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Realizing effective enhancement to the structure of interface region between explosive crystals and polymer binder plays a key role in improving the mechanical properties of the current polymer bonded explosives (PBXs). Herein, inspired by the structure of natural nacre which possesses outstanding mechanical performance, a kind of nacre-like structural layer is constructed in the interface region of PBXs composites, making use of two-dimensional graphene sheets and one-dimensional bio-macromolecules of cellulose as inorganic and organic building blocks, respectively. Our results reveal that the constructed nacre-like structural layer can effectively improve the interfacial strength and then endow the PBXs composites with significantly enhanced mechanical properties involving of creep resistance, Brazilian strength and fracture toughness, demonstrating the obvious advantage of such bioinspired interface structure design strategy. In addition, the thermal conduction performance of PBXs composites also exhibits noticeable enhancement due to the remarkable phonon transport capability endowed by the as-designed nacre-like structural layer. We believe this work provides a novel design route to conquer the issue of weak interfacial strength in PBXs composites and greatly increase the comprehensive properties for better meeting the higher requirements proposed to the explosive part of weapon equipment in new era.

Abstract Fritillaria unibracteata is an endangered medicinal material species endemic to the Qinghai Tibet Plateau, and belongs to the national Class III endangered plant. In addition to expelling wind and removing damne, it also warms menstruation and relieves pain in clinic use of tranditional Chinese medicine. In recent years, affected by the destruction of shrubs and climate change, the habitat of F. unibracteata wild resources has been seriously damaged, indicating of great significance to predict its potential suitable habitat using MaxEnt model. The AUC values without human activities were 0.983 ± 0.013–0.988 ± 0.001, while it is 0.982 ± 0.015–0.989 ± 0.000 with human activities, justifying their applications for predicting the potential areas of F. unibracteata. Without human activities, there were 8.47 × 104 km2 of highly suitable habitats in northern Sichuan, southern Gansu and southeastern Qinghai. But the poorly, moderately and highly suitable areas of F. unibracteata have decreased to 33.8 × 104 km2, 9.66 × 104 km2 and 6.64 × 104 km2 due to human activities. Environmental variables affecting F. unibracteata distribution included the minimum temperature in the coldest month (−16.89–−4.96 °C), annual precipitation (416.64–866.96 mm), temperature annual range (24.83–31.97 °C), elevation (2879.69–3981.82 m), human footprint (2.58–23.66) and mean UV-B of highest month (7381.92–8574.27 kJ/m2). In the 2050s and 2090s, human activities would significantly reduce the highly suitable habitats of F. unibracteata. Under SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios, the centroid would move to the low latitude area from the current position first, and then to a high latitude area. Wild resources of F. unibracteata in China can be effectively conserved based on our results.

Abstract Background The proteome is a major source of therapeutic targets. We conducted a proteome-wide Mendelian randomization (MR) study to identify candidate protein markers and therapeutic targets for colorectal cancer (CRC). Methods Protein quantitative trait loci (pQTLs) were derived from seven published genome-wide association studies (GWASs) on plasma proteome, and summary-level data were extracted for 4853 circulating protein markers. Genetic associations with CRC were obtained from a large-scale GWAS meta-analysis (16,871 cases and 26,328 controls), the FinnGen cohort (4957 cases and 304,197 controls), and the UK Biobank (9276 cases and 477,069 controls). Colocalization and summary-data-based MR (SMR) analyses were performed sequentially to verify the causal role of candidate proteins. Single cell-type expression analysis, protein-protein interaction (PPI), and druggability evaluation were further conducted to detect the specific cell type with enrichment expression and prioritize potential therapeutic targets. Results Collectively, genetically predicted levels of 13 proteins were associated with CRC risk. Elevated levels of two proteins (GREM1, CHRDL2) and decreased levels of 11 proteins were associated with an increased risk of CRC, among which four (GREM1, CLSTN3, CSF2RA, CD86) were prioritized with the most convincing evidence. These protein-coding genes are mainly expressed in tissue stem cells, epithelial cells, and monocytes in colon tumor tissue. Two interactive pairs of proteins (GREM1 and CHRDL2; MMP2 and TIMP2) were identified to be involved in osteoclast differentiation and tumorigenesis pathways; four proteins (POLR2F, CSF2RA, CD86, MMP2) have been targeted for drug development on autoimmune diseases and other cancers, with the potentials of being repurposed as therapeutic targets for CRC. Conclusions This study identified several protein biomarkers to be associated with CRC risk and provided new insights into the etiology and promising targets for the development of screening biomarkers and therapeutic drugs for CRC.

Excessive use of organophosphate pesticides (OP), such as dichlorvos, in farming system poses a threat to human health through potential contamination of environment. To date, biodegradation has been prospected most promising approach to eliminate environmental OP residues. Trichoderma species as a biological control microorganism is often exposed to the chemical pesticides applied in environments, so it is necessary to understand the mechanism of degradation of dichlorvos by Trichoderma. In this study, dichlorvos significantly inhibited the growth, sporulation and pigmentation of T. atroviride T23, and the dichlorvos degradation activity of T23 required the initial induction effect of dichlorvos and the culture conditions, including the nutrient and pH values of the medium. Various changed primary and secondary metabolites released from T23 in the presence of dichlorvos were speculated as the energy and antioxidants for the strain itself to tolerate dichlorvos stress. The results showed that T23 could produce a series of enzymes, especially the intracellular enzymes, to degrade dichlorvos. The activities of the intracellular enzyme generated by T23 were differentially changed along time course and especially relied on initial dichlorvos concentration, ammonium sulfate and phosphate added in the medium. In conclusion, some dichlorvos-induced chemical degradation related enzymes of T23 were proved to be involved in the degradation of dichlorvos.

Abstract Background Class attendance is important for academic performance. Personal interactions between teachers and students are difficult in large classes; the number of medical undergraduate students in China ranges from dozens to over 100. It is important for teachers to control the teaching process to improve student attendance and participation. Methods Two classes of fourth-year undergraduate medical students, with each class comprising 115 students, participated in the study. One class, the trial group, was taught by the block-based teaching method based on cybernetics. This study was conducted with three of the courses in the Introduction to Oncology subject, and the trial group’s courses included several blocks. Each block had a test paper that the students responded to immediately in class using the Internet. The teacher obtained feedback from the students when the rate of correct responses to block-test questions was less than 90%. The teacher adjusted the teaching in the following blocks according to the feedback information. The other class, the control group, was taught using the traditional lecture-based teaching method. Results The average attendance in the trial group was 104/115 (90.43%), and that in the control group was 83/115 (72.17%) (p = 0.0003). The teacher adjusted the teaching three times in the radiotherapy course owing to the complex ideas. After feedback, information on chemotherapy for the upper body was adjusted once, as was that on chemotherapy for the lower body, owing to students’ attitudes. The average total score of the trial group was 86.06 ± 17.46 and that of the control group was 80.38 ± 6.97 (p = 0.041). Questionnaire I showed that the trial group students’ attendance and participation were better than in the control group. Questionnaire II showed that the block-based teaching method based on cybernetics was approved by the students. Conclusions The block-based teaching method based on cybernetics used in medical classes with large numbers of Chinese undergraduate students had positive effects.

Abstract Pyopneumothorax with bronchopleural fistula is a rare complication of lung infection. We herein report a case of pyopneumothorax with bronchopleural fistula caused by Porphyromonas gingivalis infection, a common pathogenic pathogen of periodontitis, in a 49‐year‐old man with periodontitis. The patient was admitted with respiratory failure. Pleural puncture yielded a lot of gas continually and foul‐smelling light brown pus, which was found to be caused due to infection with P. gingivalis by the metagenomic next generation sequencing (mNGS) and anaerobic culture.

Abstract Objective To systematically evaluate the effect of Acceptance and Commitment Therapy (ACT) on depressive disorders. Methods The electronic databases of Web of Science Core Collection, Pubmed, EMBASE, Cochrane Library, PsycInfo, CNKI, Wanfang and Weipu were used to select relevant publications. Screening, data extraction, and quality assessment were undertaken following PRISMA guidelines for preferred reporting of systematic reviews and meta-analysis. RevMan5.4 was used for meta-analysis. Results 11 studies with a total of 962 patients were included. Random-effects model analysis showed that ACT could effectively reduce the level of depressive symptoms in patients with depressive disorders (SMD = − 1.05, 95% CI: − 1.43–− 0.66, P

Due to the rapid development of renewable energy (RE), the power transmission and transformation equipment of some renewable energy gathering stations are congested especially at noon. Therefore, an operation simulation method considering energy storage system (ESS) is proposed, and some evaluation indices of source-network-storage are given. This paper proposes two solutions to alleviate the contradiction between renewable energy utilization and equipment congestion: expanding equipment and configuring ESS. To compare the utilization rate of renewable energy and the investment cost of the power grid, the cost of two schemes of expanding key gathering station equipment and configuring ESS under the condition of increasing the same utilization rate of renewable energy are compared, to give suggestions for the coordinated development of renewable energy and power transmission and transformation investment. ROTS system is used to compare two schemes of equipment expansion and ESS configuration in some renewable energy gathering stations with transmission and transformation congestion. The appropriate scheme is selected according to the indices proposed.

Due to computational limitations, generation expansion planning often selects representative days to ensure computational efficiency. The optimality of the generation expansion planning solution greatly depends on the accuracy of the selected representative days. At present, the selection of representative days mostly adopts historical data. This method is essentially to separate the selection of representative days from the planning. We get the planning results according to the selected representative days, and then operate the simulation under the representative days. This method is feasible without considering the renewable energy expansion planning, because the net load curve does not change before and after the planning. However, in the context of the increasing penetration of renewable energy, this method of selecting representative days cannot represent the actual operating situation of the system. The net load data before and after the planning changes, and the representative days before the planning cannot reflect the actual running situation after the planning. Based on the above questions, this paper has proposed a representative day selection method based on forward–backward sweep that provides three advantages: the target level of net-load curve is captured, the representative days can reflect the future situation in reality, and a linear relaxation method to enhance computational effectiveness is designed. This method can effectively reduce the error of traditional methods and the effectiveness has been demonstrated in XJTU-ROTS test system.

Renewable energy sources, such as wind and solar photovoltaic, have been widely deployed in power systems due to the decarbonization transition target and technological advances. The large-share integration of renewable generation contributes to the construction of a low-carbon power system and imposes significant flexibility requirements for the power system. The reliability and security in power system operation and RES generation accommodation are deeply involved with the configuration mixes and the portfolio of flexible resources. Therefore, this paper proposes a coordinated capacity expansion planning model with a variety of flexibility technologies, including thermal power flexibility retrofitting, energy storage systems, demand-side responses, as well as concentrating solar power plants. A scenario-based approach is adopted to capture uncertainties from electric load and renewable generation. The proposed planning model is constructed as a two-stage stochastic planning framework, where the first stage optimizes investment strategies of flexible technologies while the second stage determines the optimal power dispatch for all generation assets under different operation conditions. The hourly operation simulation model is also embedded in the proposed planning model with detailed operation constraints. The effectivity of the proposed coordinated planning model is verified by a modified reliability and operation test system. Numerical results show that different combinations of flexibility technologies have distinct impacts on the power system’s economic and environmental performances, which implies the significance of finding an optimal portfolio of flexibility resources in the power system with large-scale renewable energy sources.

Wildlife serve as potential microbial reservoirs, accounting for approximately 70% of emerging infectious diseases. Crimean–Congo hemorrhagic fever virus (CCHFV), which causes Crimean–Congo hemorrhagic fever (CCHF) in humans, is a highly pathogenic tick-borne virus prevalent in several parts of Asia, Africa, and Europe with high case fatality rates. Several CCHFV cases have been reported in Asia, the Middle East, Africa, and Southern and Eastern Europe. The disease is endemic in several parts of western China, particularly Xinjiang. Ticks of the genus Hyalomma have been identified as a principal vector and reservoir for CCHFV, although other tick species may also have a crucial role in maintaining CCHFV in endemic regions. On infection, CCHF begins as a nonspecific febrile illness that can progress to severe hemorrhagic manifestations with a higher case fatality due to the unavailability of vaccines or other therapeutic agents. In this study, we collected tissue samples from a wild dead Chinese serow (Capricornis milneedwardsii) and three Naemorhedus griseuses from Deqin County, Tibetan Autonomous Prefecture, Yunnan, China, to investigate for contagious viruses that could be transmitted to humans. We identified a novel CCHFV strain, YNDQL-415G, in the liver tissue of a dead C. milneedwardsii. We performed nucleotide and amino acid sequence homology on the full-length viral genome. The results revealed significant homology between the viral S segment to that of the Africa1 strain, while the M and L segments showed similarity with the Asia CCHFV strain, indicating potential gene reassortment in the YNDQL-415G strain. The genetic characterization of a novel CCHFV strain from a dead C. milneedwardsii raises concerns about the possibility of a new zoonotic infection. A regular survey program is recommended to track the distribution of wild animals as well as the viruses they may transmit to humans and other domestic mammals in the region.

Road extraction from high-resolution remote sensing images (HRSIs) is one of the tasks in image analysis. Deep convolutional neural networks have become the primary method for road extraction due to their powerful feature representation capability. However, roads are often obscured by vegetation, buildings, and shadows in HRSIs, resulting in incomplete and discontinuous road extraction results. To address this issue, we propose a lightweight post-processing network called RIRNet in this study, which include an information inference module and a road direction inference task branch. The information inference module can infer spatial information relationships between different rows or columns of feature images from different directions, effectively inferring and repairing road fractures. The road direction inference task branch performs the road direction prediction task, which can constrain and promote the road extraction task, thereby indirectly enhancing the inference ability of the post-processing model and realizing the optimization of the initial road extraction results. Experimental results demonstrate that the RIRNet model can achieve an excellent post-processing effect, which is manifested in the effective repair of broken road segments, as well as the handling of errors such as omission, misclassification, and noise, proving the effectiveness and generalization of the model in post-processing optimization.

People’s reduced connection with nature has led to many health problems. In the NBS framework, urban wildscapes (UWSs) are considered an important solution. They can contribute to improving the health of residents and ecosystems within the city. However, overly wild green spaces may also be offensive to residents. It is necessary to understand the public’s acceptance of UWSs. Current studies on the acceptance of UWSs have used vague terms to generalize the “wildness degree”. In this study, we attempted to quantify the degree of wildness using plant height and plant abundance in Japan and analyzed the results through mediated effect analysis. We discovered the following: 1. Japanese residents have low acceptance of UWSs in vacant lots. 2. The use of “height” and “abundance” may be a more objective way to quantify wildness. 3. The negative effects of abundance can be minimized. The negative effect of height cannot be controlled. This study addresses a gap in the study of Asian cities and proposes a novel approach to quantifying “wildness.” It improves the health benefits of UWSs. Furthermore, it can offer guidance on the management and construction of urban green spaces.

Capacitors are crucial components in power electronic converters, responsible for harmonic elimination, energy buffering, and voltage stabilization. However, they are also the most susceptible to damage due to their operational environment. Accurate temperature estimation of capacitors is essential for monitoring their condition and ensuring the reliability of the converter system. This paper presents a novel method for estimating the core temperature of capacitors using a long short-term memory (LSTM) algorithm. The approach incorporates a continued training mechanism to adapt to variable load conditions in converters. Experimental results demonstrate the proposed method’s high accuracy and robustness, making it suitable for real-time capacitor temperature monitoring in practical applications.

Reconstructing the state of quantum many-body systems is of fundamental importance in quantum information tasks, but extremely challenging due to the curse of dimensionality. In this work, we present an efficient quantum tomography protocol that combines the state-factored with eigenvalue mapping to address the rank-deficient issue and incorporates a momentum-accelerated gradient descent algorithm to speed up the optimization process. We implement extensive numerical experiments to demonstrate that our factored gradient descent algorithm efficiently mitigates the rank-deficient problem and admits orders of magnitude better tomography accuracy and faster convergence. We also find that our method can accomplish the full-state tomography of random 11-qubit mixed states within one minute.

In adapting to the double-high development trend of high-voltage direct current (HVDC) receiving-end power systems and solving optimization problems in emergency frequency control (EFC) supporting virtual power plants (VPPs) in large-scale power systems, a parameter estimation method for a VPP frequency response model based on a successive linear programming (SLP) method is proposed. First, a “centralized/decentralized” hierarchical control architecture for VPP participation in EFC is designed. Second, the frequency response characteristics of multiple flexible resources are scientifically analyzed, and the system frequency response (SFR) model and equivalent model of VPP are constructed. Subsequently, parameter estimation of the VPP frequency response model is carried out based on the SLP method, aiming to balance the accuracy and computational efficiency of the model. Finally, the effectiveness of the proposed methodology is verified by using PSD-BPA to simulate and test the three-zone HVDC recipient area grid.

Wave-induced radiation stress (RS), as a primary driver of ocean currents influenced by waves, plays an important role in the response of upper ocean temperatures under typhoons. Previous studies have mainly focused on wave-generated currents and coastal currents in nearshore areas. This paper incorporates the geostrophic effect into the wave-induced radiation stress of wave-current interaction, and the effect of waves on the changes in upper ocean temperature (including sea surface temperature (SST) and mixed layer temperature) under typhoon Nanmadol (2022) is studied. The FVCOM-SWAVE model is used to conduct a preliminary numerical study in the western Pacific Ocean. The RS with the geostrophic effect increased the horizontal and vertical components, leading to an enhancement in turbulent mixing and a decrease in SST by up to 1.0 °C to 1.4 °C, which is closer to the SST obtained by OISST remote sensing fusion observation data. In the strong divergence domain, the direction of the vortex flow exhibits a more pronounced turn to the right, accompanied by an increase in water velocity. The vertical temperature profile of the ocean shows that the water below is perturbed by the RS component of the geostrophic effect, and the depth of the mixed layer increases by about 2 m, which is closer to the depth of the mixed layer observed by the Argo floats, indirectly enhancing the vertical mass transport of the ocean. In general, this shows that RS, which takes into account geostrophic effects, enhances the effect of waves on the water below, indirectly leading to lower temperatures in the upper ocean, and the simulated results align more closely with the observed data, offering valuable insights for enhancing marine numerical forecasting accuracy.

The GNSS-based bistatic SAR (GNSS-BSAR) system has emerged as a hotspot due to its low power consumption, nice concealment, and worldwide reach. However, the weak landing power density of the GNSS signal often necessitates prolonged integration to achieve an adequate signal-to-noise ratio (SNR). In this case, the effects of the receiver’s time-frequency errors and atmospheric disturbances are significant and cannot be ignored. Therefore, we propose an ionospheric scintillation compensation-based imaging scheme for dual-channel GNSS-BSAR system. This strategy first extracts the reference phase, which contains the ionospheric phase scintillation and other errors. Subsequently, the azimuth phase of the target is divided into difference phase and reference phase. We apply the two-step phase compensation to eliminate Doppler phase errors, thus achieving precise focusing of SAR images. Three sets of experiments using the GPS L5 signal as the illuminator were conducted, coherently processing a 1.5 km by 0.8 km scene about 300 s. The comparative results show that the proposed method exhibited better focusing performance, avoiding the practical challenges encountered by traditional autofocus algorithms. Additionally, ionospheric phase scintillation extracted at different times of the day suggest diurnal variations, preliminary illustrating the potential of this technology for ionospheric-related studies.

SAR (synthetic aperture radar) ship detection is a hot topic due to the breadth of its application. However, limited by the volume of the SAR image, the generalization ability of the detector is low, which makes it difficult to adapt to new scenes. Although many data augmentation methods—for example, clipping, pasting, and mixing—are used, the accuracy is improved little. In order to solve this problem, the adversarial training is used for data generation in this paper. Perturbation is added to the SAR image to generate new samples for training, and it can make the detector learn more abundant features and promote the robustness of the detector. By separating batch normalization between clean samples and disturbed images, the performance degradation on clean samples is avoided. By simultaneously perturbing and selecting large losses of classification and location, it can keep the detector adaptable to more confrontational samples. The optimization efficiency and results are improved through K-step average perturbation and one-step gradient descent. The experiments on different detectors show that the proposed method achieves 8%, 10%, and 17% AP (Average Precision) improvement on the SSDD, SAR-Ship-Dataset, and AIR-SARShip, compared to the traditional data augmentation methods.

In order to investigate the contact characteristics of the mechanical parts of the brewing robot with wine lees particles, it is essential to calibrate the parameters of the discrete elemental model of wine lees particles. This paper proposes a method based on tests of the angle of repose. The simulation test is conducted to establish a regression model and combined with physical tests to find optimization. The contact model used in simulation modeling is Hertz-Mindlin with Johnson-Kendall-Roberts. Not all discrete element model parameters of wine lees particles have a significant impact on the angle of repose, so screening through Plackett-Burman Design is performed. The results indicate that the restitution coefficient between wine lees particles and restitution coefficient between wine lees particle and steel plate have a significant impact on angle of repose. Additionally, another parameter that is difficult to obtain, namely surface energy (JKR), also plays a crucial role. The optimal value interval for these three parameters is determined by the steepest ascent test, and a linear regression model for angle of repose is built through Box-Behnken Design. The optimal values obtained are as follows: restitution coefficient between wine lees particles—0.603; restitution coefficient between wine lees particle and steel plate—0.595; JKR—0.083. Finally, in order to verify the accuracy of calibrated parameters, simulation verification tests are carried out which show that there is only a relative error rate at 0.18% between simulated angle of repose and actual angle of repose, indicating that accurate calibration parameters were achieved. This study can provide reference for selecting discrete element model parameters for wine lees particles in future research endeavors.

Focusing on the comparison of aging resistance between styrene-butadiene-styrene (SBS) modified asphalt (SBSMA) and crumb rubber modified asphalt binders (CRMA), the influences of aging on rheological properties and microstructural characteristics of different modified asphalts were investigated in this work. Dynamic Shear Rheometer (DSR) and Bending Beam Rheometer (BBR) tests were carried out, and the variations in rheological properties for different modified asphalts after the rotating thin film oven test (RTFOT) were analyzed with the rutting factor aging index (RAI) and creep rate aging index (CAI). By using Fluorescence microscopy (FM) and Fourier transform infrared (FTIR) spectroscopy, the evolutions of microstructure and chemical composition for two modified asphalts were analyzed with carbonyl index growth rate (CIR) and sulfoxide index growth rate (SIR). Then, The relationships between CIR/SIR and RAI/CAI were established to show the correlation between the deterioration of macroscopic performance and the evolution of micro-structure. The results indicated that the aging degree of asphalt increases with elevated temperatures, leading to decreasing low-temperature performance while improving high-temperature performance. Nevertheless, SBSMA exhibited strong sensitivity to aging temperature. Under thermo-oxidative aging, the RAI and CAI of SBSMA were lower than those of CRMA, whereas the regularities of CIR and SIR were opposite, indicating that CRMA was superior to SBSMA in terms of anti-aging properties due to the rupture of the cross-linked network structure of SBSMA. However, CRMA experienced aging accompanied by full swelling, and thus, relatively minor performance declined. The CIR and SIR exhibited a better correlation with the RAI and CAI, illustrating that both CIR and SIR could characterize the aging degree of modified asphalts well.

Aeromagnetic surveys are widely used in geological exploration, mineral resource assessment, environmental monitoring, military reconnaissance, and other areas. It is necessary to perform magnetic compensation for interference in these fields. In recent years, large unmanned aerial vehicles (UAVs) have been more suitable for magnetic detection missions because of the greater loads they can carry. This article proposes some methods for the magnetic compensation of large multiload UAVs. Because of the interference of the large platform and instrument noise, the standard deviations (stds) of the compensation data used in this paper are larger. At the beginning of this article, using the traditional T-L model, we avoid the shortcomings of the anti-magnetic interference ability of triaxial magnetic gate magnetometers. The direction cosine information is obtained by using an inertial navigation system, the global positioning system, and a triaxial magnetic gate magnetometer. Then, we increase the amplitude of the maneuvers in the compensation process; this reduces the multicollinearity problems in the compensation matrix to a certain extent, but it also results in greater magnetic field interference. Lastly, we employ the method of Lasso regularization Newton iteration (LRNM). Compared to the traditional methods of least squares (LS) and singular value decomposition (SVD), LRNM provides improvements of 34% and 27%, respectively. In summary, this series of schemes can be used to perform effective compensation for large multi-load UAVs and improve the actual use of large UAVs, making them more accurate in the measurement of aeromagnetic survey data.

Electromagnetic micro mirrors are in great demand for light detection and ranging (LiDAR) applications due to their light weight and low power consumption. The driven frequency of electromagnetic micro mirrors is very important to their performance and consumption. An electromagnetic micro mirror system is proposed in this paper. The model of the system was composed of a micro mirror, an integrated piezoresistive (PR) sensor, and a driving circuit was developed. The twisting angle of the mirror edge was monitored by an integrated PR sensor, which provides frequency feedback signals, and the PR sensor has good sensitivity and linearity in testing, with a maximum of 24.45 mV/deg. Stable sinusoidal voltage excitation and frequency tracking was realized via a phase-locked loop (PLL) in the driving circuit, with a frequency error within 10 Hz. Compared with other high-cost solutions using PLL circuits, it has greater advantages in power consumption, cost, and occupied area. The mechanical and piezoresistive properties of micro mirrors were performed in ANSYS 19.2 software. The behavior-level models of devices, circuits, and systems were validated by MATLAB R2023a Simulink, which contributes to the research on the large-angle deflection and low-power-consumption drive of the electromagnetic micro mirror. The maximum optical scan angle reached 37.6° at 4 kHz in the behavior-level model of the micro mirror.

Rainfall-induced landslides are a major hazard in the Three Gorges Reservoir area (TGRA) of China, encompassing 19 districts and counties with extensive coverage and significant spatial variation in terrain. This study introduces the Gradient Boosting Decision Tree (GBDT) model, implemented on the Google Earth Engine (GEE) cloud platform, to dynamically assess landslide risks within the TGRA. Utilizing the GBDT model for landslide susceptibility analysis, the results show high accuracy with a prediction precision of 86.2% and a recall rate of 95.7%. Furthermore, leveraging GEE’s powerful computational capabilities and real-time updated rainfall data, we dynamically mapped landslide hazards across the TGRA. The integration of the GBDT with GEE enabled near-real-time processing of remote sensing and meteorological radar data from the significant “8–31” 2014 rainstorm event, achieving dynamic and accurate hazard assessments. This study provides a scalable solution applicable globally to similar regions, making a significant contribution to the field of geohazard analysis by improving real-time landslide hazard assessment and mitigation strategies.

BackgroundThis study aims to investigate the changes in circulating dipeptidyl peptidase-4 (DPP-4) activity following short-term intensive insulin therapy (SIIT) in newly diagnosed type 2 diabetes (T2D) patients and to assess its potential in predicting long-term remission.MethodsNinety-five patients underwent SIIT for 2-3 weeks to attain and sustain near-normal glycemia. Insulin was then discontinued, and patients were followed for a year to evaluate glycemic outcomes. Biochemical tests, serum DPP-4 activity, and mixed meal tolerance tests were conducted at baseline, post-SIIT, and the 3-month follow-up.ResultsDPP-4 activity decreased from 44.08 ± 9.58 to 40.53 ± 8.83 nmol/min/mL after SIIT (P

BackgroundThe objective of this study was to examine differences in availability and use of telehealth services among Medicare enrollees according to Alzheimer’s disease and related dementias (ADRD) status and enrollment in Medicare Advantage (MA) versus Traditional Medicare (TM) during the period surrounding the COVID-19 pandemic.MethodsThis was a retrospective cross-sectional analysis of data from community-dwelling MA and TM enrollees with and without ADRD from the Medicare Current Beneficiary Survey (MCBS) Fall 2020 and Winter 2021 COVID-19 Supplement Public Use Files. We examined self-reported availability of telehealth service before and during the COVID-19 pandemic and use of telehealth services during COVID-19. We analyzed marginal effects under multivariable logistic regression.ResultsThere were 13,700 beneficiaries with full-year enrollment in MA (6,046) or TM (7,724), 518 with ADRD and 13,252 without ADRD. Telehealth availability during COVID-19 was positively associated with having a higher income (2.81 pp. [percentage points]; 95% CI: 0.57, 5.06), having internet access (7.81 pp.; 95% CI: 4.96, 10.66), and owning telehealth-related technology (3.86; 95% CI: 1.36, 6.37); it was negatively associated with being of Black Non-Hispanic ethnicity (−8.51 pp.; 95% CI: −12.31, −4.71) and living in a non-metro area (−8.94 pp.; 95% CI: −13.29, −4.59). Telehealth availability before COVID-19 was positively associated with being of Black Non-Hispanic ethnicity (9.34 pp.; 95% CI: 3.74, 14.94) and with enrollment in MA (4.72 pp.; 95% CI: 1.63, 7.82); it was negatively associated having dual-eligibility (−5.59 pp.; 95% CI: −9.91, −1.26). Telehealth use was positively associated with being of Black Non-Hispanic ethnicity (6.47 pp.; 95% CI: 2.92, 10.01); it was negatively associated with falling into the age group of 75+ years (−4.98 pp.; 95% CI: −7.27, −2.69) and with being female (−4.98 pp.; 95% CI: −7.27, −2.69).ConclusionTelehealth services were available to and used by Medicare enrollees with ADRD to a similar extent compared to their non-ADRD counterparts. Telehealth services were available to MA enrollees to a greater extent before COVID-19 but not during COVID-19, and this group did not use telehealth services more than TM enrollees during COVID-19.

Introduction Radiographic bone age (BA) assessment is widely used to evaluate children’s growth disorders and predict their future height. Moreover, children are more sensitive and vulnerable to X-ray radiation exposure than adults. The purpose of this study is to develop a new, safer, radiation-free BA assessment method for children by using three-dimensional ultrasound (3D-US) and artificial intelligence (AI), and to test the diagnostic accuracy and reliability of this method.Methods and analysis This is a prospective, observational study. All participants will be recruited through Paediatric Growth and Development Clinic. All participants will receive left hand 3D-US and X-ray examination at the Shanghai Sixth People’s Hospital on the same day, all images will be recorded. These image related data will be collected and randomly divided into training set (80% of all) and test set (20% of all). The training set will be used to establish a cascade network of 3D-US skeletal image segmentation and BA prediction model to achieve end-to-end prediction of image to BA. The test set will be used to evaluate the accuracy of AI BA model of 3D-US. We have developed a new ultrasonic scanning device, which can be proposed to automatic 3D-US scanning of hands. AI algorithms, such as convolutional neural network, will be used to identify and segment the skeletal structures in the hand 3D-US images. We will achieve automatic segmentation of hand skeletal 3D-US images, establish BA prediction model of 3D-US, and test the accuracy of the prediction model.Ethics and dissemination The Ethics Committee of Shanghai Sixth People’s Hospital approved this study. The approval number is 2022-019. A written informed consent will be obtained from their parent or guardian of each participant. Final results will be published in peer-reviewed journals and presented at national and international conferences.Trial registration number ChiCTR2200057236.

In buildings that experience fires, cement mortar is subjected to high-temperature environments and not only the weight of the structure above but also blast loads, leading to structural damage and loss of load-bearing capacity. To investigate the static and dynamic mechanical properties of thermally damaged mortar, a series of tests utilizing modified split Hopkinson pressure bar were conducted. These tests included quasi-static, conventional dynamic and coupled static-dynamic loading tests on mortar specimens that were subjected to seven temperature levels: 20°C, 100°C, 200°C, 300°C, 400°C, 500°C, and 600°C. The test results revealed that both the thermal damage and loading method had an impact on the mechanical properties and damage characteristics of the mortar specimens. The compressive strength, elastic modulus and absorbed energy ratio of mortar decreased as temperature increased. Notably, the quasi-static strength loss rate was 60% when the temperature reached 600°C. Under coupled static-dynamic loading, the specimens exhibited higher strength, elastic modulus, reflected energy ratio, and transmitted energy ratio. Conversely, they had lower average strain rates and absorbed energy ratios. Intriguingly, the dynamic growth factor had a relative increase of 0.7–2.0 compared with other loading methods. Furthermore, the higher temperature, the higher fragmentation of the specimens in the fragmentation pattern. Conventional dynamic loading resulted in the greatest degree of fragmentation. The findings provide a scientific basis for the design and evaluation of concrete shockproof and explosion-resistant structures.

ABSTRACT Microsporidia are obligate intracellular parasites that infect a wide variety of hosts including humans. Microsporidian spores possess a unique, highly specialized invasion apparatus involving the polar filament, polaroplast, and posterior vacuole. During spore germination, the polar filament is discharged out of the spore forming a hollow polar tube that transports the sporoplasm components including the nucleus into the host cell. Due to the complicated topological changes occurring in this process, the details of sporoplasm formation are not clear. Our data suggest that the limiting membrane of the nascent sporoplasm is formed by the polaroplast after microsporidian germination. Using electron microscopy and 1,1′-dioctadecyl-3,3,3′,3′ tetramethyl indocarbocyanine perchlorate staining, we describe that a large number of vesicles, nucleus, and other cytoplasm contents were transported out via the polar tube during spore germination, while the posterior vacuole and plasma membrane finally remained in the empty spore coat. Two Nosema bombycis sporoplasm surface proteins (NbTMP1 and NoboABCG1.1) were also found to localize in the region of the polaroplast and posterior vacuole in mature spores and in the discharged polar tube, which suggested that the polaroplast during transport through the polar tube became the limiting membrane of the sporoplasm. The analysis results of Golgi-tracker green and Golgi marker protein syntaxin 6 were also consistent with the model of the transported polaroplast derived from Golgi transformed into the nascent sporoplasm membrane.IMPORTANCEMicrosporidia, which are obligate intracellular pathogenic organisms, cause huge economic losses in agriculture and even threaten human health. The key to successful infection by the microsporidia is their unique invasion apparatus which includes the polar filament, polaroplast, and posterior vacuole. When the mature spore is activated to geminate, the polar filament uncoils and undergoes a rapid transition into the hollow polar tube that transports the sporoplasm components including the microsporidian nucleus into host cells. Details of the structural difference between the polar filament and polar tube, the process of cargo transport in extruded polar tube, and the formation of the sporoplasm membrane are still poorly understood. Herein, we verify that the polar filament evaginates to form the polar tube, which serves as a conduit for transporting the nucleus and other sporoplasm components. Furthermore, our results indicate that the transported polaroplast transforms into the sporoplasm membrane during spore germination. Our study provides new insights into the cargo transportation process of the polar tube and origin of the sporoplasm membrane, which provide important clarification of the microsporidian infection mechanism.

Exosomes, extracellular vesicles secreted by cells, have garnered significant attention in recent years for their remarkable therapeutic potential. These nanoscale carriers can be harnessed for the targeted delivery of therapeutic agents, such as pharmaceuticals, proteins, and nucleic acids, across biological barriers. This versatile attribute of exosomes is a promising modality for precision medicine applications, notably in the realm of cancer therapy. However, despite their substantial therapeutic potential, exosomes still confront challenges tied to standardization and scalability that impede their practice in clinical applications. Moreover, heterogeneity in isolation methodologies and limited cargo loading mechanisms pose obstacles to ensuring consistent outcomes, thereby constraining their therapeutic utility. In contrast, exosomes exhibit a distinct advantage in cancer diagnosis, as they harbor specific signatures reflective of the tumor’s genetic and proteomic profile. This characteristic endows them with the potential to serve as valuable liquid biopsies for non-invasive and real-time monitoring, making possible early cancer detection for the development of personalized treatment strategies. In this review, we provide an extensive evaluation of the advancements in exosome research, critically examining their advantages and limitations in the context of cancer therapy and early diagnosis. Furthermore, we present a curated overview of the most recent technological innovations utilizing exosomes, with a focus on enhancing the efficacy of early cancer detection.

The objective of this paper is to discuss the influence of geometric parameters on the performance of the rotational hydrodynamic cavitation reactor (RHCR) using numerical method. The novel RHCR is implemented by modifying a centrifugal impeller into a new one using the annular slit constriction (ASC) with circumferentially distributed blind holes. The cavitation intensity and cavitation generation rate are selected to evaluate the cavitation performance, the head is used to assess conveying performance, and the entropy generation theory is used to evaluate the energy loss in the impeller. The effect of the axial width, radial length and radial position of the ASC on the cavitating flow of the RHCR is investigated by CFD method. The results indicate that three patterns of cavitation are induced in the RHCR, including separation cavitation, vortex cavitation and shear cavitation. The axial width, radial length and radial position of the ASC are the important geometric parameter that affect the performance of the RHCR. A small width is superior to a large width in terms of cavitation performance, although the conveying performance suffers as a result. The energy loss in the impeller initially increases and then decreases as the width decreases. Both a reduction in radial length and radial position leads to higher cavitation and conveying capacity, accompanying slight increase in energy loss. Compared to the original model, the RHCR with an axial width of 3 mm, a radial length of 17 mm, and a radial position of 0.541 achieves the highest performance.

ObjectiveMany patients treated with immune checkpoint inhibitors (ICIs) developed primary or secondary drug resistance for unknown reasons. This study investigates whether mismatch repair (MMR) genes are responsible for this therapeutic restriction.MethodsWe obtained the transcriptional, clinical and single nucleotide polymorphism data for endometrial cancer (EC) from The Cancer Genome Atlas and the immunophenoscore data of EC from The Cancer Immunome Atlas, then analyzed in R to evaluate the relationship between MMR genes and clinicopathological features, prognosis, immune infiltration, immune checkpoint expression and responsiveness to ICIs in EC. We used differentially expressed genes in the MSH6 high and low expression groups to conduct GO and KEGG analyses to explore the impact of MSH6 on the biological functions of EC. Finally, we verified the bioinformatics results with in vitro experiments.ResultsOur analyses showed that compared with the high MSH6 expression group, the low MSH6 expression group had better survival outcomes and less aggressive clinicopathological features. In the multivariate Cox analysis, MSH6 was the only independent risk factor that could predict the prognosis of EC. Besides, the low MSH6 expression group also had a higher immune score, more active immune infiltration and higher immune checkpoint expression, resulting in better responsiveness to ICIs treatment, consistent with the enrichment of GO terms and KEGG pathways related to immune response in this group. Meanwhile, the GO and KEGG enrichment results of the MSH6 high expression group were associated with cell cycle, DNA damage repair and tumorigenesis. To exclude the influence of MSH6 mutations, we performed the previous analyses on the MSH6 wild-type tumor samples and obtained consistent results. In vitro experiments also confirmed that after knocking down MSH6 in endometrial cancer cells, their proliferation, migration and invasion abilities were weakened, while the expression levels of PD-L1 and PD-L2 were elevated. In comparison, overexpression of MSH6 showed an opposite trend.ConclusionReduced MSH6 expression could serve as a potential biomarker for predicting better prognosis, active immune status, higher immune checkpoint expression level and better responsiveness to ICIs treatment in EC. MSH6 may become a potential target for treating solid tumors.

ObjectiveTo determine whether the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism is associated with cognitive impairment (CI) in community-dwelling Chinese older adults, and to investigate whether this relationship is modified by the Apolipoprotein E (APOE) ɛ4 allele.MethodsThe study is a secondary analysis of 703 participants aged ≥60 years randomly enrolled from the Beijing Longitudinal Study of Aging II prospective cohort. The education-adjusted Mini-Mental State Examination and the Clinical Dementia Rating Scale were used to measure the cognitive performance of the subjects. The main effects and interactions (additive and multiplicative) of the BDNF Met and the APOE ε4 alleles on CI were estimated by logistic regression models.ResultsIn total, 84 out of 703 older adults aged ≥60 years old had CI. No significant difference was observed in the risk of CI between participants with the BDNF Met allele and that of subjects without the BDNF Met allele (p = 0.213; p = 0.164). Individuals carrying both the BDNF Met and APOE ε4 alleles had an almost 1.5-fold increased odds of CI compared with carriers of the BDNF Met allele but without the APOE ε4 allele. The additive association indicated a positive interaction of both BDNF Met and APOE ε4 alleles with wide CIs (p = 0.021; p = 0.018).ConclusionThe results suggest that the APOE ε4 allele may be a potential modifier for the association of the BDNF Val66Met polymorphism with CI in community-dwelling older adults.

Prior investigations have primarily focused on the impact of L-arabinose on gut microbiota, with limited exploration into the dual mechanisms of L-arabinose on microbiota and metabolism both in vivo and in vitro. Thus, this study aimed to elucidate the anti-inflammatory effects of 5 % L-arabinose under different diet in mice. Additionally, a colon simulation system (CDMN) with utilizing 1.72 % (w/v) L-arabinose in the lumen and mucus layers, to provide further insights into the underlying mechanisms. The results revealed that L-arabinose significantly altered the gut microbiome structure, particularly elevating Bifidobacterium and short-chain fatty acids (SCFAs) both in vivo and in vitro. Subsequent in vitro experiments confirmed that L-arabinose increased the relative abundance of SCFAs-producing bacteria, facilitated linoleic acid metabolism, and enhanced downstream metabolites (12,13-DHOME, 9,10-DHOME), potentially mediated by Bifidobacterium in the descending colon. These findings underscore the role of L-arabinose in modulating intestinal flora and metabolism, thereby promoting intestinal and body health.

IntroductionDepression is a prevalent mental illness that is primarily diagnosed using psychological and behavioral assessments. However, these assessments lack objective and quantitative indices, making rapid and objective detection challenging. In this study, we propose a novel method for depression detection based on eye movement data captured in response to virtual reality (VR).MethodsEye movement data was collected and used to establish high-performance classification and prediction models. Four machine learning algorithms, namely eXtreme Gradient Boosting (XGBoost), multilayer perceptron (MLP), Support Vector Machine (SVM), and Random Forest, were employed. The models were evaluated using five-fold cross-validation, and performance metrics including accuracy, precision, recall, area under the curve (AUC), and F1-score were assessed. The predicted error for the Patient Health Questionnaire-9 (PHQ-9) score was also determined.ResultsThe XGBoost model achieved a mean accuracy of 76%, precision of 94%, recall of 73%, and AUC of 82%, with an F1-score of 78%. The MLP model achieved a classification accuracy of 86%, precision of 96%, recall of 91%, and AUC of 86%, with an F1-score of 92%. The predicted error for the PHQ-9 score ranged from -0.6 to 0.6.To investigate the role of computerized cognitive behavioral therapy (CCBT) in treating depression, participants were divided into intervention and control groups. The intervention group received CCBT, while the control group received no treatment. After five CCBT sessions, significant changes were observed in the eye movement indices of fixation and saccade, as well as in the PHQ-9 scores. These two indices played significant roles in the predictive model, indicating their potential as biomarkers for detecting depression symptoms.DiscussionThe results suggest that eye movement indices obtained using a VR eye tracker can serve as useful biomarkers for detecting depression symptoms. Specifically, the fixation and saccade indices showed promise in predicting depression. Furthermore, CCBT demonstrated effectiveness in treating depression, as evidenced by the observed changes in eye movement indices and PHQ-9 scores. In conclusion, this study presents a novel approach for depression detection using eye movement data captured in VR. The findings highlight the potential of eye movement indices as biomarkers and underscore the effectiveness of CCBT in treating depression.

BackgroundS100A8, a calcium-binding protein belonging to the S100 family, is involved in immune responses and multiple tumor pathogens. Diffuse large B-cell lymphoma (DLBCL) is one of the most common types of B-cell lymphoma and remains incurable in 40% of patients. However, the role of S100A8 and its regulation of the immune response in DLBCL remain unclear.MethodsThe differential expression of S100A8 was identified via the GEO and TCGA databases. The prognostic role of S100A8 in DLBCL was calculated using the Kaplan-Meier curve. The function enrichment of differentially expressed genes (DEGs) was explored through GO, KEGG, GSEA, and PPI analysis. In our cohort, the expression of S100A8 was verified. Meanwhile, the biological function of S100A8 was applied after the inhibition of S100A8 in an in vitro experiment. The association between S100A8 and immune cell infiltration and treatment response in DLBCL was analyzed.ResultsS100A8 was significantly overexpressed and related to a poor prognosis in DLBCL patients. Function enrichment analysis revealed that DEGs were mainly enriched in the IL-17 signaling pathway. Our cohort also verified this point. In vitro experiments suggested that inhibition of S100A8 should promote cell apoptosis and suppress tumor growth. Single-cell RNA sequence analysis indicated that S100A8 might be associated with features of the tumor microenvironment (TME), and immune infiltration analyses discovered that S100A8 expression was involved in TME. In terms of drug screening, we predicted that many drugs were associated with preferable sensitivity.ConclusionElevated S100A8 expression is associated with a poor prognosis and immune infiltration in DLBCL. Inhibition of S100A8 could promote cell apoptosis and suppress tumor growth. Meanwhile, S100A8 has the potential to be a promising immunotherapeutic target for patients with DLBCL.

Introduction: Postoperative nausea and vomiting (PONV) and pain are common and distressing complications in patients undergoing surgery. However, it remains uncertain whether timing of the postoperative course or the diel rhythm influences the occurrence of PONV or severe pain. Therefore, we aimed to explore the temporal distribution of PONV and severe pain. Material and methods: In this prospective observational study, we enrolled patients aged 18–65 years with American Society of Anesthesiologists classifications I–III, who were scheduled for surgery under general anesthesia. Patients were visited postoperatively at regular intervals (every 6 h over a 24-h period). Incidence of PONV was recorded and categorized based on real-time divisions: before dawn (00:00–05:59), morning (06:00–11:59), afternoon (12:00–17:59), and evening (18:00–23:59) and as sequential periods (i.e., 0–6, 6–12, 12–18, and 18–24 h). Severe pain and use of additional remedies were also recorded. Results: A total of 724 patients were included in the final analysis. Of these, 14.92 % experienced PONV within the first 6 h, and 8.29 % received antiemetic therapy. Occurrence of PONV and administration of remedies declined over the 24-h postoperative period. The lowest rate of PONV was observed during the pre-dawn hours (5.66 %). There was no statistically significant difference in the incidence of PONV 24-h postoperatively between surgeries with different end times. Patients underwent orthopedic surgeries had the highest incidence of PONV during 18:00–23:59, gynecological surgery patients had the highest incidence at 12:00–17:59, and 6:00–11:59 for other surgery patients. All patients had the lowest incidence during 0:00–5:59. During the initial 6-h postoperative period, 24.59 % of patients experienced severe pain, which declined in the remaining episodes. Patients who underwent orthopedic and gynecological surgeries exhibited similar temporal patterns and distribution characteristics of PONV and severe pain. Discussion: Both PONV and severe pain declined within the 24-h postoperative period, particularly within the first 6 h. Additionally, the onset patterns of PONV vary among patients undergoing different types of surgeries, all patients demonstrated decreased susceptibility to PONV between 00:00–05:59. Our findings enhance prevention and treatment strategies within an optimized timeframe during the postoperative course.

Spatial association rule mining can reveal the inherent laws of spatial object interdependence and is an important part of spatial data mining. Most of the existing algorithms for mining local spatial association rules are oriented towards the spatial association between two categories of points and cannot fully reflect the spatial heterogeneity of complex spatial relations among multiple categories of points. In addition, the interactions between points in different categories are often asymmetrical. However, the existing algorithms ignore this asymmetry. To address the above problems, an algorithm for mining local spatial association rules for point data of multiple categories based on position quotients is proposed. First, the proximity relationship between points is determined by an adaptive filter, and the spatial weight value is given according to Gaussian kernel function. Then, the multivariate local colocation quotient of each point is calculated to measure the strength of the local regional spatial association rule. Finally, the Monte Carlo simulation function is used to generate a random sample distribution to test the significance of the results. The algorithm is verified on artificial simulation data and real Point of Interest (POI) data. The experimental results show that the algorithm can identify significant association regions of different spatial association rules for point sets.

Objective Gastrointestinal (GI) involvements were scarcely reported in adult anti-nuclear matrix protein 2 (NXP2) dermatomyositis (NXP2+DM). In this study, we investigated the clinical, pathological and molecular features as well as treatment options of this rare yet life-threatening disease.Methods We retrospectively collected the data of the cohort of NXP2+ DM from 2012 to 2022 in our hospital. RNA sequencing was performed in intestinal samples of perforated patients compared with healthy controls data set.Results A total of 56 patients with adult NXP2+DM were collected including 10 cases with GI involvements. Abdominal pain and melena were the initial manifestations for GI involvements with a median 10-month time lag after the diagnosis of NXP2+DM when myositis largely subsided. Within weeks, GI perforation occurred in 8 of 10 patients, while five patients underwent eight surgical interventions subsequently. The short-term mortality was observed in four patients. NXP2+DM with GI involvements presented with more extramuscular systemic manifestations such as interstitial lung disease and subcutaneous calcinosis. The GI pathological features encompassed vasculitis/vasculopathy with high MxA expression, intestinal smooth muscle necrosis and serosal calcinosis. Gene expression profile validated the type-I interferon activation and revealed that epithelial mesenchymal transition and focal adhesion pathway may also contribute. Finally, vedolizumab, an anti-α4β7-integrin monoclonal antibody, exhibited promising therapeutic signals which should be further investigated.Conclusions GI involvement is a unique complication in patients with adult NXP2+DM. Timely recognition and targeted therapy may turn out to be lifesaving.

Ophiocordyceps sinensis is a genus of ascomycete fungi that has been widely used as a valuable tonic or medicine. However, due to over-exploitation and the destruction of natural ecosystems, the shortage of wild O. sinensis resources has led to an increase in artificially cultivated O. sinensis. To rapidly and accurately identify the molecular differences between cultivated and wild O. sinensis, this study employs surface-enhanced Raman spectroscopy (SERS) combined with machine learning algorithms to distinguish the two O. sinensis categories. Specifically, we collected SERS spectra for wild and cultivated O. sinensis and validated the metabolic profiles of SERS spectra using Ultra-Performance Liquid Chromatography coupled with Orbitrap High-Resolution Mass Spectrometry (UPLC-Orbitrap-HRMS). Subsequently, we constructed machine learning classifiers to mine potential information from the spectral data, and the spectral feature importance map is determined through an optimized algorithm. The results indicate that the representative characteristic peaks in the SERS spectra are consistent with the metabolites identified through metabolomics analysis, confirming the feasibility of the SERS method. The optimized support vector machine (SVM) model achieved the most accurate and efficient capacity in discriminating between wild and cultivated O. sinensis (accuracy = 98.95%, 5-fold cross-validation = 98.38%, time = 0.89s). The spectral feature importance map revealed subtle compositional differences between wild and cultivated O. sinensis. Taken together, these results are expected to enable the application of SERS in the quality control of O. sinensis raw materials, providing a foundation for the efficient and rapid identification of their quality and origin.

With the development of artificial intelligence and breakthroughs in deep learning, large-scale foundation models (FMs), such as generative pre-trained transformer (GPT), Sora, etc., have achieved remarkable results in many fields including natural language processing and computer vision. The application of FMs in autonomous driving holds considerable promise. For example, they can contribute to enhancing scene understanding and reasoning. By pre-training on rich linguistic and visual data, FMs can understand and interpret various elements in a driving scene, and provide cognitive reasoning to give linguistic and action instructions for driving decisions and planning. Furthermore, FMs can augment data based on the understanding of driving scenarios to provide feasible scenes of those rare occurrences in the long tail distribution that are unlikely to be encountered during routine driving and data collection. The enhancement can subsequently lead to improvement in the accuracy and reliability of autonomous driving systems. Another testament to the potential of FMs’ applications lies in world models, exemplified by the DREAMER series, which showcases the ability to comprehend physical laws and dynamics. Learning from massive data under the paradigm of self-supervised learning, world models can generate unseen yet plausible driving environments, facilitating the enhancement in the prediction of road users’ behaviors and the off-line training of driving strategies. In this paper, we synthesize the applications and future trends of FMs in autonomous driving. By utilizing the powerful capabilities of FMs, we strive to tackle the potential issues stemming from the long-tail distribution in autonomous driving, consequently advancing overall safety in this domain.

Background: This study aimed to explore the time-varying impact of COVID-19 on acute kidney disorders, including acute kidney injury and other acute kidney diseases. Methods: From the UK Biobank, 10,121 participants with COVID-19 were matched with up to 3 historically unexposed controls by age, sex, Townsend deprivation index, and the status of hospitalization or receiving critical care. We investigated the association between COVID-19 and incidence of acute kidney disorders, within the first 4 weeks after infection, using conditional and time-varying Cox proportional hazard regression. In addition, one-sample Mendelian randomization, utilizing the polygenic risk score for COVID-19 as an instrumental variable, was conducted to explore the potential causality of the association. Results: In the matched cohort study, we observed a significant association between COVID-19 and acute kidney disorders predominantly within the first 3 weeks. The impact of COVID-19 was time dependent, peaking in the second week (hazard ratio, 12.77; 95% confidence interval, 5.93 to 27.70) and decreasing by the fourth week (hazard ratio, 2.28; 95% confidence interval, 0.75 to 6.93). In subgroup analyses, only moderate to severe COVID-19 cases were associated with acute worsening of renal function in a time-dependent pattern. One-sample Mendelian randomization analyses further showed that COVID-19 might exert a “short-term” causal effect on the risk of acute kidney disorders, primarily confined to the first week after infection. Conclusions: The risk of acute kidney disorders following COVID-19 demonstrates a time-varying pattern. Hazard effects were observed only in patients with moderate or severe but not mild COVID-19.

Hyperthermia therapy is considered an effective anticancer strategy. However, high temperature can trigger an excessive inflammatory response, leading to tumor self-protection, immunosuppression, metastasis, and recurrence. To address this issue, we reported a multifunctional photothermal nanoplatform to achieve mild hyperthermia photothermal therapy (mild PTT) based on cisplatin (DDP) and a ferrocene metal-organic framework (MOF-Fc) nanocomposite, which can specifically enhance ferroptosis-triggered oxidative stress levels and synchronously amplify mild hyperthermia PTT-mediated anticancer responses. Both in vitro and in vivo antineoplastic results verify the superiority of mild PTT with DDP/MOF-Fc@HA. The combination of DDP and MOF-Fc exhibits Fenton catalytic activity and glutathione depletion capacity, magnifying mild hyperthermia effects via the radical oxygen species (ROS)-adenosine triphosphate (ATP)-HSP silencing pathway, with important implications for clinical hyperthermia therapy.

Structural analyses of transmission towers against tornados, which are of vital practical significance in design and maintenance of the structures in regions suffering from the convective weather, were rarely reported by the wind engineering community up to today. To balance the computing efficiency and the simulation accuracy, numerical calculations based on Wen’s tornadic velocity model are employed to analyze the tornado-induced structural responses of a 131-meter-high free-standing transmission tower in east China in this article. Results suggest that both the tornadic load and the structural response are noticeably greater in the lateral direction than in the longitudinal direction, and they are found to be highly nonstationary due to the traveling nature of the tornado. In addition, according to the present study, the transmission tower is not prone to the strength failure during the tornadic event and slight fatigue damages are accumulated on the tower body due to the tornadic action which can be timely warned using the structural health monitoring strategy based on field measurements of low-order structural natural frequencies. Besides the points mentioned above, the innovations of the present research additionally include the following: (1) tornado-induced structural responses and atmospheric boundary layer wind-induced structural behaviors have been compared to provide conclusions of theoretical significance; (2) a novel fatigue damage assessment method based on the high-circle fatigue damage accumulation theory has been applied to the analysis of tornado-induced structural damage; (3) the structural configuration of a key joint on a main chord has been optimized against the tornado based on the advanced response surface optimization method.

Manual acupuncture manipulation (MAM) is essential in traditional Chinese medicine treatment. MAM action recognition is important for junior acupuncturists’ training and education; however, there are obvious personalized differences in hand gestures among expert acupuncturists for the same type of MAM. In addition, during the MAM operations, the magnitude and frequency of the expert acupuncturists’ hand shape and relative needle-holding finger position changes are tiny and fast, resulting in difficulties in observing MAM action details. Thus, we propose a Spatial Multiscale Interactive Fusion MAM Recognition Network to solve the difficulties in MAM recognition. First, this paper presents an optical flow-based hand motion contour global feature extraction method for acupuncture hand shape. Second, to explore the motion rule between the needle-holding fingers during the MAM operations, we design a quantitative description method of the relative motion of the needle-holding fingers: an “interactive attention module,” which achieves feature fusion and mines the correlation between different scales of MAM action features. Finally, the proposed MAM recognition method was validated by 20 acupuncturists from the Beijing University of Traditional Chinese Medicine and 10 from the Beijing Zhongguancun Hospital who participated in the MAM video signal collection. The proposed recognition method achieves the highest average validation accuracy of 95.3% and the highest test accuracy of 96.0% for four typical MAMs, proving its feasibility and effectiveness.

The remote forcing from land surface changes in the Sahara is hypothesized to play a pivotal role in modulating the intensity of the East Asian summer monsoon (EASM) through ocean-atmospheric teleconnections. This modulation has far-reaching consequences, particularly in facilitating societal shifts documented in northern China. Here, we present a well-dated lake-level record from the Daihai Lake Basin in northern China, providing quantitative assessments of Holocene monsoonal precipitation and the consequent migrations of the northern boundary of the EASM. Our reconstruction, informed by a water-and-energy balance model, indicates that annual precipitation reached ∼700 mm during 8–5 ka, followed by a rapid decline to ∼550 mm between 5 and 4 ka. This shift coherently aligns with a significant ∼300 km northwestward movement of the EASM northern boundary during the Middle Holocene (MH), in contrast to its current position. Our findings underscore that these changes cannot be entirely attributed to orbital forcing, as corroborated by simulation tests. Climate model simulations deployed in our study suggest that the presence of the Green Sahara during the MH significantly strengthened the EASM and led to a northward shift of the monsoon rainfall belt. Conversely, the Sahara’s reversion to a desert landscape in the late Holocene was accompanied by a corresponding southward retraction of monsoon influence. These dramatic hydroclimate changes during ∼5–4 ka likely triggered or at least contributed to a shift in Neolithic cultures and societal transformation in northern China. With decreasing agricultural productivity, communities transitioned from millet farming to a mixed rainfed agriculture and animal husbandry system. Thus, our findings elucidate not only the variability of the EASM but also the profound implications of a remote forcing, such as surface transformations of the Sahara, on climatic changes and cultural evolution in northern China.

ObjectiveThe objective of this review was to provide a comprehensive summary and analysis of the risk factors associated with suicidal ideation among cancer patients.MethodsThis review adhered to the PICO/S framework and guidelines outlined in the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) framework (PROSPERO CRD42023433639). We searched Web of Science, PubMed, Embase, Scopus, PsycINFO, and Cochrane Library from the establishment date of the databases until June 9, 2023 for observational studies that reveal risk factors associated with suicidal ideation among cancer patients. Software Review Manager 5 (vision 5.4) was used for Meta-analyses.Results4,921 studies were obtained through the search of the databases, 40 of which were eligible. Meta-analysis revealed that suicidal ideation in cancer patients was significantly associated with marital status, living alone, post-traumatic stress disorder (PTSD), panic disorder, education, psychiatric illness history, social functioning, childhood adversity experience, financial problems, pain, depression, demoralization, vomiting, residence and anxiety.ConclusionBeing unmarried, living alone, less educated, living in rural, financial problems, pain, vomiting, PTSD, psychiatric illness history, lower social functioning, childhood adversity experience, anxiety, depression, demoralization, panic disorder were risk factors for suicidal ideation among cancer patients. This review provided evidence-based information for identifying and reducing the risk of suicide in cancer survivors.Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, CRD42023433639.

Background and aimsTo investigate the effect of short-term very-low-calorie restriction (VLCR) on metabolism in patients with type 2 diabetes (T2D), and elucidate the molecular mechanism through analyses on gut microbiota and small-molecule metabolites.MethodsFourteen T2D patients were hospitalized to receive VLCR (300-600 kcal/d) for 9 days. BMI, BP, and HR were taken before and after VLCR. Levels of blood lipids, fasting insulin, FBG, and 2h PBG were assessed. The microbial diversity in feces was detected by 16S rDNA high-throughput sequencing technology, and small-molecule metabolites in plasma and feces by untargeted metabolomics technology.ResultsAfter VLCR, BW, BMI, WC, BP, and levels of FBG and 2h PBG, insulin, HOMA-IR, and triglyceride decreased significantly in T2D patients (P