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Abstract The advent of polyadenosine diphosphate ribose polymerase inhibitors (PARPi) has brought about significant changes in the field of ovarian cancer treatment. However, in 2022, Rucaparib, Olaparib, and Niraparib, had their marketing approval revoked for third-line and subsequent therapies due to an increased potential for adverse events. Consequently, the exploration of new treatment modalities remains imperative. Recently, the integration of PARPi with immune checkpoint inhibitors (ICIs) has emerged as a potential remedy option within the context of ovarian cancer. This article offers a comprehensive examination of the mechanisms and applications of PARPi and ICIs in the treatment of ovarian cancer. It synthesizes the existing evidence supporting their combined use and discusses key considerations that merit attention in ongoing development efforts.

Abstract Dissimilatory nitrate reduction to ammonium (DNRA) received more attention for its ability to recover ammonium. This study investigated the possibility of low-frequency infrared electromagnetic field (IR-EMF) to improve DNRA. The optimal IR-EMF intensity of 0.04 μT could effectively improve DNRA activity of nonwoven fabric membrane bioreactors. In the long-term operation, the average ammonium conversion efficiency was enhanced by 117.7% and 62.5% under 0.04 μT and 0.06 μT IR-EMF, respectively. The highest nrfA-gene abundance and potential DNRA rate were obtained under 0.04 μT IR-EMF exposure. Bacteroidetes fragilis, Shewanelle oneidensis MR-1, and Thauera sp. RT1901 were selected to investigate the dynamic response of nitrogen transformation and energy metabolism to IR-EMF. The transcriptome sequencing and RT-qPCR results suggested that IR-EMF could enhance both denitrification and DNRA process, mainly by improving ATP synthesis to boost metabolic activity. This study provided an efficient method for the nitrogen recovery via DNRA process by applying IR-EMF.

Abstract Dissimilatory nitrate reduction to ammonium (DNRA) has garnered attention due to its ability to recover ammonia and reduce greenhouse gas emissions simultaneously. In this study, the potential of using static magnetic field (SMF) to improve DNRA process was explored from the sight of molecular biology. Functional genes, microbial community structure, and metabolism pathways were discussed. SMF of 40 mT shortened the start-up time of DNRA from 75 days to 41 days, while 80 mT SMF delayed it to 103 days. On day 80, DNRA potential rate under 40 mT SMF, reached 174 ± 11 μmol kg−1 h−1, significantly surpassing 0 mT (88 ± 6 μmol kg−1 h− 1) and 80 mT SMF (52 ± 4 μmol kg−1 h−1). SMF of 40 mT also accelerated community succession and the enrichment of functional bacteria like Geobacter (from 15.71% to 32.11%). qPCR results suggested that 40 mT SMF promoted the rapid enrichment of DNRA functional gene nrfA and 80 mT SMF promoted the enrichment of nirS gene on day 40. Dynamic responses of Thauera sp. RT1901, Stutzerimonas stutzeri, Shewanella oneidensis MR-1, and Shewanella loihica PV-4 to SMF at transcriptional levels confirmed SMF could improve the nitrogen removal and electron transfer of DNRA and denitrification bacteria. Consequently, this work validated the possibility of using SMF to improve DNRA process for ammonia recovery and investigated the underlying mechanisms, which could promote the application of DNRA in full-scale.

The forecast of the global numerical weather prediction model is often used as the background field to drive the regional mesoscale weather models, and its forecast quality has an important impact on the prediction skill of regional models. The mesoscale operational model in Central China uses the Global Forecast Field (NCEP GFS) of the US Center for Environmental Prediction as the background field, and its forecast accuracy needs to be improved. This paper proposes a method to improve the initial field of the model by using the three-dimensional variational method to assimilate the high-quality European Centre for Medium-range Weather Forecasts (ECMWF) fine-grid forecast field to improve the short-term forecasting ability of the model. At first, the error characters of the 12 h forecast products of NCEP GFS and ECMWF were analyzed by using sounding observations. The RMSE (root mean square error) of temperature, horizontal wind field and relative humidity of ECMWF 12 h forecast are smaller than those of NCEP GFS forecast. Second, sensitivity experiments of ECMWF forecast field assimilation with different resolutions were conducted. Finally, 1°×1° resolution was selected based on the sensitivity experiments and a series of the data assimilation experiments with 1°×1° resolution was performed for August 2021. The results are as follows. (1) The assimilation forecast of heavy rain from 11 to 13 August 2021 shows that after 12 hours of spin-up, the forecast error of the element field has been significantly improved, especially at the bottom of the model. The TS score of 12-36 h, 36-60 h and 60-84 h cumulative precipitation has a certain improvement, especially the forecast of rainstorm magnitude. (2) ECMWF forecast field assimilation sensitivity experiments with different resolutions show that the forecast effect of ECMWF forecast field with 1°×1° resolution is better than 0.5°×0.5° and 0.25°×0.25°. (3) A series of the data assimilation experiments for August 2021 shows that the assimilation of ECMWF 12 h 1°×1° predicted variables has a lower RMSE of the 12 h, 36 h and 60 h forecasted temperature, humidity and wind field in the vertical direction than the control experiments, and the TS score was significantly improved, especially for 50 mm heavy rain precipitation, with an increase of 13.33%, which can effectively improve the forecast skills of the Wuhan Mesoscale Model.

Dust pollution can harm the urban environment and the health of citizens. Each stage in highway construction generates unorganized dust emissions to varying degrees, which complicates their quantification. To precisely forecast dust emissions during the construction of highway subgrades and reduce the associated pollution risks, this study introduces a predictive model based on a deep neural network (DNN) for dust emissions during highway subgrade-filling operations. Dust concentration is treated as a nonlinear multivariate problem, with predictive indicators encompassing particulate matter 2.5 (PM2.5), particulate matter 10 (PM10), ground surface temperature, wind speed, air temperature, surface pressure, and relative humidity. Using a DNN model, this study forecasts the concentrations of PM2.5 and PM10 at highway construction sites. Based on a highway project in Hebei Province, this study predicts dust-emission concentrations via field monitoring conducted using self-developed equipment. The model’s predictions exhibit a small mean-absolute-percentage error and root-mean-square error compared with the actual values, and the model’s accuracy significantly surpasses that of conventional regression models. Accurate forecasting can facilitate the timely control of dust concentrations at construction sites, thus facilitating more environmentally friendly and efficient construction. Doi: 10.28991/HIJ-2024-05-02-03 Full Text: PDF

[Introduction] Fusion energy has the characteristics of large energy released through reactions, safe and reliable operation, abundant fuel sources, and low environmental pollution. Therefore, it is expected to become a commercial energy source that can be supplied in the market on a large scale, providing stable energy output and power supply in the future. To popularize the development path of magnetic confined fusion energy in China, the article reviews the discovery and realization path of fusion energy. [Method] The article provided an overview of the early research and development process of magnetic confined fusion energy in China by the method of literature review. The paper took the development of magnetic confined fusion energy as an example to provide a preliminary overview of the construction of typical research devices in China, such as tokamak, stellarator, spherical tokamak, reversed field pinch, magnetic mirror field, linear plasma, and dipole magnetic field devices. [Result] Based on the construction and researches of these devices, China has cultivated a group of scientific and technological talents in the field of magnetic confined fusion research, achieving significant progress. In addition, the article provides an overview of international cooperation in fusion energy research, as well as the International Thermonuclear Experimental Reactor (ITER) project that China is participating in construction. [Conclusion] Although the current research on fusion energy still needs to overcome significant challenges from various aspects, such as fusion plasma physics, fusion reactor materials, and tritium self-sustaining technology, it is believed that the magnetic confined fusion energy in China will turn from a blueprint into a reality in the future thanks to the urgent need for energy structure transformation and the strong support for fusion researches in China.

Background: Sepsis-associated coagulopathy specifically refers to widespread systemic coagulation activation accompanied by a high risk of hemorrhage and organ damage, which in severe cases manifests as disseminated intravascular coagulation (DIC), or even develops into multiple organ dysfunction syndrome (MODS). The complement system and the coagulation system as the main columns of innate immunity and hemostasis, respectively, undergo substantial activation after sepsis. Summary: Dysfunction of the complement, coagulation/fibrinolytic cascades caused by sepsis leads to “thromboinflammation,” which ultimately amplifies the systemic inflammatory response and accelerates the development of MODS. Recent studies have revealed that massive activation of the complement system exacerbates sepsis-induced coagulation and even results in DIC, which suggests that inhibition of complement activation may have therapeutic potential in the treatment of septic coagulopathy. Key Messages: Sepsis-associated thrombosis involves the upregulation or activation of procoagulant factors, down-regulation or inactivation of anticoagulant factors, and impairment of the fibrinolytic mechanism. This review aims to summarize the latest literature and analyze the underlying molecular mechanisms of the activation of the complement system on the abnormal coagulation cascades in sepsis.

Abstract Carbon quantum dots are emerging as promising nanomaterials for next-generation displays. The elaborate structural design is crucial for achieving thermally activated delayed fluorescence, particularly for improving external quantum efficiency of electroluminescent light-emitting diodes. Here, we report the synthesis of onion-like multicolor thermally activated delayed fluorescence carbon quantum dots with quantum yields of 42.3–61.0%. Structural, spectroscopic characterization and computational studies reveal that onion-like structures assembled from monomer carbon quantum dots of different sizes account for the decreased singlet-triplet energy gap, thereby achieving efficient multicolor thermally activated delayed fluorescence. The devices exhibit maximum luminances of 3785–7550 cd m−2 and maximum external quantum efficiency of 6.0–9.9%. Importantly, owing to the weak van der Waals interactions and adequate solution processability, flexible devices with a maximum luminance of 2554 cd m−2 are realized. These findings facilitate the development of high-performance carbon quantum dots-based electroluminescent light-emitting diodes that are promising for practical applications.

Abstract White light‐emitting diodes (WLEDs) with high color‐rendering index (CRI, >90) are important for backlight displays and solid‐state lighting applications. Although the well‐developed colloidal quantum dots (QDs) based on heavy metals such as cadmium and lead are promising candidates for WLEDs, the low CRI still remains a significant limitation. In addition, the severe toxicity of heavy metals greatly limits their widespread use. Herein, the study demonstrates low‐cost and environmentally friendly carbon quantum dots (CQDs)‐based WLEDs that exhibit a high CRI of 94.33, surpassing that of conventional cadmium/lead‐containing QD‐based WLEDs. This achievement is attained through the employment of a binary host‐induced exciplex strategy. The high hole/electron mobility and suitable energy levels of the donor and acceptor give rise to a broadband orange–yellow emission stemming from the exciplex. As the host, the binary exciplex is capable of contributing blue and orange–yellow emission components while efficiently mitigating the aggregation‐induced quenching of CQDs. Meanwhile, CQDs effectively address the deep‐red emission gap, enabling the realization of CQDs‐based WLEDs with high CRI. These WLEDs also exhibit a remarkably low turn‐on voltage of 2.8 V, a maximum luminance exceeding 2000 cd m−2, a correlated color temperature of 4976 K, and Commission Internationale de l'Eclairage coordinates of (0.34, 0.32).

Abstract Eleutherococcus senticosus (Rupr. & Maxim.) Maxim. fruits (ESF), as a natural edible fruit, has long been popularized. However, few studies have conducted comprehensive chemical analyses of it. This study aimed to assess nonvolatile, volatile, and fatty oil components of ESF and to preliminarily explore the antioxidant activities. The qualitative and quantitative analyses of volatile and fatty oil components of ESF from 15 different regions were performed by the gas chromatography–mass spectrometry (GC–MS). Totally, 37 and 28 compounds were identified from volatile oil and fatty oil, respectively. The ultra‐high‐performance liquid chromatography–quadrupole time‐of‐flight mass spectrometry (UPLC–QTOF–MS/MS) was used to accurately detect 43 compounds of nonvolatile components. The volatile and fatty oil components and nonvolatile components of ESF were used as samples to determine the antioxidant activity of 2,2‐diphenyl‐1‐picrylhydrazyl (DPPH) in vitro. The components of ESF had antioxidant activity, and the nonvolatile components had stronger antioxidant activity. The results revealed that the proposed method, which is of great significance for the screening of new active ingredients, is valuable for the identification of pharmaceutical component and further development of food industry.

ABSTRACTGround surface deformation must be monitored to understand and prevent geological hazards. Global navigation satellite system (GNSS) technology has been widely used in deformation monitoring; however, current GNSS station layout strategies are often subjective and lack theoretical guidance. Therefore, in this study, a GNSS deformation observation network optimization method was developed based on interferometric synthetic aperture radar (InSAR) prior to deformation assistance. This method considers the deformation distribution, cost, accuracy, topography, and actual monitoring requirements and uses kriging interpolation and multiscale iterative optimization to obtain the reference number, spatial distribution, and deformation capture accuracy of GNSS stations in areas experiencing deformation. Simulation experiments showed that the proposed method strengthened the spatial deformation monitoring ability of GNSS by 46%–68% compared with the traditional station layout methods, which ignore the distribution of the deformation. Then, based on the small baseline subset (SBAS) InSAR technology and applying the new method, we evaluated the number and location of the most suitable GNSS stations for a mining area and found that 89.6% of the error was less than 1.5 cm, which further illustrates the practicability and reliability of the proposed method. This method provides an effective supplement to station layouts for monitoring GNSS deformation.

Both the composition and architecture of artificial bone govern bone regeneration. Herein, carbonate apatite (CAp), which has a similar mineral composition to bone, was prepared by immersing calcium carbonate (CaCO3) in a phosphate solution with varying acidification levels (pH 6.0) to pH 8.9, to reveal the influence of pH on the composition and architecture of the resultant CAp granules. The composition, crystal morphology, and architecture of resultant CAp granules was well-characterized by X-ray diffraction, scanning electron microscopy, mercury intrusion porosimetry and so on. Consequently, the rate of compositional transformation from CaCO3 to CAp was much higher at pH 6.0 and pH 7.0 than pH 8.0 and pH 8.9. The pH of the phosphate solution did not affect the macroarchitecture of the resultant CAp granules. In contrast, the composition, crystal morphology, microarchitecture, and degradation behavior of the resultant CAp granules were affected by pH of the phosphate solution. In particular, the open-pore distributions and volumes of the CAp granules prepared at pH 6.0–8.9 were changed to reflect the microarchitecture of the samples. Therefore, this study revealed that the pH-controlled elution precipitation reaction is useful for controlling the composition, crystal morphology, microarchitecture, and degradation behavior of the resultant CAp, while preserving its macroarchitecture. Our findings provide fundamental insights into the design of artificial bones for bone regeneration.

In2O3 based materials are one of the most promising high-temperature thermoelectric materials for application. Herein, Sm doped In2O3 samples were prepared by mechanical alloying, high-temperature calcination, and discharge plasma sintering, and the influence mechanism of rare earth element doping on the thermoelectric properties of In2O3 based semiconductors was studied. The results indicate that the electrical conductivity increased significantly. Due to the introduction of Sm impurity levels, the density of states near the Fermi level significantly increases. The bandgap widens, and the mobility first decreases and then increases. Due to the increase in carrier concentration, the absolute value of the Seebeck coefficient decreases, but the gain effect caused by the increase in conductivity is greater than the debuff caused by the decrease in the absolute value of the Seebeck coefficient. The power factor increases after Sm doping.The thermal conductivity decreases due to the decrease in Young's modulus, enhanced heterogeneous scattering, and enhanced heavy element scattering. The ZT value was raised to ∼0.327 at 973 K, obtained by Sm doped In2O3 sample with x = 0.060, which is ∼6 times as that of the pristine In2O3 sample.

Abstract Objective The current body of evidence on the association between the ratio of triglycerides to high-density lipoprotein cholesterol (TG/HDL-c) and the reversal of prediabetes to normoglycemia remains limited. The aim of this study is to investigate the association between TG/HDL-c and the reversion to normoglycemia in patients with prediabetes. Methods This retrospective cohort study included 15,107 individuals with prediabetes from 32 Chinese districts and 11 cities who completed health checks from 2010 to 2016. The Cox proportional-hazards regression model examined baseline TG/HDL-c and reversion to normoglycemia from prediabetes. Cox proportional hazards regression with cubic spline functions and smooth curve fitting determined the non-linear connection between TG/HDL-c and reversion to normoglycemia. We also ran sensitivity and subgroup analysis. By characterizing progression to diabetes as a competing risk for the reversal of prediabetes to normoglycemic event, a multivariate Cox proportional hazards regression model with competing risks was created. Results Upon adjusting for covariates, the findings indicate a negative association between TG/HDL-c and the likelihood of returning to normoglycemia (HR = 0.869, 95%CI:0.842–0.897). Additionally, a non-linear relationship between TG/HDL-c and the probability of reversion to normoglycemia was observed, with an inflection point of 1.675. The HR on the left side of the inflection point was 0.748 (95%CI:0.699, 0.801). The robustness of our results was confirmed through competing risks multivariate Cox's regression and a series of sensitivity analyses. Conclusion The present study reveals a negative and non-linear correlation between TG/HDL-c and the reversion to normoglycemia among Chinese individuals with prediabetes. The findings of this study are anticipated to serve as a valuable resource for clinicians in managing dyslipidemia in prediabetic patients. Interventions aimed at reducing the TG/HDL-c ratio through the reduction of TG or elevation of HDL-c levels may substantially enhance the likelihood of achieving normoglycemia in individuals with prediabetes.

The failure mechanism and size effect during the quasi-static and dynamic shear tests of hat-shaped specimens were investigated in this study. Three types of specimens with different shear ring thicknesses (800, 400, and 50 μm) were designed. Quasi-static tests were carried out using an electronic universal testing machine, while dynamic impact tests were carried out using split Hopkinson pressure bar (SHPB) tests. The adiabatic temperature rises with different strain rates, and the shear ring thickness was calculated. We found that the adiabatic temperature rises of the specimens with shear ring thicknesses of 800 and 400 μm were much larger than those of the specimens with shear ring thicknesses of 50 μm. The failure surfaces after the SHPB test were investigated via scanning electron microscopy, and the failure surfaces after the SHPB test could be divided into three zones: tensile, shear, and impact zones. The effect of the shear ring thickness and impact speed on the failure surface morphology was discussed. The typical shear stress–strain curves could be divided into three sections: elastic, plastic rise, and plastic plateau sections. Subsequently, a modified Johnson–Cook constitutive model was employed to fit the shear stress–strain results, and the fitted curves showed good agreement with the tested curves.

Photoelectric dual-mode sensors, which respond to strain signal through photoelectric dual-signals, hold great promise as wearable sensors in human motion monitoring. In this work, a photoelectric dual-mode sensor based on photonic crystals hydrogel was developed for human joint motion detection. The optical signal of the sensor originated from the structural color of photonic crystals, which was achieved by tuning the polymethyl methacrylate (PMMA) microspheres diameter. The reflective peak of the sensor, based on 250 nm PMMA PCs, shifted from 623 nm to 492 nm with 100% strain. Graphene was employed to enhance the electrical signal of the sensor, resulting in a conductivity increase from 9.33 × 10−4 S/m to 2 × 10−3 S/m with an increase in graphene from 0 to 8 mg·mL−1. Concurrently, the resistance of the hydrogel with 8 mg·mL−1 graphene increased from 160 kΩ to 485 kΩ with a gauge factor (GF) = 0.02 under 100% strain, while maintaining a good cyclic stability. The results of the sensing and monitoring of finger joint bending revealed a significant shift in the reflective peak of the photoelectric dual-mode sensor from 624 nm to 526 nm. Additionally, its resistance change rate was measured at 1.72 with a 90° bending angle. These findings suggest that the photoelectric dual-mode sensor had the capability to detect the strain signal with photoelectric dual-mode signals, and indicates its great potential for the sensing and monitoring of joint motion.

Fritillaria ussuriensis Maxim. (F.M.) has been widely used in both food and medication for more than 2000 years. In order to achieve its comprehensive utilization and investigate the structural characterization and biology activity, response surface methodology (RSM) was used to optimize the ultrasound-assisted extraction conditions of F.M. polysaccharides. The optimal extraction conditions were ultrasonic power of 174.2 W, ratio of liquid to material of 40.7 mL/g and ultrasonic time of 82.0 min. In addition, a neutral polysaccharide F-1 was obtained, and its structure characterization, antioxidant and immunological activity were evaluated. The structural properties of the polysaccharide were characterized by UV, IR, GC-MS, NMR and AFM. Monosaccharide composition of F-1 (MW 18.11 kDa) was rhamnose, arabinose, glucosamine hydrochloride, galactose, and glucose which under the ratio of 0.9: 3.8: 0.2: 2.9: 92.2. The fractions of F-1 were mainly linked by → 6)-α-D-Glcp-(1 → with branch chain α-D-Glcp-(1 → 4)-α-D-Glcp-(1 → and 4,6)-α-D-Glcp-(1 → residues. Moreover, F-1 has a significant scavenging activity, which can clear hydroxyl radicals, superoxide anion, DPPH and ABTS. In addition, the immunological activity showed that F-1 had an effect on macrophage phagocytic activity. And it can increase the release of inflammatory factors including TNF-α, IL-1β and IL-6. F-1 is a novel polysaccharide with significant activity in antioxidant and immunological activity, which has great potential for antioxidant and immunizer in food, pharmaceutical and cosmetic industries. The study can provide a methodological basis for polysaccharide research and theoretical basis for the industrialized production and practical application.

Environmentally friendly technologies for the prevention and control of crop diseases and insect pests are important to reduce the use of chemical pesticides, improve the quality of agricultural products, protect the environment, and promote sustainable development of crop production. On the basis of Internet of Things (IoT) technology, we developed a prevention and control system for crop diseases and insect pests with two main components: a plant protection device (the hardware) and an information management system (the software). To be suitable for both facility- and field-based production scenarios, we incorporated two types of plant protection devices, utilizing ozone sterilization and light-trap technologies. The devices were equipped with various sensors to realize real-time collection and monitoring of data on the crop production environment. The information management system has an IoT-based architecture and includes a mobile device app to enable remote control of the plant protection devices for intelligent management of plant protection data. The system can achieve efficient management of large-scale equipment applications and multi-device collaborative work to prevent and control pests and diseases. The developed system has operated successfully for several years in China and has been applied to cucumber, tomato, rice, and other crops. We demonstrate the effectiveness and practicality of the system in a greenhouse facility and in the field.

Based on numerical simulation software LSDYNA and field monitoring data, this paper analyzes the peak particle velocity (PPV) of rock mass at different distances from the blasting face of the roadway. At the same time, the dynamic stress concentration coefficient of surrounding rock under the action of different blasting times and the blasting damage effect of the tunnel are studied. The results show that in the tunnel blasting near the area, the PPV in the vertical direction of the tunnel is maximum in three directions; PPV decreases more slowly in the excavated zone than in the nonexcavated zone. When the explosion source is close to the roadway, the dynamic stress concentration coefficient of the blasting side and the rear side is large, so the vibration standard of surrounding rock should be strictly controlled.

Poly (adenosine 5′-diphosphate-ribose) polymerase inhibitors (PARPi) are increasingly important in the treatment of ovarian cancer. However, more than 40% of BRCA1/2-deficient patients do not respond to PARPi, and BRCA wild-type cases do not show obvious benefit. In this study, we demonstrated that progesterone acted synergistically with niraparib in ovarian cancer cells by enhancing niraparib-mediated DNA damage and death regardless of BRCA status. This synergy was validated in an ovarian cancer organoid model and in vivo experiments. Furthermore, we found that progesterone enhances the activity of niraparib in ovarian cancer through inducing ferroptosis by up-regulating palmitoleic acid and causing mitochondrial damage. In clinical cohort, it was observed that progesterone prolonged the survival of patients with ovarian cancer receiving PARPi as second-line maintenance therapy, and high progesterone receptor expression combined with low glutathione peroxidase 4 (GPX4) expression predicted better efficacy of PARPi in patients with ovarian cancer. These findings not only offer new therapeutic strategies for PARPi poor response ovarian cancer but also provide potential molecular markers for predicting the PARPi efficacy.

Abstract Background Previous studies have found a correlation between coronavirus disease 2019 (COVID-19) and changes in brain structure and cognitive function, but it remains unclear whether COVID-19 causes brain structural changes and which specific brain regions are affected. Herein, we conducted a Mendelian randomization (MR) study to investigate this causal relationship and to identify specific brain regions vulnerable to COVID-19. Methods Genome-wide association study (GWAS) data for COVID-19 phenotypes (28,900 COVID-19 cases and 3,251,161 controls) were selected as exposures, and GWAS data for brain structural traits (cortical thickness and surface area from 51,665 participants and volume of subcortical structures from 30,717 participants) were selected as outcomes. Inverse-variance weighted method was used as the main estimate method. The weighted median, MR-Egger, MR-PRESSO global test, and Cochran’s Q statistic were used to detect heterogeneity and pleiotropy. Results The genetically predicted COVID-19 infection phenotype was nominally associated with reduced cortical thickness in the caudal middle frontal gyrus (β = − 0.0044, p = 0.0412). The hospitalized COVID-19 phenotype was nominally associated with reduced cortical thickness in the lateral orbitofrontal gyrus (β = − 0.0049, p = 0.0328) and rostral middle frontal gyrus (β = − 0.0022, p = 0.0032) as well as with reduced cortical surface area of the middle temporal gyrus (β = − 10.8855, p = 0.0266). These causal relationships were also identified in the severe COVID-19 phenotype. Additionally, the severe COVID-19 phenotype was nominally associated with reduced cortical thickness in the cuneus (β = − 0.0024, p = 0.0168); reduced cortical surface area of the pericalcarine (β = − 2.6628, p = 0.0492), superior parietal gyrus (β = − 5.6310, p = 0.0408), and parahippocampal gyrus (β = − 0.1473, p = 0.0297); and reduced volume in the hippocampus (β = − 15.9130, p = 0.0024). Conclusions Our study indicates a suggestively significant association between genetic predisposition to COVID-19 and atrophy in specific functional regions of the human brain. Patients with COVID-19 and cognitive impairment should be actively managed to alleviate neurocognitive symptoms and minimize long-term effects.

Finite element method (FEM) based model of broaching Inconel 718 was established to optimize an asymmetrical cutting-edge by the commercial software AdvantEdge in this paper. The asymmetrical cutting-edge form by two circles was proposed. The power-law (P-L) material constitutive model, including strain hardening, strain rate hardening and thermal softening was developed by split Hopkinson pressure bar (SHPB) test and high-temperature Vickers hardness test. The parameters of thermal properties were measured by laser flash diffusivity apparatus. The friction model between TiN (The outer layer coating material of the tool) and Inconel 718 was obtained by ball on disc friction test. The simulated and experimental results have been compared comprehensively in the items of chip formation and tool wear width. The results showed that the simulated results were consistent with the experimental results. The average errors of chip curl radius, chip thickness, wear width of rake face and flank face were 7.68%, 3.56%, 13.64% and 12.24%, respectively, which proved the accuracy of the simulation model. Then the optimal asymmetrical cutting-edge of broach were obtained through orthogonal test based on the accurate FEM model. The rise per tooth of the optimal broach tool is 0.04 mm/tooth, the rake angle is 13°, the circle radius R1 is 0.13 mm, and the circle radius R2 is 0.02 mm.

This article systematically reviews the extraction and purification methods, structural characteristics, structure–activity relationship, and health benefits of C. speciosa polysaccharides, and their potential application in food, medicine, functional products, and feed, in order to provide a useful reference for future research. Chaenomeles speciosa (Sweet) Nakai. has attracted the attention of health consumers and medical researchers as a traditional Chinese medicine with edible, medicinal, and nutritional benefits. According to this study, C. speciosa polysaccharides have significant health benefits, such as anti-diaetic, anti-inflammatory and analgesic, anti-tumor, and immunomodulatory effects. Researchers determined the molecular weight, structural characteristics, and monosaccharide composition and ratio of C. speciosa polysaccharides by water extraction and alcohol precipitation. This study will lay a solid foundation for further optimization of the extraction process of C. speciosa polysaccharides and the development of their products. As an active ingredient with high value, C. speciosa polysaccharides are worthy of further study and full development. C. speciosa polysaccharides should be further explored in the future, to innovate their extraction methods, enrich their types and biological activities, and lay a solid foundation for further research and development of products containing polysaccharides that are beneficial to the human body.

Cancer represents one of the most significant health challenges currently facing humanity, and plant-derived antitumour drugs represent a prominent class of anticancer medications in clinical practice. Isovaleryl sucrose esters, which are natural constituents, have been identified as having potential antitumour effects. However, the mechanism of action remains unclear. In this study, 12 isovaleryl sucrose ester components, including five new (1–5) and seven known compounds (6–12), were isolated from the roots of Atractylodes japonica. The structures of the compounds were elucidated using 1D and 2D-NMR spectroscopy, complemented by HR-ESI-MS mass spectrometry. The cytotoxic activities of all the compounds against human colon cancer cells (HCT-116) and human lung adenocarcinoma cells (A549) were also evaluated using the CCK8 assay. The results demonstrated that compounds 2, 4, and 6 were moderately inhibitory to HCT-116 cells, with IC50 values of 7.49 ± 0.48, 9.03 ± 0.21, and 13.49 ± 1.45 μM, respectively. Compounds 1 and 6 were moderately inhibitory to A549, with IC50 values of 8.36 ± 0.77 and 7.10 ± 0.52 μM, respectively. Molecular docking revealed that compounds 1–9 exhibited a stronger affinity for FGFR3 and BRAF, with binding energies below −7 kcal/mol. Compound 2 exhibited the lowest binding energy of −10.63 kcal/mol to FGFR3. We screened the compounds with lower binding energies, and the protein-ligand complexes already obtained after molecular docking were subjected to exhaustive molecular dynamics simulation experiments, which simulated the dynamic behaviour of the molecules in close proximity to the actual biological environment, thus providing a deeper understanding of their functions and interaction mechanisms. The present study provides a reference for the development and use of iso-valeryl sucrose esters in the antitumour field.

Freeze–thaw effect is one of the most important environmental conditions that rocks may be subjected to. Through laboratory model tests, the damage characteristics of rocks under the FTC were studied. Based on assuming that the strength of rocks subject to the FTC follows the Weibull distribution, the cumulative damage variable of the number of FTCs was introduced. A cumulative damage constitutive model of shear strength attenuation of rock that meets the Mohr–Coulomb criterion is established. The rationality and applicability of the proposed damage constitutive model are verified by comparing the results of rock shear strength parameters under cyclic freeze–thaw loads.

Regional haze often occurs after the New Year holiday. To explore the characteristics of PM2.5 pollutions under the influence of the New Year’s Day effect, this study analyzed the spatiotemporal changes relating to PM2.5 during and around the New Year’s Day holiday in China from 2015 to 2022, and used the Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model to study the effects of human activities and meteorological factors on PM2.5 pollutions, as well as the differences in the contributions of different industries to PM2.5 pollutions. The results show that for the entire study period (i.e., before, during, and after the New Year’s Day holiday) from 2015 to 2022, the average concentrations of PM2.5 in China decreased by 41.9% overall. In 2019~2022, the New Year’s Day effect was significant, meaning that the average concentrations of PM2.5 increased by 18.9~46.8 μg/m3 from before to after the New Year’s Day holiday, with its peak occurring (64.3~74.9 μg/m3) after the holiday. In terms of spatial differences, the average concentrations of PM2.5 were higher in the Beijing–Tianjin–Hebei region, the Yangtze River Delta, and central China. Moreover, the Beijing–Tianjin–Hebei region and its surrounding areas, the Chengdu–Chongqing region, the Fenwei Plain, and the middle reaches of the Yangtze River region were greatly affected by the New Year’s Day effect. Human activities led to higher increases in PM2.5 in Henan, Hubei, Hebei, and Anhui on 3 and 4 January 2022. If the haze was accompanied by cloudy days or weak precipitation, the accumulation of surface water vapor and atmospheric aerosols further increased the possibility of heavy pollution. It was found that, for the entire study period, PM2.5 generated by residential sources contributed the vast majority (60~100 μg/m3) of PM2.5 concentrations, and that the main industry sources that caused changes in time distributions were industrial and transportation sources.

Diabetes mellitus is a widely prevalent chronic disease, and effective treatments for it remain limited. Allicin has anti-diabetic effect, however, the detailed mechanism has not been well investigated. The diabetic rats were treated with allicin for 6 weeks, and then the fecal samples, serum and tissues were collected for measurement of gut microbiota (GM), bile acids (BAs) and other indexes. Allicin decreased the blood glucose levels, serum lipid levels, and alleviated hepatic lipid deposition of the diabetic rats. Simultaneously, allicin changed the composition of GM and increased secondary BAs in serum. Interestingly, allicin significantly increased the glucagon-like peptide-1 (GLP-1) content in colon homogenate, and reduced the protein expression of fibroblast growth factor 15 (FGF15) in ileum. Moreover, allicin increased 7α-hydroxylase 1 (CYP7A1) expression in liver. The study demonstrated that allicin ameliorates metabolisms in the diabetic rats though modulating gut microbiota, bile acids, and inhibiting enterohepatic FGF15-CYP7A1 signaling.

Insulin resistance presents a formidable public health challenge that is intricately linked to the onset and progression of various chronic ailments, including diabetes, cardiovascular disease, hypertension, metabolic syndrome, nonalcoholic fatty liver disease, and cancer. Effectively addressing insulin resistance is paramount in preventing and managing these metabolic disorders. Natural herbal remedies show promise in combating insulin resistance, with anthraquinone extracts garnering attention for their role in enhancing insulin sensitivity and treating diabetes. Anthraquinones are believed to ameliorate insulin resistance through diverse pathways, encompassing activation of the AMP-activated protein kinase (AMPK) signaling pathway, restoration of insulin signal transduction, attenuation of inflammatory pathways, and modulation of gut microbiota. This comprehensive review aims to consolidate the potential anthraquinone compounds that exert beneficial effects on insulin resistance, elucidating the underlying mechanisms responsible for their therapeutic impact. The evidence discussed in this review points toward the potential utilization of anthraquinones as a promising therapeutic strategy to combat insulin resistance and its associated metabolic diseases.

Chronic obstructive pulmonary disease (COPD) is a lung inflammatory disease that is associated with environmental allergic component exposure. Cigarette smoke is an environmental toxicant that induces lung malfunction leading to various pulmonary diseases. Astaxanthin (AST) is a carotenoid that shows antioxidant and anti-inflammatory activities which might be a promising candidate for COPD therapy. In this study, we released that AST could attenuate cigarette smoke-induced DNA damage and apoptosis in vivo and in vitro. AST administration ameliorated cigarette smoke extract (CSE)-induced activation of Caspase-3 and apoptosis. Pretreated mice with AST significantly decrease CSE-induced DNA damage which shows lower nuclear γ-H2AX level. AST treatment also dramatically reduces the production of intracellular reactive oxygen species (ROS) by suppressing the expression of nicotinamide adenine dinucleotide phosphate (NADPH) oxidase enzyme 4 (NOX4) and dual oxidase 1 (DUOX1). Taken together, this study suggested that AST can decrease CSE-induced DNA damage and apoptosis by inhibiting NOX4/DUOX1 expression that promotes ROS generation. AST may be a potential protective agent against CSE-associated lung disease that is worth in-depth investigation.

Background: Ginsenoside Rg2 (Rg2) has a variety of pharmacological activities and provides benefits during inflammation, cancer, and other diseases. However, there are no reports about the relationship between Rg2 and atherosclerosis. Methods: We used 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) to detect the cell viability of Rg2 in vascular smooth muscle cells (VSMCs) and human umbilical vein endothelial cells (HUVECs). The expression of inflammatory factors in HUVECs and the expression of phenotypic transformation-related marker in VSMCs were detected at mRNA levels. Western blot method was used to detect the expression of inflammation pathways and the expression of phenotypic transformation at the protein levels. The rat carotid balloon injury model was performed to explore the effect of Rg2 on inflammation and phenotypic transformation in vivo. Results: Rg2 decreased the expression of inflammatory factors induced by lipopolysaccharide in HUVECs–without affecting cell viability. These events depend on the blocking regulation of NF-κB and p-ERK signaling pathway. In VSMCs, Rg2 can inhibit the proliferation, migration, and phenotypic transformation of VSMCs induced by platelet derived growth factor-BB (PDGF-BB)–which may contribute to its anti-atherosclerotic role. In rats with carotid balloon injury, Rg2 can reduce intimal proliferation after injury, regulate the inflammatory pathway to reduce inflammatory response, and also suppress the phenotypic transformation of VSMCs. Conclusion: These results suggest that Rg2 can exert its anti-atherosclerotic effect at the cellular level and animal level, which provides a more sufficient basis for ginseng as a functional dietary regulator.

Images captured under foggy or hazy weather conditions are affected by the scattering of atmospheric particles, resulting in decreased contrast and color variation, thereby limiting their practical applications. In recent years, deep learning methods showcase significant advancements in image dehazing. However, the complexity and degradation factors in hazy images challenge the generalization capacity of dehazing methods. This paper comprehensively reviews the recent developments in single-image dehazing techniques based on deep learning. From the perspectives of Convolutional Neural Networks (CNN) and Generative Adversarial Networks (GAN), different models are introduced and classified into four categories: Encoder-Decoder, Multi-Module, Multi-Branch, and Dual-Generative Adversarial Networks. The robustness and effectiveness of deep learning models are analyzed by comparing their performance and model complexity on public datasets. Additionally, limitations of current benchmark datasets and evaluation metrics are identified, and unresolved issues and future research directions are discussed. Our efforts in this paper will serve as a comprehensive reference for future research and call for further development in deep learning-based image dehazing.

We present a new explicit quasi-Lagrangian integration scheme with the three-dimensional cubic spline function transform (transform = fitting + interpolation, referred to as the “spline format”) on a spherical quasi-uniform longitude–latitude grid. It is a consistent longitude–latitude grid, and to verify the feasibility, accuracy, convergence, and stability of the spline format interpolation scheme for the upstream point on the longitude–latitude grid, which may map a quasi-uniform longitude–latitude grid, a set of ideal, exact test schemes is adopted, which are recognized and proven to be effective internationally. The equilibrium flow test, cross-polar flow test, and Rossby–Haurwitz wave test are used to illustrate the spline scheme uniformity to the linear scheme and to overcome the over-dense grid in the polar region and the non-singularity of the poles. The cross-polar flow test demonstrates that the geostrophic wind crosses the polar area correctly, including the South Pole and North Pole. A non-hydrostatic, fully compressible dynamic core is used to complete the density flow test, demonstrating the existence of a time-varying reference atmosphere and that the spline format can simulate highly nonlinear fine-scale transient flows. It can be compared for the two results of the density flow test between the solution with the spline format and the benchmark reference solution with the linear format. Based on the findings, the non-hydrostatic dynamic core with the spline format is recommended for adoption. When simulated for the flow over an ideal mountain, through the “topographic gravity wave test”, the bicubic surface terrain and terrain-following height coordinates, time-split integration, and vector discrete decomposition can be derived successfully. These may serve as the foundations for a global, unified spline-format numerical model in the future.

The onboard energy supply of Autonomous Underwater Vehicles (AUVs) is one of the main limiting factors for their development. The existing methods of deploying and retrieving AUVs from mother ships consume a significant amount of energy during submerging and surfacing, resulting in a small percentage of actual working time. Underwater docking chambers provide support to AUVs underwater, saving their precious energy and addressing this issue. When an AUV cluster is assigned multiple tasks, scheduling the cluster becomes essential, and task allocation and path planning are among the core problems in AUV cluster scheduling research. In this paper, based on the underwater docking chamber, an Improved Genetic Local Search Algorithm with Prior Knowledge (IGLSAPK) is proposed to simultaneously solve the task allocation and path planning problems. Under constraints such as onboard energy supply, AUV quantity, and AUV type, the algorithm groups AUVs, assigns tasks, and plans paths to accomplish tasks at different locations, aiming to achieve overall efficiency. The algorithm first generates an initial population using prior knowledge to improve its search efficiency. It then combines an improved local search algorithm to efficiently solve large-scale, complex, and highly coupled problems. The algorithm has been evaluated through simulation experiments and comparative experiments, and the results demonstrate that the proposed algorithm outperforms other algorithms in terms of speed and optimality. The algorithm presented in this paper addresses the grouping, task allocation, and path planning problems in heterogeneous AUV clusters. Its practical significance lies in its ability to handle tasks executed by a heterogeneous AUV group, making it more practical compared to previous algorithms.

Abstract Background The incidence of gastroesophageal reflux disease (GERD) has been shown to be elevated in individuals with epilepsy. Traditional observational studies have led to a limited understanding of the effects of GERD and BE on epilepsy due to the interference of reverse causation and potential confounders. Methods We conducted a bidirectional two‐sample Mendelian randomization (MR) analysis to determine whether GERD and BE can increase the risk of epilepsy. Genome‐wide association study data on epilepsy and its subgroups were obtained from the International League Against Epilepsy consortium for primary analysis using three MR approaches and the FinnGen consortium for replication and meta‑analysis. We calculated causal estimates between the two esophageal diseases and epilepsy using the inverse‐variance weighted method. Sensitivity analysis was conducted to detect heterogeneity and pleiotropy. Results We found a potential effect of genetically predicted GERD on the risk of epilepsy (odds ratio [OR] = 1.078; 95% confidence interval [CI], 1.014–1.146, p = .016). Specifically, GERD showed an effect on the risk of generalized epilepsy (OR = 1.163; 95% CI, 1.048–1.290, p = .004) but not focal epilepsy (OR = 1.059, 95% CI, 0.992–1.131, p = .084). Notably, BE did not show a significant causal relationship with the risks of generalized and focal epilepsy. Conclusions Under MR assumptions, our findings suggest a potential risk‐increasing effect of GERD on epilepsy, especially generalized epilepsy. Considering the exploratory nature of our study, the association between GERD and epilepsy needs to be confirmed by future prospective studies.

Objectives To explore the effect of dexmedetomidine (DEX) on postoperative nausea and vomiting (PONV) in adult patients after general anaesthesia.Design Systematic review and meta-analysis.Eligibility criteria for selecting studies Randomised controlled trials (RCTs) comparing the efficacy of DEX with placebo or a single drug on PONV in adult patients after general anaesthesia.Data sources We searched the PubMed, the Web of Science, the Cochrane Library and Embase (1 January 2000 to 30 June 2022) to select the relevant RCTs.Data analysis All the relevant data were analysed by using RevMan V.5.4. Heterogeneity was tested for each outcome, and random-effect or fixed-effect models was selected according to the level of heterogeneity. The primary outcome was the incidence of PONV. The secondary outcomes were the incidence of bradycardia, perioperative opioid consumption, extubation time and the length of hospitalisation.Results A total of 18 trials involving 2018 patients were included in this meta-analysis. Notably, 15 updated studies were not involved in the previous meta-analysis. The incidence of PONV in DEX group was lower than that in the control group (OR=0.49, 95% CI: 0.36 to 0.67) and the perioperative opioid consumption in DEX group was also decreased significantly (standard mean difference (SMD)=−1.04, 95% CI: −1.53 to −0.54). Moreover, the length of hospitalisation (SMD=−2.29, 95% CI: −4.31 to −0.28) and the extubation time (SMD=−0.75, 95% CI: −1.26 to −0.25) in DEX group were shorter. Whereas, more number of patients receiving DEX might increase the occurrence of bradycardia (OR=1.60, 95% CI: 1.13 to 2.27).Conclusions DEX could decrease the occurrence of PONV in adult patients under general anaesthesia and promote the recovery after surgery. However, DEX might increase the occurrence of bradycardia.PROSPERO registration number CRD 42022341548.

Background: Hepatocellular carcinoma (HCC), a malignancy with high mortality and recurrence rates, has very limited options for treatment strategies. Dehydrocostus lactone (DL) is the principal quality marker extracted from Aucklandia lappa Decne. and has been demonstrated to possess excellent anticancer activity. The key purpose of this study was to explore the therapeutic effects and potential mechanisms of DL on HCC. Methods: The effect of DL on the cell viability of HCC cell lines (HepG2 and SK-HEP-1) and normal human hepatocyte cell line (L-O2) was examined by CCK8, colony formation, and BeyoClickTMEdU-488 assays; Hoechst 33,258 staining and flow cytometry were utilized to determine the impact of DL on apoptosis; the sensitivity of HCC cells to DL was explored by adding Z-VAD-fmk. In addition, the expression of apoptosis-related proteins Bax, Bcl-2, and PARP was detected by western blotting; the expression of p-H2AX was investigated by western blotting and immunofluorescence staining; cell cycle distribution was observed using flow cytometry; the migration ability and invasiveness of HCC cells were assessed by wound healing assay and transwell assay; immunoblotting was applied to visualize the levels of EMT markers in the two HCC cell lines. Transcriptome sequencing was performed to reveal the underlying mechanisms of DL anti-tumor; western blotting and qRT-PCR were employed to verify the mRNA and protein abundance of p53, p21, and CDK2; HepG2 xenograft in mice was used to test the anti-tumor effects of DL in vivo. Results: DL suppressed the proliferation of HCC cell lines (HepG2 and SK-HEP-1) but had little effect on a normal human liver cell line (L-O2). In addition, DL also induced apoptotic death of the HCC cells by activating Bax and downregulating Bcl-2. The antiproliferative effects of DL could be attributed to increased DNA damage and G1-phase cell cycle arrest. Moreover, DL inhibited HCC cell invasiveness and migration in vitro by decreasing the levels of β-catenin, N-cadherin, and TCF8/ZEB1, and increasing the E-cadherin level. RNA sequencing indicated that DL exerted its anti-hepatoma effects partly via regulation of p53-p21-CDK2 signaling. These results were validated by our in vivo experiments, in which DL markedly suppressed the growth of HepG2 xenografts in a mouse model without any toxic side effects, which corresponded to decreased expression of Ki67 and MMP9 in the tumor tissues. Conclusion: DL has significant anti-cancer effects in both in vivo and in vitro HCC models, and therefore could be further developed as a promising drug for the treatment of HCC.

Narirutin, extracted from the dried ripe pericarp of Rutaceae orange and its cultivated varieties, is a dihydroflavone compound with various biological activities and pharmacological effects. So far as we know, the metabolism profiling of narirutin has been insufficient until now. In the present study, an efficient method was employed to perform rapid analysis and identification of narirutin metabolites by using ultra-high performance liquid chromatography quadrupole exactive orbitrap MS/MS (UHPLC-Q-Exactive Orbitrap MS/MS) combined with an analogous core recursion (ACR) analysis strategy. Firstly, according to the basic core structure of the dihydroflavonoid, the cleavage mode and fragmentation ions of narirutin were summarized. Secondly, based on the difference of the substituent groups, the fragment ions of narirutin were preliminarily inferred and verified by the secondary mass spectra of its standard compound. Thirdly, the fragment ions of narirutin in positive and negative ion modes were summarized to provide a basis for the identification of metabolites. Fourthly, candidate metabolites were accurately and tentatively identified according to the cleavage law of mass spectrometry, literature reports, comparison of reference substances, and especially the diagnostic fragment ion clusters (DFICs) and characteristic suggestive ions (CSIs) deduced preliminarily. Finally, a total of 46 metabolites (30 in vivo and 19 in vitro), including prototype drugs were identified based on the ACR analysis strategy, chromatographic retention behavior of metabolites, corresponding ClogP value and accurate molecular weight. Among them, 22 metabolites were discovered in rats plasma, 12 in urine, 4 in liver tissue, 19 in liver microsomes, respectively. Additionally, metabolites relative contents were also studied by extracted ion chromatography (EIC) method. Our result also illustrated that narirutin primarily underwent glucuronidation, sulfation, glutathione binding, deglycosylation, oxidation, reduction, methylation, hydroxylation, ring-opening and their composite reactions. A novel strategy was constructed to comprehensively elucidate the biotransformation pathways of narirutin in vitro and in vivo, and a systematic metabolic profile of narirutin was generated. This study provided a great reference for further understanding of the biotransformation pathways and guiding for clinical application of narirutin.

Abstract The use of double emulsions (DEs), which represent colloidal structures composed of droplets nested within droplets, can provide for unparallel droplet manipulation in droplet‐based microfluidic technology due to their unique core–shell structures. The controlled release of cores in DEs is of particular interest. However, this process remains poorly explored. In this work, the thermocapillary flow induced by a temperature gradient is used as a driving force to control the core release and the impacts of different linear temperature gradients, core diameters, shell diameter, and core/shell diameter ratios on the thermocapillary flow and core release characteristics of DE droplets consisting of a water‐in‐n‐hexadecane‐in‐water system within a cylindrical microchannel are investigated. Most of the core and shell diameter conditions considered result in a double‐core release process, where the inner droplet volume is partially ejected before the remaining core is rewrapped by the outer droplet, and the remaining inner droplet volume is ejected later during a second core release event. However, relatively small core diameters of 50 and 75 μm produce conditions where the full inner droplet volume is ejected during a single‐core release process. In addition, we provide empirical relationships for accurately determining the time at which core release initially occurs under given DE parameters as well as for precisely determining whether the applied conditions will lead to single‐ or double‐core release processes. Therefore, the results of this study provide insights enabling the development of accurate inner droplet release technologies under thermocapillary migration.

Abstract Codonopsis Radix (CR) is an edible food and traditional Chinese herb medicine in China. Various varieties of Codonopsis Radix have different tastes. To make the flavor of processed food stable, two kinds of electronic sensory devices, electronic nose and electronic tongue, were used to establish a discrimination model to identify the botanical origin of each sample. The optimal model built on the 88 batches of samples was selected from the models trained with all combination of two pretreatment methods and three classification methods. A comparison were performed on the models trained on the data collected by electronic nose and electronic tongue. The results showed that the model trained on the fused dataset outperformed the models trained separately on the electronic nose data and electronic tongue data. The two preprocessing approaches could improve the prediction performance of all classification methods. Classification and Regression Tree approach performed better than Partial Least Square Discriminant Analysis and Linear Discriminant Analysis in terms of accuracy. But Classification and Regression Tree tends to assign the samples of minority class to the majority class. Meanwhile, Partial Least Square Discriminant Analysis keeps a good balance between the identification requirements of all the two groups of samples. Taking all the results above, the model built using the Partial Least Square Discriminant Analysis method on the fused data after z-score was used to identify the botanical origin of Codonopsis Radix.

Abstract Ultrasonic‐assisted extraction is a rapid and effective extraction method that uses ultrasound energy and solvents to extract target compounds from various plant matrices. In this study, the ultrasonic‐assisted extraction conditions of sour jujube were optimized. A five‐level central composite design (CCD) with four variables was used to evaluate ultrasonic treatment variables influencing the total saponin content (TSC), total flavonoid content (TFC), and total phenolic content (TPC) extracted from sour jujube. The solvent concentration, extraction time, ultrasonic power, and solid‐to‐liquid (S/L) ratio were optimized using aqueous ethanol and methanol solutions as extraction solvents. A central composite design (CCD) was used for an in‐depth study, and then the optimal value that could produce the maximum TPC, TFC, TSC, and four in vitro antioxidant activities (scavenging activity of hydroxyl free radicals, ferric‐reducing antioxidant power (FRAP), phosphomolybdic acid reduction method, and 1,1‐diphenyl‐2‐picrylhydrazyl (DPPH) radical‐scavenging activity) was determined. Hydrogen peroxide‐induced oxidative stress experiment confirmed that the Jujube extract could have an antioxidant role in vivo. The relationship between the contents of three compounds and the antioxidant activity in vitro and in vivo was further studied. The results showed that optimizing methanol and ethanol extraction process parameters could improve target components’ extraction efficiency. Under the optimum conditions, the TFC and TPC yields of sour jujube by ethanol are better than methanol, while the yield of TSC by methanol is better than ethanol. In vivo data showed that Jujube extract protects against the adverse effects of oxidative stress and improves the life span of female and male Drosophila. This study provides a valuable reference for the full use of Ziziphus jujube, as well as a new direction in food development.

Abstract Purpose Restoration of the segment lordosis angle (SLA) can effectively reduce the risk of adjacent segment degeneration. This study aimed to perform a comprehensive multifactor analysis of the risk factors affecting restoration and maintenance of the SLA in oblique lumbar interbody fusion (OLIF). Methods Seventy-three patients (93 segments) who underwent OLIF with posterior pedicle screw fixation due to lumbar degenerative disease between January 2015 and December 2019 were included. Radiographic parameters including the middle disc height (MDH), segment lordosis angle (SLA), cage center point ratio (CPR), cage subsidence, and L1 CT Hounsfield Unit (HU) were measured. Results The postoperative SLA increased from 3.5° to 8.7°, and decreased to 6.7° at the last follow-up. Multivariate analysis showed that preoperative SLA, CPR and cage subsidence were significantly correlated with SLA restoration. The significant correlations were between restoration of SLA with pre-operative SLA (r=-0.575, adjusted R2 = 0.323, P preoperative MDH were risk factors for cage subsidence. Cages placed anteriorly (CPR ≥ 50%) showed a large SLA increase and lower incidence of cage subsidence than those placed posteriorly (5.9 ± 3.9° versus 4.2 ± 3.2°, P

Abstract The current understanding of lactate extends from its origins as a byproduct of glycolysis to its role in tumor metabolism, as identified by studies on the Warburg effect. The lactate shuttle hypothesis suggests that lactate plays an important role as a bridging signaling molecule that coordinates signaling among different cells, organs and tissues. Lactylation is a posttranslational modification initially reported by Professor Yingming Zhao’s research group in 2019. Subsequent studies confirmed that lactylation is a vital component of lactate function and is involved in tumor proliferation, neural excitation, inflammation and other biological processes. An indispensable substance for various physiological cellular functions, lactate plays a regulatory role in different aspects of energy metabolism and signal transduction. Therefore, a comprehensive review and summary of lactate is presented to clarify the role of lactate in disease and to provide a reference and direction for future research. This review offers a systematic overview of lactate homeostasis and its roles in physiological and pathological processes, as well as a comprehensive overview of the effects of lactylation in various diseases, particularly inflammation and cancer.

An improved position estimation of the sensorless control system with online parameter identification based on back-Electromotive Force (EMF) voltage is presented for the dual-winding fault-tolerant permanent magnet motor (FTPMM). In this control system, the rotor position is estimated by the flux linkage and the back-EMF which are generated by each phase winding. By introducing phase-locked loop technology to compensate the steady-state error of the system and online identification of motor parameters which is using the least-square method with forgetting factor, more accurate position estimation can be obtained. The current vector fault-tolerant control strategy improves the fault tolerance of the system and makes it strong robust stability. The simulation results have shown that the accurate position data can be acquired both under healthy condition and single-phase fault condition. Then, the hardware experimental results show the feasibility and validity of the proposed algorithm.

Abstract Objective Evidence regarding the relationship between serum triglyceride-to-high density lipoprotein cholesterol (TG/HDL-c) ratio and outcomes in acute ischemic stroke (AIS) patients is still mixed. Therefore, the present study was undertaken to explore the link between the TG/HDL-c ratio and unfavorable outcomes in patients with AIS. Methods This was a second analysis based on a cohort study. The study population was 1764 patients with AIS collected from January 2010 to December 2016 at a hospital in South Korea. We used a binary logistic regression model to assess the linear association between the TG/HDL-c ratio and unfavorable outcomes for AIS patients. A generalized additive model (GAM) and smooth curve fitting (penalized spline method) was conducted to explore the nonlinear relationship between TG/HDL-c ratio and unfavorable outcomes for AIS patients. Additionally, we compute the inflection point using a recursive algorithm and then build a two-piece binary logistic regression model on both sides of the inflection point. A log-likelihood ratio test was used to determine the most appropriate model describing the association of TG/HDL-c ratio and unfavorable outcomes in patients with AIS. Results The incidence rate of unfavorable outcomes was 28.2%, and the median TG/HDL-c ratio was 2.130. After adjusting covariates, the results of the binary logistic regression model suggested that the relationship between the TG/HDL-c ratio and the risk of unfavorable outcomes for AIS patients was not statistically significant. However, there was a nonlinear relationship between them, and the inflection point of the TG/HDL-c ratio was 3.515. On the left side of the inflection point, each 1-unit increase in the TG/HDL-c ratio was associated with a 22.6% lower risk of unfavorable outcomes (OR = 0.774, 95%CI:0.656 to 0.914, p = 0.002). On the right side of the inflection point, the effect size (OR) was 1.195 (95%CI:1.004 to1.423, p = 0.003). Conclusion There is a nonlinear relationship and threshold effect between the TG/HDL-c ratio and 3-month unfavorable outcomes in AIS patients. When the TG/HDL-c ratio is lower than 3.515, the TG/HDL-c ratio is significantly negatively related to the risk of unfavorable outcomes. When the TG/HDL-c ratio is greater than 3.515, the TG/HDL-c ratio was positively associated with the risk of unfavorable outcomes in AIS patients. This provides a reference for optimizing lipidemia intervention and promoting clinical communication in patients with AIS.

AimsTo systematically evaluate the diagnostic value of an artificial intelligence (AI) algorithm model for various types of diabetic retinopathy (DR) in prospective studies over the previous five years, and to explore the factors affecting its diagnostic effectiveness.Materials and methodsA search was conducted in Cochrane Library, Embase, Web of Science, PubMed, and IEEE databases to collect prospective studies on AI models for the diagnosis of DR from January 2017 to December 2022. We used QUADAS-2 to evaluate the risk of bias in the included studies. Meta-analysis was performed using MetaDiSc and STATA 14.0 software to calculate the combined sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of various types of DR. Diagnostic odds ratios, summary receiver operating characteristic (SROC) plots, coupled forest plots, and subgroup analysis were performed according to the DR categories, patient source, region of study, and quality of literature, image, and algorithm.ResultsFinally, 21 studies were included. Meta-analysis showed that the pooled sensitivity, specificity, pooled positive likelihood ratio, pooled negative likelihood ratio, area under the curve, Cochrane Q index, and pooled diagnostic odds ratio of AI model for the diagnosis of DR were 0.880 (0.875-0.884), 0.912 (0.99-0.913), 13.021 (10.738-15.789), 0.083 (0.061-0.112), 0.9798, 0.9388, and 206.80 (124.82-342.63), respectively. The DR categories, patient source, region of study, sample size, quality of literature, image, and algorithm may affect the diagnostic efficiency of AI for DR.ConclusionAI model has a clear diagnostic value for DR, but it is influenced by many factors that deserve further study.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42023389687.

Necrotizing enterocolitis (NEC) is one of the most fatal diseases in premature infants. Damage to the intestinal epithelial barrier (IEB) is an important event in the development of intestinal inflammation and the evolution of NEC. The intestinal epithelial monolayer formed by the tight arrangement of intestinal epithelial cells (IECs) constitutes the functional IEB between the organism and the extra-intestinal environment. Programmed death and regenerative repair of IECs are important physiological processes to maintain the integrity of IEB function in response to microbial invasion. However, excessive programmed death of IECs leads to increased intestinal permeability and IEB dysfunction. Therefore, one of the most fundamental questions in the field of NEC research is to reveal the pathological death process of IECs, which is essential to clarify the pathogenesis of NEC. This review focuses on the currently known death modes of IECs in NEC mainly including apoptosis, necroptosis, pyroptosis, ferroptosis, and abnormal autophagy. Furthermore, we elaborate on the prospect of targeting IECs death as a treatment for NEC based on exciting animal and clinical studies.

Abstract The atmospheric radiative transfer calculations are among the most time‐consuming components of the numerical weather prediction (NWP) models. Deep learning (DL) models have recently been increasingly applied to accelerate radiative transfer modeling. Besides, a physical relationship exists between the output variables, including fluxes and heating rate profiles. Integration of such physical laws in DL models is crucial for the consistency and credibility of the DL‐based parameterizations. Therefore, we propose a physics‐incorporated framework for the radiative transfer DL model, in which the physical relationship between fluxes and heating rates is encoded as a layer of the network so that the energy conservation can be satisfied. It is also found that the prediction accuracy was improved with the physic‐incorporated layer. In addition, we trained and compared various types of DL model architectures, including fully connected (FC) neural networks (NNs), convolutional‐based NNs (CNNs), bidirectional recurrent‐based NNs (RNNs), transformer‐based NNs, and neural operator networks, respectively. The offline evaluation demonstrates that bidirectional RNNs, transformer‐based NNs, and neural operator networks significantly outperform the FC NNs and CNNs due to their capability of global perception. A global perspective of an entire atmospheric column is essential and suitable for radiative transfer modeling as the changes in atmospheric components of one layer/level have both local and global impacts on radiation along the entire vertical column. Furthermore, the bidirectional RNNs achieve the best performance as they can extract information from both upward and downward directions, similar to the radiative transfer processes in the atmosphere.

Abstract Perovskite nanocrystals (NCs) with intentionally introduced Mn2+/Yb3+ activators enable tunable emissions covering UV‐orange‐NIR spectral range. However, the exact microscopic energy transfer mechanisms in this system remain unknown. Herein, Mn/Yb codoped CsPbCl3 perovskite NCs with triple emissions originated from exciton recombination of host, 3d–3d transition of Mn2+ and 4f–4f transition of Yb3+ are prepared. Femtosecond resolution transient absorption spectra performed on the pristine CsPbCl3, Mn‐doped, Yb‐doped and Mn/Yb codoped samples clarify efficient and simultaneous energy transfer (ET) from excitons to Mn2+ and Yb3+ dopants. It is testified the sensitizations of dopants mainly result from the trapped hole, taking 285 ps for Mn2+ and 17 ps for Yb3+ respectively, which make less trapped hole recombine with de‐localized carriers. Importantly, energy transfer processes from host to Mn2+ and Yb3+ activators emerge as competition, and the ET probability of exciton‐to‐Mn2+ is higher than that of exciton‐to‐Yb3+. Finally, control experiments further prove that tunable Mn2+ orange emission and Yb3+ NIR emission are achievable via elaborate adjustment of the dopant concentrations.