Photoactivated room temperature phosphorescence from lignin.

Sustainable photoactivated room temperature phosphorescent materials exhibit great potential but are difficult to obtain. Here, we develop photoactivated room temperature phosphorescent materials by covalently attaching lignin to polylactic acid, where lignin and polylactic acid are the chromophore and matrix, respectively. Initially the phosphorescence of the lignin is quenched by residual O2. However, the phosphorescence is switched on when the residual oxygen is consumed by the triplet excitons of lignin under continuous UV light irradiation. As such, the lifetime increases from 3.0 ms to 221.1 ms after 20 s of UV activation. Interestingly, the phosphorescence is quenched again after being kept under an atmosphere of air for 2 h in the absence of UV irradiation due to the diffusion of oxygen into the materials. Using these properties, as-developed material is successfully used as a smart anti-counterfeiting logo for a medicine bottle and for information recording.

Disulfidptosis-related gene expression reflects the prognosis of drug-resistant cancer patients and inhibition of MYH9 reverses sorafenib resistance.

The onset of drug resistance in advanced cancer patients markedly diminishes their prognosis. Recently, disulfidptosis, a novel form of cell death, has been identified, triggered by excessive disulfide formation leading to cell shrinkage and F-actin contraction. Previous studies have identified 15 essential genes (FLNA, FLNB, MYH9, TLN1, ACTB, MYL6, MYH10, CAPZB, DSTN, IQGAP1, ACTN4, PDLIM1, CD2AP, INF2, SLC7A11) associated with disulfidptosis. This study sourced pan-cancer mRNA expression data from Xena to thoroughly evaluate the molecular and clinical characteristics of disulfidptosis-related genes. Through unsupervised clustering, mRNA expression data identified the expression levels of disulfidptosis-related genes and potential clusters related to this form of cell death. Kaplan-Meier survival curves illustrated the correlation between different clusters and overall survival. The findings reveal that high expression of disulfidptosis-related genes is linked to poor survival in liver cancer. The GDSC database was utilized to analyze the relationship between disulfidptosis-related genes and the AUC of 198 drugs. The results demonstrate that 12 disulfidptosis-related genes influence sorafenib resistance, as revealed by the intersection of differential genes related to sorafenib resistance from the GSE109211 dataset. Among them, the MYH9 gene was found to play a crucial role in both. Finally, experimental evidence confirmed that MYH9 mitigates sorafenib resistance in hepatocellular carcinoma through disulfidptosis-like changes. This study identifies disulfidptosis as a promising avenue for enhancing the sensitivity of tumor cells to drugs, offering new therapeutic perspectives for future research on disulfidptosis and drug resistance in cancer patients.

Aloe-emodin alleviates inflammatory bowel disease in mice by modulating intestinal microbiome homeostasis via the IL-4/IL-13 axis.

Introduction: Inflammatory bowel disease (IBD) is a global health concern. Aloe-emodin (AE) has diverse pharmacological benefits, including anti-inflammatory effects. However, its role in IBD remains unclear, prompting our investigation of its regulatory effects and mechanisms in an IBD mouse model. Methods: We studied the therapeutic efficacy of AE in alleviating symptoms and modulating cytokine secretion in a murine model of dextran sulfate sodium (DSS)-induced colitis. BALB/c mice were administered DSS to induce colitis and were subsequently treated with varying doses of AE. Changes in body weight, fecal lipocalin-2 (LCN2) levels, colon tissue histology, and serum cytokine concentrations were evaluated to assess the effects of AE treatment. Additionally, 16 S rRNA sequencing was used to analyze alterations in the composition of the gut microbiota following AE intervention. Finally, the database was used to analyze the signaling pathways associated with IBD in AE and to detect the expression levels of interleukin (IL)-4 pathway using real-time quantitative reverse transcription PCR. Exogenous IL-4 was used in rescue experiments to observe its effects on the disease process of IBD under AE regulation. Results: AE treatment resulted in a dose-dependent mitigation of weight loss, reduction in fecal LCN2 levels, and amelioration of histological damage in DSS-induced colitis in mice. The levels of superoxide dismutase and catalase increased, whereas malondialdehyde decreased following AE treatment, indicating a dose-dependent alleviation of colitis symptoms. Furthermore, AE administration attenuated the secretion of pro-inflammatory cytokines, including IL-17, tumor necrosis factor-alpha (TNF-α), and chemokine ligand 1, while promoting the expression of anti-inflammatory cytokines IL-4 and IL-13. Analysis of the gut microbiota revealed that AE effectively suppressed the overgrowth of colitis-associated bacterial species and restored microbial homeostasis. Finally, we found that overexpression of IL-4 was able to reverse the therapeutic effect of AE for DSS-induced IBD. Conclusion: AE shows promise in alleviating colitis severity, influencing inflammatory cytokines, and modulating the gut microbiota in an IBD mouse model via the IL-4/IL-13 pathway, suggesting its potential as a natural IBD remedy.

Enhancing lower limb and core muscle activation with blood flow restriction training: a randomized crossover study on high-intensity squat exercises.

Objective: The primary objective of this study was to assess the impact of high-intensity deep squat training integrated with various blood flow restriction (BFR) modalities on the activation of lower limb and core muscles. Methods: A randomized, self-controlled crossover experimental design was employed with 12 participants. The exercise protocol consisted of squat training at 75% of one-repetition maximum (1RM), performed in 3 sets of 8 repetitions with a 2-min inter-set rest period. This was conducted under four distinct BFR conditions: continuous low BFR (T1), intermittent medium BFR (T2), intermittent high BFR (T3), and a non-restricted control (C). Surface electromyography (EMG) was utilized to collect EMG signals from the target muscles during the BFR and squat training sessions. The root mean square (RMS) amplitude standard values were calculated for each squat set to quantify muscle activation levels, with these values expressed as a percentage of the maximum voluntary contraction (%MVC). Rating of Perceived Exertion was evaluated after each squat set, and leg circumference measurements were taken. Results: 1) During the first two sets of deep squats, the %MVC of the vastus lateralis and vastus medialis in all compression groups was significantly higher than that in the control group (p < 0.05). Furthermore, in the first set, the %MVC of the vastus lateralis in Group T3 was significantly higher than in Group T2 (p < 0.05). In the third set, the %MVC of the vastus medialis in Groups T1 and T3 was significantly lower than in the first two sets (p < 0.05). 2) Group T1 showed an increased activation of the biceps femoris and semitendinosus muscles in the second and third sets, with %MVC values significantly greater than in the first set (p < 0.05). Group T2 only showed an increase in biceps femoris activation in the third set (p < 0.05). Group T3 significantly increased the activation of the biceps femoris and semitendinosus muscles only in the first set (p < 0.05). 3) No significant differences were observed in the changes of rectus abdominis %MVC among the groups (p > 0.05). In the first set, Group T3's erector spinae %MVC was significantly higher than the control group's; in the second set, it was significantly higher than both Group T2 and the control group's (p < 0.05). 4) After training, a significant increase in thigh circumference was observed in all groups compared to before training (p < 0.05). 5) For RPE values, Group T2's post-squat values were significantly higher than the control group's after all three sets (p < 0.05). Group T1's RPE values were also significantly higher than the control group's after the third set (p < 0.05). Groups T1, T2, and C all had significantly higher RPE values in the second and third sets compared to the first set (p < 0.05). Conclusion: All BFR modalities significantly enhanced the activation level of the anterior thigh muscles, with the continuous low BFR mode demonstrating a more stable effect. No significant differences were found in the activation level of the rectus abdominis among the groups. However, the intermittent high BFR mode was the most effective in increasing the activation level of the erector spinae muscles. While BFR did not further augment leg circumference changes, it did elevate subjective fatigue levels. The RPE was lowest during squatting under the intermittent high BFR condition.

Radiomics of intrathrombus and perithrombus regions for Post-EVT intracranial hemorrhage risk Prediction: A multicenter CT study.

OBJECTIVES: This study aimed to assess the predictive performance of radiomics derived from computed tomography (CT) images of thrombus regions in predicting the risk of intracranial hemorrhage (ICH) following endovascular thrombectomy (EVT). MATERIALS AND METHODS: This retrospective multicenter study included 336 patients who underwent admission CT and EVT for acute anterior-circulation large vessel occlusion between December 2018 and December 2023. Follow-up imaging was performed 24 h post-procedure to evaluate the occurrence of ICH. 230 patients from centers A and B were randomly allocated into training and test groups in a 7:3 ratio, while the remaining 106 patients from center C comprised the validation cohort. Radiologists manually segmenting the thrombus on CT images, and the perithrombus region was defined by expanding the initial region of interest (ROI). A total of 428 radiomics features were extracted from both intrathrombus and perithrombus regions on CT images. The Mann-Whitney U test was used for feature selection, and least absolute shrinkage and selection operator (LASSO) regression was employed for model development, followed by validation using a 5-fold cross-validation approach. Model performance was assessed using the area under the curve (AUC) of the receiver operating characteristic (ROC). RESULTS: Among the eligible patients, 128 (38.1 %) experienced ICH after EVT. The combined model exhibited superior performance in the training cohort (AUC: 0.913, 95 % CI: 0.861-0.965), test cohort (AUC: 0.868, 95 % CI: 0.775-0.962), and validation cohort (AUC: 0.850, 95 % CI: 0.768-0.912). Notably, in the validation group, both the perithrombus and combined models demonstrated higher predictive accuracy compared to the intrathrombus model (0.837 vs. 0.684, p = 0.02; AUC: 0.850 vs. 0.684, p = 0.01). CONCLUSIONS: Radiomics features derived from the perithrombus region significantly enhance the prediction of ICH after EVT, providing valuable insights for optimizing post-procedural clinical decisions. CLINICAL RELEVANCE STATEMENT: This study highlights the importance of radiomics extracted from intrathrombus and perithrombus region in predicting intracranial hemorrhagefollowing endovascular thrombectomy, which can aid in improving patient outcomes.

Complete genome sequence of a novel botourmiavirus infecting the fungus Phomopsis asparagi.

Here, we report a novel ourmia-like mycovirus, named "Phomopsis asparagi magoulivirus 1" (PaMV1), derived from the phytopathogenic fungus Phomopsis asparagi. The genome of PaMV1 consists of a positive-sense single-stranded RNA (+ ssRNA) that is 2,639 nucleotides in length, with a GC content of 57.13%. It contains a single open reading frame (ORF) encoding a putative RNA-dependent RNA polymerase (RdRp) consisting of 686 amino acids with a molecular mass of 78.57 kDa. Phylogenetic analysis based on RdRp sequences revealed that PaMV1 grouped together with Diaporthe gulyae magoulivirus 1 (DgMV1) in a distinct clade. Sequence comparisons and phylogenetic analysis suggest that PaMV1 is a novel member of the genus Magoulivirus, family Botourmiaviridae.

Deep representation learning of chemical-induced transcriptional profile for phenotype-based drug discovery.

Artificial intelligence transforms drug discovery, with phenotype-based approaches emerging as a promising alternative to target-based methods, overcoming limitations like lack of well-defined targets. While chemical-induced transcriptional profiles offer a comprehensive view of drug mechanisms, inherent noise often obscures the true signal, hindering their potential for meaningful insights. Here, we highlight the development of TranSiGen, a deep generative model employing self-supervised representation learning. TranSiGen analyzes basal cell gene expression and molecular structures to reconstruct chemical-induced transcriptional profiles with high accuracy. By capturing both cellular and compound information, TranSiGen-derived representations demonstrate efficacy in diverse downstream tasks like ligand-based virtual screening, drug response prediction, and phenotype-based drug repurposing. Notably, in vitro validation of TranSiGen's application in pancreatic cancer drug discovery highlights its potential for identifying effective compounds. We envisage that integrating TranSiGen into the drug discovery and mechanism research holds significant promise for advancing biomedicine.

Nonlinear 3D Ligand-Based Metal-Organic Framework for Thermodynamic-Kinetic Synergistic Splitting of Mono-/Dibranched Hexane Isomers.

The selective splitting of hexane isomers without the use of energy-intensive phase-change processes is essential for the low-carbon production of clean fuels and also very challenging. Here, we demonstrate a strategy to achieve a complete splitting of the high-RON dibranched isomer from the monobranched and linear isomers, by using a nonlinear 3D ligand to form pillar-layered MOFs with delicate pore architecture and chemistry. Compared with its isoreticular MOFs with the same ted pillar but different linear 3D or linear 2D in-layer ligands, the new MOF constructed in this work, Cu(bhdc)(ted)0.5 (ZUL-C5), exhibited an interesting "channel switch" effect which creates pore space with reduced window size and channel dimensionality together with unevenly distributed alkyl-rich adsorption sites, contributing to a greatly enhanced ability to discriminate between mono- and dibranched isomers. Evidenced by a series of studies including adsorption equilibrium/kinetics/breakthrough tests, guest-loaded single-crystal/powder XRD measurement, and DFT-D modeling, a thermodynamic-kinetic synergistic mechanism in the separation was proposed, resulting in a record production time for high-purity 2,2-dimethylbutane along with a high yield.

KinomeMETA: a web platform for kinome-wide polypharmacology profiling with meta-learning.

Kinase-targeted inhibitors hold promise for new therapeutic options, with multi-target inhibitors offering the potential for broader efficacy while minimizing polypharmacology risks. However, comprehensive experimental profiling of kinome-wide activity is expensive, and existing computational approaches often lack scalability or accuracy for understudied kinases. We introduce KinomeMETA, an artificial intelligence (AI)-powered web platform that significantly expands the predictive range with scalability for predicting the polypharmacological effects of small molecules across the kinome. By leveraging a novel meta-learning algorithm, KinomeMETA efficiently utilizes sparse activity data, enabling rapid generalization to new kinase tasks even with limited information. This significantly expands the repertoire of accurately predictable kinases to 661 wild-type and clinically-relevant mutant kinases, far exceeding existing methods. Additionally, KinomeMETA empowers users to customize models with their proprietary data for specific research needs. Case studies demonstrate its ability to discover new active compounds by quickly adapting to small dataset. Overall, KinomeMETA offers enhanced kinome virtual profiling capabilities and is positioned as a powerful tool for developing new kinase inhibitors and advancing kinase research. The KinomeMETA server is freely accessible without registration at https://kinomemeta.alphama.com.cn/.

Machine learning approaches to debris flow susceptibility analyses in the Yunnan section of the Nujiang River Basin.

Background: The Yunnan section of the Nujiang River (YNR) Basin in the alpine-valley area is one of the most critical areas of debris flow in China. Methods: We analyzed the applicability of three machine learning algorithms to model of susceptibility to debris flow-Random Forest (RF), the linear kernel support vector machine (Linear SVM), and the radial basis function support vector machine (RBFSVM)-and compared 20 factors to determine the dominant controlling in debris flow occurrence in the region. Results: We found that (1) RF outperformed RBFSVM and Linear SVM in terms of accuracy, (2) topographic conditions were prerequisites, and geology, precipitation, vegetation, and anthropogenic influence were critical to forming debris flows. Also, the relative elevation difference was the most prominent evaluation factor of debris flow susceptibility, and (3) susceptibility maps based on RF's debris flow susceptibility (DFS) showed that zones with very high susceptibility were distributed along the mainstream of the Nujiang River. These findings provide methodological guidance and reference for improvement of DFS assessment. It enriches the content of DFS studies in the alpine-valley areas.

The combined exposure of polystyrene microplastics and high-fat feeding affects the intestinal pathology damage and microbiome in zebrafish.

The pervasive utilization of plastics and their integration into ecosystems has resulted in significant environmental issues, particularly the pollution of microplastics (MPs). In aquaculture, high-fat feed (HFD) is frequently employed to enhance the energy intake and economic fish production. This study utilized zebrafish as a model organism to investigate the impact of concurrent exposure to HFD and MPs on fish intestinal pathology damage and intestinal microbiome. The experimental design involved the division of zebrafish into two groups: one receiving a normal diet (ND) and the other receiving HFD. The zebrafish were exposed to a control group, as well as polystyrene (PS) MPs of varying sizes (5 and 50 µm). Histopathological examination revealed that the combination of 5 µm MPs and HFD resulted in the most significant damage to the zebrafish intestinal tract. Furthermore, gut microbiome assays indicated that exposure to MPs and HFD altered the composition of the gut microbiome. This study demonstrates that in aquaculture, the issue of HFD must be considered alongside concerns about MPs contamination, as both factors appear to have a combined effect on the intestinal pathology damage and intestinal microbiome. The findings of this research offer valuable insights for the improvement of fish farming practices.

Cascade reaction triggered colorimetric array for identification of organophosphorus pesticides congeners.

A modern agriculture uses alternative pest control methods to boost productivity, leading to an accumulation of organophosphorus (OPPs) congeners. This necessitates an intuitive and quick way to identify OPPs congeners. A colorimetric sensor for detecting OPPs congeners using a double-enzyme cascade reaction has been successfully designed and constructed in this study. The OPPs regulate the color changes induced by manganese dioxide nanoflowers (MnO2 NFs) and specific alkaline phosphatases (ALP) during the etching of gold nanopyramids (Au NBPs). The ascorbic acid (AA) produced by ALP hydrolysis inhibits Au NBPs etching by MnO2 NFs oxidized 3, 3', 5, 5'-tetramethylbenzidine (TMB). By inhibiting ALP catalytic activity, OPPs prevent AA formation. In this process, Au NBPs will undergo further etching, resulting in various colors so they can be analyzed semi-quantitatively with the naked eye. It has been found that different types of OPPs inhibit enzymes differently and therefore result in varying degrees of etching of Au NBPs. Principal Component Analysis (PCA) is performed by smart devices that convert R, G, and B signals into digital signals. This colorimetric array tests various foods (tea, apple, and cabbage). Colorimetric visualization sensors combined with data analysis will be used in real-life product development.

Targeting pro-inflammatory T cells as a novel therapeutic approach to potentially resolve atherosclerosis in humans.

Atherosclerosis (AS), a leading cause of cardio-cerebrovascular disease worldwide, is driven by the accumulation of lipid contents and chronic inflammation. Traditional strategies primarily focus on lipid reduction to control AS progression, leaving residual inflammatory risks for major adverse cardiovascular events (MACEs). While anti-inflammatory therapies targeting innate immunity have reduced MACEs, many patients continue to face significant risks. Another key component in AS progression is adaptive immunity, but its potential role in preventing AS remains unclear. To investigate this, we conducted a retrospective cohort study on tumor patients with AS plaques. We found that anti-programmed cell death protein 1 (PD-1) monoclonal antibody (mAb) significantly reduces AS plaque size. With multi-omics single-cell analyses, we comprehensively characterized AS plaque-specific PD-1+ T cells, which are activated and pro-inflammatory. We demonstrated that anti-PD-1 mAb, when captured by myeloid-expressed Fc gamma receptors (FcγRs), interacts with PD-1 expressed on T cells. This interaction turns the anti-PD-1 mAb into a substitute PD-1 ligand, suppressing T-cell functions in the PD-1 ligands-deficient context of AS plaques. Further, we conducted a prospective cohort study on tumor patients treated with anti-PD-1 mAb with or without Fc-binding capability. Our analysis shows that anti-PD-1 mAb with Fc-binding capability effectively reduces AS plaque size, while anti-PD-1 mAb without Fc-binding capability does not. Our work suggests that T cell-targeting immunotherapy can be an effective strategy to resolve AS in humans.

Diagnostic significance and predictive efficiency of metabolic risk score for fertility-sparing treatment in patients with atypical endometrial hyperplasia and early endometrial carcinoma.

OBJECTIVE: This study aims to assess the impact of the metabolic risk score (MRS) on time to achieve complete remission (CR) of fertility-sparing treatments for atypical endometrial hyperplasia (AEH) and early endometrial cancer (EC) patients. METHODS: Univariate and multivariate cox analyses were employed to identify independent risk factors affecting the time to CR with patients at our center. These factors were subsequently incorporated into receiver operator characteristic curve analysis and decision curve analysis to assess the predictive accuracy of time to CR. Additionally, Kaplan-Meier analysis was utilized to determine the cumulative CR rate for patients. RESULTS: The 173 patients who achieved CR following fertility preservation treatment (FPT) were categorized into three subgroups based on their time to CR (<6, 6-9, >9 months). Body mass index (hazard ratio [HR]=0.20; 95% confidence interval [CI]=0.03, 0.38; p=0.026), MRS (HR=0.31; 95% CI=0.09, 0.52; p=0.005), insulin resistance (HR=1.83; 95% CI=0.05, 3.60; p=0.045), menstruation regularity (HR=3.77; 95% CI=1.91, 5.64; p=0.001), polycystic ovary syndrome (HR=-2.16; 95% CI=-4.03, -0.28; p=0.025), and histological type (HR=0.36; 95% CI=0.10, 0.62; p=0.005) were identified as risk factors for time to CR, with MRS being the independent risk factor (HR=0.29; 95% CI=0.02, 0.56; p=0.021). The inclusion of MRS significantly enhanced the predictive accuracy of time to CR (area under the curve [AUC]=0.789 for Model 1, AUC=0.862 for Model 2, p=0.032). Kaplan-Meier survival curves revealed significant differences in the cumulative CR rate among different risk groups. CONCLUSION: MRS emerges as a novel evaluation system that substantially enhances the predictive accuracy for the time to achieve CR in AEH and early EC patients seeking fertility preservation.

KinomeMETA: meta-learning enhanced kinome-wide polypharmacology profiling.

Kinase inhibitors are crucial in cancer treatment, but drug resistance and side effects hinder the development of effective drugs. To address these challenges, it is essential to analyze the polypharmacology of kinase inhibitor and identify compound with high selectivity profile. This study presents KinomeMETA, a framework for profiling the activity of small molecule kinase inhibitors across a panel of 661 kinases. By training a meta-learner based on a graph neural network and fine-tuning it to create kinase-specific learners, KinomeMETA outperforms benchmark multi-task models and other kinase profiling models. It provides higher accuracy for understudied kinases with limited known data and broader coverage of kinase types, including important mutant kinases. Case studies on the discovery of new scaffold inhibitors for membrane-associated tyrosine- and threonine-specific cdc2-inhibitory kinase and selective inhibitors for fibroblast growth factor receptors demonstrate the role of KinomeMETA in virtual screening and kinome-wide activity profiling. Overall, KinomeMETA has the potential to accelerate kinase drug discovery by more effectively exploring the kinase polypharmacology landscape.

Functional and structural analysis of a novel splice site HMBS variant in a Chinese AIP patient.

Background: Acute intermittent porphyria (AIP) is a rare metabolic disorder that results from mutations in the gene encoding hydroxymethylbilane synthase (HMBS), an enzyme involved in heme biosynthesis. AIP follows an autosomal dominant inheritance pattern, but most carriers are asymptomatic. The clinical manifestations of AIP include acute attacks of abdominal pain and neuropsychiatric disturbances. The pathogenicity of novel HMBS variants identified in Chinese patients has not been well established. Objective: The article aims to identify the pathogenic mutation in an AIP patient and prove its pathogenicity through in vitro experiments. Methods: A 22-year-old female diagnosed with AIP participated in the study. Variant screening of her HMBS gene was carried out through Sanger sequencing. To ascertain the consequences of the newly discovered variant, we conducted in vitro experimentation targeting HMBS gene expression and enzymatic function. Additionally, protein structure analysis was performed. Cycloheximide treatment and UPF1-specific siRNA knockdown were employed to assess the impact of the mutation on the mechanism of non-sense-mediated mRNA decay (NMD). Results: A novel splice site variant in the HMBS gene (c.648_651+1delCCAGG) was detected in the patient, which caused aberrant mRNA splicing. In vitro experiments demonstrated that this variant significantly decreased the expression of HMBS. Further investigation confirmed that this decrease was due to NMD. Additionally, structural analysis indicated that this variant would destabilize the HMBS protein and impair its catalytic activity. To gain a comprehensive understanding of HMBS mutations in the context of AIP, we conducted a literature search on PubMed using the keywords 'HMBS' and 'Acute intermittent porphyria' from 2013 to 2023. This search yielded 19 clinical case reports written in English, which collectively described 220 HMBS gene mutations worldwide. Conclusion: The study identified and proved the pathogenicity of a novel splice site HMBS variant for the first time. Our results elucidated the pathological mechanism by which this mutation causes AIP through reducing HMBS expression and activity. These findings provide theoretical guidance for the diagnosis, treatment and genetic counseling of AIP patients.