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Abstract Hyperspectral images (HSIs) contain rich spectral and spatial information, motivating the development of a novel circulant singular spectrum analysis (CiSSA) and multiscale local ternary pattern fusion method for joint spectral-spatial feature extraction and classification. Due to the high dimensionality and redundancy in HSIs, principal component analysis (PCA) is used during preprocessing to reduce dimensionality and enhance computational efficiency. CiSSA is then applied to the PCA-reduced images for robust spatial pattern extraction via circulant matrix decomposition. The spatial features are combined with the global spectral features from PCA to form a unified spectral-spatial feature set (SSFS). Local ternary pattern (LTP) is further applied to the principal components (PCs) to capture local grayscale and rotation-invariant texture features at multiple scales. Finally, the performance of the SSFS and multiscale LTP features is evaluated separately using a support vector machine (SVM), followed by decision-level fusion to combine results from each pipeline based on probability outputs. Experimental results on three popular HSIs show that, under 1% training samples, the proposed method achieves 95.98% accuracy on the Indian Pines dataset, 98.49% on the Pavia University dataset, and 92.28% on the Houston2013 dataset, outperforming several traditional classification methods and state-of-the-art deep learning approaches.

In hyperspectral image (HSI) classification, convolutional neural networks (CNNs) are widely used due to their ability to leverage the rich spectral information across multiple bands. However, HSI classification still faces various challenges, including insufficient spectral-spatial representation, excessive redundant information, and difficulties in effectively integrating features of different scales, etc., which may lead to reduced classification accuracy. In order to reduce the computational cost and improve the classification accuracy of land cover categories, an efficient spectral-spatial fusion method (ESSF) is proposed, which is based on the following modules: a multiscale feature fusion module (MSFFM), an efficient adaptive spectral-spatial feature extraction module (EASSFEM), and a context-aware fusion network (CFN). First, the MSFFM utilizes CNNs to extract and fuse features from various scales to comprehensively capture detailed spectral information in HSIs. Second, the EASSFEM dynamically adjusts the feature extraction process to optimize the fusion and representation of spectral-spatial features. In addition, it incorporates an adaptive attention mechanism to enhance the focus on relevant spectral-spatial features. Finally, the CFN enhances the model's ability to understand contextual relationships within the images, thereby improving classification accuracy. Extensive experiments conducted on four public datasets (Houston2013, Botswana, WHU-Hi-HanChuan and WHU-Hi-HongHu) demonstrate that the proposed ESSF method significantly outperforms nine other state-of-the-art methods in terms of classification accuracy.

Purpose Radiotherapy (RT) is the primary treatment for prostate cancer (PCa); however, the emergence of castration-resistant prostate cancer (CRPC) often leads to treatment failure and cancer-related deaths. In this study, we aimed to explore the use of microwave hyperthermia (MW-HT) to sensitize PCa to RT and investigate the underlying molecular mechanisms.Methods We developed a dedicated MW-HT heating setup, created an in vitro and in vivo MW-HT + RT treatment model for CRPC. We evaluated PC3 cell proliferation using CCK-8, colony experiments, DAPI staining, comet assay and ROS detection method. We also monitored nude mouse models of PCa during treatment, measured tumor weight, and calculated the tumor inhibition rate. Western blotting was used to detect DNA damage repair protein expression in PC3 cells and transplanted tumors.Results Compared to control, PC3 cell survival and clone formation rates decreased in RT + MW-HT group, demonstrating significant increase in apoptosis, ROS levels, and DNA damage. Lower tumor volumes and weights were observed in treatment groups. Ki-67 expression level was reduced in all treatment groups, with significant decrease in RT + MW-HT groups. The most significant apoptosis induction was confirmed in RT + MW-HT group by TUNEL staining. Protein expression levels of DNA-PKcs, ATM, ATR, and P53/P21 signaling pathways significantly decreased in RT + MW-HT groups.Conclusion MW-HT + RT treatment significantly inhibited DNA damage repair by downregulating DNA-PKcs, ATM, ATR, and P53/P21 signaling pathways, leading to increased ROS levels, aggravate DNA damage, apoptosis, and necrosis in PC3 cells, a well-established model of CRPC.

BackgroundChinese patent medicines are specialty preparations in China that are produced using traditional prescriptions processed by modern pharmaceutical technology. They contain complex ingredients and much attention is paid to their clinical safety. Demonstrating the clinical safety of Chinese patent medicines containing toxic ingredients in modern pharmacological studies has become one of the urgent issues to be solved for the safe use of clinical medicines.ObjectivesThe aim of this research is to evaluate the safety of Chinese patent medicines containing toxic ingredients by applying the risk-benefit assessment method. Additionally, a database of ‘toxic ingredients–toxic Chinese herbal medicines-adverse reactions’ will be established to explore the relationship between toxic ingredients and adverse reactions. This will lay the foundation for the rational clinical use of Chinese patent medicines containing toxic ingredients.Methods1) Establish a database of ‘toxic Chinese herbal medicines–toxic ingredients–toxic Chinese patent medicines’ to count the Chinese patent medicines containing toxic ingredients in the 2020 edition of Chinese Pharmacopoeia. 2) Filtered the clinical studies, extracted the drug-related ADEs, and analyzed the characteristics and correlations of these ADEs. 3) Finally, this section summarizes the causes of ADEs related to Chinese patent medicines containing toxic ingredients and extracts the main risk factors to provide a reference for further study.Outcomes1) There are four main types of Chinese patent medicines containing toxic ingredients. These include medicines with diester aconitine metabolites, mineral composition, Araceae metabolites, and hydrogen cyanide. 2) Digestive system, skin and its appendages, and allergic reactions were the main types of ADEs related to four types of Chinese patent medicines containing toxic ingredients. 3) There are four primary risk factors associated with the clinical use of Chinese patent medicines containing toxic ingredients: medicine, medication, individual and regulatory factors.

Introduction: Tripterygium species have been traditionally used in Chinese medicine for treating various conditions. The aim of the study was to construct a drug-modified renal infarction targeting liposome (rTor-LIP) containing Tripterygium in order to improve the therapeutic effect on renal injury.Methods: rTor-LIP was prepared using the extruder method containing Tripterygium solution. The preparation was characterized by transmission electron microscopy, Marvin laser particle size analyzer, and Western blotting. In vitro experiments were conducted to verify the biocompatibility of rTor-LIP, and in vivo experiments were conducted to verify the therapeutic effect of rTor- LIP on renal injury.Results and discussion: The surface of rTor-LIP was regular and oval. In vitro results showed that after co-incubation with rTor-LIP, endothelial cells did not show significant apoptosis, and there were no significant abnormalities in the mitochondrial metabolism. The in vivo results showed that the morphology of endothelial cells in the rTor-LIP group was uniform and the cytoplasmic striations were clear, but the local striations had disappeared. Thus, rTor-LIP nano-targeted liposomes can effectively target hypoxic kidney tissue, providing a new idea for the treatment of renal infarction.

AbstractLudwigia adscendens (L.) Hara, 1953 (L. adscendens) belongs to the family Onagraceae, which is a traditional medicinal plant distributed worldwide. In this study, the first complete chloroplast genome of L. adscendens was sequenced and assembled. The assembled chloroplast genome of L. adscendens is 159,560 bp in length, containing a pair of inverted repeat region A (IRA) of 24,762 bp, inverted repeat region B (IRB) of 24,762 bp, separated by a large single-copy (LSC) sequence of 90,276 bp and a small single-copy (SSC) region of 19, 760 bp, respectively. A total of 129 genes were annotated in the entire chloroplast genome, consisting of 37 transfer RNA (tRNA) genes, 8 ribosomal RNA (rRNA) genes, and 84 protein-coding genes, with a total GC content of 37.27%. The phylogenomic analysis showed that L. adscendens was closely related to L. octovalvis in the Onagraceae family. Further evolutionary studies of the genus Ludwigia could benefit from the complete chloroplast genome of L. adscendens present in this study and the obtained results would provide useful information for future phylogenetic, taxonomic, and evolutionary studies on Onagraceae.

ABSTRACTIn this paper, a multi-strategy fusion (MSF) framework, based on improved MBLBP and bi-exponential edge-preserving smoother (BEEPS), is proposed for hyperspectral image (HSI) classification. First, MBLBP operator is adopted to characterize the overall structural information of HSI, where the averaging strategy allocates same weights for the pixels in a local sub-region, so that the edges tend to be blurred due to being isotropic. To solve this question, the steering kernel is first introduced into MBLBP for learning the local structure prior of HSI. Then, a support vector machine classifier is used to calculate the soft classified probabilities of pixels. Furthermore, BEEPS is adopted to smooth the soft classified probabilities maps in the post-processing stage, and the purpose is to further improve classification accuracy of HSI by considering context-aware information for each class label. Experiments are performed on three real hyperspectral datasets, namely, Indian Pines, KSC, and Houston 2013, only 1%, 6, and 5 labeled samples are randomly selected for training, the overall accuracy(kappa) obtained by MSF is 99.47%(99.40), 99.52%(99.47), and 94.25%(93.78), respectively, which is far better than the contrast methods.

Diabetic nephropathy (DN) is one of the most common and intractable microvascular complications of diabetes worldwide, serving as the main cause of terminal renal disease. Due to the lack of early specific symptoms and diagnostic markers, DN severely threatens the sufferer’s life. MicroRNA-192 (miR-192) was early identified in human renal cortical tissue and stored and excreted in urine as microvesicles. MiR-192 was found to be involved in the development of DN. For the first time, the present review summarized all the current evidence on the topic of the roles of miR-192 in DN. Finally, 28 studies (ten clinical trials and eighteen experimental studies) were eligible for thorough reviewing. Most of the clinical trials (7/10, 70%) indicated miR-192 might be a protective factor for DN development and progression, while the majority of experimental studies (14/18, 78%) suggested miR-192 might be a pathogenic factor for DN. Mechanistically, miR-192 interacts with various direct targeted proteins (i.e., ZEB1, ZEB2, SIP1, GLP1R, and Egr1) and signaling cascades (i.e., SMAD/TGF-β and PTEN/PI3K/AKT), together contribute to the pathogenesis of DN through epithelial-to-mesenchymal transition (EMT), extracellular matrix deposition, and fibrosis formation. The current review highlights the dual role of miR-192 in the development of DN. Low serum miR-192 expression could be applied for the early prediction of DN (the early stage of DN), while the high miR-192 level in renal tissues and urine may imply the progression of DN (the late stage of DN). Further investigations are still warranted to illustrate this inconsistent phenomenon, which may facilitate promoting the therapeutic applications of miR-192 in predicting and treating DN.

ABSTRACT The 2019 coronavirus disease pandemic and distrust for popular media have highlighted the need for effective methods of direct communication of biomedical science to the public. It is presently unclear how well nonexperts can learn from primary scientific sources and what factors predict such learning in the general public. The present study examined three modalities for learning about biomedical science directly from study investigators: primary scientific articles, annotated primary scientific articles presented online with interactive learning features, and TEDTalks about scientific studies presented by a study investigator. Each modality presented the same study, “Sleep Drives Metabolite Clearance from the Adult Brain” (L. Xie, H. Kang, Q. Chen, Y. Liao, et al., Science 342:373–377, 2013, https://doi.org/10.1126/science.1241224). Knowledge about the study’s scientific content was assessed before and after the randomly assigned learning modality using multiple-choice questions. Participants included a sample of college psychology students and a sample of community-dwelling older adults. Cognitive tests were used to assess individual differences in working memory, processing speed, science literacy, and semantic knowledge. Surveys were used to assess trust in science and scientists, attitudes toward science, and attitudes toward cognitive tasks. Results indicated that both younger and older adults can learn basic biomedical science from a primary source. Knowledge gains were observed in all three learning modalities with no evidence of age group differences. Notably, the largest learning gains for undergraduates and older adults were observed in the primary scientific article condition, followed by the TEDTalk, and the annotated paper. Baseline knowledge about the science study topic and adoption of “scientific attitudes” (e.g., open-mindedness) predicted learning across age groups and learning modalities. These findings suggest that science educators, communicators, and outreach professionals should consider methods of promoting science literacy in the general public through direct access to primary scientific sources.

Anthracyclines resistance is commonly seen in patients with estrogen receptor α (ERα) positive breast cancer. Epithelial-mesenchymal transition (EMT), which is characterized with the loss of epithelial cell polarity, cell adhesion and acquisition of new invasive property, is considered as one of the mechanisms of chemotherapy-induced drug resistance. In order to identify factors that associated with doxorubicin resistance, we performed in vitro and in vivo experiments using human and mouse breast cancer cell lines with different ERα status. Cell survival experiments revealed that ERα-positive cells (MCF-7 and MCF-7/ADR cell lines), were less sensitive to doxorubicin than ERα-negative (MDA-MB-231, MDA-MB-468) cells, and mouse mammary carcinoma cells (4T-1). The expression of E-cadherin reduced in low-invasive ERα-positive MCF-7 cells after treatment with doxorubicin, indicating epithelial mesenchymal transition. In contrast, the expression of E-cadherin was upregulated in high-invasive ERα-negative cells, showing mesenchymal-epithelial transition (MET). Moreover, it was found that the growth inhibition of 4T-1 cells by doxorubicin was positively correlated with the expression of E-cadherin. In a mouse breast cancer xenograft model, E-cadherin was overexpressed in the primary tumor tissues of the doxorubicin-treated mice. In ERα-positive MCF-7 cells, doxorubicin treatment upregulated the expression of EMT-related transcription factors Snail and Twist, that regulate the expression of E-cadherin. Following overexpression of ERα in ERα-negative cells (MDA-MB-231 and MDA-MB-468), doxorubicin enhanced the upregulation of Snail and Twist, decreased expression of E-cadherin, and decreased the sensitivity of cells to doxorubicin. In contrast, inhibition of ERα activity increased the sensitivity to doxorubicin in ERα-positive MCF-7 cells. These data suggest that the regulation of Snail and/or Twist varies depends on different ERα status. Therefore, doxorubicin combined with anti-estrogen receptor α therapy could improve the treatment efficacy of doxorubicin in ERα-positive breast cancer.

Cavitation is a phenomenon that occurs during the continuous operation of a hydro turbine that directly affects the efficiency and working capacity of the unit. This paper proposes an innovative classification paradigm that uses deep learning-based methodologies in order to identify both cavitation noise signal and non-cavitation noise signal that will help prevent the damage or breakage in the earliest possible time to avoid more irreversible and irreparable damage to the hydro turbine. The stacked sparse autoencoder (SSA) nuclear framework is utilized to learn more abstract and invariant high-level features from the multiple feature sets. Then, the method on minimum redundancy maximum relevance (mRMR) selection is used to evaluate and sort out all the characteristics found by the stacked sparse autoencoder. Finally, the random forest (RF) classifier algorithm is employed to perform supervised fine-tuning and classification. The traditional supervised learning models such as support vector machine, logistic regression, and sparse representation classification are chosen to be used as contrast algorithms. SSA-mRMR-RF generally produces a better performance than the support vector machine, logistic regression and sparse representation classification when used in the same set of features. The SSA-mRMR-RF produced the highest overall average accuracy since it reached 93.18%. The SSA-mRMR-RF offers a 3.85% higher overall accuracy than the support vector machine. It also offers a 2.44% higher overall accuracy than logistic regression. In addition, it also offers a 20.30% higher overall accuracy than the sparse representation classification on the average. When the signals are divided into three categories, the highest overall accuracy decreased to 71.88%, and the classification accuracy of incipient noise signals is very low. Therefore, this paper proposes the models of power spectral-SSA-mRMR-RF and fast Fourier transform-SSA-mRMR-RF to be used, and these discoveries are based on the frequency characteristics of the cavitation noise signal. The highest overall accuracy rebound went back to 88.97% based on the power spectrum, and 96.05% based on fast Fourier transform. The corresponding experimental results found on the four data sets of the different operating conditions demonstrate that the proposed methods for discovering the extent of cavitation outperforms these traditional alternatives.

Abstract Background Oridonin, the major terpene found in Rabdosia rubescens (Henmsl.) Hara, is widely used as a dietary supplement and therapeutic drug. Oridonin has been proven to possess good anti-tumour activity, but little is known about its effect on angiogenesis. The aim of this study was to investigate the antiangiogenic effects of oridonin in vivo and in vitro and prove that oridonin anti-tumour activity is based on suppressing angiogenesis. Methods In vitro, the antiangiogenesis effect was studied by proliferation, apoptosis, migration, invasion, and tube formation experiments on human umbilical vascular endothelial cells (HUVECs). In vivo, using the Tg (fli1: GFP) zebrafish model, the embryonic vasculogenesis and postnatal regeneration were evaluated. The vascular endothelial growth factor (VEGF) signalling pathway gene expressions were assessed by reverse transcription-polymerase chain reaction (RT-PCR). Furthermore, the inhibition effects on tumour growth and metastasis were observed using a xenograft zebrafish tumour model and xenograft nude mouse tumour model. Angiogenesis was assayed by immunostaining with cluster of differentiation 31. Importantly, the proteins were identified as being differentially expressed in an in vivo model by two-dimensional electrophoresis-mass spectrometry (2D–MS) and western blot (WB). Results The results indicated that oridonin inhibited HUVEC proliferation, migration, invasion, and tube formation and induced cell apoptosis. Oridonin inhibited zebrafish angiogenesis during embryonic development and tail fin regeneration. RT-PCR showed that oridonin decreased the VEGFA, VEGFR2, and VEGFR3 expressions in zebrafish, while the TP53 expression increased. Moreover, oridonin had strong effects on tumour growth and metastasis in vivo. 2D–MS identified a total of 50 proteins differentially expressed (17 up-expressed, 28 down-expressed). Lastly, WB showed that Claudin 1, Claudin 4, and Claudin 7 were closely related to tumour growth and metastasis. Conclusion This study demonstrated that oridonin could inhibit tumour growth and metastasis, which mainly based on oridonin antiangiogenic effects. Claudin 1, Claudin 4, and Claudin 7 were the main contributors to the mechanism.

It is of great interest in exploiting spectral-spatial information for hyperspectral image (HSI) classification at different spatial resolutions. This paper proposes a new spectral-spatial deep learning-based classification paradigm. First, pixel-based scale transformation and class separability criteria are employed to measure appropriate spatial resolution HSI, and then we integrate the spectral and spatial information (i.e., both implicit and explicit features) together to construct a joint spectral-spatial feature set. Second, as a deep learning architecture, stacked sparse autoencoder provides strong learning performance and is expected to exploit even more abstract and high-level feature representations from both spectral and spatial domains. Specifically, random forest (RF) classifier is first introduced into stacked sparse autoencoder for HSI classification, based on the fact that it provides better tradeoff among generalization performance, prediction accuracy and operation speed compared to other traditional procedures. Experiments on two real HSIs demonstrate that the proposed framework generates competitive performance.

Abstract The Grey Wolf Optimization (GWO) algorithm is acknowledged as an effective method for rock acoustic emission localization. However, the conventional GWO algorithm encounters challenges related to solution accuracy and convergence speed. To address these concerns, this paper develops a Simplex Improved Grey Wolf Optimizer (SMIGWO) algorithm. The randomly generating initial populations are replaced with the iterative chaotic sequences. The search process is optimized using the convergence factor optimization algorithm based on the inverse incomplete Г function. The simplex method is utilized to address issues related to poorly positioned grey wolves. Experimental results demonstrate that, compared to the conventional GWO algorithm-based AE localization algorithm, the proposed algorithm achieves a higher solution accuracy and showcases a shorter search time. Additionally, the algorithm demonstrates fewer convergence steps, indicating superior convergence efficiency. These findings highlight that the proposed SMIGWO algorithm offers enhanced solution accuracy, stability, and optimization performance. The benefits of the SMIGWO algorithm extend universally across various materials, such as aluminum, granite, and sandstone, showcasing consistent effectiveness irrespective of material type. Consequently, this algorithm emerges as a highly effective tool for identifying acoustic emission signals and improving the precision of rock acoustic emission localization.

Abstract Background Intratumor heterogeneity (ITH) is a key biological characteristic of gliomas. This study aimed to characterize ITH in adult-type diffuse gliomas and assess the feasibility of using habitat imaging based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) to preoperatively predict isocitrate dehydrogenase (IDH) genotypes and prognosis. Methods Sixty-three adult-type diffuse gliomas with known IDH genotypes were enrolled. Volume transfer constant (Ktrans) and apparent diffusion coefficient (ADC) maps were acquired from DCE-MRI and DWI, respectively. After tumor segmentation, the k-means algorithm clustered Ktrans and ADC image voxels to generate spatial habitats and extract quantitative image features. Receiver operating characteristic (ROC) curves and area under the curve (AUC) were used to evaluate IDH predictive performance. Multivariable logistic regression models were constructed and validated using leave-one-out cross-validation, and the contrast-enhanced subgroup was analyzed independently. Kaplan-Meier and Cox proportional hazards regression analyses were used to investigate the relationship between tumor habitats and progression-free survival (PFS) in the two IDH groups. Results Three habitats were identified: Habitat 1 (hypo-vasopermeability and hyper-cellularity), Habitat 2 (hypo-vasopermeability and hypo-cellularity), and Habitat 3 (hyper-vasopermeability). Compared to the IDH wild-type group, the IDH mutant group exhibited lower mean Ktrans values in Habitats 1 and 2 (both P

Abstract Coronavirus disease 2019 (COVID-19) presents a wide spectrum of symptoms, the causes of which remain poorly understood. This study explored the associations between autoantibodies (AABs), particularly those targeting G protein-coupled receptors (GPCRs) and renin‒angiotensin system (RAS) molecules, and the clinical manifestations of COVID-19. Using a cross-sectional analysis of 244 individuals, we applied multivariate analysis of variance, principal component analysis, and multinomial regression to examine the relationships between AAB levels and key symptoms. Significant correlations were identified between specific AABs and symptoms such as fever, muscle aches, anosmia, and dysgeusia. Notably, anti-AGTR1 antibodies, which contribute to endothelial glycocalyx (eGC) degradation, a process reversed by losartan, have emerged as strong predictors of core symptoms. AAB levels increased with symptom accumulation, peaking in patients exhibiting all four key symptoms. These findings highlight the role of AABs, particularly anti-AGTR1 antibodies, in determining symptom severity and suggest their involvement in the pathophysiology of COVID-19, including vascular complications.

To study the types of quorum quenching bacteria in soil and their quorum quenching characteristics, the study screened, isolated, and identified quorum quenching strains from soil and assessed their quorum quenching properties, the inhibitory and dispersion abilities on the biofilm of Hafnia alvei (H. alvei), and the potential types of quorum quenching enzymes by specific primer amplification. Four bacteria that showed significant degrading activity against the quorum sensing signals produced by H. alvei were isolated and identified as Enterobacter hormaechei (GS31), Bacillus cereus (GS44), Bacillus thuringiensis (GS48), and Serratia sp. (GS53). E. hormaechei GS31 exhibited the highest level of quenching activity, followed by Serratia sp. GS53, B. cereus GS44, and B. thuringiensis GS48. The cell-free supernatant of E. hormaechei GS31 and Serratia sp. GS53 contained compounds with potential quorum quenching activity, whereas the crude cell extract of B. cereus GS44 and B. thuringiensis GS48 contained such chemicals. The crystal violet staining and optical microscopy assay indicated that the isolated strains exhibited different inhibitory and dispersion capabilities against the biofilm of H. alvei. Among them, E. hormaechei GS31 exhibited the most significant effect, with inhibition and dispersion rates of 42.9% and 53.0%, respectively. The homologous gene amplification results suggested E. hormaechei GS31, B. cereus GS44, and Serratia sp. GS53 likely involved AiiA lactonase and PvdQ acylase gene. Additionally, B. thuringiensis GS48 was likely to possess AiiA lactonase gene. The screening and study of quorum quenching activity of strains degrading N-acyl homoserine lactone in soil enriching quorum quenching bacterial resources and provide a theoretical reference for developing aquaculture preservatives based on quorum quenching bacteria.

Abstract The ability to lubricate and resist wear at temperatures above 600 °C in an oxidative environment remains a significant challenge for metals due to their high-temperature softening, oxidation, and rapid degradation of traditional solid lubricants. Herein, we demonstrate that high-temperature lubricity can be achieved with coefficients of friction (COF) as low as 0.10-0.32 at 600-900 °C by tailoring surface oxidation in additively-manufactured Inconel superalloy. By integrating high-temperature tribological testing, advanced materials characterization, and computations, we show that the formation of spinel-based oxide layers on superalloy promotes sustained self-lubrication due to their lower shear strength and more negative formation and cohesive energy compared to other surface oxides. A reversible phase transformation between the cubic and tetragonal/monoclinic spinel was driven by stress and temperature during high temperature wear. To span Ni- and Cr-based ternary oxide compositional spaces for which little high-temperature COF data exist, we develop a computational design method to predict the lubricity of oxides, incorporating thermodynamics and density functional theory computations. Our finding demonstrates that spinel oxide can exhibit low COF values at temperatures much higher than conventional solid lubricants with 2D layered or Magnéli structures, suggesting a promising design strategy for self-lubricating high-temperature alloys.

Abstract Anther development involves a series of important biological events that are precisely regulated by many genes. Although several important genes involved in rice anther development have been identified, the regulatory network involved in tapetal development and pollen wall formation is still largely unclear. PERSISTENT TAPETAL CELL 1 (PTC1) encodes a PHD-Finger protein, which plays a critical role in the regulation of tapetal cell death and pollen development in rice. Here, we report the isolation and characterization of a new allele ptc1-2 with 2-base deletion in the third exon, causing the absent of the PHD domain due to the sequence change. Cytological analysis revealed delayed tapetal PCD, defective pollen exine formation and abnormal ubisch bodies development. Transcriptome analysis revealed that genes related to pollen wall formation (secondary metabolism, phenylalanine synthesis, and cutin and wax biosynthesis pathways), cell death (cysteine and methionine metabolism and DNA repair pathways), and carbohydrate synthesis (starch and sucrose metabolism pathways) were significantly altered in ptc1-2 mutant. A total of 13 reported anther development genes exhibited significant expression changes in the ptc1-2 mutant. Yeast two-hybrid and BiFC analyses showed that PTC1 could interact with API5, an inhibitor of apoptosis, and the citrin-binding enzyme EDT1. This work is helpful in deepening the understanding of the regulatory network of male reproductive development in rice.

Abstract Background Patient-derived xenograft (PDX) is currently considered a preferred preclinical model to evaluate drug sensitivity, explore drug resistance mechanisms, and select individualized treatment regimens. Methods Histopathological examination, immunohistochemistry and whole-exome sequencing confirmed similarity between our PDX tumors and primary tumors in terms of morphology and genetic characteristics. The drug reactivity of the PDX tumor was validated in vivo. The mechanisms of acquired resistance to Osimertinib PDX tumors were investigated by WES and WB. Results We successfully established 13 NSCLC-PDXs derived from 62 patients, including eight adenocarcinomas, four squamous-cell carcinoma, and one large-cell neuroendocrine carcinoma. Histological subtype and clinical stage were significant factors affecting the successful PDXs establishment. The treatment responses to conventional chemotherapy in PDXs were entirely consistent with that of their corresponding patients. According to the genetic status of tumors, more appropriate targeted agents were selected in PDXs for their corresponding patients as alternative treatment options. In addition, a PDX model with acquired resistance to osimertinib was induced, and the overactivation of RAS mitogen-activated protein kinase (MAPK)-extracellular signal-regulated kinase (ERK) signaling pathway caused by the dual-specificity phosphatase 6 (DUSP6) M62I mutation was found to play a key role in the development of osimertinib resistance. Trametinib, a specific inhibitor of the MAPK-ERK pathway significantly slowed down the tumor growth in osimertinib-resistant PDX models, providing an alternative treatment in patients after osimertinib failure.

The purpose of our work is to analyze the effect of wave breaking on dual-polarized (vertical-vertical (VV) and vertical-horizontal (VH)) synthetic aperture radar (SAR) image in the C-band during tropical cyclones (TCs) based on the machine learning method. In this study, more than 1300 Sentinel-1 (S-1) interferometric-wide (IW) and extra wide (EW) mode SAR images are collocated with wave simulations from the WAVEWATCH-III (WW3) model during 400 TCs. The validation of the significant wave height (SWH) simulated using the WW3 model against Jason-2 altimeter data. The winds for S-1 SAR images are reconstructed using wind retrievals in VV and VH polarization. The non-polarized (NP) contribution σwb caused by wave breaking is assumed to be the result of the SAR-measured normalized radar cross-section (NRCS) σ0 minus the Bragg resonant roughness σbr without the distortion of rain cells during TCs. The σbr is simulated by imputing wave spectra from the WW3 model into the theoretical backscattering model. It is found that the ratio (σwb/σ0) in VV polarization is related to the wind speed, the wind direction relative with the flight orientation, and radar incidence angle. Following this rationale, the Adaptive Boosting (AdaBoost) model was used for the estimation of NP contribution σwb during TCs and are implemented for more than 300 dual-polarized S-1 images to validate the model. It is found that for the comparison between the sum of simulation NRCS and SAR observations, the root mean squared error (RMSE) is 1.95 dB and the coefficient (COR) is 0.86, which is better than a 2.83 dB RMSE and a 0.67 COR by empirical model. It is concluded that the AdaBoost model has a good performance on NP component simulation during TCs.

Abstract Background Dyslipidemia is prominently associated with adverse outcomes in patients with coronary artery disease (CAD). The non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) is a novel comprehensive lipid index. However, limited evidence exists on the relationship of the NHHR with the risk of adverse outcomes in patients with CAD. This study aimed to explore the associations between the NHHR and adverse outcomes and identify the optimal NHHR ranges linked to the lowest adverse outcome risk in patients with CAD undergoing percutaneous coronary intervention (PCI). Methods Among 2253 patients with CAD undergoing PCI, 2251 with available total cholesterol and HDL-C levels were analyzed. Furthermore, all patients were classified into quintiles based on the NHHR. The primary outcome was the incidence of MACCEs, comprising cardiac mortality, acute myocardial infarction, stroke, and repeat revascularization. Multivariable logistic regression analysis was used to assess the relationship between the NHHR and MACCEs. Moreover, restricted cubic spline (RCS) analysis was performed to quantify nonlinearity. Lastly, the consistency between these associations was confirmed by conducting subgroup and interaction analyses. Results A total of 270 patients experienced MACCEs over a median follow-up of 29.8 months (interquartile range, 25.6–34 months). After adjustment for confounding variables, the adjusted ORs (95% CIs) of the patients in quintiles 2, 3, 4, and 5 were 0.79 (0.52–1.20), 0.64 (0.42–0.99), 1.00 (0.67–1.48), and 1.17 (0.74–1.64), respectively (reference group: quintile 1). Additionally, RCS analysis demonstrated a U-shaped relationship between the NHHR and MACCEs, with an inflection point at an NHHR of 3.119 using a two-piecewise regression model. This relationship was consistent across the various subgroups, while significant interactions were not observed in these associations.The ORs and 95% CIs to the left and right of the inflection point were 0.734 (0.551–0.978) and 1.231 (1.038–1.460), respectively. Conclusions This study reveals a U-shaped association between baseline NHHR and MACCE incidence in patients with CAD undergoing PCI.

IntroductionUrethral injury caused by various reasons usually leads to urethral stricture. And severe urethral stricture can further induce complications such as bladder stones, fistulas, sepsis, and even renal failure. At present, surgical methods such as urethral reconstruction and end-to-end anastomosis are commonly used to solve this problem. But this treatment method often has a high recurrence rate. So simply relying on the repair of surrounding autologous tissue cells to reconstruct the urethra is difficult to achieve long-term stability, and constructing a suitable urethral graft is an effective and feasible solution.MethodsHere, we designed and prepared a double-layer PLGA/CoI-MeHA tissue engineering scaffold to better simulate the natural anatomy of the urethra and achieve urethral tissue regeneration and reconstruction in patients with urethral stricture and Hypospadias caused by various reasons. The double-layer tissue engineering scaffold was generated using electrospinning and light curing technology.ResultsThrough electrospinning and light curing technology, we successfully screened the PLGA/CoI (7:3) electrospun membrane and MeHA (40.72%) hydrogel. Furthermore, we successfully prepared PLGA/CoI-MeHA bilayer urethral stents loaded with rabbit urethral smooth muscle cells and rabbit urethral epithelial cells, respectively, and achieved favorable results for urethral defect repair and urethral reconstruction in rabbits. The mechanical characterization of the scaffold indicates that it has sufficient mechanical strength to meet experimental and clinical needs. In addition, it showed satisfactory biocompatibility in cell experiments and in the in vitro degradation experiments. The double-layer urethral stents demonstrated exceptional performance in repairing urethral defects in rabbits.DiscussionWe had successfully designed and prepared a double-layer PLGA/CoI-MeHA tissue engineering scaffold. The stent displayed sufficient mechanical strength, good biocompatibility and degradation characteristics, and effectively simulated the natural anatomy of urethra, achieving satisfactory urethral defect reconstruction results.

This retrospective cohort study using SEER data from 2000 to 2020 examines the impact of radiotherapy on the risk of Secondary Primary Lung Cancer (SPLC) in 224,396 elderly female breast cancer survivors. Patients treated with radiotherapy displayed a 31 % increased SPLC risk compared to those not treated. Utilizing Cox Proportional Hazards and Poisson regression models, the study assessed various factors including age, race, and tumor characteristics. Propensity Score Matching (PSM) was employed to balance cohorts for survival analysis, which revealed that radiotherapy did not negatively impact overall survival despite the increased risk of SPLC. A nomogram was developed to aid clinical decision-making by predicting survival outcomes. The findings advocate for personalized treatment strategies and continuous monitoring to manage potential long-term adverse effects effectively, highlighting the need for a balanced approach in the treatment of breast cancer survivors.

Objective: This study compared the clinical effectiveness after radiofrequency ablation (RFA) of the great saphenous veins with the experimental or control systems in a prospective, randomized, controlled clinical trial. Methods: Fifty-four patients with varicose veins had their unilateral limb treated with RFA and completed 6 months of follow-up. Preprocedural, intraprocedural, and follow-up data were collected and compared. Results: Patients had a procedural success rate of 100% (defined as complete occlusion of the treated vein segment or a partial recanalization of

ObjectiveWe aimed to explore the application value of unsupervised machine learning in identifying acute gastrointestinal injury (AGI) after extracorporeal circulation for acute type A aortic dissection (ATAAD).MethodsPatients who underwent extracorporeal circulation for ATAAD at the First Hospital of Lanzhou University from January 2016 to January 2021 were included. Unsupervised machine learning algorithm was used to stratify patients into different phenogroups according to the similarity of their clinical features and laboratory test results. The differences in the incidence of perioperative AGI and other adverse events among different phenogroups were compared. Logistic regression was used to analyze the high-risk factors for AGI in each phenogroups and random forest (RF) algorithms were used to construct diagnostic models for AGI in different phenogroups.ResultsA total of 188 patients were included, with 166 males and 22 females. Unsupervised Machine Learning stratified patients into three phenogroups (phenogroup A, B, and C). Compared with other phenogroups, phenogroup B patients were older (P

Simultaneous estimation of multiple soil properties from vis-NIR hyperspectra presents a cost-effective and time-efficient approach. Previous studies have utilized multi-task convolutional neural network (multi-CNN) with share-bottom structures based on the hard parameter sharing. However, multi-CNN often ignores the differential characteristics of correlations between soil properties, limiting the accuracy of soil property estimation. The multi-gate mixture-of-experts network (MMoE) offers a solution by extracting both common features across all soil properties and unique features specific to each soil property, which probably could provide better estimation outcomes than the conventional shared-bottom multi-CNN. In the present study, a MMoE was built based on a total of 17,272 mineral soil samples from the Land Use/Cover Area Frame Survey (LUCAS) topsoil database that includes vis-NIR spectra with ten physicochemical properties, i.e., clay, silt, sand, pH (in water), organic content (OC), calcium carbonate (CaCO3), nitrogen (N), phosphorous (P), potassium (K), and cation exchange capacity (CEC). To evaluate the performance of MMoE, a series of other models were also built, i.e., partial least square regression (PLSR), single-task convolutional neural network (single-CNN), multi-task convolutional neural network (multi-CNN) and multi-task long short-term memory (multi-LSTM). Furthermore, performance of feature-spectrum selected by competitive adaptive reweighted sampling (CARS) on the accuracy of the MMoE was also explored, as well as a data augmentation method of stacking raw spectra with five preprocessed spectra data. The results demonstrated that MMoE had higher accuracy than PLSR, single-CNN, and multi-LSTM models, with RMSE reduction of 5 %–48 %, R2 improvement of 1 %–119 %, and CCC improvement of 0 %–74 %. Compared with multi-CNN, MMoE showed better accuracy for all properties except pH, with RMSE reduction of 3 %–8 %, R2 improvement of 1 %–12 %, and CCC improvement of 0 %–5 %. However, the feature-spectrum selected by CARS did not improve the accuracy of MMoE compared to full-band spectrum, whereas the data augmentation method was effective in improving the estimation accuracy of MMoE compared to raw spectra, with RMSE reduction of 14 %–28 %, R2 improvement of 3 %–88 %, and CCC improvement of 1 %–63 %. Consequently, this study proves that MMoE based on data augmentation is an efficient and accurate method for the simultaneous estimation of multiple soil properties from vis-NIR spectra.

Abstract Heat stress (HS) poses a significant challenge to plant survival, necessitating sophisticated molecular mechanisms to maintain cellular homeostasis. Here, we identify SICKLE (SIC) as a key modulator of HS responses in Arabidopsis (Arabidopsis thaliana). SIC is required for the sequestration of RNA DEBRANCHING ENZYME 1 (DBR1), a rate-limiting enzyme of lariat intronic RNA (lariRNA) decay, into stress granules (SGs). The sequestration of DBR1 by SIC enhances the accumulation of lariRNAs, branched circular RNAs derived from excised introns during pre-mRNA splicing, which in turn promote the transcription of their parental genes. Our findings further demonstrate that SIC-mediated DBR1 sequestration in SGs is crucial for plant HS tolerance, as deletion of the N-terminus of SIC (SIC1–244) impairs DBR1 sequestration and compromises plant response to HS. Overall, our study unveils a mechanism of transcriptional regulation in the HS response, where lariRNAs are enriched through DBR1 sequestration, ultimately promoting the transcription of heat stress tolerance genes.

Abstract The advent of immunotherapy has greatly improved the prognosis of non-small cell lung (NSCLC) patients. However, given its low response rate and high cost of treatment, the search for valuable predictive markers of treatment efficacy is necessary. Considering the complexity and heterogeneity of the tumour and tumour microenvironment, the construction of a multi-dimensional prediction model is necessary. Therefore, we aimed to integrate clinical parameters, radiomic features, and immune signature data from NSCLC patients receiving immunotherapy to construct a multi-dimensional prediction model to better predict the efficacy of immunotherapy. The current study enrolled 137 NSCLC patients who received immunotherapy. We collected baseline clinical information, CT images, and tumour tissue specimens. Using 3D-Slicer software, radiomic features were extracted from patient CT images, and tumor tissue samples obtained before immunotherapy were subjected to immunohistochemical staining. Then, the least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied to downscale the data, and the radiomic features and immune signatures associated with the prognosis of immunotherapy patients were identified. The modified lung immune predictive index (mLIPI), radiomics score (Radioscore), immune score and multi-dimensional model nomogram were constructed. The C-index and area under the curve (AUC) were applied to evaluate the predictive efficacy of the models. Three radiomic features and three immune signatures that could predict the efficacy of immunotherapy were eventually screened. Multivariate analysis showed that the mLIPI, Radioscore, and immune score were independent predictive factors for PFS and OS (P

Fault-slip rockbursts are a major type of rockbursts in coal mine roadways, posing great hazards. Currently, there is a lack of systematic research on the entire process of fault-slip rockbursts, and prediction and prevention remain fundamental challenges. To achieve experimental simulation of fault-slip rockbursts, a testing system was developed, along with the development of low-strength high-brittleness similar simulation materials. A large-scale similar model containing faults and roadways was prepared, and a series of verification experiments were conducted, realizing the simulation of roadway shock failure and fault shear slip. The testing system is equipped with a triaxial six-face loading function, with a vertical loading capacity of 20 MPa and a model size of 1.50 m×0.75 m×0.75 m. The main frame innovatively adopts a key plate connection, ensuring high rigidity of the main frame. A honeycomb loading shell structure was invented, achieving oil cylinder group loading, which can meet the requirements of fault-slip rockburst simulation. A similar material suitable for fault-slip rockburst simulation was developed, which uses water glass as the binder, sodium fluosilicate as the curing agent, and talcum powder as the aggregate. The similar material has characteristics of both low strength and high brittleness, with a uniaxial compressive strength ranging from 3.44 to 7.81 MPa, an impact energy index of 9.2, and an elastic energy index of 8.83. Based on the test system and low-strength and high-brittleness materials, the bursting failure simulation of roadway under static load was realized, and the feasibility of simulating bursting failure of roadway using low-strength and high-brittleness materials was verified. The loading conditions of the critical equilibrium state of the roadway were obtained, with the continuous shedding of the roadway's side as a significant precursor characteristic of roadway damage. The shear slip of rough serrated faults was realized, confirming that the shear slip of rough faults would cause significant dynamic load disturbances to the roadway, obtaining a reasonable loading method for fault slip. The method of loading the top of the dynamic zone first and unloading the bottom later can achieve instantaneous slip of the fault and eliminate the influence on the static zone stress state.

The frequent occurrence of coal burst seriously threatens the safe and efficient recovery of coal resources. The research on the mechanism of coal burst is the basis of prediction and disaster prevention. Aiming at the coal burst event under the condition that the stress environment is stable and not affected by dynamic load, the concept of local mine stiffness (LMS) is introduced. Taking the mining area with complex mining layout of the mine as the engineering background, the mechanical response of coal pillar in the process of large-scale mining is analyzed by comprehensively using numerical analysis and field measurement, The evolution of LMS in this process is investigated. It is pointed out that the mining leads to the reduction of LMS, the rapid accumulation of energy in the coal seam and its roof and floor system, and the rapid release of energy when the coal pillar is unstable, resulting in impact damage. The engineering verification is carried out by comparing the evolution of LMS with the mining and the field measured ground sound and microseismic data. The research shows that:①the deformation, load and elastic energy accumulation of coal pillar increase with the overall mining operation, but the LMS decreases. The mining space size and the distance between the mining space and the research area are the main influencing factors. The response degree of the two to the mining of the working face is significantly greater than that of the roadway excavation. The significant influence range of the mining of the working face on the LMS reduction is 3.67 times that of the roadway excavation, and the LMS reduction under the unit advancing distance is 6.41 times that of the roadway excavation.②The good correspondence between the evolution of local mine stiffness with the advancement of the working face and the on-site ground sound and microseismic data indicates that the reduction of local mine stiffness caused by coal mining directly affects the failure mode of coal pillars. The energy in the coal seams and their roof and floor systems accumulates rapidly with the reduction of local mine stiffness and is released rapidly when the bearing capacity of coal pillars decreases, resulting in impact damage. ③After using large-diameter drilling to weaken the coal body, the microseismic energy and frequency are significantly reduced, indicating that large-diameter drilling destroys the coal body in this area, reduces its post peak stiffness, and effectively realizes the impact prevention effect.

Abstract With increases in life expectancy, the number of patients requiring joint replacement therapy and experiencing periprosthetic osteolysis, the most common complication leading to implant failure, is growing or underestimated. In this study, we found that osteolysis progression and osteoclast differentiation in the surface of the skull bone of adult mice were accompanied by significant expansion of lymphatic vessels within bones. Using recombinant VEGF-C protein to activate VEGFR3 and promote proliferation of lymphatic vessels in bone, we counteracted excessive differentiation of osteoclasts and osteolysis caused by titanium alloy particles or inflammatory cytokines LPS/TNF-α. However, this effect was not observed in aged mice because adipogenically differentiated mesenchymal stem cells (MSCs) inhibited the response of lymphatic endothelial cells to agonist proteins. The addition of the JAK inhibitor ruxolitinib restored the response of lymphatic vessels to external stimuli in aged mice to protect against osteolysis progression. These findings suggest that inhibiting SASP secretion by adipogenically differentiated MSCs while activating lymphatic vessels in bone offers a new method to prevent periprosthetic osteolysis during joint replacement follow-up.

Abstract pH value is a crucial index used to evaluate pork quality due to its direct impact on specific meat characteristics. This study investigated the genetic mechanisms influencing pH values through measurements taken from the longissimus dorsi muscle of Beijing Black pigs at 2 h (pH2h) and 24 h (pH24h) postmortem. A total of 614 Beijing Black pigs were subsequently genotyped using the Illumina Porcine 50K SNP Chip. Heritability estimates for pH2h and pH24h were found to be 0.19 and 0.25, respectively, with a genetic correlation of 0.53. Furthermore, we conducted both a genome‐wide association study (GWAS) and an RNA sequencing (RNA‐seq) analysis, the latter of which identified differentially expressed genes (DEGs) between high and low pH groups. We identified 31, 6, and 32 single‐nucleotide polymorphisms in the pH2h, pH24h, and pH2–24h traits, respectively. The GWAS results revealed the presence of the SYT5 gene in both the pH2h and pH2–24h traits, while the SNX13 gene was simultaneously identified in the pH24h and pH2–24h traits. The RNA‐seq results also found SYT5 to be highly expressed, while SNX13 did not exhibit differential expression. Moreover, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses based on the DEGs revealed potential links between pH levels and the glycogen metabolic process as well as associations with the regulation of cell proliferation and calcium ion transmembrane transport. Ultimately, SYT5 and SNX13 emerged as key candidate genes affecting pH values at 2 and 24 h, respectively. These findings contribute to a better understanding of the genetic mechanisms affecting pork quality and safety and offer insights for enhancing meat quality through genetic improvement.

Abstract This study aims to illustrate epidemiology of comorbid CVD in the real-world clinical setting of patients with psoriasis in China. We used data of adult patients with psoriasis who were registered in the register of China National Clinical Center for Skin and Immune Diseases between August 2020 and September 2021. Psoriasis was clinically diagnosed following the national guidelines. Univariate and multivariate logistic regression models were used to examine the factors associated with comorbid CVD in patients with psoriasis. Of the 11,560 psoriasis patients (age ≥ 18 years, mean age 41.87 years, 64.88% males), 236 were ascertained with CVD, with the overall prevalence being 2.62%. Multivariate logistic regression analysis suggested that the odds ratio (95% confidence interval) of CVD in psoriasis patients was 2.27 (2.03–2.54) for older age (per 10-year increment), 0.65 (0.48–0.90) for female, 2.07 (1.39–3.06) for obesity (BMI ≥ 28 vs.

Abstract The Huang-Huai-Hai region accounts for 80% of China’s wheat production, leading to severe groundwater depletion and substantial environmental impacts. Here we present an optimization framework for wheat redistribution to reduce both water requirements and environmental impacts without compromising production. Our results show that environmental footprints can be reduced—blue water by 16%, grey water by 21%, and greenhouse gas emissions by 18%—while enhancing resource use efficiency, with irrigation water productivity improving by 21% and nitrogen use efficiency by 11%. Maintaining current production levels is achievable with these adjustments. Furthermore, allowing a 17–18% decrease in wheat production could result in a groundwater depth increase of 9.03–9.38 m by 2030, ensuring sustainable groundwater use. In regions experiencing groundwater depletion, blue water, grey water and greenhouse gas emissions could decrease by over one third. Our findings offer an alternative strategy for promoting sustainable agriculture in regions facing groundwater depletion worldwide.

Abstract Automatic Speech Scoring (ASS) has increasingly become a useful tool in oral proficiency testing for Second Language (L2) learners. However, limited studies investigate the alignment of ASS indices with the Complexity, Accuracy, and Fluency (CAF)—the three dimensions in evaluating L2 speakers’ oral proficiency, and the subsequent impact indices on the oral performance of Chinese college students. To bridge this gap, this study used comparative analysis, Pearson analysis, and linear regression analysis to delve into the relationship and correlations between paired ASS indicators of “pronunciation”, “fluency”, “integrity”, “speed”, “duration”, and “overall”, while also analyzing the relationships between “overall” and other variables. These analyses were conducted using 956 audio clips of freshmen who took the College English Test-Spoken English Test Band 4 (CET-SET-4) in May 2022 in China. The findings reveal that (1) the ASS indicators and evaluation methods are similar but not identical to those employed in prior studies; (2) “pronunciation” encapsulates both the accuracy and fluency dimensions of CAF; (3) “pronunciation” and “integrity” have significant impacts on Chinese college students’ oral English performance in read-aloud tasks. The study suggests that future research should further investigate the specific pronunciation challenges faced by Chinese college students, such as phonetics, stress, and intonation. Additionally, it highlights the need to comprehend teachers’ attitudes and preferences towards ASS to enhance its effectiveness in assessing second language (L2) learners’ oral proficiency. The study would provide some references to teachers for oral English teaching design and students for their self-assessment of oral English proficiencies.

Periocular basal cell carcinoma (pBCC) is the most common malignancy in the periocular region, characterized by local aggressiveness, high incidence, and significant recurrence rates. While surgery is the primary treatment option, achieving complete lesion removal can be challenging due to the sensitive anatomy of this area and associated cosmetic considerations. Recent advancements in photodynamic therapy (PDT) have demonstrated promising efficacy and cosmetic outcomes for superficial BCC, offering alternatives to traditional treatments. However, PDT's effectiveness is often limited by the penetration depth of photosensitizers, particularly for deep tumors. To address these challenges, we developed a regimen that combines palliative surgery with immediate PDT for pBCC cases with inadequate or positive surgical margins. This integrated approach aims to overcome the penetration limitations of PDT while enhancing tumor clearance and preserving cosmetic outcomes. We report on three cases where all patients achieved complete clinical remission, with satisfactory cosmetic results and no recurrence observed during follow-up periods ranging from 12 to 23 months. Our findings suggest that palliative surgical resection, in conjunction with PDT, represents an effective treatment strategy for pBCC. This approach is particularly valuable when standard surgical margins cannot be achieved, especially considering the importance of cosmetic healing.

On-surface chemistry provides an efficient approach to construction of diverse covalent architectures with atomic precision, ranging from one-dimensional chains and ribbons to two-dimensional covalent organic frameworks (COFs) and metal-organic frameworks (MOFs) on coinage metal substrates. This study explores a distinct on-surface pyrolysis approach to MOFs derived from a crown ether molecular precursor on Au(111) and Ag(111) surfaces. Utilizing scanning tunneling microscopy (STM) and non-contact atomic force microscopy (nc-AFM) combined with density functional theory (DFT) calculations, we elucidate the adsorption behavior and the characteristic macrocyclic configuration of the crown ether on Au(111). Subsequent surface-catalyzed Ullmann coupling reactions at an annealing temperature of 470 K lead to highly disordered COFs with the formation of four-membered and six-membered rings through dimerization and trimerization. For the Ag(111) surface, further annealing at 520 K initiates a unique dehydrogenative reaction within the macrocyclic rings, resulting in the loss of six hydrogen atoms. At an elevated temperature of 720 K, breaking of the second C−O bonds yields a long-range ordered triphenylene-based MOF structure. Electronic characterizations reveal the presence of both regular and diatomic kagome lattices, together with distinct quantum-dot states emerging in the pore regions. Additionally, we investigate the selective encapsulation of single guest picenes within the MOF structure, emphasizing the potential of triphenylene-based frameworks for advanced applications in sensing and molecular filtering. Our findings provide a comprehensive insight into the chemical reactivity of crown ethers on metal substrates and demonstrate a novel pathway to designing MOFs through an on-surface pyrolysis process.

Abstract Background and Aims Microglia are the innate immune cells of central nervous system which play critical roles in brain homeostasis. Recently, the effects of general anesthetic agents (GAAs) on microglia and their potential neurotoxicity in neurodevelopment have attracted the attention of anesthesiologists and neuroscientists. Methods Here, we review the physiology of microglia in neurodevelopment, the potential mechanisms of GAAs on microglia and the consequent changes in microglial function. Outcomes Microglia‐mediated neuroinflammation is a key mechanism of neurocognitive deficits during neurodevelopment. In addition, microglia could be primed by active inflammatory processes and have innate immune memory, both of which make them a potential candidate responsible of long‐term neural deficits. Conclusion This review aims in summarizing the in vivo and in vitro studies associating microglia with general anesthesia and describing how GAAs induce neurocognitive deficits via microglia to further explore the effects of GAAs on neurodevelopment.

ObjectivesTo examine the association between the age at onset of diabetes and the risk of all-cause mortality in a population of individuals diagnosed with type 2 diabetes mellitus (T2DM) and to identify risk factors associated with all-cause mortality in young-onset T2DM (YOD) patients in China.MethodsThis study utilized a cohort of 9759 patients who were diagnosed with T2DM and who were registered and enrolled in the National Basic Public Health Service Management Program in Qinghe District (now Qingjiangpu District) and Huai’an District, Huai’an City, Jiangsu Province, China. The patients were observed from November 2013 to July 2014, and all-cause mortality data were obtained by comprehensive matching with the Huai’an City Resident Mortality Database as of December 31, 2019. A Cox proportional hazards model was used to compute the hazard ratios (HRs) and their corresponding 95% confidence intervals (95% CIs) for all-cause mortality risk during the follow-up period among patients with varying disease onset ages. Additionally, subgroup analyses were conducted based on sex, age, lifestyle factors, and baseline clinical parameters.ResultsA total of 7572 patients with T2DM, including 2874 men and 4698 women aged 57.9 ± 8.0 years, were ultimately included in the study. 1) At baseline, a greater proportion of YOD patients were engaged in high-intensity activities, had a longer sleep duration, had a longer duration of T2DM, had a family history of T2DM, had microvascular complications (kidney disease, retinopathy, neuropathy, diabetic foot, etc.), and received glucose-lowering treatment. Moreover, patients in the YOD group also had significantly greater baseline HbA1c, FBG, and estimated glomerular filtration rate (eGFR) than did those in the onset at 41-60 years (MD) group and the onset at 61-75 years (SD) group. 2) During the six-year follow-up period, a total of 1057 deaths were documented. After adjusting for confounding factors and utilizing SD as the reference group, the HRs for deaths occurring in the YOD and MD groups were 1.383 (95% CI: 0.717-2.667) and 1.006 (95% CI: 0.763-1.326), respectively. Moreover, the risk of death in the YOD group remained highest in the sensitivity analysis that excluded patients with coronary heart disease at baseline, stroke patients, and patients who died within the first three years of follow-up. 3) Sleep duration was identified as an independent risk factor for mortality in the YOD group, with a notable increase in the risk of all-cause mortality when sleep duration exceeded 9 hours per day.ConclusionThe risk of all-cause mortality in YOD patients was 1.38 times greater than that in MD and SD patients, and the longer the sleep duration was, the greater the risk of death, especially when sleep duration exceeded 9 hours per day.

BackgroundStudies on lower urinary tract symptoms (LUTS) in women, especially in relation to different modes of delivery, are limited. The relationship between the emergence of LUTS and the decline of pelvic muscle function after childbirth remains uncertain.Study designThis observational study was carried out at the Peking University First Hospital over a time span of 2019–2022. A total of 2,462 women were recruited and surveyed 6 weeks after delivery, utilizing questionnaires for data collection. Additionally, gynecological physical examinations and pelvic floor muscle screenings were conducted as part of the study. To assess individual LUTS and the level of discomfort caused by these symptoms, a modified Chinese version of the Bristol Female Lower Urinary Tract Symptoms questionnaire was employed. Data analysis methods such as descriptive statistics, χ2 tests, one-way ANOVAs, and multivariate logistic regressions were used to thoroughly examine the collected data.ResultsA high prevalence of LUTS was observed in the study participants, with 70.6% experiencing any symptoms. Storage symptoms were reported by 65.4%, while voiding symptoms were reported by 23.0%. Nocturia was the most commonly reported symptom (35.4%), followed by frequency (25.6%) and urgency (25.3%). Stress urinary incontinence (SUI) was reported by 20.8% of women. Interestingly, nocturia and frequency were generally perceived as less troublesome, with only a minority rating them as problematic. In contrast, urinary incontinence (UI) was frequently reported as highly bothersome, with SUI and urge urinary incontinence (UUI) accounting for significant proportions. Vaginal delivery (VD) and forceps delivery (FD) were identified as significant predictors of LUTS, with statistical significance observed (P

This study innovatively utilized coffee grounds oil (CGO) extracted from waste coffee grounds to modify base asphalt, aiming to promote sustainable reuse of coffee waste. The effects of modifier dosage, type, and aging conditions on the rheological properties of asphalt were investigated. After determining the extraction protocol, coffee grounds oil-modified asphalt (CGOA) and waste cooking oil-modified asphalt (WCOA) were prepared and subjected to short-term aging. Fourier transform infrared spectroscopy (FTIR) analyzed the modification mechanism, while temperature sweep, frequency sweep, bending beam rheometer, and multiple stress creep recovery (MSCR) tests assessed the rheological properties at high and low temperatures. Results showed that before aging, CGO improved thermal stability at medium to high temperatures and enhanced deformation and stress relaxation at low temperatures, though it reduced rutting resistance at high temperatures. After aging, CGOA with a dosage limited to 4 % exhibited rheological properties approaching base asphalt and improved the viscoelasticity of aged asphalt. In comparison, WCOA demonstrated significantly weaker performance, particularly after aging. This study provides practical insights into the novel application of CGO in pavement engineering.

Background The potential impact of elevated intra-abdominal pressure (IAP) on residual renal function (RRF) has not been determined. The objective of this study was to investigate the relationship between IAP and the rate of RRF decline in newly initiated peritoneal dialysis (PD) patients, and to identify the optimal IAP threshold value for delaying the deterioration of RRF.Methods A cohort of 62 newly initiated PD patients who completed both 6- and 12-month follow-up evaluations was obtained using the Durand method. A logistic regression model was used to identify variables associated with a rapid decline in RRF. Receiver operating characteristic (ROC) curves were generated to determine the optimal threshold value. Another retrospective cohort analysis was performed to validate the identified critical value.Results For each 1 cmH2O increase in IAP, the risk of a rapid decline in the RRF increased by a factor of 1.679. Subsequent analysis revealed that patients in the high IAP group had more significant decreases in residual renal estimated glomerular filtration rate (eGFR) (Z = −3.694, p

Elderly individuals undergoing surgical procedures are often confronted with the peril of experiencing postoperative cognitive dysfunction (POCD). Prior research has demonstrated the exacerbating effect of sevoflurane anesthesia on neuroinflammation, which can further deteriorate the condition of POCD in elderly patients. Intermittent fasting (IF) restricts food consumption to a specific time window and has been demonstrated to ameliorate cognitive dysfunction induced by neuropathic inflammation. We subjected 18-month-old male mice to 16 hours of fasting and 8 hours of unrestricted eating over a 24-hour period for 0, 1, 2, and 4 weeks, followed by abdominal exploration under sevoflurane anesthesia. In this study, we aim to explore the potential impact of IF on postoperative cognitive function in aged mice undergoing sevoflurane surgery through the preoperative implementation of IF measures. The findings indicate two weeks of IF leads to a significant enhancement of learning and memory capabilities in mice following surgery. The cognitive performance, as determined by the novel object recognition and Morris water maze tests, as well as the synaptic plasticity, as measured by in vivo electrophysiological recordings, has demonstrated marked improvements. Furthermore, the administration of IF markedly enhances the expression of synaptic-associated proteins in hippocampal neurons, concomitant with a decreasing expression of pro-inflammatory factors and a reduced density of microglial cells within the hippocampal brain region. To summarize, the results of this study indicate that IF may mitigate inflammation in the hippocampal area of the brain. Furthermore, IF appears to provide a safeguard against cognitive impairment and synaptic plasticity impairment brought on by sevoflurane anesthesia.