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Nucleus basalis of Meynert (NbM), one of the earliest targets of Alzheimer's disease (AD), may act as a seed for pathological spreading to its connected regions. However, the underlying basis of regional vulnerability to NbM dysconnectivity remains unclear. NbM functional dysconnectivity was assessed using resting-state fMRI data of health controls and mild cognitive impairment (MCI) patients from the Alzheimer's disease Neuroimaging Initiative (ADNI2/GO phase). Transcriptional correlates of NbM dysconnectivity was explored by leveraging public intrinsic and differential post-mortem brain-wide gene expression datasets from Allen Human Brain Atlas (AHBA) and Mount Sinai Brain Bank (MSBB). By constructing an individual-level tissue-specific gene set risk score (TGRS), we evaluated the contribution of NbM dysconnectivity-correlated gene sets to change rate of cerebral spinal fluid (CSF) biomarkers during preclinical stage of AD, as well as to MCI onset age. An independent cohort of health controls and MCI patients from ADNI3 was used to validate our main findings. Between-group comparison revealed significant connectivity reduction between the right NbM and right middle temporal gyrus in MCI. This regional vulnerability to NbM dysconnectivity correlated with intrinsic expression of genes enriched in protein and immune functions, as well as with differential expression of genes enriched in cholinergic receptors, immune, vascular and energy metabolism functions. TGRS of these NbM dysconnectivity-correlated gene sets are associated with longitudinal amyloid-beta change at preclinical stages of AD, and contributed to MCI onset age independent of traditional AD risks. Our findings revealed the transcriptional vulnerability to NbM dysconnectivity and their crucial role in explaining preclinical amyloid-beta change and MCI onset age, which offer new insights into the early AD pathology and encourage more investigation and clinical trials targeting NbM.

Volumetric magnetic resonance imaging (MRI) atrophy is a hallmark of Rasmussen’s encephalitis (RE). Here, we aim to investigate voxel-wise gray matter (GM) atrophy in RE, and its associations with glucose hypometabolism and neurotransmitter distribution utilizing MRI and PET data. In this study, fifteen RE patients and fourteen MRI normal subjects were included in this study. Voxel-wise GM volume and glucose metabolic uptake were evaluated using structural MRI and FDG-PET images, respectively. Spatial Spearman’s correlation was performed between GM atrophy of RE with FDG uptake alterations, and neurotransmitter distributions provided in the JuSpace toolbox. Compared with the control group, RE patients displayed extensive GM volume loss not only in the ipsilateral hemisphere, but also in the frontal lobe, basal ganglia, and cerebellum in the contralateral hemisphere. Within the RE group, the insular and temporal cortices exhibited significantly more GM atrophy on the ipsilesional than the contralesional side. FDG-PET data revealed significant hypometabolism in areas surrounding the insular cortices in the ipsilesional hemisphere. RE-related GM volumetric atrophy was spatially correlated with hypomebolism in FDG uptake, and with spatial distribution of the dopaminergic and serotonergic neurotransmitter systems. The spatial concordance of morphological changes with metabolic abnormalities suggest FDG-PET offers potential value for RE diagnosis. The GM alterations associated with neurotransmitter distribution map could provide novel insight in understanding the neuropathological mechanisms and clinical feature of RE.

As sustainable natural sources such as wind and solar are increasingly integrated into power grids, conventional fossil fuel-based generating units will be gradually replaced, resulting in enormous pressure on frequency regulation of the novel power systems. This paper proposes a method for implementing a cascaded load-damping factor controller based on the controlled load-damping factor controller. Series-type voltage regulators, namely, solid-state transformers or dynamic voltage restorers, can regulate the voltage of the 10 kV feeder within the allowed range. Therefore real-time control of composite load power is realized, which significantly improves the primary frequency regulation capability of novel power systems with renewable energy generation(REG). The effect of actuator regulation time constant is considered, The impact of dynamic loads on the primary frequency regulation of the controller, designed based on a static load model, is analyzed, The effectiveness of the controller on the primary frequency regulation under different renewable energy penetration rates is discussed, The effectiveness of the controller in smoothing short-term power fluctuations of REG is examined. Finally, the effectiveness of the series-connected controlled load-damping factor controller in primary frequency regulation is verified on the RTDS simulation experimental platform. The proposed control system is characterized by a simple structure, easy implementation, and convenient maintenance, which can realize the coordination and unification of reactive-voltage and active-frequency control of the novel power system in the 110 kV customer substation and is beneficial to practical application in engineering.

As the result of renewable energy natural intermittency, load shedding and renewables curtailment are inevitable to keep supply and demand balance in high penetration level power systems. Luckily, with accurate estimation and proper allocation of the reserve, power fluctuation can be smoothed appreciably. Therefore, this study presents a novel coordinated day-ahead economic dispatch model for both energy and reserve in bulk hybrid AC/DC power systems. Flexible frequency operation for each regional sub AC system is applied to estimate reserve demand, while renewable energy forecast error is described by the versatile probability distribution. Considering practical operation structure in China, a non-iterative bi-layer dispatch algorithm is proposed to share power and reserve between interconnected subsystems by applying DC tie-lines’ flexibility. This bi-layer structure is achieved through the upper layer deciding the boundary variables with aggregated generation information provided by the lower layer. Then each lower layer regional AC grid solves its own programming with the boundary variables. Simulation is carried out to verify the efficacy of the proposed dispatch model and distributed solution methodology.

In order to realize the energy supply-side reform and promote the “double carbon” goal, the power supply structure of China is being optimized and the proportion of renewable energy sources (RES) is gradually increasing, resulting in the traditional mechanism model analysis methods can hardly satisfy the requirements of monitoring and operation optimization of new power systems. Digital twin technology utilizes sensors, big data, artificial intelligence and other technologies to establish the mirroring from physical space to virtual space, and it is an effective way to analyze the evolution law of dynamic behavior of key equipment and power systems, and propose optimal control strategies. Based on the technical connotation of digital twin, this paper proposes a framework for the construction of digital twin microgrids with high percentage of RES. A real-time digital simulator (RTDS) is used to build a grid-level digital twin microgrid to digitally reproduce the equipment, environment and other key aspects of the physical grid. A digital twin framework for power equipment is proposed to provide a systematic structural support for the digital management of microgrid power equipment. Finally, the advanced application module of digital twin microgrid is prospected to provide lessons and references for the construction of digital twin microgrid.

Fully utilizing local clean energy by regional Integrated Energy System is a effective way to alleviate energy crisis and reduce carbon emissions. Due to clean energy resources e.g., photovoltaic, wind power and low-grade heat distribute in region which results to be difficult to integrate, this paper provide improved two-steps k-means arithmetic for cluster partition of Regional Integrated Energy System for utilizing distributed energy. Firstly, the weight index is defined for direction of cluster partition. Secondly, according to the resource endowment and located position of distributed energy, the initial energy cluster partition and cluster center considering weight coefficient is determined. Finally, load is divided into the cluster according to the distance of source load and matching coefficient. The practical case indicate that the method proposed can effectively realize cluster partition and integration of distributed energy.

Toxoplasmosis is a widespread disease in humans and animals. Currently, toxoplasmosis chemotherapy options are limited due to severe side effects. There is an urgent need to develop new drugs with better efficacy and few side effects. HQNO, a cytochrome bc1 and type II NADH inhibitor in eukaryotes and bacteria, possesses extensive bioactivity. In this study, the cytotoxicity of HQNO was evaluated in Vero cells. The in vitro effects of HQNO were determined by plaque assay and qPCR assay. To determine the in vivo effect of HQNO, pharmacokinetic experiments and in vivo infection assays were performed in mice. The changes in tachyzoites after HQNO exposure were examined by transmission electron microscopy (TEM), MitoTracker Red CMXRos staining, ROS detection and ATP detection. HQNO inhibited T. gondii invasion and proliferation with an EC50 of 0.995 μM. Pharmacokinetic experiments showed that the Cmax of HQNO (20 mg/kg·bw) was 3560 ± 1601 ng/mL (13.73 μM) in healthy BALB/c mouse plasma with no toxicity in vivo. Moreover, HQNO induced a significant decrease in the parasite burden load of T. gondii in mouse peritoneum. TEM revealed alterations in the mitochondria of T. gondii. Further assays verified that HQNO also decreased the mitochondrial membrane potential (ΔΨm) and ATP levels and enhanced the level of reactive oxygen species (ROS) in T. gondii. Hence, HQNO exerted anti-T. gondii activity, which may be related to the damage to the mitochondrial electron transport chain (ETC).

Summary: Exploring key genes for antineutrophil cytoplasmic antibody (ANCA)-associated glomerulonephritis (ANCA-GN) is of great significance. Through bioinformatics analysis, 79 immune protein-differentially expressed genes (IP-DEGs) were obtained. Six hub genes (PTPRC, CD86, TLR2, IL1B, CSF-1R, and CCL2) were identified and verified to be increased in ANCA-GN patients. Random forest algorithm and ROC analysis showed that CSF-1R was a potential biomarker. Plasma CSF-1R levels increased significantly in ANCA-GN-active patients compared with remission stage and control. Correlation analysis revealed that CSF-1R levels had positive relationship with serum creatinine and Birmingham scoring, while inversely correlated with eGFR. Multivariate analysis revealed that plasma CSF-1R were an independent poor prognostic variable for end-stage renal disease or death, after adjusting for age and gender (HR = 3.05, 95% CI = 1.45–6.43, p = 0.003). Overall, we revealed that the CSF-1R is related to disease activity and might be a vital gene associated with the pathogenesis of ANCA-GN.

The isolated power system has a simple structure with small inertia and no support from the large-scale power system, so the frequency stability problem is more prominent. A frequency control method based on coordinated control of flexible loads (FL) and energy storage systems (ESS) is proposed in this paper. The ESS adopts the droop control considering the state of charge (SOC) to quickly respond to the system frequency deviation and provide fast frequency support. Based on the load power–voltage sensitivity, the FL participates in frequency control by adjusting the load voltage and thus the load demand. Based on the two frequency regulation resources, the active–reactive cooperative control strategy is proposed to adopt the fast response characteristics of ESS to cooperate with the synchronous unit to prioritize frequency regulation and enable the FL reactive control strategy when the system disturbance is larger than the primary frequency regulation capacity of the synchronous unit. The effectiveness of the proposed control strategy for isolated power systems is verified by building a modified IEEE33 node islanding system simulation in the real-time digital simulator (RTDS).

At present, on-line pre-decision and real-time matching control forms are the most widely used emergency control forms in the power system. The safety control system predicts the accidents according to the current operation state of the power grid and sets the emergency control strategy for the predicted accidents to ensure the safety and stability of the power grid when the fault occurs. However, the voltage level controlled by the safety control system is relatively high, which leads to a large granularity of load control. Because load nodes are mainly mixed users of various types, the strategy under large-scale centralized control may include important load nodes. It is necessary to replace the important load with other controllable low voltage nodes in the area to ensure that the load-shedding quantity set by the safety control system can be implemented sufficiently. Most emergency control optimization problems regard the load-shedding cost as a definite and constant value, but in fact, the load-shedding cost will change with the environmental factors. Based on the analysis of the influence of environmental factors on the cost of load shedding, this paper uses the reinforcement learning method to learn historical operation data and adapt to the variability of load-shedding cost to decide the best alternatives. The results of an example show that the proposed method can make replacement decisions in any scene based on adaptive environmental variability and can effectively prevent over-cutting through the design of a precise final reward.

The load characteristics have a significant impact on the static voltage stability analysis of the power grid. Wenshan power grid has a large amount of relatively centralized electrolytic aluminum load, accounting for 65% of the total local load. Due to the different load characteristics of electrolytic aluminum shown in the big closed-loop feedback current stabilizing state, the detailed load characteristics of electrolytic aluminum must be considered when analyzing the static voltage stability of the Wenshan power grid. Firstly, based on the actual production process of electrolytic aluminum, an accurate load characteristic model of electrolytic aluminum under the big closed-loop feedback current stabilizing state is built; secondly, a static voltage stability analysis model on account of the electrolytic aluminum load characteristic is established, and solving this model can obtain the generalized Jacobi matrix J and reduced dimensional Jacobi matrix J1which considers comprehensively the influence of system active and reactive power on the static voltage stability, based on the singular value decomposition theory, the static voltage stability margins MSV-J and MSV-J1 decomposed from the matrix J and J1respectively can be obtained to describe the stability degree of system static voltage accurately. And the effect of adjusting the current stabilizing device on the load characteristics of electrolytic aluminum and the static voltage stability of the system is also studied. Finally, the influence of load characteristics of electrolytic aluminum on the system static voltage stability is analyzed by some examples, and the results indicate that the static voltage stability margin indexes MSV-J and MSV-J1 can well describe the static voltage stability of the grid.

The national ”double carbon” plan promotes the reform of the power system, and large-scale distributed energy is connected to the power system. It is difficult to control the fluctuation of new energy only by the reserve of thermal power units. Therefore, it is urgent to excavate new auxiliary service subjects and increase the flexibility of power grid frequency control. Taking electrolytic aluminum as an example, the traditional high load capacity load has large capacity continuous regulation ability, but it is seldom used in frequency stability control of power grid. Thus this paper proposes the precise coordinated frequency modulation control strategy of electrolytic aluminum load in the case of large N-1 failure. By means of updating the running status of electrolytic aluminum load regularly and calculating the load damping coefficient adaptively, this strategy can realize the rapid response to the system frequency change and ensure that the system frequency fluctuation does not exceed the limit. Finally, we built the regional power grid of Wenshan in Yunnan province and the results verify the feasibility of the effectiveness of the proposed strategy in dealing with DC locking.

With the rapid developments of renewable energy sources, the uncertainty of the power supply will bring new challenges to scheduling problems, and conventional scheduling strategies may lose their effectiveness. The current general scheduling strategies need to model the uncertainty of the environment, while it is difficult to achieve a high degree of accuracy in the power system with high penetration rate of new energy, which will directly affect the scheduling result. In response to this problem, this paper studies the economic dispatch of power systems based on deep deterministic policy gradient (DDPG),which avoids the uncertainty modeling of the environment in principle. Combined with the basic economic dispatch model, this paper has defined a learning mode of the algorithm and built an algorithm framework of economic dispatch of power system based on DDPG. The results of the experiment show that proposed algorithm is highly adaptable to random fluctuation of renewable energy.

Background and objectives: The associations of intrinsic capacity (IC) with dietary diversity and body mass index (BMI) remain unclear in older adults. This study aimed to examine the associations of dietary diversity and BMI on high IC. Methods: The cross-sectional study used data from the Fujian Prospective Aging Cohort, which included 1972 individuals aged 60–98 from 2020 to 2021. The dietary diversity score (DDS) was constructed with eight food varieties, and consuming ≥five varieties of food daily was considered a high DDS. BMI was grouped into underweight, normal weight, overweight, and obesity according to the Chinese guidelines. High IC was defined as ≥three unimpaired domains of cognition, locomotion, sensory, vitality, and psychology. Results: Multivariate logistic regression analysis was used to assess the separate association of high DDS and BMI groups with high IC. Compared with low DDS, high DDS had a positive association with high IC (OR = 1.42, 95 % CI = 1.16–1.74). Compared with normal weight, underweight was inversely related to high IC (OR = 0.18, 95 % CI = 0.09–0.36), overweight was positively related to high IC (OR = 1.65, 95 % CI = 1.33–2.06), while no significant association was observed between obesity and high IC. The restricted cubic spline model exhibited an inverted U-shaped nonlinear curve of BMI and high IC and identified an optimal BMI of 25.7 kg/m2 for high IC. Conclusions: High DDS is a protective factor of high IC in older adults. Overweight had the most protective association with high IC among the four BMI subgroups. Individuals with overweight and higher dietary diversity had higher IC.

Objectives: To analyze the correlations between the expression and effect of DNA damage repair genes and the immune status and clinical outcomes of urothelial bladder cancer (BLCA) patients. In addition, we evaluate the efficacy and value of utilizing the DNA damage repair genes signature as a prognosis model for BLCA. Methods: Two subtype groups (C1 and C2) were produced based on the varied expression of DNA damage repair genes. Significantly differentiated genes and predicted enriched gene pathways were obtained between the two subtypes. Seven key genes were obtained from the DNA damage repair-related genes and a 7-gene signature prognosis model was established based on the key genes. The efficacy and accuracy of this model in prognosis prediction was evaluated and verified in two independent databases. Also, the difference in biological functions, drug sensitivity, immune infiltration and affinity between the high-risk group and low-risk group was analyzed. Results: The DNA damage repair gene signature could significantly differentiate the BLCA into two molecular subgroups with varied genetic expression and enriched gene pathways. Seven key genes were screened out from the 232 candidate genes for prognosis prediction and a 7-gene signature prognosis model was established based on them. Two independent patient cohorts (TCGA cohort and GEO cohort) were utilized to validate the efficacy of the prognosis model, which demonstrated an effective capability to differentiate and predict the overall survival of BLCA patients. Also, the high-risk group and low-risk group derived from the 7-gene model exhibited significantly differences in drug sensitivity, immune infiltration status and biological pathways enrichment. Conclusions: Our established 7-gene signature model based on the DNA damage repair genes could serve as a novel prognosis predictive tool for BLCA. The differentiation of BLCA patients based on the 7-gene signature model may be of great value for the appropriate selection of specific chemotherapy agents and immune-checkpoint blockade therapy administration.

Collagen-based scaffolds lack mechanical strength, flexibility, and tunable pore structure, affecting tissue repair outcomes and restricting their wide clinical application. Here, two kinds of scaffolds were prepared by a combination of vacuum homogenization, natural air drying, water soaking, lyophilization, and crosslinking. Compared with the scaffolds made of collagen molecules (Col-M), the scaffolds made of collagen aggregates (Col-A) exhibited higher mechanical strength (ultimate tensile strength: 1.38 ​± ​0.26 ​MPa vs 15.46 ​± ​1.55 ​MPa), stronger flexibility, advanced cell adhesion, survival, and proliferation. Subcutaneous implantation in rats showed that Col-A scaffolds promoted cell infiltration, macrophage polarization, and vascularization. Furthermore, the Col-A scaffolds inhibited abdominal bulges due to their adequate mechanical support, and they also promoted vascularized muscle regeneration in a rat abdominal hernia defect model. Our study provides a novel strategy for generating high-strength, flexible, porous collagen-based scaffolds, which can be applied to tissue repair with mechanical strength requirements. It broadens their application range in the field of regenerative medicine.

Feature selection is a powerful tool for choosing a feature subset of relevant attributes and has been widely used in many research fields, including power system. In this paper, we have introduced a two-step feature selection algorithm that combines the advantages of Grey Relation Analysis (GRA) and Binary Particle Swarm Optimization (BPSO) search method. The proposed method aims to solve the problem of massive-scale feature selection in power system and find these attributes which are highly related to the target power system scenario. This algorithm would eliminate some features based on GRA correlation coefficient in step 1, and the remaining features would accept further selection in step 2, in the meanwhile, the modified initialization rule based on GRA coefficient would be used to enhance the optimization speed and improve the performance of the final feature subset. The effectiveness of the selected feature subset is evaluated using the classification and prediction accuracy. After some experiments based on actual power system scenario data, our method has shown strong ability to find a subset with high classification accuracy and low dimension, while the predictor also has better forecasting performance when using the selected feature subset, which would help operators to judge the state of the power system, so that they could make some more accurate decisions to improve the safety and stability of the grid.

Introduction: Whereas interpatient heterogeneity in clinical characteristics and treatment outcomes of NSCLC harboring a KRAS mutation is recognized, the characterization of these patients in Asia has been limited. Methods: A multicenter, retrospective cohort study was conducted in eight academic centers across Asia. Patients diagnosed with advanced NSCLC harboring a KRAS mutation and who had received at least one line of anticancer therapy between January 2014 and December 2018 were included. Modified time to next treatment (TTNT) was adopted as a proxy for progression-free survival. Results: A total of 216 patients were analyzed. The median age at diagnosis of advanced NSCLC was 63.3 years, 70.8% were men and 89.8% had adenocarcinoma. KRAS G12D was the most common subtype (25.5%), followed by G12C (24.5%), and G12V (19.4%) The proportion of current or former smokers was 65.7% in the overall population, with 86.8% in G12C and 58.9% in non-G12C subgroups. For all treatments combined for the total population, the first-line duration of therapy, modified TTNT, and TTNT were 4.5 (95% confidence interval: 3.4–5.9), 6.2 (4.9–8.8), and 9.5 (7.1–11.4) months, respectively. The median overall survival for the total population was 10.3 (6.9–12.4) months and was prolonged in patients ever treated with immunotherapy (14.6 [8.6–19.1] versus 7.0 [5.9–10.6] mo, hazard ratio = 0.54, p < 0.001), with left truncation to account for the time of KRAS testing. Conclusions: Whereas treatment outcomes with conventional anticancer therapy are reasonable and immunotherapy looks promising, the unmet need remains high for patients with KRAS-mutated NSCLC in Asia, underscoring the need for novel therapeutic approaches.

Summary: The COVID-19 pandemic has caused over 220 million infections and 4.5 million deaths worldwide. Current risk factor cannot fully explain the diversity in disease severity. Here, we present a comprehensive analysis of a broad range of patients' laboratory and clinical assessments to investigate the genetic contributions to COVID-19 severity. By performing GWAS analysis, we discovered several concrete associations for laboratory traits and used Mendelian randomization (MR) analysis to further investigate the causality of traits on disease severity. Two causal traits, WBC counts and cholesterol levels, were identified based on MR study, and their functional genes are located at genes MHC complex and ApoE, respectively. Our gene-based analysis and GSEA revealed four interferon pathways, including type I interferon receptor binding and SARS coronavirus and innate immunity. We hope that our work will contribute to studying the genetic mechanisms of disease and serve as a useful reference for COVID-19 diagnosis and treatment.

Background: Recent studies showed that immune-checkpoint blockade (ICB) has significantly improved clinical outcomes of melanoma and lung cancer patients. However, only a small subset of patients can benefit from ICB. Deep learning has been successfully implemented in complementary clinical diagnosis. The aim of this study is to demonstrate the potential of deep learning to facilitate the prediction of anti-PD-1 response from H&E images directly. Methods: In this study, 190 H&E slides of melanoma were segmented into 256 × 256 tiles which were used as the training set for the convolutional neural network (CNN). Additional 54 melanoma and 55 lung cancer H&E slides were collected as independent testing sets. Findings: An AUC of 0.778(95% CI: 63.8%-90.5%) was achieved for 54 melanoma testing samples with 15(65.2%) responders and 23(74.2%) non-responders correctly classified. We also obtained an AUC of 0.645(95% CI: 49.4%-78.4%) for 55 lung cancer samples. Interpretation: To our knowledge, this is the first study of using deep learning to determine patients’ anti-PD-1 response from H&E slides directly. Our CNN model achieved the state-of-the-art performance and has the potential to screen ICB beneficial patients in routine clinical practice.

Objective: This study utilized genotypic and in-house recombinant virus phenotypic assays to examine HIV-1 variant susceptibility to antiretroviral (ARV) drugs; comparisons were made between the analyses. Methods: A nested PCR was employed to amplify the HIV-1 gag-pol gene, which comprised the entire PR gene (codons 1–99) and the former RT gene (codons 1–312). Genetic resistance was determined by submitting the sequences to the Stanford University Network HIV-1 Database. Phenotypic susceptibilities to six ARV drugs were measured using a high-throughput, multi-cycle, recombinant virus phenotypic assay. Results were expressed in terms of the IC50 (half maximal inhibitory concentration) and fold-change values. The relationship between phenotypic drug resistance and genetic polymorphisms was determined. Results: Nineteen fragment sequences for which recombinant viruses were successfully constructed were translated and compared with the consensus B sequences in the Stanford University Network HIV-1 Database. No recognizable genotypic resistance-associated mutations were noted, except in one sample. Each homologous replication-competent recombinant viral fold-change in the presence of six ARV drugs used widely in China was measured. According to the clinical and statistical criteria, 16 of the 19 samples were susceptible to the six drugs tested. The majority of phenotypic and genotypic results obtained were in agreement, with a concordance rate of 97.4%. Both phenotypic and genotypic assays suggested that sample HN2009001 was resistant to all drugs tested. All phenotypic and genotypic results obtained regarding the susceptibility of the 19 recombinant viruses to nucleoside reverse transcriptase inhibitors (NRTIs) were in agreement. With regard to the genotypic results for the non-nucleoside reverse transcriptase inhibitors (NNRTIs), 7.9% (3/38) were inconsistent with the phenotypic results. Conclusions: The in-house recombinant virus phenotypic assay was able to provide a straightforward quantitative assessment of resistance. In most cases, the genotypic and novel phenotypic assays yielded similar results. The disparity in HIV-1 susceptibility indicates a need to further investigate the clinical outcomes of antiretroviral therapy in certain individuals.