Drug-Online: an online platform for drug-target interaction, affinity, and binding sites identification using deep learning.

BACKGROUND: Accurately identifying drug-target interaction (DTI), affinity (DTA), and binding sites (DTS) is crucial for drug screening, repositioning, and design, as well as for understanding the functions of target. Although there are a few online platforms based on deep learning for drug-target interaction, affinity, and binding sites identification, there is currently no integrated online platforms for all three aspects. RESULTS: Our solution, the novel integrated online platform Drug-Online, has been developed to facilitate drug screening, target identification, and understanding the functions of target in a progressive manner of "interaction-affinity-binding sites". Drug-Online platform consists of three parts: the first part uses the drug-target interaction identification method MGraphDTA, based on graph neural networks (GNN) and convolutional neural networks (CNN), to identify whether there is a drug-target interaction. If an interaction is identified, the second part employs the drug-target affinity identification method MMDTA, also based on GNN and CNN, to calculate the strength of drug-target interaction, i.e., affinity. Finally, the third part identifies drug-target binding sites, i.e., pockets. The method pt-lm-gnn used in this part is also based on GNN. CONCLUSIONS: Drug-Online is a reliable online platform that integrates drug-target interaction, affinity, and binding sites identification. It is freely available via the Internet at http://39.106.7.26:8000/Drug-Online/ .

MH-STRALP: A scoring system for prognostication in patients with upper gastrointestinal bleeding.

BACKGROUND: Upper gastrointestinal bleeding (UGIB) is a common medical emergency and early assessment of its outcomes is vital for treatment decisions. AIM: To develop a new scoring system to predict its prognosis. METHODS: In this retrospective study, 692 patients with UGIB were enrolled from two centers and divided into a training (n = 591) and a validation cohort (n = 101). The clinical data were collected to develop new prognostic prediction models. The endpoint was compound outcome defined as (1) demand for emergency surgery or vascular intervention, (2) being transferred to the intensive care unit, or (3) death during hospitalization. The models' predictive ability was compared with previously established scores by receiver operating characteristic (ROC) curves. RESULTS: Totally 22.2% (131/591) patients in the training cohort and 22.8% (23/101) in the validation cohort presented poor outcomes. Based on the stepwise-forward Logistic regression analysis, eight predictors were integrated to determine a new post-endoscopic prognostic scoring system (MH-STRALP); a nomogram was determined to present the model. Compared with the previous scores (GBS, Rockall, ABC, AIMS65, and PNED score), MH-STRALP showed the best prognostic prediction ability with area under the ROC curves (AUROCs) of 0.899 and 0.826 in the training and validation cohorts, respectively. According to the calibration curve, decision curve analysis, and internal cross-validation, the nomogram showed good calibration ability and net clinical benefit in both cohorts. After removing the endoscopic indicators, the pre-endoscopic model (pre-MH-STRALP score) was conducted. Similarly, the pre-MH-STRALP score showed better predictive value (AUROCs of 0.868 and 0.767 in the training and validation cohorts, respectively) than the other pre-endoscopic scores. CONCLUSION: The MH-STRALP score and pre-MH-STRALP score are simple, convenient, and accurate tools for prognosis prediction of UGIB, and may be applied for early decision on its management strategies.

DRP1 inhibition-mediated mitochondrial elongation abolishes cancer stemness, enhances glutaminolysis, and drives ferroptosis in oral squamous cell carcinoma.

BACKGROUND: Mitochondrial dynamics play a fundamental role in determining stem cell fate. However, the underlying mechanisms of mitochondrial dynamics in the stemness acquisition of cancer cells are incompletely understood. METHODS: Metabolomic profiling of cells were analyzed by MS/MS. The genomic distribution of H3K27me3 was measured by CUT&Tag. Oral squamous cell carcinoma (OSCC) cells depended on glucose or glutamine fueling TCA cycle were monitored by 13C-isotope tracing. Organoids and tumors from patients and mice were treated with DRP1 inhibitors mdivi-1, ferroptosis inducer erastin, or combination with mdivi-1 and erastin to evaluate treatment effects. RESULTS: Mitochondria of OSCC stem cells own fragment mitochondrial network and DRP1 is required for maintenance of their globular morphology. Imbalanced mitochondrial dynamics induced by DRP1 knockdown suppressed stemness of OSCC cells. Elongated mitochondria increased α-ketoglutarate levels and enhanced glutaminolysis to fuel the TCA cycle by increasing glutamine transporter ASCT2 expression. α-KG promoted the demethylation of histone H3K27me3, resulting in downregulation of SNAI2 associated with stemness and EMT. Significantly, suppressing DRP1 enhanced the anticancer effects of ferroptosis. CONCLUSION: Our study reveals a novel mechanism underlying mitochondrial dynamics mediated cancer stemness acquisition and highlights the therapeutic potential of mitochondria elongation to increase the susceptibility of cancer cells to ferroptosis.

A comprehensive review of the recent advances on predicting drug-target affinity based on deep learning.

Accurate calculation of drug-target affinity (DTA) is crucial for various applications in the pharmaceutical industry, including drug screening, design, and repurposing. However, traditional machine learning methods for calculating DTA often lack accuracy, posing a significant challenge in accurately predicting DTA. Fortunately, deep learning has emerged as a promising approach in computational biology, leading to the development of various deep learning-based methods for DTA prediction. To support researchers in developing novel and highly precision methods, we have provided a comprehensive review of recent advances in predicting DTA using deep learning. We firstly conducted a statistical analysis of commonly used public datasets, providing essential information and introducing the used fields of these datasets. We further explored the common representations of sequences and structures of drugs and targets. These analyses served as the foundation for constructing DTA prediction methods based on deep learning. Next, we focused on explaining how deep learning models, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Transformer, and Graph Neural Networks (GNNs), were effectively employed in specific DTA prediction methods. We highlighted the unique advantages and applications of these models in the context of DTA prediction. Finally, we conducted a performance analysis of multiple state-of-the-art methods for predicting DTA based on deep learning. The comprehensive review aimed to help researchers understand the shortcomings and advantages of existing methods, and further develop high-precision DTA prediction tool to promote the development of drug discovery.

Oral epithelial dysplasia detection and grading in oral leukoplakia using deep learning.

BACKGROUND: The grading of oral epithelial dysplasia is often time-consuming for oral pathologists and the results are poorly reproducible between observers. In this study, we aimed to establish an objective, accurate and useful detection and grading system for oral epithelial dysplasia in the whole-slides of oral leukoplakia. METHODS: Four convolutional neural networks were compared using the image patches from 56 whole-slide of oral leukoplakia labeled by pathologists as the gold standard. Sequentially, feature detection models were trained, validated and tested with 1,000 image patches using the optimal network. Lastly, a comprehensive system named E-MOD-plus was established by combining feature detection models and a multiclass logistic model. RESULTS: EfficientNet-B0 was selected as the optimal network to build feature detection models. In the internal dataset of whole-slide images, the prediction accuracy of E-MOD-plus was 81.3% (95% confidence interval: 71.4-90.5%) and the area under the receiver operating characteristic curve was 0.793 (95% confidence interval: 0.650 to 0.925); in the external dataset of 229 tissue microarray images, the prediction accuracy was 86.5% (95% confidence interval: 82.4-90.0%) and the area under the receiver operating characteristic curve was 0.669 (95% confidence interval: 0.496 to 0.843). CONCLUSIONS: E-MOD-plus was objective and accurate in the detection of pathological features as well as the grading of oral epithelial dysplasia, and had potential to assist pathologists in clinical practice.

Construction of resveratrol and quercetin nanoparticles based on folic acid targeted Maillard products between Jiuzao glutelin isolate and carboxymethyl chitosan: Improved stability and function.

Advanced targeted nanoparticles (NPs) were designed to enhance the targeted delivery of resveratrol (RES) and quercetin (QUE) by utilizing carboxymethyl chitosan (CTS) and Jiuzao glutelin isolate (JGI) conjugates. Briefly, RES and QUE were encapsuled within CTS-JGI-2 (CTS/JGI, m/m, 2:1). The carrier's targeting properties were further improved through the incorporation of folic acid (FA) and polyethylenimine (PEI). Moreover, the stability against digestion was enhanced by incorporating baker yeast cell walls (BYCWs) to construct RES-QUE/FA-PEI/CTS-JGI-2/MAT/BYCW NPs. The results demonstrated that FA-PEI/CTS-JGI-2/MAT/BYCW NPs could improve cellular uptake and targeting property of RES and QUE through endocytosis of folic acid receptors (FOLRs). Additionally, RES-QUE successfully alleviated LPS- and DSS-induced inflammation by regulating NF-κB/IkBa/AP-1 and AMPK/SIRT1signaling pathways and reducing the secretion of inflammatory mediators and factors. These findings indicate FA-PEI/CTS-JGI-2/MAT/BYCW NPs hold promise as an oral drug delivery system with targeted delivery capacities for functional substances prone to instability in dietary supplements.

Exciton polariton condensation from bound states in the continuum at room temperature.

Exciton-polaritons (polaritons) resulting from the strong exciton-photon interaction stimulates the development of novel low-threshold coherent light sources to circumvent the ever-increasing energy demands of optical communications1-3. Polaritons from bound states in the continuum (BICs) are promising for Bose-Einstein condensation owing to their theoretically infinite quality factors, which provide prolonged lifetimes and benefit the polariton accumulations4-7. However, BIC polariton condensation remains limited to cryogenic temperatures ascribed to the small exciton binding energies of conventional material platforms. Herein, we demonstrated room-temperature BIC polariton condensation in perovskite photonic crystal lattices. BIC polariton condensation was demonstrated at the vicinity of the saddle point of polariton dispersion that generates directional vortex beam emission with long-range coherence. We also explore the peculiar switching effect among the miniaturized BIC polariton modes through effective polariton-polariton scattering. Our work paves the way for the practical implementation of BIC polariton condensates for integrated photonic and topological circuits.

Glutenin-chitosan 3D porous scaffolds with tunable stiffness and systematized microstructure for cultured meat model.

A glutenin (G)-chitosan (CS) complex (G-CS) was cross-linked by water annealing with aim to prepare structured 3D porous cultured meat scaffolds (CMS) here. The CMS has pore diameters ranging from 18 to 67 µm and compressive moduli from 16.09 to 60.35 kPa, along with the mixing ratio of G/CS. SEM showed the porous organized structure of CMS. FTIR and CD showed the increscent content of α-helix and ß-sheet of G and strengthened hydrogen-bondings among G-CS molecules, which strengthened the stiffness of G-CS. Raman spectra exhibited an increase of G concentration resulted in higher crosslinking of disulfide-bonds in G-CS, which aggrandized the bridging effect of G-CS and maintained its three-dimensional network. Cell viability assay and immuno-fluorescence staining showed that G-CS effectively facilitated the growth and myogenic differentiation of porcine skeletal muscle satellite cells (PSCs). CLSM displayed that cells first occupied the angular space of hexagon and then ring-growth circle of PSCs were orderly formed on G-CS. The texture and color of CMS which loaded proliferated PSCs were fresh-meat like. These results showed that physical cross-linked G-CS scaffolds are the biocompatible and stable adaptable extracellular matrix with appropriate architectural cues and natural micro-environment for structured CM models.

Lifestyle behaviors and risk of cardiovascular disease and prognosis among individuals with cardiovascular disease: a systematic review and meta-analysis of 71 prospective cohort studies.

BACKGROUND: Healthy lifestyle behaviors (LBs) have been widely recommended for the prevention and management of cardiovascular disease (CVD). Despite a large number of studies exploring the association between combined LBs and CVD, a notable gap exists in integration of relevant literatures. We conducted a systematic review and meta-analysis of prospective cohort studies to analyze the correlation between combined LBs and the occurrence of CVD, as well as to estimate the risk of various health complications in individuals already diagnosed with CVD. METHODS: Articles published up to February 10, 2023 were sourced through PubMed, EMBASE and Web of Science. Eligible prospective cohort studies that reported the relations of combined LBs with pre-determined outcomes were included. Summary relative risks (RRs) and 95% confidence intervals (CIs) were estimated using either a fixed or random-effects model. Subgroup analysis, meta-regression, publication bias, and sensitivity analysis were as well performed. RESULTS: In the general population, individuals with the healthiest combination of LBs exhibited a significant risk reduction of 58% for CVD and 55% for CVD mortality. For individuals diagnosed with CVD, adherence to the healthiest combination of LBs corresponded to a significant risk reduction of 62% for CVD recurrence and 67% for all-cause mortality, when compared to those with the least-healthy combination of LBs. In the analysis of dose-response relationship, for each increment of 1 healthy LB, there was a corresponding decrease in risk of 17% for CVD and 19% for CVD mortality within the general population. Similarly, among individuals diagnosed with CVD, each additional healthy LB was associated with a risk reduction of 27% for CVD recurrence and 27% for all-cause mortality. CONCLUSIONS: Adopting healthy LBs is associated with substantial risk reduction in CVD, CVD mortality, and adverse outcomes among individuals diagnosed with CVD. Rather than focusing solely on individual healthy LB, it is advisable to advocate for the adoption of multiple LBs for the prevention and management of CVD. TRIAL REGISTRATION: PROSPERO: CRD42023431731.

Resveratrol regulates Thoc5 to improve maternal immune activation-induced autism-like behaviors in adult mouse offspring.

Maternal infection during pregnancy is an important cause of autism spectrum disorder (ASD) in offspring, and inflammatory infiltration caused by maternal immune activation (MIA) can cause neurodevelopmental disorders in the fetus. Medicine food homologous (MFH) refers to a Traditional Chinese Medicine (TCM) concept, which effectively combines food functions and medicinal effects. However, no previous study has screened, predicted, and validated the potential targets of MFH herbs for treating ASD. Therefore, in this study, we used comprehensive bioinformatics methods to screen and analyze MFH herbs and drug targets on a large scale, and identified resveratrol and Thoc5 as the best small molecular ingredient and drug target, respectively, for the treatment of MIA-induced ASD. Additionally, the results of in vitro experiments revealed that resveratrol increased the expression of Thoc5 and effectively inhibited lipopolysaccharide-induced inflammatory factor production by BV2 cells. Moreover, in vivo, resveratrol increased the expression of Thoc5 and effectively inhibited placental and fetal brain inflammation in MIA pregnancy mice, and improved ASD-like behaviors in offspring.

A wearable flexible electrochemical biosensor with CuNi-MOF@rGO modification for simultaneous detection of uric acid and dopamine in sweat.

BACKGROUND: In health assessment and personalized medical services, accurate detection of biological markers such as dopamine (DA) and uric acid (UA) in sweat is crucial for providing valuable physiological information. However, there are challenges in detecting sweat biomarkers due to their low concentrations, variations in sweat yield among individuals, and the need for efficient sweat collection. RESULTS: We synthesized CuNi-MOF@rGO as a high-activity electrocatalyst and investigated its feasibility and electrochemical mechanism for simultaneously detecting low-concentration biomarkers UA and DA. Interaction between the non-coordinating carboxylate group and the sample produces effective separation signals for DA and UA. The wearable biomimetic biosensor has a wide linear range of 1-500 µM, with a detection limit of 9.41 µM and sensitivity of 0.019 µA µM-1 cm-2 for DA, and 10-1000 µM, with a detection limit of 9.09 µM and sensitivity of 0.026 µA µM-1 cm-2 for UA. Thus, our sensor performs excellently in detecting low-concentration biomarkers. To improve sweat collection, we designed a microfluidic-controlled device with hydrophilic modification in the microchannel. Experimental results show optimal ink flow at 2% concentration. Overall, we developed an innovative and highly active electrocatalyst, successfully enabling simultaneous detection of low-concentration biomarkers UA and DA. SIGNIFICANCE: This study provides a strategy for sweat analysis and health monitoring. Moreover, the sensor also showed good performance in detecting real sweat samples. This study has shown great potential in future advances in sweat analysis and health monitoring.

Comparison of the effects of monounsaturated fatty acids and polyunsaturated fatty acids on the lipotoxicity of islets.

Background: Monounsaturated fatty acids (MUFAs) and polyunsaturated fatty acids (PUFAs) have been reported to combat saturated fatty acid (SFA)-induced cellular damage, however, their clinical effects on patients with metabolic diseases such as diabetes and hyperlipidemia are still controversial. Since comparative studies of the effects of these two types of unsaturated fatty acids (UFAs) are still limited. In this study, we aimed to compare the protective effects of various UFAs on pancreatic islets under the stress of SFA-induced metabolic disorder and lipotoxicity. Methods: Rat insulinoma cell line INS-1E were treated with palmitic acid (PA) with or without UFAs including eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), arachidonic acid (AA), and oleic acid (OA) to determine cell viability, apoptosis, endoplasmic reticulum (ER) stress, and inflammatory. In vivo, male C57BL/6 mice were fed a 60% high-fat diet (HFD) for 12 w. Then the lard in HFD was partially replaced with fish oil (FO) and olive oil (OO) at low or high proportions of energy (5% or 20%) to observe the ameliorative effects of the UFA supplement. Results: All UFAs significantly improved PA-induced cell viability impairment in INS-1E cells, and their alleviation on PA induced apoptosis, ER stress and inflammation were confirmed. Particularly, OA had better effects than EPA, DHA, and AA on attenuating cellular ER stress. In vivo, the diets with a low proportion of UFAs (5% of energy) had limited effects on HFD induced metabolic disorder, except for a slight improved intraperitoneal glucose tolerance in obese mice. However, when fed diets containing a high proportion of UFAs (20% of energy), both the FO and OO groups exhibited substantially improved glucose and lipid metabolism, such as decrease in total cholesterol (TC), low-density lipoprotein (LDL), fasting blood glucose (FBG), and fasting blood insulin (FBI)) and improvement of insulin sensitivity evidenced by intraperitoneal glucose tolerance test (IPGTT) and intraperitoneal insulin tolerance test (IPITT). Unexpectedly, FO resulted in abnormal elevation of the liver function index aspartate aminotransferase (AST) in serum. Pathologically, OO attenuated HFD-induced compensatory hyperplasia of pancreatic islets, while this effect was not obvious in the FO group. Conclusions: Both MUFAs and PUFAs can effectively protect islet ß cells from SFA-induced cellular lipotoxicity. In particular, both OA in vitro and OO in vivo showed superior activities on protecting islets function and enhance insulin sensitivity, suggesting that MUFAs might have greater potential for nutritional intervention on diabetes.

Compound collagen peptide powder improves skin photoaging by reducing oxidative stress and activating TGF-ß1/Smad pathway.

Fish collagen peptide (FCP) has been extensively investigated as a natural product that can combat photoaging; however, its efficacy is limited by its singular composition. Compound collagen peptide powder (CCPP) is a novel functional food formulation that exhibits photoprotective properties and comprises FCP and a blend of natural botanical ingredients. The objective of this study was to investigate the efficacy of CCPP and its molecular mechanism. CCPP had a low molecular weight, facilitating its efficient absorption, and was abundant in amino acids, total polyphenols, and total flavonoids. The results of in vivo studies demonstrated that CCPP exhibited significant efficacy in reducing skin wrinkles, enhancing the contents of water and oil in the skin, and ameliorating histopathological alterations in mice. The results of in vitro studies demonstrated that CCPP effectively mitigated photoaging in human skin fibroblasts by attenuating oxidative stress and promoting extracellular matrix (ECM) synthesis. Moreover, we clearly demonstrated that the TGF ß1/Smad pathway was involved in the promotion of ECM synthesis and cell proliferation by CCPP in human skin fibroblasts. These findings suggest that, compared with single collagen, CCPP has a more comprehensive range of antiphotoaging properties.

Microplastics dampen the self-renewal of hematopoietic stem cells by disrupting the gut microbiota-hypoxanthine-Wnt axis.

Microplastics (MPs) are contaminants ubiquitously found in the global biosphere that enter the body through inhalation or ingestion, posing significant risks to human health. Recent studies emerge that MPs are present in the bone marrow and damage the hematopoietic system. However, it remains largely elusive about the specific mechanisms by which MPs affect hematopoietic stem cells (HSCs) and their clinical relevance in HSC transplantation (HSCT). Here, we established a long-term MPs intake mouse model and found that MPs caused severe damage to the hematopoietic system. Oral gavage administration of MPs or fecal transplantation of microbiota from MPs-treated mice markedly undermined the self-renewal and reconstitution capacities of HSCs. Mechanistically, MPs did not directly kill HSCs but disrupted gut structure and permeability, which eventually ameliorated the abundance of Rikenellaceae and hypoxanthine in the intestine and inactivated the HPRT-Wnt signaling in bone marrow HSCs. Furthermore, administration of Rikenellaceae or hypoxanthine in mice as well as treatment of WNT10A in the culture system substantially rescued the MPs-induced HSC defects. Finally, we validated in a cohort of human patients receiving allogenic HSCT from healthy donors, and revealed that the survival time of patients was negatively correlated with levels of MPs, while positively with the abundance of Rikenellaceae, and hypoxanthine in the HSC donors' feces and blood. Overall, our study unleashes the detrimental roles and mechanisms of MPs in HSCs, which provides potential strategies to prevent hematopoietic damage from MPs and serves as a fundamental critique for selecting suitable donors for HSCT in clinical practice.

Role of HCN channels in the functions of basal ganglia and Parkinson's disease.

Parkinson's disease (PD) is a motor disorder resulting from dopaminergic neuron degeneration in the substantia nigra caused by age, genetics, and environment. The disease severely impacts a patient's quality of life and can even be life-threatening. The hyperpolarization-activated cyclic nucleotide-gated (HCN) channel is a member of the HCN1-4 gene family and is widely expressed in basal ganglia nuclei. The hyperpolarization-activated current mediated by the HCN channel has a distinct impact on neuronal excitability and rhythmic activity associated with PD pathogenesis, as it affects the firing activity, including both firing rate and firing pattern, of neurons in the basal ganglia nuclei. This review aims to comprehensively understand the characteristics of HCN channels by summarizing their regulatory role in neuronal firing activity of the basal ganglia nuclei. Furthermore, the distribution and characteristics of HCN channels in each nucleus of the basal ganglia group and their effect on PD symptoms through modulating neuronal electrical activity are discussed. Since the roles of the substantia nigra pars compacta and reticulata, as well as globus pallidus externus and internus, are distinct in the basal ganglia circuit, they are individually described. Lastly, this investigation briefly highlights that the HCN channel expressed on microglia plays a role in the pathological process of PD by affecting the neuroinflammatory response.

Activation of Bivalent Gene POU4F1 Promotes and Maintains Basal-like Breast Cancer.

Basal-like breast cancer (BLBC) is the most aggressive molecular subtype of breast cancer with worse prognosis and fewer treatment options. The underlying mechanisms upon BLBC transcriptional dysregulation and its upstream transcription factors (TFs) remain unclear. Here, among the hyperactive candidate TFs of BLBC identified by bioinformatic analysis, POU4F1 is uniquely upregulated in BLBC and is associated with poor prognosis. POU4F1 is necessary for the tumor growth and malignant phenotypes of BLBC through regulating G1/S transition by direct binding at the promoter of CDK2 and CCND1. More importantly, POU4F1 maintains BLBC identity by repressing ERα expression through CDK2-mediated EZH2 phosphorylation and subsequent H3K27me3 modification in ESR1 promoter. Knocking out POU4F1 in BLBC cells reactivates functional ERα expression, rendering BLBC sensitive to tamoxifen treatment. In-depth epigenetic analysis reveals that the subtype-specific re-configuration and activation of the bivalent chromatin in the POU4F1 promoter contributes to its unique expression in BLBC, which is maintained by DNA demethylase TET1. Together, these results reveal a subtype-specific epigenetically activated TF with critical role in promoting and maintaining BLBC, suggesting that POU4F1 is a potential therapeutic target for BLBC.

An efficient and accurate 2D human pose estimation method using VTTransPose network.

Human pose estimation is a crucial area of study in computer vision. Transformer-based pose estimation algorithms have gained popularity for their excellent performance and relatively compact parameterization. However, these algorithms often face challenges including high computational demands and insensitivity to local details. To address these problems, the Twin attention module was introduced in TransPose to improve model efficiency and reduce resource consumption. Additionally, to address issues related to insufficient joint feature representation and poor network recognition performance, the enhanced TransPose model, named VTTransPose, replaced the basic block in the third subnet with the intra-level feature fusion module V block. The performance of the proposed VTTransPose model was validated on the public datasets COCO val2017 and COCO test-dev2017. The experimental results on COCO val2017 and COCO test-dev2017 indicate that the AP evaluation index scores of the VTTransPose network proposed are 76.5 and 73.6 respectively, marking improvements of 0.4 and 0.2 over the original TransPose network. Additionally, VTTransPose exhibited a reduction of 4.8G FLOPs, 2M parameters, and approximately 40% lower memory usage during training compared to the original TransPose model. All the experimental results demonstrate that the proposed VTTransPose is more accurate, efficient, and lightweight compared to the original TransPose model.

Extended Conjugation Strategy Enabling Red-Shifted and Efficient Emission of Orange-Red Thermally Activated Delayed Fluorescence Materials.

In account of the energy gap law, the development of efficient narrow-band gap thermally activated delayed fluorescence (TADF) materials remains a major challenge for the application of organic light-emitting diodes (OLEDs). The orange-red TADF materials are commonly designed with either large π-conjugated systems or strong intramolecular donor-acceptor (D-A) interactions for red-shift emission and small singlet-triplet energy gap (ΔEST). There are rare reports on the simultaneous incorporation of these two strategies on the same material systems. Herein, two orange-red emitters named 1P2D-BP and 2P2D-DQ have been designed by extending the conjugation degree of the center acceptor DQ and increasing the number distribution of the peripheral donor PXZ units, respectively. The emission peak of 1P2D-BP is red-shifted to 615 nm compared to 580 nm for 2P2D-DQ, revealing the pronounced effect of the conjugation extension on the emission band gap. In addition, the distorted molecular structure yields a small ΔEST of 0.02 eV, favoring the acquisition of a high exciton utilization through an efficient reverse intersystem crossing process. As a result, orange-red OLEDs with both 1P2D-BP and 2P2D-DQ have achieved an external quantum efficiency (EQE) of more than 17%. In addition, the efficient white OLED based on 1P2D-BP is realized through precise exciton assignment and energy transport modulation, showing an EQE of 23.6% and a color rendering index of 82. The present work provides an important reference for the design of high-efficiency narrow-band gap materials in the field of solid-state lighting.

Yigansan ameliorates maternal immune activation-induced autism-like behaviours by regulating the IL-17A/TRAF6/MMP9 pathway: Network analysis and experimental validation.

BACKGROUND: Maternal immune activation (MIA) is a significant factor inducing to autism spectrum disorder (ASD) in offspring. The fundamental principle underlying MIA is that inflammation during pregnancy impedes fetal brain development and triggers behavioural alterations in offspring. The intricate pathogenesis of ASD renders drug treatment effects unsatisfactory. Traditional Chinese medicine has strong potential due to its multiple therapeutic targets. Yigansan, composed of seven herbs, is one of the few that has been proven to be effective in treating neuro-psychiatric disorders among numerous traditional Chinese medicine compounds, but its therapeutic effect on ASD remains unknown. HYPOTHESIS: Yigansan improves MIA-induced ASD-like behaviours in offspring by regulating the IL-17 signalling pathway. METHODS: Pregnant C57BL/6J mice were intraperitoneally injected with poly(I:C) to construct MIA models and offspring ASD models. Network analysis identified that the IL-17A/TRAF6/MMP9 pathway is a crucial pathway, and molecular docking confirmed the binding affinity between the monomer of Yigansan and target proteins. qRT-PCR and Western blot were used to detect the expression levels of inflammatory factors and pathway proteins, immunofluorescence was used to detect the distribution of IL-17A, and behavioural tests were used to evaluate the ASD-like behaviours of offspring. RESULTS: We demonstrated that Yigansan can effectively alleviate MIA-induced neuroinflammation of adult offspring by regulating the IL-17A/TRAF6/MMP9 pathway, and the expression of IL-17A was reduced in the prefrontal cortex. Importantly, ASD-like behaviours have been significantly improved. Moreover, we identified that quercetin is the effective monomer for Yigansan to exert therapeutic effects. CONCLUSION: Overall, this study was firstly to corroborate the positive therapeutic effect of Yigansan in the treatment of ASD. We elucidated the relevant molecular mechanism and regulatory pathway involved, determined the optimal therapeutic dose and effective monomer, providing new solutions for the challenges of drug therapy for ASD.

Pulsed electric field-assisted extraction of hesperidin from tangerine peel and its technological optimization through response surface methodology.

BACKGROUND: Tangerine peel is rich in flavonoids, particularly hesperidin, which has anti-inflammatory, antioxidant and anticancer biological activities. However, it is often wasted during citrus processing. The current common extraction method for hesperidin is solvent extraction, which has the characteristics of low extraction rate and high contamination. The aim of this study was to investigate the effect of pulsed electric field-assisted alkali dissolution extraction, followed by an acidification precipitation method, on the extraction rate and structure of hesperidin from tangerine peel. RESULTS: The results showed that the selected factors (material/liquid ratio, electric field intensity and pulse number) had a significant effect on the extraction yield. An optimum condition of 66.00 mL g-1, 4.00 kV cm-1 and 35.00 pulses gave the maximum amount (669.38 µg mL-1), which was consistent with the theoretically predicted value by software (672.10 µg mL-1), indicating that the extraction process was feasible. In addition, the purified extract was further identified as hesperidin from UV and NMR spectra. CONCLUSION: An appropriate strength of pulsed electric field-assisted alkali dissolution extraction followed by an acidification precipitation method can effectively improve the extraction rate of orange peel, and the purity of the extracted orange peel is higher. Compared with the traditional extraction, the pulsed electric field-assisted extraction method may be a potential technology for hesperidin extraction, which is beneficial for the high-value utilization of citrus resources. © 2024 Society of Chemical Industry.