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Abstract Purpose The present study aimed to investigate the clinical characteristics and lung function impairment in young people diagnosed with chronic obstructive pulmonary disease (COPD). Patients and methods We retrospectively enrolled patients with COPD who underwent symptom assessment and comprehensive pulmonary function tests at the First Affiliated Hospital of Guangzhou Medical University between August 2017 and March 2022. The patients were categorized into two groups based on age: a young COPD group (aged 20–50 years) and an old COPD group (aged > 50 years). Results A total of 1282 patients with COPD were included in the study, with 76 young COPD patients and 1206 old COPD patients. Young COPD patients exhibited a higher likelihood of being asymptomatic, lower rates of smoking, and a lower smoking index compared to old COPD patients. Although young COPD patients had higher median post-bronchodilator forced expiratory volume in 1 s (post-BD FEV1) (1.4 vs.1.2 L, P = 0.019), diffusing capacity of the lung for carbon monoxide (DLCO) (7.2 vs. 4.6, P 120%) between two groups. Surprisingly, the prevalence of reduced DLCO was found to be 71.1% in young COPD, although lower than in old COPD (85.2%). Conclusion Young COPD showed fewer respiratory symptoms, yet displayed a similar severity distribution by GOLD categories. Furthermore, a majority of them demonstrated lung hyperinflation and reduced DLCO. These results underscore the importance of a comprehensive assessment of lung function in young COPD patients.

Abstract Hydraulic technology with smaller sizes and higher reliability trends, including fault prediction and intelligent control, requires high-performance temperature and pressure-integrated sensors. Current designs rely on planar wafer- or chip-level integration, which is limited by pressure range, chip size, and low reliability. We propose a small-size temperature/high-pressure integrated sensor via the flip-chip technique. The pressure and temperature units are arranged vertically, and the sensing signals of the two units are integrated into one plane through silicon vias and gold–gold bonding, reducing the lateral size and improving the efficiency of signal transmission. The flip-chip technique ensures a reliable electrical connection. A square diaphragm with rounded corners is designed and optimised with simulation to sense high pressure based on the piezoresistive effect. The temperature sensing unit with a thin-film platinum resistor measures temperature and provides back-end high-precision compensation, which will improve the precision of the pressure unit. The integrated chip is fabricated by MEMS technology and packaged to fabricate the extremely small integrated sensor. The integrated sensor is characterised, and the pressure sensor exhibits a sensitivity and sensitivity drift of 7.97 mV/MPa and −0.19% FS in the range of 0–20 MPa and −40 to 120 °C. The linearity, hysteresis, repeatability, accuracy, basic error, and zero-time drift are 0.16% FS, 0.04% FS, 0.06% FS, 0.18% FS, ±0.23% FS and 0.04% FS, respectively. The measurement error of the temperature sensor and temperature coefficient of resistance is less than ±1 °C and 3142.997 ppm/°C, respectively. The integrated sensor has broad applicability in fault diagnosis and safety monitoring of high-end equipment such as automobile detection, industrial equipment, and oil drilling platforms.

ObjectiveTo evaluate the value of ultrasound in tip location of tunnel-cuffed central venous catheter through internal jugular vein.MethodsFrom February 2022 to July 2023, 42 patients of chronic renal failure and uremia were admitted for internal jugular vein tunnel insertion with cuff central venous catheter. They were randomized into two groups of ultrasound and control. Tip of catheter was located by ultrasound during operation in ultrasound group and tip of catheter by chest radiograph in control group. Postoperative chest computed tomography (CT) was performed in both groups to determine the tip of catheter. Demographic data, clinical laboratory tests and intraoperative parameters were recorded for examining the differential accuracy of catheter tip between two methods.ResultsNo significant inter-group differences existed in age, gender, body mass index (BMI), primary disease, history of catheterization or laboratory tests (P>0.05). And significant inter-group differences existed in ectopic rate of catheter tip, puncture time and puncture complications (P

Abstract Background The purpose of this research is to study the sonographic and clinicopathologic characteristics that associate with axillary lymph node metastasis (ALNM) for pure mucinous carcinoma of breast (PMBC). Methods A total of 176 patients diagnosed as PMBC after surgery were included. According to the status of axillary lymph nodes, all patients were classified into ALNM group (n = 15) and non-ALNM group (n = 161). The clinical factors (patient age, tumor size, location), molecular biomarkers (ER, PR, HER2 and Ki-67) and sonographic features (shape, orientation, margin, echo pattern, posterior acoustic pattern and vascularity) between two groups were analyzed to unclose the clinicopathologic and ultrasonographic characteristics in PMBC with ALNM. Results The incidence of axillary lymph node metastasis was 8.5% in this study. Tumors located in the outer side of the breast (upper outer quadrant and lower outer quadrant) were more likely to have lymphatic metastasis, and the difference between the two group was significantly (86.7% vs. 60.3%, P = 0.043). ALNM not associated with age (P = 0.437). Although tumor size not associated with ALNM(P = 0.418), the tumor size in ALNM group (32.3 ± 32.7 mm) was bigger than non-ALNM group (25.2 ± 12.8 mm). All the tumors expressed progesterone receptor (PR) positively, and 90% of all expressed estrogen receptor (ER) positively, human epidermal growth factor receptor 2 (HER2) were positive in two cases of non-ALNM group. Ki-67 high expression was observed in 36 tumors in our study (20.5%), and it was higher in ALNM group than non-ALNM group (33.3% vs. 19.3%), but the difference wasn’t significantly (P = 0.338). Conclusions Tumor location is a significant factor for ALNM in PMBC. Outer side location is more easily for ALNM. With the bigger size and/or Ki-67 higher expression status, the lymphatic metastasis seems more likely to present.

Background: Stroke is the second leading cause of death for all human beings and poses a serious threat to human health. Environmental exposure to a mixture of metals may be associated with the occurrence and development of stroke, but the evidence in the Chinese population is not yet conclusive. Objectives: This study evaluated the association between stroke risk and 13 metals Methods: Metal concentrations in whole blood samples from 100 stroke cases and 100 controls were measured by ICP-MS. The cumulative impact of mixed metal on stroke risk was investigated by using three statistical models, BKMR, WQS and QGC. Results: The case group had higher concentrations of Mg, Mn, Zn, Se, Sn, and Pb than the control group (p

Abstract Background Anticipating the postoperative pathological stage and potential for adverse features of prostate cancer (PCa) patients before radical prostatectomy (RP) is crucial for guiding perioperative treatment. Methods A cohort consisting of three sub‐cohorts with a total of 709 patients has been enlisted from two major tertiary medical centres in China. The primary assessment parameters for adverse pathological features in this study are the pathological T stage, the AJCC prognostic stage groups and perineural invasion (PNI). Logistic regression analyses were performed to investigate the relationship between prostate specific antigen (PSA), its derivatives (incluing Prostate Health Index, phi and phi density, phiD), and the pathological outcomes after RP. Results Both phi and phiD showed a significant association with pathologic T stage of pT3 or above (phi, adjusted OR, AOR = 2.82, 95% confidence interval, 95% CI: 1.88–4.23, p

Background Beat‐to‐beat blood pressure variability (BPV) is based on each heartbeat and represents a dynamic equilibrium process modulated by artery and cardiac involvement of pressure‐receptive reflexes. To date, there remains a lack of prospective studies illustrating the clinical value of beat‐to‐beat BPV within 24 hours of acute ischemic stroke onset. Methods and Results This study prospectively monitored beat‐to‐beat blood pressure and heart rate in patients with acute ischemic stroke within 24 hours of onset using a noninvasive plethysmograph and calculated beat‐to‐beat BPV, heart rate variability, and the cross‐correlation baroreflex sensitivity. A modified Rankin Scale score of ≥2 at 90 days was defined as an unfavorable prognosis. Multivariate logistic regression was performed, and the nomogram model was developed by adding the beat‐to‐beat BPV to the traditional model for predicting prognosis. Beat‐to‐beat BPV increased significantly in the unfavorable outcome group (P0.05). Furthermore, beat‐to‐beat BPV within 24 hours of acute ischemic stroke onset was independently associated with unfavorable outcome at 90 days (P

Hepatocyte transplantation is an effective treatment for end-stage liver disease. However, due to the limited supply of human hepatocytes, porcine hepatocytes have garnered attention as a potential alternative source. Nonetheless, traditional primary porcine hepatocytes exhibit certain limitations in function maintenance and in vitro proliferation. This study has discovered that by using histone deacetylase inhibitors (HDACi), primary porcine hepatocytes can be successfully reprogrammed into liver progenitor cells with high proliferative potential. This method enables porcine hepatocytes to proliferate over an extended period in vitro and exhibit increased susceptibility in lentivirus-mediated gene modification. These liver progenitor cells can readily differentiate into mature hepatocytes and, upon microencapsulation transplantation into mice with acute liver failure, significantly improve the survival rate. This research provides new possibilities for the application of porcine hepatocytes in the treatment of end-stage liver disease.

Abstract Background Urinary incontinence symptoms severely affect older people with different body mass index (BMI).To compare the efficacy of the pelvic floor muscle training (PFMT) in patients with post-prostatectomy incontinence with different BMI. Methods Thirty-seven patients with post-prostatectomy incontinence were included. They were divided into group A (BMI ≤ 25,12), group B (26 ≤ BMI ≤ 30,14), and group C (BMI ≥ 31,11) based on difference BMI. Three groups of patients underwent the same Pilates combined with kegel training. Participants were assessed with 1-hour pad test, the number of incontinence episodes, International Consultation on Incontinence Questionnaire and Oxford Grading Scale. Results In the 1-hour pad test, the differences before and after training were statistically significant in all three groups of participants. Group A decreased from 81.83 ± 8.79 to 31.08 ± 5.64 g (P

Inflammatory cytokine storms can trigger disease exacerbation and even death and have reached a consensus in the clinical treatment of acute organ failure. However, the existing strategies remain a great challenge to efficiently suppress inflammatory cytokine storms for promoting organ repair and regeneration. Herein, fully human umbilical cord (UC)-derived adhesive materials (UCAM) that integrate decellularized extracellular matrix (ECM) nanofiber hydrogel and homologous mesenchymal stem cells (MSCs) are demonstrated to greatly suppress inflammatory cytokine storms, demonstrating high efficacy in treating acute liver failure (ALF) in rats with 90% hepatectomy. The UC-derived adhesive materials have the capacity to secrete a significant quantity of cytokines by MSCs to recruit activated immune cells to migrate into their ECM nanofiber networks, segregating them away from the infection area and thereby greatly suppressing the inflammatory cytokine storms. As expected, the UC-derived adhesive materials can significantly promote hepatocyte proliferation to achieve functional recovery and regeneration of the liver, significantly improving the survival rate in rats. Our fully human UC-derived adhesive materials provide a new avenue in suppressing inflammatory cytokine storms for promoting organ regeneration that would be really utility in clinical organ transplantation-related treatment.

Abstract Background Identifying breast cancer (BC) patients with germline breast cancer susceptibility gene (gBRCA) mutation is important. The current criteria for germline testing for BC remain controversial. This study aimed to develop a nomogram incorporating ultrasound radiomic features and clinicopathological factors to predict gBRCA mutations in patients with BC. Materials and methods In this retrospective study, 497 women with BC who underwent gBRCA genetic testing from March 2013 to May 2022 were included, including 348 for training (84 with and 264 without a gBRCA mutation) and 149 for validation(36 patients with and 113 without a gBRCA mutation). Factors associated with gBRCA mutations were identified to establish a clinicopathological model. Radiomics features were extracted from the intratumoral and peritumoral regions (3 mm and 5 mm) of each image. The least absolute shrinkage and selection operator regression algorithm was used to select the features and logistic regression analysis was used to construct three imaging models. Finally, a nomogram that combined clinicopathological and radiomics features was developed. The models were evaluated based on the area under the receiver operating characteristic curve (AUC), calibration, and clinical usefulness. Results Age at diagnosis, family history of BC, personal history of other BRCA-related cancers, and human epidermal growth factor receptor 2 status were independent predictors of the clinicopathological model. The AUC of the imaging radiomics model combining intratumoral and peritumoral 3 mm areas in the validation set was 0.783 (95% confidence interval [CI]: 0.702—0.862), which showed the best performance among three imaging models. The nomogram yielded better performance than the clinicopathological model in validation sets (AUC: 0.824 [0.755—0.894] versus 0.659 [0.563—0.755], p = 0.007). Conclusion The nomogram based on ultrasound images and clinicopathological factors performs well in predicting gBRCA mutations in BC patients and may help to improve clinical decisions about genetic testing.

Abstract Background Previous research has indicated the inverse association between physical activity (PA) and gestational diabetes mellitus (GDM). However, the dose–response relationship currently remains undetermined. This study aims to explore the dose–response relationship between PA during the first and second trimesters of pregnancy and GDM risk. Methods Studies on the relationship between PA during pregnancy and GDM risk published before April 25, 2023, were searched for in six databases. According to the inclusion and exclusion criteria, all literature was screened for eligibility. The Newcastle-Ottawa Scale (NOS) was used to assess risk of bias. Publication bias was examined using funnel plots, Begg’s and Egger’s tests, as well as trim-and-fill analysis. We harmonized exposure estimates of PA during pregnancy to the common unit of the metabolic equivalent of task (MET)-h/week. Restricted cubic splines were used to model the dose–response relationship. The criteria from the World Cancer Research Fund were used to assess the certainty of evidence across outcomes. All analyses were performed using Stata 15.1. Results The results indicated that in contrast with the lowest level of PA, promoting the highest PA level lowers the risk of GDM by 36% (RR = 0.64, 95%CI: 0.53 ~ 0.78). We found a curvilinear dose–response association between PA during the first trimester and incident GDM (P nonlinearity = 0.012). Compared to inactive pregnant women, for those who achieved the guidelines-suggested minimum level (10 MET-h/week) of PA during the first trimester, the GDM risk was decreased by 13% (RR = 0.87, 95%CI: 0.79 ~ 0.96). A linear relationship was found between PA during the second trimester and the GDM risk (P nonlinearity = 0.276). The results with a restricted cubic spline model suggested that pregnant women who accumulate 10 MET-h/week have a 1% reduced risk of GDM compared to completely inactive individuals. Twice (20 MET-h/week) or a higher amount of PA (50 MET-h/week) contributed to further reductions in GDM risk. Conclusion There is a dose–response relationship between higher levels of PA in both the first and second trimesters and reduced risk of GDM; the relationship is stronger in the first trimester. Increasing PA during pregnancy can prevent the development of GDM. PROSPERO registration number CRD42023420564.

Abstract In practice, the near-bit drilling tool confronts with strong vibrations and high-speed rotation. Therein the original signal amplitude of the tool attitude measurements is relatively feeble, and the signal-to-noise ratio (SNR) is exceptionally low. To handle this issue, this paper proposes a weak SNR signal extraction method, frequency selecting complementary ensemble empirical mode decomposition, which is based on ensemble empirical mode decomposition combining with complementary noise and frequency selecting. This method firstly adds different positive and negative pairs of auxiliary white noise to the original near-bit weak SNR signal, secondly adopts empirical mode decomposition on each pair of noise-added signals, then performs ensemble averaging on the obtained multiple sets of intrinsic mode function (IMF) to output more stable IMF of each order and set suitable weights according to designed frequency threshold, and finally reconstructs the original useful signal through weighted summing IMFs. Simulation results show that the extraction accuracy of well inclination angle ranges about ± 0.51°, and the extraction accuracy of tool face angle ranges about ± 1.35°, and meanwhile experimental results are provided compared with other advanced methods, which verifies the effectiveness of our method.

Abstract Background In the context of increasing population aging, ongoing drug-resistant pathogens and the COVID-19 epidemic, the changes in the epidemiological and clinical characteristics of patients with pneumonia remain unclear. This study aimed to assess the trends in hospitalization, case fatality, comorbidities, and isolated pathogens of pneumonia-related adult inpatients in Guangzhou during the last decade. Methods We retrospectively enrolled hospitalized adults who had doctor-diagnosed pneumonia in the First Affiliated Hospital of Guangzhou Medical University from January 1, 2013 to December 31, 2022. A natural language processing system was applied to automatically extract the clinical data from electronic health records. We evaluated the proportion of pneumonia-related hospitalizations in total hospitalizations, pneumonia-related in-hospital case fatality, comorbidities, and species of isolated pathogens during the last decade. Binary logistic regression analysis was used to assess predictors for patients with prolonged length of stay (LOS). Results A total of 38,870 cases were finally included in this study, with 70% males, median age of 64 (53, 73) years and median LOS of 7.9 (5.1, 12.8) days. Although the number of pneumonia-related hospitalizations showed an upward trend, the proportion of pneumonia-related hospitalizations decreased from 199.6 per 1000 inpatients in 2013 to 123.4 per 1000 in 2021, and the case fatality decreased from 50.2 per 1000 in 2013 to 23.9 per 1000 in 2022 (all P

The high-speed vibration rotation of the drill bit during drilling causes the logging tool to be damaged or distorted, resulting in inaccurate or lost data collection. Traditional prediction methods such as dynamic modeling and geological modeling have problems such as incomplete data and difficult modeling, which cannot meet the accuracy and stability requirements of wellbore trajectory prediction. The long short-term memory neural network (LSTM) for predicting time series can achieve accurate prediction, but there are problems such as difficulty in adjusting the hyperparameters of the LSTM model, slow convergence speed, and easy overfitting. This paper absorbs the advantages of the LSTM algorithm, ridge regression (L2 regularization), and sparrow optimization algorithm (SSA) in machine learning and proposes a well trajectory prediction model of steerable drilling based on L2 regularization and SSA optimized LSTM (L2-SSA-LSTM). The model takes the LSTM hyperparameter as the parameter optimization goal of SSA and adds L2 regularization to the model to prevent model overfitting to complete modeling and prediction. The experiment was conducted using measured data sets from directional drilling in two different oilfields. The results show that compared with the back propagation algorithm (BP), consolidated memory gated recurrent unit (CMGRU), dual-thread gated recurrent unit (DTGRU), Attention-based Spatiotemporal Graph Recurrent Neural Network (ASTG-RNN), LSTM, and the L2-SSA-LSTM prediction model has significantly higher accuracy in predicting directional drilling trajectories than other models and has the better predictive ability.

Pulmonary tuberculosis (PTB) is a major global health threat. Diagnosing PTB infectiousness is vital for clinical decision-making, but existing etiological examination methods do not meet the requirements for speed, accuracy, and cost effectiveness. Developing deep learning models for infectiousness identification based on computed tomography (CT) volume measurements holds promise for meeting these requirements. However, with limited samples and coarse annotations, the large amount of information in the CT volume poses a challenge for models to distinguish information related to patient-level labels, which often leads to severe model overfitting. In this study, A dual-branch framework is developed for identifying PTB infectiousness using CT volume. To address the issue of imbalance between the CT volume information and the patient-level labels, we propose a method for selecting representative slices to reduce redundant information and adopt a multiple-instance learning framework to improve label supervision. Furthermore, we incorporate multi-view projection information to compensate for the deficiency of global information caused by using single-dimensional slices as the input. Experimental results demonstrate that our strategy effectively mitigates overfitting and achieves desirable performance on an external test set, with an area under the receiver operating characteristic curve of 80.48%. This performance is superior to that obtained for models using the 3D CT volume or 2D projection images alone as the input.

Mangroves are among the most carbon-rich ecosystems in the world. However, they have experienced widespread loss due to climate change and have been reclaimed for coastal cropland and aquaculture ponds. Studying the impact of climate change on the potential distribution and carbon benefits of mangroves is crucial for their conservation and restoration. Currently, there is limited research on the potential distribution of mangroves in China under future climate change scenarios using ensemble models. Furthermore, there is a relative scarcity of studies that apply simulation results to the restoration and protection of mangroves. Therefore, based on 15 dominant mangrove species, we constructed high-precision species distribution models to simulate the potential distribution of mangroves in China during the current period (1981–2010) and predicted their potential distribution under three climate scenarios (SSP1-2.6, SSP3-7.0, and SSP5-8.5) in the late 21st century (2071–2100). Our study showed that 1) the four most crucial drivers of mangrove suitability in China are: air temperature in the coldest quarter, sea surface temperature range, isothermality, and annual precipitation amount. 2) mangroves tend to expand northward by 2–2.5 degrees of latitude in the end of the 21st century. Meanwhile, the potential distribution of Spartina alterniflora is expected to expand rapidly and pose a significant competitive threat to native mangrove species; 3) by restoring coastal cropland and aquaculture ponds to mangroves in the potential mangrove distribution area, the potential carbon stocks of mangroves would increase by 178.22–296.44 % and 170.31–277.13 % compared to the current carbon stocks of mangroves, the annual blue carbon would increase by 242.64–262.70 % compared to the current blue carbon of mangroves. Our research could provide valuable information for the future conservation and restoration of mangroves in China.

ObjectiveExploring the Incidence, Epidemic Trends, and Spatial Distribution Characteristics of Sporadic Hepatitis E in Hainan Province from 2013 to 2022 through four major tertiary hospitals in the Province.MethodsWe collected data on confirmed cases of hepatitis E in Hainan residents admitted to the four major tertiary hospitals in Haikou City from January 2013 to December 2022. We used SPSS software to analyze the correlation between incidence rate and economy, population density and geographical location, and origin software to draw a scatter chart and SAS 9.4 software to conduct a descriptive analysis of the time trend. The distribution was analyzed using ArcMap 10.8 software (spatial autocorrelation analysis, hotspot identification, concentration, and dispersion trend analysis). SAS software was used to build an autoregressive integrated moving average model (ARIMA) to predict the monthly number of cases in 2023 and 2024.ResultsFrom 2013 to 2022, 1,922 patients with sporadic hepatitis E were treated in the four hospitals of Hainan Province. The highest proportion of patients (n = 555, 28.88%) were aged 50–59 years. The annual incidence of hepatitis E increased from 2013 to 2019, with a slight decrease in 2020 and 2021 and an increase in 2022. The highest number of cases was reported in Haikou, followed by Dongfang and Danzhou. We found that there was a correlation between the economy, population density, latitude, and the number of cases, with the correlation coefficient |r| value fluctuating between 0.403 and 0.421, indicating a linear correlation. At the same time, a scatter plot shows the correlation between population density and incidence from 2013 to 2022, with r2 values fluctuating between 0.5405 and 0.7116, indicating a linear correlation. Global Moran’s I, calculated through spatial autocorrelation analysis, showed that each year from 2013 to 2022 all had a Moran’s I value >0, indicating positive spatial autocorrelation (p

Background Cisplatin is a commonly used nephrotoxic drug and can cause acute kidney injury (AKI). In the present study, isobaric tags for relative and absolute quantification (iTRAQ) and parallel reaction monitoring (PRM)-based comparative proteomics were used to analyze differentially expressed proteins (DEPs) to determine the key molecular mechanism in mice with cisplatin-induced AKI in the presence or absence of SIS3, a specific p-smad3 inhibitor, intervention. Methods The cisplatin-induced AKI mouse model was established and treated with SIS3. We used iTRAQ to search for DEPs, PRM to verify key DEPs and combined Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) for bioinformatics analysis. We then assessed lipid deposition, malondialdehyde (MDA) and reactive oxygen species (ROS) and detected the expression of SREBF1, SCD1, CPT1A, PPARα and NDRG1 in vitro. Results Proteomic analysis showed that the identified DEPs were mainly enriched in energy metabolism pathways, especially in lipid metabolism. When SIS3 was applied to inhibit the phosphorylation of Smad3, the expression of NDRG1 and fatty acid oxidation key proteins CPT1A and PPARα increased, the expression of lipid synthesis related proteins SREBF1 and SCD1 decreased and the production of lipid droplets, MDA and ROS decreased. Conclusion SIS3 alleviates oxidative stress, reduces lipid accumulation and promotes fatty acid oxidation through NDRG1 in cisplatin-induced AKI. Our study provides a new candidate protein for elucidating the molecular mechanisms of fatty acid metabolism disorders in cisplatin-induced acute kidney injury.

BackgroundSocial transition is one of the multi-level mechanisms that influence health disparities. However, it has received less attention as one of the non-traditional social determinants of health. A few studies have examined China’s social transition and its impact on health inequality in self-rated health (SRH). Therefore, this study explores the impact of China’s market-oriented reforms—social transition and socioeconomic status (SES)—on residents’ SRH.MethodsUsing the cross-sectional data from the Chinese General Social Survey (CGSS) in 2017, we analyzed the effects of social transition and SES on the SRH of Chinese residents using the RIF (Recentered influence function) method. The RIF decomposition method investigated health differences among different populations and their determinants.ResultsSocial transition and SES have significant positive effects on the SRH of Chinese residents. The correlation between SES and the SRH of Chinese residents is moderated by social transition, implying that social transition can weaken the correlation between SES and the SRH of Chinese residents. The impacts of SES and social transition on SRH vary across populations.ConclusionPromoting social transition and favoring disadvantaged groups with more resources are urgently needed to promote equitable health outcomes.

Background The prevalence, Medicaid use and mortality risk associated with low forced expiratory volume in 1 s (FEV1) among young adults aged 20–35 years are not well understood, despite its potential implications for the development of chronic pulmonary disease and overall prognosis.Methods A retrospective cohort study was conducted among young adults aged 20–35 years old, using data from the National Health and Nutrition Examination Survey, National Death Index and Centers for Medicare & Medicaid Services. Participants were categorised into a low FEV1 group (pre-bronchodilator FEV1%pred

Abstract All provinces of China respond to the central government, predict future carbon dioxide emissions, and formulate action plans detailing how the province intends to fulfill its target of carbon emission peaking before 2030. Based on the bottom‐up energy consumption prediction and top‐down goal verification, this paper constructs a set of regional carbon dioxide emission prediction methods. Compared to the traditional bottom‐up prediction method, this method could simplify the parameters while improving the prediction accuracy. This model is used to predict and analyze the process of carbon dioxide emission peaking in Zhejiang. The results show that the mean absolute percentage error of the retrospective prediction value is only 1.56%. Zhejiang will reach carbon dioxide emission peaking around 2029–2030, and the peak value will be 569.7 million tons. Different factors have different effects on the process of carbon dioxide emission peaking. There is a strong correlation between the peak time of carbon dioxide emission and the production time of major energy‐consuming projects in Zhejiang. Meanwhile, if the 16 nuclear reactors are not put into operation, Zhejiang will not be able to achieve the goal of carbon dioxide emission peaking. Besides, the basic data used in this model is mainly from the local statistical departments of the region. Thus, it can be applied to other provinces and regions conveniently.

Abstract Pressure sensors play a vital role in aerospace, automotive, medical, and consumer electronics. Although microelectromechanical system (MEMS)-based pressure sensors have been widely used for decades, new trends in pressure sensors, including higher sensitivity, higher accuracy, better multifunctionality, smaller chip size, and smaller package size, have recently emerged. The demand for performance upgradation has led to breakthroughs in sensor materials, design, fabrication, and packaging methods, which have emerged frequently in recent decades. This paper reviews common new trends in MEMS pressure sensors, including minute differential pressure sensors (MDPSs), resonant pressure sensors (RPSs), integrated pressure sensors, miniaturized pressure chips, and leadless pressure sensors. To realize an extremely sensitive MDPS with broad application potential, including in medical ventilators and fire residual pressure monitors, the “beam-membrane-island” sensor design exhibits the best performance of 66 μV/V/kPa with a natural frequency of 11.3 kHz. In high-accuracy applications, silicon and quartz RPS are analyzed, and both materials show ±0.01%FS accuracy with respect to varying temperature coefficient of frequency (TCF) control methods. To improve MEMS sensor integration, different integrated “pressure + x” sensor designs and fabrication methods are compared. In this realm, the intercoupling effect still requires further investigation. Typical fabrication methods for microsized pressure sensor chips are also reviewed. To date, the chip thickness size can be controlled to be

Abstract Given afferent functions, sensory nerves have recently been found to exert efferent effects and directly alter organ physiology. Additionally, several studies have highlighted the indirect but crucial role of sensory nerves in the regulation of the physiological function of osteoclasts. Nonetheless, evidence regarding the direct sensory nerve efferent influence on osteoclasts is lacking. In the current study, we found that high levels of efferent signals were transported directly from the sensory nerves into osteoclasts. Furthermore, sensory hypersensitivity significantly increased osteoclastic bone resorption, and sensory neurons (SNs) directly promoted osteoclastogenesis in an in vitro coculture system. Moreover, we screened a novel neuropeptide, Cyp40, using an isobaric tag for relative and absolute quantitation (iTRAQ). We observed that Cyp40 is the efferent signal from sensory nerves, and it plays a critical role in osteoclastogenesis via the aryl hydrocarbon receptor (AhR)-Ras/Raf-p-Erk-NFATc1 pathway. These findings revealed a novel mechanism regarding the influence of sensory nerves on bone regulation, i.e., a direct promoting effect on osteoclastogenesis by the secretion of Cyp40. Therefore, inhibiting Cyp40 could serve as a strategy to improve bone quality in osteoporosis and promote bone repair after bone injury.

Abstract Background In view of the fact that radiomics features have been reported as predictors of immunotherapy to various cancers, this study aimed to develop a prediction model to determine the response to anti‐programmed death‐1 (anti‐PD‐1) therapy in esophageal squamous cell carcinoma (ESCC) patients from contrast‐enhanced CT (CECT) radiomics features. Methods Radiomic analysis of images was performed retrospectively for image samples before and after anti‐PD‐1 treatment, and efficacy analysis was performed for the results of two different time node evaluations. A total of 68 image samples were included in this study. Quantitative radiomic features were extracted from the images, and the least absolute shrinkage and selection operator method was applied to select radiomic features. After obtaining selected features, three classification models were used to establish a radiomics model to predict the ESCC status and efficacy of therapy. A cross‐validation strategy utilizing three folds was employed to train and test the model. Performance evaluation of the model was done using the area under the curve (AUC) of receiver operating characteristic, sensitivity, specificity, and precision metric. Results Wavelet and area of gray level change (log‐sigma) were the most significant radiomic features for predicting therapy efficacy. Fifteen radiomic features from the whole tumor and peritumoral regions were selected and comprised of the fusion radiomics score. A radiomics classification was developed with AUC of 0.82 and 0.884 in the before and after‐therapy cohorts, respectively. Conclusions The combined model incorporating radiomic features and clinical CECT predictors helps to predict the response to anti‐PD‐1therapy in patients with ESCC.

Abstract Due to the federal Kalman filter is used to directly fuse the measurement information into the main filter without processing, resulting in the problem of reduced filtering accuracy. An adaptive weighted federated Kalman filtering based on Mahalanobis distance was proposed in this paper. By calculating the Mahalanobis distance between the predicted value and the measurements of the system, the random fluctuation of the measurements is detected. The statistical characteristics of the system measurement noise are adjusted at any time according to random fluctuations in the measurements. And then by using a adaptive amplification factor to dynamically adjust the measurement noise in the subsystems, and reduce the impact of measurement information contamination in subfilters on the main filter. The adaptive federated information distribution coefficient is used to realize the global information fusion of the federal Kalman filter method, to reduce the influence of inaccurate estimation of subfilters on the main filter.Simulation results and comparison analysis prove that the filtering performance of the proposed is better than the traditional federated Kalman filter (FKF) and adaptive FKF, which can improve the accuracy of the integrated navigation system.

With the gradual emergence of trends such as the asynchronous interconnection of power grids and the increasing penetration of renewable energy, the issues of ultra-low-frequency oscillations and low-frequency stability in power grids have become more prominent, posing serious challenges to the safety and stability of systems. The voltage-source converter-based HVDC (VSC-HVDC) interconnection is an effective solution to the frequency stability problems faced by regional power grids. VSC-HVDC can participate in system frequency stability control through a frequency limit controller (FLC). This paper first analyses the basic principles of how VSC-HVDC participates in system frequency stability control. Then, in response to the frequency stability control requirements of the sending and receiving power systems, a droop FLC strategy is designed. Furthermore, a multi-objective optimization method for the parameters of the droop FLC is proposed. Finally, a large-scale electromagnetic transient simulation model of the VSC-HVDC interconnected power system is constructed to verify the effectiveness of the proposed droop FLC method.

Background: The alternations of brain responses to a strong desire to void were unclear, and the gender differences under the strong desire to void remain controversial. The present study aims to identify the functional brain network’s topologic property changes evoked by a strong desire to void in healthy male and female adults with synchronous urodynamics using a graph theory analysis. Methods: The bladders of eleven healthy males and eleven females were filled via a catheter using a specific infusion and withdrawal pattern. A resting-state functional magnetic resonance imaging (fMRI) was performed on the enrolled subjects, scanning under both the empty bladder and strong desire to void states. An automated anatomical labeling (AAL) atlas was used to identify the ninety cortical and subcortical regions. Pearson’s correlation calculations were performed to establish a brain connection matrix. A paired t-test (p < 0.05) and Bonferroni correction were applied to identify the significant statistical differences in topological properties between the two states, including small-world network property parameters [gamma (γ) and lambda (λ)], characteristic path length (Lp), clustering coefficient (Cp), global efficiency (Eglob), local efficiency (Eloc), and regional nodal efficiency (Enodal). Results: The final data suggested that females and males had different brain response patterns to a strong desire to void, compared with an empty bladder state. Conclusions: More brain regions involving emotion, cognition, and social work were active in females, and males might obtain a better urinary continence via a compensatory mechanism.

Direct current (DC) bias induced by the DC transmission and geomagnetically induced current is a critical factor in the abnormal operation of electrical equipment and is widely used in the field of power transmission and distribution system state evaluation. As the main affected component, the vector magnetization state of a transformer core under DC bias has rarely been studied, resulting in inaccurate transformer operation state estimations. In this paper, a dynamic vector hysteresis model that considers the impact of rotating and DC-biased fields is introduced into the numerical analysis to simulate the distribution of magnetic properties, iron loss and temperature of the transformer core model and a physical 110 kV single-phase autotransformer core. The maximum values of B, H and iron loss exist at the corners and T-joint of the core under rotating and DC-biased fields. The corresponding maximum value of the temperature increase is found in the main core limb area. The temperature rise of the 110 kV transformer core under various DC-biased conditions is measured and compared with the FEM (Finite Element Method) results of the proposed model and the model solely based on the magnetization curve B||H. The calculation error of the temperature rise obtained by the improved model is approximately 3.76–15.73% and is much less than the model solely based on magnetization curve B||H (approximately 50.71–66.92%).

Searching for natural products with anti-tumor activity is an important aspect of cancer research. Seaweed polysaccharides from brown seaweed have shown promising anti-tumor activity; however, their structure, composition, and biological activity vary considerably, depending on many factors. In this study, 16 polysaccharide fractions were extracted and purified from three large brown seaweed species (Sargassum horneri, Scytosiphon lomentaria, and Undaria pinnatifida). The chemical composition analysis revealed that the polysaccharide fractions have varying molecular weights ranging from 8.889 to 729.67 kDa, and sulfate contents ranging from 0.50% to 10.77%. Additionally, they exhibit different monosaccharide compositions and secondary structures. Subsequently, their anti-tumor activity was compared against five tumor cell lines (A549, B16, HeLa, HepG2, and SH-SY5Y). The results showed that different fractions exhibited distinct anti-tumor properties against tumor cells. Flow cytometry and cytoplasmic fluorescence staining (Hoechst/AO staining) further confirmed that these effective fractions significantly induce tumor cell apoptosis without cytotoxicity. qRT-RCR results demonstrated that the polysaccharide fractions up-regulated the expression of Caspase-3, Caspase-8, Caspase-9, and Bax while down-regulating the expression of Bcl-2 and CDK-2. This study comprehensively compared the anti-tumor activity of polysaccharide fractions from large brown seaweed, providing valuable insights into the potent combinations of brown seaweed polysaccharides as anti-tumor agents.

Assessing the hazard of inundation due to extreme storm surges in low-lying coastal areas and fragile ecosystems has become necessary and important. In this study, Xincun Lagoon and Li’an Lagoon in the Lingshui area of Hainan, China, were selected as the study areas, a high-resolution storm surge inundation numerical model was established, and the model reliability was tested. Based on data on typhoons affecting the study area from 1949 to 2022, the typhoon parameters for the extreme storm surge scenario were set and used for model numerical simulation and hazard assessment. The results revealed that in the extreme storm surge scenario, the average maximum tidal level, average maximum flow velocity, maximum inundation area, and average maximum inundation depth in the lagoon area were 2.29 m, 1.03 m/s, 14.8124 km2, and 1.20 m, respectively. Under the extreme storm surge scenario, a flow velocity of 2.0 m/s off the coasts of the lagoons could damage coastal aquaculture facilities, harbors, and ecosystems, while an inundation depth exceeding 1 m along the coasts of the lagoons could lead to the salinization of inundated land and severely affect the safety of residents. The hazard analysis of storm surge inundation in the land area of the lagoons revealed that hydrographic nets and coastal wetlands are the major land types inundated by storm surges, with the two accounting for approximately 70% of the total inundation area. According to China’s technical guidelines, the hazard levels of the inundated land area of the lagoons are mostly level 3 (moderate hazard) and level 2 (high hazard), together accounting for approximately 90% of the total inundation area. If the government deems the measures feasible based on strict estimation and scientific evaluation of economic benefits and disaster prevention, planting mangroves in coastal wetlands and/or establishing adjustable tidal barriers at narrow entrances to lagoons could minimize disaster losses.

Line planning and timetabling play important roles in the design of urban rail transportation services. Due to the complexity of the integrated optimization of entire transportation plans, previous studies have generally considered line planning and timetabling design independently, which cannot ensure the global optimality of transportation services. In this study, the integrated design problem of line planning and timetabling was characterized as an equilibrium space–time network design problem and solved with a bi-objective nonlinear integer programming model. The model, in which train overtaking and passenger path choice behavior were considered, adjusted the network topology and link attributes (time and capacity) of the travel space–time network by optimizing the train service frequency, operation zone, stopping pattern, train formation, and train order to minimize the system life cycle cost and total passenger travel time perception. An algorithm was constructed using the non-dominated sorting genetic algorithm II combined with the self-adaptive gradient projection algorithm to solve the model. A real-world case was considered to evaluate the effectiveness of the proposed model and algorithm. The results showed that the model not only performed well in the trade-off between system cost and passenger travel efficiency, but it could also reduce the imbalance of train and station loads. Pareto front analysis of the model with different parameters showed that more types of trains did not correlate with a better performance, some line-planning strategies had a combination effect, and multi-strategy line planning was more suitable for scenarios with a high imbalance in the temporal and spatial distributions of passenger flow.

Abstract Industrial defect detection is an important part of intelligent manufacturing, and Internet of things (IoT)‐based defect detection is receiving more and more attention. Although deep learning (DL) can help defect detection reduce the cost and improve the accuracy of traditional manual quality inspection, DL requires huge computational resources and is difficult to be simply deployed on IoT devices with limited computational power and memory resources. Digital signal processor (DSP) is an important IoT device with small size, high performance and low energy consumption, which has been widely used in intelligent manufacturing. In order to perform accurate defect detection on DSP, the authors proposed various optimisation strategies and then used a parallel scheme to scale the model to execute on multiple cores. The authors’ method evaluated it on Northeastern University Surface Defect Dataset, Magnetic Tile Defect Dataset, Rail Surface Defect Dataset and Silk Cylinder Defect Dataset, and the experimental results showed that the authors’ method obtains faster speeds without accuracy loss compared to running the same Convolutional Neural Networks model on a mainstream desktop CPU. This means that the authors’ method can realise efficient and accurate defect detection on IoT devices with limited computational power and memory resources, which opens up new possibilities for future development in the field of smart manufacturing.

Crohn's disease (CD) is a chronic, non-specific inflammatory disease of the intestinal tract with an unknown etiology. It presents with clinical symptoms such as abdominal distension, abdominal pain, diarrhea, bloody stools containing mucus or pus, and other manifestations. CD has a prolonged and chronic course and can lead to various complications that significantly impact patients’ quality of life. Patients with CD have hypercoagulable blood and are prone to thromboembolic diseases, which pose a serious threat to their lives. Several studies have indicated that inflammatory bowel disease is a risk factor for venous thromboembolism. The pathogenesis involves abnormalities in the coagulation-anticoagulation system, fibrinolytic system, platelets, vascular endothelial dysfunction, as well as the effects of therapeutic agents. In this case report, we present a rare case of a 15-year-old female patient with active CD complicated by the presence of a right atrial thrombus. Laboratory tests revealed abnormalities in both the coagulation-anticoagulation system and fibrinolysis system in the patient. The initial diagnosis, based on transthoracic echocardiography and contrast-enhanced echocardiography, confirmed the presence of a thrombus in the right atrium. Subsequent administration of anticoagulant and thrombolytic therapy resulted in gradual reduction in size until complete disappearance, as evidenced by dynamic monitoring. Ultrasound examination is considered as the preferred method for follow-up evaluation in patients with CD due to its ability not only to assess gastrointestinal complications but also to aid early identification of cardiovascular complications, thereby enabling timely intervention and treatment—which remains our primary focus of research and effort.

Widespread adoption of air-conditioning significantly enhances indoor thermal comfort in summer, but the heat dissipation from these outdoor units contributes to an increase in ambient air temperature, exacerbating urban heat island effects. Consequently, as outdoor thermal conditions worsen, the energy consumption associated with air-conditioning is likely to escalate. The spray system becomes a suitable choice due to the obvious advantage of heat absorption through the droplet evaporation. To assess the effectiveness of the spray system in reducing heat release, a comparative study was conducted between two identical buildings with the same air-conditioning system, but only one of which incorporated the spray system. Three installed locations are considered with the spray location in inlet (Case 1), outlet (Case 2) and both inlet & outlet (Case 3) of outdoor units. The results demonstrated the average temperatures of air outlet were reduced by 4.0 °C, 6.3 °C, and 7.9 °C for Cases 1–3, respectively, accompanied by a reduction in energy consumption of the air-conditioning system by 18.8%, 13.9%, and 37.3% respectively. The most significant benefits were observed when the spray location was installed in both outdoor unit inlet and outlet (Case 3). The spray system established a virtuous cycle in heat dissipation improvement, evaporation enhancement, and air temperature reduction.

Summary: Human umbilical cord mesenchymal stem cells (UC-MSCs)-derived hepatocyte-like cells (HLCs) have shown great promise in the treatment of liver diseases. However, most current induction protocols yield hepatocyte-like cells with limited function as compared with primary hepatocytes. Schisandrin B (Sch B) is one of the main components of Schisandra chinensis, which can prevent fibrosis progression and promote liver cell regeneration. Herein, we investigated the effects of Sch B on hepatic differentiation of UC-MSCs. We found that treatment with 10 μM Sch B from the second stage of the differentiation process increased hepatic marker levels and hepatic function. Additionally, RNA-seq analysis revealed that Sch B promoted hepatic differentiation via activating the JAK2/STAT3 pathway. When transplanted HLCs into mice with CCL4-induced liver fibrosis, Sch B-treated HLCs exhibited significant therapeutic effects. This study provides an optimized hepatic differentiation protocol for UC-MSCs based on Sch B, yielding functioning cells for liver disease treatment.

CA1 subfield and subiculum of the hippocampus contain a series of dentate bulges, which are also called hippocampus dentation (HD). There have been several studies demonstrating an association between HD and brain disorders. Such as the number of hippocampal dentation correlates with temporal lobe epilepsy. And epileptic hippocampus have a lower number of dentation compared to contralateral hippocampus. However, most studies rely on subjective assessment by manual searching and counting in HD areas, which is time-consuming and labor-intensive to process large amounts of samples. And to date, only one objective method for quantifying HD has been proposed. Therefore, to fill this gap, we developed an automated and objective method to quantify HD and explore its relationship with neurodegenerative diseases. In this work, we performed a fine-scale morphological characterization of HD in 2911 subjects from four different cohorts of ADNI, PPMI, HCP, and IXI to quantify and explore differences between them in MR T1w images. The results showed that the degree of right hippocampal dentation are lower in patients with Alzheimer's disease than samples in mild cognitive impairment or cognitively normal, whereas this change is not significant in Parkinson's disease progression. The innovation of this paper that we propose a quantitative, robust, and fully automated method. These methodological innovation and corresponding results delineated above constitute the significance and novelty of our study. What’s more, the proposed method breaks through the limitations of manual labeling and is the first to quantitatively measure and compare HD in four different brain populations including thousands of subjects. These findings revealed new morphological patterns in the hippocampal dentation, which can help with subsequent fine-scale hippocampal morphology research.

BackgroundCurrent research suggests that prostate cancer (PCa), one of the most common cancers in men, may be linked to insulin resistance (IR).Triglyceride-glucose index (TyG index) was made for a marker of insulin resistance. We investigated the relationship between the TyG index and the risk of PCa.ObjectiveTo assess the correlation and dose-response relationship between TyG index and prostate cancer.MethodRetrospectively, 316 patients who required prostate biopsy puncture in the First Affiliated Hospital of Xinjiang Medical University from March 2017 to July 2021 were collected, and the relationship between factors such as the TyG index and prostate cancer was analyzed by Logistic regression model combined with a restricted cubic spline.Results(1) The differences in age, initial PSA and TyG index between the two groups were statistically significant; (2) Logistic regression results showed that the risk of prostate cancer in the highest quartile of the TyG index (Q4) was 3.387 times higher than that in the lowest quartile (Q1) (OR=3.387,95% CI [1.511,7.593], P=0.003); (3) The interaction results showed a significant interaction between the TyG index Q4 group and age with the risk of developing prostate cancer (P for interaction

Abstract Background Currently, the clinical strategy for diagnosis of non-muscle invasive bladder cancer (NMIBC) such as cystoscopy and cytology are invasive and/or with limited accuracy. OncoUrine, a urinary assay for mutation and methylation biomarkers, have showed a high accuracy in the detection of upper tract urinary carcinoma (UTUC) patients with hematuria. The aim of this study is to evaluate the performance of OncoUrine in diagnosis of NMIBC patients. Methods In this multicenter prospective study, a total of 203 patients were enrolled, including 60 patients present with hematuria and 143 NMIBC patients under recurrence surveillance. Urine samples were collected before cystoscopy to undergo OncoUrine test. OncoUrine performance was calculated compared to clinical standard methods in hematuria cohort and recurrence surveillance cohort, respectively. Furthermore, NMIBC patients were followed up with a median time of 20.5 months (range 0.03 to 24.03 months) to assess the predictive value of OncoUrine during recurrence monitoring. Results For bladder cancer diagnosis, OncoUrine tested 47 samples and achieved a sensitivity/specificity/positive predictive value (PPV)/negative predictive value (NPV) of 80% (95% CI 44.2–96.5)/91.9% (95% CI 77.0–97.9)/72.7% (95% CI 39.3–92.7)/94.4% (95% CI 80.0–99.0) (kappa value 69.4%, 95% CI 44.4–94.3), indicating 72.3% of unnecessary cystoscopy. For recurrence diagnosis, OncoUrine tested 93 samples, and the sensitivity/specificity/PPV/NPV was 100% (95% CI 59.8–100.0)/68.2% (95% CI 57.1–77.7)/22.9% (95% CI 11.0–40.6)/100% (95% CI 92.3–100.0) (kappa value 27.0%, 95% CI 11.1–42.8), indicating 62.4% of spared cystoscopy. What is more, OncoUrine correctly predicted 80% (20/25) of final recurrence with 12/25 (48%) patients who were OncoUrine positive, but cystoscopy negative was followed with recurrence during follow-up. The test result of OncoUrine was also found significantly correlated with recurrence free survival (RFS) of NMIBC patients (median 34.4-month vs unreached; HR 6.0, 95% CI 2.7–13.5, P

Abstract Background Nowadays, the incidence rate of advanced and metastatic prostate cancer at the first time of diagnosis grows higher in China yearly. At present, androgen deprivation therapy (ADT) is the primary treatment of advanced prostate cancer. However, after several years of ADT, most patients will ultimately progress to castration-resistant prostate cancer (CRPC). Previous studies mainly focus on Caucasian and very few on East Asian patients. Methods In this study, the pre- and post-ADT tumor samples were collected from five Chinese patients with advanced prostate cancer. The whole-exome sequencing, tumor heterogeneity, and clonal evolution pattern were analyzed. Results The results showed that the gene mutation pattern and heterogeneity changed significantly after androgen deprivation therapy. Tumor Mutational Burden (TMB) and Copy Number Alteration (CNA) were substantially reduced in the post-treatment group, but the Mutant-allele tumor heterogeneity (MATH), Socio-Demographic Index (SDI), Intratumor heterogeneity (ITH), and weighted Genome Instability Index (wGII) had no significant difference. According to the clone types and characteristics, the presence of main clones in five pre-and post-treatment samples, the clonal evolution pattern can be further classified into two sub-groups (the Homogeneous origin clonal model or the Heterogeneous origin clonal model). The Progression-free survival (PFS) of the patients with the “Homogeneous origin clonal model” was shorter than the “Heterogeneous origin clonal model”. The longer PFS might relate to MUC7 and MUC5B mutations repaired. ZNF91 mutation might be responsible for resistance to ADT resistance. Conclusion Our findings revealed potential genetic regulators to predict the castration resistance and provide insights into the castration resistance processes in advanced prostate cancer. The crosstalk between clonal evolution patterns and tumor microenvironment may also play a role in castration resistance. A multicenter-research including larger populations with different background are needed to confirm our conclusion in the future.

Abstract The extreme power output scenarios of renewable energy sources (RES) proposed new challenges to the safe and stable operation of the power system. Transmission expansion planning (TEP) with large‐scale RES grid integration needs considering the risk of extreme scenarios. In this paper, an adaptive decision‐making approach for the TEP problem based on planning‐risk assessment‐replanning iterative process is proposed. The method obtains massive temporal and spatial correlated wind‐photovoltaic (PV) power output scenarios by generalizing the historical data to describe the uncertainties. A data‐driven load loss risk assessment model (RAM) based on the power system's actual operating state is built, referring to the degree of extreme scenario risks on the balance of supply and demand, and the probability of extreme scenario occurrence. The planning decision is progressively revised according to the risk assessment result. The Garver's 6‐bus system and the IEEE RTS 24‐bus system are adopted as simulation cases. The results show that the optimal expansion plans achieve a balance between the economy and robustness, which verifies the effectiveness of the proposed method.

Abstract Background Liver stiffness relates to more advanced tumor status and poor outcomes in primary liver cancer, while its prognostic role in pancreatic cancer with liver metastasis is unclear. Therefore, the current study aimed to explore the correlation of elastic modulus (EM)-reflected liver lesion stiffness with clinical characteristics, tumor markers, and survival among pancreatic cancer patients with liver metastasis. Methods Fifty-four pancreatic cancer patients with liver metastasis were enrolled, and the EM of liver metastasis and peripheral liver tissue was measured by two-dimensional shear wave elastography. Relative EM was calculated as the ratio of EM in liver metastasis to that in peripheral liver tissue, which reflected the relative liver lesion stiffness. Results The median relative EM of liver metastasis was 7.8 (interquartile range: 4.8–10.7) folds. Relative EM of liver metastasis was correlated with primary pancreatic cancer location (P = 0.048), the presence of extra lung metastasis (P = 0.040), liver metastasis ≥ 3 cm (P = 0.007), and the absence of extraskeletal metastasis (P = 0.036); but it was not correlated with tumor markers such as CA199, CA125, or CEA (all P > 0.05). Encouragingly, high relative EM of liver metastasis (cut off by median value) was correlated with poor progression-free survival (PFS) (P = 0.032) but not overall survival (OS) (P = 0.285). Multivariable Cox analysis showed that high relative EM of liver metastasis (hazard ratio (HR) = 1.768, P = 0.048) and multiple metastases (HR = 2.262, P = 0.036) independently predicted decreased PFS, but only abnormal CEA independently forecasted decreased OS (HR = 2.390, P = 0.027). Conclusion Elastic modulus reflected liver lesion stiffness may predict a worse prognosis in pancreatic cancer patients with liver metastasis.

The explosive growth of mobile data traffic has resulted in a significant increase in the energy consumption of 5G base stations (BSs). However, the existing energy conservation technologies, such as traditional BS sleep strategy, rarely consider the dynamic real-time changes of users (UEs), which may make it difficult to maximize sleep idle or lightly loaded BSs, thereby affecting the reduction of BS energy consumption. Therefore, an energy consumption optimization strategy of 5G BSs considering variable threshold sleep mechanism (ECOS-BS) is proposed in this paper. Compared to current strategies, the ECOS-BS strategy can dynamically adjust BSs’ optimal sleep threshold on the premise of considering UEs’ dynamic changes, which is conducive to maximize sleep available BSs and realize the optimal management of BS energy consumption. Taking a heterogeneous cellular network as an example, numerical simulations are conducted to validate the effectiveness of the proposed strategy.

Abstract Background Osteosarcoma (OS) has been the most common malignancy of the bone in children and adolescents, and the unsatisfactory prognosis of OS sufferers has long been a hard nut. Here, we delved into the markers with a prognostic value for predicting the prognosis of OS patients. Methods The messenger RNA (mRNA) sequencing data and clinical data of OS were retrieved from a Gene Expression Omnibus (GEO) dataset (GSE39058). Next, prognosis-related genes (PRGs) were filtered with the aid of Kaplan–Meier (K-M) curves and Cox regression analysis (CRA). Later, Gene Ontology (GO) biological process analysis was used in verifying the function of different genes. CCK-8 and cell apoptosis assay were performed to evaluate the function of MFNG in U2OS cells. Results Among the obtained genes, Manic Fringe (MFNG) had the closest relevance to prognosis and clinical traits, thus becoming the research object herein. In light of the expression level of MFNG, patients fell into high- and low-MFNG groups. Patients with elevated MFNG expression had a worse prognosis, according to the survival analysis. It was unveiled by the univariate and multivariate analyses that MFNG expression was an independent adverse prognostic factor for disease-free survival in OS patients (p = 0.006). Meanwhile, MFNG expression was linked to gender and tumor recurrence, and it was higher in patients with OS recurrence. Moreover, overexpression of MFNG promoted the cell proliferation and inhibited the cell apoptosis of U2OS cells. Conclusions The expression level of MFNG negatively correlated with OS progression, and as an independent adverse prognostic factor for disease-free survival in OS patients. Moreover, MFNG regulated the cell proliferation and apoptosis of OS cells.

As an important part of the additive manufacturing technology, wire arc additive manufacture (WAAM) is outstanding with high deposition efficiency, large size of deposited parts, short periodic time, and low costs. WAAM also shows potential in in-situ composite manufacturing and gradient material preparation. Given the potential in wire arc manufacturing of double-alloy gradient structured materials, the walls were deposited using alternating feeds (depositing a layer of A wire and then depositing a layer of B wire) of high-strength-low-plasticity ZL205 and low-strength-high-plasticity 4043 welding wire. In this process, the liquid phases of the two types of wire were efficiently mixed, which showed a regular distribution of molten pool track and avoided evident defects. Generally, through such gradient structure design, high-strength low-toughness materials and high-toughness low-strength materials can be effectively combined, which achieves the regulation of mechanical properties. Specifically, the overall structural and mechanical properties can be improved by adjusting the proportion of a certain component. As an extension from the wire arc printing technology, WAAM shows extremely high application potential and industrial values. Moreover, the addition of a dissimilar alloy can decrease the formation of columnar grains during additive manufacturing. Such compositional gradient can destroy the columnar extensive growth during the deposition in WAAM.

Plants photoreceptors perceive changes in light quality and intensity and thereby regulate plant vegetative growth and reproductive development. By screening a γ irradiation-induced mutant library of the soybean (Glycine max) cultivar “Dongsheng 7”, we identified Gmeny, a mutant with elongated nodes, yellowed leaves, decreased chlorophyll contents, altered photosynthetic performance, and early maturation. An analysis of bulked DNA and RNA data sampled from a population segregating for Gmeny, using the BVF-IGV pipeline established in our laboratory, identified a 10 bp deletion in the first exon of the candidate gene Glyma.02G304700. The causative mutation was verified by a variation analysis of over 500 genes in the candidate gene region and an association analysis, performed using two populations segregating for Gmeny. Glyma.02G304700 (GmHY2a) is a homolog of AtHY2a in Arabidopsis thaliana, which encodes a PΦB synthase involved in the biosynthesis of phytochrome. A transcriptome analysis of Gmeny using the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed changes in multiple functional pathways, including photosynthesis, gibberellic acid (GA) signaling, and flowering time, which may explain the observed mutant phenotypes. Further studies on the function of GmHY2a and its homologs will help us to understand its profound regulatory effects on photosynthesis, photomorphogenesis, and flowering time.

In the interiors of ancient Huizhou buildings in China, a profusion of wood carvings are employed for decoration, with traditional research interpreting their function from decorative and aesthetic perspectives. However, this research suggests that the role of Huizhou wood carvings in interior spaces surpasses mere decoration; they enhance the expression and experience of spatial concepts through narrative imagery. By analyzing the mechanism and intrinsic logic behind the spatial concepts formed in Huizhou residential buildings, this study investigates how wood-carving imagery contributes to shaping spatial concepts through narrative techniques, as well as their creativity and expressiveness in architectural design. Utilizing literature reviews, field surveys for case selection, and case analysis methods combined with observation, interviews, and measurements, this research ultimately employs image analysis to interpret the narrative structures and styles of wood-carving imagery in detail. This study reveals that (1) the spatial concepts of Huizhou residential buildings are influenced by traditional thought, social culture, and other factors, leading to an interweaving of material, cultural, and social spaces that results in a spatial concept characterized by harmony between heaven and humanity, clear hierarchy, and orderliness; (2) Huizhou wood-carvings, through their narrative images, actively engage in the production of spatial concepts, employing thematic juxtaposition narrative modes and utilizing singular-scene narration, composite-scene narration, and cyclical narration to articulate these concepts. These findings significantly deepen our comprehension of the relationship between the spatial concepts of Huizhou’s traditional residential architecture and social culture. By integrating cultural elements with spatial production theory, this research addresses the limitations of existing studies and augments their theoretical interpretative power. Additionally, clarifying the connection between the cultural elements of wood-carving imagery and the formation of spatial concepts offers a novel perspective on the study of Huizhou wood carvings, moving beyond their longstanding categorization as purely decorative elements.

Jujube (Ziziphus jujuba) exhibits a rich diversity in fruit shape, with natural occurrences of gourd-like, flattened, and other special shapes. Despite the ongoing research into fruit shape, studies integrating elliptical Fourier descriptors (EFDs) with both Short Time-series Expression Miner (STEM) and weighted gene co-expression network analysis (WGCNA) for gene discovery remain scarce. In this study, six cultivars of jujube fruits with distinct shapes were selected, and samples were collected from the fruit set period to the white mature stage across five time points for shape analysis and transcriptome studies. By combining EFDs with WGCNA and STEM, the study aimed to identify the critical periods and key genes involved in the formation of jujube fruit shape. The findings indicated that the D25 (25 days after flowering) is crucial for the development of jujube fruit shape. Moreover, ZjAGL80, ZjABI3, and eight other genes have been implicated to regulate the shape development of jujubes at different periods of fruit development, through seed development and fruit development pathway. In this research, EFDs were employed to precisely delineate the shape of jujube fruits. This approach, in conjunction with transcriptome, enhanced the precision of gene identification, and offered an innovative methodology for fruit shape analysis. This integration facilitates the advancement of research into the morphological characteristics of plant fruits, underpinning the development of a refined framework for the genetic underpinnings of fruit shape variation.

The single-image super-resolution task benefits has a wide range of application scenarios, so has long been a hotspot in the field of computer vision. However, designing a continuous-scale super-resolution algorithm with excellent performance is still a difficult problem to solve. In order to solve this problem, we propose a continuous-scale SR algorithm based on a Transformer, which is called residual dense Swin Transformer (RDST). Firstly, we design a residual dense Transformer block (RDTB) to enhance the information flow before and after the network and extract local fusion features. Then, we use multilevel feature fusion to obtain richer feature information. Finally, we use the upsampling module based on the local implicit image function (LIIF) to obtain continuous-scale super-resolution results. We test RDST on multiple benchmarks. The experimental results show that RDST achieves SOTA performance in the fixed scale of super-resolution tasks in the distribution, and significantly improves (0.1∼0.6 dB) the arbitrary scale of super-resolution tasks out of distribution. Sufficient experiments show that our RDST can use fewer parameters, and its performance is better than the SOTA SR method.