Nitrogenous fertilizer plays a more important role than cultivars in shaping sorghum-associated microbiomes.

The plant microbiome plays a crucial role in facilitating plant growth through enhancing nutrient cycling, acquisition and transport, as well as alleviating stresses induced by nutrient limitations. Despite its significance, the relative importance of common agronomic practices, such as nitrogenous fertilizer, in shaping the plant microbiome across different cultivars remains unclear. This study investigated the dynamics of bacterial and fungal communities in leaf, root, rhizosphere, and bulk soil in response to nitrogenous fertilizer across ten sorghum varieties, using 16S rRNA and ITS gene amplicon sequencing, respectively. Our results revealed that nitrogen addition had a greater impact on sorghum-associated microbial communities compared to cultivar. Nitrogen addition significantly reduced bacterial diversity in all compartments except for the root endophytes. However, N addition significantly increased fungal diversity in both rhizosphere and bulk soils, while significantly reducing fungal diversity in the root endophytes. Furthermore, N addition significantly altered the community composition of bacteria and fungi in all four compartments, while cultivars only affected the community composition of root endosphere bacteria and fungi. Network analysis revealed that fertilization significantly reduced microbial network complexity and increased fungal-related network complexity. Collectively, this study provides empirical evidence that sorghum-associated microbiomes are predominantly shaped by nitrogenous fertilizer rather than by cultivars, suggesting that consistent application of nitrogenous fertilizer will ultimately alter plant-associated microbiomes regardless of cultivar selection.

Xinyang tablet alleviated cardiac dysfunction in a cardiac pressure overload model by regulating the receptor-interacting serum/three-protein kinase 3/FUN14 domain containing 1-mediated mitochondrial unfolded protein response and mitophagy.

ETHNOPHARMACOLOGICAL RELEVANCE: Xinyang tablet (XYT) has been used for heart failure (HF) for over twenty years in clinical practice, but the underlying molecular mechanism remains poorly understood. AIMS OF THE STUDY: In the present study, we aimed to explore the protective effects of XYT in HF in vivo and in vitro. MATERIALS AND METHODS: Transverse aortic constriction was performed in vivo to establish a mouse model of cardiac pressure overload. Echocardiography, tissue staining, and real-time quantitative PCR (qPCR) were examined to evaluate the protective effects of XYT on cardiac function and structure. Adenosine 5'-triphosphate production, reactive oxygen species staining, and measurement of malondialdehyde and superoxide dismutase was used to detect mitochondrial damage. Mitochondrial ultrastructure was observed by transmission electron microscope. Immunofluorescence staining, qPCR, and Western blotting were performed to evaluate the effect of XYT on the mitochondrial unfolded protein response and mitophagy, and to identify its potential pharmacological mechanism. In vitro, HL-1 cells and neonatal mouse cardiomyocytes were stimulated with Angiotensin II to establish the cell model. Western blotting, qPCR, immunofluorescence staining, and flow cytometry were utilized to determine the effects of XYT on cardiomyocytes. HL-1 cells overexpressing receptor-interacting serum/three-protein kinase 3 (RIPK3) were generated by transfection of RIPK3-overexpressing lentiviral vectors. Cells were then co-treated with XYT to determine the molecular mechanisms. RESULTS: In the present study, XYT was found to exerta protective effect on cardiac function and structure in the pressure overload mice. And it was also found XYT reduced mitochondrial damage by enhancing mitochondrial unfolded protein response and restoring mitophagy. Further studies showed that XYT achieved its cardioprotective role through regulating the RIPK3/FUN14 domain containing 1 (FUNDC1) signaling. Moreover, the overexpression of RIPK3 successfully reversed the XYT-induced protective effects and significantly attenuated the positive effects on the mitochondrial unfolded protein response and mitophagy. CONCLUSIONS: Our findings indicated that XYT prevented pressure overload-induced HF through regulating the RIPK3/FUNDC1-mediated mitochondrial unfolded protein response and mitophagy. The information gained from this study provides a potential strategy for attenuating mitochondrial damage in the context of pressure overload-induced heart failure using XYT.

The inverted U-shaped relationship between epinephrine and pancreatic ductal adenocarcinoma patients' survival with compensation of lymphocyte.

BACKGROUND: The relationship between epinephrine and cancer can be dose-dependent in in vivo study. Whether it is the same in human body still needs verification. METHOD: We used frozen human pancreatic ductal adenocarcinoma (PDAC) tissues to detect epinephrine content and analyzed its relationship with survival using the K-M method and Cox regression. Disturbance of blood cell count and C-reactive protein and identification of related potent intermediary factors were also analyzed. RESULTS: K-M plot and Cox regression all showed the inverted U-shaped relationship between epinephrine and PDAC survival. Lymphocyte adjustment can increase the HRs of epinephrine for PDAC death by >10%. CONCLUSION: Epinephrine played an anti-tumor or pro-tumor effect depending on the specific concentration. Circulating lymphocyte count was elevated and might acted as a compensation pathway to reduce the pro-tumor effect of epinephrine to PDAC.

Study of radiomics based on dual-energy CT for nuclear grading and T-staging in renal clear cell carcinoma.

INTRODUCTION: Clear cell renal cell carcinoma (ccRCC) is the most lethal subtype of renal cell carcinoma with a high invasive potential. Radiomics has attracted much attention in predicting the preoperative T-staging and nuclear grade of ccRCC. OBJECTIVE: The objective was to evaluate the efficacy of dual-energy computed tomography (DECT) radiomics in predicting ccRCC grade and T-stage while optimizing the models. METHODS: 200 ccRCC patients underwent preoperative DECT scanning and were randomized into training and validation cohorts. Radiomics models based on 70 KeV, 100 KeV, 150 KeV, iodine-based material decomposition images (IMDI), virtual noncontrasted images (VNC), mixed energy images (MEI) and MEI + IMDI were established for grading and T-staging. Receiver operating characteristic analysis and decision curve analysis (DCA) were performed. The area under the curve (AUC) values were compared using Delong test. RESULTS: For grading, the AUC values of these models ranged from 0.64 to 0.97 during training and from 0.54 to 0.72 during validation. In the validation cohort, the performance of MEI + IMDI model was optimal, with an AUC of 0.72, sensitivity of 0.71, and specificity of 0.70. The AUC value for the 70 KeV model was higher than those for the 100 KeV, 150 KeV, and MEI models. For T-staging, these models achieved AUC values of 0.83 to 1.00 in training and 0.59 to 0.82 in validation. The validation cohort demonstrated AUCs of 0.82 and 0.70, sensitivities of 0.71 and 0.71, and specificities of 0.80 and 0.60 for the MEI + IMDI and IMDI models, respectively. In terms of grading and T-staging, the MEI + IMDI model had the highest AUC in validation, with IMDI coming in second. There were statistically significant differences between the MEI + IMDI model and the 70 KeV, 100 KeV, 150 KeV, MEI, and VNC models in terms of grading (P < .05) and staging (P ≤ .001). DCA showed that both MEI + IDMI and IDMI models outperformed other models in predicting grade and stage of ccRCC. CONCLUSIONS: DECT radiomics models were helpful in grading and T-staging of ccRCC. The combined model of MEI + IMDI achieved favorable results.

The Value of Dual-Energy Computed Tomography-Based Radiomics in the Evaluation of Interstitial Fibers of Clear Cell Renal Carcinoma.

OBJECTIVE: We investigated the potential of dual-energy computed tomography (DECT) radiomics in assessing cancer-associated fibroblasts in clear cell renal carcinoma (ccRCC). METHODS: A retrospective analysis was conducted on 132 patients with ccRCC. The arterial and venous phase iodine-based material decomposition images (IMDIs), virtual non-contrast images, 70 keV, 100 keV, and 150 keV virtual monoenergetic images, and mixed energy images (MEIs) were obtained from the DECT datasets. On the Radcloud platform, radiomics feature extraction, feature selection, and model establishment were performed. Seven radiomics models were established using the support vector machine. The predictive performance was evaluated by utilizing receiver operating characteristic and the area under the curve (AUC) was calculated. Nomograms were constructed. RESULTS: The combined model demonstrated high efficiency in evaluating pseudocapsule thickness with AUC, specificity, and sensitivity of 0.833, 0.870, and 0.750, respectively in the validation set, surpassing those of other models. The precision, F1-score, and Youden index were also higher for the combined model. For evaluating the number of collagen fibers, the combined model exhibited the highest AUC (0.741) among all models, with a specificity of 0.830 and a sensitivity of 0.330. The AUC in the 150 kv model and IMDI model were slightly lower than those in the combined model (0.728 and 0.710, respectively), with corresponding sensitivity and specificity of 0.560/0.780 and 0.670/0.830. The nomogram exhibited that Rad-score had good prediction efficiency. CONCLUSION: DECT radiomics features have significant value in evaluating the interstitial fibers of ccRCC. The combined model of IMDI + MEI exhibits superior performance in assessing the thickness of the pseudocapsule, while the combined, 150 keV, and IMDI models demonstrate higher efficacy in evaluating collagen fiber number. Radiomics, combined with imaging features and clinical features, has excellent predictive performance. These findings offer crucial support for the clinical diagnosis, treatment, and prognosis of ccRCC and provide valuable insights into the application of DECT.

DMGL-MDA: A dual-modal graph learning method for microbe-drug association prediction.

The interaction between human microbes and drugs can significantly impact human physiological functions. It is crucial to identify potential microbe-drug associations (MDAs) before drug administration. However, conventional biological experiments to predict MDAs are plagued by drawbacks such as time-consuming, high costs, and potential risks. On the contrary, computational approaches can speed up the screening of MDAs at a low cost. Most computational models usually use a drug similarity matrix as the initial feature representation of drugs and stack the graph neural network layers to extract the features of network nodes. However, different calculation methods result in distinct similarity matrices, and message passing in graph neural networks (GNNs) induces phenomena of over-smoothing and over-squashing, thereby impacting the performance of the model. To address these issues, we proposed a novel graph representation learning model, dual-modal graph learning for microbe-drug association prediction (DMGL-MDA). It comprises a dual-modal embedding module, a bipartite graph network embedding module, and a predictor module. To assess the performance of DMGL-MDA, we compared it against state-of-the-art methods using two benchmark datasets. Through cross-validation, we illustrated the superiority of DMGL-MDA. Furthermore, we conducted ablation experiments and case studies to validate the effective performance of the model.

Radiomic features of the hippocampal based on magnetic resonance imaging in the menopausal mouse model linked to neuronal damage and cognitive deficits.

Estrogen deficiency in the early postmenopausal phase is associated with an increased long-term risk of cognitive decline or dementia. Non-invasive characterization of the pathological features of the pathological hallmarks in the brain associated with postmenopausal women (PMW) could enhance patient management and the development of therapeutic strategies. Radiomics is a means to quantify the radiographic phenotype of a diseased tissue via the high-throughput extraction and mining of quantitative features from images acquired from modalities such as CT and magnetic resonance imaging (MRI). This study set out to explore the correlation between radiomics features based on MRI and pathological features of the hippocampus and cognitive function in the PMW mouse model. Ovariectomized (OVX) mice were used as PWM models. MRI scans were performed two months after surgery. The brain's hippocampal region was manually annotated, and the radiomic features were extracted with PyRadiomics. Chemiluminescence was used to evaluate the peripheral blood estrogen level of mice, and the Morris water maze test was used to evaluate the cognitive ability of mice. Nissl staining and immunofluorescence were used to quantify neuronal damage and COX1 expression in brain sections of mice. The OVX mice exhibited marked cognitive decline, brain neuronal damage, and increased expression of mitochondrial complex IV subunit COX1, which are pathological phenomena commonly observed in the brains of AD patients, and these phenotypes were significantly correlated with radiomics features (p < 0.05, |r|>0.5), including Original_firstorder_Interquartile Range, Original_glcm_Difference Average, Original_glcm_Difference Average and Wavelet-LHH_glszm_Small Area Emphasis. Meanwhile, the above radiomics features were significantly different between the sham-operated and OVX groups (p < 0.01) and were associated with decreased serum estrogen levels (p < 0.05, |r|>0.5). This initial study indicates that the above radiomics features may have a role in the assessment of the pathology of brain damage caused by estrogen deficiency using routinely acquired structural MR images.

The value of a dual-energy CT Iodine map radiomics model for the prediction of collagen fiber content in the ccRCC tumor microenvironment.

BACKGROUND AND PURPOSE: Renal cell carcinoma (RCC) is a heterogeneous group of cancers. The collagen fiber content in the tumor microenvironment of renal cancer has an important role in tumor progression and prognosis. A radiomics model was developed from dual-energy CT iodine maps to assess collagen fiber content in the tumor microenvironment of ccRCC. METHODS: A total of 87 patients with ccRCC admitted to our hospital were included in this retrospective study. Among them, 59 cases contained large amounts of collagen fibers and 28 cases contained a small amount of collagen fibers. We established a radiomics model using preoperative dual-energy CT scan Iodine map (IV) imaging to distinguish patients with multiple collagen fibers from those with few collagen fibers in the tumor microenvironment of ccRCC. We extracted features from dual-energy CT Iodine map images to evaluate the effects of six classifiers, namely k-nearest neighbor (KNN), support vector machine (SVM), extreme gradient boosting (XGBoost), random forest (RF), logistic regression (LR), and decision tree (DT). The effects of the models built based on the dynamic and venous phases are also compared. Model performance was evaluated using quintuple cross-validation and area under the receiver operating characteristic curve (AUC). In addition, a clinical model was developed to assess the clinical factors affecting collagen fiber content. RESULTS: Compared to KNN, SVM, and LR classifiers, RF, DT, and XGBoost classifiers trained with higher AUC values, with training sets of 0.997, 1.0, and 1.0, respectively. In the validation set, the highest AUC was found in the SVM classifier with a size of 0.722. In the comparative test of the active and intravenous phase models, the SVM classifier had the best effect with its validation set AUC of 0.698 and 0.741. In addition, there was a statistically significant effect of patient age and maximum tumor diameter on the collagen fiber content in the tumor microenvironment of kidney cancer. CONCLUSION: Radionics features based on preoperative dual-energy CT IV can be used to predict the amount of collagen fibers in the tumor microenvironment of renal cancer. This study better informs clinical prognosis and patient management. Iodograms may add additional value to dual-energy CTs.

ADMET property prediction via multi-task graph learning under adaptive auxiliary task selection.

It is a critical step in lead optimization to evaluate the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of drug-like compounds. Classical single-task learning (STL) has effectively predicted individual ADMET endpoints with abundant labels. Conversely, multi-task learning (MTL) can predict multiple ADMET endpoints with fewer labels, but ensuring task synergy and highlighting key molecular substructures remain challenges. To tackle these issues, this work elaborates a multi-task graph learning framework for predicting multiple ADMET properties of drug-like small molecules (MTGL-ADMET) by holding a new paradigm of MTL, "one primary, multiple auxiliaries." It first adeptly combines status theory with maximum flow for auxiliary task selection. The subsequent phase introduces a primary-task-centric MTL model with integrated modules. MTGL-ADMET not only outstrips existing STL and MTL methods but also offers a transparent lens into crucial molecular substructures. It is anticipated that this work can promote lead compound finding and optimization in drug discovery.

CMMS-GCL: cross-modality metabolic stability prediction with graph contrastive learning.

MOTIVATION: Metabolic stability plays a crucial role in the early stages of drug discovery and development. Accurately modeling and predicting molecular metabolic stability has great potential for the efficient screening of drug candidates as well as the optimization of lead compounds. Considering wet-lab experiment is time-consuming, laborious, and expensive, in silico prediction of metabolic stability is an alternative choice. However, few computational methods have been developed to address this task. In addition, it remains a significant challenge to explain key functional groups determining metabolic stability. RESULTS: To address these issues, we develop a novel cross-modality graph contrastive learning model named CMMS-GCL for predicting the metabolic stability of drug candidates. In our framework, we design deep learning methods to extract features for molecules from two modality data, i.e. SMILES sequence and molecule graph. In particular, for the sequence data, we design a multihead attention BiGRU-based encoder to preserve the context of symbols to learn sequence representations of molecules. For the graph data, we propose a graph contrastive learning-based encoder to learn structure representations by effectively capturing the consistencies between local and global structures. We further exploit fully connected neural networks to combine the sequence and structure representations for model training. Extensive experimental results on two datasets demonstrate that our CMMS-GCL consistently outperforms seven state-of-the-art methods. Furthermore, a collection of case studies on sequence data and statistical analyses of the graph structure module strengthens the validation of the interpretability of crucial functional groups recognized by CMMS-GCL. Overall, CMMS-GCL can serve as an effective and interpretable tool for predicting metabolic stability, identifying critical functional groups, and thus facilitating the drug discovery process and lead compound optimization. AVAILABILITY AND IMPLEMENTATION: The code and data underlying this article are freely available at https://github.com/dubingxue/CMMS-GCL.

GPR35-mediated kynurenic acid sensing contributes to maintenance of gut microbiota homeostasis in ulcerative colitis.

Ulcerative colitis (UC) is a recurrent inflammatory disease related to gut microbiota disorder. Metabolites and their sensors play an important role in the communication between gut microbes and their host. Our previous study revealed that G protein-coupled receptor 35 (GPR35) is a key guardian of kynurenic acid (KA) and a core element of the defense responses against gut damage. However, the mechanism remains unknown. In this study, a DSS-induced rat colitis model was established and 16S rRNA sequencing was applied to explore the influence of GPR35-mediated KA sensing on gut microbiota homeostasis. Our results demonstrated that GPR35-mediated KA sensing is a necessary component in maintaining gut barrier integrity against DSS-induced damage. Furthermore, we provide compelling evidence suggesting that GPR35-mediated KA sensing plays a crucial role in maintaining gut microbiota homeostasis, which contributes to alleviation of DSS-induced colitis. In addition, five classes (Actinobacteria, Beta-/Gamma-proteobacteria, Erysipelotrichi, and Coriobacteriia) and six genera (Corynebacterium, Allobaculum, Parabacteroides, Sutterella, Shigella, and Xenorhabdus) were identified as the marked bacterial taxa that characterized the progression and outcome of colitis and are regulated by GPR35-mediated KA sensing. Our findings highlight that GPR35-mediated KA sensing is an essential defense mechanism against disorder of gut microbiota in UC. The results provide insights into the key role of specific metabolites and their monitor in maintaining gut homeostasis.

A facile alternative strategy of upcycling mixed plastic waste into vitrimers.

Chemical depolymerization has been identified as a promising approach towards recycling of plastic waste. However, complete depolymerization may be energy intensive with complications in purification. In this work, we have demonstrated upcycling of mixed plastic waste comprising a mixture of polyester, polyamide, and polyurethane through a reprocessable vitrimer of the depolymerized oligomers. Using poly(ethylene terephthalate) (PET) as a model polymer, we first demonstrated partial controlled depolymerization, using glycerol as a cleaving agent, to obtain branched PET oligomers. Recovered PET (RPET) oligomer was then used as a feedstock to produce a crosslinked yet reprocessable vitrimer (vRPET) despite having a wide molecular weight distribution using a solventless melt processing approach. Crosslinking and dynamic interactions were observed through rheology and dynamic mechanical analysis (DMA). Tensile mechanical studies showed no noticeable decrease in mechanical strength over multiple repeated melt processing cycles. Consequently, we have clearly demonstrated the applicability of the above method to upcycle mixed plastic wastes into vitrimers and reprocessable composites. This work also afforded insights into a potentially viable alternative route for utilization of depolymerized plastic/mixed plastic waste into crosslinked vitrimer resins manifesting excellent mechanical strength, while remaining reprocessable/ recyclable for cyclical lifetime use.

Association between Peripartum Mean Arterial Pressure and Postpartum Readmission for Preeclampsia with Severe Features.

OBJECTIVE: This study aimed to evaluate the relationship between peripartum mean arterial pressure (MAP) and postpartum readmission for preeclampsia with severe features. STUDY DESIGN: This is a retrospective case-control study comparing adult parturients readmitted for preeclampsia with severe features to matched nonreadmitted controls. Our primary objective was to evaluate the association between MAP at three time points during the index hospitalization (admission, 24-hour postpartum, and discharge) and readmission risk. We also evaluated readmission risk by age, race, body mass index, and comorbidities. Our secondary aim was to establish MAP thresholds to identify the population at highest risk of readmission. Multivariate logistic regression and chi-squared tests were used to determine the adjusted odds of readmission based on MAP. Receiver operating characteristic analyses were performed to evaluate risk of readmission relative to MAP; optimal MAP thresholds were established to identify those at highest risk of readmission. Pairwise comparisons were made between subgroups after stratifying for history of hypertension, with a focus on readmitted patients with new-onset postpartum preeclampsia. RESULTS: A total of 348 subjects met inclusion criteria, including 174 controls and 174 cases. We found that elevated MAP at both admission (adjusted odds ratio [OR]: 1.37 per 10 mm Hg, p < 0.0001) and 24-hour postpartum (adjusted OR: 1.61 per 10 mm Hg, p = 0.0018) were associated with increased risk of readmission. African American race and hypertensive disorder of pregnancy were independently associated with increased risk of readmission. Subjects with MAP > 99.5 mm Hg at admission or >91.5 mm Hg at 24-hour postpartum had a risk of at least 46% of requiring postpartum readmission for preeclampsia with severe features. CONCLUSION: Admission and 24-hour postpartum MAP correlate with risk of postpartum readmission for preeclampsia with severe features. Evaluating MAP at these time points may be useful for identifying women at higher risk for postpartum readmission. These women may otherwise be missed based on standard clinical approaches and may benefit from heightened surveillance. KEY POINTS: · Existing literature focuses on management of antenatal hypertensive disorders of pregnancy.. · Elevated peripartum MAP is associated with increased odds of readmission for preeclampsia.. · Peripartum MAP may predict readmission risk for de novo postpartum preeclampsia..

Revision of the subgenus Stegana (Steganina) from China, with assessment of species delimitation using DNA barcodes (Diptera, Drosophilidae).

A total of 58 (eight known and 50 new) species of the subgenus Stegana (Steganina) from China were surveyed and (re)described: S. (S.) bacilla Chen & Aotsuka, 2004, S. (S.) belokobylskiji Sidorenko, 1997, S. (S.) hirticeps Wang, Gao, & Chen, 2013, S. (S.) izu Sidorenko, 1997, S. (S.) kanmiyai Okada & Sidorenko, 1992, S. (S.) masanoritodai Okada & Sidorenko, 1992, S. (S.) maymyo Sidorenko, 1997, stat. rev., S. (S.) nigripes Zhang & Chen, 2015, S. (S.) alafoliacea Zhang & Chen, sp. nov., S. (S.) baoxing Li & Chen, sp. nov., S. (S.) bibarbata Li & Chen, sp. nov., S. (S.) bimai Cui & Chen, sp. nov., S. (S.) cinereipecta Zhang & Chen, sp. nov., S. (S.) cardua Cui & Chen, sp. nov., S. (S.) cordhirsuta Wang & Chen, sp. nov., S. (S.) cornuta Li & Chen, sp. nov., S. (S.) cucullata Li & Chen, sp. nov., S. (S.) cultella Cui & Chen, sp. nov., S. (S.) curvitabulata Cui & Chen, sp. nov., S. (S.) daiya Cui & Chen, sp. nov., S. (S.) dendrophila Zhang & Chen, sp. nov., S. (S.) flabella Li & Chen, sp. nov., S. (S.) flavipes Li & Chen, sp. nov., S. (S.) formosa Zhang & Chen, sp. nov., S. (S.) fusca Li & Chen, sp. nov., S. (S.) fuscipes Li & Chen, sp. nov., S. (S.) glaucopalpula Cui & Chen, sp. nov., S. (S.) haba Zhang & Chen, sp. nov., S. (S.) hirticlavata Cui & Chen, sp. nov., S. (S.) iaspidea Zhang & Chen, sp. nov., S. (S.) idiasta Cui & Chen, sp. nov., S. (S.) kanda Cui & Chen, sp. nov., S. (S.) labao Li & Chen, sp. nov., S. (S.) lancang Li & Chen, sp. nov., S. (S.) latifoliacea Wang & Chen, sp. nov., S. (S.) liusanjieae Li & Chen, sp. nov., S. (S.) magniflava Cui & Chen, sp. nov., S. (S.) mailangang Li & Chen, sp. nov., S. (S.) marenubila Cui & Chen, sp. nov., S. (S.) menghai Zhang & Chen, sp. nov., S. (S.) menglian Li & Chen, sp. nov., S. (S.) minutiflava Li & Chen, sp. nov., S. (S.) multiprocera Li & Chen, sp. nov., S. (S.) nayun Li & Chen, sp. nov., S. (S.) nigridentata Wang & Chen, sp. nov., S. (S.) nigripalpula Cui & Chen, sp. nov., S. (S.) otphylla Cui & Chen, sp. nov., S. (S.) radiciflava Zhang & Chen, sp. nov., S. (S.) rava Cui & Chen, sp. nov., S. (S.) sciophila Li & Chen, sp. nov., S. (S.) septencolorata Li & Chen, sp. nov., S. (S.) serrata Zhang & Chen, sp. nov., S. (S.) silvestrella Zhang & Chen, sp. nov., S. (S.) simola Cui & Chen, sp. nov., S. (S.) yani Li & Chen, sp. nov., S. (S.) yixiang Zhang & Chen, sp. nov., S. (S.) zaduo Cui & Chen, sp. nov., and S. (S.) zhuoma Cui & Chen, sp. nov. We also provided a complete list of Chinese Steganina species together with their geographical distributions. In addition, the majority of currently available DNA barcode (partial sequence of the mitochondrial cytochrome c oxidase subunit I (COI) gene) sequences of this subgenus (435 sequences of 102 spp.) were employed in a molecular analysis for species delimitation. Taken together, morphology- and molecular-based species delimitation results reached a consensus for an overwhelming majority of these Steganina species (98 of 102 spp.).

Causal effects of fatty acids on atopic dermatitis: A Mendelian randomization study.

Background: Some evidence suggests abnormalities in fatty acids in patients with atopic dermatitis (AD), and benefits of supplementation with these fatty acids have been reported. However, there is still substantial controversy on the correlation between fatty acids and AD. Therefore, the aim of this study was to determine whether fatty acid levels are causally related to AD using a Mendelian randomization approach. Methods: We evaluated the data about the fatty acids levels and AD with various methods from Genome-Wide Association Study (GWAS). GWAS results were available both from European ancestry. Mendelian randomization methods were used to analysis the casual inference of fatty acids on AD. MR Egger and MR-PRESSO were used to determine pleiotropy and heterogeneity. Further analysis was conducted using instruments associated with the FADS genes to address mechanisms involved. We also used Multivariate MR (MVMR) to show the independent casual inference of omega-3 (n-3) fatty acids on AD. Results: Mendelian randomization (MR) analysis suggests that n-3 fatty acid levels are associated with a lower risk of AD (n-3 ORIVW: 0.92, 95% confidence interval [CI]: 0.87-0.98; p = 0.01). Moreover, docosahexaenoic acids (DHA) levels, which is a kind of long-chain, highly unsaturated omega-3 (n-3) fatty acid, and its higher level was associated with a lower risk of AD (DHA ORIVW: 0.91, 95% CI: 0.84-0.98; p = 0.02). We ran multivariable MR analysis while controlling for variables within the other types of fatty acids. The effect estimates agreed with the preliminary MR analysis indicating the effect of n-3 fatty acids levels on AD was robust. MR-egger suggest no significant pleiotropy and heterogeneity on genetic instrumental variants. Outliers-corrected MR analyses after controlling horizontal pleiotropy were still robust. The single-SNP analyses revealed that n-3 fatty acids are likely linked to a decreased risk of AD through FADS cluster, highlighting the significance of the FADS gene in the fatty acids synthesis pathway in the development of AD. Conclusion: Our studies suggest that n-3 fatty acids may reduce the risk of AD. Risk prediction tools based on n-3 fatty acid levels may be valuable methods for improving AD screening and primary prevention. To reduce the risk of AD, individuals could enhance n-3 fatty acids intake through supplement or diet.

Clinical manifestations of adult hereditary spherocytosis with novel SPTB gene mutations and hyperjaundice: A case report.

BACKGROUND: The aim of the present study was to enhance understanding of the diagnosis and treatment of atypical hereditary spherocytosis (HS), and to broaden the diagnostic thoughts of physicians for patients with jaundice. CASE SUMMARY: A 28-year-old male presented with jaundice, bile duct stone, and splenomegaly, but without anemia. Other causes of jaundice were excluded, and gene sequencing revealed a novel heterozygous variant of c.1801C>T (p.Q601X) in exon 14 of the SPTB (NM_01355436) gene on chromosome 14 (chr14: 65260580) in the patient's blood; the biological parents and child of the patient did not have similar variants. A splenectomy was performed on the patient and his bilirubin levels returned to normal after surgery. Thus, a novel gene variant causing HS was identified. This variant may result in the truncation of ß-hemoglobin in the erythrocyte membrane, leading to loss of normal function, jaundice, and hemolytic anemia. The clinical manifestations of the patient were hyperjaundice and an absence of typical hemolysis during the course of the disease, which caused challenges for diagnosis by the clinicians. CONCLUSION: Following a definitive diagnosis, genetic testing and response to treatment identified a gene variant site for a novel hemolytic anemia.

A hierarchical hub location model for the integrated design of urban and rural logistics networks under demand uncertainty.

This paper contributes to the integrated design issue of urban and rural logistics networks under demand uncertainty. A hierarchical hub location model is proposed, which minimizes the expected total system cost by optimizing the locations, number and capacities of "urban-town‒village" hierarchical logistics hubs. The interactions among the logistics hubs and among the hub‒and‒spoke connections, as well as the hub capacity constraints are explicitly considered in the presence of logistics demand uncertainty. A demand scenario‒based branch‒and‒Benders‒cut algorithm is developed to solve the proposed model. A case study of Jiangling urban‒rural region in Hubei province of China is conducted for the illustration of the model and solution algorithm. The results generated by the proposed algorithm are benchmarked against those obtained by GUROBI solver and the practical scheme being currently implemented in the region. The results showed that the proposed methodology can greatly improve the efficiency of the urban‒rural logistics system in terms of expected total system cost. It is important to explicitly model the demand uncertainty, otherwise a significant decision bias may emerge. The proposed algorithm outperforms the GUROBI solver in terms of problem size solved and computational time.

Research and application of model fruit fly in prevention and treatment of neuropsychiatric disorders by traditional Chinese medicine and natural compounds: a review / 中国中药杂志

As an important model animal, fruit fly is characterized by outstanding genetic characteristics, relatively perfect nervous system, rapid reproduction, and low cost. Thus, it has been applied in the research on neuropsychiatric disorders in recent years, showing great potential in life science. The incidence of neuropsychiatric disorders has been on the rise, and the disorders have high disability rate and low case fatality rate. The global drug demand for such diseases is second only to cardiovascular and cerebrovascular diseases. At the moment, the demand of the drugs for the diseases have been rising, and it is an urgent task to develop related drugs. However, the research and development of the drugs are time-intensive and have a high failure rate. A suitable animal model can help shorten the time for drug screening and development, thereby reducing the cost and failure rate. This study reviews the application of fruit flies in several common neuropsychiatric disorders, which is expected to provide new ideas for the research and application of the model animals in traditional Chinese medicine.

Effects of raw and wine-processed Schisandra chinensis on neuro-endocrine-immune network in insomnia mice and its mechanism / 中国药房

OBJECTIVE To investigate the effect of raw and wine-processed Schisandra chinensis on neuro-immune-endocrine network in insomnia mice and its mechanism. METHODS Fifty mice were randomly divided into blank group， model group， diazepam group， raw S. chinensis group and wine-processed S. chinensis group， with 10 mice in each group. Except for blank group， the mice in the other groups were intraperitoneally injected with thyroxine solution to establish mice model of insomnia； at the end of each day’s modeling， the corresponding doses of diazepam，raw and wine-processed S. chinensis were given by gavage. The blank group and model group were given constant volume of normal saline. The general state of the mice was observed and recorded， and the total activity distance and upright times of the mice were detected； the EEG and EMG signals of mice were recorded， and the time ratio of sleep wake time （wake）， non-rapid eye movement （NREM） and rapid eye movement （REM） was analyzed； the contents of neurotransmitters [γ-aminobutyric acid （GABA）， 5-hydroxytryptamine （5-HT）， dopamine （DA）， norepinephrine （NE）， cortisol （CORT）] in brain suprachiasmatic nucleus （SCN） were detected； and the expressions of tumor necrosis factor α （TNF-α） and interleukin 1β （IL-1β） were detected； the mRNA expressions of clock gene Bmal1， circadian clock gene Clock and cycle gene Per2 were all detected. RESULTS Compared with the blank group， the mental state of the model group mice was relatively depressed， the amount of food and water increased， the body mass decreased， the hair was rough and shiny， and the circadian rhythm was irregular； the total activity distance and upright times decreased significantly； the time ratio of wake increased significantly， while the time ratios of REM and NREM decreased significantly； the content of 5- HT in brain SCN decreased significantly， while the content of NE， DA and CORT increased significantly； the fluorescence intensity of IL-1β and TNF-α was significantly increased； the relative expression level of Bmal1 and Clock mRNA was significantly increased， while the relative expression level of Per2 mRNA was significantly decreased （P＜0.05 or P＜0.01）. Compared with the model group， the general state of mice in diazepam group， raw S. chinensis group and wine-processed S. chinensis group was improved obviously， and most of the above index levels were significantly reversed （P＜0.05 or P＜0.01）. CONCLUSIONS Raw and wine-processed S. chinensis have a certain therapeutic effect on insomnia mice， the mechanism of which may be related to the regulation of neuro-endocrine-immune system related biological indicators in insomnia mice.