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The object detection of synthetic aperture radar (SAR) ships holds significant promise for water traffic monitoring, ship search and rescue, and maritime warning tasks. Regrettably, most of the existing SAR ship object detection is limited to the fully supervised paradigm, exhibiting a firm reliance on data labels, and inherent challenges such as multiscale ship feature disparities and indistinct small-sized ships also make SAR ship detection difficult. To address these, we propose a scale-mixing enhanced and dual consistency guided semisupervised object detection (SMDC-SSOD) method. Specifically, this method is based on the teacher–student framework and primarily comprises three core components: cross-scale feature mixing (CSFM) scheme, scale change consistency guidance (SCCG) strategy, and proposal consistency guidance (PCG) strategy, which can efficiently conduct end-to-end semisupervised learning from limited data labeling, achieving low-cost and high-performance ship perception. CSFM scheme includes interpyramid and intrapyramid feature cross-scale mixings, which can improve the network's adaptability for multiscale ship characteristics and increase focus on small-sized ships. SCCG strategy leverages variations in confidence scores at different scales to select valuable pseudolabels, providing more precise guidance for the student network. PCG strategy further reflects the positioning quality of pseudolabels through the proposal consistency generated by the student network, guiding it to make high-quality predictions. The experimental results on the publicly available HRSID, BBox-SSDD, and SAR-Ship-Dataset demonstrate that SMDC-SSOD can accurately detect SAR ships with an extremely low data annotation rate (below 10%) and achieve optimal detection performance compared to state-of-the-art methods.

Background: A new type of silver alloy hydrogel-coated (SAH) catheter has been shown to prevent bacterial adhesion and colonization by generating a microcurrent, and to block the retrograde infection pathway. However, these have only been confirmed in ordinary patients. This study aims to evaluate the effectiveness of a SAH catheter for preventing urinary tract infections in critically ill patients. Methods: This was a prospective single-center, single-blind, randomized, controlled study. A total of 132 patients requiring indwelling catheterization in the intensive care unit (ICU) of the First Affiliated Hospital of the University of Science and Technology of China between October 2022 and February 2023 and who met the study inclusion/exclusion criteria were randomly divided into two groups. Patients in the SAH catheter group received a SAH catheter, while patients in the conventional catheter group received a conventional siliconized latex Foley catheter. The main outcome measure was the incidence of catheter-associated urinary tract infections (CAUTIs). Secondary outcome indicators included urine positivity for white blood cells and positive urine cultures on 3 days, 7 days, 10 days, and 14 days after catheterization, number of viable bacteria in the catheter biofilm on day 14, pathogenic characteristics of positive urine cultures, length of ICU stay, overall hospital stay, ICU mortality, and 28-day mortality. All the data were compared between the two groups. Results: A total of 68 patients in the conventional catheter group and 64 patients in the SAH catheter group were included in the study. On day 7 after catheter placement, the positivity rate for urinary white blood cells was significantly higher in the conventional catheter group than in the SAH catheter group (33.8% vs. 15.6%, P=0.016). On day 10, the rates of positive urine cultures (27.9% vs. 10.9%, P=0.014) and CAUTIs (22.1% vs. 7.8%, P=0.023) were significantly higher in the conventional catheter group than in the SAH catheter group. On day 14, the numbers of viable bacteria isolated from the catheter tip ([3.21±1.91]×106 colony-forming units [cfu]/mL vs. [7.44±2.22]×104 cfu/mL, P

Bearing health is key for maintaining good performance and safety in rotating machinery. As the diagnosis of mechanical faults develops toward intelligence and automation, accurate and systematic fault diagnosis algorithms are imperative. Focusing on the diagnosis of rolling bearing failures, this study utilizes a sliding time window to extract essential data segments. A series of signal processing techniques, including filtering, amplitude–frequency analysis, Hilbert envelope analysis, and energy analysis, is applied to establish a comprehensive dataset. For extraction of the hidden properties of the data, the recurrence quantity spectrum is defined for the input of the neural network. The goal is to obtain a cleaner dataset with enhanced features. A convolution neural network is constructed. Different activation functions in the activation layer are compared for better fault diagnosis algorithms. The established feature matrices are specifically defined to accurately identify the subtlest defects of bearings, thereby facilitating early detection. The proposed procedure distinguishes various fault modes. As for the multidimensional complexities of fault signals, this study carries out a comprehensive comparison of energies, recurrence quantification, and amplitude–frequency characteristics of bearing fault detection to assess the accuracy, computational efficiency, and robustness of bearing fault diagnosis. The proposed method and bearing fault detection procedures have potential in practical applications.

Background: Cuproptosis is a copper-dependent cell death that is connected to the development and immune response of multiple diseases. However, the function of cuproptosis in the immune characteristics of sepsis remains unclear. Method: We obtained two sepsis datasets (GSE9960 and GSE134347) from the GEO database and classified the raw data with R packages. Cuproptosis-related genes were manually curated, and differentially expressed cuproptosis-related genes (DECuGs) were identified. Afterwards, we applied enrichment analysis and identified key DECuGs by performing machine learning techniques. Then, the immune cell infiltrations and correlation between DECuGs and immunocyte features were created by the CIBERSORT algorithm. Subsequently, unsupervised hierarchical clustering analysis was performed based on key DECuGs. We then constructed a ceRNA network based on key DECuGs by using multi-step computational strategies and predicted potential drugs in the DrugBank database. Finally, the role of these key genes in immune cells was validated at the single-cell RNA level between septic patients and healthy controls. Results: Overall, 16 DECuGs were obtained, and most of them had lower expression levels in sepsis samples. Afterwards, we obtained six key DECuGs by performing machine learning. Then, the LIPT1-T-cell CD4 memory resting was the most positively correlated DECuG–immunocyte pair. Subsequently, two different subclusters were identified by six DECuGs. Bioinformatics analysis revealed that there were different immune characteristics between the two subclusters. Moreover, we identified the key lncRNA OIP5-AS1 within the ceRNA network and obtained 4 drugs that may represent novel drugs for sepsis. Finally, these key DECuGs were statistically significantly dysregulated in another validation set and showed a major distribution in monocytes, T cells, B cells, NK cells and platelets at the single-cell RNA level. Conclusion: These findings suggest that cuproptosis might promote the progression of sepsis by affecting the immune system and metabolic dysfunction, which provides a new direction for understanding potential pathogenic processes and therapeutic targets in sepsis.

Phosphorus deficiency severely limits crop yields and hinders sustainable agricultural development. Phosphate-solubilizing bacteria (PSB) are beneficial for crop growth because they enhance the uptake and utilization of phosphorus. This study explored the phosphorus-solubilizing, IAA-producing, nitrogen-fixing, potassium-solubilizing, and siderophore-producing abilities of three bacterial strains (Pantoea sp. J-1, Burkholderia cepacia Z-7, and Acinetobacter baumannii B-6) screened from the maize rhizosphere. A pot experiment was also conducted to explore the role of screened PSB in the growth of maize. Finally, the effects of the PSB on the physicochemical properties, enzyme activities, and microbial community structure of maize rhizosphere soil were analyzed. The results showed that strain Z-7 had the strongest abilities phosphorus solubilization, nitrogen fixation, potassium solubilization, and siderophore production, while strain J-1 exhibited the highest yield of IAA. The application of PSB promoted the growth of maize plants to different extents. Among the different treatments, the mixed bacterial treatment (J-1 + Z-7 + B-6) had the most potent growth promotion effect, and the consortium treatment significantly enhanced the activity of soil phosphatase. Soil pH, total phosphorus (TP), total potassium (TK), available phosphorus (AP), NH4+-N, and NO3−-N are key factors for the growth of maize plants. In addition, PSB significantly altered the microbial community structure in the maize rhizosphere soil, and the relative abundance of Proteobacteria increased by 16.07–69.10% compared to the control. These PSB have obvious growth-promoting abilities, with the potential to enhance crop productivity as excellent candidate strains for the development of biological fertilizers.

Abstract Background Sepsis is a high mortality disease which seriously threatens human life and health, for which the pathogenetic mechanism still unclear. There is increasing evidence showed that immune and inflammation responses are key players in the development of sepsis pathology. LncRNAs, which act as ceRNAs, have critical roles in various diseases. However, the regulatory roles of ceRNA in the immunopathogenesis of sepsis have not yet been elucidated. Results In this study, we aimed to identify immune biomarkers associated with sepsis. We first generated a global immune-associated ceRNA (IMCE) network based on data describing interactions pairs of gene–miRNA and miRNA–lncRNA. Afterward, we excavated a dysregulated sepsis immune-associated ceRNA (SPIMC) network from the global IMCE network by means of a multi-step computational approach. Functional enrichment indicated that lncRNAs in SPIMC network have pivotal roles in the immune mechanism underlying sepsis. Subsequently, we identified module and hub genes (CD4 and STAT4) via construction of a sepsis immune-related PPI network. Then, we identified hub genes based on the modular structure of PPI network and generated a ceRNA subnetwork to analyze key lncRNAs associated with sepsis. Finally, 6 lncRNAs (LINC00265, LINC00893, NDUFA6-AS1, NOP14-AS1, PRKCQ-AS1 and ZNF674-AS1) that identified as immune biomarkers of sepsis. Moreover, the CIBERSORT algorithm and the infiltration of circulating immune cells types were performed to identify the inflammatory state of sepsis. Correlation analyses between immune cells and sepsis immune biomarkers showed that the LINC00265 was strongly positive correlated with the macrophages M2 (r = 0.77). Conclusion Collectively, these results may suggest that these lncRNAs (LINC00265, LINC00893, NDUFA6-AS1, NOP14-AS1, PRKCQ-AS1 and ZNF674-AS1) played important roles in the immune pathogenesis of sepsis and provide potential therapeutic targets for further researches on immune therapy treatment in patients with sepsis.

Abstract There are few studies focus on post-neoadjuvant treatment in hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-)/lymph node-positive (LN+) breast cancer, a multi-center, open-label, randomized, controlled phase III trial was conducted to evaluate pathological response-guided non-cross-resistant adjuvant chemotherapy in patients with HR+/HER2-/LN+ breast cancer who were non-responsive to primary chemotherapy. Patients received four cycles of non-cross-resistant adjuvant chemotherapy plus endocrine therapy (ET), or ET alone. Forty patients responsive to neoadjuvant chemotherapy and with Miller and Payne G4 or G5 and LN- status were assigned to the observation group. Distant disease-free survival was the primary endpoint. The final intention-to-treat analysis comprised 379 patients. After a median follow-up period of 72.4 months, the 5-year distant disease-free survival was 92% and 90% in the chemotherapy plus ET and ET-alone groups, respectively. Comparatively, the observation group showed a trend towards better distant disease-free survival. For patients non-responsive to neoadjuvant chemotherapy, adjuvant non-cross-resistant chemotherapy did not significantly improve distant disease-free survival compared to ET alone.

Background: The association between breast cancer patients with a TP53 pathogenic variant and risk of local recurrence and contralateral breast cancer remains largely unknown. Methods: The study population of 11093 patients was derived from two cohorts at the Breast Center of Peking University Cancer Hospital in China from November 2003, to March 2018. TP53 germline variants were determined for all patients. Results: In the study, forty-one (0.37%) carried a TP53 germline pathogenic variant, and 11052 were non-carriers (99.63%). Nineteen TP53 carriers (46.3%) and 4173 non-carriers (37.8%) were treated with breast-conserving therapy (BCT), while the remaining were treated with mastectomy. After a median follow-up of 6.7 years, the rate of ipsilateral breast tumor recurrence (IBTR) in TP53 carriers was significantly higher than that in non-carriers when treated with BCT (21.1% vs 3.8%, P = 0.006). No difference in the rate of IBTR was found between TP53 carriers and non-carriers when treated with mastectomy (0.0% vs 2.6%, P = 1.0). Furthermore, the rate of IBTR in TP53 carriers treated with BCT was significantly higher than that in those treated with mastectomy (21.1% vs 0.0%, P = 0.038). The 10-year cumulative risk of contralateral breast cancer in TP53 carriers was significantly higher than that in non-carriers (17.9% vs 3.6%, hazard ratio (HR) = 7.0, 95% CI: 3.3–14.9, P

Abstract The rockburst dynamic disasters in the process of deep coal mining become more and more serious. Taking the rockburst occurred in the 23130 working face of Yuejin Coal Mine as the engineering background, we study the characteristics of mining stress field around roadway, the plastic failure morphological characteristics of surrounding rock and the accumulation/release law of elastic energy before and after burst. An analysis model quantitatively describing the physical process of rockburst in the mining roadway is established, and the calculation method of dynamic release of elastic energy in the physical process of rockburst is educed. The mechanism of rockburst in mining roadway is revealed. The results show that an “L-shaped” stress concentration zone is formed within 100 m of the 23130 working face, and the principal stress ratio of the surrounding rock of the transportation roadway is 2.59–4.26. The change of the direction of the maximum principal stress has a significant effect on the burst appearance characteristics. The failure strength of different sections of the mining roadway is characterized by the elastic energy release value. With the increase of the working face distance, the elastic energy released by burst failure and the expansion variation of failure boundary radius show a nonlinear variation law that tends to decrease steadily after sharp fluctuation. The closer to the working face, the higher the burst risk. At a distance of 10 m from the working surface, the maximum principal stress reaches its maximum value. The butterfly-shaped failure system generated by the surrounding rock of the roadway has energy self-sustainability, and the elastic energy released by the sudden expansion of the butterfly leaf is enough to cause a burst damage of 1.9 magnitude. This work could provide theoretical support for the prediction and prevention of rockburst.

The operating temperature of anaerobic digesters should be adjusted to adapt to seasonal variations in environmental temperature and the composition of organic solid waste. This study investigated the effects of one-step abrupt temperature changes (from mesophilic to thermophilic temperature, M–T, and from thermophilic to mesophilic temperature, T–M) and the inoculation ratio on methane yield and microbial diversity during the anaerobic co-digestion of kitchen waste with dewatered sludge. The results showed that the cumulative methane yield (CMY) level resulting from thermophilic control and the M–T digesters was greater than that resulting from mesophilic control and the T–M digesters. The CMF of M–T digesters increased, whereas the CMY of T–M digesters gradually decreased with an increase in the inoculation ratio. The maximal CMY was 385.1 mL/g-VSSadded, which corresponded to an M–T digester with a 5% inoculation ratio. In the later stage of anaerobic digestion, the bacterial community of T–M was more diverse than that of M–T, but the archaeal community of M–T was more diverse than that of T–M. The one-step temperature change from thermophilic to mesophilic temperature was more stable than that from mesophilic to thermophilic temperature.

With the growing scale of pre-trained language models (PLMs), full parameter fine-tuning becomes prohibitively expensive and practically infeasible. Therefore, parameter-efficient adaptation techniques for PLMs have been proposed to learn through incremental updates of pre-trained weights, such as in low-rank adaptation (LoRA). However, LoRA relies on heuristics to select the modules and layers to which it is applied, and assigns them the same rank. As a consequence, any fine-tuning that ignores the structural information between modules and layers is suboptimal. In this work, we propose structure-aware low-rank adaptation (SaLoRA), which adaptively learns the intrinsic rank of each incremental matrix by removing rank-0 components during training. We conduct comprehensive experiments using pre-trained models of different scales in both task-oriented (GLUE) and task-agnostic (Yelp and GYAFC) settings. The experimental results show that SaLoRA effectively captures the structure-aware intrinsic rank. Moreover, our method consistently outperforms LoRA without significantly compromising training efficiency.

This study investigated the performance of thermophilic–mesophilic (T-M) and mesophilic–thermophilic (M-T) two-phase sludge anaerobic digestion at different inoculation proportions after a change in digestion temperature. After temperature change, the pH, total ammonia nitrogen (TAN), free ammonia nitrogen (FAN), solubility chemical oxygen demand (SCOD), and total alkalinity (TA) levels of two-phase digesters were between thermophilic control digesters and mesophilic control digesters. However, the volatile fatty acid (VFA) levels of two-phase digesters were higher than those of thermophilic or mesophilic control digesters. The bacteria communities of M-T two-phase digesters were more diverse than those of T-M. After a change in digestion temperature, the bacterial community was dominated by Coprothermobacter. After a change of digestion temperature, the relative abundance (RA) of Methanobacterium, Methanosaeta, and Methanospirillum of M-T two-phase digesters was higher than that of T-M two-phase digesters. In comparison, the RA of Methanosarcina of T-M two-phase digesters was higher than that of M-T two-phase digesters. The ultimate methane yields of thermophilic control digesters were greater than those of mesophilic control digesters. Nevertheless, the ultimate methane yield levels of M-T two-phase digesters were greater than those of T-M two-phase digesters. The ultimate methane yields of all two-phase digesters presented an earlier increase and later decrease trend with the increasing inoculation proportion. Optimal methane production condition was achieved when 15% of sludge (T-M15) was inoculated under mesophilic–thermophilic conditions, which promoted 123.6% (based on mesophilic control) or 27.4% (based on thermophilic control). An optimal inoculation proportion (about 15%) balanced the number and activity of methanogens of high-solid sludge anaerobic digestion.

Abstract Myasthenia gravis (MG) is a complex neurological autoimmune disease with a pathogenetic mechanism that has yet to be elucidated. Emerging evidence has revealed that genes, non-coding RNAs and genetic variants play significant roles in the pathogenesis of MG. However, the molecular mechanisms of single nucleotide polymorphisms (SNPs) located on lncRNAs could disturb lncRNA-mediated ceRNA regulatory functions still unclear in MG. In this study, we collated 276 experimentally confirmed MG risk genes and 192 MG risk miRNAs. We then constructed a lncRNA-mediated ceRNA network for MG based on multi-step computational strategies. Next, we systematically integrated risk pathways and identified candidate SNPs in lncRNAs for MG based on data acquired from public databases. In addition, we constructed a pathway-based lncRNA-SNP mediated network (LSPN) that contained 128 lncRNAs targeting 8 MG risk pathways. By analyzing network, we propose a latent mechanism for how the “lncRNA-SNP-mRNA-pathway” axis affects the pathogenesis of MG. Moreover, 25 lncRNAs and 51 SNPs on lncRNAs were extracted from the “lncRNA-SNP-mRNA-pathway” axis. Finally, functional analyses demonstrated lncRNA-SNPs mediated ceRNA regulation pairs associated with MG participated in the MAPK signaling pathway. In summary, we constructed MG-specific lncRNA-SNPs mediated ceRNA regulatory networks based on pathway in the present study, which was helpful to elucidate the roles of lncRNA-SNPs in the pathogenesis of MG and provide novel insights into mechanism of lncRNA-SNPs as potential genetic risk biomarkers of MG.

Background: Whether sentinel lymph node biopsy should be performed in patients ≥70 years old with early-stage invasive breast cancer is controversial. We examined the effect of sentinel lymph node biopsy on the treatment and outcomes in this population. Materials and Methods: In this retrospective study, patients aged ≥70 years who were treated for invasive breast cancer with sentinel lymph node biopsy followed by mastectomy or lumpectomy between 2010 and 2019 were identified from our database. Patients were compared according to sentinel lymph node status. Outcomes were analyzed using the Kaplan–Meier method and Cox multivariate analysis. Results: Of the 376 patients enrolled in this study, 311 (82.7%) were sentinel lymph node-negative and 65 (17.3%) were sentinel lymph node-positive. The median follow-up duration for all patients was 70 months. Systemic treatment and radiation were similar between sentinel lymph node-negative and -positive groups. Disease-free survival, distant disease-free survival, breast cancer-specific survival, overall survival were not significantly different between groups (88.2% vs 87.6%, 96.7% vs 94.8%, 96.2% vs 93.6%, and 93.5% vs 90.0%, respectively). Sentinel lymph node status, tumor size, chemotherapy, endocrine therapy, and adjuvant radiation were included in Cox multivariate analysis. None of the variables were found to significantly affect disease-free survival, distant disease-free survival, breast cancer-specific survival, and overall survival. Conclusions: Our analysis indicated that sentinel lymph node status may not affect systemic treatment decisions or survival in patients aged ≥70 years with breast cancer.

Abstract Background Long non-coding RNAs (lncRNAs), functioning as competing endogenous RNAs (ceRNAs), have been reported to play important roles in the pathogenesis of autoimmune diseases. However, little is known about the regulatory roles of lncRNAs underlying the mechanism of myasthenia gravis (MG). The aim of the present study was to explore the roles of lncRNAs as ceRNAs associated with the progression of MG. Methods MG risk genes and miRNAs were obtained from public databases. Protein–protein interaction (PPI) network analysis and module analysis were performed. A lncRNA-mediated module-associated ceRNA (LMMAC) network, which integrated risk genes in modules, risk miRNAs and predicted lncRNAs, was constructed to systematically explore the regulatory roles of lncRNAs in MG. Through performing random walk with restart on the network, HCG18/miR-145-5p/CD28 ceRNA axis was found to play important roles in MG, potentially. The expression of HCG18 in MG patients was detected using RT-PCR. The effects of HCG18 knockdown on cell proliferation and apoptosis were determined by CCK-8 assay and flow cytometry. The interactions among HCG18, miR-145-5p and CD28 were explored by luciferase assay, RT-PCR and western blot assay. Results Based on PPI network, we identified 9 modules. Functional enrichment analyses revealed these modules were enriched in immune-related signaling pathways. We then constructed LMMAC network, containing 25 genes, 50 miRNAs, and 64 lncRNAs. Through bioinformatics algorithm, we found lncRNA HCG18 as a ceRNA, might play important roles in MG. Further experiments indicated that HCG18 was overexpressed in MG patients and was a target of miR-145-5p. Functional assays illustrated that HCG18 suppressed Jurkat cell apoptosis and promoted cell proliferation. Mechanistically, knockdown of HCG18 inhibited the CD28 mRNA and protein expression levels in Jurkat cells, while miR-145-5p inhibitor blocked the reduction of CD28 expression induced by HCG18 suppression. Conclusion We have reported a novel HCG18/miR-145-5p/CD28 ceRNA axis in MG. Our findings will contribute to a deeper understanding of the molecular mechanism of and provide a novel potential therapeutic target for MG.

Abstract To compare outcomes in patients with human epidermal growth factor receptor-2 (HER2)-positive breast cancer who received either dose-dense neoadjuvant chemotherapy (NAC) with trastuzumab or standard-interval chemotherapy with trastuzumab. Patients with HER2-positive breast cancer who received NAC, including epirubicin and cyclophosphamide followed by paclitaxel with trastuzumab were included. Patients were divided into either the dose-dense or standard-interval group. We compared pathologic complete remission (pCR), distant disease-free survival (DDFS), event-free survival (EFS), and breast cancer-specific survival (BCSS) between the two groups. Two hundred (49.6%) patients received dose-dense NAC, and 203 (50.4%) received standard-interval NAC. The pCR rate was 38.4% in the dose-dense group and 29.2% in the standard-interval group (P = 0.052). In patients with lymph node (LN) metastases, the LN pCR rate was 70.9% in the dose-dense group and 56.5% in the standard-interval group (P = 0.037). After a median follow-up of 54.6 months, dose-dense chemotherapy presented an improvement on DDFS (hazard ratio [HR] = 0.49, 95% confidence interval [CI]: 0.19–1.28, EFS (HR = 0.54, 95% CI: 0.24–1.21), and BCSS (HR = 0.41, 95% CI: 0.11–1.51), but the difference was not significant. Compared with standard-interval chemotherapy, dose-dense chemotherapy resulted in a superior 5-year DDFS (100% vs. 75.3%, P = 0.017) and 5-year EFS (96.9% vs. 78.3%, P = 0.022) in patients younger than 40 years. HER2-positive patients can achieve a higher LN pCR rate with dose-dense NAC than with standard-interval NAC with trastuzumab. Better survival may also be achieved with dose-dense chemotherapy with trastuzumab than with standard-interval chemotherapy with trastuzumab among young patients (age ≤ 40 years).

Ischemic stroke (IS) is a high-incidence disease that seriously threatens human life and health. Neuroinflammation and immune responses are key players in the pathophysiological processes of IS. However, the underlying immune mechanisms are not fully understood. In this study, we attempted to identify several immune biomarkers associated with IS. We first retrospectively collected validated human IS immune-related genes (IS-IRGs) as seed genes. Afterward, potential IS-IRGs were discovered by applying random walk with restart on the PPI network and the permutation test as a screening strategy. Doing so, the validated and potential sets of IS-IRGs were merged together as an IS-IRG catalog. Two microarray profiles were subsequently used to explore the expression patterns of the IS-IRG catalog, and only IS-IRGs that were differentially expressed between IS patients and controls in both profiles were retained for biomarker selection by the Random Forest rankings. CLEC4D and CD163 were finally identified as immune biomarkers of IS, and a classification model was constructed and verified based on the weights of two biomarkers obtained from the Neural Network algorithm. Furthermore, the CIBERSORT algorithm helped us determine the proportions of circulating immune cells. Correlation analyses between IS immune biomarkers and immune cell proportions demonstrated that CLEC4D was strongly correlated with the proportion of neutrophils (r = 0.72). These results may provide potential targets for further studies on immuno-neuroprotection therapies against reperfusion injury.

Background and PurposeMyasthenia gravis (MG) is a T cell-dependent antibody-mediated autoimmune disorder that can seriously affect patients' quality of life. However, few studies have focused on the severity of MG. Moreover, existing therapeutic efforts, including those targeting biomarkers for MG, remain unsatisfactory. Therefore, it is vital that we investigate the pathogenesis of MG and identify new biomarkers that can not only evaluate the severity of the disease but also serve as potential therapeutic targets. Long noncoding RNA LINC00680 has been found to be associated with the progression of a variety of diseases as a competing endogenous RNA (ceRNA). However, the specific role of LINC00680 in MG has yet to be clarified. Here, we aimed to investigate the association between LINC00680 and the severity of MG.MethodsBioinformatics tools, quantitative real-time PCR, Western blotting, and luciferase assays were selected to investigate key signaling pathways and RNA expression in patients with MG. The Quantitative MG Score scale and the MG Composite scale were used to evaluate the severity of MG in the included patients. Cell viability assays and flow cytometry analysis were selected to analyze cell proliferation and apoptosis.ResultsCompared with control subjects, the expression levels of LINC00680 and mitogen-activated protein kinase 1 (MAPK1) in peripheral blood mononuclear cells of patients with MG were both upregulated; the levels of miR-320a were downregulated. A positive correlation was detected between LINC00680 expression and the severity of MG. Luciferase reporter assays identified that LINC00680 acts as a target for miR-320a. The in vitro analysis confirmed that LINC00680 regulates the expression of MAPK1 by sponging miR-320a. Finally, the functional analysis indicated that LINC00680 promoted Jurkat cell proliferation and inhibited cellular apoptosis by sponging miR-320a.ConclusionLINC00680 may be associated with the severity of MG as a ceRNA by sponging miR-320a to upregulate MAPK1. These findings suggest that LINC00680 may represent a potential biomarker which evaluates the severity of MG and may serve as a therapeutic target.

Background Myasthenia gravis (MG) is an antibody-mediated autoimmune disease. In recent years, accumulating evidence has indicated that long non-coding RNAs (lncRNAs) can function as competing endogenous RNAs (ceRNAs), contributing to the progression of various autoimmune diseases. Nevertheless, the regulatory roles of ceRNAs in MG pathogenesis remain unclear. In this study, we aimed to elucidate the role of lncRNA OIP5-AS1 as a ceRNA associated with MG progression. Methods Real-time PCR was used to detect OIP5-AS1 levels in peripheral blood mononuclear cells (PBMCs) from patients with MG. Luciferase reporter assays were performed to validate the relationship between OIP5-AS1 and miR-181c-5p. CCK-8 and flow cytometry were performed to test the proliferation and apoptotic abilities of OIP5-AS1 in Jurkat cells. Furthermore, real-time PCR and Western blot assays were performed to explore the interactions between OIP5-AS1, miR-181c-5p, and IL-7. Results The expression of OIP5-AS1 was up-regulated in patients with MG. Luciferase reporter assay indicated that OIP5-AS1 targeted the miR-181c-5p. Functional assays showed that OIP5-AS1 suppressed Jurkat cell apoptosis and promoted cell proliferation by sponging miR-181c-5p. Mechanistically, knockdown of OIP5-AS1 inhibited IL-7 expression at both the mRNA and protein levels in Jurkat cells, whereas the miR-181c-5p inhibitor blocked the reduction of IL-7 expression induced by OIP5-AS1 suppression. Conclusions We confirmed that OIP5-AS1 serves as an endogenous sponge for miR-181c-5p to regulate the expression of IL-7. Our findings provide novel insights into MG processes and suggests potential therapeutic targets for patients with MG.

Background The association between the type of anesthesia used and the recurrence of cancer remains controversial. This study aimed to compare the effects of local vs general anesthesia on recurrence-free survival and cost after breast-conserving surgery. Materials and Methods We reviewed the data of 2778 patients who underwent breast-conserving surgery followed by radiation at our center between 1999 and 2014. We analyzed the data of 994 patients with hormone receptor-positive and Her2-negative tumors who underwent breast-conserving surgery without axillary lymph node dissection under local or general anesthesia. Patients were grouped according to whether local or general anesthesia was used for the surgery. Results Of the 994 patients enrolled in this study, 367 received local anesthesia and 627 patients received general anesthesia. The median follow-up duration for all patients was 93 months. The Kaplan–Meier survival curves did not reveal significant differences between the recurrence-free survival of the two groups, with 5-year recurrence-free survival rates of 96.3% (95% CI, 94.3–98.3%) in the local anesthesia group and 97.3% (95% CI, 95.9–98.7%) in the general anesthesia group. The total cost of hospitalization in the local anesthesia group was significantly lower than that in the general anesthesia group ( P

Light therapies can be used to treat fungal infections. A general mechanism is attributed to the generation of cytotoxic reactive oxygen species (ROS) due to light stimulation. The effectiveness of these therapies has been widely studied in the literature via conducting biological experiments, where fungi are exposed to light with various wavelengths and power. However, despite the large amount of work reporting the experimental results, few efforts have been given to build a mathematical model that describes the amount of generated ROS as a function of the photon energy and power of the stimulating light. The lack of such a model still hinders the optimization of the light doses. In this work, we propose a novel modeling method based on experimental data, so as to establish a mathematical relationship between the ROS concentration and the stimulating photon energy and light fluence (energy density). The anti-fungal experiments were performed on Candida albicans (C. albicans) using four LED light sources with different wavelengths ranging from 385nm to 450nm. Both the viability of the fungi and the ROS concentration therein were measured during the experiments. High fitting accuracy has been achieved by the model, which therefore demonstrates the effectiveness of the proposed modeling techniques.

MEC (Mobile Edge Computing) provides both IT service environment and cloud computation on the edge of the network. This technology not only minimizes the end-to-end latency but also increases the efficiency of computing. Some latency-sensitive applications, such as cloud video, online game, and augmented reality, take advantage of the MEC system to provide fast and stable services. Several new network techniques, including the implementation of NFV (Network Function Virtualization), the placement of VNF (Virtual Network Function) and the scheduling of SFC (Service Function Chain), should be considered to be applied in the MEC system. In this paper, we focus on the research about the scheduling of SFC in the NFV enabled MEC system and propose a solution accordingly. First, we make reasonable assumptions on the settings of MEC systems and model the SFC scheduling problem into a flexible job-shop scheduling problem. Since minimizing the latency can significantly improve the quality of service (QoS) and increase the revenue of Internet Service Providers, our optimization goal is to minimize the overall scheduling latency. To solve this optimization problem, a deep reinforcement learning based algorithm DQS is proposed. DQS can detect the variation of the MEC system's environment and perform adaptive scheduling for SFC requests. As the results of the simulation indicate, DQS works better than the other off-the-shelf algorithms in two key indexes: overall scheduling latency and average resource usage. Moreover, DQS can shorten the decision time and schedule SFCs stably with high performance. It is suitable to be extended to an online scheduling algorithm.

Background The status of axillary lymph nodes (ALNs) is one of the important factors in decision‐making for breast cancer treatment. Physical examination (PE) has long been the main, or even the only, means of clinical staging for ALNs in breast cancer. However, the sensitivity and accuracy of PE remains unsatisfactory. The results from this study suggest that axillary ultrasonography (US) should replace PE as a standard method for the clinical staging of ALNs in breast cancer. Methods Consecutive and nonselective breast cancer patients treated between September 2018 and November 2018 in our center were enrolled in the study. Comparisons of ALN results between PE/US and pathological results were conducted and the difference in sensitivity, specificity and accuracy between PE and US were tested by McNemar chi‐square test. Results A total of 123 patients were enrolled into the study. Their ages ranged from 28 to 76 years with a median age of 53 ± 10. There were 83 ALN positive cases and 40 ALN negative cases confirmed pathologically. The sensitivity, specificity, accuracy, positive predictive value and negative predictive value of PE and US were 54.2%, 90.0%, 65.9%, 91.8%, 48.7% versus 86.8%, 72.5%, 82.1%, 86.8%, 72.5%, respectively. The sensitivity and accuracy of US was significantly higher than that of PE (P = 0.004 and P = 0.002). Conclusion The results of this study demonstrated that US is superior in evaluating ALNs when compared with PE and that US should replace PE as the standard method for the clinical staging of ALNs in breast cancer.

Myasthenia gravis (MG) is an autoimmune disease associated with autoantibody production that leads to skeletal muscle weakness. The molecular mechanisms underlying MG are not fully understood. We analyzed the gene expression profile (GSE85452) and methylation profile (GSE85647) of MG samples from the GEO database to identify aberrantly methylated-differentially expressed genes. By integrating the datasets, we identified 143 hypermethylation-low expression genes and 91 hypomethylation-high expression genes. Then we constructed PPI network and ceRNA networks by these genes. Phosphatase and tensin homolog (PTEN) and Abelson tyrosine-protein kinase (ABL)1 were critical genes in both PPI networks and ceRNA networks. And potential MG associated lncRNAs were selected by comprehensive analysis of the critical genes and ceRNA networks. In the hypermethylation-low expression genes associated ceRNA network, sirtuin (SIRT)1 was the most important gene and the lncRNA HLA complex (HC) P5 had the highest connection degree. Meanwhile, PTEN was the most important gene and the lncRNA LINC00173 had the highest connection degree in the hypomethylation-high expression genes associated ceRNA network. LINC00173 was validated to be upregulated in MG patients by qRT-PCR (P = 0.005), which indicated LINC00173 might be a potential biomarker for MG. These results provide a basis for future studies on the molecular pathogenesis of MG.

Abstract Background Myasthenia gravis (MG) is an autoimmune diseases characterized by fatigue and weakness of skeletal muscles. B-lymphocyte-activating factor (BAFF), an essential factor for B cell differentiation and development, is important in the progression of MG. The current study aimed to investigate the association between single nucleotide polymorphism rs2893321 in BAFF with MG susceptibility in Chinese Han population. Methods One hundred forty-nine patients with MG and 148 healthy controls were recruited. Using improved multiple ligase detection reaction technology, the polymorphisms of rs2893321 between groups and among MG subgroups have been compared. Results A significant differences between the MG group and the healthy control group was observed. Additionally, rs2893321 was found to be associated with gender and age in patients with MG. Conclusion Genetic variations of rs2893321 in BAFF might be associated with susceptibility to MG in the Chinese Han population.

Abstract Knowledge of the pathology of axillary lymph nodes (ALN) in breast cancer patients is critical for determining their treatment. Ultrasound is the best noninvasive evaluation for the ALN status. However, the correlation between negative ultrasound results and the sentinel lymph nodes (SLN) pathology remains unknown. To test the hypothesis that negative ultrasound results of ALN predict the negative pathology results of SLN in breast cancer patients, we assessed the association between ALN ultrasonography‐negative results and the SLN pathology in 3115 patients with breast cancer recruited between October 2010 and April 2016 from a single cancer center, prospective database. Of these patients who met the inclusion criteria, 2317 (74.4%) had no SLN pathological metastasis. In the univariate analysis, other 798 patient with positive SLN tended to be under age 40 and premenopausal, having large tumor sizes (>2 cm), higher histological grade of primary tumor, positive hormone receptors, and negative HER‐2 status (P .05. In conclusion, only a 74.4% consistency between ALN ultrasonography‐negative results and negative pathological SLN results, although menstrual status, tumor size, histologic subtypes of primary tumor and ER status were found to be statistically independent predictors of positive SLN among patients negative for ALN ultrasonography. Therefore, the present study suggests that negative ultrasound results of ALN do not adequately predict the negative pathology results of SLN in breast cancer patients.

Abstract Background RECQL is a number of the RecQ DNA helicase family and plays an important role in maintaining genome stability. Although several studies have reported that RECQL mutations were correlated with the susceptibility to breast cancer, the effect on prognosis in breast cancer was not yet clarified. Here, we explored the association between RECQL expression level and survival in patients with breast cancer. Methods In the first cohort, the RECQL mRNA expression level was evaluated in 774 primary breast cancer patients using a quantitative real-time PCR assay. Then, in the second independent cohort, the level of RECQL protein expression was detected in 322 patients with breast cancer using immunohistochemistry assay. Survival curves of patients with RECQL expression were compared using the Kaplan-Meier method with log-rank test. Results In the first cohort of 774 breast cancer patients, the low expression level of RECQL mRNA was significantly correlated with aggressive clinicopathological characteristics, including the positive lymph node status (P = 0.026), HER2 overexpression (P

Dead time between the complementary driving signals is needed to avoid short circuit in voltage source inverters (VSIs), however, this raises issues such as voltage distortion and harmonic generation. In wireless power transfer (WPT) systems, the ratio of dead time versus operating period becomes more problematic due to the high frequency, where the dead time can cause serious concerns regarding the phase errors and control performance deterioration. Therefore, this paper presents a comprehensive analysis of the dead-time effect for WPT systems based on a series–series (SS) topology. Firstly, it is found that voltage distortion appears in two regions in comparison with the three in one active bridge WPT system, and seven regions, as compared to the eight in dual active bridge (DAB) WPT system. Afterwards, a novel pulse width modulation (PWM) method is proposed, where the driving signals of the same phase leg are no longer complementary to each other. By employing the proposed method, the dead-time effect can be addressed up to a certain extent, and the desired voltage can be obtained in all the regions. In addition, the proposed method is not influenced by the system parameters, and can be easily applied to other high-frequency resonant converters. Simulated and experimental results are added to verify the feasibility and efficacy of the proposed control scheme.

The genetic cause for approximately 80% of familial breast cancer patients is unknown. Here, by sequencing the entire exomes of nine early-onset familial breast cancer patients without BRCA1/2 mutations (diagnosed with breast cancer at or before the age of 35) we found that two index cases carried a potentially deleterious mutation in the RECQL gene (RecQ helicase-like; chr12p12). Recent studies suggested that RECQL is involved in DNA double-strand break repair and it plays an important role in the maintenance of genomic stability. Therefore, we further screened the RECQL gene in an additional 439 unrelated familial breast cancer patients. In total, we found three nonsense mutations leading to a truncated protein of RECQL (p.L128X, p.W172X, and p.Q266X), one mutation affecting mRNA splicing (c.395-2A>G), and five missense mutations disrupting the helicase activity of RECQL (p.A195S, p.R215Q, p.R455C, p.M458K, and p.T562I), as evaluated through an in vitro helicase assay. Taken together, 9 out of 448 BRCA-negative familial breast cancer patients carried a pathogenic mutation of the RECQL gene compared with one of the 1,588 controls (P = 9.14×10-6). Our findings suggest that RECQL is a potential breast cancer susceptibility gene and that mutations in this gene contribute to familial breast cancer development.

Nowadays, work on Wireless Power Transfer (WPT) systems with dual active bridges is attracting great attention due to their low conduction losses, power regulation, load transformation and reactance compensation. However, in these studies limitations such as overall analysis, design and realization techniques of the system were not considered properly. To address the aforementioned issues, this paper presents a detailed analysis, design and realization of a Series-Series (SS) WPT system with dual active bridges, which will improve the overall performance. Three independent Phase Angles (PAs) have been analyzed and designed in this study, one PA on the primary side and the other two PAs on the secondary side. This Multiple Degrees of Phase Control (MDPC) method can achieve additional reactance compensation, load transformation and output regulation simultaneously. To realize the proposed method in practice, key implementation techniques have been investigated in detail, including additional reactance estimation, mutual inductance estimation, phase detection and synchronization. The feasibility and effectiveness of the proposed system is verified through simulation and experimental results.