A socioemotional network perspective on momentary experiences of family conflict in young adults.

Family conflict is an established predictor of psychopathology in youth. Traditional approaches focus on between-family differences in conflict. Daily fluctuations in conflict within families might also impact psychopathology, but more research is needed to understand how and why.

Machine learning application for predicting key properties of activated carbon produced from lignocellulosic biomass waste with chemical activation.

The successful application of gradient boosting regression (GBR) in machine learning to forecast surface area, pore volume, and yield in biomass-derived activated carbon (AC) production underscores its potential for enhancing manufacturing processes. The GBR model, collecting 17 independent variables for two-step activation (2-SA) and 14 for one-step activation (1-SA), demonstrates effectiveness across three datasets-1-SA, 2-SA, and a combined dataset. Notably, in 1-SA, the GBR model yields R values of 0.

A practical evaluation of measures derived from compressed sensing diffusion spectrum imaging.

Diffusion Spectrum Imaging (DSI) using dense Cartesian sampling of q-space has been shown to provide important advantages for modeling complex white matter architecture. However, its adoption has been limited by the lengthy acquisition time required. Sparser sampling of q-space combined with compressed sensing (CS) reconstruction techniques has been proposed as a way to reduce the scan time of DSI acquisitions.

Height-renderable morphable tactile display enabled by programmable modulation of local stiffness in photothermally active polymer.

Reconfigurable tactile displays are being used to provide refreshable Braille information; however, the delivered information is currently limited to an alternative of Braille because of difficulties in controlling the deformation height. Herein, we present a photothermally activated polymer-bilayer-based morphable tactile display that can programmably generate tangible three-dimensional topologies with varying textures on a thin film surface. The morphable tactile display was composed of a heterogeneous polymer structure that integrated a stiffness-tunable polymer into a light-absorbing elastomer, near-infra-red light-emitting diode (NIR-LED) array, and small pneumatic chamber.

Topology-Accelerated and Selective Cascade Depolymerization of Architecturally Complex Polyesters.

Despite considerable recent advances already made in developing chemically circular polymers (CPs), the current framework predominantly focuses on CPs with linear-chain structures of different monomer types. As polymer properties are determined by not only composition but also topology, manipulating the topology of the single-monomer-based CP systems from linear-chain structures to architecturally complex polymers could potentially modulate the resulting polymer properties without changing the chemical composition, thereby advancing the concept of monomaterial product design. To that end, here, we introduce a chemically circular hyperbranched polyester (HBPE), synthesized by a mixed chain-growth and step-growth polymerization of a rationally designed bicyclic lactone with a pendent hydroxyl group (BiL).

Augmented-reality-assisted intraoral scanning: A proof-of-concept study.

Purpose: The aims of the present study were (a) to compare the scanning time and image count to complete optical scans of a typodont between augmented-reality-assisted intraoral scanning (ARIOS) and intraoral scanning (IOS); (b) to compare the accuracy of the digital casts derived from ARIOS and IOS; (c) to compare participant-related outcomes between ARIOS and IOS.

Materials And Methods: A multi-session within-subject experiment was conducted to compare ARIOS and IOS. Thirty-one dental students participated in the study.

Advances in lipid nanoparticle mRNA therapeutics beyond COVID-19 vaccines.

The remarkable success of two lipid nanoparticle-mRNA vaccines against coronavirus disease (COVID-19) has placed the therapeutic and prophylactic potential of messenger RNA (mRNA) in the spotlight. It has also drawn attention to the indispensable role of lipid nanoparticles in enabling the effects of this nucleic acid. To date, lipid nanoparticles are the most clinically advanced non-viral platforms for mRNA delivery.

Influence of ionizable lipid tail length on lipid nanoparticle delivery of mRNA of varying length.

RNA-based therapeutics have gained traction for the prevention and treatment of a variety of diseases. However, their fragility and immunogenicity necessitate a drug carrier. Lipid nanoparticles (LNPs) have emerged as the predominant delivery vehicle for RNA therapeutics.

Interpreting chemisorption strength with AutoML-based feature deletion experiments.

The chemisorption energy of reactants on a catalyst surface, [Formula: see text], is among the most informative characteristics of understanding and pinpointing the optimal catalyst. The intrinsic complexity of catalyst surfaces and chemisorption reactions presents significant difficulties in identifying the pivotal physical quantities determining [Formula: see text]. In response to this, the study proposes a methodology, the feature deletion experiment, based on Automatic Machine Learning (AutoML) for knowledge extraction from a high-throughput density functional theory (DFT) database.

High-Throughput Single-Cell, Single-Mitochondrial DNA Assay Using Hydrogel Droplet Microfluidics.

There is growing interest in understanding the biological implications of single cell heterogeneity and heteroplasmy of mitochondrial DNA (mtDNA), but current methodologies for single-cell mtDNA analysis limit the scale of analysis to small cell populations. Although droplet microfluidics have increased the throughput of single-cell genomic, RNA, and protein analysis, their application to sub-cellular organelle analysis has remained a largely unsolved challenge. Here, we introduce an agarose-based droplet microfluidic approach for single-cell, single-mtDNA analysis, which allows simultaneous processing of hundreds of individual mtDNA molecules within >10,000 individual cells.

Investigating brain dynamics and their association with cognitive control in opioid use disorder using naturalistic and drug cue paradigms.

Objectives: Opioid use disorder (OUD) impacts millions of people worldwide. The prevalence and debilitating effects of OUD present a pressing need to understand its neural mechanisms to provide more targeted interventions. Prior studies have linked altered functioning in large-scale brain networks with clinical symptoms and outcomes in OUD.

Evaluating the representational power of pre-trained DNA language models for regulatory genomics.

The emergence of genomic language models (gLMs) offers an unsupervised approach to learning a wide diversity of -regulatory patterns in the non-coding genome without requiring labels of functional activity generated by wet-lab experiments. Previous evaluations have shown that pre-trained gLMs can be leveraged to improve predictive performance across a broad range of regulatory genomics tasks, albeit using relatively simple benchmark datasets and baseline models. Since the gLMs in these studies were tested upon fine-tuning their weights for each downstream task, determining whether gLM representations embody a foundational understanding of -regulatory biology remains an open question.

Accurate Surface and Finite-Temperature Bulk Properties of Lithium Metal at Large Scales Using Machine Learning Interaction Potentials.

The properties of lithium metal are key parameters in the design of lithium-ion and lithium-metal batteries. They are difficult to probe experimentally due to the high reactivity and low melting point of lithium as well as the microscopic scales at which lithium exists in batteries where it is found to have enhanced strength, with implications for dendrite suppression strategies. Computationally, there is a lack of empirical potentials that are consistently quantitatively accurate across all properties, and ab initio calculations are too costly.

Challenges in computational discovery of bioactive peptides in 'omics data.

Peptides have a plethora of activities in biological systems that can potentially be exploited biotechnologically. Several peptides are used clinically, as well as in industry and agriculture. The increase in available 'omics data has recently provided a large opportunity for mining novel enzymes, biosynthetic gene clusters, and molecules.

Motor neurons and endothelial cells additively promote development and fusion of human iPSC-derived skeletal myocytes.

Background: Neurovascular cells have wide-ranging implications on skeletal muscle biology regulating myogenesis, maturation, and regeneration. Although several in vitro studies have investigated how motor neurons and endothelial cells interact with skeletal myocytes independently, there is limited knowledge about the combined effect of neural and vascular cells on muscle maturation and development.

Methods: Here, we report a triculture system comprising human-induced pluripotent stem cell (iPSC)-derived skeletal myocytes, human iPSC-derived motor neurons, and primary human endothelial cells maintained under controlled media conditions.

Dose-Dependent Tranexamic Acid Blunting of Penumbral Leukocyte Mobilization and Blood-Brain Barrier Permeability Following Traumatic Brain Injury: An In Vivo Murine Study.

Background: Early posttraumatic brain injury (TBI) tranexamic acid (TXA) may reduce blood-brain barrier (BBB) permeability, but it is unclear if this effect is fixed regardless of dose. We hypothesized that post-TBI TXA demonstrates a dose-dependent reduction of in vivo penumbral leukocyte mobilization, BBB microvascular permeability, and enhancement of neuroclinical recovery.

Methods: CD1 male mice (n = 40) were randomly assigned to TBI by controlled cortical impact (injury [I]) or sham TBI (S), followed by intravenous bolus of either saline (placebo [P]) or TXA (15, 30, or 60 mg/kg).

Training pathologists to assess stromal tumour-infiltrating lymphocytes in breast cancer synergises efforts in clinical care and scientific research.

A growing body of research supports stromal tumour-infiltrating lymphocyte (TIL) density in breast cancer to be a robust prognostic and predicive biomarker. The gold standard for stromal TIL density quantitation in breast cancer is pathologist visual assessment using haematoxylin and eosin-stained slides. Artificial intelligence/machine-learning algorithms are in development to automate the stromal TIL scoring process, and must be validated against a reference standard such as pathologist visual assessment.

The feasibility of a novel 3D-Printed patient specific cutting guide for extended trochanteric osteotomies.

Background: The extended trochanteric osteotomy (ETO) is a surgical technique utilized to expose the intramedullary canal of the proximal femur, protect the soft tissues and promote reliable healing. However, imprecise execution of the osteotomy can lead to fracture, soft tissue injury, non-union, and unnecessary morbidity. We developed a technique to create patient specific, 3D-printed cutting guides to aid in accurate positioning of the ETO and improve osteotomy quality and outcomes.

Antigen Presenting Cell Mimetic Lipid Nanoparticles for Rapid mRNA CAR T Cell Cancer Immunotherapy.

Chimeric antigen receptor (CAR) T cell therapy has achieved remarkable clinical success in the treatment of hematological malignancies. However, producing these bespoke cancer-killing cells is a complicated ex vivo process involving leukapheresis, artificial T cell activation, and CAR construct introduction. The activation step requires the engagement of CD3/TCR and CD28 and is vital for T cell transfection and differentiation.

Compartmentalized ocular lymphatic system mediates eye-brain immunity.

The eye, an anatomical extension of the central nervous system (CNS), exhibits many molecular and cellular parallels to the brain. Emerging research demonstrates that changes in the brain are often reflected in the eye, particularly in the retina. Still, the possibility of an immunological nexus between the posterior eye and the rest of the CNS tissues remains unexplored.

An immunosuppressive vascular niche drives macrophage polarization and immunotherapy resistance in glioblastoma.

Cancer immunity is subjected to spatiotemporal regulation by leukocyte interaction with neoplastic and stromal cells, contributing to immune evasion and immunotherapy resistance. Here, we identify a distinct mesenchymal-like population of endothelial cells (ECs) that form an immunosuppressive vascular niche in glioblastoma (GBM). We reveal a spatially restricted, Twist1/SATB1-mediated sequential transcriptional activation mechanism, through which tumor ECs produce osteopontin to promote immunosuppressive macrophage (Mφ) phenotypes.

CtDNA based molecular residual disease outcompetes carcinoembryonic antigen in predicting postoperative recurrence of non-small cell lung cancer.

Background: Carcinoembryonic antigen (CEA) has been routinely used as a postoperative monitoring biomarker for non-small cell lung cancer (NSCLC). Emergingly, circulating tumor DNA (ctDNA)-molecular residual disease (MRD) detection is a well-established prognostic marker, with better positive predictive value (PPV) and negative predictive value (NPV). However, the actual clinical efficiency of CEA in MRD context remain unknown.

Synthetic angiotensin II peptide derivatives confer protection against cerebral and severe non-cerebral malaria in murine models.

Malaria can have severe long-term effects. Even after treatment with antimalarial drugs eliminates the parasite, survivors of cerebral malaria may suffer from irreversible brain damage, leading to cognitive deficits. Angiotensin II, a natural human peptide hormone that regulates blood pressure, has been shown to be active against Plasmodium spp.