[Transformation of scientific research results into teaching resources to improve the teaching effect: taking the teaching of the chromatographic method in the pharmaceutical analysis course as an example].

The pharmaceutical analysis course is a three-dimensional knowledge network that connects several courses to form a new comprehensive knowledge node involving a large knowledge system and flexible knowledge structure. In this course, the subject of chromatography covers a wide range of topics. However, because accurate content is challenging to present, the teaching effect of this subject is poor. In this work, we sought to achieve the educational purpose of establishing morality and cultivating talent, as well as the goal of training highly skilled professionals, by taking the teaching of chromatography in the pharmaceutical analysis course as an example of transforming scientific research results into teaching resources. The resources obtained are integrated into the teaching process to provide innovative and scientific research ideas to students with the aim of not only helping them understand and master technical knowledge but also exercise their ability to raise and solve problems. Furthermore, we expound on how to introduce scientific development frontiers and formulate scientific problems through curriculum design. We also describe how our strategy can promote the teaching effect and achieve teaching objectives. Based on the characteristics of rapid knowledge update and equal emphasis on theory and practice in pharmaceutical analysis, the course is designed by introducing new advances in scientific development, formulating scientific problems, and adopting question- and problem-based learning methods for teaching. The teaching effect is then evaluated through diversified assessment, student feedback, and self-evaluation. The results show that the transformation of scientific research results into teaching resources plays a significant role in stimulating students' interest in learning, improving students' ability to solve problems, and achieving curriculum objectives, all of which greatly improve the teaching effect.

Association analysis between CD14 gene polymorphisms and peri-implantitis susceptibility in a Chinese population.

OBJECTIVE: The goal of the study was to examine the genetic correlation of cluster of differentiation 14 (CD14) gene polymorphisms with peri-implantitis (PI) predisposition in a Chinese Han population. METHODS: In the case-control study, blood samples were collected from PI patients and healthy individuals (n = 120/group), who were admitted to the Affiliated Hospital of Yangzhou University from 2021 to 2023. One-way analysis of variance (ANOVA) was applied to compare differences of continuous variables among different groups. Genotype and allele distributions of CD14 gene rs2569190 and rs2915863 polymorphisms were analyzed between groups via χ2 test. RESULTS: A high percentage of rs2569190 GG genotype or G allele carriers were identified in PI group compared with control group (p < .01). Rs2569190 GG genotype carriers had high risk to develop PI (odds ratio: 2.545, 95% confidence interval: 1.257-5.156, p = .009). The rs2569190 AA genotype carriers had the lowest values of gingival index, plaque index, calculus index, peri-implant pocket depth, and clinical attachment level, which were the highest in cases with GG genotype. CONCLUSION: Rs2569190 polymorphism of CD14 gene was significantly associated with PI predisposition in the Chinese Han population, and the GG genotype and G allele were risk factors for the development of PI.

Multimodal data integration for predicting progression risk in castration-resistant prostate cancer using deep learning: a multicenter retrospective study.

Purpose: Patients with advanced prostate cancer (PCa) often develop castration-resistant PCa (CRPC) with poor prognosis. Prognostic information obtained from multiparametric magnetic resonance imaging (mpMRI) and histopathology specimens can be effectively utilized through artificial intelligence (AI) techniques. The objective of this study is to construct an AI-based CRPC progress prediction model by integrating multimodal data. Methods and materials: Data from 399 patients diagnosed with PCa at three medical centers between January 2018 and January 2021 were collected retrospectively. We delineated regions of interest (ROIs) from 3 MRI sequences viz, T2WI, DWI, and ADC and utilized a cropping tool to extract the largest section of each ROI. We selected representative pathological hematoxylin and eosin (H&E) slides for deep-learning model training. A joint combined model nomogram was constructed. ROC curves and calibration curves were plotted to assess the predictive performance and goodness of fit of the model. We generated decision curve analysis (DCA) curves and Kaplan-Meier (KM) survival curves to evaluate the clinical net benefit of the model and its association with progression-free survival (PFS). Results: The AUC of the machine learning (ML) model was 0.755. The best deep learning (DL) model for radiomics and pathomics was the ResNet-50 model, with an AUC of 0.768 and 0.752, respectively. The nomogram graph showed that DL model contributed the most, and the AUC for the combined model was 0.86. The calibration curves and DCA indicate that the combined model had a good calibration ability and net clinical benefit. The KM curve indicated that the model integrating multimodal data can guide patient prognosis and management strategies. Conclusion: The integration of multimodal data effectively improves the prediction of risk for the progression of PCa to CRPC.

EVM: Incorporating Model Checking into Exploratory Visual Analysis.

Visual analytics (VA) tools support data exploration by helping analysts quickly and iteratively generate views of data which reveal interesting patterns. However, these tools seldom enable explicit checks of the resulting interpretations of data-e.g., whether patterns can be accounted for by a model that implies a particular structure in the relationships between variables. We present EVM, a data exploration tool that enables users to express and check provisional interpretations of data in the form of statistical models. EVM integrates support for visualization-based model checks by rendering distributions of model predictions alongside user-generated views of data. In a user study with data scientists practicing in the private and public sector, we evaluate how model checks influence analysts' thinking during data exploration. Our analysis characterizes how participants use model checks to scrutinize expectations about data generating process and surfaces further opportunities to scaffold model exploration in VA tools.

Discovery of novel and potent dual-targeting AXL/HDAC2 inhibitors for colorectal cancer treatment via structure-based pharmacophore modelling, virtual screening, and molecular docking, molecular dynamics simulation studies, and biological evaluation.

Colorectal cancer (CRC) is one of the most common cancers worldwide. Nowadays, owing to the complex mechanism of tumorigenesis, simultaneous inhibition of multiple targets is an important anticancer strategy. Recent studies have demonstrated receptor tyrosine kinase AXL (AXL) and histone deacetylase 2 (HDAC2) are closely associated with colorectal cancer. Herein, we identified five hit compounds concurrently targeting AXL and HDAC2 using virtual screening. Inhibitory experiments revealed these hit compounds potently inhibited AXL and HDAC2 in the nanomolar range. Among them, Hit-3 showed the strongest inhibitory effects which were better than that of the positive control groups. Additionally, MD assays showed that Hit-3 could bind stably to the AXL and HDAC2 active pockets. Further MTT assays demonstrated that Hit-3 showed potent anti-proliferative activity. Most importantly, Hit-3 exhibited significant in vivo antitumor efficacy in xenograft models. Collectively, this study is the first discovery of dual-targeting AXL/HDAC2 inhibitors for colorectal cancer treatment.

Serum exosomal hsa-circ-0004771 modulates the resistance of colorectal cancer to 5-fluorouracil via regulating miR-653/ZEB2 signaling pathway.

BACKGROUND: Drug resistance is a major obstacle causing chemotherapy failure, and enabling cancer progression. Exosome excreted by cancer cells is participated in cancer progression and chemoresistance, and can be used as an prognostic biomarker. Previous studies have revealed that serum exosomal hsa-circ-0004771 is over-expressed in colorectal cancer (CRC) sufferers and suggested it as a predictive biomarker for early diagnosis and prognosis of CRC. This work will to investigate the role and mechanism of serum exosomal hsa-circ-0004771 in mediating resistance to 5-fluorouracil (5-FU) in CRC. METHODS: Serum and tissue samples were collected from 60 patients with CRC/ benign intestinal disease, and 60 healthy control. Exosomes were isolated and identified from serum samples and cell cultured media with TEM, WB, NTA, and flow cytometry. qRT-PCR and WB were performed to evaluate mRNA expressions of exosomal has-circ-0004771 and miR-653, and ZEB2 protein expression, respectively. Cell proliferation, migration, invasion, and apoptosis abilities were assessed with BrdU and colony formation assay, wound-healing assay, and flow cytometry, respectively. RESULTS: Exosomal hsa-circ-0004771 was over-expressed in CRC serum and cell cultured media, while miR-653 was lower-expressed in CRC tissues and cells. Negative correlations existed between exosomal hsa-circ-0004771 in the patients' serum/cell culture media and miR-653 in CRC tissues/cells, and between miR-653 and ZEB2 in CRC cells. Exosomal hsa-circ-0004771 in CRC cell cultured media was positively related to ZEB2 in CRC cells. MiR-653 was associated with poor prognosis of CRC patients, and its upregulation restrained CRC cell proliferation, migration and invasion, and stimulated apoptosis. Exosomal hsa-circ-0004771 was higher-expressed in 5-FU-resistant CRC serum and cell cultured media, miR-653 was downregulated and ZEB2 was overexpressed in 5-FU-resistant CRC cells. In vitro, exosomal hsa-circ-0004771 in cell cultured media may be involved in 5-FU-resistance by modulating miR-653/ZEB2 pathway. CONCLUSIONS: miR-653 plays as a tumour suppressor in CRC progression, and serum exosomal hsa-circ-0004771 may be a predictive biomarker for 5-FU-resistance in CRC patients, potentially through miR-653/ZEB2 axis.

[Modified styrene-maleic anhydride copolymer-based chromatographic stationary phase for phospholipid separation and analysis].

Phospholipids are important signaling molecules, and their metabolism is closely related to various diseases, such as neurodegenerative diseases and cancers. Phospholipids are typically characterized with extreme complexity and structural diversity. For example, phospholipids present in many different forms, such as sn position isomers, double-bond position isomers, double-bond stereochemical isomers, and enantiomers. Therefore, further research on novel separation and analytical techniques for phospholipids is of great importance. As an amphiphilic alternating copolymer, styrene-maleic anhydride copolymer (SMA) can be inserted into the phospholipid bilayer of biofilms to form lipid nanodisks with membrane proteins as the centers, thereby solubilizing membrane proteins and phospholipids. Thus, the introduction of SMA into a chromatographic stationary phase can potentially improve the separation and analysis of phospholipids. In this paper, SMA was successfully grafted onto the surface of silica gel via the "click" reaction and free radical polymerization. After further ring-opening modification of SMA with methyl methionine hydrochloride (MME·HCl), a novel SMA-modified stationary phase material (Sil-SMA-MME) was fabricated. The Sil-SMA-MME stationary phase was characterized using thermogravimetric analysis and Fourier transform infrared spectroscopy (FT-IR), and the results indicated the successful fabrication of the target material. The retention mechanism of the packed Sil-SMA-MME chromatographic column was investigated using hydrophilic nucleosides and nucleic acid bases via high performance liquid chromatography (HPLC) and UV detection. According to the retention characteristics of the nucleosides and nucleic acid bases in different mobile phases, the Sil-SMA-MME chromatographic column exhibited a typical hydrophilic-interaction-based retention mechanism, similar to that of a commercially available amino (SiO2-NH2) column. The separation performance of the Sil-SMA-MME column was evaluated using three types of small-molecule substances, including amides, nucleoside/nucleic acid bases, and phenols. Cyanoacetamide, 2-iodoacetamide, benzamide, p-aminobenzamide, and nicotinamide were used to evaluate the chromatographic performance of the developed Sil-SMA-MME column. When acetonitrile-H2O (96∶4, v/v) was used as the mobile phase, the five compounds exhibited good peak shapes and could be baseline-separated within 8 min. The highest column efficiency achieved was 90900 N/m. By contrast, under the same chromatographic conditions, the test substances were not separated effectively on the SiO2-NH2 column. Regardless of the mobile phase ratio, the peaks of benzamide and 2-iodoacetamide overlapped. These results demonstrate that the developed Sil-SMA-MME column has good separation selectivity. The separation performance of the Sil-SMA-MME column for phospholipid samples was also investigated by HPLC and evaporative light scattering detection (ELSD) to explore its feasibility for phospholipid separation and analysis. Different phospholipid standards were used to evaluate the separation performance of the column. Under certain mobile phase conditions, baseline separation could be achieved for dipalmityl phosphatidyl serine sodium (DPPS), diolyl phosphatidyl choline (DOPC), and dipalmityl phosphatidyl ethanolamine (DPPE), as well as four phosphatidyl choline (PC) standards, namely, lysophosphatidylcholine (LysoPC), dimyristoyl phosphatidyl choline (DMPC), distearyl phosphatidyl choline (DSPC), and dipalmitoyl phosphatidyl choline (DPPC). The separation potential of the developed Sil-SMA-MME column was further evaluated by separating and analyzing phospholipid extracts from Antarctic krill oil and human serum. The results showed that the developed Sil-SMA-MME column has good potential for phospholipid separation and analysis.

Parental presence during induction of anesthesia in children undergoing tonsillectomy and adenoidectomy.

OBJECTIVE: To investigate the effect of parental presence during induction of anesthesia (PPIA) in relieving preoperative anxiety of children undergoing tonsillectomy and adenoidectomy. METHODS: One hundred and sixty children undergoing tonsillectomy and adenoidectomy were divided into the control group and the trial group. The control group received routine nursing in the operation room, while anesthesia was induced in the trial group children in the presence of their parents as part of the routine nursing. The differences in heart rate and mean dynamic pressure during pre-operative visit and anesthesia induction between the two groups were observed and recorded. The Modified Yale Preoperative Anxiety Scale (m-YPAS) and the Induction Compliance Checklist (ICC) were scored. The anxiety status of the children and their family members in the two groups was scored at different times, and the psychological stress of anesthesiologists during anesthesia induction was scored by a visual analogue scale. The differences in each index between the two groups were compared. Operation time and costs in-hospital were also compared. RESULTS: Compared with the control group, the heart rate and blood pressure scores as well as the ICC in the trial group were lower than those in the control group (P < 0.01). On comparing the scores of m-YPAS between the two groups, we observed that the scores of the children in the trial group were lower than those in the control group before entering the induction room and anesthesia induction (P < 0.01). There was no statistical difference between the scores of the children in the trial group and the control group on the day of operation and on the way to the operating room (P > 0.05). The nursing satisfaction scores of the family members in the trial group were significantly superior to those in the control group (P < 0.01). The scores of the visual analogue scale for psychological pressure of anesthesiologists during anesthesia induction were higher in the trial group than in the control group (P < 0.05). The operation time and costs in study group were both significantly higher than those of control group (P < 0.05). CONCLUSION: PPIA can significantly reduce preoperative anxiety and surgical physiological stress response in children undergoing tonsillectomy and adenoidectomy, and it is worth being encouraged.

Peritumoral Radiomics Strategy Based on Ensemble Learning for the Prediction of Gleason Grade Group of Prostate Cancer.

RATIONALE AND OBJECTIVES: To develop and evaluate a peritumoral radiomic-based machine learning model to differentiate low-Gleason grade group (L-GGG) and high-GGG (H-GGG) prostate lesions. MATERIALS AND METHODS: In this retrospective study, a total of 175 patients with prostate cancer (PCa) confirmed by puncture biopsy were recruited and included 59 patients with L-GGG and 116 patients with H-GGG. The original PCa regions of interest (ROIs) were delineated on T2-weighted (T2WI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) maps, and then centra-tumoral and peritumoral ROIs were defined. Features were meticulously extracted from each ROI to establish radiomics models, employing distinct sequence datasets. Peritumoral radiomics models were specifically developed for both the peripheral zone (PZ) and transitional zone (TZ), utilizing dedicated PZ and TZ datasets, respectively. The performances of the models were evaluated by using the receiver operating characteristic (ROC) curve and precision-recall curve. RESULTS: The classification model with combined peritumoral features based on T2 + DWI + ADC sequence dataset demonstrated superior performance compared to the original tumor and centra-tumoral classification models. It achieved an area under the ROC curve (AUC) of 0.850 [95% confidence interval, 0.849, 0.860] and an average accuracy of 0.950. The combined peritumoral model outperformed the regional peritumoral models with AUC of 0.85 versus 0.75 for PZ lesions and 0.88 versus 0.69 for TZ lesions, respectively. The peritumoral classification models exhibit greater efficacy in predicting PZ lesions as opposed to TZ lesions. CONCLUSION: The peritumoral radiomics features showed excellent performance in predicting GGG in PCa patients and might be a valuable addition to the non-invasive assessment of PCa aggressiveness.

Multiparametric MRI radiomics in prostate cancer for predicting Ki-67 expression and Gleason score: a multicenter retrospective study.

PURPOSE: Prostate cancer (PCa) with high Ki-67 expression and high Gleason Scores (GS) tends to have aggressive clinicopathological characteristics and a dismal prognosis. In order to predict the Ki-67 expression status and the GS in PCa, we sought to construct and verify MRI-based radiomics signatures. METHODS AND MATERIALS: We collected T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) images from 170 PCa patients at three institutions and extracted 321 original radiomic features from each image modality. We used support vector machine (SVM) and least absolute shrinkage and selection operator (LASSO) logistic regression to select the most informative radiomic features and built predictive models using up sampling and feature selection techniques. Using receiver operating characteristic (ROC) analysis, the discriminating power of this feature was determined. Subsequent decision curve analysis (DCA) assessed the clinical utility of the radiomic features. The Kaplan-Meier (KM) test revealed that the radiomics-predicted Ki-67 expression status and GS were prognostic factors for PCa survival. RESULT: The hypothesized radiomics signature, which included 15 and 9 selected radiomics features, respectively, was significantly correlated with pathological Ki-67 and GS outcomes in both the training and validation datasets. Areas under the curve (AUC) for the developed model were 0.813 (95% CI 0.681,0.930) and 0.793 (95% CI 0.621, 0.929) for the training and validation datasets, respectively, demonstrating discrimination and calibration performance. The model's clinical usefulness was verified using DCA. In both the training and validation sets, high Ki-67 expression and high GS predicted by radiomics using SVM models were substantially linked with poor overall survival (OS). CONCLUSIONS: Both Ki-67 expression status and high GS correlate with PCa patient survival outcomes; therefore, the ability of the SVM classifier-based model to estimate Ki-67 expression status and the Lasso classifier-based model to assess high GS may enhance clinical decision-making.

[Acupuncture for chronic prostatitis/chronic pelvic pain syndrome: a randomized controlled trial].

OBJECTIVE: To observe the short-term efficacy, long-term efficacy and safety of acupuncture for chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS). METHODS: Forty-two patients with CP/CPPS were randomly divided into an acupuncture group (21 cases, 1 case dropped off) and a sham acupuncture group (21 cases). The patients in the acupuncture group were treated with acupuncture at bilateral Zhongliao (BL 33), Huiyang (BL 35), Shenshu (BL 23) and Sanyinjiao (SP 6); the needling depth of Zhongliao (BL 33) and Huiyang (BL 35) was 60 to 80 mm, while Shenshu (BL 23) and Sanyinjiao (SP 6) was directly punctured of 30 mm. The patients in the sham acupuncture group were treated with acupuncture at non-acupoints, including points 2 cm next to Shenshu (BL 23), Zhongliao (BL 33) and Huiyang (BL 35), and the midpoint of the connecting line between the spleen meridian and the kidney meridian. All the non-acupoints were treated with directly puncture of 2 to 3 mm. The needles were left for 30 min in both groups, once every other day in the first four weeks, three times a week, and twice a week in the next four weeks, totally 20 treatments. Before treatment, after treatment and in follow-up of 24 weeks after treatment completion, the National Institutes of Health-chronic prostatitis symptom index (NIH-CPSI) score and urinary flow rate were observed in both groups; the clinical efficacy and safety were evaluated. RESULTS: Compared with those before treatment, the pain and discomfort scores, urination symptoms scores, quality of life scores and total scores of NIH-CPSI in both groups were reduced after treatment in the two groups (P<0.01), while each item score and total score of NIH-CPSI in the acupuncture group were reduced in follow-up (P<0.01, P<0.05). After treatment and in follow-up, each item score and total score of NIH-CPSI in the acupuncture group were lower than those in the sham acupuncture group (P<0.05, P<0.01). After treatment, the maximum and average urinary flow rates in the acupuncture group were higher than those before treatment (P<0.05), and the average urinary flow rate in the acupuncture group was higher than that in the sham acupuncture group (P<0.05). The total effective rate was 75.0% (15/20) in the acupuncture group, which was higher than 42.9% (9/21) in the sham acupuncture group (P<0.05). No significant adverse reactions were observed in the two groups, and there was no significant difference in the incidence of adverse reactions between the two groups (P>0.05). CONCLUSION: Acupuncture could effectively alleviate the clinical symptoms, improve quality of life, and has a sustained, safe and reliable therapeutic effect in patients with CP/CPPS.

Interaction of lactate/albumin and geriatric nutritional risk index on the all-cause mortality of elderly patients with critically ill heart failure: A cohort study.

BACKGROUND: Whether there is a multiplicative interaction of lactate/albumin (L/A) ratio and geriatric nutritional risk index (GNRI) on the mortality of critically ill elderly patients with heart failure (HF) remains unclear. HYPOTHESIS: To assess the interaction of L/A ratio and GNRI on the all-cause mortality in critically ill elderly patients with HF. METHODS: This was a retrospective cohort study and data were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. The endpoints were 28-day and 1-year all-cause mortality, and the independent variables were L/A ratio and GNRI. The multiplicative interaction of L/A ratio and GNRI on the mortality was examined using Cox proportional-hazards model. RESULTS: A total of 5627 patients were finally included. Results showed that patients with higher L/A ratio or GNRI ≤ 58 had higher risk of 28-day and 1-year all-cause mortality (all p < .01). We also found the significant multiplicative interaction effect between L/A ratio and GNRI score on the 28-day and 1-year all-cause mortality (both p < .05). The increased L/A ratio was associated with higher risk of 28-day and 1-year all-cause mortality in patients with GNRI ≤ 58 than those with GNRI > 58. CONCLUSIONS: There was a multiplicative interaction effect between L/A ratio and GNRI score on the mortality, and low GNRI score was associated with the increased risk of all-cause mortality with the increase of L/A ratio, suggesting the importance of nutrition-oriented intervention in critically ill elderly HF patients with high L/A ratio.

Cinchonine-induced cell death in pancreatic cancer cells by downregulating RRP15.

Pancreatic cancer is characterized by poor prognosis and high mortality, while its treatment remains unsatisfactory. Cinchonine, a natural compound present in cinchona bark, is a potential anticancer drug. Whether cinchonine is of relevance to pancreatic cancer therapeutics is unclear. This research showed that the ribosomal RNA-processing 15 homolog (RRP15) expression is decreased in the pancreatic cancer, and RRP15 knockdown inhibited autophagy, and caused apoptosis in pancreatic cancer cells. Cinchonine treatment inhibits the expression of RRP15 and autophagy, and caused apoptosis by leading to the activation of Nrf2 axis in pancreatic cancer cells. Taken together, the above results indicate that cinchonine treatment inhibited autophagy and induced apoptosis through activating Nrf2 axis by downregulating RRP15 in pancreatic cancer cells.

The interaction between cellular senescence and chronic kidney disease as a therapeutic opportunity.

Chronic kidney disease (CKD) is an increasingly serious public health problem in the world, but the effective therapeutic approach is quite limited at present. Cellular senescence is characterized by the irreversible cell cycle arrest, senescence-associated secretory phenotype (SASP) and senescent cell anti-apoptotic pathways (SCAPs). Renal senescence shares many similarities with CKD, including etiology, mechanism, pathological change, phenotype and outcome, however, it is difficult to judge whether renal senescence is a trigger or a consequence of CKD, since there is a complex correlation between them. A variety of cellular signaling mechanisms are involved in their interactive association, which provides new potential targets for the intervention of CKD, and then extends the researches on senotherapy. Our review summarizes the common features of renal senescence and CKD, the interaction between them, the strategies of senotherapy, and the open questions for future research.

Population Pharmacokinetics of Cyclosporine in Chinese Pediatric Patients With Acquired Aplastic Anemia.

Cyclosporine (CsA) is a component of the first-line treatment for acquired aplastic anemia (acquired AA) in pediatric patients. This study aimed to develop a population pharmacokinetic (PK) model of CsA in Chinese pediatric patients with acquired AA to inform individual dosage regimens. A total of 681 CsA whole blood concentrations and laboratory data of 157 pediatric patients with acquired AA were retrospectively collected from two hospitals in Shanghai. A nonlinear mixed-effect model approach was used to build the population PK model. Potential covariate effects of age, body weight, and biochemical measurements (renal and liver functions) on CsA PK disposition were evaluated. Model fit was assessed using the basic goodness of fit and a visual predictive check. The CsA concentration data were accurately described using a two-compartment disposition model with first-order absorption and elimination. Body weight value was implemented as a fixed allometric function on all clearance and volume of distribution parameters. Total bilirubin level was identified as a significant covariate on apparent clearance (CL/F), with a 1.07% reduction per 1 nmol/L rise in total bilirubin level. The final estimates for CL/F and central volume (Vc/F) were 29.1 L/h and 325 L, respectively, for a typical 28 kg child. Other covariates (e.g., gender, age, albumin, hemoglobin, hematocrit, serum creatinine, and concomitant medication) did not significantly affect the PK properties of CsA. This population PK model, along with a maximum a posteriori Bayesian approach, could estimate individual PK parameters in pediatric patients with acquired AA to conduct individual CsA therapy.

Radiomics-Based Machine Learning Models for Predicting P504s/P63 Immunohistochemical Expression: A Noninvasive Diagnostic Tool for Prostate Cancer.

Objective: To develop and validate a noninvasive radiomic-based machine learning (ML) model to identify P504s/P63 status and further achieve the diagnosis of prostate cancer (PCa). Methods: A retrospective dataset of patients with preoperative prostate MRI examination and P504s/P63 pathological immunohistochemical results between June 2016 and February 2021 was conducted. As indicated by P504s/P63 expression, the patients were divided into label 0 (atypical prostatic hyperplasia), label 1 (benign prostatic hyperplasia, BPH) and label 2 (PCa) groups. This study employed T2WI, DWI and ADC sequences to assess prostate diseases and manually segmented regions of interest (ROIs) with Artificial Intelligence Kit software for radiomics feature acquisition. Feature dimensionality reduction and selection were performed by using a mutual information algorithm. Based on screened features, P504s/P63 prediction models were established by random forest (RF), gradient boosting decision tree (GBDT), logistic regression (LR), adaptive boosting (AdaBoost) and k-nearest neighbor (KNN) algorithms. The performance was evaluated by the area under the ROC curve (AUC) and accuracy. Results: A total of 315 patients were enrolled. Among the 851 radiomic features, the 32 top features were derived from T2WI, in which the gray-level run length matrix (GLRLM) and gray-level cooccurrence matrix (GLCM) features accounted for the largest proportion. Among the five models, the RF algorithm performed best in general evaluations (microaverage AUC=0.920, macroaverage AUC=0.870) and provided the most accurate result in further sublabel prediction (the accuracies of label 0, 1, and 2 were 0.831, 0.831, and 0.932, respectively). In comparative sequence analyses, T2WI was the best single-sequence candidate (microaverage AUC=0.94 and macroaverage AUC=0.78). The merged datasets of T2WI, DWI, and ADC yielded optimal AUCs (microaverage AUC=0.930 and macroaverage AUC=0.900). Conclusions: The radiomic-based RF classifier has the potential to be used to evaluate the presurgical P504s/P63 status and further diagnose PCa noninvasively and accurately.

Genetic variations in GABA metabolism and epilepsy.

Epilepsy is a paroxysmal brain disorder that results from an imbalance between neuronal excitation and inhibition. Gamma-aminobutyric acid (GABA) is the most important inhibitory neurotransmitter in the brain and plays an important role in the occurrence and development of epilepsy. Abnormalities in all aspects of GABA metabolism, including GABA synthesis, transport, genes encoding GABA receptors, and GABA inactivation, may lead to epilepsy. GABRA1, GABRA2, GABRA5, GABRB1, GABRB2, GABRB3, GABRG2 and GABBR2 are genes that encode GABA receptors and are commonly associated with epilepsy. Mutations of these genes lead to a variety of epilepsy syndromes with different clinical phenotypes, primarily by down regulating receptor expression and reducing the amplitude of GABA-evoked potentials. GABA is metabolized by GABA transaminase and succinate semi aldehyde dehydrogenase, which are encoded by the ABAT and ALDH5A1 genes, respectively. Mutations of these genes result in symptoms related to deficiency of GABA transaminase and succinate semi aldehyde dehydrogenase, such as epilepsy and cognitive impairment. Most of the variation in genes associated with GABA metabolism are accompanied by developmental disorders. This review focuses on advances in understanding the relationship between genetic variation in GABA metabolism and epilepsy to establish a basis for the accurate diagnosis and treatment of epilepsy.

Interferon regulatory factor 5­induced upregulation of zinc­finger protein 217 promotes pancreatic carcinoma progression.

The aim of the present study was to investigate the molecular mechanisms of zinc­finger protein 217 (ZNF217) in pancreatic carcinoma (PC) progression. ZNF217­associated expression and survival data from patients with PC were retrieved from the Gene Expression Profiling Interactive Analysis server. The mRNA expression level of ZNF217 was detected by reverse transcription­quantitative PCR. Cell Counting Kit­8, colony formation, wound­healing and Transwell assays were conducted to assess cellular proliferation, migratory and invasive abilities. Proliferation was also examined by immunofluorescence detection of Ki67 expression, and chromatin immunoprecipitation (ChIP) and luciferase reporter assays were performed to detect the interaction between ZNF217 and interferon regulatory factor 5 (IRF5). ZNF217 was found to be significantly upregulated in tumor tissues and cancer cell lines, which was associated with a poor survival rate in patients with PC. ZNF217 silencing markedly suppressed cellular proliferation and migratory and invasive abilities, as well as decreased the expression of Ki67. IRF5 was also upregulated in PC tumor tissues and was shown to positively regulate the activity of the ZNF217 promoter and its mRNA expression levels. Furthermore, ChIP assays demonstrated that IRF5 bound to the promoter region of ZNF217 in vitro. In conclusion, ZNF217 silencing exerted notable inhibitory effects on the progression of PC. Thus, ZNF217 may serve as a potential target for developing novel therapeutic strategies for PC.