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Brain structural circuitry shapes a richly patterned functional synchronization, supporting for complex cognitive and behavioural abilities. However, how coupling of structural connectome (SC) and functional connectome (FC) develops and its relationships with cognitive functions and transcriptomic architecture remain unclear. We used multimodal magnetic resonance imaging data from 439 participants aged 5.7–21.9 years to predict functional connectivity by incorporating intracortical and extracortical structural connectivity, characterizing SC–FC coupling. Our findings revealed that SC–FC coupling was strongest in the visual and somatomotor networks, consistent with evolutionary expansion, myelin content, and functional principal gradient. As development progressed, SC–FC coupling exhibited heterogeneous alterations dominated by an increase in cortical regions, broadly distributed across the somatomotor, frontoparietal, dorsal attention, and default mode networks. Moreover, we discovered that SC–FC coupling significantly predicted individual variability in general intelligence, mainly influencing frontoparietal and default mode networks. Finally, our results demonstrated that the heterogeneous development of SC–FC coupling is positively associated with genes in oligodendrocyte-related pathways and negatively associated with astrocyte-related genes. This study offers insight into the maturational principles of SC–FC coupling in typical development.

Aberrant susceptibility due to iron level abnormality and brain network disconnections are observed in Alzheimer's disease (AD), with disrupted iron homeostasis hypothesized to be linked to AD pathology and neuronal loss. However, whether associations exist between abnormal quantitative susceptibility mapping (QSM), brain atrophy, and altered brain connectome in AD remains unclear. Based on multi-parametric brain imaging data from 30 AD patients and 26 healthy controls enrolled at the China-Japan Friendship Hospital, we investigated the abnormality of the QSM signal and volumetric measure across 246 brain regions in AD patients. The structural and functional connectomes were constructed based on diffusion MRI tractography and functional connectivity, respectively. The network topology was quantified using graph theory analyses. We identified seven brain regions with both reduced cortical thickness and abnormal QSM (p < 0.05) in AD, including the right superior frontal gyrus, left superior temporal gyrus, right fusiform gyrus, left superior parietal lobule, right superior parietal lobule, left inferior parietal lobule, and left precuneus. Correlations between cortical thickness and network topology computed across patients in the AD group resulted in statistically significant correlations in five of these regions, with higher correlations in functional compared to structural topology. We computed the correlation between network topological metrics, QSM value and cortical thickness across regions at both individual and group-averaged levels, resulting in a measure we call spatial correlations. We found a decrease in the spatial correlation of QSM and the global efficiency of the structural network in AD patients at the individual level. These findings may provide insights into the complex relationships among QSM, brain atrophy, and brain connectome in AD.

Objective Diffuse idiopathic skeletal hyperostosis (DISH) is characterized by osteophytes in the anterior vertebrae, and the presence of aorta may have an impact on their formation. However, the anatomical positional relationship between the aorta and osteophytes in patients with DISH remains controversial. This study aimed to evaluate the position of osteophytes in relation to aorta in DISH, and the influence of aortic pulsation on the formation of osteophytes from the perspective of morphology. Methods We conducted a retrospective review of 101 patients diagnosed with DISH and symptomatic lumbar spinal stenosis between June 2018 and December 2021. A total of 637 segments with heterotopic ossification in DISH were used for quantitative measurements on CT scans. The Cartesian coordinate system was built up on the axial CT scans to reflect the relative position between aorta and osteophytes. Osteophytes were divided into adjacent aorta group (AD group) and non‐adjacent aorta group (N‐AD group). In terms of the morphology, osteophytes in the AD group were further divided into convex, flat, and concave types. The relative position between aorta and osteophytes, and the aorta‐osteophyte distance and morphology of osteophytes were compared. Univariate analysis of variance was performed for multiple groups, and two independent‐samples t‐tests were used for two groups. Results From T5 to L4, aorta gradually descended from left side to middle of vertebrae, and osteophytes gradually shifted from right side of vertebrae (T5‐T10) to bilateral sides (T11‐L4). Of 637 osteophytes in DISH, 60.1% (383/637) were in AD group, including convex type 0.6% (4/637), flat type 34.7% (221/637), and concave type 24.8% (158/637). The N‐AD group accounted for 39.9% (254/637). Flat osteophytes were concentrated in T5‐T12, while concave osteophytes in T11‐L4. Overall, the aorta‐osteophyte distance of concave type was significantly smaller than that of flat type. Conclusion Osteophytes are not always located on the right side of vertebrae, but move with the position of the descending aorta. Furthermore, the morphology of osteophytes varies by vertebral segment in DISH, which is related to aorta descending anteriorly in the spine.

Abstract In today's rapidly developing technological era, the technological revolution triggered by the rapid iteration of artificial intelligence and augmented reality has provided brand-new digital intelligent empowerment for orthopaedic clinical operation. Although traditional arthroscopy has been widely promoted globally due to its advantages such as minimally invasive, safety and early functional exercise, it still has deficiencies in precision and personalization. The assistance of artificial intelligence and augmented reality enables precise positioning and navigation in arthroscopic surgery, as well as personalized operations based on patient conditions, which lifts the objective limitations of traditional sports medicine surgery. The integration of artificial intelligence and augmented reality with orthopaedic arthroscopy surgery is still in infancy, even though there are still some insufficient to be solved, but its prospect is bright.

Abstract Gastric remnant carcinoma (GRC), which occurs in the stomach after partial gastrectomy, is a rare and aggressive form of gastric adenocarcinoma (GAC). Comprehensive profiling of genomic mutations in GRC could provide the basis for elucidating the origin and characteristics of this cancer. Herein, whole‐exome sequencing (WES) was performed on 36 matched tumor–normal samples from patients with GRC and identified recurrent mutations in epigenetic modifiers, notably KMT2C, ARID1A, NSD1, and KMT2D, in 61.11% of cases. Mutational signature analysis revealed a low frequency of microsatellite instability (MSI) in GRC, which was further identified by MSIsensor, MSI‐polymerase chain reaction, and immunohistochemistry analysis. Comparative analysis demonstrated that GRC had a distinct mutation spectrum compared to that of GAC in The Cancer Genome Atlas samples, with a significantly higher mutation rate of KMT2C. Targeted deep sequencing (Target‐seq) of an additional 25 paired tumor–normal samples verified the high mutation frequency (48%) of KMT2C in GRC. KMT2C mutations correlated with poor overall survival in both WES and Target‐seq cohorts and were independent prognosticators in GRC. In addition, KMT2C mutations were positively correlated with favorable outcomes in immune checkpoint inhibitor‐treated pan‐cancer patients and associated with higher intratumoral CD3+, CD8+ tumor‐infiltrating lymphocyte counts, and PD–L1 expression in GRC samples (p = 0.018, 0.092, 0.047, 0.010, and 0.034, respectively). Our dataset provides a platform for information and knowledge mining of the genomic characteristics of GRC and helps to frame new therapeutic approaches for this disease.

Ma2 and Ma3 hydrocarbon source rock samples from the Fengcheng Formation in well Maye 1, Mahu Depression, Junggar Basin, were studied using conventional geochemical analysis methods and saturated hydrocarbon gas chromatography–mass spectrometry. The distribution patterns, abundance, relative content, and ratios of different carbon compounds of tricyclic terpane in hydrocarbon source rocks from fresh-to-mildly-saline (type I), moderately saline (type II), and saline (type III) water environments significantly differed. The C28–C29TT/C30H and C19–C29TT/C30H ratios were the lowest in the type I hydrocarbon source rock. The relative ratios of C23TT/C21TT, C25TT/C24TT, C28TT/C26TT, (C23–C26TT)/(C19–C22TT), and (C28–C29TT)/(C19–C22TT) gradually increased with the increase in the salinity of the hydrocarbon source rock. The percentage of low-carbon tricyclic terpanes gradually decreased to 28%, whereas those of the medium- and high-carbon tricyclic terpanes increased to 52% and 20%, respectively. The differences in triterpane types of different hydrocarbon source rocks were mainly controlled by the depositional environment. The primary factor that controlled the distribution pattern; relative abundance, especially the high carbon tricyclic terpane content; and differences in the relative ratio of different carbon compounds in different hydrocarbon source rocks was the salinity of the ancient waterbody during deposition.

The J-TEXT capability is enhanced compared to two years ago with several upgrades of its diagnostics and the increase of electron cyclotron resonance heating (ECRH) power to 1 MW. With the application of electron cyclotron wave (ECW), the ECW assisted plasma startup is achieved; the tearing mode is suppressed; the toroidal injection of 300 kW ECW drives around 24 kA current; fast electrons are generated with toroidal injected ECW and the runaway current conversion efficiency increases with ECRH power. The mode coupling between 2/1 and 3/1 modes are extensively studied. The coupled 2/1 and 3/1 modes usually lead to major disruption. Their coupling can be either suppressed or avoided by external resonant magnetic perturbation fields and hence avoids the major disruption. It is also found that the 2/1 threshold of external field is significantly reduced by a pre-excited 3/1 mode, which can be either a locked island or an external kink mode. The disruption control is studied by developing prediction methods capable of cross tokamak application and by new mitigation methods, such as the biased electrode or electromagnetic pellet injector. The high-density operation and related disruptions are studied from various aspects. Approaching the density limit, the collapse of the edge shear layer is observed and such collapse can be prevented by applying edge biasing, leading to an increased density limit. The density limit is also observed to increase, if the plasma is operated in the poloidal divertor configuration or the plasma purity is increased by increasing the pre-filled gas pressure or ECRH power during the start-up phase.

ABSTRACT Diabetes and Alzheimer's disease (AD) are associated with specific changes in the composition of the intestinal flora. Studies have shown that the supplementation with pasteurized Akkermansia muciniphila has therapeutic and preventive effects on diabetes. However, it is not clear whether there is any association with improvement in and prevention of Alzheimer's disease and diabetes with Alzheimer's disease. Here, we found that pasteurized Akkermansia muciniphila can significantly improve the blood glucose, body mass index, and diabetes indexes of zebrafish with diabetes mellitus complicated with Alzheimer's disease and also alleviate the related indexes of Alzheimer's disease. The memory, anxiety, aggression, and social preference behavior of zebrafish with combined type 2 diabetes mellitus (T2DM) and Alzheimer’s disease (TA zebrafish) were significantly improved after pasteurized Akkermansia muciniphila treatment. Moreover, we examined the preventive effect of pasteurized Akkermansia muciniphila on diabetes mellitus complicated with Alzheimer's disease. The results showed that the zebrafish in the prevention group were better in terms of biochemical index and behavior than the zebrafish in the treatment group. These findings provide new ideas for the prevention and treatment of diabetes mellitus complicated with Alzheimer's disease. IMPORTANCE The interaction between intestinal microflora and host affects the progression of diabetes and Alzheimer's disease. As a recognized next-generation probiotic, Akkermansia muciniphila has been shown to play a key role in the progression of diabetes and Alzheimer's disease, but whether A. muciniphila can improve diabetes complicated with Alzheimer's disease and its potential mechanism are unclear. In this study, a new zebrafish model of diabetes mellitus complicated with Alzheimer's disease was established, and the effect of Akkermansia muciniphila on diabetes mellitus complicated with Alzheimer's disease is discussed. The results showed that Akkermansia muciniphila after pasteurization significantly improved and prevented diabetes mellitus complicated with Alzheimer's disease. Treatment with pasteurized Akkermansia muciniphila improved the memory, social preference, and aggressive and anxiety behavior of TA zebrafish and alleviated the pathological characteristics of T2DM and AD. These results provide a new prospect for probiotics in the treatment of diabetes and Alzheimer's disease.

Sediment bacterial communities are a vital component of microbial communities in aquatic and terrestrial ecosystems and they play a critical role in lake wetlands. We aimed to investigate the effect of season, depth and regional environmental factors on the composition and diversity of bacterial communities in a plain river network area from Taihu Basin. The millions of Illumina reads (16S rRNA gene amplicons) at the surface 25 cm inside samples of the study area were examined using a technically consistent approach. Results from the diversity index, relative abundance, principal component analysis (PCA), redundancy analysis (RDA) and linear discriminant analysis effect size (LEfSe) analysis indicated that the diversity of the bacterial community in summer was generally higher than in other seasons. Proteobacteria were the most abundant phylum in the sediment samples in different seasons (43.15–57.41%) and different layers (39.66–77.97%); the autumn sediments were enriched with Firmicutes (5.67%) and Chloroflexi (12.5%); in all four seasons the sediments were enriched with Betaproteobacteria (14.98–23.45%), Gammaproteobacteria (11.98–14.36%) and Deltaproteobacteria (8.68–14.45%). In the bottom sediments (10–25 cm), Chloroflexi were abundant (average value 10.42%), while Bacteroidetes was the dominant phylum in the surface sediments; redundancy analysis found that total phosphorus (TP) (p = 0.036) was the main environmental factor influencing the sediment bacterial community in different layers. This study provides a reference for further understanding the effects of seasonal changes on sediment microorganisms in lake wetlands.

Abstract Drug resistance is responsible for castration-resistant prostate cancer (CRPC)-associated mortality. While ATP binding cassette subfamily C member 5 (ABCC5) has been reported to regulate multiple drug resistance, its drug-efflux function may not be the main reason underlying resistance to enzalutamide, an androgen receptor inhibitor. Here, we aimed to determine whether the non-drug efflux function of ABCC5 affects enzalutamide resistance. The ABCC5 expression data in patients with prostate cancer (PCa) were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus, and their correlation with disease prognosis was analyzed. Immunohistochemical staining was performed on a cohort of 80 patient samples. Proliferation of enzalutamide-resistant 22RV1 and C4-2B cells was investigated using CCK-8, EdU, and colony formation assays. The effect of ABCC5 silencing on enzalutamide resensitization was evaluated in vitro and in vivo. Functional assays indicated that ABCC5 depletion resensitized enzalutamide-resistant cells to inhibit cell growth and impeded xenograft tumor proliferation. Mechanistically, luciferase and ChIP assays confirmed that P65 regulated AR expression and activity by binding to its promoter, while ABCC5-mediated resistance effected by AR-V7 (one of the widely studied AR splicing variants that meditate AR antagonist resistance) upregulation could be reversed by P65 knockdown. Furthermore, activation of the NF-κB pathway reversed the effects of ABCC5 knockdown by extra AR-V7 expression. Thus, ABCC5 might be a novel target for enzalutamide-resistant CRPC treatment.

With the in-depth and comprehensive study of bacteria and their related ecosystems in the human body, bacterial-based drug delivery system has become an emerging biomimetic platform that can retain the innate biological functions. Benefiting from its good biocompatibility and ideal targeting ability as a biological carrier, Escherichia coli Nissle 1917 (ECN) has been focused on the treatment strategies of inflammatory bowel disease and tumor. The advantage of a bacterial carrier is that it can express exogenous protein while also acting as a natural capsule by releasing drug slowly as a result of its own colonization impact. In order to survive in harsh environments such as the digestive tract and tumor microenvironment, ECN can be modified or genetically engineered to enhance its function and host adaptability. The adoption of ECN carries or expresses drugs which are essential for accurate diagnosis and treatment. This review briefly describes the properties of ECN, the relationship between ECN and inflammation and tumor, and the strategy of using surface modification and genetic engineering to modify ECN as a delivery carrier for disease treatment.

Cultivated land protection and quality improvement have become inevitable requirements for alleviating ecological and environmental pressure and sustainable agricultural development. It is of practical significance to explore the differences and causes of cultivated land protection behaviors (CLPB) between smallholders and professional farmers for formulating targeted protection policies and improving their effectiveness. Based on 422 mango farmers' survey data in Hainan Province, this paper explored the internal and external characteristics between smallholders and professional farmers, and used the Fairlie decomposition method to compare and analyze the sources of differences in farmers' CLPB. The results showed that: (1) the CLPB of smallholders and professional farmers differ significantly; (2) the sources of differences in CLPB between smallholders and professional farmers are different, including differences in internal characteristics and differences in external characteristics; (3) differences in internal characteristics are the main cause of the differences in farmer's CLPB, and the contribution of differences in external characteristics was smaller, of which planting years, annual household income and planting scale are the top three factors. It is suggested that differential protection policies should be designed for smallholders and professional farmers, such as guiding smallholders to carry out large-scale operations and improve their organizational level, encouraging and guiding professional farmers to sign long-term contracts to stabilize the land tenure, and formulating subsidy policies for cultivated land protection.

Abstract Identifying genomic regions with hypervariable ChIP-seq or ATAC-seq signals across given samples is essential for large-scale epigenetic studies. In particular, the hypervariable regions across tumors from different patients indicate their heterogeneity and can contribute to revealing potential cancer subtypes and the associated epigenetic markers. We present HyperChIP as the first complete statistical tool for the task. HyperChIP uses scaled variances that account for the mean-variance dependence to rank genomic regions, and it increases the statistical power by diminishing the influence of true hypervariable regions on model fitting. A pan-cancer case study illustrates the practical utility of HyperChIP.

Paclobutrazol (PBZ) is a plant growth inhibitor and fungicide, but it is also carcinogenic and teratogenic, and has potential harm to human health. In this study, two PBZ haptens (PBZ-1, PBZ-2) were synthesized and conjugated with carrier proteins to get artificial antigens. A highly specific monoclonal antibody (mAb) against PBZ was prepared. The antibody subtype was IgG1 and the concentration was 11.03 mg/mL. A sensitive and rapid time-resolved fluorescence microsphere lateral flow immunoassay (TRFMs-LFIA) was established based on the mAb. The activated pH, the mAbs diluents, the mAb reacting concentration and the probe amount were optimized. The visual limit of detection (vLOD) and quantitative limit of detection (qLOD) of the TRFMs-LFIA for PBZ were 50 and 1.72 ng/mL respectively, and the 50% inhibiting concentration (IC50) was 9.38 ng/mL. The pretreatment procedures are simple and rapid, and the detection time of TRFMs-LFIA strip is 6 min. Qualitative and quantitative analysis of PBZ could be achieved under a UV light or with a portable fluorescence immunoassay analyzer. The average recovery rates ranged from 96.2% to 111.9% and the corresponding coefficients of variation (CV) were 4.0%–11.2% in spiked wheat and rice samples. Twenty real wheat and rice samples were measured by the TRFMs-LFIA and compared with Ultra-performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS). The measured values showed a good accordance. These results indicated that the proposed assay will provide a novel effective strategy for on-site detection of PBZ.

This paper addresses the problem of relative position-based formation planning for a leader–follower multi-robot setup, where the robots adjust the formation parameters, such as size and three-dimensional orientation, to avoid collisions and progress toward their goal. Specifically, we develop a virtual sub-target-based obstacle avoidance method, which involves a transitional virtual sub-target that guides the robots to avoid obstacles according to obstacle information, target, and boundary. Moreover, we develop a changing formation strategy to determine the necessity to avoid collisions and a priority-based model to determine which robots move, thus dynamically adjusting the relative distance between the followers and the leader. The backstepping-based sliding motion controller guarantees that the trajectory and velocity tracking errors converge to zero. The proposed robot navigation method can be employed in various environments and types of obstacles, allowing for a formation change. Furthermore, it is efficient and scalable under various numbers of robots. The approach is experimentally verified using three real mobile robots and up to five mobile robots in simulated scenarios.

Cardiovascular diseases (CVDs) are the leading cause of mortality globally. Benefiting from the advantages of early diagnosis and precision medicine, stem cell-based therapies have emerged as promising treatment options for CVDs. However, autologous or allogeneic stem cell transplantation imposes a potential risk of immunological rejection, infusion toxicity, and oncogenesis. Fortunately, exosome can override these limitations. Increasing evidence has demonstrated that long non-coding RNAs (lncRNAs) in exosome from stem cell paracrine factors play critical roles in stem cell therapy and participate in numerous regulatory processes, including transcriptional silencing, transcriptional activation, chromosome modification, and intranuclear transport. Accordingly, lncRNAs can treat CVDs by directly acting on specific signaling pathways. This mini review systematically summarizes the key regulatory actions of lncRNAs from different stem cells on myocardial aging and apoptosis, ischemia-reperfusion injury, retinopathy, atherosclerosis, and hypertension. In addition, the current challenges and future prospects of lncRNAs treatment for CVDs are discussed.

Background: To study the pathogenesis of steroid-induced femoral head osteonecrosis, an ideal animal model is very important. As experimental animals, mice are beneficial for studying the pathogenesis of disease. However, there are currently few mouse models of steroid-induced femoral head osteonecrosis, and there are many questions that require further exploration and research.Purposes: The purpose of this study was to establish a new model of osteonecrosis in mice using angiotensin II (Ang II) combined with asparaginase (ASP) and dexamethasone (DEX) and to study the effects of this drug combination on femoral head osteonecrosis in mice.Methods: Male BALB/c mice (n = 60) were randomly divided into three groups. Group A (normal control, NC) was treated with physiological saline and given a normal diet. Group B (DEX + ASP, DA) was given free access to food and water (containing 2 mg/L DEX) and subjected to intraperitoneal injection of ASP (1200 IU/kg twice/week for 8 weeks). Group C (DEX + ASP + Ang II, DAA) was treated the same as group B, it was also given free access to food and water (containing 2 mg/L DEX) and subjected to intraperitoneal injection of ASP (1200 IU/kg twice/week for 8 weeks), but in the 4th and 8th weeks, subcutaneous implantation of a capsule osmotic pump (0.28 mg/kg/day Ang II) was performed. The mice were sacrificed in the 4th and 8th weeks, and the model success rate, mouse mortality rate, body weight, blood lipids, coagulation factors, histopathology, and number of local vessels in the femoral head were evaluated.Results: DAA increased the model success rate [4th week, 30% (DA) vs. 40% (DAA) vs. 0% (NC); 8th week, 40% (DA) vs. 70% (DAA) vs. 0% (NC)]. There was no significant difference in mortality rate between the groups [4th week, 0% (DA) vs. 0% (DAA) vs. 0% (NC); 8th week, 5% (DA) vs. 10% (DAA) vs. 0% (NC)]. DAA affected mouse body weight and significantly affected blood lipids and blood coagulation factors. DAA reduces the number of blood vessels in the femoral head and destroys the local blood supply.Conclusion: Angiotensin II combined with asparaginase and dexamethasone can obviously promote the necrosis of femoral head and provide a new idea for the model and treatment of osteonecrosis.

ObjectiveTo identify less invasive and easily applicable serum cytokine-derived biomarkers which contribute to the diagnostic utility and risk assessment ability of the prostate health index (PHI) based multivariable model in grey zone aggressive prostate cancer (AG PCa) early detection.MethodsSerum 45 cytokines screening was performed in a small training cohort consisting of 10 sera by Luminex liquid array-based multiplexed immunoassays and identified TRAIL and IL-10 as new biomarkers for PHI diagnostic utility adjustment for further validation with a multivariable predictive model in a cohort including 79 aggressive prostate cancer patients and 209 benign prostatic hyperplasia or indolent PCa patients within the PSA grey zone.ResultsTRAIL and IL-10 were identified as potential serum biomarkers for AG PCa detection by the result of multi-cytokines screening in the univariate analysis, while multivariable logistic regression confirmed the AUC of the full risk predictive model (0.915) including tPSA, fPSA, PHI, TRAIL, and IL-10 was higher than various diagnostic strategies. DCA suggested a superior net benefit and indicated a good discriminative ability of the full risk model consistently with the result of the nomogram.ConclusionWe suggest a significant advantage for the PHI-based multivariate combinations of serum TRAIL and IL-10 comparing to PHI or other serum-derived biomarkers alone in the detection and risk stratification of grey zone AG PCa.

Improved human material living standards have resulted in a continuous increase in the rate of obesity caused by excessive sugar intake. Consequently, the number of diabetic patients has skyrocketed, not only resulting in a global health problem but also causing huge medical pressure on the government. Limiting sugar intake is a serious problem in many countries worldwide. To this end, the market for sugar substitute products, such as artificial sweeteners and natural sugar substitutes (NSS), has begun to rapidly grow. In contrast to controversial artificial sweeteners, NSS, which are linked to health concepts, have received particular attention. This review focuses on the extraction technology and biomedical function of NSS, with a view of generating insights to improve extraction for its large-scale application. Further, we highlight research progress in the use of NSS as food for special medical purpose (FSMP) for patients.

Abstract Background Lung adenocarcinoma (LUAD) is a highly malignant and heterogeneous tumor that involves various oncogenic genetic alterations. Epigenetic processes play important roles in lung cancer development. However, the variation in enhancer and super-enhancer landscapes of LUAD patients remains largely unknown. To provide an in-depth understanding of the epigenomic heterogeneity of LUAD, we investigate the H3K27ac histone modification profiles of tumors and adjacent normal lung tissues from 42 LUAD patients and explore the role of epigenetic alterations in LUAD progression. Results A high intertumoral epigenetic heterogeneity is observed across the LUAD H3K27ac profiles. We quantitatively model the intertumoral variability of H3K27ac levels at proximal gene promoters and distal enhancers and propose a new epigenetic classification of LUAD patients. Our classification defines two LUAD subgroups which are highly related to histological subtypes. Group II patients have significantly worse prognosis than group I, which is further confirmed in the public TCGA-LUAD cohort. Differential RNA-seq analysis between group I and group II groups reveals that those genes upregulated in group II group tend to promote cell proliferation and induce cell de-differentiation. We construct the gene co-expression networks and identify group-specific core regulators. Most of these core regulators are linked with group-specific regulatory elements, such as super-enhancers. We further show that CLU is regulated by 3 group I-specific core regulators and works as a novel tumor suppressor in LUAD. Conclusions Our study systematically characterizes the epigenetic alterations during LUAD progression and provides a new classification model that is helpful for predicting patient prognosis.

Abstract Soft, low‐cost, high‐performance generators are highly desirable for harvesting ambient low frequency mechanical energy. Here, a dielectric elastomer nanogenerator (DENG) is reported, which consists of a dielectric elastomer capacitor, an electret electrostatic voltage source, and a charge pump circuit. Under biaxial stretching, DENG can convert tensile mechanical energy into electrical power without any external power supply. Different from traditional DEG with the charge outward transfer in direct current (DC), the DENG works based on shuttle movement of internal charges in an alternating current (AC). Through alternating current (AC) method, the charge density of the DENG can reach 26 mC m−2 per mechanical cycle, as well as energy density of up to 140 mJ g−1. Due to the all‐solid‐state structure without air gap, the DENG is capable of working stably under different ambient humidity (20 RH%–100 RH%). To demonstrate the applications, a water wave harvester based on the DENG is constructed. The integrated device powers a sensing communication module for self‐powered remote weather monitoring, showing the potential application in ocean wave energy harvesting.

In this study, two hybrid metaheuristic models are developed to discover the applicability of using an optimized radial basis function neural network to predict the undrained shear strength (USS) from cone penetration test (CPT) records. To this aim, genetic algorithm (GA) and grey wolf optimization (GWO) were integrated with radial basis function (RBFNN), named GA-RBFNN and GWO-RBFNN, to determine the optimal determinative parameters of RBFNN. Models trained with five input variables named cone tip resistance, sleeve friction, liquid limit, plastic limit, and overburden weight. To assess the precision of developed models, four statistical performance indices (R2, RMSE, MAE, and PI) were considered. The results demonstrate powerful potential in the learning section as well as approximating in the testing phase. It means that the correlation between observed and predicted USS from hybrid models is acceptable to represent the high accuracy in the training and approximating process. Concerning developed RBFNN models, it can be observed that GWO-RBFNN has better performance than GA-RBFNN based on evaluating the performance evaluator indices. Based on the outline of this paper aimed at finding RBFNN optimal parameters with optimization algorithms, GWO is more capable and rapid than GA for determining these parameters. Therefore, GWO-RBFNN outperforms the GA-RBFNN model with a total ranking of 16, consequently being recognized as the proposed model.

BackgroundEarly screening of clinically significant prostate cancer (csPCa) may offer opportunities in revolutionizing the survival benefits of this lethal disease. We sought to introduce a modified prostate health index density (mPHI) model using imaging indicators and to compare its diagnostic performance for early detection of occult onset csPCa within the prostate-specific antigen (PSA) gray zone with that of PHI and PHID.Methods and ParticipationBetween August 2020 and January 2022, a training cohort of 278 patients (total PSA 4.0–10.0 ng/ml) who were scheduled for a prostate biopsy were prospectively recruited. PHI and PHID were compared with mPHI (LDTRD×APD×TPV×PHI) for the diagnosis performance in identifying csPCa. Pathology outcomes from systematic prostate biopsies were considered the gold standard.ResultsThis model was tested in a training cohort consisting of 73 csPCa, 14 non-clinically significant prostate cancer(non-csPCa), and 191 benign prostatic hyperplasia (BPH) samples. In the univariate analysis for the PSA gray zone cohort, for overall PCa, the AUC of mPHI (0.856) was higher than PHI (0.774) and PHID (0.835). For csPCa, the AUC of mPHI (0.859) also surpassed PHI (0.787) and PHID (0.825). For detection of csPCa, compared with lower specificities from PHI and PHID, mPHI performed the highest specificity (76.5%), by sparing 60.0% of unnecessary biopsies at the cost of missing 11 cases of csPCa. The mPHI outperformed PHI and PHID for overall PCa detection. In terms of csPCa, mPHI exceeds diagnostic performance with a better net benefit in decision curve analysis (DCA) compared with PHI or PHID.ConclusionsWe have developed a modified PHI density (mPHI) model that can sensitively distinguish early-stage csPCa patients within the PSA gray zone.Clinical Trial RegistrationClinicalTrials.gov, NCT04251546.

In the computer vision field, underwater object detection has been a challenging task. Due to the attenuation of light in a medium and the scattering of light by suspended particles in water, underwater optical images often face the problems of color distortion and target feature blurring, which greatly affect the detection accuracy of underwater object detection. Although deep learning-based algorithms have achieved state-of-the-art results in the field of object detection, most of them cannot be applied to practice because of the limited computing capacity of a low-power processor embedded in unmanned underwater vehicles. This paper proposes a lightweight underwater object detection network based on the YOLOX model called LUO-YOLOX. A novel weighted ghost-CSPDarknet and simplified PANet were used in LUO-YOLOX to reduce the parameters of the whole model. Moreover, aiming to solve the problems of color distortion and unclear features of targets in underwater images, this paper proposes an efficient self-supervised pre-training joint framework based on underwater auto-encoder transformation (UAET). After the end-to-end pre-training process with the self-supervised pre-training joint framework, the backbone of the object detection network can extract more essential and robust features from degradation images when retrained on underwater datasets. Numerous experiments on the URPC2021 and detecting underwater objects (DUO) datasets verify the performance of our proposed method. Our work can assist unmanned underwater vehicles to perform underwater object detection tasks more accurately.

An explosion inside a cabin will converge at the corners to form high-pressure areas, significantly impacting the destruction of a bulkhead structure. This paper investigates shock wave convergence characteristics at the corners when the explosive detonates at the center of the cabin, based on a combination of the wall reflection law for shock waves and a numerical simulation method. The parameter K represents the aspect ratio of the cabin structure. This study shows that when 1 ≤ K ≤ 1.19, the high pressure at the corner is caused by the superposition of Mach waves along both wall surfaces. However, for the initial shock wave, when 1.2 < K ≤ 2, the high pressure is caused by the superposition of Mach waves along the longer wall surface and regular reflected waves on the shorter wall surface; when 2 < K, the cause are Mach waves along the longer wall surface and the corresponding positive reflection on the shorter wall surface. The influence of K on the range for the high-pressure region at the corner is also analyzed, the functional relationship between the range of the high-pressure area and K is given, and the universality is verified.

Recently proposed organic flash cycles maintain lower irreversibility in the evaporator than traditional organic Rankine cycles. This study presented a novel combined heat and power system that was based on a regenerative organic flash cycle, in order to improve thermal efficiency. Parametric analyses for the proposed combined heat and power system were carried out, using six working fluids, and performed with heat source temperatures and heat sink temperatures that ranged from 130 °C to 170 °C, and from 20 °C to 40 °C, respectively. The results showed that the preferable working fluid was altered, with a change in the operating condition. Isopentane, R1234ze(Z), R1233zd(E), and R245fa performed better at a cooling water temperature of 20 °C. The system that used R245fa showed more promising performance when the heat source temperatures were set to 150 °C and 160 °C. R365mfc was determined to be the best working fluid at a heat source temperature of 150 °C, and at cooling water temperatures of 30–40 °C. Finally, the analyses evaluated the year-round system performance on the basis of monthly ambient and water temperatures in Daegu, Korea, as the system’s parameters. Compared to the single regenerative organic flash cycle, the thermal efficiency of the novel system improved significantly, from 8.37 % to 32.80% in August, and to 74.34% in February.

Along with the wide use of deep learning technology, its security issues have drawn much attention over the years. Adversarial examples expose the inherent vulnerability of deep learning models and make it a challenging task to improve their robustness. Model robustness is related not only to its parameters but also to its architecture. This paper proposes a novel robustness enhanced approach for neural networks based on a neural architecture search. First, we randomly sample multiple neural networks to construct the initial population. Second, we utilize the individual networks in the population to fit and update the surrogate models. Third, the population of neural networks is evolved through a multi-objective evolutionary algorithm, where the surrogate models accelerate the performance evaluation of networks. Finally, the second and third steps are performed alternately until a network architecture with high accuracy and robustness is achieved. Experimental results show that the proposed method outperforms some classical artificially designed neural networks and other architecture search algorithms in terms of robustness.

Three new polyhydroxylated oleanane triterpenoids, cissatriterpenoid A−C (1−3), along with one known analogue (4), were isolated from the whole plant of Cissampelos pareira var. hirsuta. Their chemical structures were elucidated by extensive spectroscopic data (IR, HR-ESI-MS, 1H-NMR, 13C-NMR, DEPT, 1H-1H COSY, HSQC, HMBC, NOESY) and the microhydrolysis method. The isolation of compounds 1–4 represents the first report of polyhydroxylated oleanane triterpenoids from the family Menispermaceae. All isolated compounds were evaluated for their cytotoxicity against five human cancer cell lines, and the inhibitory activity against NO release in LPS-induced RAW 264.7 cells. Compound 3 showed the most potent cytotoxic activities against the A549, SMMC-7721, MCF-7, and SW480 cell lines, with IC50 values of 17.55, 34.74, 19.77, and 30.39 μM, respectively, whereas three remaining ones were found to be inactive. The preliminary structure–activity relationship analysis indicated that the γ-lactone ring at C-22 and C-29, and the olefinic bond at C-12 and C-13 were structurally required for the cytotoxicity of polyhydroxylated oleanane triterpenoids against these four cell lines. Based on lipid-water partition coefficients, compound 3 is less lipophilic than 1 and 4, which agrees with their cytotoxic activities. This confirms the potential of C. pareira var. hirsuta in the tumor treatment.

Bacterial ghosts (BGs) are empty bacterial envelopes of Gram-negative bacteria produced by controlled expressions of cloned gene E, forming a lysis tunnel structure within the envelope of the living bacteria. Globally, BGs have been used as vaccine delivery systems and vaccine adjuvants. There is an increasing interest in the development of novel delivery systems that are based on BGs for biomedical applications. Due to intact reservation of bacterial cell membranes, BGs have an inherent immunogenicity, which enables targeted drug delivery and controlled release. As carrier vehicles, BGs protect drugs from interference by external factors. In recent years, there has been an increasing interest in BG-based delivery systems against tumors, inflammation, and infection, among others. Herein, we reviewed the preparation methods for BGs, interactions between BGs and the host, and further highlighted research progress in BG development.

This paper discovers how the surface texture of micro-dimples impacts the tribological performance of the interface between cylinder block and valve plate. For this, a mathematical model which considers the cavitation effect for calculating oil film pressure and oil leakage is established. The radius of the micro dimples is considered for studying the influence of the pressure field and the leakage flow. Then a simulation model is built up according to the mathematical model. Meanwhile, a particular test rig was designed and established to verify the theoretical results. Both simulation and experimental results show that a good designed surface texture of micro-dimples could improve the lubrication performance a lot and the structure parameters could be optimized. The leakage flow of the port plate pair will be greatly decreased by micro dimples and it is positive correlated with the radius of the micro dimples.

To solve the problem of front wheels being jammed due to the passive trajectory tracking of the conventional car-like robot in the leader–follower formation control, we propose a novel car-like robot with the integration of front-wheel driving and steering. We establish its kinematic model, then analyze its controllability via the method of chained form system, and design the trajectory-tracking controller via the backstepping method. Simulations and experimental results validate our algorithm. This novel car-like robot with the integration of front-wheel driving and steering system not only avoids the jamming in the formation motion, but also owes the advantages of compacter structure, lighter body, and lower energy consumption.

Sixteen new prenylated flavonoids, sinoflavonoids P−Z (1−11) and sinoflavonoids NA−NE (12−16), were isolated from the fruit of Sinopodophyllum hexandrum, along with eight known analogues (17−24). Their structures were elucidated on the basis of extensive spectroscopic data (HR-ESI-MS, 1H-NMR, 13C-NMR, HSQC, HMBC). The cytotoxic activities of compounds 1−18, 20, and 22 were evaluated by MTT assay. Compound 6 showed the most potent cytotoxicity in MCF-7, and HepG2 cell lines, with IC50 values of 6.25 and 3.83 μM, respectively.

Six new coumarin glycosides, genglycoside A–F (1–6), were isolated from the aerial parts of Gendarussa vulgaris, along with ten known analogues (7–16). Their structures were unambiguously established on the basis of extensive spectroscopic data and HPLC analysis. The cytotoxic activities of all isolated compounds were evaluated by MTT assay. Compound 12 showed the most potent cytotoxicity in Eca-109, MCF-7, and HepG2 cell lines. By the preliminary structure–activity relationships, it was firstly discovered that the glycosylation or esterification at 7,8-dihydroxy or 7-hydroxy drastically reduced the cytotoxic activity of the parent coumarin.