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BackgroundAcute kidney injury (AKI) is a common complication after surgery and is associated with detrimental outcomes. This systematic review and meta-analysis evaluated perioperative dexmedetomidine on AKI and renal function after non-cardiac surgery.MethodsPubMed, Embase, and Cochrane Library databases were searched until August 2023 for randomised trials comparing dexmedetomidine with normal saline on AKI and renal function in adults undergoing non-cardiac surgery. The primary outcome was the incidence of AKI (according to Kidney Disease Improving Global Outcomes or Acute Kidney Injury Network criteria). Meta-analysis was performed using a random-effect model. We conducted sensitivity analysis, trial sequential analysis (TSA), and Grading of Recommendations Assessment, Development and Evaluation level of evidence.ResultsTwenty-three trials involving 2440 patients were included. Dexmedetomidine administration, as compared to normal saline, significantly reduced the incidence of AKI (7.4% vs. 13.2%; risk ratio = 0.57, 95% CI = 0.40 to 0.83, P =  0.003, I2 = 0%; a high level of evidence); TSA and sensitivity analyses suggested the robustness of this outcome. For the renal function and inflammation parameters, dexmedetomidine decreased serum creatinine, blood urea nitrogen, cystatin C, tumour necrosis factor-α, and interleukin-6, and increased urine output and estimated glomerular filtration rate. Additionally, dexmedetomidine reduced postoperative nausea and vomiting and length of hospital stay. Dexmedetomidine was associated with an increased rate of bradycardia, but not hypotension.ConclusionDexmedetomidine administration reduced the incidence of AKI and improved renal function after non-cardiac surgery. Based on a high level of evidence, dexmedetomidine is recommended as a component of perioperative renoprotection.RegistrationInternational Prospective Register of Systematic Reviews; Registration number: CRD42022299252.

Objective To investigate the application value of combining the Demirjian’s method with machine learning algorithms for dental age estimation in northern Chinese Han children and adolescents. Methods Oral panoramic images of 10 256 Han individuals aged 5 to 24 years in northern China were collected. The development of eight permanent teeth in the left mandibular was classified into different stages using the Demirjian’s method. Various machine learning algorithms, including support vector regression （SVR）, gradient boosting regression （GBR）, linear regression （LR）, random forest regression （RFR）, and decision tree regression （DTR） were employed. Age estimation models were constructed based on total, female, and male samples respectively using these algorithms. The fitting performance of different machine learning algorithms in these three groups was evaluated. Results SVR demonstrated superior estimation efficiency among all machine learning models in both total and female samples, while GBR showed the best performance in male samples. The mean absolute error （MAE） of the optimal age estimation model was 1.246 3, 1.281 8 and 1.153 8 years in the total, female and male samples, respectively. The optimal age estimation model exhibited varying levels of accuracy across different age ranges, which provided relatively accurate age estimations in individuals under 18 years old. Conclusion The machine learning model developed in this study exhibits good age estimation efficiency in northern Chinese Han children and adolescents. However, its performance is not ideal when applied to adult population. To improve the accuracy in age estimation, the other variables can be considered.

AbstractEfferocytosis refers to the process by which phagocytes remove apoptotic cells and related apoptotic products. It is essential for the growth and development of the body, the repair of damaged or inflamed tissues, and the balance of the immune system. Damaged efferocytosis will cause a variety of chronic inflammation and immune system diseases. Many studies show that efferocytosis is a process mediated by mitochondria. Mitochondrial metabolism, mitochondrial dynamics, and communication between mitochondria and other organelles can all affect phagocytes’ clearance of apoptotic cells. Therefore, targeting mitochondria to modulate phagocyte efferocytosis is an anticipated strategy to prevent and treat chronic inflammatory diseases and autoimmune diseases. In this review, we introduced the mechanism of efferocytosis and the pivoted role of mitochondria in efferocytosis. In addition, we focused on the therapeutic implication of drugs targeting mitochondria in diseases related to efferocytosis dysfunction. [ABSTRACT FROM AUTHOR]