Neutrophil-Lymphocyte Ratio and Urine Albumin-Creatinine Ratio As Indicators of Microvascular Complications in Type 2 Diabetes Mellitus: A Cross-Sectional Study.

Background Type 2 diabetes mellitus (T2DM) is associated with a high risk of developing microvascular complications such as diabetic nephropathy, diabetic neuropathy (DN), and diabetic retinopathy (DR), leading to significant morbidity. Early detection of these complications is crucial for improving patient outcomes. Neutrophil-lymphocyte ratio (NLR) and urine albumin-creatinine ratio (UACR) show promise as cost-effective and accessible biomarkers for the early detection of microvascular complications in T2DM.

How to build the virtual cell with artificial intelligence: Priorities and opportunities.

Cells are essential to understanding health and disease, yet traditional models fall short of modeling and simulating their function and behavior. Advances in AI and omics offer groundbreaking opportunities to create an AI virtual cell (AIVC), a multi-scale, multi-modal large-neural-network-based model that can represent and simulate the behavior of molecules, cells, and tissues across diverse states. This Perspective provides a vision on their design and how collaborative efforts to build AIVCs will transform biological research by allowing high-fidelity simulations, accelerating discoveries, and guiding experimental studies, offering new opportunities for understanding cellular functions and fostering interdisciplinary collaborations in open science.

Revisiting the Emerging Role of Light-Based Therapies in the Management of Spinal Cord Injuries.

The surge in spinal cord injuries (SCI) attracted many neurobiologists to explore the underlying complex pathophysiology and to offer better therapeutic outcomes. The multimodal approaches to therapy in SCI have proven to be effective but to a limited extent. The clinical basics involve invasive procedures and limited therapeutic interventions, and most preclinical studies and formulations are yet to be translated due to numerous factors.

Image processing tools for petabyte-scale light sheet microscopy data.

Light sheet microscopy is a powerful technique for high-speed three-dimensional imaging of subcellular dynamics and large biological specimens. However, it often generates datasets ranging from hundreds of gigabytes to petabytes in size for a single experiment. Conventional computational tools process such images far slower than the time to acquire them and often fail outright due to memory limitations.

How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities.

The cell is arguably the most fundamental unit of life and is central to understanding biology. Accurate modeling of cells is important for this understanding as well as for determining the root causes of disease. Recent advances in artificial intelligence (AI), combined with the ability to generate large-scale experimental data, present novel opportunities to model cells.

Neural space-time model for dynamic multi-shot imaging.

Computational imaging reconstructions from multiple measurements that are captured sequentially often suffer from motion artifacts if the scene is dynamic. We propose a neural space-time model (NSTM) that jointly estimates the scene and its motion dynamics, without data priors or pre-training. Hence, we can both remove motion artifacts and resolve sample dynamics from the same set of raw measurements used for the conventional reconstruction.

Nanoscale volumetric fluorescence imaging via photochemical sectioning.

Optical nanoscopy of intact biological specimens has been transformed by recent advancements in hydrogel-based tissue clearing and expansion, enabling the imaging of cellular and subcellular structures with molecular contrast. However, existing high-resolution fluorescence microscopes have limited imaging depth, which prevents the study of whole-mount specimens without physical sectioning. To address this challenge, we developed "photochemical sectioning," a spatially precise, light-based sample sectioning process.

Torques within and outside the human spindle balance twist at anaphase.

At each cell division, nanometer-scale motors and microtubules give rise to the micron-scale spindle. Many mitotic motors step helically around microtubules in vitro, and most are predicted to twist the spindle in a left-handed direction. However, the human spindle exhibits only slight global twist, raising the question of how these molecular torques are balanced.

ℏ 4 quantum corrections to semiclassical transmission probabilities.

The combination of vibrational perturbation theory with the replacement of the harmonic oscillator quantization condition along the reaction coordinate with an imaginary action to be used in the uniform semiclassical approximation for the transmission probability has been shown in recent years to be a practical method for obtaining thermal reaction rates. To date, this theory has been developed systematically only up to second order in perturbation theory. Although it gives the correct leading order term in an ℏ2 expansion, its accuracy at lower temperatures, where tunneling becomes important, is not clear.

Corrections to Semiclassical Transmission Coefficients.

The uniform semiclassical expression for the energy-dependent transmission probability through a barrier has been a staple of reaction rate theory for almost 90 years. Yet, when using the classical Euclidean action, the transmission probability is identical to 1/2 when the energy equals the barrier height since the Euclidean action vanishes at this energy. This result is generally incorrect.

Torques within and outside the human spindle balance twist at anaphase.

At each cell division, nanometer-scale motors and microtubules give rise to the micron-scale spindle. Many mitotic motors step helically around microtubules in vitro, and most are predicted to twist the spindle in a left-handed direction. However, the human spindle exhibits only slight global twist, raising the question of how these molecular torques are balanced.

Accelerating Charge Separation and CO Photoreduction in Aqueous Phase under Visible Light with Ru Nanoparticles Loaded on Ga-Doped NiTiO in a Batch Photoreactor.

Titanate perovskite (ATiO) semiconductors show prospects of being active photocatalysts in the conversion of CO to chemical fuels such as methanol (CHOH) in the aqueous phase. Some of the challenges in using ATiO are limited light-harvesting capability, rapid bulk charge recombination, and the low density of catalytic sites participating in CO reduction. To address these challenges, Ga-doped NiTiO (GNTO) photocatalysts in which Ga ions substitute for Ti ions in the crystal lattice to form electron trap states and oxygen vacancies have been synthesized in this work.

Visualizing PIEZO1 Localization and Activity in hiPSC-Derived Single Cells and Organoids with HaloTag Technology.

PIEZO1 is critical to numerous physiological processes, transducing diverse mechanical stimuli into electrical and chemical signals. Recent studies underscore the importance of visualizing endogenous PIEZO1 activity and localization to understand its functional roles. To enable physiologically and clinically relevant studies on human PIEZO1, we genetically engineered human induced pluripotent stem cells (hiPSCs) to express a HaloTag fused to endogenous PIEZO1.

O-Vacancy Mediated Partially Inverted Ferrospinels for Enhanced Activity in the Sulfuric Acid Decomposition for Hydrogen Production.

Understanding the characterization of a tailored CoO spinel with Fe doping poses a challenge due to the surface state complexity in bifunctional catalysts with higher cation diversity. Doping with secondary metal results in a double spinel structure (a hybrid of normal and inverted spinels). This enhances the catalytic properties by generating more active oxygen vacancies.

Findings from the Longitudinal CINRG Becker Natural History Study.

Background: Becker muscular dystrophy is an X-linked, genetic disorder causing progressive degeneration of skeletal and cardiac muscle, with a widely variable phenotype.

Objective: A 3-year, longitudinal, prospective dataset contributed by patients with confirmed Becker muscular dystrophy was analyzed to characterize the natural history of this disorder. A better understanding of the natural history is crucial to rigorous therapeutic trials.

Uniform Semiclassical Instanton Rate Theory.

The instanton expression for the thermal transmission probability through a one-dimensional barrier is derived by using the uniform semiclassical energy-dependent transmission coefficient of Kemble. The resulting theory does not diverge at the "crossover temperature" but changes smoothly. The temperature-dependent energy of the instanton is the same as the barrier height when ℏ = π and not 2π as in the "standard" instanton theory.

Characterization, comparison, and optimization of lattice light sheets.

Lattice light sheet microscopy excels at the noninvasive imaging of three-dimensional (3D) dynamic processes at high spatiotemporal resolution within cells and developing embryos. Recently, several papers have called into question the performance of lattice light sheets relative to the Gaussian sheets most common in light sheet microscopy. Here, we undertake a theoretical and experimental analysis of various forms of light sheet microscopy, which demonstrates and explains why lattice light sheets provide substantial improvements in resolution and photobleaching reduction.

The synergistic effect of climatic factors on malaria transmission: a predictive approach for northeastern states of India.

The northeast region of India is highlighted as the most vulnerable region for malaria. This study attempts to explore the epidemiological profile and quantify the climate-induced influence on malaria cases in the context of tropical states, taking Meghalaya and Tripura as study areas. Monthly malaria cases and meteorological data from 2011 to 2018 and 2013 to 2019 were collected from the states of Meghalaya and Tripura, respectively.

Origin of wiring specificity in an olfactory map revealed by neuron type-specific, time-lapse imaging of dendrite targeting.

How does wiring specificity of neural maps emerge during development? Formation of the adult olfactory glomerular map begins with the patterning of projection neuron (PN) dendrites at the early pupal stage. To better understand the origin of wiring specificity of this map, we created genetic tools to systematically characterize dendrite patterning across development at PN type-specific resolution. We find that PNs use lineage and birth order combinatorially to build the initial dendritic map.

Multiobjective Bayesian Optimization Framework for the Synthesis of Methanol from Syngas Using Interpretable Gaussian Process Models.

Methanol production has gained considerable interest on the laboratory and industrial scale as it is a renewable fuel and an excellent hydrogen energy storehouse. The formation of synthesis gas (CO/H) and the conversion of synthesis gas to methanol are the two basic catalytic processes used in methanol production. Machine learning (ML) approaches have recently emerged as powerful tools in reaction informatics.

Seroprevalence of Adeno-Associated Virus Neutralizing Antibodies in Males with Duchenne Muscular Dystrophy.

Adeno-associated virus (AAV)-based gene therapies are emerging strategies in Duchenne muscular dystrophy (DMD) treatment. Exposure to wild-type AAV can lead to development of neutralizing antibodies (NAbs) and blocking of AAV transduction, thereby limiting the delivery of AAV vector-based gene therapy. Therefore, it is imperative to check for the presence of AAV NAbs in a patient who is a candidate for gene therapy.