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Abstract The novel diagnostic term Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) requires at least one cardiovascular risk factor for diagnosis. While the relationship between gallstones and Non-Alcoholic Fatty Liver Disease (NAFLD) has been debated, the association between MASLD and gallstones remains unclear. This cross-sectional study aimed to explore this relationship using National Health and Nutrition Examination Survey (NHANES) data from 2017 to 2020. Participants were stratified into two groups based on MASLD diagnosis, and propensity score matching (PSM) was employed to reduce biases. Of 15,560 participants, 7922 met the inclusion criteria, with 2697 (34.0%) diagnosed with MASLD. Gallstone prevalence was higher in the MASLD group (14.2%) compared to the non-MASLD group (8.5%). After PSM, 4536 participants were analyzed, revealing a significant association between MASLD and gallstones (OR = 1.30, 95% CI 1.09–1.56, P = 0.003). This association remained robust across crude and adjusted analyses, with subgroup and sensitivity analyses further supporting the findings. In conclusion, MASLD is significantly associated with an increased risk of gallstones in the US population. These findings highlight the need to consider this relationship in clinical strategies for prevention and management of gallstone disease.

Abstract Objective Although Mammotome-assisted minimally invasive resection (MAMIR) has been widely accepted for treating breast benign nodules, the procedure remains very technical and challenging. The present study aimed to assess the efficacy of norepinephrine application in MAMIR concerning intraoperative hemorrhage, postoperative pain and postoperative hospitalization. Methods A total of 306 patients with breast nodules admitted at the Xishan people’s Hospital of Wuxi City between June 2021 and July 2023 were included in this retrospective cohort study. The patient’s age, comorbidities (hypertension and diabetes), and characteristics of the breast nodule (number, unilateral or bilateral nature, inner quadrant volume and total volume) were all meticulously documented. Operation time, intraoperative hemorrhage, postoperative hospitalization and Visual analogue scale(VAS) score (postoperative 6-hour pain score) were recorded. Based on the application of norepinephrine, patients were categorized into non-NPP(norepinephrine) and NPP group. Univariate and multivariate analyses were performed to estimate the odds ratio (OR) and the 95% confidence intervals (CIs) for outcomes. Results A total of 155 who accepted MAMIR were included in this study. The NPP group exhibited reduced intraoperative bleeding, diminished postoperative pain, and a shorter duration of hospitalization (p

Abstract Background Postoperative recurrence is a vital reason for poor 5-year overall survival in hepatocellular carcinoma (HCC) patients. The ADV score is considered a parameter that can quantify HCC aggressiveness. This study aimed to identify HCC patients at high-risk of recurrence early using the ADV score. Methods The medical data of consecutive HCC patients undergoing hepatectomy from The First Affiliated Hospital of Nanjing Medical University (TFAHNJMU) and Nanjing Drum Tower Hospital (NJDTH) were retrospectively reviewed. Based on the status of microvascular invasion and the Edmondson-Steiner grade, HCC patients were divided into three groups: low-risk group (group 1: no risk factor exists), medium-risk group (group 2: one risk factor exists), and high-risk group (group 3: coexistence of two risk factors). In the training cohort (TFAHNJMU), the R package nnet was used to establish a multi-categorical unordered logistic regression model based on the ADV score to predict three risk groups. The Welch’s T-test was used to compare differences in clinical variables in three predicted risk groups. NJDTH served as an external validation center. At last, the confusion matrix was developed using the R package caret to evaluate the diagnostic performance of the model. Results 350 and 405 patients from TFAHNJMU and NJDTH were included. HCC patients in different risk groups had significantly different liver function and inflammation levels. Density maps demonstrated that the ADV score could best differentiate between the three risk groups. The probability curve was plotted according to the predicted results of the multi-categorical unordered logistic regression model, and the best cut-off values of the ADV score were as follows: low-risk ≤ 3.4 log, 3.4 log 5.7 log. The sensitivities of the ADV score predicting the high-risk group (group 3) were 70.2% (99/141) and 78.8% (63/80) in the training and external validation cohort, respectively. Conclusion The ADV score might become a valuable marker for screening patients at high-risk of HCC recurrence with a cut-off value of 5.7 log, which might help surgeons, pathologists, and HCC patients make appropriate clinical decisions.

Abstract Objective The ultrasonographic characteristics of lymph node metastasis in breast cancer patients were retrospectively analyzed, and a predictive nomogram model was constructed to provide an imaging basis for better clinical evaluation. Methods B-mode ultrasound was used to retrospectively analyze the imaging characteristics of regional lymph nodes and tumors. Pathological examination confirmed the presence of lymph node metastasis in breast cancer patients. Univariable and multivariable logistic regression analyses were performed to analyze the risk factors for lymph node metastasis. LASSO regression analysis was performed to screen noninvasive indicators, and a nomogram prediction model was constructed for breast cancer patients with lymph node metastasis. Results A total of 187 breast cancer patients were enrolled, including 74 patients with lymph node metastasis in the positive group and 113 patients without lymph node metastasis in the negative group. Multivariate analysis revealed that pathological type (OR = 4.58, 95% CI: 1.44–14.6, p = 0.01), tumor diameter (OR = 1.37, 95% CI: 1.07–1.74, p = 0.012), spiculated margins (OR = 7.92, 95% CI: 3.03–20.67, p

BackgroundT lymphocytes, integral to the adaptive immune system, wield pivotal influence in bolstering anti-tumor responses, and are strictly regulated by ubiquitination modification. The objective of this investigation was to devise a novel prognostic and immunotherapeutic efficacy predictor for hepatocellular carcinoma patients utilizing T cell-related ubiquitination genes (TCRUG).MethodThe single-cell RNA sequencing (scRNA-seq) data and bulk RNA data of HCC patients are derived from the GEO database and TCGA database. Based on the processing of scRNA-seq, T cell marker genes are obtained and TCRUG is obtained. Further combined with WGCNA, differential analysis, univariate Cox regression analysis, LASSO analysis, and multivariate Cox regression analysis to filter and screen TCRUG. Finally construct a riskscore for predicting the prognosis of HCC patients, the predictive effect of which is validated in the GEO dataset. In addition, we also studied the correlation between riskscore and immunotherapy efficacy. Finally, the oncogenic role of UBE2E1 in HCC was explored through various in vitro experiments.ResultBased on patients’ scRNA-seq data, we finally obtained 3050 T cell marker genes. Combined with bulk RNA data and clinical data from the TCGA database, we constructed a riskscore that accurately predicts the prognosis of HCC patients. This riskscore is an independent prognostic factor for HCC and is used to construct a convenient column chart. In addition, we found that the high-risk group is more suitable for immunotherapy. Finally, the proliferation, migration, and invasion abilities of HCC cells significantly decreased after UBE2E1 expression reduction.ConclusionThis study developed a riskscore based on TCRUG that can accurately and stably predict the prognosis of HCC patients. This riskscore is also effective in predicting the immune therapy response of HCC patients.

During performing multiple tasks of a redundant manipulator, the obstacles affect the sequential order of task areas and the joint trajectories. The end-effector is constrained to visit multiple task areas with an optimal anti-collision path, while the joints are required to move smoothly and avoid predefined obstacles. A special encoding genetic algorithm (SEGA) is proposed for multitask-based anti-collision trajectory planning. Firstly, the spatial occupancy relationship between obstacles and manipulator is developed utilizing the theory of spherical enclosing box and spatial superposition. The obstacles are detected according to the relative position relationship between linear segments and spheres. Secondly, each joint trajectory between adjacent task areas is depicted with a sixth-degree polynomial. Additionally, each joint trajectory is improved via optimizing the unknown six-order coefficient. By searching for optimal sequential order of task areas, optimal collision detection results, and optimal joint trajectories, the multitask-based anti-collision trajectory planning problem is transformed into a parameter optimization problem. In SEGA, the cost function consists of two parts, including the end-effector path length and the variation of joint angles. Moreover, each chromosome consists of three categories of genes, including the sequential order of task areas, the sequential order of joint configurations corresponding to task areas, and the unknown coefficients for anti-collision joint trajectories. Finally, numerical simulations are carried out to verify the proposed method.

Abstract Because of uncertain random noise and unknown disturbance, the observer‐based inverter fault diagnosis meets the problems of large deviation of current observation value and high false alarm rate. An inverter open‐circuit fault diagnosis method is proposed via residual performance evaluation. Firstly, the interval sliding mode observer is constructed by combining the interval observer with the sliding mode observer. Three phase current estimates are obtained and current residuals are calculated. Secondly, the residual performance indicators are calculated using the evaluation function. The fault detection is derived by comparing residual performance with the threshold. Thirdly, a residual information table is established based on the fault information contained in the residual for fault isolation. Finally, the proposed algorithm is validated on simulation and physical platforms. Compared with traditional observer‐based diagnostic methods, the introduction of residual performance evaluation improves the diagnostic speed by more than 50%. The interval sliding mode observer has higher estimation accuracy and anti‐interference ability in the presence of noise and external disturbances.

Hepatocellular carcinoma (HCC) is the most common pathologic type of primary liver cancer. Liver transplantation (LT) is a radical strategy for treating patients with early-stage HCC, which may lead to a better prognosis compared to hepatectomy and ablation. However, survival of patients who develop HCC recurrence after LT is short, and early recurrence is the most common cause of death. Thus, efficient biomarkers are also needed in LT to guide precision therapy to improve patient prognosis and 5-year survival. Protein induced by vitamin K absence or antagonist II (PIVKA-II) is an abnormal prothrombin that cannot activate coagulation, and it is significantly increased in patients with HCC, obstructive jaundice, and those taking vitamin K antagonists. Over the past decades, substantial progress has been made in the study of PIVKA-II in diagnosing, surveilling, and treating HCC, but its role in LT still needs to be elaborated. In this review, we focused on the role of PIVKA-II as a biomarker in LT for HCC, especially its relationship with clinicopathologic features, early recurrence, long-term survival, and donor-recipient selection.

Abstract Progressive hepatic damage and fibrosis are major features of chronic liver diseases of different etiology, yet the underlying molecular mechanisms remain to be fully defined. N-RAS, a member of the RAS family of small guanine nucleotide-binding proteins also encompassing the highly homologous H-RAS and K-RAS isoforms, was previously reported to modulate cell death and renal fibrosis; however, its role in liver damage and fibrogenesis remains unknown. Here, we approached this question by using N-RAS deficient (N-RAS−/−) mice and two experimental models of liver injury and fibrosis, namely carbon tetrachloride (CCl4) intoxication and bile duct ligation (BDL). In wild-type (N-RAS+/+) mice both hepatotoxic procedures augmented N-RAS expression in the liver. Compared to N-RAS+/+ counterparts, N-RAS−/− mice subjected to either CCl4 or BDL showed exacerbated liver injury and fibrosis, which was associated with enhanced hepatic stellate cell (HSC) activation and leukocyte infiltration in the damaged liver. At the molecular level, after CCl4 or BDL, N-RAS−/− livers exhibited augmented expression of necroptotic death markers along with JNK1/2 hyperactivation. In line with this, N-RAS ablation in a human hepatocytic cell line resulted in enhanced activation of JNK and necroptosis mediators in response to cell death stimuli. Of note, loss of hepatic N-RAS expression was characteristic of chronic liver disease patients with fibrosis. Collectively, our study unveils a novel role for N-RAS as a negative controller of the progression of liver injury and fibrogenesis, by critically downregulating signaling pathways leading to hepatocyte necroptosis. Furthermore, it suggests that N-RAS may be of potential clinical value as prognostic biomarker of progressive fibrotic liver damage, or as a novel therapeutic target for the treatment of chronic liver disease.

The accuracy of relative pose estimation is an important foundation for ensuring the safety and stability of autonomous aerial refueling (AAR) of unmanned aerial vehicles (UAV), and in response to this problem, a relative pose estimation method of UAVs based on the spatial equivalent plane is proposed in this paper. The UAV is equivalent to a spatial polygonal plane, and according to the measurement information of the Global Navigation Satellite System (GNSS) receivers, the equivalent polygonal plane equation is solved through the three-point normal vector and the minimum sum of squares of the distance from the four points to the plane. The equations of the distance between the geometric centers of the two polygonal planes, the angle between planes, and the angle between lines are used to calculate the relative pose information of the UAVs. Finally, the simulation environment and initial parameters are utilized for numerical simulation and results analysis. The simulation results show that without considering the motion model of the UAV, the proposed method can accurately estimate the relative pose information of the UAVs. In addition, in the presence of measurement errors, the relative pose estimation method based on the equivalent triangle plane can identify the position of the measurement point with the error, and the relative pose estimation method based on the equivalent quadrilateral plane has good robustness. The simulation results verify the feasibility and effectiveness of the proposed method.

This study proposes a wind farm active power dispatching (WFAPD) algorithm based on the grey incidence method, which does not rely on an accurate mathematical model of wind turbines. Based on the wind turbine start-stop data at different wind speeds, the weighting coefficients, which are the participation degrees of a variable speed system and a variable pitch system in power regulation, are obtained using the grey incidence method. The incidence coefficient curve is fitted by the B-spline function at a full range of wind speeds, and the power regulation capacity of all wind turbines is obtained. Finally, the WFAPD algorithm, which is based on the regulating capacity of each wind turbine, is compared with the wind speed weighting power dispatching (WSWPD) algorithm in MATLAB. The simulation results show that the active power fluctuation of the wind farm is smaller, the rotating speed of wind turbines is smoother, and the fatigue load of high- speed turbines is effectively reduced.

Abstract Background Perioperative bleeding and allogeneic blood transfusion are generally thought to affect the outcomes of patients. This meta-analysis aimed to determine the benefits and risks of several cardiovascular interventions in patients undergoing hepatectomy. Methods In this systematic review and meta-analysis, randomised controlled trials (RCTs) were searched in the Cochrane Library, Medline, Embase, and Web of Science to February 02, 2023. RCTs focused on cardiovascular interventions aimed at reducing blood loss or blood transfusion requirements during hepatectomy were included. The primary outcomes were perioperative blood loss amount, number of patients requiring allogeneic blood transfusion and overall occurrence of postoperative complications. The secondary outcomes were operating time, perioperative mortality rate, postoperative liver and kidney function and length of hospital stay. Results Seventeen RCTs were included in the analysis. A total of 841 patients who underwent hepatectomy in 10 trials were included in the comparative analysis between low central venous pressure (CVP) and control groups. The forest plots showed a low operative bleeding volume [(mean difference (MD): -409.75 mL, 95% confidence intervals (CI) -616.56 to -202.94, P

Abstract Background Although laparoscopic pancreaticoduodenectomy (LPD) has been accepted worldwide for treating pancreatic ductal adenocarcinoma (PDA), it is a very technical and challenging procedure. Also, it is unclear whether LPD is superior to open pancreaticoduodenectomy (OPD). This study summarized the experience and efficacy of LPD for treating PDA in our medical center. Methods This retrospective cohort study included patients with PDA admitted at the Affiliated Hospital of Jiangnan University from October 2019 and January 2021. Patients received either LPD or OPD. Clinical outcomes (operation time, duration of anesthesia, intraoperative hemorrhage), postoperative complications, and short-term outcomes were compared. Cox proportional hazard model and Kaplan-Meier method were used to analyze overall survival (OS) and progression-free survival (PFS). Results Among the PDA patients, 101 patients underwent surgical treatment, 4 patients converted from LPD to OPD, and 7 of them received conservative treatment. Forty-six patients were cured of LPD, and 1 of them died shortly after the operation. Moreover, 44 patients received OPD, and there were 2 postoperative deaths. There were significant differences in the location of the operation time, duration of anesthesia, postoperative hemorrhage, abdominal infections, and postoperative pneumonia between the two groups (all p < 0.05). Multivariate analysis showed that LPD was an independent factor negatively correlated with the incidence of pneumonia (relative risk (RR) = 0.072, 95%CI: 0.016–0.326, p = 0.001) and abdominal infection (RR = 0.182, 95%CI: 0.047–0.709, p = 0.014). Also, there were no differences in OS (hazard ratio (HR) = 1.46, 95%CI: 0.60–3.53, p = 0.40) and PFS (HR = 1.46, 95%CI: 0.64–3.32, p = 0.37) at 12 months between the two groups. Conclusions LPD could be efficacy and feasible for managing selected PDA patients. Also, LPD has a better effect in reducing postoperative pneumonia and abdominal infection compared to OPD.

This paper proposes a method for retired batteries based on SOC consistency matching. This method takes the SOC consistency of the battery pack as the standard, which calculates the model parameter matching relationship to optimize the performance of the pack. Based on Thevenin equivalent circuit model, the mathematical model of lithium ion battery is established and the model is parameterized. Additionally, a battery pack reconfiguration criterion based on SOC consistency is proposed to reveal the mapping relationship between cell parameters and battery pack SOC consistency. Finally, the battery parameters are identified by the recursive least squares (RLS) algorithm to select two groups of batteries. Dynamic and constant current tests are performed on battery packs with different topologies, which are used to verify the feasibility of the proposed method. The experimental results show that the proposed reorganization scheme can better ensure the consistency of the SOC of the battery pack during charging and discharging.

Background The severity of liver cirrhosis in hepatocellular carcinoma (HCC) patients is essential for determining the scope of surgical resection. It also affects the long-term efficacy of systemic anti-tumor therapy and transcatheter arterial chemoembolization (TACE). Non-invasive tools, including aspartate aminotransferase to platelet ratio index (APRI), fibrosis-4 (FIB-4), and γ-glutamyl transferase to platelet ratio (GPR), are less accurate in predicting cirrhosis in HCC patients. We aimed to build a novel decision tree model to improve diagnostic accuracy of liver cirrhosis. Patients and Methods The Mann-Whitney U test, χ2 test, and multivariate logistic regression analysis were used to identify independent cirrhosis predictors. A decision tree model was developed using machine learning algorithms in a training cohort of 141 HCC patients. Internal validation was conducted in 99 HCC patients. The diagnostic accuracy and calibration of the established model were evaluated using receiver operating characteristic (ROC) and calibration curves, respectively. Results Sex and platelet count were identified as independent cirrhosis predictors. A decision tree model integrating imaging-reported cirrhosis, APRI, FIB-4, and GPR was established. The novel model had an excellent diagnostic performance in the training and validation cohorts, with area under the curve (AUC) values of 0.853 and 0.817, respectively. Calibration curves and the Hosmer-Lemeshow test showed good calibration of the novel model. The decision curve analysis (DCA) indicated that the decision tree model could provide a larger net benefit to predict liver cirrhosis. Conclusion Our developed decision tree model could successfully predict liver cirrhosis in HCC patients, which may be helpful in clinical decision-making.

Key Clinical Message For potentially resectable HCC, a more aggressive conversion therapy strategy (high‐intensity combined with multiple treatment modalities) can be used. Abstract Hepatocellular carcinoma (HCC) is the sixth most common malignancy worldwide. The best treatment for HCC is radical surgical resection, but 70%–80% of patients are ineligible for surgery. Although conversion therapy is an established treatment strategy for various solid tumors, there is no uniform protocol for treating HCC. In this case, we present a 69‐year‐old male patient diagnosed with massive HCC with Barcelona clinical liver cancer (BCLC) stage B. Because of the insufficient volume of the future liver remnant, we believed radical surgical resection was temporarily impossible. Therefore, the patient received conversion therapy, including four cycles of transcatheter arterial embolization (TAE) and hepatic arterial infusion chemotherapy (HAIC‐Folfox), lenvatinib (8 mg orally once a day), and tislelizumab (an anti‐PD‐1 antibody, 200 mg intravenously once every 3 weeks). Fortunately, the patient achieved a good treatment response (smaller lesions and improved liver function) and underwent radical surgery finally. There was no clinical evidence of recurrence at 6 months of follow‐up. For potentially resectable HCC, this case reveals that a more aggressive conversion therapy strategy (high‐intensity combined with multiple treatment modalities) can be used.

Key Clinical Message In conclusion author highlights the tumor cell genetic testing or molecular pathological diagnosis plays a key role in the individualized treatment of PSC, which could benefit patients with advanced PSC. Abstract An uncommon form of non‐small‐cell lung cancer (NSCLC) with a poor prognosis is pulmonary sarcomatoid carcinoma (PSC). Surgical resection is currently the preferred treatment, but guidelines for adjuvant chemotherapy have not yet been established, especially for the advanced stage. The development of molecular subgroups in the field of tumors may be advantageous to advanced PSC patients with the ongoing progress of genomics and immunology. A 54‐year‐old man presented to Xishan People's Hospital of Wuxi City with recurrent intermittent dry cough with fever for 1 month. Further examinations suggested the diagnosis of PSC occupying almost the entire right interlobar fissure area combined with malignant pleural effusion (Stage IVa). Pathological examination confirmed the diagnosis of PSC with ROS1 overexpressing via genetic testing. However, after three cycles of chemo‐, antiangiogenetic‐ and immunochemical therapy, the lesion was localized, and pleural effusion disappeared, the patient subsequently received an operation which was performed as R0 resection. Unfortunately, the patient became deteriorated quickly followed by extensive metastatic nodules in the thoracic cavity. Although the patient continued to receive chemo‐ and immunochemical‐therapy, it did not limit the progress of the tumor, leading to widespread metastasis, and eventually died of multiple organ failure. For PSC patients with Stage IVa, chemo‐, antiangiogenetic‐ and immunochemical‐therapy performs well in clinical efficacy, and comprehensive panel‐based genetic testing may offer PSC patients a somewhat better prognosis. However, blindly implementing surgical treatment may bring harm to the patient and affect long‐term survival. It's essential to know the surgical indications precisely by NSCLC guidelines.

Abstract Objectives Although laparoscopic inguinal hernia repair (LIHR) has been widely accepted for treating inguinal hernia, the procedure remains very technical and challenging. The present study aimed to assess the effect of LIHR in relation to operation time, intraoperative hemorrhage and postoperative hospitalization. Methods A total of 503 patients with inguinal hernia admitted at the Wuxi Rehabilitation Hospital between June 2019 and July 2021 were included in this retrospective cohort study. Binary logistic and linear regressions were used for categorical and continuous outcomes, respectively. The learning curve was drawn by cumulative sum analysis. Results Multivariate logistic regression analysis identified LIHR as an independent factor associated with prolonging operation time (odd ratio [OR] = 1.750, 95% confidence interval [CI]: 1.215−2.520, p = 0.003) and decreasing intraoperative hemorrhage levels (OR = 0.079, 95 CI: 0.044−0.142, p

Abstract Acetaminophen (APAP) hepatotoxicity induces endoplasmic reticulum (ER) stress which triggers the unfolded protein response (UPR) in hepatocytes. However, the mechanisms underlying ER stress remain poorly understood, thus reducing the options for exploring new pharmacological therapies for patients with hyperacute liver injury. Eight-to-twelve-week-old C57BL/6J Xbp1-floxed (Xbp1 f/f ) and hepatocyte-specific knockout Xbp1 mice (Xbp1 ∆hepa ) were challenged with either high dose APAP [500 mg/kg] and sacrificed at early (1–2 h) and late (24 h) stages of hepatotoxicity. Histopathological examination of livers, immunofluorescence and immunohistochemistry, Western blot, real time (RT)-qPCR studies and transmission electron microscopy (TEM) were performed. Pharmacological inhibition of XBP1 using pre-treatment with STF-083010 [STF, 75 mg/kg] and autophagy induction with Rapamycin [RAPA, 8 mg/kg] or blockade with Chloroquine [CQ, 60 mg/kg] was also undertaken in vivo. Cytoplasmic expression of XBP1 coincided with severity of human and murine hyperacute liver injury. Transcriptional and translational activation of the UPR and sustained activation of JNK1/2 were major events in APAP hepatotoxicity, both in a human hepatocytic cell line and in a preclinical model. Xbp1 ∆hepa livers showed decreased UPR and JNK1/2 activation but enhanced autophagy in response to high dose APAP. Additionally, blockade of XBP1 splicing by STF, mitigated APAP-induced liver injury and without non-specific off-target effects (e.g., CYP2E1 activity). Furthermore, enhanced autophagy might be responsible for modulating CYP2E1 activity in Xbp1 ∆hepa animals. Genetic and pharmacological inhibition of Xbp1 specifically in hepatocytes ameliorated APAP-induced liver injury by enhancing autophagy and decreasing CYP2E1 expression. These findings provide the basis for the therapeutic restoration of ER stress and/or induction of autophagy in patients with hyperacute liver injury.

Metabolic conditions associated with alterations of the gut microbiome, such as obesity and diabetes, predispose to gallstone disease. Here the authors demonstrate that the gut microbiome, in particular the genus Desulfovibrionale, contribute to gallstone formation in mice.

Both torque ripple and current harmonics are enlarged due to single-phase open-circuit fault of five-phase permanent magnet synchronous motor (FPMSM). Based on chaotic-particle swarm, an adaptive optimization fault tolerant control algorithm is proposed for the FPMSM current. First, Park and Clarke matrices are modified in coordinate transformation process. A reduced-order decoupling matrix is obtained under the open-circuit fault of FPMSM stator winding. Second, the fault-tolerant current is generated with the principle of constant magnetomotive force. Third, the current is adaptively optimized using chaotic-particle swarm algorithm. Hence, motor torque and motor current keep uniform steady state and dynamic performance with them in regular operation. Finally, numerical simulations are carried out to verify the effectiveness of the developed method.

Deep learning (DL) is a hot topic in the machine vision. A large number of data sets are necessary for efficient image recognition. Otherwise the overfitting will easily occur. However, most actual samples are limited and unbalanced. To diminish the negative impact of small unbalanced samples on image recognition, the Deep Convolutional Generative Adversarial Network (DC-GAN) was improved to simulate data distribution, and relied on the improved network to generate a highly diverse dataset of balanced fire images in the work. Then, the number of output layer nodes was finetuned for the training of the target dataset by the layer freezing method. The training of small unbalanced samples was realized, using exponentially decaying learning rate, L2 regularization method, and Adam optimization algorithm. Simulation results showed that the proposed algorithm converged faster by fixing the convolutional layer parameters of the pre-trained model and finetuning the fully connected layer through transfer learning. Besides, 99% of fire images were correctly recognized, without inducing the problem of small sample overfitting. The proposed algorithm provides a desirable tool for outdoor fire recognition.

Individuals exhibiting an intermediate alcohol drinking pattern in conjunction with signs of metabolic risk present clinical features of both alcohol‐associated and metabolic‐associated fatty liver diseases. However, such combination remains an unexplored area of great interest, given the increasing number of patients affected. In the present study, we aimed to develop a preclinical DUAL (alcohol‐associated liver disease plus metabolic‐associated fatty liver disease) model in mice. C57BL/6 mice received 10% vol/vol alcohol in sweetened drinking water in combination with a Western diet for 10, 23, and 52 weeks (DUAL model). Animals fed with DUAL diet elicited a significant increase in body mass index accompanied by a pronounced hypertrophy of adipocytes, hypercholesterolemia, and hyperglycemia. Significant liver damage was characterized by elevated plasma alanine aminotransferase and lactate dehydrogenase levels, extensive hepatomegaly, hepatocyte enlargement, ballooning, steatosis, hepatic cell death, and compensatory proliferation. Notably, DUAL animals developed lobular inflammation and advanced hepatic fibrosis. Sequentially, bridging cirrhotic changes were frequently observed after 12 months. Bulk RNA‐sequencing analysis indicated that dysregulated molecular pathways in DUAL mice were similar to those of patients with steatohepatitis. Conclusion: Our DUAL model is characterized by obesity, glucose intolerance, liver damage, prominent steatohepatitis and fibrosis, as well as inflammation and fibrosis in white adipose tissue. Altogether, the DUAL model mimics all histological, metabolic, and transcriptomic gene signatures of human advanced steatohepatitis, and therefore serves as a preclinical tool for the development of therapeutic targets.

A novel optimal control problem is considered for multiple input multiple output (MIMO) stochastic systems with mixed parameter drift, external disturbance and observation noise. The proposed controller can not only track and identify the drift parameters in finite time but, furthermore, drive the system to move towards the desired trajectory. However, there is a conflict between control and estimation, which makes the analytic solution unattainable in most situations. A dual control algorithm based on weight factor and innovation is, therefore, proposed. First, the innovation is added to the control goal by the appropriate weight and the Kalman filter is introduced to estimate and track the transformed drift parameters. The weight factor is used to adjust the degree of drift parameter estimation in order to achieve a balance between control and estimation. Then, the optimal control is derived by solving the modified optimization problem. In this strategy, the analytic solution of the control law can be obtained. The control law obtained in this paper is optimal because the estimation of drift parameters is integrated into the objective function rather than the suboptimal control law, which includes two parts of control and estimation in other studies. The proposed algorithm can achieve the best compromise between optimization and estatimation. Finally, the effectiveness of the algorithm is verified by numerical experiments in two different cases.

The multispectral information, including both visible information and infrared information, can describe the detection target in a comprehensive manner. The deep learning (DL)-based detectors that fuse the multispectral features can detect pedestrians robustly in various environments. Therefore, this paper puts forward a robust multispectral feature fusion network (MSFFN) for pedestrian detection, which fully integrates the features extracted from visible light and infrared channels. Specifically, multiscale semantic features were extracted by two core modules, namely, multiscale feature extraction of visible images (MFEV) and multiscale feature extraction of infrared images (MFEI), and fused by the improved YOLOv3 network for pedestrian recognition. Through experiments on the KAIST dataset, it is proved that the MSFFN model can detect pedestrians more accurately than both MFEV and MFEI over daytime and nighttime images on multiple scales. The experimental results on the KAIST multispectral data set in the last section showed that our proposed MFMFN model was superior to a number of state-of-the-art multispectral pedestrian detectors methods in accuracy and speed. The model was also found to strike a good balance between accuracy and speed, and perform excellently on small input images. The research results shed important new light on the design of self-driving vehicles.

Abstract Background The treatment of hepatic injury can be complex. Medical clinical centers are often the first line hospitals for the diagnosis and treatment of hepatic trauma in China. The aim of the study is to summarize the experience in the diagnosis and treatment of hepatic trauma in one medical clinical center in China. Methods This retrospective study included patients with hepatic trauma admitted between January 2002 and December 2019 at the Xishan People’s Hospital of Wuxi. The outcomes were cure rate and death within 14 days post-discharge. Results Among the 318 patients with hepatic trauma, 146 patients underwent surgical treatment, and 172 received conservative treatment; three patients were transferred to other hospitals for further treatment; 283 patients were cured, and 35 died. Severe hepatic trauma occurred in 74 patients, with a mortality rate of 31.1% and accounting for 65.7% of total mortality. American Association for the Surgery of Trauma (AAST) grading ≥ III (OR = 3.51, 95%CI: 1.32–9.37, P = 0.012) and multiple organ injury (OR = 7.51, 95%CI: 2.51–22.46, P

Targeted inhibition of the c‐Jun N‐terminal kinases (JNKs) has shown therapeutic potential in intrahepatic cholangiocarcinoma (CCA)‐related tumorigenesis. However, the cell‐type‐specific role and mechanisms triggered by JNK in liver parenchymal cells during CCA remain largely unknown. Here, we aimed to investigate the relevance of JNK1 and JNK2 function in hepatocytes in two different models of experimental carcinogenesis, the dethylnitrosamine (DEN) model and in nuclear factor kappa B essential modulator (NEMO)hepatocyte‐specific knockout (Δhepa) mice, focusing on liver damage, cell death, compensatory proliferation, fibrogenesis, and tumor development. Moreover, regulation of essential genes was assessed by reverse transcription polymerase chain reaction, immunoblottings, and immunostainings. Additionally, specific Jnk2 inhibition in hepatocytes of NEMOΔhepa/JNK1Δhepa mice was performed using small interfering (si) RNA (siJnk2) nanodelivery. Finally, active signaling pathways were blocked using specific inhibitors. Compound deletion of Jnk1 and Jnk2 in hepatocytes diminished hepatocellular carcinoma (HCC) in both the DEN model and in NEMOΔhepa mice but in contrast caused massive proliferation of the biliary ducts. Indeed, Jnk1/2 deficiency in hepatocytes of NEMOΔhepa (NEMOΔhepa/JNKΔhepa) animals caused elevated fibrosis, increased apoptosis, increased compensatory proliferation, and elevated inflammatory cytokines expression but reduced HCC. Furthermore, siJnk2 treatment in NEMOΔhepa/JNK1Δhepa mice recapitulated the phenotype of NEMOΔhepa/JNKΔhepa mice. Next, we sought to investigate the impact of molecular pathways in response to compound JNK deficiency in NEMOΔhepa mice. We found that NEMOΔhepa/JNKΔhepa livers exhibited overexpression of the interleukin‐6/signal transducer and activator of transcription 3 pathway in addition to epidermal growth factor receptor (EGFR)‐rapidly accelerated fibrosarcoma (Raf)‐mitogen‐activated protein kinase kinase (MEK)‐extracellular signal‐regulated kinase (ERK) cascade. The functional relevance was tested by administering lapatinib, which is a dual tyrosine kinase inhibitor of erythroblastic oncogene B‐2 (ErbB2) and EGFR signaling, to NEMOΔhepa/JNKΔhepa mice. Lapatinib effectively inhibited cystogenesis, improved transaminases, and effectively blocked EGFR‐Raf‐MEK‐ERK signaling. Conclusion: We define a novel function of JNK1/2 in cholangiocyte hyperproliferation. This opens new therapeutic avenues devised to inhibit pathways of cholangiocarcinogenesis.

Abstract The paper presents a model set adaptive filtering algorithm based on variational Bayesian approximation (MSA-VB) for the target tracking system with the model and noise uncertainties. The Rényi information divergence, as a criterion, is to choose the best match model that has the minimum divergence between candidate models and true mode. Subsequently, the model-conditioned estimation based on variational Bayesian approximation is proposed to estimate system state and measurement noise variances. To deal with the coupled noise intractability, the moments matching technique is used to obtain the mixed statistics of measurement noise at the fusion stage. The proposed algorithm is compared with the interacting multiple models (IMM) algorithm and the variational Bayesian-interacting multiple models (IMM-VB) algorithm via two scenarios for maneuvering target tracking, and simulation results show that the MSA-VB has improved estimation and tracking performance.

In this study, an adaptive output feedback fault tolerant control (FTC) scheme is proposed for a class of multi-input and multioutput (MIMO) nonlinear systems with multiple constraints. The neural network (NN) is adopted to handle the unknown nonlinearity by means of its superior approximation capability. Based on it, the state observer is designed to estimate the unmeasured states, and the nonlinear disturbance observer is constructed to tackle the external disturbances. In addition, the Nussbaum function is utilized to cope with the actuator faults, which are coupled with the unknown control directions. Combining with the Lyapunov theory, a NN-based output feedback FTC law is developed for the MIMO nonlinear systems, and the boundedness of all closed-loop system error signals is proved. Simulation results on the unmanned helicopter are performed to demonstrate the effectiveness of the proposed controller.

BackgroundHepatic lipid metabolism regulates biliary composition and influences the formation of cholesterol gallstones. The genes Hmgcr and Cyp7a1, which encode key liver enzymes, are regulated by circadian rhythm-related transcription factors. We aimed to investigate the effect of circadian rhythm disruption on hepatic cholesterol and bile acid metabolism and the incidence of cholesterol stone formation.MethodsAdult male C57BL/6J mice were fed either a lithogenic diet (LD) only during the sleep phase (time-restricted lithogenic diet feeding, TRF) or an LD ad libitum (non-time-restricted lithogenic diet feeding, nTRF) for 4 weeks. Food consumption, body mass gain, and the incidence of gallstones were assessed. Circulating metabolic parameters, lipid accumulation in the liver, the circadian expression of hepatic clock and metabolic genes, and the gut microbiota were analyzed.ResultsTRF caused a dysregulation of the circadian rhythm in the mice, characterized by significant differences in the circadian expression patterns of clock-related genes. In TRF mice, the circadian rhythms in the expression of genes involved in bile acid and cholesterol metabolism were disrupted, as was the circadian rhythm of the gut microbiota. These changes were associated with high biliary cholesterol content, which promoted gallstone formation in the TRF mice.ConclusionDisordered circadian rhythm is associated with abnormal hepatic bile acid and cholesterol metabolism in mice, which promotes gallstone formation.

Tracking extended targets aims to estimate the kinematic state and shape of the target of interest with a varying number of noisy detections received by a sensor. The key challenge in this problem stems from its nonlinearity and high dimensionality due to the target maneuver and model complexities. This paper presents a modified adaptive extended Kalman filter based on the random hypersurface model (RHM) to address this problem. First, the target maneuver is judged by using the input estimate (IE) chi-square detector. Then, the magnitude of the target maneuver is used to modify the prior of the shape parameters. Based on the prior information, we derive an extended Kalman filter for a closed-form recursive measurement update. The simulation and experimental results demonstrate the usefulness of the proposed method for tracking the maneuvering star-convex extended target.

In this paper, the quadratic optimal control problem is investigated for the discrete-time linear systems with process and measurement noises which belong to specified ellipsoidal sets. As the noises are non-stochastic, the traditional Kalman filtering and Dynamic Bellman Equation are not applicable for the proposed control problem. To obtain the optimal control, we firstly converted the multi-step quadratic global optimal control problem to multiple one-step quadratic local approximate optimal control problems. For each one-step quadratic optimal control problem, considering that the system states are not fully available, the set-membership filtering is applied to estimate the true state feasible set. Then based on robust optimization, a robust state feedback control strategy can be obtained by solving a certain semidefinite programming (SDP) problem. The method can not only achieve the optimal control, but also estimate the system states more accurately. Finally, the simulation results verify the effectiveness of the proposed algorithm.

The trajectory planning of an aerial robotic manipulator system is studied using Hybrid Particle Swarm Optimization (HPSO). The aerial robotic manipulator is composed of an unmanned aerial vehicle (UAV) base and a robotic manipulator. The robotic manipulator is dynamically singular. In addition, strong coupling exists between the UAV base and the robotic manipulator. To overcome the problems, the trajectory planning is studied in the join space using HPSO. HPSO combines superiorities of PSO and GA (Genetic Algorithm), prohibiting particles from becoming trapped in a local minimum. In addition, the control parameters are self-adaptive and contribute to fast searching for the global optimum. The trajectory planning problem is converted into a parameter optimization problem. Each joint trajectory is parameterized with a Bézier curve. The HPSO is implemented to optimize joint trajectories, satisfying specific objectives and imposed constraints. Numerical simulations are also carried out to validate the effectiveness of the proposed method.

The motions of power sources in industrial applications were always provided by electromechanical systems, which use around 70% of the gross energy consumption of industrialized economies [...]

To solve the problems of data loss and unequal interval of momentum wheel (MW) speed during a satellite stable operation, this paper presents a multidimensional AR model. A Lagrange interpolation method is used to convert measurements to equal interval data, and the FFT algorithm is adopted to calculate the period of MW speed variation. The long data sequence is converted into multidimensional time series, based on the equal interval data and the period. A multidimensional AR model is established, and the least square method is used to estimate the model parameters. The future data trend is predicted by the proposed model. Simulation results show that the prediction algorithm can achieve the across cycle prediction of the MW speed data.

Cholestatic liver diseases including primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC) are associated with active hepatic fibrogenesis, which can ultimately lead to the development of cirrhosis. However, the exact relationship between the development of liver fibrosis and the progression of cholestatic liver disease remains elusive. Periductular fibroblasts located around the bile ducts seem biologically different from hepatic stellate cells (HSCs). The fibrotic events in these clinical conditions appear to be related to complex crosstalk between immune/inflammatory mechanisms, cytokine signalling, and perturbed homeostasis between cholangiocytes and mesenchymal cells. Several animal models including bile duct ligation (BDL) and the Mdr2-knockout mice have improved our understanding of mechanisms underlying chronic cholestasis. In the present review, we aim to elucidate the mechanisms of fibrosis in order to help to identify potential diagnostic and therapeutic targets.

In recent years, the incidence of both liver and biliary tract cancer has increased. Hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA) are the two most common types of hepatic malignancies. Whereas HCC is the fifth most common malignant tumor in Western countries, the prevalence of CCA has taken an alarming increase from 0.3 to 2.1 cases per 100,000 people. The lack of specific biomarkers makes diagnosis very difficult in the early stages of this fatal cancer. Thus, the prognosis of CCA is dismal and surgery is the only effective treatment, whilst recurrence after resection is common. Even though chemotherapy and radiotherapy may prolong survival in patients with CCA, the 5-year survival rate is still very low—a significant global problem in clinical diagnosis and therapy. The mitogen-activated protein kinase (MAPK) pathway plays an important role in signal transduction by converting extracellular stimuli into a wide range of cellular responses including inflammatory response, stress response, differentiation, survival, and tumorigenesis. Dysregulation of the MAPK cascade involves key signaling components and phosphorylation events that play an important role in tumorigenesis. In this review, we discuss the pathophysiological role of MAPK, current therapeutic options, and the current situation of MAPK-targeted therapies in CCA.

To deal with the problem of multitarget tracking with measurement origin uncertainty, the paper presents a multitarget tracking algorithm based on Adaptive Network Graph Segmentation (ANGS). The multitarget tracking is firstly formulated as an Integer Programming problem for finding the maximum a posterior probability in a cost flow network. Then, a network structure is partitioned using an Adaptive Spectral Clustering algorithm based on the Nyström Method. In order to obtain the global optimal solution, the parallel A* search algorithm is used to process each sub-network. Moreover, the trajectory set is extracted by the Track Mosaic technique and Rauch⁻Tung⁻Striebel (RTS) smoother. Finally, the simulation results achieved for different clutter intensity indicate that the proposed algorithm has better tracking accuracy and robustness compared with the A* search algorithm, the successive shortest-path (SSP) algorithm and the shortest path faster (SPFA) algorithm.