Characterization of ultrasonic vibration and polishing force in sapphire ultrasonic vibration-assisted flexible polishing: Insights from in-situ monitoring systems.

Sapphire ultrasonic vibration-assisted flexible polishing (UVAFP) is a promising technique for comprehensively improving the surface integrity of machined parts. The technique was performed on an ultra-precision machine tool with the in-situ monitoring systems in this paper, which aims to provide a new perspective for understanding the material removal mechanisms in the sapphire UVAFP process. A Taguchi L9 (43) orthogonal experiment was conducted to investigate the effects of feed distance, spindle speed, ultrasonic vibration (UV), and polishing time on the surface finish and material removal in the process. In addition, the effect of a polyurethane ball tool is not trivial. A single-factor experiment was conducted for exploring it. Based on a laser displacement measurement system and an acoustic emission sensor system, the characteristics of time-dependent ultrasonic amplitude and ultrasonic frequency for the sapphire UVAFP system were analyzed, with the effectiveness of UV demonstrated. Based on a three-component force measurement system, the characteristics of normal force and its relationship with process parameters and tool deformation were analyzed, with macro- and micro-level examined. In conclusion, this paper presents the characterization of UV and polishing force in the sapphire UVAFP process, providing novel insights into understanding the material removal mechanisms of sapphire and even more manufacturing problems.

[Current clinical application of glomerular filtration rate assessment methods in pediatric populations]. / 肾小球滤过率评估方法在儿童人群中的应用现状.

Glomerular filtration rate (GFR) is a critical indicator of renal function assessment, which exhibits age-dependency in children and may differ from adults under various disease conditions. In recent years, there has been a growing focus on GFR among scholars, with an increasing number of clinical studies dedicated to refining and optimizing GFR estimation to span all pediatric age groups. However, the methods and assessment equations for estimating GFR may vary under different disease conditions, affecting the accuracy and applicability of assessments. This article reviews the peculiarities of renal function in children, explores GFR measurement methods, and evaluates the application of various GFR assessment equations in pediatric clinical practice, providing a reference for clinical assessment of renal function in children.

Artificial intelligence for geoscience: Progress, challenges, and perspectives.

This paper explores the evolution of geoscientific inquiry, tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence (AI) and data collection techniques. Traditional models, which are grounded in physical and numerical frameworks, provide robust explanations by explicitly reconstructing underlying physical processes. However, their limitations in comprehensively capturing Earth's complexities and uncertainties pose challenges in optimization and real-world applicability. In contrast, contemporary data-driven models, particularly those utilizing machine learning (ML) and deep learning (DL), leverage extensive geoscience data to glean insights without requiring exhaustive theoretical knowledge. ML techniques have shown promise in addressing Earth science-related questions. Nevertheless, challenges such as data scarcity, computational demands, data privacy concerns, and the "black-box" nature of AI models hinder their seamless integration into geoscience. The integration of physics-based and data-driven methodologies into hybrid models presents an alternative paradigm. These models, which incorporate domain knowledge to guide AI methodologies, demonstrate enhanced efficiency and performance with reduced training data requirements. This review provides a comprehensive overview of geoscientific research paradigms, emphasizing untapped opportunities at the intersection of advanced AI techniques and geoscience. It examines major methodologies, showcases advances in large-scale models, and discusses the challenges and prospects that will shape the future landscape of AI in geoscience. The paper outlines a dynamic field ripe with possibilities, poised to unlock new understandings of Earth's complexities and further advance geoscience exploration.

Impact of multiple infections on risk of incident dementia according to subjective cognitive decline status: a nationwide population-based cohort study.

Background: The interrelation between infections, subjective cognitive decline (SCD), and dementia development is recognized, but not fully understood. This study explored the combined effect of specific infections and SCD on the risk of dementia. Objectives: To assess the influence of Helicobacter pylori, herpes simplex virus, varicella-zoster virus, and human papillomavirus on dementia risk in individuals with varying cognitive statuses, especially focusing on those with and without SCD. Methods: A cohort of 1,100,540 participants aged 66 years from the Korean National Health Insurance Service was divided into cognitively preserved (CP, n = 825,405) and SCD (n = 275,135) groups. This study analyzed the effects of single, dual, and triple infections on the risk of overall dementia, Alzheimer's disease (AD), and vascular dementia (VaD) using incidence rates and hazard ratios. Results: The SCD group consistently showed a doubled risk of dementia, particularly AD, regardless of the number of infections. In the initial data, both the presence and number of infections, especially in the CP group, were associated with an increased dementia incidence and risk; however, this correlation disappeared after adjusting for covariates, hinting at a possible protective effect. Conclusion: Our findings emphasize that, while SCD is a steadfast risk factor for dementia, the role of infections is layered, subject to various influences, and requires more comprehensive exploration to fully understand their impact on dementia development.

The dual role of glucocorticoid regeneration in inflammation at parturition.

Introduction: Fetal membrane inflammation is an integral event of parturition. However, excessive pro-inflammatory cytokines can impose threats to the fetus. Coincidentally, the fetal membranes express abundant 11ß-hydroxysteroid dehydrogenase 1 (11ß-HSD1), which generates biologically active cortisol to promote labor through induction of prostaglandin synthesis. Given the well-recognized anti-inflammatory actions of glucocorticoids, we hypothesized that cortisol regenerated in the fetal membranes might be engaged in restraining fetus-hazardous pro-inflammatory cytokine production for the safety of the fetus, while reserving pro-labor effect on prostaglandin synthesis to ensure safe delivery of the fetus. Methods: The hypothesis was examined in human amnion tissue and cultured primary human amnion fibroblasts as well as a mouse model. Results: 11ß-HSD1 was significantly increased in the human amnion in infection-induced preterm birth. Studies in human amnion fibroblasts showed that lipopolysaccharide (LPS) induced 11ß-HSD1 expression synergistically with cortisol. Cortisol completely blocked NF-κB-mediated pro-inflammatory cytokine expression by LPS, but STAT3-mediated cyclooxygenase 2 expression, a crucial prostaglandin synthetic enzyme, remained. Further studies in pregnant mice showed that corticosterone did not delay LPS-induced preterm birth, but alleviated LPS-induced fetal organ damages, along with increased 11ß-HSD1, cyclooxygenase 2, and decreased pro-inflammatory cytokine in the fetal membranes. Discussion: There is a feed-forward cortisol regeneration in the fetal membranes in infection, and cortisol regenerated restrains pro-inflammatory cytokine expression, while reserves pro-labor effect on prostaglandin synthesis. This dual role of cortisol regeneration can prevent excessive pro-inflammatory cytokine production, while ensure in-time delivery for the safety of the fetus.

Composition Characterization of Crossostephium chinense Leaf Essential Oil and Its Anti-Inflammatory Activity Mechanisms.

This study investigates the composition characteristics and anti-inflammatory activity mechanisms of the essential oil from the leaves of Crossostephium chinense. C. chinense is a perennial herb commonly found in East Asia, traditionally used to treat various ailments. The essential oil extracted through water distillation, primarily contains 1,8-cineole (13.73%), santolina triene (13.53%), and germacrene D (10.67%). Three compounds were identified from the essential oil, namely 1-acetoxy-2-(2-hydroxypropyl)-5-methylhex-3,5-diene, 1-acetoxy-isopyliden-hex-5-en-4-one, and chrysanthemyl acetate, with the first two being newly discovered compounds. Then, the essential oil of C. chinense exhibits significant anti-inflammatory effects on RAW264.7 macrophages, effectively inhibiting the production of NO and ROS, with the IC50 value of 10.3 µg/mL. Furthermore, the essential oil reduces the expression of pro-inflammatory cytokines such as TNF-α, IL-6, and IL-1ß. Mechanistic studies indicate that the essential oil affects the inflammatory response by inhibiting the expression of iNOS but has no significant impact on COX-2. Further analysis suggests that the essential oil may regulate the inflammatory response through the ERK protein in the MAPK pathway and IκBα in the NF-κB pathway, while also promoting the activity of the NRF2/HO-1 antioxidant pathway, enhancing the cell's antioxidant capacity, thereby achieving an effect of inhibiting the inflammatory response. These results highlight the potential application value of C. chinense leaf essential oil in the medical and healthcare fields.

Benchmarking reverse docking through AlphaFold2 human proteome.

Predicting the binding of ligands to the human proteome via reverse-docking methods enables the understanding of ligand's interactions with potential protein targets in the human body, thereby facilitating drug repositioning and the evaluation of potential off-target effects or toxic side effects of drugs. In this study, we constructed 11 reverse docking pipelines by integrating site prediction tools (PointSite and SiteMap), docking programs (Glide and AutoDock Vina), and scoring functions (Glide, Autodock Vina, RTMScore, DeepRMSD, and OnionNet-SFCT), and then thoroughly benchmarked their predictive capabilities. The results show that the Glide_SFCT (PS) pipeline exhibited the best target prediction performance based on the atomic structure models in AlphaFold2 human proteome. It achieved a success rate of 27.8% when considering the top 100 ranked prediction. This pipeline effectively narrows the range of potential targets within the human proteome, laying a foundation for drug target prediction, off-target assessment, and toxicity prediction, ultimately boosting drug development. By facilitating these critical aspects of drug discovery and development, our work has the potential to ultimately accelerate the identification of new therapeutic agents and improve drug safety.

Interactive computer-aided diagnosis on medical image using large language models.

Computer-aided diagnosis (CAD) has advanced medical image analysis, while large language models (LLMs) have shown potential in clinical applications. However, LLMs struggle to interpret medical images, which are critical for decision-making. Here we show a strategy integrating LLMs with CAD networks. The framework uses LLMs' medical knowledge and reasoning to enhance CAD network outputs, such as diagnosis, lesion segmentation, and report generation, by summarizing information in natural language. The generated reports are of higher quality and can improve the performance of vision-based CAD models. In chest X-rays, an LLM using ChatGPT improved diagnosis performance by 16.42 percentage points compared to state-of-the-art models, while GPT-3 provided a 15.00 percentage point F1-score improvement. Our strategy allows accurate report generation and creates a patient-friendly interactive system, unlike conventional CAD systems only understood by professionals. This approach has the potential to revolutionize clinical decision-making and patient communication.

Analyzing sex-specific differences in sleep quality, resilience, and biomarkers among older adults in the Gan-Dau Healthy Longevity Plan.

BACKGROUND: Limited knowledge exists regarding the interrelations between sleep quality and resilience within the demographic of healthy, community-residing middle-aged and older adults, with a particular dearth of information regarding sex-specific associations. This study aimed to examine the sex-specific associations between sleep quality, resilience, and biomarkers in community-dwelling middle-aged and older adults. METHODS: This cross-sectional study was conducted using data from the 2022 Gan-Dau Healthy Longevity Plan survey initiated by the locality-based community hospital, Taipei Municipal Gan-Dau Hospital (TMGDH). A total of 770 participants (240 men, 530 women) who met the inclusion criteria were included in the study. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), while resilience was measured using the Brief Resilience Scale (BRS). Patient demographic data, including age, education, marital status, and depression level, were also collected. The sex-specific associations between sleep quality and resilience were first examined using multivariate generalized linear models (GLMs). In addition, the associations between sleep quality, resilience, and selected biomarkers were examined using multivariate GLMs. RESULTS: Approximately 55% of men and 60% of women reported poor sleep quality. Individuals with good sleep quality had significantly lower levels of depressive symptoms (p=0.028 for men, p<0.001 for women) and fewer chronic conditions (p=0.0015 for men, p<0.001 for women). Notably, women in the "poor sleep quality" group exhibited higher proportions of low habitual sleep efficiency (35.9%) and frequent use of sleeping medications (23.2%), whereas the proportions were lower in men in the "poor sleep quality" group (29.8% and 9.9%, respectively). Good sleep quality was associated with better resilience in both men (mean BRS score: good sleep quality=25.1 [standard deviation (SD) 4.3] vs. poor sleep quality=23.4 [SD 4.7], p=0.044) and women (mean BRS score: good sleep quality=24.3 [SD 5.1] vs. poor sleep quality=22.3 [SD 5.4], p<0.001). After adjusting for depressive symptoms and chronic conditions, this association remained significant for men (p=0.022) and women (p=0.001). In addition, greater depressive symptoms were associated with poorer resilience in both sexes (p<0.001). No significant associations were noted between sleep quality or resilience and the selected biomarkers. CONCLUSION: This study highlights the association between sleep quality and resilience in older adults. Good sleep quality is related to better resilience, but greater depressive symptoms are also linked to poorer resilience in both sexes. Nevertheless, the low habitual sleep efficiency and frequent use of sleeping medications in women but not men with poor sleep quality highlight the need to explore sex-specific approaches to address the interplay of sleep quality, resilience and other demographic factors (such as depressive symptoms) in healthy aging.

Comparison of postoperative pain between InterTan and proximal femoral nail anti-rotation in femoral intertrochanteric fractures: a retrospective study.

OBJECTIVE: To compare the postoperative pain experienced by elderly patients with unstable trochanteric fractures treated with proximal femoral nail anti-rotation (PFNA) and InterTan Nail, focusing on identifying differences among this demographic. METHODS: A total of 40 elderly patients (age >80 years old) underwent treatment with either the PFNA Nail or InterTan Nail. Observational metrics included the Visual Analogue Scale (VAS) for pain, changes in implant position via X-ray, blood loss, fixation failures, and Harris Hip Scores (HHS) to assess complications and hip function at various time points. RESULTS: The study included 26 patients in the PFNA Nail group (Group A) and 26 patients in the InterTan Nail group (Group B). No significant differences were found in the main observational indicators between the two groups (all P>0.05). Both groups showed significant improvement in HHS post-surgery (all P<0.05). However, early post-operative pain scores were lower in the Group B (3.65±1.2) compared to Group A (5.5±0.9) (P<0.001). CONCLUSIONS: Despite different implant materials being used, outcomes in both groups were consistent and reliable among elderly patients. No significant differences were observed in terms of postoperative functional recovery, mortality, or complications between the groups. Notably, in the early postoperative period (3 days postoperatively), the Group B demonstrated significantly superior pain scores.

Three patients with new mutations in the EPCAM variant gene for congenital tufting enteropathy and a mutation review in China: a case report.

Background: Congenital tufting enteropathy (CTE) is a rare cause of intractable congenital diarrhea in children, always resulting in parenteral nutrition (PN) dependency. We aimed to report novel mutations in Chinese patients and to illustrate the clinical, histopathological, and molecular features of CTE in China. Case Description: We report three cases of CTE diagnosed with whole-exome sequencing (WES) and MOC31 [a monoclonal antibody of epithelial cell adhesion molecule (EPCAM)] immunohistochemistry. The main manifestations in the three patients were watery diarrhea and growth retardation. Upper endoscopy in three patients revealed villous atrophy of the duodenal mucosa. Histological examination revealed villus abnormalities and two patients with focal tufting. All of the three patients revealed a complete absence of EPCAM expression through MOC31 immunohistochemistry. Five novel mutations, including c.319delG, c.505_507delGAG, c.491+1G>C, c.60del (p.F20Lfs*17), and c.353G>A, in EPCAM were identified through molecular analysis. In our review, there were 18 different mutations in 11 patients from nine studies, with 12 mutations reported only once. In China, 73% of the patients were compound heterozygotes, and most of the pathogenic variants were in exon 3. All patients presented with congenital diarrhea and needed PN because of growth retardation, even when diarrhea was improved. Of the 11 patients, 3 (27%) died. Conclusions: CTE is rare and fatal, and lacks characteristic changes during endoscopy. Patients with CTE require early diagnosis via histological examination and genetic detection to improve survival.

In-situ nanozyme catalytic amplification coupled with a universal antibody orientation strategy based electrochemical immunosensor for AD-related biomarker.

An in-situ nanozyme signal tag combined with a DNA-mediated universal antibody-oriented strategy was proposed to establish a high-performance immunosensing platform for Alzheimer's disease (AD)-related biomarker detection. Briefly, a Zr-based metal-organic framework (MOF) with peroxidase (POD)-like activity was synthesized to encapsulating the electroactive molecule methylene blue (MB), and subsequently modified with a layer of gold nanoparticles on its surface. This led to the creation of double POD-like activity nanozymes surrounding the MB molecule to form a nanozyme signal tag. A large number of hydroxyl radicals were generated by the nanozyme signal tag with the help of H2O2, which catalyzed MB molecules in situ to achieve efficient signal amplification. Subsequently, a DNA-aptamer-mediated universal antibody-oriented strategy was proposed to enhance the binding efficiency for the antigen (target). Meanwhile, a poly adenine was incorporated at the end of the aptamer, facilitating binding to the gold electrode and providing anti-fouling properties due to the hydrophilicity of the phosphate group. Under optimal conditions, this platform was successfully employed for highly sensitive detection of AD-associated tau protein and BACE1, achieving limits of detection with concentrations of 3.34 fg/mL and 1.67 fg/mL, respectively. It is worth mentioning that in the tau immunosensing mode, 20 clinical samples from volunteers of varying ages were analyzed, revealing significantly higher tau expression levels in the blood samples of elderly volunteers compared to young volunteers. This suggests that the developed strategy holds great promise for early AD diagnosis.

Prognostic Hypoxia-Angiogenesis-Related Gene Signature in Hepatocellular Carcinoma, in Which HILPDA Contributes to Tumor Progression.

Objective: Hepatocellular carcinoma (HCC) is the predominant form of liver cancer. Hypoxia can be involved in HCC tumor growth, invasion and metastasis through inducing angiogenesis. Nevertheless, the assessment of the impact of hypoxia and angiogenesis on the prognosis of HCC remains inadequate. Methods: According to hypoxia-angiogenesis-related genes (HARGs) expression information and clinical data from patients within the Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort, we constructed a prognostic model (HARG-score) using bioinformatic tools. In addition to assessing the predictive ability of this prognostic model in both Liver Cancer-Riken-Japan (LIRI-JP) and GSE14520 cohorts, we analyzed the correlation between HARG-score and clinical characteristics, immune infiltration and immunotherapy efficacy. Moreover, we investigated the exact role and underlying mechanism of key HARGs through molecular experiments. Results: We constructed a 5-gene prognostic model HARG-score consisting of hypoxia-inducible lipid droplet-associated (HILPDA), erythropoietin (EPO), solute carrier family 2 member 1 (SLC2A1), proteasome subunit alpha type 7 (PSMA7) and cAMP responsive element-binding protein 1 (CREB1) through differentially expressed HARGs. The findings demonstrated that HARG-score was a good predictor of the prognosis of HCC patients from distinct cohorts and was correlated with clinical characteristics and immune infiltration. Furthermore, the HARG-score was identified as an independent prognostic factor. Lower HARG-score implied greater immunotherapy efficacy and better response. The expression and prognostic significance of these 5 genes were additionally validated in clinical data. In addition, experimental data revealed that the key gene HILPDA contributes to the progression of HCC through facilitating angiogenesis and affecting the expression of cytotoxic T-lymphocyte-associated protein 4 (CTLA4). Conclusion: HARG-score has promising applications in prognosis prediction of HCC patients, in which HILPDA may be a latent prognostic biomarker and therapeutic target, providing a foundation for further research and treatment of HCC.

Cholesterol suppresses AMFR-mediated PDL1 ubiquitination and degradation in HCC.

The degradation of proteasomes or lysosomes is emerging as a principal determinant of programmed death ligand 1 (PDL1) expression, which affects the efficacy of immunotherapy in various malignancies. Intracellular cholesterol plays a central role in maintaining the expression of membrane receptors; however, the specific effect of cholesterol on PDL1 expression in cancer cells remains poorly understood. Cholesterol starvation and stimulation were used to modulate the cellular cholesterol levels. Immunohistochemistry and western blotting were used to analyze the protein levels in the samples and cells. Quantitative real-time PCR, co-immunoprecipitation, and confocal co-localization assays were used for mechanistic investigation. A xenograft tumor model was constructed to verify these results in vivo. Our results showed that cholesterol suppressed the ubiquitination and degradation of PDL1 in hepatocellular carcinoma (HCC) cells. Further mechanistic studies revealed that the autocrine motility factor receptor (AMFR) is an E3 ligase that mediated the ubiquitination and degradation of PDL1, which was regulated by the cholesterol/p38 mitogenic activated protein kinase axis. Moreover, lowering cholesterol levels using statins improved the efficacy of programmed death 1 (PD1) inhibition in vivo. Our findings indicate that cholesterol serves as a signal to inhibit AMFR-mediated ubiquitination and degradation of PDL1 and suggest that lowering cholesterol by statins may be a promising combination strategy to improve the efficiency of PD1 inhibition in HCC.

Physics-Informed Inverse Design of Programmable Metasurfaces.

Emerging reconfigurable metasurfaces offer various possibilities for programmatically manipulating electromagnetic waves across spatial, spectral, and temporal domains, showcasing great potential for enhancing terahertz applications. However, they are hindered by limited tunability, particularly evident in relatively small phase tuning over 270°, due to the design constraints with time-intensive forward design methodologies. Here, a multi-bit programmable metasurface is demonstrated capable of terahertz beam steering facilitated by a developed physics-informed inverse design (PIID) approach. Through integrating a modified coupled mode theory (MCMT) into residual neural networks, the PIID algorithm not only significantly increases the design accuracy compared to conventional neural networks but also elucidates the intricate physical relations between the geometry and the modes. Without decreasing the reflection intensity, the method achieves the enhanced phase tuning as large as 300°. Additionally, the inverse-designed programmable beam steering metasurface is experimentally validated, which is adaptable across 1-bit, 2-bit, and tri-state coding schemes, yielding a deflection angle up to 68° and broadened steering coverage. The demonstration provides a promising pathway for rapidly exploring advanced metasurface devices, with potentially great impact on communication and imaging technologies.

Reduction of circulating IgE and allergens by a pH-sensitive antibody with enhanced FcγRIIb binding.

Allergen-crosslinked IgE triggers allergy by interacting with its receptor on basophils and mast cells. The anti-IgE monoclonal antibody omalizumab can alleviate allergy by competing with the receptor for IgE binding. However, along with neutralization, omalizumab also inhibits IgE degradation, which is clinically associated with high dose and total IgE accumulation problems. In this study, we have developed an IgE-eliminating antibody on the basis of omalizumab, which has pH-dependent Fabs and an Fc with high affinity for FcγRIIb. In mice, the antibody rapidly eliminated total serum IgE to baseline levels and caused lower free IgE levels than omalizumab. At low dosages, the antibody also exhibited favorable IgE elimination effects. In addition, the antibody can degrade the corresponding allergen with the removal of IgE, addressing the allergy from its source. Introduction of the M252Y/S254T/T256E (YTE) mutation into this antibody prolongs its serum half-life without reducing potency. Thus, this engineered antibody holds a promising therapeutic option for allergy patients. Mechanistic insights are also included in this study.

Transcranial direct current stimulation and neuronal functional connectivity in MCI: role of individual factors associated to AD.

Background: Alzheimer's disease (AD) encompasses a spectrum that may progress from mild cognitive impairment (MCI) to full dementia, characterized by amyloid-beta and tau accumulation. Transcranial direct current stimulation (tDCS) is being investigated as a therapeutic option, but its efficacy in relation to individual genetic and biological risk factors remains underexplored. Objective: To evaluate the effects of a two-week anodal tDCS regimen on the left dorsolateral prefrontal cortex, focusing on functional connectivity changes in neural networks in MCI patients resulting from various possible underlying disorders, considering individual factors associated to AD such as amyloid-beta deposition, APOE ϵ4 allele, BDNF Val66Met polymorphism, and sex. Methods: In a single-arm prospective study, 63 patients with MCI, including both amyloid-PET positive and negative cases, received 10 sessions of tDCS. We assessed intra- and inter-network functional connectivity (FC) using fMRI and analyzed interactions between tDCS effects and individual factors associated to AD. Results: tDCS significantly enhanced intra-network FC within the Salience Network (SN) and inter-network FC between the Central Executive Network and SN, predominantly in APOE ϵ4 carriers. We also observed significant sex*tDCS interactions that benefited inter-network FC among females. Furthermore, the effects of multiple modifiers, particularly the interaction of the BDNF Val66Met polymorphism and sex, were evident, as demonstrated by increased intra-network FC of the SN in female Met non-carriers. Lastly, the effects of tDCS on FC did not differ between the group of 26 MCI patients with cerebral amyloid-beta deposition detected by flutemetamol PET and the group of 37 MCI patients without cerebral amyloid-beta deposition. Conclusions: The study highlights the importance of precision medicine in tDCS applications for MCI, suggesting that individual genetic and biological profiles significantly influence therapeutic outcomes. Tailoring interventions based on these profiles may optimize treatment efficacy in early stages of AD.

Dementia Incidence in Survivors of Multiple Myeloma: A National Case-Control Study Conducted in Korea (The CAREMM-2106 Study).

BACKGROUND: Dementia, a growing global health issue, affects older adults and specific groups like long-term cancer survivors. The link between cancer survival and dementia is debated. Multiple myeloma (MM), a common blood cancer in older adults, is often linked with cognitive issues. This study investigated dementia incidence in long-term MM survivors using Korean national data. METHODS: A retrospective case-control study used data from the Korea National Health Insurance Service (KNHIS), covering about 50 million Koreans. Patients diagnosed with MM between 2009 and 2020 formed the case cohort, while the control cohort included matched individuals without MM using propensity-score matching. Analyzing baseline characteristics, comorbidities, and socioeconomic status, the primary outcome was dementia incidence identified via ICD-10 codes. Statistical methods included Kaplan-Meier plots, cause-specific and Fine-Gray subdistribution hazard models, and a 3-year landmark analysis for immortal time bias. RESULTS: The study included 33,864 patients, with 16,932 in each cohort. The overall cumulative dementia incidence was lower in the MM cohort compared to controls. However, in the first 3 years, MM patients had a higher dementia risk (HR: 1.711, 95% CI, 1.562-1.874) than controls. After 3 years, the risk significantly decreased (HR: 0.625, 95% CI, 0.560-0.696). Age-specific analysis showed a consistent pattern, particularly among MM patients aged 70-79, where dementia risk increased post-3 years. CONCLUSION: This study reveals a lower long-term dementia risk in MM survivors compared to non-MM individuals. Further prospective studies are needed to confirm these findings and explore the underlying mechanisms.

A cross-sectional study on predictors of patients' tinnitus severity.

Objective: To identify factors that influence the severity of tinnitus via a hierarchical multiple linear regression model. Methods: The study was a retrospective cross-sectional analysis. The study included 331 patients experiencing tinnitus as their primary concern, who visited Shanghai Changzheng Hospital of the Navy Medical University between 2019 and 2021. Data on general health status and disease characteristics were collected from all patients. With their consent, participants underwent audiological evaluatons and completed questionnaires to analyze the characteristics of their tinnitus and the factors influencing its severity. Results: The correlation analysis showed a positive relationship between tinnitus frequency, tinnitus loudness, SAS scores, and PSQI scores with THI scores (P < 0.05) among nine examined variables (gender, handedness, employment status, age, BMI, tinnitus frequency, tinnitus loudness, SAS scores, and PSQI scores). The variables that were extracted from the multiple regression were; for the constant; ß = -51.797, t = -4.484, P < 0.001, variable is significant; for the tinnitus loudness; ß = 0.161, t = 2.604, P < 0.05, variable is significant; for the tinnitus frequency; ß = 0.000, t = 1.269, P = 0.206, variable is not significant; for the SAS scores; ß = 1.310, t = 7.685, P < 0.001, variable is significant; for the PSQI scores; ß = 1.680, t = 5.433, P < 0.001, variable is significant. Therefore, the most accurate model for predicting severity in tinnitus patients is a linear combination of the constant, tinnitus loudness, SAS scores, and PSQI scores, Y(Tinnitus severity) = ß 0 + ß 1 (Tinnitus loudness) + ß 2 (SAS scores) + ß 3 (PSQI scores). ß 0, ß 1, ß 2, and ß 3 are -51.797, 0.161, 1.310 and 1.680, respectively. Conclusion: Tinnitus severity is positively associated with loudness, anxiety levels, and sleep quality. To effectively manage tinnitus in patients, it is essential to promptly identify and address these accompanying factors and related symptoms.