Objective To investigate the diagnosis and treatment of 2 cases with spontaneous renal vascular rupture, and discuss the possible causes and treatment methods of this disease. Methods The clinical data and treatment methods of the 2 patients with spontaneous renal vascular rupture treated with renal artery embolization in Universal Global Xi'an Beihuan Hospital were analyzed. Relevant literature was reviewed to summarize the possible causes of this condition. Results The patients had no obvious history of trauma and no obvious abnormal coagulation function, and sought treatment due to sudden lumbar and abdominal pain. Laboratory tests revealed significantly decreased hemoglobin level, and elevated blood glucose (27.8, 27.6mmol/L). Abdominal computed tomography (CT) indicated perirenal hematoma and active bleeding. The bleeding arteries were located at the terminal branches of the anterior renal artery. Precise embolization was performed using CT angiography and selective renal artery angiography plus embolization, achieving an immediate hemostasis success rate of 100%. Postoperative hemoglobin level stabilized, and follow-up CT scans showed significant absorption of the perirenal hematoma without significant deterioration of renal function. Based on literature review and case analysis, the possible cause of spontaneous renal vascular rupture in these two patients was renal vascular sclerosis due to long-term diabetes. Other common etiologies of this condition included renal tumor, vascular malformation, and hypertension. Conclusion Spontaneous renal vascular rupture is rare. Renal artery embolization, as aminimally invasive treatment, can effectively control bleeding and protect renal function. The specific pathogenesis of this condition still requires further investigation. Long-term diabetes mellitus with poor blood glucose control may be associated factors, but more evidence is needed.

Blood transfusion is an important life-support measure in modern medicine. As clinical demand for transfusion continues to rise, blood supply remains under persistent strain, making the efficient utilization of this precious medical resource a critical component of blood management. Accurate prediction of transfusion needs is of great significance for optimizing blood resource allocation and conserving blood products. Traditional transfusion decision-making relies on clinical experience and simplified scoring systems, which are insufficient to meet the demands of precision medicine. Machine learning (ML) technology can integrate multidimensional data—including demographic characteristics, laboratory indicators, surgical information, and dynamic physiological waveforms—to construct high-performance predictive models, offering a new approach to transfusion prediction. This article systematically reviews the application progress of ML in transfusion prediction across clinical scenarios such as trauma, the perioperative period, and obstetrics. In trauma, ML has been applied to early massive transfusion prediction, prehospital transfusion decision-making, and precise prediction in pediatric trauma. In the perioperative field, applications span specialties including traumatic brain injury, orthopedic surgery, cardiovascular and major vascular surgery, and hepatic surgery. In obstetrics, models can effectively predict postpartum hemorrhage and transfusion requirements associated with cesarean section. Studies have shown that algorithms such as random forest, gradient boosting machines, and deep neural networks achieve area under the receiver operating characteristic curve (AUC) values of 0.83-0.98 in massive transfusion prediction, 0.75-0.97 in perioperative scenarios, and 0.80-0.89 in obstetric transfusion prediction—significantly outperforming traditional scoring tools. However, current studies are generally limited by single-center retrospective designs, insufficient external validation, and inadequate reporting standards; limited model interpretability and challenges in clinical integration further constrain practical translation. Future research should focus on constructing multicenter data cohorts, integrating multimodal data, conducting prospective implementation studies, and deeply embedding models within electronic health record systems, thereby advancing the application of ML to optimize clinical transfusion decision-making.

BackgroundBoth modified Suanzaoren Decoction and estazolam serve as effective treatments for chronic insomnia disorder （CID）. Default mode network （DMN） dysfunction is recognized as the primary pathophysiological mechanism underlying CID. However， it remains unclear whether the two treatments exert their therapeutic effects via convergent modulation of DMN functional connectivity. ObjectiveTo investigate the convergent remodeling characteristics of bidirectional effective connectivity （EC） of core DMN nodes with both the intra-network and the remaining whole-brain regions in CID patients with Yin-deficiency and fire-hyperactivity syndrome following the treatment with modified Suanzaoren Decoction or estazolam， so as to provide neuroimaging evidence for the convergent neural mechanisms underlying the therapeutic effects of both therapies in treating CID. MethodsEighty-two patients diagnosed with CID according to the International Classification of Sleep Disorder， third edition （ICSD-3） were consecutively recruited from the outpatient clinic of the Inner Mongolia Autonomous Region Mental Health Center from October 2020 to September 2023. Based on treatment preference， patients were assigned to receive a 6-week intervention in either the modified Suanzaoren Decoction group （n=52） or the estazolam group （n=30）. Ultimately， 66 patients completed follow-up assessments （modified Suanzaoren Decoction group， n=41； estazolam group， n=25）. All CID patients underwent resting-state functional magnetic resonance imaging scanning before and after treatment. Core DMN nodes including medial prefrontal cortex （mPFC）， bilateral inferior parietal lobule （IPL）， and precuneus （PCUN） were selected as seed regions. Granger causality analysis （GCA） was employed to assess bidirectional EC between the seed regions and both the other intra-DMN nodes and the remaining whole-brain regions. Hepatic and renal function indices were detected pre- and post-treatment to evaluate the safety profiles of both treatments. ResultsAt baseline， significant between-group differences were identified in EC from the left IPL to the left middle fronto-orbital gyrus/gyrus rectus （t=5.24， Z=4.84， voxel-level P<0.001， cluster-level P<0.05， GRF-corrected）， with the modified Suanzaoren Decoction group exhibiting stronger EC than the estazolam group. No significant between-group differences were observed in EC between other core DMN nodes and remaining whole-brain regions （P>0.05）. Within-group pre- to post-treatment comparisons demonstrated consistent connectivity alterations in both groups. Specifically， EC from the left IPL to the supplementary motor area （SMA） decreased after treatment （modified Suanzaoren Decoction group： t=-6.28， Z=5.208； estazolam group： t=-5.58， Z=4.425）. Conversely， EC from the SMA to the left IPL increased （modified Suanzaoren Decoction group： t=5.89， Z=4.968； estazolam group： t=6.15， Z=4.720）. Furthermore， both groups demonstrated reduced EC from the PCUN to the left IPL （modified Suanzaoren Decoction group： t=-5.85， Z=4.94； estazolam group： t=-5.75， Z=4.515）， and elevated EC from the left IPL to the PCUN （modified Suanzaoren Decoction group： t=5.29， Z=4.579； estazolam group： t=4.55， Z=3.826） （voxel-level P<0.001， cluster-level P<0.05， GRF-corrected）. No significant pre- to post-treatment differences were observed in hepatic or renal function indices in either group （P>0.05）. ConclusionIn CID patients with Yin-deficiency and fire-hyperactivity syndrome， both modified Suanzaoren Decoction and estazolam induce convergent bidirectional remodeling of EC between the left IPL and the SMA and the PCUN. ［Funded by Natural Science Fund Project of Inner Mongolia Autonomous Region （number， 2019MS08099）； ClinicalTrials.gov number， NCT06452953］

Objective:To investigate the association between serum ferritin levels, erythrocyte parameters, and the risk of developing type 2 diabetes mellitus.Methods:A total of 11 408 subjects aged 40 to 70 years who underwent physical examinations at a hospital in Qingdao from 2014 to 2015 were enrolled in the study. Data were collected through questionnaires, physical examinations, and assessments of blood biochemical indices, serum ferritin, and related erythrocyte parameters. A multivariate logistic regression model was employed to analyze the relationship of serum ferritin and red cell parameters with type 2 diabetes mellitus, while a linear regression model was utilized to examine the association between serum ferritin, red cell parameters and fasting blood glucose levels.Results:The median ( Q1, Q3) age of the subjects was 51 (45, 58) years, with 55.3% (6 305) being male. The prevalence of type 2 diabetes in women was 5.9% (300/5 103), which was lower than that in men [13.0% (817/6 305)] ( P<0.001).After adjusting for age, sex, body mass index (BMI), smoking status, alcohol consumption, and family history of diabetes, serum ferritin levels were found to be positively associated with both type 2 diabetes and fasting blood glucose levels, with OR (95% CI) and β(95% CI) values of 1.70 (1.37, 2.11) and 0.002 (0.002, 0.003), respectively. Additionally, hemoglobin, red blood cell count, and hematocrit were positively correlated with type 2 diabetes and fasting blood glucose, with OR (95% CI) values of 1.72 (1.32, 2.24), 1.91 (1.51, 2.41), and 1.52 (1.17, 1.97), and β (95% CI) values of 0.008 (0.006, 0.011), 0.365 (0.286, 0.445), and 2.543 (1.564, 3.521), respectively. Conversely, mean erythrocyte volume was negatively associated with type 2 diabetes and fasting blood glucose, with OR (95% CI) and β (95% CI) values of 0.54 (0.45, 0.66) and -0.017 (-0.023, -0.011), respectively (all P values<0.001). Conclusion:The findings indicate that serum ferritin and related erythrocyte parameters are significantly correlated with the risk of type 2 diabetes mellitus and fasting blood glucose levels.

Objective:To explore the value of ultrasound imaging characteristics combined with clinical indicators in assessing the prognosis of patients with pancreatic ductal adenocarcinoma (PDAC).Methods:A retrospective analysis was conducted for patients who underwent pancreatic contrast-enhanced ultrasound (CEUS) from September 2017 to October 2023 at Peking Union Medical College Hospital and were diagnosed with PDAC based on pathological findings. Various parameters were recorded, including CA19-9 levels, tumor size, location, morphologic features, echogenicity, presence of internal cystic components, dilatation of the main pancreatic duct, peripheral vascular invasion, CEUS characteristics, presence or absence of liver metastasis, and treatment methods. In April 2024, patient survival information was obtained through telephone follow-up or review of medical records. Based on the results of the cox regression model analysis, a nomogram model of the risk of death was developed. The receiver operating characteristic (ROC) curves were applied to evaluate the predictive efficacy of the model. The calibration curves were plotted to evaluate the accuracy of the model, and clinical decision curves were used to evaluate the clinical benefit of the model.Results:This study included a total of 207 patients with PDAC. As of April 2024, 71 patients were alive and 136 died, with a median survival time of 14 months (95% CI: 12 -17). Multivariate analysis confirmed that the elevated CA19-9 ( HR=1.689, 95% CI: 1.102-2.588), tumor size >4 cm ( HR=1.641, 95% CI: 1.159-2.322), taller-than-wide shapes ( HR=1.450, 95% CI: 1.019-2.065), incomplete hypo-enhancement ( HR=1.618, 95% CI: 1.100-2.380), and liver metastasis ( HR=1.687, 95% CI: 1.175-2.423) were independent risk factors for survival in patients with PDAC. A nomogram model was further constructed for 6-month, 12-month and 3-year survival of patients with PDAC. The areas under the ROC curve were 0.679, 0.705 and 0.815, respectively. The calibration curves suggested that the model was more accurate, and the clinical decision curves showed that the model had a better clinical benefit. Conclusion:The combined use of ultrasound imaging characteristics and clinical indicators could effectively predict the prognosis of PDAC patients. Specifically, tumor size >4 cm, taller-than-wide shapes, incomplete hypo-enhancement, elevated CA19-9, and the presence of liver metastasis are correlated with poorer survival outcomes. The nomogram model constructed on the basis of these factors can be used to assess the survival of patients with PDAC.

Pancreatic cancer has a concealed onset and poor prognosis,and surgical resection is the main treatment method.Neoadjuvant therapy may improve the rate of negative resection margin and prolong overall survival of patients with pancreatic cancer.Functional and quantitative imaging can non-invasively reflect tumor microenvironment characteristics related to chemotherapy resistance,providing a new perspective for evaluating and predicting the efficacy of neoadjuvant therapy for pancreatic cancer.The research progresses in functional and quantitative imaging for evaluating and predicting the efficacy of neoadjuvant therapy of pancreatic cancer were reviewed in this article.

Objective To explore the impact of peptidylarginine deiminase 2(Padi2)-knockout on depressive-like behaviors in socially isolated mice.Methods Using CRISPR/Cas9 technology,a Padi2-knockout(Padi2-/-)mouse model with a C57BL/6J background was established,and the effect of Padi2 knockout was identified by genotyping and RT-qPCR detection.Six-week-old male Padi2-/- mice and wild-type C57BL/6J mice were selected and divided into normal rearing and social isolation groups,with 15 mice per group.The normal rearing group mice were housed with 5 mice per cage,and the social isolation group was housed with 1 mouse per cage,and weighed once a week.After 4 weeks,forced swimming and open field tests were conducted.After the behavioral experiments,brain tissues were taken from mice in each group,and changes in microglia in the brains were detected by immunofluorescence.Results We successfully established Padi2-/- mice.There was no difference in behavior between Padi2-/- mice and C57BL/6J mice in the normal rearing group.After social isolation,compared with C57BL/6J mice,Padi2-/- mice showed a significant increase in depressive symptoms,obvious weight gain,and a significant increase in the number of microglia in brain tissue.Conclusions Padi2 knockout exacerbated depressive-like behaviors and obesity in socially isolated mice,indicating that Padi2 is involved in the progression of depression and may be an effective target for the prevention and treatment of depression.

Ultrasound has become the primary imaging method for screening,diagnosing and following up of liver diseases,especially metabolic associated fatty liver disease(MAFLD)and hepatocellular carcinoma(HCC).In recent years,artificial intelligence(AI),especially deep learning(DL)developed rapidly,being able to deeply extract ultrasonic features and achieve quantitative analysis.The research status,challenges and prospects of AI in ultrasound imaging of diffuse liver diseases and focal liver lesions were reviewed in this article.

Objective:To observe the application effect of nursing risk management based on PDCA (plan, do, check, action) cycle quality control concept on patients with diabetic ketoacidosis, and provide reference for improving the nursing quality of diabetic ketoacidosis.Methods:A historical control study was adopted. Using simple random sampling method, patients with diabetic ketoacidosis admitted to Emergency Intensive Care Unit of Lishui Central Hospital from January 2019 to March 2020 were selected as the research subjects, patients admitted from January to September 2019 were treated as the control group and received routine care, while patients admitted from October 2019 to March 2020 were treated as the experimental group and received nursing risk management based on PDCA cycle quality control concept. Blood glucose control time, urine ketone negative conversion time, acidosis correction time, hospital stay, occurrence of complications, depression and anxiety scores, nursing quality and nursing satisfaction were compared between the two groups after intervention.Results:A total of 89 patients were included. There were 43 patients in the control group, including 16 males and 27 females, aged (64.37 ± 15.85) years old; 46 patients in the experimental group, including 23 males and 23 females, aged (59.28 ± 13.66) years old. Before intervention, there were no significant differences in depression and anxiety scores between 2 groups (both P<0.05). After intervention, the blood glucose control time, urine ketone negative conversion time, acidosis correction time and hospital stay were (9.24 ± 1.26), (38.39 ± 3.28), (12.23 ± 1.39) h and (11.34 ± 2.28) d in the experimental group, shorter than (9.94 ± 1.40), (40.12 ± 3.67), (13.66 ± 2.47) h and (13.62 ± 3.40) d in the control group, the differences were statistically significant ( t values were 2.35-3.74, all P<0.05). The occurrence of complications, depression and anxiety scores in the experimental group were 13.04% (6/46), (3.18 ± 0.37) points, (4.69 ± 1.33) points, lower than 30.23% (13/43), (3.72 ± 0.96) points, (5.77 ± 1.60) points in the control group, the differences were statistically significant ( χ2=3.91, t=3.55, 3.47, all P<0.05). The total score of nursing quality and nursing satisfaction in the experimental group were (82.91 ± 4.22), (89.02 ± 4.95) points, higher than (76.86 ± 5.01), (81.14 ± 7.89) points in the control group, the differences were statistically significant ( t=6.18, 5.68, both P<0.05). Conclusions:Nursing risk management based on PDCA cycle quality control concept can shorten the treatment time of patients with diabetic ketoacidosis, reduce the risk of complications, ensure the nursing quality, relieve the negative emotions during hospitalization, and improve satisfaction of patients.

Diabetes of the exocrine pancreas(DEP) refers to a complication of diseases of the exocrine pancreas, associated with an increased risk of pancreatic cancer. Recent evidence has indicated that DEP, after type 2 diabetes, has become the second most common type of adults-onset diabetes, with a higher prevalence than type 1 diabetes. DEP is not a single condition but encompasses various exocrine pancreatic disorders that lead to hyperglycemia through different mechanisms, creating significant diagnostic and therapeutic challenges. This review examines the latest research on the risk factors and pathogenesis of DEP, aiming to provide insights to improve its clinical management strategies.