Objective To construct the molecular transmission networks of HIV-1 CRF01 AE strains circulating in China and to analyze their characteristics. Methods Sequences of the pol genes of Chinese CRF01 AE strains were downloaded from Los Alamos database and the related demographic informa-tion was checked. Transmission networks were created by four steps,including phylogenetic tree construc-tion,transmission cluster extraction,minimum genetic distance identification and network visualization. Chi-square test was performed to analyze the differences in the distribution of different populations in the networks and the differences in the distribution of subjects with different degrees among different sub-populations. De-scriptive analysis was used to investigate the transmission links between sub-populations and various regions. Results The 2 419 sequences constituted 250 separate networks including 847 nodes and 610 edges. The number of subjects covered by different networks ranged from 2 to 25. Subjects with degree ≥2 represented only 26. 4%(224 / 847)of network-individuals,but were connected with 66. 5%(563 / 847)of all network-individuals. There were 37. 6%(669 / 1 781)of men who have sex with men(MSM),28. 4%(102 / 359) of heterosexual men,16. 1%(10 / 62)of intravenous drug users(IDUs)and 30. 4%(66 / 217)of hetero-sexual women involved in the networks(χ2 =23. 774,P﹤0. 001). The percentage of subjects with degree ≥2 was high in MSM(10. 8% ,193 / 1 781)compared to that in heterosexual men(5. 6% ,20 / 359)(P =0. 002)and heterosexual women(4. 6% ,10 / 217)(P=0. 004). Of the 669 MSM in the networks,95. 5%(639 / 669)linked to other MSM and only 2. 4% (16 / 669)linked to heterosexual women. However, 15. 1%(10 / 66)of the heterosexual women in the networks linked to MSM. Of the heterosexual men in the networks,35. 3%(36 / 102)linked to heterosexual women,9. 8%(10 / 102)linked to MSM. Of the sub-jects in the networks,20. 9%(177 / 847)linked to other regions' individuals. Conclusion The super-spreaders played an important role in the molecular transmission networks of HIV-1 CRF01 AE strains even though they were in a minority. The transmission of HIV-1 CRF01 AE strains between sub-populations and various regions was complicated and active.

OBJECTIVES: The magnesium depletion score (MDS) is considered more reliable than traditional approaches for predicting magnesium deficiency in humans. We explored the associations of MDS and dietary magnesium intake with diabetes. METHODS: We obtained data from 18,853 participants in the National Health and Nutrition Examination Survey 2011-2018. Using multivariate regression and stratified analysis, we investigated the relationships of both MDS and magnesium intake with diabetes. To compute prevalence ratios (PRs), we employed modified Poisson or log-binomial regression. We characterized the non-linear association between magnesium intake and diabetes using restricted cubic spline analysis. RESULTS: Participants with MDS ≥2 exhibited a PR of 1.26 (95% confidence interval [CI], 1.19 to 1.34) for diabetes. Per-standard deviation (SD) increase in dietary magnesium intake was associated with a lower prevalence of diabetes (PR, 0.91; 95% CI, 0.87 to 0.96). Subgroup analyses revealed a positive association between MDS ≥2 and diabetes across all levels of dietary magnesium intake, including the lowest (PR, 1.35; 95% CI, 1.18 to 1.55), middle (PR, 1.23; 95% CI, 1.12 to 1.35), and highest tertiles (PR, 1.25; 95% CI, 1.13 to 1.37; pinteraction<0.001). Per-SD increase in magnesium intake was associated with lower diabetes prevalence in participants with MDS <2 (PR, 0.92; 95% CI, 0.87 to 0.98) and those with MDS ≥2 (PR, 0.91; 95% CI, 0.84 to 0.98; pinteraction=0.030). CONCLUSIONS MDS is associated with diabetes, particularly among individuals with low magnesium intake. Adequate dietary magnesium intake may reduce diabetes risk, especially in those with high MDS.

Objective:To investigate the antibody-dependent cell-mediated cytotoxicity (ADCC) in plasma samples from patients with SARS-CoV-2 infection and to evaluate its correlation with antibody titer and neutralizing activity.Methods:A simple method for ADCC detection was established using HEK293T cells expressing SARS-CoV-2 spike (S) protein as target cells and FcγRⅢa-V158-expressing Jurkat cells as effector cells. It was used to analyze the ADCC activity in 38 plasma samples after the ratio of effector cells to target cells was optimized. Plasma-specific antibody was detected by capturing ELISA, which was to capture the C-terminal-tagged recombinant SARS-CoV-2 S protein with an anti-tag antibody. The neutralizing activity in plasma samples was detected using a pseudovirus neutralization assay. Mann-Whitney U test was used for comparison between different groups and non-parametric Spearman correlation test was performed for correlation analysis. Results:The seroconversion rates for antibodies specific for S protein, S1 protein and RBD were all 97.4% (37/38), and the dynamic changes in antibody titers with recovery time showed that antibody titers peaked at 3-4 weeks. Among the plasma samples with neutralizing activity, those with antibody titers >1∶320 had stronger neutralizing activity than the plasma samples with antibody titers <1∶320 [IC 50: 749.6 (396.5-3 772.0) vs 81.4 (11.6-228.4), P<0.01]. ADCC activity was detectable in 86.8% (33/38) of the plasma samples, and its dynamic change with recovery time were consistent with that of specific antibody titer with a peak at 3-4 weeks. Correlation analysis showed ADCC was positively correlated with the titers of antibodies specific for S protein, S1 protein and RBD ( r=0.686, 0.535 and 0.471, all P<0.01). A positive correlation was also found between ADCC and neutralizing activity ( r=0.573, P<0.01). Conclusions:This study established a simple method for the detection of ADCC. Results of this study suggested that SARS-CoV-2 could induce specific ADCC in plasma and the ADCC might be associated with non-neutralizing antibodies. Besides, the activity of ADCC peaked at 3-4 weeks. These findings would be of reference value for clinical treatment with convalescent plasma.

The identification and use of molecular biomarkers have greatly improved the diagnosis and treatment of malignant tumors. However, a much deeper understanding of oncogenic proteins is needed for the benefit to cancer patients. The lipid raft marker proteins, flotillin-1 and flotillin-2, were first found in goldfish retinal ganglion cells during axon regeneration. They have since been found in a variety of cells, mainly on the inner surface of cell membranes, and not only act as a skeleton to provide a platform for protein-protein interactions, but also are involved in signal transduction, nerve regeneration, endocytosis, and lymphocyte activation. Previous studies have shown that flotillins are closely associated with tumor development, invasion, and metastasis. In this article, we review the functions of flotillins in relevant cell processes, their underlying mechanisms of action in a variety of tumors, and their potential applications to tumor molecular diagnosis and targeted therapy.
Animals ; Cell Differentiation ; Endocytosis ; Humans ; Membrane Proteins/physiology* ; Neoplasms/etiology* ; Nerve Regeneration

As a typical human pathogenic fungus,

ObjectiveTo observe the intervention effect of Ruyi Zhenbao pills （RYZBP） on central pain after thalamic stroke in mice and explore the underlying mechanism. MethodThe central post-stroke pain syndrome （CPSP） model was induced by stereotactic injection of type Ⅳ collagenase into the hypothalamus in mice. The mice were divided into a sham group， a model group， low-， medium-， and high-dose RYZBP groups （0.65， 1.3， 2.6 g·kg^-1）， and a pregabalin group （0.075 g·kg^-1）. Seven days after modeling， the mice in the groups with drug intervention were administered with corresponding drugs by gavage according to the body mass， once per day for 25 days， while those in the sham group and the model group received an equal volume of normal saline. During this period， mechanical pain and cold pain were detected at different time points， and the apoptotic state of brain tissue cells was detected by in situ terminal deoxynucleotidyl transferase-mediated dUTP nick end-labeling （TUNEL）. The 36 classical broad-spectrum inflammatory factors were quantitatively analyzed by liquid-phase chip technology， and differential molecules were screened out and verified by Western blot and enzyme-linked immunosorbent assay （ELISA）. ResultCompared with sham operation group, mechanical pain threshold and cold sensitive pain threshold in model group were significantly changed （P<0.01）. TUNEL results showed that apoptosis of brain cells was obvious. Western blot and ELISA results showed that the expressions of interleukin-1α (IL-1α) and chemokine ligand 5 (CCL5) increased in hypothalamus tissue and serum， while the expressions of Ang-2, granulocyte-colony-stimulating factor (G-CSF) and IL-4 decreased significantly （P<0.01）. Compared with model group， RYZBW dose groups significantly increased mechanical pain threshold， decreased cold sensitivity pain threshold， decreased hypothalamus cell apoptosis ratio （P<0.01）， decreased the expression of IL-1α and CCL5 in hypothalamus tissue and serum， while the expression of ANG-2， G-CSF and IL-4 were significantly increased （P<0.05）. ConclusionRYZBP can relieve hyperalgesia in CPSP mice， and its mechanism is related to the regulation of the expression of pro-/anti-inflammatory factors IL-1α， CCL5， IL-4， G-CSF， and Ang-2.

Pharmacokinetics (PK) is the study of the absorption, distribution, metabolism, and excretion (ADME) processes of a drug. Understanding PK properties is essential for drug development and precision medication. In this review we provided an overview of recent research on PK with focus on the following aspects: (1) an update on drug-metabolizing enzymes and transporters in the determination of PK, as well as advances in xenobiotic receptors and noncoding RNAs (ncRNAs) in the modulation of PK, providing new understanding of the transcriptional and posttranscriptional regulatory mechanisms that result in inter-individual variations in pharmacotherapy; (2) current status and trends in assessing drug-drug interactions, especially interactions between drugs and herbs, between drugs and therapeutic biologics, and microbiota-mediated interactions; (3) advances in understanding the effects of diseases on PK, particularly changes in metabolizing enzymes and transporters with disease progression; (4) trends in mathematical modeling including physiologically-based PK modeling and novel animal models such as CRISPR/Cas9-based animal models for DMPK studies; (5) emerging non-classical xenobiotic metabolic pathways and the involvement of novel metabolic enzymes, especially non-P450s. Existing challenges and perspectives on future directions are discussed, and may stimulate the development of new research models, technologies, and strategies towards the development of better drugs and improved clinical practice.