Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

BACKGROUND: Generalized pustular psoriasis (GPP), a rare and recurrent autoinflammatory disease, imposes a substantial burden on patients and society. Awareness of GPP in China remains limited. METHODS: This cross-sectional survey, conducted between September 2021 and May 2023 across 14 hospitals in China, included GPP patients of all ages and disease phases. Data collected encompassed demographics, clinical characteristics, economic impact, disease severity, quality of life, and treatment-related complications. Risk factors for GPP recurrence were analyzed. RESULTS: Among 127 patients (female/male ratio = 1.35:1), the mean age of disease onset was 25 years (1st quartile [Q1]-3rd quartile [Q3]: 11-44 years); 29.2% had experienced GPP for more than 10 years. Recurrence occurred in 75.6% of patients, and nearly half reported no identifiable triggers. Younger age at disease onset ( P  = 0.021) and transitioning to plaque psoriasis ( P  = 0.022) were associated with higher recurrence rates. The median diagnostic delay was 8 months (Q1-Q3: 2-41 months), and 32.3% of patients reported misdiagnoses. Comorbidities were present in 53.5% of patients, whereas 51.1% experienced systemic complications during treatment. Depression and anxiety affected 84.5% and 95.6% of patients, respectively. During GPP flares, the median Dermatology Life Quality Index score was 19.0 (Q1-Q3: 13.0-23.5). This score showed significant differences between patients with and without systemic symptoms; it demonstrated correlations with both depression and anxiety scores. Treatment costs caused financial hardship in 55.9% of patients, underscoring the burden associated with GPP. CONCLUSIONS The substantial disease and economic burdens among Chinese GPP patients warrant increased attention. Patients with early onset disease and those transitioning to plaque psoriasis require targeted interventions to mitigate the high recurrence risk.
Humans ; Male ; Female ; Psoriasis/pathology* ; Adult ; Cross-Sectional Studies ; Adolescent ; Child ; Young Adult ; Quality of Life ; Middle Aged ; China/epidemiology* ; Recurrence ; Risk Factors ; Surveys and Questionnaires ; East Asian People

Lysosomes represent a promising target for cancer therapy and reducing drug resistance. However, the short treatment time and low efficiency of lysosomal targeting have limited the application in lysosome-targeting anticancer drugs. In this study, we proposed an adhesive-bandage approach and synthesized a new lysosomal targeting drug, namely long-term lysosome-targeting anticancer drug (LLAD). It contains a SLC38A9-targeting covalently bound moiety and an alkaline component both to prolong the inhibition of SLC38A9 in lysosomes and alkalinize lysosomes. Upon short term and low-dose treatment of HeLa cells, at passage 0, with LLAD, it rapidly alkalinized lysosomes and also can be detected in lysosomes even at passage 15. LLAD induced apoptosis in HeLa cells through long-term lysosomal damage, and showed better long-term anticancer effect than cisplatin in vivo. Overall, our study paves the way for developing long-term lysosomal targeting drugs to treat cancer and overcome the drug resistance of cancer cells, and also provides a candidate drug, LLAD, for treating cancer.

Objective:To observe the effect of methylprednisolone (MP) combined with cyclophosphamide (CTX) on inflammation and immune cell activity in bleomycin (BLM)-induced pulmonary fibrosis rat model.Methods:Forty healthy 6 to 8-week-old SD rats were randomly divided into blank control, BLM model, BLM+MP, and BLM+MP+CTX groups, with 10 rats in each group. The rat model of pulmonary fibrosis was prepared by intratracheal infusion of BLM (5 mg/kg, only once). From the 7th day of modeling, MP (3 mg/kg) was injected in rats in the BLM+MP group and MP (3 mg/kg)+CTX (8 mg/kg) was injected via tail vein in rats in the BLM+MP+CTX group, once daily for 21 days. The degree of lung inflammation and fibrosis in rats was detected using HE and Masson staining methods. The numbers of granu-locytes and neutrophils in bronchoalveolar lavage fluid (BALF) and blood T cell subsets in rats were detected using flow cytometry.Results:On the 7th day of modeling, the external morphology, HE and Masson staining results of rat lung tissue showed that BLM-induced pulmonary fibrosis model was successfully prepared. On the 28th day of modeling, the lung tissue structure of the BLM group was disordered with obvious collagen deposition, the number of granulocytes and neutrophils in BALF increased significantly, the proportion of blood T cells, CD4 + T cells, and regulatory T cells (Tregs) decreased, the proportion of CD8 + T cells, and the CD4 +/CD8 + T cells ratio decreased significantly (all P<0.05). Compared with the BLM group, the degree of pulmonary fibrosis in the BLM+MP+CTX group was improved significantly, the number of granulocytes and neutrophils in BALF decreased significantly, the proportion of blood T cells, CD4 + T cells and Tregs cells increased significantly, the proportion of CD8 + T cells decreased, and the ratio of CD4 +/CD8 + T cells increased significantly (all P<0.05). The improvement effect in rats of BLM+MP+CTX group was better than that of BLM+MP group, and the difference was statistically significant ( P<0.05). Conclusion:MP combined with CTX can reduce the degree of inflammatory reaction in rats with pulmonary fibrosis and improve T cell immune activity.

Hippo signal pathway is one of the main signal pathways regulating cell proliferation and apoptosis in multicellular animals, which plays a vital role in the maintenance of tissue homeostasis and the regulation of organ growth. Most mammals have limited regenerative potential, and recent studies have shown that Hippo signal pathway is critical in the regeneration of various tissues and organs. The role of Hippo signaling pathway in organ regeneration and the research progress of related targets were introduced, the mechanism of Hippo signaling pathway promoting regeneration analyzes were aralyzed in this review, which provide theoretical reference for the treatment of diseases related to organ regeneration.

Solenopsis invicta is a kind of invasive pest that causes serious damage to local agriculture, environment, and human health. They attack mainly with venom within stingers. Those who are allergic to the venom would suffer a systemic anaphylaxis, even fatal shock, after being stinged by these ants. Many studies reveal that their venom is mainly composed by water, insoluble alkaloids and trace proteins, within which alkaloids are the main cause of burning sensation and blisters, while allergic reactions are caused by proteins or peptides. The research progress of toxic substances in the venom of Solenopsis invicta as well as the roles and functions of each component were reviewed in this paper.

Objective:To investigate the mechanism of Candida albicans Int1 in regulating septin organization. Methods:A series of full-length and truncated fragments of Int1 were constructed and fused with green fluorescent protein (GFP). The intracellular localization of the fusion proteins was observed under a fluorescence microscope. The region in Int1 that was required for bud neck localization was identified. Full-length and fragments of Int1 were overexpressed in the yeast Saccharomyces cerevisiae and the changes in cell growth, cell morphology and septin organization were investigated to determine the functional region in Int1 that mediated the interaction with septin. Moreover, the co-localization of the region and septin was analyzed. Results:The full-length Int1 consisted of 1 661 amino acid residues. A middle region of 209 amino acid residues, Int1-M4 (739-947 aa), that could be localized at the bud neck during both small and large bud periods was identified. Overexpression of Int1-M4 led to significant growth defects, elongated bud and disorganized septin. In the cells with elongated bud, Int1-M4 and septin with abnormal structures could be co-localized.Conclusions:Int1-M4 (739-947 aa), the middle region of Int1 containing 209 amino acid residues, mediated the bud neck localization and the interaction with septin, playing an important role in regulating septin organization.

【Objective】 To evaluate and analyze the impact of COVID-19 epidemic on inventory of red blood cells (RBCs)in local and municipal blood stations in China, and to provide reference for the management of public health emergencies. 【Methods】 Relevant data from 2018 to 2021 were collected, and the differences in the volume of qualified RBCs, the usage efficiency of inventory RBCs, the average daily distribution of RBCs,the blood distribution rate of RBCs prepared by 400 mL whole blood, the difference in the average storage days of RBCs at the time of distribution, the average daily inventory of RBCs and the time of the average daily inventory of RBCs to maintain the distribution in 24 local and municipal blood stations in China during the COVID-19 epidemic and non-epidemic periods were retrospectively analyzed. 【Results】 Compared with non-epidemic periods, the volume of qualified RBCs [(117 525.979 ±52 203.175)U] and the average daily distribution of RBCs [( 156. 468 ± 70. 186) U ] increased significantly, but the usage efficiency of inventory RBCs decreased(97.24%±0.51%) significantly (P<0.05).There was no significant difference in the blood distribution rate of RBCs prepared by 400 mL whole blood(73.88%±20.30%), the average storage days of RBCs distribution(13.040 ±3.486), the average daily stock quantity of RBCs[(2 280.542 ±1 446.538) U ] and the time of the average daily inventory of RBCs to maintain the distribution[(15.062 ±7.453) d] (P>0.5). 【Conclusion】 During the COVID-19 epidemic, the inventory management of RBCs operated well, the overall inventory remained relatively stable, the stock composition and storage period showed no significant change.