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Objective:BOLA2B is a recently discovered protein-coding gene. Here, pan-cancer analysis was conducted to determine the expression patterns of BOLA2B and its impact on immune response, gene mutation, and possible molecular biological mechanisms in different tumors, together with investigating its potential usefulness for cancer prognosis.Methods: Data on BOLA2B expression and mutations were downloaded from TCGA and GTEx databases. Clinical survival data from TCGA were used to analyze the prognostic value of BOLA2B. TIMER and ESTIMATE algorithms were used to assess correlations between BOLA2B and tumor-infiltrating immune cells, immune cytokines, and immune scores.Results: BOLA2B was found to be highly expressed at both mRNA and protein levels in multiple tumors, where it was associated with worse overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in all cancers apart from ovarian cancer. BOLA2B was also found to be positively correlated with copy number variation (CNV), and mutations in TP53, TTN, and MUC16 were found to influence BOLA2B expression. Post-transcriptional modifications, including m5C, m1A, and m6A, were observed to regulate BOLA2B expression in all cancers. Functional analysis showed that BOLA2B was enriched in pathways associated with iron–sulfur cluster formation, mTOR-mediated autophagy, and cell cycle inhibition. Decreased BOLA2B expression induced the proliferation of breast cancer cells and G2/M cell cycle arrest.Conclusion:BOLA2B was found to be highly expressed in malignant tumors and could be used as a biomarker of poor prognosis in multiple cancers. Further investigation into BOLA2B’s role and molecular functions in cancer would provide new insights for cancer diagnosis and treatment.

Digital technology can be an effective tool to facilitate emergency assistance in a pandemic, but many deaf and hard-of-hearing elders may experience challenges in using and adopting these technologies. In the context of the second wave of the COVID-19 outbreak, this study employs a qualitative research method based on in-depth interviews to explore technology challenges among deaf and hard-of-hearing elders in China. The results showed that this group's technology challenges arose mainly from barriers to the mastery of digital technology tools, among which barriers to the use of smartphones, to the accessibility of online medical consultations, and to the presentation of health codes, were most noteworthy. For the informants, these barriers led to social isolation and technology avoidance. What's more, the expectation of individuals to adopt certain types of digital intelligence technologies can inadvertently create inequities for disadvantaged groups and exacerbate the “digital divide.” This study highlights the need for emergency management systems to be inclusive of elders with hearing loss in times of public health crises, by providing effective technology support and training to facilitate individuals' access to services and to safeguard their health, interests, and livelihood.

IntroductionWhile most epidemiological studies have focused on the effects of individual dietary patterns and nutritional status on health, the relationships between the combinations of these factors and patient prognosis requires further investigation.ObjectiveThis study explored mortality risk in individuals with different combinations of dietary patterns or nutritional status.MethodsUnsupervised K-means clustering was used to classify populations. The analyses included Cox proportional risk and competing risk models.ResultsAfter considering a complex sampling design, the results showed that among 12,724 participants aged >60 years, 6.99% died from cancer and 10.47% from cardiovascular and cerebrovascular disease (CCVD). After correcting for participant baseline information and chronic conditions, the geriatric nutritional risk index and healthy eating index (HEI) were negatively associated with the risk of all-cause and cause-specific mortality. The opposite was true for the dietary inflammatory index (DII). After sorting the population three clusters based on study scores showed higher risks of all-cause mortality and cancer-related death in Cluster 2 and 3.DiscussionThese results suggest that different nutritional status and dietary patterns are associated with the risk of all-cause mortality and death from cancer and CCVD in people aged >60 years in the United States. Dietary patterns with high HEI and low DII were beneficial to health, whereas nutritional status needs to be maintained at a level that is not too low.

Abstract Triple negative (TN) breast cancer is a subtype of breast cancer which is difficult for early detection and the prognosis is poor. In this paper, 910 benign and 934 malignant (110 TN and 824 NTN) B-mode breast ultrasound images were collected. A Resnet50 deep convolutional neural network was fine-tuned. The results showed that the averaged area under the receiver operating characteristic curve (AUC) of discriminating malignant from benign ones were 0.9789 (benign vs. TN), 0.9689 (benign vs. NTN). To discriminate TN from NTN breast cancer, the AUC was 0.9000, the accuracy was 88.89%, the sensitivity was 87.5%, and the specificity was 90.00%. It showed that the computer-aided system based on DCNN is expected to be a promising noninvasive clinical tool for ultrasound diagnosis of TN breast cancer.

BackgroundCardiovascular disease (CVD) poses a tremendous threat to global health, giving rise to exceedingly high morbidity and mortality among patients. A migraine is a common neurological disorder characterized by recurrent attacks of severe headache, while its cardiovascular burden remains unclear. Therefore, this study aims to investigate whether migraine is associated with CVD.MethodsThe cross-sectional data of 5,692 subjects aged 20 or above was obtained from the National Health and Nutrition Examination Survey (NHANES) 1999–2004. To determine whether migraine is associated with CVD, weighted logistic regression models were used. In a subsequent subgroup analysis, several confounding factors were also explored to investigate the association between migraine and CVD.ResultsIn total, 5,692 subjects were enrolled in this study, with the prevalence of CVD being 13.3%. Participants with CVD tended to be older, male, non-Hispanic whites, more educated, former smokers, and alcohol drinkers, and had a higher waist circumference, less physical activity, a higher level of triglyceride and creatinine as well as a lower level of high-density lipoprotein cholesterol (HDL-C) and estimated glomerular filtration rate (eGFR) (all P < 0.05). Considering all potential confounders, migraine was associated with a higher risk of CVD [odds ratios (ORs) 2.77; 95% confidence intervals (CIs): 1.56–4.90]. Subgroup analysis showed a higher risk of CVD in females, those older than 60 years, with a lower body mass index (BMI) level (≤ 30 kg/m2), a higher level of eGFR (> 90 mL/min/1.73 m2), hypertension and hyperlipidemia and without diabetes.ConclusionIn summary, our study revealed a positive association between migraine with CVD in a nationally representative US adult population. Our findings highlighted that migraine should be considered an important risk factor for CVD.

ObjectiveTo evaluate the advantages and disadvantages of da Vinci robot and laparoscopy in treating pediatric choledochal cysts.MethodsWe retrospectively analyzed clinical data from forty-two children diagnosed with choledochal cysts in our hospital from January 2018 to January 2021. Twenty children underwent da Vinci robotic surgery, and the others underwent traditional laparoscopy. We compared differences in general information and preoperative, intraoperative, and postoperative differences between the two surgical groups.ResultsThere was no statistically significant difference in age, gender, weight, type, maximum cyst diameter, preoperative C-reactive protein (CRP) value, postoperative complication rate, and postoperative pain score between the two surgical groups (P > 0.05). The average age of the robot-assisted group was 3.62 ± 0.71 years old (range = 1–12 years). There were nineteen cases of Todani type I, one patients of other types, and the maximum cyst diameter was 35.45 ± 9.32 mm (range = 12–56 mm). In the laparoscopic group, the average age was 3.08 ± 0.82 years old (range = 3–10 years). Twenty-one patients had Todani type I, and one had other types. The maximum cyst diameter was 31.94 ± 8.64 mm (range = 10–82 mm). The robot-assisted group had better abdominal drainage, postoperative CRP value, fasting time, and discharge time than the laparoscopic group (P

BackgroundDiabetes is a critical contributor to the pathogenesis of cardiovascular diseases. Klotho is an anti−aging protein with cardiovascular-renal protective effects. However, the relationship between serum Klotho levels and diabetes remains poorly understood.ObjectivesThis study aimed to investigate the relationship between serum Klotho levels and diabetes in US adults.MethodsWe analyzed the cross-sectional data obtained from 13751 subjects aged 40-79 years in the National Health and Nutrition Examination Survey (NHANES) (2007–2016). Serum Klotho concentration was measured using an enzyme-linked immunosorbent assay (ELISA) and categorized into four quartiles (Q1-Q4). Multivariate logistic regression and restricted cubic spline (RCS) regression were conducted to explore the association between serum Klotho levels and the prevalence of diabetes.ResultsAs compared with quartile 1, serum Klotho levels in quartiles 2-4 yielded odds ratios (OR) (95% CI) of diabetes of 0.96 (0.80–1.15), 0.98 (0.82–1.18), and 1.25 (1.04–1.50), respectively, after covariate adjustment (P for trend = 0.018). The results implied an increased risk of diabetes. The RCS plot showed a U-shaped relationship linking serum Klotho levels with diabetes (P for nonlinearity = 0.003).ConclusionsIn summary, a nonlinear and positive association was found between serum Klotho levels and the prevalence of diabetes. Further study is needed to verify the causality of this association and elucidate the underlying mechanisms.

Adaptation during the domestication from wolves (Canis lupus) to dogs (Canis lupus familiaris) is a debated ecological topic. Changes in food and environment are major divergences in the domestication of dogs. Gut microbes play an important role in animal adaptation to the food and environmental changes. In this study, shotgun sequencing was performed to compare the species diversity and functional diversity of gut microbes in wild wolves (group CLW, n = 3), captive wolves (group CLC, n = 4), and domestic dogs (group CLF, n = 4). The results found that Bacteroidetes, Firmicutes, Fusobacteria, Proteobacteria and Actinobacteria were the most abundant phyla and Bacteroides, Fusobacterium, Prevotella, Megamonas, Paraprevotella, Faecalibacterium, Clostridium were the most abundant genera in the gut of wolves and dogs. Groups CLW, CLC and CLF have shown significant difference in gut microbial species diversity and functional diversity. Bacteroides, Fusobacterium and Faecalibacterium were most abundant genera in groups CLW, CLC and CLF, respectively. Their abundance varied significantly among groups. Compared to the wild wolves, the intestinal microbiol genes of domestic dogs were significantly enriched in the carbohydrate metabolism pathway of KEGG database. One hundred and seventy-seven enzymes were detected with significantly higher abundance in group CLF than that in group CLW, and 49 enzymes showed extremely significant higher abundance in group CLF than that in group CLW (q

ObjectiveThis study aimed to compare the effects of various trocar placements in robot-assisted and laparoscopic pyeloplasty involving children diagnosed with obstruction of the ureteropelvic junction (OUPJ).MethodsWe retrospectively collected the data on 74 patients under 14 years of age who had been diagnosed with OUPJ; these patients underwent either robot-assisted or laparoscopic pyeloplasty in our hospital between January 2015 and November 2021. There were four groups, as follows: •Laparoscopic multiport pyeloplasty (LMPY),•Laparoscopic single-port pyeloplasty (LSPY),•Robotic-assisted multiport pyeloplasty (RMPY),•Robotic-assisted single-port-plus-one pyeloplasty (RSPY).Patients' characteristics as well as their perioperative and follow-up data were collected and evaluated.ResultsThere was no significant difference in the data regarding patients' characteristics. These data included the grade of hydronephrosis according to the Society of Fetal Urology (SFU grade), anterior and posterior diameter of the renal pelvis and ureter (APDRPU), and the differential degree of renal function (DRF) at following time points: preoperative, postoperative, and comparison of preoperative and postoperative. There was no difference among these groups. During surgery, the time of trocar placement, urethroplasty time, and total operative time in the robotic groups (RMPY and RSPY) were longer than those in the laparoscopic groups (LMPY and LSPY). However, the ratio of the urethroplasty time and full operative time (UT/WT) in the robotic groups (RMPY and RSPY) was lower than that in the laparoscopic groups (LMPY and LSPY) (P = 0.0075). Also, the volume of blood loss was lower in the robotic groups (RMPY and RSPY) than that in the laparoscopic groups (LMPY and LSPY), although there was no statistical difference (P = 0.11). There were, however, significant differences in hospitalization days (P

In complex industrial environments, the vibration signal of the rolling bearing is covered by noise, which makes fault diagnosis inaccurate. In order to overcome the effect of noise on the signal, a rolling bearing fault diagnosis method based on the WOA-VMD (Whale Optimization Algorithm-Variational Mode Decomposition) and the GAT (Graph Attention network) is proposed to deal with end effect and mode mixing issues in signal decomposition. Firstly, the WOA is used to adaptively determine the penalty factor and decomposition layers in the VMD algorithm. Meanwhile, the optimal combination is determined and input into the VMD, which is used to decompose the original signal. Then, the Pearson correlation coefficient method is used to select IMF (Intrinsic Mode Function) components that have a high correlation with the original signal, and selected IMF components are reconstructed to remove the noise in the original signal. Finally, the KNN (K-Nearest Neighbor) method is used to construct the graph structure data. The multi-headed attention mechanism is used to construct the fault diagnosis model of the GAT rolling bearing in order to classify the signal. The results show an obvious noise reduction effect in the high-frequency part of the signal after the application of the proposed method, where a large amount of noise was removed. In the diagnosis of rolling bearing faults, the accuracy of the test set diagnosis in this study was 100%, which is higher than that of the four other compared methods, and the diagnosis accuracy rate of various faults reached 100%.

Abstract Background and aims Limited data is available on the efficacy of direct acting anti-viral drugs on hepatitis C in drug users. The aim of this meta-analysis was to comprehensively analyze the efficacy and safety of LDV/SOF in drug users infected with the hepatitis C virus (HCV). Methods The PubMed, Cochrane library, Embase and Web of Science databases were searched for articles published till April 2021 on HCV-positive drug users who were treated with ledipasvir/sofosbuvir (LDV/SOF). The primary endpoint was pooled sustained virological response at 12 weeks (SVR12) with 95% confidence interval (95% CI). Funnel plots and Egger’s test were used to assess the publication bias. Results A total of 12 studies and 711 subjects treated with LDV/SOF-based regimen for HCV were included, and the pooled SVR12 rate was 89.8% (95% CI 85.9–92.7). The pooled SVR12 rate of genotype 1 drug users was 92.4% (95% CI 88.6–95.0). Subgroup analysis showed that pooled SVR12 rates of patients treated with LDV/SOF and LDV/SOF ± RBV were 89.2% (95% CI 83.4–93.1), 90.4% (95% CI 83.6–94.5) respectively. In addition, the SVR12 rates were 88% (95% CI 70.7–95.7) for 8 weeks, 89.9% (95% CI 81.0–94.9) for 12 weeks and 82.2% (95% CI 24.9–98.5) for 24 weeks of treatment. Conclusion LDV/SOF is a safe and relatively effective treatment for hepatitis C in drug users.

Abstract Background ICP pregnant women have a unique profile of serum bile acid metabolism, thus the early and accurate identification of ICP patients is beneficial to early appropriate treatment and improvement of pregnancy outcomes. In this study, ultra-high performance liquid chromatography-mass spectrometry/mass spectrometry (UPLC-MS/MS) was used to analyze the 15 types of serum bile acid profiles among patients with ICP in third trimester, patients with cholelithiasis, and patients with hepatitis B virus. The ICP diagnostic model established by partial least squares-discriminant analysis (PLS-DA) was used to screen the differential bile acids for clinical subtypes of ICP. 144 cases of ICP patients were involved in this study, and divided into four subgroups according to serum level of TBA, DBIL, and ALT. Results (1) The differential serum bile acid profiles of ICP group and normal pregnant women were DCA, TDCA, TCA, GDCA and GLCA. (2) The differential serum bile acid profiles of the ICP1 group (ICP with jaundice) and normal pregnant women were TCDCA, TCA, GCA, GCDCA, TUDCA and GUDCA. (3) The differential serum bile acid profiles of the ICP3 group (Hyperchoicemia of pregnancy) and normal pregnant group was GUDCA, LCA, GLCA, UDCA, TUDCA, CDCA, and TLCA (P 0.05). Conclusion Maternal serum bile acid profiles are useful to differentiate the four subtypes of ICP. ICP with jaundice could be an important predictor of adverse pregnancy outcomes of ICP.

Abstract The short-faced moles (Scaptochirus moschata) are unique Chinese mammal that live in burrows for life. They have complex ecological adaptation mechanisms to adapt to perennial underground life. Intestinal microbes play an important role in the ecological adaptation of wild animals. The gut microbiota diversity and its function in short-faced moles’ ecological adaptation is a scientific issue worth exploring. In this study, the Illumina HiSeq sequencing platform was used to sequence the V3-V4 hypervariable regions of the 16S rRNA genes of 22 short-faced moles’ intestinal samples to study the composition and functional structure of their intestinal microbiota. The results showed that in the short-faced moles’ intestine, there are four main phyla, Firmicutes, Proteobacteria, Actinobacteria and Bacteroidete. At the family level, Peptostreptococcaceae and Enterobacteriaceae have the highest abundance. At the genus level, Romboutsia is the genus with the highest microbial abundance. According to the KEGG database, the main functions of short-faced mole gut microbes are metabolism, genetic information processing, environmental information processing, and cellular processes. The function of short-faced mole intestinal microbiota is suitable for its long-term burrowing life. No gender difference is found in the composition and function of the short-faced mole intestinal microbiota. There are significant differences in the composition and functional structure of the short-faced mole gut microbiota between samples collected from different habitats. We conferred that this is related to the different environment factors in which they live, especially to the edaphic factors.

Experience value is positively associated with user voice toward social media, but existing research lacks an examination of its mechanisms of action. Based on value co-creation theory, this paper explores the relationship between experience value (i.e., social value, entertainment value, information value) and customer voice, and explains the specific influence mechanism through the mediating role of user loyalty. The results of the empirical tests show that social value, entertainment value and information value have significant effects on user loyalty; user loyalty has a significant effect on promotive voice but not on prohibitive voice; user loyalty mediates the relationship between body social value, entertainment value, information value and promotive voice. The findings of this research reveal the important role of experience value on customer voice, which is an important guide for social media to achieve sustainable development.

Background: Cataract is the leading cause of blindness worldwide. In order to achieve large-scale cataract screening and remarkable performance, several studies have applied artificial intelligence (AI) to cataract detection based on fundus images. However, the fundus images they used are original from normal optical circumstances, which is less impractical due to the existence of poor-quality fundus images for inappropriate optical conditions in actual scenarios. Furthermore, these poor-quality images are easily mistaken as cataracts because both show fuzzy imaging characteristics, which may decline the performance of cataract detection. Therefore, we aimed to develop and validate an antiinterference AI model for rapid and efficient diagnosis based on fundus images.Materials and Methods: The datasets (including both cataract and noncataract labels) were derived from the Chinese PLA general hospital. The antiinterference AI model consisted of two AI submodules, a quality recognition model for cataract labeling and a convolutional neural networks-based model for cataract classification. The quality recognition model was performed to distinguish poor-quality images from normal-quality images and further generate the pseudo labels related to image quality for noncataract. Through this, the original binary-class label (cataract and noncataract) was adjusted to three categories (cataract, noncataract with normal-quality images, and noncataract with poor-quality images), which could be used to guide the model to distinguish cataract from suspected cataract fundus images. In the cataract classification stage, the convolutional-neural-network-based model was proposed to classify cataracts based on the label of the previous stage. The performance of the model was internally validated and externally tested in real-world settings, and the evaluation indicators included area under the receiver operating curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE).Results: In the internal and external validation, the antiinterference AI model showed robust performance in cataract diagnosis (three classifications with AUCs >91%, ACCs >84%, SENs >71%, and SPEs >89%). Compared with the model that was trained on the binary-class label, the antiinterference cataract model improved its performance by 10%.Conclusion: We proposed an efficient antiinterference AI model for cataract diagnosis, which could achieve accurate cataract screening even with the interference of poor-quality images and help the government formulate a more accurate aid policy.

Intestinal microbes are important symbiotes in the gastrointestinal tract of mammals, which are affected by food, environment, climate, genetics, and other factors. The gut microbiota of felines has been partially studied, but a comprehensive comparison of the gut microbiota of Panthera species was less reported. In this study, we compared the gut microbial composition and diversity of five species of Panthera (Panthera tigris, Panthera leo, Panthera onca, Panthera pardus, and Panthera uncia) by 16S ribosomal RNA (rRNA) amplicon sequencing. The results showed that Firmicutes was the most abundant phylum among all the Panthera species, followed by Actinobacteria, Fusobacteria, Bacteroidetes, Proteobacteria, Acidobacteria, Verrucomicrobia, Gemmatimonadetes, and Euryarchaeota. There were significant differences in observed species of fecal microbiota among different Panthera animals (P < 0.05), indicating that there is species specificity among Panthera fecal microbiota. When the samples were further grouped according to sampling locations, the comparison of the alpha diversity index between groups and beta diversity analysis showed that there were significant differences in the fecal microflora of animals from different sampling locations. Cluster analysis showed that fecal microbes of animals from the same sampling location were clustered, while gut microbes of animals of the same species, but from different sampling locations, were separated. These results indicate that environment may have more influence on mammals’ fecal microbial diversity than genetic relationships.

Cancer persists as a worldwide disease that contributes to high morbidity and mortality rates. As a class of non-coding RNA, microRNAs (miRNAs) are one kind of important regulators in cancer and frequently implicated in tumor development and progression. Emerging experiments have suggested that miRNA-195–5p (miR-195–5p) can regulate neoplastic processes in many pathways. For instance, miR-195–5p can not only regulate proliferation, migration and invasion of tumor cells but also promote tumor cell apoptosis. Furthermore, low expression of miR-195–5p could induce drug resistance. Our review focuses on the expression of miR-195–5p in various tumors and elucidates the related mechanisms of which miR-195–5p participates in tumor biology, as well as summarizes the roles of miR-195–5p in tumor progression. We believe that miR-195–5p might have potential utility as a novel diagnostic biomarker and therapeutic target for cancer.

Abstract Circular RNAs (circRNAs) are increasingly gaining importance and attention due to their diverse potential functions and their value as diagnostic biomarkers (disease specific). This study aims to explore the novel mechanisms by which exosome-contained circRNAs promote tumor development and metastasis in TNBC. We identified increased circRNA circPSMA1 in TNBC cells, their exosomes, and serum exosomes samples from TNBC patients. The overexpression of circPSMA1 promoted TNBC cell proliferation, migration, and metastasis both in vitro and in vivo. Moreover, we investigated the tumor-infiltrating immune cells (TICs) or stromal components in immune microenvironment (IME), and identified the significant differences in the immune cells between TNBC and non-TNBC samples. Mechanistically, circPSMA1 acted as a “miRNAs sponge” to absorb miR-637; miR-637 inhibited TNBC cell migration and metastasis by directly targeted Akt1, which recognized as a key immune-related gene and affected downstream genes β-catenin and cyclin D1. Subsequent co-culture experiments also demonstrated that exosomes from TNBC carrying large amounts of circPSMA1 could transmit migration and proliferation capacity to recipient cells. Kaplan–Meier plots showed that high expression of Akt1 and low expression of mir-637 are highly correlated with poor prognosis in patients with lymph node metastasis of TNBC. Collectively, all these results reveal that circPSMA1 functions as a tumor promoter through the circPSMA1/miR-637/Akt1-β-catenin (cyclin D1) regulatory axis, which can facilitate the tumorigenesis, metastasis, and immunosuppression of TNBC. Our research proposes a fresh perspective on novel potential biomarkers and immune treatment strategies for TNBC.

In order to solve the design problem of electric vehicle charging station distribution, based on the consideration of user and investor costs, this paper establishes a mixed integer model for charging station site selection based on game theory ideas. Among them, the user cost is determined by two indicators, namely, the cost of time for users to reach the charging station and the cost of time for users to wait in line, while the cost of the charging station is determined by the construction cost and the daily operation and maintenance cost. In the established model, the hierarchical analysis is used to minimize the combined cost of users and charging stations as the objective. In addition, an improved artificial bee colony algorithm is designed to solve the model. The improved algorithm adds a neighborhood search method and a feasible decoding scheme to the honey bee harvesting and tracking process, thus solving the problems of low search accuracy, poor convergence, and inability to directly calculate the mixed integer model of the original algorithm. Simulation results show that the improved artificial bee colony algorithm can effectively solve the mixed integer model and has higher search accuracy and convergence speed compared with the traditional method. By applying the algorithm to solve the siting model, the location and number of charging stations can be clearly planned, thus improving charging efficiency and reliability.

Background: Suppression of thoracic bone shadows on chest X-rays (CXRs) can improve the diagnosis of pulmonary disease. Previous approaches can be categorized as either unsupervised physical models or supervised deep learning models. Physical models can remove the entire ribcage and preserve the morphological lung details but are impractical due to the extremely long processing time. Machine learning (ML) methods are computationally efficient but are limited by the available ground truth (GT) for effective and robust training, resulting in suboptimal results. Purpose: To improve bone shadow suppression, we propose a generalizable yet efficient workflow for CXR rib suppression by combining physical and ML methods. Materials and Method: Our pipeline consists of two stages: (1) pair generation with GT bone shadows eliminated by a physical model in spatially transformed gradient fields; and (2) a fully supervised image denoising network trained on stage-one datasets for fast rib removal from incoming CXRs. For stage two, we designed a densely connected network called SADXNet, combined with a peak signal-to-noise ratio and a multi-scale structure similarity index measure as the loss function to suppress the bony structures. SADXNet organizes the spatial filters in a U shape and preserves the feature map dimension throughout the network flow. Results: Visually, SADXNet can suppress the rib edges near the lung wall/vertebra without compromising the vessel/abnormality conspicuity. Quantitively, it achieves an RMSE of ~0 compared with the physical model generated GTs, during testing with one prediction in

Flow Direction Algorithm (FDA) has better searching performance than some traditional optimization algorithms. To give the basic Flow Direction Algorithm more effective searching ability and avoid multiple local minima under the searching space, and enable it to obtain better search results, an improved FDA based on the Lévy flight strategy and the self-renewable method (LSRFDA) was proposed in this paper. The Lévy flight strategy and the self-renewable approach were added to the basic Flow Direction Algorithm. Random parameters generated by the Lévy flight strategy can increase the algorithm’s diversity of feasible solutions in a short calculation time and greatly enhance the operational efficiency of the algorithm. The self-renewable method lets the algorithm quickly obtain a better possible solution and jump to the local solution space. Then, this paper tested different mathematical testing functions, including low-dimensional and high-dimensional functions, and the test results were compared with those of different algorithms. This paper includes iterative figures, box plots, and search paths to show the different performances of the LSRFDA. Finally, this paper calculated different engineering optimization problems. The test results show that the proposed algorithm in this paper has better searching ability and quicker searching speed than the basic Flow Direction Algorithm.

This paper provides a review of models commonly used over the years in the study of microscopic models of material corrosion mechanisms, data mining methods and the corrosion-resistant performance control of structural steels. The virtual process of material corrosion is combined with experimental data to reflect the microscopic mechanism of material corrosion from a nano-scale to macro-scale, respectively. Data mining methods focus on predicting and modeling the corrosion rate and corrosion life of materials. Data-driven control of the corrosion resistance of structural steels is achieved through micro-alloying and organization structure control technology. Corrosion modeling has been used to assess the effects of alloying elements, grain size and organization purity on corrosion resistance, and to determine the contents of alloying elements.

Development of low-cost and eco-friendly approaches to fight bacterial pathogens is especially needed in aquaculture. We previously showed that exogenous malate reprograms zebrafish’s metabolome to potentiate zebrafish survival against Vibrio alginolyticus infection. However, the underlying mechanism is unknown. Here, we use GC-MS based metabolomics to identify the malate-triggered metabolic shift. An activated TCA cycle and elevated taurine are identified as the key metabolic pathways and the most crucial biomarker of the reprogrammed metabolome, respectively. Taurine elevation is attributed to the activated TCA cycle, which is further supported by the increased expression of genes in the metabolic pathway of taurine biosynthesis from the isocitrate of the TCA cycle to taurine. Exogenous taurine increases the survival of zebrafish against V. alginolyticus infection as malate did. Moreover, exogenous taurine and malate regulate the expression of innate immunity genes and promote the generation of reactive oxygen species and nitrogen oxide in a similar way. The two metabolites can alleviate the excessive immune response to bacterial challenge, which protects fish from bacterial infection. These results indicate that malate enhances the survival of zebrafish to V. alginolyticus infection via taurine. Thus, our study highlights a metabolic approach to enhance a host’s ability to fight bacterial infection.

Background: Resting myocardial perfusion (MP) and wall motion (WM) imaging during real-time myocardial contrast echocardiography (MCE) improves the detection of coronary artery disease (CAD). However, its prognostic role in different clinical settings (emergency department and outpatient setting) remains unclear. Methods: A systematic search in PubMed and Embase databases, and the Cochrane library, was conducted to evaluate the role of resting MP and WM in predicting major adverse cardiac events (MACE), including death, nonfatal myocardial infarction (NFMI) and urgent revascularization in patients presenting to either outpatient clinics or emergency departments with suspected symptomatic CAD. Summary receiver operating characteristic (SROC) curves, sensitivity and specificity plots were applied to assess diagnostic performance using RevMan 5.3. Results: Seven studies met criteria, including 3668 patients (six with follow up ranging from 2 days to 2.6 years). The Relative Risk (RR) for predicting MACE in patients with both abnormal resting MP and WM was 6.1 (95% CI, 5.1–7.2) and 14.3 (95% CI, 10.3–19.8) for death/NFMI, when compared to normal resting MP and WM patients. Having both abnormal resting MP and WM was also more predictive of MACE (RR, 1.7; 95% CI 1.5–1.9) and death/NFMI (RR, 2.2; 95% CI, 1.8–2.7) when compared to abnormal WM with normal resting MP. Conclusion: In this meta-analysis of both ED and outpatient clinic presentations for suspected CAD, having both a resting regional MP and WM abnormality identifies the highest risk patient for adverse events.

Abstract The comprehensive evaluation of ammonia production systems is of great significance for improving the sustainability of energy management and food supply. Therefore, an important contribution could be provided by developing a generic decision‐making framework for prioritizing multiple ammonia production systems and identifying the best one. In this view, this paper aims to propose an integrated fuzzy MADM (multiattribute decision making) framework combining fuzzy BWM (best‐worst method), fuzzy CRITIC (Criteria Importance Through Intercriteria Correlation), and fuzzy GRP (gray relational projection) approaches for the sustainability assessment of ammonia production systems under hybrid information. Comparing with the previous MADM‐based frameworks for sustainability assessment, this framework adopts the TFN (triangular fuzzy number) to deal with the hybrid information (ie, crisp numbers, interval values, and fuzzy numbers) that arise from real‐world decision‐making issues. Accordingly, the weights of criteria can be comprehensively determined by integrating the fuzzy BWM and fuzzy CRITIC, which balance experts’ subjective preferences and system's objective properties under uncertainties in the determination of the weights, while the sequence of alternatives can be reliably prioritized by extending the GRP into fuzzy conditions, which escalates the ranking capability under hybrid information via considering the relationships and relative balance among the alternatives’ performances regarding the multicriteria. Seven alternative systems were studied by the proposed framework, indicating that ammonia generated from hydropower‐electrolysis and coal gasification would be more preferable than the others, by considering 12 criteria from the concerns of technological, environmental, economic, and social‐political. Additionally, sensitivity analysis and result comparison were conducted to verify the rationality and feasibility of the framework. This work makes a methodological contribution to the MADM‐based sustainability research and serves as a reference for developing the ammonia economy in the future.

Abstract Student clickstream data—time-stamped records of click events in online courses—can provide fine-grained information about student learning. Such data enable researchers and instructors to collect information at scale about how each student navigates through and interacts with online education resources, potentially enabling objective and rich insight into the learning experience beyond self-reports and intermittent assessments. Yet, analyses of these data often require advanced analytic techniques, as they only provide a partial and noisy record of students’ actions. Consequently, these data are not always accessible or useful for course instructors and administrators. In this paper, we provide an overview of the use of clickstream data to define and identify behavioral patterns that are related to student learning outcomes. Through discussions of four studies, we provide examples of the complexities and particular considerations of using these data to examine student self-regulated learning.

IntroductionCardiac pacing has been an effective treatment in the management of patients with bradyarrhythmia and tachyarrhythmia. Different pacemaker location has different responses, and pacemaker effectiveness to each individual can also be different. A novel image-based ventricle animal modeling approach was proposed to optimize ventricular pacemaker site for better cardiac outcome.MethodOne health female adult pig (weight 42.5 kg) was used to make a pacing animal model with different ventricle pacing locations. Ventricle surface electric signal, blood pressure and echo image were acquired 15 min after the pacemaker was implanted. Echo-based left ventricle fluid-structure interaction models were constructed to perform ventricle function analysis and investigate impact of pacemaker location on cardiac outcome. With the measured electric signal map from the pig associated with the actual pacemaker site, electric potential conduction of myocardium was modeled by material stiffening and softening in our model, with stiffening simulating contraction and softening simulating relaxation. Ventricle model without pacemaker (NP model) and three ventricle models with the following pacemaker locations were simulated: right ventricular apex (RVA model), posterior interventricular septum (PIVS model) and right ventricular outflow tract (RVOT model). Since higher peak flow velocity, flow shear stress (FSS), ventricle stress and strain are linked to better cardiac function, those data were collected for model comparisons.ResultsAt the peak of filling, velocity magnitude, FSS, stress and strain for RVOT and PIVS models were 13%, 45%, 18%, 13% and 5%, 30%, 10%, 5% higher than NP model, respectively. At the peak of ejection, velocity magnitude, FSS, stress and strain for RVOT and PIVS models were 50%, 44%, 54%, 59% and 23%, 36%, 39%, 53% higher than NP model, respectively. RVA model had lower velocity, FSS, stress and strain than NP model. RVOT model had higher peak flow velocity and stress/strain than PIVS model. It indicated RVOT pacemaker site may be the best location.ConclusionThis preliminary study indicated that RVOT model had the best performance among the four models compared. This modeling approach could be used as “virtual surgery” to try various pacemaker locations and avoid risky and dangerous surgical experiments on real patients.

ObjectiveWe introduce the trans-umbilical single-site plus one robotic-assisted surgery for the treatment of pediatric choledochal cyst. Compare the intraoperative and postoperative outcomes between the new method and traditional laparoscopy-assisted procedure.MethodWe retrospectively analyzed the clinical data of 51 children diagnosed with choledochal cysts and received surgery from June 2019 to December 2020 at our department. About 24 patients who underwent the robot-assisted procedure were selected as the R group, and 27 patients who underwent the laparoscope-assisted procedure were selected as the L group. We compare the intraoperative and postoperative outcomes between the two groups.ResultNo significant differences were found in demographic information between the two groups (P > 0.05). The median total operative time, median port/trocar installation time, and median wound suture time of the R group were a little longer than the L group (217.63 ± 5.90 vs. 199.37 ± 5.13 min; 30.71 ± 3.18 vs. 6.11 ± 1.15 min; 30.79 ± 1.82 vs. 20.40 ± 3.12 min, respectively; P < 0.001). However, the R group had shorter choledochal cyst excision time and mean hepaticojejunostomy anastomosis time than the L group (52.04 ± 2.74 vs. 59.26 ± 3.23 min; 52.42 ± 2.72 vs. 60.63 ± 3.30 min, respectively, P < 0.001). The mean extracorporeal Roux-y jejunojejunostomy time of two groups has no remarkable difference (P > 0.05). The R group also had less mean volume of blood loss (7.04 ± 1.16 vs. 29.04 ± 18.21 mL; P < 0.001). The R group had a shorter indwelling time of gastric tube, anal exhaust time, water feeding time, solids feeding time, and hospital stay time than the L group (P < 0.05). The R group had a lower early complication rate than the L group (4.2 vs. 29.63%; P = 0.026). No statistical differences were identified between the two groups in late or any single complication (0.00 vs. 11.11%; P > 0.05).ConclusionsA resection of the choledochal cyst and a Roux-en-Y hepaticojejunostomy can be performed much more precisely by single-site plus one robotic-assisted surgery. Patients can achieve rapid recovery, and the umbilical incision is more concealed and beautiful. Combing the experience of single-site surgery with robot-assisted surgery, the operators can implement the technique in children safely and feasibly.

The importance of online learning in higher education settings is growing, not only in wake of the Covid-19 pandemic. Therefore, metrics to evaluate and increase the quality of online instruction are crucial for improving student learning. Whereas instructional quality is traditionally evaluated with course observations or student evaluations, course syllabi offer a novel approach to predict course quality even prior to the first day of classes. This study develops an online course design characteristics rubric for science course syllabi. Utilizing content analysis, inductive coding, and deductive coding, we established four broad high-quality course design categories: course organization, course objectives and alignment, interpersonal interactions, and technology. Additionally, this study exploratively applied the rubric on 11 online course syllabi (N = 635 students) and found that these design categories explained variation in student performance.

Entering the 21st century, material abundance has been greatly enriched, and living standards have been continuously improved. Now society is gradually moving towards the era of experience economy. From the perspective of experience economy, patients’ demands for hospitals are not only the satisfaction of medical technology, but their catering consumption also has begun to change to the pursuit of higher requirements. Decision tree algorithm is a kind of data mining algorithm. Data mining technology is a young technology for data analysis. It can simulate mathematical models or algorithms through data analysis, which greatly improves the prediction accuracy. This paper aims to study how to identify the influencing factors of hospital catering service satisfaction, and proposes the application of decision tree algorithm to the hospital catering service satisfaction research, and proposes decision tree-related algorithms, such as ID3, C4.5, and C5.0. Based on the analysis of patients’ satisfaction with the hospital catering service in a certain hospital, the results of the model study based on the decision tree algorithm show that the risk estimation value of the training set is 0.064, and the total correct percentage is 93.6%. The risk estimate for the test set was 0.065, for a total correct percentage of 93.5%. It can be seen that the effect of the model is good and can be effectively predicted.

Early forecasting of crop yield from field to region is important for stabilizing markets and safeguarding food security. Producing a precise forecasting result with fewer inputs is an ongoing goal for the large-area yield evaluation. We present one approach of yield prediction for maize that was explored by incorporating remote-sensing-derived land surface temperature (LST) and field in-season data into a series of logistic models with only a few parameters. Continuous observation data of maize were utilized to calibrate and validate the corresponding logistic models for regional biomass estimating based on field temperatures (including crop canopy temperature (Tc)) and relative dry/fresh biomass accumulation. The LST maps from MOD11A1 products, which are considered to be matched as Tc in large irrigation districts, were assimilated into the validated models to estimate the biomass accumulation. It was found that the temporal-scale difference between the instantaneous LST and the daily average value of field-measured Tc was eliminated by data normalization method, indicating that the normalized LST could be input directly into the model as an approximation of the normalized Tc. Making one observed biomass in-season as the driving force, the maximum of dry/fresh biomass accumulation (DBA/FBA) at harvest could be estimated. Then, grain yield forecasting could be achieved according to the local harvest index of maize. Silage and grain yields were evaluated reasonably well compared with field observations based on the regional map of LST values obtained in 2017 in Changchun, Jilin Province, China. Here, satisfactory grain and silage yield forecasting was provided by assimilating once measured value of DBA/FBA at the middle growth period (early August) into the model in advance of harvest. Meanwhile, good results were obtained in the application of this approach using field data in 2016 to predict grain yield ahead of harvest in the Jiefangzha sub-irrigation district, Inner Mongolia, China. This study demonstrated that maize yield can be forecasted accurately prior to harvest by assimilating remote-sensing-derived LST and field data into the logistic models at a regional scale considering the spatio-temporal scale extension of ground information and crop dynamic growth in real time.

Ribosomal proteins (RPs) constitute the ribosome, thus participating in the protein biosynthesis process. Emerging studies have suggested that many RPs exhibit different expression levels across various tissues and function in a context-dependent manner for animal development. Drosophila melanogaster RpS3 encodes the ribosomal protein S3, one component of the 40S subunit of ribosomes. We found that RpS3 is highly expressed in the reproductive organs of adult flies and its depletion in male germline cells led to severe defects in sperm production and male fertility. Immunofluorescence staining showed that RpS3 knockdown had little effect on early germ cell differentiation, but strongly disrupted the spermatid elongation and individualization processes. Furthermore, we observed abnormal morphology and activity of mitochondrial derivatives in the elongating spermatids of RpS3-knockdown testes, which could cause the failure of axoneme elongation. We also found that RpS3 RNAi inhibited the formation of the individualization complex that takes charge of disassociating the spermatid bundle. In addition, excessive apoptotic cells were detected in the RpS3-knockdown testes, possibly to clean the defective spermatids. Together, our data demonstrated that RpS3 plays an important role in regulating spermatid elongation and individualization processes and, therefore, is required for normal Drosophila spermatogenesis.

Talpidae is a model group for evolutionary studies due to their highly specialized morphologies and diverse lifestyles. Mitochondrial genomes are molecular markers commonly used in species evolution and phylogenetic studies. In this study, the complete mitochondrial genome sequence of Scaptochirus moschatus was obtained by Illumina NovaSeq sequencing. The complete mitochondrial genomes of 14 Talpidae species (including Scaptochirus moschatus obtained in the present study) and the cytochrome b (Cyt b) gene sequences of 48 Talpidae species were downloaded from the NCBI database for comparison and phylogenetic studies to analyze the phylogenetic relationships and to find the possible reasons of the niche differentiation and ecotype specialization of Talpidae animals. The results showed that the mitochondrial genome sequences of 14 species belonging to the family Talpidae were 16,528 to 16,962 bp, all containing 13 protein-coding genes, 22 tRNA, two rRNA, and a non-coding region (control region). The difference in the number of repetitive repeats in the control region is responsible for the difference in the length of Talpidae mitochondrial genome sequences. Combining the divergence time of Talpidae animals with the geological history, it is found that the niche differentiation and ecotype divergence of Talpidae is closely related to historically global climate changes. Semi-aquatic groups diverged in the early Oligocene (about 31.22 MYA), probably in response to the global climate transition from warm to cool. During the early Miocene (about 19.54 MYA), some species of Talpidae moved to underground habitats and formed fossorial groups that were adept at digging due to the effects of the glaciation. In the middle Miocene (about 16.23 MYA), some Talpidae animals returned to the ground and formed semi-fossorial shrew moles as global climate warming again.

Rolling bearing health status monitoring is essential for identifying early failures and avoiding un-planned downtime in industrial systems. To overcome the problems of existing entropy methods with multiple faults that are easily confounded at different scales, a weak signal feature extraction method based on refined composite multi-scale weighted entropy is proposed in this paper. The time–frequency domain features are constituted into a multi-dimensional original fault feature set, and the feature sensitivity is evaluated in terms of four feature evaluation criteria, in order to filter out a sensitive feature subset. Three types of refined composite multi-scale entropy are combined with sensitive feature parameters, in a weighted manner, through the use of the Hadamard product operation. The effects of different combinations of feature parameters on the refined composite multi-scale entropy are analyzed through experimental validation. According to the analysis of the experimental data from two test stations, the fault recognition rate reached 100% and 92.22%, respectively, based on the RCMWE method, starting from the first features. The results indicate that the proposed method can identify bearing fault types under different damage states at any scale, with the fault recognition rate being more stable than that of other methods. The proposed method can effectively distinguish rolling bearing health and fault states, providing higher classification accuracy for rolling bearing fault types and fault damage degrees. This puts forward a new idea for rolling bearing health state assessment, which has high engineering application value.

Radix Polygoni Multiflori (PM) is a well−known nootropic used in traditional Chinese medicine (TCM). Considering the efficacy and application discrepancy between raw (RPM) and processed PM (PPM), the similarities and differences between them in the treatment of vascular dementia (VaD) is intriguing. In this study, a VaD rat model was constructed by 2−vessel occlusion (2−VO). During 28 days of treatment, plasma was collected on days 7, 14, 21, and 28 after the start of dosing and the metabolic profile was analyzed by HPLC−MS/MS−based metabolomics. The Morris Water Maze Test, hematoxylin–eosin and Nissl staining, and biochemical analysis were used to assess cognitive function, pathogenic alterations and oxidative stress, respectively. RPM and PPM effectivelyreducedthe 2VO−induced cognitive impairment and mitigated histological alterations in hippocampus tissue. The 2−VO model significantly elevated MDA level and decreased SOD activity and GSH level, indicating severe oxidative stress, which could also be attenuated by RPM and PPM treatment. RPM outperformed PPM in decreasing MDA levels while PPM outperformed RPM in increasing GSH levels. Differential metabolites were subjected to Metabolite Set Enrichment Analysis (MSEA) and genes corresponding to proteins having interactions with metabolites were further annotated with Gene Ontology (GO). Both RPM and PPM ameliorated VaD−relevant vitamin B6 metabolism, pentose phosphate pathways, and taurine and hypotaurine metabolism. In addition, the metabolism of cysteine and methionine was regulated only by RPM, and riboflavin metabolism was modulated only by PPM. The results suggested that raw and processed PM had comparable efficacy in the treatment of VaD but also with some mechanistic differenece.

With the rapid growth of online learning at community colleges and the low course completion and performance associated with it, there has been increasing need to identify effective ways to address the challenges in online teaching and learning at this setting. Based on open-ended survey responses from 105 instructors and 365 students from multiple community colleges in a state, this study examined instructors’ and students’ perceptions of effective and ineffective instructional practices and changes needed in online coursework. By combining structural topic modelling techniques with human coding, we identified instructional practices that were perceived by both instructors and students as effective in supporting online learning as well as ineffective and needing improvement. Moreover, we identified a handful of misalignments between instructors and students in their perceptions of online teaching, including course workload and effective ways to communicate.

One of the major challenges in treating Alzheimer's disease (AD) is its early diagnosis. Increasing data from clinical and animal research indicate that the retina may facilitate an early diagnosis of AD. However, a previous study on the 5xFAD (a fast AD model), showing retinal changes before those in the brain, has been questioned because of the involvement of the retinal degeneration allele Pde6brd1. Here, we tested in parallel, at 4 and 6 months of age, both the retinal and the brain structure and function in a 5xFAD mouse line that carries no mutation of rd1. In the three tested regions of the 5xFAD brain (hippocampus, visual cortex, and olfactory bulb), the Aβ plaques were more numerous than in wild-type (WT) littermates already at 4 months, but deterioration in the cognitive behavioral test and long-term potentiation (LTP) lagged behind, showing significant deterioration only at 6 months. Similarly in the retina, structural changes preceded functional decay. At 4 months, the retina was generally normal except for a thicker outer nuclear layer in the middle region than WT. At 6 months, the visual behavior (as seen by an optomotor test) was clearly impaired. While the full-field and pattern electroretinogram (ERG) responses were relatively normal, the light responses of the retinal ganglion cells (measured with multielectrode-array recording) were decreased. Structurally, the retina became abnormally thick with few more Aβ plaques and activated glia cells. In conclusion, the timeline of the degenerative processes in the retina and the brain is similar, supporting the use of non-invasive methods to test the retinal structure and function to reflect changes in the brain for early AD diagnosis.

ObjectivesTo explore the relationship between ultrasound (US) features and Ki-67 labeling index (LI) of soft tissue sarcoma (STS).MethodsForty-six patients with 47 STS lesions, between September 2014 and April 2020, were enrolled in the study. Point-biserial correlation analysis and Spearman’s correlation analysis were utilized to examining the relationship between the US features and the Ki-67 LI of STS. The differences of US features between high and low Ki-67 proliferation groups were statistically analyzed by independent t test, Wilcoxon rank-sum test, and Fisher’s exact test. The optimal cut-off points of US features revealing significant differences were estimated by the maximum Youden index.ResultsA moderate correlation between the vascular density grade and the Ki-67 LI (ρ = 0.409, P = 0.004) was found in this study. In addition, other ultrasound features were irrelevant to the Ki-67 LI. The cut-off for differentiating low- and high-proliferation groups was grade II according to the best Youden index. The area under receiver operating characteristic (ROC) curve was 0.74 (p = 0.011) with a sensitivity of 60.6% and specificity of 78.6%.ConclusionsOnly the vascular density grade of STS had a weak positive correlation with Ki-67 LI, and might be capable of predicting the proliferation of STS. Other ultrasonographic features of STS such as shape and tumor margin have no correlation with Ki-67 LI.

The short-faced mole (Scaptochirus moschatus) is a unique Chinese mammal that lives in burrows for life. In this study, we used Illumina NovaSeq sequencing to obtain the complete mitochondrial genome of the short-faced mole. The total length of the genome is 16,699 bp, containing 13 protein-coding genes, 22 transfer RNA genes (tRNA), 2 ribosomal RNA genes (rRNA), and 1 control region, with a base composition of 33.82% A, 26.89% T, 25.27% C, and 14.01% G. Phylogenetic analysis of the Talpidae by using complete mitochondrial genome sequences of 14 Talpidae species shows that short-faced mole is closely related to Parascaptor leucura.

Abstract In this article, we regard the generalized Riccati transformation and Riemann–Liouville fractional derivatives as the principal instrument. In the proof, we take advantage of the fractional derivatives technique with the addition of interval segmentation techniques, which enlarge the manners to demonstrate the sufficient conditions for oscillation criteria of certain fractional partial differential equations.

Abstract Background To present a modified laparoscopic surgical technique that works to optimize the surgical view in laparoscopic total excision of choledochal cyst in pediatric patients. Methods From June 2015 to June 2017, a total of 48 pediatric cases of choledochal cyst were admitted. Their age ranged from 15 month to 8 years (average 3.5 years). The Todani types were: type I (n = 32) and type IVa (n = 16), according to the diagnostic criteria of ultrasound, abdominal computed tomography (CT) and magnetic resonance cholangiopancreatography (MRCP). Results Total cystic excision with hepaticoenterostomy was accomplished laparoscopically in 48 cases with our transumbilical single -incision method without conversion to open surgery. Average duration of operation was 200 min (range 170–240 min), average intraoperative blood loss was 9 ml (range 6–14 ml) without the need for blood transfusion. The 72-h postoperative ultrasound reported no abdominal effusion, when the intraperitoneal drainage tube was removed. There was no postoperative complication during the 6 months of follow-up. Conclusions We accomplished the same postoperative outcome in laparoscopic total cyst excision with our modified method as that with conventional laparoscopic surgery. This technique allows the operator to have a stabilized surgical view without needing to rely on an assistant to hold up the liver lobe for larger operative space.

Abstract Background Circulating tumor cells (CTC) shows great prospect to realize precision medicine in cancer patients. Methods We developed the NanoVelcro Chip integrating three functional mechanisms. NanoVelcro CTC capture efficiency was tested in stage III or IV lung adenocarcinoma. Further, ALK-rearrangement status was examined through fluorescent in situ hybridization in CTCs enriched by NanoVelcro. Results NanoVelcro system showed higher CTC-capture efficiency than CellSearch in stage III or IV lung adenocarcinoma. CTC counts obtained by both methods were positively correlated (r = 0.45, p

Lactobacillus delbrueckii subsp. bulgaricus (LDB) is an approved feed additive on the Chinese ‘Approved Feed Additives’ list. However, the possibility of LDB as an antibiotic replacement remains unclear. Particularly, the effect of LDB on microbiota and metabolites in the gastrointestinal tract (GIT) requires further explanation. This study aimed to identify the microbiota and metabolites present in fecal samples and investigate the relationship between the microbiota and metabolites to evaluate the potential of LDB as an antibiotic replacement in pig production. A total of 42 female growing-finishing pigs were randomly allocated into the antibiotic group (basal diet + 75 mg/kg aureomycin) and LDB (basal diet + 3.0 × 109 cfu/kg LDB) groups. Fecal samples were collected on days 0 and 30. Growth performance was recorded and assessed. 16S rRNA sequencing and liquid chromatography-mass spectrometry-based non-targeted metabolomics approaches were used to analyze the differences in microbiota and metabolites. Associations between the differences were calculated using Spearman correlations with the Benjamini–Hochberg adjustment. The LDB diet had no adverse effect on feed efficiency but slightly enhanced the average daily weight gain and average daily feed intake (p > 0.05). The diet supplemented with LDB increased Lactobacillus abundance and decreased that of Prevotellaceae_NK3B31_group spp. Dietary-supplemented LDB enhanced the concentrations of pyridoxine, tyramine, D-(+)-pyroglutamic acid, hypoxanthine, putrescine and 5-hydroxyindole-3-acetic acid and decreased the lithocholic acid concentration. The Lactobacillus networks (Lactobacillus, Peptococcus, Ruminococcaceae_UCG-004, Escherichia-Shigella, acetophenone, tyramine, putrescine, N-methylisopelletierine, N1-acetylspermine) and Prevotellaceae_NK3B31_group networks (Prevotellaceae_NK3B31_group, Treponema_2, monolaurin, penciclovir, N-(5-acetamidopentyl)acetamide, glycerol 3-phosphate) were the most important in the LDB effect on pig GIT health in our study. These findings indicate that LDB may regulate GIT function through the Lactobacillus and Prevotellaceae_NK3B31_group networks. However, our results were restrained to fecal samples of female growing-finishing pigs; gender, growth stages, breeds and other factors should be considered to comprehensively assess LDB as an antibiotic replacement in pig production.

To solve the problem of layout design of charging stations in the early stage of the electric vehicle industry, the user’s satisfaction and the charging convenience are considered. An electric vehicle charging station site-selection model is established based on the kernel density analysis of the urban population. The goal of this model is maximum electric vehicle user satisfaction and the highest charging convenience. Then, according to model characteristics, the immune algorithm is designed and optimized to solve the model. The optimization of the immune algorithm includes two aspects. On the one aspect, judging that the stop condition is added in the mutation link. On the other aspect, two mutation operators are designed in the optimized immune algorithm. Finally, the simulation example is determined by a three-step method in Jinan City. The results show that the electric vehicle charging station site-selection model in this paper can better meet user needs compared with traditional models. Compared with the traditional immune algorithm, the convergence speed of the optimized immune algorithm is improved, and the proposed algorithm is superior to the traditional immune algorithm in terms of stability and accuracy.

In this research, we designed a rapid tricolour immunochromatographic test strip with double test lines (TS-DTL) and two-colour AuNP probes, which realised the simultaneous detection of tricaine mesylate (TMS) and malachite green (MG). Through a distinct tricolour system (red T1 line, blue T2 line and purple C line), a visual identification of TMS (0.2 μg/mL) and MG (0.5 μg/mL) was quickly achieved on site, which improved the accuracy of naked eye observations. The LODs of TMS in aquaculture water, fish and shrimp were 11.0, 29.6 and 61.4 ng/mL, respectively. MG LODs were 47.0 ng/mL (aquaculture water), 82.8 ng/mL (fish) and 152.4 ng/mL (shrimp). The LOD of MG was close to the similar TS methods. However, visual detection of TMS could meet the requirements of the residue limit (1 μg/mL) of TMS in the USA, and the quantitative detection of TMS was over 16 times lower than the USA standard. The developed platform was rapid (~20 min, HPLC~3 h) and accurate, which was verified using a traditional HPLC method. The recovery rates ranged from 82.2% to 108.6% in three types of real samples, indicating a potential application in on-site fast screening or multiple detection for TMS and MG residues in aquatic products.

Reasonable quantitative assessment on urban ecosystem health is conducive to the sustainable development of the economy and human society. This paper quantitatively evaluated the impact of land use change on ecosystem services and ecosystem health by building a comprehensive evaluation system (vigor–organization–resilience–ecosystem services), and then analyzed the spatial-temporal pattern, evolution characteristics, and driving factors in the Shanghai–Hangzhou Bay area (SHB) over the 2000–2015 period. The results show that: the area of cropland and forest accounted for more than 65% and was mainly converted into built-up land in the past 15 years. The overall ESV showed a trend of first increasing and then decreasing. Forest accounted for the largest proportion of the total ESV, more than 60% in each year. The ecosystem health value of SBH decreased from 2000 to 2015. At the city scale, the ecosystem health was significantly deteriorated. All cities reached the lowest value by 2015. At the districts/counties scale, the number with the relatively well or well level decreased from 32 in 2000 to 20 in 2015 by 24.64% of the total area. Overall, inland regions of SBH had better ecosystem health situation than coastal areas. The rapid urbanization of population and economy were driving factors for the decline of the ecosystem health. The indicator system of integrating the vigor, organization, resilience, and ecosystem service for ecosystem health assessment is a potential method which could provide a quantitative and comprehensive way for evaluating ecological and environmental effects in the future.

Aiming to resolve the problem of redundant information concerning rolling bearing degradation characteristics and to tackle the difficulty faced by convolutional deep learning models in learning feature information in complex time series, a prediction model for remaining useful life based on multiscale fusion permutation entropy (MFPE) and a multiscale convolutional attention neural network (MACNN) is proposed. The original signal of the rolling bearing was extracted and decomposed by resonance sparse decomposition to obtain the high-resonance and low-resonance components. The multiscale permutation entropy of the low-resonance component was calculated. Moreover, the locally linear-embedding algorithm was used for dimensionality reduction to remove redundant information. The multiscale convolution module was constructed to learn the feature information at different time scales. The attention module was used to fuse the feature information and input it into the remaining useful life prediction module for evaluation. The appropriate network structure and parameter configuration were determined, and a multiscale convolutional attention neural network was designed to determine the remaining useful life prediction model. The results show that the method demonstrates effectiveness and superiority in degrading the feature information representation and improving the remaining useful life prediction accuracy compared with other models.

BackgroundIt is well known that obesity is one of the risks for incurrence and development in breast cancer patients. Long non-coding RNAs (lncRNAs) are reported to participate in the composition of tumor microenvironment and to regulate breast cancer cell metabolic activities. However, there was rare study focused on the lncRNAs in breast cancer with the influences of adipocytes. The study aimed to investigate lncRNAs expression profiles and discover potential biomarkers to predict the incidence and progression of adipocyte-associated-breast cancer.MethodsWe co-cultured adipocytes with breast cancer cells and profiled the expression of lncRNAs as well as mRNAs by using the RNA-sequencing method. Wound Healing, Migration assays and Invasion assays were applied to verify the invasion and metastasis of cancer cells.ResultsMDA-MB-231/Hpa-V and SK-BR-3/Hpa-V cells showed elevated migration and invasiveness compared to the control group. A sum of 371 mRNAs (181 upregulated and 190 downregulated) and 850 lncRNAs(414 upregulated and 436 downregulated) were differentially expressed in MDA-MB-231/Hpa-V comparing to MDA-MB-231(P < 0.05; |log2 (fold change)|>1.2). GO enrichment, KEGG pathway and interaction networks demonstrated that differentially expressed lncRNAs were involved in functional categories, such as material metabolism, which might lead to the progression of breast cancer.ConclusionOur study detected a lncRNA profile in breast cancer cells affecting by adipocytes and provided a better understanding of the tumor microenvironment. LncRNAs may be helpful to predict the therapeutic responses and prognosis of obese breast cancer patients.

Like all educational institutions, community colleges rapidly shifted to online instruction in the wake of the COVID-19 pandemic. However, little is known about what factors shaped individual college responses. This survey of distance education leaders (N = 45) in the California community colleges system aimed to: a) characterize pre-COVID distance education resources, emergency responses to the pandemic, and readiness for online instruction in the fall, and b) determine how pre-COVID distance education resources, emergency responses, and fall readiness relate to each other. We find wide variability in pre-COVID distance education resources. These pre-existing resources were related to institutions’ responses: Colleges with fewer pre-COVID resources focused on foundational efforts such as creating online student services, while institutions with greater pre-COVID resources offered somewhat broader responses to training students and faculty in skills to successfully transition online. Finally, although colleges improved their readiness for continued remote instruction in the fall term in terms of training faculty and providing students with technology to access classes, respondents estimated that roughly a third of students would still face barriers accessing remote classes.

To understand instruction during the spring 2020 transition to emergency distance learning (EDL), we surveyed a sample of instructors teaching undergraduate EDL courses at a large university in the southwest. We asked them how frequently they used and how confident they were in their ability to implement each of nine promising practices, both for their spring 2020 EDL course and a time when they previously taught the same course face-to-face (F2F). Using latent class analysis, we examined how behavioral frequencies and confidence clustered to form meaningful groups of instructors, how these groups differed across F2F and EDL contexts, and what predicted membership in EDL groupings. Results suggest that in the EDL context, instructors fell into one of three profiles in terms of how often they used promising practices: Highly Supportive, Instructor Centered, and More Detached. When moving from the F2F to EDL context, instructors tended to shift “down” in terms of their profile—for example, among F2F Highly Supportive instructors, 34% shifted to the EDL Instructor Centered profile and 30% shifted to the EDL More Detached Profile. Instructors who reported lower self-efficacy for EDL practices were also more likely to end up in the EDL More Detached profile. These results can assist universities in understanding instructors' needs in EDL, and what resources, professional development, and institutional practices may best support instructor and student experiences.