Rhabdomyosarcoma of the biliary tract in a child: a case report.

Pediatric rhabdomyosarcoma of the biliary tract (BRMS) is extremely rare. Here, we present a case of a 2-year-old child who was initially misdiagnosed with choledocholithiasis upon admission. The diagnosis was later confirmed as BRMS through endoscopic retrograde cholangiopancreatography (ERCP). The patient was cured through surgery followed by chemotherapy. Due to the lack of specific early symptoms and the challenges in imaging differentiation, particularly in pediatric patients, clinical awareness of this condition needs to be heightened. Our findings indicate that ERCP is currently the optimal diagnostic tool for this disease, and a combination of surgery and chemotherapy can yield better therapeutic outcomes.

Effects of Preoperative Oral Carbohydrates on Recovery After Laparoscopic Cholecystectomy: A Meta-analysis of Randomized Controlled Trials.

PURPOSE: The objective of this meta-analysis was to evaluate the efficacy of administering preoperative oral carbohydrates (CHO) compared to a control treatment in improving postoperative recovery outcomes for patients undergoing laparoscopic cholecystectomy (LC). DESIGN: A meta-analysis of randomized controlled trials. METHODS: Through systematic searches in PubMed, Embase, and the Cochrane Library, randomized controlled trials focusing on preoperative oral carbohydrates for patients undergoing LC were collected. Data analysis was conducted using the Revman 5.3 software. FINDINGS: The meta-analysis incorporated 19 randomized studies, with a total of 1,568 participants. Meta-analysis results indicated that patients receiving CHO reported notably lower postoperative pain compared to those fasting (P = .006) or on placebo (P = .003). Furthermore, a significant reduction in preoperative hunger was observed in the CHO group compared to the controls (P = .002). A notable difference was also identified in the postoperative Homeostasis Model Assessment-IR changes between the CHO and control groups (P = .02). No significant variations were observed in thirst, postoperative nausea and vomiting, insulin level alterations, glucose level changes, duration of hospital stay, or recovery quality. CONCLUSIONS: Preoperative oral carbohydrates may alleviate hunger and pain, and attenuate postoperative insulin resistance more effectively than either overnight fasting or placebo in patients undergoing LC.

Scalable parameterized quantum circuits classifier.

As a generalized quantum machine learning model, parameterized quantum circuits (PQC) have been found to perform poorly in terms of classification accuracy and model scalability for multi-category classification tasks. To address this issue, we propose a scalable parameterized quantum circuits classifier (SPQCC), which performs per-channel PQC and combines the measurements as the output of the trainable parameters of the classifier. By minimizing the cross-entropy loss through optimizing the trainable parameters of PQC, SPQCC leads to a fast convergence of the classifier. The parallel execution of identical PQCs on different quantum machines with the same structure and scale reduces the complexity of classifier design. Classification simulations performed on the MNIST Dataset show that the accuracy of our proposed classifier far exceeds that of other quantum classification algorithms, achieving the state-of-the-art simulation result and surpassing/reaching classical classifiers with a considerable number of trainable parameters. Our classifier demonstrates excellent scalability and classification performance.

Blurred interface induced control of electrical transport properties in Josephson junctions.

The interfacial microstructures of Josephson junctions are vital for understanding the microscopic mechanism to improve the performance of superconducting qubits further. However, there remain significant concerns about well understanding the correlation between atomic structures and electrical behaviors. Here, we propose a new method to define the interface of the barrier in Josephson junctions, and investigate the factors that affect the electrical properties of junctions using material analysis techniques and first principles. We find that the aluminium-oxygen ratio of the interface contributes greatly to the electrical properties of junctions, which is consistent with the conclusions obtained by utilizing the generative adversarial network for data augmentation. When the aluminium-oxygen ratio of the interface is 0.67-1.1, the model exhibits a lower barrier height and better electrical properties of the junction. Moreover, when the thickness of the barrier is fixed, the impact of the aluminium-oxygen ratio becomes prominent. A detailed analysis of Josephson junctions using a microscopic model has led to identifying of process defects that can enhance the yield rate of chips. It has a great boost for determining the relationship between microstructures and macroscopic performances.

Recurrent quantum embedding neural network and its application in vulnerability detection.

In recent years, deep learning has been widely used in vulnerability detection with remarkable results. These studies often apply natural language processing (NLP) technologies due to the natural similarity between code and language. Since NLP usually consumes a lot of computing resources, its combination with quantum computing is becoming a valuable research direction. In this paper, we present a Recurrent Quantum Embedding Neural Network (RQENN) for vulnerability detection. It aims to reduce the memory consumption of classical models for vulnerability detection tasks and improve the performance of quantum natural language processing (QNLP) methods. We show that the performance of RQENN achieves the above goals. Compared with the classic model, the space complexity of each stage of its execution is exponentially reduced, and the number of parameters used and the number of bits consumed are significantly reduced. Compared with other QNLP methods, RQENN uses fewer qubit resources and achieves a 15.7% higher accuracy in vulnerability detection.

A general quantum algorithm for numerical integration.

Quantum algorithms have shown their superiority in many application fields. However, a general quantum algorithm for numerical integration, an indispensable tool for processing sophisticated science and engineering issues, is still missing. Here, we first proposed a quantum integration algorithm suitable for any continuous functions that can be approximated by polynomials. More impressively, the algorithm achieves quantum encoding of any integrable functions through polynomial approximation, then constructs a quantum oracle to mark the number of points in the integration area and finally converts the statistical results into the phase angle in the amplitude of the superposition state. The quantum algorithm introduced in this work exhibits quadratic acceleration over the classical integration algorithms by reducing computational complexity from O(N) to O(√N). Our work addresses the crucial impediments for improving the generality of quantum integration algorithm, which provides a meaningful guidance for expanding the superiority of quantum computing.

Effects of Zhuangyao Shuanglu Tongnao Formula on neuronal apoptosis of rats with ischemia-reperfusion induced injury / 中成药

AIM To investigate the effects of Zhuangyao Shuanglu Tongnao Formula on neuronal apoptosis in rats with cerebral ischemia-reperfusion injury based on the study of oxidative stress and inflammatory response.METHODS The rats were randomly divided into the sham operation group,the model group,the edaravone group(3.0 mg/kg),the low,medium and high dose groups(9.0,18.0,36.0 g/kg)of Zhuangyao Shuanglu Tongnao Formula,with 18 rats in each group.The middle cerebral artery occlusion/reperfusion was conducted by thread embolism method to simulate cerebral ischemia reperfusion injury in rats followed by 6 days corresponding drugs administration.Subsequently,the rats had their neurological function deficit scored by Zeal Longa scoring method;their sizes of cerebral infarction areas measured by TTC staining;their pathological damage and apoptosis of neurons in hippocampal CA1 area of ischemic penumbra of the brain tissue detected by HE staining and TUNEL staining;their SOD activity and levels of GSH,MDA,IL-6,IL-1β,TNF-α in brain tissue detected by kits;and their protein expressions of Bax,Bcl-2,caspase-3,cleaved-capase-3,TLR4,NF-κB p65,Nrf2,HO-1 in rat brain tissue determined by Western blot.RESULTS Compared with the model group,the groups intervened with edaravone,medium and high dose of Zhuangyao Shuanglu Tongnao Formula displayed improvements in the scores of nerve function defects,the rate of cerebral infarction,the rate of neuronal apoptosis,the levels of IL-6,IL-1β,TNF-α and MDA in the ischemic penumbra of brain tissues,the protein expressions of Bax and TLR4,the ratio of cleaved-capase-3/caspase-3 and p-NF-κB p65/NF-κB p65(P＜0.05),the levels of GSH,the activity of SOD and the protein expressions of Bcl-2,Nrf2 and HO-1(P＜0.05).CONCLUSION Being an inhibitor of oxidative stress and inflammatory response,Zhuangyao Shuanglu Tongnao Formula can alleviate brain injury in rats with cerebral ischemia reperfusion injury through the inhibition of neuronal apoptosis and improvement of neural function mediated by the inhibition of TLR4/NF-κB signal pathway and activation of Nrf2/HO-1 signal pathway.

Fast reconstruction algorithm based on HMC sampling.

In Noisy Intermediate-Scale Quantum (NISQ) era, the scarcity of qubit resources has prevented many quantum algorithms from being implemented on quantum devices. Circuit cutting technology has greatly alleviated this problem, which allows us to run larger quantum circuits on real quantum machines with currently limited qubit resources at the cost of additional classical overhead. However, the classical overhead of circuit cutting grows exponentially with the number of cuts and qubits, and the excessive postprocessing overhead makes it difficult to apply circuit cutting to large scale circuits. In this paper, we propose a fast reconstruction algorithm based on Hamiltonian Monte Carlo (HMC) sampling, which samples the high probability solutions by Hamiltonian dynamics from state space with dimension growing exponentially with qubit. Our algorithm avoids excessive computation when reconstructing the original circuit probability distribution, and greatly reduces the circuit cutting post-processing overhead. The improvement is crucial for expanding of circuit cutting to a larger scale on NISQ devices.

Binary code similarity analysis based on naming function and common vector space.

Binary code similarity analysis is widely used in the field of vulnerability search where source code may not be available to detect whether two binary functions are similar or not. Based on deep learning and natural processing techniques, several approaches have been proposed to perform cross-platform binary code similarity analysis using control flow graphs. However, existing schemes suffer from the shortcomings of large differences in instruction syntaxes across different target platforms, inability to align control flow graph nodes, and less introduction of high-level semantics of stability, which pose challenges for identifying similar computations between binary functions of different platforms generated from the same source code. We argue that extracting stable, platform-independent semantics can improve model accuracy, and a cross-platform binary function similarity comparison model N_Match is proposed. The model elevates different platform instructions to the same semantic space to shield their underlying platform instruction differences, uses graph embedding technology to learn the stability semantics of neighbors, extracts high-level knowledge of naming function to alleviate the differences brought about by cross-platform and cross-optimization levels, and combines the stable graph structure as well as the stable, platform-independent API knowledge of naming function to represent the final semantics of functions. The experimental results show that the model accuracy of N_Match outperforms the baseline model in terms of cross-platform, cross-optimization level, and industrial scenarios. In the vulnerability search experiment, N_Match significantly improves hit@N, the mAP exceeds the current graph embedding model by 66%. In addition, we also give several interesting observations from the experiments. The code and model are publicly available at https://www.github.com/CSecurityZhongYuan/Binary-Name_Match .

Machine Learning Prediction Model and Risk Factor Analysis of Reoperation in Recurrent Lumbar Disc Herniation Patients After Percutaneous Endoscopic Lumbar Discectomy.

OBJECTIVE: To investigate the risk factors of reoperation after percutaneous endoscopic lumbar discectomy (PELD) due to recurrent lumbar disc herniation (rLDH) and to establish a set of individualized prediction models. METHODS: Patients who underwent PELD successfully from January 2016 to February 2022 in a single institution were enrolled in this study. Six methods of machine learning (ML) were used to establish an individualized prediction model for reoperation in rLDH patients after PELD, and these models were compared with logistics regression model to select optimal model. RESULTS: A total of 2603 patients were enrolled in this study. 57 patients had repeated operation due to rLDH and 114 patients were selected from the remaining 2546 nonrecurrent patients as matched controls. Multivariate logistic regression analysis showed that disc herniation type (P < .001), Modic changes (type II) (P = .003), sagittal range of motion (sROM) (P = .022), facet orientation (FO) (P = .028) and fat infiltration (FI) (P = .001) were independent risk factors for reoperation in rLDH patients after PELD. The XGBoost AUC was of 90.71%, accuracy was approximately 88.87%, sensitivity was 70.81%, specificity was 97.19%. The traditional logistic regression AUC was 77.4%, accuracy was about 77.73%, sensitivity was 47.15%, specificity was 92.12%. CONCLUSION: This study showed that disc herniation type (extrusion, sequestration), Modic changes (type II), a large sROM, a large FO and high FI were independent risk factors for reoperation in LDH patients after PELD. The prediction efficiency of XGBoost model was higher than traditional Logistic regression analysis model.

Effect of the Al/AlOx interfacial stacking sequence on the transport properties of alumina tunnel junctions.

Superconducting quantum bits based on Al/AlOx/Al Josephson junction devices are among the most developed quantum bits at present. The microstructure of the device interface critically affects the electrical properties of Josephson junctions, which in turn severely affects the superconducting quantum bits. Further progress towards scalable superconducting qubits urgently needs to be guided by novel analysis mechanisms or methods to improve the performance of junctions. A direct experimental study of the atomic structure of the device is very challenging. Therefore, we simulated three-dimensional Al/α-Al2O3/Al Josephson junction devices via first-principles electronic structure and ballistic transport calculations to investigate the relationship between transport properties and the Al/Al2O3 stacking sequence. This work elucidates in detail the effects of the aluminum and alumina stacking sequence on the electron transport properties of the Al/Al2O3/Al system at the microscopic level by combining first-principles density functional theory and a non-equilibrium Green's function formalism. It is first revealed that the oxygen termination mode exhibits the least sensitivity to conductance changes in the Al/Al2O3 stacking sequence, offering useful theoretical guidance for increasing the yield of fixed-frequency multi-qubit quantum chips which require tight control on qubit frequency.

Computational Simulations of Fabrication of Aluminum-Based Josephson Junctions: Topological Aspects of the Barrier Structure.

Although the performance of qubits has been improved in recent years, the differences in the microscopic atomic structure of the Josephson junctions, the core devices prepared under different preparation conditions, are still underexplored. In this paper, the effects of the oxygen temperature and upper aluminum deposition rate on the topology of the barrier layer in the aluminum-based Josephson junctions have been presented by classical molecular dynamics simulations. We apply a Voronoi tessellation method to characterize the topology of the interface and central regions of the barrier layers. We find that when the oxygen temperature is 573 K and the upper aluminum deposition rate is 4 Å/ps, the barrier has the fewest atomic voids and the most closely arranged atoms. However, if only the atomic arrangement of the central region is considered, the optimal rate of the aluminum deposition is 8 Å/ps. This work provides microscopic guidance for the experimental preparation of Josephson junctions, which helps to improve the performance of qubits and accelerate the practical application of quantum computers.

Directly Controlling the Transport Properties of All-Nitride Josephson Junctions by N-Vacancy Defects.

All-nitride Josephson junctions are being actively explored for applications in superconducting quantum chips because of their unique advantages including their antioxidant chemical stability and high crystal quality. However, the theoretical research on their microstructure mechanism that determines transport properties is still absent, especially on the defects. In this paper, we apply the first principles and non-equilibrium Green's function to calculate the electrical transport characteristics of the yellow preset model. It is first revealed that the N-vacancy defects play a crucial role in determining the conductivity of the NbN-based Josephson junctions, and demonstrate the importance for the uniformity of vacancy distribution. It is found that the uniform number of vacancies can effectively increase the conductance of Josephson junction, but the position distribution of vacancies has little effect on the conductance. The work clarifies the effect of the N-vacancy defects on the conductivity of the NbN-based Josephson junctions, which offers useful guidance for understanding the microscope mechanism of the NbN-based Josephson junction, thus showing a great prospect in the improvement of the yield of superconducting quantum chips in the future.

An Enhanced Quantum K-Nearest Neighbor Classification Algorithm Based on Polar Distance.

The K-nearest neighbor (KNN) algorithm is one of the most extensively used classification algorithms, while its high time complexity limits its performance in the era of big data. The quantum K-nearest neighbor (QKNN) algorithm can handle the above problem with satisfactory efficiency; however, its accuracy is sacrificed when directly applying the traditional similarity measure based on Euclidean distance. Inspired by the Polar coordinate system and the quantum property, this work proposes a new similarity measure to replace the Euclidean distance, which is defined as Polar distance. Polar distance considers both angular and module length information, introducing a weight parameter adjusted to the specific application data. To validate the efficiency of Polar distance, we conducted various experiments using several typical datasets. For the conventional KNN algorithm, the accuracy performance is comparable when using Polar distance for similarity measurement, while for the QKNN algorithm, it significantly outperforms the Euclidean distance in terms of classification accuracy. Furthermore, the Polar distance shows scalability and robustness superior to the Euclidean distance, providing an opportunity for the large-scale application of QKNN in practice.

Association between perfluorinated alkyl substances and depression / 环境与职业医学

Background Perfluorinated alkyl substances (PFAS) are a class of synthetic organic fluorides, which have adverse health effects on brain function, and limited research has been conducted on their effects on depression. Objective To assess potential correlation between serum PFAS and depression. Methods Using the 2015—2016 and 2017—2018 National Health and Nutrition Examination Survey (NHANES) datasets, 2626 subjects with complete relevant information in people ≥20 years old were selected. Logistic regression and restricted cubic splines were used to analyze the association and dose-response relationship between serum PFAS concentration and depression. Subgroup analysis was performed on sex, age, race, education level, marital status, family income to poverty ratio, moderate exercise, body mass index, and drinking status. Results Among the 2626 subjects, there were 666 patients (25.4%) with mild or above depression. After adjusting for race, education level, marital status, body mass index, moderate exercise, drinking history, cotinine, and other types of PFAS, serum perfluorooctane sulfonate (PFOS) was positively associated with the risk of depression (OR=1.85, 95%CI: 1.14, 3.02), and showed a nonlinear dose-response relationship (χ2=6.37, Pnonlinear=0.012). Perfluorononanoic acid (PFNA) was inversely associated with the risk of depression (OR=0.23, 95%CI: 0.14, 0.39), and showed a linear dose-response relationship (Ptrend<0.001, χ2=35.13, Poverall<0.001). After subgroup analysis, it was found that males, 20-39 year-olds and 40-64 year-olds were more sensitive to PFNA exposure (OR=0.15, 95%CI: 0.06, 0.37; OR=0.16, 95%CI: 0.06, 0.40; OR=0.18, 95%CI: 0.08, 0.39). PFOS only showed a statistically significant health effect in people aged 20-39 years (OR=3.00, 95%CI: 1.14, 7.94). In addition, among subgroups of non-Hispanic blacks, cohabitants, current drinkers, high school graduates, and obese patients, exposure to PFAS was significantly associated with the risk of depression. Conclusion PFOS exposure may be associated with increased levels of depression, whereas PFNA exposure may be protective.

Analysis of adverse events in cancer radiotherapy with the first carbon ion therapy system in China / 中华放射肿瘤学杂志

Objective:To analyze the clinical adverse events of the first carbon ion therapy system in radiotherapy for cancer patients in China.Methods:A retrospective analysis was conducted on the clinical trial monitoring data of the carbon ion therapy system obtained by the Pharmacovigilance Center of Gansu Province. A descriptive study was conducted on the demographic characteristics, radiotherapy techniques, irradiation site and dose parameters, postoperative follow-up, and adverse event information of 46 tumor patients who received carbon ion therapy and participated in the clinical trial in Wuwei Cancer Hospital, Gansu Province from November 2018 to February 2019. Frequency and percentage were used to describe and analyze the occurrence of adverse events after carbon ion therapy for cancer patients in different groups. All subjects who received radiotherapy were grouped according to the treatment dose and fractionation method.Results:The median age of the 46 patients was 47 years old, and the male to female ratio was 30∶16. There were 15, 5, 8, 9, and 9 patients with head and neck, chest, abdomen, pelvic cavity, and limb spinal tumors, respectively. The total duration of radiotherapy was 2-4 weeks for 10-16 times. There were 246 adverse events in 45 cases, with an incidence of 98%. No severe adverse events occurred. The adverse events definitely related to carbon ion devices accounted for 19.1%, and no severe adverse events related to carbon ion devices occurred. According to the evaluation criteria of common terminology criteria for adverse events (CTCAE), the main adverse events were CTCAE grade 2 and below, with only 1 (2%) head and neck tumor patient (nasopharyngeal malignant tumor) experienced CTCAE grade 3 adverse events after treatment. In addition, 43 patients developed acute adverse reactions, with an incidence of 93%, mainly involving the skin, mucosa, eyes, ears, pharynx and esophagus, upper gastrointestinal tract, lower gastrointestinal tract (including pelvic cavity), lung, genitourinary tract, heart, central nervous system and hematology (white blood cells, platelets and neutrophils), etc. Conclusion:The adverse reactions of patients treated with the first carbon ion therapy system are mainly CTCAE grade 2 and below, and the clinical adverse events are mild and controllable.

Succinate dehydrogenase deficiency renal cell carcinoma: a case report / 中华泌尿外科杂志

Succinate dehydrogenase (SDH) defective renal cell carcinoma (RCC) is a new subtype of renal carcinoma newly identified by WHO(2016). Until now, only a few samples and a few cases have been reported retrospectively. This article reported a young female patient who was found to have a small tumor in the left kidney by physical examination and underwent left partial nephrectomy. The postoperative pathological result was SDH-RCC. There was no recurrence and metastasis of the tumor 3 months after operation.

Interpretation and reunderstanding of the updated pathological classification of renal tumors of World Health Organization in 2022 / 肿瘤研究与临床

In 2022, World Health Organization (WHO) launched the 5th edition of the classification of renal tumors. This classification continues to use the previous classification framework of renal tumors based on morphology and tissue structure, and proposes the concept of renal cell carcinoma defined by molecular features for the first time. This article interprets from the 3 aspects of historical changes of WHO classification and grading of renal tumors, comparison of 2022 and 2016 WHO classification of renal tumors, and the role of molecular characteristics in the new pathological types such as ELOC mutant renal cell carcinoma, ALK rearrangement renal cell carcinoma, eosinophilic solid and cystic renal cell carcinoma. The purpose is to better understand the WHO from the traditional classification system based on tissue morphology to a three-in-one integrated classification system covering morphology, immunophenotype and genetic characteristics, and to understand the important value of molecular pathology in guiding the work of pathologists and clinicians under the new classification system.

Clinical Efficacy of Niaoxue No.1 Prescription in Treatment of Henoch-Schönlein Purpura Nephritis with Blood Heat and Stasis Syndrome in Children / 中国实验方剂学杂志

ObjectiveTo investigate the clinical efficacy of Niaoxue No.1 Prescription in treating Henoch-Schönlein purpura （HSP） nephritis with blood heat and stasis syndrome and its effect on urine erythrocyte， urine protein， blood neutrophils， and blood routine-derived indicators. MethodA multicenter， randomized controlled trial （RCT） was conducted involving 108 HSP nephritis patients from three hospitals. The patients were randomly divided into a control group （54 cases） and a treatment group （54 cases）. The treatment group received Niaoxue No.1 prescription once daily， while the control group was treated with captopril and ferulic acid tablets. Both groups underwent a 4-week course of treatment. The urine erythrocyte， urine microalbumin （mAlb）， urine sediment red blood cell count， traditional Chinese medicine （TCM） syndrome score， 24-hour urine protein， blood neutrophil count， neutrophil to lymphocyte ratio （NLR）， platelet to lymphocyte ratio （PLR）， lymphocyte to monocyte ratio （LMR）， D-dimer， and immunoglobulin A were detected. The recurrence rate of HSP nephritis was followed up for 6 months. ResultThe total effective rates were 88.9% （48/54） in the treatment group and 70.4% （38/54） in the control group， and the treatment group was superior to the control group （χ2=5.708， P<0.05）. Compared with the results before treatment， after 14 days of treatment， the TCM syndrome total score， urine erythrocyte， urine mAlb， and 24-hour urine protein in both groups significantly decreased （P<0.05，P<0.01）， and the improvement was more significant in the treatment group than the control group （P<0.05）. After 28 days of treatment， compared with the results before treatment， the TCM syndrome total score， urine erythrocyte， urine mAlb， urine sediment red blood cell count， D-dimer， and 24-hour urine protein in both groups significantly decreased （P<0.05，P<0.01）， with the treatment group showing a more significant reduction in urine mAlb than the control group （P<0.05）. On the 14th and 28th days of treatment， the neutrophil percentage and NLR were lower in the treatment group than in the control group （P<0.05）， while there was no statistically significant difference in PLR and LMR. The recurrence rate of nephritis in both groups showed no statistically significant difference after a 6-month follow-up. ConclusionNiaoxue No.1 Prescription in the treatment of HSP nephritis with blood heat and stasis syndrome can significantly improve clinical symptoms， shorten the course of the disease， and reduce urine erythrocyte， urine mAlb， 24-hour urine protein， blood neutrophils， and NLR， thereby effectively alleviating the inflammatory state and reducing kidney damage in children with HSP nephritis.