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With the gradual improvement of open teacher selection mechanisms, the comparison of traditionally and alternatively certified teachers has become one of the international focuses in teacher research. Current studies have compared teachers of different certification pathways from multidimensional perspectives; however, no study has yet compared the differences in curriculum leadership between the two types of teachers. Teacher curriculum leadership is the ability of teachers to collaborate with stakeholders in the curriculum area to promote curriculum optimization and the development of students and teachers, and it includes three dimensions: teachers' curriculum leadership views, practices and identity. This study conducted a comparative analysis of the curriculum leadership of traditionally and alternatively certified teachers based on data from 9,068 teachers of 20 provinces in China. Independent samples t-test and multiple linear regression analysis revealed no significant differences between traditionally and alternatively certified teachers on the overall level of curriculum leadership and the three sub-dimensions of curriculum leadership views, practices, and identity. Theoretically, it provides new evidence for the debate about whether there are differences between the two types of teachers by further corroborating the conclusion that there is no significant difference in the educational effectiveness of traditionally and alternatively certified teachers. Practically, it justifies the rationality of an open teacher selection mechanism and points the way to further reforms in university teacher education.

Developing an oral in situ-forming hydrogel that targets the inflamed intestine to suppress bleeding ulcers and alleviate intestinal inflammation is crucial for effectively treating ulcerative colitis (UC). Here, inspired by sandcastle worm adhesives, we proposed a water-immiscible coacervate (EMNs-gel) with a programmed coacervate-to-hydrogel transition at inflammatory sites composed of dopa-rich silk fibroin matrix containing embedded inflammation-responsive core-shell nanoparticles. Driven by intestinal peristalsis, the EMNs-gel can be actuated forward and immediately transform into a hydrogel once contacting with the inflamed intestine to yield strong tissue adhesion, resulting from matrix metalloproteinases (MMPs)-triggered release of Fe3+ from embedded nanoparticles and rearrangement of polymer network of EMNs-gel on inflamed intestine surfaces. Extensive in vitro experiments and in vivo UC models confirmed the preferential hydrogelation behavior of EMNs-gel to inflamed intestine surfaces, achieving highly effective hemostasis, and displaying an extended residence time (> 48 h). This innovative EMNs-gel provides a non-invasive solution that accurately suppresses severe bleeding and improves intestinal homeostasis in UC, showcasing great potential for clinical applications.

Abstract Web command injection attacks pose significant security threats to web applications, leading to potential server information leakage or severe server disruption. Traditional detection methods struggle with the increasing complexity and obfuscation of these attacks, resulting in poor identification of malicious code, complicated feature extraction processes, and low detection efficiency. To address these challenges, a novel detection model, the Convolutional Channel-BiLSTM Attention (CCBA) model, is proposed, leveraging deep learning techniques to enhance the identification of web command injection attacks. The model utilizes dual CNN convolutional channels for comprehensive feature extraction and employs a BiLSTM network for bidirectional recognition of temporal features. An attention mechanism is also incorporated to assign weights to critical features, improving the model’s detection performance. Experimental results demonstrate that the CCBA model achieves 99.3% accuracy and 98.2% recall on a real-world dataset. To validate the robustness and generalization of the model, tests were conducted on two widely recognized public cybersecurity datasets, consistently achieving over 98% accuracy. Compared to existing methods, the proposed model offers a more effective solution for identifying web command injection attacks.

Abstract Although the cellular prion protein (PrPC) has been evolutionarily conserved, the role of this protein remains elusive. Recent evidence indicates that PrPC may be involved in neuroinflammation and the immune response in the brain, and its expression may be modified via various mechanisms. Histamine is a proinflammatory mediator and neurotransmitter that stimulates numerous cells via interactions with histamine receptors 1-4 (HRH1-4). Since microglia are the innate immune cells of the central nervous system, we hypothesized that histamine-induced stimulation regulates the expression of PrPC in human-derived microglia. The human microglial clone 3 (HMC3) cell line was treated with histamine, and intracellular calcium levels were measured via a calcium flux assay. Cytokine production was monitored by enzyme-linked immunosorbent assay (ELISA). Western blotting and quantitative reverse transcription-polymerase chain reaction were used to determine protein and gene expression of HRH1-4. Flow cytometry and western blotting were used to measure PrPC expression levels. Fluorescence microscopy was used to examine Iba-1 and PrPC localization. HMC3 cells stimulated by histamine exhibited increased intracellular calcium levels and increased release of IL-6 and IL-8, while also modifying PrPC localization. HMC3 stimulated with histamine for 6 and 24 hours exhibited increased surface PrPC expression. Specifically, we found that stimulation of the HRH2 receptor was responsible for changes in surface PrPC. Histamine-induced increases in surface PrPC were attenuated following inhibition of the HRH2 receptor via the HRH2 antagonist ranitidine. These changes were unique to HRH2 activation, as stimulation of HRH1, HRH3, or HRH4 did not alter surface PrPC. Prolonged stimulation of HMC3 decreased PrPC expression following 48 and 72 hours of histamine stimulation. HMC3 cells can be stimulated by histamine to undergo intracellular calcium influx. Surface expression levels of PrPC on HMC3 cells are altered by histamine exposure, primarily mediated by HRH2. While histamine exposure also increases release of IL-6 and IL-8 in these cells, this cytokine release is not fully dependent on PrPC levels, as IL-6 release is only partially reduced and IL-8 release is unchanged under the conditions of HRH2 blockade that prevent PrPC changes. Overall, this suggests that PrPC may play a role in modulating microglial responses.

Abstract This post hoc analysis explored the age-specific risk of cervical precancer in women infected with human papillomavirus (HPV), using data from a cohort of 7263 participants aged 21-71years undergoing cervical screening. We found a slightly varied prevalence of high-risk HPV (hrHPV) in different age, with highest in women under 30 years old (9.28% for 13 hrHPVs tested by HC2-HPV, 10.82% for 14 hrHPVs tested by DH3-HPV). However, the prevalence of cytology abnormalities peaked in age 30–39 years (~ 3.6%). A total of 5840 women completed 3-year follow-up. Among them, 558 were positive for HC2 assay and 583 were positive for DH3-HPV at baseline. Of note, the 3-year cumulative risks for cervical intraepithelial neoplasia grade 2+ (CIN2+) or grade 3+ (CIN3+) in women infected with high-risk HPV did not increase with age but declined (e.g., 41.67%, 27.78%, 26.42%, 15.98%, and 18% for CIN2 + risk in HC2-positive women at year 25–29, year 30–39, year 40–49, year 50–59, and year 60–71, respectively). If stratified by the median age, younger women (25–48 years) positive with HC2-HPV at baseline had a higher 3-year CIN2+/CIN3 + risk than older women (49–71 years) [26.55% (95%CI = 21.8-31.92%) vs. 18.28% (95%CI = 14.11-23.34%), P = 0.019; 15.52% (95%CI = 11.81-20.14%) vs. 9.7% (95%CI = 6.71-13.83%), P = 0.039]. Similarly, for women positive with DH3-HPV at baseline, younger group had a higher 3-year CIN2+/CIN3 + risk than older group [26.44% (95%CI = 21.73-31.75%) vs. 17.01% (95%CI = 13.11-21.78%), P = 0.006; 15.25% (95%CI = 11.6-19.8%) vs. 9.03% (95%CI = 6.24-12.9%), P = 0.021]. These findings indicate the potential value of age-specific risk assessment in cervical cancer screening.

Abstract Osteopetrosis is an inherited metabolic disease, characterized by increased bone density and narrow marrow cavity. Patients with severe osteopetrosis exhibit abnormal bone brittleness, anemia, and infection complications, which commonly cause death within the first decade of life. Pathologically, osteopetrosis impairs not only the skeletal system, but also the hemopoietic and immune systems during development, while the underlying osteoimmunological mechanisms remain unclear. Osteoclastic mutations are regarded as the major causes of osteopetrosis, while osteoclast non-autonomous theories have been proposed in recent years with unclear underlying mechanisms. Retinoic acid (RA), the metabolite of Vitamin A, is an essential requirement for skeletal and hematopoietic development, through the activation of retinoic acid signaling. RA can relieve osteopetrosis symptoms in some animal models, while its effect on bone health is still controversial and the underlying mechanisms remain unclear. In this study, we constructed an osteoblast-specific inhibitory retinoic acid signaling mouse model and surprisingly found it mimicked the symptoms of osteopetrosis found in clinical cases: dwarfism, increased imperfectly-formed trabecular bone deposition with a reduced marrow cavity, thin cortical bone with a brittle skeleton, and hematopoietic and immune dysfunction. Micro-CT, the three-point bending test, and histological analysis drew a landscape of poor bone quality. Single-cell RNA sequencing (scRNA-seq) of the femur and RNA-seq of osteoblasts uncovered an atlas of pathological skeletal metabolism dysfunction in the mutant mice showing that osteogenesis was impaired in a cell-autonomous manner and osteoclastogenesis was impaired via osteoblast-osteoclast crosstalk. Moreover, scRNA-seq of bone marrow and flow cytometry of peripheral blood, spleen, and bone marrow uncovered pathology in the hematopoietic and immune systems in the mutant mice, mimicking human osteopetrosis. Results showed that hematopoietic progenitors and B lymphocyte differentiation were affected and the osteoblast-dominated cell crosstalk was impaired, which may result from transcriptional impairment of the ligands Pdgfd and Sema4d. In summary, we uncovered previously unreported pathogenesis of osteopetrosis-like disorder in mice with skeletal, hematopoietic, and immune system dysfunction, which was induced by the inhibition of retinoic acid signaling in osteoblasts, and sheds new insights into a potential treatment for osteopetrosis.

Abstract Background This study aimed to investigate the effect of laser peripheral iridotomy (LPI) on intraocular lens (IOL) power in patients with primary angle closure disease (PACD), and to construct mathematical models to assess changes in IOL power. Methods This study included 58 eyes of PACD patients. IOL Master700 was used to analyze and compare the changes of IOL power and ocular related parameters in each formula before and after LPI. The number of cases with IOL power changes greater than 0.5 diopters (D) in each group were counted and significant differences were analyzed using Fisher’s exact test. Pearson’s linear correlation analysis was used to ascertain the relationship between IOL power changes and ocular parameter changes to establish mathematical models. Results No significant difference was found in calculated IOL power changes before and after LPI in each group. There was significant difference in the number of cases with IOL change values greater than 0.5D between the primary angle closure glaucoma (PACG) and the other two groups for each formula. IOL power changes were mainly associated with △K and △AL. Mathematical models of IOL power changes after LPI were constructed based on linear regression analysis.(PAC group: △IOLHaigis=0.026–2.950×△AL-1.414×△K, △IOLHoffer Q=-3.578×△AL-1.412×△K, △IOLSRK/T=-3.152×△AL-1.114×△K, △IOLHolladay 1=-3.405×△AL-1.291×△K, △IOLHolladay 2=-3.467×△AL-1.483×△K, △IOLBUII=-3.185×△AL-1.301×△K; PACG group:△IOLHaigis=-1.632×△K, △IOLHoffer Q=-3.770×△AL-1.434×△K, △IOLSRK/T=-3.427×△AL-1.102×△K, △IOLHolladay 1=-3.625×△AL-1.278×△K, △IOLHolladay 2=-4.764×△AL-1.272×△K, △IOLBUII=-4.935×△AL-1.304×△K). Conclusions LPI will cause changes in some ocular parameters in patients with PACD, with great effects on IOL power calculations was observed in patients with PACG. Mathematical models based on multivariate analysis hold promise for predicting IOL power changes subsequent to LPI.

Abstract Porcine circoviruses, particularly porcine circovirus type 2 (PCV2) and porcine circovirus type 3 (PCV3), significantly impact the global pig industry due to their high prevalence and pathogenicity. Conversely, porcine circovirus type 1 (PCV1) and porcine circovirus type 4 (PCV4) currently have low positivity rates. This study aimed to characterize the distribution and epidemiology of porcine circoviruses in Xinjiang, while also analyzing the genetic diversity and evolution of PCV2 and PCV3, which pose the greatest threats to the industry. In this study, we collected blood and tissue samples from 453 deceased pigs across eight regions in Xinjiang Province from 2022 to 2024. We utilized real-time PCR to detect the presence of PCV1, PCV2, PCV3, and PCV4. The positive rates were 15%, 71%, 25%, and 17%, respectively. Genetic analysis showed 9 PCV2 sequences and 12 PCV3 sequences. The capsid protein of PCV2 showed significant variability. In contrast, the amino acid sequences of capsid in PCV3 were relatively stable. Moreover, we predicted antigenic epitopes for PCV3 capsid using IEDB and ElliPro. The findings from this study provide valuable epidemiological data on PCV coinfection in the Xinjiang region and enhance the understanding of virus diversity nationwide. This research may serve as an important reference for the development of strategies to prevent and control porcine circovirus infections.

Abstract Most existing scene classification methods based on remote sensing images tend to ignore important interactive information at different levels in the image. We propose an effective remote sensing scene classification method named multi-scale dense residual correlation network. The method is divided into three parts. First, the multi-stream feature extraction module is introduced which effectively utilizes features at different scales to extract different levels of information. Secondly, the dense residual connected feature fusion technology is proposed, which allows for a wide range of feature fusion. The Correlation Attention Module learn feature representations at multiple levels. This improves classification performance. The method outperforms existing algorithms in terms of effectiveness and accuracy, achieving state-of-the-art results on widely used remote sensing scene classification benchmarks.

Two new species; Lobothallia crenulata Lun Wang & Y. Y. Zhang, L. lobulata Lun Wang & Y. Y. Zhang and one new variety; L. subdiffracta var. rimosa Lun Wang & Y. Y. Zhang, are reported from China and described, based on morphological, chemical and molecular characters. Phylogenetic analyses showed that these new taxa form monophyletic groups. Lobothallia crenulata and L. lobulata, together with L. hydrocharis, L. radiosa and L. recedens, form a well-supported clade, whereas L. subdiffracta var. rimosa is nested within the samples of L. subdiffracta. Lobothallia crenulata is characterised by its placodioid thallus, thickly pruinose upper surface with a rimose appearance, aspicilioid to lecanorine apothecia with a crenate thalline margin and concave, black and pruinose discs. Lobothallia lobulata is characterised by its placodioid thallus, pruinose upper surface with lobules, aspicilioid when immature, lecanorine to zeorine apothecia at maturity and concave to plane, dark brown, shiny and epruinose discs. Lobothallia subdiffracta var. rimosa is characterised by its areolate thallus, rimose and pruinose upper surface, lecanorine apothecia and slightly concave to plane, black and pruinose discs. Secondary metabolites were not detected in the two new species nor the new variety. A key is provided for the species of Lobothallia in China.

Background/Aims: Metabolic syndrome is common in patients with acute pancreatitis and its components have been reported to be associated with infectious complications. In this post hoc analysis, we aimed to evaluate whether metabolic abnormalities impact the effect of immune-enhancing thymosin alpha-1 (Tα1) therapy in acute necrotizing pancreatitis (ANP) patients. Methods: All data were obtained from the database for a multicenter randomized clinical trial that evaluated the efficacy of Tα1 in ANP patients. Patients who discontinued the Tα1 treatment prematurely were excluded. The primary outcome was 90-day infected pancreatic necrosis (IPN) after randomization. Three post hoc subgroups were defined based on the presence of hyperglycemia, hypertriglyceridemia, or both at the time of randomization. In each subgroup, the correlation between Tα1 and 90-day IPN was assessed using the Cox proportional-hazards regression model. Multivariable propensity-score methods were used to control potential bias. Results: Overall, 502 participants were included in this post hoc analysis (248 received Tα1 treatment and 254 received matching placebo treatment). Among them, 271 (54.0%) had hyperglycemia, 371 (73.9%) had hypertriglyceridemia and 229 (45.6%) had both. Tα1 therapy was associated with reduced incidence of IPN among patients with hyperglycemia (18.8% vs 29.7%: hazard ratio, 0.80; 95% confidence interval, 0.37 to 0.97; p=0.03), but not in the other subgroups. Additional multivariate regression models using three propensity-score methods yielded similar results. Conclusions: Among ANP patients with hyperglycemia, immune-enhancing Tα1 treatment was associated with a reduced risk of IPN (ClinicalTrials.gov, Registry number: NCT02473406).

Abstract Oracle bone script, one of the earliest known forms of ancient Chinese writing, presents invaluable research materials for scholars studying the humanities and geography of the Shang Dynasty, dating back 3,000 years. The immense historical and cultural significance of these writings cannot be overstated. However, the passage of time has obscured much of their meaning, presenting a significant challenge in deciphering these ancient texts. With the advent of Artificial Intelligence (AI), employing AI to assist in deciphering Oracle Bone Characters (OBCs) has become a feasible option. Yet, progress in this area has been hindered by a lack of high-quality datasets. To address this issue, this paper details the creation of the HUST-OBC dataset. This dataset encompasses 77,064 images of 1,588 individual deciphered characters and 62,989 images of 9,411 undeciphered characters, with a total of 140,053 images, compiled from diverse sources. The hope is that this dataset could inspire and assist future research in deciphering those unknown OBCs. All the codes and datasets are available at https://github.com/Pengjie-W/HUST-OBC .

Background The 6-minute walk test (6MWT) is extensively used to assess the exercise capacity of obese populations and offers a reference for devising intervention measures. While reference equations for the 6MWT distance for various populations have been proposed internationally, there is a scarcity of studies on reference equations for the 6MWT distance among Chinese obese subjects aged 17 to 45 years with a BMI ≥ 30 kg/m2. Objective To develop reference equations for the 6MWT distance for outpatient obese subjects aged 17 to 45 years and to assess its influencing factors. Methods Following the American Thoracic Society guidelines, from June 2022 to September 2023, 143 adults aged 17 to 45 years with a BMI ≥30 kg/m2 (71 males and 72 females) who visitied the Department of Endocrinology, Northern Jiangsu People's Hospital, were prospectively selected for anthropometric measurements and the 6MWT. A stepwise multiple regression model was employed to establish reference equations for the 6MWT distance, and the newly developed equations were compared with existing prediction equations. Results The average 6MWT distance for the 143 subjects was (506.1±49.8) m, with males averaging (515.7±50.14) m, which was greater than the females' average of (496.6±47.9) m (P

This study proposes an IoT data management framework based on blockchain and edge computing and conducts detailed simulation experiment design and performance evaluation for the field of supply chain finance. Previous methods often struggled with high latency, limited scalability, and inadequate risk management, and to address these issues, the experimental platform includes traditional centralized systems, distributed systems, blockchain-based systems, and edge computing + blockchain systems. By monitoring indicators such as data processing delay, data transmission delay, data retrieval time, system throughput, and data integrity of each platform, and introducing evaluation formulas for credit risk, operational risk, and market risk, the performance of different systems in processing supply chain financial data is comprehensively analyzed. The experimental results show that the edge computing + blockchain system performs well in data processing efficiency, security, real-time, and system throughput, especially under high load conditions. Our market risk value is reduced to 0.015. This framework improves the efficiency and security of data transmission and effectively reduces credit risk and operational risk, providing an efficient and reliable solution for data management in supply chain finance.

Research on solvent effects is an important and long-standing topic, but there still is some room, especially for the special solvent effect of fluoroalcohols. In this work, we investigated the stability of phenoxyl radical in monohydric alcohol solvents through in-situ electron paramagnetic resonance detections. The decay behavior of phenoxyl radical showed a reasonable relationship with the mesoscopic structure of alcohols, characterized by small- and wide-angle X-ray scattering. Moreover, the distinct solvent effects of fluoroalcohols were emphasized, and the significant influence of van der Waals distance in the solvents was suggested. Overall, the stability of phenoxyl radical in alcohols was quantified and correlated with the solvent structures. We believe that the established method for stability study on radicals will encourage solvent effect studies on various organic reactions, and the proposed solvent effects in fluoroalcohols may inspire the development of green solvents in both industrial conversions and organic synthesis.

ABSTRACTSoybean is one of the important oil crops and a major source of protein and lipids. Drought can cause severe soybean yields. Dehydrin protein (DHN) is a subfamily of LEA proteins that play an important role in plant responses to abiotic stresses. In this study, the soybean GmDHN9 gene was cloned and induced under a variety of abiotic stresses. Results showed that the GmDHN9 gene response was more pronounced under drought induction. Subcellular localization results indicated that the protein was localized in the cytoplasm. The role of transgenic Arabidopsis plants in drought stress response was further studied. Under drought stress, the germination rate, root length, chlorophyll, proline, relative water content, and antioxidant enzyme content of transgenic Arabidopsis thaliana transgenic genes were higher than those of wild-type plants, and transgenic plants contained less O2−, H2O2 and MDA contents. In short, the GmDHN9 gene can regulate the homeostasis of ROS and enhance the drought resistance of plants.

In recent years, DNA origami-based nanocarriers have been extensively utilized for efficient cancer therapy. However, developing a nanocarrier capable of effectively protecting cargos such as RNA remains a challenge. In this study, we designed a compact and controllable DNA tubular origami (DTO) measuring 120 nm in length and 18 nm in width. The DTO exhibited appropriate structural characteristics for encapsulating and safeguarding cargo. Inside the DTO, we incorporated 20 connecting points to facilitate the delivery of cargoes to various ovarian and normal epithelial cell lines. Specifically, fluorescent-labeled DNA strands were attached to these sites as cargoes. The DTO was engineered to open upon encountering miR-21 through RNA/DNA strand displacement. Significantly, for the first time, we inhibited fluorescence using the compact DNA nanotube and observed dynamic fluorescent signals, indicating the controllable opening of DTO through live-cell imaging. Our results demonstrated that the DTO remained properly closed, exhibited effective internalization in ovarian cancer cells in vitro, showcasing marked differential expression of miR-21, and efficiently opened with short-term exposure to miR-21. Leveraging its autonomous behavior and compact design, the DTO emerges as a promising nanocarrier for various clinically relevant materials. It holds significant application prospects in anti-cancer therapy and the development of flexible biosensors.

Abstract Background The DELLA proteins, a class of GA signaling repressors, belong to the GRAS family of plant-specific nuclear proteins. Members of DELLA gene family encode transcriptional regulators with diverse functions in plant development and abiotic stress responses. To date, DELLAs have been identified in various plant species, such as Arabidopsis thaliana, Malus domestica, Populus trichocarpa, and other land plants. Most information of DELLA family genes was obtained from A. thaliana, whereas little is known about the DELLA gene family in blueberry. Results In this study, we identified three DELLA genes in blueberry (Vaccinium darrowii, VdDELLA) and provided a complete overview of VdDELLA gene family, describing chromosome localization, protein properties, conserved domain, motif organization, and phylogenetic analysis. Three VdDELLA members, containing two highly conserved DELLA domain and GRAS domain, were distributed across three chromosomes. Additionally, cis-acting elements analysis indicated that VdDELLA genes might play a critical role in blueberry developmental processes, hormone, and stress responses. Expression analysis using quantitative real-time PCR (qRT-PCR) revealed that all of three VdDELLA genes were differentially expressed across various tissues. VdDELLA2 was the most highly expressed VdDELLA in all denoted tissues, with a highest expression in mature fruits. In addition, all of the three VdDELLA genes actively responded to diverse abiotic stresses. Based on qRT-PCR analysis, VdDELLA2 might act as a key regulator in V. darrowii in response to salt stress, whereas VdDELLA1 and VdDELLA2 might play an essential role in cold stress response. Under drought stress, all of three VdDELLA genes were involved in mediating drought response. Furthermore, their transiently co-localization with nuclear markers in A. thaliana protoplasts demonstrated their transcriptional regulator roles. Conclusions In this study, three VdDELLA genes were identified in V. darrowii genome. Three VdDELLA genes were closely related to the C. moschata DELLA genes, S. lycopersicum DELLA genes, and M. domestica DELLA genes, respectively, indicating their similar biological functions. Expression analysis indicated that VdDELLA genes were highly efficient in blueberry fruit development. Expression patterns under different stress conditions revealed the differentially expressed VdDELLA genes responding to salt, drought, and cold stress. Overall, these results enrich our understanding of evolutionary relationship and potential functions of VdDELLA genes, which provide valuable information for further studies on genetic improvement of the plant yield and plant resistance.

Abstract Innate lymphoid cells (ILCs) are a heterogeneous population that play diverse roles in airway inflammation after exposure to allergens and infections. However, how ILCs respond after exposure to environmental toxins is not well understood. Here we show a novel method for studying the heterogeneity of rare lung ILC populations by magnetic enrichment for lung ILCs followed by particle-templated instant partition sequencing (PIP-seq). Using this method, we were able to identify novel group 1 and group 2 ILC subsets that exist after exposure to both fungal allergen and burn pit-related constituents (BPC) that include dioxin, aromatic hydrocarbon, and particulate matter. Toxin exposure in combination with fungal allergen induced activation of specific ILC1/NK and ILC2 populations as well as promoted neutrophilic lung inflammation. Oxidative stress pathways and downregulation of specific ribosomal protein genes (Rpl41 and Rps19) implicated in anti-inflammatory responses were present after BPC exposure. Increased IFNγ expression and other pro-neutrophilic mediator transcripts were increased in BPC-stimulated lung innate lymphoid cells. Further, the addition of BPC induced Hspa8 (encodes HSC70) and aryl hydrocarbon transcription factor activity across multiple lung ILC subsets. Overall, using an airway disease model that develops after occupational and environmental exposures, we demonstrate an effective method to better understand heterogenous ILC subset activation.

Abstract Observational studies have suggested the potential benefits of several medications for Parkinson’s disease (PD) and their potential for repurposing. However, the conclusions drawn from these studies are not entirely consistent. To address this inconsistency, we used the two-sample Mendelian randomization (MR) method to explore the putative causal relationships between 23 medications and the risk and progression of PD. We applied inverse-variance weighted meta-analysis (IVW) to combine MR estimates. Additionally, sensitivity analyses were conducted to evaluate the robustness of the results. Our genetic evidence suggests that thyroid preparations and calcium channel blockers reduce the risk of PD, and salicylic acid and derivatives slow the progression of PD motor symptoms. Additionally, genetic evidence also suggests that four medications were associated with PD risk or progression, but the sensitivity analysis revealed that three of the medications may have interference caused by reverse causality. Our findings suggest that there are weak causal relationships between several medications and the risk or progression of PD. Though further replication studies are needed to verify these findings, these new insights may help in understanding the etiology of the disease, generate new clues related to drug discovery, and quantify the risk of future drug intake.

In recent years, surface molecular imprinting technology has drawn a lot of attention for its application in sample pretreatment for food analysis. Due to the complexity of the food matrix, there are high requirements for the sensitivity and selectivity of food detection. Surface molecularly imprinted polymers are polymerized on the surface of a solid support, and when the template is removed, a cavity is formed to adsorb the target or its structural analogues. Various targets ranging from contaminants, toxicants and adulterants to natural active ingredients can be efficiently imprinted, thus making it easier to extract them from food matrices like dairy products, fruits and vegetables, meat products, and drinks. Owing to their potential to improve the selectivity and adsorption capacity and hence the accuracy of analysis, multi-template imprinting strategies and virtual template imprinting have become research hotspots. This article summarizes the design strategies, carrier types, preparation methods of surface molecularly imprinted polymers and reviews the progress made over the past five years in their application in sample pretreatment for food analysis in order to provide a reference for the application of surface molecularly imprinted technology in food analysis.

Abstract Aims/Introduction The aim of the present study was to evaluate the status of glycemic control, and assess the effects of the disease course and comprehensive management measures on the blood glucose level in children and adolescents with type 2 diabetes mellitus. Materials and Methods The study collected the clinical data of type 2 diabetes patients in Beijing Children's Hospital from January 2015 to September 2020. Patients were grouped based on the disease course to compare their glycated hemoglobin (HbA1c) level, islet β‐cell function, insulin resistance and comprehensive management measures. Results Of the 170 participants, the median disease course was 2.0 years (interquartile range [IQR] 1.0–4.0 years). The baseline HbA1c was 11.2% (IQR 9.2–12.4%). According to the grouping by the disease course, the median HbA1c was the lowest (5.7% [IQR 5.3–6.1%]) in the half‐year course group and the highest in the 4‐year course group (9.0 [IQR 6.8%–11.3%]). Compared with the group with a disease duration 4 years group had a lower proportion of patients with HbA1c

Abstract Background Adenomyosis is a commonly observed benign gynecological disease that affects the quality of life and social psychology of women of childbearing age. However, because of the unknown etiology and incidence of adenomyosis, its pathophysiological mechanism remains unclear; further, because no noninvasive, accurate, and individualized diagnostic methods are available, treatment and efficacy evaluations are limited. Notably, the interaction between the changes in the microecological environment of the female reproductive tract and human immunity, endocrine, and other links leads to the occurrence and development of diseases. In addition, the vaginal microbiome differs in different menstrual cycles; therefore, assessing the differences between the microbiomes of patients with adenomyosis and healthy individuals in different menstrual cycles will improve the understanding of the disease and provide references for the search for noninvasive diagnosis and individualized precision treatment of adenomyosis. This study aimed to explored the data of individuals in different menstrual cycles. Results Differences in the vaginal microbiome between patients with adenomyosis and healthy individuals were observed. At phylum level, the relative abundance of Firmicutes in the adenomyosis group was higher than that in the control group, which contributed the most to the species difference between the two groups. At the genus level, Lactobacillus was the most dominant in both groups, Alpha-diversity analysis showed significant differences in the adenomyosis and control group during luteal phase (Shannon index, p = 0.0087; Simpson index, p = 0.0056). Beta-diversity index was significantly different between the two groups (p = 0.018). However, based on Weighted Unifrac analysis, significant differences were only observed throughout the luteal phase (p = 0.0146). Within the adenomyosis group, differences between women with different menstrual cycles were also observed. Finally, 50 possible biomarkers including were screened and predicted based on the random forest analyse. Conclusions The vaginal microbiome of patients with adenomyosis and healthy individuals differed during menstrual periods, especially during the luteal phase. These findings facilitate the search for specific biological markers within a limited range and provide a more accurate, objective, and individualized diagnostic and therapeutic evaluation method for patients with adenomyosis, compared to what is currently available.

Abstract Remote sensing scene images contain numerous feature targets with unrelated semantic information, so how to extract to the local key information and semantic features of the image becomes the key to achieving accurate classification. Existing Convolutional Neural Networks (CNNs) mostly concentrate on the global representation of an image and lose the shallow features. To overcome these issues, this paper proposes LPNet for remote sensing scene image classification. First, LPNet employs LKConv to extract the semantic features in the image, while using standard convolution to extract local key information in the image. Additionally, the LPNet applies a shortcut residual concatenation branch to reuse features. Then, parameter fusion combines parameters from previous branches, improving the capacity of the model to obtain a more comprehensive and rich feature representation of the image. Finally, considering the relationship between the classification ability of the model and the depth of feature extraction, the Feature Mixture (FM) Block is used to deepen the model for feature extraction. Comparative experiments on four publicly available datasets show that LPNet provides comparable results to other state‐of‐the‐art methods. The effectiveness of LPNet is further demonstrated by visualizing the effective receptive fields (ERFs).

Abstract Background Epstein-Barr virus-associated lymphoproliferative disorders (EBV-LPDs) are a group of disorders involving lymphoid tissues or lymphocytes. The epidemiology and economic burden of hospitalized children with EBV-LPDs in China have not been well studied. This study aimed to reveal the epidemic characteristics and disease burden of EBV-LPDs among the Chinese hospitalized children, providing strategies for the prevention and management. Methods This study was based on the FUTang Updating medical REcords (FUTURE) database of China and collected the medical records from 27 tertiary children’s hospitals between January 2016 and December 2021 in China, counting five types of EBV-LPDs, namely EBV-positive T-cell lymphoproliferative disease, NK/T cell lymphoma, extranodal NK/T-cell lymphoma (nasal type), systemic EBV-positive T-cell lymphoproliferative disease of childhood and posttransplant lymphoproliferative disorders. We conducted a retrospective syhthesis and analysis of the epidemiological characteristics, expenses, length of stay (LOS), as well as complications among hospitalized children diagnosed with five types of EBV-LPDs and compared parameters using appropriate statistical tests. Results The study described 153 children aged 0–18 years hospitalized with EBV-LPDs from 2016 to 2021 in the FUTURE database. The male-to-female ratio was 1.10:1, and more than half of the age distribution was in the 6–12 y group. Among EBV-LPDs cases, EBV+ T-LPD accounted for the largest proportion (65.36%). Complications were presented in 93 children with EBV-LPDs, mainly hemophagocytic lymphohistiocytosis (HLH). The median LOS of NKTL was 26.5 days [interquartile range (IQR) = 3–42], which was the longest among EBV-LPDs. The median hospitalization cost of PTLD was 10 785.74 United States dollars (IQR = 7 329.38–16 531.18), which was the heaviest among EBV-LPDs. Conclusions Compared with the total number of hospitalized children in China during the same period and in the same age group, the proportion of EBV-LPD is very low. EBV-LPD can develop in all age groups, but it is more common in school-age children. Among 5 EBV-LPDs, the disease with the highest proportion is EBV+ T-LPD. The overall disease burden of EBV-LPD was heavy, especially the economic burden. HLH was one of the most common complications, which could directly affect the burden of patients because of prolonged hospitalization. These data are taken from a very large database, illustrating the epidemiological and economic burden of EBV-LPDs hospitalized children in China, which enriched the existing epidemiological and disease burden content of EBV-LPDs.

Abstract Background Multiple epiphyseal dysplasia-4 (MED-4, MIM 226900) is a rare autosomal recessive disease characterized by disproportionate height and early onset osteoarthritis of the lower limbs. MED-4 is caused by homozygous or compound heterozygous pathogenic variants in the SLC26A2 gene. However, the underlying pathogenic mechanisms in chondrocytes remains unknown. This study aimed to identify the pathogenic variants within a MED-4 family and explore the molecular etiology of this condition in human primary chondrocyte cells. Methods Clinical data were recorded and peripheral blood samples were collected for analysis. Whole exome sequencing (WES) and bioinformatic analyses were performed to determine causative variants. Wild-type SLC26A2 and corresponding mutant expression plasmids were constructed and transfected into human primary chondrocytes. The expression and subcellular distribution of SLC26A2 protein in chondrocytes were detected by immunoblotting and immunofluorescence. Effects of these variants on chondrocytes viability and apoptosis were measured by Cell Counting Kit-8 (CCK-8) assay. Expression of genes related to cartilage homeostasis was subsequently analyzed by quantitative real-time polymerase chain reaction (qRT-PCR). Results We identified two compound heterozygous variants c.1020_1022delTGT(p.Val341del) and c.1262 T > C(p.Ile421Thr) in the SLC26A2 gene in the patients. Mutant SLC26A2Val341del and SLC26A2Ile421Thr proteins were distributed in relatively few cells and were observed only within the nucleus. The viability of chondrocytes with the SLC26A2 variant group was similar to the wild-type (WT) group. However, the protein expressions of SLC26A2Val341del and SLC26A2Ile421Thr were decreased compared with SLC26A2WT. Expression levels of matrix metallopeptidase 13 (MMP13), α-1 chain of type X collagen (COL10A1), and Runt-related transcription factor 2 (RUNX2) were significantly decreased in the variant group. However, aggrecan (ACAN) expression was higher in the variant group than the WT group. Conclusions Overall, our data demonstrate that the variants p.Val341del and p.Ile421Thr in SLC26A2 cause MED-4 and that these two variants promote chondrocyte proliferation while inhibiting chondrocyte differentiation.

Erdheim-Chester Disease (ECD) is a rare form of histiocytosis characterized by xanthomatous infiltration of affected organs. We present a case of a 62-year-old man with ECD initially presenting with constrictive pericarditis. Comprehensive imaging revealed systemic involvement, including the skeleton, orbit, pituitary, lung, kidney, and retroperitoneum, despite the absence of related symptoms. The diagnosis of ECD was eventually confirmed through histopathological evidence from a CT-guided biopsy. The patient responded well to interferon-α2b treatment, with gradual symptom amelioration and improvement in imaging and laboratory findings over a 5-month follow-up period. This case highlights the importance of considering ECD in the differential diagnosis of constrictive pericarditis and the utility of multimodal imaging for accurate diagnosis and management of this rare disease. The patient's positive response to treatment also highlights the potential for effective management of ECD, particularly with early diagnosis and intervention.

Owing to the integration of energy digitization and artificial intelligence technology, smart energy grids can realize the stable, efficient and clean operation of power systems. However, the emergence of cyber-physical attacks, such as dynamic load-altering attacks (DLAAs) has introduced great challenges to the security of smart energy grids. Thus, this study developed a novel cyber-physical collaborative security framework for DLAAs in smart energy grids. The proposed framework integrates attack prediction in the cyber layer with the detection and localization of attacks in the physical layer. First, a data-driven method was proposed to predict the DLAA sequence in the cyber layer. By designing a double radial basis function network, the influence of disturbances on attack prediction can be eliminated. Based on the prediction results, an unknown input observer-based detection and localization method was further developed for the physical layer. In addition, an adaptive threshold was designed to replace the traditional precomputed threshold and improve the detection performance of the DLAAs. Consequently, through the collaborative work of the cyber-physics layer, injected DLAAs were effectively detected and located. Compared with existing methodologies, the simulation results on IEEE 14-bus and 118- bus power systems verified the superiority of the proposed cyber-physical collaborative detection and localization against DLAAs.

Cutaneous neurofibroma (cNF) is a prevalent clinical manifestation of neurofibromatosis type 1, significantly affecting the well-being and quality of life of the affected individuals. The adoption of reliable and reproducible volumetric measurement techniques is essential for precisely evaluating tumor burden and plays a critical role in the development of effective treatments for cNF. This study focuses on widely used volumetric measurement techniques, including vernier calipers, ultrasound, computed tomography, magnetic resonance imaging, and three-dimensional scanning imaging. It outlines the merits and drawbacks of each technique in assessing the cNF load, providing an overview of their current applications and ongoing research advancements in this domain.

Abstract Background There is no individualized prediction model for intensive care unit (ICU) admission on patients with community-acquired pneumonia (CAP) and connective tissue disease (CTD) so far. In this study, we aimed to establish a machine learning-based model for predicting the need for ICU admission among those patients. Methods This was a retrospective study on patients admitted into a University Hospital in China between November 2008 and November 2021. Patients were included if they were diagnosed with CAP and CTD during admission and hospitalization. Data related to demographics, CTD types, comorbidities, vital signs and laboratory results during the first 24 h of hospitalization were collected. The baseline variables were screened to identify potential predictors via three methods, including univariate analysis, least absolute shrinkage and selection operator (Lasso) regression and Boruta algorithm. Nine supervised machine learning algorithms were used to build prediction models. We evaluated the performances of differentiation, calibration, and clinical utility of all models to determine the optimal model. The Shapley Additive Explanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) techniques were performed to interpret the optimal model. Results The included patients were randomly divided into the training set (1070 patients) and the testing set (459 patients) at a ratio of 70:30. The intersection results of three feature selection approaches yielded 16 predictors. The eXtreme gradient boosting (XGBoost) model achieved the highest area under the receiver operating characteristic curve (AUC) (0.941) and accuracy (0.913) among various models. The calibration curve and decision curve analysis (DCA) both suggested that the XGBoost model outperformed other models. The SHAP summary plots illustrated the top 6 features with the greatest importance, including higher N-terminal pro-B-type natriuretic peptide (NT-proBNP) and C-reactive protein (CRP), lower level of CD4 + T cell, lymphocyte and serum sodium, and positive serum (1,3)-β-D-glucan test (G test). Conclusion We successfully developed, evaluated and explained a machine learning-based model for predicting ICU admission in patients with CAP and CTD. The XGBoost model could be clinical referenced after external validation and improvement.

Abstract Tumorigenesis is a multistep process, with oncogenic mutations in a normal cell conferring clonal advantage as the initial event. However, despite pervasive somatic mutations and clonal expansion in normal tissues, their transformation into cancer remains a rare event, indicating the presence of additional driver events for progression to an irreversible, highly heterogeneous, and invasive lesion. Recently, researchers are emphasizing the mechanisms of environmental tumor risk factors and epigenetic alterations that are profoundly influencing early clonal expansion and malignant evolution, independently of inducing mutations. Additionally, clonal evolution in tumorigenesis reflects a multifaceted interplay between cell-intrinsic identities and various cell-extrinsic factors that exert selective pressures to either restrain uncontrolled proliferation or allow specific clones to progress into tumors. However, the mechanisms by which driver events induce both intrinsic cellular competency and remodel environmental stress to facilitate malignant transformation are not fully understood. In this review, we summarize the genetic, epigenetic, and external driver events, and their effects on the co-evolution of the transformed cells and their ecosystem during tumor initiation and early malignant evolution. A deeper understanding of the earliest molecular events holds promise for translational applications, predicting individuals at high-risk of tumor and developing strategies to intercept malignant transformation.

Abstract Rock abrasivity is one of the main factors affecting the wear of rock-cutting tools, which is usually quantified by the CERCHAR Abrasivity Index (CAI). Researchers and engineers study tool wear and predict tool life based on the CAI of rocks. However, there is still a lack of a dataset on rock properties, especially the abrasivity of various rocks. This paper reports the abrasive dataset of 10 kinds of rocks, including sedimentary rocks, metamorphic rocks, and igneous rocks, with the aid of the CERCHAR Abrasivity Test and digital measurement techniques. The dataset comprises rock abrasivity data, point cloud data for visualization, scratch photos, CERCHAR Abrasivity Test force data, and mechanical properties (uniaxial compressive strength) of rock samples. This dataset facilitates future research on rock abrasivity and rock-cutting tool wear.

To investigate the effects of different brine and fermentation methods on the quality characteristics of fermented chili peppers, this study employed four different fermentation methods: Natural fermentation with sterile water, co-inoculation fermentation (Lactiplantibacillus plantarum KUST-D1303:Pichia manshurica KUST-F1705=1:1) with sterile water, natural fermentation with aged brine and co-inoculation fermentation with aged brine. The quality characteristics of the fermented chili peppers were compared and analyzed. Results showed that compared to other fermentation methods, co-inoculation fermentation with aged brine significantly (P

Objective: Type 2 diabetes (T2DM) is a significant risk factor for coronary heart disease (CHD). This study aimed to assess the variations in biomarkers associated with CHD in T2DM patients across different age groups in the Han Chinese population. Methods: A strict selection process was employed, involving three groups: a control group (n = 300) with no medical history, a new-onset T2DM group (n = 300), and a new-onset T2DM + CHD group (n = 300). Participants in each group were further categorized based on age: Group 1 (75 years). Fasting glucose, hemoglobin A1c (HbA1c), triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), ApoB/ApoA1 ratio, lipoprotein(a) [Lp(a)], high-sensitivity C-reactive protein (hsCRP), and homocysteine (HCY) levels were analyzed in all groups. Results: Both T2DM and T2DM + CHD groups exhibited elevated levels of TG, TC, LDL-C, ApoB, ApoB/ApoA1, Lp(a), hsCRP, and HCY, alongside decreased levels of HDL-C and ApoA1 in comparison to the control group. Notably, when comparing the T2DM to the T2DM + CHD groups, significant increases were noted in ApoB, Lp(a), and hsCRP levels in the T2DM + CHD group, whereas other biomarkers did not show significant differences. Across all age groups, the patterns remained consistent, with the T2DM and T2DM + CHD groups showing elevated levels of TG, TC, LDL-C, ApoB, ApoB/ApoA1, Lp(a), hsCRP, and HCY, and decreased levels of HDL-C and ApoA1 compared to their respective age-matched control groups. Furthermore, within each age category, significant increases in ApoB, Lp(a), and hsCRP were specifically observed with advancing age in the T2DM + CHD group, with Lp(a) and hsCRP levels showing particularly notable elevations, underscoring their potential as significant indicators of CHD risk in the T2DM population. Conclusion: Lp(a) and hsCRP may serve as valuable risk biomarkers for the development of CHD in T2DM patients. Understanding the variations in these biomarkers across different age groups can assist in risk assessment and the development of personalized management strategies for CHD in T2DM patients.

To investigate the functioning mechanism of cruise altitude on transportation and discharging dynamics of onboard fire-extinguishants, a numerical model coupling the vaporization and flowing process is established for the Halon 1301-N2 multi-component two-phase flow inside the onboard fire-extinguishing system based on computational fluid dynamics. Flowing and transportation parameters are simulated and compared for Halon 1301 at 0 m, 3000 m, 6000 m and 12000 m. Moreover, the peak discharging fluid pressure, velocity and density are also analyzed to evaluate the impact of altitude on discharging dynamics of Halon 1301. Notably, the maximum discharging velocity at 3000 m, 6000 m and 12000 m are reduced by 4 %, 9 % and 15 % relative to that at 0 m; the maximum discharging fluid pressure and density at 12000 m are respectively reduced by 32 % and 12 % relative to those at 0 m. High altitude is unraveled to inhibit the vaporization of Halon 1301 and lower the discharging efficiency at the pipeline outlet, consequently lowering the diffusion efficiency and effective concentration of Halon 1301 in the protected area and further weakening the fire-suppression effectiveness. The unveiled insights afford guidance for the optimization of fire-extinguishing systems to improve the fire-fighting capability of airplanes at high altitudes.

Abstract The molecular representation model is a neural network that converts molecular representations (SMILES, Graph) into feature vectors, and is an essential module applied across a wide range of artificial intelligence‐driven drug discovery scenarios. However, current molecular representation models rarely consider the three‐dimensional conformational space of molecules, losing sight of the dynamic nature of small molecules as well as the essence of molecular conformational space that covers the heterogeneity of molecule properties, such as the multi‐target mechanism of action, recognition of different biomolecules, dynamics in cytoplasm and membrane. In this study, a new model named GeminiMol is proposed to incorporate conformational space profiles into molecular representation learning, which extracts the feature of capturing the complicated interplay between the molecular structure and the conformational space. Although GeminiMol is pre‐trained on a relatively small‐scale molecular dataset (39290 molecules), it shows balanced and superior performance not only on 67 molecular properties predictions but also on 73 cellular activity predictions and 171 zero‐shot tasks (including virtual screening and target identification). By capturing the molecular conformational space profile, the strategy paves the way for rapid exploration of chemical space and facilitates changing paradigms for drug design.

Abstract The response of vegetation to climate change on a large scale should be studied at the community level rather than the species level. This necessitates a focused exploration of emerging spatial patterns. Here, we surveyed 264 sites in the Inner Mongolia typical steppe, using the “needling” method to investigate 39,600 clumps formed through the coexistence relationships of dominant species. We found that the effects of slow climate change on grassland communities can be categorized into two general trends: (1) a monotone relationship, characterized by changes in the number of dominant species, compositional diversity, and optimal patch area, and (2) a unimodal relationship, reflected in variations in the number of patches and interspecific associations. The two distinct trends, connected by optimal patch area, concurrently support both the habitat amount hypothesis and the intermediate disturbance hypothesis. These findings suggest that climate change indirectly influences the area and amount of vegetation patches by regulating the arrangement of clumps. Moreover, they indicate that it is the distribution, rather than the number, of species that serves as the front line for plant communities adapting to climate change.

BackgroundAging is marked by the gradual deterioration of cells, tissues, and organs and is a major risk factor for many chronic diseases. Considering the complex mechanisms of aging, traditional Chinese medicine (TCM) could offer distinct advantages. However, due to the complexity and variability of metabolites in TCM, the comprehensive screening of metabolites associated with pharmacology remains a significant issue.MethodsA reliable and integrated identification method based on UPLC-Q Exactive-Orbitrap HRMS was established to identify the chemical profiles of Huan Shao Dan (HSD). Then, based on the theory of sequential metabolism, the metabolic sites of HSD in vivo were further investigated. Finally, a deep learning model and a bioactivity assessment assay were applied to screen potential anti-aging metabolites.ResultsThis study identified 366 metabolites in HSD. Based on the results of sequential metabolism, 135 metabolites were then absorbed into plasma. A total of 178 peaks were identified from the sample after incubation with artificial gastric juice. In addition, 102 and 91 peaks were identified from the fecal and urine samples, respectively. Finally, based on the results of the deep learning model and bioactivity assay, ginsenoside Rg1, Rg2, and Rc, pseudoginsenoside F11, and jionoside B1 were selected as potential anti-aging metabolites.ConclusionThis study provides a valuable reference for future research on the material basis of HSD by describing the chemical profiles both in vivo and in vitro. Moreover, the proposed screening approach may serve as a rapid tool for identifying potential anti-aging metabolites in TCM.

IntroductionThe objective of this study was to assess the clinical characteristics and biometric parameters, as measured by the IOLMaster, of patients suffering from acute secondary angle closure due to zonular dialysis (ASAC-ZD) who were misdiagnosed with acute primary angle closure (APAC).MethodsIn this retrospective study, 34 ASAC-ZD and 39 APAC eyes were examined. Sex, age, best-corrected visual acuity, axial length (AL), anterior chamber depth (ACD), anterior chamber depth standard deviation (ACDSD), lens thickness (LT), and lens thickness standard deviation (LTSD) were measured using the IOLMaster and compared between the two groups. In addition, the difference in ACD (ACD difference) between the affected eye and the contralateral eye was analyzed. Logistic regression analysis was performed to determine the predictive factors of lens subluxation. To determine the appropriate cutoff values for biometric parameters, ROC curves were constructed to distinguish between ASAC-ZD, APAC, and cataracts.ResultsCompared to the APAC group, the ASAC-ZD group was younger (69.92 ± 9.345, 63.74 ± 6.947), had longer AL (22.39 ± 0.7852, 23.23 ± 1.168), shallower ACD (2.120 ± 0.2986, 1.889 ± 0.5167), higher ACDSD (7.605 ± 5.425, 9.941 ± 6.120), higher LTSD (28.00 ± 19.52, 39.79 ± 22.74), and larger ACD differences (−0.1249 ± 0.2349, −0.7306 ± 0.5332) in the affected eye. Younger age, longer AL, lower ACD, higher LTSD, and higher ACD differences were associated with lens subluxation in the univariate logistic regression analysis. ACD difference (p = 0.0003), age (p = 0.0024), and ACD (p = 0.0491) were significantly associated with lens subluxation in the multivariable logistic regression analysis. Furthermore, the ROC curve analysis showed that the cutoff values for lens subluxation were a difference in ACD of 0.225 mm and 1.930 mm.ConclusionAsymmetric ACD in both eyes with normal AL and increasing ACDSD and LTSD may support the clinical diagnosis of lens subluxation.

ABSTRACT Brain abscess is a severe infection characterized by the accumulation of pus within the brain parenchyma. Accurate identification of the causative pathogens is crucial for effective treatment and improved patient outcomes. This 10-year retrospective, single-center study aimed to compare the detection performance of conventional culture methods and metagenomic next-generation sequencing (mNGS) in brain abscess. We reviewed 612 patients diagnosed with brain abscess and identified 174 cases with confirmed etiology. The median age was 52 years, with 69.5% males. Culture tests predominately identified gram-positive bacteria, particularly Streptococcus spp. Gram-negative bacteria, including Klebsiella spp., were also detected. However, mNGS revealed a more diverse pathogen spectrum, focusing on anaerobes (e.g., Fusobacterium spp., Parvimonas spp., Porphyromonas spp., Prevotella spp., and Tannerella spp.). mNGS exhibited significantly higher overall pathogen-positive rates in pus samples (85.0% vs 50.0%, P = 0.0181) and CSF samples (84.2% vs 7.9%, P < 0.0001) compared to culture. Furthermore, the detection rates for anaerobes displayed a notable disparity, with mNGS yielding significantly higher positive detections in both pus samples (50.0% vs 10%, P = 0.0058) and CSF samples (18.4% vs 0%, P = 0.0115) when compared to culture methods. The assistance of mNGS in pathogen detection, particularly anaerobes in brain abscess, was evident in our findings. mNGS demonstrated the ability to identify rare and fastidious pathogens, even in culture-negative cases. These results emphasize the clinical value of mNGS as a supplement for brain abscess, enabling more comprehensive and accurate pathogen identification.IMPORTANCEThe accurate identification of pathogens causing brain abscess is crucial for effective treatment and improved patient outcomes. In this 10-year retrospective study, the detection performance of conventional culture methods and metagenomic next-generation sequencing (mNGS) was compared. The study analyzed 612 patients with brain abscess and confirmed etiology in 174 cases. The results showed that culture tests predominantly identified gram-positive bacteria, while mNGS unveiled a broader diverse pathogen spectrum, particularly anaerobes. The mNGS method exhibited significantly higher overall rates of pathogen positivity both in pus and cerebrospinal fluid (CSF) samples, surpassing the culture methods. Notably, mNGS detected a significantly higher number of anaerobes in both pus and CSF samples compared to culture methods. These findings underscore the clinical value of mNGS as a supplement for brain abscess diagnosis, enabling more comprehensive and accurate pathogen identification, particularly for rare and fastidious pathogens that evade detection by conventional culture methods.

The aroma profile of fermented chili pepper was analyzed using gas chromatography–mass spectrometry (GC–MS) coupled with chromatography-olfactometry (GC-O). A total of 19 aroma-active compounds were detected, exhibiting aroma intensities spanning from 1.8 to 4.2. And 12 aroma-active compounds were determined as pivotal odorants through odor activity value (OAV) calculation. Concentrations of these aroma-active compounds were quantified and subsequently employed in reconstructing the aroma profile of fermented chili pepper. Quantitative descriptive sensory analysis and electronic nose analysis proved that the aroma profile of fermented chili pepper was basically reconstituted. Omission experiments confirmed that methyl salicylate, linalool, 2-methoxy-3-isobutylpyrazine, and phenylethyl alcohol were the key aroma-active compounds of fermented chili pepper. Moreover, the perceptual interactions between the key aroma-active compounds were investigated. It was found that methyl salicylate masked the floral aroma, while phenylethyl alcohol had an additive effect on the aroma of linalool and 2-methoxy-3-isobutylpyrazine.

IntroductionOsteoarthritis (OA) is a globally prevalent joint disorder affecting approximately 240 million individuals worldwide. Cinnamaldehyde, known for its broad anti-inflammatory and anti-aging effects across various cell types, has not been investigated for its potential impact on apoptosis in OA chondrocytes.MethodsTo explore the effectiveness of cinnamaldehyde in mitigating knee osteoarthritis by reducing chondrocyte apoptosis, bioinformatics analysis was first conducted to identify apoptosis-associated differentially expressed genes (APDEGs). Gene expression datasets GSE55235 and GSE114007 were analyzed using weighted gene co-expression network analysis (WGCNA). Gene modules of interest were cross-referenced with APDEGs to identify those specific to OA. LASSO regression analysis was employed to build a risk model, and this model, along with datasets GSE114007, GSE55457, and GSE12021, was validated using ROC analysis. Cellular experiments and blood analyses from OA patients were performed to evaluate the effects of cinnamaldehyde on apoptosis-related gene expression.ResultsCinnamaldehyde administration was found to rectify the abnormal expression of key apoptosis-related genes in OA patients. Specifically, cinnamaldehyde may affect knee osteoarthritis by regulating apoptosis-related genes such as ZFAND5, BCL6, ELL2, FOSL2, MARCKS, and SGCD. Additionally, three novel apoptotic targets in OA chondrocytes—ZFAND5, ELL2, and SGCD—were identified.DiscussionThese findings provide significant theoretical support for the clinical use of cinnamaldehyde in OA treatment. The discovery of novel apoptotic targets presents new therapeutic possibilities for future OA interventions.

BackgroundIn recent years, the position of PCSK9 inhibitors as adjuvant therapy to statins in guidelines has further improved. However, there remained a dearth of direct comparative studies among different PCSK9 inhibitors. Therefore, this study aimed to conduct a network meta-analysis to evaluate the efficacy and safety of different PCSK9 inhibitors combined with statins.MethodsA comprehensive literature search was conducted from the study's inception to 12 November 2023, encompassing multiple online databases including PubMed, Embase, Cochrane Central, Web of Science, and ClinicalTrials.gov to obtain relevant randomized controlled trials. Frequentist network meta-analysis was employed to compare the efficacy and safety of different PCSK9 inhibitors. The efficacy endpoints were low-density lipoprotein cholesterol (LDL-C), apolipoprotein B (ApoB), and lipoprotein (a) (Lp(a)). The safety endpoints were any adverse events (AE), severe adverse events (SAE), AE leading to treatment discontinuation, and injection-site reaction.ResultsCompared with placebo and ezetimibe, all PCSK9 inhibitors demonstrated significant reductions in LDL-C levels. Notably, evolocumab exhibited the most pronounced effect with a treatment difference of −63.67% (−68.47% to −58.87%) compared with placebo. Regarding dosage selection for evolocumab, the regimen of 140 mg Q2W (−69.13%, −74.55% to −63.72%) was superior to 420 mg QM (−61.51%, −65.97% to −57.05%). Based on rankings and P-scores analysis, tafolecimab 150 mg Q2W demonstrated superior efficacy in reducing ApoB levels (−61.70%, −84.38% to −39.02%) and Lp(a) levels (−43%, 30%, −68%, 81% to −17%, 79%). Furthermore, the safety profile of PCSK9 inhibitors was favorable with no increase in the incidence of AE, SAE, or AE leading to treatment discontinuation; however, alirocumab, inclisiran, and tafolecimab may potentially entail a potential risk associated with injection-site reactions.ConclusionCompared with placebo and ezetimibe, PCSK9 inhibitors can significantly reduce LDL-C, ApoB, and Lp(a) when combined with statins to treat hypercholesterolemia. Furthermore, PCSK9 inhibitors and ezetimibe exhibit similar safety profiles.Systematic Review Registration[PROSPERO], identifier [CRD42023490506].

IntroductionUnderstanding the microbial diversity and potential functional dynamics within the rhizocompartments of Dendrobium huoshanense is crucial for unraveling the plant–microbe interactions that influence its medicinal properties.MethodsThis study is the first to characterize the microbiome associated with the rhizocompartments of D. huoshanense, including its cultivation medium, rhizosphere, rhizoplane, and root endosphere, using high-throughput sequencing and subsequent bioinformatic analysis.ResultsBacterial phylogenetic diversity was significantly higher in the endosphere than in the rhizosphere, while fungal α-diversity significantly decreased from the cultivation medium to the endosphere. Both bacterial and fungal niche widths decreased from the cultivation medium to the endosphere. β-Diversity analysis revealed distinct spatial patterns in both bacterial and fungal communities across the rhizocompartments, with the most pronounced differences between the cultivation medium and the endosphere. Taxonomically, Proteobacteria and Ascomycota were predominant in the endosphere for bacterial and fungal communities, respectively. Functional predictions showed significant enrichment of pathways related to xenobiotics biodegradation, lipid metabolism, and nitrogen fixation in the endosphere, while functions associated with plant pathogens and saprotrophs were significantly reduced.DiscussionThe results indicate a shift from generalist to specialist microbes from the cultivation medium to the endosphere, suggesting that D. huoshanense exerts strong selective pressure for endophytic fungi. Interestingly, a high proportion of fungi with unknown functions were found in the endosphere, highlighting an area for further research regarding the medicinal efficacy of D. huoshanense. Overall, this study provides foundational data for understanding the adaptive evolution of these microbial communities in response to specific microhabitats.

Background: Pancreatic cancer is a serious, usually fatal disease and one of the most aggressive malignancies. Research into whether hormone replacement therapy (HRT) might protect against pancreatic cancer has yielded mixed results. This study aimed to investigate the potential association between HRT and the risk of pancreatic cancer in postmenopausal women. Methods: This population-based, retrospective study extracted data from the US National Inpatient Sample (NIS) 2008–2018. Hospitalized females aged ≥55 years were eligible for inclusion. Associations between HRT, other study variables, and pancreatic cancer diagnosis were determined using univariate and multivariable regression analyses. Results: After 1:4 matching by age, data of postmenopausal women with (n = 35,309) and without (n = 141,236) HRT were included in the analysis. The mean age was 73.4 years. Multivariable analyses showed that women with HRT had significantly decreased odds of pancreatic cancer (adjusted OR [aOR], 0.69, 95 % CI: 0.53–0.90). Compared to patients without HRT, patients with HRT in the 55-64-year-old group (aOR 0.48, 95 % CI: 0.32–0.74), 65-74-year-old group (aOR 0.49, 95 % CI: 0.34–0.71), non-hypertensive group (aOR 0.55, 95 % CI: 0.38–0.79), and non-hyperlipidemia group (aOR 0.59, 95 % CI: 0.42–0.82) had significantly decreased odds of pancreatic cancer. Conclusions: In US postmenopausal women, HRT is associated with a reduced risk of pancreatic cancer, especially those aged 55–74 year. Further study is needed to clarify the mechanisms underlying the associations.

Drug conjugates are obtained from tumor-located vectors connected to cytotoxic agents via linkers, which are designed to deliver hyper-toxic payloads directly to targeted cancer cells. These drug conjugates include antibody-drug conjugates (ADCs), peptide-drug conjugates (PDCs), small molecule-drug conjugates (SMDCs), nucleic acid aptamer-drug conjugates (ApDCs), and virus-like drug conjugate (VDCs), which show great therapeutic value in the clinic. Drug conjugates consist of a targeting carrier, a linker, and a payload. Payloads are key therapy components. Cytotoxic molecules and their derivatives derived from natural products are commonly used in the payload portion of conjugates. The ideal payload should have sufficient toxicity, stability, coupling sites, and the ability to be released under specific conditions to kill tumor cells. Microtubule protein inhibitors, DNA damage agents, and RNA inhibitors are common cytotoxic molecules. Among these conjugates, cytotoxic molecules of natural origin are summarized based on their mechanism of action, conformational relationships, and the discovery of new derivatives. This paper also mentions some cytotoxic molecules that have the potential to be payloads. It also summarizes the latest technologies and novel conjugates developed in recent years to overcome the shortcomings of ADCs, PDCs, SMDCs, ApDCs, and VDCs. In addition, this paper summarizes the clinical trials conducted on conjugates of these cytotoxic molecules over the last five years. It provides a reference for designing and developing safer and more efficient conjugates.

The delicate plateau lake ecosystem has been further damaged by extensive human construction projects, leading to water pollution in Lake Dianchi, China. This serves as a prominent example of urbanization and human interference, drawing global scholarly interest. Restoring Lake Dianchi’s water quality remains a global challenge despite 40 years of treatment, with unclear links to surrounding land development. Therefore, this study constructed a GIS database, combined with 2013–2023 landsat-8/MODIS, Land Use/Land Cover (LULC) remote sensing data and multi-year water quality monitoring, to conduct a multi-scale analysis of the plateau Lake Dianchi and its surrounding land, and implemented it through a Self-Organizing Map (SOM). The classification of lakeshore pollution source clusters was further analyzed through Redundancy Analysis to explore the interaction and future trends between lake water quality and land development in the lakeshore zone. Research indicates the following: (1) According to cluster analysis, water quality in semi-urban lakeside areas (cluster 2) had the highest correlation with lakeside land use, followed by urban areas (cluster 1) and rural areas (cluster 3); (2) Lake water pollution was difficult to improve through the optimization of land development in the lakeshore zone. Combined with the results from (1), although semi-urban areas had a certain impact on water quality, over time, there was a trend of decorrelation between the steady state of water quality pollution and the development of urban construction. This trend indicates that urban development consistently contributes to single pollution sources in water quality; (3) At different scales, the water pollution index in semi-urban areas responded significantly to construction activities, indicating signs of tele-coupling; the response to farmland was complex, while the response to green space was small; (4) In the process of decorrelation between lake water quality and land development, the rate in urban areas (cluster 1) and rural areas (cluster 3) was faster than that in semi-urban lakeside areas (cluster 2). To sum up, it is difficult to restore the water quality of Lake Dianchi through optimizing urban land layout. Meanwhile, it is necessary to further prevent and control the impact of remote pollution sources on the water quality of Lake Dianchi. Protection of the plateau lake environment cannot remain at the optimization level; it should further realize the principles of multi-dimensional governance. This is also the key to addressing the lack of results in Lake Dianchi management for many years.