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Abstract Background This study aimed to investigate the knowledge, attitude and practice (KAP) of pediatric healthcare staff towards the therapy for patients with congenital heart disease (CHD). CHD is a major global health concern, posing significant risks to health and life despite advancements in early detection and treatment. Methods This web-based cross-sectional study was conducted from May 04, 2023 to August 12, 2023 in the Bengbu area (three counties and one city) for pediatric healthcare staff. Correlations between knowledge, attitude and practice scores were evaluated by Pearson correlation analysis. Factors associated with knowledge, attitude and practice scores were identified by multivariate logistic regression. Results A total of 332 valid questionnaires were enrolled, including 258 (77.7%) females, and 161 (48.5%) were pediatrician. The median (25% quartile, 75% quintile) of knowledge, attitude, and practice scores were 38 (36, 40) (possible range: 10—49), 28 (27, 31) (possible range: 7—35), and 35 (32, 39) (possible range: 9—45), respectively. Correlation analysis showed that significant positive correlations were found between knowledge and attitude (r = 0.528, P

Abstract Currently, the global prevalence of myopia is high and on the rise, seriously affecting the health of students. Studies have suggested that dietary factors may be associated with the occurrence and development of myopia, but the results are inconsistent. This survey aims to analyze the correlation between dietary factors and myopia while controlling for more confounding factors. A multi-stage stratified cluster sampling method was performed to select 10,619 primary and secondary school students in Shenyang for visual examination, and questionnaires were administered to 6974 of them. Logistic regression was performed with myopia as the dependent variable and the variables with p

As an excellent means of improving students' effective learning, knowledge tracking can assess the level of knowledge mastery and discover latent learning patterns based on students' historical learning evaluation of related questions. The advantage of knowledge tracking is that it can better organize and adjust students' learning plans, provide personalized guidance, and thus, achieve the purpose of artificial intelligence-assisted education. However, existing methods, for instance, convolutional knowledge tracing, lacking consideration of graph structure and multivariate time-series prediction, result in poor prediction accuracy. Inspired by recent successes of the graph neural network (GNN), we present a novel multivariate graph knowledge tracking (MVGKT) framework to address these limitations. Specifically, a multivariate time-series knowledge tracking system based on spatio-temporal GNN is designed to model student learning trajectories in different spatial and temporal dimensions and capture both temporal dependencies and interstudent correlations. MVGKT incorporates a gate recurrent unit attentive mechanism and graph Fourier transform, discrete Fourier transform, and graph convolution network to increase the predictive accuracy of the student performances. In addition, we design a question difficulty extraction system to obtain information on the difficulty of the questions, and thus, enhance the data features. Numerous experiments on the ASSISTments dataset have demonstrated that MVGKT is superior to existing knowledge-tracking methods on four metrics and has shown that our approach can enhance the predictive accuracy of student performance.

Study DesignA systematic review and Meta-analysisObjectiveTo compare the efficacy and safety of denosumab and teriparatide versus oral bisphosphonates to treat postmenopausal osteoporosis.Summary of Background DataWhile bisphosphonates have historically been the cornerstone of pharmacological management for bone protection in patients, emerging evidence suggests that teriparatide and denosumab warrant further investigation as potential first-line treatments. The optimal choice among denosumab, teriparatide, and oral bisphosphonates for the treatment of postmenopausal osteoporosis remains a subject of ongoing debate and controversy within the scientific community.MethodsThis systematic review adhered meticulously to the rigorous standards outlined by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines as well as the Cochrane Collaboration recommendations. Additionally, it employed the AMSTAR (Assessing the methodological quality of systematic reviews) criteria to ensure methodological robustness and enhance the credibility of the findings. A systematic electronic search was conducted across Web of Science, PubMed, and the Cochrane Library databases from their inception dates up to February 2024.ResultsIn this meta-analysis of studies, our findings suggest that compared to bisphosphonates, both teriparatide and denosumab demonstrated notable increases in percentage changes in lumbar spine bone mineral density (BMD) among postmenopausal osteoporosis patients. Furthermore, denosumab exhibited superiority over teriparatide and oral bisphosphonates in enhancing percentage changes in both femoral neck and total hip BMD, indicating its potential as a more efficacious option. Regarding safety outcomes, no significant differences were observed in the incidence of serious adverse events among patients treated with teriparatide, denosumab, and bisphosphonates. However, teriparatide showed superiority over oral bisphosphonates in terms of a lower risk of general adverse events, suggesting a favorable safety profile.ConclusionIn conclusion, our study suggests that teriparatide and denosumab demonstrate comparable or potentially superior efficacy and safety profiles compared to oral bisphosphonates for the treatment of postmenopausal osteoporosis.Systematic Review RegistrationPROSPERO, identifier CRD42024508382.

IntroductionWhen a distributed photovoltaic (PV) system has access to a large urban distribution network, the active balance is primarily borne by the main network gas unit; when the scale of the distributed PV system is very large, the main network can only provide limited regulation capacity, and the distribution network must determine the active optimal scheduling strategy.MethodsThis work proposes an active optimization scheduling model for the distribution network by considering the regulation capacity of the main network. In terms of the optimisation objectives, the maximum consumption of the distributed PVs and minimum power fluctuation at the demarcation point of the main distribution network are proposed as the main objectives, while the minimum total exchanged power in a cycle at the main distribution demarcation point and minimum distribution network loss are considered as the secondary objectives. In terms of constraints, it is proposed that the main network’s regulation capacity be characterized by the main network’s gas-fired unit creep constraints. A fast solution method for active optimization of the distribution network is designed herein to formulate the priority control order of the adjustable units according to the dispatch economic performances of various types of adjustable resources in the distribution network; this reduces the number of variables involved in the optimization at each step and improves the optimized solution speed.ResultsFinally, Simulation verification by IEEE 33-node distribution network arithmetic example based on Matlab simulation platform.DiscussionSimulation results show the effectiveness of the method in achieving maximum PV consumption and reflecting the limited regulation capacity of the main grid.

Hepatic hemangioma in children is the most common benign angiogenic tumor of the liver in infancy. It is difficult to differentiate hepatic hemangioma from malignant liver tumors in some children, and there is also the possibility of malignant transformation and life-threatening complications. This article reviews the classification, clinical features, diagnosis, treatment, and prognosis of hepatic hemangioma, in order to provide a reference for the clinical diagnosis and treatment of this disease.

Abstract Background Identification of the causes of stroke of undetermined etiology, specifically cardioembolism (CE) and non-CE causes, can inform treatment planning and prognosis prediction. The objective of this study was to analyze the disparities in thrombus composition, particularly Semaphorin-7A (Sema7A) and CD163, between patients diagnosed with large-artery atherosclerosis (LAA) and those with CE, and to investigate their potential association with prognosis. Methods Thrombi were collected from patients who underwent mechanical thrombectomy at two hospitals. The patients were categorized into two groups: LAA and CE. We compared the levels of Sema7A and CD163 between these groups and analyzed their relationships with stroke severity, hemorrhagic transformation and prognosis. Results The study involved a total of 67 patients. Sema7A expression was found to be significantly higher in the CE group compared to LAA (p 0.05). However, both Sema7A (OR, 2.017; 95% CI, 1.301–3.518; p = 0.005) and CD163 (OR, 2.283; 95% CI, 1.252–5.724; p = 0.03) were associated with the poor prognosis for stroke, after adjusting for stroke severity. Conclusion This study highlights that CE thrombi exhibited higher levels of Sema7A expression compared to LAA thrombi. Moreover, we found a positive correlation between Sema7A/CD163 levels and the poor prognosis of patients with acute ischemic stroke.

Demand response (DR) can ensure electricity supply security by shifting or shedding loads, which plays an important role in a power system with a high proportion of renewable energy sources. Industrial loads are vital participants in DR, but it is difficult to assess DR potential because of many complex factors. In this paper, a new method based on fuzzy control is given to assess the DR potential of industrial loads. A complete assessment framework including four steps is presented. Firstly, the industrial load data are preprocessed to mitigate the influence of noisy and transmission losses, and then the K-means algorithm considering the optimal cluster number is used to calculate baseline load of industrial load. Subsequently, an open-loop fuzzy controller is designed to predict the response factor of different industrial loads. Three strongly correlated indicators, namely peak load rate, electricity intensity, and load flexibility, are selected as the input of fuzzy control, which represents response willingness. Finally, the baseline load of diverse clustering scenarios and the response factor are used to calculate the DR potential of different industrial loads. The proposed method takes into account both economic and technical factors comprehensively, and thus, the results better represent the available DR potential in real-world situations. To demonstrate the effectiveness of the proposed method, the case of a medium-sized city in China is studied. The simulation focuses on the top eight industrial types, and the results show they can contribute about 189 MW available DR potential.

Abstract Social insects are prone to pathogen infection because of high exposure rates from social interactions. However, it remains unclear whether queens have enhanced pathogen resistance, because reproduction is largely confined to queens. Here, we used a natural host–pathogen system, the subterranean termite Reticulitermes chinensis and the entomopathogenic fungus Metarhizium anisopliae, to investigate the differences in allogrooming, locomotion, and immune gene expression between queens and workers against pathogen infection. We found that fungal infection significantly reduced survival in both queens and workers. Infected queens received significantly more grooming time from sanitary nestmates than infected workers, but they returned much less grooming time to sanitary nestmates than infected workers. Infection resulted in a reduction in the average locomotion speed and distance of queens but had no effect on worker locomotion. Infection resulted in upregulated expression of two immune genes (termicin and transferrin), two antioxidant genes (CAT and SOD), and phosphate genes CYP450 in queens but not in workers. Our results indicated that eusocial termites evolved strategies that prioritize the reproductive castes' welfare in defending against the pathogen infection to ensure continued reproduction and colony persistence.

IntroductionThe uridine diphosphate (UDP)-glycosyltransferase (UGT) family is the largest glycosyltransferase family, which is involved in the biosynthesis of natural plant products and response to abiotic stress. UGT has been studied in many medicinal plants, but there are few reports on Platycodon grandiflorus. This study is devoted to genome-wide analysis of UGT family and identification of UGT genes involved in drought stress of Platycodon grandiflorus (PgUGTs).MethodsThe genome data of Platycodon grandiflorus was used for genome-wide identification of PgUGTs, online website and bioinformatics analysis software was used to conduct bioinformatics analysis of PgUGT genes and the genes highly responsive to drought stress were screened out by qRT-PCR, these genes were cloned and conducted bioinformatics analysis.ResultsA total of 75 PgUGT genes were identified in P.grandiflorus genome and clustered into 14 subgroups. The PgUGTs were distributed on nine chromosomes, containing multiple cis-acting elements and 22 pairs of duplicate genes were identified. Protein-protein interaction analysis was performed to predict the interaction between PgUGT proteins. Additionally, six genes were upregulated after 3d under drought stress and three genes (PGrchr09G0563, PGrchr06G0523, PGrchr06G1266) responded significantly to drought stress, as confirmed by qRT-PCR. This was especially true for PGrchr06G1266, the expression of which increased 16.21-fold after 3d of treatment. We cloned and conducted bioinformatics analysis of three candidate genes, both of which contained conserved motifs and several cis-acting elements related to stress response, PGrchr06G1266 contained the most elements.DiscussionPgGT1 was confirmed to catalyze the C-3 position of platycodin D and only eight amino acids showed differences between gene PGr008G1527 and PgGT1, which means PGr008G1527 may be able to catalyze the C-3 position of platycodin D in the same manner as PgGT1. Seven genes were highly expressed in the roots, stems, and leaves, these genes may play important roles in the development of the roots, stems, and leaves of P. grandiflorus. Three genes were highly responsive to drought stress, among which the expression of PGrchr06G1266 was increased 16.21-fold after 3d of drought stress treatment, indicating that PGrchr06G1266 plays an important role in drought stress tolerance. To summarize, this study laied the foundation to better understand the molecular bases of responses to drought stress and the biosynthesis of platycodin.

Grain boundary (GB) precipitation-induced cracking is a significant issue for S31254 super austenitic stainless steel during hot working. Investigating the deformation behavior based on precipitate morphology and distribution is essential. In this study, continuous smaller and intermittent larger precipitates were obtained through heat treatments at 950 °C and 1050 °C. The microstructure evolution and mechanical properties influenced by precipitates were experimentally investigated using an in situ tensile stage inside a scanning electron microscope (SEM) combined with electron backscatter diffraction (EBSD). The results showed that continuous precipitates at 950 °C had a stronger pinning effect on the GB, making grain rotation difficult and promoting slip deformation in the plastic interval. Continuous precipitates caused severe stress concentration near GB and reduced coordinated deformation ability. Additionally, the crack propagation path changed from transcrystalline to intercrystalline. Furthermore, internal precipitates were a crucial factor affecting the initial crack nucleation position. Interconnected precipitates led to an intergranular fracture tendency and severe deterioration of the material’s plasticity, as observed in fracture morphology.

Abstract Background and aim DRP1 and OPA1 play important roles in mitochondrial fusion and fission. However, the role of DRP1 and OPA1 amplification in mitochondrial cognitive impairment has not been reported. This study aimed to investigate the relationship between DRP1 and OPA1 and the risk of cognitive impairment. Methods In this study, 45 elderly patients with diabetes admitted to the Lianyungang Second People’s Hospital from September 2020 to January 2021 were included. The patients were divided into normal group, mild cognitive impairment group and dementia group by using MMSE score, and the clinical characteristics of the three groups were compared. The amplification multiples of the two genes’ DNA were calculated by ΔΔCT and defined as 2− K. Spearman rank correlation was used to analyze the correlation between the DNA amplification multiples of patients’ DRP1 and OPA1 and AD8 and MoCA scores. The sensitivity and specificity of DNA amplification multiples of DRP1 and OPA1 to predict clinical outcomes of diabetic cognitive impairment were evaluated using Receiver operator characteristic (ROC) curves. Multiple logistic regression was used to evaluate the relationship between DNA amplification factor of DRP1 and OPA1 and cognitive function. Results DRP1(2− K) and OPA1(2− K) significantly increased and decreased in dementia and MCI groups compared with the normal group (P ≤ 0.001). The DNA amplification factor of DRP1 was positively correlated with AD8 score and negatively correlated with MoCA score (P

BackgroundThe infiltration and activation of immune cells in the tumor microenvironment (TIME) affect the prognosis of patients with cancer. Tertiary lymphoid structure (TLS) formation favors tumour- infiltrating-lymphocyte (TIL) recruitment and is regarded as an important indicator of good prognosis associated with immunotherapy in patients with tumors. Chemotherapy is currently one of the most commonly used clinical treatment methods. However, there have been no clear report to explore the effects of different types of chemotherapy on TLS formation in the TIME. This study examined the effects of immunogenic cell death (ICD)-inducing chemotherapeutics on immune cells, high-endothelial venules (HEV), and TLSs in mouse melanomas.MethodsDoxorubicin (an ICD inducer), gemcitabine (non-ICD inducer), and a combination of the two drugs was delivered intra-peritoneally to B16F1-loaded C57BL/6 mice. The infiltration of immune cells into tumor tissues was evaluated using flow cytometry. HEV and TLS formation was assessed using immunohistochemistry and multiple fluorescent immunohistochemical staining.ResultsDoxorubicin alone, gemcitabine alone, and the two-drug combination all slowed tumor growth, with the combined treatment demonstrating a more pronounced effect. Compared with the control group, the doxorubicin group showed a higher infiltration of CD8+ T cells and tissue-resident memory T cells (TRM) and an increase in the secretion of interferon-γ, granzyme B, and perforin in CD8+ T subsets and activation of B cells and dendritic cells. Doxorubicin alone and in combination with gemcitabine decreased regulatory T cells in the TIME. Moreover, doxorubicin treatment promoted the formation of HEV and TLS. Doxorubicin treatment also upregulated the expression of programmed cell death protein (PD)-1 in CD8+ T cells and programmed cell death protein ligand (PD-L)1 in tumor cells.ConclusionsThese results indicate that doxorubicin with an ICD reaction promotes TLS formation and increases PD-1/PD-L1 expression in tumor tissues. The results demonstrate the development of a therapeutic avenue using combined immune checkpoint therapy.

The localization of electromagnetic radiation leakage through cabin gaps is a critical and challenging aspect of electromagnetic compatibility (EMC) design for spacecraft with complex electromagnetic environments. This paper proposes a localization method based on synthetic aperture interferometric passive radiometry imaging. Electromagnetic radiation signals are measured at a certain distance from the spacecraft surface to form visibility samples. A Fourier transform pair between the visibility sample and the corrected brightness temperature for electromagnetic radiation leakage is established. The spacecraft surface electromagnetic leakage location image is obtained through the inverse Fourier transform. A sparse sampling method based on ant colony optimization was proposed to improve testing efficiency. The impacts of various factors, including positional parameters, positioning accuracy of the test antenna, scanning parameters, and measurement receiver amplitude/phase errors on the imaging results are analyzed. Experiments were conducted on a 1 m × 1 m × 1 m cabin with 51 holes on one surface, and the algorithm proposed in this paper was validated to effectively image and locate electromagnetic leakage points at different frequencies. The effectiveness of sparse sampling was also verified, with a localization accuracy of 90.2% and a testing time savings of 81.9%.

Abstract Objective This study aimed to identify potential biomarkers for prostate cancer (PCa) progression and metastasis, and to discern their biological functions. Methods Bioinformatics methods were used to screen for hub genes. The expression level of key hub genes in PCa was determined and their prognostic significance was examined. A series of functional assays were performed to investigate the function of the highest-ranking hub gene. Results Actin related protein 2/3 complex subunit 1A (ARPC1A) was identified as the hub gene. ARPC1A was highly expressed in PCa tissues and cell lines, and was an independent prognostic factor for predicting biochemical recurrence after radical prostatectomy and overall survival of PCa patients. Knockdown of ARPC1A inhibited PCa cell migration, invasion and cytoskeleton formation, but had no impact on cell proliferation and cell cycle progression. In vivo, ARPC1A overexpression promoted lung metastasis of PCa, but had no efffect on tumor growth. Additionally, glutamine metabolism was identified as an upstream regulator of ARPC1A, and promoted migration, invasion and cytoskeletal changes of PCa cell through ARPC1A. Conclusion These findings suggested that ARPC1A, which correlates with poor prognosis in PCa, functions downstream of glutamine metabolism to regulate cytoskeletal changes, cellular migration and cellular invasion in this disease.

Abstract Background and purpose Cerebral small vessel disease (CSVD) is a common cause of stroke and senile vascular cognitive impairment, imposing a heavy burden on public health care systems worldwide. Hypertension and 24-hour blood pressure variability (BPV), known to be significant risk factors for cognitive dysfunction, have been found to be associated with cognitive function in CSVD patients in previous studies. However, as a derived part of BPV, there are few studies on the relationship between circadian rhythm of blood pressure and cognitive dysfunction in CSVD patients, and the relationship between them is still unclear. Thus, this study aimed to investigate whether the disturbance of circadian rhythm of blood pressure can affect the cognitive function of patients with CSVD. Methods A total of 383 CSVD patients hospitalized in the Geriatrics Department of the Lianyungang Second People’s Hospital between May 2018 and June 2022 were enrolled in this study. The clinical information and parameters of 24-hour ambulatory blood pressure monitoring were compared between the cognitive dysfunction group (n = 224) and the normal group (n = 159). Finally, a binary logistic regression model was used to assess the relationship between circadian rhythm of blood pressure and cognitive dysfunction in patients with CSVD. Results (1) Patients in the cognitive dysfunction group were older, had lower blood pressure on admission, and had a greater number of previous cardiovascular and cerebrovascular diseases (P

Although traditional convolutional neural networks (CNN) have been significantly improved for target detection, they cannot be completely applied to objects with occlusions in commodity detection. Therefore, we propose a target detection method based on an improved YOLOv5 model and an improved attention mechanism algorithm is proposed to solve the commodity occlusion problem. This method improves the traditional YOLO deep convolution network, features a more detailed BiFPN layer, and performs lightweight two-way feature fusion, where the multidimensional features of the commodities are convolved and fused, thus improving the overall detection speed and accuracy of the YOLO-R algorithm. Feature entropy is introduced to the attention channel to restrict the threshold value and obtain the global information of the occlusion target. The global information obtained is fused with a bidirectional feature pyramid layer to enhance the robustness of the features. This method could accurately and quickly detect the occluded commodities and the detection accuracy has been greatly improved. Experiments show that the improved YOLO-R model can improve the accuracy and speed of commodity detection, and can achieve good results in objective evaluation. The average accuracy of commodity detection on the self-made product dataset is up to 97.80%, and the detection rate is 22.72F/s. Therefore, the method in this paper has high detection accuracy and fast detection speed.

Abstract With the rapid increase of the penetration rate of renewable energy sources in power system, the decrease of system inertia will threaten the frequency stability, and the dispersion of frequency response cannot be ignored. This paper proposes a method to estimate area inertia of power system containing wind power considering dispersion of frequency response. Firstly, the impact of inertia distribution between areas on the frequency stability and the inter‐area oscillation are analysed. Secondly, the system is divided based on the spectral clustering algorithm and the frequency similarity index is defined according to the Pearson correlation coefficient to determine the measurement locations for area frequency. Thirdly, the measured tie‐line power and frequency deviation are used to estimate the area inertia based on the numerical integration method. Finally, the case study is conducted based on the modified IEEE 39‐bus system. The simulation results revealed that the proposed method is accurate and reliable in different scenarios.

Wind power forecast is becoming more and more important as the ever-increasing penetration of renewable energies brings uncertainties to the power systems. Although the numerical weather prediction (NWP) has already been widely applied on wind power forecast, it involves high computational burden with complex meteorological models, which has great uncertainty in real environment, so machine learning methods are the significant supplement for accurate wind power forecast. This paper proposes a deep learning model to improve the prediction accuracy based on the NWP data. Variational Mode Decomposition (VMD) is applied to extract time-series information. Furthermore, an encoder–decoder structure consisting of a dual attention-long short term memory (LSTM) neural network is constructed to enhance the forecasting accuracy. The comparison between the proposed model and several benchmark models, show the superiority of proposed model in effectively enhancing the prediction performance.

Abstract Objective To investigate the impact of N-terminal pro-B-type natriuretic peptide (NT-proBNP) on CTP infarct core volume and poor 90-day functional outcomes in acute ischemic stroke (AIS). Methods A total of 403 hospitalized patients with AIS in the Stroke Center of the First Hospital Affiliated to Soochow University were enrolled from March 2018 to January 2021. The association between NT-proBNP and clinical outcomes in acute ischemic patients was assessed by logistic regression and adjusted for confounding factors. Also, subgroup analyses were conducted based on treatment decisions. Results NT-proBNP was positively correlated with CTP ischemic volume (p

BackgroundAlthough many efforts have been devoted to identify biomarkers to predict the responsiveness of immune checkpoint inhibitors, including expression of programmed death-ligand 1 (PD-L1) and major histocompatibility complex (MHC) I, microsatellite instability (MSI), mismatch repair (MMR) defect, tumor mutation burden (TMB), tertiary lymphoid structures (TLSs), and several transcriptional signatures, the sensitivity of these indicators remains to be further improved.Materials and methodsHere, we integrated T-cell spatial distribution and intratumor transcriptional signals in predicting the response to immune checkpoint therapy in MMR-deficient tumors including tumors of Lynch syndrome (LS).ResultsIn both cohorts, MMR-deficient tumors displayed personalized tumor immune signatures, including inflamed, immune excluded, and immune desert, which were not only individual-specific but also organ-specific. Furthermore, the immune desert tumor exhibited a more malignant phenotype characterized by low differentiation adenocarcinoma, larger tumor sizes, and higher metastasis rate. Moreover, the tumor immune signatures associated with distinct populations of infiltrating immune cells were comparable to TLSs and more sensitive than transcriptional signature gene expression profiles (GEPs) in immunotherapy prediction. Surprisingly, the tumor immune signatures might arise from the somatic mutations. Notably, patients with MMR deficiency had benefited from the typing of immune signatures and later immune checkpoint inhibition.ConclusionOur findings suggest that compared to PD-L1 expression, MMR, TMB, and GEPs, characterization of the tumor immune signatures in MMR-deficient tumors improves the efficiency of predicting the responsiveness of immune checkpoint inhibition.

With wind power integrated into the power system on a large scale, the system has become vulnerable to the frequency stability issue. The battery energy storage system (BESS) is considered the key solution to improving the system frequency regulation performance due to its fast response ability. Furthermore, the construction of wind-storage combined frequency regulation systems has been developed for many years, in which the optimal capacity configuration of the wind-storage system is getting more attention. However, the secondary frequency drop (SFD) caused by wind turbines (WTs) participating in primary frequency regulation (PFR) is neglected in most existing capacity configurations, which is worthy of further study. In this paper, the optimal capacity of the wind-storage combined frequency regulation system is studied from the perspective of SFD. The time-domain expressions of two-stage system frequency response considering SFD are derived based on the wind-storage combined frequency regulation model. Next, considering the technical and economic characteristics of wind-storage combined frequency regulation, an optimization model of the energy storage capacity configuration is established with the objective of minimizing the sum of the maximum frequency deviations in two stages and the energy storage cost. The optimization model is solved by the multi-objective salp swarm algorithm (MSSA) to obtain the setting value of wind-storage combined frequency regulation parameters and the optimal energy storage capacity. The effectiveness of the proposed method is verified in MATLAB. The simulation results show that the proposed model can effectively improve the frequency regulation effect of the system and ensure the optimal capacity configuration with better economy.

We utilized a first-principle density functional theory for a comprehensive analysis of CsPbX3 (X = F, Cl, Br, I) to explore its physical and chemical properties, including its mechanical behavior, electronic structure and optical properties. Calculations show that all four materials have good stability, modulus of elasticity, hardness and wear resistance. Additionally, CsPbX3 demonstrates a vertical electron leap and serves as a semiconductor material with direct band gaps of 3.600 eV, 3.111 eV, 2.538 eV and 2.085 eV. In examining its optical properties, we observed that the real and imaginary components of the dielectric function exhibit peaks within the low-energy range. Furthermore, the dielectric function gradually decreases as the photon energy increases. The absorption spectrum reveals that the CsPbX3 material exhibits the highest UV light absorption, and as X changes (with the increase in atomic radius within the halogen group of elements), the light absorption undergoes a red shift, becoming stronger and enhancing light utilization. These properties underscore the material’s potential for application in microelectronic and optoelectronic device production. Moreover, they provide a theoretical reference for future investigations into CsPbX3 materials.

The acid-induced gelation of pectin in potato cell walls has been gradually recognized to be related to the improvement in the cell wall integrity after heat processing. The aim of this study was to characterize the acid-induced gelation of original pectin from a potato cell wall (OPP). Rheological analyses showed a typical solution–sol–gel transition process of OPP with different additions of gluconic acid-δ-lactone (GDL). The gelation time (Gt) of OPP was significantly shortened from 7424 s to 2286 s. The complex viscosity (η*) of OPP gradually increased after 4000 s when the pH was lower than 3.13 and increased from 0.15 to a range of 0.20~6.3 Pa·s at 9000 s. The increase in shear rate caused a decrease in η, indicating that OPP belongs to a typical non-Newtonian fluid. Furthermore, a decrease in ζ-potential (from −21.5 mV to −11.3 mV) and an increase in particle size distribution (from a nano to micro scale) was observed in OPP after gelation, as well as a more complex (fractal dimension increased from 1.78 to 1.86) and compact (cores observed by cryo-SEM became smaller and denser) structure. The crystallinity of OPP also increased from 8.61% to 26.44%~38.11% with the addition of GDL. The above results call for an investigation of the role of acid-induced OPP gelation on potato cell walls after heat processing.

Background and purposePrevious studies demonstrated that elevated brain natriuretic peptide (BNP) level is associated with adverse clinical outcomes of acute cerebral infarction (ACI). Researchers hypothesized that BNP might be a potential neuroprotective factor against cerebral ischemia because of the antagonistic effect of the natriuretic peptide system on the renin-angiotensin system and regulation of cardiovascular homeostasis. However, whether decreasing the BNP level can improve the prognosis of ACI has not been studied yet. The main effect of sacubitril/valsartan is to enhance the natriuretic peptide system. We investigated whether the intervention of plasma BNP levels with sacubitril/valsartan could improve the prognosis of patients with ACI.MethodsIn a randomized, controlled, parallel-group trial of patients with ACI within 48 hours of symptom onset and need for antihypertensive therapy, patients have randomized within 24 hours to sacubitril/valsartan 200mg once daily (the intervention group) or to conventional medical medication (the control group). The primary outcome was a change in plasma BNP levels before and after sacubitril/valsartan administration. The secondary outcomes included plasma levels of brain-derived neurotrophic factor (BDNF), Corin and neprilysin (NEP) before and after medication, the modified Rankin scale, and the National Institutes of Health Stroke Scale (at onset, at discharge, 30 days, and 90 days after discharge).ResultsWe evaluated 80 eligible patients admitted to the Stroke Center of Lianyungang Second People's Hospital between 1st May, 2021 and 31st June, 2022. Except for 28 patients excluded before randomization and 14 patients who did not meet the criteria or dropped out or lost to follow-up during the trial, the remaining 38 patients (intervention group: 17, control group: 21) had well-balanced baseline features. In this trial, we found that plasma BNP levels (P = 0.003) decreased and NEP levels (P = 0.006) increased in enrolled patients after treatment with sacubitril/valsartan. There were no differences in plasma BDNF and Corin levels between the two groups. Furthermore, no difference in functional prognosis was observed between the two groups (all P values>0.05).ConclusionsSacubitril/valsartan reduced endogenous plasma BNP levels in patients with ACI and did not affect their short-term prognosis.

Platycodon grandiflorus, a perennial flowering plant widely distributed in China and South Korea, is an excellent resource for both food and medicine. The main active compounds of P. grandiflorus are triterpenoid saponins. WRKY transcription factors (TFs) are among the largest gene families in plants and play an important role in regulating plant terpenoid accumulation, physiological metabolism, and stress response. Numerous studies have been reported on other medicinal plants; however, little is known about WRKY genes in P. grandiflorus. In this study, 27 PgWRKYs were identified in the P. grandiflorus transcriptome. Phylogenetic analysis showed that PgWRKY genes were clustered into three main groups and five subgroups. Transcriptome analysis showed that the PgWRKY gene expression patterns in different tissues differed between those in Tongcheng City (Southern Anhui) and Taihe County (Northern Anhui). Gene expression analysis based on RNA sequencing and qRT-PCR analysis showed that most PgWRKY genes were expressed after induction with methyl jasmonate (MeJA). Co-expressing PgWRKY genes with triterpenoid biosynthesis pathway genes revealed four PgWRKY genes that may have functions in triterpenoid biosynthesis. Additionally, functional annotation and protein-protein interaction analysis of PgWRKY proteins were performed to predict their roles in potential regulatory networks. Thus, we systematically analyzed the structure, evolution, and expression patterns of PgWRKY genes to provide an important theoretical basis for further exploring the molecular basis and regulatory mechanism of WRKY TFs in triterpenoid biosynthesis.

Abstract Background To investigate the renal dysfunction in patients with hyperuricemia by employing a multiparametric MRI protocol, consisting of quantitative water molecule diffusion, microstructure, microscopic perfusion, and oxygenation measurements in kidneys. Materials and methods A total of 48 patients with hyperuricemia (HU) and 22 age-matched healthy control subjects (HC) were enrolled in the study. For each participant, three different functional magnetic resonance imaging (fMRI) sequences were acquired and analyzed, including intravoxel incoherent motion imaging (IVIM), diffusion tensor imaging (DTI), and blood-oxygen-level-dependent MRI (BOLD). Thereafter, an independent two-sample t-test was applied to discover the significant differences of MRI indices between the hyperuricemia (HU) and HC groups, and the specific potential biomarkers between two subgroups of HU group (asymptomatic hyperuricemia group (AH) and gouty arthritis group (GA)). Further, multivariate logistic regression analyses were performed to classify the AH from the GA group using the MRI indices with significant between-group differences. The receiver operating characteristic (ROC) curve was plotted, and the area under the ROC curve (AUC) was calculated to assess the performance of each MR index for differentiation between the AH and GA groups. Results Ten parametric values of the HU group were significantly lower than those of the HC group among the 14 fMRI parameters (P

BackgroundWe aimed to investigate the biological mechanism and feature genes of Duchenne muscular dystrophy (DMD) by multi-omics and experimental verification strategy.MethodsWe integrated the transcriptomic and proteomic methods to find the differentially expressed mRNAs (DEMs) and proteins (DEPs) between DMD and Control groups. Weighted gene co-expression network analysis (WGCNA) was then used to identify modules of highly correlated genes and hub genes. In the following steps, the immune and stromal cells infiltrations were accomplished by xCELL algorithm. Furthermore, TF and miRNA prediction were performed with Networkanalyst. ELISA, western blot and external datasets were performed to verify the key proteins/mRNAs in DMD patient and mouse. Finally, a nomogram model was established based on the potential biomarkers.Results4515 DEMs and 56 DEPs were obtained from the transcriptomic and proteomic study respectively. 14 common genes were identified, which is enriched in muscle contraction and inflammation-related pathways. Meanwhile, we observed 33 significant differences in the infiltration of cells in DMD. Afterwards, a total of 22 miRNAs and 23 TF genes interacted with the common genes, including TFAP2C, MAX, MYC, NFKB1, RELA, hsa-miR-1255a, hsa-miR-130a, hsa-miR-130b, hsa-miR-152, and hsa-miR-17. In addition, three genes (ATP6AP2, CTSS, and VIM) showed excellent diagnostic performance on discriminating DMD in GSE1004, GSE3307, GSE6011 and GSE38417 datasets (all AUC > 0.8), which is validated in patients (10 DMD vs. 10 controls), DMD with exon 55 mutations, mdx mouse, and nomogram model.ConclusionTaken together, ATP6AP2, CTSS, and VIM play important roles in the inflammatory response in DMD, which may serve as diagnostic biomarkers and therapeutic targets.

Ataxia with oculomotor apraxia type 1 (AOA1) is a rare genetic disorder and is inherited in an autosomal recessive manner. It is mainly characterized by childhood-onset progressive cerebellar ataxia, with dysarthria and gait disturbance being the two most common and typical manifestations. Axonal sensorimotor peripheral neuropathy, dystonia, chorea, and cognitive impairment are common associated symptoms, as are hypoalbuminemia and hypercholesterolemia. Oculomotor apraxia (OMA)has been reported to be a feature often, although not exclusively, associated with AOA1. The Aprataxin gene, APTX, is ubiquitously expressed, and numerous APTX mutations are associated with different clinical phenotypes have been found. In the present study, we enrolled a 14-year-old boy who developed ataxia with staggering gait from the age of 4 years. Early-onset cerebellar ataxia, peripheral axonal neuropathy, cognitive impairment and hypoalbuminemia, hypercholesterolemia were presented in this patient, except for OMA. We applied ataxia-related genes filtering strategies and whole-exome sequencing (WES) to discover the genetic factors in a Chinese family. Sanger sequencing was used in the co segregation analysis in the family members. A compound heterozygous mutation in APTX gene (c.739C>T and c.501dupG) was identified. This is the first description of a genetically confirmed patient of AOA1 in a Chinese family in addition to a novel mutation of c.501dupG in APTX.

Understanding building metabolism is critical for guiding urban resource management and addressing challenges in urban sustainable development. Key attributes of buildings, including geolocation, footprint, height, and vintage, are crucial to characterizing spatiotemporal patterns of building metabolism. However, these attributes are usually challenging to obtain broadly and automatically, which obscures a comprehensive understanding and accurate assessment of urban metabolism. Moreover, the lack of a finer spatial pattern of these attributes shadows a spatially explicit characterization of material stock and flow in cities. In this study, we took Shenzhen—whose urbanization over the past three decades has been unprecedented in China and even around the world— has been taken as an example to develop a city-level building dataset based on a random-forest model and quantify the spatiotemporal patterns of material metabolism at relatively high spatial resolution (in 500 m × 500 m grids) by combing material flow analysis (MFA) with geographic information system (GIS). The results show that Shenzhen grew from a small town with 281.02 × 106 m3 of buildings in the 1990s to a mega-city with 3585.5 × 106 m3 of buildings in 2018 and expanded both outward and upward from downtown to suburban areas. The urban “weight” (material stock) increased from 92.69 Mt in the 1990s to 1667.8 Mt in 2018 and tended to be saturated, with an average growth rate of 9.5% per year. Spatially, the south-central areas were the largest container of material stocks and generated the most demolition waste. The spatially explicit maps of building three-dimensional (3-D) form and vintage provide detailed information for architectural conservation and could support the decision-making for urban renewal planning. The spatiotemporal patterns of in-use material stocks and potential generation of construction and demolition waste (CDW) provide a benchmark of environmental risk assessment and potential secondary resources to reduce “original” material consumption, which could help alter urban renewal to an environmental-friendly and sustainable trajectory.

17a-Hydroxylase/17,20-lyase deficiency (17OHD) is caused by pathogenic mutations in CYP17A1. Female patients present with hypertension, hypokalemia, and sexual infantilism while males present with sex development disorder. Moyamoya disease (MMD) is a chronic cerebrovascular disease that frequently results in intracranial ischemia or hemorrhage. The present study describes a case of 17OHD and MMD in a 27-year-old phenotypically female (46, XY) patient and discusses the clinical features and characteristics of her genetic defect. Clinical, hormonal, radiological, and genetic analyses were performed and blood samples were collected for whole-exome sequencing (WES). The results of the WES revealed a homozygous intronic mutation (c.297+2T>C) in CYP17A1, which led to combined 17a-hydroxylase/17,20-lyase deficiency, as well as novel variants in PCNT and CNOT3 that might lead to MMD. To our knowledge, this study is the first to describe 17OHD accompanied by MMD. While several cases have previously described patients with 17OHD with histories of cerebral hemorrhage or cerebral ischemia, a correlation in genetic levels between 17OHD and MMD was not found. The risk of cerebrovascular accidents should be considered in patients with 17OHD and hypertension. Cerebrovascular examination in patients with 17OHD may be beneficial for the prevention of life-threatening intracranial vascular disease.

The deleterious effects of methamphetamine (METH) exposure extend beyond abusers, and may potentially impact the vulnerability of their offspring in developing addictive behaviors. Epigenetic signatures have been implicated in addiction, yet the characteristics to identify prenatal METH abuse to offspring addiction risk remains elusive. Here, we used escalating doses of METH-exposed mouse model in F0 female mice before and during pregnancy to simulate the human pattern of drug abuse and generated METH-induced behavioral sensitization to investigate the addictive behavior in offspring mice. We then utilized whole genome-bisulfite sequencing (WGBS) to investigate the methylation signature of nucleus accumbens (NAc) in male METH-sensitized mice. Interestingly, male but not female offspring exhibited an enhanced response to METH-induced behavioral sensitization. Additionally, the METH-exposed group of male mice underwent a more comprehensive wave of epigenome remodeling over all genomic elements compared with unexposed groups due to drug exposure history. 104,219 DMCs (METH-SAL vs. SAL-SAL) induced by prenatal METH-exposure were positively correlated with that of postnatal METH-exposure (38,570, SAL-METH vs. SAL-SAL). Moreover, 4,983 DMCs induced by pre- and postnatal METH exposure (METH-METH vs. SAL-METH) were negatively correlated with that of postnatal METH exposure, and 371 commonly changed DMCs between the two comparison groups also showed a significantly negative correlation and 86 annotated genes functionally enriched in the pathways of neurodevelopment and addiction. Key annotated genes included Kirrel3, Lrpprc, and Peg3, implicated in neurodevelopmental processes, were down-regulated in METH-METH group mice compared with the SAL-METH group. Taken together, we render novel insights into the epigenetic correlation of drug exposure and provide evidence for epigenetic characteristics that link maternal METH exposure to the intensity of the same drug-induced behavioral sensitization in adult offspring.

Abstract Background Middle-aged females, especially perimenopausal females, are vulnerable to depression, but the potential mechanism remains unclear. Dopaminergic and GABAergic system dysfunction is involved in the pathophysiology of depression. In the current study, we used 2-month-old and 11-month-old C57BL/6 mice as young and middle-aged mice, respectively. Chronic immobilization stress (CIS) was used to induce depressive-like behaviour, and the sucrose preference test (SPT), tail suspension test (TST) and forced swim test (FST) were used to assess these behaviours. We then measured the mRNA levels of dopamine receptor D1 (DRD1) and the GABAA receptors GABRA1, GABRB2 and GABRG2 in the nucleus accumbens (NAc) and prefrontal cortex (PFC). Results We found that immobility time in the FST was significantly increased in the middle-aged mice compared with the middle-aged control mice and the young mice. In addition, the preference for sucrose water was reduced in the middle-aged mice compared with the middle-aged control mice. However, CIS did not induce obvious changes in the performance of the young mice in our behavioural tests. Moreover, the middle-aged mice exhibited equal immobility times as the young mice in the absence of stress. Decreases in the mRNA levels of DRD1, GABRA1, and GABRB2 but not GABRG2 were found in the NAc and PFC in the middle-aged mice in the absence of stress. Further decreases in the mRNA levels of DRD1 in the NAc and GABRG2 in the NAc and PFC were found in the middle-aged mice subjected to CIS. Conclusions Our results suggested that ageing could not directly induce depression in the absence of stress. However, ageing could induce susceptibility to depression in middle-aged mice in the presence of stress. CIS-induced decreases in DRD1 and GABRG2 levels might be involved in the increase in susceptibility to depression in this context.

In austenitic steels, the co-segregation of C and Cr at grain boundaries can result in the formation of Cr23C6. However, the addition of B to steels can effectively reduce the amount of Cr23C6 formed and inhibit its ripening in experiments, simultaneously transforming it into Cr23(BC)6. Therefore, the effect of B on the co-segregation of C and Cr at the Σ5(210), Σ9(221) and Σ11(113) grain boundaries in austenitic steels was investigated using density functional theory. The results indicate that B, C, and Cr all tend to segregate at the three grain boundaries, with B and C showing a stronger segregation tendency. Furthermore, co-segregation of C and Cr with short distances occurs readily at the Σ5(210), Σ9(221) and Σ11(113) grain boundaries. The presence of B at grain boundaries can impede the segregation of Cr, particularly at the Σ9(221) and Σ11(113) grain boundaries. When B is pre-segregating at the Σ5(210) grain boundary, B, C, and Cr tend to co-segregate at the grain boundary. The grain boundary B hinders the accumulation of Cr near it for most grain boundaries, thereby inhibiting the co-segregation of Cr and C, making it difficult for B, C, and Cr to aggregate at most grain boundaries. This is beneficial for controlling the nucleation of Cr23(BC)6.