STF-Net: sparsification transformer coding guided network for subcortical brain structure segmentation.

Subcortical brain structure segmentation plays an important role in the diagnosis of neuroimaging and has become the basis of computer-aided diagnosis. Due to the blurred boundaries and complex shapes of subcortical brain structures, labeling these structures by hand becomes a time-consuming and subjective task, greatly limiting their potential for clinical applications. Thus, this paper proposes the sparsification transformer (STF) module for accurate brain structure segmentation. The self-attention mechanism is used to establish global dependencies to efficiently extract the global information of the feature map with low computational complexity. Also, the shallow network is used to compensate for low-level detail information through the localization of convolutional operations to promote the representation capability of the network. In addition, a hybrid residual dilated convolution (HRDC) module is introduced at the bottom layer of the network to extend the receptive field and extract multi-scale contextual information. Meanwhile, the octave convolution edge feature extraction (OCT) module is applied at the skip connections of the network to pay more attention to the edge features of brain structures. The proposed network is trained with a hybrid loss function. The experimental evaluation on two public datasets: IBSR and MALC, shows outstanding performance in terms of objective and subjective quality.

Overexpressing S100A9 ameliorates NK cell dysfunction in estrogen receptor-positive breast cancer.

BACKGROUND: Estrogen receptor (ER) positive human epidermal growth factor receptor 2 (HER2) negative breast cancer (ER+/HER2-BC) and triple-negative breast cancer (TNBC) are two distinct breast cancer molecular subtypes, especially in tumor immune microenvironment (TIME). The TIME of TNBC is considered to be more inflammatory than that of ER+/HER2-BC. Natural killer (NK) cells are innate lymphocytes that play an important role of tumor eradication in TME. However, studies focusing on the different cell states of NK cells in breast cancer subtypes are still inadequate. METHODS: In this study, single-cell mRNA sequencing (scRNA-seq) and bulk mRNA sequencing data from ER+/HER2-BC and TNBC were analyzed. Key regulator of NK cell suppression in ER+/HER2-BC, S100A9, was quantified by qPCR and ELISA in MCF-7, T47D, MDA-MB-468 and MDA-MB-231 cell lines. The prognosis predictability of S100A9 and NK activation markers was evaluated by Kaplan-Meier analyses using TCGA-BRAC data. The phenotype changes of NK cells in ER+/HER2-BC after overexpressing S100A9 in cancer cells were evaluated by the production levels of IFN-gamma, perforin and granzyme B and cytotoxicity assay. RESULTS: By analyzing scRNA-seq data, we found that multiple genes involved in cellular stress response were upregulated in ER+/HER2-BC compared with TNBC. Moreover, TLR regulation pathway was significantly enriched using differentially expressed genes (DEGs) from comparing the transcriptome data of ER+/HER2-BC and TNBC cancer cells, and NK cell infiltration high/low groups. Among the DEGs, S100A9 was identified as a key regulator. Patients with higher expression levels of S100A9 and NK cell activation markers had better overall survival. Furthermore, we proved that overexpression of S100A9 in ER+/HER2-cells could improve cocultured NK cell function. CONCLUSION: In conclusion, the study we presented demonstrated that NK cells in ER+/HER2-BC were hypofunctional, and S100A9 was an important regulator of NK cell function in ER+BC. Our work contributes to elucidate the regulatory networks between cancer cells and NK cells and may provide theoretical basis for novel drug development.

Comparing survival outcomes between neoadjuvant and adjuvant chemotherapy within T2N1M0 stage hormone receptor-positive, HER2-negative breast cancer: a retrospective cohort study based on SEER database.

BACKGROUND: Guideline recommendations for the application of neoadjuvant chemotherapy (NACT) in T2N1M0 stage hormone receptor-positive, HER2-negative (HR + /HER2-) breast cancer are ambiguous. The debate continues regarding whether NACT or adjuvant chemotherapy (ACT) offers superior survival outcomes for these patients. MATERIALS AND METHODS: Female patients diagnosed with HR + /HER2- breast cancer at T2N1M0 stage between 2010 and 2020, were identified from the Surveillance, Epidemiology, and End Results database and divided into two groups, the NACT group and the ACT group. Propensity score matching (PSM) was utilized to establish balanced cohorts between groups, considering baseline features. Kaplan-Meier (K-M) analysis and the Cox proportional hazards model were executed to assess the efficacy of both NACT and ACT in terms of overall survival (OS) and breast cancer-specific survival (BCSS). A logistic regression model was employed to examine the association between predictive variables and response to NACT. RESULTS: After PSM, 4,682 patients were finally included. K-M curves showed that patients receiving NACT exhibited significantly worse OS and BCSS when compared with patients undergoing ACT. Multivariable Cox analysis indicated that not achieving pathologic complete response (non-pCR) after NACT (versus ACT), was identified as an adverse prognostic factor for OS (HR 1.58, 95% CI 1.36-1.83) and BCSS (HR 1.70, 95% CI 1.44-2. 02). The logistic regression model revealed that low tumor grade independently predicted non-pCR. CONCLUSION: Among T2N1M0 stage HR + /HER2- patients, OS and BCSS of NACT were inferior to ACT. Patients who attained non-pCR after NACT demonstrated significantly worse survival outcomes compared with those who received ACT.

Modulating electron density enable efficient cascade conversion from peroxymonosulfate to superoxide radical driven by electron-rich/poor dual sites.

The superoxide radical (•O2-)-mediated peroxymonosulfate (PMS)-based photo-Fenton-like reaction enables highly selective water decontamination. Nevertheless, the targeted construction of •O2--mediated photo-Fenton-like system has been challenging. Herein, we developed an electron-rich/-poor dual sites driven •O2--mediated cascade photo-Fenton-like system by modulating electron density. Experimental and theoretical results demonstrated that PMS was preferentially adsorbed on electron-poor Co site. This adsorption promoted O-O bond cleavage of PMS to generate hydrogen peroxide (H2O2), which then migrated to electron-rich O site to extract eg electrons for O-H bond cleavage, rather than competing with PMS for Co site. The developed versatile cascade reaction system could selectively eliminate contaminants with low n-octanol/water partition constants (KOW) and dissociation constants (pKa) and remarkably resist inorganics (Cl-, H2PO4- and NO3-), humic acid (HA) and even real water matrices (tap water and secondary effluent). This finding provided a novel and plausible strategy to accurately and efficiently generate •O2- for the selective water decontamination.

Interactions between overweight/obesity and alcohol dependence impact human brain white matter microstructure: evidence from DTI.

There is inconsistent evidence for an association of obesity with white matter microstructural alterations. Such inconsistent findings may be related to the cumulative effects of obesity and alcohol dependence. This study aimed to investigate the possible interactions between alcohol dependence and overweight/obesity on white matter microstructure in the human brain. A total of 60 inpatients with alcohol dependence during early abstinence (44 normal weight and 16 overweight/obese) and 65 controls (42 normal weight and 23 overweight/obese) were included. The diffusion tensor imaging (DTI) measures [fractional anisotropy (FA) and radial diffusivity (RD)] of the white matter microstructure were compared between groups. We observed significant interactive effects between alcohol dependence and overweight/obesity on DTI measures in several tracts. The DTI measures were not significantly different between the overweight/obese and normal-weight groups (although widespread trends of increased FA and decreased RD were observed) among controls. However, among the alcohol-dependent patients, the overweight/obese group had widespread reductions in FA and widespread increases in RD, most of which significantly differed from the normal-weight group; among those with overweight/obesity, the alcohol-dependent group had widespread reductions in FA and widespread increases in RD, most of which were significantly different from the control group. This study found significant interactive effects between overweight/obesity and alcohol dependence on white matter microstructure, indicating that these two controllable factors may synergistically impact white matter microstructure and disrupt structural connectivity in the human brain.

Comparative Analysis of Macro/Microstructures and Constituents of Sorghum and Reed Straw.

Node-containing straws exhibit superior mechanical properties compared to node-free straw plants, particularly in terms of shear resistance and compression resistance. We explore the relationship between the structure and mechanical properties of straw materials, providing deeper insights for the field of biomechanics. In this study, we focused on two node-containing straw plants, namely sorghum and reed. The main characteristics of sorghum and reed stalks were compared using macroscopic observation, stereomicroscopy, scanning electron microscopy, infrared spectroscopy, and EDS analysis. This study revealed numerous similarities and differences in the macro- and microstructures as well as the elemental composition of sorghum and reed stalks. The functional groups in sorghum and reed stalks were largely similar, with the primary elements being C and O. Distinguishing features included a higher tapering and a slightly larger reduction in wall thickness in sorghum stalks compared to reed stalks. The cross-section of sorghum stalks was filled with pith structures, while reed stalks exhibited a hollow structure. The vascular bundles in sorghum typically showed a paired arrangement, whereas those in reeds were arranged in odd numbers. Furthermore, sorghum straws contained more Cl and no Br, while the parenchyma of reed straws contained higher Br. The C and O proportions of sorghum straws and reed straws are 50-53% (50-51%) and 45-46% (48-49%), respectively. These variations in elemental composition are believed to be correlated with the mechanical properties of the materials. By conducting a detailed study of the micro/macrostructures and material composition of sorghum and reed straw, this paper provides valuable insights for the field of biomechanics.

Bioinspired phosphorus-free and halogen-free biomass coatings for durable flame retardant modification of regenerated cellulose fibers.

Inspired by mussel adhesion and intrinsic flame retardant alginate fibers, a biomass flame retardant (PPCA) containing adhesive catechol and sodium carboxylate structure (-COO-Na+) based on biomass amino acids and protocatechualdehyde was designed to prepare flame retardant Lyocell fibers (Lyocell@PPCA@Na). Furthermore, through the substitution and chelation of metal ions by PPCA in the cellulose molecular chain, flame retardant Lyocell fibers chelating copper and iron ions (Lyocell@PPCA@Cu, Lyocell@PPCA@Fe) were prepared. Compared with the original sample, the peak heat release rate (PHRR) and total heat release (THR) for modified Lyocell fibers were significantly reduced. In addition, the modified sample exhibited a certain flame retardant durability. TG-FTIR analysis showed that the release of flammable gaseous substances was inhibited. The introduction of Schiff bases and aromatic structures in PPCA, as well as the decomposition of carboxylic metal salts were beneficial for the formation of char residue containing metal carbonates and metal oxides to play the condensed phase flame retardant effect. This work develops a new idea for the preparation of eco-friendly flame retardant Lyocell fibers without the traditional flame retardant elements such as P, Cl, and Br.

Selective ensemble method for anomaly detection based on parallel learning.

Anomaly detection is a highly important task in the field of data analysis. Traditional anomaly detection approaches often strongly depend on data size, structure and features, while introducing the idea of ensemble into anomaly detection can greatly improve the generalization ability. Ensemble-based anomaly detection methods still face some challenges, however, such as data imbalance, time and space demand and the selection of base detectors. To this end, we propose a selective ensemble method for anomaly detection based on parallel learning (SEAD-PL). First, a differentiated stratified sampling method is designed to alleviate the problem of data imbalance. Then, a distributed parallel training frame is built to address the problem of excessive time and space consumption for base detector training. Finally, a clustering-based ensemble selection strategy is introduced to balance the accuracy and diversity of base detectors. Experiments are performed on six datasets, which demonstrate that the proposed method has obvious advantages over four selected methods.

Manganese and IL-12 treatment alters the ovarian tumor microenvironment.

Metal immunotherapy is a novel adjuvant immunotherapy. Mn2+ can activate STING-a type I IFN response protein-that promotes innate immunity and increases anti-tumor activity by promoting macrophage phagocytosis. IL-12, a cytokine that increases the antigen-presenting ability to promote effector T-cell activation, has potent antitumor activity, albeit with severe adverse effects. In this study, we observed that the combination of Mn2+ and IL-12 has a better antitumor effect and possibly reflects a better safety profile, providing a novel approach and theoretical basis for safe and rapid cancer treatment.

An ensemble learning method with GAN-based sampling and consistency check for anomaly detection of imbalanced data streams with concept drift.

A challenge to many real-world data streams is imbalance with concept drift, which is one of the most critical tasks in anomaly detection. Learning nonstationary data streams for anomaly detection has been well studied in recent years. However, most of the researches assume that the class of data streams is relatively balanced. Only a few approaches tackle the joint issue of imbalance and concept drift. To overcome this joint issue, we propose an ensemble learning method with generative adversarial network-based sampling and consistency check (EGSCC) in this paper. First, we design a comprehensive anomaly detection framework that includes an oversampling module by generative adversarial network, an ensemble classifier, and a consistency check module. Next, we introduce double encoders into GAN to better capture the distribution characteristics of imbalanced data for oversampling. Then, we apply the stacking ensemble learning to deal with concept drift. Four base classifiers of SVM, KNN, DT and RF are used in the first layer, and LR is used as meta classifier in second layer. Last but not least, we take consistency check of the incremental instance and check set to determine whether it is anormal by statistical learning, instead of threshold-based method. And the validation set is dynamic updated according to the consistency check result. Finally, three artificial data sets obtained from Massive Online Analysis platform and two real data sets are used to verify the performance of the proposed method from four aspects: detection performance, parameter sensitivity, algorithm cost and anti-noise ability. Experimental results show that the proposed method has significant advantages in anomaly detection of imbalanced data streams with concept drift.

Identification of a PANoptosis-related Gene Signature for Predicting the Prognosis, Tumor Microenvironment and Therapy Response in Breast Cancer.

Breast cancer (BC) is the most prevalent malignancy among women worldwide. Mounting evidence suggests that PANoptosis participates in cancer development and therapy. However, the role of PANoptosis in BC remains unclear. In this study, we identified ten PANoptosis-related genes using Cox regression analysis, random forest (RF) algorithm and least absolute shrinkage and selection operator (LASSO) algorithm. A PANoptosis-related score (PRS) was calculated based on the coefficient of LASSO. Notably, we divided the patients into high- and low-risk groups according to the PRS and revealed a negative correlation between PRS and overall survival. Next, a nomogram model was constructed and validated to improve the clinical application of PRS. Functional enrichment analyses and the Bayesian network demonstrated that differentially expressed genes between high- and low-risk groups were mainly enriched in immune-related pathways. Besides, we found significant differences in tumor mutation burden and tumor immune microenvironment between patients in these two groups using bulk-RNA and single-cell RNA sequencing data. Furthermore, charged multivesicular body protein 2B (CHMP2B) was identified as the hub gene by combining LASSO, weighted gene co-expression network analysis, RF and eXtreme Gradient Boosting. Importantly, using immunohistochemistry analysis based on our tissue microarray, we found that CHMP2B was highly expressed in tumor tissue, and CD4 and CD8 were more likely to be positive in the CHMP2B-negative group. Survival analyses revealed that CHMP2B adversely impacted the survival of BC patients. In conclusion, we not only constructed a highly accurate predictive model based on PRS, but also revealed the importance of PANoptosis-related gene signature in the modulation of the tumor microenvironment and drug sensitivity in BC.

Downhill running and caloric restriction attenuate insulin resistance associated skeletal muscle atrophy via the promotion of M2-like macrophages through TRIB3-AKT pathway.

BACKGROUD: Downhill running has recently become a promising exercise modality for metabolic syndrome, but the effect and precise mechanism of downhill running training on insulin resistance (IR) induced skeletal muscle atrophy remains unclear. The current study aimed to explore the benefits of downhill running training accompanied by a low-fat diet on skeletal muscle atrophy in IR mice and its possible mechanisms. METHODS: For in vivo study, high fat diet (HFD) -induced IR mice were submitted to the downhill running training or/and caloric restriction for 8 weeks. In vitro study was performed using co-cultured RAW264.7 macrophages and C2C12 myoblasts model. Glucose tolerance test (GTT), insulin tolerance test (ITT), immunofluorescence staining, Western blot analysis, hematoxylin and eosin (H&E) staining, enzyme-linked immunosorbent assay (ELISA), Cell counting kit-8 (CCK-8) assays and glucose uptake assays were employed to explore the benefits and possible mechanisms of downhill running training accompanied by a low-fat diet on IR mice. RESULTS: Our data revealed that HFD induces IR, which leading to skeletal muscle atrophy. Downhill running accompanied by caloric restriction mitigated HFD-induced IR and improve skeletal muscle atrophy. Further study suggested that descended TRIB3 mediated the favorable impact of downhill running on IR induced skeletal muscle atrophy by suppressing M1-like macrophages and promoting M2-like macrophages. Macrophages-specific knockdown of TRIB3 exerted similar effects on the macrophage polarization and IR related myogenesis to downhill running training accompanied by caloric restriction. In contrast, macrophages-specific overexpression of TRIB3 descended phosphorylation of AKT, further activated M1-like macrophages and aggravated IR related inhibition of myogenesis. CONCLUSIONS: This finding demonstrated the beneficial effects of downhill running training and caloric restriction on IR related skeletal muscle atrophy by promoting M2-like macrophages through TRIB3-AKT pathway.

In-bag extraction of tissue through an incision in the posterior vaginal wall in laparoscopic myomectomy: a large retrospective study.

BACKGROUND: Our purpose was to describe the outcomes of transvaginal in-bag tissue extraction tissue through an incision in the posterior vaginal wall the middle part incision of posterior vagina in laparoscopic myomectomy. METHODS: This was a retrospective study of patients who received laparoscopic myomectomy and in-bag tissue extraction through an incision in the posterior vaginal wall between January 2016 and December 2022. Patient characteristics, intra- and post-operative complications, and outcomes were collected and analyzed. RESULTS: A total of 511women were included in the analysis. The mean largest myoma diameter was 8.44 ± 3.56 cm; mean specimen weight was 789.23 ± 276.97 g; mean operative time was 129.01 ± 53.13minutes; and mean blood loss was 175.99 ± 210.96 mL. Within 30-days of surgery, no fever, infection, or vaginal bleeding was noted in any patient, and the vaginal incisions of all patients had healed well. There were no incisional hernias, pelvic infections, and vaginal adhesions noted at follow-up 3 months after the operation. There were 37 cases of vaginal delivery of the patients after surgery, and there were no lacerations of the posterior wall vaginal incision. CONCLUSIONS: Transvaginal in-bag extraction though an incision in the posterior vaginal wall is feasible and safe for removing tissue after laparoscopic myomectomy.

miR-9-5p deficiency contributes to schizophrenia.

MicroRNA-9-5p (miR-9-5p) is highly expressed in the brain and has been implicated in the risk of schizophrenia. We compared the expression levels of miR-9-5p in schizophrenia cases and healthy controls and evaluated whether regulatory targets of miR-9-5p are enriched in schizophrenia genome-wide risk genes. Literature-based analysis was conducted to construct molecular pathways connecting miR-9-5p and schizophrenia. We found that the expression levels of miR-9-5p were down-regulated in the peripheral blood of schizophrenia patients compared with those in healthy controls. miR-9-5p can regulate 24 out of the 1136 genome-wide risk genes of schizophrenia, which was higher than by chance (hypergeometric test P = 4.09E-06). The literature-based analysis showed that quantitative genetic changes driven by miR-9 exert more inhibitory (the IL1B, ABCB1, FGFR1 genes) than promoting (the INS gene) effects on schizophrenia, suggesting that miR-9 may protect against schizophrenia. Our results suggest that miR-9-5p deficiency may contribute to the development of schizophrenia.

Dexmedetomidine alleviates renal tubular ferroptosis in sepsis-associated AKI by KEAP1 regulating the degradation of GPX4.

Sepsis-associated acute kidney injury (SA-AKI) has a high mortality rate and lacks effective targeted treatment. We applied lipopolysaccharides-induced injury models in human and mouse renal tubular epithelial cells, and at the same time, we selected a commonly used sedative drug, dexmedetomidine, to investigate its potential for renal protection. We found a significant increase in the expression level of HSP90, and the interaction with glutathione peroxidase 4 (GPX4) led to autophagic degradation of GPX4, triggering ferroptosis. Dexmedetomidine reduced the degradation of GPX4 by increasing the binding of KEAP1 and HSP90 in the cytoplasm. Therefore, lipid peroxidation and ferroptosis were reduced. Similarly, dexmedetomidine showed renal protective effects in C57BL/6J male mice with SA-AKI induced by cecal ligation. Our study reveals a new mechanism of renal tubular epithelial cell ferroptosis in SA-AKI treated with dexmedetomidine.

Aberrant degree centrality profiles during rumination in major depressive disorder.

Rumination is closely linked to the onset and maintenance of major depressive disorder (MDD). Prior neuroimaging studies have identified the association between self-reported rumination trait and the functional coupling among a network of brain regions using resting-state functional magnetic resonance imaging (MRI). However, little is known about the underlying neural circuitry mechanism during active rumination in MDD. Degree centrality (DC) is a simple metric to denote network integration, which is critical for higher-order psychological processes such as rumination. During an MRI scan, individuals with MDD (N = 45) and healthy controls (HC, N = 46) completed a rumination state task. We examined the interaction effect between the group (MDD vs. HC) and condition (rumination vs. distraction) on vertex-wise DC. We further characterized the identified brain region's functional involvement with Neurosynth and BrainMap. Network-wise seed-based functional connectivity (FC) analysis was also conducted for the identified region of interest. Finally, exploratory correlation analysis was conducted between the identified region of interest's network FCs and self-reported in-scanner affect levels. We found that a left superior frontal gyrus (SFG) region, generally overlapped with the frontal eye field, showed a significant interaction effect. Further analysis revealed its involvement with executive functions. FCs between this region, the frontoparietal, and the dorsal attention network (DAN) also showed significant interaction effects. Furthermore, its FC to DAN during distraction showed a marginally significant negative association with in-scanner affect level at the baseline. Our results implicated an essential role of the left SFG in the rumination's underlying neural circuitry mechanism in MDD and provided novel evidence for the conceptualization of rumination in terms of impaired executive control.

An evaluation of cervical maturity for Chinese women with labor induction by machine learning and ultrasound images.

BACKGROUND: To evaluate the improvement of evaluation accuracy of cervical maturity for Chinese women with labor induction by adding objective ultrasound data and machine learning models to the existing traditional Bishop method. METHODS: The machine learning model was trained and tested using 101 sets of data from pregnant women who were examined and had their delivery in Peking University Third Hospital in between December 2019 and January 2021. The inputs of the model included cervical length, Bishop score, angle, age, induced labor time, measurement time (MT), measurement time to induced labor time (MTILT), method of induced labor, and primiparity/multiparity. The output of the model is the predicted time from induced labor to labor. Our experiments analyzed the effectiveness of three machine learning models: XGBoost, CatBoost and RF(Random forest). we consider the root-mean-squared error (RMSE) and the mean absolute error (MAE) as the criterion to evaluate the accuracy of the model. Difference was compared using t-test on RMSE between the machine learning model and the traditional Bishop score. RESULTS: The mean absolute error of the prediction result of Bishop scoring method was 19.45 h, and the RMSE was 24.56 h. The prediction error of machine learning model was lower than the Bishop score method. Among the three machine learning models, the MAE of the model with the best prediction effect was 13.49 h and the RMSE was 16.98 h. After selection of feature the prediction accuracy of the XGBoost and RF was slightly improved. After feature selection and artificially removing the Bishop score, the prediction accuracy of the three models decreased slightly. The best model was XGBoost (p = 0.0017). The p-value of the other two models was < 0.01. CONCLUSION: In the evaluation of cervical maturity, the results of machine learning method are more objective and significantly accurate compared with the traditional Bishop scoring method. The machine learning method is a better predictor of cervical maturity than the traditional Bishop method.

Characteristics of Shisa Family Genes in Zebrafish.

Shisa represents a type of single-transmembrane adaptor protein containing an N-terminal cysteine-rich domain and a proline-rich C-terminal region. Nine shisa subfamily genes have been proposed in most vertebrates; however, some might be species-specific. The number of shisa genes present in zebrafish remains unclear. This study aimed to investigate the evolutionary relationships among shisa family genes in zebrafish (TU strain) using phylogenetic and syntenic analyses. The function of shisa-2 was preliminarily examined via CRISPR/Cas13d-mediated knockdown. Following identification in zebrafish, 10 shisa family genes, namely shisa-1, 2, 3, 4, 5, 6, 7, 8, 9a, and 9b, were classified into three main clades and six subclades. Their encoding proteins contained a cysteine-rich N-terminal domain and a proline-rich C-terminal region containing different motifs. A specific syntenic block containing atp8a2 and shisa-2 was observed to be conserved across all species. Furthermore, all these genes were expressed during embryogenesis. Shisa-2 was expressed in the presomitic mesoderm, somites, and so on. Shisa-2 was identified as a regulator of the expression of the somite formation marker mesp-ab. Overall, our study provides new insights into the evolution of shisa family genes and the control of shisa-2 over the convergent extension cells of somitic precursors in zebrafish.

Multivariate classification based on large-scale brain networks during early abstinence predicted lapse among male detoxified alcohol-dependent patients.

Identifying biomarkers to predict lapse of alcohol-dependence (AD) is essential for treatment and prevention strategies, but remains remarkably challenging. With an aim to identify neuroimaging features for predicting AD lapse, 66 male AD patients during early-abstinence (baseline) after hospitalized detoxification underwent resting-state functional magnetic resonance imaging and were then followed-up for 6 months. The relevance-vector-machine (RVM) analysis on baseline large-scale brain networks yielded an elegant model for differentiating relapsing patients (n = 38) from abstainers, with the area under the curve of 0.912 and the accuracy by leave-one-out cross-validation of 0.833. This model captured key information about neuro-connectome biomarkers for predicting AD lapse.

Isolation of a newly Trichoderma asperellum LYS1 with abundant cellulase-hemicellulase enzyme cocktail for lignocellulosic biomass degradation.

As the most abundant and renewable natural resource in the world, lignocellulose is a promising alternative to fossil energy to relieve environmental concerns and resource depletion. However, due to its recalcitrant structure, strains with efficient degradation capability still need exploring. In this study, a fungus was successfully isolated from decayed wood and named as Trichoderma asperellum LYS1 by phylogenetic and draft genomic analysis. The further investigations showed that strain LYS1 had an outstanding performance on lignocellulose degradation, especially for hemicellulose-rich biomass. After the analysis of encoded CAZymes, mainly on GH family, a large amount of genes coding ß-glucosidase and xylanase may contribute to the high degradation of cellulose and hemicellulose. Collectively, the results generated in this study demonstrated that T. asperellum LYS1 is a potential cell factory for lignocellulose biorefinery.