Variations in the oxidation potential of PM2.5 in an old industrial city in China from 2015 to 2018.

PM2.5 pollution in China has decreased dramatically, but how its health effects change is not clear. There are 120 old industrial cities in China, where the sources, composition, and health effects of PM2.5 may be significantly different with other cities. Huangshi, an old industrial city in central China, underwent intense green transformations from 2015 to 2018. In this study, we collected ambient PM2.5 samples in 2015 and 2018 at an urban site in Huangshi. The average PM2.5 concentration decreased from 83.44 ± 48.04 µg/m3 in 2015 to 68.03 ± 39.41 µg/m3 in 2018. However, the average volume-normalized dithiothreitol (DTTv) of PM2.5 increased from 1.38 ± 0.45 nmol/min/m3 to 2.14 ± 1.31 nmol/min/m3 and the DTT normalized by particulate mass (DTTm) increased from 20.6 ± 10.1 pmol/min/µg to 40.07 ± 21.9 pmol/min/µg, indicating increased exposure risk and inherent toxicity. The increased toxicity of PM2.5 might be related to the increased trace elements (TEs) concentrations. The positive matrix factorization and multiple linear regression methods were employed to quantify the contributions of emission sources to PM2.5 and DTTv. The results showed that the contribution of coal combustion, industry, and dust to PM2.5 decreased significantly from 2015 to 2018, while that of vehicle emission and secondary sources increased. Despite the decreased fraction of coal combustion and industry sources, their contribution to DTTv increased slightly, which was caused by the increased intrinsic toxicity. The increased intrinsic toxicity was possibly caused by increased TEs, such as Pb, Cu, and V. Besides, the contribution of vehicle emission to DTTv also increased. Overall, these results provide valuable insights into the effectiveness of controlling strategies in reducing particulate health impacts in old industrial cities, and stress the necessity of formulating toxicity-oriented controlling strategies, with special attention to TEs from coal combustion and industry sources as well as vehicle emissions.

Hippocampal Crhr1 conditional gene knockout ameliorated the depression-like behavior and pathological damage in male offspring mice caused by chronic stress during pregnancy.

Numerous studies have demonstrated that chronic stress during pregnancy (CSDP) can induce depression and hippocampal damage in offspring. It has also been observed that high levels of corticotropin-releasing hormone (CRH) can damage hippocampal neurons, and intraperitoneal injection of a corticotropin releasing hormone receptor 1 (CRHR1) antagonist decreases depression-like behavior and hippocampal neuronal damage in a mouse depression model. However, whether CSDP causes hippocampal damage and depression in offspring through the interaction of CRH and hippocampal CRHR1 remains unknown and warrants further investigation. Therefore, hippocampal Crhr1 conditional gene knockout mice and C57/BL6J mice were used to study these questions. Depression-related indexs in male offspring mice were examined using the forced swim test (FST), sucrose preference test (SPT), tail suspension test (TST) and open field test (OFT). Serum CRH levels were measured by enzyme-linked immunosorbent assay (ELISA). Golgi-Cox staining was used to examine the morphological changes of hippocampal neuronal dendrites. Neuronal apoptosis in the hippocampal CA3 regions was detected by terminal deoxynucleotidy transferase dUTP nick end labeling (TUNEL) staining. The levels of mammalian target of rapamycin (mTOR), phosphorylated mTOR (p-mTOR) and protein kinase B (AKT) proteins were measured by Western blot analysis. This study showed that CSDP induces depression-like behavior, hippocampal neuronal dendrite damage and apoptosis in male offspring mice. Conditional gene knockout of hippocampal Crhr1 in mice reduced CSDP-induced depression-like behavior, hippocampal neuronal dendrite damage and apoptosis in male offspring, and counteracted the CSDP-induced decreased expression of p-Akt and mTOR activity in male offspring hippocampus. These findings demonstrated that CSDP might inhibit the Akt/mTOR pathway by increasing the levels of CRH, leading to increased CRH-mediated activation of hippocampal CRHR1, thereby inducing synaptic impairment and apoptosis in hippocampal neurons, which in turn leads to depression-like behavior in offspring.

Shrimp hemocyanin elicits a potent humoral response in mammals and is favorable to hapten conjugation.

Conjugation to a carrier protein is essential to give rise to the antigenicity of hapten. Three carrier proteins e.g. KLH (Keyhole Limpet hemocyanin), BSA (bovine serum albumin), and OVA (Ovalbumin) were used mostly. KLH is advantageous to the others, majorly owing to its strong immunogenicity and limited usage in other biological assays. However, the cost of obtaining Keyhole Limpet is high and the solubility of KLH is not as well as the other carriers, especially after hapten conjugation. Here, we extracted the shrimp hemocyanin (SHC) from Litopenaeus vannamei (L. vannamei), which is a commonly sea product worldwide. The high pure SHC could be acquired by two-step purification, with a production yield of > 1 g proteins (98% pure) per 1 kg shrimp. Compared to KLH, the peptide-SHC conjugates exhibit higher solubility after hapten conjugation. Meanwhile, compared with KLH, SHC induces comparable antibody production efficiency in mammals, with or without conjugation. Furthermore, rabbit polyclonal antibodies or mouse monoclonal antibodies were generated by immunizing SHC-peptide conjugates, and the subsequent antibodies were confirmed to be used in western blot, immunofluorescence and immunohistochemistry. Therefore, we demonstrated that SHC may be used as a substitute for KLH in future antibody and vaccine development.

ZIPK collaborates with STAT5A in p53-mediated ROS accumulation in hyperglycemia-induced vascular injury.

In this study we investigate the role of Zipper-interacting protein kinase (ZIPK) in high glucose-induced vascular injury, focusing on its interaction with STAT5A and its effects on p53 and inducible nitric oxide synthase (NOS2) expression. Human umbilical vein endothelial cells (HUVECs) are cultured under normal (5 mM) and high (25 mM) glucose conditions. Protein and gene expression levels are assessed by western blot analysis and qPCR respectively, while ROS levels are measured via flow cytometry. ZIPK expression is manipulated using overexpression plasmids, siRNAs, and shRNAs. The effects of the ZIPK inhibitor TC-DAPK6 are evaluated in a diabetic rat model. Our results show that high glucose significantly upregulates ZIPK, STAT5A, p53, and NOS2 expressions in HUVECs, thus increasing oxidative stress. Silencing of STAT5A reduces p53 and NOS2 expressions and reactive oxygen species (ROS) accumulation. ZIPK is essential for high glucose-induced p53 expression and ROS accumulation, while silencing of ZIPK reverses these effects. Overexpression of ZIPK combined with STAT5A silencing attenuates glucose-induced alterations in p53 and NOS2 expression, thereby preventing cell damage. Coimmunoprecipitation reveals a direct interaction between ZIPK and STAT5A in the nucleus under high-glucose condition. In diabetic rats, TC-DAPK6 treatment significantly decreases ZIPK, p53, and NOS2 expressions. Our findings suggest that ZIPK plays a critical role in high glucose-induced vascular injury via STAT5A-mediated pathways, proposing that ZIPK is a potential therapeutic target for diabetic vascular complications.

Distribution of EGFR fusions in 35,023 Chinese patients with solid tumors-the frequency, fusion partners and clinical outcome.

BACKGROUND: Epidermal growth factor receptor (EGFR) fusions are rare but potentially actionable oncogenic drivers across multiple solid tumors. However, the distribution and molecular characteristics of EGFR fusions in Chinese patients with solid malignancies have not been explored. METHODS: Panel-based next-generation sequencing (NGS) data of 35,023 patients with various types of solid tumors was collected and analyzed from the Simcere Diagnostics (Nanjing, China) database. A 9563-patient cohort was derived from The Cancer Genome Atlas (TCGA) to explore the relationship between EGFR fusion status and overall survival (OS). RESULTS: In this study, prevalence of functional EGFR fusions was 0.303% (106/35,023) in total across solid tumors, which occur more commonly in gastroesophageal junction cancer (1/61, 1.613%), followed by medulloblastoma (1/66, 1.515%) and glioma (33/2409, 1.370%). Analysis showed a prevalence for fusion partners in different tumor types. The top 3 co-mutant genes with EGFR fusion were TP53 (mutation frequency, MF: 65%), BRCA2 (MF: 43%), and ALK (MF: 41%). Furthermore, patients in the EGFR fusion group had a significantly shorter OS than those in the non-EGFR fusion group (p < 0.0001) in the TCGA cohort, suggesting that EGFR fusion might be a high-risk factor for poor prognosis. CONCLUSIONS: Our study is the first retrospective analysis of EGFR fusions in a large-scale solid tumor population, which may provide a reference for future EGFR-TKI clinical trials with EGFR fusions.

Research on the quantitative relationship of the viscosity reduction effect of large-ring cyclodextrin on potato starch during gelatinization process and mechanism analysis.

Starch is extensively used across various fields due to its renewable properties and cost-effectiveness. Nonetheless, the high viscosity that arises from gelatinization poses challenges in the industrial usage of starch at high concentrations. Thus, it's crucial to explore techniques to lower the viscosity during gelatinization. In this study, large-ring cyclodextrins (LR-CDs) were synthesized from potato starch (PS) by using 4-α-glucanotransferase and then added to PS to alleviate the increased viscosity during gelatinization. The results from rapid viscosity analyzer (RVA) demonstrated that the inclusion of 5 % (w/w) LR-CDs markedly reduced the peak viscosity (PV) and final viscosity (FV) of PS by 49.85 % and 28.17 %. In addition, there was a quantitative relationship between PV and LR-CDs. The equation was fitted as y = 2530.73×e-x/2.48+1832.79, which provided a basis for the regulation of PS viscosity. The mechanism of LR-CDs reducing the viscosity of PS was also studied. The results showed that the addition of LR-CDs inhibited the gelatinization of PS by enhancing orderliness and limiting water absorption, resulting in a decrease in viscosity. This study provides a novel method for reducing the viscosity of starch, which is helpful for increasing its concentration and reducing energy consumption in industrial applications.

Fairness in Classifying and Grouping Health Equity Information.

This paper explores the balance between fairness and performance in machine learning classification, predicting the likelihood of a patient receiving anti-microbial treatment using structured data in community nursing wound care electronic health records. The data includes two important predictors (gender and language) of the social determinants of health, which we used to evaluate the fairness of the classifiers. At the same time, the impact of various groupings of language codes on classifiers' performance and fairness is analyzed. Most common statistical learning-based classifiers are evaluated. The findings indicate that while K-Nearest Neighbors offers the best fairness metrics among different grouping settings, the performance of all classifiers is generally consistent across different language code groupings. Also, grouping more variables tends to improve the fairness metrics over all classifiers while maintaining their performance.

A pair of nuclear factor Y transcription factors act as positive regulators in jasmonate signaling and disease resistance in Arabidopsis.

The plant hormone jasmonate (JA) regulates plant growth and immunity by orchestrating a genome-wide transcriptional reprogramming. In the resting stage, JASMONATE-ZIM DOMAIN (JAZ) proteins act as main repressors to regulate the expression of JA-responsive genes in the JA signaling pathway. However, the mechanisms underlying de-repression of JA-responsive genes in response to JA treatment remain elusive. Here, we report two nuclear factor Y transcription factors NF-YB2 and NF-YB3 (thereafter YB2 and YB3) play key roles in such de-repression in Arabidopsis. YB2 and YB3 function redundantly and positively regulate plant resistance against the necrotrophic pathogen Botrytis cinerea, which are specially required for transcriptional activation of a set of JA-responsive genes following inoculation. Furthermore, YB2 and YB3 modulated their expression through direct occupancy and interaction with histone demethylase Ref6 to remove repressive histone modifications. Moreover, YB2 and YB3 physically interacted with JAZ repressors and negatively modulated their abundance, which in turn attenuated the inhibition of JAZ proteins on the transcription of JA-responsive genes, thereby activating JA response and promoting disease resistance. Overall, our study reveals the positive regulators of YB2 and YB3 in JA signaling by positively regulating transcription of JA-responsive genes and negatively modulating the abundance of JAZ proteins.

An Improvement Method for Improving the Surface Defect Detection of Industrial Products Based on Contour Matching Algorithms.

Aiming at the problems of the poor robustness and universality of traditional contour matching algorithms in engineering applications, a method for improving the surface defect detection of industrial products based on contour matching algorithms is detailed in this paper. Based on the image pyramid optimization method, a three-level matching method is designed, which can quickly obtain the candidate pose of the target contour at the top of the image pyramid, combining the integral graph and the integration graph acceleration strategy based on weak classification. It can quickly obtain the rough positioning and rough angle of the target contour, which greatly improves the performance of the algorithm. In addition, to solve the problem that a large number of duplicate candidate points will be generated when the target candidate points are expanded, a method to obtain the optimal candidate points in the neighborhood of the target candidate points is designed, which can guarantee the matching accuracy and greatly reduce the calculation amount. In order to verify the effectiveness of the algorithm, functional test experiments were designed for template building function and contour matching function, including uniform illumination condition, nonlinear condition and contour matching detection under different conditions. The results show that: (1) Under uniform illumination conditions, the detection accuracy can be maintained at about 93%. (2) Under nonlinear illumination conditions, the detection accuracy can be maintained at about 91.84%. (3) When there is an external interference source, there will be a false detection or no detection, and the overall defect detection rate remains above 94%. It is verified that the proposed method can meet the application requirements of common defect detection, and has good robustness and meets the expected functional requirements of the algorithm, providing a strong technical guarantee and data support for the design of embedded image sensors in the later stage.

High-density mapping of durable and broad-spectrum stripe rust resistance gene Yr30 in wheat.

KEY MESSAGE: The durable stripe rust resistance gene Yr30 was fine-mapped to a 610-kb region in which five candidate genes were identified by expression analysis and sequence polymorphisms. The emergence of genetically diverse and more aggressive races of Puccinia striiformis f. sp. tritici (Pst) in the past twenty years has resulted in global stripe rust outbreaks and the rapid breakdown of resistance genes. Yr30 is an adult plant resistance (APR) gene with broad-spectrum effectiveness and its durability. Here, we fine-mapped the YR30 locus to a 0.52-cM interval using 1629 individuals derived from residual heterozygous F5:6 plants in a Yaco"S"/Mingxian169 recombinant inbred line population. This interval corresponded to a 610-kb region in the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq version 2.1 on chromosome arm 3BS harboring 30 high-confidence genes. Five genes were identified as candidate genes based on functional annotation, expression analysis by RNA-seq and sequence polymorphisms between cultivars with and without Yr30 based on resequencing. Haplotype analysis of the target region identified six haplotypes (YR30_h1-YR30_h6) in a panel of 1215 wheat accessions based on the 660K feature genotyping array. Lines with YR30_h6 displayed more resistance to stripe rust than the other five haplotypes. Near-isogenic lines (NILs) with Yr30 showed a 32.94% higher grain yield than susceptible counterparts when grown in a stripe rust nursery, whereas there was no difference in grain yield under rust-free conditions. These results lay a foundation for map-based cloning Yr30.

Trends and cross-country inequalities in the global burden of osteoarthritis, 1990-2019: A population-based study.

OBJECTIVE: To evaluate the trends and cross-country inequalities of global osteoarthritis (OA) burden over the last 30 years, and further predicted its changes to 2035. METHODS: The estimates and 95 % uncertainty intervals (UIs) for incidence, prevalence, and disability-adjusted life-years (DALYs) of OA were extracted from Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. We described OA epidemiology at global, regional, and national levels, analyzed 1990-2019 trends in OA burden from overall, local, and multi-dimension scopes, decomposed OA burden according to population size, age structure, and epidemiologic changes, quantified cross-country inequalities in OA burden using standard health equity methods recommended by World Health Organization, and predicted changes of OA burden to 2035. RESULTS: GBD 2019 estimated 527,811,871 (95 % UIs: 478,667,549 to 584,793,491) prevalent cases, 41,467,542 (95 % UIs: 36,875,471 to 46,438,409) incident cases and 18,948,965 (95 % UIs: 9,571,298 to 37,659,660) DALYs cases of OA worldwide in 2019, with the highest cases in East Asia and highest age-standardized rate (ASR) in high-income North America. The global burden of OA increased overall from 1990 to 2019 with the fastest growth observed in the first decade of the 21st century. Decomposition analysis revealed that OA knee (62.78 %), women (60.47 %), and middle sociodemographic index (SDI) quintile (32.35 %) were responsible for the most significant DALYs, whose changes were primarily driven by population growth and aging. A significant increase in SDI-related inequalities was detected, and the gap in DALYs between the highest SDI country and the lowest SDI country increased from 179.5 [95 % confidence interval (CI): 149.3-209.8] per 100,000 in 1990 to 341.9 (95 % CI: 309.5-374.4) per 100,000 in 2019. Notably, although the ASR of incidence, prevalence, and DALYs of OA was predicted to decrease annually from 2020 to 2035, the case number of these metrics was predicted to keeping increasing, with predicted values of 52,870,737 [95 % credible interval (Crl): 39,330,063 to 66,411,411], 727,532,373 (95 % Crl: 542,765,783 to 912,298,962), and 25,986,983 (95 % Crl: 19,216,928 to 32,757,038) in 2035, respectively. CONCLUSIONS: As a major public health issue, the global burden of OA showed an overall increasing trend from 1990 to 2019, which was primarily driven by population growth and aging. Countries with high SDI shouldered disproportionately high OA burden, and the SDI-related inequalities across countries exacerbated over time. This study highlighted great challenges in the control and management of OA, including both growing case number and distributive inequalities worldwide, which may be instructive for better making public health policy and reasonably allocating medical source.

MMGPL: Multimodal Medical Data Analysis with Graph Prompt Learning.

Prompt learning has demonstrated impressive efficacy in the fine-tuning of multimodal large models to a wide range of downstream tasks. Nonetheless, applying existing prompt learning methods for the diagnosis of neurological disorder still suffers from two issues: (i) existing methods typically treat all patches equally, despite the fact that only a small number of patches in neuroimaging are relevant to the disease, and (ii) they ignore the structural information inherent in the brain connection network which is crucial for understanding and diagnosing neurological disorders. To tackle these issues, we introduce a novel prompt learning model by learning graph prompts during the fine-tuning process of multimodal models for diagnosing neurological disorders. Specifically, we first leverage GPT-4 to obtain relevant disease concepts and compute semantic similarity between these concepts and all patches. Secondly, we reduce the weight of irrelevant patches according to the semantic similarity between each patch and disease-related concepts. Moreover, we construct a graph among tokens based on these concepts and employ a graph convolutional network layer to extract the structural information of the graph, which is used to prompt the pre-trained multimodal models for diagnosing neurological disorders. Extensive experiments demonstrate that our method achieves superior performance for neurological disorder diagnosis compared with state-of-the-art methods and validated by clinicians.

Mendelian Randomization Analysis of Circulating Cytokines and Risk of Autoimmune Neuroinflammatory Diseases.

Background: Cytokines act a vital role in autoimmune neuroinflammatory diseases (ANDs) with undetermined causal relationships. Mendelian randomization (MR) analysis was performed to estimate the causal effects of circulating levels of cytokines on the risk of ANDs. Methods: The causal relationship between 34 circulating cytokines and 4 kinds of ANDs, including multiple sclerosis (MS), neuromyelitis optica (NOM), chronic inflammatory demyelinating polyneuropathy (CIDP) and myasthenia gravis (MG) were explored using four methods of MR analysis. MR-PRESSO, MR-Egger regression methods and Cochran's Q statistic were utilized to identify the instrumental variables (IVs) with potential pleiotropy and heterogeneity. The Bonferroni correction was used for multiple group comparisons. P-value less than 3.68E-04 (0.05/ (34*4)) was considered statistically significant. Results: Negative causal effects of circulating levels of interleukin (IL)-8 (OR = 0.648, 95% CI: 0.494-0.851, P = 0.002) on risk of MS, chemokine (C-C Motif) ligand (CCL)-5 (OR = 0.295, 95% CI: 0.103-0.841, P = 0.022) and stem cell growth factor-beta (SCGF-ß) (OR = 0.745, 95% CI: 0.565-0.984, P = 0.038) on risk of CIDP, as well as positive causal effects of circulating levels of IL-2 receptor α (IL-2Rα) (OR = 1.216, 95% CI: 1.120-1.320, P = 3.20E-06) and chemokine C-X-C motif ligand (CXCL)-10 (OR = 1.404, 95% CI: 1.094-1.803, P = 0.008) on MS were observed. Nevertheless, only IL-2Rα still had a causal effect on MS after Bonferroni correction. Conclusion: The results identify a genetically predicted causal effect of IL-2Rα, IL-8 and CXCL-10 on MS, CCL-5 and SCGF-ß on CIDP.

Structural elucidation and functional characteristics of novel potential prebiotics produced from Limosilactobacillus reuteri N1 GtfB-treated maize starches.

The recently characterized Limosilactobacillus reuteri N1 GtfB (LrN1 GtfB) from glycoside hydrolase family 70 is a novel 4,6-α-glucanotransferase acting on starch/maltooligosaccharides with high enzyme activity and soluble protein yield (in heterogenous system). In this study, the influence of the treatment by LrN1 GtfB on the fine structure and functional characteristics of three maize starches were furtherly investigated and elucidated. Due to the treatment of LrN1 GtfB, the starch molecules were transformed into reuterans containing linear and branched (α1 â†’ 6) linkages with notably smaller molecular weight and shorter chain length. Moreover, the (α1 â†’ 6) linkage ratios in the GtfB-modified high-amylose maize starch (GHMS)/normal maize starch (GNMS)/waxy maize starch (GWMS) increased by 18.3 %/12.6 %/9.0 % as compared to their corresponding controls. In vitro digestibility experiment revealed that the resistant starch content of GHMS, GNMS and GWMS increased by 16 %, 18 % and 25 % as compared to the starch substrates. Furthermore, the butyric acid yielded from GHMS, GNMS and GWMS in the in vitro fermentation experiments were 1.4, 1.5 and 1.4 times higher than those of commercial galactose oligosaccharides. These results indicated that the highly-branched short-clustered reuteran synthesized by LrN1 GtfB might serve as novel potential prebiotics, and provide insights for the synthesis of promising prebiotic dietary fiber from starch.

CCSI: Continual Class-Specific Impression for data-free class incremental learning.

In real-world clinical settings, traditional deep learning-based classification methods struggle with diagnosing newly introduced disease types because they require samples from all disease classes for offline training. Class incremental learning offers a promising solution by adapting a deep network trained on specific disease classes to handle new diseases. However, catastrophic forgetting occurs, decreasing the performance of earlier classes when adapting the model to new data. Prior proposed methodologies to overcome this require perpetual storage of previous samples, posing potential practical concerns regarding privacy and storage regulations in healthcare. To this end, we propose a novel data-free class incremental learning framework that utilizes data synthesis on learned classes instead of data storage from previous classes. Our key contributions include acquiring synthetic data known as Continual Class-Specific Impression (CCSI) for previously inaccessible trained classes and presenting a methodology to effectively utilize this data for updating networks when introducing new classes. We obtain CCSI by employing data inversion over gradients of the trained classification model on previous classes starting from the mean image of each class inspired by common landmarks shared among medical images and utilizing continual normalization layers statistics as a regularizer in this pixel-wise optimization process. Subsequently, we update the network by combining the synthesized data with new class data and incorporate several losses, including an intra-domain contrastive loss to generalize the deep network trained on the synthesized data to real data, a margin loss to increase separation among previous classes and new ones, and a cosine-normalized cross-entropy loss to alleviate the adverse effects of imbalanced distributions in training data. Extensive experiments show that the proposed framework achieves state-of-the-art performance on four of the public MedMNIST datasets and in-house echocardiography cine series, with an improvement in classification accuracy of up to 51% compared to baseline data-free methods. Our code is available at https://github.com/ubc-tea/Continual-Impression-CCSI.

MSGM: An Advanced Deep Multi-Size Guiding Matching Network for Whole Slide Histopathology Images Addressing Staining Variation and Low Visibility Challenges.

Matching whole slide histopathology images to provide comprehensive information on homologous tissues is beneficial for cancer diagnosis. However, the challenge arises with the Giga-pixel whole slide images (WSIs) when aiming for high-accuracy matching. Learning-based methods are difficult to generalize well with large-size WSIs, necessitating the integration of traditional matching methods to enhance accuracy as the size increases. In this paper, we propose a multi-size guiding matching method applicable high-accuracy requirements. Specifically, we design learning multiscale texture to train deep descriptors, called TDescNet, that trains 64 ×64×256 and 256 ×256×128 size convolution layer as C64 and C256 descriptors to overcome staining variation and low visibility challenges. Furthermore, we develop the 3D-ring descriptor using sparse keypoints to support the description of large-size WSIs. Finally, we employ C64, C256, and 3D-ring descriptors to progressively guide refined local matching, utilizing geometric consistency to identify correct matching results. Experiments show that when matching WSIs of size 4096×4096 pixels, our average matching error is 123.48 [Formula: see text] and the success rate is 93.02 % in 43 cases. Notably, our method achieves an average improvement of 65.52 [Formula: see text] in matching accuracy compared to recent state-of-the-art methods, with enhancements ranging from 36.27 [Formula: see text] to 131.66 [Formula: see text]. Therefore, we achieve high-fidelity whole-slice image matching, and overcome staining variation and low visibility challenges, enabling assistance in comprehensive cancer diagnosis through matched WSIs.

Halogenated Dibenzo[f,h]quinoxaline Units Constructed 2D-Conjugated Guest Acceptors for 19% Efficiency Organic Solar Cells.

Halogenation of Y-series small-molecule acceptors (Y-SMAs) is identified as an effective strategy to optimize photoelectric properties for achieving improved power-conversion-efficiencies (PCEs) in binary organic solar cells (OSCs). However, the effect of different halogenation in the 2D-structured large π-fused core of guest Y-SMAs on ternary OSCs has not yet been systematically studied. Herein, four 2D-conjugated Y-SMAs (X-QTP-4F, including halogen-free H-QTP-4F, chlorinated Cl-QTP-4F, brominated Br-QTP-4F, and iodinated I-QTP-4F) by attaching different halogens into 2D-conjugation extended dibenzo[f,h]quinoxaline core are developed. Among these X-QTP-4F, Cl-QTP-4F has a higher absorption coefficient, optimized molecular crystallinity and packing, suitable cascade energy levels, and complementary absorption with PM6:L8-BO host. Moreover, among ternary PM6:L8-BO:X-QTP-4F blends, PM6:L8-BO:Cl-QTP-4F obtains a more uniform and size-suitable fibrillary network morphology, improved molecular crystallinity and packing, as well as optimized vertical phase distribution, thus boosting charge generation, transport, extraction, and suppressing energy loss of OSCs. Consequently, the PM6:L8-BO:Cl-QTP-4F-based OSCs achieve a 19.0% efficiency, which is among the state-of-the-art OSCs based on 2D-conjugated Y-SMAs and superior to these devices based on PM6:L8-BO host (17.70%) and with guests of H-QTP-4F (18.23%), Br-QTP-4F (18.39%), and I-QTP-4F (17.62%). The work indicates that halogenation in 2D-structured dibenzo[f,h]quinoxaline core of Y-SMAs guests is a promising strategy to gain efficient ternary OSCs.

The mediation effects of malalignment on the relation of sex to the risk of incidence tibiofemoral osteoarthritis.

OBJECTIVE: To investigate to what extent the higher risk of tibiofemoral radiographic osteoarthritis (TFROA) in females vs. males can be explained by knee malalignment. DESIGN: Using data from Multicenter Osteoarthritis Study (MOST) and Osteoarthritis Initiative (OAI), we examined the relation of sex to the incident medial and lateral TFROA and performed mediation analyses to assess to what extent varus and valgus malalignments account for sex differences in the incident medial or lateral TFROA. RESULTS: Of the 3462 knees without medial and lateral TFROA in MOST, the 7-year risks of medial and lateral TFROA were 16.9% and 10.0% in females, and 15.8% and 4.2% in males, respectively. Females had 2.31-fold (95% confidence interval [95% CI]: 1.73 to 3.08) higher incident lateral TFROA than males, and the relative risk (RR) of the indirect effect of sex on lateral TFROA through valgus malalignment was 1.15 (95% CI: 1.09 to 1.20), accounting for 23% of its total effect on lateral TFROA. In OAI (n = 3095 knees), females had 1.54-fold (95% CI: 1.15 to 2.04) higher incident lateral TFROA than males, and RR of the indirect effect of sex on lateral TFROA through valgus malalignment was 1.10 (95% CI: 1.04 to 1.21), accounting for 26% of its total effect on lateral TFROA. No apparent sex difference in the incident medial TFROA was found in MOST (RR = 1.05, 95% CI: 0.89 to 1.25) or OAI (RR = 1.02, 95% CI: 0.84 to 1.19). CONCLUSION: Females had a higher risk of developing lateral TFROA than males; however, valgus malalignment only modestly explained such a difference.

Capture and Storage of Cell-Free DNA via Bio-Informational Hydrogel Microspheres.

Excessive cell-free DNA (cfDNA) can induce chronic inflammation by activating intracellular nucleic acid sensors. Intervention in cfDNA-mediated "pro-inflammatory signaling transduction" could be a potential alleviating strategy for chronic inflammation, such as in diabetic wounds. However, effectively and specifically downgrading cfDNA concentration in the pathological microenvironment remains a challenge. Therefore, this work prepares free-standing polydopamine nanosheets through DNA-guided assembly and loaded them into microfluidic hydrogel microspheres. The π─π stacking/hydrogen bonding interactions between polydopamine nanosheets and the π-rich bases of cfDNA, along with the cage-like spatial confinement created by the hydrogel polymer network, achieved cfDNA capture and storage, respectively. Catechol in polydopamine nanosheets can also assist in reducing reactive oxygen species (ROS) levels. Efficient cfDNA binding independent of serum proteins, specific interdiction of abnormal activation of cfDNA-associated toll-like receptor 9, as well as down-regulation of inflammatory cytokines and ROS levels are shown in this system. The chronic inflammation alleviating and the pro-healing effects on the mice model with diabetic wounds are also investigated. This work presents a new strategy for capturing and storing cfDNA to intervene in cell signaling transduction. It also offers new insights into the regulatory mechanisms between inflammatory mediators and biomaterials in inflammation-related diseases.

Ammonia stripping by in situ biogas self-circulation to upgrade continuous thermophilic and mesophilic digestion of hydrothermal high-solid sludge.

High-solid anaerobic digestion of hydrothermal sewage sludge has been developed. In order to upgrade the process by focusing on ammonia inhibition, a simply-equipped stripping system without additional alkali or heat supply was introduced by in situ biogas self-circulation. As the determined limit of total ammonia nitrogen at 1500 mg/L and 1000 mg/L for the mesophilic (MAD) and thermophilic anaerobic digestion (TAD) respectively and stripping rate at 5 L/min, continuous MAD and TAD was conducted in parallel. The stripping system successfully polished up the ammonia inhibition, and methanogenic capability of the TAD was promoted to approximately 90.0 % of the potential. Intermittent stripping mode proved usable. More frequent stripping was inevitable for the TAD as compared to the MAD. Hydraulic retention time below 20 d resulted in failure of the stripping mode due to rapid ammonia generation. Overall, this technology was practical in upgrading high-solid sludge digestion by effective ammonia control.