatient setting with no improvement of his symptoms.

mHealth video gaming for human papillomavirus vaccination among college men-qualitative inquiry for development.

Background: Human papillomavirus (HPV) is the most common sexually transmitted infection in the United States. Persistent infection with HPV can cause various cancers; however, HPV vaccination can prevent infections associated with high risk, cancerous strains of the virus. As it relates to HPV, college age men have been identified as one of the catch-up vaccination groups.

Ultrafast Preparation of Nonequilibrium FeNi Spinels by Magnetic Induction Heating for Unprecedented Oxygen Evolution Electrocatalysis.

Carbon-supported nanocomposites are attracting particular attention as high-performance, low-cost electrocatalysts for electrochemical water splitting. These are mostly prepared by pyrolysis and hydrothermal procedures that are time-consuming (from hours to days) and typically difficult to produce a nonequilibrium phase. Herein, for the first time ever, we exploit magnetic induction heating-quenching for ultrafast production of carbon-FeNi spinel oxide nanocomposites (within seconds), which exhibit an unprecedentedly high performance towards oxygen evolution reaction (OER), with an ultralow overpotential of only +260 mV to reach the high current density of 100 mA cm.

Effect of Silica Nanoparticles in Xanthan Gum Solutions: Evolution of Viscosity over Time.

The effect of silica nanoparticles (NP-SiO) in xanthan gum (XG) solutions was investigated through the analysis of viscosity profiles. First, hydrocolloid XG solutions and hydrophilic NP-SiO suspensions were characterized individually through rheological measurements, with and without salt (NaCl). Then, nanofluids composed of XG and NP-SiO dispersed in water and brine were studied through two different aging tests.

Photodynamic Activity of Graphene Oxide/Polyaniline/Manganese Oxide Ternary Composites toward Both Gram-Positive and Gram-Negative Bacteria.

Graphene derivatives have been attracting extensive interest as effective antimicrobial agents. In the present study, ternary nanocomposites are prepared based on graphene oxide quantum dots (GOQD), polyaniline (PANI), and manganese oxides. Because of the hydrophilic GOQD and PANI, the resulting GPM nanocomposites are readily dispersible in water and upon photoirradiation at 365 nm exhibit antimicrobial activity toward both Gram-negative () and Gram-positive ().

Multivariate Characterization of Temperature Fluctuations in a Historical Building Using Energy-Efficient IoT Wireless Sensors.

Adequate thermic conditions are required for the preventive conservation of artworks, but such optimum conditions cannot always be achieved in historical buildings such as ancient churches. In those cases, it is of interest to assess the potential risk of punctual changes in indoor environments that can be harmful to artworks. These conditions can be assessed by means of a microclimate monitoring system comprised of a set of energy-efficient wireless sensors connected to the cloud using IoT techniques.

Exploring Graph Traversal Algorithms in Graph-Based Molecular Generation.

Here, we explore the impact of different graph traversal algorithms on molecular graph generation. We do this by training a graph-based deep molecular generative model to build structures using a node order determined via either a breadth- or depth-first search algorithm. What we observe is that using a breadth-first traversal leads to better coverage of training data features compared to a depth-first traversal.