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Background: The rapid aging of Korea's population underscores the urgent need for effective programs to enhance the well-being and longevity of the elderly. This study presents preliminary results from the Korean project, examining the impact of cost-effective and accessible exercise programs on functional performance of older people and to determine the long-term maintenance of intervention. Methods: We randomized 90 older adults aged ≥65 years to the walking group (WG), resistance + walking (RWG), or active control (CG) group. We designed a 12-week main intervention (supervised resistance training 2 d/week and individual walking exercise) and a 12-week follow-up through self-directed exercise (same protocol but unsupervised). The participants’ mini mental state examination, color-word Stroop test and 5-time sit to stand, timed up & go, handgrip strength, and knee extensor strength tests were assessed at pre, post, as well as follow-up. Results: For the RWG group, significant improvements were found in timed up & go (P

Abstract Sarcopenic obesity (SO) is characterized by concomitant sarcopenia and obesity and presents a high risk of disability, morbidity, and mortality among older adults. However, predictions based on sequential neural network SO studies and the relationship between physical fitness factors and SO are lacking. This study aimed to develop a predictive model for SO in older adults by focusing on physical fitness factors. A comprehensive dataset of older Korean adults participating in national fitness programs was analyzed using sequential neural networks. Appendicular skeletal muscle/body weight was defined as SO using an anthropometric equation. Independent variables included body fat (BF, %), waist circumference, systolic and diastolic blood pressure, and various physical fitness factors. The dependent variable was a binary outcome (possible SO vs normal). We analyzed hyperparameter tuning and stratified K-fold validation to optimize a predictive model. The prevalence of SO was significantly higher in women (13.81%) than in men, highlighting sex-specific differences. The optimized neural network model and Shapley Additive Explanations analysis demonstrated a high validation accuracy of 93.1%, with BF% and absolute grip strength emerging as the most influential predictors of SO. This study presents a highly accurate predictive model for SO in older adults, emphasizing the critical roles of BF% and absolute grip strength. We identified BF, absolute grip strength, and sit-and-reach as key SO predictors. Our findings underscore the sex-specific nature of SO and the importance of physical fitness factors in its prediction.

Background As a relatively novel approach to enhancing skeletal muscle health, mixed protein supplementation has shown similar responses to whey protein. However, no previous studies have examined its impact on golf swing performance. This study aimed to examine the effect of mixed protein supplementation on the swing performance and muscle strength of casual golfers.Methods Sixty participants with a handicap of less than 20 were recruited and randomly assigned to a double-blind, placebo-controlled study design. The participants were divided into two groups: a mixed protein group (MG, n = 30), and a placebo control group (CG, n = 30). They were instructed to ingest either a supplement containing casein calcium, whey protein, and isolated pea protein, or a placebo, once daily for 8 weeks. Pre- and posttests consisted of anthropometric measurements, muscle strength (isokinetic knee and trunk strength, and handgrip strength), 2-minute push-ups, balance, and golf swing performance using a driver and 7-iron.Results After the 8-week supplementation period, ANCOVA, using baseline values as covariates, revealed significant differences for driver distance (p = .004) and driver ball speed (p .05).Conclusion The intake of a mixed protein containing both animal and plant proteins had positive effects on golf performance and muscle function. Therefore, mixed proteins may represent a safe and effective approach to enhancing skeletal muscle health in golf players.

Background: Patients with colorectal cancer commonly experience disturbances in coagulation homeostasis. Activation of the coagulation system contributes to cancer-associated thrombosis as the second risk factor for death in cancer patients. This study intended to discover coagulation-related genes and construct a risk model for colorectal cancer patients' prognosis. Methods: Coagulation-related genes were identified by searching coagulation-related pathways in the Molecular Signatures Database. Transcriptomic data and clinical data were downloaded from the Cancer Genome Atlas and Gene Expression Omnibus datasets. Univariate Cox and backward stepwise regression were utilized to identify prognosis-related genes and construct a predictive risk model for the training cohort. Next, survival analysis determines the risk model's predictive power, correlation with clinicopathological characteristics, and nomogram. Additionally, we characterized the variances in immune cell infiltration, somatic mutations, immune checkpoint molecules, biological functions, and drug sensitivity between the high- and low-score patients. Result: Eight hundred forty-five genes were obtained by searching the theme term ''coagulation'' after de-duplication. After univariate regression analysis, 69 genes correlated with prognosis were obtained from the Cancer Genome Atlas dataset. A signature consisting of 17 coagulation-related genes was established through backward stepwise regression. The Kaplan-Meier curve indicated a worse prognosis for high-score patients. Time-dependent receiver operating characteristic curve analysis demonstrated high accuracy in predicting overall survival. Further, the results were validated by two independent datasets (GSE39582 and GSE17536). Combined with clinicopathological characteristics, the risk model was proven to be an independent prognostic factor to predict poor pathological status and worse prognosis. Furthermore, high-score patients had significantly higher stromal cell infiltration. Low-score patients were associated with high infiltration of resting memory CD4+ T cells, activated CD4+ T cells, and T follicular helper cells. The low-score patients exhibited increased expression of immune checkpoint genes, and this might be relevant to their better prognosis. High-score patients exhibited lower IC50 values of Paclitaxel, Rapamycin, Temozolomide, Cyclophosphamide, etc. The differential signaling pathways mainly involve the calcium signaling pathway and the neuroactive ligand-receptor interaction. Lastly, a nomogram was constructed and showed a good prediction. Conclusion: The prognostic signature of 17 coagulation-related genes had significant prognostic value for colorectal cancer patients. We expect to improve treatment modalities and benefit more patients through research on molecular features.

Abstract Background The morbidity of cancer keeps growing worldwide, and among that, the colorectal cancer (CRC) has jumped to third. Existing early screening tests for CRC are limited. The aim of this study was to develop a diagnostic strategy for CRC by plasma metabolomics. Methods A targeted amino acids metabolomics method was developed to quantify 32 plasma amino acids in 130 CRC patients and 216 healthy volunteers, to identify potential biomarkers for CRC, and an independent sample cohort comprising 116 CRC subjects, 33 precancerosiss patients and 195 healthy volunteers was further used to validate the diagnostic model. Amino acids-related genes were retrieved from Gene Expression Omnibus and Molecular Signatures Database and analyzed. Results Three were chosen out of the 32 plasma amino acids examined. The tryptophan / sarcosine / glutamic acid -based receiver operating characteristic (ROC) curve showed the area under the curve (AUC) of 0.955 (specificity 83.3% and sensitivity 96.8%) for all participants, and the logistic regression model were used to distinguish between early stage (I and II) of CRC and precancerosiss patients, which showed superiority to the commonly used carcinoembryonic antigen. The GO and KEGG enrichment analysis proved many alterations in amino acids metabolic pathways in tumorigenesis. Conclusion This altered plasma amino acid profile could effectively distinguish CRC patients from precancerosiss patients and healthy volunteers with high accuracy. Prognostic tests based on the tryptophan/sarcosine/glutamic acid biomarkers in the large population could assess the clinical significance of CRC early detection and intervention. Graphical Abstract

This study aimed to investigate the effect of Kinect-based mixed reality (KMR) exercise and unsupervised individual exercise on health-related fitness. A total of 27 participants underwent cardiorespiratory fitness tests for the inclusion criteria and were randomly assigned to three groups: a KMR group (KMRG), an unsupervised individual group (UIG), or a control group (CG). Pre and post-tests were conducted to measure Maximum oxygen uptake (VO₂max), body composition, upper and lower-body (LB) muscle strength, and endurance. KMRG and UIG attended exercise sessions 3 days per week for 8 weeks. KMRG used the KMR device and UIG used an instructive banner for exercise. All groups maintained their daily routines and submitted diet records every 4 weeks. Results showed that VO₂max, upper-body muscle endurance, and LB muscle endurance of knee extension was increased in KMRG and UIG. LB muscle strength in knee flexion was increased in UIG and LB muscle endurance in knee flexion was increased in KMRG. VO₂max, LB muscle strength, and LB muscle endurance were greater in KMRG than in CG. LB muscle strength in knee flexion was greater in KMRG than in UIG. Body fat was increased and skeletal muscle mass was decreased in CG. KMR exercise showed better performance than unsupervised individual (UI) exercise, and the exercise program was effective in both KMR and UI environments. These findings contribute to the growing evidence supporting the use of technology-based exercise interventions as a potential strategy to enhance health-related fitness.

Summary: Upregulation of FGL1 helps tumors escape from immune surveillance, and therapeutic antibodies targeting FGL1 have potential as another immune checkpoint inhibitor. However, the underlying mechanism of high FGL1 protein level in cancers is not well defined. Here, we report that FBXO38 interacts with and ubiquitylates FGL1 to negatively regulate its stability and to mediate cancer immune response. Depletion of FBXO38 markedly augments FGL1 abundance, not only suppressing CD8+ T cell infiltration and enhancing immune evasion of tumor but also increasing inflammation in mice. Importantly, we observe a negative correlation of FBXO38 with FGL1 and IL-6 in non-small cell lung cancer specimens. FGL1 and IL-6 levels positively correlate with TNM (tumor, lymph node, metastasis) stages, while FBXO38 and the infiltrating CD8+ T cells negatively correlate with TNM stages. Our study identifies a mechanism regulating FGL1 stability and a target to enhance the immunotherapy and suggests that the combination of anti-FGL1 and anti-IL-6 is a potential therapeutic strategy for cancer immunotherapy.

Background: Regular physical activity is an effective means to enhance university students’ subjective well-being. However, current research needs to understand how physical activity enhances the subjective well-being of Chinese university students. Therefore, the study investigated the mechanism of physical activity’s impact on university students’ subjective well-being and the mediating roles of cognitive reappraisal and resilience in this mechanism. Methods: The physical activity scale, subjective well-being scale, cognitive reappraisal scale and resilience scale were used to investigate 1350 university students, and the relationship between physical activity, cognitive reappraisal, resilience and university students’ subjective well-being was verified through correlation analysis, regression analysis and a Bootstrap method. Results: (1) There is a significant positive correlation between physical activity, cognitive reappraisal, resilience and university students’ subjective well-being (p < 0.01); (2) physical activity, cognitive reappraisal and resilience all have a significant positive effects on university students’ subjective well-being (p < 0.01); (3) cognitive reappraisal and resilience have significant mediating roles in the process of physical activity affecting university students’ well-being, with mediating-effect values of 0.052 and 0.285; (4) the chain-mediating role of cognitive reappraisal and resilience in the process of physical activity affecting university students’ well-being is significant, with the chain-mediating effect value of 0.062. Conclusion: Promoting university students’ participation in physical activity not only directly enhances university students’ subjective well-being but also indirectly improves university students’ subjective well-being through cognitive reappraisal and resilience.

We report a monolithic heterodyne receiver that uses the AlGaN/GaN nonlinear transmission line as a local oscillator and a mixer simultaneously. This heterodyne receiver has a high RF bandwidth from 80 to 360 GHz and a high intermediate frequency bandwidth of 18 GHz. These results indicate that this nonlinear transmission line receiver has promising potential in broadband spectrum analysis.

The rapid development of modern quantum mechanical theories and computational resources facilitates extended characterization of molecular systems of increasing size and complexity, including chromophores of biochemical or technological interest. Efficient and accurate computations of molecular structure and properties in the ground and excited electronic states are routinely performed using density functional theory (DFT) and its time-dependent (TD-DFT) counterpart. However, the direct comparison with experiment requires simulation of electronic absorption or emission spectra, for which inclusion of vibrational effects leads to more realistic line shapes while at the same time allowing for more reliable interpretation and prediction of optical properties and providing additional information that is not available from experimental low-resolution UV-vis spectra. Computational support can help identify the most interesting chromophores among a large number of potential candidates for designing new materials or sensors, as well as unraveling effects contributing to the overall spectroscopic phenomena. In this perspective, recently developed viologen derivatives (1,1′-disubstituted-4,4′-bipyridyl cation salts, viol) are selected as test cases to illustrate the advantages of spectroscopic theoretical methodologies, which are still not widely used in “chemical” interpretation. Although these molecules are characterized by improved stability as well as the dual function of chromism and luminescence, their detailed spectroscopic characterization is hampered due to the availability of only low-resolution experimental spectra. DFT-based absorption and emission spectra are exploited in the analysis of optical properties, allowing detailed investigation of vibrational effects and gaining more insights on the structure–spectra relationship, which can be extended to develop further viologen dyes with improved optical properties.

Background A predictive tool is required to identify the cancer-specific survival in rectal cancer (RC) patients who have opted to receive preoperative radiotherapy. Methods A database containing the data on RC patients’ records of Surveillance, Epidemiology, and End Results (SEER) receiving surgery during 2000–2014 was selected. All patients received neoadjuvant radiotherapy (NR). The correlation of clinicopathological parameters was analyzed using the Chi-square test and the survival risk factors were analyzed using the Cox proportional hazards analysis (univariate and multivariate). Finally, the nomogram was developed and validated to visually represent an accurate prediction of the probability of 3- and 5-year cancer-specific survival (CSS) based on the screened variables of the cohort. Results 11,499 rectal cancer patients were included in our cohort. Patients’ records were randomly allocated to either the development or validation cohorts based on an equal ratio (1:1). Performing the multivariate Cox regression analysis incorporating these variables in the development cohort determined 11 independent prognostic factors. Statistically significant differences were recorded among subgroups using log-rank tests, which confirmed the appropriateness and acceptability of factor stratifications. Then, the nomogram was constructed and its concordance index (C-index) values in the development cohort (0.720) and validation cohort (0.717) were evaluated to be higher (P

Abstract Background and Aims The annual incidence of early‐onset colorectal cancer (EOCRC) is increasing at an alarming rate. The prognosis of EOCRC remains controversial, and whether the early onset is a risk factor for colorectal cancer remains unclear. Methods We searched four electronic bibliographic databases from database inception to April 25, 2022 for studies that included both early‐ and later‐onset patients and performed a prognostic analysis. Random‐effects models were used to summarize the prognostic information extracted by the investigators, including overall survival (OS), cancer‐special survival (CSS), and disease‐free survival (DFS). Network meta‐analysis (NMA) was used to compare patients' long‐term prognoses in different age subgroups. Results After 694 reports were screened, 13 studies were included in the final analysis, with a total of 448,781 CRC cases. In the meta‐analysis of the 5‐year OS, EOCRC had a better prognosis compared to LOCRC (hazard ratio [HR] 0.87, 95% confidence interval [CI], 0.74–0.99; relative risk [RR] 0.83, 95% CI, 0.78–0.89). No difference in prognosis was found between the two groups in terms of 5‐year CSS (RR 0.99, 95% CI, 0.93–1.05), 5‐year DFS (RR 0.90, 95% CI, 0.74–1.09), and short‐term OS. In the NMA, patients aged

Spatially resolved transcriptomics (SRT) provides an unprecedented opportunity to investigate the complex and heterogeneous tissue organization. However, it is challenging for a single model to learn an effective representation within and across spatial contexts. To solve the issue, we develop a novel ensemble model, AE-GCN (autoencoder-assisted graph convolutional neural network), which combines the autoencoder (AE) and graph convolutional neural network (GCN), to identify accurate and fine-grained spatial domains. AE-GCN transfers the AE-specific representations to the corresponding GCN-specific layers and unifies these two types of deep neural networks for spatial clustering via the clustering-aware contrastive mechanism. In this way, AE-GCN accommodates the strengths of both AE and GCN for learning an effective representation. We validate the effectiveness of AE-GCN on spatial domain identification and data denoising using multiple SRT datasets generated from ST, 10x Visium, and Slide-seqV2 platforms. Particularly, in cancer datasets, AE-GCN identifies disease-related spatial domains, which reveal more heterogeneity than histological annotations, and facilitates the discovery of novel differentially expressed genes of high prognostic relevance. These results demonstrate the capacity of AE-GCN to unveil complex spatial patterns from SRT data.

The global ionosphere map (GIM) total electron content (TEC) data are extensively employed to statistically study the seismic ionospheric disturbance characteristics. Due to the limitation of spatial coverage of ground-based GNSS receivers, in many regions, the GIM TEC results are obtained by interpolation or extrapolation, and therefore the actual accuracy is different. In this paper, based on the CMONOC GNSS data, a high-precision regional ionospheric map (RIM) model over China is established, and the assessment and analysis of the post-processed IGS GIM over China are conducted. Statistical results show that the average RMS of IGS GIM over China is less than 2 TECu. The comparison of the TEC values calculated by the GIM with the RIM shows that the two models give similar results. The Bias and STD of the difference over most of China is less than 2 TECu except in some low latitude areas. Meanwhile, the correlation between GIM and RIM is better in the daytime than at night, and it is not affected by space electromagnetic disturbance. The assessment results of accuracy in this paper are only applicable to the China region, and the accuracy of other regions needs to be further assessed.

BackgroundDiversion colitis (DC) is nonspecific inflammation of the distal intestinal mucosa following disruption of colonic continuity with colonic dysfunction. The colonscopic score is a good tool for differentiating the severity of patients with DC. At present, no studies have analyzed the pathogenesis of DC from the perspective of the diversity and and differences of intestinal flora.MethodsRetrospective study: Clinical information were collected from patients with low rectal cancer admitted to the Department of Anorectal Surgery, Changzheng Hospital, from April 2017 to April 2019. These patients underwent laparoscopic low anterior resection (LAR) combined with terminal ileum enterostomy (dual-chamber). We used chi-square test to comparethe clinical baseline information, clinical symptoms, and colonscopic characteristics between different severity of DC. Propsective oberservational study: We recruited 40 patients with laparoscopic anterior low resection combined with terminal ileum enterostomy and they were further classified into mild group and severe group according to the scores of colonscopic examinations for DC. 16s-rDNA sequencing was carried out to analyze the diversity and and differences of intestinal flora in the intestinal lavage fluid of the two groups.ResultsIn retrospective study, we found that age, BMI, history of diabetes, and symptoms associated with the stoma state were the independent risk factors that affect DC severity (P

Main pointOur retrospective analysis of a large number of cases found in patients with primary colorectal cancer (CRC) carrying positive HBsAg inhibited the occurrence of synchronous liver metastases (SLM). However, liver cirrhosis caused by non-HBV factors promoted the occurrence of SLM.ObjectivesThis study aimed to investigate the effect of HBV on the occurrence of synchronous liver metastases (SLM) of colorectal cancer (CRC).MethodsUnivariate and multivariate analyses were used to analyze the influence of clinical parameters on the occurrence of SLM.ResultsA total of 6, 020 patients with primary CRC were included in our study, of which 449 patients carrying HBsAg(+) accounted for 7.46%. 44 cases of SLM occurred in the HBsAg(+) group, accounting for 9.80%, which was much lower than 13.6% (758/5571) in the HBsAg(-) group (X=5.214, P=0.022). Among CRC patients with HBsAg(-), the incidence of SLM was 24.9% and 14.9% in the group with high APRI and FIB-4 levels, respectively, which were significantly higher than that in the compared groups (12.3% and 12.5%, all P

Purpose: The purpose of this study was to investigate the association between moderate to vigorous physical activity (MVPA), sedentary behavior, fruit and vegetable intake, and the risk of sarcopenia among older Chinese adults. Methods: This cross-sectional study enrolled 5418 older Chinese adults who participated in the Study on Global Aging and Adult Health (SAGE). Participants reported information about their physical activity, sedentary behavior, and dietary habits (fruit and vegetable intake). Sarcopenia was defined as the presence of low skeletal muscle mass and either a slow gait speed or weak handgrip strength. A multiple logistic regression model was employed to determine the relationship between MVPA, sedentary behavior, fruit and vegetable intake, and the risk of sarcopenia. Results: Only 32.63% of participants met all three recommendations (for MVPA, sedentary behavior, and fruit and vegetable intake). Compared with meeting none of the recommendations, meeting all three recommendations was associated with a lower risk of sarcopenia (OR = 0.63, 95% CI = 0.41–0.98). Moreover, meeting the recommendation for sufficient fruit and vegetable intake (OR = 0.69, 95% CI = 0.58–0.83), MVPA and fruit/vegetable intake (OR = 0.67, 95% CI = 0.52–0.86), and sedentary behavior and fruit/vegetable intake (OR = 0.69, 95% CI = 0.48–0.98) was associated with a lower risk of sarcopenia. Conclusion: Our findings indicate that in this large representative sample of older Chinese adults, meeting lifestyle recommendations for MVPA, sedentary behavior, and fruit and vegetable intake protected against sarcopenia.

Background: Although mRNA vaccines have been effective against multiple cancers, their efficacy against stomach adenocarcinoma (STAD) remains undefined. Immunotyping can indicate the comprehensive immune status in tumors and their immune microenvironment, which is closely associated with therapeutic response and vaccination potential. The aim of this study was to identify potential antigens in STAD for mRNA vaccine development, and further distinguish immune subtypes of STAD to construct an immune landscape for selecting suitable patients for vaccination.Methods: The gene expression and clinicopathological features of patients with gastric cancer were downloaded from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression Program (GTEx). 729 samples from GSE66229 and GSE84437 were downloaded through GEO and were used as the validation cohorts. Differential gene expression, genetic alterations and prognosis were analyzed using the R package, cBioPortal program and Kaplan-Meier. The relationship between tumor antigens and immune cells was evaluated and plotted by TIMER. ConsensusClusterPlus was used for consistency matrix construction and data clustering, and graph learning-based dimensional reduction was used to depict immune landscape. WGCNA was used to estimate the relationship between the color modules and immune subtypes.Results: Two overexpressed and mutated tumor antigens associated with poor prognosis and infiltration of antigen presenting cells were identified in STAD, including RAI14 and NREP. The immune subtypes showed distinct molecular, cellular and clinical characteristics. IS1 and IS2 exhibited immune-activated phenotypes and correlated to better survival compared to IS3, while IS3 tumors was immunologically cold. Immunogenic cell death modulators, immune checkpoints, and CA125, and CEA were also differentially expressed among the three immune subtypes. Finally, the immune landscape of STAD showed a high degree of heterogeneity between individual patients.Conclusion: RAI14 and NREP are potential antigens for developing anti-STAD mRNA vaccine, and patients with IS1 and IS3 tumors may be suitable for vaccination.

Single-cell RNA-sequencing (scRNA-seq) techniques provide unprecedented opportunities to investigate phenotypic and molecular heterogeneity in complex biological systems. However, profiling massive amounts of cells brings great computational challenges to accurately and efficiently characterize diverse cell populations. Single cell discriminant analysis (scDA) solves this problem by simultaneously identifying cell groups and discriminant metagenes based on the construction of cell-by-cell representation graph, and then using them to annotate unlabeled cells in data. We demonstrate scDA is effective to determine cell types, revealing the overall variabilities between cells from eleven data sets. scDA also outperforms several state-of-the-art methods when inferring the labels of new samples. In particular, we found scDA less sensitive to drop-out events and capable to label a mass of cells within or across datasets after learning even from a small set of data. The scDA approach offers a new way to efficiently analyze scRNA-seq profiles of large size or from different batches. scDA was implemented and freely available at https://github.com/ZCCQQWork/scDA.

The integrated structure of graphene single-electron transistor and nanostrip electrometer was prepared using the semiconductor fabrication process. Through the electrical performance test of the large sample number, qualified devices were selected from low-yield samples, which exhibited an obvious Coulomb blockade effect. The results show that the device can deplete the electrons in the quantum dot structure at low temperatures, thus, accurately controlling the number of electrons captured by the quantum dot. At the same time, the nanostrip electrometer coupled with the quantum dot can be used to detect the quantum dot signal, that is, the change in the number of electrons in the quantum dot, because of its quantized conductivity characteristics.

Abstract The aim of our study was to explore the value of the 8th edition TNM staging system on evaluating the prognosis of colorectal carcinoid. Colorectal carcinoid patients between 1988 and 2015 were selected in the Surveillance, Epidemiology, and End Results Program (SEER) database for analysis. About 4286 patients with colorectal carcinoid tumors were identified, of which were carcinoid tumor NOS (n = 1726), neuroendocrine carcinoma (NEC) (n = 1346) and other carcinoid tumor (OCT) (n = 591). Worsening 10‐year CSS rates with increasing N status, M status, and SEER historic stage were demonstrated across all three above groups (all P

Human tumors harbor a plethora of microbiota. It has been shown that the composition and diversity of intratumor microbiome are significantly associated with the survival of patients with pancreatic ductal adenocarcinoma (PDAC). However, the association in Chinese patients as well as the effect of different microorganisms on inhibiting tumor growth are unclear. In this study, we collected tumor samples resected from long-term and short-term PDAC survivors and performed 16S rRNA amplicon sequencing. We found that the microbiome in samples with different survival time were significantly different, and the differential bacterial composition was associated with the metabolic pathways in the tumor microenvironment. Furthermore, administration of Megasphaera, one of the differential bacteria, induced a better tumor growth inhibition effect when combined with the immune checkpoint inhibitor anti-programmed cell death-1 (anti-PD-1) treatment in mice bearing 4T1 tumor. These results indicate that specific intratumor microbiome can enhance the anti-tumor effect in the host, laying a foundation for further clarifying the underlying detailed mechanism.

Leafy vegetables are consumed in most daily xdiets worldwide. As living standards improve, food quality, safety requirements, and nutrition are becoming increasingly important to consumers when purchasing leafy vegetables. This study proposes an evaluation and traceability method that can be used to track the nutritional quality of leafy vegetables. Employing the principles of the Hazard Analysis and Critical Control Point (HACCP) system combined with fault tree analysis (FTA), a traceability model for the entire production and sale process of leafy vegetables is constructed. Four common leafy vegetables, spinach, rape, lettuce, and celery are examined in this research to establish a nutritional quality index system using fuzzy mathematics subordinate function method to evaluate nutritional quality. A nutritional quality and safety traceability system based on browser/server architecture and quick response (QR) code is then designed and developed for full traceability of leafy vegetable quality. This method can ensure food safety and hygiene through the control of key factors affecting food safety throughout the entire supply chain process.

Abstract Inflammation is a complex physiological process that poses a serious threat to people’s health. However, the potential molecular mechanisms of inflammation are still not clear. Moreover, there is lack of effective anti-inflammatory drugs that meet the clinical requirement. Procyanidin A1 (PCA1) is a monomer component isolated from Procyanidin and shows various pharmacological activities. This study further demonstrated the regulatory role of PCA1 on lipopolysaccharide (LPS)-stimulated inflammatory response and oxidative stress in RAW264.7 cells. Our data showed that PCA1 dramatically attenuated the production of pro-inflammatory cytokines such as NO, iNOS, IL-6, and TNF-α in RAW264.7 cells administrated with LPS. PCA1 blocked IκB-α degradation, inhibited IKKα/β and IκBα phosphorylation, and suppressed nuclear translocation of p65 in RAW264.7 cells induced by LPS. PCA1 also suppressed the phosphorylation of JNK1/2, p38, and ERK1/2 in LPS-stimulated RAW264.7 cells. In addition, PCA1 increased the expression of HO-1, reduced the expression of Keap1, and promoted Nrf2 into the nuclear in LPS-stimulated RAW264.7 cells. Cellular thermal shift assay indicated that PCA1 bond to TLR4. Meanwhile, PCA1 inhibited the production of intracellular ROS and alleviated the depletion of mitochondrial membrane potential in vitro. Collectively, our data indicated that PCA1 exhibited a significant anti-inflammatory effect, suggesting that it is a potential agent for the treatment of inflammatory diseases.

We used ground-based ionosonde observations at Ganzi (31.2° N, 100.4° E) to validate the COSMIC measurement in the middle latitude region of China during low solar activity. First, eligible data pairs from two kinds of techniques were selected for the validation. Then, we investigated the consistency of the ionospheric parameters’ F layer peak density (NmF2) from selected data pairs at different local times in different seasons, and we also investigated the F layer peak height (hmF2). The correlation of the parameters (including NmF2 and hmF2) were good in general. The correlation coefficients of the NmF2 and hmF2 from all selected data pairs were 0.94 and 0.77, respectively. The correlation coefficients were higher in the daytime than those at night for both the NmF2 and hmF2. The correlation coefficients in different seasons were close to each other for both the NmF2 and hmF2. The NmF2 from the COSMIC tends to be overestimated during the whole day except in the morning; the hmF2 from the COSMIC tends to be overestimated in the morning and underestimated in the afternoon.

In this paper, polystyrene microspheres were firstly prepared by seeded emulsion polymerization, and the uniform monolayer of polystyrene microspheres was prepared on the substrate by the dipping method. Then, polystyrene monolayer film was used as a mask and a low dimensional array structure of gold was prepared by bottom-up self-assembly process. After that, the method of solution etching and annealing was used, and the gold nanoparticle array was post-processed. As a result, gold nanoparticles were recrystallized, with an average diameter of about 50 nm. Subsequently, the semiconductor process was adopted, with focused ion beams induced deposition and electron beam evaporation, and single electron transistors were fabricated, based on self-assembled gold nanoparticles. Finally, the devices were fixed in a liquid helium cryostat and Coulomb blockade was observed at 320 mK. It is a novel fabrication of a single electron transistor based on gold nanoparticle array template and prepared with polystyrene nanospheres.

Background: The mesh infection is mostly related to the gram-negative bacteria, such as Escherichia coli (E. coli) for emergency surgery of incarcerated hernia. However, few study investigated the effects of E. coli concentration, mesh materials and antibiotic prophylaxis on mesh infection after hernioplasty. The aim of this study was to evaluate the bacterial resistance to E. coli for three different materials of mesh, and to measure the minimum E. coli concentration for mesh infection with and without antibiotic prophylaxis in a rat model.Methods: Three types of mesh (polytetrafluoroethylene, polypropylene, and biologic meshes) were used in the repair of an acute ventral hernia rat model in the setting of different concentrations of E. coli loads and antibiotics. At the 8th day after surgery, mesh samples were sent for microbiologic and histologic analyses.Results: The positive rates of bacterial culture increased with E. coli concentration. The biologic mesh showed better bacterial resistance compared to polytetrafluoroethylene mesh and polypropylene mesh when the concentration of E. coli ranges from 106 CFU/ml to 108 CFU/ml (P = 0.002 and P = 0.029, respectively). Prophylactical ceftriaxone treatment could not decrease the colonization rate of E. coli at 106 CFU/ml or 108 CFU/ml in each group (P > 0.05). The scores of neovascularization in polypropylene mesh and biologic mesh were similar, which was higher than that of polytetrafluoroethylene mesh (P < 0.05). Compared with other meshes, biologic mesh showed better tolerance to 106 CFU/ml E. coli with respect to inflammation, depth of inflammation, neovascularization, cellular repopulation and foreign body giant cells.Conclusion: The biologic mesh had better E. coli resistance compared to polytetrafluoroethylene mesh and polypropylene mesh when the E. coli concentration is higher than 106 CFU/ml in rats. Antibiotic prophylaxis was useful when the contamination was not particularly severe.

The electromagnetic satellite Zhangheng 01 (ZH-01) was successfully launched on February 2, 2018. The GNSS Radio Occultation (GRO) receiver on board the satellite is able to observe the occultation events of GPS and BeiDou navigation satellites. We analyzed the data acquired during the in-orbit testing period. We concludes that the GRO ionosphere inversion results are reasonable, the trend is correct, the satellite can observe about 600 ionosphere occultation events each day. The global coverage of more than 30000 consecutive GRO events in more than two months were analyzed and compared with COSMIC observations: both the GRO and COSMIC occultation can realize global coverage: the NmF2 and HmF2 global distributions are similar and change obviously with latitude. We used three digisondes at different latitudes to analyze and compare the spatio-temporally consistent GRO data: the RMSE of GRO NmF2 relative to digisonde is better than 9.41%, the correlation coefficient is better than 0.8682: the relative RMSE of HmF2 is better than 7.80% and the correlation coefficient is better than 0.7066.

There is an increasing drug resistance of animal-derived pathogens, seriously posing a huge threat to the health of animals and humans. Traditional drug resistance testing methods are expensive, have low efficiency, and are time-consuming, making it difficult to evaluate overall drug resistance. To develop a better approach to detect drug resistance, a small sample of Escherichia coli resistance data from 2003 to 2014 in Chengdu, Sichuan Province was used, and multiple regression interpolation was applied to impute missing data based on the time series. Next, cluster analysis was used to classify anti-E. coli drugs. According to the classification results, a GM(1,1)-BP model was selected to analyze the changes in the drug resistance of E. coli, and a drug resistance prediction system was constructed based on the GM(1,1)-BP Neural Network model. The GM(1,1)-BP Neural Network model showed a good prediction effect using a small sample of drug resistance data, with a determination coefficient R2 of 0.7830 and an RMSE of only 0.0527. This model can be applied for the prediction of drug resistance trends of other animal-derived pathogenic bacteria, and provides the scientific and technical means for the effective assessment of bacterial resistance.

A portable and flexible self-powered biosensor based on ZnO nanowire arrays (ZnO NWs) and flexible PET substrate has been designed and fabricated for real-time monitoring in swimming. Based on the piezoelectric effect of polar ZnO NWs, the fabricated biosensor can work in both air and water without any external power supply. In addition, the biosensor can be easily attached to the surface of the skin to precisely monitor the motion state such as joint moving angle and frequency during swimming. The constant output piezoelectric signal in different relative humidity levels enables actual application in different sports, including swimming. Therefore, the biosensor can be utilized to monitor swimming strokes by attaching it on the surface of the skin. Finally, a wireless transmitting application is demonstrated by implanting the biosensor in vivo to detect angiogenesis. This portable and flexible self-powered biosensor system exhibits broad application prospects in sport monitoring, human–computer interaction and wireless sport big data.

Abstract Marital status has been found to be a prognostic factor for survival in various cancers, but its role in gallbladder cancer (GBC) has not been fully studied. In this study, we used the Surveillance, Epidemiology, and End Results Program (SEER)-registered database to analyze the survival of GBC patients with different marital status. A total of 6,627 GBC patients were selected from SEER database from 2004 to 2013. The age, race, grade, histologic type, AJCC stage, SEER stage and marital status were identified as independent prognostic factors. Married GBC patients had a higher 5-year cancer-specific survival (CSS) than that of unmarried ones (20.1% v.s. 17.8%, P

Abstract Background Negative lymph node (NLN) count has been reported to provide more accurate prognostic information than the N stage alone in patients with rectal cancer (RC). Since preoperative radiotherapy (Pre-RT) can significantly affect the LN status, it is unclear whether NLN count still has prognostic value count on survival of patients with RC who received Pre-RT. Methods In this study, clinicopathological characteristics, number of positive LNs and survival time were collected from Surveillance, Epidemiology, and End Results Program (SEER)-registered RC patients. Univariate and multivariate Cox proportional hazards models were used to assess the risk factors for survival. Results X-tile plots identified 9 (P

Colorectal cancer is the most common critical disease both in the developed and developing countries. Capecitabine, which has served in clinical practice at least for 10 years, is a first-line antidigestive tract cancer drug for its better efficacy, patient compliance, and lower side effects. An ultra-high-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) method has been developed and completely validated for simultaneous determination of capecitabine and its five metabolites in human plasma from colorectal cancer patients after administration of capecitabine tablet. One-step liquid-liquid extraction was successfully applied using ethyl acetate and isopropanol (19 : 1, V : V) for sample pretreatment. Chromatographic separation was achieved within 5 min based on an Atlantis T3-C18 column (3.0 µm, 2.1 × 100 mm) with gradient elution using mobile phases consisting of 0.0075% formic acid in water (pH 4) and in acetonitrile, and the flow rate was 0.3 mL/min. Linear range was approximately 20.0–5000.0 ng/mL for all analytes. Linear correlation coefficients were >0.99 for all regression curves. The intraday and interday accuracy and precision of the method were within ±15.0% and less than 15.0%, respectively. The mean recovery and matrix effect as well as stability of all the analytes ranged from 59.27% to 90.15% and from 74.84% to 114.48% as well as within ±15.0%. This simple, rapid, and sensitive method was successfully applied in 42 sparse clinical samples to verify its practicability.

ZrO _2 /Ni _3 Al-Ni _3 Al double-layer coating on stainless steel was prepared by powder sintering one-step forming process. The surface-interface morphologies, chemical element distribution and phase compositions of the coatings before and after thermal oxidation or hot corrosion were analyzed using scanning electron microscope (SEM), energy dispersive spectrometer (EDS) and X-ray diffractometer (XRD). The microstructure of the coating was Ni _3 Al matrix with dispersed ZrO _2 particles, which was pure and compacted. The Ni _3 Al intermediate layer compactly formed between stainless steel substrate and ZrO _2 /Ni _3 Al composite coating, with good metallurgical bonding interfaces. The ZrO _2 /Ni _3 Al-Ni _3 Al double-layer coating exhibited a relatively high outmost microhardness of about 500 HV, and then gradually decreased from the coating to the substrate. When thermal oxidized or hot corroded at 1050 °C, a mixed oxide layer of NiO, Al _2 O _3 and NiAl _2 O _4 formed on the coating surface, which effectively acted as a diffusion barrier for oxygen and corrosive substances, and thus demonstrated the good protective effect of ZrO _2 /Ni _3 Al coating.

Currently, seafloor topography inversion based on satellite altimetry gravity data provides the principal means to predict the global seafloor topography. Researchers often use sea surface geoid height or gravity anomaly to predict sea depth in the space domain. In this paper, a comprehensive discussion on seafloor topography inversion formulas in the space domain is presented using sea surface geoid height, gravity anomaly and introduces an approach that uses vertical gravity gradient. This would be the first study to estimate seafloor topography by vertical gravity gradient in the space domain. Further, a nonlinear iterative least-square inversion process is discussed. Using the search area for the Malaysia Airlines Flight MH370 as study site, we used the DTU17 gravity anomaly model and SIO V29.1 vertical gravity gradient to generate the seafloor topography. The results of the proposed bathymetric models were analyzed and compared with the DTU18 and SIO V20.1 bathymetric models. The experimental results show that the gravity anomaly and vertical gravity gradient in the study area are strongly correlated with the seafloor topography in the 20–200 km wavelength range. The optimal initial iteration values for seafloor topography variance and correlation length are 0.6365 km2 and 10.5′, respectively. Shipborne measurements from SONAR data were used as external checkpoints to evaluate the bathymetric models. The results show that the RMS for BAT_VGG_ILS (inversion model constructed by vertical gravity gradient) is smaller than for BAT_GA_ILS (inversion model constructed by gravity anomaly) and BAT_GA_VGG_ILS (inversion model constructed by gravity anomaly and vertical gravity gradient). The relative accuracy of the DTU18 bathymetry model was 9.27%, while the relative accuracy of the proposed seafloor models was higher than 4%. Within the 200 m difference range, the proportion of checkpoints for BAT_VGG_ILS was close to 95%, about 80% for BAT_GA_ILS and BAT_GA_VGG_ILS, and less than 50% for the DTU18. The results show that the nonlinear iterative least square method in the space domain is feasible.

(1) Background: The high use of antibiotics has made the issue of antimicrobial resistance (AMR) increasingly serious, which poses a substantial threat to the health of animals and humans. However, there remains a certain gap in the AMR system and risk assessment models between China and the advanced world level. Therefore, this paper aims to provide advanced means for the monitoring of antibiotic use and AMR data, and take piglets as an example to evaluate the risk and highlight the seriousness of AMR in China. (2) Methods: Based on the principal component analysis method, a drug resistance index model of anti-E. coli drugs was established to evaluate the antibiotic risk status in China. Additionally, based on the second-order Monte Carlo methods, a disease risk assessment model for piglets was established to predict the probability of E. coli disease within 30 days of taking florfenicol. Finally, a browser/server architecture-based visualization database system for animal-derived pathogens was developed. (3) Results: The risk of E. coli in the main area was assessed and Hohhot was the highest risk area in China. Compared with the true disease risk probability of 4.1%, the result of the disease risk assessment model is 7.174%, and the absolute error was 3.074%. Conclusions: Taking E. coli as an example, this paper provides an innovative method for rapid and accurate risk assessment of drug resistance. Additionally, the established system and assessment models have potential value for the monitoring and evaluating AMR, highlight the seriousness of antimicrobial resistance, advocate the prudent use of antibiotics, and ensure the safety of animal-derived foods and human health.

Peaches are a popular fruit appreciated by consumers due to their eating quality. Quality evaluation of peaches is important for their processing, inventory control, and marketing. Eleven quality indicators (shape index, volume, mass, density, firmness, color, impedance, phase angle, soluble solid concentration, titratable acidity, and sugar−acid ratio) of 200 peach fruits (Prunus persica (L.) Batsch “Spring Belle”) were measured within 48 h. Quality indicator data were normalized, outliers were excluded, and correlation analysis showed that the correlation coefficients between dielectric properties and firmness were the highest. A back propagation (BP) neural network was used to predict the firmness of fresh peaches based on their dielectric properties, with an overall fitting ratio of 86.9%. The results of principal component analysis indicated that the cumulative variance of the first five principal components was 85%. Based on k-means clustering analysis, normalized data from eleven quality indicators in 190 peaches were classified into five clusters. The proportion of red surface area was shown to be a poor basis for picking fresh peaches for the consumer market, as it bore little relationship with the comprehensive quality scores calculated using the new grading model.

Rice is one of the most important crops in the world; meanwhile, the rice field is also an important contributor to greenhouse gas methane emission. Therefore, it is important to get an accurate estimation of rice acreage for both food production and climate change related studies. The eastern plain region is one of the major single-cropped rice (SCR) growing areas in China. Subjected to the topography and intensified human activities, the rice fields are generally fragmented and irregular. How remote sensing can meet this challenge to accurately estimate the acreage of the rice in this region using medium-resolution imagery is the topic of this study. In this study, the applicability of the Chinese HJ-1A/B satellites and a two-band enhanced vegetation index (EVI2) was investigated. Field campaigns were carried out during the rice growing season and ground-truth data were collected for classification accuracy assessments in 2012. A stepwise classification strategy utilizing the EVI2 signatures during key phenology stages, i.e., the transplanting and the vegetative to reproductive transition phases, of the SCR was proposed, and the overall classification accuracy was 91.7%. The influence of the mixed pixel and boundary effects to classification accuracy was also investigated. This work demonstrates that the Chinese HJ-1A/B data are suitable data source to estimating SCR cropping area under complex land cover composition.

The urban heat island is generally conducted based on ground observations of air temperature and remotely sensing of land surface temperature (LST). Satellite remotely sensed LST has the advantages of global coverage and consistent periodicity, which overcomes the weakness of ground observations related to sparse distributions and costs. For human related studies and urban climatology, canopy layer urban heat island (CUHI) based on air temperatures is extremely important. This study has employed remote sensing methodology to produce monthly CUHI climatology maps during the period 2000–2013, revealing the spatiotemporal characteristics of daytime and nighttime CUHI during this period of rapid urbanization in Shanghai. Using stepwise linear regression, daytime and nighttime air temperatures at the four overpass times of Terra/Aqua were estimated based on time series of Terra/Aqua-MODIS LST and other auxiliary variables including enhanced vegetation index, normalized difference water index, solar zenith angle and distance to coast. The validation results indicate that the models produced an accuracy of 1.6–2.6 °C RMSE for the four overpass times of Terra/Aqua. The models based on Terra LST showed higher accuracy than those based on Aqua LST, and nighttime air temperature estimation had higher accuracy than daytime. The seasonal analysis shows daytime CUHI is strongest in summer and weakest in winter, while nighttime CUHI is weakest in summer and strongest in autumn. The annual mean daytime CUHI during 2000–2013 is 1.0 and 2.2 °C for Terra and Aqua overpass, respectively. The annual mean nighttime CUHI is about 1.0 °C for both Terra and Aqua overpass. The resultant CUHI climatology maps provide a spatiotemporal quantification of CUHI with emphasis on temperature gradients. This study has provided information of relevance to urban planners and environmental managers for assessing and monitoring urban thermal environments which are constantly being altered by natural and anthropogenic influences.

Grain-yield prediction using remotely sensed data have been intensively studied in wheat and maize, but such information is limited in rice, barley, oats and soybeans. The present study proposes a new framework for rice-yield prediction, which eliminates the influence of the technology development, fertilizer application, and management improvement and can be used for the development and implementation of provincial rice-yield predictions. The technique requires the collection of remotely sensed data over an adequate time frame and a corresponding record of the region's crop yields. Longer normalized-difference-vegetation-index (NDVI) time series are preferable to shorter ones for the purposes of rice-yield prediction because the well-contrasted seasons in a longer time series provide the opportunity to build regression models with a wide application range. A regression analysis of the yield versus the year indicated an annual gain in the rice yield of 50 to 128 kg ha(-1). Stepwise regression models for the remotely sensed rice-yield predictions have been developed for five typical rice-growing provinces in China. The prediction models for the remotely sensed rice yield indicated that the influences of the NDVIs on the rice yield were always positive. The association between the predicted and observed rice yields was highly significant without obvious outliers from 1982 to 2004. Independent validation found that the overall relative error is approximately 5.82%, and a majority of the relative errors were less than 5% in 2005 and 2006, depending on the study area. The proposed models can be used in an operational context to predict rice yields at the provincial level in China. The methodologies described in the present paper can be applied to any crop for which a sufficient time series of NDVI data and the corresponding historical yield information are available, as long as the historical yield increases significantly.

Parkinson disease (PD) progresses relentlessly and affects approximately 4% of the population aged over 80 years old. It is difficult to diagnose in its early stages. The purpose of our study is to identify molecular biomarkers for PD initiation using a computational bioinformatics analysis of gene expression. We downloaded the gene expression profile of PD from Gene Expression Omnibus and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in PD patients compared to controls. Besides, we built a regulatory network by mapping the DCGs to known regulatory data between transcription factors (TFs) and target genes and calculated the regulatory impact factor of each transcription factor. As the results, a total of 1004 genes associated with PD initiation were identified. Pathway enrichment of these genes suggests that biological processes of protein turnover were impaired in PD. In the regulatory network, HLF, E2F1 and STAT4 were found have altered expression levels in PD patients. The expression levels of other transcription factors, NKX3-1, TAL1, RFX1 and EGR3, were not found altered. However, they regulated differentially expressed genes. In conclusion, we suggest that HLF, E2F1 and STAT4 may be used as molecular biomarkers for PD; however, more work is needed to validate our result.