Greater Pain Severity Is Associated With Higher Glucocorticoid Levels in Hair Among a Cohort of People Living With HIV

Background: Pain is a common occurrence and persistent symptom, which has an adverse impact on individual well-being and quality of life among people living with HIV (PLHIV). Alteration in the activity of the Hypothalamic-Pituitary-Adrenal (HPA) axis resulting in abnormal glucocorticoid levels had been proposed to play important roles in those associations. Purpose: This study aimed to investigate whether pain severity was associated with hair glucocorticoid levels, a novel method of measuring long-term glucocorticoid exposure, among a large cohort of Chinese PLHIV. Methods: A measure of pain severity and hair samples were collected from 431 adults PLHIV in Guangxi, China. Glucocorticoid (cortisol and cortisone) in hair were quantified by liquid chromatography-tandem mass spectrometry. The general linear model was used to test the associations of pain severity with hair glucocorticoid levels after adjusting for potential confounding factors. Results: Of the 431 PLHIV, 273 reported none pain, 87 reported mild pain, and 71 reported moderate-severe pain. Hair cortisone, but not hair cortisol, was found to differ significantly among the three pain severity groups (F=3.90, p=0.021). PLHIV reported moderate-severe pain had higher hair cortisone than those reported mild (p=0.070) or none pain (p=0.014), with no differences between the latter two pain severity groups. Conclusion: Greater pain severity is associated with higher hair cortisone levels among Chinese PLHIV. In order to reduce the long-term glucocorticoid levels, interventions managing pain should be considered for PLHIV with moderate-severe pain

The Relationship of Hair Glucocorticoid Levels to Immunological and Virological Outcomes in a Large Cohort of Combination Antiretroviral Therapy Treated People Living With HIV

Background Existing literature mostly investigated the relationship of acute or short-term glucocorticoid exposure to HIV disease progression using cortisol levels in serum, saliva, or urine. Data are limited on the relationship of long-term glucocorticoid exposure to HIV disease progression. This study examined whether hair glucocorticoid levels, novel retrospective indicators of long-term glucocorticoid exposure, are associated with two common indicators of HIV disease progression (CD4 count and HIV viral load) among a large cohort of combination antiretroviral therapy treated Chinese people living with HIV (PLHIV). Methods A total of 1198 treated PLHIV provided hair samples for glucocorticoid (cortisol and cortisone) assay and completed a survey assessing sociodemographic, lifestyle, and HIV-related characteristics. Meanwhile, CD4 count and HIV viral load were retrieved from their medical records. Spearman correlation was used to examine the associations of hair cortisol and cortisone levels to continuous CD4 count and HIV viral load. Multivariate logistic regression was used to predict CD4 count \u3c 500 cells/mm3. Results Both hair cortisol and cortisone levels were negatively associated with CD4 count but not with HIV viral load. The odds ratio for CD4 count \u3c 500 cells/mm3 was 1.41 [95% CI 0.99–2.00] and 2.15 [95% CI 1.51–3.05] for those with hair cortisol and cortisone levels in the highest quartile compared to the lowest when controlling for sociodemographic, lifestyle, HIV-related covariates, and HIV viral load. Conclusion Hair glucocorticoid levels were associated with CD4 count but not viral load in treated Chinese PLHIV. Our data furtherly supported the hypothesis that elevated glucocorticoid levels are associated with the lower CD4 count

Association of Hair Concentrations of Antiretrovirals With Virologic Outcomes Among People Living With HIV in Guangxi, China

Background: Hair concentrations of antiretrovirals are an innovative and non-invasive method for measuring cumulative antiretroviral exposure and assessing long-term antiretroviral adherence. This study aimed to examine hair concentrations of antiretrovirals in relation to virologic outcomes among PLHIV in Guangxi, China.Methods: Cross-sectional data of hair concentrations of antiretrovirals and HIV viral load were collected from 215 PLHIV in Guangxi, China. Multivariate logistic regression analyses were used to examine the association of hair concentrations of antiretrovirals with virologic outcomes.Results: Of the 215 participants, 215, 67, and 163 PLHIV are receiving lamivudine, zidovudine, and efavirenz, respectively. Multivariate analysis revealed that hair concentrations of lamivudine [odds ratio = 16.52, 95% CI 2.51– 108.60, p = 0.004] and efavirenz [odds ratio = 14.26, 95% CI 1.18– 172.01, p = 0.036], but not zidovudine [odds ratio = 1.77, 95% CI 0.06– 56.14, p = 0.747], were the strongest independent predictor of virologic suppression when controlling for sociodemographic and other HIV-related characteristics.Conclusion: Hair concentrations of lamivudine and efavirenz were the strongest independent predictor of virologic suppression among Chinese PLHIV. Hair analysis of antiretrovirals may provide a non-invasive, cost-effective tool that predicts virologic suppression among PLHIV in China

LC-MS/MS Quantification of Nevirapine and Its Metabolites in Hair for Assessing Long-Term Adherence

The adherence assessment based on the combination of nevirapine (NVP) and its two metabolites (2-hydroxynevirapine and 3-hydroxynevirapine) would more comprehensively and accurately reflect long-term adherence than that of a single prototype. This study aimed to develop a specific, sensitive and selective method for simultaneous detection of the three compounds in hair and explore whether there was consistency among the three compounds in assessing long-term adherence. Furthermore, 75 HIV-positive patients who were taking the NVP drug were randomly recruited and divided into two groups (high-and low-adherence group). All participants self-reported their days of oral drug administration per month and provided their hair strands closest to the scalp at the region of posterior vertex. The concentrations of three compounds in the hair were determined using a developed LC-MS/MS method in multiple reaction monitoring. This method showed good performances in limit of quantification and accuracy with the recoveries from 85 to 115% and in precision with the intra-day and inter-day coefficients of variation within 15% for the three compounds. The population analysis revealed that patients with high-adherence showed significantly higher concentrations than those with low-adherence for all three compounds. There were significantly moderate correlations of nevirapine with 2-hydroxynevirapine and 3-hydroxynevirapin and high correlation between 2-hydroxynevirapine and 3-hydroxynevirapin. The two NVP’s metabolites showed high consistency with NVP in evaluating long-term adherence

Clinical value of the systemic immune-inflammation index in moyamoya disease

BackgroundMoyamoya disease (MMD) is a rare cerebrovascular disorder with unknown etiology. The underlying pathophysiological mechanism of moyamoya disease remains to be elucidated, but recent studies have increasingly highlighted that abnormal immune response may be a potential trigger for MMD. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) are inflammatory markers that can reflect the immune-inflammation state of the disease.ObjectiveThe purpose of this study was to investigate SII, NLR, and PLR in patients with moyamoya disease.MethodsA total of 154 patients with moyamoya disease (MMD group) and 321 age- and sex-matched healthy subjects (control group) were included in this retrospective case–control study. Complete blood count parameters were assayed to calculate the SII, NLR, and PLR values.ResultsThe SII, NLR, and PLR values in the moyamoya disease group were significantly higher than those in the control group [754 ± 499 vs. 411 ± 205 (P < 0.001), 2.83 ± 1.98 vs. 1.81 ± 0.72 (P < 0.001), and 152 ± 64 vs. 120 ± 42 (P < 0.001), respectively]. The SII in the medium-moyamoya vessels of moyamoya disease was higher than that in the high-moyamoya vessels and low-moyamoya vessels (P = 0.005). Using the receiver operating characteristic (ROC) curve analysis to predict MMD, the highest area under the curve (AUC) was determined for SII (0.76 for SII, 0.69 for NLR, and 0.66 for PLR).ConclusionBased on the results of this study, patients with moyamoya disease admitted for inpatient care due to acute or chronic stroke have significantly higher SII, NLR, and PLR when compared to blood samples drawn from completely healthy controls in a non-emergent outpatient setting. While the findings may suggest that inflammation plays a role in moyamoya disease, further studies are warranted to corroborate such an association. In the middle stage of moyamoya disease, there may be a more intense imbalance of immune inflammation. Further studies are needed to determine whether the SII index contributes to the diagnosis or serves as a potential marker of an inflammatory response in patients with moyamoya disease

Source-Free Object Detection by Learning to Overlook Domain Style

Source-free object detection (SFOD) needs to adapt a detector pre-trained on a labeled source domain to a target domain, with only unlabeled training data from the target domain. Existing SFOD methods typically adopt the pseudo labeling paradigm with model adaption alternating between predicting pseudo labels and fine-tuning the model. This approach suffers from both unsatisfactory accuracy of pseudo labels due to the presence of domain shift and limited use of target domain training data. In this work, we present a novel Learning to Overlook Domain Style (LODS) method with such limitations solved in a principled manner. Our idea is to reduce the domain shift effect by enforcing the model to overlook the target domain style, such that model adaptation is simplified and becomes easier to carry on. To that end, we enhance the style of each target domain image and leverage the style degree difference between the original image and the enhanced image as a self-supervised signal for model adaptation. By treating the enhanced image as an auxiliary view, we exploit a student-teacher architecture for learning to overlook the style degree difference against the original image, also characterized with a novel style enhancement algorithm and graph alignment constraint. Extensive experiments demonstrate that our LODS yields new state-of-the-art performance on four benchmarks

A Restoring Force Model for Prefabricated Concrete Shear Walls with Built-In Steel Sections

Prefabricated shear walls have been widely used in engineering structures. Vertical connection joints of the walls are the key to ensure the safety of the structures. Steel–concrete composite structures have been proved to have a good bearing capacity and ductility. In this paper, a new type of prefabricated structure is proposed, in which vertical wall members are connected together through built-in steel sections and cast-in-place concrete. This paper studies the seismic performance of the proposed prefabricated concrete shear wall structure. Hysteretic curves and skeleton curves of the shear wall are obtained based on experimental analyses. A dimensionless skeleton curve model is developed using the theory of material mechanics and the method of regression analysis. A stiffness calculation method for different loading stages is obtained and a restoring force model is proposed. The proposed innovative prefabricated shear wall structure provides good resistance to seismic performance and the related analysis provides a fundamental reference for studies of prefabricated shear wall structures

A Restoring Force Model for Prefabricated Concrete Shear Walls with Built-In Steel Sections

Prefabricated shear walls have been widely used in engineering structures. Vertical connection joints of the walls are the key to ensure the safety of the structures. Steel–concrete composite structures have been proved to have a good bearing capacity and ductility. In this paper, a new type of prefabricated structure is proposed, in which vertical wall members are connected together through built-in steel sections and cast-in-place concrete. This paper studies the seismic performance of the proposed prefabricated concrete shear wall structure. Hysteretic curves and skeleton curves of the shear wall are obtained based on experimental analyses. A dimensionless skeleton curve model is developed using the theory of material mechanics and the method of regression analysis. A stiffness calculation method for different loading stages is obtained and a restoring force model is proposed. The proposed innovative prefabricated shear wall structure provides good resistance to seismic performance and the related analysis provides a fundamental reference for studies of prefabricated shear wall structures

Identification of LOX as a candidate prognostic biomarker in Glioblastoma multiforme

Background: Glioblastoma multiforme (GBM) is the most malignant type of glioma. GBM tumors grow rapidly, have a high degree of malignancy, and are characterized by a fast disease progression. Unfortunately, there is a lack of effective treatments. An effective strategy for the treatment of GBM would be to identify key biomarkers correlating with the occurrence and progression of GBM and developing these biomarkers into therapeutic targets. Method and Results: In this study, using integrated bioinformatics analysis, we identified differentially expressed genes (DEGs), including 130 genes that were upregulated in GBM compared to normal brain tissue, and 128 genes that were downregulated in GBM. Based on Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis, these genes were associated with regulation of tumor cell adhesion, differentiation, morphology in GBM and were mainly enriched in Complement and coagulation cascades pathway. The Search Tool for the Retrieval of Interacting Genes (STRING) database was used to construct a Protein-Protein Interaction network. Ten hub genes were identified, including FN1, CD44, MYC, CDK1, SERPINE1, COL3A1, COL1A2, LOX, POSTN and EZH2, all of which were significantly upregulated in GBM, these results were confirmed by oncomine database exploration. Alteration analysis of hub genes found that patients with alteration in at least one of the hub genes showed shorter median survival times (p = 0.013) and shorter median disease-free survival times (p = 2.488E-3) than patients without alterations in any of the hub genes. Multiple tests for survival analysis showed that among individual hub genes only expression of LOX was correlated with patient survival (P < 0.05).GDS4467 data set was used to analyze the expression of LOX in gliomas with different degrees of malignancy, and it was found that the expression level of LOX was positively correlated with the malignant degree of gliomas.By analyzing GDS 4535 data set showed that the expression level of LOX was positively correlated with the differentiation degree of GBM cells Conclusion: This research suggests that FN1, CD44, MYC, CDK1, SERPINE1, COL3A1, COL1A2, LOX, POSTN and EZH2 are key genes in GBM. However, only LOX is correlated with patient survival and promotes glioblastoma cell differentiation and tumor recurrence. LOX may be a candidate prognostic biomarker and potential therapeutic target for GBM