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Abstract Investigating social vulnerability is a crucial aspect of attaining an in-depth understanding of disasters and disaster risk. This study developed a measurement framework for social vulnerability to geological disasters, obtained a comprehensive social vulnerability index, and compared the spatial distribution patterns of fatalities, social vulnerability, and geological disaster-prone zones. These efforts assisted in determining the strength and character of the relationship between geological disaster fatality risk and social vulnerability at the county level. The findings show that: (1) the social vulnerability to geological disasters index varies significantly between counties. High social vulnerability is primarily concentrated in Bijie City, Guizhou province, which shows concentrated clustering. Conversely, low social vulnerability is mainly concentrated in Guiyang City: (2) the spatial distribution patterns reveal the limitations of disaster exposure in explaining fatality risk and demonstrate the ability of social vulnerability to amplify disaster risk; (3) the zero-inflated negative binomial regression model fit the data significantly better than the negative binomial regression model, suggesting that for every one unit increase in the social vulnerability index, there is a 6.33% increase in the risk of fatalities, holding all other variables constant. This study establishes a specific framework for measuring social vulnerability to geological disasters and provides new evidence of how social vulnerability influences disaster risk intensity. The county-level spatial measurement results can further assist disaster management personnel in formulating more localized mitigation strategies. The findings will further support the identification of core remediation sites and the implementation of management and relocation (avoidance) projects during Guizhou Province’s 14th Five-Year Plan for geological disaster prevention and control.

Abstract Background S100β is a biomarker of astroglial damage, the level of which is significantly increased following brain injury. However, the characteristics of S100β and its association with prognosis in patients with acute ischemic stroke following intravenous thrombolysis (IVT) remain unclear. Methods Patients in this multicenter prospective cohort study were prospectively and consecutively recruited from 16 centers. Serum S100β levels were measured 24 h after IVT. National Institutes of Health Stroke Scale (NIHSS) and hemorrhagic transformation (HT) were measured simultaneously. NIHSS at 7 days after stroke, final infarct volume, and modified Rankin Scale (mRS) scores at 90 days were also collected. An mRS score ≥ 2 at 90 days was defined as an unfavorable outcome. Results A total of 1072 patients were included in the analysis. The highest S100β levels (> 0.20 ng/mL) correlated independently with HT and higher NIHSS at 24 h, higher NIHSS at 7 days, larger final infarct volume, and unfavorable outcome at 3 months. The patients were divided into two groups based on dominant and non-dominant stroke hemispheres. The highest S100β level was similarly associated with the infarct volume in patients with stroke in either hemisphere (dominant: β 36.853, 95% confidence interval (CI) 22.659–51.048, P

The presence of probability-driven models is highly influential in setting the stage for vital decision-making in domains including reliability, engineering, music engineering, and other closely interconnected scenarios. With a deep understanding of the consequential roles played by probability-arisen models, we have developed and implemented a new probabilistic model. This model is constructed by utilizing the sine-based function and the exponentiated Weibull distribution, and it is known as the exponent power sine exponentiated Weibull (EPSE-Weibull) distribution. Point estimators are derived for the EPSE-Weibull distribution. These estimators are then evaluated through a simulation study. The significance of the EPSE-Weibull distribution is demonstrated through the analysis of reliability and music engineering data sets. In addition to the above, we also utilize two deep learning algorithms, namely Artificial Neural Networks (ANN) and Support Vector Regression (SVR), to forecast the same data sets. The findings indicate that the ANN model consistently exhibits higher levels of accuracy, as evidenced by its lower Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) values compared to the SVR model for both data sets. These findings indicate that ANN is better at capturing the fundamental patterns in the underlying data sets. In addition, visual representations, such as bar charts and line charts, further emphasize the superior performance of the ANN across both data sets.

Abstract Acute pancreatitis (AP) is an inflammatory disease of the pancreas. Despite of a steadily increasing in morbidity and mortality, there is still no effective therapy. Gut microbial dysbiosis and its derived-metabolites disorder have been shown to play an important role in the development of AP, however, little is known regarding the crosstalk between gut microbiota and metabolites. In this study, we assessed the alterations in gut microbiota and metabolites by constructing three AP mouse models by means of metagenomic and metabolomic sequencing, and further clarified their relationship by correlation analysis. The results revealed that each model exhibited unique flora and metabolite profiles. KEGG analysis showed that the differential flora and metabolite-enriched pathway functions were correlated with lipid metabolism and amino acid metabolism. Moreover, two core differential bacterial species on Burkholderiales bacterium YL45 and Bifidobacterium pseudolongum along with eleven differential metabolites appeared to exert certain effects during the course of AP. In conclusion, further exploration of the crosstalk between microbiota and derived metabolites may provide novel insights and strategies into the diagnosis and treatment of AP.

Abstract Anal swabs of 1-month-old Holstein calves with diarrhea were collected from an intensive cattle farm, and a highly pathogenic Escherichia coli strain was obtained by isolation and purification. To study the virulence and resistance genes of pathogenic E. coli that cause diarrhea in calves, a strain of E. coli E12 isolated from calf diarrhea samples was used as experimental material in this experiment, and the virulence of the E12 strain were identified by the mouse infection test, and the whole genome map of the E12 strain were obtained by whole-genome sequencing and analyzed for genome characterization. The results showed that the lethality of strain E12 was 100%, the total length of E12-encoded genes was 4,294,530 bp, Cluster of Orthologous Groups of proteins (COG) annotated to 4,194 functional genes, and the virulence genes of sequenced strain E12 were compared with the virulence genes of sequenced strain E12 from the Virulence Factors of Pathogenic Bacteria (VFDB), which contained a total of 366 virulence genes in sequenced strain E12. The analysis of virulence genes of E12 revealed a total of 52 virulence genes in the iron transferrin system, 56 virulence genes in the secretory system, 41 virulence genes in bacterial toxins, and a total of 217 virulence genes in the Adhesin and Invasins group. The antibiotic resistance genes of sequenced strain E12 were identified through the Antibiotic Resistance Genes Database (ARDB) and Comprehensive Antibiotic Research Database, and it was found that its chromosome and plasmid included a total of 127 antibiotic resistance genes in four classes, and that E12 carried 71 genes related to the antibiotic efflux pumps, 36 genes related to antibiotic inactivation, and 14 antibiotic target alteration and reduced penetration into antibiotics, and 6 antibiotic resistance genes, and the resistance phenotypes were consistent with the genotypes. The pathogenic E. coli that causes diarrhea in calves on this ranch contains a large number of virulence and resistance genes. The results provide a theoretical basis for the prevention and treatment of diarrhea and other diseases caused by E. coli disease.

Abstract Background the mortality associated with severe malaria due to Plasmodiun falciparum remains high despite improvements in malaria management. Case prensentation: this case series aims to describe the efficacy and safety of the exchange transfusion combined with artesunate (ET-AS) regimen in severe P. falciparum malaria. Eight patients diagnosed with severe P. falciparum malaria were included. All patients underwent ET using the COBE Spectra system. The aimed for a post-exchange hematocrit of 30%. Half the estimated blood volume was removed and replaced using fresh frozen plasma. The regimen was well-tolerated without complications. The parasite clearance time ranged from 1 ~ 5 days. Five patients with cerebral malaria exhibited full improved consciousness within 3 days, while patient2 with hemolysis improved on day 2. Liver function improved within 1 ~ 6 days, and patient 1 and patient 6 showed improvements renal function on days 18 and 19, respectively. The length of intensive care unit stay range from 2 ~ 10 days, and all patients treated with ET-AS remained in the hospital for 3 ~ 19 days. Conclusions: these preliminary results suggest that ET-AS regimens are a safe and effective therapy for severe P. falciparum malaria and can benefit patients in clinical settings.

Abstract Ovarian cancer is a common malignant tumor in women, with a high mortality rate ranking first among gynecological tumors. Currently, there is insufficient understanding of the causes, pathogenesis, recurrence and metastasis of ovarian cancer, and early diagnosis and treatment still face great challenges. The sensitivity and specificity of existing ovarian cancer screening methods are still unsatisfactory. Centromere protein O (CENP-O) is a recently discovered structural centromere protein that is involved in cell death and is essential for spindle assembly, chromosome separation, and checkpoint signaling during mitosis. The abnormal high expression of CENP-O was detected in various tumors such as bladder cancer and gastric cancer, and it participates in the regulation of tumor cell proliferation. In this study, we detect the expression abundance of CENP-O mRNA in different ovarian cancer cells ( ES-2, A2780, Caov-3, OVCAR-3 and SK-OV-3). The biological function changes of cell proliferation and apoptosis were detected and the role of CENP-O in ovarian cancer cell proliferation and apoptosis was explored by knocking down the expression of CENP-O gene. The results showed that CENP-O gene was significantly expressed in 5 types of ovarian cancer cell lines. After knocking down the CENP-O gene, the proliferation and cloning ability of ovarian cancer cells decreased, and the apoptosis increased. This study indicates that CENP-O has the potential to be a molecular therapeutic target, and downregulating the expression of CENP-O gene can break the unlimited proliferation ability of cancer cells and promote their apoptosis, providing a foundation and new ideas for subsequent molecular mechanism research and targeted therapy.

BackgroundSoil salinization is one of the significant factors limiting high crop yields and expansion of arable land, seriously affecting global agricultural production. Rice is an essential food crop throughout the world, and its seedlings are particularly susceptible to salt stress, which can directly affect the growth and development of rice and its final yield. We used the natural population as the material for genome-wide association study (GWAS) and the recombinant inbred line (RIL) population from CD (salt sensitive)/WD20342 (salt tolerant) hybridization as the material for linkage analysis.ResultsThe degree of salt tolerance was evaluated by using the relative root length (RRL), relative root number (RRN), relative root fresh weight (RRFW), and relative root dry weight (RRDW) as indicators. Fifteen and six major quantitative trait loci (QTLs) were identified by GWAS and linkage analysis, respectively. Meanwhile, the GWAS identified the lead SNP (Chr2_22340368), which was located within qRRL2 and qRRDW2 identified by linkage analysis. GWAS, combined with linkage analysis, selected a 196-kb overlapping region on chromosome 2, including 22 candidate genes. LOC_Os02g36880 was discovered as the candidate gene involved in salt tolerance by haplotype analysis, qRT-PCR, and sequence analysis. The score of salinity toxicity (SST) and seedling survival rate (SSR) were determined for CRISPR/Cas9 mutants (CR-1 and CR-15) and wild-type (ZH11), respectively.ConclusionThe phenotypic validation indicated that LOC_Os02g36880 negatively regulated the salt tolerance at the seedling stage. This study provides resources for breeding Japonica rice to improve its response to salt stress.

Abstract Host immunity is central to the virus's spread dynamics, which is significantly influenced by vaccination and prior infection experiences. In this work, we analyzed the co‐evolution of SARS‐CoV‐2 mutation, angiotensin‐converting enzyme 2 (ACE2) receptor binding, and neutralizing antibody (NAb) responses across various variants in 822 human and mice vaccinated with different non‐Omicron and Omicron vaccines is analyzed. The link between vaccine efficacy and vaccine type, dosing, and post‐vaccination duration is revealed. The classification of immune protection against non‐Omicron and Omicron variants is co‐evolved with genetic mutations and vaccination. Additionally, a model, the Prevalence Score (P‐Score) is introduced, which surpasses previous algorithm‐based models in predicting the potential prevalence of new variants in vaccinated populations. The hybrid vaccination combining the wild‐type (WT) inactivated vaccine with the Omicron BA.4/5 mRNA vaccine may provide broad protection against both non‐Omicron variants and Omicron variants, albeit with EG.5.1 still posing a risk. In conclusion, these findings enhance understanding of population immunity variations and provide valuable insights for future vaccine development and public health strategies.

Abstract The lymph node is the most common site of distant metastasis of cervical squamous cell carcinoma (CSCC), which elicits dismal prognosis and limited efficiency for treatment. Elucidation of the mechanisms underlying CSCC lymphatic metastasis would provide potential therapeutic strategies for nodal metastatic of CSCC. Here, based on in vivo lymphatic metastasis screening model, a circular RNA is identified that is termed as lymph node metastasis associated circRNA (LNMAC), is markedly upregulated in lymphatic metastatic CSCC and correlated with lymph node metastasis. Overexpression of LNMAC dramatically augments the metastatic capability of CSCC cells to the lymph node via inducing lymphangiogenesis. Mechanistically, LNMAC epigenetically upregulates fibroblast growth factor 2 (FGF2) expression by directly associating with histone acacetylase 1 (HDAC1), preventing Importin α6/8‐mediated nuclear translocation of HDAC1 and eliciting histone H3K27ac‐induced FGF2 transcriptional activation. Treatment with 3F12E7, an anti‐FGF2 monoclonal antibody, effectively inhibits LNMAC‐induced CSCC lymphatic metastasis. Taken together, these findings indicate that LNMAC plays a crucial role in FGF2‐mediated lymphangiogenesis and lymphatic metastasis, highlighting that LNMAC might be a therapeutic target for lymph node metastasis in CSCC patients.

IntroductionGradual pollen presentation is a reproductive strategy for plants to improve the efficiency and accuracy of pollen export and acceptance as well as to promote outcrossing. Vaccinium corymbosum Berkeley has a typical mechanism of gradual pollen presentation.MethodsIn this study, we used indoor and outdoor observations to investigate the floral characteristics, pollination characteristics and breeding system of this species in open ground and greenhouse.ResultsThe results showed that the single white, inverted bell-shaped flower of V. corymbosum was able to effectively avoid the negative effects of rainfall, nectar dilution and pollen removal by wind, and improved pollen viability and the duration of stigma receptivity. The setting rate of ‘Northland’ is higher than open ground by artificial pollination in greenhouse, therefore, greenhouses are more suitable for ‘Northland’ reproduction. The gradual pollen presentation prolongs dispersal time, promotes pollinator participation in the pollination process, increases staminate fitness, and provides for nectar feeding by pollinators as well as pollen export. Bombus spp. and A. m. ligustica were effective pollinators in the open ground and greenhouse, and the pollination efficiency of Bombus spp. was higher than that of A. m. ligustica, and greenhouse pollination is more efficient than open ground. The coincidence of the peak period of pollinator visits with the period of highest pollen viability and optimal pollination of stigmas, as well as the high nectar production, could maximize the frequency of pollinator visits and increase the chances of successful pollination as well as the pollination efficiency.DiscussionTherefore, it is important to study the floral characteristics of V. corymbosum Berkeley and the mechanism of gradual pollen presentation in order to improve the pollination efficiency and promote the success of outcrossing, which can provide a theoretical basis for the breeding of V. corymbosum.

PurposeTriple-negative breast cancer (TNBC) is a highly challenging subtype due to a unique tumor microenvironment. Several evidence (IMpassion130 trial and KEYNOTE-355 trial) supported the therapeutic effect of the immune checkpoint inhibitor in TNBC. However, the efficacy and safety of the PD-1 inhibitor sintilimab in breast cancer (BC) has not been well-investigated. So the real-world data on sintilimab-treated patients with metastatic BC were collected and analyzed in this study.MethodsThe patients were eligible according to the requirements included: ages between 18 years and 75 years; recurrent or metastatic TNBC; measurable disease based on RECIST v1.1; no limitation on the prior systemic treatments; and ECOG performance status of 0–1. Patients received sintilimab 200 mg intravenously every 3 weeks until unacceptable toxicity or disease progression.ResultsFrom 1 June 2019 to 1 October 2022, 40 female patients (median age, 55.5 years) with metastatic TNBC (mTNBC) were enrolled into the study. The median prior lines of systemic therapy for mTNBC was three (range, 1–8), with 60% of cases receiving at least three lines of therapy for metastatic disease. The visceral or brain metastasis was detected in 40.4% or 9.6% of patients, respectively. The median duration of response was 2.8 months (range, 0.7–21.0), and the median number of sintilimab doses administered was 4 (range, 1–30). The ORR and DCR were 22.5% and 72.5%, separately. The median PFS was 3.5 months (range, 1.4–21.0), with a 6-month PFS rate of 15.0% (6/40). The median OS was 52.5 months (range, 9.0–247.0) as of data cut-off. Common adverse effects were acceptable, and fatigue, skin rash, and pruritus were the frequent toxicity observed. Two cases of grade 3 curable adverse events were considered to be treatment-related. PD-L1-positive tumor was found in 40% cases (4/10) of mTNBC. Although statistical difference was not reached, the trend was obvious. Patients with PD-L1-positive tumor gained better treatment response, while the TMB-high carrier received more benefits of PFS and OS.ConclusionIn our study, preliminary evidence provided the anticancer activity and acceptable adverse effects of sintilimab administered every 3 weeks to pretreated patients with mTNBC. Sintilimab showed its efficacy and safety of immunotherapy for patients with advanced TNBC.

Abstract Dynamic manipulation of an object's infrared radiation characteristics is a burgeoning technology with significant implications for energy and information fields. However, exploring efficient stimulus–spectral response mechanism and realizing simple device structures remains a formidable challenge. Here, a novel dynamic infrared emissivity regulation mechanism is proposed by controlling the localized surface plasmon resonance absorption of aluminum‐doped zinc oxide (AZO) nanocrystals through ultraviolet photocharging/oxidative discharging. A straightforward device architecture that integrates an AZO nanocrystal film with an infrared reflective layer and a substrate, functioning as a photo‐induced dynamic infrared emissivity modulator, which can be triggered by weak ultraviolet light in sunlight, is engineered. The modulator exhibits emissivity regulation amount of 0.72 and 0.61 in the 3–5 and 8–13 µm ranges, respectively. Furthermore, the modulator demonstrates efficient light triggering characteristic, broad spectral range, angular‐independent emissivity, and long cyclic lifespan. The modulator allows for self‐adaptive daytime radiative cooling and nighttime heating depending on the ultraviolet light in sunlight and O2 in air, thereby achieving smart thermal management for buildings with zero‐energy expenditure. Moreover, the potential applications of this modulator can extend to rewritable infrared displays and deceptive infrared camouflage.

Abstract The Global Navigation Satellite Systems (GNSS), including the US’s GPS, China’s BDS, the European Union’s Galileo, and Russia’s GLONASS, offer real-time, all-weather, any-time, anywhere and high precision observations by transmitting L band signals continuously, which have been widely used for positioning, navigation and timing. With the development of GNSS technology, it has been found that GNSS-reflected signals can be used to detect Earth’s surface characteristics together with other signals of opportunity. In this paper, the current status and latest advances are presented on Global Navigation Satellite System-Reflectometry (GNSS-R) in theory, methods, techniques and observations. New developments and progresses in GNSS-R instruments, theoretical modeling, and signal processing, ground and space-/air-borne experiments, parameters retrieval (e.g. wind speed, sea surface height, soil moisture, ice thickness), sea surface altimetry and applications in the atmosphere, oceans, land, vegetation, and cryosphere are given and reviewed in details. Meanwhile, the challenges in the GNSS-R development of each field are also given. Finally, the future applications and prospects of GNSS-R are discussed, including multi-GNSS reflectometry, new GNSS-R receivers, GNSS-R missions, and emerging applications, such as mesoscale ocean eddies, ocean phytoplankton blooms, microplastics detection, target recognition, river flow, desert studies, natural hazards and landslides monitoring.

In this paper, the electromagnetic performance of variable flux memory (VFM) machines with series-magnetic-circuit is investigated and compared for different rotor topologies. Based on a V-type VFM machine, five topologies with different interior permanent magnet (IPM) arrangements are evolved and optimized under same constrains. Based on two-dimensional (2-D) finite element (FE) method, their electromagnetic performance at magnetization and demagnetization states is evaluated. It reveals that the iron bridge and rotor lamination region between constant PM (CPM) and variable PM (VPM) play an important role in torque density and flux regulation (FR) capabilities. Besides, the global efficiency can be improved in VFM machines by adjusting magnetization state (MS) under different operating conditions.

Abstract Background In HBV-associated HCC, T cells often exhibit a state of functional exhaustion, which prevents the immune response from rejecting the tumor and allows HCC to progress. Moreover, polymerase-specific T cells exhibit more severe T-cell exhaustion compared to core-specific T cells. However, whether HBV DNA polymerase drives HBV-specific CD8+ T cell exhaustion in HBV-related HCC remains unclear. Methods We constructed a Huh7 cell line stably expressing HA-HBV-DNA-Pol and applied co-culture systems to clarify its effect on immune cell function. We also examined how HBV-DNA-Pol modulated PD-L1 expression in HCC cells. In addition, HBV-DNA-Pol transgenic mice were used to elucidate the underlying mechanism of HBV-DNA-Pol/PD-L1 axis-induced T cell exhaustion. Results Biochemical analysis showed that Huh7 cells overexpressing HBV-DNA-Pol inhibited the proliferation, activation, and cytokine secretion of Jurkat cells and that this effect was dependent on their direct contact. A similar inhibitory effect was observed in an HCC mouse model. PD-L1 was brought to our attention during screening. Our results showed that the overexpression of HBV-DNA-Pol upregulated PD-L1 mRNA and protein expression. PD-L1 antibody blockade reversed the inhibitory effect of Huh7 cells overexpressing HBV-DNA-Pol on Jurkat cells. Mechanistically, HBV-DNA-Pol interacts with PARP1, thereby inhibiting the nuclear translocation of PARP1 and further upregulating PD-L1 expression. Conclusions Our findings suggest that HBV-DNA-Pol can act as a regulator of PD-L1 in HCC, thereby directing anti-cancer immune evasion, which further provides a new idea for the clinical treatment of liver cancer.

Abstract A series of siloxane‐containing polyimide films (PIS) were prepared by copolymerising with rigid aromatic dianhydride, siloxane diamines and six different aromatic diamines. The effects of siloxane structures, fluorine and imide content, rigid or flexible segment on the heat resistance, moisture absorption, dielectric performance, mechanical and bonding properties were systematically studied. The results show that PIS films maintain good heat resistance with Tg between 292 and 420°C and 5% weight loss temperature higher than 500°C. The moisture absorption and dielectric constant can be significantly reduced due to the presence of siloxanes and fluorinated groups, with the absorption rate as low as 1.2% and dielectric constant of 2.85 at 1 MHz. When measured at 10 GHz, the dielectric constant ranges from 3.10 to 3.50, and dielectric loss varies from 0.0059 to 0.0098. The PIS‐6 film has the best comprehensive performance due to the low imide content, introduction of trifluoromethyl and ether bonds. The peeling strength of bonding PIS‐6 film with a copper foil can reach 9.2 N/cm. It is proven that siloxane‐containing PIS films with high heat resistance, low dielectric and outstanding adhesion are achieved, which can be applied for flexible integrated circuit boards, high‐frequency electronics and microelectronics fields.

ABSTRACTThe estimation of soil moisture (SM) utilizing the data from the Cyclone Global Navigation Satellite System (CYGNSS) has attracted significant interest in recent times. However, CYGNSS’ inherent capability of variable resolution has not been fully exploited, often resulting in a loss of detailed spatial information in the raw data. In this paper, a novel downscaling scheme tailored for CYGNSS data is introduced to yield a “self-adjusting adaptive resolution” SM product, which dynamically varies the resolution of SM estimates based on the available CYGNSS data resolution at different geographic locations. Initially, a direct quantitative relationship is established between the key CYGNSS parameters reflecting SM variations and the reference SM from the Soil Moisture Active Passive (SMAP) mission with a coarse resolution of 36 km. This model is then applied to CYGNSS observations with resolutions down to 3 km to generate high-resolution, self-adjusting SM estimates that better conserve the fine-scale information linked to the original CYGNSS data. Extensive experimental results with error ratio diagrams show that the advanced geographically weighted regression (GWR)-based SM estimation method outperforms other competing estimation models and better retains localized spatial relationships and patterns. This study underscores the potential of CYGNSS as a novel and robust independent data source capable of delivering fine-resolution SM estimations by harnessing its unique multiresolution observational capability.

Abstract A stable and highly active core‐shell heterostructure electrocatalyst is essential for catalyzing oxygen evolution reaction (OER). Here, a dual‐trimetallic core‐shell heterostructure OER electrocatalyst that consists of a NiFeWS2 inner core and an amorphous NiFeW(OH)z outer shell is designed and synthesized using in situ electrochemical tuning. The electrochemical measurements of different as‐synthesized catalysts with a similar mass loading suggest that the core‐shell Ni0.66Fe0.17W0.17S2@amorphous NiFeW(OH)z nanosheets exhibit the highest overall performance compared with that of other bimetallic reference catalysts for the OER. Additionally, the nanosheet arrays were in situ grown on hydrophilic‐treated carbon paper to fabricate an integrated three‐dimensional electrode that affords a current density of 10 mA cm−2 at a small overpotential of 182 mV and a low Tafel slope of 35 mV decade−1 in basic media. The Faradaic efficiency of core‐shell Ni0.66Fe0.17W0.17S2@amorphous NiFeW(OH)z is as high as 99.5% for OER. The scanning electron microscope, transmission electron microscope, and X‐ray photoelectron spectroscopy analyses confirm that this electrode has excellent stability in morphology and elementary composition after long‐term electrochemical measurements. Importantly, density functional theory calculations further indicate that the core‐shell heterojunction increased the conductivity of the catalyst, optimized the adsorption energy of the OER intermediates, and improved the OER activity. This study provides a universal strategy for designing more active core‐shell structure electrocatalysts based on the rule of coordinated regulation between electronic transport and active sites.

Abstract Identifying mechanisms underlying cancer resistance to therapy is vital for advancing treatment strategies. Pathogenic mutations of homologous recombination repair (HRR) genes are known biomarkers for platinum (Pt)‐based chemotherapy and poly ADP ribose polymerase inhibitors (PARPi) effectiveness. Yet, the dynamics of HRR reversion mutations, which may herald therapy resistance, are not fully elucidated. Addressing this gap, our study analyzed secondary HRR gene mutations in a comprehensive pan‐cancer data set of approximately 13,000 patients who underwent targeted next‐generation sequencing. We identified a subset of patients harboring secondary mutations, which were further categorized into three tiers based on their nature, and occur in the presence of a primary pathogenic mutation, notably in BRCA1, BRCA2, PALB2, and RAD51D genes. Here we show that secondary BRCA2 mutations, indicative of adaptive resistance, emerge post‐Pt/Olaparib treatment. This challenges the prevailing notion that pathogenic HRR mutations uniformly predict therapeutic sensitivity, highlighting a nuanced genetic interplay that impacts treatment success. This investigation enriches our understanding of cancer's adaptive mechanisms against therapy, suggesting a pivotal shift towards more personalized, dynamic treatment strategies. It underscores the imperative of adapting to cancer's genetic evolution, aiming for a step ahead in the ongoing battle against this disease.

Abstract The vaginal microbiome plays an essential role in the reproductive health of human females. As infertility increases worldwide, understanding the roles that the vaginal microbiome may have in infertility and in vitro fertilization (IVF) treatment outcomes is critical. To determine the vaginal microbiome composition of 1411 individuals (1255 undergoing embryo transplantation) and their associations with reproductive outcomes, clinical and biochemical features are measured, and vaginal samples are 16S rRNA sequenced. Our results suggest that both too high and too low abundance of Lactobacillus is not beneficial for pregnancy; a moderate abundance is more beneficial. A moderate abundance of Lactobacillus crispatus and Lactobacillus iners (~80%) (with a pregnancy rate of I‐B: 54.35% and III‐B: 57.73%) is found beneficial for pregnancy outcomes compared with a higher abundance (>90%) of Lactobacillus (I‐A: 44.81% and III‐A: 51.06%, respectively). The community state type (CST) IV‐B (contains a high to moderate relative abundance of Gardnerella vaginalis) shows a similar pregnant ratio (48.09%) with I‐A and III‐A, and the pregnant women in this CST have a higher abundance of Lactobacillus species. Metagenome analysis of 71 samples shows that nonpregnant women are detected with more antibiotic‐resistance genes, and Proteobacteria and Firmicutes are the main hosts. The inherent differences within and between women in different infertility groups suggest that vaginal microbes might be used to detect infertility and potentially improve IVF outcomes.

Abstract Accumulating evidence indicates that metabolic reprogramming of cancer cells supports the energy and metabolic demands during tumor metastasis. However, the metabolic alterations underlying lymph node metastasis (LNM) of cervical cancer (CCa) have not been well recognized. In the present study, it is found that lymphatic metastatic CCa cells have reduced dependency on glucose and glycolysis but increased fatty acid oxidation (FAO). Inhibition of carnitine palmitoyl transferase 1A (CPT1A) significantly compromises palmitate‐induced cell stemness. Mechanistically, FAO‐derived acetyl‐CoA enhances H3K27 acetylation (H3K27Ac) modification level in the promoter of stemness genes, increasing stemness and nodal metastasis in the lipid‐rich nodal environment. Genetic and pharmacological loss of CPT1A function markedly suppresses the metastatic colonization of CCa cells in tumor‐draining lymph nodes. Together, these findings propose an effective method of cancer therapy by targeting FAO in patients with CCa and lymph node metastasis.

Abstract Background Cervical cancer (CCa) is the fourth most common cancer among females, with high incidence and mortality rates. Circular RNAs (circRNAs) are key regulators of various biological processes in cancer. However, the biological role of circRNAs in cervical cancer (CCa) remains largely unknown. This study aimed to elucidate the role of circMAST1 in CCa. Methods CircRNAs related to CCa progression were identified via a circRNA microarray. The relationship between circMAST1 levels and clinicopathological features of CCa was evaluated using the clinical specimens and data of 131 patients with CCa. In vivo and in vitro experiments, including xenograft animal models, cell proliferation assay, transwell assay, RNA pull-down assay, whole-transcriptome sequencing, RIP assay, and RNA-FISH, were performed to investigate the effects of circMAST1 on the malignant behavior of CCa. Results CircMAST1 was significantly downregulated in CCa tissues, and low expression of CircMAST1 was correlated with a poor prognosis. Moreover, our results demonstrated that circMAST1 inhibited tumor growth and lymph node metastasis of CCa. Mechanistically, circMAST1 competitively sequestered N-acetyltransferase 10 (NAT10) and hindered Yes-associated protein (YAP) mRNA ac4C modification to promote its degradation and inhibit tumor progression in CCa. Conclusions CircMAST1 plays a major suppressive role in the tumor growth and metastasis of CCa. In particular, circMAST1 can serve as a potential biomarker and novel target for CCa.

Global Navigation System Reflectometry (GNSS-R) is a microwave remote sensing technology that enables Earth observation by receiving GNSS signals reflected from the Earth's surface. The Cyclone Global Navigation Satellite System (CYGNSS) constellation is a satellite system that uses GNSS-R technology with high temporal resolution and has been a popular data source in soil moisture retrieval in recent years. However, the constant movement of GNSS transmitters and GNSS-R satellites results in potentially chaotic and random observations of the Earth's surface, with many unevenly distributed gaps in the observed data. In this paper, a gap-filling method based on spatial autocorrelation is proposed to interpolate the gaps within these observation datasets, with SM being estimated post-interpolation. The sample set for the model comprises points surrounding the interpolation target, with modeling conducted considering factors of spatial weighting to estimate values at the interpolation target. Different autocorrelation-based gap-filling methods using CYGNSS data can achieve good estimation accuracy, and the data coverage after interpolation is on average 1.8 times greater than before interpolation. The gap-filling method using XGBoost achieves the best performance and offers the highest accuracy in SM estimation, with an average correlation coefficient of 0.8445, and an average RMSE of 0.0457 m3/m3. The gap-filling approach can significantly enhance data coverage and facilitate the filling of daily gaps in CYGNSS data with all maintaining high SM estimation accuracy. The estimation of daily missing values using CYGNSS data can fully exploit the embedded surface features in the data's fine resolution and can provide high-resolution SM retrieval.

With the widespread popularity of deep learning, various neural network models are extensively employed in the recognition, classification, and segmentation of remote sensing images. Convolutional neural networks (CNNs), fully convolutional networks, including their variants like Unet, have demonstrated significant results within this particular domain. Nevertheless, CNNs exhibit limitations when it comes to grasping extended global dependencies. Conversely, transformers exhibit exceptional ability in effectively dealing with long-range dependencies. Considering this, we have introduced the efficient channel attention-enhanced dual-stream neural network (ECA-DSNN) to improve the identification of buildings across various scenes. Specifically, we developed a dual-stream network that incorporates the Unet and transformer framework in order to capture both the local and global context. In addition, we introduced an attention mechanism module to augment the model's generalization capability. With the advanced identification and generalization capability of ECA-DSNN, only fine-tuning and data augmentation are needed to achieve superior performance in cross-scene transfer, even with limited samples in the target domain. The outcomes indicated that the ECA-DSNN proposed achieved superior performance in comparison to the state-of-the-art methodologies, particularly in the experiment transferring from the source domain Beijing to the target domain Shanghai. In this scenario, the overall accuracy surpassed 96.3% and an F1 score exceeded 78.6%.

Satellite-based solar-induced chlorophyll fluorescence (SIF) has emerged as a valuable tool for monitoring the photosynthetic activity of vegetation at both regional and global scales. Downscaling techniques offer the opportunity to utilize coarse-spatial-resolution SIF products for investigating carbon cycles and ecological processes at finer resolutions. However, the lack of pre-2000 downscaled products and the limited utilization of residual information in existing models pose challenges in fully harnessing the potential of SIF downscaling. In this study, we generated a new monthly SIF product, DSIFRFK*_EA0.05, at a resolution of 0.05° in East Asia from July 1995 to June 2003. Random forest kriging (RFK) was employed, incorporating GOME SIF, AVHRR data, ERA5 climate data, and using the optimal explanatory variables. Compared with other downscaled results, the produced DSIFRFK*_EA0.05 has higher accuracy and more accurate details of SIF distribution with the highest mean R2 value of 0.83 and smallest root mean squared error value of 0.08 mW/m2/nm/sr. The DSIFRFK*_EA0.05 estimates showed a strong correlation with gross primary productivity data from eight flux sites (R2 = 0.73), as well as high correlation coefficient values of 0.73, 0.88, and 0.89 with three other fine-resolution products. This study addresses the gap in statistical downscaling of SIF before 2000 and demonstrates the feasibility of utilizing AVHRR data for fine-resolution SIF prediction. Our developed product offers improved detail compared to the original GOME SIF, thereby enhancing the application of satellite SIF for understanding early carbon cycles and ecological processes at a finer resolution.

The spatially variant apodization (SVA) algorithm, a classic super-resolution method for synthetic aperture radar (SAR) images, can suppress side lobes while maintain the resolution of the main lobe. To address the problem of residual side lobes or loss of main lobe energy in improved SVA algorithms, the article proposes a new side lobe suppression method combining the bidirectional recurrent neural network (BiRNN) and the SVA algorithm, employing BiRNN to extract the main lobe and side lobe features of radar data to achieve side lobe suppression at any Nyquist sampling rate. The land flight experiment data of the fully polarized microwave scatterometer is used to quantitatively evaluate the side lobe suppression performance and the main lobe energy in order to verify the effectiveness of the BiRNN-SVA method. The experimental results demonstrate that the BiRNN-SVA method can be applied to data at any Nyquist sampling rate and has superior PSLR and ISLR compared to the GSVA algorithm and MSVA algorithm. The image processed with the proposed method retains more fine details and edge features. In comparison to the GSVA algorithm and MSVA algorithm, the image contrast and focus have increased by 31.6% and 3.6%, respectively, and by 4.4% and 1.1%.

Algal blooms, resulting from the overgrowth of algal plankton in water bodies, pose significant environmental problems and necessitate effective remote sensing methods for monitoring. In recent years, Global Navigation Satellite System–Reflectometry (GNSS-R) has rapidly advanced and made notable contributions to many surface observation fields, providing new means for identifying algal blooms. Additionally, meteorological parameters such as temperature and wind speed, key factors in the occurrence of algal blooms, can aid in their identification. This paper utilized Cyclone GNSS (CYGNSS) data, Sentinel-3 OLCI data, and ECMWF Re-Analysis-5 meteorological data to retrieve Chlorophyll-a values. Machine learning algorithms were then employed to classify algal blooms for early warning based on Chlorophyll-a concentration. Experiments and validations were conducted from May 2023 to September 2023 in the Hongze Lake region of China. The results indicate that classification and early warning of algal blooms based on CYGNSS data produced reliable results. The ability of CYGNSS data to accurately reflect the severity of algal blooms opens new avenues for environmental monitoring and management.

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system primarily mediated by CD4+ T helper cells. This study investigated the dynamic changes of natural killer (NK) cells and follicular T helper (Tfh) cells and their associations in relapsing-remitting MS patients. The findings revealed inverse relationships between NK cells and CD4+ T cells or Tfh cells. Specifically, CD56dim NK cells, not CD56bright NK cells, were negatively correlated with CD4+ T cells and Tfh cells. However, no significant correlations were found between NK cells and sNfL levels or EDSS scores. The ratio of CD56dim NK cells to circulating Tfh (cTfh) cells demonstrated superior discriminatory ability in distinguishing relapsing MS patients from healthy controls (HCs) and remitting patients, as determined by receiver operating characteristic (ROC) analysis. Following treatment with immunosuppressants or disease-modifying therapies (DMTs), a significant increase in the CD56dim NK/cTfh ratio was observed. These findings suggest that the CD56dim NK/cTfh ratio holds promise as a prognostic indicator for clinical relapse and treatment response in MS.

BackgroundInternational health policies and researchers have emphasized the value of evaluating patient-reported outcomes (PROs) in clinical studies. However, the characteristics of PROs in adult tumor clinical trials in China remain insufficiently elucidated. ObjectiveThis study aims to assess the application and characteristics of PRO instruments as primary or secondary outcomes in adult randomized clinical trials related to tumors in China. MethodsThis cross-sectional study identified tumor-focused randomized clinical trials conducted in China between January 1, 2010, and June 30, 2022. The ClinicalTrials.gov database and the Chinese Clinical Trial Registry were selected as the databases. Trials were classified into four groups based on the use of PRO instruments: (1) trials listing PRO instruments as primary outcomes, (2) trials listing PRO instruments as secondary outcomes, (3) trials listing PRO instruments as coprimary outcomes, and (4) trials without any mention of PRO instruments. Pertinent data, including study phase, settings, geographic regions, centers, participant demographics (age and sex), funding sources, intervention types, target diseases, and the names of PRO instruments, were extracted from these trials. The target diseases involved in the trials were grouped according to the American Joint Committee on Cancer Staging Manual, 8th Edition. ResultsAmong the 6445 trials examined, 2390 (37.08%) incorporated PRO instruments as part of their outcomes. Within this subset, 26.82% (641/2390) listed PRO instruments as primary outcomes, 52.72% (1260/2390) as secondary outcomes, and 20.46% (489/2390) as coprimary outcomes. Among the 2,155,306 participants included in these trials, PRO instruments were used to collect data from 613,648 (28.47%) patients as primary or secondary outcomes and from 74,287 (3.45%) patients as coprimary outcomes. The most common conditions explicitly using specified PRO instruments included thorax tumors (217/1280, 16.95%), breast tumors (176/1280, 13.75%), and lower gastrointestinal tract tumors (173/1280, 13.52%). Frequently used PRO instruments included the European Organisation for Research and Treatment of Cancer Quality of Life Core Questionnaire–30, the visual analog scale, the numeric rating scale, the Traditional Chinese Medicine Symptom Scale, and the Pittsburgh Sleep Quality Index. ConclusionsOver recent years, the incorporation of PROs has demonstrated an upward trajectory in adult randomized clinical trials on tumors in China. Nonetheless, the infrequent measurement of the patient’s voice remains noteworthy. Disease-specific PRO instruments should be more effectively incorporated into various tumor disease categories in clinical trials, and there is room for improvement in the inclusion of PRO instruments as clinical trial end points.

Paclitaxel (trade name Taxol) is a rare diterpenoid with anticancer activity isolated from Taxus. At present, paclitaxel is mainly produced by the semi-synthetic method using extract of Taxus tissues as raw materials. The studies of regulatory mechanisms in paclitaxel biosynthesis would promote the production of paclitaxel through tissue/cell culture approaches. Here, we systematically identified 990 transcription factors (TFs), 460 microRNAs (miRNAs), and 160 phased small interfering RNAs (phasiRNAs) in Taxus chinensis to explore their interactions and potential roles in regulation of paclitaxel synthesis. The expression levels of enzyme genes in cone and root were higher than those in leaf and bark. Nearly all enzyme genes in the paclitaxel synthesis pathway were significantly up-regulated after jasmonate treatment, except for GGPPS and CoA Ligase. The expression level of enzyme genes located in the latter steps of the synthesis pathway was significantly higher in female barks than in male. Regulatory TFs were inferred through co-expression network analysis, resulting in the identification of TFs from diverse families including MYB and AP2. Genes with ADP binding and copper ion binding functions were overrepresented in targets of miRNA genes. The miRNA targets were mainly enriched with genes in plant hormone signal transduction, mRNA surveillance pathway, cell cycle and DNA replication. Genes in oxidoreductase activity, protein-disulfide reductase activity were enriched in targets of phasiRNAs. Regulatory networks were further constructed including components of enzyme genes, TFs, miRNAs, and phasiRNAs. The hierarchical regulation of paclitaxel production by miRNAs and phasiRNAs indicates a robust regulation at post-transcriptional level. Our study on transcriptional and posttranscriptional regulation of paclitaxel synthesis provides clues for enhancing paclitaxel production using synthetic biology technology.

ObjectiveTo investigate the predictors of clinical pregnancy and live birth rate in patients with recurrent embryo implantation failure (RIF) treated with in vitro fertilization-embryo transfer (IVF-ET) technique.MethodThis retrospective cohort study was conducted in Jinjiang District Maternal and Child Health Hospital, Chengdu City, Sichuan Province, China. Patients were recruited who were enrolled at this hospital between November 1, 2019 and August 31, 2022, and who met the following criteria: a frozen embryo transfer (FET) at day 5 or 6 blastocyst stage was performed and the number of transfer cycles was not less than two. We collected information on age, height, weight, number of embryo transfer cycles, and information related to clinical outcomes. We used the group of patients who underwent ERA testing as the study group and those who underwent FET only as the control group, and matched baseline characteristics between the two groups by propensity score to make them comparable. We compared the differences in clinical outcomes between the two groups and further explored predictors of pregnancy and live birth using survival analysis and COX regression modeling.ResultsThe success rate of clinical pregnancy in RIF patients was 50.74% and the live birth rate was 33.09%. Patients in the FET group were less likely to achieve clinical pregnancy compared to the ERA group (HR = 0.788, 95%CI 0.593–0.978, p 3 previous implantation failures had a lower probability of achieving a clinical pregnancy (HR = 0.058, 95%CI 0.026–0.128, p 3 previous implantation failures, using single embryo transfer and not transferring quality embryos are predictors for clinical pregnancy in patients with RIF. Having>3 previous implantation failures and using single embryo transfer were predictors for live birth in patients with RIF.

IntroductionLow-temperature stress negatively impacts rice yield, posing a significant risk to food security. While previous studies have explored the physiological and linear gene expression alterations in rice under low-temperature conditions, the changes in competing endogenous RNA (ceRNA) networks remain largely unexamined.MethodsWe conducted RNA sequencing on two japonica rice varieties with differing cold-tolerance capabilities to establish ceRNA networks. This enabled us to investigate the transcriptional regulatory network and molecular mechanisms that rice employs in response to low-temperature stress.ResultsWe identified 364 differentially expressed circular RNAs (circRNAs), 224 differentially expressed microRNAs (miRNAs), and 12,183 differentially expressed messenger RNAs (mRNAs). WRKY family was the most prominent transcription factor family involved in cold tolerance. Based on the expression patterns and targeted relationships of these differentially expressed RNAs, we discerned five potential ceRNA networks related to low-temperature stress in rice: osa-miR166j-5p from the miR166 family was associated with cold tolerance; osa-miR528-3p and osa-miR156j-3p were linked to stress response; and osa-miR156j-3p was involved in the antioxidant system. In addition, Os03g0152000 in the antioxidant system, as well as Os12g0491800 and Os05g0381400, correlated with the corresponding stress response and circRNAs in the network. A gene sequence difference analysis and phenotypic validation of Os11g0685700 (OsWRKY61) within the WRKY family suggested its potential role in regulating cold tolerance in rice.Discussion and conclusionWe identified Os11g0685700 (OsWRKY61) as a promising candidate gene for enhancing cold tolerance in japonica rice. The candidate miRNAs, mRNAs, and circRNAs uncovered in this study are valuable targets for researchers and breeders. Our findings will facilitate the development of cold-tolerant rice varieties from multiple angles and provide critical directions for future research into the functions of cold-tolerance-related miRNAs, mRNAs, and circRNAs in rice.

Metasurfaces provide excellent design flexibility, allowing for the creation of versatile integrated designs with significant potential for practical applications. This paper proposes a dual-channel polarization-modulated metasurface, which realizes the modulation of line-polarized light (LP) to circularly polarized light (CP) with opposite rotation. The polarization state of the dual channels can be changed by adjusting the polarization angle of the line-polarized light. Through the reasonable selection of element atoms, the function of the quarter waveplate is combined with the wavefront control of the general metalens, and the spiral phase can be arbitrarily added to the two channels to realize the simultaneous generation of multi-mode vortex beams. This work achieves functional integration on a single-layer metasurface, enabling its application in polarization imaging and other areas. This work achieves functional integration on a single-layer metasurface, enabling its application in polarization imaging and other areas.

Abstract Purpose To investigate the clinical value of radiomic analysis on [18F]FDG and [18F]FLT PET on the differentiation of [18F]FDG-avid benign and malignant pulmonary nodules (PNs). Methods Data of 113 patients with inconclusive PNs based on preoperative [18F]FDG PET/CT who underwent additional [18F]FLT PET/CT scans within a week were retrospectively analyzed in the present study. Three methods of analysis including visual analysis, radiomic analysis based on [18F]FDG PET/CT images alone, and radiomic analysis based on dual-tracer PET/CT images were evaluated for differential diagnostic value of benign and malignant PNs. Results A total of 678 radiomic features were extracted from volumes of interest (VOIs) of 123 PNs. Fourteen valuable features were thereafter selected. Based on a visual analysis of [18F]FDG PET/CT images, the diagnostic accuracy, sensitivity, and specificity were 61.6%, 90%, and 28.8%, respectively. For the test set, the area under the curve (AUC), sensitivity, and specificity of the radiomic models based on [18F]FDG PET/CT plus [18F]FLT signature were equal or better than radiomics based on [18F]FDG PET/CT only (0.838 vs 0.810, 0.778 vs 0.778, 0.750 vs 0.688, respectively). Conclusion Radiomic analysis based on dual-tracer PET/CT images is clinically promising and feasible for the differentiation between benign and malignant PNs. Clinical relevance statement Radiomic analysis will add differential diagnostic value of benign and malignant pulmonary nodules: a hybrid imaging study based on [18F]FDG and [18F]FLT PET/CT. Key points • Radiomics brings new insights into the differentiation of benign and malignant pulmonary nodules beyond the naked eyes. • Dual-tracer imaging shows the biological behaviors of cancerous cells from different aspects. • Radiomics helps us get to the histological view in a non-invasive approach. Graphical Abstract

Abstract Heparin (HP) and heparan sulfate (HS) are multifunctional polysaccharides widely used in clinical therapy. Heparinases (Hepases) are enzymes that specifically catalyse HP and HS degradation, and they are valuable tools for studying the structure and function of these polysaccharides and for preparing low molecular weight heparins. In this study, by searching the NCBI database, a novel enzyme named PCHepII was discovered in the genome of the marine bacterium Puteibacter caeruleilacuae. Heterologously expressed PCHepII in Escherichia coli (BL21) has high expression levels and good solubility, active in sodium phosphate buffer (pH 7.0) at 20°C. PCHepII exhibits an enzyme activity of 254 mU/mg towards HP and shows weak degradation capacity for HS. More importantly, PCHepII prefers to catalyse the high-sulfated regions of HP and HS rather than the low-sulfated regions. Although PCHepII functions primarily as an endolytic Hepase, it mainly generates disaccharide products during the degradation of HP substrates over time. Investigations reveal that PCHepII exhibits a preference for catalysing the degradation of small substrates, especially HP tetrasaccharides. The catalytic sites of PCHepII include the residues His199, Tyr254, and His403, which play crucial roles in the catalytic process. The study and characterization of PCHepII can potentially benefit research and applications involving HP/HS, making it a promising enzyme.

Abstract Background Microbiome changes on the ocular surface may cause dry eyes. A metagenome assay was used to compare the microbiome composition and function of the ocular surface between diabetic children and adolescents with dry eye, diabetic children and adolescents without dry eye, and normal children. Materials and methods Twenty children and adolescents aged 8 to 16 with diabetes were selected from the Shanghai Children and Adolescent Diabetes Eye Study. Ten healthy children and adolescents belonging to the same age group were selected from the outpatient clinic during the same period. The participants were classified into the dry eye group (DM-DE group, n = 10), the non-dry eye group (DM-NDE group, n = 10) and the normal group (NDM group, n = 10). A conjunctival sac swab was collected for metagenomic sequencing, and the relationship between the microbiome composition and functional gene differences on the ocular surface with dry eye was studied. Results The classification composition and metabolic function of the microorganisms on the ocular surface of children in the 3 groups were analyzed. It was found that children’s ocular microbiota was composed of bacteria, viruses and fungi. There were significant differences in α diversity and β diversity of microbial composition of ocular surface between DM-DE group and NDM group(P

Self-compacting concrete (SCC), known for its excellent fluidity and self-compacting ability, is widely used in civil engineering. To enhance the comprehensive performance of SCC, dolomite powder (DP) is integrated as a substitute for cement. This study aims to analyze the impact of DP on the yield stress relationship between self-compacting mortar (SCM) and self-compacting paste (SCP) from a multi-scale perspective. A new predictive model for the yield stress relationship between SCM and SCP incorporating DP is established by improving the n value in the existing ϕe model, which characterizes the sensitivity of the mortar yield stress relative to changes in the paste yield stress. By conducting mini-slump flow tests on nine sets of cement–DP mixtures, it is found that DP impacts the yield stress relationship between SCM and SCP mainly through changes in the inter-particle filling effect, and the n value in the predictive model is roughly between 2.4 and 3.6. When the DP content is kept constant and the particle size is changed, the n value shows a strong positive linear relationship with the packing density of the paste (ϕe,p). The relationship between n and ϕe,p is derived using the linear fitting method, which improves the model’s predictive accuracy by 95.2%.

Heap bioleaching is considered to be a less energy-intensive metal-extraction technique compared to other methods, making it particularly attractive for low-grade sulfide ores. It has been successfully applied to recovery of copper, gold, and uranium from ores over decades. Despite its seemingly straightforward nature, heap bioleaching can experience failures if the ore is unsuitable or the heap leach process is not thoroughly investigated and well-developed. Therefore, multidisciplinary approaches are essential for research and development in heap bioleaching, as its performance depends on numerous processes operating across a wide range of length scales. This review focused on the current state of knowledge regarding the understanding of multi-scale mechanisms in heap bioleaching and the use of multidisciplinary approaches at different scales to develop the process. The investigation covered various scales, such as atomic and molecular, mineralogy and microbes, reaction particles, heap bioleaching units and full-scale factory production. Different approaches were employed to gain a comprehensive understanding of the microbial molecular structure and metabolism, the structure and reaction of minerals, microbial–mineral interaction, particles and aggregation states, and multiphase flow transfer, as well as laboratory experiments, modeling, industrialization, and operation optimization. We emphasized the need for collaboration among researchers from different disciplines and stress the importance of considering the coupling effects of physical, chemical, and microbiological factors when running heap bioleaching plants. Such collaboration and coupling are vital for successful implementation and optimization of heap bioleaching processes. This paper aimed to provide a comprehensive overview of current research related to heap bioleaching at different scales and disciplines, and gave implications to heap bioleaching technology development.

The recently introduced complex-valued convolutional neural network (CV-CNN) has shown considerable advancements for polarimetric synthetic aperture radar (PolSAR) image classification by effectively incorporating both magnitude and phase information. However, a solitary 2D or 3D CNN encounters challenges such as insufficiently extracting scattering channel dimension features or excessive computational parameters. Moreover, these networks’ default is that all information is equally important, consuming vast resources for processing useless information. To address these issues, this study presents a new hybrid CV-CNN with the attention mechanism (CV-2D/3D-CNN-AM) to classify PolSAR ground objects, possessing both excellent computational efficiency and feature extraction capability. In the proposed framework, multi-level discriminative features are extracted from preprocessed data through hybrid networks in the complex domain, along with a special attention block to filter the feature importance from both spatial and channel dimensions. Experimental results performed on three PolSAR datasets demonstrate our present approach’s superiority over other existing ones. Furthermore, ablation experiments confirm the validity of each module, highlighting our model’s robustness and effectiveness.

Abstract Dynamic infrared emissivity regulators, which can efficiently modulate infrared radiation beyond vision, have emerged as an attractive technology in the energy and information fields. The realization of the independent modulation of visible and infrared spectra is a challenging and important task for the application of dynamic infrared emissivity regulators in the fields of smart thermal management and multispectral camouflage. Here, we demonstrate an electrically controlled infrared emissivity regulator that can achieve independent modulation of the infrared emissivity while maintaining a high visible transparency (84.7% at 400–760 nm). The regulators show high degree of emissivity regulation (0.51 at 3–5 μm, 0.41 at 7.5–13 μm), fast response ( 104 cycles). The infrared emissivity regulation is attributed to the modification of the carrier concentration in the surface depletion layer of aluminum-doped zinc oxide nanocrystals. This transparent infrared emissivity regulator provides opportunities for applications such as on-demand smart thermal management, multispectral displays, and adaptive camouflage.

Abstract Background Measles-containing vaccine (MCV) has been effective in controlling the spread of measles. Some countries have declared measles elimination. But recently years, the number of cases worldwide has increased, posing a challenge to the global goal of measles eradication. This study estimated the relationship between meteorological factors and measles using spatiotemporal Bayesian model, aiming to provide scientific evidence for public health policy to eliminate measles. Methods Descriptive statistical analysis was performed on monthly data of measles and meteorological variables in 136 counties of Shandong Province from 2009 to 2017. Spatiotemporal Bayesian model was used to estimate the effects of meteorological factors on measles, and to evaluate measles risk areas at county level. Case population was divided into multiple subgroups according to gender, age and occupation. The effects of meteorological factors on measles in subgroups were compared. Results Specific meteorological conditions increased the risk of measles, including lower relative humidity, temperature, and atmospheric pressure; higher wind velocity, sunshine duration, and diurnal temperature variation. Taking lowest value (Q1) as reference, RR (95%CI) for higher temperatures (Q2–Q4) were 0.79 (0.69–0.91), 0.54 (0.44–0.65), and 0.48 (0.38–0.61), respectively; RR (95%CI) for higher relative humidity (Q2–Q4) were 0.76 (0.66–0.88), 0.56 (0.47–0.67), and 0.49 (0.38–0.63), respectively; RR (95%CI) for higher wind velocity (Q2–Q4) were 1.43 (1.25–1.64), 1.85 (1.57–2.18), 2.00 (1.59–2.52), respectively. 22 medium-to-high risk counties were identified, mainly in northwestern, southwestern and central Shandong Province. The trend was basically same in the effects of meteorological factors on measles in subgroups, but the magnitude of the effects was different. Conclusions Meteorological factors have an important impact on measles. It is crucial to integrate these factors into public health policies for measles prevention and control in China.

Abstract Predicting potential facts in the future, Temporal Knowledge Graph (TKG) extrapolation remains challenging because of the deep dependence between the temporal association and semantic patterns of facts. Intuitively, facts (events) that happened at different timestamps have different influences on future events, which can be attributed to a hierarchy among not only facts but also relevant entities. Therefore, it is crucial to pay more attention to important entities and events when forecasting the future. However, most existing methods focus on reasoning over temporally evolving facts or mining evolutional patterns from known facts, which may be affected by the diversity and variability of the evolution, and they might fail to attach importance to facts that matter. Hyperbolic geometry was proved to be effective in capturing hierarchical patterns among data, which is considered to be a solution for modelling hierarchical relations among facts. To this end, we propose ReTIN, a novel model integrating real‐time influence of historical facts for TKG reasoning based on hyperbolic geometry, which provides low‐dimensional embeddings to capture latent hierarchical structures and other rich semantic patterns of the existing TKG. Considering both real‐time and global features of TKG boosts the adaptation of ReTIN to the ever‐changing dynamics and inherent constraints. Extensive experiments on benchmarks demonstrate the superiority of ReTIN over various baselines. The ablation study further supports the value of exploiting temporal information.

This study proposed the multi-coupling grouting system with the aim to tackle green mine problems such as surface collapse, water resources destruction and coal based solid waste accumulation.Successfully applied, this system yielded the following major achievements: this study (1) probed into the patterns of development and evolution in mining separation space and primary fracture space, and conducted the intelligent identification of grouting space by means of theoretical analysis, physical and numerical simulation and field detection.(2) prepared multi-source inorganic high-performance grouting materials for different scenarios by using coal-based solid wastes (coal gangue, fly ash), and developed a new KEP grouting material with underwater dispersion resistance, high volume coefficient and high plastic strength.(3) applied cluster well and feather well to grouting hole drilling and and developed an all-weather, high pump pressure and large flow intelligent grouting system; The reinforcement grouting technology is applied for the first time to strengthen the effect of grouting to reduce settlement.(4)put forward the technology system of grouting effect monitoring and detection, and emphatically expounded the borehole detection method of combining drilling core and well logging.(5)formed an intelligent technology system based on the methods of separation space grouting to reduce settlement and treat waste, caving zone grouting to treat waste, goaf grouting to strengthen foundation bearing capacity and treat waste, and roof fissure grouting to control water gushing as the core.Engineering demonstrations of this system have been carried out in Xiadian coal mine, Xinpu phosphate mine, Caojiatan coal mine, Gaojiabao coal mine and other places, which yielded good results.

Abstract Background Chinese nurses working with immense stress may have issues with burnout during COVID-19 regular prevention and control. There were a few studies investigating status of burnout and associated factors among Chinese nurses. However, the relationships remained unclear. Objectives To investigate status and associated factors of nurses’ burnout during COVID-19 regular prevention and control. Methods 784 nurses completed questionnaires including demographics, Generalized Anxiety Disorder-7, Patient Health Questionnaire-9, Insomnia Severity Index, Impact of Event Scale-revised, Perceived Social Support Scale, Connor–Davidson Resilience Scale, General Self-efficacy Scale and Maslach Burnout Inventory. Results 310 (39.5%), 393 (50.1%) and 576 (73.5%) of respondents were at high risk of emotional exhaustion (EE), depersonalization (DP) and reduced personal accomplishment (PA). The risk of EE, DP and reduced PA were moderate, high and high. Nurses with intermediate and senior professional rank and title and worked >40 h every week had lower scores in EE. Those worked in low-risk department reported lower scores in PA. Anxiety, post-traumatic stress disorder (PTSD), self-efficacy and social support were influencing factors of EE and DP, while social support and resilience were associated factors of PA. Conclusion Chinese nurses’ burnout during COVID-19 regular prevention and control was serious. Professional rank and title, working unit, weekly working hours, anxiety, PTSD, self-efficacy, social support and resilience were associated factors of burnout.

IntroductionHelicobacter pylori (H.pylori, Hp) affects billions of people worldwide. However, the emerging resistance of Hp to antibiotics challenges the effectiveness of current treatments. Investigating the genotype-phenotype connection for Hp using next-generation sequencing could enhance our understanding of this resistance.MethodsIn this study, we analyzed 52 Hp strains collected from various hospitals. The susceptibility of these strains to five antibiotics was assessed using the agar dilution assay. Whole-genome sequencing was then performed to screen the antimicrobial resistance (AMR) genotypes of these Hp strains. To model the relationship between drug resistance and genotype, we employed univariate statistical tests, unsupervised machine learning, and supervised machine learning techniques, including the development of support vector machine models.ResultsOur models for predicting Amoxicillin resistance demonstrated 66% sensitivity and 100% specificity, while those for Clarithromycin resistance showed 100% sensitivity and 100% specificity. These results outperformed the known resistance sites for Amoxicillin (A1834G) and Clarithromycin (A2147), which had sensitivities of 22.2% and 87%, and specificities of 100% and 96%, respectively.DiscussionOur study demonstrates that predictive modeling using supervised learning algorithms with feature selection can yield diagnostic models with higher predictive power compared to models relying on single single-nucleotide polymorphism (SNP) sites. This approach significantly contributes to enhancing the precision and effectiveness of antibiotic treatment strategies for Hp infections. The application of whole-genome sequencing for Hp presents a promising pathway for advancing personalized medicine in this context.

Summary: The carcinogenesis and progression of hepatocellular carcinoma (HCC) are closely related to viral infection and intestinal bacteria. However, little is known about bacteria within the HCC tumor microenvironment. Here, we showed that intratumoral Mycoplasma hyorhinis (M. hyorhinis) promoted the initiation and progression of HCC by enhancing nuclear ploidy. We quantified M. hyorhinis in clinical tissue specimens of HCC and observed that patients with high M. hyorhinis load had poor prognosis. We found that gastrointestinal M. hyorhinis can retrogradely infect the liver through the oral-duodenal-hepatopancreatic ampulla route. We further found that the increases in mononuclear polyploidy and cancer stemness resulted from mitochondrial fission caused by intracellular M. hyorhinis. Mechanistically, M. hyorhinis infection promoted the decay of mitochondrial fusion protein (MFN) 1 mRNA in an m6A-dependent manner. Our findings indicated that M. hyorhinis infection promoted pathological polyploidization and suggested that Mycoplasma clearance with antibiotics or regulating mitochondrial dynamics might have the potential for HCC therapy.

With the development of rice varieties and mechanized planting technology, reliable and efficient nitrogen and planting density status diagnosis and recommendation methods have become critical to the success of precise nitrogen and planting density management in crops. In this study, we combined population structure, plant shape characteristics, environmental weather conditions, and management information data using a machine learning model to simulate the responses of the yield and nitrogen nutrition index and developed an ensemble learning model-based nitrogen and planting density recommendation strategy for different varieties of rice types. In the third stage, the NNI and yield prediction effect of the ensemble learning model was more significantly improved than that of the other two stages. The scenario analysis results show that the optimal yields and nitrogen nutrition indices were obtained with a density and nitrogen amount of 100.1 × 104 plant/ha and 161.05 kg·ha−1 for the large-spike type variety of rice, 75.08 × 104 plant/ha and 159.52 kg·ha−1 for the intermediate type variety of rice, and 75.08 × 104 plant/ha and 133.47 kg·ha−1 for the panicle number type variety of rice, respectively. These results provide a scientific basis for the nitrogen application and planting density for a high yield and nitrogen nutrition index of rice in northeast China.

This study explores how a tea room in China integrates traditional Chinese culture and Zen aesthetics into interior design to give end users a good experience. This study adopts qualitative methods and conducts a case study of a tea room in China through observation and interviews. To implement this study, Zen aesthetics were applied in a tea room with design and aesthetic value. Research shows that traditional Chinese culture and Zen aesthetics can be used in interior design to give customers a better experience. These research results will provide a reference for enriching further research.