Objective:To evaluate the efficacy of peritoneal dialysis (PD) in the treatment of acute kidney injury (AKI) in critically ill neonates.Methods:It was a retrospective study. The baseline characteristic data, PD protocols, PD catheter placement methods and clinical outcomes of AKI neonates who underwent PD in the General Hospital of Ningxia Medical University between July 2015 and December 2024 were collected and analyzed.Results:(1) Among the 8 neonates with AKI, gestational age was (30.38±6.02) weeks, and birth weight was 1 397.5 (839.0, 2 312.5) g, with 6 premature infants. The time from birth to AKI onset was 144 (48, 294) hours. The leading cause of AKI was sepsis (6/8). The treatment time of PD was (93.12±37.20) hours. (2) Renal function recovery: After PD treatment, urine output was significantly increased ( Z=-3.29, P<0.001), and serum creatinine was significantly decreased ( t=2.66, P=0.032). (3) Hyperkalemia: Six out of 8 patients presented with hyperkalemia, which significantly decreased after PD treatment ( t=3.37, P=0.008). (4) Acid-base balance:Five out of 8 neonates had metabolic acidosis, and 3 of 5 neonates achieved basically complete correction (including lactic acidosis). There was no statistically significant difference in acid-base balance indicators before and after PD treatment (all P>0.05). (5) PD-related complications: Two out of 8 patients experienced peritoneal dialysate leakage, and no other PD-related complications occurred. (6) Outcomes: The hospital stay was 27.0 (8.0, 57.5) days. Four out of 8 neonates survived, while the other 4 neonates died after withdrawal of treatment. The primary cause was multiple organ failure. Conclusions:PD is a safe and effective treatment for neonatal AKI, facilitating early renal recovery and correction of electrolyte and acid-base imbalances.

Objective:To analyze patch test results in patients with rosacea, investigate the prevalence of contact sensitization, and identify common allergens, to provide relevant evidence for the diagnosis, treatment, and preventive interventions for rosacea.Methods:A cross-sectional retrospective survey was conducted to analyze the positive contact allergy rate and allergen distribution in 186 rosacea patients who underwent the 60-item China Standard Series Patch Test (CB-1000) at the Department of Dermatology, Peking University First Hospital, from January 2023 to September 2024.Results:Among the 186 patients, 159(85.5%) showed positive reactions in patch tests. The top three allergens with the highest positivity rates were: metal salts, preservatives and fragrances. The top 10 individual allergens with the highest positivity rates were: nickelsulfate hexahydrate 46.8%(87/186), cobaltchloride hexahydrate 29.0%(54/186), hydroperoxides of linalool 15.1%(28/186), carba mix 14.0%(26/186), propolis 9.7%(18/186), fragrance mix Ⅰ 8.6%(16/186), methyl dibromo glutaronitrile 8.1%(15/186), Peru balsam 7.5%(14/186), gold sodium thiosulfate dihydrate 7.5%(14/186), and hydroperoxides of limonene 7.5%(14/186). The overall positivity rate for cosmetics-related allergens was 56.5% (105/186), with the top five allergens being: hydroperoxide of linalool 15.1%(28/186), propolis 9.7%(18/186), fragrance mix Ⅰ 8.6%(16/186), methyl dibromo glutaronitrile 8.1%(15/186), and Peru balsam 7.5%(14/186).Conclusion:The overall positivity rate for patch test allergens in rosacea patients is high. The most common allergen types are metal salts, preservatives, and fragrance agents. Cosmetics-related allergens also show a high positivity rate. Rosacea patients should avoid exposure to these allergens.

Objective: To establish a prenatal non-invasive method for combined detection of fetal ABO, RhD, and RhCE blood group genotypes based on fluorescence quantitative PCR (FQ-PCR) technology, and to evaluate its clinical value in the early prenatal diagnosis of hemolytic disease of the fetus and newborn (HDFN). Methods: A total of 200 high-risk singleton pregnant women who underwent prenatal examinations in our hospital from January 2022 to December 2024 were prospectively enrolled. They were divided into four groups: the ABO incompatibility group (n=100), the RhD incompatibility group (n=50), the RhCE incompatibility group (n=50), and the control group (n=200). FQ-PCR technology was used to detect cell-free fetal DNA (cff-DNA) in maternal plasma, targeting the ABO system (261delG, 796C>A), exons 5/7 of the RHD gene, and the key loci of RhCE system (C/c, E/e). After delivery, the blood group of newborn was verified by serological testing of umbilical cord blood., and the hemolysis panel tests (direct antiglobulin test, free antibody test, and antibody release test) were performed to evaluate the detection consistency and identify high-risk factors. Results: The detection coincidence rates for ABO, RhD, and RhCE blood groups were 98.0% (98/100), 100.0% (50/50), and 96.0% (48/50), respectively. The incidence of HDFN in the ABO incompatibility group was 69.0% (69/100), which is significantly higher than that in the RhD incompatibility group (10.0%, 5/50) and the RhCE incompatibility group (2.0%, 1/50). Multivariate analysis identified maternal blood type O (OR=3.021), maternal RhD-negative (OR=5.253), and maternal age ≥35 years (OR=1.950) as independent risk factors for HDFN (all P<0.05). Conclusion: Prenatal non-invasive combined detection of multiple blood group antigen genotypes can significantly improve the efficiency of early diagnosis of HDFN and provide accurate early warning for high-risk pregnant women.

Objective To analyze dynamic contrast-enhanced MRI (DCE-MRI) radiomic features using machine learning algorithms, and to develop and validate a predictive model for HER-2 status in breast cancer. Methods The DCE-MRI images of 272 treatment-naive female patients with breast cancer between 2020 and 2022 were included in this study. Regions of interest (ROIs) were manually segmented using 3d-Slicer software, and radiomic features were extracted. All patients were randomly divided into training sets or validation sets at a ratio of 4∶1. The least absolute shrinkage and selection operator (LASSO) algorithm was used for feature screening on the training set, followed by the development of predictive models using six machine learning algorithms. Internal cross-validation was performed to compare the performance differences between the models. The best-performing model was selected, trained on the training set, and evaluated on the validation set. Evaluation metrics included area under the curve (AUC), sensitivity, specificity, precision, and recall rate. Results The clinical data of patients in the training set and validation set showed no significant differences. Five features were identified by the LASSO algorithm. With these features, six machine learning models were developed on the training set, and their predictive performance was internally cross-validated using the bagging method. XGBoost model had the highest mean AUC (0.696), followed by RF model (0.690); XGBoost model had the highest mean precision (0.756), followed by LR and RF models. Therefore, XGBoost was the optimal model. An HER-2 predictive model was built using the XGBoost algorithm on the training set and applied to the validation set. The AUC, precision, sensitivity, and specificity of the predictive model on the validation set were calculated, and ROC curves, precision-recall curves, calibration curves, and decision-making curves were plotted. Conclusion This study constructed and evaluated different DCE-MRI radiomics-based machine learning models for predicting HER-2 status in breast cancer. Among them, XGBoost algorithm performed the best and has the potential to become a new non-invasive method for preoperative prediction of HER-2 status, providing reliable evidence for personalized clinical diagnosis and treatment.

The scientific interpretation of the theory of medicinal properties of TCM is a research hotspot in the modernization of TCM. It is of great value to clarify the property and degree of cold and heat in Chinese materia medica for guiding clinical precise medication. In recent years, the research on the cold and heat properties of Chinese materia medica has been carried out at the animal, cell and molecular levels. Based on the objective material basis of medicinal properties, from the perspective of biological effects such as thermodynamics and multiomics; with the help of infrared thermal imaging and other technologies for analysis; forming a variety of research models such as "property-structure relationship". Related research has developed from a single material component or index to a new model that tends to integrate multi-source information and multi-dimensional data. However, how to deal with the problems of large sample size, strong redundancy, high heterogeneity, and how to integrate multi-dimensional information are still research difficulties. With its powerful computing and learning ability, machine learning can show good discrimination and prediction ability in the study of cold and hot properties of Chinese materia medica, and play an important role in the study of cold and hot properties of Chinese materia medica. At present, the most widely used algorithms are linear discriminant analysis, Logistic discriminant analysis, support vector machine, decision tree, random forest and so on. The data dimension of the existing research needs to be enriched, the algorithm has room for further optimization, and a more detailed discriminant model of cold and hot properties of Chinese materia medica needs to be established.

Objective : To investigate the effects of acarbose and pioglitazone on the levels of sex hormones in adult female rats ，and to explore their regulatory effects on the hypothalamic-pituitary-ovarian axis ( HPOA) and its mechanism． Methods : Adult female SD rats aged 2 months were randomly divided into 0．9% sodium chloride so- lution control group (NS) ，acarbose low (AL) ，medium (AM) and high (AH) dose groups and pioglitazone low (PL) ，medium (PM) and high (PH) dose groups．AL，AM and AH groups were given 20，40 and 60 mg / (kg · d) acarbose，and PL，PM and PH groups were given 5，10 and 15 mg / (kg · d) pioglitazone，respectively．Af- ter 28 days of intervention，serum gonadotropin (FSH，LH) and ovarian secreted hormone ( E2，P，T) were de- tected by ELISA，and the effects of acarbose and pioglitazone on HPOA were investigated by organ index analysis and histopathological observation of pituitary gland and ovary． Results : Compared with the NS group，the serum FSH in the PL，PM and PH groups decreased ( all P＜0. 01) ，the serum LH in the PL，PM and PH groups de- creased (P＜0. 05，P＜0. 01，P ＜0. 01) ，and the organ indices in the PM and PH groups decreased ( all P < 0. 01) ．HE staining of the adenohypophysis in the PL，PM and PH groups showed an increase in eosinophils，a de- crease in basophils，and an expansion and increase in the number of blood sinuses．In the PM and PH groups，HE staining of the ovaries showed that there were no significant differences in follicles at all levels，but the development was poor，the number of primordial follicles decreased，and the number of corpus luteum increased．Compared with the NS group，the serum P in the AM and AH groups decreased ( all P ＜0. 01) ，and serum E2 in AM and AH groups decreasd (all P＜0. 05) ． Conclusion Pioglitazone affects HPOA by regulating pituitary function directly． However，the effect of acarbose on HPOA may be mediated through the gut-brain axis，and has no direct correlation with the ovarian structure．

Immunotherapy based on immune checkpoint inhibitor (ICI) has shown remarkable efficacy in the treatment of microsatellite instability (MSI)-high CRC. However, the monotherapy of ICI in microsatellite stable (MSS) CRC has not been satisfactory. Some patients with MSS CRC can benefit from various combination immunotherapy regimens. Identifying appropriate biomarkers to select MSS-type CRC patients who will benefit from ICI treatment prior to therapy initiation and dynamically monitoring treatment efficacy during the therapeutic course have become crucial components of precision medicine in clinical practice. This article reviews the current research status of traditional biomarkers such as tumor mutation burden (TMB) and PD-L1 expression. It also explores the latest research progress and clinical translation potential of emerging biomarkers, including POLE/POLD1 mutations, immune score, circulating tumor DNA, and gut microbiome. Furthermore, it addresses the challenges in the clinical application of biomarkers, such as the controversy over TMB cutoff values and the heterogeneity of PD-L1 expression. Finally, it outlines future research directions with the aim of providing a basis for clinical decision-making in immunotherapy and facilitating the realization of precision medicine.

Immunotherapy based on immune checkpoint inhibitor (ICI) has shown remarkable efficacy in the treatment of microsatellite instability (MSI)-high CRC. However, the monotherapy of ICI in microsatellite stable (MSS) CRC has not been satisfactory. Some patients with MSS CRC can benefit from various combination immunotherapy regimens. Identifying appropriate biomarkers to select MSS-type CRC patients who will benefit from ICI treatment prior to therapy initiation and dynamically monitoring treatment efficacy during the therapeutic course have become crucial components of precision medicine in clinical practice. This article reviews the current research status of traditional biomarkers such as tumor mutation burden (TMB) and PD-L1 expression. It also explores the latest research progress and clinical translation potential of emerging biomarkers, including POLE/POLD1 mutations, immune score, circulating tumor DNA, and gut microbiome. Furthermore, it addresses the challenges in the clinical application of biomarkers, such as the controversy over TMB cutoff values and the heterogeneity of PD-L1 expression. Finally, it outlines future research directions with the aim of providing a basis for clinical decision-making in immunotherapy and facilitating the realization of precision medicine.

Objective:To evaluate the efficacy of peritoneal dialysis (PD) in the treatment of acute kidney injury (AKI) in critically ill neonates.Methods:It was a retrospective study. The baseline characteristic data, PD protocols, PD catheter placement methods and clinical outcomes of AKI neonates who underwent PD in the General Hospital of Ningxia Medical University between July 2015 and December 2024 were collected and analyzed.Results:(1) Among the 8 neonates with AKI, gestational age was (30.38±6.02) weeks, and birth weight was 1 397.5 (839.0, 2 312.5) g, with 6 premature infants. The time from birth to AKI onset was 144 (48, 294) hours. The leading cause of AKI was sepsis (6/8). The treatment time of PD was (93.12±37.20) hours. (2) Renal function recovery: After PD treatment, urine output was significantly increased ( Z=-3.29, P<0.001), and serum creatinine was significantly decreased ( t=2.66, P=0.032). (3) Hyperkalemia: Six out of 8 patients presented with hyperkalemia, which significantly decreased after PD treatment ( t=3.37, P=0.008). (4) Acid-base balance:Five out of 8 neonates had metabolic acidosis, and 3 of 5 neonates achieved basically complete correction (including lactic acidosis). There was no statistically significant difference in acid-base balance indicators before and after PD treatment (all P>0.05). (5) PD-related complications: Two out of 8 patients experienced peritoneal dialysate leakage, and no other PD-related complications occurred. (6) Outcomes: The hospital stay was 27.0 (8.0, 57.5) days. Four out of 8 neonates survived, while the other 4 neonates died after withdrawal of treatment. The primary cause was multiple organ failure. Conclusions:PD is a safe and effective treatment for neonatal AKI, facilitating early renal recovery and correction of electrolyte and acid-base imbalances.

Objective:To analyze patch test results in patients with rosacea, investigate the prevalence of contact sensitization, and identify common allergens, to provide relevant evidence for the diagnosis, treatment, and preventive interventions for rosacea.Methods:A cross-sectional retrospective survey was conducted to analyze the positive contact allergy rate and allergen distribution in 186 rosacea patients who underwent the 60-item China Standard Series Patch Test (CB-1000) at the Department of Dermatology, Peking University First Hospital, from January 2023 to September 2024.Results:Among the 186 patients, 159(85.5%) showed positive reactions in patch tests. The top three allergens with the highest positivity rates were: metal salts, preservatives and fragrances. The top 10 individual allergens with the highest positivity rates were: nickelsulfate hexahydrate 46.8%(87/186), cobaltchloride hexahydrate 29.0%(54/186), hydroperoxides of linalool 15.1%(28/186), carba mix 14.0%(26/186), propolis 9.7%(18/186), fragrance mix Ⅰ 8.6%(16/186), methyl dibromo glutaronitrile 8.1%(15/186), Peru balsam 7.5%(14/186), gold sodium thiosulfate dihydrate 7.5%(14/186), and hydroperoxides of limonene 7.5%(14/186). The overall positivity rate for cosmetics-related allergens was 56.5% (105/186), with the top five allergens being: hydroperoxide of linalool 15.1%(28/186), propolis 9.7%(18/186), fragrance mix Ⅰ 8.6%(16/186), methyl dibromo glutaronitrile 8.1%(15/186), and Peru balsam 7.5%(14/186).Conclusion:The overall positivity rate for patch test allergens in rosacea patients is high. The most common allergen types are metal salts, preservatives, and fragrance agents. Cosmetics-related allergens also show a high positivity rate. Rosacea patients should avoid exposure to these allergens.