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ObjectiveAnti-dipeptidyl-peptidase-like protein-6 (DPPX) encephalitis is a rare autoimmune encephalitis, and clinical and experimental information regarding this disease is limited. We conducted this study to comprehensively describe the clinical characteristics, ancillary test results, neuroimaging results, and treatment response in a group of Chinese patients with anti-DPPX encephalitis for better understanding this disease.MethodsWe recruited 14 patients who tested positive for anti-DPPX antibodies in the serum and/or cerebrospinal fluid from 11 medical centers between March 2021 and June 2023. This retrospective study evaluated data on symptoms, autoantibody test, auxiliary examinations, treatments, and outcomes.ResultsThe average age at diagnosis was 45.93 ± 4.62 years (range: 11–72 years), and 9 of the 14 patients were males. The main symptoms included cognitive impairment (50.0%, 7/14), central nervous system hyperexcitability (42.9%, 6/14), gastrointestinal dysfunction (35.7%, 5/14), and psychiatric disorders (35.7%, 5/14). Notably, we discovered specific findings on 18F-fluorodeoxyglucose positron-emission tomography (PET)/magnetic resonance imaging in two patients. Co-existing autoantibodies were identified in two patients. Parainfection was identified in four patients. One patient had other autoimmune diseases, and one had tumor. Eleven patients received immunotherapy and most patients improved at discharge. Surprisingly, three male patients but no female patients relapsed during the 6 months of follow-up.ConclusionThe development and outcome of anti-DPPX encephalitis are variable. Male patients were predominant in our cohort. The most common symptoms were the classical triad of prodromal gastrointestinal dysfunction, cognitive and mental disorders, and central nervous system hyperexcitability. Infections, immune dysregulation, and tumors may be important etiologies. Long-term monitoring of disease development should be done in male patients. Overall, our results highlight novel clinical characteristics of anti-DPPX encephalitis.

Background The standardised management of neonatal critical care centres can help improve health outcomes of vulnerable newborns. Guidance is required to update evidence related to construction and management of neonatal critical care centres in China.Objective To establish expert consensus on the essential capability lists for neonatal critical care at three levels in China.Design and setting According to China’s administrative divisions, the Chinese guidelines stratifies neonatal critical care into three levels: county level (basic and special care), city level (intensive care) and province level (comprehensive care including neonatal surgery and more subspecialty interventions). A modified Delphi study was conducted. A group of 20 neonatologists from the Chinese Association of Neonatologists rated the importance of capability items on a 5-point Likert scale.Results At county level, the list consisted of 29 items related to basic and special care, and 3 items were unanimously rated very important by all experts: neonatal resuscitation, endotracheal intubation and continuous positive airway pressure ≥72 hours. At city level, group consensus defined 38 items as essential. Besides the essential items of county level, more items for intensive care were included in city level. At province level, 64 items reached consensus, including neonatal surgery and more advanced subspecialty interventions. The Kendall’s W values showed good agreement among experts in both rounds, and an increase from round 1 to round 2.Conclusions We developed the capability lists for neonatal critical care at three levels in China. Neonatal resuscitation should be provided by all levels. Interventions for preterm newborns are stratified according to gestational age and birth weight. Congenital abnormalities requiring surgical services need to be managed in high-level centres.

Time-of-use pricing of electric energy, as an important part of the national policy of energy conservation and emission reduction, requires accurate electric energy data as support. However, due to various reasons, the electric energy data are often missing. To address this thorny problem, this paper constructs a CNN and GRU-based recovery model (RCNN-BiGRU) for electric energy data by taking the missing data as the output and the historical data of the neighboring moments as the input. Firstly, a convolutional network with a residual structure is used to capture the local dependence and periodic patterns of the input data, and then a bidirectional GRU network utilizes the extracted potential features to model the temporal relationships of the data. Aiming at the difficult selection of network structure parameters and training process parameters, an accelerated adaptive differential evolution (AADE) algorithm is proposed to optimize the electrical energy data recovery model. The algorithm designs an accelerated mutation operator and at the same time adopts an adaptive strategy to set the two key parameters. A large amount of real grid data are selected as samples to train the network, and the comparison results verify that the proposed combined model outperforms the related CNN and GRU networks. The comparison experimental results with other optimization algorithms also show that the AADE algorithm proposed in this paper has better data recovery performance on the training set and significantly better performance on the test set.

Background: No evidence exists on the impact of bivalirudin in patients with the acute coronary syndrome undergoing rotational atherectomy. This study aimed to evaluate the impact of bivalirudin on patients with acute coronary syndrome undergoing rotational atherectomy. Methods: This was a retrospective cohort study conducted in our hospital between January 2017 and December 2019. The study included patients with acute coronary syndrome undergoing rotational atherectomy. Furthermore, 2 cohorts were included in this study (bivalirudin cohort and control cohort unfractionated heparin). The primary end-point was in-hospital net adverse clinical events. The secondary endpoint was all-cause mortality at 23 months. Results: The study included 157 patients with 33 (21.0%) in the bivalirudin cohort and 124 (79.0%) in the control cohort. Net adverse clinical events during hospitalization in the bivalirudin cohort were higher than that in the control cohort [9 (27.3%) vs. 14 (11.3%), P = .021]. However, there was no significant difference in all-cause mortality at 23 months between the 2 cohorts [25 (20.2%) vs. 10 (30.3%), P =.214]. After adjusting for potential confounders, the usage of bivalirudin was not associated with net adverse clinical event (odds ratio = 0.90; 95% CI: 0.18-4.45; P =.890), and the hazard ratio for all-cause mortality at 23 months was 1.01 (95% CI: 0.33-3.15; P =.983). Conclusion: Bivalirudin appears to exhibit a similar impact as unfractionated heparin on patients with acute coronary syndrome undergoing rotational atherectomy in real-life setting.

Abstract Non-ST-elevation acute coronary syndrome (NSTE-ACS) is a specific type of acute coronary syndrome. We applied the Thrombolysis in Myocardial Infarction (TIMI) score for risk stratification of patient prognosis. There was uncertainty about the routine revascularization time in patients with intermediate-risk NSTE-ACS. A total of 2835 patients with intermediate-risk NSTE-ACS (TIMI score 3–4) included in the China Acute Myocardial Infarction Registry from November 2014 to January 2017 were analyzed according to the time window from symptom onset to revascularization: within 24 h, Group I (814/28.7%); within 24 to 48 h, Group II (526/18.6%); within 48 to 72 h, Group III (403/14.2%); and after 72 h, Group IV (1092/38.5%). Risk factors, management and in-hospital outcomes were analyzed in the four groups. The results of the chi-square test showed that there was a significant difference in the incidence of in-hospital major adverse cardiovascular events (MACEs) when revascularization was completed within 48 h than when it was completed after 48 h (P

BackgroundArtificial intelligence technology has become a mainstream trend in the development of medical informatization. Because of the complex structure and a large amount of medical data generated in the current medical informatization process, big data technology to assist doctors in scientific research and analysis and obtain high-value information has become indispensable for medical and scientific research.MethodsThis study aims to discuss the architecture of diabetes intelligent digital platform by analyzing existing data mining methods and platform building experience in the medical field, using a large data platform building technology utilizing the Hadoop system, model prediction, and data processing analysis methods based on the principles of statistics and machine learning. We propose three major building mechanisms, namely the medical data integration and governance mechanism (DCM), data sharing and privacy protection mechanism (DPM), and medical application and medical research mechanism (MCM), to break down the barriers between traditional medical research and digital medical research. Additionally, we built an efficient and convenient intelligent diabetes model prediction and data analysis platform for clinical research.ResultsResearch results from this platform are currently applied to medical research at Shanghai T Hospital. In terms of performance, the platform runs smoothly and is capable of handling massive amounts of medical data in real-time. In terms of functions, data acquisition, cleaning, and mining are all integrated into the system. Through a simple and intuitive interface operation, medical and scientific research data can be processed and analyzed conveniently and quickly.ConclusionsThe platform can serve as an auxiliary tool for medical personnel and promote the development of medical informatization and scientific research. Also, the platform may provide the opportunity to deliver evidence-based digital therapeutics and support digital healthcare services for future medicine.

To evaluate hepatobiliary-specific contrast agent (CA) mangafodipir trisodium (Mn-DPDP)–enhanced magnetic resonance imaging (MRI) for predicting the therapeutic efficacy of the vascular disrupting agent combretastatin A4 phosphate (CA4P) in rats with primary and secondary liver tumors, 36 primary hepatocellular carcinomas (HCCs) were raised by diethylnitrosamine gavage in 16 male rats, in 6 of which one rhabdomyosarcomas (R1) was intrahepatically implanted as secondary liver tumors. On a 3.0T MR scanner with a wrist coil, tumors were monitored weekly by T2-/T1-weighted images (T2WI/T1WI) and characterized by Mn-DPDP-enhanced MRI. CA4P-induced intratumoral necrosis was depicted by nonspecific gadoterate meglumine (Gd-DOTA)–enhanced MRI before and 12 h after therapy. Changes of tumor-to-liver contrast (ΔT/L) on Mn-DPDP-enhanced images were analyzed. In vivo MRI findings were verified by postmortem microangiography and histopathology. Rat models of primary HCCs in a full spectrum of differentiation and secondary R1 liver tumors were successfully generated. Mn-DPDP-enhanced ΔT/L was negatively correlated with HCC differentiation grade (P

Abstract Background With the rapid development of economy in recent two decades, neonatology has been progressing quickly in China. However, there is little knowledge about the exact developmental status of neonatal departments in China. The aim of this study was to assess resources available for care of sick newborns in mainland China. Methods Questionnaires were sent to the membership of the Chinese Neonatologist Association (CNA) and used to survey the scale, facilities, staff, technologies, transport systems and preterm infants’ outcomes of neonatal departments (NDs) in different areas of China from June 2012 to December 2012. Results The result of this survey including a total of 117 questionnaires showed that investigated ND had a mean of 65 (median 47; range 5–450) beds, including 19.59 (median 15, range 0–100) NICU beds. The overall doctor/bed and nurse/bed ratio was 1:3.84 and 1:1.43, respectively. Lack of medical equipment was one of the main problems in most NDs surveyed, and only 26 NDs (22.2%) had more than one neonatal incubator per bed. Only 70.1, 30.6, 30.8 and 4.3% NDs carried out high-frequency ventilation, hypothermia, nitric oxide inhalation, and ECMO respectively. The capacity to provide advanced therapies increased with the size of the NDs (P

The support theory of the excavation disturbance zone (EDZ) cannot provide an accurate physical explanation or theoretical description of the time-dependent properties required for the development of an EDZ. Therefore, the primary factors that cause the formation of an EDZ should be determined to further improve the support theory of the EDZ and grasp the principle underlying the control of the long-term stability of rock masses. Considering the headrace tunnel and nuclear waste repository as the research background, this study aimed to understand the deformation damage evolution process of the surrounding rock after tunnel excavation under different working conditions using the self-developed realistic failure process analysis (RFPA2D) code. The simulation revealed the following. First, an EDZ is formed, although the deformation damage to the surrounding rock is relatively small under the action of environmental factors. Second, under the action of stress in the abovementioned case, the deformation speed, damage degree, and scope of the surrounding rock significantly increase, accelerating the formation and development of the EDZ. Therefore, the boundary of the EDZ expands significantly. Third, when environmental factors are blocked, the range of the EDZ is small due to the small deformation damage to the surrounding rock. Thus, the main factors responsible for the formation of the EDZ are environmental factors, whereas stress is only an auxiliary factor. A numerical simulation method that considers environmental factors can more accurately reproduce the formation of an EDZ. Therefore, a study of the internal mechanism of the EDZ phenomenon can provide a more in-depth understanding of the essential characteristics of an EDZ at the macro level. Furthermore, it can provide a scientific basis and method for the construction and support designs of underground excavation projects and widen the possibilities for further improving the support theory of the EDZ.

Background: Proteomic studies investigating novel molecular markers of coronary artery calcification (CAC) are scarce.This study compared the protein expression in the serum of patients with severe CAC and non-CAC. Methods: The serum from 30 patients with severe CAC and 30 matched-controls were screened by data-independent acquisition(DIA)-based proteomic technology. Bioinformatics analysis tools were used to analyze the underlying molecular mechanisms of the differentially expressed proteins. Candidate proteins were further validated by an enzyme-linked immunosorbent assay (ELISA) in an independent cohort. A receiver operating characteristic (ROC) curve was used to estimate the diagnostic power of the candidate proteins. Results: Among the 110 identified proteins, the expression of 81 was significantly upregulated, whereas 29 proteins were downregulated (fold change ≥1.5; p < 0.05) between patients with and without CAC. Bioinformatics analysis indicated that the differential proteins are involved in complement and coagulation cascades, platelet activation, regulation of actin cytoskeleton, or glycolysis/gluconeogenesis pathways. Further verification showed that serum levels of complement C5 (C5), fibrinogen gamma (FGG), pyruvate kinase isoform M2 (PKM2), and tropomyosin 4 (TPM4) were consistent with the proteomic findings, which could allow discrimination between CAC and non-CAC patients. Conclusions: This study revealed that high serum levels of serum C5, FGG, PKM2, and TPM4 proteins were linked to severe CAC. These proteins may be developed as biomarkers to predict coronary calcification.

Electric energy metering plays a crucial role in ensuring fair and equitable transactions between grid companies and power users. With the implementation of the State Grid Corporation’s energy Internet strategy, higher requirements have been put forward for power grid companies to reduce costs and increase efficiency and user service capabilities. Meanwhile, the accuracy and real-time requirements for electric energy measurements have also increased. Electricity information collection systems are mainly used to collect the user-side energy metering data for the power users. Attributed to communication errors, communication delays, equipment failures and other reasons, some of the collected data is missed or confused, which seriously affects the refined management and service quality of power grid companies. How to deal with such data has been one of the important issues in the fields of machine learning and data mining. This paper proposes a collaborative fitting algorithm to solve the problem of missing collected data based on latent semantics. Firstly, a tree structure of user history data is established, and then the user groups adjacent to the user with missing data are obtained from this. Finally, the missing data are recovered using the alternating least-squares matrix factorization algorithm. Through numerical verification, this method has high reliability and accuracy in recoverying the missing data.

Objective ST-segment elevation myocardial infarction (STEMI) is the most serious type of acute coronary syndrome. This study aimed to investigate the efficacy and safety of bivalirudin application during primary percutaneous coronary intervention (PPCI) in older patients with acute STEMI. Methods A total of 672 older patients with STEMI (>75 years) who underwent PPCI were studied. The primary endpoints were 30-day net adverse clinical events (NACEs) post-emergency percutaneous coronary intervention, including major adverse cardiac and cerebrovascular events (MACCEs) and Bleeding Academic Research Consortium grades 2 to 5 (BARC 2–5) bleeding events. Results The incidence of NACEs and BARC 2–5 bleeding events in the bivalirudin group was significantly lower than that in the unfractionated heparin group. Multivariate Cox regression analysis showed that bivalirudin significantly reduced 30-day NACEs (odds ratio: 0.700, 95% confidence interval: 0.492–0.995) and BARC 2–5 bleeding events (odds ratio: 0.561, 95% confidence interval: 0.343–0.918). At 1-year follow-up, these results were similar. Conclusions Bivalirudin can be safely and effectively used during PPCI in older patients with STEMI. Bivalirudin reduces the risks of NACEs and bleeding within 30 days after PPCI, without increasing the risks of MACCEs and stent thrombosis compared with heparin.

A domestic surfactant preparation has been used in China for a number of years. However, as for other surfactant preparations, there is debate among neonatologists regarding the optimal dose, mode of administration, and the best time of intervention. Objective: To evaluate whether prophylactic administration of surfactant is superior to early treatment in preterm infants < 32 weeks with a high risk of respiratory distress syndrome (RDS). Methods: We prospectively compared small premature infants (< 32 weeks) receiving 70 mg/kg bovine surfactant within 30 minutes after birth (prophylactic group, N = 116) with infants who received surfactant therapy for established RDS (early treatment group, N = 91). The primary outcome assessed was the incidence of RDS. The secondary outcomes assessed were severity of RDS, mortality, and bronchopulmonary dysplasia morbidity. Results: Compared with the early treatment group, the prophylactic group had a significantly better PaO2 (at 1 hour, 4 hours, and 12 hours postdose, respectively), better a/APO2 (at 1 hour, 4 hours, 12 hours, and 24 hours postdose, respectively), lower PaCO2 (at 1 hour postdose), and a significantly decreased need for mean airway pressure (MAP) and FiO2 on ventilation (p

This paper is concerned with the output synchronization problems for a class of delayed complex dynamical networks. Based on the invariant principle of functional differential equations and Lyapunov stability theory, the feedback controller and parameter update laws are constructed for a large-scale network with uncertainties. The general complex delayed network can achieve synchronization by adaptively adjusting their feedback gains. Numerical examples are presented to further verify the effectiveness of the proposed control scheme.

In order to prevent and control the large deformation of surrounding rock of tunnels, the selection of section type and the determination of excavation method were numerically investigated by using the self-developed code--Realistic Failure Process Analysis (RFPA2D) and taking a specific project as the engineering background--Ruyi tunnel. Then, special measures were employed to deal with the dangerous parts of the section of the tunnel. Finally, the control effect of surrounding rock deformation was checked with displacement monitoring and microseismic monitoring. The results showed that the horseshoe-shaped tunnels with six centers and the bench excavation can prevent the occurrence of large deformation. The "support resistant limiting damper-H230 grid steel frame" and the increased depth of the inverted arch can effectively control the deformation of the vault and the arch bottom. Besides, it was revealed that the propagation and connection of cracks at the top of the tunnel are the most critical cause for the instability failure of the tunnel. Engineering application indicated that the selected section type, excavation method and special support measures for dangerous parts greatly reduce the deformation of surrounding rock and effectively solve the problem of large deformation of the weak broken surrounding rock. [ABSTRACT FROM AUTHOR]