Porous SnO nanosheets for room temperature ammonia sensing in extreme humidity.

Gas sensors based on tin dioxide (SnO) for the detection of ammonia (NH) have become commercially available for environmental monitoring due to their reactive qualities when exposed to different gaseous pollutants. Nevertheless, their implementation in the medical field has been hindered by certain inherent drawbacks, such as needing to operate at high temperatures, lack of selectivity, unreliable operation under high-humidity conditions, and a lower detection limit. To counter these issues, this study created 2D nanosheets of SnO through an optimized solvothermal method.

Drug Dissolution in Oral Drug Absorption: Workshop Report.

The in-person workshop "Drug Dissolution in Oral Drug Absorption" was held on May 23-24, 2023, in Baltimore, MD, USA. The workshop was organized into lectures and breakout sessions. Three common topics that were re-visited by various lecturers were amorphous solid dispersions (ASDs), dissolution/permeation interplay, and in vitro methods to predict in vivo biopharmaceutics performance and risk.

Biocontrol of biofilm forming Burkholderia cepacia using a quorum quenching crude lactonase enzyme extract from a marine Chromohalobacter sp. strain D23.

Biofilm plays advantageous role in Burkholderia cepacia by exerting multi-drug resistance. As quorum sensing (QS) system regulates biofilm formation and pathogenicity in B. cepacia strains, quorum quenching (QQ) may be a novel strategy to control persistent B.

Lattice strain induced d-band centre engineering enabled pseudocapacitive energy storage in 2D hypo-hyper electronic V-NiCoO for asymmetric supercapacitors.

Understanding the role of fundamental structural engineering of materials in unravelling the underlying rudimentary electronic structure-dependent charge storage mechanisms is crucial for developing new strategic approaches toward high-performance electrochemical energy storage devices. Here, we demonstrate the role of strain engineering by V doping-induced lattice contraction in NiCoO for increasing the energy density and power density of aqueous asymmetric hybrid supercapacitors. For application in energy storage, we demonstrate the influence of electron-deficient V doping in electron-rich Ni sites, which has been found to result in the formation of a hypo-hyper electronically coupled cation pair causing a shift in the d-band and O 2p band centres and distortion of CoO octahedra.

Metronomic and single high-dose paclitaxel treatments produce distinct heterogenous chemoresistant cancer cell populations.

More than 75% of epithelial ovarian cancer (EOC) patients experience disease recurrence after initial treatment, highlighting our incomplete understanding of how chemoresistant populations evolve over the course of EOC progression post chemotherapy treatment. Here, we show how two paclitaxel (PTX) treatment methods- a single high dose and a weekly metronomic dose for four weeks, generate unique chemoresistant populations. Using mechanically relevant alginate microspheres and a combination of transcript profiling and heterogeneity analyses, we found that these PTX-treatment regimens produce distinct and resilient subpopulations that differ in metabolic reprogramming signatures, acquisition of resistance to PTX and anoikis, and the enrichment for cancer stem cells (CSCs) and polyploid giant cancer cells (PGCCs) with the ability to replenish bulk populations.

Machine Learning the Quantum Mechanical Wave Function.

Strongly correlated systems have been challenging to computational chemists for a long time. To solve these systems, multireference methods have been developed over the years. Recently, with the fast development of machine learning and artificial intelligence methods, these methods have also influenced the quest for optimal wave function ansatz.

A causal roadmap for generating high-quality real-world evidence.

Increasing emphasis on the use of real-world evidence (RWE) to support clinical policy and regulatory decision-making has led to a proliferation of guidance, advice, and frameworks from regulatory agencies, academia, professional societies, and industry. A broad spectrum of studies use real-world data (RWD) to produce RWE, ranging from randomized trials with outcomes assessed using RWD to fully observational studies. Yet, many proposals for generating RWE lack sufficient detail, and many analyses of RWD suffer from implausible assumptions, other methodological flaws, or inappropriate interpretations.

Field evaluation of a simple and rapid diagnostic test, RLDT to detect Shigella and enterotoxigenic E. coli in Indian children.

The diagnostic assays currently used to detect spp. (Shigella) and enterotoxigenic (ETEC) are complex or elaborate which make them difficult to apply in resource poor settings where these diseases are endemic. The simple and rapid nucleic acid amplification-based assay "Rapid LAMP-based Diagnostic Test (RLDT)" was evaluated to detect (Shigella) and enterotoxigenic Escherichia coli (ETEC) and determine the epidemiology of these pathogens in Kolkata, India.

TreeKernel: interpretable kernel machine tests for interactions between -omics and clinical predictors with applications to metabolomics and COPD phenotypes.

Background: In this paper, we are interested in interactions between a high-dimensional -omics dataset and clinical covariates. The goal is to evaluate the relationship between a phenotype of interest and a high-dimensional omics pathway, where the effect of the omics data depends on subjects' clinical covariates (age, sex, smoking status, etc.).

SMASH: Scalable Method for Analyzing Spatial Heterogeneity of genes in spatial transcriptomics data.

In high-throughput spatial transcriptomics (ST) studies, it is of great interest to identify the genes whose level of expression in a tissue covaries with the spatial location of cells/spots. Such genes, also known as spatially variable genes (SVGs), can be crucial to the biological understanding of both structural and functional characteristics of complex tissues. Existing methods for detecting SVGs either suffer from huge computational demand or significantly lack statistical power.

Nanoclusters with specific DNA overhangs: modifying configurability, engineering contrary logic pairs and the parity generator/checker for error detection.

The most promising alternative for next-generation molecular computers is biocomputing, which uses DNAs as its primary building blocks to perform a Boolean operation. DNA nanoclusters (NCs) have emerged as promising candidates for biosensing applications due to their unique self-assembly properties and programmability. It has been demonstrated that adding DNA overhangs to DNA NCs improves their adaptability in identifying specific biomolecular interactions.

The impact of spatially heterogeneous chemical doping on the electronic properties of CdSe quantum dots: insights from computation.

The introduction of copper (Cu) impurity in semiconductor CdSe quantum dots (QDs) gives rise to unique photoluminescence (PL) bands exhibiting distinctive characteristics, like broad line width, significant Stokes shift, and complex temporal decay. The atomistic origins of these spectral features are yet to be understood comprehensively. We employed multiple computational techniques to systematically study the impact of the spatial heterogeneity of Cu atoms on the stability and photophysical properties, including the emission linewidth of doped QDs under ambient conditions.

Composition Dependent Strain Engineering of Lead-Free Halide Double Perovskite: Computational Insights.

The critical photophysical properties of lead-free halide double perovskites (HDPs) must be substantially improved for various applications. In this regard, strain engineering is a powerful tool for enhancing optoelectronic performance with precise control. Here, we employ simulations to investigate the impact of mild compressive and tensile strains on the photophysics of CsAgB'X (B' = Sb, Bi; X = Cl, Br) perovskites.

Effect of mutations on the folding and stability of D-crystallin protein.

Interprotein interactions between the partially unfolded states of D-crystallin (D-crys) protein are known to cause cataracts. Therefore, understanding the unfolding pathways of native D-crys is extremely crucial to delineate their aggregation mechanism. In this study, we have performed extensive all-atom Molecular Dynamics simulations with explicit solvent to understand the role of the critical residues that drive the stability of the motifs and domains of D-crys in its wild type and mutant forms.

Implementation of Exome Sequencing to Identify Rare Genetic Diseases.

Modern high-throughput genomic testing using next-generation sequencing (NGS) has led to a significant increase in the successful diagnosis of rare genetic disorders. Recent advances in NGS tools and techniques have led to accurate and timely diagnosis of a large proportion of genetic diseases by finding sequence variations in clinical samples. One of the NGS techniques, exome sequencing (ES), is considered as a powerful and easily approachable method for genetic disorders in terms of rapid and cost-effective diagnostic yields.

Search for a τ^{+}τ^{-} Resonance in e^{+}e^{-}→μ^{+}μ^{-}τ^{+}τ^{-} Events with the Belle II Experiment.

We report the first search for a nonstandard-model resonance decaying into τ pairs in e^{+}e^{-}→μ^{+}μ^{-}τ^{+}τ^{-} events in the 3.6-10  GeV/c^{2} mass range. We use a 62.

Aromatase and steroid sulfatase from human placenta.

Cytochrome P450 aromatase (AROM) and steroid (estrone (E1)/dehydroepiandrosterone (DHEA)) sulfatase (STS) are the two key enzymes responsible for the biosynthesis of estrogens in human, and maintenance of the critical balance between androgens and estrogens. Human AROM, an integral membrane protein of the endoplasmic reticulum, is a member of the Fe-heme containing cytochrome P450 superfamily having a cysteine thiolate as the fifth Fe-coordinating ligand. It is the only enzyme known to catalyze the conversion of androgens with non-aromatic A-rings to estrogens characterized by the aromatic A-ring.

Learning with limited target data to detect cells in cross-modality images.

Deep neural networks have achieved excellent cell or nucleus quantification performance in microscopy images, but they often suffer from performance degradation when applied to cross-modality imaging data. Unsupervised domain adaptation (UDA) based on generative adversarial networks (GANs) has recently improved the performance of cross-modality medical image quantification. However, current GAN-based UDA methods typically require abundant target data for model training, which is often very expensive or even impossible to obtain for real applications.

Measurement of CP Violation in B^{0}→K_{S}^{0}π^{0} Decays at Belle II.

We report a measurement of the CP-violating parameters C and S in B^{0}→K_{S}^{0}π^{0} decays at Belle II using a sample of 387×10^{6}  BB[over ¯] events recorded in e^{+}e^{-} collisions at a center-of-mass energy corresponding to the ϒ(4S) resonance. These parameters are determined by fitting the proper decay-time distribution of a sample of 415 signal events. We obtain C=-0.

FunSpace: A functional and spatial analytic approach to cell imaging data using entropy measures.

Spatial heterogeneity in the tumor microenvironment (TME) plays a critical role in gaining insights into tumor development and progression. Conventional metrics typically capture the spatial differential between TME cellular patterns by either exploring the cell distributions in a pairwise fashion or aggregating the heterogeneity across multiple cell distributions without considering the spatial contribution. As such, none of the existing approaches has fully accounted for the simultaneous heterogeneity caused by both cellular diversity and spatial configurations of multiple cell categories.

Assessment of treatment outcomes of visceral leishmaniasis (VL) treated cases and impact of COVID-19 on VL management and control services in Bangladesh.

Background: COVID-19 has largely impacted the management of Visceral leishmaniasis (VL), like several other Neglected Tropical Diseases. The impact was particularly evident in Lower and Middle-Income countries where the already inadequate healthcare resources were diverted to managing the COVID-19 pandemic. Bangladesh achieved the elimination target for VL in 2016.

Enhanced remediation of polyaromatic hydrocarbon using agro-industrial waste for biofuel production and environmental pollution mitigation.

In the present study, attention has been paid to the development of economically feasible strategies for enhanced remediation of anthracene and its conversion into biofuels. The strategies developed (B1, B2, B3, and B4) include bagasse and lipid-producing strain Rhodotorula mucilagenosa IIPL32 synthesizing surface active metabolites. The results indicate the highest production of surface-active metabolites in strategies B2, B3, and B4 along with a maximum biodegradation rate.