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Abstract Background Preeclampsia (PE) is the primary cause of maternal and neonatal morbidity and mortality. However, comprehensive studies on the related risk factors with PE and its effects on adverse perinatal outcomes are limited. This study aimed to evaluate the prevalence, risk factors, and adverse perinatal outcomes in Chinese women with preeclampsia. Methods We conducted a retrospective cohort study from January 1, 2018, to December 31, 2019, which enrolled 38,496 women without preeclampsia (non-PE) and 1130 women with PE. Univariate and multivariate logistic regression models were used to determine the risk factors and adverse perinatal outcomes of PE. Results Multivariate logistic regression models showed that maternal age > 35 years, pp-BMI overweight/obesity, excessive gestational weight gain, multiparity, twin pregnancy, IVF, cesarean section history, times of abortion history ≥ 2, GDM, and ICP were significantly associated with the risk of PE (all P

Abstract Background CRF01_AE and CRF07_BC are the two most prevalent HIV-1 genotypes in China, and the co-circulation of these two genotypes has led to the continuous generation of CRF_0107 viruses in recent years. However, little is known about the origin and spread of CRF_0107 viruses thus far. This study focused on HIV-1 CRF80_0107, which we previously identified among the MSM population in Beijing and Hebei Province, to explore the demographic distribution, transmission links, and temporal-spatial evolutionary features of the HIV-1 CRF80_0107 strain in China. Methods With the partial pol region fragment of the HIV-1 CRF80_0107 subtype standard sequence as a reference, BLAST was used to search for highly similar sequences in the Los Alamos HIV Sequence Database, followed by preliminary subtype identification via COMET. Further phylogenetic and recombination breakpoint analyses were conducted to verify the subtypes and recombination patterns. We also performed a distance-based molecular network analysis to identify potential relationships among different HIV-positive individuals. In addition, spatiotemporal evolutionary dynamics analysis of the candidate CRF80_0107 sequences was performed via a Bayesian approach. Results A total of 36 partial pol gene sequences of HIV-1 CRF80_0107 were identified from 2009 to 2018 from 5 provinces in China. Phylogenetic and spatial-temporal dynamics analyses indicated that CRF80_0107 likely originated in Beijing around 2009 and spread to Guangdong Province around 2012. Population dynamics analysis revealed that CRF80_0107 experienced a significant increase in population size from 2009 to 2011 and then stabilized. The study also found that the number of cases in Guangdong Province was second only to that in Beijing and formed 2 relatively independent transmission clusters in the MSM population in Shenzhen, Guangdong Province. Conclusions The HIV-1 CRF80_0107 strain has spread to cities beyond its origin, particularly the MSM population in Shenzhen city, Guangdong Province, which is an area with a high incidence of HIV. This highlights the importance of continuous monitoring for the emergence and dynamic changes of novel HIV-1 recombinant viruses and the necessity of implementing effective preventive measures targeting specific populations in particular regions.

This article presents a multiscale feature-enhanced water detector using truncated Gaussian clutter (TGCFeWD) for synthetic aperture radar (SAR) imagery. It aims to improve detection accuracy through adaptive elimination of high-intensity outliers and shadows. High-intensity outliers cause overestimation of parameters used for water data statistical modeling, resulting in inaccurate thresholds. Furthermore, shadows in SAR imagery have similar digital numbers and statistical parameters to water, making them difficult to distinguish. To address these two key issues, this article proposes a comprehensive approach comprised of three main components: Part A is to calculate Gaussian distance based on which the land surfaces or artificial objects can be removed easily by Otsu. Part B is to expand the difference between water and shadows through feature enhancing. Part C is to segment water and shadows according to the expanding differences. The proposed TGCFeWD method effectively detects water bodies including seas, rivers, and lakes. Compared to several existing methods, TGCFeWD greatly improves water detection accuracy in complex environments. Based on metrics of accuracy, F1, and mean of intersection over union, TGCFeWD achieves the best performance (92.4%, 82.4%, and 80.1% for all data with five water body types) compared to several traditional methods, and even outperforms some neural-network-based methods in certain scenarios. The results are validated on the HISEA flooding dataset.

Abstract A randomized double-blind phase 3 trial (CHOICE-01, NCT03856411) demonstrated that combining toripalimab with chemotherapy substantially improves progression-free survival (PFS) in advanced non-small cell lung cancer (NSCLC) patients without pretreatment. This study presents the prespecified final analysis of overall survival (OS) and biomarkers utilizing circulating tumor DNA (ctDNA) and tissue-based sequencing. Additionally, the analysis revealed a higher median overall survival (OS, 23.8 months) in the toripalimab group than that in the control group (17.0 months). (HR = 0.69, 95%CI: 0.57–0.93, nominal P = 0.01). This survival benefit was particularly notable in the non-squamous subgroup. As the first phase 3 study to perform both baseline tissue whole-exome sequencing (WES) and peripheral blood ctDNA testing, we investigated efficacy predictive biomarkers based on both tissue and ctDNA, Genomic sequencing of ctDNA showed high concordance with tumor tissue independently confirmed that individuals exhibiting a high tumor mutational burden, as well as mutations in the FA-PI3K-Akt and IL-7 signaling pathways benefited more from the toripalimab treatment. Furthermore, a ctDNA response observed on cycle 3 day 1, was associated with improved clinical outcomes for patients treated with the combination therapy. In conclusion, Toripalimab plus chemotherapy yields significant improvements in OS as a first-line treatment. The study highlights the utility of ctDNA as a proxy for tumor tissue, providing novel prospects for predicting efficacy of immuno-chemotherapy through continuous ctDNA monitoring.

Abstract Background Integrating multi-layered information can enhance the accuracy of genomic prediction for complex traits. However, the improvement and application of effective strategies for genomic prediction (GP) using multi-omics data remains challenging. Methods We generated 11 feature sets for sequencing variants from genomics, transcriptomics, metabolomics, and epigenetics data in beef cattle, then we assessed the contribution of functional variants using genomic restricted maximum likelihood (GREML). We next estimated and ranked variant scores for 43 economically important traits, and compared the prediction accuracy of the top and bottom sets using genomic best linear unbiased prediction (GBLUP) and BayesB model. In addition, we annotated the variants from GWAS with functional feature sets and performed enrichment analysis. Results We observed significant enrichments for 32 functional categories in 11 feature sets. The evolutionary related sets (conservation regions and selection signatures) contributed significantly to heritability (31.78-fold and 14.48-fold enrichment), while metabolomics and transcriptomics showed low heritability enrichments. We observed a significant increase in prediction accuracy using the top feature set variants compared to whole-genome sequencing (WGS) data. The prediction accuracy based on the top 10% variant set showed an average increase of 11.6% and 7.54% using BayesB and GBLUP across traits, respectively. Notably, the greatest increase of 31.52% was obtained for spleen weight (SW) using BayesB. Also, we found that the top 10% of variants show strong enrichment with weight related QTLs based on the Cattle QTL database. Conclusions Our findings suggest that integrating biological prior information from multiple layers can enhance our understanding of the genetic architecture underlying complex traits and further improve genomic prediction in beef cattle.

Abstract Background Genomic mating (GM) can effectively control the growth rate of inbreeding in population and achieve long-term sustainable genetic progress. However, the design of GM method and assessment of its effects during long-term selection have not been fully explored in beef cattle breeding. Results In this study, we constructed a simulated population based on the real genotypes of Huaxi cattle, where five generations of simulated breeding were carried out using the genomic optimal contribution selection (GOCS), genetic algorithms strategy and three traditional mating strategies. During the breeding process, genetic parameters including average genomic estimated breeding value (GEBV), genetic gain values ( $$\Delta G$$ Δ G ), the rate of inbreeding values ( $$\Delta F$$ Δ F ) were calculated and compared across generations. Our results showed that the GM method could significantly improve the genetic gain while effectively controlling the inbreeding accumulation within the population. When using the GM method, there was an increase in genetic gain for Huaxi cattle ranging from 1.1% to 25.6% compared to traditional mating strategy, with inbreeding decreasing in the range of 5.8% to 36.2%. Validation using the real dataset from Huaxi cattle further confirmed our findings from the simulated study, offspring populations using the GM strategy exhibited a 7.3% increase in genetic gain compared to positive assortative mating. Conclusions These findings suggest that the GM method shows potential for achieving sustainable genetic gain and could be utilized during long-term selection in beef cattle breeding.

Abstract The pathogen Verticillium dahliae secreted effector V. dahliae Aspf2-like protein (VDAL) has been found to cause leaf wilting in cotton, but the ectopic expression of VDAL-encoding gene enhances the resistance to V. dahliae in cotton and Arabidopsis. The application of the VDAL protein powder with optimal dosage promotes the growth and yield in multiple crop species, such as rice and wheat. However, the promotive effects of VDAL on these aspects are sporadically reported in asexually propagated species, including potato, while the molecular regulatory network involved in the process remains unclear. In this study, we observed that VDAL promotes sprouting of the potato pre-basic seed (PBS) tubers and enhances the development of both above-ground and below-ground tissues. Strikingly, VDAL increases the tuber yield in both greenhouse and field trials by up to 18.97%. The time-course transcriptomic analysis and the endogenous phytohormone detection revealed that cytokinin may play an important role in response to VDAL-promoted growth. Interestingly, VDAL-treated PBS tubers show higher resistance to cold temperature (late-spring cold), a phenomenon that is diminished when the lovastatin, a cytokinin inhibitor is applied, indicating that the VDAL-promoted potato growth, particularly under low temperature, is associated with cytokinin.

Abstract Our study develops a generative adversarial network (GAN)-based method that generates faithful synthetic image data of human cardiomyocytes at varying stages in their maturation process, as a tool to significantly enhance the classification accuracy of cells and ultimately assist the throughput of computational analysis of cellular structure and functions. Human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) were cultured on micropatterned collagen coated hydrogels of physiological stiffnesses to facilitate maturation and optical measurements were performed for their structural and functional analyses. Control groups were cultured on collagen coated glass well plates. These image recordings were used as the real data to train the GAN model. The results show the GAN approach is able to replicate true features from the real data, and inclusion of such synthetic data significantly improves the classification accuracy compared to usage of only real experimental data that is often limited in scale and diversity. The proposed model outperformed four conventional machine learning algorithms with respect to improved data generalization ability and data classification by incorporating synthetic data. This work demonstrates the importance of integrating synthetic data in situations where there are limited sample sizes and thus, effectively addresses the challenges imposed by data availability.

Abstract Diabetes is a global chronic disease that seriously endangers human health and characterized by abnormally high blood glucose levels in the body. Diabetic wounds are common complications which associate with impaired healing process. Biomarkers monitoring of diabetic wounds is of great importance in the diabetes management. However, actual monitoring of biomarkers still largely relies on the complex process and additional sophisticated analytical instruments. In this work, we prepared hydrogels composed of different modules, which were designed to monitor different physiological indicators in diabetic wounds, including glucose levels, pH, and temperature. Glucose monitoring was achieved based on the combination of photonic crystal (PC) structure and glucose-responsive hydrogels. The obtained photonic crystal hydrogels (PCHs) allowed visual monitoring of glucose levels in physiological ranges by readout of intuitive structural color changes of PCHs during glucose-induced swelling and shrinkage. Interestingly, the glucose response of double network PCHs was completed in 15 min, which was twice as fast as single network PCHs, due to the higher volume fraction of glucose-responsive motifs. Moreover, pH sensing was achieved by incorporation of acid-base indicator dyes into hydrogels; and temperature monitoring was obtained by integration of thermochromic powders in hydrogels. These hydrogel modules effectively monitored the physiological levels and dynamic changes of three physiological biomarkers, both in vitro and in vivo during diabetic wound healing process. The multifunctional hydrogels with visual monitoring of biomarkers have great potential in wound-related monitoring and treatment. Graphical abstract

Abstract Biochar has been extensively utilized to amend soil and mitigate greenhouse gas (GHG) emissions from croplands. However, the effectiveness of biochar application in reducing cropland GHG emissions remains uncertain due to variations in soil properties and environmental conditions across regions. In this study, the impact of biochar surface functional groups on soil GHG emissions was investigated using molecular model calculation. Machine learning (ML) technology was applied to predict the responses of soil GHG emissions and crop yields under different biochar feedstocks and application rates, aiming to determine the optimum biochar application strategies based on specific soil properties and environmental conditions on a global scale. The findings suggest that the functional groups play an essential role in determining biochar surface activity and the soil’s capacity for adsorbing GHGs. ML was an effective method in predicting the changes in soil GHG emissions and crop yield following biochar application. Moreover, poor-fertility soils exhibited greater changes in GHG emissions compared to fertile soil. Implementing an optimized global strategy for biochar application may result in a substantial reduction of 684.25 Tg year−1 CO2 equivalent (equivalent to 7.87% of global cropland GHG emissions) while simultaneously improving crop yields. This study improves our understanding of the interaction between biochar surface properties and soil GHG, confirming the potential of global biochar application strategies in mitigating cropland GHG emissions and addressing global climate degradation. Further research efforts are required to optimize such strategies. Graphical Abstract

Abstract Adaptive microlearning has emerged as a crucial approach for enhancing the working skills of in-service personnel. This study introduces the design and development of an innovative adaptive microlearning (AML) system and investigates its effectiveness compared to a conventional microlearning (CML) system. The main distinguishing feature of an AML system from a CML system is its adaptive features that tailor the learning experience to individual needs, including personalized content delivery, real-time feedback, and adaptive learning paths. A quasi-experimental study involving 111 in-service personnel (NAML = 56, NCML = 55) was conducted. ANCOVA results confirmed that the AML system significantly reduced unnecessary cognitive load due to inappropriate instructional design (mean difference of -20.02, p

Abstract Background To explore the associations of computed tomography (CT) image features with the serum cryptococcal antigen (CrAg) titers measured by the lateral flow assay (LFA) in localized pulmonary cryptococcosis patients. Methods A retrospective analysis of patients with pathologically confirmed pulmonary cryptococcosis admitted to the First Affiliated Hospital of Xiamen University from January 2016 to December 2022 was performed. Clinical data, CT results, serum CrAg-LFA test results, and follow-up data were collected and analyzed. Results A total of 107 patients with localized pulmonary cryptococcosis were included, of which 31 had a single lesion in chest CT and the other 76 had multiple lesions. The positivity rate was (94.74% vs 64.52%) and titers of serum CrAg-LFA (1.77 ± 0.87 vs 0.91 ± 0.98) in the multiple lesion group were higher than those in the single lesion group, respectively. Multivariate linear regression analysis showed that the serum CrAg titers were positively associated with the number of lesions (β, 0.08; 95% CI, 0.05 to 0.12) and the lesion size (β, 0.40; 95% CI, 0.31 to 0.50) after adjusting other covariates. The serum CrAg-LFA titers of 60 pulmonary cryptococcosis patients showed a decreasing trend with the reduction in pulmonary lesion size after effective therapy. Conclusion In pulmonary cryptococcosis patients, the number and size of lung lesions are positively correlated with the titers of the serum CrAg-LFA test. The CrAg-LFA test could be a useful tool for the diagnosis, severity assessment, and therapeutic monitoring of localized pulmonary cryptococcosis patients.

Objective To better interpret the geological information contained in geophysical logging data and expand the application scope of well logs in geology, Methods several typical cases of representative logging data are analyzed. This analysis seeks to enhance the use of well logs in geological research. Logging data can aid in the deployment of sidetracking wells by identifying tectonic occurrences and variations in their combination characteristics. Image log data also enable determintion of palaeocurrent directions and the identification of bidirectional provenance supply, thus providing refined and scientifically calibrated interpretations in alignment with geological understanding. Results Logging data, often regarded as the "eyes" of geologists, are advantageous for identifying and evaluating pores, caves, fractures, and other subsurface features. These data are crucial for discovering hydrocarbon reservoirs and facilitating the fine and continuous calculation of reserve parameters. The coupling relationships between mudstone resistivity, acoustic interval transit time, and in situ stress in logging curves can also be used to indirectly predict the quality of ultradeep reservoirs and hydrocarbon productivity. Moreover, combining geology, logging, and seismic activity allows for the delineation of hydrocarbon traps and supports oil and gas exploration and production. Conclusion The analysis of these typical cases assists geologists in better interpreting the geological information in logging curves and further broadens the application field and scope of geophysical logging data.

Soil acidification poses a significant threat to agricultural productivity and ecological balance. While lime is a common remedy, it can have limitations, including nutrient deficiencies and potential soil compaction. Therefore, exploring alternative and sustainable amendments is crucial. This study investigated the efficacy of biochar as a substitute for lime in reducing soil acidification and improving soil quality. Through incubation experiments, we compared the effects of biochar and lime on soil properties. Additionally, we employed density functional theory (DFT) calculations to elucidate the mechanisms underlying biochar's ability to immobilize exchangeable Al3+. Furthermore, we conducted 15N double-labeled incubation experiments to examine the impact of biochar on soil nitrogen (N) transformation in acidic conditions. Our results indicated that biochar was as effective as lime in enhancing soil quality and mitigating acidification. Soils developed from the Jurassic Shaximiao Formation (J2s) purple mudstone with 3 % biochar addition exhibited a 31.15 % and 17.43 % increase in total N compared to soils treated with 0.1 % and 0.2 % lime, respectively. Similarly, soils developed from the Cretaceous Jiaguan Formation (K2j) purplish red sandstone with 1 % and 3 % biochar addition showed a 38.75 % and 64.30 % increase in soil organic carbon compared to soils treated with 0.2 % lime. DFT calculations revealed that biochar's functional groups exhibited a stronger affinity for immobilizing exchangeable Al3+ than other soil cations. This preferential adsorption was attributed to the stronger interaction and higher bond dissociation energy between biochar functional groups and Al3+. These findings collectively highlight the potential of biochar as a sustainable and effective amendment to reduce Al toxicity in acidic soils, thereby promoting soil quality and sustainable agricultural and ecological practices.

IntroductionFusarium oxysporum f. sp. Lycopersici (Fol) is one of the most devastating plant pathogenic fungi, the causal agent of root rot for Atractylides macrocephala Koidz (AMK). An accurate rapid and convenient diagnosis for FoL detection is essential for determining management practices and preventing future losses for AMK.MethodsHere, we developed a novel method for Fol detection by integrating loop-mediated isothermal amplification (LAMP) assay and CRISPR/Cas12b detection in one-pot, and the whole reaction can simultaneously amplify and detect the target gene of Fol in one-step.ResultsThe total time of the present method is limited to 45 min and isothermally performed at 60°C. The limit of detection of this assay is 88.9 copies per reaction. The specificity of the LAMP-CRISPR/Cas12b method was 100% without any cross-reaction of other pathogens. A total of 24 nucleic acid samples were used to evaluate the performance of the LAMP-CRISPR/Cas12b method, including 12 with-Fol and 12 without-Fol. Compared with the gold standard results from real-time PCR, the present method provides a sensitivity of 100% (12/12), specificity of 100% (12/12), and consistency of 100% (24/24).DiscussionTogether, our preliminary results illustrated that the LAMP-CRISPR/Cas12b method is a rapid simple, and reliable tool for Fol diagnosis and could be applied in point-of-need phytopathogen detection.

Regional geomagnetic field models can provide detailed insights into the geomagnetic field and are of substantial value for precise maritime navigation and the detection of marine targets. In light of the polynomial model’s numerous advantages, including straightforward computation, rapid computation speed, and high model resolution, this study delves into the polynomial modeling method. To address the challenges of enhancing solution precision, selecting the optimal polynomial function, and determining the optimal truncation degree, it introduces an improved method based on singular value decomposition to enhance the model’s accuracy at higher degrees. A comparison of the Taylor polynomial model, the Laguerre polynomial model, and the Chebyshev polynomial model revealed the superiority of the Legendre polynomial model in terms of truncation degree, modeling accuracy, and boundary effect. In addition, by employing K-fold cross-validation, the complete dataset is effectively leveraged for both fitting and validation, thereby facilitating the identification of the optimal truncation degree for each polynomial model. The superior accuracy of the regional geomagnetic field models is validated through a comparative analysis of the calculation results derived from the EMM2017 model.

The goal of combination cancer therapy, including chemo-phototherapy, is to achieve highly efficient antitumor effects while minimizing the adverse reactions associated with conventional chemotherapy. Nevertheless, enhancing the contribution of non-chemotherapeutic strategies in combination therapy is often challenging because this requires multiple active ingredients to be encapsulated in a single delivery system. However, most commonly used photothermal reagents are challenging to be loaded in large quantities and have poor biocompatibility. Herein, we developed photothermal co-micelles through a co-assembly strategy using a cholesterol-based liquid crystal block copolymer (LC-BCP) with disulfide bonds in the side chain of the LC blocks and a croconaine-based amphiphile (CBA) containing a cholesterol moiety. This approach allowed the CBA to be effectively embedded within LC-BCPs, serving as the functional component of the drug-loaded carrier. These co-micelles could encapsulate doxorubicin (DOX), showed tunable reduction-responsive drug release, and enabled near-infrared laser-triggered photothermal therapy as well as in vivo fluorescence and photothermal imaging. Following laser irradiation, the photothermal activity of the co-micelles rapidly induced tumor cell death and accelerated drug release. In vitro and in vivo experiments demonstrated that the synergistic photo-chemotherapeutic effects of these drug-loaded co-micelles offer a promising avenue for synergistic precision photothermal-chemotherapy.

AbstractBackground Although ERAS Program had some advantages in laparoscopic distal gastrectomy (LDG), its efficacy and safety remained unclear. We conducted a systematic review and meta-analysis to assess the efficacy and safety of the ERAS group and the traditional care (TC) group in LDG.Methods Multiple databases were retrieved from 1 January 2000 to 30 April 2023. The risk ratio (RR), standardized mean difference (SMD) and their 95% confidence interval (CI) were used to estimate the results.Results Our meta-analysis contained 17 randomized controlled trials (RCTs) studies, which comprised 1468 patients. Regarding efficacy, the ERAS group had significantly shorter postoperative time to first flatus (SMD = −1.29 [95% CI: −1.68, −0.90]), shorter time to first defecation (SMD = −1.26 [95% CI: −1.90, −0.61]), shorter hospital stays (SMD = −0.99 [95% CI: −1.34, −0.63]), and lower hospitalization costs (SMD = −1.17 [95% CI: −1.86, −0.48]) compared to the TC group. Furthermore, in the ERAS group, C-reactive protein levels were lower on postoperative days 1, 3 or 4, and 7; albumin levels were higher on postoperative days 3 or 4 and 7; and interleukin-6 levels were lower on postoperative days 1 and 3. Regarding safety, the overall postoperative complication rate was lower in the ERAS group (RR: 0.76 [95% CI: 0.60, 0.97]), but there was no significant difference in the individual postoperative complication rate. Other indicators were also not statistically significant.Conclusion The combination of ERAS Program with laparoscopy surgery was safe and effective for the perioperative management of patients with distal gastric cancer.

Tobacco fields have been continuously cropped for several years because of the high demand for tobacco leaves and limited land resources. To explore the effects of continuous cropping on tobacco growth and soil microecological community structure, this study compared the agronomic traits and physiological resistance characteristics of tobacco plants grown in noncontinuous cropping soil and soil with different continuous cropping years. High-throughput sequencing technology was used to analyze and predict the microbial community structure and functional gene variation patterns of tobacco soil. The results demonstrated that continuous cropping significantly impacted the average height, leaf area, and stem diameter of tobacco plants, as well as the contents of malondialdehyde, hydrogen peroxide, and glutathione in tobacco leaves that were continuously cropped. The relative abundances of Proteobacteria, Bacteroidetes, and Gemmatimonadetes in tobacco soil decreased with an increase in continuous cropping years, while relative abundance of Acidobacteria increased. The biodiversity index of tobacco soil samples showed a decreasing trend with an increase in continuous cropping years, with the sample with the longest continuous cropping year (33 years) having the lowest biodiversity index. Prediction of the potential functions of soil samples with different continuous cropping years revealed that the Z-scores of each pathway in noncontinuous cropping soil samples ranged from 1.12 to 0.078, while those in 33-year continuous cropping samples decreased from −0.10 to −1.41. Our findings indicate that continuous cropping has negative impacts on soil health and microecology, leading to a reduction in beneficial microbial population and microbial diversity.

Abstract Background Understanding the mechanism of male sterility is crucial for producing hybrid seeds and developing sterile germplasm resources. However, only a few cytoplasmic male sterility (CMS) lines of cotton have been produced due to several challenges, like inadequate variation of agronomic traits, incomplete sterility, weak resilience of restorer lines, and difficulty in combining strong dominance. Therefore, the morphological and cytological identification of CMS in cotton will facilitate hybrid breeding. Results Two F2 segregating populations of cotton were constructed from cytoplasmic male sterile lines (HaA and 01A, maternal) and restorer lines (HaR and 26R, paternal). Genetic analysis of these populations revealed a segregation ratio of 3:1 for fertile to sterile plants. Phenotypic analysis indicated no significant differences in traits of flower bud development between sterile and fertile plants. However, sterile plants exhibited smaller floral organs, shortened filament lengths, and anther atrophy on the flowering day in comparison with the fertile plants. When performed scanning electron microscopy (SEM), the two F2 populations revealed morphological variations in the anther epidermis. Cellular analysis showed no significant differences in pollen development before pollen maturation. Interestingly, between the pollen maturation and flowering stages, the tapetum layer of sterile plants degenerated prematurely, resulting in abnormal pollen grains and gradual pollen degradation. Conclusion The results of this study suggest that fertility-restoring genes are controlled by a single dominant gene. Sterile plants exhibit distinctive floral morphology, which is characterized by stamen atrophy and abnormal anthers. Pollen abortion occurs between pollen maturity and flowering, indicating that premature tapetum degradation may be the primary cause of pollen abortion. Overall, our study provides a theoretical basis for utilizing CMS in hybrid breeding and in-depth investigation of the dominant configuration of cotton hybrid combinations, mechanisms of sterility, and the role of sterile and restorer genes.

ObjectiveTo analyze and compare the differences in cancer early diagnosis and treatment literacy levels between urban and rural residents in Liaoning province, China, and to provide a basis for improving residents’ cancer awareness and literacy. MethodsIn 2021, a convenient online sampling method was used to conduct a questionnaire survey on the significance of early diagnosis and treatment of cancer, recognition of cancer warning signs, early detection of cancer, and timely medical treatment among 17 474 residents aged 15 – 69 years old in 14 cities of Liaoning province. The χ2 test and multivariate logistic regression analysis were used to compare the differences and influencing factors of early diagnosis and treatment literacy levels among different groups. ResultsIn 2021, the overall level of cancer early diagnosis and treatment literacy among residents in Liaoning province was 35.61% (95%CI: 33.87% – 37.36%), with 41.36% (95%CI: 39.39% – 43.32%) in urban areas, higher than 23.67% (95%CI: 20.37% – 26.99%) in rural areas. Among different dimensions, residents' literacy levels on the significance of early diagnosis and treatment (67.19%, 95%CI: 65.09% – 69.28%) and timely medical treatment (64.56%, 95%CI: 62.43% – 66.69%) were relatively high, while the literacy levels on recognition of cancer warning signs (25.98%, 95%CI: 24.24% – 27.73%) and early detection of cancer (31.18%, 95%CI: 29.52% – 32.84%) were relatively low. The results of multivariate logistic regression analysis showed that among urban residents, females, those aged 35 – 54 years old, those with a college education or above, those with an annual per capita household income of ≥ 16 666.6 yuan, and those with a family history of cancer or cancer screening history were more likely to have cancer early diagnosis and treatment literacy (all P < 0.05), while those engaged in the primary industry and current or former smokers were less likely to have early diagnosis and treatment literacy (all P < 0.05). Among rural residents, females, those aged 35 – 54 years old, those with a middle school education or above, and those with an annual per capita household income of ≥ 10 000 yuan were more likely to have cancer early diagnosis and treatment literacy (all P < 0.01), while those who were unemployed or retired and current or former smokers were less likely to have early diagnosis and treatment literacy (all P < 0.05). ConclusionThere are significant differences in cancer early diagnosis and treatment literacy levels between urban and rural residents in Liaoning province, China. In the future, cancer screening programs can be used to carry out targeted interventions and health education for key populations in key areas.

Abstract Background Exploration of the relationship between nursing staffs’ justice in belief world and fair behavior is important to promote equity and access to health services in health organizations, as well as to enhance the quality of care. In order to further dissect the influencing factors of fair behavior among clinical nurses, the current study aims to investigate how belief in a just world influences the fair behavior among nurses. Based on the belief in a just world theory, the empathy-altruism theory and the protective-protective model, the current study aimed to provide a deeper understanding of the effect of belief in a just world on fair behavior by investigating the mediating role of empathy and the moderating role of observer justice sensitivity. Method This was a cross-sectional study. 571 registered clinical nurses were included from five hospitals in Fuzhou through a convenience sampling method. Measurements included Chinese translations of belief in a just world scale, empathy scale, observer justice sensitivity scale, fair behavior scale. SPSS 22.0 was used to describe descriptive statistics and the variables’ Pearson correlation coefficient. SPSS PROCESS macro Model 4 and model 14 were used to examine the mediation and the moderation between the relationship of belief in a just world and fairness behavior. Result The results shower that fairness behavior was positively correlated with one’s belief in a just world (r = 0.26, p

Abstract Collagen hydrogel has been shown promise as an inducer for chondrogenic differentiation of bone marrow mesenchymal stem cells (BMSCs), contributing to the repair of cartilage defects. However, the precise molecular mechanism underlying this phenomenon remains poorly elucidated. Here, we induced chondrogenic differentiation of BMSCs using collagen hydrogel and identified 4451 differentially expressed genes (DEGs) through transcriptomic sequencing. Our analysis revealed that DEGs were enriched in the focal adhesion pathway, with a notable decrease in expression levels in the collagen hydrogel group compared to the control group. Protein-protein interaction network analysis suggested that actinin alpha 1 (ACTN1) and actinin alpha 4 (ACTN4), two proteins also involved in cytoskeletal recombination, may be crucial in collagen hydrogel-induced chondrogenic differentiation of BMSCs. Additionally, we found that N6-methyladenosine RNA methylation (m6A) modification was involved in collagen hydrogel-mediated chondrogenic differentiation, with fat mass and obesity-associated protein (FTO) implicated in regulating the expression of ACTN1 and ACTN4. These findings suggest that collagen hydrogel might regulate focal adhesion and actin cytoskeletal signaling pathways through down-regulation of ACTN1 and ACTN4 mRNA via FTO-mediated m6A modification, ultimately driving chondrogenic differentiation of BMSCs. In conclusion, our study provides valuable insights into the molecular mechanisms of collagen hydrogel-induced chondrogenic differentiation of BMSCs, which may aid in developing more effective strategies for cartilage regeneration. Graphical Abstract

Abstract Radish exhibits significant variation in color, particularly in sprouts, leaves, petals, fleshy roots, and other tissues, displaying a range of hues such as green, white, red, purple, and black. Although extensive research has been conducted on the color variation of radish, the underlying mechanism behind the variation in radish flower color remains unclear. To date, there is a lack of comprehensive research investigating the variation mechanism of radish sprouts, leaves, fleshy roots, and flower organs. This study aims to address this gap by utilizing transcriptome sequencing to acquire transcriptome data for white and purple radish flowers. Additionally, the published transcriptome data of sprouts, leaves, and fleshy roots were incorporated to conduct a systematic analysis of the regulatory mechanisms underlying anthocyanin biosynthesis in these four radish tissues. The comparative transcriptome analysis revealed differential expression of the anthocyanin biosynthetic pathway genes DFR, UGT78D2, TT12 and CPC in the four radish tissues. Additionally, the WGCNA results identified RsDFR.9c and RsUGT78D2.2c as hub genes responsible for regulating anthocyanin biosynthesis. By integrating the findings from the comparative transcriptome analysis, WGCNA, and anthocyanin biosynthetic pathway-related gene expression patterns, it is hypothesized that genes RsDFR.9c and RsUGT78D2.2c may serve as pivotal regulators of anthocyanins in the four radish tissues. Furthermore, the tissue-specific expression of the four copies of RsPAP1 is deemed crucial in governing anthocyanin synthesis and accumulation. Our results provide new insights into the molecular mechanism of anthocyanin biosynthesis and accumulation in different tissues of radish.

Abstract Background Cotton is an economically important crop. It is crucial to find an effective method to improve cotton yield, and one approach is to decrease the abscission of cotton bolls and buds. However, the lack of knowledge of the genetic and molecular mechanisms underlying cotton boll abscission traits has hindered genetic improvements. Results Pearson’s correlation analysis revealed a significant positive correlation between boll abscission rates 1 (AR1) and boll abscission rates 2 (AR2). A genome-wide association study was conducted on 145 loci that exhibited high polymorphism and were uniformly distributed across 26 chromosomes (pair). The study revealed 18, 46, and 62 markers that were significantly associated with boll abscission, fiber quality, and yield traits (P

ObjectiveTo understand the structural variation in hospitalization costs for patients with cervical cancer and to investigate the reasons for these variations. MethodsUsing the degree of structural variation (DSV) analysis and grey relational analysis methods, we analyzed the hospitalization data of 5 654 cervical cancer patients from three class A tertiary hospitals in northern China from 2013 to 2022. The DSV was used to describe the overall characteristics and dynamic trends of the hospitalization cost composition, while gray relational analysis assessed the correlation between hospitalization costs and individual cost items. ResultsDuring this period, the average individual total cost of hospitalization for all patients studied showed an upward trend with a low overall DSV and an average annual DSV of 18.60%. Diagnostic fees and drug costs were two significant factors influencing cost changes. In particular, the structural variation values of diagnostic fees and drug costs showed positive changes during this period. The top three cost items contributing to the change in hospital cost structure were other fees (contribution rate: 35.87%), diagnostic fees (32.09%), and drug costs (16.44%), with a cumulative structural contribution rate of 84.40%. The proportion of diagnostic fees has increased significantly, contributing to the structural variation, indicating that diagnostic fees are a major component of hospitalization costs. Although the proportion of drug costs has decreased in recent years, it remains an important factor influencing cost changes. Gray relation analysis showed that from 2013 to 2022, other fees had the highest correlation with hospitalization costs (correlation coefficient: 0.855), followed by diagnostic fees (0.824) and drug costs (0.781). ConclusionFor the hospitalization costs of cervical cancer patients from tertiary hospitals in northern China, diagnostic fees, drug costs, and other fees contribute significantly to the cost structure and have the highest correlation with hospitalization costs, which are significant factors influencing the fluctuation of hospitalization costs. The structural contribution rates of comprehensive medical service fees and treatment fees are relatively low, and their correlation with hospitalization costs is also lower, so they have minimal impact on the structure and changing trends of hospitalization costs.

The present study was to evaluate the effects of different levels of soybean meal (SBM) substitute for fish meal (FM) on the growth performance, antioxidant capacities, and intestine health of Asian red-tailed catfish, Hemibagrus wyckioides. Five isonitrogenous and isolipidic diets were prepared: the FM diets contained 50 % fish meal, based on which four SBM diets were formulated as substitutes for 15 %, 30 %, 45 % and 60 % FM in the FM group diets, namely SBM15, SBM30, SBM45, and SBM60. Compared with the FM group, the SBM45 and SBM60 groups exhibited significantly elevated serum glutamate pyruvate transaminase (GPT) levels and showed evidence of liver oxidative stress injury. Concurrently, there were decreases in triglyceride (TG) and total cholesterol (TC) levels (P

Summary: Background: It is generally recognized that there is unequal mortality in childhood central nervous system (CNS) malignancy in the United States (US), but little is known about the trends and contributors of racial/ethnic disparities in death. We assessed the trends of racial/ethnic disparities in all-cause and cause-specific death, and the contributions of tumour, treatment and socioeconomic factors to this disparity. Methods: This registry-based cohort study included children (aged ≤19 years) diagnosed with malignant CNS tumours, using data from the US population-based cancer registry in the Surveillance, Epidemiology, and End Results (SEER) Program. The clinical outcomes were all-cause and cause-specific death for each racial/ethnic group (White, Black, Hispanic, non-Hispanic Asian/Pacific Islander [API], and non-Hispanic American Indian/Alaska Native [AI/AN] children). We quantified absolute disparities using absolute rate difference in 5-year cumulative incidence of death. Cox proportion risk models were used to estimate the relative racial/ethnic disparities, and the contribution of factors to disparities in death. Findings: In this study, data from 14,510 children with malignant CNS tumours (mean [SD] age, 8.5 [5.7]; 7988 [55.1%] male) were analysed. Overall, the cumulative incidence of death from CNS tumours across four racial/ethnic groups decreased from 2001 to 2020. Black patients had the highest risk of death from all causes and CNS tumours between 2001 and 2020, with adjusted hazard ratios (HR) of 1.52 (1.38–1.68) and 1.47 (1.31–1.64), respectively. The absolute disparity in all-cause death between Hispanic and White patients increased slightly (from 8.2 percentage points [ppt] to 9.4 ppt), and the relative disparity in death from CNS tumours increased from 1.33 (1.15–1.55) in 2001–2005 to 1.78 (1.44–2.20) in 2016–2020. The absolute disparities in death from CNS tumours between Black and White patients (from 11.8 ppt to 4.3 ppt) and between API and White patients (from 10.1 ppt to 5.1 ppt) decreased from 2001–2005 to 2011–2015. Interpretation: Race/ethnicity disparities in death from CNS tumours among childhood malignant CNS tumours had reduced from 2001 to 2020, and quantifying the contribution of factors to this disparity in death could provide a basis for decreasing mortality among racial/ethnic minority patients. Funding: Shenyang Young and Middle-aged Science and Technology Innovation Talent Support Program.

BackgroundCharacterized by an immune-suppressive tumor microenvironment (TME), pancreatic ductal adenocarcinoma (PDAC) is well-known for its poor prognosis. Tumor associated macrophages (TAMs) play a critical role in PDAC TME. An in-depth understanding of TAMs is helpful to develop new strategies for immunotherapy.MethodsA large number of single-cell RNA sequencing data and bulk RNA sequencing data of PDAC were collected for systematic bioinformatics analysis. Characterize subtypes of TAMs at single-cell resolution and its effect on prognosis. Differential gene analysis and cell-cell communication were used to describe the effect on prognosis and validated by the TCGA dataset.ResultsWe used two prognosis-favorable genes, SLC12A5 and ENPP2, to identify a benign M2-like TAMs (bM2-like TAMs), which shared similarities with C1QC + TAMs, CXCL9+ TAMs and CD169+ TAMs, by analyzing scRNA-seq data and bulk RNA data of PDAC. The bM2-like TAMs were revealed to promote T cell activation and proliferation through ALCAM/CD6 interaction. Meanwhile, the bM2-like TAMs were responsible for stroma modeling by altering αSMA+/αSMA-cell ratio. On the contrast, the rest of the M2-like TAMs were defined as malignant M2-like TAMs (mM2-like TAMs), partly overlapping with SPP1+ TAMs. mM2-like TAMs were revealed to promote tumor progression by secretion of MIF and SPP1.ConclusionOur study used two prognosis-favorable genes to divide M2-like TAMs of PDAC into anti-tumor bM2-like TAMs and pro-tumor mM2-like TAMs. The bM2-like TAMs activate T cells through ALCAM/CD6 and generate prognosis-favorable αSMA+ myofibroblasts through secreting TGFβ, which brings insight into heterogeneity of TAMs, prognosis prediction and immunotherapy of PDAC.

Introduction This study evaluates the efficacy of integrating percutaneous electrical nerve stimulation at the pericardium 6 (PC6) acupuncture point through a wearable acustimulation device with standard pharmacological prophylaxis to prevent postoperative nausea and vomiting (PONV) compared with pharmacological prophylaxis alone in patients undergoing laparoscopic abdominal surgery.Method and analysis This prospective study will enrol 302 patients scheduled for elective laparoscopic surgery. Participants will be randomly allocated to one of two groups: acustimulation combined with pharmacological prophylaxis or sham stimulation combined with pharmacological prophylaxis. Randomisation will involve a computer-generated sequence, with allocation concealment implemented through sealed envelopes. The acustimulation group will receive electrical stimulation at the PC6 point starting 30 min before surgery and continuing until discharge from the postanaesthesia care unit. Sham group will wear a wristband that does not provide stimulation. The primary outcome is the incidence of PONV. Secondary outcomes include the severity of PONV, incidence rates of nausea and vomiting at different postoperative intervals and indices of gastrointestinal functional recovery. Exploratory outcomes will assess haemodynamic parameters, baroreflex sensitivity, hospital stay duration, costs and both short-term and long-term postoperative recovery.Ethics and dissemination All participants will provide written informed consent. The study has been approved by the Ethics Committee of Peking Union Medical Hospital (approval number: I-23PJ1712). Results will be published open access.Trial registration number NCT06241547.

Abstract Background Cancer is the leading cause of death among older adults. Although the integration of immunotherapy has revolutionized the therapeutic landscape of cancer, the complex interactions between age and immunotherapy efficacy remain incompletely defined. Here, we aimed to elucidate the relationship between aging and immunotherapy resistance. Methods Flow cytometry was performed to evaluate the infiltration of immune cells in the tumor microenvironment (TME). In vivo T cell proliferation, cytotoxicity and migration assays were performed to evaluate the antitumor capacity of tumor antigen-specific CD8+ T cells in mice. Real-time quantitative PCR (qPCR) was used to investigate the expression of IFN-γ-associated gene and natural killer (NK)-associated chemokine. Adoptive NK cell transfer was adopted to evaluate the effects of NK cells from young mice in overcoming the immunotherapy resistance of aged mice. Results We found that elderly patients with advanced non-small cell lung cancer (aNSCLC) aged ≥ 75 years exhibited poorer progression-free survival (PFS), overall survival (OS) and a lower clinical response rate after immunotherapy. Mechanistically, we showed that the infiltration of NK cells was significantly reduced in aged mice compared to younger mice. Furthermore, the aged NK cells could also suppress the activation of tumor antigen-specific CD8+ T cells by inhibiting the recruitment and activation of CD103+ dendritic cells (DCs). Adoptive transfer of NK cells from young mice to aged mice promoted TME remodeling, and reversed immunotherapy resistance. Conclusion Our findings revealed the decreased sensitivity of elderly patients to immunotherapy, as well as in aged mice. This may be attributed to the reduction of NK cells in aged mice, which inhibits CD103+ DCs recruitment and its CD86 expression and ultimately leads to immunotherapy resistance.

Superalloys play a critical role in aerospace applications due to their exceptional mechanical properties at high temperatures. The application of magnetic fields to regulate superalloys presents novel avenues for optimizing microstructures, controlling solidification defects, and enhancing their high-temperature properties. This paper provides a comprehensive review of research findings on the influence of magnetic fields on the microstructure and properties of superalloys. It systematically elucidates the effects of different types and intensities of magnetic fields on alloy solidification. Moreover, this paper extensively explores the effects of various types of magnetic fields on the phase composition, microstructure, and properties of superalloys, including Ni-based and Co-based alloys, as well as high-entropy alloys. The underlying mechanisms behind the impact of magnetic fields on these alloy types are thoroughly analyzed. Finally, the last section offers a brief summary of the current development status and prospects of magnetic field-regulated superalloys.

Abstract Background Adequate preoperative evaluation of the post-intubation hemodynamic instability (PIHI) is crucial for accurate risk assessment and efficient anesthesia management. However, the incorporation of this evaluation within a predictive framework have been insufficiently addressed and executed. This study aims to developed a machine learning approach for preoperatively and precisely predicting the PIHI index values. Methods In this retrospective study, the valid features were collected from 23,305 adult surgical patients at Peking Union Medical College Hospital between 2012 and 2020. Three hemodynamic response sequences including systolic pressure, diastolic pressure and heart rate, were utilized to design the post-intubation hemodynamic instability (PIHI) index by computing the integrated coefficient of variation (ICV) values. Different types of machine learning models were constructed to predict the ICV values, leveraging preoperative patient information and initiatory drug infusion. The models were trained and cross-validated based on balanced data using the SMOTETomek technique, and their performance was evaluated according to the mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE) and R-squared index (R2). Results The ICV values were proved to be consistent with the anesthetists’ ratings with Spearman correlation coefficient of 0.877 (P

Abstract Dense matching of remote sensing images is crucial for 3D reconstruction. This study proposes an enhanced dense matching method employing the CPS image denoising algorithm, aiming to boost the SGM algorithm's accuracy and efficiency in remote sensing image matching. The stereo image pair's quality is evaluated using the PSNR index, and a decision-making criterion based on the CPS algorithm is incorporated to determine the need for denoising. Preprocessing steps, including image cropping and pixel coordinate transformation, significantly reduce computational requirements. An epipolar line model, minimizing the disparity between two pixels, is used for calculations. This model is employed to construct an epipolar image, enhancing the accuracy and efficiency of the process. The study conducted experimental validation and analysis of the mismatch rate, running time, and denoising effect of the algorithm using the Middlebury 2021 stereo datasets. Additionally, the matching results of the World-View3 satellite stereo image pairs were visualized and analyzed. The experimental results indicate that the proposed algorithm reduces the average mismatch rate by 13.1% and increases the running speed by about 3 to 4 times compared to the SGBM algorithm. Specifically, the denoising effect reduces the mismatch rate of the reconstructed image by an average of 8.97%. The results indicate that the CPS method effectively addresses dense matching challenges in the presence of image blur and noise, thereby improving the operational efficiency and accuracy of the dense matching algorithm.

Abstract Background Epigenetic marks are reprogrammed during sexual reproduction. In flowering plants, DNA methylation is only partially remodeled in the gametes and the zygote. However, the timing and functional significance of the remodeling during plant gametogenesis remain obscure. Results Here we show that DNA methylation remodeling starts after male meiosis in rice, with non-CG methylation, particularly at CHG sites, being first enhanced in the microspore and subsequently decreased in sperm. Functional analysis of rice CHG methyltransferase genes CMT3a and CMT3b indicates that CMT3a functions as the major CHG methyltransferase in rice meiocyte, while CMT3b is responsible for the increase of CHG methylation in microspore. The function of the two histone demethylases JMJ706 and JMJ707 that remove H3K9me2 may contribute to the decreased CHG methylation in sperm. During male gametogenesis CMT3a mainly silences TE and TE-related genes while CMT3b is required for repression of genes encoding factors involved in transcriptional and translational activities. In addition, CMT3b functions to repress zygotic gene expression in egg and participates in establishing the zygotic epigenome upon fertilization. Conclusion Collectively, the results indicate that DNA methylation is dynamically remodeled during male gametogenesis, distinguish the function of CMT3a and CMT3b in sex cells, and underpin the functional significance of DNA methylation remodeling during rice reproduction.

Leveraging whole-genome sequencing (WGS) that includes the full spectrum of genetic variation provides a better understanding of the biological mechanisms involved in the economically important traits of farm animals. However, the effectiveness of WGS in improving the accuracy of genomic prediction (GP) is limited. Recent genetic analyses of complex traits, such as genome-wide association study (GWAS), have identified numerous genomic regions and potential genes, which can provide valuable prior information for the improvement of genomic selection (GS). In this study, we applied different genome prediction methods to integrate GWAS results and gene feature annotations, which significantly improved the accuracy of GS for beef production traits. The Bayesian models incorporating genomic features showed the highest prediction accuracy, particularly for average daily gain (ADG) and bone weight (BW). Compared to prediction models based on WGS data, GP including biological prior can optimize the prediction accuracy by up to 11.56% for ADG and 14.60% for BW. Also, GP using GBLUP and Bayesian methods integrating biological priors for single-trait GWAS can significantly increase the prediction accuracy. Bayesian methods generally outperformed GBLUP models, with average improvements of 2.25% for ADG, 5.04% for BW, and 3.44% for live weight (LW). Our results indicate that leveraging biological prior knowledge can significantly refine GS models and underline the potential of combining WGS data with biological prior knowledge to further enhance the breeding process.

Objective Current biomarkers for predicting immunotherapy response in non-small-cell lung cancer (NSCLC) are derived from invasive procedures with limited predictive accuracy. Thus, identifying a non-invasive predictive biomarker would improve patient stratification and precision immunotherapy.Methods and analysis In this retrospective multicohort study, the discovery cohort included 205 NSCLC patients screened from ORIENT-11 and an external validation (EV) cohort included 99 real-world NSCLC patients. The ‘onion-mode segmentation’ method was developed to extract ‘onion-mode perfusion’ (OMP) from contrast-enhanced CT images. The predictive performance of OMP or its combination with the PD-L1 Tumour Proportion Score (TPS) was evaluated by the area under the curve (AUC).Results High baseline OMP was associated with significantly longer survival and predicted patient response to combination anti-PD-(L)1 therapy in the discovery and EV cohorts. OMP complemented the PD-L1 TPS with superior predictive sensitivity (p=0.02). In the PD-L1 TPS

IntroductionFusarium oxysporum is a significant soil-borne fungal pathogen that affects over 100 plant species, including crucial crops like tomatoes, bananas, cotton, cucumbers, and watermelons, leading to wilting, yellowing, growth inhibition, and ultimately plant death. The root rot disease of A. macrocephala, caused by F. oxysporum, is one of the most serious diseases in continuous cropping, which seriously affects its sustainable development.MethodsIn this study, we explored the interaction between A. macrocephala and F. oxysporum through integrated small RNA (sRNA) and degradome sequencing to uncover the microRNA (miRNA)–mediated defense mechanisms.ResultsWe identified colonization of F. oxysporum in A. macrocephala roots on day 6. Nine sRNA samples were sequenced to examine the dynamic changes in miRNA expression in A. macrocephala infected by F. oxysporum at 0, 6, and 12 days after inoculation. Furthermore, we using degradome sequencing and quantitative real-time PCR (qRT-PCR), validated four miRNA/target regulatory units involved in A. macrocephala–F. oxysporum interactions.DiscussionThis study provides new insights into the molecular mechanisms underlying A. macrocephala's early defense against F. oxysporum infection, suggesting directions for enhancing resistance against this pathogen.

Abstract Background The aim was to evaluate the effect of beta‐blockers (BB) on the response of heart rate (HR) to 6‐min walk test (6MWT) in atrial fibrillation (AF) and whether the AF patients treated with BB have a similar HR response to 6MWT as the AF and sinus rhythm (SR) patients without BB treatment at the same resting HR level. Methods The before–after study involving 74 AF patients was to evaluate the effect of BB treatment (pre‐BB and with BB). The comparison study included 74 BB‐treated AF patients (with BB), 74 matched AF patients without BB (no BB), and 74 SR patients. The percentage increase amplitude of HR (HR‐PIA) in 6MWT was calculated: [(the exercise HR − the resting HR)/(the resting HR)] × 100%. Results The before–after study showed that BB treatment decreased the resting and mean exercise HR (98.6 ± 15.2 vs. 85.5 ± 11.2 bpm and 121.3 ± 17.3 vs. 109.0 ± 16.7 bpm) during 6MWT. The comparison study demonstrated that against the SR, the AF with BB and no BB groups have higher mean exercise HR‐PIA (28.2 ± 17.1% and 22.0 ± 9.6%, vs. 6.9 ± 3.7%) when their resting HR is similar. Moreover, the mean exercise HR‐PIA was also significantly higher in the with BB group than in the no BB group. Conclusion In AF patients with relatively higher resting HR, BB treatment could decrease the resting and exercise HR during 6MWT. However, BB treatment could not effectively attenuate the exercise HR rise as compared with AF without BB treatment, even with similar resting HR levels.

The immune response plays a crucial role in the functionality of oncolytic viruses. In this study, Albendazole, an antihelminthic drug known to modulate the immune checkpoint PD-L1, was combined with the oncolytic virus M1 (OVM1) to treat mice with either prostate cancer (RM-1) or glioma (GL261) tumors. This combination therapy enhanced anti-tumor effects in immunocompetent mice, but not in immunodeficient ones, without increasing OVM1 replication. Instead, it led to an increase in the number of CD8+ T cells within the tumor, downregulated the expression of PD1 on CD8+ T cells, and upregulated activation markers such as Ki67, CD44, and CD69 and the secretion of cytotoxic factors including interferon (IFN)-γ, granzyme B, and tumor necrosis factor (TNF)-α. Consistently, it enhanced the in vitro tumor-killing activity of lymphocytes from tumor-draining lymph nodes or spleens. The synergistic effect of Albendazole on OVM1 was abolished by depleting CD8+ T cells, suggesting a CD8+ T cell-dependent mechanism. In addition, Albendazole and OVM1 therapy increased CTLA4 expression in the spleen, and the addition of CTLA4 antibodies further enhanced the anti-tumor efficacy in vivo. In summary, Albendazole can act synergistically with oncolytic viruses via CD8+ T cell activation, and the Albendazole/OVM1 combination can overcome resistance to CTLA4-based immune checkpoint blockade therapy.

Targeting specific molecular drivers of tumor growth is a key approach in cancer therapy. Among these targets, the low-density lipoprotein receptor-related protein 6 (LRP6), a vital component of the Wnt signaling pathway, has emerged as an intriguing candidate. As a cell-surface receptor and vital co-receptor, LRP6 is frequently overexpressed in various cancer types, implicating its pivotal role in driving tumor progression. The pursuit of LRP6 as a target for cancer treatment has gained substantial traction, offering a promising avenue for therapeutic intervention. Here, this comprehensive review explores recent breakthroughs in our understanding of LRP6's functions and underlying molecular mechanisms, providing a profound discussion of its involvement in cancer pathogenesis and drug resistance. Importantly, we go beyond discussing LRP6's role in cancer by discussing diverse potential therapeutic approaches targeting this enigmatic protein. These approaches encompass a wide spectrum, including pharmacological agents, natural compounds, non-coding RNAs, epigenetic factors, proteins, and peptides that modulate LRP6 expression or disrupt its interactions. In addition, also discussed the challenges associated with developing LRP6 inhibitors and their advantages over Wnt inhibitors, as well as the drugs that have entered phase II clinical trials. By shedding light on these innovative strategies, we aim to underscore LRP6’s significance as a valuable and multifaceted target for cancer treatment, igniting enthusiasm for further research and facilitating translation into clinical applications.

BackgroundAcute Ischemic Stroke (AIS) remains a leading cause of mortality and disability worldwide. Rapid and precise prognostication of AIS is crucial for optimizing treatment strategies and improving patient outcomes. This study explores the integration of machine learning-derived radiomics signatures from multi-parametric MRI with clinical factors to forecast AIS prognosis.ObjectiveTo develop and validate a nomogram that combines a multi-MRI radiomics signature with clinical factors for predicting the prognosis of AIS.MethodsThis retrospective study involved 506 AIS patients from two centers, divided into training (n = 277) and validation (n = 229) cohorts. 4,682 radiomic features were extracted from T1-weighted, T2-weighted, and diffusion-weighted imaging. Logistic regression analysis identified significant clinical risk factors, which, alongside radiomics features, were used to construct a predictive clinical-radiomics nomogram. The model’s predictive accuracy was evaluated using calibration and ROC curves, focusing on distinguishing between favorable (mRS ≤ 2) and unfavorable (mRS > 2) outcomes.ResultsKey findings highlight coronary heart disease, platelet-to-lymphocyte ratio, uric acid, glucose levels, homocysteine, and radiomics features as independent predictors of AIS outcomes. The clinical-radiomics model achieved a ROC-AUC of 0.940 (95% CI: 0.912–0.969) in the training set and 0.854 (95% CI: 0.781–0.926) in the validation set, underscoring its predictive reliability and clinical utility.ConclusionThe study underscores the efficacy of the clinical-radiomics model in forecasting AIS prognosis, showcasing the pivotal role of artificial intelligence in fostering personalized treatment plans and enhancing patient care. This innovative approach promises to revolutionize AIS management, offering a significant leap toward more individualized and effective healthcare solutions.

Abstract In nature, various animal groups like bird flocks display proficient collective navigation achieved by maintaining high consistency and cohesion simultaneously. Both metric and topological interactions have been explored to ensure high consistency among groups. The topological interactions found in bird flocks are more cohesive than metric interactions against external perturbations, especially the spatially balanced topological interaction (SBTI). However, it is revealed that in complex environments, pursuing cohesion via existing interactions compromises consistency. The authors introduce an innovative solution, assemble topological interaction, to address this challenge. Contrasting with static interaction rules, the new interaction empowers individuals with self‐awareness to adapt to the complex environment by switching between interactions through visual cues. Most individuals employ high‐consistency k‐nearest topological interaction when not facing splitting threats. In the presence of such threats, some switch to the high‐cohesion SBTI to avert splitting. The assemble topological interaction thus transcends the limit of the trade‐off between consistency and cohesion. In addition, by comparing groups with varying degrees of these two features, the authors demonstrate that group effects are vital for efficient navigation led by a minority of informed agents. Finally, the real‐world drone‐swarm experiments validate the applicability of the proposed interaction to artificial robotic collectives.

Abstract Immune checkpoint inhibitor (ICI) rechallenge in non‐small cell lung cancer (NSCLC) is a promising therapeutic strategy. The situation for ICI rechallenge can be divided into three categories: adverse events (AEs); resistance to ICIs, and rechallenge becomes compulsive because of tumor relapse while the patients had completed a 2 year course of immunotherapy. However, these categories are still controversial and should be explored further. Through voting at the 6th Straits Summit Forum on Lung Cancer, in this study we summarize the consensus of 147 experts in ICI rechallenges. A total of 97.74% experts agreed to rechallenge; 48.87% experts rechallenge with the original drug, and the others rechallenge with a different drug; 40.3% agreed to rechallenge directly after progression; 88.06% experts agreed to ICI rechallenge with a combination regimen; and factors such as previous performance status score, PD‐1 expression, and age should also be considered. Understanding the the clinical studies in ICI rechallenge could bring us one step closer to understanding the consensus. In patients with advanced NSCLC who have suffered recurrent or distant metastasis after immunotherapy, the option of rechallenge with ICIs is a promising treatment option.

Abstract Background The incidence of breast cancer among Chinese women has gradually increased in recent years. This study aims to analyze the situation of breast cancer screening programs in China and compare the cancer detection rates (CDRs), early-stage cancer detection rates (ECDRs), and the proportions of early-stage cancer among different programs. Methods We conducted a systematic review and meta-analysis of studies in multiple literature databases. Studies that were published between January 1, 2010 and June 30, 2023 were retrieved. A random effects model was employed to pool the single group rate, and subgroup analyses were carried out based on screening model, time, process, age, population, and follow-up method. Results A total of 35 studies, including 47 databases, satisfied the inclusion criteria. Compared with opportunistic screening, the CDR (1.32‰, 95% CI: 1.10‰–1.56‰) and the ECDR (0.82‰, 95% CI: 0.66‰–0.99‰) were lower for population screening, but the proportion of early-stage breast cancer (80.17%, 95% CI: 71.40%–87.83%) was higher. In subgroup analysis, the CDR of population screening was higher in the urban group (2.28‰, 95% CI: 1.70‰–2.94‰), in the breast ultrasonography (BUS) in parallel with mammography (MAM) group (3.29‰, 95% CI: 2.48‰–4.21‰), and in the second screening follow-up group (2.47‰, 95% CI: 1.64‰–3.47‰), and the proportion of early-stage breast cancer was 85.70% (95% CI: 68.73%–97.29%), 88.18% (95% CI: 84.53%–91.46%), and 90.05% (95% CI: 84.07%–94.95%), respectively. Conclusion There were significant differences between opportunistic and population screening programs. The results of these population screening studies were influenced by the screening process, age, population, and follow-up method. In the future, China should carry out more high-quality and systematic population-based screening programs to improve screening coverage and service.

Abstract Background Rett Syndrome (RTT) is a rare, severe, and progressive developmental disorder with intellectual disability. Anesthesia in RTT patients presents a range of challenges. We report a child with RTT who received dental treatment under muscle relaxant-free general anesthesia in our ambulatory center. Case presentation A 15-year-old girl with RTT was admitted to our dental clinic with multiple dental caries and residual roots. Dental treatment was scheduled under ambulatory general anesthesia. After anesthesia induction, a nasal tube was initiated under the guidance of a fiberoptic bronchoscope. Multimodal analgesia, body temperature monitoring, and postoperative nausea and vomiting prevention were applied. No muscle relaxants were used throughout the process. The endotracheal tube was successfully removed after the operation and the patient was discharged home the same day. Conclusion An individualized anesthesia strategy enabled a quick and safe recovery for this RTT patient after dental treatment under muscle relaxant-free general anesthesia.