Artificial intelligence as a prediction tool for orthognathic surgery assessment.

INTRODUCTION: An ideal orthodontic treatment involves qualitative and quantitative measurements of dental and skeletal components to evaluate patients' discrepancies, such as facial, occlusal, and functional characteristics. Deciding between orthodontics and orthognathic surgery remains challenging, especially in borderline patients. Advances in technology are aiding clinical decisions in orthodontics. The increasing availability of data and the era of big data enable the use of artificial intelligence to guide clinicians' diagnoses. This study aims to test the capacity of different machine learning (ML) models to predict whether orthognathic surgery or orthodontics treatment is required, using soft and hard tissue cephalometric values. METHODS: A total of 920 lateral radiographs from patients previously treated with either conventional orthodontics or in combination with orthognathic surgery were used, comprising n = 558 Class II and n = 362 Class III patients, respectively. Thirty-two measures were obtained from each cephalogram at the initial appointment. The subjects were randomly divided into training (n = 552), validation (n = 183), and test (n = 185) datasets, both as an entire sample and divided into Class II and Class III sub-groups. The extracted data were evaluated using 10 machine learning models and by a four-expert panel consisting of orthodontists (n = 2) and surgeons (n = 2). RESULTS: The combined prediction of 10 models showed top-ranked performance in the testing dataset for accuracy, F1-score, and AUC (entire sample: 0.707, 0.706, 0.791; Class II: 0.759, 0.758, 0.824; Class III: 0.822, 0.807, 0.89). CONCLUSIONS: The proposed combined 10 ML approach model accurately predicted the need for orthognathic surgery, showing better performance in Class III patients.

A case report of sustained remission after radiotherapy combined with ICI in NEPC with primary drug resistance to chemotherapy.

Advanced prostate cancer (PCa) is usually treated initially with androgen deprivation therapy (ADT). Although they experience a period of disease regression, most patients progress to metastatic castration-resistant prostate cancer (mCRPC). Patients with mCRPC now have an unprecedented number of approved treatment options, including chemotherapies, hormone therapies, targeted therapies, etc. However, the improvement of overall survival (OS) in patients with mCRPC and its special subtype neuroendocrine prostate cancer (NEPC) is limited. In recent years, with the use of immune checkpoint inhibitors (ICIs), such as PD1/PDL1 and CTLA4 inhibitors, immunotherapy has once again become a promising treatment choice to stimulate antitumor immunity. However, the efficacy of NEPC receiving ICI has not been reported. Here, we describe a patient with mCRPC who developed primary resistance to current endocrine and chemotherapy regimens and progressed to mCRPC with NEPC as the main component, showing a significant and lasting response to PD1 monoclonal antibody combined with radiotherapy.

Exploring causality with biliary atresia at different levels: two-sample Mendelian randomization study.

Background: In recent years, Mendelian randomization (MR) has been widely used to infer causality of related disease risk exposures. However, this strategy has not been applied to biliary atresia (BA). Methods: Genome-wide association studies (GWAS) data of 41 inflammatory cytokines, 731 immune cell traits, and 1400 metabolites were obtained from public databases as exposure factors. The outcome information was obtained from a GWAS meta-analysis of 499 children with BA and 1928 normal controls. Inverse variance weighting was the primary causality analysis. Cochran Q-test, MR-Egger intercept, MR pleiotropy residual sum and outlier, and 'leave-one-out' analyses were used for sensitivity analysis. Reverse MR, MR-Steiger, and Linkage Disequilibrium Score were used to exclude the effects of reverse causality, genetic association, and linkage disequilibrium. Results: MR results showed that a total of seven traits had potential causal relationships with BA, including three inflammatory cytokines: eotaxin (odds ratio (OR)=1.45, 95% confidence interval (CI): 1.08 to 1.95, p FDR=0.18), G-CSF (OR=4.21, 95% CI: 1.75 to 10.13, p FDR=0.05) and MCP-1/MCAF (OR=1.53, 95% CI: 1.12 to 2.10, p FDR=0.14); three immune cell traits: CD8dim NKT/T cells ratio (OR=0.59, 95% CI: 0.45 to 0.77, p FDR=0.06), CD8dim NKT counts (OR=0.58, 95% CI: 0.43 to 0.78, p FDR=0.06), CD8dim NKT/lymphocyte ratio (OR=0.63, 95% CI: 0.49 to 0.81, p FDR=0.06); one metabolite: X-12261 levels (OR=2.86, 95% CI: 1.73 to 4.74, p FDR=0.06). Conclusions: In this study, eotaxin, G-CSF, MCP-1/MCAF, and X-12261 levels were shown to be risk factors for BA. However, CD8dim NKT/T cells ratio, CD8dim NKT counts, and CD8dim NKT/lymphocyte ratio were protective factors for BA. These findings provided a promising genetic basis for the etiology, diagnosis, and treatment of BA.

Acute exposure to tris(2,4-di-tert-butylphenyl)phosphate elicits cardiotoxicity in zebrafish (Danio rerio) larvae via inducing ferroptosis.

Tris(2,4-di-tert-butylphenyl)phosphate (AO168 =O), a novel organophosphate ester, is prevalent and abundant in the environment, posing great exposure risks to ecological and public health. Nevertheless, the toxicological effects of AO168 =O remain entirely unknown to date. The results in this study indicated that acute exposure to AO168 =O at 10 and 100 µg/L for 5 days obviously impaired cardiac morphology and function of zebrafish larvae, as proofed by decreased heartbeat, stroke volume, and cardiac output and the occurrence of pericardial edema and ventricular hypertrophy. Transcriptomics, polymerase chain reaction, and molecular docking revealed that the strong interaction of AO168 =O and transferrin receptor 1 activated the transportation of ferric iron into intracellular environment. The release of free ferrous ion to cytoplasmic iron pool also contributed to the iron overload in heart region, thus inducing ferroptosis in larvae via generation of excessive reactive oxygen species, glutathione peroxidase 4 inhibition, glutathione depletion and lipid peroxidation. Ferroptosis inhibitor (Fer-1) co-exposure effectively relieved the cardiac dysfunctions of zebrafish, verifying the dominant role of ferroptosis in the cardiotoxicity caused by AO168 =O. This research firstly reported the adverse impact and associated mechanisms of AO168 =O in cardiomyogenesis of vertebrates, underlining the urgency of concerning the health risks of AO168 =O.

Systematic investigation of genetically determined plasma and urinary metabolites to discover potential interventional targets for colorectal cancer.

BACKGROUND: We aimed to identify plasma and urinary metabolites related to colorectal cancer (CRC) risk and elucidate their mediator role in the associations between modifiable risk factors and CRC. METHODS: Metabolite quantitative trait loci were derived from two published metabolomics genome-wide association studies (GWASs), and summary-level data were extracted for 651 plasma metabolites and 208 urinary metabolites. Genetic associations with CRC were obtained from a large-scale GWAS meta-analysis (100,204 cases; 154,587 controls) and the FinnGen cohort (4,957 cases; 304,197 controls). Mendelian randomization (MR) and colocalization analyses were performed to evaluate the causal roles of metabolites in CRC. Druggability evaluation was employed to prioritize potential therapeutic targets. Multivariable MR and mediation estimation were conducted to elucidate the mediating effects of metabolites on the associations between modifiable risk factors and CRC. RESULTS: The study identified 30 plasma metabolites and four urinary metabolites for CRC. Plasma sphingomyelin and urinary lactose, which were positively associated with CRC risk, could be modulated by drug interventions (ie, Olipudase alfa, Tilactase). Thirteen modifiable risk factors were associated with nine metabolites and eight of these modifiable risk factors were associated with CRC risk. These nine metabolites mediated the effect of modifiable risk factors (Actinobacteria, BMI, waist-hip ratio, fasting insulin, smoking initiation) on CRC. CONCLUSION: This study identified key metabolite biomarkers associated with CRC and elucidated their mediator roles in the associations between modifiable risk factors and CRC. These findings provide new insights into the etiology and potential therapeutic targets for CRC and the etiological pathways of modifiable environmental factors with CRC.

Advancements in PSMA ligand radiolabeling for diagnosis and treatment of prostate cancer: a systematic review.

Prostate cancer(PCa), a leading global health concern, profoundly impacts millions of men worldwide. Progressing through two stages, it initially develops within the prostate and subsequently extends to vital organs such as lymph nodes, bones, lungs, and the liver. In the early phases, castration therapy is often employed to mitigate androgen effects. However, when prostate cancer becomes resistant to this treatment, alternative strategies become imperative. As diagnostic and treatment methodologies for prostate cancer continually advance, radioligand therapy (RLT) has emerged as a promising avenue, yielding noteworthy outcomes. The fundamental principle of RLT involves delivering radionuclide drugs to cancerous lesions through specific carriers or technologies. Subsequently, these radionuclide drugs release radioactive energy, facilitating the destruction of cancer cell tissues. At present, the positron emission tomography (PET) targeting PSMA has been widely developed for the use of diagnosis and staging of PCa. Notably, FDA-approved prostate-specific membrane antigen (PSMA) targeting agents, such as 68Ga-PSMA-11 and 177Lu-PSMA-617, represent significant milestones in enhancing diagnostic precision and therapeutic efficacy. This review emphasizes the current research status and outcomes of various radionuclide-labeled PSMA ligands. The objective is to provide valuable insights for the continued advancement of diagnostic and therapeutic approaches in the realm of prostate cancer.

Elevated DAS28-ESR in patients with rheumatoid arthritis who have comorbid fibromyalgia is associated more with tender joint counts than with patient global assessment or swollen joint counts: implications for assessment of inflammatory activity.

OBJECTIVES: More than 20% of rheumatoid arthritis (RA) patients have comorbid fibromyalgia (FM+), which may elevate DAS28-ESR (disease activity score 28-erythrocyte sedimentation rate) and other indices, resulting in challenges to assess inflammatory disease activity. Although several reports indicate that elevated patient global assessment (PATGL) may elevate DAS28 in the absence of inflammatory activity, less information is available concerning the other three components, tender joint count (TJC), swollen joint count (SJC), and erythrocyte sedimentation rate (ESR), to possibly elevate DAS28 in FM+ vs. FM- RA patients. METHODS: A PubMed search identified 14 reports which presented comparisons of DAS28-ESR and its four components in RA FM+ vs. FM- groups. Median DAS28, component arithmetic differences, pooled effect sizes and 95% confidence intervals were analysed in the FM+ vs. FM- groups. RESULTS: In FM+ vs. FM- groups, median DAS28 was 5.3 vs. 4.2, SJC 4.0 vs. 3.0, TJC 13.2 vs. 5.3, PATGL 61.6 vs. 39.9, ESR 26.3 vs. 26.5. DAS28-ESR was classified as "high" (>5.1) in 11/14 FM+ groups and "moderate" (3.2-5.1) in all 14 FM- groups. Effect sizes in FM+ vs. FM- groups for DAS28-ESR, SJC, TJC, PATGL, and ESR were large (≥0.8) in 10/14, 1/13, 12/13, 7/13, and 1/13 comparisons, respectively, and pooled effect sizes 0.84 (0.3, 1.4), 0.33 (-0.4, 1.0), 1.27 (0.01, 2.5), 0.91 (-0.6, 2.4), and 0.07 (-0.6, 0.7), respectively. CONCLUSIONS: DAS28-ESR is elevated significantly in FM+ vs. FM- RA patients; pooled effect sizes were highest for TJC, followed by PATGL, SJC and ESR. The findings appear relevant to response and remission criteria, treat-to-target, and general management of RA.

FPLS-DC: functional partial least squares through distance covariance for imaging genetics.

MOTIVATION: Imaging genetics integrates imaging and genetic techniques to examine how genetic variations influence the function and structure of organs like the brain or heart, providing insights into their impact on behavior and disease phenotypes. The use of organ-wide imaging endophenotypes has increasingly been used to identify potential genes associated with complex disorders. However, analyzing organ-wide imaging data alongside genetic data presents two significant challenges: high dimensionality and complex relationships. To address these challenges, we propose a novel, nonlinear inference framework designed to partially mitigate these issues. RESULTS: We propose a functional partial least squares through distance covariance (FPLS-DC) framework for efficient genome wide analyses of imaging phenotypes. It consists of two components. The first component utilizes the FPLS-derived base functions to reduce image dimensionality while screening genetic markers. The second component maximizes the distance correlation between genetic markers and projected imaging data, which is a linear combination of the FPLS-basis functions, using simulated annealing algorithm. In addition, we proposed an iterative FPLS-DC method based on FPLS-DC framework, which effectively overcomes the influence of inter-gene correlation on inference analysis. We efficiently approximate the null distribution of test statistics using a gamma approximation. Compared to existing methods, FPLS-DC offers computational and statistical efficiency for handling large-scale imaging genetics. In real-world applications, our method successfully detected genetic variants associated with the hippocampus, demonstrating its value as a statistical toolbox for imaging genetic studies. AVAILABILITY AND IMPLEMENTATION: The FPLS-DC method we propose opens up new research avenues and offers valuable insights for analyzing functional and high-dimensional data. In addition, it serves as a useful tool for scientific analysis in practical applications within the field of imaging genetics research. The R package FPLS-DC is available in Github: https://github.com/BIG-S2/FPLSDC.

Living Synthelectronics: A New Era for Bioelectronics Powered by Synthetic Biology.

Bioelectronics, which converges biology and electronics, has attracted great attention due to their vital applications in human-machine interfaces. While traditional bioelectronic devices utilize nonliving organic and/or inorganic materials to achieve flexibility and stretchability, a biological mismatch is often encountered because human tissues are characterized not only by softness and stretchability but also by biodynamic and adaptive properties. Recently, a notable paradigm shift has emerged in bioelectronics, where living cells, and even viruses, modified via gene editing within synthetic biology, are used as core components in a new hybrid electronics paradigm. These devices are defined as "living synthelectronics," and they offer enhanced potential for interfacing with human tissues at informational and substance exchange levels. In this Perspective, the recent advances in living synthelectronics are summarized. First, opportunities brought to electronics by synthetic biology are briefly introduced. Then, strategic approaches to designing and making electronic devices using living cells/viruses as the building blocks, sensing components, or power sources are reviewed. Finally, the challenges faced by living synthelectronics are raised. It is believed that this paradigm shift will significantly contribute to the real integration of bioelectronics with human tissues.

Deuteration-enhanced neutron contrasts to probe amorphous domain sizes in organic photovoltaic bulk heterojunction films.

An organic photovoltaic bulk heterojunction comprises of a mixture of donor and acceptor materials, forming a semi-crystalline thin film with both crystalline and amorphous domains. Domain sizes critically impact the device performance; however, conventional X-ray scattering techniques cannot detect the contrast between donor and acceptor materials within the amorphous intermixing regions. In this study, we employ neutron scattering and targeted deuteration of acceptor materials to enhance the scattering contrast by nearly one order of magnitude. Remarkably, the PM6:deuterated Y6 system reveals a new length scale, indicating short-range aggregation of Y6 molecules in the amorphous intermixing regions. All-atom molecular dynamics simulations confirm that this short-range aggregation is an inherent morphological advantage of Y6 which effectively assists charge extraction and suppresses charge recombination as shown by capacitance spectroscopy. Our findings uncover the amorphous nanomorphology of organic photovoltaic thin films, providing crucial insights into the morphology-driven device performance.

Applications of FAPI PET/CT in the diagnosis and treatment of breast and the most common gynecologic malignancies: a literature review.

The fibroblast activating protein (FAP) is expressed by some fibroblasts found in healthy tissues. However, FAP is overexpressed in more than 90% of epithelial tumors, including breast and gynecological tumors. As a result, the FAP ligand could be used as a target for diagnosis and treatment purposes. Positron emission tomography/computed tomography (PET/CT) is a hybrid imaging technique commonly used to locate and assess the tumor's molecular and metabolic functions. PET imaging involves the injection of a radiotracer that tends to accumulate more in metabolically active lesions such as cancer. Several radiotracers have been developed to target FAP in PET/CT imaging, such as the fibroblast-activation protein inhibitor (FAPI). These tracers bind to FAP with high specificity and affinity, allowing for the non-invasive detection and quantification of FAP expression in tumors. In this review, we discussed the applications of FAPI PET/CT in the diagnosis and treatment of breast and the most common gynecologic malignancies. Radiolabeled FAPI can improve the detection, staging, and assessment of treatment response in breast and the most common gynecologic malignancies, but the problem with normal hormone-responsive organs remains insurmountable. Compared to the diagnostic applications of FAPI, further research is needed for future therapeutic applications.

Safety and Efficacy of LVIS Jr Stent-assisted Coiling of Intracranial Aneurysms in Small-diameter Parent Arteries : A Single-center Experience.

OBJECTIVE: To investigate the safety and efficacy of LVIS Jr stent-assisted coiling (SAC) of intracranial aneurysms (IAs) in small-diameter parent arteries and determine the factors influencing incomplete aneurysm occlusion. MATERIAL AND METHODS: Clinical and imaging data of 130 patients with IAs in small-diameter parent arteries that were treated with LVIS Jr SAC were retrospectively analyzed. Stent apposition was evaluated by high-resolution flat detector CT, and aneurysm embolization density was evaluated using 2D-DSA. Perioperative complications were recorded. Multivariate logistic regression analyses were performed to determine possible factors for incomplete aneurysm occlusion. RESULTS: In this study, 130 patients (60 and 70 patients with ruptured and unruptured aneurysms, respectively) were successfully treated with LVIS Jr SAC. Immediate digital subtraction angiography (DSA) showed that the aneurysm occlusion was Raymond-Roy class I, II, IIIa, and IIIb in 93 (71.5%), 24 (18.5%), 8 (6.2%), and 5 (3.8%) cases, respectively. There were three cases of acute in-stent thrombosis and two cases of severe vasospasm observed during the perioperative period. The 6­month follow-up angiograms indicated that complete aneurysm occlusion in 122 patients was 79.5% (97/122). Multivariate logistic regression analyses showed that an aneurysm size > 10.0 mm, parent artery mean diameter < 2.0 mm, and incomplete stent apposition at the aneurysm neck were possible risk factors for incomplete aneurysm occlusion. CONCLUSION: The LVIS Jr SAC is effective for managing IAs in small-diameter parent arteries. An aneurysm size > 10.0 mm, parent artery mean diameter < 2.0 mm, and incomplete stent apposition at the aneurysm neck are possible risk factors for incomplete aneurysm occlusion.

Sustainable Electrosynthesis of Cyclohexanone Oxime through Nitrate Reduction on a Zn-Cu Alloy Catalyst.

Cyclohexanone oxime is an important precursor for Nylon-6 and is typically synthesized via the nucleophilic addition-elimination of hydroxylamine with cyclohexanone. Current technologies for hydroxylamine production are, however, not environment-friendly due to the requirement of harsh reaction conditions. Here, we report an electrochemical method for the one-pot synthesis of cyclohexanone oxime under ambient conditions with aqueous nitrate as the nitrogen source. A series of Zn-Cu alloy catalysts are developed to drive the electrochemical reduction of nitrate, where the hydroxylamine intermediate formed in the electroreduction process can undergo a chemical reaction with the cyclohexanone present in the electrolyte to produce the corresponding oxime. The best performance is achieved on a Zn93Cu7 electrocatalyst with a 97% yield and a 27% Faradaic efficiency for cyclohexanone oxime at 100 mA/cm2. By analyzing the catalytic activities/selectivities of the different Zn-Cu alloys and conducting in-depth mechanistic studies via in situ Raman spectroscopy and theoretical calculations, we demonstrate that the adsorption of nitrogen species plays a central role in catalytic performance. Overall, this work provides an attractive strategy to build the C-N bond in oxime and drive organic synthesis through electrochemical nitrate reduction, while highlighting the importance of controlling surface adsorption for product selectivity in electrosynthesis.

PROMIS-29 in rheumatoid arthritis patients who screen positive or negative for fibromyalgia on MDHAQ FAST4 (fibromyalgia assessment screening tool) or 2011 fibromyalgia criteria.

BACKGROUND: PROMIS-29 T-scores query health-related quality of life (HRQL) in 7 domains, physical function, pain, fatigue, anxiety, depression, sleep quality, and social participation, to establish population norms. An MDHAQ (multidimensional health assessment questionnaire) scores these 7 domains and includes medical information such as a FAST4 (fibromyalgia assessment screening tool) index. We analyzed PROMIS-29 T-scores in rheumatoid arthritis (RA) patients vs population norms and for positive vs negative fibromyalgia (FM) screens and compared PROMIS-29 T-scores to MDHAQ scores to assess HRQL. METHODS: A cross-sectional study was performed at one routine visit of 213 RA patients, who completed MDHAQ, PROMIS-29, and reference 2011 FM Criteria. PROMIS-29 T-scores were compared in RA vs population norms and in FM+ vs FM- RA patients, based on MDHAQ/FAST4 and reference criteria. Possible associations between PROMIS-29 T-scores and corresponding MDHAQ scores were analyzed using Spearman correlations and multiple regressions. RESULTS: Median PROMIS-29 T-scores indicated clinically and statistically significantly poorer status in 26-29% FM+ vs FM- RA patients, with larger differences than in RA patients vs population norms for 6/7 domains. MDHAQ scores were correlated significantly with each of 7 corresponding PROMIS-29 domains (|rho|≥0.62, p<0.001). Linear regressions explained 55-73% of PROMIS-29 T-score variation by MDHAQ scores and 56%-70% of MDHAQ score variation by PROMIS-29 T-scores. CONCLUSIONS: Scores for 7 PROMIS-29 domains and MDHAQ were highly correlated. The MDHAQ is effective to assess HRQL and offers incremental medical information, including FAST4 screening. The results indicate the importance of assessing comorbidities such as fibromyalgia screening in interpreting PROMIS-29 T-scores.

Interactive effects of grassland utilization and climatic factors govern the plant diversity-soil C relationship in steppe of North China.

The relationship between plant diversity and the ecosystem carbon pool is important for understanding the role of biodiversity in regulating ecosystem functions. However, it is not clear how the relationship between plant diversity and soil carbon content changes under different grassland use patterns. In a 3-year study from 2013 to 2015, we investigated plant diversity and soil total carbon (TC) content of grasslands in northern China under different grassland utilization methods (grazing, mowing, and enclosure) and climatic conditions. Shannon-Wiener and Species richness index of grassland were significantly decreased by grazing and mowing. Plant diversity was positively correlated with annual precipitation (AP) and negatively correlated with annual mean temperature (AMT). AP was the primary regulator of plant diversity. Grazing and mowing decreased TC levels in grasslands compared with enclosures, especially in topsoil (0-20 cm). The average TC content was decreased by 58 % and 36 % in the 0-10 cm soil layer, while it was decreased by 68 % and 39 % in 10-20 cm soil layer. TC was positively correlated with AP and negatively correlated with AMT. Principal component analysis (PCA) showed that plant diversity was positively correlated with soil TC, and the correlation decreased with an increase in the soil depth. Overall, this study provides a theoretical basis for predicting soil carbon storage in grasslands under human disturbances and climate change impacts.

A comprehensive patient-specific prediction model for temporomandibular joint osteoarthritis progression.

Temporomandibular joint osteoarthritis (TMJ OA) is a prevalent degenerative disease characterized by chronic pain and impaired jaw function. The complexity of TMJ OA has hindered the development of prognostic tools, posing a significant challenge in timely, patient-specific management. Addressing this gap, our research employs a comprehensive, multidimensional approach to advance TMJ OA prognostication. We conducted a prospective study with 106 subjects, 74 of whom were followed up after 2 to 3 y of conservative treatment. Central to our methodology is the development of an innovative, open-source predictive modeling framework, the Ensemble via Hierarchical Predictions through Nested cross-validation tool (EHPN). This framework synergistically integrates 18 feature selection, statistical, and machine learning methods to yield an accuracy of 0.87, with an area under the ROC curve of 0.72 and an F1 score of 0.82. Our study, beyond technical advancements, emphasizes the global impact of TMJ OA, recognizing its unique demographic occurrence. We highlight key factors influencing TMJ OA progression. Using SHAP analysis, we identified personalized prognostic predictors: lower values of headache, lower back pain, restless sleep, condyle high gray level-GL-run emphasis, articular fossa GL nonuniformity, and long-run low GL emphasis; and higher values of superior joint space, mouth opening, saliva Vascular-endothelium-growth-factor, Matrix-metalloproteinase-7, serum Epithelial-neutrophil-activating-peptide, and age indicate recovery likelihood. Our multidimensional and multimodal EHPN tool enhances clinicians' decision-making, offering a transformative translational infrastructure. The EHPN model stands as a significant contribution to precision medicine, offering a paradigm shift in the management of temporomandibular disorders and potentially influencing broader applications in personalized healthcare.

A Comparison of Statistical Methods to Construct Confidence Intervals and Fiducial Intervals for Measures of Health Disparities.

Health disparities are differences in health status across different socioeconomic groups. Classical methods, e.g., the Delta method, have been used to estimate the standard errors of estimated measures of health disparities and to construct confidence intervals for these measures. However, the confidence intervals constructed using the classical methods do not have good coverage properties for situations involving sparse data. In this article, we introduce three new methods to construct fiducial intervals for measures of health disparities based on approximate fiducial quantities. Through a comprehensive simulation study, We compare the empirical coverage properties of the proposed fiducial intervals against two Monte Carlo simulation-based methods-utilizing either a truncated Normal distribution or the Gamma distribution-as well as the classical method. The findings of the simulation study advocate for the adoption of the Monte Carlo simulation-based method with the Gamma distribution when a unified approach is sought for all health disparity measures.

The Long Non-Coding RNA NR3C2-8:1 Promotes p53-Mediated Apoptosis through the miR-129-5p/USP10 Axis in Amyotrophic Lateral Sclerosis.

Motor neuron degeneration in amyotrophic lateral sclerosis (ALS) is a form of apoptosis, but the mechanisms underlying this neuronal cell death remain unclear. Numerous studies demonstrate abnormally elevated and active p53 in the central nervous system of ALS patients. Activation of p53-regulated pro-apoptotic signaling pathways may trigger motor neuron death. We previously reported decreased expression of the long non-coding RNA NR3C2-8:1 (Lnc-NR3C) in leukocytes of ALS patients. Here, we show lnc-NR3C promotes p53-mediated cell death in ALS by upregulating USP10 and promoting lnc-NR3C-triggered p53 activation, resulting in cell death. Conversely, lnc-NR3C knockdown inhibited USP10-triggered p53 activation, thereby protecting cells against oxidative stress. As a competitive endogenous RNA, lnc-NR3C competitively binds miR-129-5p, regulating the usp10/p53 axis. Elucidating the link between Lnc-NR3C and the USP10/p53 axis in an ALS cell model reveals a role for long non-coding RNAs in activating apoptosis. This provides new therapeutic opportunities in ALS.

Identification and validation of supervariants reveal novel loci associated with human white matter microstructure.

As an essential part of the central nervous system, white matter coordinates communications between different brain regions and is related to a wide range of neurodegenerative and neuropsychiatric disorders. Previous genome-wide association studies (GWASs) have uncovered loci associated with white matter microstructure. However, GWASs suffer from limited reproducibility and difficulties in detecting multi-single-nucleotide polymorphism (multi-SNP) and epistatic effects. In this study, we adopt the concept of supervariants, a combination of alleles in multiple loci, to account for potential multi-SNP effects. We perform supervariant identification and validation to identify loci associated with 22 white matter fractional anisotropy phenotypes derived from diffusion tensor imaging. To increase reproducibility, we use United Kingdom (UK) Biobank White British (n = 30,842) data for discovery and internal validation, and UK Biobank White but non-British (n = 1927) data, Europeans from the Adolescent Brain Cognitive Development study (n = 4399) data, and Europeans from the Human Connectome Project (n = 319) data for external validation. We identify 23 novel loci on the discovery set that have not been reported in the previous GWASs on white matter microstructure. Among them, three supervariants on genomic regions 5q35.1, 8p21.2, and 19q13.32 have P-values lower than 0.05 in the meta-analysis of the three independent validation data sets. These supervariants contain genetic variants located in genes that have been related to brain structures, cognitive functions, and neuropsychiatric diseases. Our findings provide a better understanding of the genetic architecture underlying white matter microstructure.

Blood Eosinophil Percentage and Improved Sinus CT Score as Diagnostic Tools for ECRS.

Objective: Differentiating 2 types of chronic rhinosinusitis with nasal polyps (CRSwNP) is important for the treatment. The current diagnostic methods using single indicators, including peripheral blood eosinophils and traditional sinus computed tomography (CT) scores, are not accurate. In this study, we aimed to investigate the diagnostic value of combining peripheral blood eosinophils and improved sinus CT scores for eosinophic chronic rhinosinusitis (ECRS). Study Design: Retrospective cohort. Setting: Tertiary medical center. Methods: We conducted a study involving 81 patients with CRSwNP. Peripheral blood samples were collected from the non-ECRS and ECRS groups. Improved three-dimensional volume image analysis and Lund-Mackay scoring system were performed to quantify the thickening of sinus mucosa. Multivariate binary logistic regression analysis was carried out to detect the predictive value of the scoring indicators. For significant indexes, receiver operating characteristic (ROC) curve analysis was applied. Results: The ECRS group had higher levels of blood eosinophil percentage and count, ethmoid sinus score, total sinus score, the ratio of ethmoid sinus score and maxillary sinus score, and the difference between ethmoid and maxillary score, compared to the non-ECRS group (P < 0.05). Binary logistic regression analysis demonstrated that both blood eosinophil percentage and the improved E - M score (subtraction of ethmoid and maxillary sinus scores) were significant predictors of ECRS diagnosis (P < .01). ROC curve analysis indicated that the combination of improved E - M score and blood eosinophil percentage had a higher diagnostic value compared to either factor alone (area under the curve = 0.874). Conclusion: Our study suggested the combination of improved total ethmoid sinus-maxillary score and blood eosinophil percentage is more accurate in predicting the diagnosis of ECRS.