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Gastric cancer (GC) represents a significant burden of cancer-related mortality worldwide, underscoring an urgent need for the development of early detection strategies and precise postoperative interventions. However, the identification of non-invasive biomarkers for early diagnosis and patient risk stratification remains underexplored. Here, we conduct a targeted metabolomics analysis of 702 plasma samples from multi-center participants to elucidate the GC metabolic reprogramming. Our machine learning analysis reveals a 10-metabolite GC diagnostic model, which is validated in an external test set with a sensitivity of 0.905, outperforming conventional methods leveraging cancer protein markers (sensitivity < 0.40). Additionally, our machine learning-derived prognostic model demonstrates superior performance to traditional models utilizing clinical parameters and effectively stratifies patients into different risk groups to guide precision interventions. Collectively, our findings reveal the metabolic landscape of GC and identify two distinct biomarker panels that enable early detection and prognosis prediction respectively, thus facilitating precision medicine in GC. Gastric cancer detection by endoscopy is intrusive and time-consuming, and early detection is key to improving survival. Here, the authors propose a metabolite-based model to enable early detection. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the predictive factors of therapeutic efficacy for chronic subdural hematoma (CSDH) patients receiving atorvastatin combined with dexamethasone therapy by using clinical imaging characteristics in conjunction with computed tomography (CT) texture analysis (CTTA). Clinical imaging characteristics and CT texture parameters at admission were retrospectively investigated in 141 CSDH patients who received atorvastatin combined with dexamethasone therapy from June 2019 to December 2022. The patients were divided into a training set (n = 81) and a validation set (n = 60). Patients in the training data were divided into two groups based on the effectiveness of the treatment. Univariate and multivariate analyses were performed to assess the potential factors that could indicate the prognosis of CSDH patients in the training set. The receiver operating characteristic (ROC) curve was used to analyze the predictive efficacy of the significant factors in predicting the prognosis of CSDH patients and was validated using a validation set. The multivariate analysis showed that the hematoma density to brain parenchyma density ratio, singal min (minimum) and singal standard deviation of the pixel distribution histogram, and inhomogeneity were independent predictors for the prognosis of CSDH patients based on atorvastatin and dexamethasone therapy. The area under the ROC curve between the two groups was between 0.716 and 0.806. As determined by significant factors, the validation's accuracy range was 0.816 to 0.952. Clinical imaging characteristics in conjunction with CTTA could aid in distinguishing patients with CSDH who responded well to atorvastatin combined with dexamethasone. [ABSTRACT FROM AUTHOR]

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The objective of this study is to explore whether craniocervical manual lymphatic drainage (cMLD) can promote hematoma absorption and increase the efficiency of atorvastatin-based conservative treatment in chronic subdural hematoma (CSDH) patients. All CSDH patients treated with atorvastatin-based therapy between October 2020 and February 2022 in our department were retrospectively screened for enrollment. The patients were divided into the control and cMLD groups according to whether cMLD was performed. Head CT or MR images in both groups were obtained before the treatment and 2 weeks and 4 weeks after the treatment. MR images of the deep cervical lymphatic nodes (dCLNs) in 23 patients were obtained in the cMLD group before and approximately 2 weeks after treatment. The volumes of the dCLNs and hematoma were calculated. The primary outcomes are the differences in hematoma volume reduction after 4 weeks of treatment. The secondary outcomes were (1) the differences in hematoma volume reduction between the patients in these two groups in the 2nd week, (2) the dCLN volume change in the cMLD group before and after 2 weeks of treatment, and (3) the percentage of patients who transitioned to surgery because of failure to the conservative treatment. A total of 106 consecutive patients were enrolled in this study for analysis; 54 patients received atorvastatin-based treatment (control group), and 52 were treated with both atorvastatin-based treatment and cMLD (cMLD group). At baseline, the mean hematoma volume was 76.53 ± 42.97 ml in the control group and 88.57 ± 49.01 ml in the cMLD group (p = 0.181). In the 4th week, the absolute number of hematoma reductions (20.79 ± 34.73 ml vs. 37.28 ± 28.24 ml, p = 0.009) and percentage of hematoma reductions (22.58% ± 60.01% vs. 46.43% ± 30.12%, p = 0.012) in the cMLD group were greater than those in the control group. After 2 weeks of treatment, the absolute number of hematoma reductions showed no difference in the two groups, while the percentage of hematoma reduction was higher in the cMLD group (18.18% ± 24.61% vs. 2.08% ± 25.72%, p = 0.001). One patient in cMLD and 8 patients in the control group were transitioned to receive surgical treatment. The dCLN volumes in 23 experimental patients increased significantly after 2 weeks of treatment in the cMLD group (p = 0.032). There were no severe side effects that needed to be reported. Combined with atorvastatin-based therapy, cMLD can promote hematoma absorption and decrease the surgery rate, which provides a new therapeutic strategy for CSDH. [ABSTRACT FROM AUTHOR]

Accurate motion feature extraction and recognition provide critical information for many scientific problems. Herein, a new paradigm for a wearable seamless multimode sensor with the ability to decouple pressure and strain stimuli and recognize the different joint motion states is reported. This wearable sensor is integrated into a unique seamless structure consisting of two main parts (a resistive component and a capacitive component) to decouple the different stimuli by an independent resistance-capacitance sensing mechanism. The sensor exhibits both high strain sensitivity (GF = 7.62, 0–140% strain) under the resistance mechanism and high linear pressure sensitivity (S = 3.4 kPa−1, 0–14 kPa) under the capacitive mechanism. The sensor can differentiate the motion characteristics of the positions and states of different joints with precise recognition (97.13%) with the assistance of machine learning algorithms. The unique integrated seamless structure is achieved by developing a layer-by-layer casting process that is suitable for large-scale manufacturing. The proposed wearable seamless multimode sensor and the convenient process are expected to contribute significantly to developing essential components in various emerging research fields, including soft robotics, electronic skin, health care, and innovative sports systems applications. [ABSTRACT FROM AUTHOR]

Metabolic reprogramming evolves during cancer initiation and progression. However, thorough understanding of metabolic evolution from preneoplasia to lung adenocarcinoma (LUAD) is still limited. Here, we perform large-scale targeted metabolomics on resected lesions and plasma obtained from invasive LUAD and its precursors, and decipher the metabolic trajectories from atypical adenomatous hyperplasia (AAH) to adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC), revealing that perturbed metabolic pathways emerge early in premalignant lesions. Furthermore, three panels of plasma metabolites are identified as non-invasive predictive biomarkers to distinguish IAC and its precursors with benign diseases. Strikingly, metabolomics clustering defines three metabolic subtypes of IAC patients with distinct clinical characteristics. We identify correlation between aberrant bile acid metabolism in subtype III with poor clinical features and demonstrate dysregulated bile acid metabolism promotes migration of LUAD, which could be exploited as potential targetable vulnerability and for stratifying patients. Collectively, the comprehensive landscape of the metabolic evolution along the development of LUAD will improve early detection and provide impactful therapeutic strategies. Metabolic reprogramming occurs during tumor progression. Here the authors decipher metabolic trajectories from preneoplasia to lung adenocarcinoma in tumor samples and identify plasma metabolites as potential predictive biomarkers for early detection. [ABSTRACT FROM AUTHOR]

Cytokine release syndrome (CRS) is a major cause of the multi-organ injury and fatal outcome induced by SARS-CoV-2 infection in severe COVID-19 patients. Metabolism can modulate the immune responses against infectious diseases, yet our understanding remains limited on how host metabolism correlates with inflammatory responses and affects cytokine release in COVID-19 patients. Here we perform both metabolomics and cytokine/chemokine profiling on serum samples from healthy controls, mild and severe COVID-19 patients, and delineate their global metabolic and immune response landscape. Correlation analyses show tight associations between metabolites and proinflammatory cytokines/chemokines, such as IL-6, M-CSF, IL-1α, IL-1β, and imply a potential regulatory crosstalk between arginine, tryptophan, purine metabolism and hyperinflammation. Importantly, we also demonstrate that targeting metabolism markedly modulates the proinflammatory cytokines release by peripheral blood mononuclear cells isolated from SARS-CoV-2-infected rhesus macaques ex vivo, hinting that exploiting metabolic alterations may be a potential strategy for treating fatal CRS in COVID-19. Metabolism changes can modulate immune responses in many contexts, and vice versa. Here the authors associate metabolomic, as well as cytokine and chemokine, data from stratified COVID-19 patients to find that arginine, tryptophan and purine metabolic pathways correlate with hyperproliferation, thus hinting at potential therapeutic targets for severe COVID-19 patients. [ABSTRACT FROM AUTHOR]

Multi-pole arrangements in magnetorheological plane finishing technology have been investigated in this study. A method of combining the material removal mechanism of micro-points using the empirical Preston equation is proposed to establish a prediction model for surface flatness, and the new Semiconductor Equipment and Materials International (SEMI) standard has been used to evaluate workpiece surface flatness. Based on the model, the effects of process parameters (polishing time, speed ratio, translational amplitude, polishing gap, etc.) on the flatness of workpieces with different shapes are predicted through simulation, and the effects of multi-pole arrangements are explored. The results of the analysis indicate that with changes in process parameters, the extent of change in surface flatness differs based on the shape of the workpiece. After polishing, concave workpieces show the highest levels of surface flatness. From simulations of magnetic pole arrangements, it is also found that magnetic field generators with different magnetic pole arrangements can be used for workpieces with different shapes to improve their surface flatness. Experiments with a workpiece with its shape measured using a white light interferometer showed that the surface flatness improved from being 33.561 μm initially to 21.822 μm after polishing, thereby demonstrating the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Magnetorheological finishing (MRF), considered as a promising polishing technique that can finish a nano-level smooth surface and free of surface or subsurface damage, has been widely utilized in ultra-smooth polishing of hard-to-machine materials. MRF process is mainly rely on shear stress to remove material. In this study, α-cellulose used as an additive agent to improve the rheological properties of magnetorheological polishing slurry (MRPS). The rheometer measurement results and polishing results showed that: (1) α-cellulose can enhance the shear stress of MRPS, but increased the apparent viscosity of MRPS. (2) α-cellulose can effectively improve the stability of MRPS, when the weight fraction of α-cellulose was 0.6 wt%, both stability and internal uniform of MRPS can be obtained. (3) If the weight fraction of α-cellulose was bigger than 0.6 wt%, the machining ability of MPRS was stable and the smooth polished surface can be obtained. [ABSTRACT FROM AUTHOR]

Magnetorheological finishing, considered as a promising polishing technique that can finish a nano-level smooth surface and free of surface or subsurface damage, has been widely utilized in ultra-smooth polishing of hard-to-machine materials. However, there are still several practical weaknesses in magnetorheological finishing (MRF) applied for wafer surface polishing. In this study, a new method using MRF effect was proposed for wafer polishing. Concretely, porous foam was used as a storage carrier of MR slurry, and thus, MR slurry can be bounded in porous foam in the finishing process (cluster MR-porous foam polishing, CMRPP). In this paper, an experimental rig was constructed to achieve CMRPP mechanism, the processing principle and material removal process in CMRPP were analyzed, and CMRPP experiments were conducted to investigate the effects of porous foam on surface polishing. The results indicate the following: (1) The polishing forces in CMRPP were increased compared to that of a cluster MR polishing without porous foam (CMRP), and CMRPP can get a greater shear force than of CMRP at a same normal force; (2) CMRPP can well hinder the solid-liquid separation and sustain the stability of the slurry performance; (3) CMRPP achieved a higher volumetric removal rate than that of CMRP and improving of material removal efficiency; (4) CMRPP can effectively achieve a nano-level smooth surface compared to that of CMRP. [ABSTRACT FROM AUTHOR]

Recently, flexible strain sensors with excellent stretchability and sensitivity have attracted increasing interests. Most flexible strain sensors have multifunctional applications in human motion monitoring, transparent and wearable electronic systems, however, they also can be applied in other fields such as structural health monitoring (SHM). In this paper, a flexible strain sensor which was assembled by adhering graphene mesh film on liquid crystal polymer substrate constructed by an efficient, low-cost fabrication strategy for applying in SHM is presented. By means of monitoring the relative resistance change of graphene mesh film of the strain sensor, the strain caused by the minor displacement of the structure could be detected. The experiment results showed that the strain sensor had a high gauge factor (375–473) under different tensile strain (0.1–1.4%) and good stability (1000 test cycles). It can be verified that the sensor has high sensitivity and good stability, which makes it have potential application in SHM. [ABSTRACT FROM AUTHOR]

A piezoresistive pressure sensor with the electrostatic self-detecting structure was developed in the paper, which can solve the issue of low efficiency and time-consuming drawbacks of the traditional method in testing and calibrating the sensor with the specialized equipment. The theoretical model of the composite membrane piezoresistive sensor was established, the analytical model of the electrostatic force driven by an electrostatic voltage was obtained, a feasible fabrication process based on flip-chip process was proposed based on the MEMS processing, the pressure sensor and its detection structure were manufactured to verify the validity of the model in the paper. From the experiment results, it can be verified that the sensitivity of the pressure sensor was 1.77 mV/hPa and the non-linearity was 1.19% respectively. At the same time, the electrostatic force used to test sensor calibration could replace the loaded pressure in the range between 110 and 500 hPa. [ABSTRACT FROM AUTHOR]

Silicon carbide (SiC) ceramics play a key role in various engineering applications due to their desirable properties, however, they are typical hard-brittle materials and famous for their poor machinability. Ultrasonic-assisted grinding, a processing method hybridizing the conventional grinding and ultrasonic vibration (UV) machining, is employed as the one applicable machining method for hard-brittle materials. This study focuses on internal grinding of SiC ceramics with the assistance of the UV, and its ductile-brittle transition behavior in the grinding process were investigated experimentally. Following the processing principal of internal grinding and UV machining (i.e., UV-assisted internal grinding, UVAIG), the UVAIG experiment rig were constructed. Conventional internal grinding (CIG) tests, i.e., internal grinding without UV, were also performed on the constructed rig for comparison. In addition, the grinding force and the grinding chips variation behavior with the UV amplitude were also investigated to explore the ductile-brittle transition mechanism in UVAIG. The experiment results evidence that (1) ductile mode grinding is easily achieved in UVAIG, and the critical depth of the cut is deeper in UVAIG than that in CIG, i.e., 0.072 μm in CIG and 0.093 μm in UVAIG; (2) increasing of the critical depth of cut in UVAIG is likely owing to the lower grinding force in UVAIG than that in CIG; and (3) the ultrasonic vibration acted on the axis of the grinding wheel helps in the removal of material on the work-surface, but decreases the grinding energy in the ductile-brittle transition. [ABSTRACT FROM AUTHOR]

The sexual reproduction of annual and perennial Zostera marina was investigated in Moon Lake, Shandong, China. Based on the disturbance and stress regimes, the Z. marina beds were classified into five types: intertidal annual (IA) and perennial (IP) eelgrass patches, subtidal patch area (PA), meadow margin (MM) and meadow center (MC). Seed dispersal was investigated using artificial seagrass units in the five areas and another two areas [adjacent bare area and Zostera japonica meadow (Zj)]. Total and flowering shoot density and aboveground biomass of flowering shoots per unit area were higher in PA and MM, and lower in IA and IP, whereas the total biomass per unit area in MC showed the highest value. Reproductive effort (RE) in IA showed negative response to intertidal stress, while in perennial IP, PA and MM it showed significantly positive response to anthropogenic or natural disturbances. The density-based RE in perennial IP, PA and MM was 1.1-, 5.1- and 5.1-fold higher than that in MC, while in annual IA it was 0.46-fold lower. Additionally, the biomass-based RE in IP, PA and MM was 1.8-, 3.5- and 3.8-fold higher than that in MC, while the RE in IA was 0.84-fold lower. The estimated seed production per unit area was much greater in PA (60,793 ± 9,843 seeds m) and MM (43,414 ± 8,718 seeds m) than in IA (416 ± 83 seeds m), IP (3,820 ± 1,470 seeds m) and MC (9,779 ± 631 seeds m), while the seed density ranged from 24 ± 6 to 584 ± 56 seeds m. Results suggested that in response to disturbances and stress, Z. marina in subtidal areas increased their RE and seed production and thus seeds were available to be dispersed into areas where seed production was limited. [ABSTRACT FROM AUTHOR]

Zika virus (ZIKV) infection during pregnancy can cause microcephaly in newborns, yet the underlying mechanisms remain largely unexplored. Here, we reveal extensive and large-scale metabolic reprogramming events in ZIKV-infected mouse brains by performing a multi-omics study comprising transcriptomics, proteomics, phosphoproteomics and metabolomics approaches. Our proteomics and metabolomics analyses uncover dramatic alteration of nicotinamide adenine dinucleotide (NAD + )-related metabolic pathways, including oxidative phosphorylation, TCA cycle and tryptophan metabolism. Phosphoproteomics analysis indicates that MAPK and cyclic GMP-protein kinase G signaling may be associated with ZIKV-induced microcephaly. Notably, we demonstrate the utility of our rich multi-omics datasets with follow-up in vivo experiments, which confirm that boosting NAD + by NAD + or nicotinamide riboside supplementation alleviates cell death and increases cortex thickness in ZIKV-infected mouse brains. Nicotinamide riboside supplementation increases the brain and body weight as well as improves the survival in ZIKV-infected mice. Our study provides a comprehensive resource of biological data to support future investigations of ZIKV-induced microcephaly and demonstrates that metabolic alterations can be potentially exploited for developing therapeutic strategies., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)