Cortical lipid metabolic pathway alteration of early Alzheimer's disease and candidate drugs screen.

BACKGROUND: Lipid metabolism changes occur in early Alzheimer's disease (AD) patients. Yet little is known about metabolic gene changes in early AD cortex. METHODS: The lipid metabolic genes selected from two datasets (GSE39420 and GSE118553) were analyzed with enrichment analysis. Protein-protein interaction network construction and correlation analyses were used to screen core genes. Literature analysis and molecular docking were applied to explore potential therapeutic drugs. RESULTS: 60 lipid metabolic genes differentially expressed in early AD patients' cortex were screened. Bioinformatics analyses revealed that up-regulated genes were mainly focused on mitochondrial fatty acid oxidation and mediating the activation of long-chain fatty acids, phosphoproteins, and cholesterol metabolism. Down-regulated genes were mainly focused on lipid transport, carboxylic acid metabolic process, and neuron apoptotic process. Literature reviews and molecular docking results indicated that ACSL1, ACSBG2, ACAA2, FABP3, ALDH5A1, and FFAR4 were core targets for lipid metabolism disorder and had a high binding affinity with compounds including adenosine phosphate, oxidized Photinus luciferin, BMS-488043, and candidate therapeutic drugs especially bisphenol A, benzo(a)pyrene, ethinyl estradiol. CONCLUSIONS: AD cortical lipid metabolism disorder was associated with the dysregulation of the PPAR signaling pathway, glycerophospholipid metabolism, adipocytokine signaling pathway, fatty acid biosynthesis, fatty acid degradation, ferroptosis, biosynthesis of unsaturated fatty acids, and fatty acid elongation. Candidate drugs including bisphenol A, benzo(a)pyrene, ethinyl estradiol, and active compounds including adenosine phosphate, oxidized Photinus luciferin, and BMS-488043 have potential therapeutic effects on cortical lipid metabolism disorder of early AD.

The Fitting Optimization Path Analysis on Scale Missing Data: Based on the 507 Patients of Poststroke Depression Measured by SDS.

OBJECTIVE: To explore the optimal fitting path of missing data of the Scale to make the fitting data close to the real situation of patients' data. METHODS: Based on the complete data set of the SDS of 507 patients with stroke, the data simulation sets of Missing Completely at Random (MCAR), Missing at Random (MAR), and Missing Not at Random (MNAR) were constructed by R software, respectively, with missing rates of 5%, 10%, 15%, 20%, 25%, 30%, 35%, and 40% under three missing mechanisms. Mean substitution (MS), random forest regression (RFR), and predictive mean matching (PMM) were used to fit the data. Root mean square error (RMSE), the width of 95% confidence intervals (95% CI), and Spearman correlation coefficient (SCC) were used to evaluate the fitting effect and determine the optimal fitting path. RESULTS: when dealing with the problem of missing data in scales, the optimal fitting path is ① under the MCAR deletion mechanism, when the deletion proportion is less than 20%, the MS method is the most convenient; when the missing ratio is greater than 20%, RFR algorithm is the best fitting method. ② Under the Mar mechanism, when the deletion ratio is less than 35%, the MS method is the most convenient. When the deletion ratio is greater than 35%, RFR has a better correlation. ③ Under the mechanism of MNAR, RFR is the best data fitting method, especially when the missing proportion is greater than 30%. In reality, when the deletion ratio is small, the complete case deletion method is the most commonly used, but the RFR algorithm can greatly expand the application scope of samples and save the cost of clinical research when the deletion ratio is less than 30%. The best way to deal with data missing should be based on the missing mechanism and proportion of actual data, and choose the best method between the statistical analysis ability of the research team, the effectiveness of the method, and the understanding of readers.

PPARγ and mitophagy are involved in hypoxia/reoxygenation-induced renal tubular epithelial cells injury.

Renal tubular epithelial cell (RTEC) injury is the main cause and common pathological process of various renal diseases. Mitochondrial dysfunction (MtD) is a pathological process after renal injury. Mitophagy is vital for mitochondrial function. Hypoxia is a common cause of RTEC injury. Peroxisome proliferator-activated receptor γ (PPARγ) is involved in cell proliferation, apoptosis, and inflammation. Previous studies have shown that the low expression of PPARγ might be involved in hypoxia-induced RTEC injury. The present study aimed to investigate the correlation between PPARγ and mitophagy in damaged RTEC in the hypoxia/reoxygenation (HR) model. The results showed that HR inhibited the expression of PPARγ, but increased the expression of LC3II, Atg5, SQSTM1/P62, and PINK1 in a time-dependent manner. Moreover, mitochondrial DNA (mt DNA) copy number, mitochondria membrane potential (MMP) levels, ATP content, and cell viability were decreased in hypoxic RTECs, the expression of SQSTM1/P62 and PINK1, the release of cytochrome c (cyt C), and production of reactive oxygen species (ROS) were increased. Mitochondrial-containing autophagosomes (APs) were detected using transmission election microscope (TEM) and laser scanning confocal microscope (LSCM). Furthermore, PPARγ protein expression was negatively correlated with that of LC3II, PINK1, and the positive rate of RTEC-containing mitochondrial-containing APs (all p < .05), but positively correlated with cell viability, MMP level, and ATP content (all p < .05). These data suggested that PPARγ and mitophagy are involved in the RTEC injury process. Thus, a close association could be detected between PPARγ and mitophagy in HR-induced RTEC injury, albeit additional investigation is imperative.

A safe and potent anti-CD19 CAR T cell therapy.

Anti-CD19 chimeric antigen receptor (CAR) T cell therapies can cause severe cytokine-release syndrome (CRS) and neurotoxicity, impeding their therapeutic application. Here we generated a new anti-CD19 CAR molecule (CD19-BBz(86)) derived from the CD19-BBz prototype bearing co-stimulatory 4-1BB and CD3ζ domains. We found that CD19-BBz(86) CAR T cells produced lower levels of cytokines, expressed higher levels of antiapoptotic molecules and proliferated more slowly than the prototype CD19-BBz CAR T cells, although they retained potent cytolytic activity. We performed a phase 1 trial of CD19-BBz(86) CAR T cell therapy in patients with B cell lymphoma (ClinicalTrials.gov identifier NCT02842138 ). Complete remission occurred in 6 of 11 patients (54.5%) who each received a dose of 2 × 108-4 × 108 CD19-BBz(86) CAR T cells. Notably, no neurological toxicity or CRS (greater than grade 1) occurred in any of the 25 patients treated. No significant elevation in serum cytokine levels after CAR T cell infusion was detected in the patients treated, including in those who achieved complete remission. CD19-BBz(86) CAR T cells persistently proliferated and differentiated into memory cells in vivo. Thus, therapy with the new CD19-BBz(86) CAR T cells produces a potent and durable antilymphoma response without causing neurotoxicity or severe CRS, representing a safe and potent anti-CD19 CAR T cell therapy.

Protective effect of retinoic acid receptor α on hypoxia-induced epithelial to mesenchymal transition of renal tubular epithelial cells associated with TGF-ß/MMP-9 pathway.

Retinoic acid receptor α (RARα), a member of family of the nuclear retinoic acid receptors (RARs), plays an essential role in various chronic kidney diseases (CKD). Renal tubular epithelial to mesenchymal transition (EMT) is a common mechanism of progression of renal interstitial fibrosis (RIF). Hypoxia has been extensively considered as one of major inducers of renal tubular EMT. However, the effects of RARα on hypoxia-induced EMT have not yet been described so far. The aim of the present study was to explore the roles and potential mechanisms of RARα in hypoxia-induced EMT of renal tubular epithelial cells (RTECs). Our results showed that expression of RARα in RTECs subjected to hypoxia significantly was reduced, accompanied by decreased expression level of the epithelial marker E-cadherin, and increased expression levels of the mesenchymal markers α-smooth muscle actin (α-SMA) and vimentin, in accord with EMT. Meanwhile, hypoxia could cause RTECs to obviously express TGF-ß and matrix metalloproteinase-9 (MMP-9). Furthermore, using lentivirus-based delivery vectors to overexpress RARα in RTECs, we demonstrated that RARα alleviated hypoxia-induced EMT of RTECs and downregulated the expression levels of TGF-ß and MMP-9. In a word, RARα protects RTECs against EMT induced by hypoxia associated with TGF-ß/MMP-9 pathway.

Cluster analysis for syndromes of real-world coronary heart disease with angina pectoris.

Syndromes of coronary heart disease with angina pectoris were analyzed to provide guidance for clinical practice and to improve accuracy of traditional Chinese medicine (TCM) diagnoses and efficacy of TCM treatment. A total of 860 cases with coronary heart disease with angina pectoris were selected from TCM Clinical Research Information Sharing System for TCM clinics and research. Syndromes were automatically extracted with the cluster method and were analyzed to provide objective evidence for clinical studies. Final syndrome classifications were recognized and confirmed by clinical experts. Popular syndromes included Qi and blood deficiency, blood stasis and obstruction collaterals, liver depression and spleen deficiency, and Qi stagnation and blood stasis. Syndromes Qi and blood deficiency and blood stasis and obstruction collaterals accounted for 28.61% of total syndromes, whereas liver depression and spleen deficiency and Qi stagnation and blood stasis accounted for 26.44%. The main syndrome elements comprised Qi deficiency, blood deficiency, blood stasis, and Qi stagnation.

A novel classification method for aid decision of traditional Chinese patent medicines for stroke treatment.

Traditional Chinese patent medicines are widely used to treat stroke because it has good efficacy in the clinical environment. However, because of the lack of knowledge on traditional Chinese patent medicines, many Western physicians, who are accountable for the majority of clinical prescriptions for such medicine, are confused with the use of traditional Chinese patent medicines. Therefore, the aid-decision method is critical and necessary to help Western physicians rationally use traditional Chinese patent medicines. In this paper, Manifold Ranking is employed to develop the aid-decision model of traditional Chinese patent medicines for stroke treatment. First, 115 stroke patients from three hospitals are recruited in the cross-sectional survey. Simultaneously, traditional Chinese physicians determine the traditional Chinese patent medicines appropriate for each patient. Second, particular indicators are explored to characterize the population feature of traditional Chinese patent medicines for stroke treatment. Moreover, these particular indicators can be easily obtained byWestern physicians and are feasible for widespread clinical application in the future. Third, the aid-decision model of traditional Chinese patent medicines for stroke treatment is constructed based on Manifold Ranking. Experimental results reveal that traditional Chinese patent medicines can be differentiated. Moreover, the proposed model can obtain high accuracy of aid decision.