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IntroductionMigraine is a prevalent neurological disorder characterized by recurrent attacks, leading to a substantial global disease burden. Recent observational studies have reported the onset and worsening of migraine following COVID-19 infection and vaccination. However, traditional observational study designs have limitations in controlling for confounding factors, potentially resulting in biased and inconsistent conclusions. To address this, we applied Mendelian randomization (MR) to investigate the causal relationship between COVID-19 infection and vaccination with migraine.MethodsThis study utilized summary-level genome-wide association study (GWAS) data from the GWAS catalog and FinnGen database to evaluate the effects of varying degrees of COVID-19 infection and vaccination on migraine. We employed inverse variance weighted (IVW) fixed-effect and random-effect models as the primary methods for MR analysis, with MR-Egger and other approaches as complementary methods. Sensitivity analyses, including Cochran's Q test, MR-Egger intercept regression, and MR-PRESSO, were conducted to ensure robustness of the results.ResultsOur MR analysis revealed no significant causal association between COVID-19 infection and migraine. However, a significant causal association was found between COVID-19 vaccination and migraine (beta = 0.071, P = 0.034). The results were confirmed through a series of sensitivity tests, demonstrating the robustness of the findings.DiscussionThis study provides novel evidence of a significant causal link between COVID-19 vaccination and migraine, while no such association was observed with COVID-19 infection. These findings may have important implications for clinical practice, particularly in planning treatment adjustments and optimizing patient care for individuals with migraines in the context of COVID-19 vaccination.

Accurate coastline extraction is crucial for the scientific management and protection of coastal zones. Due to the diversity of ground object details and the complexity of terrain in remote sensing images, the segmentation of sea and land faces challenges such as unclear segmentation boundaries and discontinuous coastline contours. To address these issues, this study improve the accuracy and efficiency of coastline extraction by improving the DeepLabv3+ model. Specifically, this study constructs a sea-land segmentation network, DeepSA-Net, based on strip pooling and coordinate attention mechanisms. By introducing dynamic feature connections and strip pooling, the connection between different branches is enhanced, capturing a broader context. The introduction of coordinate attention allows the model to integrate coordinate information during feature extraction, thereby allowing the model to capture longer-distance spatial dependencies. Experimental results has shown that the model can achieves a land-sea segmentation mean intersection over union (mIoU) ration and Recall of over 99% on all datasets. Visual assessment results show more complete edge details of sea-land segmentation, confirming the model’s effectiveness in complex coastal environments. Finally, using remote sensing data from a coastal area in China as an application instance, coastline extraction and dynamic change analysis were implemented, providing new methods for the scientific management and protection of coastal zones.

Migraine is a prevalent and disabling neurovascular disorder, with women being more susceptible, characterized by unilateral throbbing headache, often accompanied by nausea and vomiting, and often associated with various comorbidities such as brain and cardiovascular diseases, which can have a serious impact on quality of life. Although nonsteroidal anti-inflammatory drugs (NSAIDs) are the main first-line medications for the treatment of pain, long-term use often leads to side effects and drug addiction, which emphasizes the need to investigate alternative pain management strategies with fewer adverse effects. Complementary and alternative medicine is a viable pain intervention often used in conjunction with traditional medications, including acupuncture, herbs, moxibustion, transcutaneous electrical stimulation, bio-supplements, and acupressure, which offer non-pharmacological alternatives that are now viable pain management options. This review focuses on the mechanistic doctrine of migraine generation and the role and potential mechanisms of Complementary and Alternative Therapies (CAT) in the treatment of migraine, summarizes the research evidences for CAT as an adjunct or alternative to conventional therapies for migraine, and focuses on the potential of novel migraine therapies (calcitonin gene-related peptide (CGRP) antagonists and pituitary adenylyl cyclase-activating peptide (PACAP) antagonists) with the aim of evaluating CAT therapies as adjunctive or alternative therapies to conventional migraine treatment, thereby providing a broader perspective on migraine management and the design of treatment programs for more effective pain management.

BackgroundUncertainty still remained about the relationship between visceral adiposity index (VAI) and hyperuricemia. The aim of this study was to investigate whether VAI was an independent risk factor for hyperuricemia in hypertensive Chinese patients.MethodsA cross-sectional study including 13176 hypertensive participants (6478 males) recruited from Wuyuan County, Jiangxi province, was conducted. All patients received anthropometric measurements, completed questionnaires and provided blood samples for biochemical testing. VAI was calculated by waist circumference, BMI, triglyceride and high-density lipoprotein cholesterol. Hyperuricemia was defined as serum uric acid ≥ 7 mg/dL in men and ≥ 6 mg/dL in women.ResultsOverall, the average level of uric acid was 7.8 ± 2.0 mg/dL in males and 6.34 ± 1.78 in females and prevalence of hyperuricemia was 61.4% and 51.30%, respectively. In multivariate logistic regression analysis, the risk of hyperuricemia increased 1.77 times and 1.88 times with the increase of ln VAI in males (OR:1.77, 95% CI: 1.62, 1.94) and females (OR:1.88, 95% CI: 1.73, 2.04). For males, compared to quartile 1, the risk of hyperuricemia in the second, third and the forth quartile of visceral adiposity index were 1.34 (95% CI: 1.14, 1.57),1.82(95% CI: 1.54, 2.14) and 2.97 (95% CI: 2.48, 3.57). For females, compared to quartile 1, the risk of hyperuricemia in the second, third and the forth quartile of visceral adiposity index were 1.48 (95% CI: 1.28, 1.72), 1.99 (95% CI: 1.71, 2.32) and 2.92 (95% CI: 2.50, 3.42).ConclusionsThis study found that VAI was an independent risk factor for hyperuricemia among hypertensive patients, which may provide some strategies for reducing the level of uric acid.

BackgroundEpithelial ovarian tumors (EOTs) are a group of heterogeneous neoplasms. It is importance to preoperatively differentiate the histologic subtypes of EOTs. Our study aims to investigate the potential of radiomics signatures based on diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) maps for categorizing EOTs.MethodsThis retrospectively enrolled 146 EOTs patients [34 with borderline EOT(BEOT), 30 with type I and 82 with type II epithelial ovarian cancer (EOC)]. A total of 390 radiomics features were extracted from DWI and ADC maps. Subsequently, the LASSO algorithm was used to reduce the feature dimensions. A radiomics signature was established using multivariable logistic regression method with 3-fold cross-validation and repeated 50 times. Patients with bilateral lesions were included in the validation cohort and a heuristic selection method was established to select the tumor with maximum probability for final consideration. A nomogram incorporating the radiomics signature and clinical characteristics was also developed. Receiver operator characteristic, decision curve analysis (DCA), and net reclassification index (NRI) were applied to compare the diagnostic performance and clinical net benefit of predictive model.ResultsFor distinguishing BEOT from EOC, the radiomics signature and nomogram showed more favorable discrimination than the clinical model (0.915 vs. 0.852 and 0.954 vs. 0.852, respectively) in the training cohort. In classifying early-stage type I and type II EOC, the radiomics signature exhibited superior diagnostic performance over the clinical model (AUC 0.905 vs. 0.735). The diagnostic efficacy of the nomogram was the same as that of the radiomics model with NRI value of -0.1591 (P = 0.7268). DCA also showed that the radiomics model and combined model had higher net benefits than the clinical model.ConclusionRadiomics analysis based on DWI, and ADC maps serve as an effective quantitative approach to categorize EOTs.

Bone marrow is one of the most important organs in the human body. The evaluation of bone marrow microstructure and gender-related cellular and capillary networks in healthy young adults can help to better understand the process of bone metabolism. Intravoxel incoherent motion (IVIM) provides both diffusion and perfusion quantifications without requiring intravenous contrast agent injection. In this prospective study, 60 healthy young age-matched volunteers (30 men and 30 women) underwent MRI scans at 1.5 T using multi–b-value diffusion-weighted imaging on sagittal planes covering the lumbar bone marrow. The apparent diffusion coefficient (ADC), true ADC (D), pseudo-ADC (D*), and perfusion fraction (f) were calculated from the diffusion-weighted images using the mono- and bi-exponential models. Lumbar cancellous bone (L2–L4) was selected as the region of interest. An independent t-test was used to detect significant differences in ADC values and IVIM parameters between men and women. The differences in IVIM parameters among the L2, L3, and L4 groups were compared with analysis of variance. The D and f values in women were significantly higher than that in men (p = 0.001, 0.026). However, D* was significantly lower in women than that in men (p = 0.001). Furthermore, there was no significant gender difference for the conventional ADC value (p = 0.186). Moreover, there were no significant differences in the D, f, and D* values among the L2, L3, and L4 vertebras of women or men. IVIM parameters can show differences in bone marrow between young women and men. As a non-invasive method, it can assess bone marrow microstructure, such as cellularity and perfusion.

Background and aimsThe relationship between the new obesity index weight-adjusted-waist index (WWI) and hyperuricemia is unclear. We aimed to explore the association of the WWI and hyperuricemia among the hypertensive population.MethodsA total of 14,078 hypertension participants with complete data were included in our study. WWI was calculated by waist circumference divided by the square root of weight. Specifically, men with 420 μmol/L and women with 360 μmol/L were considered to have hyperuricemia.ResultsThe prevalence of hyperuricemia was 61.1% in men and 51.4% in women. On the whole, multivariate logistic regression analyses found that there was a linear positive correlation of WWI with hyperuricemia in both men (OR: 1.37; 95%CI: 1.25, 1.49) and women (OR: 1.35; 95%CI: 1.26, 1.45). Subgroup analysis found that the relationship between WWI and hyperuricemia was stable in stratified subgroups (all P-interactions >.05).ConclusionWWI showed a positive association with hyperuricemia among hypertension patients.

BackgroundBlood parameters, such as neutrophil-to-lymphocyte ratio, have been identified as reliable inflammatory markers with diagnostic and predictive value for the coronavirus disease 2019 (COVID-19). However, novel hematological parameters derived from high-density lipoprotein-cholesterol (HDL-C) have rarely been studied as indicators for the risk of poor outcomes in patients with severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) infection. Here, we aimed to assess the prognostic value of these novel biomarkers in COVID-19 patients and the diabetes subgroup.MethodsWe conducted a multicenter retrospective cohort study involving all hospitalized patients with COVID-19 from January to March 2020 in five hospitals in Wuhan, China. Demographics, clinical and laboratory findings, and outcomes were recorded. Neutrophil to HDL-C ratio (NHR), monocyte to HDL-C ratio (MHR), lymphocyte to HDL-C ratio (LHR), and platelet to HDL-C ratio (PHR) were investigated and compared in both the overall population and the subgroup with diabetes. The associations between blood parameters at admission with primary composite end-point events (including mechanical ventilation, admission to the intensive care unit, or death) were analyzed using Cox proportional hazards regression models. Receiver operating characteristic curves were used to compare the utility of different blood parameters.ResultsOf 440 patients with COVID-19, 67 (15.2%) were critically ill. On admission, HDL-C concentration was decreased while NHR was high in patients with critical compared with non-critical COVID-19, and were independently associated with poor outcome as continuous variables in the overall population (HR: 0.213, 95% CI 0.090–0.507; HR: 1.066, 95% CI 1.030–1.103, respectively) after adjusting for confounding factors. Additionally, when HDL-C and NHR were examined as categorical variables, the HRs and 95% CIs for tertile 3 vs. tertile 1 were 0.280 (0.128–0.612) and 4.458 (1.817–10.938), respectively. Similar results were observed in the diabetes subgroup. ROC curves showed that the NHR had good performance in predicting worse outcomes. The cutoff point of the NHR was 5.50. However, the data in our present study could not confirm the possible predictive effect of LHR, MHR, and PHR on COVID-19 severity.ConclusionLower HDL-C concentrations and higher NHR at admission were observed in patients with critical COVID-19 than in those with noncritical COVID-19, and were significantly associated with a poor prognosis in COVID-19 patients as well as in the diabetes subgroup.

Background: Chronic kidney disease (CKD) has been a globally public health problem over the past decades. The maintenance of physical and mental health is of importance for patients nowadays. Notably, depression is prevalent and associated with various adverse events in CKD patients without dialysis. Prior studies have reported that pain, negative illness perception, pain, and low self-esteem are potential risk factors of depression, while few studies have comprehensively investigated the mechanisms among these factors and depression among this population.Purpose: This study aims to investigate the prevalence of depression and further explore the factors associated with depression among CKD patients without dialysis in China.Design and Methods: We conducted a cross-sectional study in patients with diagnosed CKD to investigate the prevalence of depression was by the Beck Depression Inventory-II (BDI-II). The data on pain interference, illness perception, and self-esteem were also collected via self-administered questionnaires. A structural equation model (SEM) was used to examine the factors associated with depression.Main Findings: From June to October 2019, we successfully interviewed 334 CKD patients at the outpatient clinics. Their mean age was 45.6 years (ranging from 19 to 74 years), and 48.5% were male. Most respondents were at early CKD stages (77.5% stage 1–3) and the prevalence of depression was 22.2%. We found a moderate association between illness perception and depression, which was modified by self-esteem. Similar but weaker association was found between pain interference and depression.Conclusion and Recommendations: Negative illness perception, low self-esteem and severe pain interference were associated with depression among Chinese CKD patients without dialysis. Future studies are warranted to investigate the underlying mechanism and formulate the intervention strategies for this high-risk population.

Background: Diabetes correlates with poor prognosis in patients with COVID-19, but very few studies have evaluated whether impaired fasting glucose (IFG) is also a risk factor for the poor outcomes of patients with COVID-19. Here we aimed to examine the associations between IFG and diabetes at admission with risks of complications and mortality among patients with COVID-19.Methods: In this multicenter retrospective cohort study, we enrolled 312 hospitalized patients with COVID-19 from 5 hospitals in Wuhan from Jan 1 to Mar 17, 2020. Clinical information, laboratory findings, complications, treatment regimens, and mortality status were collected. The associations between hyperglycemia and diabetes status at admission with primary composite end-point events (including mechanical ventilation, admission to intensive care unit, or death) were analyzed by Cox proportional hazards regression models.Results: The median age of the patients was 57 years (interquartile range 38–66), and 172 (55%) were women. At the time of hospital admission, 84 (27%) had diabetes (and 36 were new-diagnosed), 62 (20%) had IFG, and 166 (53%) had normal fasting glucose (NFG) levels. Compared to patients with NFG, patients with IFG and diabetes developed more primary composite end-point events (9 [5%], 11 [18%], 26 [31%]), including receiving mechanical ventilation (5 [3%], 6 [10%], 21 [25%]), and death (4 [2%], 9 [15%], 20 [24%]). Multivariable Cox regression analyses showed diabetes was associated increased risks of primary composite end-point events (hazard ratio 3.53; 95% confidence interval 1.48–8.40) and mortality (6.25; 1.91–20.45), and IFG was associated with an increased risk of mortality (4.11; 1.15–14.74), after adjusting for age, sex, hospitals and comorbidities.Conclusion: IFG and diabetes at admission were associated with higher risks of adverse outcomes among patients with COVID-19.