China emerges as a major country in nuclear energy development and the application of nuclear and radiologic technology. The diagnosis and treatment of acute radiation syndrom (ARS) caused by external irradiation represent a core function in the country′s medical rescue of nuclear and radiological emergencies. Clinically, ARS manifests hematopoietic, gastrointestinal, cutaneous, and central nervous system syndromes, with specific clinical manifestations, signs, severity, and prognosis strongly correlated with radiation dose. China has established a number of national and provincial centers for treating radiation-induced damage. Nevertheless, most medical staff have limited experience in ARS treatment. This consensus presents a summary of recent experience in treating ARS of China. In combination with recommendations from international organizations such as the World Health Organization (WHO), this consensus proposes key evidence of critical clinical issues of ARS, covering all links in the rescue of external irradiation-induced ARS. Initially, clinical diagnosis, syndromes, and severe degrees should be determined based on clinical symptoms and dose estimates. It is necessary to normalize clinical treatment measures for hematopoietic recovery, gastrointestinal injury treatment, infection control, symptomatic treatment, and multi-organ function preservation. To this end, this consensus offers cautions. This consensus provides principles of treatment with traditional Chinese medicine, psychological intervention, and follow-up. Additionally, it highlights multidisciplinary collaboration. It is recommended that this consensus be applied in relevant treatment centers.

Objective:To develop CNN-Dinov2, a deep learning-based automatic classification model for Gram-stained images, enabling rapid diagnosis of three prevalent Gram-negative bacilli in bloodstream infections: Escherichia coli ( E.coli), Klebsiella pneumoniae ( K.pneumoniae), and Pseudomonas aeruginosa ( P.aeruginosa). Methods:This evaluation study analyzed 1 425 Gram-stained microscopic images from patients with bloodstream infections at Houjie Hospital, in Dongguan City, collected between January 2023 and January 2024. The images, all positive for blood culture and identified as target strains, were categorized into Escherichia coli (419 images), Klebsiella pneumoniae (411 images), Pseudomonas aeruginosa (413 images), and other Gram-negative bacilli (182 images). They were randomly split into a training set (1 141 images), a validation set (141 images), and a test set (143 images) in an 8∶1∶1 ratio. A hybrid CNN-Dinov2 model was developed by integrating ResNet′s local feature extraction with Dinov2′s global pre-trained features, followed by a fully connected layer. The model was optimized by inputting the preprocessed images and adjusting parameters through loss calculation and backpropagation. AlexNet, Dinov2, and ResNet18 served as control models. The models′ classification performance was assessed using accuracy, precision, weighted F1 score, and recall rate, derived from the confusion matrix. The PR curve and AP value further evaluated each model′s classification capability across the four image categories. Results:The CNN-Dinov2 model achieved a training accuracy of 99.74%, a validation accuracy of 98.12%, and a validation loss of 0.070 6, demonstrating robust generalization without overfitting. Validation metrics revealed superior performance with an accuracy of 98.60%, precision of 98.65%, a weighted F1 score of 98.60%, and a recall rate of 98.60%, outperforming other models. The confusion matrix confirmed its strong classification capability, with the highest sum of diagonal values for identifying four types of bacteria. The macro average precision (AP) values under the precision-recall (PR) curves were all 1, indicating excellent discrimination across all categories. Overall, the CNN-Dinov2 model exhibited the best performance among the four models evaluated.Conclusion:This study successfully developed CNN-Dinov2, an automated classification model for Gram staining images. It offers valuable support for the rapid diagnosis of bloodstream infections caused by Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa, demonstrating practical utility.

China emerges as a major country in nuclear energy development and the application of nuclear and radiologic technology. The diagnosis and treatment of acute radiation syndrom (ARS) caused by external irradiation represent a core function in the country′s medical rescue of nuclear and radiological emergencies. Clinically, ARS manifests hematopoietic, gastrointestinal, cutaneous, and central nervous system syndromes, with specific clinical manifestations, signs, severity, and prognosis strongly correlated with radiation dose. China has established a number of national and provincial centers for treating radiation-induced damage. Nevertheless, most medical staff have limited experience in ARS treatment. This consensus presents a summary of recent experience in treating ARS of China. In combination with recommendations from international organizations such as the World Health Organization (WHO), this consensus proposes key evidence of critical clinical issues of ARS, covering all links in the rescue of external irradiation-induced ARS. Initially, clinical diagnosis, syndromes, and severe degrees should be determined based on clinical symptoms and dose estimates. It is necessary to normalize clinical treatment measures for hematopoietic recovery, gastrointestinal injury treatment, infection control, symptomatic treatment, and multi-organ function preservation. To this end, this consensus offers cautions. This consensus provides principles of treatment with traditional Chinese medicine, psychological intervention, and follow-up. Additionally, it highlights multidisciplinary collaboration. It is recommended that this consensus be applied in relevant treatment centers.

Objective:To develop CNN-Dinov2, a deep learning-based automatic classification model for Gram-stained images, enabling rapid diagnosis of three prevalent Gram-negative bacilli in bloodstream infections: Escherichia coli ( E.coli), Klebsiella pneumoniae ( K.pneumoniae), and Pseudomonas aeruginosa ( P.aeruginosa). Methods:This evaluation study analyzed 1 425 Gram-stained microscopic images from patients with bloodstream infections at Houjie Hospital, in Dongguan City, collected between January 2023 and January 2024. The images, all positive for blood culture and identified as target strains, were categorized into Escherichia coli (419 images), Klebsiella pneumoniae (411 images), Pseudomonas aeruginosa (413 images), and other Gram-negative bacilli (182 images). They were randomly split into a training set (1 141 images), a validation set (141 images), and a test set (143 images) in an 8∶1∶1 ratio. A hybrid CNN-Dinov2 model was developed by integrating ResNet′s local feature extraction with Dinov2′s global pre-trained features, followed by a fully connected layer. The model was optimized by inputting the preprocessed images and adjusting parameters through loss calculation and backpropagation. AlexNet, Dinov2, and ResNet18 served as control models. The models′ classification performance was assessed using accuracy, precision, weighted F1 score, and recall rate, derived from the confusion matrix. The PR curve and AP value further evaluated each model′s classification capability across the four image categories. Results:The CNN-Dinov2 model achieved a training accuracy of 99.74%, a validation accuracy of 98.12%, and a validation loss of 0.070 6, demonstrating robust generalization without overfitting. Validation metrics revealed superior performance with an accuracy of 98.60%, precision of 98.65%, a weighted F1 score of 98.60%, and a recall rate of 98.60%, outperforming other models. The confusion matrix confirmed its strong classification capability, with the highest sum of diagonal values for identifying four types of bacteria. The macro average precision (AP) values under the precision-recall (PR) curves were all 1, indicating excellent discrimination across all categories. Overall, the CNN-Dinov2 model exhibited the best performance among the four models evaluated.Conclusion:This study successfully developed CNN-Dinov2, an automated classification model for Gram staining images. It offers valuable support for the rapid diagnosis of bloodstream infections caused by Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa, demonstrating practical utility.

Objective Based on HPLC fingerprinting and chemometrics,to evaluate the quality of Schefflera kwangsiensis Merr.from Guangxi.Methods HPLC was used to establish fingerprints of Schefflera kwangsiensis Merr.from ten different origins,and gradient elution was carried out with methanol-0.1％phosphoric acid aqueous solution as mobile phase.Cluster analysis(CA),principal component analysis(PCA)and orthogonal partial least squares-discriminant analysis(OPLS-DA)were applied to evaluate quality.Results The fingerprints of Schefflera kwangsiensis Merr.from ten different origins were established by HPLC,a total of 22 common peaks were calibrated,with a similarity range of 0.922-0.999.Four chromatographic peaks were identified as rhodopsin,4,5-bis-O-caffeoylquinic acid,caffeic acid,and naringin.The samples were classified into four types according to the CA and OPLS-DA.PCA identified four principal components with a cumulative contribution rare of 95.39％.Conclusion The quality of Schefflera kwangsiensis Merr.can be comprehensively evaluated by fingerprinting combined with CA,PCA and OPLS-DA analysis.The Study can provide a reference for improving the quality control and assessment of Schefflera kwangsiensis Merr.

BACKGROUND: LY01005 (Goserelin acetate sustained-release microsphere injection) is a modified gonadotropin-releasing hormone (GnRH) agonist injected monthly. This phase III trial study aimed to evaluated the efficacy and safety of LY01005 in Chinese patients with prostate cancer. METHODS: We conducted a randomized controlled, open-label, non-inferiority trial across 49 sites in China. This study included 290 patients with prostate cancer who received either LY01005 or goserelin implants every 28 days for three injections. The primary efficacy endpoints were the percentage of patients with testosterone suppression ≤50 ng/dL at day 29 and the cumulative probability of testosterone ≤50 ng/dL from day 29 to 85. Non-inferiority was prespecified at a margin of -10%. Secondary endpoints included significant castration (≤20 ng/dL), testosterone surge within 72 h following repeated dosing, and changes in luteinizing hormone, follicle-stimulating hormone, and prostate specific antigen levels. RESULTS: On day 29, in the LY01005 and goserelin implant groups, testosterone concentrations fell below medical-castration levels in 99.3% (142/143) and 100% (140/140) of patients, respectively, with a difference of -0.7% (95% confidence interval [CI], -3.9% to 2.0%) between the two groups. The cumulative probabilities of maintaining castration from days 29 to 85 were 99.3% and 97.8%, respectively, with a between-group difference of 1.5% (95% CI, -1.3% to 4.4%). Both results met the criterion for non-inferiority. Secondary endpoints were similar between groups. Both treatments were well-tolerated. LY01005 was associated with fewer injection-site reactions than the goserelin implant (0% vs . 1.4% [2/145]). CONCLUSION: LY01005 is as effective as goserelin implants in reducing testosterone to castration levels, with a similar safety profile. TRIAL REGISTRATION ClinicalTrials.gov, NCT04563936.
Humans ; Male ; Antineoplastic Agents, Hormonal/therapeutic use* ; East Asian People ; Gonadotropin-Releasing Hormone/agonists* ; Goserelin/therapeutic use* ; Prostate-Specific Antigen ; Prostatic Neoplasms/drug therapy* ; Testosterone

Objective:To summarize the clinical characteristics of central nerve system (CNS) infection and grasp the necessity and possibility of early diagnosis and precise intervention of CNS infection after renal transplantation.Methods:This retrospective study enrolled consecutive recipients of renal transplantation with CNS infection after transplant between January 2000 and December 2020. Correlative factors for CNS infection after renal transplant were determined by comparing the clinical data between recipients with and without CNS infection. After screening 3, 199 consecutive renal transplant recipients, 12 patients with CNS infection post-transplant were identified and recruited. The median age-of-onset was 48.5 (23-65) years. And the median time to disease onset after transplant was 50.5(1-204) months. The most common symptoms of CNS infection after renal transplant included fever (75.00%), consciousness disorder (58.33%), headache (58.33%) and neck rigidity (41.67%).Results:Hepatitis B virus carrier and pulmonary infection were correlated with CNS infection after transplantation ( P<0.05). Nine patients failed to identify the pathogen and only received empirical anti-infective regimen. The outcomes were curing ( n=3) and death ( n=6). Metagenomic sequencing was performed for identifying the pathogen in three recipients and actively adjusting the anti-infective regimen. As a result, 2 were cured and 1 died. The overall mortality was 58.33%. The median time to death or curing from disease onset were 20(2-19) and 25(16-35) days respectively in surviving and non-surviving recipients. Conclusions:The progress of CNS infection after transplantation is rapid with a high mortality. HBV carrier and pulmonary infection are possible risk factors of CNS infection after renal transplantation. Early pathogenic identification and precise etiological intervention are vital for better clinical outcomes.

BACKGROUND: Benvitimod cream, a novel synthetic small molecule, was effective in treating mild-to-moderate plaque psoriasis. We conducted a phase III clinical trial to assess the efficacy and safety of benvitimod cream in patients with mild-to-moderate plaque psoriasis. METHODS: We randomly assigned 686 patients (2:1:1) to receive 1% benvitimod cream, 0.005% calcipotriol ointment or placebo twice a day for 12 weeks. The primary efficacy end points were the percentage of patients with a 75% or greater reduction from baseline in the psoriasis area and severity index (PASI 75) score and with a score of 0 or 1 in static physician's global assessment (sPGA) at week 12. RESULTS: The results showed that 50.4% of patients in the benvitimod group achieved PASI 75, which was significantly higher than that in the calcipotriol (38.5%, P < 0.05) and placebo (13.9%, P < 0.05) groups. The proportion of patients achieving an sPGA score 0 or 1 was 66.3% in the benvitimod group and 63.9% in the calcipotriol group, which were both significantly higher than that in the placebo group (34%, P < 0.05). In the long-term follow-up study, 50.8% of patients experienced recurrence. After retreatment with 1% benvitimod, 73.3% of patients achieved an sPGA score of 0 or 1 again at week 52. Adverse events included application site irritation, follicular papules, and contact dermatitis. No systemic adverse reactions were reported. CONCLUSION: During this 12-week study, benvitimod cream was demonstrated with high effectiveness and safety in patients with mild-to-moderate plaque psoriasis. TRIAL REGISTRATION Chinese Clinical Trial Registry (ChiCTR), ChiCTR-TRC-13003259; http://www.chictr.org.cn/showprojen.aspx?proj=6300.
Double-Blind Method ; Follow-Up Studies ; Humans ; Ointments ; Psoriasis/drug therapy* ; Resorcinols ; Severity of Illness Index ; Stilbenes ; Treatment Outcome

Objective To analyze the incidence and risk factors of de novo malignant tumors in renal transplant recipients. Methods Clinical data of 1 549 renal transplant recipients were retrospectively analyzed, including the basic status, pathological type and incidence rate of patients with de novo malignant tumors after renal transplantation. The survival situation of these patiensts was assessed. And the risk factors of de novo malignant tumors after renal transplantation were identified. Results The incidence rate of de novo malignant tumors in renal transplant recipients was 3.03%(47/1 549). The 47 recipients were (48±12) years old when undergoing renal transplantation, and they were (55±12) years old when diagnosed malignant tumors. The time interval between transplantation and diagnosis was 66 (36, 100) months. Among the de novo malignant tumors, colorectal cancer was the most common, with a cumulative incidence rate (CIR) of 0.58%. The survival time of 47 recipients with de novo malignant tumors after renal transplantation was 59 (2, 135) months, and the 5-year survival rate was 50%. The recipients with the age > 45 years old when undergoing renal transplantation was a risk factor for de novo malignant tumors after renal transplantation (P < 0.05). Conclusions The incidence rate of de novo malignant tumors is relatively high in renal transplant recipients. The recipients with the age > 45 years old when undergoing renal transplantation is a risk factor for de novo malignant tumors.

Objective:To investigate the function of miR-5581-5p and its interaction with tripartite motif 22 (TRIM22) during the terminal differentiation of human acute promyelocytic leukemia (APL) cells into granulocytes.Methods:APL cells (NB4) were differentiated into granulocytes by all-trans retinoic acid (ATRA), using dimethylsulfoxide (DMSO) as the control. The expression of TRIM22 was detected by real-time fluorescent quantitative PCR (qRT-PCR) and Western blotting, and the expression of miR-5581-5p was detected by qRT-PCR during cell differentiation. miRNA expression was regulated by cell transfection with miR-5581-5p mimic and inhibitor, and negative control was set, and qRT-PCR was used to verify the regulatory effect. Luciferase binding assay was performed to detect the presence of targeted binding. Western blotting was used to detect the expression of TRIM22 after miRNA differential expression. Flow cytometry was used to detect the effects of the regulation of miR-5581-5p on the differentiation of NB4 cells induced by ATRA.Results:After ATRA induced NB4 cells to differentiate into granulocytes, the gene expression level of TRIM22 was significantly higher than that of the control group (24.56±2.80 vs. 1.02±0.13; t=8.392, P=0.001). The level of protein expression was also significantly higher than that of the control group (0.80±0.01 vs. 0.17±0.01; t=44.900, P<0.001). The expression level of miR-5581-5p in NB4 cells differentiation group was significantly lower than that in the control group (0.14±0.02 vs. 1.01±0.08; t=10.840, P<0.001). The results of the dual luciferase reporter gene showed that the luciferase activity of the co-transfected miR-5581-5p mimic and TRIM22 WT group was significantly lower than that of the co-transfected miR-5581-5p mimic and TRIM22 MUT group (0.73±0.02 vs. 0.98±0.03; t=7.534, P=0.002). Western blotting showed that after transfection with miR-5581-5p inhibitor, the expression of TRIM22 was significantly higher than that of the negative control (0.44±0.01 vs. 0.21±0.01; t=18.290, P<0.001). While after transfection with miR-5581-5p mimic, the expression of TRIM22 decreased significantly compared with the negative control (0.62±0.01 vs. 0.80±0.02; t=6.402, P=0.003). CD11b expression of miR-5581-5p mimic group after ATRA treatment was significantly lower than that of the control group (45.80±1.80 vs. 56.61±1.88; t=4.159, P=0.014). The expression of CD11b in miR-5581-5p inhibitor group was significantly higher than that in the control group (66.48±2.54 vs. 52.60±1.70; t=4.539, P=0.011). Conclusion:miRNA-5581-5p can bind to TRIM22 3′UTR and negatively regulate TRIM22 expression. The decrease of miR-5581-5p can increase the expression of TRIM22, then promote the differentiation of ATRA-induced NB4 cells into granulocytes.