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Abstract Background The Gα family plays a crucial role in the complex reproductive regulatory network of teleosts. However, the characterization and function of Gα family members, especially Gαq, remain poorly understood in teleosts. To analyze the characterization, expression, and function of grass carp (Ctenopharyngodon idella) Gαq, we identified the Gα family members in grass carp genome, and analyzed the expression, distribution, and signal transduction of Gαq/gnaq. We also explored the role of Gαq in the reproductive regulation of grass carp. Results Our results showed that the grass carp genome contains 27 Gα genes with 46 isoforms, which are divided into four subfamilies: Gαs, Gαi/o, Gαq/11, and Gα12/13. The expression level of Cignaq in the testis was the highest and significantly higher than in other tissues, followed by the hypothalamus and brain. The luteinizing hormone receptor (LHR) was mainly localized to the nucleus in grass carp oocytes, with signals also present in follicular cells. In contrast, Gαq signal was mainly found in the cytoplasm of oocytes, with no signal in follicular cells. In the testis, Gαq and LHR were co-localized in the cytoplasm. Furthermore, the grass carp Gαq recombinant protein significantly promoted Cipgr expression. Conclusions These results provided preliminary evidence for understanding the role of Gαq in the reproductive regulation of teleosts.

Bear bile has been a valuable and effective medicinal material in traditional Chinese medicine (TCM) for over 13 centuries. However, the current practice of obtaining it through bear farming is under scrutiny for its adverse impact on bear welfare. Here, we present a new approach for creating artificial bear bile (ABB) as a high-quality and sustainable alternative to natural bear bile. This study addresses the scientific challenges of creating bear bile alternatives through interdisciplinary collaborations across various fields, including resources, chemistry, biology, medicine, pharmacology, and TCM. A comprehensive efficacy assessment system that bridges the gap between TCM and modern medical terminology has been established, allowing for the systematic screening of therapeutic constituents. Through the utilization of chemical synthesis and enzyme engineering technologies, our research has achieved the environmentally friendly, large-scale production of bear bile therapeutic compounds, as well as the optimization and recomposition of ABB formulations. The resulting ABB not only closely resembles natural bear bile in its composition but also offers advantages such as consistent product quality, availability of raw materials, and independence from threatened or wild resources. Comprehensive preclinical efficacy evaluations have demonstrated the equivalence of the therapeutic effects from ABB and those from commercially available drained bear bile (DBB). Furthermore, preclinical toxicological assessment and phase I clinical trials show that the safety of ABB is on par with that of the currently used DBB. This innovative strategy can serve as a new research paradigm for developing alternatives for other endangered TCMs, thereby strengthening the integrity and sustainability of TCM.

Abstract Background Vitamin D was shown to directly exert a protective effect on diabetic kidney disease (DKD) in our previous study. However, whether it has an effect on perirenal adipose tissue (PRAT) or the intestinal flora and its metabolites (trimethylamine N-oxide, TMAO) is unclear. Methods DKD mice were received different concentrations of 1,25-(OH)2D3 for 2 weeks. Serum TNF-α levels and TMAO levels were detected. 16S rRNA sequencing was used to analyze gut microbiota. qPCR was used to detect the expression of TLR4, NF-Κb, PGC1α, and UCP-1 in kidney and adipose tissue. Histological changes in kidney and perirenal adipose tissue were observed using HE, PAS, Masson and oil red staining. Immunofluorescence and immunohistochemistry were used to detect the expression of VDR, PGC1α, podocin, and UCP-1 in kidney and adipose tissue. Electron microscopy was used to observe the pathological changes in the kidney. VDR knockout mice were constructed to observe the changes in the gut and adipose tissue, and immunofluorescence and immunohistochemistry were used to detect the expression of UCP-1 and collagen IV in the kidney. Results 1,25-(OH)2D3 could improve the dysbiosis of the intestinal flora of mice with DKD, increase the abundance of beneficial bacteria, decrease the abundance of harmful bacteria, reduce the pathological changes in the kidney, reduce fat infiltration, and downregulate the expression of TLR4 and NF-κB in kidneys. The serum TMAO concentration in mice with DKD was significantly higher than that of the control group, and was significantly positively correlated with the urine ACR. In addition, vitamin D stimulated the expression of the surface markers PGC1α, UCP-1 and VDR in the PRAT in DKD mice, and TMAO downregulated the expression of PRAT and renal VDR. Conclusions The protective effect of 1,25-(OH)2D3 in DKD mice may affect the intestinal flora and its related metabolite TMAO on perirenal fat and kidneys.

Abstract Multi‐enzymatic cascade reaction provides a new avenue for C─C coupling directly from CO2 under mild conditions. In this study, a new pathway with four enzymes including formate dehydrogenase (PaFDH), formaldehyde dehydrogenase (BmFADH), glycolaldehyde synthase (PpGALS), and alcohol dehydrogenase (GoADH) is developed for directly converting CO2 gas molecules to ethylene glycol (EG) in vitro. A rhodium‐based NADH regeneration electrode is constructed to continuously provide the proton and electron of this multi‐enzymatic cascade reaction. The prepared electrode can reach the Faradaic Efficiency (FE) of 82.9% at −0.6 V (vs. Ag/AgCl) and the NADH productivity of 0.737 mM h−1. Shortening the reaction path is crucial for multi‐enzymatic cascade reactions. Here, a hydrogen‐bonded organic framework (HOF) nano‐reactor is successfully developed to immobilize four enzymes in one pot with a striking enzyme loading capacity (990 mg enzyme g−1 material). Through integrating and optimization of NADH electro‐regeneration and enzymatic catalysis in one pot, 0.15 mM EG is achieved with an average conversion rate of 7.15 × 10−7 mmol CO2 min−1 mg−1 enzymes in 6 h. These results shed light on electro‐driven multi‐enzymatic cascade conversion of C─C coupling from CO2 in the nano‐reactor.

Abstract Background Pathway mutations have been calculated to predict the poor prognosis and immunotherapy resistance in head and neck squamous cell carcinoma (HNSCC). To uncover the unique markers predicting prognosis and immune therapy response, the accurate quantification of pathway mutations are required to evaluate epithelial-mesenchymal transition (EMT) and immune escape. Yet, there is a lack of score to accurately quantify pathway mutations. Material and methods Firstly, we proposed Individualized Weighted Hallmark Gene Set Mutation Burden (IWHMB, https://github.com/YuHongHuang-lab/IWHMB ) which integrated pathway structure information and eliminated the interference of global Tumor Mutation Burden to accurately quantify pathway mutations. Subsequently, to further elucidate the association of IWHMB with EMT and immune escape, support vector machine regression model was used to identify IWHMB-related transcriptomic features (IRG), while Adversarially Regularized Graph Autoencoder (ARVGA) was used to further resolve IRG network features. Finally, Random walk with restart algorithm was used to identify biomarkers for predicting ICI response. Results We quantified the HNSCC pathway mutation signatures and identified pathway mutation subtypes using IWHMB. The IWHMB-related transcriptomic features (IRG) identified by support vector machine regression were divided into 5 communities by ARVGA, among which the Community 1 enriching malignant mesenchymal components promoted EMT dynamically and regulated immune patterns associated with ICI responses. Bridge Hub Gene (BHG) identified by random walk with restart was key to IWHMB in EMT and immune escape, thus, more predictive for ICI response than other 70 public signatures. Conclusion In summary, the novel pathway mutation scoring-IWHMB suggested that the elevated malignancy mediated by pathway mutations is a major cause of poor prognosis and immunotherapy failure in HNSCC, and is capable of identifying novel biomarkers to predict immunotherapy response.

Abstract Background Advanced glycation end products (AGEs) deposited in the lens are correlated with those in the kidneys, indicating a possible value in evaluating diabetic kidney disease (DKD). This study explored the value of noninvasively measuring lens AGEs to diagnose and evaluate the severity of diabetic nephropathy in patients with type 2 diabetes mellitus (T2DM). Methodology A total of 134 T2DM patients admitted to the Fifth People's Hospital of Shanghai from March 2020 to May 2021 were selected randomly. Patients were divided into low-, medium-and high-risk groups according to the risk assessment criteria for DKD progression and into DKD and non-DKD (non-DKD) groups according to the Guidelines for the Prevention and Treatment of Diabetic Nephropathy in China. The concentrations of noninvasive AGEs in the lens in all the groups were retrospectively analyzed. Results The concentration of noninvasive lens AGEs in the high-risk patients, according to the 2012 guidelines of the Global Organization for Improving the Prognosis of Kidney Diseases, was significantly higher than that in the remaining groups. Regression analysis suggested the value of lens AGEs in diagnosing DKD and evaluating DKD severity. Cox regression analysis indicated that the noninvasive lens AGE concentration was positive correlated with the course of disease. Conclusion The receiver operating characteristic (ROC) curve suggested that using noninvasive lens AGE measurements has clinical value in the diagnosis of DKD (area under the curve 62.4%,95% confidence interval (CI) 52.4%–73.9%, p = 0.014) and in assessing the severity of DKD (area under the curve 83.2%, 95% CI 74.1%–92.3%, P

Abstract Background Malnutrition and subsequent alterations in body composition (BC), particularly sarcopenia, are common but not yet elucidated in patients with inflammatory bowel disease (IBD); we aimed to detail the changes in BC and the characteristics of co‐occurrence of malnutrition and sarcopenia in IBD patients and to investigate its effect on quality of life. Methods This study was a multicentre, prospective, observational study involving four tertiary referral hospitals in China. The following data were collected from consecutive IBD inpatients: demographic information, medical history, recent weight change, handgrip strength (HGS) and BC parameters by bioelectrical impedance analysis (BIA). Nutritional assessments were performed through stepwise screening (Nutritional Risk Screening 2002) and diagnosis (World Health Organization‐related body mass index [BMI], subjective global assessment, European Society for Clinical Nutrition and Metabolism 2015 and Global Leadership Initiative on Malnutrition [GLIM] criteria). The quality of life was assessed by the Inflammatory Bowel Disease Questionnaire. IBD patients were compared with 1:1 sex‐, age‐ and BMI‐matched healthy controls (MHC). Results A total of 238 IBD patients (177 Crohn's disease [CD] and 61 ulcerative colitis [UC]), 68.5% male, with a mean age of 38.5 ± 14.0 years and a mean BMI of 19.8 ± 3.5 kg/m2, were recruited. Compared with MHC (n = 122), IBD patients showed significant deterioration in BC and physical function, characterized by muscle depletion (appendicular skeletal muscle mass index [ASMI], 8.0 ± 1.3 vs. 6.7 ± 1.2 kg/m2, Δ% −15.0% [−22.0%, −10.0%], P

Abstract Background This study aimed to assess whether a combined model incorporating radiomic and depth features extracted from PET/CT can predict disease-free survival (DFS) in patients who failed to achieve pathologic complete response (pCR) after neoadjuvant chemotherapy. Results This study retrospectively included one hundred and five non-pCR patients. After a median follow-up of 71 months, 15 and 7 patients experienced recurrence and death, respectively. The primary tumor volume underwent feature extraction, yielding a total of 3644 radiomic features and 4096 depth features. The modeling procedure employed Cox regression for feature selection and utilized Cox proportional-hazards models to make predictions on DFS. Time-dependent receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were utilized to evaluate and compare the predictive performance of different models. 2 clinical features (RCB, cT), 4 radiomic features, and 7 depth features were significant predictors of DFS and were included to develop models. The integrated model incorporating RCB, cT, and radiomic and depth features extracted from PET/CT images exhibited the highest accuracy for predicting 5-year DFS in the training (AUC 0.943) and the validation cohort (AUC 0.938). Conclusion The integrated model combining radiomic and depth features extracted from PET/CT images can accurately predict 5-year DFS in non-pCR patients. It can help identify patients with a high risk of recurrence and strengthen adjuvant therapy to improve survival.

Abstract Keratin is a recalcitrant protein and can be decomposed in nature. However, the mechanism of keratin degradation is still not well understood. In this study, Bacillus sp. 8A6 can completely degrade the feather in 20 h, which is an efficient keratin degrader reported so far. Comprehensive transcriptome analysis continuously tracks the metabolism of Bacillus sp. 8A6 throughout its growth in feather medium. It reveals for the first time how the strain can acquire nutrients and energy in an oligotrophic feather medium for proliferation in the early stage. Then, the degradation of the outer lipid layer of feather can expose the internal keratin structure for disulfide bonds reduction by sulfite from the newly identified sulfite metabolic pathway, disulfide reductases and iron uptake. The resulting weakened keratin has been further proposedly de-assembled by the S9 protease and hydrolyzed by synergistic effects of the endo, exo and oligo-proteases from S1, S8, M3, M14, M20, M24, M42, M84 and T3 families. Finally, bioaccessible peptides and amino acids are generated and transported for strain growth. The keratinase has been applied for soybean hydrolysis, which generates 2234 peptides and 559.93 mg/L17 amino acids. Therefore, the keratinases, inducing from the poultry waste, have great potential to be further applied for producing bioaccessible peptides and amino acids for feed industry.

The stembase of Flammulina velutipes was pretreated by steam explosion, to explore the effects on antioxidant and anti-inflammatory activities of its water extract. The differences of active components in water extract of F.velutipes stembase before and after steam explosion were analyzed by ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS/MS). The contents of crude polysaccharides, total phenols and total flavonoids were determined by phenol-sulfuric acid method, Folin-Ciocalteu method and aluminum chloride method. The in vitro antioxidant capacity of water extract of F.velutipes stembase before and after steam explosion was determined by DPPH, ABTS and FRAP methods. The potential anti-inflammatory activity and mechanism of F.velutipes stembase water extract on LPS-activated cells were investigated. The results showed that the relative content of active compounds of F.velutipes stembase increased significantly after steam explosion, such as betaine, trans-3-indoleacrylic acid, adenosine and nicotinamide, which were 1.14 times, 1.32 times, 3.39 times and 3.21 times of that in the non-steam explosion group, respectively, and the content of crude polysaccharide increased by 56.03%. SFVE had better antioxidant activity, the DPPH free radical scavenging ability, ABTS+ free radical scavenging ability and Fe3+ reducing ability were 1.12 times, 1.07 times and 1.12 times of those in the non-steam explosion group (FVE), respectively. The anti-inflammatory result showed that the water extract of F.velutipes stembase after steam explosion had significant inhibitory activity on LPS-induced NO production in RAW264.7 cells (P

Cadaverine is the key monomer for the synthesis of nylon 5X. Efficient and alkaline stable lysine decarboxylases are highly desirable for cadaverine production as the reaction pH increasing from 6.3 to 8.5. However, the most studied lysine decarboxylase CadA (E. coli) lost almost all activity at pH 8.0, which is the foremost challenge for the industrial-cadaverine production. In this study, we first found that the Na+-microenvironment significantly improved the alkaline stability of the disulfide engineered lysine decarboxylase ΔLdcEt3 (P233C/L628C) (half-life 362 h), compared to the conventional buffer (half-life 0.66 h) at pH 8.0. Meanwhile, the whole-cell conversion efficiency of the industrial-grade l-lysine with ΔLdcEt3 could reach up to 99% in 2 h in the fermenter. Experimental investigation and molecular dynamics confirmed that Na+-microenvironment could improve active-aggregation state and affect secondary structure of ΔLdcEt3. Therefore, Na+-microenvironment stabilizes ΔLdcEt3 providing a great potential industrial application for high-level cadaverine production.

Metabolic-associated fatty liver disease (MAFLD) is a chronic liver disease characterized by the excessive accumulation of fat in hepatocytes. However, due to the complex pathogenesis of MAFLD, there are no officially approved drugs for treatment. Therefore, there is an urgent need to find safe and effective anti-MAFLD drugs. Recently, the relationship between the gut microbiota and MAFLD has been widely recognized, and treating MAFLD by regulating the gut microbiota may be a new therapeutic strategy. Natural products, especially plant natural products, have attracted much attention in the treatment of MAFLD due to their multiple targets and pathways and few side effects. Moreover, the structure and function of the gut microbiota can be influenced by exposure to plant natural products. However, the effects of plant natural products on MAFLD through targeting of the gut microbiota and the underlying mechanisms are poorly understood. Based on the above information and to address the potential therapeutic role of plant natural products in MAFLD, we systematically summarize the effects and mechanisms of action of plant natural products in the prevention and treatment of MAFLD through targeting of the gut microbiota. This narrative review provides feasible ideas for further exploration of safer and more effective natural drugs for the prevention and treatment of MAFLD.

Liver steatosis is a common metabolic disorder resulting from imbalanced lipid metabolism, which involves various processes such as de novo lipogenesis, fatty acid uptake, fatty acid oxidation, and VLDL secretion. In this study, we discovered that KLF2, a transcription factor, plays a crucial role in regulating lipid metabolism in the liver. Overexpression of KLF2 in the liver of db/db mice, C57BL/6J mice, and Cd36-/- mice fed on a normal diet resulted in increased lipid content in the liver. Additionally, transgenic mice (ALB-Klf2) that overexpressed Klf2 in the liver developed liver steatosis after being fed a normal diet. We found that KLF2 promotes lipogenesis by increasing the expression of SCAP, a chaperone that facilitates the activation of SREBP, the master transcription factor for lipogenic gene expression. Our mechanism studies revealed that KLF2 enhances lipogenesis in the liver by binding to the promoter of SCAP and increasing the expression of genes involved in fatty acid synthesis. Reduction of KLF2 expression led to a decrease in SCAP expression and a reduction in the expression of SREBP1 target genes involved in lipogenesis. Overexpression of KLF2 also increased the activation of SREBP2 and the mRNA levels of its downstream target SOAT1. In C57BL/6J mice fed a high-fat diet, overexpression of Klf2 increased blood VLDL secretion, while reducing its expression decreased blood cholesterol levels. Our study emphasizes the novelty that hepatic KLF2 plays a critical role in regulating lipid metabolism through the KLF2/SCAP/SREBPs pathway, which is essential for hepatic lipogenesis and maintaining blood cholesterol homeostasis.

Grass carp (Ctenopharyngodon idella) and barbel chub (Squaliobarbus curriculus)—both Leuciscinae subfamily species—demonstrate differences in grass carp reovirus (GCRV) infection resistance. We infected barbel chubs with type II GCRV and subjected their liver, spleen, head kidney, and trunk kidney samples to investigate anti-GCRV immune mechanisms via RNA sequencing and quantitative real-time polymerase chain reaction (qRT-PCR). We identified 139, 970, 867, and 2374 differentially expressed genes (DEGs) in the liver, spleen, head kidney, and trunk kidney, respectively. Across all four tissues, gene ontology analysis revealed significant immune response-related DEG enrichment, and the Kyoto Encyclopedia of Genes and Genomes analysis revealed pattern recognition receptor (PRR) and cytokine-related pathway enrichment. We noted autophagy pathway enrichment in the spleen, head kidney, and trunk kidney; apoptosis pathway enrichment in the spleen and trunk kidney; and complement- and coagulation-cascade pathway enrichment in only the spleen. Comparative transcriptome analysis between GCRV-infected barbel chubs and uninfected barbel chubs comprehensively revealed that PRR, cytokine-related, complement- and coagulation-cascade, apoptosis, and autophagy pathways are potential key factors influencing barbel chub resistance to GCRV infection. qRT-PCR validation of 11 immune-related DEGs confirmed our RNA-seq data’s accuracy. These findings provide a theoretical foundation and empirical evidence for the understanding of GCRV infection resistance in barbel chub and hybrid grass carp–barbel chub breeding.

Introduction: Metabolic-associated fatty liver disease (MAFLD) is a common chronic metabolic disease that seriously threatens human health. The pharmacological activity of unsaturated fatty acid-rich vegetable oil interventions in the treatment of MAFLD has been demonstrated. This study evaluated the pharmacological activity of Polygala tenuifolia Willd, which contains high levels of 2-acetyl-1,3-diacyl-sn-glycerols (sn-2-acTAGs).Methods: In this study, a mouse model was established by feeding a high-fat diet (HFD, 31% lard oil diet), and the treatment group was fed a P. tenuifolia seed oil (PWSO) treatment diet (17% lard oil and 14% PWSO diet). The pharmacological activity and mechanism of PWSO were investigated by total cho-lesterol (TC) measurement, triglyceride (TG) measurement and histopathological observation, and the sterol regulatory element-binding protein-1 (SREBP1), SREBP2 and NF-κB signaling pathways were evaluated by immunofluorescence and Western blot analyses.Results: PWSO attenuated the increases in plasma TC and TG levels. Furthermore, PWSO reduced the hepatic levels of TC and TG, ameliorating hepatic lipid accumulation. PWSO treatment effectively improves the level of hepatitic inflammation, such as reducing IL-6 levels and TNF-α level.Discussion: PWSO treatment inactivated SREBP1 and SREBP2, which are involved in lipogenesis, to attenuate hepatic lipid accumulation and mitigate the inflammatory response induced via the NF-κB signaling pathway. This study demonstrated that PWSO can be used as a relatively potent dietary supplement to inhibit the occurrence and development of MAFLD.

Diabetic Kidney Disease (DKD) is one of the significant microvascular consequences of type 2 diabetes mellitus with a complex etiology and protracted course. In the early stages of DKD, the majority of patients experience an insidious onset and few overt clinical symptoms and indicators, but they are prone to develop end-stage renal disease in the later stage, which is life-threatening. The abnormal amino acid metabolism is tightly associated with the development of DKD, which involves several pathological processes such as oxidative stress, inflammatory response, and immune response and is also closely related to autophagy, mitochondrial dysfunction, and iron death. With a focus on taurine, branched-chain amino acids (BCAAs) and glutamine, we explored the biological effects of various amino acid mechanisms linked to DKD, the impact of amino acid metabolism in the early diagnosis of DKD, and the role of amino acid metabolism in treating DKD, to offer fresh objectives and guidelines for later early detection and DKD therapy.

Background and aimsMalnutrition is strongly linked to adverse outcomes in patients with Crohn’s disease (CD). In this study, our objective was to validate the Global Leadership Initiative on Malnutrition (GLIM) criteria and develop a fast and accurate diagnostic approach for identifying malnutrition in CD patients.MethodsThis study assessed 177 CD patients from four general hospitals. The efficacy of the GLIM criteria for the diagnosis of CD malnutrition was compared. By analyzing the independent factors, a nomogram model was derived and internally validated to predict the diagnosis of malnutrition in patients with CD. Model performance was assessed using discrimination and calibration, decision curves, and net benefit analyses.ResultsCompared with the SGA criteria, the GLIM criteria was consistent in sensitivity (88.89%) and specificity (78.43%) [AUC = 0.84; 95% Confidence Interval (CI): 0.77–0.89]. The Harvey-Bradshaw index(HBI) score (OR: 1.58; 95% CI: 1.15–2.18), body mass index (OR: 0.41; 95% CI: 0.27–0.64), and mid-upper arm circumference (OR: 0.68; 95% CI: 0.47–0.9) were independent factors associated with malnutrition. The nomogram was developed based on these indicators showing good discrimination in malnutrition diagnosis (AUC = 0.953; 95% CI: 0.922–0.984), with agreement after calibration curve and decision curve analysis.ConclusionThe GLIM criteria are appropriate for diagnosing malnutrition in CD patients. The HBI score may be used to diagnose malnutrition in patients with CD and become a possible selection for the GLIM etiologic criteria of inflammation. The HBM nomogram could be a simple, rapid, and efficient method for diagnosing malnutrition in CD patients.

Drying treatments are an effective method of preserving the beneficial properties of postharvest mushrooms. The effects of natural-air drying (ND), hot-air drying (HD), vacuum-freeze drying (FD), heat pump drying (HPD) and microwave-vacuum drying (MVD) on the microstructure, flavor- and health-related compounds of F. velutipes root were investigated. The results showed that FD had the least impact on the microstructure of F. velutipes root and its original porous fiber structure appeared complete. It also possessed the highest content of volatile compounds. MVD gave the highest contents of umami amino acids, total phenolics and total flavonoids, and its extract exhibited high antioxidant activity. In addition, different drying treatments had significant effect on the chemical components of F. velutipes root, with FD and MVD may be the potent drying strategies for preservation of flavor and nutraceuticals respectively. Therefore, our results provided essential data support for F. velutipes root processing and functional product development.

Data technology (DT) era centered on the data technology and data service was coming.To handle the major challenges in the data exchange and transactions, a new infrastructure - data sharing service network (DSSN) was proposed, which provided the data interconnection, exchange, transactions, supervision and other services for regulators, data providers, data applications and technical support providers.The design principles of DSSN system were outlined as compliance, security, fairness, openness and connection service.And the architecture of DSSN system was designed according to the principles.A layered architecture was applied to the data sharing service node with the service control layer and service capability layer.The data node was composed of the data sharing dedicated server and data source, and was connected to DSSN through data gateway.

Obesity is strongly associated with the occurrence and development of many types of cancers. Patients with obesity and cancer present with features of a disordered gut microbiota and metabolism, which may inhibit the physiological immune response to tumors and possibly damage immune cells in the tumor microenvironment. In recent years, bariatric surgery has become increasingly common and is recognized as an effective strategy for long-term weight loss; furthermore, bariatric surgery can induce favorable changes in the gut microbiota. Some studies have found that microbial metabolites, such as short-chain fatty acids (SCFAs), inosine bile acids and spermidine, play an important role in anticancer immunity. In this review, we describe the changes in microbial metabolites initiated by bariatric surgery and discuss the effects of these metabolites on anticancer immunity. This review attempts to clarify the relationship between alterations in microbial metabolites due to bariatric surgery and the effectiveness of cancer treatment. Furthermore, this review seeks to provide strategies for the development of microbial metabolites mimicking the benefits of bariatric surgery with the aim of improving therapeutic outcomes in cancer patients who have not received bariatric surgery.

Introduction: In clinical practice, warfarin is often combined with Compound Danshen dripping pill (CDDP) for the treatment of cardiovascular diseases. However, warfarin has a narrow therapeutic index, wide interindividual variability (genetic and non-genetic factors), and is susceptible to drug-drug interactions. Our previous study indicated that CDDP might interact with warfarin in individuals with the epoxide hydrolase gene (EPHX1; single-nucleotide polymorphism: rs2292566) A/A subtype. We sought to clarify the interaction between CDDP and warfarin associated with EPHX1 in a comprehensive and accurate manner.Methods: Here, EPHX1 A and EPHX1 G cell lines were established. Expression of microsomal epoxide hydrolase (mEH), vitamin K epoxide reductase (VKOR), and vitamin K-dependent clotting factors (FII, FVII, FIX, FX) was measured by western blotting upon incubation with CDDP and warfarin. mEH activity was evaluated by measuring the transformation of epoxyeicosatrienoic acids into dihydroxyeicosatrienoic acids. Then, healthy volunteers (HVs) with the EPHX1 A/A genotype were recruited and administered warfarin and CDDP to investigate the pharmacokinetics and pharmacodynamics of warfarin.Results: CDDP combined with warfarin could decrease expression of mEH and VKOR, and increase protein expression of FII, FVII, FIX, and FX, in EPHX1 A cells. CDDP could slightly influence the pharmacokinetics/pharmacodynamics of warfarin in HVs with the EPHX1 A/A genotype.Discussion: Rational combination of CDDP and warfarin was safe with no risk of bleeding, but the therapeutic management is also needed. The clinical study is posted in the China Clinical Trial Registry (ChiCTR190002434).

Summary: Background: Accurate identification of pCR to neoadjuvant chemotherapy (NAC) is essential for determining appropriate surgery strategy and guiding resection extent in breast cancer. However, a non-invasive tool to predict pCR accurately is lacking. Our study aims to develop ensemble learning models using longitudinal multiparametric MRI to predict pCR in breast cancer. Methods: From July 2015 to December 2021, we collected pre-NAC and post-NAC multiparametric MRI sequences per patient. We then extracted 14,676 radiomics and 4096 deep learning features and calculated additional delta-value features. In the primary cohort (n = 409), the inter-class correlation coefficient test, U-test, Boruta and the least absolute shrinkage and selection operator regression were used to select the most significant features for each subtype of breast cancer. Five machine learning classifiers were then developed to predict pCR accurately for each subtype. The ensemble learning strategy was used to integrate the single-modality models. The diagnostic performances of models were evaluated in the three external cohorts (n = 343, 170 and 340, respectively). Findings: A total of 1262 patients with breast cancer from four centers were enrolled in this study, and pCR rates were 10.6% (52/491), 54.3% (323/595) and 37.5% (66/176) in HR+/HER2−, HER2+ and TNBC subtype, respectively. Finally, 20, 15 and 13 features were selected to construct the machine learning models in HR+/HER2−, HER2+ and TNBC subtypes, respectively. The multi-Layer Perception (MLP) yields the best diagnostic performances in all subtypes. For the three subtypes, the stacking model integrating pre-, post- and delta-models yielded the highest AUCs of 0.959, 0.974 and 0.958 in the primary cohort, and AUCs of 0.882–0.908, 0.896–0.929 and 0.837–0.901 in the external validation cohorts, respectively. The stacking model had accuracies of 85.0%–88.9%, sensitivities of 80.0%–86.3%, and specificities of 87.4%–91.5% in the external validation cohorts. Interpretation: Our study established a novel tool to predict the responses of breast cancer to NAC and achieve excellent performance. The models could help to determine post-NAC surgery strategy for breast cancer. Funding: This study is supported by grants from the National Natural Science Foundation of China (82171898, 82103093), the Deng Feng project of high-level hospital construction (DFJHBF202109), the Guangdong Basic and Applied Basic Research Foundation (grant number, 2020A1515010346, 2022A1515012277), the Science and Technology Planning Project of Guangzhou City (202002030236), the Beijing Medical Award Foundation (YXJL-2020-0941-0758), and the Beijing Science and Technology Innovation Medical Development Foundation (KC2022-ZZ-0091-5). Funding sources were not involved in the study design, data collection, analysis and interpretation, writing of the report, or decision to submit the article for publication.

Glutamate plays an important role in excitotoxicity and ferroptosis. Excitotoxicity occurs through over-stimulation of glutamate receptors, specifically NMDAR, while in the non-receptor-mediated pathway, high glutamate concentrations reduce cystine uptake by inhibiting the System Xc-, leading to intracellular glutathione depletion and resulting in ROS accumulation, which contributes to increased lipid peroxidation, mitochondrial damage, and ultimately ferroptosis. Oxidative stress appears to crosstalk between excitotoxicity and ferroptosis, and it is essential to maintain glutamate homeostasis and inhibit oxidative stress responses in vivo. As researchers work to develop natural compounds to further investigate the complex mechanisms and regulatory functions of ferroptosis and excitotoxicity, new avenues will be available for the effective treatment of ischaemic stroke. Therefore, this paper provides a review of the molecular mechanisms and treatment of glutamate-mediated excitotoxicity and ferroptosis.

With the large-scale commercial launch of fifth generation (5G) mobile network, the development of new services and applications catering to the year 2030, along with the deep convergence of information, communication, and data technologies (ICDT), and the lessons and experiences from 5G practice will drive the evolution of the next generation of mobile networks. This article surveys the history and driving forces of the evolution of the mobile network architecture and proposes a logical function architecture for sixth generation (6G) mobile network. The proposed 6G network architecture is termed SOLIDS (related to the following basic features: soft, on-demand fulfillment, lite, native intelligence, digital twin, and native security), which can support self-generation, self-healing, self-evolution, and self-immunity without human involvement and address the primary issues in the legacy 5G network (e.g., high cost, high power consumption, and highly complicated operation and maintenance), significantly well.

Wheat stripe rust is a destructive disease in many cool and temperate regions around the world. Exploiting novel sources of resistance can provide wheat cultivars with robust and durable resistance to stripe rust. The wheat–Thinopyrum intermedium addition line TAI-14 was proven to carry a stripe rust resistance gene (named as YrT14) on the alien Th. intermedium chromosome. In order to transfer the resistance gene to wheat, wheat–Th. intermedium translocation lines were created by irradiating the pollen of the line TAI-14. We totally obtained 153 wheat–Th. intermedium translocation lines, among which the long alien segmental translocation line Zhongke 78 and the intercalary translocation line Zhongke 15 not only showed good integrated agronomic traits but also were identified as highly resistant to stripe rust in both seedling and adult plant stages. The alien chromatin in Zhongke 15 was identified as an insertion into the satellite of chromosome 6B, a type of translocation never reported before in chromosome engineering. By screening Simple Sequence Repeat (SSR) and Expressed Sequence Tag (EST) markers as well as the markers developed from RNA-sequencing (RNA-Seq) data, 14 markers were identified specific for the alien chromosome and a physical map was constructed. Both Zhongke 78 and Zhongke 15 could be used as a novel source of stripe rust resistance for wheat breeding, and the linked marker T14K50 can be used for molecular marker–assisted breeding. Finally, based on the karyotype, reaction to stripe rust, and genome resequencing data of different wheat–Th. intermedium translocation lines, the stripe rust resistance gene YrT14 was located to an 88.1 Mb interval from 636.7 to 724.8 Mb on Th. intermedium chromosome 19 corresponding to 7J or 7Js.

Background: Combination of Polygonum capitatum Buch.-Ham. ex D. Don extract (PCE) and ciprofloxacin (CIP) was commonly prescribed in the treatment of urinary tract infections. Their pharmacokinetic herb-drug interactions (HDIs) were focused in this study to assess potential impact on the safety and effectiveness.Methods: A randomized, three-period, crossover trial was designed to study the pharmacokinetic HDI between PCE and CIP in healthy humans. Their pharmacokinetic- and tissue distribution-based HDIs were also evaluated in rats. Gallic acid (GA) and protocatechuic acid (PCA) were chosen as PK-markers of PCE in humans and rats. Potential drug interaction mechanisms were revealed by assessing the effects of PCE on the activity and expression of multiple transporters, including OAT1/3, OCT2, MDR1, and BCRP.Results: Concurrent use of PCE substantially reduced circulating CIP (approximately 40%–50%) in humans and rats, while CIP hardly changed circulating GA and PCA. PCE significantly increased the tissue distribution of CIP in the prostate and testis of rats, but decreased in liver and lungs. Meanwhile, CIP significantly increased the tissue distribution of GA or PCA in the prostate and testis of rats, but decreased in kidney and heart. In the transporter-mediated in vitro HDI, GA and PCA presented inhibitory effects on OAT1/3 and inductive effects on MDR1 and BCRP.Conclusion: Multiple transporter-mediated HDI contributes to effects of PCE on the reduced systemic exposure and altered tissue distribution of CIP. More attention should be paid on the potential for PCE-perpetrated interactions.

5G is the current focus of the development of the information and communication industry, and is gradually being deployed and commercialized.The 5G network will cover toC to toB, aiming at the interconnection of everything, so the complexity and challenges are unprecedented.In order to meet the needs of multiple scenarios, 5G network technology is complex and flexible in design, and the traditional management and operation methods are difficult and costly.At the same time, industry application requirements are very different and demanding.All of these require integrated solutions such as cloud-network integration and network industry collaboration.In response to the above-mentioned problems and needs, an intelligent and simplified 5G wireless network technology framework was proposed.Through innovative thinking and technology development of wireless networks, 5G and artificial intelligence, cloud computing, big data, edge computing and other new technologies were integrated and innovated to continuously improve 5G capabilities and promote the deep convergence of 5G and DOICT.A detailed introduction to the entire framework, platforms and applications in the above technology system were given.Finally, a technical outlook was proposed for shaping a new 5G ecology that supported green, smart, efficient operation, and the internet of everything.

Abstract Background Leptin Receptor (LEPR) has been suggested to have several roles in cancer metastasis. However, the role of LEPR and its underlying mechanisms in lymphatic metastasis of hepatocarcinoma have not yet been studied. Methods We performed bioinformatics analysis, qRT-PCR, western blotting, immunohistochemistry, immunofluorescence, enzyme-linked immunosorbent, coimmunoprecipitation assays and a series of functional assays to investigate the roles of LEPR in hepatocellular carcinoma. Results We discovered that LEPR was highly expressed in liver cancer tissues, and the expression of LEPR in Hca-F cells was higher than that in Hca-P cells. Furthermore, LEPR promotes the proliferation, migration and invasion and inhibits the apoptosis of hepatocarcinoma lymphatic metastatic cells. Further studies indicated that LEPR interacts with ANXA7. Mechanistically, LEPR regulated ERK1/2 and JAK2/STAT3 expression via ANXA7 regulation. Conclusions These findings unveiled a previously unappreciated role of LEPR in the regulation of lymphatic metastatic hepatocellular carcinoma, assigning ANXA7-LEPR as a promising therapeutic target for liver cancer treatments.

Context Relinqing granules (RLQ) are being used alone or in combination with antibacterial drugs to treat urological disorders. Objective This study investigates the pharmacokinetics of RLQ in humans and the potential for RLQ-perpetrated interactions on transporters. Materials and methods Twelve healthy subjects (six women and six men) participated to compare single- and multiple-dose pharmacokinetics of RLQ. In the single-dose study, all 12 subjects received 8 g of RLQ orally. After a 7-d washout period, the subjects received 8 g of RLQ for seven consecutive days (t.i.d.) and then a single dose. Gallic acid (GA) and protocatechuic acid (PCA) in plasma and urine samples were analysed using LC-MS/MS. The transfected cells were used to study the inhibitory effect of GA (50–5000 μg/L) and PCA (10–1000 μg/L) on transporters OAT1, OAT3, OCT2, OATP1B1, P-gp and BCRP. Results GA and PCA were absorbed into the blood within 1 h after administration and rapidly eliminated with a half-life of less than 2 h. The mean peak concentrations of GA (102 and 176 μg/L) and PCA (4.54 and 7.58 μg/L) were lower in males than females, respectively. The 24 h urine recovery rates of GA and PCA were about 10% and 5%, respectively. The steady-state was reached in 7 d without accumulation. GA was a potent inhibitor of OAT1 (IC50 = 3.73 μM) and OAT3 (IC50 = 29.41 μM), but not OCT2, OATP1B1, P-gp or BCRP. Discussion and conclusions GA and PCA are recommended as PK-markers in RLQ-related pharmacokinetic and drug interaction studies. We should pay more attention to the potential for RLQ-perpetrated interactions on transporters.

To accommodate the rapid change of radio propagation environment for mobile communication scenarios, millimeter-wave beamforming requires instantaneous channel state information (CSI) to update its operational parameters in real time, resulting in heavy system overhead. As the number of antennas increases, the system overhead associated with beam management will increase dramatically. To address this overarching problem, a neural network-aided millimeter-wave beamforming algorithm is proposed in this paper. A new parameter, referred to as “beam adjustment interval”, is proposed to evaluate the beamforming performance. It is defined as the maximum time duration in which the signal-to-interference-plus-noise ratio (SINR) of the user equipment can be maintained above the predefined threshold. Besides, a predictive method of beam adjustment to maximize the beam adjustment interval is developed, which considers the SINR not only at the current location but also future possible locations. Simulation results show that the proposed algorithm can significantly increase beam adjustment interval and reduce the total number of beam adjustments for the moving user equipment, thus reducing the system overhead 41.4% on average over 10 randomly generated test traces.

Background: The immune checkpoint blockade (ICB) with anti-programmed cell death protein 1(PD-1) on HNSCC is not as effective as on other tumors. In this study, we try to find out the key factors in the heterogeneous tumor-associated monocyte/macrophage (TAMM) that could regulate immune responses and predict the validity of ICB on HNSCC.Experimental Design: To explore the correlation of the TAMM heterogeneity with the immune properties and prognosis of HNSCC, we established the differentiation trajectory of TAMM by analyzing the single-cell RNA-seq data of HNSCC, by which the HNSCC patients were divided into different sub-populations. Then, we exploited the topology of the network to screen out the genes critical for immune hot phenotype of HNSCC, as well as their roles in TAMM differentiation, tumor immune cycle, and progression. Finally, these key genes were used to construct a neural net model via deep-learning framework to predict the validity of treatment with anti-PD-1/PDL-1Results: According to the differentiation trajectory, the genes involved in TAMM differentiation were categorized into early and later groups. Then, the early group genes divided the HNSCC patients into sub-populations with more detailed immune properties. Through network topology, CXCL9, 10, 11, and CLL5 related to TAMM differentiation in the TME were identified as the key genes initiating and maintaining the immune hot phenotype in HNSCC by remarkably strengthening immune responses and infiltration. Genome wide, CASP8 mutations were found to be key to triggering immune responses in the immune hot phenotype. On the other hand, in the immune cold phenotype, the evident changes in CNV resulted in immune evasion by disrupting immune balance. Finally, based on the framework of CXCL9-11, CLL5, CD8+, CD4+ T cells, and Macrophage M1, the neural network model could predict the validity of PD-1/PDL-1 therapy with 75% of AUC in the test cohort.Conclusion: We concluded that the CXCL9, 10,11, and CCL5 mediated TAMM differentiation and constructed immune hot phenotype of HNSCC. Since they positively regulated immune cells and immune cycle in HNSCC, the CXCL9-11 and CCL5 could be used to predict the effects of anti-PD-1/PDL-1 therapy on HNSCC.

Although multimodal input has the potential to lead to more sound learning outcomes, it carries the risk of causing cognitive overload, making it difficult to determine the exact effects of multimodal input on the second language (L2) phrase learning. This study tests the efficacy of multimodal input on L2 phrase learning. It adopts a mixed-method approach by utilizing both quantitative and qualitative data. The experimental design is a 2 × 3 mixed model, with a group [the experimental group (EG) and the control group (CG)] as the between-subject factor and time (pretest, midtest, and posttest) as the within-subject factor. A total of 66 participants were divided into two groups. All materials incorporated three aspects of phrase knowledge (form, meaning, and use), but the materials of the CG were unimodal in that they were offered only on paper, and of the EG were multimodal in that they included pictures, audio recordings, and video clips. After the treatment, a questionnaire and a semi-structured interview were given to the EG learners to explore their perceptions of using multimodal materials to learn L2 phrases. The results indicate that both groups had significant gains in learning phrases, but students with the multimodal input achieved significantly better results than those with the unimodal input. Moreover, the EG students had a generally positive attitude toward the use of multimodal resources. This study validates the efficacy of multimodal input on the acquisition of English phrases and shows that cognitive overload was avoided by sequencing the information.

Since its outbreak in December 2019, a series of clinical trials on coronavirus disease 2019 (COVID-19) have been registered or carried out. However, the significant heterogeneity and less critical outcomes of such trials may be leading to a waste of research resources. This study aimed to develop a core outcome set (COS) for clinical trials on COVID-19 in order to tackle the outcome issues. The study was conducted according to the Core Outcome Measures in Effectiveness Trials (COMET) Handbook: Version 1.0, a guideline for COS development. A research group was set up that included experts in respiratory and critical medicine, traditional Chinese medicine (TCM), evidence-based medicine, clinical pharmacology, and statistics, in addition to medical journal editors. Clinical trial registry websites (www.chictr.org.cn and clinicaltrials.gov) were searched to retrieve clinical trial protocols and outcomes in order to form an outcome pool. A total of 78 clinical trial protocols on COVID-19 were included and 259 outcomes were collected. After standardization, 132 outcomes were identified within seven different categories, of which 58 were selected to develop a preliminary outcome list for further consensus. After two rounds of Delphi survey and one consensus meeting, the most important outcomes for the different clinical classifications of COVID-19 were identified and determined to constitute the COS for clinical trials on COVID-19 (COS-COVID). The COS-COVID includes one outcome for the mild type (time to 2019 novel coronavirus (2019-nCoV) reverse transcription-polymerase chain reaction (RT-PCR) negativity), four outcomes for the ordinary type (length of hospital stay, composite events, score of clinical symptoms, and time to 2019-nCoV RT-PCR negativity), five outcomes for the severe type (composite events, length of hospital stay, arterial oxygen partial pressure (PaO2)/fraction of inspired oxygen (FiO2), duration of mechanical ventilation, and time to 2019-nCoV RT-PCR negativity), one outcome for critical type (all-cause mortality), and one outcome for rehabilitation period (pulmonary function). The COS-COVID is currently the most valuable and practical clinical outcome set for the evaluation of intervention effect, and is useful for evidence assessment and decision-making. With a deepening understanding of COVID-19 and application feedback, the COS-COVID should be continuously updated.

BackgroundPrecise evaluation of the efficacy of immunotherapy is critical in the effective management and treatment of advanced hepatocellular carcinoma (HCC). Therefore, the purpose of this study was to compare the response assessments achieved by different criteria and to evaluate the correlation between survival outcome and response assessment in HCC treated with programmed cell death protein 1 (PD-1) inhibitor.MethodsFifty patients with advanced HCC treated with first-line PD-1 inhibitor with baseline and follow‐up CT images were analyzed. The patients were categorized into responders and nonresponders according to the criteria.ResultsWhen the response assessments between RECIST 1.1 and mRECIST were compared, no statistically significant differences were observed. Overall response rate was 16% by RECIST 1.1 and iRECIST and was 24% by mRECIST. According to RECIST 1.1 and mRECIST, overall survival (OS) and progression-free survival (PFS) were not statistically different between the complete response (CR) and partial response (PR) groups and the stable disease (SD) and progressive disease (PD) groups. The OS and PFS were significantly different between responders and nonresponders according to mRECIST. The Cohen’s Kappa for RECIST 1.1, iRECIST, and mRECIST was 0.534, 0.438, and 0.363, respectively.ConclusionThe mRECIST criteria have a powerful ability to discriminate between responders and nonresponders and demonstrated significantly longer OS and PFS in responders than in nonresponders. However, mRECIST needs to be further improved in order for it to be widely used in the clinical evaluation of immunotherapy in HCC.

Aim: To investigate the compliance and the outcome of Traditional Chinese Medicine (TCM) in patients with coronary heart disease (CHD) after treatment of revascularization.Methods: In this prospective cohort study, the non-exposure group (NEG), low-exposure group (LEG), and high-exposure group (HEG) were divided after 2 years follow-up. The primary outcome was a composite of death from cardiovascular causes, non-lethal myocardial infarction, heart transplantation, or stroke. Time-to-event data were evaluated by using the Cox regression analysis with hazard ratios (HRs) and 95% CIs. Then, the two-sided p-values were calculated by using the Cox models. In order to indicate the therapeutic effects of TCM on the CHD after revascularization, the survival analysis and the nested case–control study were conducted separately.Results: There were 1,003 patients with CHD enrolled, 356 patients (35.49%) did not choose the TCM, 379 patients (37.79%) used the TCM seldom, and only 268 patients (26.72%) used TCM regularly. A total of 653 patients with revascularization participated in the prospective cohort study. Over the duration of the trial, the primary endpoints occurred in 12 (4.35%), 11 (4.80%), and 2 (1.35%) patients in the NEG, LEG, and HEG, while the secondary endpoints occurred in 84 (30.43%), 57 (24.89%), and 15 (10.14%) patients in the NEG, LEG, and HEG, respectively. The occurrence time of secondary endpoint events in HEG was significantly postponed (p < 0.001) compared with the other cohorts. The Cox regression analysis indicated that the HRs in the primary endpoints, the secondary endpoint events, the major adverse cardiac and cerebrovascular events (MACCE), and the composite endpoint events for HEG were all around 0.3 (p < 0.05) and HRs for LEG were all around 0.8. The results of the nested case–control study showed that the TCM exposure was significantly different between the cases and controls in the secondary endpoints (p < 0.05), while no significant difference in the primary endpoints (p > 0.05), but the percentage of HEG in the cases was extremely lower than the controls.Conclusion: The HEG-TCM may improve the outcomes of the patients with CHD after treatment of revascularization.Registration:http://www.chictr.org.cn. Unique identifier: ChiCTR-OOC-17012995.

Heterogeneously catalyzed decarboxylation of L-lysine is a green and promising way to produce cadaverine. Here, cadaverine was firstly synthesized by using the supported nano-sized ruthenium oxide (RuOx) catalysts. Under the optimized conditions, RuOx/BaSO4 possesses an excellent catalytic performance with L-lysine conversion of 99% and cadaverine selectivity up to 62%, which has a great industrial potential.

ObjectiveTo investigate whether radiomics features extracted from multi-parametric MRI combining machine learning approach can predict molecular subtype and androgen receptor (AR) expression of breast cancer in a non-invasive way.Materials and MethodsPatients diagnosed with clinical T2–4 stage breast cancer from March 2016 to July 2020 were retrospectively enrolled. The molecular subtypes and AR expression in pre-treatment biopsy specimens were assessed. A total of 4,198 radiomics features were extracted from the pre-biopsy multi-parametric MRI (including dynamic contrast-enhancement T1-weighted images, fat-suppressed T2-weighted images, and apparent diffusion coefficient map) of each patient. We applied several feature selection strategies including the least absolute shrinkage and selection operator (LASSO), and recursive feature elimination (RFE), the maximum relevance minimum redundancy (mRMR), Boruta and Pearson correlation analysis, to select the most optimal features. We then built 120 diagnostic models using distinct classification algorithms and feature sets divided by MRI sequences and selection strategies to predict molecular subtype and AR expression of breast cancer in the testing dataset of leave-one-out cross-validation (LOOCV). The performances of binary classification models were assessed via the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). And the performances of multiclass classification models were assessed via AUC, overall accuracy, precision, recall rate, and F1-score.ResultsA total of 162 patients (mean age, 46.91 ± 10.08 years) were enrolled in this study; 30 were low-AR expression and 132 were high-AR expression. HR+/HER2− cancers were diagnosed in 56 cases (34.6%), HER2+ cancers in 81 cases (50.0%), and TNBC in 25 patients (15.4%). There was no significant difference in clinicopathologic characteristics between low-AR and high-AR groups (P > 0.05), except the menopausal status, ER, PR, HER2, and Ki-67 index (P = 0.043,

Aim: After neoadjuvant chemotherapy (NACT), tumor shrinkage pattern is a more reasonable outcome to decide a possible breast-conserving surgery (BCS) than pathological complete response (pCR). The aim of this article was to establish a machine learning model combining radiomics features from multiparametric MRI (mpMRI) and clinicopathologic characteristics, for early prediction of tumor shrinkage pattern prior to NACT in breast cancer.Materials and Methods: This study included 199 patients with breast cancer who successfully completed NACT and underwent following breast surgery. For each patient, 4,198 radiomics features were extracted from the segmented 3D regions of interest (ROI) in mpMRI sequences such as T1-weighted dynamic contrast-enhanced imaging (T1-DCE), fat-suppressed T2-weighted imaging (T2WI), and apparent diffusion coefficient (ADC) map. The feature selection and supervised machine learning algorithms were used to identify the predictors correlated with tumor shrinkage pattern as follows: (1) reducing the feature dimension by using ANOVA and the least absolute shrinkage and selection operator (LASSO) with 10-fold cross-validation, (2) splitting the dataset into a training dataset and testing dataset, and constructing prediction models using 12 classification algorithms, and (3) assessing the model performance through an area under the curve (AUC), accuracy, sensitivity, and specificity. We also compared the most discriminative model in different molecular subtypes of breast cancer.Results: The Multilayer Perception (MLP) neural network achieved higher AUC and accuracy than other classifiers. The radiomics model achieved a mean AUC of 0.975 (accuracy = 0.912) on the training dataset and 0.900 (accuracy = 0.828) on the testing dataset with 30-round 6-fold cross-validation. When incorporating clinicopathologic characteristics, the mean AUC was 0.985 (accuracy = 0.930) on the training dataset and 0.939 (accuracy = 0.870) on the testing dataset. The model further achieved good AUC on the testing dataset with 30-round 5-fold cross-validation in three molecular subtypes of breast cancer as following: (1) HR+/HER2–: 0.901 (accuracy = 0.816), (2) HER2+: 0.940 (accuracy = 0.865), and (3) TN: 0.837 (accuracy = 0.811).Conclusions: It is feasible that our machine learning model combining radiomics features and clinical characteristics could provide a potential tool to predict tumor shrinkage patterns prior to NACT. Our prediction model will be valuable in guiding NACT and surgical treatment in breast cancer.

Rheumatoid arthritis (RA) is a systemic poly-articular chronic autoimmune joint disease that mainly damages the hands and feet, which affects 0.5% to 1.0% of the population worldwide. With the sustained development of disease-modifying antirheumatic drugs (DMARDs), significant success has been achieved for preventing and relieving disease activity in RA patients. Unfortunately, some patients still show limited response to DMARDs, which puts forward new requirements for special targets and novel therapies. Understanding the pathogenetic roles of the various molecules in RA could facilitate discovery of potential therapeutic targets and approaches. In this review, both existing and emerging targets, including the proteins, small molecular metabolites, and epigenetic regulators related to RA, are discussed, with a focus on the mechanisms that result in inflammation and the development of new drugs for blocking the various modulators in RA.

The Fe-based ionic liquid doped g-C3N4 (FeCN) photocatalyst was firstly prepared base on ultrathin g-C3N4 obtained by multiple calcination method with a metal-based reactive ionic liquid [Omim]FeCl4 for the degradation of Rhodamine B (RhB). Experimental results revealed that Fe3+ species were doped into the framework of g-C3N4. The effect of the amount of Fe-doping on the catalytic activity was performed. The result showed that the FeCN could effectively degrade RhB under the condition of visible light irradiation. The photocurrent analysis showed that the incorporation of Fe3+ into g-C3N4 material could accelerate the separation of the photogenerated carriers significantly. At the same time, the reactive species generated during the photodegradation process were tested by radicals trapping experiments and electron spin resonance (ESR). It was proposed that the synergistic effect of O2•− and ·OH contributed to degrade RhB efficiently. Keywords: g-C3N4, [Omim]FeCl4, Photocatalytic, Visible light, Active species

In mobile robotic control models, control parameters are always generated by sensors' information and a set of Impact Factors (IFs, such as the P-value in the PID model). The IFs take forms of fixed coefficients in control models and need to be pre-defined at design-time. However, when operating in an open environment, IFs of the control model are expected to be adjusted automatically at run-time in order to adapt to the environment changes and improve the operation of robotics. This paper presents a clustering-based approach to continuously updating the IFs in robot control model. The proposed approach utilizes the density-based clustering method to classify environmental changes based on the effects of these changes on robots. In each cluster, the regression method is designed to learn the relationship between IFs and environment changes, and therefore generate corresponding IF adjustment model. Such approach can decrease the mutual interference of environmental changes and enhance the rationality of robotic actions. The paper presents the self-adjusting framework and designs corresponding IFs update algorithms. This paper develops robotics path-following scenario and object-following scenario in open environment and conducts experiments to evaluate the effectiveness of the proposed approach. The results show that the proposed approach has faster response to environmental changes than DQN and MPC approaches, along with a lower deviation of robot's actions.

The development of an efficient catalyst especially with a high productivity for decarboxylation of L-lysine to cadaverine, is of both industrial and economic significance. Here, we reported the synthesis of RuO2 well-confined in the supercage of FAU zeolite (RuO2@FAU) through in situ hydrothermal strategies. A set of characterizations, such as XRD, Raman, TEM, XPS, NH3-TPD and N2 physical adsorption, confirmed the successful encapsulation of RuO2 clusters (~1.5 nm) inside the FAU zeolite. RuO2@FAU had the higher cadaverine productivity of 120.9 g/L/h/mmol cat., which was almost six times that of traditionally supported ruthenium oxide catalysts (21.2 g/L/h/mmol cat.). RuO2@FAU catalysts with different ammonia exchange degrees, as well as different Si/Al ratios were further evaluated. After optimization, the highest cadaverine productivity of 480.3 g/L/h/mmol cat. was obtained. Deep analysis of the electronic properties of RuO2@FAU indicated that the surface defect structures, such as oxygen vacancies, played a vital role in the adsorption or activation of L-lysine which finally led to a boosted performance. Furthermore, the mechanism of decarboxylation of L-lysine to cadaverine was proposed.

Cancer has become the leading cause of death in recent years. As great advances in medical treatment, emerging therapies of various cancers have been developed. Current treatments include surgery, radiotherapy, chemotherapy, immunotherapy, and targeted therapy. Aptamers are synthetic ssDNA or RNA. They can bind tightly to target molecules due to their unique tertiary structure. It is easy for aptamers to be screened, synthesized, programmed, and chemically modified. Aptamers are emerging targeted drugs that hold great potentials, called therapeutic aptamers. There are few types of therapeutic aptamers that have already been approved by the US Food and Drug Administration (FDA) for disease treatment. Now more and more therapeutic aptamers are in the stage of preclinical research or clinical trials. This review summarized the screening and development of therapeutic aptamers against different types of cancer cells.

The discovery and identification of biomarkers promote the rational and fast development of medical diagnosis and therapeutics. Clinically, the application of ideal biomarkers still is limited due to the suboptimal technology in biomarker discovery. Aptamers are single-stranded deoxyribonucleic acid or ribonucleic acid molecules and can selectively bind to varied targets with high affinity and specificity. Compared with antibody, aptamers have desirable advantages, such as flexible design, easy synthesis and convenient modification with different functional groups. Currently, different aptamer-based technologies have been developed to facilitate biomarker discovery, especially CELL-SELEX and SOMAScan technology. CELL-SELEX technology is mainly used to identify cell membrane surface biomarkers of various cells. SOMAScan technology is an unbiased biomarker detection method that can analyze numerous and even thousands of proteins in complex biological samples at the same time. It has now become a large-scale multi-protein biomarker discovery platform. In this review, we introduce the aptamer-based biomarker discovery technologies, and summarize and highlight the discovered emerging biomarkers recently in several diseases.

Abstract Background SDF1/CXCR4 and AnnexinA7 play important roles in many physiological and pathological conditions, but the molecular association between them in cancer cells has not been studied thus far. Methods The expression changes of SDF1/CXCR4 were detected by gene transcriptome sequencing, qRT-PCR, Western blotting, cytoimmunofluorescence and immunohistochemistry in mouse hepatocarcinoma F/P cells, AnnexinA7 downregulated expression F (FA7DOWN) cells, AnnexinA7 overexpression P (PA7UP) cells, AnnexinA7 unrelated sequence F (FSHUS) cells, empty vector P (PNCEV) cells and normal liver cells in vitro and in vivo. Results SDF1 and CXCR4 were co-expressed in hepatocarcinoma cells. SDF1 was localized mainly in the cytoplasm of cells, while CXCR4 was mainly localized in the cell membrane. Both in vitro and in vivo, expression levels of SDF1/CXCR4 in F and P cells were higher than in normal liver cells, and expression levels of SDF1/CXCR4 in F cells with high lymphatic metastatic potential were higher than those in P cells with low lymphatic metastatic potential. Expression of SDF1 was higher than that of CXCR4 in P cells and normal liver cells, while expression of CXCR4 was higher than that of SDF1 in F cells. Expression levels of SDF1/CXCR4 were completely consistent with AnnexinA7 regulation. After the AnnexinA7 gene was downregulated or upregulated, expression levels of SDF1/CXCR4 in FA7DOWN/PA7UP cells were lower or higher than those in FSHUS/PNCEV cells. Furthermore, CXCR4 was more sensitively modulated by AnnexinA7 regulation than SDF1. Conclusions High co-expression of SDF1/CXCR4 is a molecular characteristic of hepatocarcinoma cells, especially those with high lymphatic metastatic potential. AnnexinA7 positively regulates expression levels of SDF1/CXCR4, in particular CXCR4, and AnnexinA7 is a functional regulator of SDF1/CXCR4.

Microcystis is one of the most common bloom-forming cyanobacteria in freshwater ecosystems throughout the world. However, the underlying life history mechanism and distinct temporal dynamics (inter- and intra-annual) of Microcystis populations in different geographical locations and lakes remain unclear but is critical information needed for the development of robust prediction, prevention, and management strategies. Perennial observations indicate that temperature may be the key factor driving differences in the overwintering strategy. This study quantitatively compared the overwintering abilities of Microcystis aeruginosa (Ma) in both the water column and sediments under a gradient of overwintering water temperatures (i.e., 4, 8, and 12 °C) using the death and proliferation rates of Ma. The results show that the dynamics of the Microcystis overwintering strategy were significantly affected by water temperatures. At 4 and 8 °C, Ma mainly overwintered in sediments and disappeared from the water column after exposure to low temperatures for a long duration, although some Microcystis cells can overwinter in the water column for short durations at low temperatures. At 12 °C, most Ma can overwinter in the water column. Rising temperatures promoted the proliferation of pelagic Ma but accelerated the death of benthic Ma. With warmer winter temperatures, pelagic Microcystis might become the primary inoculum sources in the spring. Our study highlights the overwintering strategy flexibility in explaining temporal dynamics differences of Microcystis among in geographical locations and should be considered in the context of global warming.

Based on the first-principles of density functional theory and Boltzmann transport theory, we report two-dimensional (2D) α -Se _2 Te monolayer to be a high-performance medium temperature p-type thermoelectric material with low lattice thermal conductivity ( κ _l ), high power factor ( PF ) and high dimensionless figure of merit ( ZT ). At the temperature of 700 K, PF is up to 3.77 and 11.5 mW m ^−1 K ^−2 , ZT is up to 0.55 and 1.91 in appropriate doping level for n- and p-types, respectively, and k _l is as low as 2.09 W m ^−1 K ^−1 . We also examine the effect of spin-orbital coupling (SOC) on the carrier transport and find that with SOC, PF and hence ZT will be reduced significantly due to the reduced band gap. The higher PF of p-type than that of n-type is evidently due to the flatter valence band edge than conduction band edge. Low k _l is inevitably attributed to the strong lattice anharmonicity.

By employing the first-principles-based transport theory, we investigate the thermoelectric performance based on the structural and electronic properties of NiCl 3 monolayer. The NiCl 3 monolayer is confirmed to be a stable Dirac spin gapless semiconductor with the linear energy dispersion having almost massless carrier, high carrier mobility and fully spin-polarization. Further, NiCl 3 monolayer processes the optimum power factor of 4.97 mWm − 1 K − 2 , the lattice thermal conductivity of 1.89 Wm − 1 K − 1 , and the dimensionless figure of merit of 0.44 at room temperature under reasonable carrier concentration, indicating that NiCl 3 monolayer may be a potential matrix for promising thermoelectrics.