A dataset for fine-grained seed recognition.

The research of plant seeds has always been a focus of agricultural and forestry research, and seed identification is an indispensable part of it. With the continuous application of artificial intelligence technology in the field of agriculture, seed identification through computer vision can effectively promote the development of agricultural and forestry wisdom. Data is the foundation of computer vision, but there is a lack of suitable datasets in the agricultural field. In this paper, a seed dataset named LZUPSD is established. A device based on mobile phones and macro lenses was established to acquire images. The dataset contains 4496 images of 88 different seeds. This dataset can not only be used as data for training deep learning models in the computer field, but also provide important data support for agricultural and forestry research. As an important resource in this field, this dataset plays a positive role in modernizing agriculture and forestry.

Exploring ncRNA-Drug Sensitivity Associations Via Graph Contrastive Learning.

Increasing evidence has shown that noncoding RNAs (ncRNAs) can affect drug efficiency by modulating drug sensitivity genes. Exploring the association between ncRNAs and drug sensitivity is essential for drug discovery and disease prevention. However, traditional biological experiments for identifying ncRNA-drug sensitivity associations are time-consuming and laborious. In this study, we develop a novel graph contrastive learning approach named NDSGCL to predict ncRNA-drug sensitivity. NDSGCL uses graph convolutional networks to learn feature representations of ncRNAs and drugs in ncRNA-drug bipartite graphs. It integrates local structural neighbours and global semantic neighbours to learn a more comprehensive representation by contrastive learning. Specifically, the local structural neighbours aim to capture the higher-order relationship in the ncRNA-drug graph, while the global semantic neighbours are defined based on semantic clusters of the graph that can alleviate the impact of data sparsity. The experimental results show that NDSGCL outperforms basic graph convolutional network methods, existing contrastive learning methods, and state-of-the-art prediction methods. Visualization experiments show that the contrastive objectives of local structural neighbours and global semantic neighbours play a significant role in contrastive learning. Case studies on two drugs show that NDSGCL is an effective tool for predicting ncRNA-drug sensitivity associations. Source code and datasets can be available on https://github.com/altriavin/NDSGCL.

Systematic review of the osteogenic effect of rare earth nanomaterials and the underlying mechanisms.

Rare earth nanomaterials (RE NMs), which are based on rare earth elements, have emerged as remarkable biomaterials for use in bone regeneration. The effects of RE NMs on osteogenesis, such as promoting the osteogenic differentiation of mesenchymal stem cells, have been investigated. However, the contributions of the properties of RE NMs to bone regeneration and their interactions with various cell types during osteogenesis have not been reviewed. Here, we review the crucial roles of the physicochemical and biological properties of RE NMs and focus on their osteogenic mechanisms. RE NMs directly promote the proliferation, adhesion, migration, and osteogenic differentiation of mesenchymal stem cells. They also increase collagen secretion and mineralization to accelerate osteogenesis. Furthermore, RE NMs inhibit osteoclast formation and regulate the immune environment by modulating macrophages and promote angiogenesis by inducing hypoxia in endothelial cells. These effects create a microenvironment that is conducive to bone formation. This review will help researchers overcome current limitations to take full advantage of the osteogenic benefits of RE NMs and will suggest a potential approach for further osteogenesis research.

IGCNSDA: unraveling disease-associated snoRNAs with an interpretable graph convolutional network.

Accurately delineating the connection between short nucleolar RNA (snoRNA) and disease is crucial for advancing disease detection and treatment. While traditional biological experimental methods are effective, they are labor-intensive, costly and lack scalability. With the ongoing progress in computer technology, an increasing number of deep learning techniques are being employed to predict snoRNA-disease associations. Nevertheless, the majority of these methods are black-box models, lacking interpretability and the capability to elucidate the snoRNA-disease association mechanism. In this study, we introduce IGCNSDA, an innovative and interpretable graph convolutional network (GCN) approach tailored for the efficient inference of snoRNA-disease associations. IGCNSDA leverages the GCN framework to extract node feature representations of snoRNAs and diseases from the bipartite snoRNA-disease graph. SnoRNAs with high similarity are more likely to be linked to analogous diseases, and vice versa. To facilitate this process, we introduce a subgraph generation algorithm that effectively groups similar snoRNAs and their associated diseases into cohesive subgraphs. Subsequently, we aggregate information from neighboring nodes within these subgraphs, iteratively updating the embeddings of snoRNAs and diseases. The experimental results demonstrate that IGCNSDA outperforms the most recent, highly relevant methods. Additionally, our interpretability analysis provides compelling evidence that IGCNSDA adeptly captures the underlying similarity between snoRNAs and diseases, thus affording researchers enhanced insights into the snoRNA-disease association mechanism. Furthermore, we present illustrative case studies that demonstrate the utility of IGCNSDA as a valuable tool for efficiently predicting potential snoRNA-disease associations. The dataset and source code for IGCNSDA are openly accessible at: https://github.com/altriavin/IGCNSDA.

The role of Neutrophil counts, infections and Smoking in mediating the Effect of Bronchiectasis on Chronic Obstructive Pulmonary Disease: a mendelian randomization study.

BACKGROUND: The causality of the relationship between bronchiectasis and chronic obstructive pulmonary disease (COPD) remains unclear. This study aims to investigate the potential causal relationship between them, with a specific focus on the role of airway inflammation, infections, smoking as the mediators in the development of COPD. METHODS: We conducted a two-sample Mendelian randomization (MR) analysis to assess: (1) the causal impact of bronchiectasis on COPD, sex, smoking status, infections, eosinophil and neutrophil counts, as well as the causal impact of COPD on bronchiectasis; (2) the causal effect of smoking status, infections and neutrophil counts on COPD; and (3) the extent to which the smoking status, infections and neutrophil counts might mediate any influence of bronchiectasis on the development of COPD. RESULTS: COPD was associated with a higher risk of bronchiectasis (OR 1.28 [95% CI 1.05, 1.56]). Bronchiectasis was associated with a higher risk of COPD (OR 1.08 [95% CI 1.04, 1.13]), higher levels of neutrophil (OR 1.01 [95% CI 1.00, 1.01]), higher risk of respiratory infections (OR 1.04 [95% CI 1.02, 1.06]) and lower risk of smoking. The causal associations of higher neutrophil cells, respiratory infections and smoking with higher COPD risk remained after performing sensitivity analyses that considered different models of horizontal pleiotropy, with OR 1.17, 1.69 and 95.13, respectively. The bronchiectasis-COPD effect was 0.99, 0.85 and 122.79 with genetic adjustment for neutrophils, respiratory infections and smoking. CONCLUSION: COPD and bronchiectasis are mutually causal. And increased neutrophil cell count and respiratory infections appears to mediate much of the effect of bronchiectasis on COPD.

In vivo study on osteogenic efficiency of nHA/ gel porous scaffold with nacre water-soluble matrix.

BACKGROUND/PURPOSE: Nano-hydroxyapatite (nHA)/ gel porous scaffolds loaded with WSM carriers are promising bone replacement materials that can improve osseointegration ability. This investigation aimed to evaluate the osteoinductive activity by implanting the composition of nano-hydroxyapatite (nHA)/ Gel porous scaffolds as a carrier of WSM via an animal model. MATERIALS AND METHODS: WSM was extracted and nHA was added to the matrix to construct porous composite scaffolds. The dose-effect curve of WSM concentration and alkaline phosphatase (ALP) activity was made by culturing rat osteoblasts and examining the absorbance. Three different materials were implanted into critical size defects (CSD) in the skulls of rats, which were further divided into four groups: WSM nHA /Gel group, n-WSM nHA /Gel group, HA powder group, and control group. RESULTS: WSM (150 µg/mL-250µg/mL) effectively improved the activity of ALP in rat osteoblasts. All rats in each group had normal healing. WSM-loaded nHA /Gel group showed better performance on newly-formed bone tissue of rat skull and back at 4th week and 8th week, respectively. At the 4th week, the network of woven bone formed in the WSM-loaded nHA/Gel scaffold material. At 8th week, the reticular trabecular bone in the WSM-loaded scaffold material became dense lamellar bone, and the defect was mature lamellar bone. In the subcutaneous implantation experiment, WSM-loaded nHA/Gel scaffold material showed a better performance of heterotopic ossification than the pure nHA/Gel scaffold material. CONCLUSION: WSM promotes osteoblast differentiation and bone mineralization. The results confirm that the nHA/ Gel Porous Scaffold with Nacre Water-Soluble Matrix has a significant bone promoting effect and can be used as a choice for tissue engineering to repair bone defects.

The miR166 targets CsHDZ3 genes to negatively regulate drought tolerance in tea plant (Camellia sinensis).

Drought is the stressor with a significant adverse impact on the yield stability of tea plants. HD-ZIP III transcription factors (TFs) play important regulatory roles in plant growth, development, and stress responses. However, whether and how HD-ZIP III TFs are involved in drought response and tolerance in tea plants remains unclear. Here, we identified seven HD-ZIP III genes (CsHDZ3-1 to CsHDZ3-7) in tea plant genome. The evolutionary analysis demonstrated that CsHDZ3 members were subjected to purify selection. Subcellular localization analysis revealed that all seven CsHDZ3s located in the nucleus. Yeast self-activation and dual-luciferase reporter assays demonstrated that CsHDZ3-1 to CsHDZ3-4 have trans-activation ability whereas CsHDZ3-5 to CsHDZ3-7 served as transcriptional inhibitors. The qRT-PCR assay showed that all seven CsHDZ3 genes could respond to simulated natural drought stress and polyethylene glycol treatment. Further assays verified that all CsHDZ3 genes can be cleaved by csn-miR166. Overexpression of csn-miR166 inhibited the expression of seven CsHDZ3 genes and weakened drought tolerance of tea leaves. In contrast, suppression of csn-miR166 promoted the expression of seven CsHDZ3 genes and enhanced drought tolerance of tea leaves. These findings established the foundation for further understanding the mechanism of CsHDZ3-miR166 modules' participation in drought responses and tolerance.

A supramolecular hydrogel dressing with antibacterial, immunoregulation, and pro-regeneration ability for biofilm-associated wound healing.

Chronic wound treatment has emerged as a significant healthcare concern worldwide due to its substantial economic burden and the limited effectiveness of current treatments. Effective management of biofilm infections, regulation of excessive oxidative stress, and promotion of tissue regeneration are crucial for addressing chronic wounds. Hydrogel stands out as a promising candidate for chronic wound treatment. However, its clinical application is hindered by the difficulty in designing and fabricating easily and conveniently. To overcome these obstacles, we present a supermolecular G-quadruplex hydrogel with the desired multifunction via a dynamic covalent strategy and Hoogsteen-type hydrogen bonding. The G-quadruplex hydrogel is made from the self-assembly of guanosine, 2-formylphenyboronic acid, polyethylenimine, and potassium chloride, employing dynamic covalent strategy and Hoogsteen-type hydrogen bonding. In the acidic/oxidative microenvironment associated with bacterial infections, the hydrogel undergoes controlled degradation, releasing the polyethylenimine domain, which effectively eliminates bacteria. Furthermore, nanocomplexes comprising guanosine monophosphate and manganese sulfate are incorporated into the hydrogel skeleton, endowing it with the ability to scavenge reactive oxygen species and modulate macrophages. Additionally, the integration of basic fibroblast growth factor into the G-quadruplex skeleton through dynamic covalent bonds facilitates controlled tissue regeneration. In summary, the facile preparation process and the incorporation of multiple functionalities render the G-quadruplex hydrogel a highly promising candidate for advanced wound dressing. It holds great potential to transition from laboratory research to clinical practice, addressing the pressing needs of chronic wound management.

Long-term efficacy of a recombinant hepatitis E vaccine in adults: 10-year results from a randomised, double-blind, placebo-controlled, phase 3 trial.

BACKGROUND: Hepatitis E virus (HEV) is a frequently overlooked causative agent of acute hepatitis. Evaluating the long-term durability of hepatitis E vaccine efficacy holds crucial importance. METHODS: This study was an extension to a randomised, double-blind, placebo-controlled, phase-3 clinical trial of the hepatitis E vaccine conducted in Dontai County, Jiangsu, China. Participants were recruited from 11 townships in Dongtai County. In the initial trial, a total of 112 604 healthy adults aged 16-65 years were enrolled, stratified according to age and sex, and randomly assigned in a 1:1 ratio to receive three doses of hepatitis E vaccine or placebo intramuscularly at month 0, month 1, and month 6. A sensitive hepatitis E surveillance system including 205 clinical sentinels, covering the entire study region, was established and maintained for 10 years after vaccination. The primary outcome was the per-protocol efficacy of hepatitis E virus vaccine to prevent confirmed hepatitis E occurring at least 30 days after administration of the third dose. Throughout the study, the participants, site investigators, and laboratory staff remained blinded to the treatment assignments. This study is registered with ClinicalTrials.gov (NCT01014845). FINDINGS: During the 10-year study period from Aug 22, 2007, to Oct 31, 2017, 90 people with hepatitis E were identified; 13 in the vaccine group (0·2 per 10 000 person-years) and 77 in the placebo group (1·4 per 10 000 person-years), corresponding to a vaccine efficacy of 83·1% (95% CI 69·4-91·4) in the modified intention-to-treat analysis and 86·6% (73·0 to 94·1) in the per-protocol analysis. In the subsets of participants assessed for immunogenicity persistence, of those who were seronegative at baseline and received three doses of hepatitis E vaccine, 254 (87·3%) of 291 vaccinees in Qindong at the 8·5-year mark and 1270 (73·0%) of 1740 vaccinees in Anfeng at the 7·5-year mark maintained detectable concentrations of antibodies. INTERPRETATION: Immunisation with this hepatitis E vaccine offers durable protection against hepatitis E for up to 10 years, with vaccine-induced antibodies against HEV persisting for at least 8·5 years. FUNDING: National Natural Science Foundation of China, Fujian Provincial Natural Science Foundation, Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences, and the Fundamental Research Funds for the Central Universities.

Monomeric CXCL12-Engineered Adipose-Derived Stem Cells Transplantation for the Treatment of Ischemic Stroke.

Adipose-derived stem cells (ASCs) possess therapeutic potential for ischemic brain injury, and the chemokine CXCL12 has been shown to enhance their functional properties. However, the cumulative effects of ASCs when combined with various structures of CXCL12 on ischemic stroke and its underlying molecular mechanisms remain unclear. In this study, we genetically engineered mouse adipose-derived ASCs with CXCL12 variants and transplanted them to the infarct region in a mice transient middle cerebral artery occlusion (tMCAO) model of stroke. We subsequently compared the post-ischemic stroke efficacy of ASC-mCXCL12 with ASC-dCXCL12, ASC-wtCXCL12, and unmodified ASCs. Neurobehavior recovery was assessed using modified neurological severity scores, the hanging wire test, and the elevated body swing test. Changes at the tissue level were evaluated through cresyl violet and immunofluorescent staining, while molecular level alterations were examined via Western blot and real-time PCR. The results of the modified neurological severity score and cresyl violet staining indicated that both ASC-mCXCL12 and ASC-dCXCL12 treatment enhanced neurobehavioral recovery and mitigated brain atrophy at the third and fifth weeks post-tMCAO. Additionally, we observed that ASC-mCXCL12 and ASC-dCXCL12 promoted angiogenesis and neurogenesis, accompanied by an increased expression of bFGF and VEGF in the peri-infarct area of the brain. Notably, in the third week after tMCAO, the ASC-mCXCL12 exhibited superior outcomes compared to ASC-dCXCL12. However, when treated with the CXCR4 antagonist AMD3100, the beneficial effects of ASC-mCXCL12 were reversed. The AMD3100-treated group demonstrated worsened neurological function, aggravated edema volume, and brain atrophy. This outcome is likely attributed to the interaction of monomeric CXCL12 with CXCR4, which regulates the recruitment of bFGF and VEGF. This study introduces an innovative approach to enhance the therapeutic potential of ASCs in treating ischemic stroke by genetically engineering them with the monomeric structure of CXCL12.

Omega-3 supplementation improves depressive symptoms, cognitive function and niacin skin flushing response in adolescent depression: A randomized controlled clinical trial.

BACKGROUND: Depressive disorder in adolescents is a major health problem with inadequate treatment. Omega-3 (ω3) polyunsaturated fatty acids are a promising adjuvant therapy in adult depression. The primary objective of this study was to investigate the efficacy of adjuvant ω3 treatment on depressive symptoms in adolescent depression. Secondarily, we explored the effects of ω3 on cognitive function and memory and niacin skin flushing response (NSFR), as their robust associations with adolescent depression. METHODS: A total of 71 adolescents with depression (aged 13-24; 59.2 % female) were randomly assigned to receive ω3 plus Paxil (n = 34) or Paxil alone (n = 37) for 12 weeks. Primary outcome was depression severity according to scores on Montgomery-Asberg Depression Rating Scale (MADRS). Secondary outcomes were cognitive function and memory, and NSFR. RESULTS: Significant improvements in depressive symptoms over time (p = 0.00027 at week 12) were observed in the ω3 + Paxil group compared with Paxil group. Additionally, in the ω3 + Paxil group, significant improvements in memory over time, and greater cognitive function and NSFR were also observed compared with the Paxil group; the NSFR was negatively correlated with MADRS scores at baseline. LIMITATIONS: The trial was open label; thus, the outcome measures should be viewed as preliminary since inherent bias in outcomes due to the potential of a placebo effect. CONCLUSIONS: Our results demonstrate that adjuvant ω3 treatment is effective for reducing depressive symptoms as well as improving cognitive function, memory and the NSFR; these results suggest ω3 is a promising adjuvant treatment for adolescent depression.

Re-expression of epigenetically silenced PTPRR by histone acetylation sensitizes RAS-mutant lung adenocarcinoma to SHP2 inhibition.

Silenced protein tyrosine phosphatase receptor type R (PTPRR) participates in mitogen-activated protein kinase (MAPK) signaling cascades during the genesis and development of tumors. Rat sarcoma virus (Ras) genes are frequently mutated in lung adenocarcinoma, thereby resulting in hyperactivation of downstream MAPK signaling. However, the molecular mechanism manipulating the regulation and function of PTPRR in RAS-mutant lung adenocarcinoma is not known. Patient records collected from the Cancer Genome Atlas and Gene Expression Omnibus showed that silenced PTPRR was positively correlated with the prognosis. Exogenous expression of PTPRR suppressed the proliferation and migration of lung cancer cells. PTPRR expression and Src homology 2 containing protein tyrosine phosphatase 2 (SHP2) inhibition acted synergistically to control ERK1/2 phosphorylation in RAS-driven lung cancer cells. Chromatin immunoprecipitation assay revealed that HDAC inhibition induced enriched histone acetylation in the promoter region of PTPRR and recovered PTPRR transcription. The combination of the HDAC inhibitor SAHA and SHP2 inhibitor SHP099 suppressed the progression of lung cancer markedly in vitro and in vivo. Therefore, we revealed the epigenetic silencing mechanism of PTPRR and demonstrated that combination therapy targeting HDAC and SHP2 might represent a novel strategy to treat RAS-mutant lung cancer.

Altered HCAR3 expression may underlying the blunted niacin responses of the psychiatric disorders and the risk of schizophrenia.

AIM: Blunted niacin response (BNR) was an endophenotype of schizophrenia, but the underlying mechanism remains unclarified. The objective of this study was to verify whether genes associated with BNR pathway constitute the genetic basis and the pathological mechanism of BNR phenotypic psychiatric patients. METHODS: Two independent sample sets consisting of 971 subjects were enrolled in this study. A total of 62 variants were genotyped in the discovery set, then the related variants were verified in the verification set. The published PGC GWAS data were used to validate the associations between the variants and psychiatry disorders. RT-PCR analysis, eQTL data, and Dual-Luciferase Reporter experiment were used to investigate the potential molecular mechanisms of the variants underlying BNR. RESULTS: The results showed that two SNPs, rs56959712 in HCAR2 and rs2454721 in HCAR3 were significantly associated with niacin response. The risk allele T of rs2454721 could affect the niacin responses of psychiatric patients through elevated HCAR3 gene expression. These two genes, especially HCAR3, were significantly associated with the risk of schizophrenia, as identified in this study and verified using the published GWAS data. CONCLUSION: HCAR3 is a novel schizophrenia susceptibility gene which is significantly associated with blunted niacin response in schizophrenia. In-depth investigation of HCAR3 is of great significance for uncovering the pathogenesis and propose new therapeutic targets for psychiatric disorders, especially for the BNR subgroup patients.

Scalable Photochromic Film for Solar Heat and Daylight Management.

The adaptive control of sunlight through photochromic smart windows could have a huge impact on the energy efficiency and daylight comfort in buildings. However, the fabrication of inorganic nanoparticle and polymer composite photochromic films with a high contrast ratio and high transparency/low haze remains a challenge. Here, a solution method is presented for the in situ growth of copper-doped tungsten trioxide nanoparticles in polymethyl methacrylate, which allows a low-cost preparation of photochromic films with a high luminous transparency (luminous transmittance Tlum = 91%) and scalability (30 × 350 cm2 ). High modulation of visible light (ΔTlum = 73%) and solar heat (modulation of solar transmittance ΔTsol = 73%, modulation of solar heat gain coefficient ΔSHGC = 0.5) of the film improves the indoor daylight comfort and energy efficiency. Simulation results show that low-e windows with the photochromic film applied can greatly enhance the energy efficiency and daylight comfort. This photochromic film presents an attractive strategy for achieving more energy-efficient buildings and carbon neutrality to combat global climate change.

A long-term experiment reveals no trade-off between seed persistence and seedling emergence.

Information on seed persistence and seedling emergence from the soil seed bank is critical for understanding species coexistence and predicting community dynamics. However, quantifying seed persistence in the soil is challenging; thus, its association with other life-history traits is poorly known on a broad scale. Using germination phenology for 349 species in a 42-yr experiment, we quantified the persistence-emergence correlations and their associations with intrinsic regeneration traits using Bayesian phylogenetic multilevel models. We showed no trade-off between seed persistence and seedling emergence. Physically dormant seeds were more persistent but exhibited lower emergence than nondormant seeds. Monocarpic species had both higher persistence and emergence than polycarpic species. Seed mass posed a marginal proxy for persistence, while emergence almost doubled from the smallest to the largest seeds. This study challenges the traditional assumption and is the first demonstration of noncorrelation between persistence and emergence, probably owing to the complexity of regenerative strategies. Species with short persistence and low emergence would be the most vulnerable for in situ conservation. Our analyses of this unique, long-term dataset provide a strong incentive for further experimental studies and a rich data resource for future syntheses.

Association between adult food insecurity and mortality among adults aged 20-79 years with diabetes: A population-based retrospective cohort study.

AIMS: There is limited research on the relationship between food insecurity and mortality among individuals with diabetes. This study aims to investigate the impact of food insecurity on all-cause and cause-specific mortality in adults with diabetes. RESEARCH DESIGN AND METHODS: This study included 5749 adults with diabetes from the National Health and Nutrition Examination Survey cycles 2003-2018 and followed up until 31 December 2019. Food insecurity was measured by the Food Security Survey Module. Cox proportional hazard models were employed to estimate hazard ratios (HRs) and 95% confidence intervals for both all-cause mortality and cause-specific mortality. RESULTS: The weighted prevalence of full food security, marginal food security, low food security, and very low food security was 70.8%, 11.0%, 10.4%, and 7.8%, respectively. Food insecurity demonstrated a significant correlation with diminished diet quality and reduced consumption of healthy foods. Over the course of 42,272.0 person-years of follow-up, we documented 1091 deaths, of which 370 were attributed to cardiovascular disease and 180 to cancer. After adjusting for multiple variables, food insecurity scores were significantly and linearly associated with increased all-cause mortality. Comparing to full food security, participants experiencing very low food security had a multivariate-adjusted HR of 1.48 (1.12, 1.95) for all-cause mortality (ptrend = 0.010). CONCLUSIONS: Food insecurity was associated with increased all-cause mortality and compromised diet quality, especially in individuals experiencing very low food security. Future strategies may necessitate the monitoring of and interventions for food insecurity among individuals with diabetes.

Harnessing Smectic Ordering for Electric-Field-Driven Guided-Growth of Surface Topography in a Liquid Crystal Polymer.

The guided-growth strategy has been widely explored and proved its efficacy in fabricating surface micro/nanostructures in a variety of systems. However, soft materials like polymers are much less investigated partly due to the lack of strong internal driving mechanisms. Herein, the possibility of utilizing liquid crystal (LC) ordering of smectic liquid crystal polymers (LCPs) to induce guided growth of surface topography during the formation of electrohydrodynamic (EHD) patterns is demonstrated. In a two-stage growth, regular stripes are first found to selectively emerge from the homogeneously aligned region of an initially flat LCP film, and then extend neatly along the normal direction of the boundary line between homogeneous and homeotropic alignments. The stripes can maintain their directions for quite a distance before deviating. Coupled with the advanced tools for controlling LC alignment, intricate surface topographies can be produced in LCP films starting from relatively simple designs. The regularity of grown pattern is determined by the LC ordering of the polymer material, and influenced by conditions of EHD growth. The proposed approach provides new opportunities to employ LCPs in optical and electrical applications.

A Self-Assembled 3D/0D Quasi-Core-Shell Structure as Internal Encapsulation Layer for Stable and Efficient FAPbI3 Perovskite Solar Cells and Modules.

FAPbI3 perovskites have garnered considerable interest owing to their outstanding thermal stability, along with near-theoretical bandgap and efficiency. However, their inherent phase instability presents a substantial challenge to the long-term stability of devices. Herein, this issue through a dual-strategy of self-assembly 3D/0D quasi-core-shell structure is tackled as an internal encapsulation layer, and in situ introduction of excess PbI2 for surface and grain boundary defects passivating, therefore preventing moisture intrusion into FAPbI3 perovskite films. By utilizing this method alone, not only enhances the stability of the FAPbI3 film but also effectively passivates defects and minimizes non-radiative recombination, ultimately yielding a champion device efficiency of 23.23%. Furthermore, the devices own better moisture resistance, exhibiting a T80 lifetime exceeding 3500 h at 40% relative humidity (RH). Meanwhile, a 19.51% PCE of mini-module (5 × 5 cm2 ) is demonstrated. This research offers valuable insights and directions for the advancement of stable and highly efficient FAPbI3 perovskite solar cells.

Efficacy, safety, and cost-effectiveness of therapeutic drug monitoring (TDM) for TNF inhibitor therapy in rheumatic disease: A systematic review and meta-analysis.

OBJECTIVE: The benefits of TDM-guided TNFi therapy in patients with rheumatic disease was still controversial. This systematic review and meta-analysis was conducted to explore if the TDM-guided TNFi therapy is superior to empirical-guided therapy. METHODS: We systematically searched PubMed, Web of Science, Cochrane Library, and EMBASE databases for articles published between database inception and October 05, 2023. Studies reporting endpoints in TDM-guided TNFi therapy and empirical therapy were included. Results would be presented in risk ratio (RR) and mean difference, with 95 % confidence interval (CI) reported. This study is registered with PROSPERO (CRD42022353956). RESULTS: A total of 14 studies (eight RCTs and six cohort studies) involving 2427 patients were included in this meta-analysis. In the scenario of response prediction, compared with empirical-guided therapy, TDM-guided TNFi therapy had association with higher treat-to-target rates (RR 1.30, 95 % CI 1.02-1.65, P=0.03, I2=79 %), more specifically, higher low disease activity rates (RR 2.11, 95 % CI 1.22-3.66, P=0.007, I2=61 %), but no difference in clinical remission rates (RR 0.98,95 % CI 0.87-1.11, P=0.75, I2=0 %). In the scenario of dose reduction prediction, lower relapse rates (RR 0.73, 95 % CI 0.65-0.82, P <0.00001, I2=0 %) were observed compared with empirical-guided dose reduction strategy, but no difference (RR 1.24, 95 % CI 0.85-1.80, P=0.27, I2=57 %) between TDM-guided dose reduction and standard-dosing therapy. No significant difference was observed in change of disease activity score, mean disease activity score, radiographic progression, and safety. And TDM-guided therapy was associated with reduced cost per patient per year calculated as the total accumulated sum of therapy cost. CONCLUSION: TDM-guided TNFi therapy was associated with increased rates of low disease activity and decreased risks of relapse, and may save cost compared with empirical-guided therapy in patients with rheumatic disease. But this does not mean that the use of TDM-guided TNFi therapy can be advocated, because there is no difference in clinical remission rates and many other outcomes. More researches, especially randomized clinical trials are needed to verify this conclusion in the future.

AntiViralDL: Computational Antiviral Drug Repurposing Using Graph Neural Network and Self-Supervised Learning.

Viral infections have emerged as significant public health concerns for decades. Antiviral drugs, specifically designed to combat these infections, have the potential to reduce the disease burden substantially. However, traditional drug development methods, based on biological experiments, are resource-intensive, time-consuming, and low efficiency. Therefore, computational approaches for identifying antiviral drugs can enhance drug development efficiency. In this study, we introduce AntiViralDL, a computational framework for predicting virus-drug associations using self-supervised learning. Initially, we construct a reliable virus-drug association dataset by integrating the existing Drugvirus2 database and FDA-approved virus-drug associations. Utilizing these two datasets, we create a virus-drug association bipartite graph and employ the Light Graph Convolutional Network (LightGCN) to learn embedding representations of viruses and drugs. To address the sparsity of virus-drug association pairs, AntiViralDL incorporates contrastive learning to improve prediction accuracy. We implement data augmentation by adding random noise to the embedding representation space of virus and drug nodes, as opposed to traditional edge and node dropout. Finally, we calculate an inner product to predict virus-drug association relationships. Experimental results reveal that AntiViralDL achieves AUC and AUPR values of 0.8450 and 0.8494, respectively, outperforming four benchmarked virus-drug association prediction models. The case study further highlights the efficacy of AntiViralDL in predicting anti-COVID-19 drug candidates.