Association between genetically predicted rheumatoid arthritis and alopecia areata: a two-sample Mendelian randomization study

BackgroundAlthough numerous observational studies have indicated a potential association between autoimmune diseases, such as rheumatoid arthritis (RA) and alopecia areata (AA), the research reports lack a clear causal relationship. In this study, our objective is to utilize the Mendelian randomization (MR) design to examine the potential causal association between RA and AA.MethodsTo investigate the causal relationship between RA and AA, we utilized large-scale gene aggregation data from genome-wide association studies (GWAS), including RA (n=58,284) and AA (n=361,822) based on previous observational studies. In our analysis, we mainly employed the inverse variance-weighted (IVW) method of the random effects model, supplemented by the weighted median (WM) method and the MR Egger method.ResultsThe findings from the IVW methods revealed a significant association between genetically predicted RA and an increased likelihood of AA, as evidenced by an odds ratio of 1.21 (95%CI = 1.11-1.32; P < 0.001. Both the WM method and MR-Egger regression consistently showed significant directional outcomes (Both P < 0.05), indicating a robust association between RA and AA. Additionally, both the funnel plot and the MR-Egger intercepts provided evidence of the absence of directional pleiotropy, suggesting that the observed association is not influenced by other common genetic factors.ConclusionsThe results of the study suggest a possible link between genetically predicted RA and AA. This finding highlights the importance for individuals diagnosed with RA to remain vigilant and aware of the potential development of AA. Regular monitoring and early detection can be crucial in managing and addressing this potential complication

A cell-permeable dominant-negative survivin protein induces apoptosis and sensitizes prostate cancer cells to TNF-α therapy

BACKGROUND: Survivin is a member of the inhibitor-of-apoptosis (IAP) family which is widely expressed by many different cancers. Overexpression of survivin is associated with drug resistance in cancer cells, and reduced patient survival after chemotherapy and radiotherapy. Agents that antagonize the function of survivin hold promise for treating many forms of cancer. The purpose of this study was to investigate whether a cell-permeable dominant-negative survivin protein would demonstrate bioactivity against prostate and cervical cancer cells grown in three dimensional culture.RESULTS: A dominant-negative survivin (C84A) protein fused to the cell penetrating peptide poly-arginine (R9) was expressed in E. coli and purified by affinity chromatography. Western blot analysis revealed that dNSurR9-C84A penetrated into 3D-cultured HeLa and DU145 cancer cells, and a cell viability assay revealed it induced cancer cell death. It increased the activities of caspase-9 and caspase-3, and rendered DU145 cells sensitive to TNF-&alpha; via by a mechanism involving activation of caspase-8.CONCLUSIONS: The results demonstrate that antagonism of survivin function triggers the apoptosis of prostate and cervical cancer cells grown in 3D culture. It renders cancer cells sensitive to the proapoptotic affects of TNF-&alpha;, suggesting that survivin blocks the extrinsic pathway of apoptosis. Combination of the biologically active dNSurR9-C84A protein or other survivin antagonists with TNF-&alpha; therapy warrants consideration as an approach to cancer therapy.<br /

Phenotypic and functional alteration of CD45+ immune cells in the decidua of preeclampsia patients analyzed by mass cytometry (CyTOF)

Preeclampsia (PE) is a severe placenta-related pregnancy disease that has been associated with maternal systemic inflammation and immune system disorders. However, the distribution and functional changes in immune cells of the maternal–placental interface have not been well characterized. Herein, cytometry by time-of-flight mass spectrometry (CyTOF) was used to investigate the immune atlas at the decidua, which was obtained from four PE patients and four healthy controls. Six superclusters were identified, namely, T cells, B cells, natural killer (NK) cells, monocytes, granulocytes, and others. B cells were significantly decreased in the PE group, among which the reduction in CD27+CD38+ regulatory B cell (Breg)-like cells may stimulate immune activation in PE. The significantly increased migration of B cells could be linked to the significantly overexpressed chemokine C-X-C receptor 5 (CXCR5) in the PE group, which may result in the production of excessive autoantibodies and the pathogenesis of PE. A subset of T cells, CD11c+CD8+ T cells, was significantly decreased in PE and might lead to sustained immune activation in PE patients. NK cells were ultimately separated into four subsets. The significant reduction in a novel subset of NK cells (CD56-CD49a-CD38+) in PE might have led to the failure to suppress inflammation at the maternal–fetal interface during PE progression. Moreover, the expression levels of functional markers were significantly altered in the PE group, which also inferred that shifts in the decidual immune state contributed to the development of PE and might serve as potential treatment targets. This is a worthy attempt to elaborate the differences in the phenotype and function of CD45+ immune cells in the decidua between PE and healthy pregnancies by CyTOF, which contributes to understand the pathogenesis of PE, and the altered cell subsets and markers may inspire the immune modulatory therapy for PE

GC-MS and UHPLC-QTOFMS-assisted identification of the differential metabolites and metabolic pathways in key tissues of Pogostemon cablin

Pogostemon cablin is an important aromatic medicinal herb widely used in the pharmaceutical and perfume industries. However, our understanding of the phytochemical compounds and metabolites within P. cablin remains limited. To our knowledge, no integrated studies have hitherto been conducted on the metabolites of the aerial parts of P. cablin. In this study, twenty-three volatile compounds from the aerial parts of P. cablin were identified by GC-MS, predominantly sesquiterpenes. Quantitative analysis showed the highest level of patchouli alcohol in leaves (24.89 mg/g), which was 9.12 and 6.69-fold higher than in stems and flowers. UHPLC-QTOFMS was used to analyze the non-volatile compounds of leaf, stem and flower tissues. The differences in metabolites between flower and leaf tissues were the largest. Based on 112, 77 and 83 differential metabolites between flower-leaf, flower-stem and leaf-stem, three tissue-specific biomarkers of metabolites were identified, and the differential metabolites were enriched in several KEGG pathways. Furthermore, labeling differential metabolites in the primary and secondary metabolic pathways showed that flowers accumulated more lipids and amino acids, including proline, lysine and tryptophan; the leaves accumulated higher levels of terpenoids, vitamins and flavonoids, and stems contained higher levels of carbohydrate compounds. Based on the role of acetyl coenzyme A, the distribution and possible exchange mechanism of metabolites in leaves, stems and flowers of P. cablin were mapped for the first time, laying the groundwork for future research on the metabolites in P. cablin and their regulatory role

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M&gt;70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0&lt;e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

Contribution of Blind Source Separation to Processing GPR Signals for NDE Applications in Civil Engineering

In this paper, we employ a blind source separation technique to estimate the thickness of thin pavement layers. The linearity of the convolution operation along with a simple data reorganization permit to formulate a multidimensional signal model in accordance with the model adopted in blind techniques. We use this model to retrieve the reflectivity series and eventually the corresponding time delays and reflection amplitudes without any a priori information. Thus, this technique enables parameter estimation without incorporating a calibration stage which might be difficult in near-field conditions. Numerical simulations indicate the feasibility of the approach

Contribution of Blind Source Separation to Processing GPR Signals for NDE Applications in Civil Engineering

In this paper, we employ a blind source separation technique to estimate the thickness of thin pavement layers. The linearity of the convolution operation along with a simple data reorganization permit to formulate a multidimensional signal model in accordance with the model adopted in blind techniques. We use this model to retrieve the reflectivity series and eventually the corresponding time delays and reflection amplitudes without any a priori information. Thus, this technique enables parameter estimation without incorporating a calibration stage which might be difficult in near-field conditions. Numerical simulations indicate the feasibility of the approach

Table_1_The synergistic effect of diabetes mellitus and osteoporosis on the all-cause mortality: a cohort study of an American population.docx

BackgroundThe increasing incidence of diabetes mellitus (DM) and osteoporosis have different effects on prognosis. The two often co-occur, so we aimed to investigate whether DM and osteoporosis have an effect on all-cause death and whether DM and osteoporosis have a synergistic effect.MethodsThis study analyzed 18,658 subjects from five cycles of the National Health and Nutrition Examination Survey (NHANES). The primary endpoint was all-cause death. The subjects were divided into four groups based on the presence or absence of DM and osteoporosis. Survival curves and Cox regression analysis based on NHANES recommended weights were used to assess the risk of all-cause death between the diseased and non-diseased groups and to calculate additive interactions to assess whether there was a synergistic effect between diabetes and osteoporosis.ResultsThe group with DM and osteoporosis had the lowest survival rate. After full adjustment for confounders, patients with DM alone had a 30% higher risk of all-cause death compared with those without DM and osteoporosis (HR: 1.30, 95%CI: 1.09-1.55). Patients with osteoporosis alone had a 67% higher risk of all-cause death (HR: 1.67, 95%CI:1.16-2.43) and patients with combined DM and osteoporosis had a 127% higher risk of all-cause death (HR:2.27, 95%CI: 1.57-3.27). There was an additive interaction between DM and osteoporosis [RERI (95%CI): 1.03(0.55-1.50)] and excess mortality risk of 38% [AP (95% CI) 0.38(0.30-0.46)].ConclusionsThere might be a synergistic effect of DM and osteoporosis on all-cause mortality, and patients with both conditions have a higher risk of death.</p

Image_1_The synergistic effect of diabetes mellitus and osteoporosis on the all-cause mortality: a cohort study of an American population.jpeg

BackgroundThe increasing incidence of diabetes mellitus (DM) and osteoporosis have different effects on prognosis. The two often co-occur, so we aimed to investigate whether DM and osteoporosis have an effect on all-cause death and whether DM and osteoporosis have a synergistic effect.MethodsThis study analyzed 18,658 subjects from five cycles of the National Health and Nutrition Examination Survey (NHANES). The primary endpoint was all-cause death. The subjects were divided into four groups based on the presence or absence of DM and osteoporosis. Survival curves and Cox regression analysis based on NHANES recommended weights were used to assess the risk of all-cause death between the diseased and non-diseased groups and to calculate additive interactions to assess whether there was a synergistic effect between diabetes and osteoporosis.ResultsThe group with DM and osteoporosis had the lowest survival rate. After full adjustment for confounders, patients with DM alone had a 30% higher risk of all-cause death compared with those without DM and osteoporosis (HR: 1.30, 95%CI: 1.09-1.55). Patients with osteoporosis alone had a 67% higher risk of all-cause death (HR: 1.67, 95%CI:1.16-2.43) and patients with combined DM and osteoporosis had a 127% higher risk of all-cause death (HR:2.27, 95%CI: 1.57-3.27). There was an additive interaction between DM and osteoporosis [RERI (95%CI): 1.03(0.55-1.50)] and excess mortality risk of 38% [AP (95% CI) 0.38(0.30-0.46)].ConclusionsThere might be a synergistic effect of DM and osteoporosis on all-cause mortality, and patients with both conditions have a higher risk of death.</p