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Atopic dermatitis (AD) is a common chronic inflammatory skin diseases that seriously affects life quality of the patients. ( ) colonization on the skin plays an important role in the pathogenesis of AD; however, the mechanism of how it modulates skin immunity to exacerbate AD remains unclear. MicroRNAs are short non-coding RNAs that act as post-transcriptional regulators of genes. They are involved in the pathogenesis of various inflammatory skin diseases. In this study, we established miRNA expression profiles for keratinocytes stimulated with heat-killed (HKSA). The expression of miR-939 in atopic dermatitis patients was analyzed by fluorescence in situ hybridization (FISH). miR-939 mimic was transfected to human primary keratinocyte to investigate its impact on the expression of matrix metalloproteinase genes (MMPs) . Subsequently, miR-939, along with Polyplus transfection reagent, was administered to MC903-induced atopic dermatitis skin to assess its function . MiR-939 was highly upregulated in HKSA-stimulated keratinocytes and AD lesions. studies revealed that miR-939 increased the expression of matrix metalloproteinase genes, including MMP1, MMP3, and MMP9, as well as the cell adhesion molecule ICAM1 in human primary keratinocytes. studies indicated that miR-939 increased the expression of matrix metalloproteinases to promote the colonization of and exacerbated -induced AD-like skin inflammation. Our work reveals miR-939 is an important regulator of skin inflammation in AD that could be used as a potential therapeutic target for AD.

The increasing need for sustainable practices has encouraged listed companies to participate in carbon trading markets. Traditional centralized systems for managing carbon trading data often face challenges such as limited transparency, poor traceability, and security risks, leading to inefficiencies and compliance issues. This research proposes a blockchain-based framework with smart contracts to provide a secure, decentralized mechanism for recording and verifying carbon trading data. The system ensures tamper-proof logs of emission allowances, trading transactions, and verification events, enabling real-time access for regulatory authorities. Data preprocessing uses Z-score normalization to standardize inputs, while Kernel Principal Component Analysis (KPCA) reduces dimensionality and extracts relevant features. To improve decision-making and cost-efficiency, a Dynamic Cuckoo Search-mutated Locust Swarm Optimization (DCSLSO) algorithm is embedded within the smart contracts to optimize carbon credit allocation and trading strategies. The framework is evaluated through simulations under varying energy demands, carbon prices, and multi-fuel scenarios, using synthetic datasets from energy-intensive industries. The DCSLSO model is implemented using Python and TensorFlow. This research demonstrates that blockchain technology, combined with intelligent smart contracts, can modernize carbon trading for listed companies, fostering transparency, accountability, and long-term economic sustainability in emissions management. This research highlights the potential of combining blockchain technology with intelligent optimization to modernize carbon markets, promoting transparency, accountability, and sustainable economic growth in emissions management.

Grassland canopy height is one of the most important traits for determining plant diversity and community structure, directly affecting the resource use efficiency of livestock in grassland ecosystems. However, broad-scale changes in grassland canopy height are seldom reported due to the complex effects of species aggregation on both interspecific and intraspecific structures. Here, we decouple grassland aboveground biomass into vertical and horizontal allocations, thereby offering a pathway to mirror changes in grassland canopy height. Grassland aboveground biomass is estimated using a machine learning algorithm by fusing climatic factors, satellite-driving metrics, and 8-year consecutive ground-truth surveys; the horizontal allocation of grassland aboveground biomass is derived from optimized linear spectral mixture analysis. We find that changes in horizontal biomass allocation primarily accounted for increases in Chinese grassland aboveground biomass from 2001 to 2022, resulting in a significant decline in grassland canopy height. The decline in grassland canopy height is shaped by reduced radiation and, more importantly, by the combined effects of warming and grazing, while also being related to variations in plant diversity. The dwarfing grassland community with declining canopy height may increase the impact of livestock disturbances, thus diminishing the resistance of grassland ecosystems to climate fluctuations. Grassland canopy height shapes plant community structure and grazing efficiency, yet large-scale trends remain poorly quantified. Using nationwide data, this study suggests that canopy height has declined across China, in association with asymmetric biomass allocation.

China has the largest population with diabetes globally, with over half of the cases going undiagnosed, highlighting the need for improved screening efforts. This study aimed to adapt the Finnish Diabetes Risk Score (FINDRSC), a widely used tool for assessing diabetes risk without relying on clinical indicators, for screening undiagnosed hyperglycemia and diabetes among Chinese adults. Data from the China Health and Nutrition Survey (CHNS), collected in the 2009 wave, were utilized as the training data (n = 7277), and data from the Guangzhou Nutrition and Health Study (GNHS, n = 2970), conducted in the years 2011-2014, were used for validation. Diabetes was defined as fasting plasma glucose (FPG) ≥ 7.0 mmol/L and/or glycated hemoglobin A1c (HbA1c) ≥ 6.5%. Hyperglycemia was defined as FPG ≥ 5.6 mmol/L and/or HbA1c ≥ 5.7%. Predictors in the original FINDRISC model were adjusted according to local standards and guidelines to develop the Modified Chinese screening model (ModChinese). Coefficients and scores of the ModChinese model were estimated using logistic regression. Area under the receiver operating characteristic curve (AUC) was calculated to evaluate model performance. The prevalence of undiagnosed diabetes and prediabetes was 8.6% and 40.1% in CHNS, and 3.1% and 27.9% in GNHS, respectively. The ModChinese demonstrated superior performance compared to the original FINDRISC, with higher AUC values for detecting both diabetes (0.707 vs. 0.681, p = 0.001) and hyperglycemia (0.680 vs. 0.661, p < 0.001) in the CHNS. Similar improvements were observed in the GNHS, where the ModChinese achieved AUC values of 0.663 for diabetes and 0.606 for hyperglycemia, compared to FINDRISC's 0.622 and 0.593, respectively. Compared with the original FINDRISC, the ModChinese model showed improved sensitivity and specificity for screening undiagnosed diabetes and enhanced sensitivity for hyperglycemia screening in both training and validation datasets. The ModChinese model is a simple and effective screening tool for identifying undiagnosed diabetes and hyperglycemia in Chinese adults.

The cell transition from an inflammatory phase to a subsequent proliferative phase is crucial for wound healing, yet the driving mechanism remains unclear. By profiling lncRNA expression changes during human skin wound healing and screening lncRNA functions, we identify SNHG26 as a pivotal regulator in keratinocyte progenitors underpinning this phase transition. Snhg26 -deficient mice exhibit impaired wound repair characterized by delayed re-epithelization accompanied by exacerbated inflammation. Single-cell transcriptome analysis combined with gain-of-function and loss-of-function of SNHG26 in vitro and ex vivo reveals its specific role in facilitating inflammatory-to-proliferative state transition of keratinocyte progenitors. A mechanistic study unravels that SNHG26 interacts with and relocates the transcription factor ILF2 from inflammatory genomic loci, such as JUN, IL6, IL8 , and CCL20 , to the genomic locus of LAMB3 . Collectively, our findings suggest that lncRNAs play cardinal roles in expediting tissue repair and regeneration and may constitute an invaluable reservoir of therapeutic targets in reparative medicine. The mechanism driving inflammatory-to-proliferative state transition during wound healing remains unclear. Here, the authors discover that SNHG26 interacts with ILF2, redirecting it from inflammatory genomic loci to the LAMB3 locus, thereby promoting wound healing.

Background: Alopecia areata (AA) is a common autoimmune alopecia disease. Evidence suggests that autophagy-related genes (ARGs) may contribute to its pathophysiology. This study aims to explore and identify potential autophagy-related biomarkers and molecular subtypes in AA. Methods: In this study, autophagy-related differential expression genes (ARDEGs) in AA were identified by comparing the differentially expressed genes (DEGs) in the GSE68801 dataset with the ARGs. Then, we applied three different machine learning methods to identify key hub genes and further verified them on independent datasets. We used the receiver operating characteristic (ROC) curve to evaluate the diagnostic potential of these hub genes and constructed a predictive nomogram. In addition, this study also used the consensus clustering method to define two AA subtypes and explored their immune characteristics and functional pathways through ssGSEA, MCPcounter and enrichment analysis. Experimental validation included qRT-PCR for four hub genes and Western blotting for critical autophagy markers. Results: Our analysis detected 10 ARDEGs in AA. Applying three machine learning algorithms, we identified four candidate hub genes, ATG9B, EIF4EBP1, WIPI1 and CCR2, and verified their expression patterns in independent cohorts. The combined four-gene model and nomogram showed potential diagnostic performance. Consensus cluster analysis divided AA cases into two subtypes, each associated with different immune infiltration and functional pathways. Downregulation of ATG9B and EIF4EBP1 and upregulation of CCR2 were verified by qRT-PCR. Western blotting further suggested altered autophagy-related protein expression in AA lesions, characterized by a reduced LC3B-II/I ratio and Beclin-1 expression and increased SQSTM1 expression. Conclusions: This study identified four candidate autophagy-related genes and two exploratory molecular subtypes in AA and may provide clues for understanding autophagy-related immune dysregulation and support further validation of candidate diagnostic markers.

Patients receiving allogeneic hematopoietic stem cell transplantation (allo-HSCT) are typically placed in a laminar air flow room until hematopoietic reconstitution occurs. In this study, we compared the differences in clinical outcomes between patients receiving allo-HSCT in a conventional laminar flow room (n = 200) and those receiving allo-HSCT in a plasma sterilizer environment (n = 201). The overall infection rates (20.4% vs 25.5%, P = 0.224) and the sites of infection (sepsis, perianal infection, and catheter-related infection) were comparable between the two groups. Additionally, the engraftment times were comparable between the two groups in terms of time to allo-HSCT, leukocyte engraftment time, and platelet engraftment time. The 100-day posttransplantation clinical outcomes were also comparable between the two groups in terms of the probability of overall survival (98.5% vs 99.5%, P = 0.316), leukemia-free survival (96.5% vs 96.5%, P = 0.991), the cumulative incidence of relapse (2.0% vs 3.0%, P = 0.523), non-relapse mortality (1.5% vs 0.5%, P = 0.316) and acute graft-versus-host disease (23.4% vs 22.0%, P = 0.723). Thus, our results demonstrated that receiving allo-HSCT via a plasma sterilizer did not increase the risk of pre-engraftment infection, and the clinical outcomes of these patients were comparable to those of patients in a conventional laminar flow room. Graphical Abstract

Introduction Prolactin (PRL) plays a key role in the regulation of reproductive functions. However, its impact on outcomes in infertility women undergoing assisted reproductive technology remains unclear. This study aimed to examine the relationship between PRL levels and reproductive outcomes in frozen embryo transfer (FET) cycles under hormone replacement therapy (HRT). Materials and methods A total of 1212 FET cycles under HRT were included from a single center in Shanghai between March 2013 and June 2023. PRL levels were measured on the day before progesterone-induced endometrial transformation and participants were stratified according to the near-quartiles cut-points of PRL. Logistic regression analyses were performed to assess the associations between different PRL levels and reproductive outcomes. Results Live birth rate was significantly lower in the highest PRL group (> 20ng/ml) compared with the rest of the groups. In line with this, the multivariable adjusted ORs with ascending PRL categories (≤ 10.0 ng/ml, 10.1–15.0 ng/ml, 15.1–20.0 ng/ml, and > 20.0 ng/ml) for live birth rates were 1.07 (95%CI: 0.75–1.52), 1.00, 0.89 (95%CI: 0.63–1.24) and 0.53 (95%CI: 0.37–0.75), respectively. Furthermore, elevated PRL levels were also significantly associated with a reduced chance of clinical pregnancy and an increased risk of early miscarriage. Conclusions High PRL levels before endometrial transformation are significantly associated with poor reproductive outcomes. These findings highlight the importance of measuring PRL during endometrial preparation in HRT-FET cycles, although PRL monitoring is not usually performed during this period in current clinical routine.

China has a large variety of edible mushrooms and ranks first in the world in terms of production and variety. Nevertheless, due to their high moisture content and rapid respiration rate, they experience constant quality deterioration, browning of color, loss of moisture, changes in texture, increases in microbial populations, and loss of nutrition and flavor during postharvest storage. Therefore, this paper reviews the effects of essential oils and plant extracts on the preservation of edible mushrooms and summarizes their mechanisms of action to better understand their effects during the storage of mushrooms. The quality degradation process of edible mushrooms is complex and influenced by internal and external factors. Essential oils and plant extracts are considered environmentally friendly preservation methods for better postharvest quality. This review aims to provide a reference for the development of new green and safe preservation and provides research directions for the postharvest processing and product development of edible mushrooms.

The king oyster mushroom (Pleurotus eryngii) is a delicious edible mushroom that is highly prized for its unique flavor and excellent medicinal properties. Its enzymes, phenolic compounds and reactive oxygen species are the keys to its browning and aging and result in its loss of nutrition and flavor. However, there is a lack of reviews on the preservation of Pl. eryngii to summarize and compare different storage and preservation methods. This paper reviews postharvest preservation techniques, including physical and chemical methods, to better understand the mechanisms of browning and the storage effects of different preservation methods, extend the storage life of mushrooms and present future perspectives on technical aspects in the storage and preservation of Pl. eryngii. This will provide important research directions for the processing and product development of this mushroom.