Regulatory T cell-associated gene signature correlates with prognostic risk and immune infiltration in patients with breast cancer.

Background: Regulatory T cells (Tregs) play a pivotal role in the development, prognosis, and treatment of breast cancer. This study aimed to develop a Treg-associated gene signature that contributes to predict prognosis and therapy benefits in breast cancer.

Methods: Treg-associated genes were screened based on single-cell RNA-sequencing (RNA-seq) in TISCH2 database and the bulk RNA-seq in The Cancer Genome Atlas (TCGA) database.

Comprehensive analysis of tumor immune-related gene signature for predicting prognosis, immunotherapy, and drug sensitivity in bladder urothelial carcinoma.

Background: Bladder urothelial carcinoma (BLCA) is globally recognized as a prevalent malignancy. Its treatment remains challenging due to the extensive morbidity, high mortality rates, and compromised quality of life from postoperative complications and the lack of specific molecular targets. Our aim was to establish a prognostic model to evaluate the prognostic significance, assess immunotherapy responses, and determine drug susceptibility in patients with BLCA.

GIS-based assessment of photovoltaic solar potential on building rooftops in equatorial urban areas.

Installing photovoltaic systems (PVs) on building rooftops is a viable and sustainable alternative to meet the growing demand for electricity in cities. This work develops a methodology that uses LiDAR (laser imaging detection and ranging) technology and roof footprints to obtain a three-dimensional representation of the rooftops in the urban centre of Santa Isabel (Azuay, Ecuador). This allowed the determination of characteristics such as area, slope, orientation, and received solar radiation, making it possible to calculate the rooftop's theoretical, technical, and economic photovoltaic potential.

Convergent-beam attosecond x-ray crystallography.

Sub-ångström spatial resolution of electron density coupled with sub-femtosecond to few-femtosecond temporal resolution is required to directly observe the dynamics of the electronic structure of a molecule after photoinitiation or some other ultrafast perturbation, such as by soft X-rays. Meeting this challenge, pushing the field of quantum crystallography to attosecond timescales, would bring insights into how the electronic and nuclear degrees of freedom couple, enable the study of quantum coherences involved in molecular dynamics, and ultimately enable these dynamics to be controlled. Here, we propose to reach this realm by employing convergent-beam x-ray crystallography with high-power attosecond pulses from a hard-x-ray free-electron laser.

Use of Oral and Intravenous Tranexamic Acid in Total Knee Arthroplasty and Total Hip Arthroplasty Procedures.

Introduction: Tranexamic acid (TXA) is an antifibrinolytic drug commonly used in total knee arthroplasty (TKA). Intravenous (IV) and topical TXA therapy have been extensively studied and shown to reduce blood loss, length of hospital stay, and blood transfusion rates following TKA. Despite the extensive literature regarding IV and topical TXA in orthopedics, there is a current dearth of studies analyzing oral usage.

Compact high-bandwidth single-beam optically-pumped magnetometer for biomagnetic measurement.

Optically-pumped magnetometer (OPM) has been of increasing interest for biomagnetic measurements due to its low cost and portability compared with superconducting quantum interference devices (SQUID). Miniaturized spin-exchange-relaxation-free (SERF) OPMs typically have limited bandwidth (less than a few hundred Hertz), making it difficult to measure high-frequency biomagnetic signals such as the magnetocardiography (MCG) signal of the mouse. Existing experiments mainly use SQUID systems to measure the signal.

Light-sheet microscopy enabled by a miniaturized plane illuminator.

We present a implementation method of light-sheet microscopy utilizing a highly miniaturized device that produces light-sheet illumination while immersed in the sample container. Our miniaturized plane illuminator (MPI) internally equips a two-axis beam-scanning mechanism based on a magnetostatically driven optical fiber cantilever. A light sheet is produced by fast scanning of the focused beam in an axis while the illumination plane can move in the other axis for positioning and 3D imaging.

Quantifying UV-induced photodamage for longitudinal live-cell imaging applications of deep-UV microscopy.

Deep-UV microscopy enables high-resolution, label-free molecular imaging by leveraging biomolecular absorption properties in the UV spectrum. Recent advances in UV-imaging hardware have renewed interest in this technique for quantitative live cell imaging applications. However, UV-induced photodamage remains a concern for longitudinal dynamic imaging studies.

Biochemical components of corneal stroma: a study on myopia classification based on Raman spectroscopy and deep learning methods.

The study aimed to identify differences in the biochemical composition of corneal stroma lenses across varying degrees of myopia using Raman spectrum characteristics. Corneal stroma lens samples from 38 patients who underwent small incision lens extraction (SMILE) surgery, were categorized into low (n = 9, spherical power -3.00D), moderate (n = 23, spherical power < -3.

Prognostic nomogram for overall survival of elderly esophageal cancer patients receiving neoadjuvant therapy: a population-based analysis.

Background: As the population of elderly patients with esophageal cancer (EC) increases, it becomes more important to understand the prognostic factors. The aim of the present study is to identify prognostic factors among elderly (>60 years) patients with EC receiving neoadjuvant therapy.

Methods: Patients with EC (>60 years) receiving neoadjuvant chemotherapy (nCT) or chemoradiotherapy (nCRT) diagnosed between 2004 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were included and divided into a training group and a validation group.

Muscular Performance of the Elbow Flexor and Extensor Muscles in Children With Myopathies: A Case-Control Study.

Background And Purpose: Children with myopathies often experience muscle weakness in their lower limbs. However, the upper limbs are also affected and, at the same time, play a key role in daily living activities as well as in transfers and assisted mobility using auxiliary devices. The objective was to assess the performance of the elbow flexor and extensor muscles through static and dynamic contractions in children with myopathies and in their typical peers.

IMPACT: In-Memory ComPuting Architecture based on Y-FlAsh Technology for Coalesced Tsetlin machine inference.

The increasing demand for processing large volumes of data for machine learning (ML) models has pushed data bandwidth requirements beyond the capability of traditional von Neumann architecture. In-memory computing (IMC) has recently emerged as a promising solution to address this gap by enabling distributed data storage and processing at the micro-architectural level, significantly reducing both latency and energy. In this article, we present In-Memory comPuting architecture based on Y-FlAsh technology for Coalesced Tsetlin machine inference (IMPACT), underpinned on a cutting-edge memory device, Y-Flash, fabricated on a 180 nm complementary metal oxide semiconductor (CMOS) process.

Protected memristive implementations of cryptographic functions.

Memristive technology mitigates the memory wall issue in von Neumann architectures by enabling in-memory data processing. Unlike traditional complementary metal-oxide semiconductor (CMOS) technology, memristors provide a new paradigm for implementing cryptographic functions and security considerations. While prior research explores memristors for cryptographic functions and side-channel attack vulnerabilities, our study uniquely addresses memristor-oriented countermeasures.

Neural in-memory checksums: an error detection and correction technique for safe in-memory inference.

The advent of in-memory computing has introduced a new paradigm of computation, which offers significant improvements in terms of latency and power consumption for emerging embedded AI accelerators. Nevertheless, the effect of the hardware variations and non-idealities of the emerging memory technologies may significantly compromise the accuracy of inferred neural networks and result in malfunctions in safety-critical applications. This article addresses the issue from three different perspectives.

AxLaM: energy-efficient accelerator design for language models for edge computing.

Modern language models such as bidirectional encoder representations from transformers have revolutionized natural language processing (NLP) tasks but are computationally intensive, limiting their deployment on edge devices. This paper presents an energy-efficient accelerator design tailored for encoder-based language models, enabling their integration into mobile and edge computing environments. A data-flow-aware hardware accelerator design for language models inspired by Simba, makes use of approximate fixed-point POSIT-based multipliers and uses high bandwidth memory (HBM) in achieving significant improvements in computational efficiency, power consumption, area and latency compared to the hardware-realized scalable accelerator Simba.

Secure artificial intelligence at the edge.

Sensors for the perception of multimodal stimuli-ranging from the five senses humans possess and beyond-have reached an unprecedented level of sophistication and miniaturization, raising the prospect of making man-made large-scale complex systems that can rival nature a reality. Artificial intelligence (AI) at the edge aims to integrate such sensors with real-time cognitive abilities enabled by recent advances in AI. Such AI progress has only been achieved by using massive computing power which, however, would not be available in most distributed systems of interest.

Exploring how structural forms of power shape the training of intraprofessional collaboration between family physicians and specialty physicians in outpatient workplace settings.

Introduction: Intraprofessional collaboration between family physicians (FPs) and specialist physicians (SPs) is posited to improve patient outcomes but is hindered by power dynamics. Research informing intraprofessional training on hospital wards often conceptualizes power at an interactional level. However, less is known about how social structures make these power dynamics possible.

Predicting Chlorophyll- Concentrations in the World's Largest Lakes Using Kolmogorov-Arnold Networks.

Accurate prediction of chlorophyll- (Chl-) concentrations, a key indicator of eutrophication, is essential for the sustainable management of lake ecosystems. This study evaluated the performance of Kolmogorov-Arnold Networks (KANs) along with three neural network models (MLP-NN, LSTM, and GRU) and three traditional machine learning tools (RF, SVR, and GPR) for predicting time-series Chl- concentrations in large lakes. Monthly remote-sensed Chl- data derived from Aqua-MODIS spanning September 2002 to April 2024 were used.

Complementary Circuits with WSe/Organic Semiconductor Heterostructure Field-Effect Transistors.

A device architecture based on heterostructure WSe/organic semiconductor field-effect transistors (FETs) is demonstrated in which ambipolar conduction is virtually eliminated, resulting in essentially unipolar FETs realized from an ambipolar semiconductor. For p-channel FETs, an electron-accepting organic semiconductor such as hexadecafluorocopperphthalocyanine (FCuPc) is used to form a heterolayer on top of WSe to effectively trap any undesirable electron currents. For n-channel FETs, a hole-accepting organic semiconductor such as pentacene is used to reduce the hole currents without affecting the electron currents.

A Combined Approach to Extract Rotational Dynamics of Globular Proteins Undergoing Liquid-Liquid Phase Separation.

The formation of protein condensates (droplets) via liquid-liquid phase separation (LLPS) is a commonly observed phenomenon in vitro. Changing the environmental properties with cosolutes, molecular crowders, protein partners, temperature, pressure, etc. has been shown to favor or disfavor the formation of protein droplets by fine-tuning the water-water, water-protein, and protein-protein interactions.

Challenges and opportunities for validation of AI-based new approach methods.

The integration of artificial intelligence (AI) into new approach methods (NAMs) for toxicology rep-resents a paradigm shift in chemical safety assessment. Harnessing AI appropriately has enormous potential to streamline validation efforts. This review explores the challenges, opportunities, and future directions for validating AI-based NAMs, highlighting their transformative potential while acknowledging the complexities involved in their implementation and acceptance.

Could Better-Quality Employment Improve Population Health? Findings From a Scoping Review of Multi-Dimensional Employment Quality Research and a Proposed Research Direction.

Background: Precarious employment, a specific part of the conceptual spectrum of employment quality (EQ), has been established as an important risk to individual and population health and well-being when compared to a standard employment circumstance. There remains a need, however, to explore whether and how EQ might be used as a tool to not only protect but also advance population health and well-being.

Methods: The purposes of this scoping review were to assess the analytic treatment of the multiple dimensions of EQ and the stances researchers take to characterize the state of knowledge of EQ that supports the idea that better EQ is a health-promoting factor.

Clusters of Patient Empowerment and Mental Health Literacy Differentiate Professional Help-Seeking Attitudes in Online Mental Health Communities Users.

Objectives: Grounded in the Health Empowerment Model, which posits that health literacy and patient empowerment are intertwined yet distinct constructs, this study investigates how the interplay of these factors influences attitudes toward seeking professional psychological help in members of online communities for mental health (OCMHs). This while acknowledging the multidimensionality of patient empowerment, encompassing meaningfulness, competence, self-determination, and impact.

Design And Methods: A cluster analysis of data gathered from 269 members of Italian-speaking OCMHs on Facebook has been performed.

3D Covalent Organic Framework Membrane with Interactive Ion Nanochannels for Hydroxide Conduction.

Crystalline porous materials, known for their ordered structures, hold promise for efficient hydroxide conductivity in alkaline fuel cells with limited ionic densities. However, the rigid cross-linking of porous materials precludes their processing into membranes, while composite membranes diminish materials' conductivity advantage due to the interrupted phases. Here, we report a self-standing three-dimensional covalent organic framework (3D COF) membrane with efficient OH-transport through its interconnected 3D ionic nanochannels.

"Encouraged to be Your True Self": An Interpretative Phenomenological Study of Medical Students' Experiences of Role Models in Shaping Sexual Minority Identity in Medical School.

Sexual and gender minority (SGM) identifying individuals experience worse health outcomes compared to non-SGM identifying counterparts. Representation of SGM individuals within medical schools may improve the delivery of more equitable healthcare through reducing biases and normalizing SGM presence within healthcare spaces. Our initial aim was to explore the extent to which role models may influence personal SGM identities within medical schools in the United Kingdom, using an interpretative phenomenological approach.