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In order to investigate the key nodes affecting the changes of Yixian dark tea flavor and quality during the Pile fermentation, in this study, the sensory quality and non-volatile profiles of Yixian dark tea samples at different pile fermentation periods (0, 3, 6, 9, 12, 15, 18 h) were investigated by sensory evaluation, amino acids analyzer, liquid chromatography and liquid chromatography mass spectrometry. The results showed that the intensity of bitterness in dark tea infusions declined after 9 h of pile fermentation, along with the increasing intensities of astringency, thickness and stale-mellow. Total catechins showed a significant decrease in concentrations during pile fermentation. In contrast, the concentration of gallic acid increased. Concentration of caffeine reduced by 14.7% compared to the original concentration after 18 h of pile fermentation. Total amino acids concentration showed an increasing tendency in the later period of pile fermentation. Concentrations of flavonoids and its mono-glycosides increased after 9~12 hours, while its di-glycosides showed an increasing tendency after 12 hours of pile fermentation. The analysis of key taste substances (VIP>1, DOT>1) showed that myricetin-3-O-galactoside, astragalin, isoquercitrin, quercetin-3-O-rutinose, epigallocatechin, epicatechin, epigallocatechin gallate, and caffeine were the most important flavor presenting substances affecting the quality changes of Yixian dark tea. Among them, the content of the first three glycosides increased significantly from 9~12 hours of stacking; The contents of epigallocatechin and epicatechin were significantly reduced during 9~12 hours. Epigallocatechin gallate and caffeine showed a significant decrease after pile fermentation; Quercetin-3-O-rutinoside decreased significantly in the middle stage (9~12 hours) and increased significantly after 15 hours. It was an important factor in the increase of astringency of tea broth in the late stage of pile fermentation. This study give a theoretical basis for improving the tea processing of Yixian dark tea and understanding the formation mechanism of its key flavor.

Abstract To date, there have been no reports on tertiary lymphoid structures (TLS) in primary adenocarcinoma of jejunum and ileum. In this study, we employed digital pathology image analysis software to classify and quantify TLS, and evaluated the maturity of TLS using immunohistochemistry. Molecular genetics and immunotherapy biomarker detection were performed using next-generation sequencing technology, such as tumor mutational burden (TMB) and microsatellite instability (MSI). The aim of this study was to investigate the presence, location, maturity, association with immunotherapy biomarkers, and prognostic value of TLS in primary adenocarcinoma of jejunum and ileum. Compared to secondary follicle-like TLS (SFL-TLS), intra-tumoral TLS (IT-TLS) were more likely to manifest as early TLS (E-TLS) (P = 0.007). Compared to IT-TLS, SFL-TLS had a higher propensity to occur at the invasive margin (IM) (P = 0.032) and showed a trend towards being more prevalent at the tumor periphery (P = 0.057). In terms of immunotherapy biomarkers, there was a higher trend of IM-TLS density in PD-L1(22C3) score CPS

Abstract Background Low levels of the essential amino acid lysine in maize endosperm is considered to be a major problem regarding the nutritional quality of food and feed. Increasing the lysine content of maize is important to improve the quality of food and feed nutrition. Although the genetic basis of quality protein maize (QPM) has been studied, the further exploration of the quantitative trait loci (QTL) underlying lysine content variation still needs more attention. Results Eight maize inbred lines with increased lysine content were used to construct four double haploid (DH) populations for identification of QTLs related to lysine content. The lysine content in the four DH populations exhibited continuous and normal distribution. A total of 12 QTLs were identified in a range of 4.42–12.66% in term of individual phenotypic variation explained (PVE) which suggested the quantitative control of lysine content in maize. Five main genes involved in maize lysine biosynthesis pathways in the QTL regions were identified in this study. Conclusions The information presented will allow the exploration of candidate genes regulating lysine biosynthesis pathways and be useful for marker-assisted selection and gene pyramiding in high-lysine maize breeding programs.

Abstract Background Natural products have a long history in drug discovery. Lycorine is an alkaloid derived from Amaryllidaceae plants, demonstrating significant pharmacological potential. Lycorine and its hydrochloride salt, lycorine hydrochloride, have shown outstanding anticancer effects both in vitro and in vivo. Purpose This review aims to comprehensively summarize recent research advancements regarding the anticancer potential of lycorine and lycorine hydrochloride. It intends to elucidate current research limitations, optimization strategies, and future research directions to guide clinical translation. Methods Various databases, e.g., Web of Science, PubMed, and Chinese National Knowledge Infrastructure, are systematically searched for relevant articles using keywords such as lycorine, cancer, pharmacokinetics, and toxicity. The retrieved literature is then categorized and summarized to provide an overview of the research advancements in the anticancer potential of lycorine and lycorine hydrochloride. Results Lycorine and lycorine hydrochloride demonstrate significant anticancer activities against various types of cancer both in vitro and in vivo, employing diverse mechanisms such as inducing cell cycle arrest, triggering cellular senescence, regulating programmed cell death, inhibiting angiogenesis, suppressing metastasis, and modulating immune system. Furthermore, pharmacokinetic profiles and toxicity data are summarized. Additionally, this review discusses the druggability, limitations, optimization strategies, and target identification of lycorine, offering insights for future preclinical studies. Conclusion The anticancer effects and safety profile of lycorine and lycorine hydrochloride suggest promising potential for clinical applications. Further research on their in-depth mechanisms and optimization strategies targeting their limitations will enhance the understanding and druggability of lycorine and lycorine hydrochloride. Graphical Abstract

To investigate the effect of baking on the flavor of albino green tea, Baiye 1 green tea samples with different treatment (0, 40, 80, and 120 min at 60 ℃) were conducted in the study. The dynamic changes of metabolites were detected and analyzed by UHPLC-Q-Exactive/MS and GC-MS. The result showed that green tea sample treated by 40 min at 60 ℃ exhibited a better quality than other green tea samples. The thickness of green tea infusions and the aroma intensity went a downtrend with the increase of baking time, while the intensity of astringency increased. The content of total free amino acids and caffeine increased remarkable with time up (P1, P

Abstract Background One of the major hurdles in clinical genetics is interpreting the clinical consequences associated with germline missense variants in humans. Recent significant advances have leveraged natural variation observed in large-scale human populations to uncover genes or genomic regions that show a depletion of natural variation, indicative of selection pressure. We refer to this as “genetic constraint”. Although existing genetic constraint metrics have been demonstrated to be successful in prioritising genes or genomic regions associated with diseases, their spatial resolution is limited in distinguishing pathogenic variants from benign variants within genes. Methods We aim to identify missense variants that are significantly depleted in the general human population. Given the size of currently available human populations with exome or genome sequencing data, it is not possible to directly detect depletion of individual missense variants, since the average expected number of observations of a variant at most positions is less than one. We instead focus on protein domains, grouping homologous variants with similar functional impacts to examine the depletion of natural variations within these comparable sets. To accomplish this, we develop the Homologous Missense Constraint (HMC) score. We utilise the Genome Aggregation Database (gnomAD) 125 K exome sequencing data and evaluate genetic constraint at quasi amino-acid resolution by combining signals across protein homologues. Results We identify one million possible missense variants under strong negative selection within protein domains. Though our approach annotates only protein domains, it nonetheless allows us to assess 22% of the exome confidently. It precisely distinguishes pathogenic variants from benign variants for both early-onset and adult-onset disorders. It outperforms existing constraint metrics and pathogenicity meta-predictors in prioritising de novo mutations from probands with developmental disorders (DD). It is also methodologically independent of these, adding power to predict variant pathogenicity when used in combination. We demonstrate utility for gene discovery by identifying seven genes newly significantly associated with DD that could act through an altered-function mechanism. Conclusions Grouping variants of comparable functional impacts is effective in evaluating their genetic constraint. HMC is a novel and accurate predictor of missense consequence for improved variant interpretation.

Abstract Background This study investigated whether the Combat compensation method can remove the variability of radiomic features extracted from different scanners, while also examining its impact on the subsequent predictive performance of machine learning models. Materials and methods 135 CT images of Credence Cartridge Radiomic phantoms were collected and screened from three scanners manufactured by Siemens, Philips, and GE. 100 radiomic features were extracted and 20 radiomic features were screened according to the Lasso regression method. The radiomic features extracted from the rubber and resin-filled regions in the cartridges were labeled into different categories for evaluating the performance of the machine learning model. Radiomics features were divided into three groups based on the different scanner manufacturers. The radiomic features were randomly divided into training and test sets with a ratio of 8:2. Five machine learning models (lasso, logistic regression, random forest, support vector machine, neural network) were employed to evaluate the impact of Combat on radiomic features. The variability among radiomic features were assessed using analysis of variance (ANOVA) and principal component analysis (PCA). Accuracy, precision, recall, and area under the receiver curve (AUC) were used as evaluation metrics for model classification. Results The principal component and ANOVA analysis results show that the variability of different scanner manufacturers in radiomic features was removed (P˃0.05). After harmonization with the Combat algorithm, the distributions of radiomic features were aligned in terms of location and scale. The performance of machine learning models for classification improved, with the Random Forest model showing the most significant enhancement. The AUC value increased from 0.88 to 0.92. Conclusions The Combat algorithm has reduced variability in radiomic features from different scanners. In the phantom CT dataset, it appears that the machine learning model’s classification performance may have improved after Combat harmonization. However, further investigation and validation are required to fully comprehend Combat’s impact on radiomic features in medical imaging.

Bone metastasis is the prevalent form of metastasis in breast cancer, resulting in severe pain, pathological fractures, nerve compression, hypercalcemia, and other complications that significantly impair patients' quality of life. The infiltration and colonization of breast cancer (BC) cells in bone tissue disrupt the delicate balance between osteoblasts and osteoclasts within the bone microenvironment, initiating a vicious cycle of bone metastasis. Once bone metastasis occurs, conventional medical therapy with bone-modifying agents is commonly used to alleviate bone-related complications and improve patients' quality of life. However, the utilization of bone-modifying agents may cause severe drug-related adverse effects. Plant-derived natural products such as terpenoids, alkaloids, coumarins, and phenols have anti-tumor, anti-inflammatory, and anti-angiogenic pharmacological properties with minimal side effects. Certain natural products that exhibit both anti-breast cancer and anti-bone metastasis effects are potential therapeutic agents for breast cancer bone metastasis (BCBM). This article reviewed the effects of plant-derived natural products against BCBM and their mechanisms to provide a reference for the research and development of drugs related to BCBM.

ERA5 (European Centre for Medium-Range Weather Forecasts Reanalysis Fifth Generation) is a significant dataset in climate reanalysis. Conducting a global-scale accuracy assessment and spatiotemporal distribution characteristic study of its temperature and precipitation data is crucial for gaining in-depth understanding of extreme climate changes. This study, based on CRU TS v4.04 (Climatic Research Unit Time-Series version 4.04) gridded data, employs multiple statistical indicators and detection metrics to assess the accuracy of the ERA5 temperature and precipitation dataset at a monthly scale over the past 70 years. Additionally, it utilizes Empirical Orthogonal Functions (EOF) to explore its spatiotemporal distribution characteristics. The results indicate that: (1) ERA5 demonstrates good consistency in most regions globally; however, the influence of uneven station density distribution results in weaker correlation in areas with sparse station density. (2) The accuracy of ERA5 data exhibits certain differences between the two periods (1950–1979, 1979–2019); with the overall performance of ERA5 temperature data near the Earth’s surface being better than that of precipitation data. (3) ERA5 precipitation data in the mid and low latitudes of the Southern and Northern Hemispheres exhibit characteristics of positive–negative distribution, while temperature data show an opposite distribution in the Northern and Southern Hemispheres (with a predominant pattern of warmer temperatures in the north and colder temperatures in the south). Additionally, the typical patterns for both variables occur in January and July each year. The above study will provide reference and insights for future climate change prediction and adaptation efforts.

Objective: Osteoporosis is an inflammatory disease that causes a large disease burden worldwide. Dietary inflammation index (DII), a comprehensive assessment index that reflects the pro-inflammatory/anti-inflammatory level of diet was related to multiple inflammatory diseases. This study aimed to explore the association between DII and all-cause mortality in patients with osteoporosis or osteopenia. Methods: In this retrospective cohort study, data of patients aged ≥ 45 years diagnosed as osteopenia or osteoporosis and had complete dietary intake information were extracted from the National Health and Nutrition Examination Survey (NHANES 2007–2010, 2013–2014, 2017–2018). Dietary intake information was obtained from 24-h dietary recall interviews and was used to calculate the DII score. Weighted univariate and multivariate Cox proportional hazard models were utilized to explore the association between DII and all-cause mortality in patients with osteoporosis or osteopenia, with hazard ratios (HRs) and 95 % confidence intervals (CIs). Subgroup analyses based on different age, gender and complications were further assessed this association. Results: A total of 5,381 patients were included. Until December 31, 2019, 1,286 all-cause deaths occurred. After adjusting all covariates, high DII was associated with the high odds of all-cause mortality among patients with osteoporosis or osteopenia (HR=1.28, 95 %CI: 1.10–1.48), especially in the male (HR=1.38, 95 %CI: 1.06–1.78), aged

Abstract Accurate preoperative differentiation of the chronic rhinosinusitis (CRS) endotype between eosinophilic CRS (eCRS) and non-eosinophilic CRS (non-eCRS) is an important topic in predicting postoperative outcomes and administering personalized treatment. To this end, we have constructed a sinus CT dataset, which comprises CT scan data and pathological biopsy results from 192 patients of chronic rhinosinusitis with nasal polyps (CRSwNP), treated at the Second Affiliated Hospital of Shantou University Medical College between 2020 and 2022. To differentiate CRSwNP endotype on preoperative CT and improve efficiency at the same time, we developed a multi-view fusion model that contains a mini-architecture with each network of 10 layers by modifying the deep residual neural network. The proposed model is trained on a training set and evaluated on a test set. The multi-view deep learning fusion model achieved the area under the receiver-operating characteristics curve (AUC) of 0.991, accuracy of 0.965 and F1-Score of 0.970 in test set. We compared the performance of the mini-architecture with other lightweight networks on the same Sinus CT dataset. The experimental results demonstrate that the developed ResMini architecture contribute to competitive CRSwNP endotype identification modeling in terms of accuracy and parameter number.

Background and objective: After vestibular schwannoma (VS) surgery, some patients exhibit different degrees of peripheral facial paralysis, which can seriously affect their quality of life. The recovery of facial nerve function after surgery typically takes a considerable amount of time; therefore, the recovery of facial nerve function depends mainly on the rehabilitation treatment and nursing after discharge. In the past, we implemented conventional paralysis rehabilitation nursing program for patients with facial paralysis due to VS surgery. However, several patients with facial paralysis have bad compliance and do not achieve ideal facial nerve function recovery. Therefore, this study aimed to investigate whether modified facial paralysis rehabilitation nursing improves the effectiveness of rehabilitation of facial paralysis after VS surgery by analysing the clinical data of patients. Methods: We screened the patients with facial paralysis after VS surgery from December 2019 to May 2023. The patients were divided into the conventional and modified groups based on the different nursing programs (conventional vs. modified facial paralysis rehabilitation nursing program) to compare the differences in facial nerve function, quality of life of patients, and compliance of rehabilitation between the two groups. Results: We analysed 128 patients with facial paralysis after VS surgery who met the inclusion and exclusion criteria; 65 and 63 patients in the conventional and modified group, respectively. The number of patients in the modified group with House–Brackmann grade changes >0 in facial nerve function was significantly higher than that in the conventional group 3 months after surgery (82.5 % vs 63.1 %, p = 0.01). Except for the lacrimal control score, the mean scores of the Chinese version of the FaCE scale were significantly higher in the modified group than those in the conventional group at 1 and 3 months postoperatively. Conclusions: The modified facial paralysis rehabilitation nursing, i.e., integrated use of facial expressive muscle exercises and facial massage with video-assisted education, substantially improved the facial nerve function, quality of life, and compliance of rehabilitation nursing of patients with facial paralysis after VS surgery.

Random-pattern skin flaps are important method for skin reconstruction after defect; however, the distal end of flaps is not easily viable due to inadequate nutrient supply. Erastin is a well-established ferroptosis inducer, but our study found that low-dose of erastin (2 μM) may reduce nutrient deficiency induced cell death in human umbilical vein endothelial cells (HUVECs). RNA-seq analysis suggested that its role was related to autophagy regulation. Follow-up studies have shown that the use of autophagy inhibitors or the knockdown of TFEB in HUVECs can both reduce the anti-apoptotic effect of erastin in HUVECs. Mechanism study demonstrated that erastin can suppress mTORC1 and promote TFEB activity in HUVECs, suggesting that the effect of erastin on the survival of HUVECs under nutrient deprivation conditions is regulated by mTORC1/TFEB. Subsequently, we evaluated the effect of erastin on the survival of random-pattern skin flaps in mice in vivo. On the postoperative day 7, we observed a significant increase in flap survival area, blood perfusion, and microvascular density after erastin treatment; also, erastin treatment showed enhanced autophagy within the ischemic region. In summary, our study demonstrates that low-dose of erastin may suppress cell death in endothelial cells under nutrient deficiency condition, and its effects may relate to the mTORC1-TFEB medicated autophagy regulation, erastin treatment may be a potential therapy for random-pattern skin flaps.

Endometrial cancer (EC), the second most common malignancy in the female reproductive system, has garnered increasing attention for its genomic heterogeneity, but understanding of its metabolic characteristics is still poor. We explored metabolic dysfunctions in EC through a comprehensive multi-omics analysis (RNA-seq datasets from The Cancer Genome Atlas [TCGA], Cancer Cell Line Encyclopedia [CCLE], and GEO datasets; the Clinical Proteomic Tumor Analysis Consortium [CPTAC] proteomics; CCLE metabolomics) to develop useful molecular targets for precision therapy. Unsupervised consensus clustering was performed to categorize EC patients into three metabolism-pathway-based subgroups (MPSs). These MPS subgroups had distinct clinical prognoses, transcriptomic and genomic alterations, immune microenvironment landscape, and unique patterns of chemotherapy sensitivity. Moreover, the MPS2 subgroup had a better response to immunotherapy. Finally, three machine learning algorithms (LASSO, random forest, and stepwise multivariate Cox regression) were used for developing a prognostic metagene signature based on metabolic molecules. Thus, a 13-hub gene-based classifier was constructed to predict patients’ MPS subtypes, offering a more accessible and practical approach. This metabolism-based classification system can enhance prognostic predictions and guide clinical strategies for immunotherapy and metabolism-targeted therapy in EC.

Hundreds of green tea products are available on the tea market and exhibit different characteristics. In the present study, seven types of green tea were processed, and their nonvolatile profiles were analyzed by liquid chromatography–mass spectrometry. Non-spreading green tea contained higher concentrations of catechins and flavonoid glycosides, but lower concentrations of amino acids, caffeine, and theaflavins. Non-rolling green teas with a straight appearance contained higher concentrations of flavonoid glycosides and theaflavins. In contrast, leaf-rolling green teas contained much lower concentrations of flavonoid glycosides and catechins. These seven green tea qualities all decreased following prolonged storage, concurrent with increasing concentrations of proanthocyanidins, catechins dimers, theaflavins, and organic acids. The leaf-rolling green teas exhibited reduced levels of deterioration during storage in terms of their nonvolatile profile and sensory quality. Findings show that moderate destruction on tea leaves during green tea processing is beneficial to both tea flavor and quality maintenance during storage.

Spinal cord injury (SCI) is a severe central nerve diseases which lacks effective of treatment. Oxidative stress is a major pathological factor for SCI. It may induce mitochondrial damage, which further lead to ferroptosis and apoptosis in neural cells during SCI. Thus, targeting oxidative stress may be the key strategy for SCI treatment. In this study, we carried out screening experiment in the natural product library against oxidative stress in neural cells. It was identified that idebenone (IDE) may potently suppress oxidative stress induced cell death in neural cells. Furthermore, we successfully developed a multifunctional nanovesicles, which we named IDE@PPNs, by encapsulating IDE within proanthocyanidin polyphenol nanovesicles (PPNs). IDE@PPNs exhibited lysosomal escape capability and mitochondrial ROS responsiveness; meanwhile, they may suppress ferroptosis and apoptosis in neural cells. In vivo study demonstrated that IDE@PPNs may promote motor function recovery in rats and suppress ferroptosis and apoptosis in neurons. It may also show high biocompatibility in in vivo study. In summary, we fabricated a novel natural product loaded ROS responsive nanovesicles, IDE@PPNs may have the great potential for SCI therapy.

Abstract Background As treatment strategies differ according to endotype, rhinologists must accurately determine the endotype in patients affected by chronic rhinosinusitis with nasal polyps (CRSwNP) for the appropriate management. In this study, we aim to construct a novel deep learning model using paranasal sinus computed tomography (CT) to predict the endotype in patients with CRSwNP. Methods We included patients diagnosed with CRSwNP between January 1, 2020, and April 31, 2023. The endotype of patients with CRSwNP in this study was classified as eosinophilic or non-eosinophilic. Sinus CT images (29,993 images) were retrospectively collected, including the axial, coronal, and sagittal planes, and randomly divided into training, validation, and testing sets. A residual network-18 was used to construct the deep learning model based on these images. Loss functions, accuracy functions, confusion matrices, and receiver operating characteristic curves were used to assess the predictive performance of the model. Gradient-weighted class activation mapping was performed to visualize and interpret the operating principles of the model. Results Among 251 included patients, 86 and 165 had eosinophilic or non-eosinophilic CRSwNP, respectively. The median (interquartile range) patient age was 49 years (37–58 years), and 153 (61.0%) were male. The deep learning model showed good discriminative performance in the training and validation sets, with areas under the curves of 0.993 and 0.966, respectively. To confirm the model generalizability, the receiver operating characteristic curve in the testing set showed good discriminative performance, with an area under the curve of 0.963. The Kappa scores of the confusion matrices in the training, validation, and testing sets were 0.985, 0.928, and 0.922, respectively. Finally, the constructed deep learning model was used to predict the endotype of all patients, resulting in an area under the curve of 0.962. Conclusions The deep learning model developed in this study may provide a novel noninvasive method for rhinologists to evaluate endotypes in patients with CRSwNP and help develop precise treatment strategies.

The clinical utilization of doxorubicin (Dox) in various malignancies is restrained by its major adverse effect: irreversible cardiomyopathy. Extensive studies have been done to explore the prevention of Dox cardiomyopathy. Currently, ferroptosis has been shown to participate in the incidence and development of Dox cardiomyopathy. Sorting Nexin 3 (SNX3), the retromer-associated cargo binding protein with important physiological functions, was identified as a potent therapeutic target for cardiac hypertrophy in our previous study. However, few study has shown whether SNX3 plays a critical role in Dox-induced cardiomyopathy. In this study, a decreased level of SNX3 in Dox-induced cardiomyopathy was observed. Cardiac-specific Snx3 knockout (Snx3-cKO) significantly alleviated cardiomyopathy by downregulating Dox-induced ferroptosis significantly. SNX3 was further demonstrated to exacerbate Dox-induced cardiomyopathy via induction of ferroptosis in vivo and in vitro, and cardiac-specific Snx3 transgenic (Snx3-cTg) mice were more susceptible to Dox-induced ferroptosis and cardiomyopathy. Mechanistically, SNX3 facilitated the recycling of transferrin 1 receptor (TFRC) via direct interaction, disrupting iron homeostasis, increasing the accumulation of iron, triggering ferroptosis, and eventually exacerbating Dox-induced cardiomyopathy. Overall, these findings established a direct SNX3–TFRC–ferroptosis positive regulatory axis in Dox-induced cardiomyopathy and suggested that targeting SNX3 provided a new effective therapeutic strategy for Dox-induced cardiomyopathy through TFRC-dependent ferroptosis.

To achieve the in situ capacity expansion of the post-denitrification biological aerated filter (BAF-DN), the integration of BAF with the anammox process (BAF/AX) was proposed. With the objective of maximizing retaining ammonia nitrogen, the operational optimization of BAF was achieved by two distinct strategies. The treatment performance of BAF demonstrated that the removal efficiencies of chemical oxygen demand (COD) and ammonia nitrogen (NH4+-N) was 66.3~67.3% and 4~12%, respectively, under conditions of low aeration intensity (0.4 m3·m−2·h−1) or a shortened empty bed residence time (EBRT) of 30 min. Residual NH4+-N in the BAF effluent served as the ammonia substrate for the subsequent anammox process, which was successfully launched by using ceramic particles and sponges as carriers. Notably, the sponge carrier facilitated a shorter start-up period of 41 to 44 days. Furthermore, the sponge-based anammox reactor exhibited a superior NH4+-N removal capacity (≥85.7%), under operations of a shorter EBRT of 40 min, low influent NH4+-N concentrations (≤30 mg/L), and COD levels of ≤67 mg/L. In addition, a comprehensive evaluation of the BAF/AX process was conducted, which considered performance, cost-effectiveness, and engineering feasibility. The performance results illustrated that the effluent quality met the standard well (with a COD level of ≤ 50 mg/L, and a TN of ≤3.1~10.5 mg/L). Following a comparison against the low aeration intensity operation, it was recommended to operate BAF at a low EBRT within the BAF/AX process. Consequently, the treated volume was double the volume of the standalone BAF-DN, synchronously achieving low costs (0.413 yuan/m3).

Background and aims: Momordica charantia L. (M. charantia) has been traditionally utilized as a medicinal intervention for managing type 2 diabetes mellitus (T2DM). The current study was designed to offer a GRADE-assessed systematic review and meta-analysis of randomized controlled trials (RCTs) examining the impact of M. Charantia intake on glycemic indexes and the lipid profile of patients with T2DM. Methods: A comprehensive search was conducted across several databases, including PubMed, EMBASE, Web of Science, and Cochrane Library, from the inception of each database until April 22, 2023. The Hartung-Knapp adjustment was applied to ensure conservative summary estimates with broad confidence intervals. Results: A total of eight trials involving 423 patients with T2DM were included in this study. Compared to the control group, the intake of M. charantia supplementation resulted in significant reductions in fasting blood glucose (FBG) (WMD: −0.85 mmol/L; 95%CI: −1.44, −0.26; p = 0.005; I2 = 73.4 %), postprandial glucose (PPG) (WMD: −2.28 mmol/L; 95%CI: −3.35, −1.21; p = 0.000; I2 = 66.9 %), glycosylated hemoglobin A1c (HbA1c) (WMD: −0.38 %; 95%CI: −0.53, −0.23; p = 0.000; I2 = 37.6 %), and total cholesterol (TC) (WMD: −0.38 mmol/L; 95%CI: −0.70, −0.07; p = 0.017; I2 = 63.6 %). These results remained statistically significant even after applying the Hartung-Knapp adjustment. However, no significant differences were observed in terms of triglyceride (TG), high-density lipoprotein (HDL), and low-density lipoprotein (LDL). Conclusions: The findings of this study suggest that M. charantia could serve as a potential alternative for individuals with T2DM, particularly those with elevated total cholesterol levels. However, further high-quality studies are necessary to validate these results.

Osteoarthritis (OA) is a common condition worldwide and one of the leading causes of disability. At present, there is no clear pathological mechanism or treatment to slow disease progression. ISO (Isoorientin) is a dietary flavonoid that has anti-inflammatory properties, it can also be present in edible plants and beverages. However, its effects on OA chondrocytes are not fully articulated. This study aims to investigate how ISO delays OA progression and its specific mechanism. The salvaging effects of ISO on extracellular matrix degradation and its protective effects against pyroptosis were studied. It was discovered that these effects might be mediated through the Nrf2/HO-1 and NQO1/NF-κB pathways. Nrf2-siRNA was then used for validation. Subsequently, the effects and mechanisms of ISO were evaluated in a mouse model of OA induced by surgery, and a certain degree of improvement in OA conditions due to ISO was observed.In conclusion, ISO may be a promising candidate drug for alleviating OA.

Sorafenib is an important treatment strategy for advanced hepatocellular carcinoma (HCC). Unfortunately, drug resistance has become a major obstacle in sorafenib application. In this study, whole transcriptome sequencing (WTS) was conducted to compare the paired differences between non-coding RNAs (ncRNAs), including long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), microRNAs (miRNAs), and mRNAs, in sorafenib-resistant and parental cells. The overlap of differentially expressed ncRNAs (DENs) between the SMMC7721/S and Huh7/S cells and their parental cells was determined. 2 upregulated and 3 downregulated lncRNAs, 2 upregulated and 1 downregulated circRNAs, as well as 10 upregulated and 2 downregulated miRNAs, in both SMMC7721/S and Huh7/S cells, attracted more attention. The target genes of these DENs were then identified as the overlaps between the differentially expressed mRNAs achieved using the WTS analysis and the predicted genes of DENs obtained using the “co-localization” or “co-expression,” miRanda, and RNAhybrid analysis. Consequently, the potential regulatory network between overlapping DENs and their target genes in both SMMC7721/S and Huh7/S cells was explored. The “lncRNA-miRNA-mRNA” and “circRNA-miRNA-mRNA” networks were constructed based on the competitive endogenous RNA (ceRNA) theory using the Cytoscape software. In particular, lncRNA MED17-203-miRNA (miR-193a-5p, miR-197-3p, miR-27a-5p, miR-320b, miR-767-3p, miR-767-5p, miR-92a-3p, let-7c-5p)-mRNA,” “circ_0002874-miR-27a-5p-mRNA” and “circ_0078607-miR-320b-mRNA” networks were first introduced in sorafenib-resistant HCC. Furthermore, these networks were most probably connected to the process of metabolic reprogramming, where the activation of the PPAR, HIF-1, Hippo, and TGF-β signaling pathways is governed. Alternatively, the network “circ_0002874-miR-27a-5p-mRNA” was also involved in the regulation of the activation of TGF-β signaling pathways, thus advancing Epithelial-mesenchymal transition (EMT). These findings provide a theoretical basis for exploring the mechanisms underlying sorafenib resistance mediated by metabolic reprogramming and EMT in HCC.

Corneal neovascularization (CoNV)is a major cause of blindness in many ocular diseases. Substantial evidence indicates that vascular endothelial growth factor (VEGF) plays an important role in the pathogenesis of corneal neovascularization. Previous evidence showed that artemisinin may inhibit angiogenesis through down regulation of the VEGF receptors. We designed and synthesized artemisinin derivatives, and validated their inhibitory effect on neovascularization in cell and animal models, and explored the mechanisms by which they exert an inhibitory effect on CoNV. Among these derivatives, P31 demonstrated significant anti-angiogenic effects in vivo and in vitro. Besides, P31 inhibited VEGF-induced HUVECs angiogenesis and neovascularization in rabbit model via AKT and ERK pathways. Moreover, P31 alleviated angiogenic and inflammatory responses in suture rabbit cornea. In conclusion, as a novel artemisinin derivative, P31 attenuates corneal neovascularization and has a promising application in ocular diseases.

Abstract The process of dike-break flood propagation in typical urban street is highly complex. The presence of buildings and trees groups in urban street profoundly alters the flood dynamics, impacting the drainage capacity of the area. In this study, a generalized sink model representing a typical urban street was established, including trees groups, buildings, sidewalks, and stormwater drainage systems. The study measured the fluctuation of water levels within the street block and the pressure variation in the pressurized stormwater drainage network during the dike-break flood propagation. Furthermore, it conducted a comparative analysis to assess the influence of different arrangements of trees groups on the maximum water depth in buildings and the discharge capacity of the pressurized stormwater drainage network. Dike-break floods give rise to large-scale water leaps and the formation of thin layer water sheets near the buildings under the influence of buildings, water tank sidewalls, and tree groups. The water leap zones exhibit lateral migration and superposition on the sidewalks during the flood propagation, gradually dissipating and disappearing in the longitudinal direction of the street. In the presence of tree groups, the water levels significantly decrease in buildings and downstream street, while the discharge capacity of the pressurized stormwater drainage network shows a slight improvement as the road’s flood-carrying capacity increases. The pressure in the main pipes fluctuates due to the switching of the grate inlet drainage mode and the hydraulic transition process in the branch pipes. The research findings not only provide valuable validation data for numerical simulations but also offer theoretical guidance for urban flood management and landscape design.

Abstract Background Evident adolescent idiopathic scoliosis (AIS) incurs high treatment costs, low quality of life, and many complications. Early screening of AIS is essential to avoid progressing to an evident stage. However, there is no valid serum biomarker for AIS for early screening. Methods Antibody-based array is a large-scale study of proteins, which is expected to reveal a serum protein signature as biomarker for AIS. There are two segments of the research, including biomarkers screening and validation. In the biomarkers screening group, a total of 16 volunteers participated in this study, and we carried out differentially expressed proteins screening via protein array assay between No-AIS group and the AIS group, through which GeneSet enrichment analysis was performed. In the validation group with a total of 62 volunteers, the differentially expressed proteins from screening group were verified by Enzyme-Linked immunosorbent assay (ELISA), and then multiple regression analysis. Results In our study, there were twenty-nine differentially expressed proteins in AIS, through Protein array assay and GeneSet enrichment analysis in the biomarkers screening group. Then the expression of FAP, CD23 and B2M decreased as the degree of AIS increased via ELISA in validation group (FAP, p

Background: The purpose of this study is to assess the effects of high serum estradiol (E2) levels on reproductive outcomes as well as to compare pregnancy outcomes of duration of vaginal E2 administration after the day of progesterone (P4) initiation in frozen-thawed embryo transfer (FET) hormonal replacement cycles. Methods: We performed a retrospective cohort study on 627 patients ≤40 years old that underwent a FET cycle. The patients were grouped based on the serum E2 level on the P4 initiation day as follows: E2 ≤600 pg/mL (n = 471); E2 ≥900 pg/mL (n = 151); the group of E2 600–900 pg/mL (n = 5) was not included in the analysis due to too small sample size. A total of 151 patients with E2 ≥900 pg/mL were grouped based on the duration of vaginal E2 administration after the day of P4 initiation: withdrawal before transfer (n = 53); constant administration (n = 98). Results: There was no significant difference in implantation rate, clinical pregnancy rate, spontaneous abortion rate, premature birth rate, live birth rate and multiple pregnancy rate between the two E2 level groups. The logistic regression analysis demonstrated that age was the only variable that significantly affected clinical pregnancy rate and live birth rate. There were no fetal malformations in either group. Baseline characteristics of patients with different duration of vaginal E2 administration were similar. The pregnancy outcomes showed no significant difference between the withdrawal before transfer group and the constant administration group. Conclusions: In FET cycles, high E2 level on the embryo transfer day did not reduce the clinical pregnancy and live birth rates. In addition, vaginal E2 could be stopped on the embryo transfer day since we found no benefit in continuing E2 until the pregnancy testing day.

The pressure characteristics of long-distance water pipelines during hydraulic transient processes are crucial for ensuring the safe, stable, and long-term operation of water transfer projects. This paper establishes a one-dimensional mathematical model based on sections of the Yinjiangjihuai long-distance water diversion project in China. The water supply requirements of the pipelines are categorized into two replenishment modes as follows: gravity supply and pump-pressurized water supply. The opening and closing strategies of the water pipelines under different flow conditions are simulated and analyzed to explore the hydraulic transient processes under various water supply modes. The transient variations of key hydraulic parameters during valve closure are clarified. Simulation results indicate that the water pipeline design is reasonable, meeting the water supply demands at relatively low Manning values and that it has the capability for long-term supply. Due to the excessive head provided by the pumps, pump-pressurized water supply and gravity supply modes cannot operate simultaneously. Under gravity supply mode, the minimum pressure in the downstream pipeline is relatively higher overall, while the maximum pressure in the upstream pipeline is relatively lower overall. In the pump-pressurized water supply mode, the safety and stability of the water supply can be ensured by adjusting the closing time of individual pumps and the interval time between adjacent pumps. The research findings provide technical guidance and scientific basis for the construction of national water networks and water transfer projects.

Abstract Somatic cell nuclear transfer (SCNT) can be used to reprogram differentiated somatic cells to a totipotent state but has poor efficiency in supporting full-term development. H3K9me3 is considered to be an epigenetic barrier to zygotic genomic activation in 2-cell SCNT embryos. However, the mechanism underlying the failure of H3K9me3 reprogramming during SCNT embryo development remains elusive. Here, we perform genome-wide profiling of H3K9me3 in cumulus cell-derived SCNT embryos. We find redundant H3K9me3 marks are closely related to defective minor zygotic genome activation. Moreover, SCNT blastocysts show severely indistinct lineage-specific H3K9me3 deposition. We identify MAX and MCRS1 as potential H3K9me3-related transcription factors and are essential for early embryogenesis. Overexpression of Max and Mcrs1 significantly benefits SCNT embryo development. Notably, MCRS1 partially rescues lineage-specific H3K9me3 allocation, and further improves the efficiency of full-term development. Importantly, our data confirm the conservation of deficient H3K9me3 differentiation in Sertoli cell-derived SCNT embryos, which may be regulated by alternative mechanisms.

Abstract Background Radiomic diagnosis models generally consider only a single dimension of information, leading to limitations in their diagnostic accuracy and reliability. The integration of multiple dimensions of information into the deep learning model have the potential to improve its diagnostic capabilities. The purpose of study was to evaluate the performance of deep learning model in distinguishing tuberculosis (TB) nodules and lung cancer (LC) based on deep learning features, radiomic features, and clinical information. Methods Positron emission tomography (PET) and computed tomography (CT) image data from 97 patients with LC and 77 patients with TB nodules were collected. One hundred radiomic features were extracted from both PET and CT imaging using the pyradiomics platform, and 2048 deep learning features were obtained through a residual neural network approach. Four models included traditional machine learning model with radiomic features as input (traditional radiomics), a deep learning model with separate input of image features (deep convolutional neural networks [DCNN]), a deep learning model with two inputs of radiomic features and deep learning features (radiomics‐DCNN) and a deep learning model with inputs of radiomic features and deep learning features and clinical information (integrated model). The models were evaluated using area under the curve (AUC), sensitivity, accuracy, specificity, and F1‐score metrics. Results The results of the classification of TB nodules and LC showed that the integrated model achieved an AUC of 0.84 (0.82–0.88), sensitivity of 0.85 (0.80–0.88), and specificity of 0.84 (0.83–0.87), performing better than the other models. Conclusion The integrated model was found to be the best classification model in the diagnosis of TB nodules and solid LC.

The exchanges between cities and counties in the Northern Slope Economic Belt of Tianshan Mountains (NSEBTM) are increasingly frequent and the economic linkages are increasingly close, but the spatial distribution of economic development and linkages among the cities and counties within NSEBTM is uneven. Therefore, it is of great significance to study the evolution of spatial-temporal pattern of the economic linkage network of cities and counties on NSEBTM to promote the coordinated and integrated development of the regional economy on NSEBTM. In this study, we used the modified gravity model and social network analysis method to analyze the spatio-temporal evolution characteristics of the economic linkage network structure of cities and counties on NSEBTM in 2000, 2010, and 2020. The results showed that the comprehensive development quality level of cities and counties on NSEBTM increased from 2000 to 2020, its growth rate also increased, and its gap between cities and counties continued expanding. Both the spatial distribution patterns of the comprehensive development quality level of cities and counties on NSEBTM in 2000 and 2010 were presented as “high in the middle and low at both ends”, while the spatial distribution pattern of 2020 was exhibited as “high value and low value staggered”. The total amount of external economic linkages of cities and counties on NSEBTM showed an obvious upward trend, and its gap between cities and counties continued expanding, also showing a pattern of “a strong middle section and weak ends”. The direction of economic linkages of NSEBTM existed obvious central orientation and geographical proximity. The density of economic linkage network of NSEBTM increased from 2000 to 2020, and the structure of economic linkage network changed from single-core structure centered with Urumqi City to multicore structure centered with Urumqi City, Karamay City, Shihezi City, and Changji City, shifting from unbalanced development to balanced development. In the future, we should accelerate the construction of urban agglomeration on NSEBTM, cultivate a modern Urumqi metropolitan area, improve the comprehensive development quality of the cities and counties at the eastern and western ends, strengthen the intensity of economic linkages between cities and counties, optimize the economic linkage network, and promote the coordinated and integrated development of regional economy.

BackgroundMaternal smoking during pregnancy (MSDP) is a known risk factor for offspring developing chronic obstructive pulmonary disease (COPD), but the underlying mechanism remains unclear. ObjectiveThis study aimed to explore whether the increased COPD risk associated with MSDP could be attributed to tobacco dependence (TD). MethodsThis case-control study used data from the nationwide cross-sectional China Pulmonary Health study, with controls matched for age, sex, and smoking status. TD was defined as smoking within 30 minutes of waking, and the severity of TD was assessed using the Fagerstrom Test for Nicotine Dependence. COPD was diagnosed when the ratio of forced expiratory volume in 1 second to forced vital capacity was

Chronic rhinosinusitis (CRS) is a global disease characterized by poor treatment outcomes and high recurrence rates, significantly affecting patients’ quality of life. Due to its complex pathophysiology and diverse clinical presentations, CRS is categorized into various subtypes to facilitate more precise diagnosis, treatment, and prognosis prediction. Among these, CRS with nasal polyps (CRSwNP) is further divided into eosinophilic CRSwNP (eCRSwNP) and noneosinophilic CRSwNP (non-eCRSwNP). However, there is a lack of precise predictive diagnostic and treatment methods, making research into accurate diagnostic techniques for CRSwNP endotypes crucial for achieving precision medicine in CRSwNP. This paper proposes a method using multiangle sinus computed tomography (CT) images combined with artificial intelligence (AI) to predict CRSwNP endotypes, distinguishing between patients with eCRSwNP and non-eCRSwNP. The considered dataset comprises 22,265 CT images from 192 CRSwNP patients, including 13,203 images from non-eCRSwNP patients and 9,062 images from eCRSwNP patients. Test results from the network model demonstrate that multiangle images provide more useful information for the network, achieving an accuracy of 98.43%, precision of 98.1%, recall of 98.1%, specificity of 98.7%, and an AUC value of 0.984. Compared to the limited learning capacity of single-channel neural networks, our proposed multichannel feature adaptive fusion model captures multiscale spatial features, enhancing the model’s focus on crucial sinus information within the CT images to maximize detection accuracy. This deep learning-based diagnostic model for CRSwNP endotypes offers excellent classification performance, providing a noninvasive method for accurately predicting CRSwNP endotypes before treatment and paving the way for precision medicine in the new era of CRSwNP.

Background. Altered maternal serum lipid metabolism is associated with hypertensive disorders in pregnancy (HDP). However, its range in pregnancy and characteristic among different subgroups of HDPs are unclear. Methods. Pregnant women with HDP who underwent antenatal care and delivered in Obstetrics and Gynecology Hospital of Fudan University during January 2018 to August 2022 were enrolled. The levels of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDLC), low-density lipoprotein cholesterol (LDLC), apolipoprotein (Apo)-A, B, and E, free fatty acids (FFA), and small and dense low-density lipoprotein cholesterol (sdLDL) were measured during 4–16 weeks and 28–42 weeks of pregnancy. Results. A total of 2648 pregnant women were diagnosed with HDP, 1,880 of whom were enrolled for final analysis, including 983 (52.3%) preeclampsia (PE), 676 (36.0%) gestational hypertension (GH), and 221 (11.7%) chronic hypertension (CH). For all HDPs, serum TC, TG, LDLC, HDLC, Apo-A, Apo-B, Apo-E, and sdLDL increased significantly during pregnancy, while FFA decreased significantly. Notably, the levels of TC, LDLC, Apo-B, and sdLDL in PE group were equal to or lower than those in CH group at 4–16 weeks of pregnancy, but increased greatly during pregnancy (P

Against the backdrop of global climate warming, the issue of flash flood disasters in small watersheds triggered by heavy rainfall is gradually becoming more prominent. Selecting an appropriate hydrological model is crucial for flash flood disaster defense. This article focuses on the Daxi Water Basin in Lianping County, Guangdong Province, as the research area. Firstly, organize the data and subject it to standardization processing. Subsequently, establish the topological relationships within the basin, construct a hydrological model for simulating flood processes in Chinese mountainous regions, and obtain a set of model parameters applicable to the specific basin. The results indicated that: ① the relative errors of flood runoff depth were all less than 7%, with an average of 4.5%; ② the relative errors of peak flow for all events were less than 6%, with an average of 4.2%; ③ peak time errors were all within ±2 h, either earlier or later than the actual peak by 1 h; ④ the Nash-Sutcliffe efficiency coefficient for floods were all greater than 0.8, with an average of 0.86. The research results above will serve as a reference and guidance for flood defense management in the Daxi Water Basin.

IntroductionWe aim to explore the microstructural and metabolic changes in visual pathways in patients with thyroid eye disease (TED) using 3T multi-parametric MRI.MethodsThirty-four TED patients (inactive group = 20; active group = 14; acute group = 18; chronic group = 16) and 12 healthy controls (HC) were recruited from November 2020 to July 2021. Proton magnetic resonance spectroscopy (1H-MRS), glutamate chemical exchange saturation transfer (GluCEST) and diffusion kurtosis imaging (DKI) were performed on 3.0T MR scanner. Data analysis and group comparisons were performed after MR data processing.ResultsAs compare to HC group, the levels of total choline (tCh) in optic radiation (OR) in active group ([1.404 ± 0.560] vs. [1.022 ± 0.260]; p < 0.05), together with tCh ([1.415 ± 0.507] vs. [1.022 ± 0.260]; p < 0.05) in OR in acute group were significantly increased. Glutamine (Gln) levels were higher in OR in the chronic group than those in HCs and were positively correlated with the levels of thyroglobulin antibody (TgAb), thyroid peroxidase antibody (TPOAb), free triiodothyronine (FT3) and FT4 in chronic group. Glutamate (Glu) levels by 1H-MRS did not show significant differences between any two groups. Interestingly, MTRasym (3.0 ppm) was higher in OL in inactive group, active group, acute group and chronic group than those in HCs, and was positively correlated with Glu levels in OL in 1H-MRS. Fractional anisotropy (FA) values from DKI in OR in acute group were significantly lower than those in HCs.DiscussionOur initial study demonstrate that GluCEST performs better than 1H-MRS to monitor Glu alterations in visual pathway in TED patients. Changes of brain glutamine levels in TED patients are closely related to their associated hormones alterations, indicating that disease injury status could be reflected through non-invasive metabolites detection by brain 1H-MRS. FA is the most sensitive DKI index to reveal the visual pathway impairment in TED patients. Altogether, our study revealed that 3T multiparametric MR techniques are useful to demonstrate metabolic and microstructural alterations in visual pathways in TED patients. We found that damage to visual pathways occurs in mild TED cases, which not only offers a new approach to the diagnosis of dysthyroid optic neuropathy, but also demonstrates neuropathy in TED is a gradual and continuous spatio-emporal progression.

A direct way to reduce scan time for chemical exchange saturation transfer (CEST)-magnetic resonance imaging (MRI) is to reduce the number of CEST images acquired in experiments. In some scenarios, a sufficient number of CEST images acquired in experiments was needed to estimate parameters for quantitative analysis, and this prolonged the scan time. For that, we aim to develop a general deep-learning framework to reconstruct dense CEST Z-spectra from experimentally acquired images at sparse frequency offsets so as to reduce the number of experimentally acquired CEST images and achieve scan time reduction. The main innovation works are outlined as follows: (1) a general sequence-to-sequence (seq2seq) framework is proposed to reconstruct dense CEST Z-spectra from experimentally acquired images at sparse frequency offsets; (2) we create a training set from wide-ranging simulated Z-spectra instead of experimentally acquired CEST data, overcoming the limitation of the time and labor consumption in manual annotation; (3) a new seq2seq network that is capable of utilizing information from both short-range and long-range is developed to improve reconstruction ability. One of our intentions is to establish a simple and efficient framework, i.e., traditional seq2seq can solve the reconstruction task and obtain satisfactory results. In addition, we propose a new seq2seq network that includes the short- and long-range ability to boost dense CEST Z-spectra reconstruction. The experimental results demonstrate that the considered seq2seq models can accurately reconstruct dense CEST images from experimentally acquired images at 11 frequency offsets so as to reduce the scan time by at least 2/3, and our new seq2seq network contributes to competitive advantage.

Chemical exchange saturation transfer (CEST)-magnetic resonance imaging (MRI) often takes prolonged saturation duration (Ts) and relaxation delay (Td) to reach the steady state, and yet the insufficiently long Ts and Td in actual experiments may underestimate the CEST measurement. In this study, we aimed to develop a deep learning-based model for quasi-steady-state (QUASS) prediction from non-steady-state CEST acquired in experiments, therefore overcoming the limitation of the CEST effect which needs prolonged saturation time to reach a steady state. To support network training, a multi-pool Bloch-McConnell equation was designed to derive wide-ranging simulated Z-spectra, so as to solve the problem of time and labor consumption in manual annotation work. Following this, we formulated a hybrid architecture of long short-term memory (LSTM)-Attention to improve the predictive ability. The multilayer perceptron, recurrent neural network, LSTM, gated recurrent unit, BiLSTM, and LSTM-Attention were included in comparative experiments of QUASS CEST prediction, and the best performance was obtained by the proposed LSTM-Attention model. In terms of the linear regression analysis, structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and mean-square error (MSE), the results of LSTM-Attention demonstrate that the coefficient of determination in the linear regression analysis was at least R2 = 0.9748 for six different representative frequency offsets, the mean values of prediction accuracies in terms of SSIM, PSNR and MSE were 0.9991, 49.6714, and 1.68 × 10−4 for all frequency offsets. It was concluded that the LSTM-Attention model enabled high-quality QUASS CEST prediction.

The repair of bone defects remains a huge clinical challenge. M2 macrophage-derived exosomes (M2-Exos) can act as immunomodulators to promote fracture healing; however, how to retain the sustained release of exosomes to the target area remains a challenge. Here, we report a composite hydrogel loaded with M2-Exos aiming to accelerate bone defect healing. It was verified that the F127/HA-NB hydrogel had a dense network structure, tissue adhesiveness, and dual sensitivity to temperature and light. F127/HA-NB loaded with M2-Exos (M2-Exos@F127/HA-NB) exhibited good biocompatibility and achieved sustained release of exosomes for up to two weeks. The study showed that both M0-Exos and M2-Exos@F127/HA-NB significantly promoted osteogenic differentiation of rat bone marrow mesenchymal stem cells. The mechanism study implied that M2-Exos activates the Wnt/β-catenin signaling pathway to promote osteogenic differentiation of BMSCs. Finally, we evaluated the osteogenetic effects of M2-Exos@F127/HA-NB in a rat cranial defect model, and the results showed that M2-Exos@F127/HA-NB had superior bone regeneration-promoting effects. This study provides a new strategy for cell-free treatment of bone defects.

ABSTRACTIn the field of water conservancy engineering, a spillway is a common hydraulic structure that plays a role in flood discharge and dam protection. The selection of the weir surface curve and shape scale of the spillway is significant, and the physical shape of the spillway flip bucket is a critical factor affecting the flood discharge and energy dissipation of the spillway. This paper focuses on a hydraulic model study of the Dashijian Reservoir spillway. The physical shape of the spillway was modified several times during the experiments; the results show that the left and right buckets consist of circular arcs with radii of 13.7 m and 10.01 m, respectively, and the middle bucket consists of a circular arc with radius 11.79 m. The flowing water tongue form is good, the energy dissipation effect is good, and the scouring and deposition form of the downstream riverbed is acceptable. The results of the study can be a valuable guideline for the design of the flip bucket shape of the drainage building.

Profiting from the sustained clinical improvement and prolonged patient survival, immune checkpoint blockade of programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) axis has emerged as a revolutionary cancer therapy approach. However, the anti-PD-1/PD-L1 antibodies only achieve a clinical response rate of approximately 20%. Herein, we identified a novel combination strategy that Chinese medicine ginseng-derived ginsenoside Rh2 (Rh2) markedly improved the anti-cancer efficacy of anti-PD-L1 antibody in mice bearing MC38 tumor. Rh2 combined with anti-PD-L1 antibody (combo treatment) further triggered the infiltration, proliferation and activation of CD8+ T cells in the tumor microenvironment (TME). Depletion of CD8+ T cells by mouse CD8 blocking antibody abolished the anti-cancer effect of combo treatment totally. Mechanistically, combo treatment further increased the expression of CXCL10 through activating TBK1-IRF3 signaling pathway, explaining the increased infiltration of T cells. Employing anti- CXC chemokine receptor 3 (CXCR3) blocking antibody prevented the T cells infiltration and abolished the anti-cancer effect of combo treatment. Meanwhile, combo treatment increased the percentage of M1-like macrophages and raised the ratio of M1/M2 macrophages in TME. By comparing the anti-cancer effect of combo treatment among MC38, CT26 and 4T1 tumors, resident T cells were considered as a prerequisite for the effectiveness of combo treatment. These findings demonstrated that Rh2 potentiated the anti-cancer effect of PD-L1 blockade via promoting the T cells infiltration and activation, which shed a new light on the combination strategy to enhance anti-PD-L1 immunotherapy by using natural product Rh2.