[Objective] To investigate and summarize the clinicopathological features, diagnosis, treatment and prognosis of adrenocortical carcinoma with rhabdoid features. [Methods] The clinical diagnosis and treatment of a case of adrenocortical carcinoma with rhabdoid features admitled to Department of Urology, Weifang People's Hospital were reported.The clinical manifestations, pathological features, diagnosis and prognosis of the disease were analyzed in combination with relevant literature. [Results] A 34-year-old male patient was admitted due to scrotal distension and pain that had persisted for 6 months.Imaging examination showed a huge soft tissue tumor in the left adrenal region of the retroperitoneum with compression displacement of the left kidney, leading to obstruction of venous return in the left spermatic vein, which in turn caused varicose veins.The levels of serum renin, angiotensin, aldosterone, cortisol, and catecholamine were within normal ranges.Surgical resection of the tumor was performed, and postoperative pathological examination revealed that the tumor tissue was predominantly composed of rhabdoid cells, exhibiting positive immunohistochemical staining for INI 1, Syn, Calretinin and Vimentin.Genetic testing did not identify any deletion of SMARCB1 and SMARCA4 mutations.Therefore, the diagnosis was adrenocortical carcinoma with rhabdoid features.At the current 20-month follow-up, no recurrence or metastasis was observed.A review of the literature found that only 7 cases of this disease had been reported. [Conclusion] Adrenocortical carcinoma with rhabdoid features is a rare disease, and a definitive diagnosis is dependent upon pathological examination.Surgical resection remains the primary treatment.Long-term follow-up is essential, and further research is needed to evaluate the impact of adjuvant therapy.

Objective Based on the radiomics features extracted from the unenhanced CT images of the lower abdomen, a variety of machine learning models were constructed to explore their application value in the assessment of split renal function. Methods A retrospective analysis was conducted on the unenhanced CT images from 240 single kidneys in patients with clinically suspected renal dysfunction. Based on the results of single-photon emission computed tomography renal dynamic imaging, the cases were classified into the normal glomerular filtration rate group (n=118) and the decreased glomerular filtration rate group (n=122). The region of interest was outlined on the unenhanced CT images and the radiomics features were extracted. The features were selected by correlation analysis and least absolute shrinkage and selection operator, and the machine learning models were constructed based on the algorithms of decision tree, support vector machine, random forest, logistic regression, and extreme gradient boosting. Area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity were calculated to compare the performance of different models. Results Sixteen radiomics features were selected for constructing the machine learning models. The support vector machine model showed relatively high performance for the assessment of split renal function on the test set, with an area under the receiver operating characteristic curve value of 0.883 (95% confidence interval: 0.804-0.961), an accuracy of 0.778, a sensitivity of 0.811, and a specificity of 0.743. Conclusion The machine learning models constructed based on unenhanced CT radiomics can be used to preliminarily assess split renal function, which provides an innovative, convenient, and safe method for clinical diagnosis and has positive significance for treatment.

【Objective】 To establish a blood quality monitoring indicator system, in order to continuously improve blood quality and standardized management. 【Methods】 Based on the research of literature and standards, and guided by the key control points of blood collection and supply process, the blood quality monitoring indicator system was developed. Through two rounds of Delphi expert consultation, the indicator content was further revised and improved according to expert opinions after six months of trial implementation. The indicator weight was calculated by questionnaire and analytic hierarchy process. 【Results】 A blood quality monitoring indicator system covering the whole process of blood collection and supply was constructed, including five primary indicators, namely blood donation service, blood component preparation, blood testing, blood supply and quality control, as well as 72 secondary indicators, including definitions, calculation formulas, etc. Two rounds of expert consultation and two rounds of feasibility study meeting were held to revise 17 items and the weight of each indicator was obtained through the analytic hierarchy process. After partial adjustments, a blood quality monitoring indicator system was formed. 【Conclusion】 A blood quality monitoring indicator system covering the whole process of blood collection and supply has been established for the first time, which can effectively evaluate the quality management level of blood banks and coordinate blood quality control activities of blood banks in Shandong like pieces in a chess game, thus improving the standardized management level

【Objective】 To objectively evaluate the quality control level of blood testing process in blood banks through quantitative monitoring and trend analysis, and to promote the homogenization level and standardized management of blood testing laboratories in blood banks. 【Methods】 A quality monitoring indicator system covering the whole process of blood collection and supply, including blood donation service, blood component preparation, blood testing, blood supply and quality control was established. The questionnaire Quality Monitoring Indicators for Blood Collection and Supply Process with clear definition of indicators and calculation formulas was distributed to 17 blood banks in Shandong province. Quality monitoring indicators of each blood bank from January to December 2022 were collected, and 31 indicators in terms of blood testing were analyzed using SPSS25.0 software. 【Results】 The proportion of unqualified serological tests in 17 blood bank laboratories was 55.84% for ALT, 13.63% for HBsAg, 5.08% for anti HCV, 5.62% for anti HIV, 18.18% for anti TP, and 1.65% for other factors (mainly sample quality). The detection unqualified rate and median were (1.23±0.57)% and 1.11%, respectively. The ALT unqualified rate and median were (0.74±0.53)% and 0.60%, respectively. The detection unqualified rate was positively correlated with ALT unqualified rate (r=0.974, P<0.05). The unqualified rate of HBsAg, anti HCV, anti HIV and anti TP was (0.15±0.09)%, (0.05±0.04)%, (0.06±0.03)% and (0.20±0.05)% respectively. The average unqualified rate, average hemolysis rate, average insufficient volume rate and the abnormal hematocrit rate of samples in 17 blood bank laboratories was 0.21‰, 0.08‰, 0.01‰ and 0.02‰ respectively. There were differences in the retest concordance rates of four HBsAg, anti HCV and anti HIV reagents, and three anti TP reagents among 17 blood bank laboratories (P<0.05). The usage rate of ELISA reagents was (114.56±3.30)%, the outage rate of ELISA was (10.23±7.05) ‰, and the out of range rate of ELISA was (0.90±1.17) ‰. There was no correlation between the out of range rate, outrage rate and usage rate (all P>0.05), while the outrage rate was positively correlated with the usage rate (r=0.592, P<0.05). A total of 443 HBV DNA positive samples were detected in all blood banks, with an unqualified rate of 3.78/10 000; 15 HCV RNA positive samples were detected, with an unqualified rate of 0.13/10 000; 5 HIV RNA positive samples were detected, with an unqualified rate of 0.04/10 000. The unqualified rate of NAT was (0.72±0.04)‰, the single NAT reaction rate [(0.39±0.02)‰] was positively correlated with the single HBV DNA reaction rate [ (0.36±0.02) ‰] (r=0.886, P<0.05). There was a difference in the discriminated reactive rate by individual NAT among three blood bank laboratories (C, F, H) (P<0.05). The median resolution rate of 17 blood station laboratories by minipool test was 36.36%, the median rate of invalid batch of NAT was 0.67%, and the median rate of invalid result of NAT was 0.07‰. The consistency rate of ELISA dual reagent detection results was (99.63±0.24)%, and the median length of equipment failure was 14 days. The error rate of blood type testing in blood collection department was 0.14‰. 【Conclusion】 The quality monitoring indicator system for blood testing process in Shandong can monitor potential risks before, during and after the experiment, and has good applicability, feasibility, and effectiveness, and can facilitate the continuous improvement of laboratory quality control level. The application of blood testing quality monitoring indicators will promote the homogenization and standardization of blood quality management in Shandong, and lay the foundation for future comprehensive evaluations of blood banks.

【Objective】 To establish an effective quality monitoring indicator system for blood quality control in blood banks, in order to analyze the quality control indicators for blood collection and supply, and evaluate blood quality control process, thus promoting continuous improvement and standardizing management of blood quality control in blood banks. 【Methods】 A quality monitoring indicator system covering the whole process of blood collection and supply, including blood donation services, component preparation, blood testing, blood supply and quality control was established. The Questionnaire of Quality Monitoring Indicators for Blood Collection and Supply Process was distributed to 17 blood banks in Shandong, which clarified the definition and calculation formula of indicators. The quality monitoring indicator data from January to December 2022 in each blood bank were collected, and 20 quality control indicators data were analyzed by SPSS25.0 software. 【Results】 The average pass rate of key equipment monitoring, environment monitoring, key material monitoring, and blood testing item monitoring of 17 blood banks were 99.47%, 99.51%, 99.95% and 98.99%, respectively. Significant difference was noticed in the pass rate of environment monitoring among blood banks of varied scales(P<0.05), and the Pearson correlation coefficient (r) between the total number of blood quality testing items and the total amount of blood component preparation was 0.645 (P<0.05). The average discarding rates of blood testing or non-blood testing were 1.14% and 3.36% respectively, showing significant difference among blood banks of varied scales (P<0.05). The average discarding rate of lipemic blood was 3.07%, which had a positive correlation with the discarding rate of non testing (r=0.981 3, P<0.05). There was a statistically significant difference in the discarding rate of lipemic blood between blood banks with lipemic blood control measures and those without (P<0.05). The average discarding rate of abnormal color, non-standard volume, blood bag damage, hemolysis, blood protein precipitation and blood clotting were 0.20%, 0.14%, 0.06%, 0.06%, 0.02% and 0.02% respectively, showing statistically significant differences among large, medium and small blood banks(P<0.05).The average discarding rates of expired blood, other factors, confidential unit exclusion and unqualified samples were 0.02%, 0.05%, 0.003% and 0.004%, respectively. The discarding rate of blood with air bubbles was 0.015%, while that of blood with foreign body and unqualified label were 0. 【Conclusion】 The quality control indicator system of blood banks in Shandong can monitor weak points in process management, with good applicability, feasibility, and effectiveness. It is conducive to evaluate different blood banks, continuously improve the quality control level of blood collection and supply, promote the homogenization and standardization of blood quality management, and lay the foundation for comprehensive evaluation of blood banks in Shandong.

【Objective】 To establish an effective quality indicator monitoring system, scientifically and objectively evaluate the quality management level of blood banks, and achieve continuous improvement of quality management in blood bank. 【Methods】 A quality monitoring indicator system that covers the whole process of blood collection and supply was established, the questionnaire of Quality Monitoring Indicators for Blood Collection and Supply Process with clear definition of indicators and calculation formulas was distributed to 17 blood banks in Shandong. Statistical analysis of 21 quality monitoring indicators in terms of blood donation service (10 indicators), blood component preparation (7 indicators ), and blood supply (4 indicators) from each blood bank from January to December 2022 were conducted using SPSS25.0 software The differences in quality monitoring indicators of blood banks of different scales were analyzed. 【Results】 The average values of quality monitoring indicators for blood donation service process of 17 blood banks were as follows: 44.66% (2 233/5 000) of regular donors proportion, 0.22% (11/50) of adverse reactions incidence, 0.46% (23/5 000) of non-standard whole blood collection rate, 0.052% (13/25 000) of missed HBsAg screening rate, 99.42% (4 971/5 000) of first, puncture successful rate, 86.49% (173/200) of double platelet collection rate, 66.50% (133/200) of 400 mL whole blood collection rate, 99.25% (397/400) of donor satisfaction rate, 82.68% (2 067/2 500) of use rate of whole blood collection bags with bypass system with sample tube, and 1 case of occupational exposure in blood collection.There was a strong positive correlation between the proportion of regular blood donors and the collection rate of 400 mL whole blood (P<0.05). The platelet collection rate, incidence of adverse reactions to blood donation, and non-standard whole blood collection rate in large blood banks were significantly lower than those in medium and small blood banks (P<0.05). The average quality monitoring indicators for blood component preparation process of 17 blood banks were as follows: the leakage rate of blood component preparation bags was 0.03% (3/10 000), the discarding rate of lipemic blood was 3.05% (61/2 000), the discarding rate of hemolysis blood was 0.13%(13/10 000). 0.06 case had labeling errors, 8 bags had blood catheter leaks, 2.76 bags had blood puncture/connection leaks, and 0.59 cases had non-conforming consumables. The discarding rate of hemolysis blood of large blood banks was significantly lower than that of medium and small blood banks (P<0.05), and the discarding rate of lipemic blood of large and medium blood banks was significantly lower than that of small blood banks (P<0.05). The average values of quality monitoring indicators for blood supply process of 17 blood banks were as follows: the discarding rate of expired blood was 0.023% (23/100 000), the leakage rate during storage and distribution was of 0.009%(9/100 000), the discarding rate of returned blood was 0.106% (53/50 000), the service satisfaction of hospitals was 99.16% (2 479/2 500). The leakage rate of blood components during storage and distribution was statistically different with that of blood component preparation bags between different blood banks (P<0.05). There were statistically significant differences in the proportion of regular blood donors, incidence of adverse reactions, non-standard whole blood collection rate, 400 mL whole blood collection rate, double platelet collection rate, the blood bag leakage rate during preparation process, the blood components leakage rate during storage and distribution as well as the discarding rate of lipemic blood, hemolysis blood, expired blood and returned blood among large, medium and small blood banks (all P<0.05). 【Conclusion】 The establishment of a quality monitoring indicator system for blood donation services, blood component preparation and blood supply processes in Shandong has good applicability, feasibility and effectiveness. It can objectively evaluate the quality management level, facilitate the continuous improvement of the quality management system, promote the homogenization of blood management in the province and lay the foundation for future comprehensive evaluation of blood banks.

Background Salidroside (SAL) has a protective effect on multiple organ systems. Exposure to fine particulate matter (PM_2.5) in the atmosphere may lead to disruptions in gut microbiota and impact intestinal health. The regulatory effect of SAL on the gut microbiota of mice exposed to PM_2.5 requires further investigation. Objective To evaluate gut microbiota disruption in mice after being exposed to PM_2.5 and the potential effect of SAL. Methods Forty male C57BL/6 mice, aged 6 to 8 weeks, were randomly divided into four groups: a control group, an SAL group, a PM_2.5 group, and an SAL+PM_2.5 group, each containing 10 mice. In the SAL group and the SAL+PM_2.5 group, the mice were administered SAL (60 mg·kg⁻¹) by gavage, while in the control group and the PM_2.5 group, sterile saline (10 mL·kg⁻¹) was administered by gavage. In the PM_2.5 group and the SAL+PM_2.5 group, PM_2.5 suspension (8 mg·kg⁻¹) was intratracheally instilled, and in the control group and SAL group, sterile saline (1.5 mL·kg⁻¹) was intratracheally administered. Each experiment cycle spanned 2 d, with a total of 10 cycles conducted over 20 d. Histopathological changes in the ileum tissue of the mice were observed after HE staining. Colon contents were collected for gut microbiota sequencing and short-chain fatty acids (SCFAs) measurements. Results The PM_2.5 group showed infiltration of inflammatory cells in the ileum tissue, while the SAL+PM_2.5 group exhibited only a small amount of inflammatory cell infiltration. Compared to the control group, the PM_2.5 group showed decreased Shannon index (P<0.05) and increased Simpson index (P<0.05), indicating that the diversity of gut microbiota in this group was decreased; the SAL+PM_2.5 group showed increased Shannon index compared to the PM_2.5 group (P<0.05) and decreased Simpson index (P<0.05), indicating that the diversity of gut microbiota in mice intervened with SAL was increased. The principal coordinates analysis (PCoA) revealed a significant separation between the PM_2.5 group and the control group, while the separation trend was less evident among the control group, the SAL group, and the SAL+PM_2.5 group. The unweighted pair-group method with arithmetic means (UPGMA) clustering tree results showed that the control group and the SAL group clustered together first, followed by clustering with the SAL+PM_2.5 group, and finally, the three groups clustered with the PM_2.5 group. The PCoA and UPGMA clustering results indicated that the uniformity and similarity of the microbiota in the PM_2.5 group were significantly decreased. Compared to the control group, the PM_2.5 group showed decreased abundance of phylum Bacteroidetes and Candidatus_Saccharimonas (P<0.05) and increased abundance of phylum Proteobacteria, genus Escherichia, genus Bacteroides, genus Prevotella, genus Enterococcus, and genus Proteus (P<0.05). Compared to the PM_2.5 group, the SAL+PM_2.5 group showed decreased abundance of phylum Proteobacteria, phylum Actinobacteria, genus Prevotella, and genus Proteus (P<0.05), and increased abundance of Candidatus_Saccharimonas (P<0.05). The PM_2.5 group showed reduced levels of propionic acid, valeric acid, and hexanoic acid compared to the control group (P<0.05), while the SAL+PM_2.5 group showed increased levels of propionic acid, isobutyric acid, butyric acid, valeric acid, and hexanoic acid compared to the PM_2.5 group (P<0.05). Conclusion Exposure to PM_2.5 can cause pathological alterations, microbial dysbiosis, and disturbing production of SCFAs in intestinal tissue in mice. However, SAL can provide a certain degree of protective effect against these changes.

Humans ; Lymph Nodes/pathology* ; Lymph Node Excision ; Neoplasms/pathology* ; Dissection

Neovascular age-related macular degeneration(nARMD)is a prevalent age-related retinal disease that significantly impairs vision. Numerous studies have shown that lipid metabolism disorders contribute to the progression of nARMD. The relationship is complex and involved factors such as fatty acids, cholesterol, variations in lipid metabolism genes, and other influencing factors. Lipid metabolism disorders lead to retinal vascular abnormalities and inflammatory responses by triggering oxidative stress and inhibiting autophagy. This, in turn, accelerates the formation of new blood vessels and causes damage to macular cells and tissues. In animal experiments, drugs designed for lipid metabolism disorders have shown that regulating lipid metabolism could be a potentially effective strategy for treating nARMD. This article reviews the role of lipid metabolism in the progression and treatment of neovascular age-related macular degeneration, aiming to offer new insights for nARMD treatment.