Search

The abandoned carbonaceous mudstone has caused severe environmental problems such as land occupation and landslides. For the consideration of economic and ecological factors, carbonaceous mudstone soil-rock mixture (CMSRM) is used as an embankment material assessed by California bearing ratio (CBR) and unconfined compression strength (UCS). A series of experiments were conducted to measure the CBR and UCS of the CMSRM with different wet-dry cycles (0, 2, 4, 6 and 8) and different rock contents (0, 20, 40, 60 and 80%). The experimental results were predicted and analysed by a convolutional neural network (CNN). The experiment results show that the CBR and UCS of CMSRM increased at first and then decreased with the increase of rock content and were negatively correlated with wet-dry cycles. The CNN predicted values were highly correlated with the measured values. The CNN model enables variable parameter analysis of the experiment results via deep learning, which provides a new method to the CMSRM embankment road performance prediction.

The paper aims to study the mechanical characteristics of disintegrated carbonaceous mudstone in a triaxial stress state from a micro-perspective of particles. Based on the discrete element method (DEM), a spherical-polymer (SP) model that includes three different types of the particles (triangle-like, rectangle-like, and sphere) was proposed and combined the error diagram with R2to analyze the difference between the SP model and Ball–Ball (BB) model. Meanwhile, a sensitive analysis of micro-mechanical characteristics was carried out, which quantitatively described the sensitivity of different parameters according to stress–strain curves. The processes of deformation and failure for the disintegrated carbonaceous mudstone were finally analyzed based on the displacement diagram of the particle according to the energy theory. The results suggest that the SP model could better reflect the mechanical characteristics of disintegrated carbonaceous mudstone, for the SP models, the correlation coefficient (R2) range was larger than the BB model. From the sensitivity analysis of parameters, the decreasing rate of initial deformation modulus was 56–66% as the stiffness ratio was modified when fixing other factors. The peak strength correlated well with the tensile-shear strength ratio, stiffness ratio, and friction coefficient. The modification of abnormal-shaped particles’ volume fraction ratio could affect the peak shear strength significantly. For the disintegrated carbonaceous mudstone, the processes of deformation and failure were discussed by energy transference which particle elements go from a low-energy state to a high-energy state.

This paper explores the parallel collaboration of multimodal physiological signals, combining eye tracker output signals, motor imagery, and error-related potentials to control a computer mouse. Specifically, a parallel working mechanism is implemented in the decision layer, where the eye tracker manages cursor movements, and motor imagery manages click functions. Meanwhile, the eye tracker output signals are integrated with electroencephalography data to detect the idle state for asynchronous control. Additionally, error-related potentials evoked by visual feedback, are detected to reduce the cost of error corrections. To efficiently collect data and provide continuous evaluations, we performed offline training and online testing in the designed paradigm. To further validate the practicability, we conducted online experiments on the real-world computer, focusing on a scenario of opening and closing files. The experiments involved seventeen subjects. The results showed that the stability of the eye tracker was optimized from 67.6% to 95.2% by the designed filter, providing the support for parallel control. The accuracy of motor imagery conducted simultaneously with fixations reached 93.41 ± 2.91%, proving the feasibility of parallel control. Furthermore, the real-world experiments took 45.86 ± 14.94 s to complete three movements and clicks, and showed a significant improvement compared to the baseline experiment without automatic error correction, validating the practicability of the system and the efficacy of error-related potentials detection. Moreover, this system freed users from the stimulus paradigm, enabling a more natural interaction. To sum up, the parallel collaboration of multimodal physiological signals is novel and feasible, the designed mouse is practical and promising.

Federated learning has shown its unique advantages in many different tasks, including brain image analysis. It provides a new way to train deep learning models while protecting the privacy of medical image data from multiple sites. However, previous studies suggest that domain shift across different sites may influence the performance of federated models. As a solution, we propose a gradient matching federated domain adaptation (GM-FedDA) method for brain image classification, aiming to reduce domain discrepancy with the assistance of a public image dataset and train robust local federated models for target sites. It mainly includes two stages: 1) pretraining stage; we propose a one-common-source adversarial domain adaptation (OCS-ADA) strategy, i.e., adopting ADA with gradient matching loss to pretrain encoders for reducing domain shift at each target site (private data) with the assistance of a common source domain (public data) and 2) fine-tuning stage; we develop a gradient matching federated (GM-Fed) fine-tuning method for updating local federated models pretrained with the OCS-ADA strategy, i.e., pushing the optimization direction of a local federated model toward its specific local minimum by minimizing gradient matching loss between sites. Using fully connected networks as local models, we validate our method with the diagnostic classification tasks of schizophrenia and major depressive disorder based on multisite resting-state functional MRI (fMRI), respectively. Results show that the proposed GM-FedDA method outperforms other commonly used methods, suggesting the potential of our method in brain imaging analysis and other fields, which need to utilize multisite data while preserving data privacy.

Two suites of mafic dykes, T1193-A and T1194-A, outcrop in Gyangze area, southeast Tibet. They are in the area of Comei LIP and have indistinguishable field occurrences with two other dykes in Gyangze, T0902 dyke with 137.7±1.3 Ma zircon age and T0907 dyke with 142±1.4 Ma zircon age reported by Wang YY et al. (2016), indicating coeval formation time. Taking all the four diabase dykes into consideration, two different types, OIB-type and weak enriched-type, can be summarized. The “OIB-type” samples, including T1193-A and T0907 dykes, show OIB-like geochemical features and have initial Sr-Nd isotopic values similar with most mafic products in Comei Large Igneous Provinces (LIP), suggesting that they represent melts directly generated from the Kerguelen mantle plume. The “weak enriched-type ” samples, including T1194-A and T0902 dykes, have REEs and trace element patterns showing within-plate affinity but have obvious Nb-Ta-Ti negative anomalies. They show uniform lower εNd(t) values (–6––2) and higher 87Sr/86Sr(t) values (0.706–0.709) independent of their MgO variation, indicating one enriched mantle source. Considering their closely spatial and temporal relationship with the widespread Comei LIP magmatic products in Tethyan Himalaya, these “weak enriched-type” samples are consistent with mixing of melts from mantle plume and the above ancient Tethyan Himalaya subcontinental lithospheric mantle (SCLM) in different proportions. These weak enriched mafic rocks in Comei LIP form one special rock group and most likely suggest large scale hot mantle plume-continental lithosphere interaction. This process may lead to strong modification of the Tethyan Himalaya lithosphere in the Early Cretaceous.

Previous studies have explored the use of deep neural networks for electroencephalography (EEG)-based motor imagery (MI) recognition, but most of the models focus on the recognition performance achieved for a single subject and are challenging to transfer due to individual differences and low signal-to-noise-ratio of EEG signals. To date, few studies have paid attention to the balance between generalizability and personalization across subjects. To this end, we propose a co-teaching graph learning method for cross-subject EEG-based MI recognition. First, A novel graph learning approach is designed to improve feature extraction from a typical graph structure containing raw EEG signals. Second, two graph learning models are constructed to filter noisy data by using a co-teaching training strategy, preventing overfitting on noisy samples obtained from different subjects. The proposed model shows a 5.4% and 3.2% increase in accuracy of single- and multisubject four-class MI recognition tasks compared to the previous best method, respectively. Experimental results also demonstrate that it is easy to derive a model that can represent generic knowledge of multiple MI subjects and can be fine-tuned efficiently for new subjects.

Tension crack zones may occur at the surface, particularly the crest, of soil slopes for various reasons. The presence of tension crack zones will provide preferential channels for water flow and considerably reduce slope stability under rainfall infiltration. This study aims to examine the influence of tension crack zones on the seepage and stability characteristics of soil slopes. To this end, the numerical model of a lateritic soil slope containing a tension crack zone of various distribution parameters (i.e., density, location, depth, and angle) is created. Then, physical model tests are conducted to validate the numerical model. Finally, the evolution of seepage characteristics and safety factors of the cracked lateritic soil slope is analyzed considering rainfall infiltration. The results indicate that neglecting the crack zone or replacing the crack zone with a single crack will overestimate the safety factor by 0.15–0.23 and 0.06–0.08, respectively. Generally, a greater crack density or crack zone depth causes a larger transient saturated zone (TSZ), while a larger crack zone angle often leads to a smaller TSZ. The formation of TSZ obviously reduces the safety factor of the soil slope. Among the examined crack parameters, the crack zone depth has the most significant influence on both the TSZ and safety factor. Thus, the development of deep crack zones must be strictly restrained to ensure the long-term stability of lateritic soil slopes.

AbstractCarbonaceous mudstone aggregates are prone to disintegrate to produce alkaline hydrosols under dry and wet cycles, which affects the planting performance of vegetation concrete (VC). To improve the planting performance of carbonaceous mudstone aggregate vegetation concrete (CMAVC), while considering the soaking time and concentration are the main factors influencing the effect of pH-reducing, pH reduction and performance improvement tests, uniaxial compressive tests under different soaking time and concentration were carried out, and verified by the vegetation tests and microscopic tests. The results show that ferrous sulfate and oxalic acid reduced the pH of CMAVC effectively; 0.9 mol/L ferrous sulfate and 1.2 mol/L oxalic acid are the best ratio of pH-reducing materials to ensure that the compressive strength of CMAVC is more than 5 MPa (require by the specification), which the pH values reduced by 20.4% and 29%, respectively, and after soaking 28d, the uniaxial compressive strength reduced by 9.2% from 5.64 to 5.12 Mpa and 5.7% from 5.64 to 5.32 Mpa; Moreover, the reaction of oxalic acid with calcium hydroxide, calcium carbonate, and calcium alumina produces calcium oxalate stone, which fills the internal pores of CMAVC to ensure the excellent mechanical strength and planting effect.

Previous studies have made great efforts to expand the instruction set in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces. However, most systems are limited to single persons and expand the instruction set by increasing the flicker stimulation frequency range or via multiple frequencies sequential coding or joint frequency/phase coding. In this article, we propose a multibrain coding SSVEP paradigm that encodes the SSVEP instructions generated by N independent subjects with M flicker stimuli, thus increasing the instruction set to MN instructions. A total of 40 subjects participated in online experiments in this article. The results show that there is no significant difference in accuracy (p > 0.05, paired t test) between the multibrain and single-brain coding systems, while the information transfer rate (ITR) increases significantly (p < 0.0001, paired t test), with the ITR increasing from 37.66 ± 3.60 bits/min for the single-brain coding system to 111.65 ± 10.84 bits/min for multibrain coding system when N = 3 and M = 5. In summary, the proposed multibrain coding paradigm exponentially increases the number of instructions without increasing the output instruction time, which is of great significance to the application and promotion of BCIs.

Insufficient annotated data and minor lung lesions pose big challenges for computed tomography (CT)-aided automatic COVID-19 diagnosis at an early outbreak stage. To address this issue, we propose a Semi-Supervised Tri-Branch Network (SS-TBN). First, we develop a joint TBN model for dual-task application scenarios of image segmentation and classification such as CT-based COVID-19 diagnosis, in which pixel-level lesion segmentation and slice-level infection classification branches are simultaneously trained via lesion attention, and individual-level diagnosis branch aggregates slice-level outputs for COVID-19 screening. Second, we propose a novel hybrid semi-supervised learning method to make full use of unlabeled data, combining a new double-threshold pseudo labeling method specifically designed to the joint model and a new inter-slice consistency regularization method specifically tailored to CT images. Besides two publicly available external datasets, we collect internal and our own external datasets including 210,395 images (1,420 cases versus 498 controls) from ten hospitals. Experimental results show that the proposed method achieves state-of-the-art performance in COVID-19 classification with limited annotated data even if lesions are subtle, and that segmentation results promote interpretability for diagnosis, suggesting the potential of the SS-TBN in early screening in insufficient labeled data situations at the early stage of a pandemic outbreak like COVID-19.

In many dynamic environment applications, with the evolution of data collection ways, the data attributes are incremental and the samples are stored with accumulated feature spaces gradually. For instance, in the neuroimaging-based diagnosis of neuropsychiatric disorders, with emerging of diverse testing ways, we get more brain image features over time. The accumulation of different types of features will unavoidably bring difficulties in manipulating the high-dimensional data. It is challenging to design an algorithm to select valuable features in this feature incremental scenario. To address this important but rarely studied problem, we propose a novel Adaptive Feature Selection method (AFS). It enables the reusability of the feature selection model trained on previous features and adapts it to fit the feature selection requirements on all features automatically. Besides, an ideal $\ell _{0}$ℓ0-norm sparse constraint for feature selection is imposed with a proposed effective solving strategy. We present the theoretical analyses about the generalization bound and convergence behavior. After tackling this problem in a one-shot case, we extend it to the multi-shot scenario. Plenty of experimental results demonstrate the effectiveness of reusing previous features and the superior of $\ell _{0}$ℓ0-norm constraint in various aspects, together with its effectiveness in discriminating schizophrenic patients from healthy controls.

Conventional chemotherapy usually fails to achieve its intended effect because of the poor water solubility, poor tumor selectivity, and low tumor accumulation of chemotherapy drugs. The systemic toxicity of chemotherapy agents is also a problem that cannot be ignored. It is expected that smart nano-drug delivery systems that are able to respond to tumor microenvironments will provide better therapeutic outcomes with decreased side effects of chemotherapeutics. Nano-drug delivery systems capable of breaking the redox balance can also increase the sensitivity of tumor cells to chemotherapeutics. In this study, using polymer-containing disulfide bonds, ester bonds, and d-α-tocopherol polyethylene glycol succinate (TPGS), which can amplify reactive oxygen species (ROS) in tumor cells, we have successfully prepared a smart glutathione (GSH) and esterase dual-responsive nano-drug delivery system (DTX@PAMBE-SS-TPGS NPs) with the ability to deplete GSH as well as amplify ROS and effectively release an encapsulated chemotherapy drug (DTX) in tumor cells. The potential of DTX@PAMBE-SS-TPGS NPs for enhanced antitumor effects was thoroughly evaluated using in vitro as well as in vivo experiments. Our research offers a promising strategy for maximizing the efficacy of tumor therapy.

With good mobility and flexibility, mobile manipulators have shown broad applications in construction scenarios. Base position (BP) planning, which refers to the robot autonomously determining its working station in the environment, is an important technique for mobile manipulators when performing the construction assembly task, especially in a large-scale construction environment. However, the BP planning process is tedious and time-consuming for a human worker to carry out. Thus, to improve the efficiency of construction assembly tasks, a novel BP planning method is proposed in this paper, which can lead to appropriate BPs and minimize the number of BPs at the same time. Firstly, the feasible BP regions are generated based on the grid division and the variable workspace of the mobile manipulator. Then, the positioning uncertainties of the mobile manipulator are considered in calculating the preferred BP areas using clustering. Lastly, a set coverage optimization model is established to obtain the minimum number of BPs using an optimization algorithm according to the greedy principle. The simulated experiment based on a 9-degree of free (DoF) mobile manipulator has been performed. The results illustrated that the time for BP planning was significantly reduced and the number of BPs was reduced by 63.41% compared to existing manual planning, which demonstrated the effectiveness of the proposed method.

Cognitive load prediction is one of the most important issues in the nascent field of neuroergonomics, and it has significant value in real-world applications. Most of the previous studies of cognitive load prediction only utilized electroencephalography (EEG)-based spectral signatures or interchannel connectivity, ignoring abundant temporal microstate features, which may represent the transient topologies of EEG signals. Furthermore, previous studies have mostly focused on the binary-level classification of cognitive load for single-type cognitive tasks. To date, there are few studies on the multilevel prediction of cognitive load during mixed cognitive tasks. Here, we first designed a new paradigm termed the “finding fault game,” mixing multiple tasks of memory, counting, and visual search, and then developed a multidimensional analysis framework to improve cognitive load prediction using a fusion of spatial, temporal, and spectral EEG features. Specifically, EEG-based functional connectivity, microstates and power spectral densities (PSD) were calculated for three cognitive load levels. Twelve adult subjects participated in the study. The experimental results show that increased cognitive load was associated with elevated theta and degraded alpha power and significant changes in interchannel connectivity and microstates, and that fusing the three types of EEG features improved the performance of three-level cognitive load prediction, achieving the accuracies of greater than 80% in the cross-validation, real-time, and over-time prediction. The findings suggest that all three types of EEG features can serve as signatures of cognitive load and that their fusion can improve multilevel prediction.

ObjectivesThe primary aim was to evaluate risk factors for surgical site infections after anterior cruciate ligament reconstruction (ACLR). The secondary aim was to investigate the surgical site infection incidence rate and the mean time to postoperative surgical site infection symptoms.DesignSystematic review and meta-analysis.Data sourcesPubMed, Embase and Web of Science were searched from database inception to September 2021 and updated in April 2022.Eligibility criteriaQuantitative, original studies reporting potential risk factors for surgical site infections after ACLR were included.ResultsTwenty-three studies with 3871 infection events from 469 441 ACLRs met the inclusion criteria. Male sex (OR 1.78, p< 0.00001), obesity (OR 1.82, p=0.0005), tobacco use (OR 1.37, p=0.01), diabetes mellitus (OR 3.40, p=0.002), steroid use history (OR 4.80, p<0.00001), previous knee surgery history (OR 3.63, p=0.02), professional athlete (OR 4.56, p=0.02), revision surgery (OR 2.05, p=0.04), hamstring autografts (OR 2.83, p<0.00001), concomitant lateral extra-articular tenodesis (OR 3.92, p=0.0001) and a long operating time (weighted mean difference 8.12, p=0.005) were identified as factors that increased the risk of surgical site infections (superficial and deep) after ACLR. Age, outpatient or inpatient surgery, bone-patellar tendon-bone autografts or allografts and a concomitant meniscus suture did not increase the risk of surgical site infections. The incidence of surgical site infections after ACLR was approximately 1% (95% CI 0.7% to 1.2%). The mean time from surgery to the onset of surgical site infection symptoms was approximately 17.1 days (95% CI 13.2 to 21.0 days).ConclusionMale sex, obesity, tobacco use, diabetes mellitus, steroid use history, previous knee surgery history, professional athletes, revision surgery, hamstring autografts, concomitant lateral extra-articular tenodesis and a long operation time may increase the risk of surgical site infections after ACLR. Although the risk of surgical site infections after ACLR is low, raising awareness and implementing effective preventions for risk factors are priorities for clinicians to reduce the incidence of surgical site infections due to its seriousness.

Citrinsorbicillin A (1), a novel homotrimeric sorbicillinoid, along with two new monomers citrinsorbicillins B (2) and C (3), were isolated from the Coptis chinensisendophyte Trichoderma citrinovirideHT-9 by liquid chromatograph mass spectrometer (LC-MS)-guided strategy. 1was the first trimeric-example from terrestrial fungi, which possessed a unique carbon skeleton with two bicyclo[2.2.2]octanedione ring connected through an enolated carbon forming by [4 + 2] cycloaddition. Their structures were elucidated by spectroscopic analysis and X-ray diffraction. 1exhibited moderate cytotoxicity against human colon cancer HT29 cells, and it induced significant cell cycle arrest by reducing the protein expression of cyclin D1.

Sepsis, defined as life-threatening organ failure caused by a dysregulated host response to severe infection, is a major cause of death among intensive care unit patients. Therapies targeting on immunomodulatory is a new research field in sepsis treatment. B- and T-lymphocyte attenuator (BTLA) is an inhibitory costimulatory factor molecule of B and T lymphocytes. Studies have shown that elevated expression of BTLA in lymphocytes can reduce mortality in sepsis, but its regulatory compounds and the underlying mechanism remains to be elucidated. Here, we show that treatment with CP-673451 significantly decreases mortality of septic mouse. CP-673451 is a PDGFR kinase inhibitor which can promote the expression of BTLA, inhibit the release of chemokines such as CXCL13, and reduce first the chemotaxis of B cells to the peripheral blood and vital organs. CP-673451 also inhibits both the release of cytokines and chemokines such as IL-1β, IL-6, IL-10, TNF-α, CCL1, CCL2 and CCL7 and reduces both the chemotactic ability of T cells. This suggests that CP-673451 may prevent septic death by inhibiting lymphocyte chemotaxis and alleviating “cytokine storm”. In conclusion, our study provides a new therapeutic target and an effective compound for sepsis treatment.

ABSTRACTFerroptosis is a form of inflammatory cell death for which key mediators remain obscure. Here, we report that the proteoglycan decorin (DCN) is released by cells that are dying from ferroptosis and then acts as an alarm signal to trigger innate and adaptive immune responses. The early release of DCN during ferroptosis is an active process that involves secretory macroautophagy/autophagy and lysosomal exocytosis. Once released, extracellular DCN binds to the receptor advanced glycosylation end-product-specific receptor (AGER) on macrophages to trigger the production of pro-inflammatory cytokines in an NFKB/NF-κB-dependent manner. Pharmacological and genetic inhibition of the DCN-AGER axis protects against ferroptotic death-related acute pancreatitis and limits the capacity of ferroptotic cancer cells to induce a tumor-protective immune response. Thus, DCN is an essential mediator of the inflammatory and immune consequences of ferroptosis.

Considering the adverse effects of nonsteroidal anti-inflammatory drugs (NSAIDs) and opioids for treating osteoarthritis (OA), development of drugs that are more effective and better tolerated than existing treatments is urgently needed. This systematic review aimed to evaluate the efficacy and safety of anti-nerve growth factor (NGF) monoclonal antibodies vs active comparator therapy, such as NSAIDs and oxycodone, in treating hip or knee OA.Databases were comprehensively searched for randomized controlled trials (RCTs) published before January 2022. Efficacy and safety outcomes were assessed.Six RCTs that included 4325 patients were identified. Almost all the RCTs indicated that moderate doses of anti-NGF monoclonal antibody treatment significantly improved efficacy outcomes based on the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain score, the WOMAC physical function score and the Patient’s Global Assessment compared with those of the active comparator. At least half of the RCTs indicated that the incidence of severe adverse events, withdrawals due to adverse events (AEs) and total joint replacement were not significantly different between anti-NGF monoclonal antibody treatment and active comparator therapy, but the outcomes of some studies may have been limited by a short duration of follow-up. Most RCTs suggested that anti-NGF monoclonal antibody treatment had a lower incidence of gastrointestinal and cardiovascular AEs. However, the majority of RCTs reported a higher incidence of abnormal peripheral sensation with anti-NGF monoclonal antibody treatment. Furthermore, the higher incidence of rapidly progressive osteoarthritis (RPOA) with anti-NGF monoclonal antibody treatment should also not be overlooked, and the identification of patient characteristics that increase the risk of RPOA is critical in further studies.Based on the current research evidence, anti-NGF monoclonal antibodies are not yet a replacement for analgesic drugs such as NSAIDs but might be a new treatment option for hip or knee OA patients who are intolerant or unresponsive to nonopioid or opioid treatment. Notably, however, considering the inconsistency and inconclusive evidence on the safety outcomes of recent studies, more research is needed, and long-term follow-up is required.

Two new metal-organic compounds (MOCs) [Cu(L)0.5(3-nba)2] (1) and [Cu(L)(2,5-tdc)] (2) have been hydrothermally synthesized by employing the ligand N,N′-di(3-pyridyl)adipoamide (L) and two carboxylic acids (3-Hnba = 3-nitrobenzoic acid, 2,5-H2tdc = 2,5-thiophenedicarboxylic acid) as ligands. Compound 1displays a metal-organic chain-like structure formed by the {Cu2(3-nba)4} double-paddle wheel units and the µ2-bridging L ligands. The adjacent polymeric chains form a supramolecular layered structure through hydrogen bonding. Compound 2shows a 3D metal-organic polymeric framework derived from Cu-L layers and µ2-bridging 2,5-tdc ligands, which presents a 3,5-connected {4.62}{4.66.83} topology. The electrochemical and electrocatalytic behavior of the two compounds has been studied in detail. Carbon paste working electrodes modified with compounds 1and 2can be used as highly selective sensors for detecting traces Cr(VI). Both electrodes show also electrocatalytic performance in oxygen evolution reactions (OERs).

Immunosuppression in response to severe sepsis remains a serious human health concern. Evidence of sepsis-induced immunosuppression includes impaired T lymphocyte function, T lymphocyte depletion or exhaustion, increased susceptibility to opportunistic nosocomial infection, and imbalanced cytokine secretion. CD4 T cells play a critical role in cellular and humoral immune responses during sepsis. Here, using an RNA sequencing assay, we found that the expression of T cell-containing immunoglobulin and mucin domain-3 (Tim-3) on CD4 T cells in sepsis-induced immunosuppression patients was significantly elevated. Furthermore, the percentage of Tim-3+CD4 T cells from sepsis patients was correlated with the mortality of sepsis-induced immunosuppression. Conditional deletion of Tim-3 in CD4 T cells and systemic Tim-3 deletion both reduced mortality in response to sepsis in mice by preserving organ function. Tim-3+CD4 T cells exhibited reduced proliferative ability and elevated expression of inhibitory markers compared with Tim-3−CD4 T cells. Colocalization analyses indicated that HMGB1 was a ligand that binds to Tim-3 on CD4 T cells and that its binding inhibited the NF-κB signaling pathway in Tim-3+CD4 T cells during sepsis-induced immunosuppression. Together, our findings reveal the mechanism of Tim-3 in regulating sepsis-induced immunosuppression and provide a novel therapeutic target for this condition.

The natriuretic peptide family (NPs) is a group of natural endocrine hormones, containing a 17-amino acid ring structure connected by disulfide bonds of two cysteines. In this review, the members of the natriuretic peptide family and their corresponding receptors as well as the anti-cancer effects are introduced. Four cardiac hormones of NPs (ANP, VD, KP and LANP) can effectively inhibit the growth of human small cell lung cancer, breast cancer and other tumors and significantly reduce tumor volume in vivo. The in vitroexperiments also show that cardiac hormones, CNP and urodilatin can effectively inhibit the growth of most tumor cells. We then further summarized the anti-cancer mechanism of natriuretic peptides. Finally, we introduce several methods that modify natriuretic peptides, leading to enhance their stability and prolong the biological effects of these peptides, which might be helpful for the clinical application in the future. Peptide therapy is a very promising field for cancer treatments since they can induce the death of cancer cells without dramatically affecting normal cells. The synthesis of a useful and stable natriuretic peptide can enhance the effect of cancer treatments and significantly reduce drug resistance and toxicity.

Rotator cuff tears are a common condition of the shoulder, and 20.7% of people with the condition have a full-thickness rotator cuff tear. The purpose of this study was to explore the risk factors for full-thickness rotator cuff tears and to provide evidence to support the accurate diagnosis of full-thickness rotator cuff tears.Studies from PubMed, Embase and Web of Science published before 30 January 2021 were retrieved. All cohort studies and cross-sectional studies on risk factors for full-thickness rotator cuff tears were included. A meta-analysis was performed in RevMan 5.3 to calculate the relative risks (RRs) or weighted mean differences (WMDs) of related risk factors. Stata 15.1 was used for the quantitative analysis of publication bias.In total, 11 articles from six countries, including 4047 cases, with 1518 cases and 2529 controls, were included. The meta-analysis showed that age (MD = 0.76, 95% CI: 0.24 to 1.28, P = 0.004), hypertension (RR = 1.46, 95% CI: 1.17 to 1.81, P = 0.0007) and critical shoulder angle (CSA) (MD = 2.02, 95% CI: 1.55 to 2.48, P < 0.00001) were risk factors for full-thickness rotator cuff tears.Our results also suggested that body mass index, sex, dominant hand, smoking, diabetes mellitus and thyroid disease were not risk factors for full-thickness rotator cuff tears. Early identification of risk factors for full-thickness rotator cuff tears is helpful in identifying high-risk patients and choosing the appropriate treatment.Cite this article: EFORT Open Rev2021;6:1087-1096. DOI: 10.1302/2058-5241.6.210027

By employing CuOAc as the catalyst, we realize a four-component reaction of 1,3-enynes, diselenides, DABCO·(SO2)2, and cycloketone oxime esters, providing facile access to diverse cyanoalkylsulfonylated allenyl selenides in moderate to good yields. This reaction features high functional group tolerance and a broad substrate scope, enabling the regioselective, sequential formation of C–SO2and C–Se bonds under mild reaction conditions. Moreover, the utility of this methodology is further illustrated through the late-stage functionalization of drug-based molecules.

Supplemental Digital Content is available in the text.

Large tumour suppressor (LATS) 1/2, the core kinases of Hippo signalling, are critical for maintaining tissue homeostasis. Here, we investigate the role of SUMOylation in the regulation of LATS activation. High cell density induces the expression of components of the SUMOylation machinery and enhances the SUMOylation and activation of Lats1 but not Lats2, whereas genetic deletion of the SUMOylation E2 ligase, Ubc9, abolishes this Lats1 activation. Moreover, SUMOylation occurs at the K830 (mouse K829) residue to activate LATS1 and depends on the PIAS1/2 E3 ligase. Whereas the K830 deSUMOylation mutation of LATS1 found in the human metastatic prostate cancers eliminates the kinase activity by attenuating the formation of the phospho-MOB1/phospho-LATS1 complex. As a result, the LATS1(K830R) transgene phenocopies Yaptransgene to cause the oversized livers in mice, whereas Lats1(K829R) knock-in phenocopies the deletion of Lats1in causing the reproductive and endocrine defects and ovary tumours in mice. Thus, SUMOylation-mediated LATS1 activation is an integral component of Hippo signalling in the regulation of tissues homeostasis.

Fluid-absent and fluid-fluxed melting of muscovite in metasedimentary sources are two types of crustal anatexis to produce the Himalaya Cenozoic leucogranites. Apatite grains separated from melts derived from the two types of parting melting have different geochemical compositions. The leucogranites derived from fluid-fluxed melting have relict apatite grains and magmatic crystallized apatite grains, by contrast, there are only crystallized apatite grains in the leucogranites derived from fluid-absent melting. Moreover, apatite grains crystallized from fluid-fluxed melting of muscovite contain higher Sr, but lower Th and LREE than those from fluid-absent melting of muscovite, which could be controlled by the distribution of partitioning coefficient (DAp/Melt) between apatite and leucogranite. DAp/Meltin granites derived from fluid-absent melting is higher than those from fluid-fluxed melting. So, not only SiO2and A/CNK, but also types of crustal anatexis are sensitive to trace element partition coefficients for apatite. In addition, due to being not susceptible to alteration, apatite has a high potential to yield information about petrogenetic processes that are invisible at the whole-rock scale and thus is a useful tool as a petrogenetic indicator.

Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer and frequently diagnosed at an advanced stage. It is prone to develop unpredictable metastases even with proper treatment. Antiangiogenic therapy is the most effective medical treatment for metastatic ccRCC. Thus, exploration of novel approaches to inhibit angiogenesis and metastasis may potentially lead to a better therapeutic option for ccRCC. Among all the types of cancer, renal cancer samples exhibited the maximum upregulation of ApoC1 as referred to in the Oncomine database. The expression of ApoC1 was increased accompanied by ccRCC progression. A high level of ApoC1 was closely related to poor survival time in ccRCC patients. Furthermore, ApoC1 was over-expressed in the highly invasive ccRCC cells as compared to that in the low-invasive ccRCC cells. Besides, ApoC1 promoted metastasis of ccRCC cells via EMT pathway, whereas depletion of ApoC1 alleviated these effects. ApoC1 as a novel pro-metastatic factor facilitates the activation of STAT3 and enhances the metastasis of ccRCC cells. Meanwhile, ApoC1 in the exosomes were transferred from the ccRCC cells to the vascular endothelial cells and promoted metastasis of the ccRCC cells via activating STAT3. Finally, the metastatic potential of the ccRCC cells driven by ApoC1 was suppressed by DPP-4 inhibition. Our study not only identifies a novel ApoC1-STAT3 pathway in ccRCC metastasis but also provides direction for the exploration of novel strategies to predict and treat metastatic ccRCC in the future.

A suite of ultramafic and mafic rocks developed in the Chigu Tso area, eastern Tethyan Himalaya. Baddeleyite and zircon U-Pb ages acquired by SIMS and LA-ICP-MS from olivine pyroxenite rocks in the Chigu Tso area are 138.9±3.0 Ma and 139.0±1.9 Ma, respectively. These two Early Cretaceous ages are similar with the ages of the more abundant mafic rocks in the eastern Tethyan Himalaya, indicating that this suite of ultramafic and mafic rocks in the Chigu Tso area should be included in the outcrop area of the Comei Large Igneous Province (LIP). These ultramafic rocks provide significant evidence that the involvement of mantle plume/hot spot activities in the formation of the Comei LIP. Baddeleyite U-Pb dating by SIMS is one reliable and convenient method to constrain the formation time of ultramafic rocks. The dating results of baddeleyite and zircon from the olivine pyroxenite samples in this paper are consistent with each other within analytical uncertainties, suggesting that baddeleyite and zircon were both formed during the same magmatic process. The consistency of baddeleyite U-Pb ages in the Chigu Tso area with zircon U-Pb ages for a large number of Early Cretaceous mafic rocks in the eastern Tethyan Himalaya further support that zircon grains from such mafic rocks yielding Early Cretaceous ages are also magmatic in origin.

Purpose: Studies have shown the association between tongue color and diseases. To help clinicians make more objective and accurate decisions quickly, we take unsupervised learning to deal with the basic clustering of tongue color in a 2D way. Methods: A total of 595 typical tongue images were analyzed. The 3D information extracted from the image was transformed into 2D information by principal component analysis (PCA). K-Means was applied for clustering into four diagnostic groups. The results were evaluated by clustering accuracy (CA), Jaccard similarity coefficient (JSC), and adjusted rand index (ARI). Results: The new 2D information totally retained 89.63% original information in the L*a*b* color space. And our methods successfully classified tongue images into four clusters and the CA, ARI, and JSC were 89.04%, 0.721, and 0.890, respectively. Conclusions: The 2D information of tongue color can be used for clustering and to improve the visualization. K-Means combined with PCA could be used for tongue color classification and diagnosis. Methods in the paper might provide reference for the other research based on image diagnosis technology.

As a basic organizing principle of the human brain, hemispheric specialization is an important perspective to explore the pathology of schizophrenia. However, it remains unclearly whether the hemispheric specialization of functional connectivity plays a role in mediating auditory verbal hallucinations in schizophrenia. In this study, 18 schizophrenic patients with auditory verbal hallucinations, 18 patients without auditory verbal hallucinations, and 18 matched healthy controls underwent resting-state functional MRI scans, and seed-based voxel-wise functional connectivity was calculated to quantify the degree of hemispheric specialization. The results revealed that both the auditory verbal hallucinations and non-auditory verbal hallucinations groups exhibited significantly increased specialization in the left middle temporal gyrus and left precuneus, and significantly reduced specialization in the right precuneus relative to healthy controls, and that the auditory verbal hallucinations severity was significantly correlated with the hemispheric specialization of the right precuneus in the auditory verbal hallucinations group. Moreover, the left frontal lobe exhibited reduced hemispheric specialization in the auditory verbal hallucinations group compared with non-auditory verbal hallucinations group, and the patients with and without auditory verbal hallucinations could be clustered into two groups with an accuracy of 80.6% based on the brain regions exhibiting significant specialization changes. The findings indicate that the hemispheric specialization of the aforementioned regions may play a role in mediating auditory verbal hallucinations in schizophrenia, and the distinct hemispheric specialization patterns of functional connectivity may provide a potential biomarker to differentiate schizophrenic patients with and without auditory verbal hallucinations.