Potential Association Research Articles

Association of dietary insulinemic potential with disease severity and symptoms in patients with COVID-19

AimCOVID-19 has threatened people's lives in world. Studies showed that level of insulin is related to function of immune system and level of inflammation in body. In this study we aimed to evaluate the association between dietary insulinemic potential and level of inflammatory biomarkers, severity and symptoms of COVID-19. MethodsParticipants of this cross-sectional study were 684 people who recovered from COVID-19. Dietary intake of participants was assessed using 168-item food frequency questionnaire during telephone interview, then dietary insulinemic index and load (DII and DIL) calculated for each participants. Data related to study outcomes, include levels of inflammatory biomarkers, disease symptoms, lung infection, saturation of peripheral oxygen, Respiratory Rate, need for respiratory support, duration of disease, hospitalization, recovery from disease and need for respiratory support and score of life satisfaction were collected through an interview with participants and review of their medical records. ResultsAfter controlling for confounders, participants in the highest quartile of DIL had a significantly higher risk of severe COVID-19 (OR: 2.66, 95% CI: 1.01–7.04, Ptrend=0.035), risk of hospitalization (OR: 3.44, 95% CI: 2.27-7.64, Ptrend>0.001), fever (OR: 2.91, 95% CI: 8.08–1.05, Ptrend=0.042), chills (OR: 4.68, 95% CI: 1.77–12.37, Ptrend=0.002) and lower risk of weakness (OR: 0.28, 95% CI: 0.10–0.74, Ptrend=0.012) and myalgia (OR:0.26, CI: 0.10–0.45, Ptrend=0.006) compared to the lowest quartile. In addition our findings showed a significant positive association between DII and risk of fever (OR: 1.71 95% CI: 2.84–1.03, Ptrend=0.049). Our finding failed to find a significand association between DII and risk of sever COVID-19 and hospitalization. Moreover we did not find significant association between DII/DIL and duration of disease, other symptoms and outcomes. ConclusionsOur findings showed that higher DIL was associated with greater risk of sever COVID-19 and hospitalization. More detailed cohort studies are needed to confirm the findings.

Work-related and non-work-related mild traumatic brain injury: Associations with mental health and substance use challenges in a Canadian population-level survey.

Mild traumatic brain injury (mTBI) can profoundly impact overall health, employment, and family life. Incidence of mTBI in the workplace represents an important subgroup with poorer outcomes. Mental health (MH) and substance use (SU) challenges are a primary correlate of TBI, but are rarely assessed among individuals with a work-related (wr)-mTBI, particularly at a population-level. This study aimed to assess the association between lifetime wr-mTBI and non-wr-mTBI and the experience of MH and SU challenges. The 2019 Centre for Addiction and Mental Health (CAMH) Monitor is a cross-sectional telephone survey of adults aged≥18 years in Ontario, Canada, employing a stratified (six regions) two-stage (telephone number, respondent) list-assisted random digit dialing probability selection procedure (N = 1792). Adjusting for sociodemographic variables, binary logistic regression was conducted to assess the association between lifetime wr-mTBI and non-wr-mTBI (relative to no TBI) and four outcomes: hazardous use of alcohol and of cannabis, psychological distress, and fair/poor mental health. Adjusting for sociodemographic variables, non-wr-mTBI demonstrated increased odds of hazardous alcohol (AOR = 2.12, 95% CI = 1.41, 3.19) and cannabis use (AOR = 1.61, 95% CI = 1.05, 2.45), psychological distress (AOR = 1.68, 95% CI = 1.14, 2.49), and fair/poor mental health (AOR = 1.70, 95% CI = 1.11, 2.59). Lifetime wr-mTBI demonstrated increased odds of reporting psychological distress (AOR = 3.40, 95% CI = 1.93, 5.97) and fair/poor mental health (AOR = 2.16, 95% CI = 1.12, 4.19) only. Non-wr-mTBI was associated with both MH and SU, whereas wr-mTBI was associated with MH only. MH outcomes were more strongly associated with wr-mTBI than non-wr-mTBI. Physicians, employers, and insurers need to consider the potential association between wr-mTBI and MH, and provide care accordingly.

STNMDA: A Novel Model for Predicting Potential Microbe-Drug Associations with Structure-Aware Transformer

Introduction: Microbes are intimately involved in the physiological and pathological processes of numerous diseases. There is a critical need for new drugs to combat microbe-induced diseases in clinical settings. Predicting potential microbe-drug associations is, therefore, essential for both disease treatment and novel drug discovery. However, it is costly and time-consuming to verify these relationships through traditional wet lab approaches. Methods: We proposed an efficient computational model, STNMDA, that integrated a StructureAware Transformer (SAT) with a Deep Neural Network (DNN) classifier to infer latent microbedrug associations. The STNMDA began with a “random walk with a restart” approach to construct a heterogeneous network using Gaussian kernel similarity and functional similarity measures for microorganisms and drugs. This heterogeneous network was then fed into the SAT to extract attribute features and graph structures for each drug and microbe node. Finally, the DNN classifier calculated the probability of associations between microbes and drugs. Results: Extensive experimental results showed that STNMDA surpassed existing state-of-the-art models in performance on the MDAD and aBiofilm databases. In addition, the feasibility of STNMDA in confirming associations between microbes and drugs was demonstrated through case validations. Conclusion: Hence, STNMDA showed promise as a valuable tool for future prediction of microbedrug associations.

Potential Association of The Pathogenic Kruppel-like Factor 14 (KLF14) and Adiponectin (ADIPOQ) SNVs with Susceptibility to T2DM.

To evaluate the associations of the pathogenic variants in Kruppel-like Factor 14 (KLF 14) and Adiponectin (ADIPOQ) with susceptibility to type 2 diabetes mellitus (T2DM). Type 2 diabetes mellitus (T2DM) is a pandemic metabolic disease characterized by increased blood sugar and caused by resistance to insulin in peripheral tissues and damage to pancreatic beta cells. Kruppel-like Factor 14 (KLF-14) is proposed to be a regulator of metabolic diseases, such as diabetes mellitus (DM) and obesity. Adiponectin (ADIPOQ) is an adipocytokine produced by the adipocytes and other tissues and was reported to be involved in T2DM. To study the possible association of the KLF-14 rs972283 and ADIPOQ-rs266729 with the risk of T2DM in the Saudi population. We have evaluated the association of KLF-14 rs972283 C>T and ADIPOQ-rs266729 C>G SNV with the risk to T2D in the Saudi population using the Amplification Refractory Mutation System PCR (ARMS-PCR), and blood biochemistry analysis. For the KLF-14 rs972283 C>T SNV we included 115 cases and 116 healthy controls, and ADIPOQ-rs266729 C>G SNV, 103 cases and 104 healthy controls were included. Results indicated that the KLF-14 rs972283 GA genotype and A allele were associated with T2D risk with OR=2.14, p-value= 0.014 and OR=1.99, p-value=0.0003, respectively. Results also ADIPOQ-rs266729 CG genotype and C allele were associated with an elevated T2D risk with an OR=2.53, p=0.003 and OR=1.66, p-value =0.012, respectively. We conclude that SNVs in KLF-14 and ADIPOQ are potential loci for T2D risk. Future large-scale studies to verify these findings are recommended. These results need further verifications in protein functional and large-scale case control studies before being introduced for genetic testing.

Subset of retinoblastoma tumours is associated with BRCA1/2 mutations

BackgroundWe investigated the potential association between pathogenic BRCA1/2 variants and retinoblastoma pathogenicity.MethodsIn this single-centre, retrospective case series, we performed hereditary cancer panel tests using blood samples for patients with retinoblastoma...

Developing mental health curricula and a service provision model for clinical associates in South Africa: a Delphi survey of family physicians and psychiatrists

BackgroundClinical associates are a health professional cadre that could be utilised in mental health task sharing in South Africa but this is training dependent. The objectives of the study were to identify the potential curricula content, training sites, and teaching modalities for undergraduate and potential postgraduate clinical associate mental health training and to identify the tasks that they should perform based on these curricula.MethodsWe utilised the Delphi method to reach consensus on items with the panel comprising psychiatrists and family physicians. The first round questionnaire of the Delphi survey was developed based on a literature review and the results from earlier phases of the overall study. The survey was administered electronically and consisted of three rounds. Following both the first and second rounds, an updated questionnaire was constructed omitting the items on which consensus was reached. The questionnaire consisted primarily of nine-point scales with consensus based on 70% of participants rating 1,2,3 or 7,8,9.ResultsThere were 26 participants in the first round with this number falling to 23 in later rounds. There was strong consensus on a training attachment to a mental health clinic at a community health centre (CHC) at undergraduate (96.2%) and postgraduate level (100%). Consensus was reached on the importance of training on the management of six categories of disorders at the undergraduate level and nine categories of disorders at the postgraduate level. Clerking patients as a teaching modality reached 100% consensus at both undergraduate and postgraduate levels. PHC clinics, CHCs and district hospitals reached consensus as appropriate settings for clinical associates to provide mental health services. In addition, GP practices and secondary hospitals reached consensus for those with postgraduate training. Consensus was reached on ten of the 21 listed tasks that could be performed based on undergraduate training and 20 of the 21 tasks based on a postgraduate qualification in mental health.ConclusionsThe Delphi panel’s recommendations provide a clear roadmap for enhancing mental health curricula for clinical associates, enabling their utilisation in mental health service provision. A future postgraduate mental health qualification for clinical associates would allow for expanded task sharing.

Long-term risk assessment in athletes with ventricular arrhythmias: the key roles of arrhythmia morphology, complexity, and substrate

Abstract Background Ventricular arrhythmias (VAs) are an important source of concern among athletes. Purpose To determine the prognostic role of non-invasive and invasive diagnostic assessments among athletes with complex VAs. Methods We included 215 athletes (83% male; 28 [19-43] years) with complex VAs in a prospective, multi-center cohort study. At baseline, each athlete underwent a prespecified comprehensive diagnostic workup, which included cardiac magnetic resonance (CMR) in 202 subjects, and electrophysiology study (EPS)/electroanatomical mapping (EAM) in 190. The primary study endpoint was the occurrence of sudden death or sustained VAs during long-term follow-up. Results During a median follow-up of 6.2 (4.4-8.1) years, 16 (7%) athletes had a primary outcome event, including one sudden cardiac death. In univariable Cox models, sustained VAs at presentation (p<0.001), uncommon VA morphology(p=0.004), syncope(p=0.005), abnormal ECG (p=0.003), VAs induction/persistence at exercise testing(p=0.021), late gadolinium enhancement (LGE;p=0.006), low-voltage areas (p=0.003) and late potentials (p<0.001) at EAM, and sustained VA induction by EPS (p<0.001) were all associated with increased risk of primary outcome events. The association of late potentials and EPS inducibility with primary outcome events was confirmed after controlling for all non-invasive predictors at univariable analysis, and the incorporation of findings of invasive tests allowed improved prediction of primary outcome events over clinical/non-invasive findings in isolation (log-likelihood ratio for nested models, p=0.043). Younger age (p=0.032), being a professional athlete (p=0.006), and absence of LGE (p=0.029) were independently associated with higher odds of uninterrupted competitive sports practice until last follow-up. Conclusions A comprehensive diagnostic assessment integrating clinical/ECG findings with CMR and EPS/EAM in selected cases may provide important prognostic information among athletes with complex VAs.

Association between eNOS gene polymorphisms and the risk of unexplained recurrent spontaneous abortion in Yunnan province, China.

Recurrent spontaneous abortion affects approximately 1-2% of reproductive-age women, with roughly half of RSA cases classified as unexplained recurrent spontaneous abortion (URSA). Genetic polymorphisms in eNOS gene have been shown to have significant implications across various disease processes. Nevertheless, the potential impact of eNOS gene polymorphisms on the susceptibility to URSA in Yunnan population has yet to be explored or documented. This study aims to investigate the potential association between specific variations in the eNOS gene (VNTR 4b/a, -786T > C, and +894G > T) and the risk of URSA in Yunnan population. A total of 243 URSA patients and 241 healthy females are involved in this study. We conducted amplification of the eNOS gene fragment and performed sanger sequencing to detect the specific eNOS gene polymorphisms, including VNTR 4b/a, -786T > C, and +894G > T. Using a multivariate logistic regression model, we evaluate the potential association between eNOS gene polymorphisms (VNTR 4b/a, -786T > C, and +894G > T) and the risk of URSA. Furthermore, serum NO levels were measured in URSA patients. The presence of VNTR 4a, -786C, and +894T alleles was found to be associated with an increased risk of URSA. Additionally, our study revealed a significant association between the G-C-4b haplotype of the investigated eNOS gene polymorphisms and a predisposition to URSA. Notably, these eNOS polymorphisms were shown to reduce serum NO levels in URSA patients. This study provides evidence supporting the association between eNOS gene polymorphisms, VNTR 4b/a, -786T > C, and +894G > T, and the occurrence of URSA in Yunnan Province, China.

Hierarchical Negative Sampling Based Graph Contrastive Learning Approach for Drug-Disease Association Prediction.

Predicting potential drug-disease associations (RDAs) plays a pivotal role in elucidating therapeutic strategies for diseases and facilitating drug repositioning, making it of paramount importance. However, existing methods are constrained and rely heavily on limited domain-specific knowledge, impeding their ability to effectively predict candidate associations between drugs and diseases. Moreover, the simplistic definition of unknown information pertaining to drug-disease relationships as negative samples presents inherent limitations. To overcome these challenges, we introduce a novel hierarchical negative sampling-based graph contrastive model, termed HSGCLRDA, which aims to forecast latent associations between drugs and diseases. In this study, HSGCLRDA integrates the association information as well as similarity between drugs, diseases and proteins. Meanwhile, the model constructs a drug-disease-protein heterogeneous network. Subsequently, employing a hierarchical structural sampling technique, we establish reliable negative drug-disease samples utilizing PageRank algorithms. Utilizing meta-path aggregation within the heterogeneous network, we derive low-dimensional representations for drugs and diseases, thereby constructing global and local feature graphs that capture their interactions comprehensively. To obtain representation information, we adopt a self-supervised graph contrastive approach that leverages graph convolutional networks (GCNs) and second-order GCNs to extract feature graph information. Furthermore, we integrate a contrastive cost function derived from the cross-entropy cost function, facilitating holistic model optimization. Experimental results obtained from benchmark datasets not only showcase the superior performance of HSGCLRDA compared to various baseline methods in predicting RDAs but also emphasize its practical utility in identifying novel potential diseases associated with existing drugs through meticulous case studies.

KFDAE: CircRNA-Disease Associations Prediction Based on Kernel Fusion and Deep Auto-Encoder.

CircRNA has been proved to play an important role in the diseases diagnosis and treatment. Considering that the wet-lab is time-consuming and expensive, computational methods are viable alternative in these years. However, the number of circRNA-disease associations (CDAs) that can be verified is relatively few, and some methods do not take full advantage of dependencies between attributes. To solve these problems, this paper proposes a novel method based on Kernel Fusion and Deep Auto-encoder (KFDAE) to predict the potential associations between circRNAs and diseases. Firstly, KFDAE uses a non-linear method to fuse the circRNA similarity kernels and disease similarity kernels. Then the vectors are connected to make the positive and negative sample sets, and these data are send to deep auto-encoder to reduce dimension and extract features. Finally, three-layer deep feedforward neural network is used to learn features and gain the prediction score. The experimental results show that compared with existing methods, KFDAE achieves the best performance. In addition, the results of case studies prove the effectiveness and practical significance of KFDAE, which means KFDAE is able to capture more comprehensive information and generate credible candidate for subsequent wet-lab.

Vitamin E Intake and Prevalence Rates of Thyroid Dysfunction and Autoimmune Thyroiditis: A Cross-Sectional Analysis of NHANES Data.

Background: Thyroid disorders are associated with various dietary factors and nutritional elements. The aim of this study was to investigate the relationships between dietary vitamin E intake and the prevalence of thyroid dysfunction and thyroid antibody positivity using data from the National Health and Nutrition Examination Survey (NHANES) database. Methods: Data from the NHANES database collected between 2007 and 2012 were analyzed. A total of 7,773 nonpregnant adults without preexisting thyroid diseases and possessing complete thyroid and vitamin E data were included in the study. The participants were categorized into tertiles based on their dietary vitamin E intake: the lowest group (T1: ≤4.53 mg), the intermediate group (T2: 4.54-8.10 mg), and the highest group (T3: ≥8.11 mg). We used a complex multistage probability sampling design in conjunction with R software. We compared thyroid indices, the prevalence of overt and subclinical hyperthyroidism or hypothyroidism, and the occurrence of thyroid antibody positivity among the three groups based on vitamin E intake. Weighted multinomial logistic regression was used to assess the association between dietary vitamin E intake and thyroid disorders. Restricted cubic splines (RCSs) were used to explore potential nonlinear associations. Results: The prevalence rates of subclinical hypothyroidism (SCH) were 3.63%, 3.07%, and 1.85% in T1, T2, and T3, respectively, indicating a decreasing trend (P-trend = 0.013). In the general population, high vitamin E intake (T3) was significantly associated with a lower prevalence of SCH (OR = 0.28, CI = 0.15-0.54, p < 0.001). Subgroup analysis revealed a more pronounced protective effect in males, with both moderate (T2, OR = 0.45, CI = 0.23-0.87, p = 0.020) and high (T3, OR = 0.19, CI = 0.09-0.39, p < 0.001) dietary vitamin E intake being associated with a lower prevalence of SCH. In addition, moderate (T2, OR = 0.59, CI = 0.37-0.93, p = 0.024) and high (T3, OR = 0.52, CI = 0.36-0.75, p < 0.001) dietary vitamin E intake was associated with a lower prevalence of autoimmune thyroiditis (AIT) in males. However, no significant association was observed among females. Conclusion: The findings of this study suggest that a higher intake of vitamin E is associated with lower prevalence rates of SCH and autoimmune thyroiditis among males.

The association of the dietary inflammatory potential with risk of overall and site-specific cancers: A community-based longitudinal study in the UK Biobank

ObjectivesThe association of the dietary inflammatory potential with cancer risk remains uncertain. We examined the relationship of the dietary inflammatory potential with risk of overall and site-specific cancers and explored its sex and age differences. DesignA community-based longitudinal study. SettingParticipants from the UK Biobank completed baseline surveys during 2006–2010 and were followed for up to 15 years to detect incident cancer. Participants170,899 cancer-free participants with dietary data available (mean age: 55.73 ± 7.95, 54.10% female). MeasurementsAt baseline, dietary intake was assessed with a 24-h dietary record for up to 5 times. The inflammatory diet index (IDI) was calculated to assess the dietary inflammatory potential as a weighted sum of 31 food groups (including 14 anti-inflammatory and 17 pro-inflammatory) based on plasma high-sensitivity C-reactive protein (hsCRP) levels, and tertiled as low (indicating low-inflammatory diet), moderate, and high IDI (as reference). Overall and site-specific cancers were ascertained via linkage to routine hospital admission, cancer registry, and death certificate data. Data were analyzed using Cox regression and Laplace regression. ResultsDuring the follow-up (median 10.32 years, interquartile range: 9.95–11.14 years), 18,884 (11.05%) participants developed cancer. In multi-adjusted Cox regression, low IDI scores were associated with decreased risk of rectal cancer (hazard ratio [95% confidence interval, CI] 0.76 [0.61, 0.94]), thyroid cancer [0.45 (0.27, 0.74)], lung cancer [0.73 (0.61, 0.88)]. However, the association between IDI score and the risk of overall cancer was not significant. Laplace regression analysis showed that 10th percentile differences (95% CIs) of cancer onset time for participants with low IDI scores was prolonged by 1.29 (0.32, 2.27), 1.44 (0.58, 2.30), and 2.62 (0.98, 4.27) years for rectal cancer, thyroid cancer, and lung cancer, respectively, compared to those with high IDI scores. Stratified analysis revealed that low IDI scores were associated with a lower risk of rectal cancer (p interaction between IDI score and sex = 0.035) and lung cancer in males, but not in females, and with a reduced risk of thyroid cancer in females, but not in males. Moreover, low IDI scores were associated with a reduced risk of rectal cancer and lung cancer in the participants aged ≥60 years, but not in those <60 years, and with a reduced risk of thyroid cancer in those aged ≥60 years and <60 years. ConclusionsA low-inflammatory diet is associated with decreased risk and prolonged onset time of rectal cancer and lung cancer, especially among males and individuals aged ≥60 years, and thyroid cancer among females.

Genetic Insights into the Association and Causality Between Blood Metabolites and Alzheimer's Disease.

Alzheimer's disease (AD) is an increasing public health concern with the aging of the global population. Understanding the genetic correlation and potential causal relationships between blood metabolites and AD may provide important insights into the metabolic dysregulation underlying this neurodegenerative disorder. The aim of this study was to investigate the causal relationship between blood metabolites and AD using Mendelian randomization (MR) analysis. Association data were obtained from three large-scale genome-wide association studies of 486 blood metabolites (N = 7,824), AD (71,880 cases and 383,378 controls), early-onset AD (N = 303,760), and late-onset AD (N = 307,112). Causal associations between blood metabolites and AD were assessed using inverse variance weighting (IVW), MR-Egger, and weighted median methods. Bidirectional two-sample MR analysis was used to identify causal blood metabolites. MR-PRESSO, MR-Egger, and Cochran-Q were used to quantify instrumental variable heterogeneity and horizontal pleiotropy. Using MR and sensitivity analysis, we identified 40 blood metabolites with potential causal associations with AD. After applying false discovery rate (FDR) correction, two metabolites, gamma-glutamylphenylalanine (OR = 1.15, 95% CI: 1.06-1.24, p = 3.88×10-4, q = 0.09) and X-11317 (OR = 1.16, 95% CI: 1.08-1.26, p = 1.14×10-4, q = 0.05), retained significant associations with AD. Reverse MR analysis indicated no significant causal effect of AD on blood metabolites. No significant instrumental variable heterogeneity or horizontal pleiotropy was found. This two-sample MR study provides compelling evidence for a potential causal relationship between blood metabolic dysregulation and susceptibility to AD. Further investigation of the biological relevance of the identified metabolites to AD and additional supporting evidence is warranted.

The Impact of Polycystic Ovary Syndrome (PCOS) on the Risk of Developing Ovarian Cancer and Thyroid Disorders: A Comprehensive Review.

Polycystic ovary syndrome (PCOS) is a common hormonal disorder that affects women. It is characterized by hyperandrogenism, polycystic ovarian morphology, and other related disorders. It is associated with various health conditions, such as infertility and increased risk of heart problems. Ovarian cancer is also a significant concern, as it is the fifth leading cause of death in women. While there is evidence suggesting a potential association between PCOS and ovarian cancer, the exact nature of this relationship remains unclear. Thyroid disorders, particularly hypothyroidism and Hashimoto's thyroiditis, have also been linked to PCOS. The presence of hypothyroidism can contribute to the development of polycystic ovarian morphology, affecting ovulation and hormone balance. Many works have shown a higher ubiquity of autoimmune thyroid disease in PCOS patients, indicating a potential association between the two conditions. The occurrence of PCOS, hirsutism, and acne underscores the frequency of endocrine disorders in women. This review paper examines the present relevant work on the association between PCOS and ovarian cancer as well as PCOS and thyroid disorders. A systematic literature search was conducted on the internet, such as PubMed, Scopus, and Google Scholar database, to identify peer-reviewed publications pertaining to PCOS, ovarian cancer, and thyroid disorders. While some studies have delineated a significant link between PCOS and ovarian cancer or thyroid disorders, others have yielded inconclusive results. Further research is necessary to establish a definitive causal relationship between these conditions. Understanding the relationship between PCOS, ovarian cancer, and thyroid disorders is crucial for early detection, accurate diagnosis, and effective management of these conditions. Identifying potential risk factors and developing appropriate screening strategies can improve women's health outcomes and reduce the burden associated with these disorders.

Empowering Graph Neural Networks with Block-Based Dual Adaptive Deep Adjustment for Drug Resistance-Related NcRNA Discovery.

Drug resistance to chemotherapeutic agents remains a formidable challenge in cancer treatment, significantly impacting treatment efficacy. Extensive research has exposed the intimate involvement of noncoding RNAs (ncRNAs) in conferring resistance to cancer drugs. Understanding the intricate associations between ncRNAs and drug resistance is of pivotal importance in advancing clinical interventions and expediting drug development. However, traditional biological experimental methods are hampered by limitations, such as labor intensiveness, time consumption, and constraints in scalability. Addressing these challenges necessitates the development of efficient computational methods for the accurate prediction of potential ncRNA-drug resistance associations (NDRA). However, most existing predictive models primarily focus on known ncRNA-drug resistance associations, often neglecting the critical aspect of similarity information between ncRNAs and drug resistance. This oversight may hinder the accuracy of characterizing these associations. To overcome the limitations of existing computational models, we proposed B-NDRA, a computational framework designed for the discovery of drug resistance-related ncRNA. Initially, we constructed a heterogeneous graph that integrates ncRNA-drug resistance pairs, leveraging both known associations and similarity fusion information between ncRNAs and drug resistance. Subsequently, we employed an attention mechanism to aggregate local features of graph nodes following a dimensionality reduction of node features. Further, a graph neural network (GNN) facilitated the learning of global node embeddings. Notably, the integration of dual adaptive deep adjustment architectures, encompassing intrablock and interblock methodologies, enabled efficient extraction of global features while balancing local and global features. Finally, B-NDRA employed a multilayer perceptron to predict associations between ncRNAs and drug resistance. Through rigorous 5-fold cross-validation, B-NDRA achieved average AUC, AUPR, Accuracy, Precision, Recall, and F1-score values of 92.2%, 91.9%, 84.88%, 86.9%, 82.37%, and 84.44%, respectively. Furthermore, comparative evaluations were conducted on established models, namely, GAEMDA, GRPAMDA, and LRGCPND. The results, obtained through three distinct 5-fold cross-validation strategies, demonstrated a notable performance improvement across almost all metrics for our B-NDRA. Specific case studies targeting Doxorubicin and Imatinib further validated the practicality of our B-NDRA in discovering potential NDRA. These results confirm the potential of our B-NDRA as a valuable tool in advancing cancer research and therapeutic development. The source code and data set of B-NDRA can be found at https://github.com/XuanLi1145/B-NDRA.

Adverse childhood experiences, dental insurance, and developmental disability: Association with unmet dental needs in Ohio.

This study investigated whether insurance status and/or developmental disability moderated the association between adverse childhood experiences (ACE) and unmet dental needs among children aged 0 to 17 in Ohio. We utilized cross-sectional data from the 2021 Ohio Medicaid Assessment Survey to assess the dental needs of children. ACE scores, dental insurance status, and developmental disability status were analyzed using multivariable logistic regression to identify their potential association with parental-reported unmet dental needs. The weighted sample represented 2,752,222 children in Ohio. Over half reported zero ACEs (55.8%) and no dental needs (56.1%). Approximately 1 in 9 lacked dental insurance (11.1%), and 1 in 10 had a developmental disability (9.9%). Children with one to three ACEs had three times the odds of unmet dental needs compared to children with zero ACEs (OR = 3.20; 95%CI [2.10, 4.89]), and children with four or more ACEs had eight times the odds of unmet dental needs (OR = 8.78; 95%CI [5.26, 14.67]). Children lacking dental insurance had over six times higher odds of unmet dental needs compared to children with dental insurance (OR = 6.10; 95%CI [3.92, 9.49]). The presence of developmental disability status did not moderate the presence of unmet dental needs; however, the lack of dental insurance status significantly moderated the association between ACEs and unmet dental needs. Insurance status, not developmental disability, moderated the association between ACEs and unmet dental needs among children in Ohio. Efforts to ensure continuous access to dental insurance are warranted.

Interaction between Fokl polymorphism and vitamin D deficiency in the symptoms of mental disorders in adults: a population-based study

Mental disorders are intricate and multifaceted and encompass social, economic, environmental, and biological factors. This study aimed to explore the potential association between vitamin D deficiency and anxiety and depression symptoms in adults, considering the role of the vitamin D receptor gene polymorphism FokI (rs2228570). This was a population-based cross-sectional study with stratified and cluster sampling, evaluating anxiety symptoms (AS) and depression symptoms (DS) in 1637 adults. Vitamin D levels were measured using electrochemiluminescence and were considered deficient when < 20 ng/mL in a healthy population or < 30 ng/mL in at-risk groups. Genotyping was performed using real-time polymerase chain reaction with TaqMan probes. The prevalence rates of AS, DS, and vitamin D deficiency were 23.5%, 15.8%, and 30.9%, respectively. No direct association was observed between vitamin D deficiency and AS or DS. However, interaction analysis revealed a combined effect of vitamin D deficiency and FokI for DS but not for AS. Individuals with vitamin deficiency and one or two copies of the altered allele of the FokI exhibited a higher prevalence of DS than individuals homozygous for the wild-type allele and vitamin D sufficiency. The interaction between vitamin D deficiency and the FokI polymorphism was associated with DS.

Evaluating cardiac disorders associated with triazole antifungal agents based on the US Food and Drug Administration Adverse Event reporting system database.

Triazole antifungal agents are widely used to treat and prevent systemic mycoses. With wide clinical use, the number of reported adverse events has gradually increased. The aim of this study was to analyze the cardiac disorders associated with TAAs (fluconazole, voriconazole, itraconazole, posaconazole and isavuconazole) based on data from the US Food and Drug Administration Adverse Event Reporting System FDA Adverse Event Reporting System. Data were extracted from the FAERS database between the first quarter of 2004 and third quarter of 2022. The clinical characteristics in TAA-associated cardiac AE reports were analyzed. Disproportionality analysis was performed to evaluate the potential association between AEs and TAAs using the reporting odds ratio (ROR) and proportional reporting ratio (PRR). Among 10,178,522 AE reports, 1719 reports were TAA-associated cardiac AEs as primary suspect drug. Most reports were related to fluconazole (38.34%), voriconazole (28.56%) and itraconazole (26.76%). Itraconazole (N = 195, 42.39%) and isavuconazole (N = 2, 14.29%) had fewer serious outcome events than three other drugs including fluconazole, voriconazole, and posaconazole. 13, 11, 26, 5 and 1 signals were detected for fluconazole, voriconazole, itraconazole, posaconazole and isavuconazole, respectively. The number of new signals unrecorded in the drug label was 9, 2, 13, 2 and 0 for fluconazole, voriconazole, itraconazole, posaconazole and isavuconazole, respectively. Isavuconazole might be the safest of the five TAAs for cardiac AEs. TAA-associated cardiac disorders may result in serious adverse outcomes. Therefore, in addition to AEs on the drug label, we should pay attention to new AEs unrecorded on the drug label during the clinical use of TAAs.

Immune Checkpoint Inhibitors and Male Fertility: Should Fertility Preservation Options Be Considered before Treatment?

In recent years, immune checkpoint inhibitors (ICIs) have become a viable option for many cancer patients, including specific subgroups of pediatric patients. Despite their efficiency in treating different types of cancer, ICIs are responsible for a number of immune-related adverse events, including inflammatory toxicities, that can affect several organs. However, our knowledge of the impact of ICIs on the testis and male fertility is limited. It is possible that ICI treatment affects testicular function and spermatogenesis either directly or indirectly (or both). Treatment with ICIs may cause increased inflammation and immune cell infiltration within the seminiferous tubules of the testis, disturbing spermatogenesis or testosterone deficiency (primary hypogonadism). Additionally, the interference of ICIs with the hypothalamic-pituitary-gonadal axis may alter testosterone production, affecting testicular function (secondary hypogonadism) and spermatogenesis. This review provides an overview of the available evidence on the potential association between ICIs and the disruption of spermatogenesis, with special focus on ICIs targeting cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), programmed death protein 1 (PD-1) and programmed death-ligand 1 (PD-L1). Moreover, it highlights the need for further investigations and encourages the discussion of associated risks and fertility-preservation considerations between clinicians and patients.

Betanin Attenuates Epigenetic Mechanisms and UV-Induced DNA Fragmentation in HaCaT Cells: Implications for Skin Cancer Chemoprevention.

Dermal photoaging refers to the skin's response to prolonged and excessive ultraviolet (UV) exposure, resulting in inflammation, changes to the tissue, redness, swelling, and discomfort. Betanin is the primary betacyanin in red beetroot (Beta vulgaris) and has excellent antioxidant properties. Yet, the specific molecular mechanisms of betanin in HaCaT cells have not been fully clarified. The objective of this study was to investigate the activity of betanin and the underlying mechanisms in HaCaT cells; furthermore, in this study, we explored the protective effect of various concentrations of betanin against UVB irradiation on HaCaT cells. Additionally, we assessed its influence on the transcription of various epigenetic effectors, including members of the DNA methyltransferase (DNMT) and histone deacetylase (HDAC) families. Our findings demonstrate a notable downregulation of genes in HaCaT cells, exhibiting diverse patterns upon betanin intake. We considered the involvement of DNMT and HDAC genes in distinct stages of carcinogenesis and the limited exploration of the effects of daily exposure dosages. Our results indicate that betanin may protect the skin from damage caused by UV exposure. Further investigation is essential to explore these potential associations.