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Abstract In recent years, two-dimensional (2D) van der Waals materials have emerged as a focal point in materials research, drawing increasing attention due to their potential for isolating and synergistically combining diverse atomic layers. Atomically thin transition metal dichalcogenides (TMDs) are one of the most alluring van der Waals materials owing to their exceptional electronic and optical properties. The tightly bound excitons with giant oscillator strength render TMDs an ideal platform to investigate strong light-matter coupling when they are integrated with optical cavities, providing a wide range of possibilities for exploring novel polaritonic physics and devices. In this review, we focused on recent advances in TMD-based strong light-matter coupling. In the foremost position, we discuss the various optical structures strongly coupled to TMD materials, such as Fabry-Perot cavities, photonic crystals, and plasmonic nanocavities. We then present several intriguing properties and relevant device applications of TMD polaritons. In the end, we delineate promising future directions for the study of strong light-matter coupling in van der Waals materials.

Abstract Missed appointments, or no-shows, disrupt healthcare delivery, exacerbating chronic disease management and leading to worse health outcomes. Telehealth has surged as a viable solution to reduce no-shows and improve healthcare accessibility, especially during the COVID-19 pandemic. However, telehealth disparities and its long-term efficacy across various medical specialties remain understudied. To address this, we performed a retrospective analysis of electronic health records from a heterogenous network of hospitals in Illinois, examining telehealth use and no-shows across among 444,752 adult patients with 1,973,098 outpatient encounters across nine specialties during the sustained pandemic phase (i.e., January 1, 2021 to July 1, 2022). Among them, 84,290 (4.27%) were no-shows, and telehealth constituted 202,933 (10.3%) of the total encounters. Telehealth use during the sustained phase varied significantly by specialty type. Overall, telehealth encounters were associated with reduced no-show odds compared to in-person encounters (OR, 0.28; 95% CI, 0.26–0.29). Black and Hispanic patients, as well as those with Medicaid, had higher no-show odds relative to their counterparts, even when using telehealth. Mental health specialty had the highest telehealth usage rate and the highest no-show odds (OR, 2.99; 95% CI, 2.84–3.14) relative to other specialties included in the study. Moreover, specialty type had differential effects on no-shows for telehealth. These results underscore the variability in telehealth use by specialty type and pervasive disparities telehealth use and no-shows. As we move beyond the pandemic, our findings can inform policymakers to tailor policies and incentives to reach different patient groups as well as specialties, with varying needs, to promote equitable telehealth utilization.

Abstract Background Stroke is a globally dangerous disease capable of causing irreversible neuronal damage with limited therapeutic options. Meldonium, an inhibitor of carnitine-dependent metabolism, is considered an anti-ischemic drug. However, the mechanisms through which meldonium improves ischemic injury and its potential to protect neurons remain largely unknown. Methods A rat model with middle cerebral artery occlusion (MCAO) was used to investigate meldonium’s neuroprotective efficacy in vivo. Infarct volume, neurological deficit score, histopathology, neuronal apoptosis, motor function, morphological alteration and antioxidant capacity were explored via 2,3,5-Triphenyltetrazolium chloride staining, Longa scoring method, hematoxylin and eosin staining, terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling assay, rotarod test, transmission electron microscopy and Oxidative stress index related kit. A primary rat hippocampal neuron model subjected to oxygen–glucose deprivation reperfusion was used to study meldonium’s protective ability in vitro. Neuronal viability, mitochondrial membrane potential, mitochondrial morphology, respiratory function, ATP production, and its potential mechanism were assayed by MTT cell proliferation and cytotoxicity assay kit, cell-permeant MitoTracker® probes, mitochondrial stress, real-time ATP rate and western blotting. Results Meldonium markedly reduced the infarct size, improved neurological function and motor ability, and inhibited neuronal apoptosis in vivo. Meldonium enhanced the morphology, antioxidant capacity, and ATP production of mitochondria and inhibited the opening of the mitochondrial permeability transition pore in the cerebral cortex and hippocampus during cerebral ischemia–reperfusion injury (CIRI) in rats. Additionally, meldonium improved the damaged fusion process and respiratory function of neuronal mitochondria in vitro. Further investigation revealed that meldonium activated the Akt/GSK-3β signaling pathway to inhibit mitochondria-dependent neuronal apoptosis. Conclusion Our study demonstrated that meldonium shows a neuroprotective function during CIRI by preserving the mitochondrial function, thus prevented neurons from apoptosis.

Abstract Spatially resolved transcriptomics integrates high-throughput transcriptome measurements with preserved spatial cellular organization information. However, many technologies cannot reach single-cell resolution. We present STdGCN, a graph model leveraging single-cell RNA sequencing (scRNA-seq) as reference for cell-type deconvolution in spatial transcriptomic (ST) data. STdGCN incorporates expression profiles from scRNA-seq and spatial localization from ST data for deconvolution. Extensive benchmarking on multiple datasets demonstrates that STdGCN outperforms 17 state-of-the-art models. In a human breast cancer Visium dataset, STdGCN delineates stroma, lymphocytes, and cancer cells, aiding tumor microenvironment analysis. In human heart ST data, STdGCN identifies changes in endothelial-cardiomyocyte communications during tissue development.

Abstract Background Acute hypobaric hypoxia-induced brain injury has been a challenge in the health management of mountaineers; therefore, new neuroprotective agents are urgently required. Meldonium, a well-known cardioprotective drug, has been reported to have neuroprotective effects. However, the relevant mechanisms have not been elucidated. We hypothesized that meldonium may play a potentially novel role in hypobaric hypoxia cerebral injury. Methods We initially evaluated the neuroprotection efficacy of meldonium against acute hypoxia in mice and primary hippocampal neurons. The potential molecular targets of meldonium were screened using drug-target binding Huprot™ microarray chip and mass spectrometry analyses after which they were validated with surface plasmon resonance (SPR), molecular docking, and pull-down assay. The functional effects of such binding were explored through gene knockdown and overexpression. Results The study clearly shows that pretreatment with meldonium rapidly attenuates neuronal pathological damage, cerebral blood flow changes, and mitochondrial damage and its cascade response to oxidative stress injury, thereby improving survival rates in mice brain and primary hippocampal neurons, revealing the remarkable pharmacological efficacy of meldonium in acute high-altitude brain injury. On the one hand, we confirmed that meldonium directly interacts with phosphoglycerate kinase 1 (PGK1) to promote its activity, which improved glycolysis and pyruvate metabolism to promote ATP production. On the other hand, meldonium also ameliorates mitochondrial damage by PGK1 translocating to mitochondria under acute hypoxia to regulate the activity of TNF receptor-associated protein 1 (TRAP1) molecular chaperones. Conclusion These results further explain the mechanism of meldonium as an energy optimizer and provide a strategy for preventing acute hypobaric hypoxia brain injury at high altitudes.

The food concept of "healthy low-fat" had attracted significant public attention in recent years. Oxidized konjac glucomannan (OKGM) was introduced as a fat replacer to address the issue of low gel strength in low-fat yoghurt. The effects of different oxidation degrees of OKGM on the quality of yoghurt were investigated by analyzing the physicochemical properties, texture, rheological properties and microstructure of yoghurt. The research demonstrated that yoghurt containing high oxidation degrees of OKGM (OK-60, OK-90, OK-120) increased the hardness from 375.90 g to 436.67 g and the water holding capacity from 28.03% to 31.89% compared to yoghurt without added OKGM. In addition, it improved the rheological properties of yoghurt including apparent viscosity and viscoelasticity. The results of scanning electron microscopy and confocal laser microscopy revealed that high oxidation degrees of OKGM reduced integral pores in yoghurt, promoted casein micelles aggregation, and increased average particle size from 88.27 nm to 125.33 nm. In contrast, natural konjac glucomannan (KGM) and lower levels of OKGM oxidation (OK-30) reduced texture, apparent viscosity, and viscoelasticity of the yoghurt, disrupted yoghurt gel structure and compromised its stability. The results of sensory evaluation showed that high oxidation levels improved the glossiness, uniformity, and overall taste of yoghurt, providing a theoretical basis for the development of high-quality, low-fat, and healthy yoghurt products.

Approaches to regenerating bone often rely on integrating biomaterials and biological signals in the form of cells or cytokines. However, from a translational point of view, these approaches are challenging due to the sourcing and quality of the biologic, unpredictable immune responses, complex regulatory paths, and high costs. We describe a simple manufacturing process and a material-centric 3D-printed composite scaffold system (CSS) that offers distinct advantages for clinical translation. The CSS comprises a 3D-printed porous polydiolcitrate-hydroxyapatite composite elastomer infused with a polydiolcitrate-graphene oxide hydrogel composite. Using a micro-continuous liquid interface production 3D printer, we fabricate a precise porous ceramic scaffold with 60 wt% hydroxyapatite resembling natural bone. The resulting scaffold integrates with a thermoresponsive hydrogel composite in situ to fit the defect, which is expected to enhance surface contact with surrounding tissue and facilitate biointegration. The antioxidative properties of citrate polymers prevent long-term inflammatory responses. The CSS stimulates osteogenesis in vitro and in vivo. Within 4 weeks in a calvarial critical-sized bone defect model, the CSS accelerated ECM deposition (8-fold) and mineralized osteoid (69-fold) compared to the untreated. Through spatial transcriptomics, we demonstrated the comprehensive biological processes of CSS for prompt osseointegration. Our material-centric approach delivers impressive osteogenic properties and streamlined manufacturing advantages, potentially expediting clinical application for bone reconstruction surgeries.

Abstract Alzheimer’s disease (AD) is a serious brain disorder characterized by the presence of beta-amyloid plaques, tau pathology, inflammation, neurodegeneration, and cerebrovascular dysfunction. The presence of chronic neuroinflammation, breaches in the blood-brain barrier (BBB), and increased levels of inflammatory mediators are central to the pathogenesis of AD. These factors promote the penetration of immune cells into the brain, potentially exacerbating clinical symptoms and neuronal death in AD patients. While microglia, the resident immune cells of the central nervous system (CNS), play a crucial role in AD, recent evidence suggests the infiltration of cerebral vessels and parenchyma by peripheral immune cells, including neutrophils, T lymphocytes, B lymphocytes, NK cells, and monocytes in AD. These cells participate in the regulation of immunity and inflammation, which is expected to play a huge role in future immunotherapy. Given the crucial role of peripheral immune cells in AD, this article seeks to offer a comprehensive overview of their contributions to neuroinflammation in the disease. Understanding the role of these cells in the neuroinflammatory response is vital for developing new diagnostic markers and therapeutic targets to enhance the diagnosis and treatment of AD patients.

On the afternoon of 4 April, 2023, an intense downburst event (referred to as the '4.04' strong downburst) occurred in Hengyang, Hunan, causing serious disasters. This study analyzes the key warning indicators and environmental conditions for extreme strong winds using conventional meteorological observations, Doppler weather radar, and NCEP 1°×1° reanalysis data. The results are as follows: (1) The '4.04' strong downburst occurred under a 'baroclinic frontogenesis' weather system configuration, with a surface cold front providing the triggering conditions. The Skew-T plots clearly showed characteristics of high-level dryness and low-level moisture, unstable atmospheric convective parameters, and corrected convective available potential energy (CAPE), along with strong vertical wind shear, all conducive to the occurrence of extreme strong winds. (2) A mesoscale convective system (MCS) with bow echoes swept through Hengyang, causing regional downbursts. Extreme strong winds occurred when the corresponding storm cells moved rapidly, with maximum reflectivity factors reaching 60 dBz. The vertical integrated liquid water content and centroid height rapidly decreased. The reflectivity factors displayed a noticeable tilted structure, with clear features of bow echoes, rear-inflow jets, and radial velocity ambiguity. The low elevation asymmetric high-speed regions and velocity convergence are key warning indicators for extreme strong winds. (3) The strong downburst exhibited significant convective potential, with strong low-level moisture flux convergence and high specific humidity. There were conditions of thermal instability and vertical upward motion, along with low-level convergence and upper-level divergence. Cold air played an important role in the occurrence and development of this downburst event.

Abstract Background Intestinal barrier is a dynamic interface between the body and the ingested food components, however, dietary components or xenobiotics could compromise intestinal integrity, causing health risks to the host. Gossypol, a toxic component in cottonseed meal (CSM), caused intestinal injury in fish or other monogastric animals. It has been demonstrated that probiotics administration benefits the intestinal barrier integrity, but the efficacy of probiotics in maintaining intestinal health when the host is exposed to gossypol remains unclear. Here, a strain (YC) affiliated to Pediococcus pentosaceus was isolated from the gut of Nile tilapia (Oreochromis niloticus) and its potential to repair gossypol-induced intestinal damage was evaluated. Results A total of 270 Nile tilapia (2.20 ± 0.02 g) were allotted in 3 groups with 3 tanks each and fed with 3 diets including CON (control diet), GOS (control diet containing 300 mg/kg gossypol) and GP (control diet containing 300 mg/kg gossypol and 108 colony-forming unit (CFU)/g P. pentosaceus YC), respectively. After 10 weeks, addition of P. pentosaceus YC restored growth retardation and intestinal injury induced by gossypol in Nile tilapia. Transcriptome analysis and siRNA interference experiments demonstrated that NOD-like receptors (NLR) family caspase recruitment domain (CARD) domain containing 3 (Nlrc3) inhibition might promote intestinal stem cell (ISC) proliferation, as well as maintaining gut barrier integrity. 16S rRNA sequencing and gas chromatography-mass spectrometry (GC-MS) revealed that addition of P. pentosaceus YC altered the composition of gut microbiota and increased the content of propionate in fish gut. In vitro studies on propionate’s function demonstrated that it suppressed nlrc3 expression and promoted wound healing in Caco-2 cell model. Conclusions The present study reveals that P. pentosaceus YC has the capacity to ameliorate intestinal barrier injury by modulating gut microbiota composition and elevating propionate level. This finding offers a promising strategy for the feed industry to incorporate cottonseed meal into fish feed formulations. Graphical Abstract

In the treatment of central nervous system disease, the blood–brain barrier (BBB) is a major obstruction to drug delivery that must be overcome. In this study, we propose a brain-targeted delivery strategy based on selective opening of the BBB. This strategy allows some simple bare nanoparticles to enter the brain when mixed with special opening material; however, the BBB still maintains the ability to completely block molecules from passing through. Based on the screening of BBB opening and matrix delivery materials, we determined that phospholipase A2-catalyzed 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoserine liposomes can efficiently carry drugs into the brain immediately. At an effective dose, this delivery system is safe, especially with its effect on the BBB being reversible. This mix & act delivery system has a simple structure and rapid preparation, making it a strong potential candidate for drug delivery across the BBB.

Abstract Introduction The rapid development of artificial intelligence (AI) in healthcare has exposed the unmet need for growing a multidisciplinary workforce that can collaborate effectively in the learning health systems. Maximizing the synergy among multiple teams is critical for Collaborative AI in Healthcare. Methods We have developed a series of data, tools, and educational resources for cultivating the next generation of multidisciplinary workforce for Collaborative AI in Healthcare. We built bulk‐natural language processing pipelines to extract structured information from clinical notes and stored them in common data models. We developed multimodal AI/machine learning (ML) tools and tutorials to enrich the toolbox of the multidisciplinary workforce to analyze multimodal healthcare data. We have created a fertile ground to cross‐pollinate clinicians and AI scientists and train the next generation of AI health workforce to collaborate effectively. Results Our work has democratized access to unstructured health information, AI/ML tools and resources for healthcare, and collaborative education resources. From 2017 to 2022, this has enabled studies in multiple clinical specialties resulting in 68 peer‐reviewed publications. In 2022, our cross‐discipline efforts converged and institutionalized into the Center for Collaborative AI in Healthcare. Conclusions Our Collaborative AI in Healthcare initiatives has created valuable educational and practical resources. They have enabled more clinicians, scientists, and hospital administrators to successfully apply AI methods in their daily research and practice, develop closer collaborations, and advanced the institution‐level learning health system.

BackgroundMore and more evidence supports the association between myocardial infarction (MI) and osteoarthritis (OA). The purpose of this study is to explore the shared biomarkers and pathogenesis of MI complicated with OA by systems biology.MethodsGene expression profiles of MI and OA were downloaded from the Gene Expression Omnibus (GEO) database. The Weighted Gene Co-Expression Network Analysis (WGCNA) and differentially expressed genes (DEGs) analysis were used to identify the common DEGs. The shared genes related to diseases were screened by three public databases, and the protein-protein interaction (PPI) network was built. GO and KEGG enrichment analyses were performed on the two parts of the genes respectively. The hub genes were intersected and verified by Least absolute shrinkage and selection operator (LASSO) analysis, receiver operating characteristic (ROC) curves, and single-cell RNA sequencing analysis. Finally, the hub genes differentially expressed in primary cardiomyocytes and chondrocytes were verified by RT-qPCR. The immune cell infiltration analysis, subtypes analysis, and transcription factors (TFs) prediction were carried out.ResultsIn this study, 23 common DEGs were obtained by WGCNA and DEGs analysis. In addition, 199 common genes were acquired from three public databases by PPI. Inflammation and immunity may be the common pathogenic mechanisms, and the MAPK signaling pathway may play a key role in both disorders. DUSP1, FOS, and THBS1 were identified as shared biomarkers, which is entirely consistent with the results of single-cell RNA sequencing analysis, and furher confirmed by RT-qPCR. Immune infiltration analysis illustrated that many types of immune cells were closely associated with MI and OA. Two potential subtypes were identified in both datasets. Furthermore, FOXC1 may be the crucial TF, and the relationship of TFs-hub genes-immune cells was visualized by the Sankey diagram, which could help discover the pathogenesis between MI and OA.ConclusionIn summary, this study first revealed 3 (DUSP1, FOS, and THBS1) novel shared biomarkers and signaling pathways underlying both MI and OA. Additionally, immune cells and key TFs related to 3 hub genes were examined to further clarify the regulation mechanism. Our study provides new insights into shared molecular mechanisms between MI and OA.

BackgroundNonadherence to medication among patients with cardiovascular diseases undermines the desired therapeutic outcomes. eHealth interventions emerge as promising strategies to effectively tackle this issue. ObjectiveThe aim of this study was to conduct a network meta-analysis (NMA) to compare and rank the efficacy of various eHealth interventions in improving medication adherence among patients with cardiovascular diseases (CVDs). MethodsA systematic search strategy was conducted in PubMed, Embase, Web of Science, Cochrane, China National Knowledge Infrastructure Library (CNKI), China Science and Technology Journal Database (Weipu), and WanFang databases to search for randomized controlled trials (RCTs) published from their inception on January 15, 2024. We carried out a frequentist NMA to compare the efficacy of various eHealth interventions. The quality of the literature was assessed using the risk of bias tool from the Cochrane Handbook (version 2.0), and extracted data were analyzed using Stata16.0 (StataCorp LLC) and RevMan5.4 software (Cochrane Collaboration). The certainty of evidence was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach. ResultsA total of 21 RCTs involving 3904 patients were enrolled. The NMA revealed that combined interventions (standardized mean difference [SMD] 0.89, 95% CI 0.22-1.57), telephone support (SMD 0.68, 95% CI 0.02-1.33), telemonitoring interventions (SMD 0.70, 95% CI 0.02-1.39), and mobile phone app interventions (SMD 0.65, 95% CI 0.01-1.30) were statistically superior to usual care. However, SMS compared to usual care showed no statistical difference. Notably, the combined intervention, with a surface under the cumulative ranking curve of 79.3%, appeared to be the most effective option for patients with CVDs. Regarding systolic blood pressure and diastolic blood pressure outcomes, the combined intervention also had the highest probability of being the best intervention. ConclusionsThe research indicates that the combined intervention (SMS text messaging and telephone support) has the greatest likelihood of being the most effective eHealth intervention to improve medication adherence in patients with CVDs, followed by telemonitoring, telephone support, and app interventions. The results of these network meta-analyses can provide crucial evidence-based support for health care providers to enhance patients’ medication adherence. Given the differences in the design and implementation of eHealth interventions, further large-scale, well-designed multicenter trials are needed. Trial RegistrationINPLASY 2023120063; https://inplasy.com/inplasy-2023-12-0063/

Abstract Progress in sequencing technologies and clinical experiments has revolutionized immunotherapy on solid and hematologic malignancies. However, the benefits of immunotherapy are limited to specific patient subsets, posing challenges for broader application. To improve its effectiveness, identifying biomarkers that can predict patient response is crucial. Machine learning (ML) play a pivotal role in harnessing multi-omic cancer datasets and unlocking new insights into immunotherapy. This review provides an overview of cutting-edge ML models applied in omics data for immunotherapy analysis, including immunotherapy response prediction and immunotherapy-relevant tumor microenvironment identification. We elucidate how ML leverages diverse data types to identify significant biomarkers, enhance our understanding of immunotherapy mechanisms, and optimize decision-making process. Additionally, we discuss current limitations and challenges of ML in this rapidly evolving field. Finally, we outline future directions aimed at overcoming these barriers and improving the efficiency of ML in immunotherapy research.

Abstract Background Systemic lupus erythematosus (SLE) is a rare autoimmune disorder characterized by an unpredictable course of flares and remission with diverse manifestations. Lupus nephritis, one of the major disease manifestations of SLE for organ damage and mortality, is a key component of lupus classification criteria. Accurately identifying lupus nephritis in electronic health records (EHRs) would therefore benefit large cohort observational studies and clinical trials where characterization of the patient population is critical for recruitment, study design, and analysis. Lupus nephritis can be recognized through procedure codes and structured data, such as laboratory tests. However, other critical information documenting lupus nephritis, such as histologic reports from kidney biopsies and prior medical history narratives, require sophisticated text processing to mine information from pathology reports and clinical notes. In this study, we developed algorithms to identify lupus nephritis with and without natural language processing (NLP) using EHR data from the Northwestern Medicine Enterprise Data Warehouse (NMEDW). Methods We developed five algorithms: a rule-based algorithm using only structured data (baseline algorithm) and four algorithms using different NLP models. The first NLP model applied simple regular expression for keywords search combined with structured data. The other three NLP models were based on regularized logistic regression and used different sets of features including positive mention of concept unique identifiers (CUIs), number of appearances of CUIs, and a mixture of three components (i.e. a curated list of CUIs, regular expression concepts, structured data) respectively. The baseline algorithm and the best performing NLP algorithm were externally validated on a dataset from Vanderbilt University Medical Center (VUMC). Results Our best performing NLP model incorporated features from both structured data, regular expression concepts, and mapped concept unique identifiers (CUIs) and showed improved F measure in both the NMEDW (0.41 vs 0.79) and VUMC (0.52 vs 0.93) datasets compared to the baseline lupus nephritis algorithm. Conclusion Our NLP MetaMap mixed model improved the F-measure greatly compared to the structured data only algorithm in both internal and external validation datasets. The NLP algorithms can serve as powerful tools to accurately identify lupus nephritis phenotype in EHR for clinical research and better targeted therapies.

Abstract Energy transfer is a ubiquitous phenomenon that delivers energy from a blue-shifted emitter to a red-shifted absorber, facilitating wide photonic applications. Two-dimensional (2D) semiconductors provide unique opportunities for exploring novel energy transfer mechanisms in the atomic-scale limit. Herein, we have designed a planar optical microcavity-confined MoS2/hBN/WS2 heterojunction, which realizes the strong coupling among donor exciton, acceptor exciton, and cavity photon mode. This configuration demonstrates an unconventional energy transfer via polariton relaxation, brightening MoS2 with a record-high enhancement factor of ~440, i.e., two-order-of-magnitude higher than the data reported to date. The polariton relaxation features a short characteristic time of ~1.3 ps, resulting from the significantly enhanced intra- and inter-branch exciton-exciton scattering. The polariton relaxation dynamics is associated with Rabi energies in a phase diagram by combining experimental and theoretical results. This study opens a new direction of microcavity 2D semiconductor heterojunctions for high-brightness polaritonic light sources and ultrafast polariton carrier dynamics.

Abstract Background Pathogenic (P) copy number variants (CNVs) may be associated with second-trimester ultrasound soft markers (USMs), and noninvasive prenatal screening (NIPS) can enable interrogate the entire fetal genome to screening of fetal CNVs. This study evaluated the clinical application of NIPS for detecting CNVs among fetuses with USMs in pregnant women not of advanced maternal age (AMA). Results Fetal aneuploidies and CNVs were identified in 6647 pregnant women using the Berry Genomics NIPS algorithm.Those with positive NIPS results underwent amniocentesis for prenatal diagnosis. The NIPS and prenatal diagnosis results were analyzed and compared among different USMs. A total of 96 pregnancies were scored positive for fetal chromosome anomalies, comprising 37 aneuploidies and 59 CNVs. Positive predictive values (PPVs) for trisomy 21, trisomy 18, trisomy 13, and sex chromosome aneuploidies were 66.67%, 80.00%, 0%, and 30.43%, respectively. NIPS sensitivity for aneuploidies was 100%. For CNVs, the PPVs were calculated as 35.59% and false positive rate of 0.57%. There were six P CNVs, two successfully identified by NIPS and four missed, of which three were below the NIPS resolution limit and one false negative. The incidence of aneuploidies was significantly higher in fetuses with absent or hypoplastic nasal bone, while that of P CNVs was significantly higher in fetuses with aberrant right subclavian artery (ARSA), compared with other groups. Conclusions NIPS yielded a moderate PPV for CNVs in non-AMA pregnant women with fetal USM. However, NIPS showed limited ability in identifying P CNVs. Positive NIPS results for CNVs emphasize the need for further prenatal diagnosis. We do not recommend the use of NIPS for CNVs screening in non-AMA pregnant women with fetal USM, especially in fetuses with ARSA.

Considerable efforts have been devoted to treating gastric ulcers. Attempts in this field tend to develop drug delivery systems with prolonged gastric retention time. Herein, we develop novel Chinese herb pollen-derived micromotors as active oral drug delivery system for treating gastric ulcer. Such Chinese herb pollen-derived micromotors are simply produced by asymmetrically sputtering Mg layer onto one side of pollen grains. When exposed to gastric juice, the Mg layer can react with the hydrogen ions, resulting in intensive generation of hydrogen bubbles to propel the micromotors. Benefiting from the autonomous motion and unique spiny structure, our micromotors can move actively in the stomach and adhere to the surrounding tissues. Besides, their special architecture endows the micromotors with salient capacity of drug loading and releasing. Based on these features, we have demonstrated that our Chinese herb pollen-derived micromotors could effective deliver berberine hydrochloride and show desirable curative effect on the gastric ulcer model of mice. Therefore, these Chinese herb pollen-derived micromotors are anticipated to serve as promising oral drug delivery carriers for clinical applications.

Abstract Background Dentigerous cyst are most common odontogenic cyst and they frequently occur at the mandibular third molar. Their asymptomatic long medical history always resulted in severe bone resorption at the distal aspect of the adjacent second molar. BonMaker® ATB demonstrate an excellent autogenous bone graft candidacy. The aim of this study is to share a single team’s experience of dentigerous cyst osseous defect repairing by applying autogenous tooth sticky bone graft. Method In total, 18 patients with dentigerous cyst, which was arised from mandibular third molar unilaterally, were enrolled in this study. Enucleation of dentigerous cyst was performed extracting with involving teeth under general anesthesia. Autogenous tooth sticky bone graft was prepared using extracted tooth and autogenous fibrin glue. Subsequently, grafting was performed above covering with concentrate growth factors. Patients were followed up at sixth months. Results They were eleven male and seven female patients. Their ages ranged from 20 to 40 years, with a mean of 31 years. Primary wound healing of all sites was achieved in all the patients. Sixth months postoperative radiographic assessment show that dentigerous cysts osseous defects of seventeen patients were good bone filling and ossification. One patient occurred slight bone resorption at the distal aspect of the adjacent second molar. Conclusion Within the limitation of sample size and retrospective nature of the present study, autogenous tooth sticky bone graft demonstrates one of the best alternative alveolar bones repairing graft.

Abstract Plants usually produce defence metabolites in non-active forms to minimize the risk of harm to themselves and spatiotemporally activate these defence metabolites upon pathogen attack. This so-called two-component system plays a decisive role in the chemical defence of various plants. Here, we discovered that Panax notoginseng, a valuable medicinal plant, has evolved a two-component chemical defence system composed of a chloroplast-localized β-glucosidase, denominated PnGH1, and its substrates 20(S)-protopanaxadiol ginsenosides. The β-glucosidase and its substrates are spatially separated in cells under physiological conditions, and ginsenoside hydrolysis is therefore activated only upon chloroplast disruption, which is caused by the induced exoenzymes of pathogenic fungi upon exposure to plant leaves. This activation of PnGH1-mediated hydrolysis results in the production of a series of less-polar ginsenosides by selective hydrolysis of an outer glucose at the C-3 site, with a broader spectrum and more potent antifungal activity in vitro and in vivo than the precursor molecules. Furthermore, such β-glucosidase-mediated hydrolysis upon fungal infection was also found in the congeneric species P. quinquefolium and P. ginseng. Our findings reveal a two-component chemical defence system in Panax species and offer insights for developing botanical pesticides for disease management in Panax species.

Systemic lupus erythematosus (SLE) is an autoimmune inflammatory tissue disease. In view of the explosive growth in research on SLE, bibliometrics was performed to evaluate the 100 top-cited papers in this realm. We performed the search with terms “systemic lupus erythematosus” the Web of Science Core Collection database on May 3, 2023. Relevant literatures were screened. Data were extracted and analyzed by SPSS. The citations of 100 top-cited SLE studies spanned from 472 to 13,557. Most studies (60 out of 100) were conducted in the United States. Total citation times were positively associated with ACY, which was negatively correlated with the length of time since publication. Approximately half of the studies focused on the underlying mechanisms of SLE. New biologic therapies garnered attention and development. Our findings provide valuable insights into the developments in crucial areas of SLE and shed contributions to future studies.

There are various types of initial defects in weld joints of orthotropic steel deck, which significantly impact the fatigue crack growth behavior of the welds. The traditional single-crack growth model is not appropriate to be utilized for the fatigue investigation of welds containing multiple defects. This study analyzed the dynamic evolution behavior of crack-inclusion interactions in the weld toe of rib-to-deck joints based on the fracture mechanics theory. The influence of defect-related parameters on crack fatigue life was discussed. Numerical simulations and fatigue test were conducted to investigate the dynamic interaction behavior of the crack-inclusion under fatigue loading. A merging criterion for multiple inclusions was proposed to simply the fatigue life analysis of coupled cracks. The numerical results show that the stiff inclusion has a shielding effect on the crack growth. The effect is affected by the relative depth of the crack and inclusion (a0/R), the interaction spacing of defects (S), and the burial depth of the inclusion (h). The shielding effect becomes negligible under the condition a0/R≥3. The fatigue life of the interactive crack increases by up to 23 % compared to single crack. Fully buried inclusions have a limited impact on crack growth. The fatigue life of the interactive crack shows a non-monotonic increase with the quantities of inclusions, with double inclusion clusters. It is demonstrated that the highest shielding effect will increase the fatigue life by 26 %. The proposed merging criterion simplifies the prediction of the fatigue life for welded joint containing multiple inclusions. The numerical result provides a referencing database for fatigue life evaluation of steel structures with multiple welding defects.

Abstract Endo‐microscopy is crucial for real‐time 3D visualization of internal tissues and subcellular structures. Conventional methods rely on axial movement of optical components for precise focus adjustment, limiting miniaturization and complicating procedures. Meta‐device, composed of artificial nanostructures, is an emerging optical flat device that can freely manipulate the phase and amplitude of light. Here, an intelligent fluorescence endo‐microscope is developed based on varifocal meta‐lens and deep learning (DL). The breakthrough enables in vivo 3D imaging of mouse brains, where varifocal meta‐lens focal length adjusts through relative rotation angle. The system offers key advantages such as invariant magnification, a large field‐of‐view, and optical sectioning at a maximum focal length tuning range of ≈2 mm with 3 µm lateral resolution. Using a DL network, image acquisition time and system complexity are significantly reduced, and in vivo high‐resolution brain images of detailed vessels and surrounding perivascular space are clearly observed within 0.1 s (≈50 times faster). The approach will benefit various surgical procedures, such as gastrointestinal biopsies, neural imaging, brain surgery, etc.

In this paper, we introduce a new structure of multioptical bottles formed by the chirped circular Bessel Gaussian beams carrying annular spiral-zone power-exponent-phase (ASP). The ASP is a general term for complex phases composed of the radial phase, equiphase, and power spiral phase. By combining the influence of autofocusing properties, chirp factor, and ASP mode, the propagation dynamics of the proposed multioptical bottles beam such as the sizes, lengths, number and locations can be flexibly manipulated. Intriguingly, the effect of the power order of ASP mode on the beam propagation dynamics is firstly introduced and examined. The proposed beams can enable diversification the optical tweezers system in multiparticle manipulation, which is verified by the radiation force analysis on a Rayleigh particle.

Few studies examining the patient outcomes of concurrent neurological manifestations during acute COVID-19 leveraged multinational cohorts of adults and children or distinguished between central and peripheral nervous system (CNS vs. PNS) involvement. Using a federated multinational network in which local clinicians and informatics experts curated the electronic health records data, we evaluated the risk of prolonged hospitalization and mortality in hospitalized COVID-19 patients from 21 healthcare systems across 7 countries. For adults, we used a federated learning approach whereby we ran Cox proportional hazard models locally at each healthcare system and performed a meta-analysis on the aggregated results to estimate the overall risk of adverse outcomes across our geographically diverse populations. For children, we reported descriptive statistics separately due to their low frequency of neurological involvement and poor outcomes. Among the 106,229 hospitalized COVID-19 patients (104,031 patients ≥18 years; 2,198 patients

Abstract The Multi‐Threat Medical Countermeasure (MTMC) technique is crucial for developing common biochemical signaling pathways, molecular mediators, and cellular processes. This study revealed that the Nod‐like receptor 3 (NLRP3) inflammasome pathway may be a significant contributor to the cytotoxicity induced by various organophosphorus pesticides (OPPs). The study demonstrated that exposure to six different types of OPPs (paraoxon, dichlorvos, fenthion, dipterex, dibrom, and dimethoate) led to significant cytotoxicity in BV2 cells, which was accompanied by increased expression of NLRP3 inflammasome complexes (NLRP3, ASC, Caspase‐1) and downstream inflammatory cytokines (IL‐1β, IL‐18), in which the order of cytotoxicity was dichlorvos > dipterex > dibrom > paraoxon > fenthion > dimethoate, based on the IC50 values of 274, 410, 551, 585, 2,158, and 1,527,566 μM, respectively. The findings suggest that targeting the NLRP3 inflammasome pathway could be a potential approach for developing broad‐spectrum antitoxic drugs to combat multi‐OPPs‐induced toxicity. Moreover, inhibition of NLRP3 efficiently protected the cells against cytotoxicity induced by these six OPPs, and the expression of NLRP3, ASC, Caspase‐1, IL‐1β, and IL‐18 decreased accordingly. The order of NLRP3 affinity for OPPs was dimethoate > paraoxon > dichlorvos > dibrom > (fenthion and dipterex) based on KD values of 89.8, 325, 1,460, and 2,690 μM, respectively. Furthermore, the common molecular mechanism of NLRP3‐OPPs was clarified by the presence of toxicity effector groups (benzene ring, nitrogen/oxygen‐containing functional group); =O, ‐O‐, or =S (active) groups; and combination residues (Gly271, Asp272). This finding provided valuable insights into exploring the common mechanisms of multiple threats and developing effective therapeutic strategies to prevent OPPs poisoning.

Antisense oligonucleotides (ASONs)-based therapeutics offers tremendous promise for the treatment of diverse diseases. However, there is still a need to develop ASONs with enhanced stability against enzymes, improved drug delivery, and enhanced biological potency. In this study, we propose a novel anisamide (AA)-conjugated hairpin oligonucleotide prodrug loading with chemotherapeutic agent (doxorubicin, DOX) (AA-loop-ASON/DOX) for oncotherapy. Results indicated that the introduction of a hairpin conformation and AA ligand in prodrug significantly improved the stability against enzymatic hydrolysis, as well as the cellar uptake of ASONs and DOX. The incorporation of disulfide bonds could trigger mechanical opening, resulting in the release of ASON and DOX in response to the intracellular glutathione (GSH) in tumors. Moreover, the composite of DOX-loading ASONs prodrug exhibited a robust and selective inhibition of tumor cell proliferation. This paper introduces a novel design concept for nucleic acid-based therapeutics, aiming to enhance the delivery of drug and improve biological effectiveness.

Abstract New therapeutic targets and drugs are urgently needed to halt the fibrosing process in idiopathic pulmonary fibrosis (IPF). SHR‐1906 is a novel fully humanized monoclonal antibody against the connective tissue growth factor, which plays an essential role in the genesis of IPF. We assessed the safety, tolerability, pharmacokinetics (PKs), and immunogenicity of single dose SHR‐1906 in healthy participants. This was a randomized, double‐blind, placebo‐controlled, dose‐escalation, phase I study. Twelve healthy participants for each dose level were enrolled to receive single ascending doses of SHR‐1906 intravenously (1.5, 6, 12, 20, 30, and 45 mg/kg) or placebo and followed for 71 days. The primary end points were safety and tolerability. Treatment‐related treatment‐emergent adverse events occurred in 25 participants (46.3%) in the SHR‐1906 group and 11 (61.1%) in the placebo group. No serious adverse events occurred. Over the dose range investigated, the geometric mean clearance was 0.14–0.63 mL/h/kg, the geometric mean volume of distribution at steady‐state was 47.4–75.5 mL/kg, and the terminal elimination half‐life was 51.9–349 h. SHR‐1906 showed nonlinear PKs. The peak concentration increased in a dose‐proportional manner, whereas the area under the concentration–time curve showed a greater than dose‐proportional increase. Anti‐drug antibodies of SHR‐1906 were detected in nine of 54 participants (16.7%). A single dose of SHR‐1906 up to 45 mg/kg demonstrated a favorable tolerability profile in healthy participants. The PKs and immunogenicity of SHR‐1906 were evaluated, supporting further clinical development.

Objective To evaluate if a machine learning approach can accurately predict antidepressant treatment outcome using electronic health records (EHRs) from patients with depression. Method This study examined 808 patients with depression at a New York City‐based outpatient mental health clinic between June 13, 2016 and June 22, 2020. Antidepressant treatment outcome was defined based on trend in depression symptom severity over time and was categorized as either “Recovering” or “Worsening” (i.e., non‐Recovering), measured by the slope of individual‐level Patient Health Questionnaire‐9 (PHQ‐9) score trajectory spanning 6 months following treatment initiation. A patient was designated as “Recovering” if the slope is less than 0 and as “Worsening” if the slope was no less than 0. Multiple machine learning (ML) models including L2 norm regularized Logistic Regression, Naive Bayes, Random Forest, and Gradient Boosting Decision Tree (GBDT) were used to predict treatment outcome based on additional data from EHRs, including demographics and diagnoses. Shapley Additive Explanations were applied to identify the most important predictors. Results The GBDT achieved the best results of predicting “Recovering” (AUC: 0.7654 ± 0.0227; precision: 0.6002 ± 0.0215; recall: 0.5131 ± 0.0336). When excluding patients with low PHQ‐9 scores (

AbstractContext Previous studies have highlighted significant therapeutic effects of Qiqilian (QQL) capsule on hypertension in spontaneously hypertensive rats (SHRs); however, its underlying molecular mechanism remains unclear.Obejective We investigated the potential mechanism by which QQL improves hypertension-induced vascular endothelial dysfunction (VED).Materials and methods In vivo, SHRs were divided into four groups (20 per group) and were administered gradient doses of QQL (0, 0.3, 0.6, and 1.2 g/kg) for 8 weeks, while Wistar Kyoto rats were used as normal control. The vascular injury extent, IL-1β and IL-18 levels, NLRP3, ASC and caspase-1 contents were examined. In vitro, the effects of QQL-medicated serum on angiotensin II (AngII)-induced inflammatory and autophagy in human umbilical vein endothelial cells (HUVECs) were assessed.Result Compared with the SHR group, QQL significantly decreased thickness (125.50 to 105.45 μm) and collagen density (8.61 to 3.20%) of arterial vessels, and reduced serum IL-1β (96.25 to 46.13 pg/mL) and IL-18 (345.01 to 162.63 pg/mL) levels. The NLRP3 and ACS expression in arterial vessels were downregulated (0.21- and 0.16-fold, respectively) in the QQL-HD group compared with the SHR group. In vitro, QQL treatment restored NLRP3 and ASC expression, which was downregulated approximately 2-fold compared with that of AngII-induced HUVECs. Furthermore, QQL decreased LC3II and increased p62 contents (p

Abstract African Americans have a significantly higher risk of developing chronic kidney disease, especially focal segmental glomerulosclerosis -, than European Americans. Two coding variants (G1 and G2) in the APOL1 gene play a major role in this disparity. While 13% of African Americans carry the high-risk recessive genotypes, only a fraction of these individuals develops FSGS or kidney failure, indicating the involvement of additional disease modifiers. Here, we show that the presence of the APOL1 p.N264K missense variant, when co-inherited with the G2 APOL1 risk allele, substantially reduces the penetrance of the G1G2 and G2G2 high-risk genotypes by rendering these genotypes low-risk. These results align with prior functional evidence showing that the p.N264K variant reduces the toxicity of the APOL1 high-risk alleles. These findings have important implications for our understanding of the mechanisms of APOL1-associated nephropathy, as well as for the clinical management of individuals with high-risk genotypes that include the G2 allele.

Abstract Poly (ADP-ribose) polymerase inhibitors (PARPi) are selectively active in ovarian cancer (OC) with homologous recombination (HR) deficiency (HRD) caused by mutations in BRCA1/2 and other DNA repair pathway members. We sought molecular targeted therapy that induce HRD in HR-proficient cells to induce synthetic lethality with PARPi and extend the utility of PARPi. Here, we demonstrate that lysine-specific demethylase 1 (LSD1) is an important regulator for OC. Importantly, genetic depletion or pharmacological inhibition of LSD1 induces HRD and sensitizes HR-proficient OC cells to PARPi in vitro and in multiple in vivo models. Mechanistically, LSD1 inhibition directly impairs transcription of BRCA1/2 and RAD51, three genes essential for HR, dependently of its canonical demethylase function. Collectively, our work indicates combination with LSD1 inhibitor could greatly expand the utility of PARPi to patients with HR-proficient tumor, warranting assessment in human clinical trials.

Abstract Clostridioides difficile (C. diff.) infection (CDI) is a leading cause of hospital acquired diarrhea in North America and Europe and a major cause of morbidity and mortality. Known risk factors do not fully explain CDI susceptibility, and genetic susceptibility is suggested by the fact that some patients with colons that are colonized with C. diff. do not develop any infection while others develop severe or recurrent infections. To identify common genetic variants associated with CDI, we performed a genome-wide association analysis in 19,861 participants (1349 cases; 18,512 controls) from the Electronic Medical Records and Genomics (eMERGE) Network. Using logistic regression, we found strong evidence for genetic variation in the DRB locus of the MHC (HLA) II region that predisposes individuals to CDI (P > 1.0 × 10–14; OR 1.56). Altered transcriptional regulation in the HLA region may play a role in conferring susceptibility to this opportunistic enteric pathogen.

Metasurfaces have attracted considerable attention because of their unique optical capabilities to control the fundamental properties of light, such as amplitude, phase, and polarization. The flat nature of metasurfaces can help reduce the complexities and bulk of conventional optical systems. After a decade of rapid progress, metasurfaces are close to maturity and have found their role in various optical applications. This review emphasizes the significant advancements and emerging applications of metasurfaces in biomedical optics, particularly focusing on beam shaping for laser treatments, light-sheet fluorescence microscopy, HiLo microscopy, and optical trapping. Looking forward, we discuss foreseeable challenges for integrating metasurfaces into biomedical, preclinical, and clinical systems.

Abstract Epigenetic regulation refers to the alteration of gene expression independent of changes in DNA sequence. It involves chemical modifications such as DNA methylation, histone methylation, and histone acetylation, which are regulated by a coordinated interplay of various regulators to ensure precise spatial and temporal regulation of gene expression. Epigenetic aberrations are commonly observed in cancer and are considered as hallmarks of cancer. In recent years, small molecules targeting specific epigenetic regulators have been developed and are demonstrating promising therapeutic potential in preclinical and clinical trials for cancer treatment. In this review, we summarize the essential regulatory mechanisms and dysfunctions of epigenetic regulators involved in DNA methylation, histone methylation, and histone acetylation during tumor development and progression. Moreover, we discuss the current advances and challenges in cancer epigenetic therapy that target these mechanisms in both hematologic malignancies and solid tumors. Finally, we discuss the potential of combining epigenetic drugs with other therapies, including chemotherapy, radiotherapy, targeted therapy, and immunotherapy, as a promising approach for cancer treatment. Overall, we aim to enhance the understanding of epigenetic regulation in cancer therapy and explore targeted therapeutic strategies based on these mechanisms, to ultimately advance cancer therapy and improve patient prognosis.

Root rot is one of the main reasons for yield losses of red kidney bean (Phaseolus vulgaris) production. Pre-inoculation with Trichoderma harzianum can effectively lower the incidence of red kidney bean root rot. In this study, four treatments including CK (control), Fu13 (Fusarium oxysporum), T891 (T. harzianum) and T891 + Fu13 (T. harzianum + F. oxysporum) were arranged in a pot experiment to investigate how T891 affected the incidence and severity of root rot, plant growth, and changes of defense enzyme activity in red kidney bean plants. Community composition and diversity of the rhizosphere microbiota was evaluated through high-throughput sequencing, and co-occurrence network was analyzed. The results showed that when compared to the Fu13 treatment, pre-inoculation with T891 reduced the incidence and severity of red kidney bean root rot by 40.62 and 68.03% (p

IntroductionImmune checkpoint inhibitor-induced inflammatory arthritis (ICI-IA) poses a major clinical challenge to ICI therapy for cancer, with 13% of cases halting ICI therapy and ICI-IA being difficult to identify for timely referral to a rheumatologist. The objective of this study was to rapidly identify ICI-IA patients in clinical data and assess associated immune-related adverse events (irAEs) and risk factors.MethodsWe conducted a retrospective study of the electronic health records (EHRs) of 89 patients who developed ICI-IA out of 2451 cancer patients who received ICI therapy at Northwestern University between March 2011 to January 2021. Logistic regression and random forest machine learning models were trained on all EHR diagnoses, labs, medications, and procedures to identify ICI-IA patients and EHR codes indicating ICI-IA. Multivariate logistic regression was then used to test associations between ICI-IA and cancer type, ICI regimen, and comorbid irAEs.ResultsLogistic regression and random forest models identified ICI-IA patients with accuracies of 0.79 and 0.80, respectively. Key EHR features from the random forest model included ICI-IA relevant features (joint pain, steroid prescription, rheumatoid factor tests) and features suggesting comorbid irAEs (thyroid function tests, pruritus, triamcinolone prescription). Compared to 871 adjudicated ICI patients who did not develop arthritis, ICI-IA patients had higher odds of developing cutaneous (odds ratio [OR]=2.66; 95% Confidence Interval [CI] 1.63-4.35), endocrine (OR=2.09; 95% CI 1.15-3.80), or gastrointestinal (OR=2.88; 95% CI 1.76-4.72) irAEs adjusting for demographics, cancer type, and ICI regimen. Melanoma (OR=1.99; 95% CI 1.08-3.65) and renal cell carcinoma (OR=2.03; 95% CI 1.06-3.84) patients were more likely to develop ICI-IA compared to lung cancer patients. Patients on nivolumab+ipilimumab were more likely to develop ICI-IA compared to patients on pembrolizumab (OR=1.86; 95% CI 1.01-3.43).DiscussionOur machine learning models rapidly identified patients with ICI-IA in EHR data and elucidated clinical features indicative of comorbid irAEs. Patients with ICI-IA were significantly more likely to also develop cutaneous, endocrine, and gastrointestinal irAEs during their clinical course compared to ICI therapy patients without ICI-IA.

Abstract Glioma is one of the most common malignant tumors of the central nervous system, leading high mortality rates in human. Aggregation‐induced emission (AIE) photosensitizers‐based photodynamic therapy (PDT) has emerged as a promising therapeutic strategy for least‐invasive treatment of glioma, which involves local irradiation of the tumor using an external near‐infrared (NIR) laser. Unfortunately, most AIE photosensitizers suffered from poorly penetration of the visible light excitation, bad spatiotemporal resolution in deep tissues and low efficient blood‐brain barrier (BBB) crossing ability, which greatly limited the clinical practice of AIE photosensitizers for especially deep‐seated brain tumor treatment. In this work, we developed a multifunctional NIR‐driven theranostic agent through hybrid of AIE photosensitizers TIND with rare‐earth doping nanoparticles (RENPs) NaGdF4:Nd/Yb/Tm with up/down dual‐mode conversion luminescence. The theranostic agent was further decorated with D‐type neuropeptide DNPY for crossing BBB and targeting glioma. Under the 808‐nm light irradiation, the down‐conversion NIR‐II luminescence could indicate the position glioma and the upconversion NIR‐I luminescence could trigger the AIE photosensitizers producing reactive oxygen species to inhibit orthotopic glioma tumor growth in situ. These results demonstrate that the integration of D‐type neuropeptide, AIE photosensitizers and RENPs could be promising candidates for in vivo NIR‐II fluorescence image‐guided through‐skull PDT treatments of brain tumors.

Abstract The characterization of atherosclerotic plaques to predict their vulnerability to rupture remains a diagnostic challenge. Despite existing imaging modalities, none have proven their abilities to identify metabolically active oxidized low‐density lipoprotein (oxLDL), a marker of plaque vulnerability. To this end, we developed a machine learning‐directed electrochemical impedance spectroscopy (EIS) platform to analyze oxLDL‐rich plaques, with immunohistology serving as the ground truth. We fabricated the EIS sensor by affixing a six‐point microelectrode configuration onto a silicone balloon catheter and electroplating the surface with platinum black (PtB) to improve the charge transfer efficiency at the electrochemical interface. To demonstrate clinical translation, we deployed the EIS sensor to the coronary arteries of an explanted human heart from a patient undergoing heart transplant and interrogated the atherosclerotic lesions to reconstruct the 3D EIS profiles of oxLDL‐rich atherosclerotic plaques in both right coronary and left descending coronary arteries. To establish effective generalization of our methods, we repeated the reconstruction and training process on the common carotid arteries of an unembalmed human cadaver specimen. Our findings indicated that our DenseNet model achieves the most reliable predictions for metabolically vulnerable plaque, yielding an accuracy of 92.59% after 100 epochs of training.

Lithium metal batteries (LMBs) with high energy density show substantial promise as advanced electrochemical energy storage solutions, although they encounter persistent challenges pertaining to cycling stability and safety performance. Conventional homogeneous electrolytes widely employed in LMBs are inherently flammable, possessing a limited electrochemical window, thereby presenting obstacles to meeting the stringent safety and cycling criteria. In this investigation, we devised an asymmetric fire-retardant quasi-solid polymer electrolyte to mitigate thermal runaway risks and chemical/electrochemical instability at the electrolyte–electrode interface in LMBs. Specifically, on the cathode side, a poly(vinylidene fluoride-co-hexafluoropropylene gel electrolyte incorporating flame-retarded organophosphates exhibited remarkable compatibility and heightened thermal stability when paired with high-voltage Ni-rich layered materials. Simultaneously, a thin yet resilient polyether gel electrolyte was in-situ synthesized on lithium metal anodes, expanding the applicability of fire-retardant electrolytes to lithium metal anodes while suppressing the formation of lithium dendrites. Consequently, high-voltage LMBs utilizing asymmetric fire-retardant electrolytes demonstrated a substantial enhancement in safety performance and cycling stability. This research delineates a viable pathway toward realizing secure and consistent cycling in high-energy-density energy storage systems.

Introduction Traditional survey-based surveillance is costly, limited in its ability to distinguish diabetes types and time-consuming, resulting in reporting delays. The Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network seeks to advance diabetes surveillance efforts in youth and young adults through the use of large-volume electronic health record (EHR) data. The network has two primary aims, namely: (1) to refine and validate EHR-based computable phenotype algorithms for accurate identification of type 1 and type 2 diabetes among youth and young adults and (2) to estimate the incidence and prevalence of type 1 and type 2 diabetes among youth and young adults and trends therein. The network aims to augment diabetes surveillance capacity in the USA and assess performance of EHR-based surveillance. This paper describes the DiCAYA Network and how these aims will be achieved.Methods and analysis The DiCAYA Network is spread across eight geographically diverse US-based centres and a coordinating centre. Three centres conduct diabetes surveillance in youth aged 0–17 years only (component A), three centres conduct surveillance in young adults aged 18–44 years only (component B) and two centres conduct surveillance in components A and B. The network will assess the validity of computable phenotype definitions to determine diabetes status and type based on sensitivity, specificity, positive predictive value and negative predictive value of the phenotypes against the gold standard of manually abstracted medical charts. Prevalence and incidence rates will be presented as unadjusted estimates and as race/ethnicity, sex and age-adjusted estimates using Poisson regression.Ethics and dissemination The DiCAYA Network is well positioned to advance diabetes surveillance methods. The network will disseminate EHR-based surveillance methodology that can be broadly adopted and will report diabetes prevalence and incidence for key demographic subgroups of youth and young adults in a large set of regions across the USA.

Studies of the AMPK/PGC-1α signaling pathway and exercise-induced metabolism have facilitated the development of anti-fatigue agents and exercise mimetics. In this work, adenosine and its 22 derivatives, typical of substitutions at the hydroxyl group of the sugar moiety, were firstly evaluated as anti-fatigue agents. In the running wheel tests, adenosine and most derivatives demonstrated a significant increase in the exhaustion distance when compared to the control group. Particularly, the optimized compound 2 exhibited a 3.1-fold increase in exhaustion distance compared to the positive control group treated with AICAR, and a remarkable 9.8-fold increase compared to the blank control group. Furthermore, improved performances were observed in weight-loaded swimming, high jumping, hanging wire, and tail suspension tests. Compound 2 not only reduced levels of lactic acid (LA) and blood urea nitrogen (BUN), but also preserved hepatic and muscle glycogen content during exercise. Notably, compound 2 activated AMPK/PGC-1α pathway without stimulating the central nervous system. Moreover, compound 2 demonstrated a favorable safety in vivo at a dose of 1.96 × 10-5 mol/kg for 21 days. This study unveils, for the first time, the ability of adenosine and its derivatives to resist exercise-induced fatigue, thereby providing promising lead compounds for the development of drugs aimed to prevent and treat fatigue-related diseases. Moreover, it sheds light on the potential therapeutic approaches utilizing endogenous substance.

Abstract Genes act in concert with each other in specific contexts to perform their functions. Determining how these genes influence complex traits requires a mechanistic understanding of expression regulation across different conditions. It has been shown that this insight is critical for developing new therapies. Transcriptome-wide association studies have helped uncover the role of individual genes in disease-relevant mechanisms. However, modern models of the architecture of complex traits predict that gene-gene interactions play a crucial role in disease origin and progression. Here we introduce PhenoPLIER, a computational approach that maps gene-trait associations and pharmacological perturbation data into a common latent representation for a joint analysis. This representation is based on modules of genes with similar expression patterns across the same conditions. We observe that diseases are significantly associated with gene modules expressed in relevant cell types, and our approach is accurate in predicting known drug-disease pairs and inferring mechanisms of action. Furthermore, using a CRISPR screen to analyze lipid regulation, we find that functionally important players lack associations but are prioritized in trait-associated modules by PhenoPLIER. By incorporating groups of co-expressed genes, PhenoPLIER can contextualize genetic associations and reveal potential targets missed by single-gene strategies.

Abstract Exciton polaritons in atomically thin transition-metal dichalcogenide microcavities provide a versatile platform for advancing optoelectronic devices and studying the interacting Bosonic physics at ambient conditions. Rationally engineering the favorable properties of polaritons is critically required for the rapidly growing research. Here, we demonstrate the manipulation of nonlinear polaritons with the lithographically defined potential landscapes in monolayer WS2 microcavities. The discretization of photoluminescence dispersions and spatially confined patterns indicate the deterministic on-site localization of polaritons by the artificial mesa cavities. Varying the trapping sizes, the polariton-reservoir interaction strength is enhanced by about six times through managing the polariton–exciton spatial overlap. Meanwhile, the coherence of trapped polaritons is significantly improved due to the spectral narrowing and tailored in a picosecond range. Therefore, our work not only offers a convenient approach to manipulating the nonlinearity and coherence of polaritons but also opens up possibilities for exploring many-body phenomena and developing novel polaritonic devices based on 2D materials.

Abstract Objective The objective of this study is to explore the relationship between family communication, family violence, problematic internet use, anxiety, and depression and validate their potential mediating role. Methods The study population consisted of Chinese adolescents aged 12 to 18 years, and a cross-sectional survey was conducted in 2022. Structural equation models were constructed using AMOS 25.0 software to examine the factors that influence adolescent anxiety and depression and the mediating effects of problematic internet use and family violence. Results The results indicate that family communication was significantly and negatively related to family violence (β = -.494, p

Citrate is an essential substrate for energy metabolism that plays critical roles in regulating glucose and lipid metabolic homeostasis. However, the action of citrate in regulating nutrient metabolism in fish remains poorly understood. Here, we investigated the effects of dietary sodium citrate on growth performance and systematic energy metabolism in juvenile Nile tilapia (Oreochromis niloticus). A total of 270 Nile tilapia (2.81 ± 0.01 g) were randomly divided into three groups (3 replicates per group, 30 fish per replicate) and fed with control diet (35% protein and 6% lipid), 2% and 4% sodium citrate diets, respectively, for 8 weeks. The results showed that sodium citrate exhibited no effect on growth performance (P > 0.05). The whole-body crude protein, serum triglyceride and hepatic glycogen contents were significantly increased in the 4% sodium citrate group (P < 0.05), but not in the 2% sodium citrate group (P > 0.05). The 4% sodium citrate treatment significantly increased the serum glucose and insulin levels at the end of feeding trial and also in the glucose tolerance test (P < 0.05). The 4% sodium citrate significantly enhanced the hepatic phosphofructokinase activity and inhibited the expression of pyruvate dehydrogenase kinase isozyme 2 and phosphor-pyruvate dehydrogenase E1 component subunit alpha proteins (P < 0.05). Additionally, the 4% sodium citrate significantly increased hepatic triglyceride and acetyl-CoA levels, while the expressions of carnitine palmitoyl transferase 1a protein were significantly down-regulated by the 4% sodium citrate (P < 0.05). Besides, the 4% sodium citrate induced crude protein deposition in muscle by activating mTOR signaling and inhibiting AMPK signaling (P < 0.05). Furthermore, the 4% sodium citrate significantly suppressed serum aspartate aminotransferase and alanine aminotransferase activities, along with the lowered expression of pro-inflammatory genes, such as nfκb, tnfα and il8 (P < 0.05). Although the 4% sodium citrate significantly increased phosphor-nuclear factor-kB p65 protein expression (P < 0.05), no significant tissue damage or inflammation occurred. Taken together, dietary supplementation of sodium citrate could exhibit a double-edged effect in Nile tilapia, with the positive aspect in promoting nutrient deposition and the negative aspect in causing hyperglycemia and insulin resistance.

Edible fungi have certain photo-sensitivity during the mushroom emergence stage, but there have been few relevant studies on the responses of Ganoderma lucidum to different light irradiation conditions. Ganoderma lucidum were planted in an environmentally controllable mushroom room with different light supply modes that were, respectively, continuous white light (CK), red light (R), green light (G), blue light (B), and intermittent red light (R-), green light (G-), and blue light (B-), with a total light intensity of 15 μmol·m−2·s−1 and a light/dark (L/D) period of 12 h/12 h for each treatment. The interval in intermittent light treatments was 30 min. The optimal light supply mode suitable for the growth of Ganoderma lucidum was explored by analyzing the characteristics, nutritional quality, and extracellular enzyme activity in mushrooms exposed to different light treatments. The results showed that red light (whether in continuous or intermittent supply modes) inhibited the fruiting body differentiation of Ganoderma lucidum, showing delayed differentiation or complete undifferentiation. The highest stipe length and pileus diameter of fruiting bodies were detected under G- treatment, which were, respectively, increased by 71.3% and 3.2% relative to the control. The highest weight of fruiting bodies was detected under G treatment, which was significantly increased by 21.4% compared to the control (p < 0.05). Intermittent light mode seemed to be more conducive to the size development of the fruiting body, while continuous light mode was beneficial for increasing the weight. The highest contents of crude protein and total triterpenes in pileus were detected under G treatment (significantly 14.9% and 28.1% higher than the control, respectively), while that of the crude polysaccharide was detected under G- treatment (significantly 35.7% higher than the control) (p < 0.05). The highest activities of extracellular enzymes such as cellulase, hemicellulase, laccase, lignin peroxidase, and amylase were detected in fruiting bodies subjected to G treatment, which were significantly increased by 11.9%~30.7% in the pileus and 9.5%~44.5% in the stipe. Green light might increase the weight and nutrient accumulation in the pileus of Ganoderma lucidum via up-regulating the extracellular enzyme activities. This study provides an effective light supply strategy for regulating the light environment in the industrial production of Ganoderma lucidum.

SiO2 has a much higher theoretical specific capacity (1965 mAh g−1) than graphite, making it a promising anode material for lithium-ion batteries, but its low conductivity and volume expansion problems need to be improved urgently. In this work, pompon mum-like SiO2/C nanospheres with the sandwich and porous nanostructure were obtained by using dendritic fibrous nano silica (DFNS) and glucose as matrix and carbon source, respectively, through hydrothermal, carbonization and etching operations. The influence of SiO2 content and porous structure on its electrochemical performance was discussed in detail. The final results showed that the C/DFNS-6 with a SiO2 content of 6 wt% exhibits the best electrochemical performance as a negative electrode material for lithium-ion batteries due to its optimal specific surface area, porosity, and appropriate SiO2 content. C/DFNS-6 displays a high specific reversible capacity of 986 mAh g−1 at 0.2 A g−1 after 200 cycles, and 529 mAh g−1 at a high current density (1.0 A g−1) after 300 cycles. It also has excellent rate capability, with a reversible capacity that rises from 599 mAh g−1 to 1066 mAh g−1 when the current density drops from 4.0 A g−1 to 0.2 A g−1. These SiO2/C specific pompon mum-like nanospheres with excellent electrochemical performance have great research significance in the field of lithium-ion batteries.

Using DNA as the next-generation medium for data storage offers unparalleled advantages in terms of data density, storage duration, and power consumption as compared to existing data storage technologies. To meet the high-speed data writing requirements in DNA data storage, this paper proposes a novel design for an ultra-high-density and high-throughput DNA synthesis platform. The presented design mainly leverages two functional modules: a dynamic random-access memory (DRAM)-like integrated circuit (IC) responsible for electrode addressing and voltage supply, and the static droplet array (SDA)-based microfluidic structure to eliminate any reaction species diffusion concern in electrochemical DNA synthesis. Through theoretical analysis and simulation studies, we validate the effective addressing of 10 million electrodes and stable, adjustable voltage supply by the integrated circuit. We also demonstrate a reaction unit size down to 3.16 × 3.16 μm2, equivalent to 10 million/cm2, that can rapidly and stably generate static droplets at each site, effectively constraining proton diffusion. Finally, we conducted a synthesis cycle experiment by incorporating fluorescent beacons on a microfabricated electrode array to examine the feasibility of our design.