Search

Abstract Background Pneumoconiosis has a significant impact on the quality of patient survival. This study aims to evaluate the performance and application value of improved Unet network technology in the recognition and segmentation of lesion areas of lung CT images in patients with pneumoconiosis. Methods A total of 1212 lung CT images of patients with pneumoconiosis were retrospectively included. The improved Unet network was used to identify and segment the CT image regions of the patients’ lungs, and the image data of the granular regions of the lungs were processed by the watershed and region growing algorithms. After random sorting, 848 data were selected into the training set and 364 data into the validation set. The experimental dataset underwent data augmentation and were used for model training and validation to evaluate segmentation performance. The segmentation results were compared with FCN-8s, Unet network (Base), Unet (Squeeze-and-Excitation, SE + Rectified Linear Unit, ReLU), and Unet + + networks. Results In the segmentation of lung CT granular region with the improved Unet network, the four evaluation indexes of Dice similarity coefficient, positive prediction value (PPV), sensitivity coefficient (SC) and mean intersection over union (MIoU) reached 0.848, 0.884, 0.895 and 0.885, respectively, increasing by 7.6%, 13.3%, 3.9% and 6.4%, respectively, compared with those of Unet network (Base), and increasing by 187.5%, 249.4%, 131.9% and 51.0%, respectively, compared with those of FCN-8s, and increasing by 14.0%, 31.2%, 4.7% and 9.7%, respectively, compared with those of Unet network (SE + ReLU), while the segmentation performance was also not inferior to that of the Unet + + network. Conclusions The improved Unet network proposed shows good performance in the recognition and segmentation of abnormal regions in lung CT images in patients with pneumoconiosis, showing potential application value for assisting clinical decision-making.

Abstract Objective To construct the deep learning convolution neural network (CNN) model and machine learning support vector machine (SVM) model of bone remodeling of chronic maxillary sinusitis (CMS) based on CT image data to improve the accuracy of image diagnosis. Methods Maxillary sinus CT data of 1000 samples in 500 patients from January 2018 to December 2021 in our hospital was collected. The first part is the establishment and testing of chronic maxillary sinusitis detection model by 461 images. The second part is the establishment and testing of the detection model of chronic maxillary sinusitis with bone remodeling by 802 images. The sensitivity, specificity and accuracy and area under the curve (AUC) value of the test set were recorded, respectively. Results Preliminary application results of CT based AI in the diagnosis of chronic maxillary sinusitis and bone remodeling. The sensitivity, specificity and accuracy of the test set of 93 samples of CMS, were 0.9796, 0.8636 and 0.9247, respectively. Simultaneously, the value of AUC was 0.94. And the sensitivity, specificity and accuracy of the test set of 161 samples of CMS with bone remodeling were 0.7353, 0.9685 and 0.9193, respectively. Simultaneously, the value of AUC was 0.89. Conclusion It is feasible to use artificial intelligence research methods such as deep learning and machine learning to automatically identify CMS and bone remodeling in MSCT images of paranasal sinuses, which is helpful to standardize imaging diagnosis and meet the needs of clinical application.

Abstract Metastasis is the major cause of cancer‐related death of cancer patients. Epithelial‐mesenchymal transition (EMT) is one critical process during the cascade of tumor metastasis. EMT is a developmental program exploited by cancer cells to transition from epithelial state to mesenchymal state and confers metastatic properties as well as treatment resistance. Finding factors to inhibit EMT will greatly improve the prognosis patients. Spermatogenesis associated 2 (SPATA2) was originally isolated from human testis and proved playing a role in spermatogenesis. To date, however, the role of SPATA2 in oncogenesis is unknown. In the current study, by mining the public database and validating in a cohort of collected non–small cell lung cancer (NSCLC) specimens, we uncovered that the expression of SPATA2 positively correlated with the prognosis of patients and was an independent prognosis marker in NSCLC. Functional studies proved that ectopic overexpression of SPATA2 inhibited EMT resulting in impaired motility and invasiveness properties in vitro and metastasis in vivo, and increased radiosensitivity in NSCLC. Mechanistic investigation showed that SPATA2 could suppress the β‐catenin signaling via attenuating DVL1 ubiquitination to achieve the functions. Taken together, the current study revealed an inhibitory role of SPATA2 on EMT and that SPATA2 could be a potential target for therapy of NSCLC.

ObjectiveDifferent semicircular canal surgery techniques have been used to treat patients with labyrinthine fistulas caused by middle ear cholesteatoma. This study evaluated postoperative hearing and vestibular function after various semicircular canal surgeries.Materials and methodsIn group 1, from January 2008 to December 2014, 29 patients with middle ear cholesteatoma complicated by labyrinthine fistulas were treated with surgery involving covering the fistulas with simple fascia. In group 2, from January 2015 to October 2021, 36 patients with middle ear cholesteatoma complicated by labyrinthine fistulas were included. Cholesteatomas on the surface of type I labyrinthine fistulas were cleaned using the “under water technique” and capped with a “sandwich” composed of fascia, bone meal, and fascia. Cholesteatomas on the surface of type II and III fistulas were cleaned using the “under water technique,” and the labyrinthine fistula was plugged with a “pie” composed of fascia, bone meal, and fascia, and then covered with bone wax.ResultsSome patients with labyrinthine fistulas in group 1 exhibited symptoms of vertigo after surgery. In group 2 Patients with type II labyrinthine fistulas experienced short-term vertigo after semicircular canal occlusion, but no cases of vertigo were reported during long-term follow-up. “sandwich.” In patients with type II labyrinthine fistulas, the semicircular canal occlusion influenced postoperative hearing improvement. However, postoperative patient hearing was still superior to preoperative hearing.ConclusionThe surface of type I labyrinthine fistulas should be capped by a “sandwich” composed of fascia, bone meal, and fascia. Type II and III labyrinthine fistulas should be plugged with a “pie” composed of fascia, bone meal, and fascia, covered with bone wax.

Recent evidence shows that cyclic GMP-AMP synthase (cGAS)/stimulator of interferon (IFN) genes (STING) signaling is essential for antitumor immunity by inducing the production of type I IFN and thus activating both innate and adaptive immunity based on gene knockout mouse models. However, the extensive detection of the expression of cGAS/STING signaling in human cancer and mining the roles of this signaling pathway in human cancer immunity have not been performed until now. In this study, we revealed that four key molecules (cGAS, STING, TANK binding kinase 1 [TBK1], and IFN regulatory factor 3 [IRF3]) in the cGAS/STING signaling are highly expressed in cancer tissues, and the expression levels of these genes are negatively correlated with their methylation levels in most of the detected cancer types. We also showed that highly upregulated cGAS/STING signaling is negatively correlated with the infiltration of immune cells in some tumor types, and consistent with these findings, we showed that a high level of cGAS/STING signaling predicts a poor prognosis in patients with certain cancers. This study suggests that it is necessary to deeply and fully evaluate the function of cGAS/STING signaling in cancer immunity and cancer progression before the application of the STING agonist-based anticancer immune therapy in the clinic. Keywords: cGAS/STING, immune infiltration, prognosis, methylation, interferon

Abstract Background Baryscapus dioryctriae (Chalcidodea: Eulophidae) is a parasitic wasp that parasitizes the pupae of many Pyralidae members and has been used as a biological control agent against Dioryctria pests of pinecones. Results This B. dioryctriae assembly has a genome size of 485.5 Mb with a contig N50 of 2.17 Mb, and scaffolds were assembled onto six chromosomes using Hi-C analysis, significantly increasing the scaffold N50 to 91.17 Mb, with more than 96.13% of the assembled bases located on chromosomes, and an analysis revealed that 94.73% of the BUSCO gene set. A total of 54.82% (279.27 Mb) of the assembly was composed of repetitive sequences and 24,778 protein-coding genes were identified. Comparative genomic analysis demonstrated that the chemosensory perception, genetic material synthesis, and immune response pathways were primarily enriched in the expanded genes. Moreover, the functional characteristics of an odorant-binding protein (BdioOBP45) with ovipositor-biased expression identified from the expanded olfactory gene families were investigated by the fluorescence competitive binding and RNAi assays, revealing that BdioOBP45 primarily binds to the D. abietella-induced volatile compounds, suggesting that this expanded OBP is likely involved in locating female wasp hosts and highlighting a direction for future research. Conclusions Taken together, this work not only provides new genomic sequences for the Hymenoptera systematics, but also the high-quality chromosome-level genome of B. dioryctriae offers a valuable foundation for studying the molecular, evolutionary, and parasitic processes of parasitic wasps.

Abstract Background Understanding factors associated with antiretroviral treatment (ART) adherence is crucial for ART success among people living with HIV (PLHIV) in the “test and treat” era. Multiple psychosocial factors tend to coexist and have a syndemic effect on ART adherence. We aimed to explore factors associated with ART adherence and the syndemic effect of multiple psychosocial factors on ART adherence among PLHIV newly starting ART in Guangdong Province, China. Methods Newly diagnosed PLHIV from six cities in Guangdong Province were recruited between May 2018 and June 2019, and then followed up from May 2019 to August 2020. Baseline and follow-up data were collected from a questionnaire and the national HIV surveillance system, the follow-up data of which were analyzed in this study. A Center for Adherence Support Evaluation (CASE) index > 10 points was defined as optimal ART adherence, which was measured via participants’ self-reported adherence during follow-up survey. Multivariable logistic regression was used to identify factors associated with ART adherence. Exploratory factor analysis (EFA) and multi-order latent variable structural equation modeling (SEM) were performed to explore the syndemic effect of multiple psychosocial factors on ART adherence. Results A total of 734 (68.53%) follow-up participants were finally included in this study among the 1071 baseline participants, of whom 91.28% (670/734) had self-reported optimal ART adherence. Unemployment (aOR = 1.75, 95%CI: 1.01–3.02), no medication reminder (aOR = 2.28, 95%CI: 1.09–4.74), low medication self-efficacy (aOR = 2.28, 95%CI: 1.27–4.10), low social cohesion (aOR = 1.82, 95%CI: 1.03–3.19), no social participation (aOR = 5.65, 95%CI: 1.71–18.63), and ART side effects (aOR = 0.46, 95%CI: 0.26–0.81) were barriers to optimal ART adherence. The EFA and second-order latent variable SEM showed a linear relationship (standardized coefficient = 0.43, P

The heat island effect has far-reaching impacts on human settlements and natural ecosystems. Current research predominantly focuses on urban areas and overlooks the broader natural ecosystems beyond urban boundaries. Therefore, there’s an increasing urgency to reassess and study the heat island effect from a regional spatial perspective. This study introduces the concept of Land Heat Island (LHI) and quantifies it through Land Heat Island Intensity (LHII). Utilizing multivariate data and statistical analyses, this study investigates the spatiotemporal evolution of LHII in the Beibu Gulf urban agglomeration from 2012 to 2021. Redundancy analysis (RDA) and spatial bivariate correlation analysis were used to understand the relationships and evolution of factors influencing LHII. The results showed: (1) From 2012 to 2021, the heat island effect within the Beibu Gulf urban agglomeration gradually intensified. LHII was higher in the coastal areas compared to the inland regions, more developed economic areas exhibited higher LHII than less developed ones, and areas characterized by concentrated human activities had higher LHII than ecological agglomeration areas. (2) The primary zones of LHII growth in the Beibu Gulf urban agglomeration were slightly hot island areas and weakly hot island areas. The northern part of the area where forestland was clustered had a greater influence on the cold island pattern than on the heat island pattern; the lower latitude area had a greater influence on the heat island pattern than on the cold island pattern; and the eastern part of the area where the economy was well developed had an increasing influence on the heat island pattern year by year. (3) The enhancement of LHII in the Beibu Gulf urban agglomeration is primarily driven by urban construction and socio-economic factors. Specifically, Carbon Emissions and the Nighttime Light Index (NLI), which representing the strength of urban construction, contribute 11.4% and 8.3% respectively. Additionally, the Population Size (PS), representing the strength of socio-economic factors, contributes 12%. (4) The weakening of LHII was primarily affected by natural ecological factors, with the top two contributors being the average Digital Elevation Model (DEM) of cultivated land and average Normalized Difference Vegetation Index (NDVI), accounting for 32.9% and 14% respectively. This study enhances our understanding of the spatiotemporal evolution of the heat island effect and aims to mitigate it in the Bay Area urban agglomeration.

BackgroundVaccination can be viewed as comprising the most important defensive barriers to protect susceptible groups from infection. However, vaccine hesitancy for COVID-19 is widespread worldwide. ObjectiveWe aimed to systematically review studies eliciting the COVID-19 vaccine preference using discrete choice experiments. MethodsA literature search was conducted in PubMed, Embase, Web of Science, Scopus, and CINAHL Plus platforms in April 2023. Search terms included discrete choice experiments, COVID-19, and vaccines and related synonyms. Descriptive statistics were used to summarize the study characteristics. Subgroup analyses were performed by factors such as high-income countries and low- and middle-income countries and study period (before, during, and after the pandemic wave). Quality appraisal was performed using the 5-item Purpose, Respondents, Explanation, Findings, and Significance checklist. ResultsThe search yield a total of 623 records, and 47 studies with 53 data points were finally included. Attributes were grouped into 4 categories: outcome, process, cost, and others. The vaccine effectiveness (21/53, 40%) and safety (7/53, 13%) were the most frequently reported and important attributes. Subgroup analyses showed that vaccine effectiveness was the most important attribute, although the preference varied by subgroups. Compared to high-income countries (3/29, 10%), a higher proportion of low- and middle-income countries (4/24, 17%) prioritized safety. As the pandemic progressed, the duration of protection (2/24, 8%) during the pandemic wave and COVID-19 mortality risk (5/25, 20%) after the pandemic wave emerged as 2 of the most important attributes. ConclusionsOur review revealed the critical role of vaccine effectiveness and safety in COVID-19 vaccine preference. However, it should be noticed that preference heterogeneity was observed across subpopulations and may change over time. Trial RegistrationPROSPERO CRD42023422720; https://tinyurl.com/2etf7ny7

Abstract Background Condom use at last intercourse is an effective indicator for human immunodeficiency virus (HIV) prevention. To identify at-risk individuals and improve prevention strategies, this study explored factors associated with condomless sex at last intercourse in the last year and developed a risk estimation model to calculate the individual possibility of condomless sex among college students in Zhuhai, China. Methods A cross-sectional study was conducted among 1430 college students who had sex in the last year from six universities in Zhuhai. The least absolute shrinkage and selection operator (LASSO) and logistic regression were performed to explore the predictors of condomless sex. The nomogram was constructed to calculate the individual possibility of condomless sex. Discrimination and calibration of the nomogram were evaluated using the area under the receiver-operator characteristic curve (AUROC) and the calibration curve. Results The proportion of students who had condomless sex at last intercourse was 18.2% (260/1430). Students who had experienced more types of intimate partner violence (aOR, 1.58; 95% CI, 1.31 ~ 1.92) and had anal sex (aOR, 1.75; 95% CI, 1.06 ~ 2.84) were more likely to have condomless sex. Students who had heterosexual intercourse (aOR, 0.37; 95% CI, 0.21 ~ 0.70), used condoms at first sex (aOR, 0.20; 95% CI, 0.14 ~ 0.27), had high attitudes towards condom use (aOR, 0.87; 95% CI, 0.80 ~ 0.95) and self-efficacy for condom use (aOR, 0.84; 95% CI, 0.78 ~ 0.90) were less likely to have condomless sex. The nomogram had high accuracy with an AUROC of 0.83 and good discrimination. Conclusions Intimate partner violence, anal sex, condom use at first sex, attitude towards condom use, and self-efficacy for condom use were associated with condomless sex among college students. The nomogram was an effective and convenient tool for calculating the individualized possibility of condomless sex among college students. It could help to identify individuals at risk and help universities and colleges to formulate appropriate individualized interventions and sexual health education programs.

After an earthquake, efficiently and accurately acquiring information about damaged buildings can help reduce casualties. Earth observation data have been widely used to map affected areas after earthquakes. However, fine post-earthquake assessment results are needed to manage recovery and reconstruction and to estimate economic losses. In this paper, for quantification and precision purposes, a method of earthquake-induced building damage information extraction incorporating multi-source remote sensing data is proposed. The method consists of three steps： (1) Analysis of multisource features that describe texture, colour, and geometry, (2) rough set theory is carried out to further determine the feature parameters, (3) Logistic regression model (LRM) was built to describe the relationship between the occurrence and absence of destroyed buildings within an individual object. Old Beichuan County (centered at approximately 31.833︒N, 104.459° E), China, the area most devastated by the Wenchuan earthquake on May 12, 2008, is used to test the proposed hypothesis. Multi-source remote sensing imagery include optical data, synthetic aperture radar (SAR) data, and digital surface model (DSM) data generated by interpolating light detection and ranging (LiDAR) point cloud data. Through comparison with the ground survey, the experimental results show that the detection accuracy of the proposed method is 94.2 %; the area under the receiver operating characteristic (ROC) curve is 0.827. The efficiency of the proposed method is demonstrated using 6 modes of data combination acquired from the same area in old Beichuan County. The approach is one of the first attempts to extract damaged buildings through the fusion of three types of data with different features. The approach addresses multivariate regression methodologies and compares the potential of features for application in the damage detection field.

BackgroundSexual health influencers (SHIs) are individuals actively sharing sexual health information with their peers, and they play an important role in promoting HIV care services, including the secondary distribution of HIV self-testing (SD-HIVST). Previous studies used a 6-item empirical leadership scale to identify SHIs. However, this approach may be biased as it does not consider individuals’ social networks. ObjectiveThis study used a quasi-experimental study design to evaluate how well a newly developed machine learning (ML) model identifies SHIs in promoting SD-HIVST compared to SHIs identified by a scale whose validity had been tested before. MethodsWe recruited participants from BlueD, the largest social networking app for gay men in China. Based on their responses to the baseline survey, the ML model and scale were used to identify SHIs, respectively. This study consisted of 2 rounds, differing in the upper limit of the number of HIVST kits and peer-referral links that SHIs could order and distribute (first round ≤5 and second round ≤10). Consented SHIs could order multiple HIV self-testing (HIVST) kits and generate personalized peer-referral links through a web-based platform managed by a partnered gay-friendly community-based organization. SHIs were encouraged to share additional kits and peer-referral links with their social contacts (defined as “alters”). SHIs would receive US $3 incentives when their corresponding alters uploaded valid photographic testing results to the same platform. Our primary outcomes included (1) the number of alters who conducted HIVST in each group and (2) the number of newly tested alters who conducted HIVST in each. We used negative binomial regression to examine group differences during the first round (February-June 2021), the second round (June-November 2021), and the combined first and second rounds, respectively. ResultsIn January 2021, a total of 1828 men who have sex with men (MSM) completed the survey. Overall, 393 SHIs (scale=195 and ML model=198) agreed to participate in SD-HIVST. Among them, 229 SHIs (scale=116 and ML model=113) ordered HIVST on the web. Compared with the scale group, SHIs in the ML model group motivated more alters to conduct HIVST (mean difference [MD] 0.88, 95% CI 0.02-2.22; adjusted incidence risk ratio [aIRR] 1.77, 95% CI 1.07-2.95) when we combined the first and second rounds. Although the mean number of newly tested alters was slightly higher in the ML model group than in the scale group, the group difference was insignificant (MD 0.35, 95% CI –0.17 to –0.99; aIRR 1.49, 95% CI 0.74-3.02). ConclusionsAmong Chinese MSM, SHIs identified by the ML model can motivate more individuals to conduct HIVST than those identified by the scale. Future research can focus on how to adapt the ML model to encourage newly tested individuals to conduct HIVST. Trial RegistrationChinese Clinical Trials Registry ChiCTR2000039632; https://www.chictr.org.cn/showprojEN.html?proj=63068 International Registered Report Identifier (IRRID)RR2-10.1186/s12889-021-11817-2

Summary: Extracellular vesicles (EVs) were promising circulating biomarkers for multiple diseases, but whether serum EVs-derived proteins could be used as a reliable tumor biomarker for colorectal cancer (CRC) remained inconclusive. In this study, we identified CXCL4 by a 4D data-independent acquisition-based quantitative proteomics assay of serum EVs-derived proteins in 40 individuals and subsequently analyzed serum EVs-derived CXCL4 levels by ELISA in 2 cohorts of 749 individuals. The results revealed that EVs-derived CXCL4 levels were dramatically elevated in CRC patients than in benign colorectal polyp patients or healthy controls (HC). Furthermore, receiver operating characteristic curves revealed that EVs-derived CXCL4 exhibited superior diagnostic performance with area under the curve of 0.948 in the training cohort. Additionally, CXCL4 could effectively distinguish CRC in stage I/II from HC. Notably, CRC patients with high levels of EVs-derived CXCL4 have shorter 2-year progression-free survival than those with low levels. Overall, our findings demonstrated that serum EVs-derived CXCL4 was a candidate diagnostic and prognostic biomarker for CRC.

Objectives The elimination of mother-to-child transmission (MTCT) of syphilis has been set as a public health priority. However, an instrument to predict the MTCT of syphilis is not available. We aimed to develop and validate an intuitive nomogram to predict the individualised risk of MTCT in pregnant women with syphilis in China.Design Retrospective cohort study.Setting Data was acquired from the National Information System of Prevention of MTCT of Syphilis in Guangdong province between 2011 and 2020.Participants A total of 13 860 pregnant women with syphilis and their infants were included and randomised 7:3 into the derivation cohort (n=9702) and validation cohort (n=4158).Primary outcome measures Congenital syphilis.Results Among 13 860 pregnant women with syphilis and their infants included, 1370 infants were diagnosed with congenital syphilis. Least absolute shrinkage and selection operator regression and multivariable logistic regression showed that age, ethnicity, registered residence, marital status, number of pregnancies, transmission route, the timing of syphilis diagnosis, stage of syphilis, time from first antenatal care to syphilis diagnosis and toluidine red unheated serum test titre were predictors of MTCT of syphilis. A nomogram was developed based on the predictors, which demonstrated good calibration and discrimination with an area under the curve of the receiver operating characteristic of 0.741 (95% CI: 0.728 to 0.755) and 0.731 (95% CI: 0.710 to 0.752) for the derivation and validation cohorts, respectively. The net benefit of the predictive models was positive, demonstrating a significant potential for clinical decision-making. We have also developed a web calculator based on this prediction model.Conclusions Our nomogram exhibited good performance in predicting individualised risk for MTCT of syphilis, which may help guide early and personalised prevention for MTCT of syphilis.

Abstract The sensory neocortex has been suggested to be a substrate for long-term memory storage, yet which exact single cells could be specific candidates underlying such long-term memory storage remained neither known nor visible for over a century. Here, using a combination of day-by-day two-photon Ca2+ imaging and targeted single-cell loose-patch recording in an auditory associative learning paradigm with composite sounds in male mice, we reveal sparsely distributed neurons in layer 2/3 of auditory cortex emerged step-wise from quiescence into bursting mode, which then invariably expressed holistic information of the learned composite sounds, referred to as holistic bursting (HB) cells. Notably, it was not shuffled populations but the same sparse HB cells that embodied the behavioral relevance of the learned composite sounds, pinpointing HB cells as physiologically-defined single-cell candidates of an engram underlying long-term memory storage in auditory cortex.

Vehicular lithium-ion batteries (LIBs) may suffer from minor damage or defects owing to external mechanical abuse, such as deformation and scratches, during cycling. This study uses non-destructive testing methods to analyze the effects of minor mechanical deformation on the lifetime and performance of commercial 21700 lIBs. Firstly, incremental capacity analysis (ICA) is performed to quantify the charge/discharge performance and cycle aging behavior of LIBs under different deformations. Secondly, X-ray computed tomography (XCT) technology is utilized to qualitatively analyze the internal structure variations of LIBs caused by minor mechanical deformation. Results show that with an increase in mechanical deformation, the internal resistances of LIBs increase, charging curves move to high voltage areas, and peak points of the incremental capacity (IC) curves decrease and move to high voltage areas. Cyclic charge/discharge of LIBs with different deformations show that with an increase in cycles, the capacity and state-of-health (SOH) of mechanically deformed LIBs decrease significantly due to the changes in the internal structure of batteries. Furthermore, the tomographic images of LIBs demonstrate that the increased internal gaps within the electrodes result in the increase of internal resistance, and the mechanism for capacity loss of batteries in the cyclic is revealed. [ABSTRACT FROM AUTHOR]

The optical image sub-pixel correlation (SPC) technique is an important method for monitoring large-scale surface deformation. RapidEye images, distinguished by their short revisit period and high spatial resolution, are crucial data sources for monitoring surface deformation. However, few studies have comprehensively analyzed the error sources and correction methods of the deformation field obtained from RapidEye images. We used RapidEye images without surface deformation to analyze potential errors in the offset fields. We found that the errors in RapidEye offset fields primarily consist of decorrelation noise, orbit error, and attitude jitter distortions. To mitigate decorrelation noise, the careful selection of offset pairs coupled with spatial filtering is essential. Orbit error can be effectively mitigated by the polynomial fitting method. To address attitude jitter distortions, we introduced a linear fitting approach that incorporated the coherence of attitude jitter. To demonstrate the performance of the proposed methods, we utilized RapidEye images to extract the coseismic displacement field of the 2019 Ridgecrest earthquake sequence. The two-dimensional (2D) offset field contained deformation signals extracted from two earthquakes, with a maximum offset of 2.8 m in the E-W direction and 2.4 m in the N-S direction. A comparison with GNSS observations indicates that, after error correction, the mean relative precision of the offset field improved by 92% in the E-W direction and by 89% in the N-S direction. This robust enhancement underscores the effectiveness of the proposed error correction methods for RapidEye data. This study sheds light on large-scale surface deformation monitoring using RapidEye images.

The tomato leafminer, Tuta absoluta (Lepidoptera: Gelechiidae), is a highly destructive invasive pest targeting Solanaceae crops. Its olfactory system plays a crucial role in host location, mate finding, and other behavioral activities. However, there is a notable gap in the literature regarding the characterization of its chemosensory genes. In this study, we conducted a genome-wide identification of 58 odorant receptors (ORs) of T. absoluta. The identified ORs exhibit coding sequence (CDS) lengths ranging from 1062 bp to 1419 bp, encoding proteins of 354 to 473 amino acids. Gene structure analysis showed that the majority of these ORs consist of five, seven, eight, or nine exons, collectively representing 67% of the total ORs identified. Through chromosomal mapping, we identified several tandemly duplicate genes, including TabsOR12a, TabsOR12b, TabsOR12c, TabsOR21a, TabsOR21b, TabsOR34a, TabsOR34b, TabsOR34c, TabsOR62a, and TabsOR62b. The phylogenetic analysis indicated that six TabsORs were clustered within the lepidopteran sex pheromone receptor clade, while an expansion clade containing ten TabsORs resulted from tandem duplication events. Additionally, five TabsORs were classified into a specific OR clade in T. absoluta. Furthermore, through RNA-Seq and RT-qPCR analyses, we identified five TabsORs (TabsOR21a, TabsOR26a, TabsOR34a, TabsOR34c, and TabsOR36) exhibiting female-antennae-biased expression. Our study provides a valuable foundation to further investigations into the molecular and ecological functions of TabsORs, particularly in relation to oviposition behavior. These findings provide foundational data for the future exploration of the functions of female-biased expression OR genes in T. absoluta, thereby facilitating the further development of eco-friendly attract-and-kill techniques for the prevention and control of T. absoluta.

Ferroptosis and neuroinflammation contribute to the development of Alzheimer's disease (AD). Isoforsythiaside (IFY) is a phenylethanoid glycoside isolated from the dried fruit of Forsythia suspensa (Thunb.) Vahl that has been confirmed to improve the memory and cognitive abilities of APP/PS1 mice in our previous study. The purpose of this study was to explore the anti-ferroptosis and anti-neuroinflammatory properties of IFY-mediated neuroprotection. In APP/PS1 mice, erastin-damaged HT22 cells, and LPS-exposed BV2 cells, the neuroprotective effects against ferroptosis and neuroinflammation were investigated using immunohistochemistry, label-free proteomics, western blot, ELISA, MTT, fluorescence, and TEM. IFY alleviated the expression levels of NO, IL-6, and IL-1β in LPS-exposed BV2 cells and improved the morphology of mitochondria in erastin-damaged HT22 cells. Additionally, IFY upregulated the expression levels of GPX4, FTH, FTL, p-GSK-3β, Nrf2, and NQO1, and downregulated the expression of TFR1, DMT1, p-Fyn, GFAP, p-IKKα+β, p-IκBα, p-NF-κB, and pro-inflammatory factors in the brains of APP/PS1 mice and erastin-damaged HT22 cells. In conclusion, IFY inhibits ferroptosis and neuroinflammation in erastin-damaged HT22 cells and APP/PS1 mice, at least partially by regulating the activation of Nrf2 and NF-κB signaling. IFY may prevent ferroptosis and neuroinflammation in AD and provide a new treatment strategy for AD.

China's 2021 White Paper, China's International Development Cooperation in the New Era, offers a new vision for a more people-centred approach to its development cooperation. While the White Paper extensively discusses partnerships, it only briefly mentions encouraging cooperation with non-governmental organisations (NGOs). This article argues that NGO engagement in international development activities would improve their effectiveness, a view shared by many Chinese scholars and practitioners. However, challenges exist that constrain optimal engagement, especially access to funding, and a weak enabling environment and policy framework. This article addresses these challenges, drawing from the literature on 'going out' among Chinese NGOs and social organisations, along with interviews with key players in the Chinese NGO ecosystem. The article recommends, among other things, that the government clarify and improve its policy framework for NGOs/social organisations in support of China's international development collaboration, especially regarding funding flows, personnel regulations, and material and capital outflows. [ABSTRACT FROM AUTHOR]

Metschnikowia bicuspidata, a globally distributed opportunistic pathogenic fungus, poses a significant threat to crustaceans in diverse aquatic ecosystems, causing severe diseases. Iron, recognized as a virulence factor, plays a crucial role in successful infection with M. bicuspidata. Therefore, this study aims to investigate the transcriptome response of M. bicuspidata to low- and high-iron conditions. Overall, 1082 differentially expressed genes (DEGs) (FDR < 0.05, |log2FC ≥ 1.5|) were identified, comprising 977 and 105 DEGs, in response to low- and high-iron conditions, respectively. These genes predominantly participate in altering metabolism, cell membranes, or cellular structure, allowing the organism to adapt to varying iron levels. Iron limitation-induced genes play crucial roles in energy metabolism, transport, and catabolism pathways. Moreover, 27 ortholog genes were associated with iron transport and homeostasis, with 7 of them participating in iron uptake and regulation under low-iron conditions. This study contributes to the comprehension of iron homeostasis in aquatic fungi. It may offer potential therapeutic strategies for managing M. bicuspidata diseases.

The timing, location, intensity, and drivers of forest disturbance and recovery are crucial for developing effective management strategies and policies for forest conservation and ecosystem resilience. Although many algorithms and improvement methods have been developed, it is still difficult to guarantee the detection accuracy for forest disturbance and recovery patterns in southern China due to the complex climate and topography, faster forest recovery after disturbance, and the low availability of noise-free Landsat images. Here, we improved the LandTrendr parameters for different provinces to detect forest disturbances and recovery trajectories based on the LandTrendr change detection algorithm and time-series Landsat images on the GEE platform, and then applied the secondary random forest classifier to classify the forest disturbance and recovery patterns in southern China during 1990–2020. The accuracy evaluation indicated that our approach and improved parameters of the LandTrendr algorithm can increase the detection accuracy for both the spatiotemporal patterns and multiple events of forest disturbance and recovery, with an overall accuracy greater than 86% and a Kappa coefficient greater than 0.91 for different provinces. The total forest loss area was 1.54 × 105 km2 during 1990–2020 (4931 km2/year); however, most of these disturbed forests were recovered and only 6.39 × 104 km2 was a net loss area (converted to other land cover types). The area with two or more times of disturbance events accounted for 11.50% of the total forest loss area. The total forest gain area (including gain after loss and the afforestation area) was 5.44 × 105 km2, among which, the forest gain area after loss was 8.94 × 104 km2, and the net gain area from afforestation was 4.55 × 105 km2. The timing of the implementation of forestry policies significantly affected the interannual variations in forest disturbance and recovery, with large variations among different provinces. The detected forest loss and gain area was further compared against with inventory and other geospatial products, and proved the effectiveness of our method. Our study suggests that parameter optimization in the LandTrendr algorithm could greatly increase the accuracy for detecting the multiple and lower rate disturbance/recovery events in the fast-regrowing forested areas. Our findings also offer a long-term, moderate spatial resolution, and precise forest dynamic data for achieving sustainable forest management and the carbon neutrality goal in southern China.

In the working process of the tethered unmanned aerial vehicle (UAV), there is interference from the tethered cable, which can easily lead to the instability of the UAV. To solve the above problems, a method based on the Lyapunov exponent is proposed to analyze the stability of tethered cables for tethered UAVs. The dynamics equation of the UAV platform is established using the Euler–Poincare equation. The tension formula of the tethered cable is derived from the catenary theory and the principle of micro-segment equilibrium. Based on the Lyapunov exponential method, the stability changes of the tethered UAV in the takeoff, hovering, and landing stages are simulated and analyzed in a MATLAB environment. Prototype tests are carried out to prove the correctness of the simulation model and calculation conclusions. The results show that with an increase in the density of the tethered cable, the stability of the tethered UAV tends to decrease. At the same time, stability is affected by the density of the tethered cable more often during takeoff than during landing.

The state of water flow is recognized as a key driver of the structure and function of river ecosystems. We selected streamflow data (1960–2020) from three key hydrological stations in the upper Yangtze River: Pingshan, Cuntan, and Yichang. We analyzed the characteristics and changes of the hydrologic regimes of the Yangtze River using the Mann–Kendall method, wavelet analysis, and the IHA-RVA method, and explored the response mechanisms of fish to changes in the hydrological regimes. The results show that (1) the average annual discharge of the upper reaches of the Yangtze River is decreasing, and the abrupt changes in Pingshan, Cuntan, and Yichang stations occurred in 1985, 1998, and 2002, respectively, with the main period of 24–32 years. (2) The overall degree of hydrological changes at Pingshan, Cuntan, and Yichang stations is 45%, 50%, and 61%, respectively, all of which are moderate changes. (3) Dams in the upper reaches of the Yangtze River have caused changes in the flow regime of the Yangtze River. Among them, the changes in the alternating frequency of flow and the annual extreme flow have affected the habitat of aquatic organisms and seriously affected the reproduction of important fishes in the Yangtze River. HIGHLIGHTS Analysis of the variation of the hydrological regime of the upper Yangtze over the past 60 years.; Quantitative evaluation of the degree of alteration of the overall hydrological regime.; Establishing correlation between hydrological indicators and fish reproduction.; Revealing the ecological effects caused by reservoir operation.;

Abstract Background Ankylosing spondylitis (AS) is one of the most common immune-mediated arthritic diseases worldwide. Despite considerable efforts to elucidate its pathogenesis, the molecular mechanisms underlying AS are still not fully understood. Methods To identify candidate genes involved in AS progression, the researchers downloaded the microarray dataset GSE25101 from the Gene Expression Omnibus (GEO) database. They identified differentially expressed genes (DEGs) and functionally enriched them for analysis. They also constructed a protein–protein interaction network (PPI) using STRING and performed cytoHubba modular analysis, immune cell and immune function analysis, functional analysis and drug prediction.The results showed that DEGs were mainly associated with histone modifications, chromatin organisation, transcriptional coregulator activity, transcriptional co-activator activity, histone acetyltransferase complexes and protein acetyltransferase complexes. Results The researchers analysed the differences in expression between the CONTROL and TREAT groups in terms of immunity to determine their effect on TNF-α secretion. By obtaining hub genes, they predicted two therapeutic agents, AY 11–7082 and myricetin. Conclusion The DEGs, hub genes and predicted drugs identified in this study contribute to our understanding of the molecular mechanisms underlying the onset and progression of AS. They also provide candidate targets for the diagnosis and treatment of AS.

The hybrid mode-locking scheme holds great potential in obtaining high power ultrashort laser source since it overcomes low damage threshold, self-starting difficulty in single real saturable absorber (SA) or artificial SA mode-locking scheme. Here we numerically studied the effect of SA’s recovery time on the stability of laser output in an all polarization-maintaining (PM) Erbium-doped fiber laser with hybrid mode-locking scheme, operating at the near zero net dispersion. The mapping relationship between fiber fused angles of nonlinear polarization rotation (NPR) section and different mode-locking states is demonstrated. The proportion of stable single pulse operating points increased from 7 % to more than 77 %, as the recovery time of the SA was reduced from 10 ps to 0.1 ps. The results indicate that the laser output states with hybrid mode-locking scheme could be highly affected by the SA recovery time, when the cavity net dispersion is in near zero regime.

This paper evaluates the influence of mineral admixtures partially replacing cement, sea sand replacing quartz, sea water replacing fresh water on ultra-high performance concrete (UHPC). The fluidity and mechanical properties were studied. Besides, the impermeability, chloride resistance and freeze-thaw resistance were investigated. Failure modes, scanning electron microscope (SEM) analysis, mass loss, relative dynamic modulus of elasticity and mechanical properties of UHPCs after freeze-thaw cycles were conducted. The results showed the fluidity of UHPC paste gradually increases with the improvement of water-binder ratio. It is recommended that the water-binder ratio of UHPC be set at 0.19. The fluidity also increases with the improvement of the content of slag, fly ash and water reducer, but decreases with the improvement of silica fume content. The flexural and compressive strengths of UHPC enhance with the improvement of the content of silica fume, but reduce with the improvement of the content of fly ash and slag. The UHPCs made of quartz sand, river sand and sea sand, all, achieve a high strength. UHPCs prepared at standard curing conditions, with or without steel fibers, mixed by artificial seawater and made of sea sand, exhibited excellent impermeability and chloride resistance. The frost resistant grade of all UHPC specimens prepared by standard curing are greater than F500 exhibiting excellent freeze-thaw resistance and sustainability.

BackgroundHIV self-testing (HIVST) has been rapidly scaled up and additional strategies further expand testing uptake. Secondary distribution involves people (defined as “indexes”) applying for multiple kits and subsequently sharing them with people (defined as “alters”) in their social networks. However, identifying key influencers is difficult. ObjectiveThis study aimed to develop an innovative ensemble machine learning approach to identify key influencers among Chinese men who have sex with men (MSM) for secondary distribution of HIVST kits. MethodsWe defined three types of key influencers: (1) key distributors who can distribute more kits, (2) key promoters who can contribute to finding first-time testing alters, and (3) key detectors who can help to find positive alters. Four machine learning models (logistic regression, support vector machine, decision tree, and random forest) were trained to identify key influencers. An ensemble learning algorithm was adopted to combine these 4 models. For comparison with our machine learning models, self-evaluated leadership scales were used as the human identification approach. Four metrics for performance evaluation, including accuracy, precision, recall, and F1-score, were used to evaluate the machine learning models and the human identification approach. Simulation experiments were carried out to validate our approach. ResultsWe included 309 indexes (our sample size) who were eligible and applied for multiple test kits; they distributed these kits to 269 alters. We compared the performance of the machine learning classification and ensemble learning models with that of the human identification approach based on leadership self-evaluated scales in terms of the 2 nearest cutoffs. Our approach outperformed human identification (based on the cutoff of the self-reported scales), exceeding by an average accuracy of 11.0%, could distribute 18.2% (95% CI 9.9%-26.5%) more kits, and find 13.6% (95% CI 1.9%-25.3%) more first-time testing alters and 12.0% (95% CI –14.7% to 38.7%) more positive-testing alters. Our approach could also increase the simulated intervention’s efficiency by 17.7% (95% CI –3.5% to 38.8%) compared to that of human identification. ConclusionsWe built machine learning models to identify key influencers among Chinese MSM who were more likely to engage in secondary distribution of HIVST kits. Trial RegistrationChinese Clinical Trial Registry (ChiCTR) ChiCTR1900025433; https://www.chictr.org.cn/showproj.html?proj=42001

Tomato is the most preferred host plant for Tuta absoluta, a newly emerged devastating invasive pest in China. However, no study has evaluated the damage risk of T. absoluta on processed tomato worldwide. In the current study, the life table parameters of T. absoluta were systematically investigated on five tomato cultivars (one fresh tomato cultivar, four processed tomato cultivars) to determine their susceptibility to T. absoluta infestation. T. absoluta had a better population growth ability on the fresh tomato, “Dafen”, showing shorter duration of the preadult stage, higher lifetime fecundity, and a higher intrinsic rate of increase compared to four processed tomato cultivars. Meanwhile, the life table parameters of T. absoluta among different processed tomato cultivars also showed significant differences. Th9 was the most susceptible to T. absoluta attack, while Th1902, Heinz1015, and Dimen2272 were the least suitable ones for its development and reproduction. In summary, these tomato cultivars are the most recommended for commercial tomato production to reduce the damage caused by T. absoluta and improve the integrated pest management strategy.

In order to promote the utilization of high strength materials and application of prefabricated structures, flexural behaviour of section steel-precast UHPC (Ultra-High performance concrete) slab composite beams prefabricated with bolt shear connectors are numerically simulated by the finite element (FE) software ABAQUS. The model is verified by three prefabricated steel-concrete composite beams tested. Numerical analysis results are in good accordance with experimental results. Furthermore, parametric studies are conducted to investigate the effects of strength of section steel and concrete of precast slab, thickness of section steel, width and height of precast concrete slab, diameters of steel bars and bolt shear connectors. The flexural behaviour of composite beams, in terms of bearing capacity, deflection, ductility and energy dissipation, are compared. The numerical results indicate that the improvement of strength of section steel results in a decrease of ductility, but a significant increase of the ultimate load and energy dissipation. Compared with composite beam made of section steel with thickness of 10 mm, the ultimate load of beams made of section steel with thickness of 14 and 18 mm improve by 29.0% and 58.8%, respectively, the ductility enhance by 2.8% and 8.3%, respectively, and the energy dissipation improve by 8.0% and 12.3%, respectively. With the increase of concrete strength, the ultimate load, deflection and energy dissipation gradually increase. The ductility of steel-UHPC composite beam is the highest, that of steel-HSC composite beam is the lowest. The effect of reinforcement ratio of concrete slab and diameter of shear bolts on the ultimate load of composite beam is limited. Simplified formulae for two different sectional types of proper-reinforced section steel-precast UHPC slab composite beams occurred bending failure are proposed, and the predicted results fit well with the simulated results. The results can be taken as a reference for the design and construction of section steel-precast UHPC slab composite beams.

In order to investigate the influence of various factors on working performance, mechanical properties and durability of sustainable Reactive Powder Concrete (RPC), and make it convenient for choose more cost-effective RPC incorporating industrial byproducts. The effective parameters (water-binder ratio, contents of water reducer, replacement ratios of fly ash (FA), silica fume (SF) and slag powder (SL)) of RPCs were examined by the tests of paste fluidity, compressive and flexural strength as well as water absorption. Besides, the effect of the active mineral admixtures on pore size distribution and surface morphology of RPCs was studied by Mercury Injection Porosimeter (MIP) and Scanning electron microscope (SEM). Results indicate that an obvious reduction in the workability of RPC, enhancement of strength, and reduction in water absorption can be achieved by substituting part of the cement with silica fume. Fly ash and slag powder can be used to substitute some cement in producing RPC, and the workability is improved, meanwhile the effect of fly ash is higher than that of slag powder. However, excessive replacement of cement with slag powder or fly ash leads to a reduction of the strength in the early stage and a greater absorption of water. Increment of curing age is associated with an enhancement of strength and a decrease in water absorption. The porosity is reduced by 5.2 % when cement is partially replaced with silica fume, and the microstructure is dominated by harmless pores. When replacement of silica fume is kept at 25 %, using slag powder or fly ash substitute part of cement also reduces the number of less harmful pores. It is beneficial to add slag powder to increase the number of gel pores, whereas fly ash reduces the number of gel pores. RPC can achieve a high strength, low water absorption, and improved economy and environmental protection when silica fume replaces up to 25 % cement, slag powder or fly ash replaces up to 30 % cement. This investigation is expected to provide a practical method in the mix design and engineering application of economical and sustainable RPC.