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Objective: To model interdependencies of serum neurofilament light chain (sNfL), a clinically useful biomarker of axonal injury in neurological diseases, with demographic, anthropometric, physiological, and disease biomarkers in the United States population. Methods: sNfL and 80 biomarkers were obtained from the National Health and Nutrition Examination Survey (n = 2071, age: 20–75 years). Body habitus and composition, electrolytes, blood cell, metabolic, liver, and kidney function biomarkers, and common diseases were assessed with weighted regression adjusted for age, sex, and race/ethnicity. Salient biomarkers were modeled with ensemble learning; a Bayesian network structure was obtained for interdependencies. Results: Age was strongly associated with sNfL. sNfL levels were 13% higher in men versus women. Mexican Americans had 18.5% lower sNfL versus Non‐Hispanic Whites. sNfL was similar in pregnant versus nonpregnant women. Lymphocyte, and neutrophil numbers, and phosphorus, and chloride levels were associated with sNfL. Multiple liver function (e.g., albumin and gamma‐glutamyltransferase), renal function (e.g., creatinine and urea), and carbohydrate/lipid metabolism markers (e.g., glucose and triglycerides) were associated with sNfL. A 50% greater creatinine was associated with 26.8% greater sNfL. Diabetes, kidney disease, congestive heart failure, and stroke were associated with sNfL. The ensemble learning algorithm predicted high sNfL outliers with 5.06%–9.16% test error. Bayesian network modeling indicated sNfL had neighbor dependencies with age, creatinine, albumin, and chloride. Interpretation: sNfL is associated with age, kidney and liver function, diabetes, blood cell subsets, and electrolytes. sNfL may be a useful biomarker for biological age of the whole body and major organ systems including the brain. [ABSTRACT FROM AUTHOR]

Objective: Early identification of cognitive impairment in neurodegenerative diseases like Alzheimer's disease (AD) is crucial. Neurofilament, a potential biomarker for neurological disorders, has gained attention. Our study aims to investigate the relationship between serum neurofilament light (sNfL) levels and cognitive function in elderly individuals in the United States. Methods: This cross‐sectional study analyzed data from participants aged 60 and above in the National Health and Nutrition Examination Survey (2013–2014). We collected sNfL levels, cognitive function tests, sociodemographic characteristics, comorbidities, and other variables. Weighted multiple linear regression models examined the relationship between ln(sNfL) and cognitive scores. Restricted cubic spline (RCS) visualization explored nonlinear relationships. The stratified analysis examined subgroups' ln(sNfL) and cognitive function association. Results: The study included 446 participants (47.73% male). Participants with ln(sNfL) levels between 2.58 and 2.81 pg/mL (second quintile) performed relatively well in cognitive tests. After adjusting for multiple factors, ln(sNfL) levels were negatively correlated with cognitive function, with adjusted β (95% CI) as follows: immediate recall test (IRT): −0.763 (−1.301 to −0.224), delayed recall test (DRT): −0.308 (−0.576 to −0.04), animal fluency test (AFT): −1.616 (−2.639 to −0.594), and digit symbol substitution test (DSST): −2.790 (−4.369 to −1.21). RCS curves showed nonlinear relationships between ln(sNfL) and DRT, AFT, with inflection points around 2.7 pg/mL. The stratified analysis revealed a negative correlation between ln(sNfL) and cognition in specific subgroups with distinct features, with an interaction between diabetes and ln(sNfL). Interpretation: Higher sNfL levels are associated with poorer cognitive function in the elderly population of the United States. sNfL shows promise as a potential biomarker for early identification of cognitive decline. [ABSTRACT FROM AUTHOR]

Background: Serum levels of neurofilament light chain (sNfL) are a potentially useful biomarker for assessing the efficacy of multiple sclerosis (MS) treatments. Objective: To compare levels of sNfL in patients with MS who switched from natalizumab every 4 weeks (Q4W) to extended interval dosing (EID) and patients who remained on Q4W dosing in real-world clinical practice. Methods: This was a retrospective analysis of samples from patients treated with natalizumab from 2010 to 2015 at a single center in the United States. Levels of sNfL were compared in patients who stayed on Q4W dosing or who switched to EID (parallel-arm analyses) and during Q4W and EID periods in patients who switched to EID (pre- and post-switch analyses). Results: The analysis included 139 patients (Q4W: n = 79; EID: n = 60). After adjustment, levels of sNfL did not significantly differ between patients who remained on Q4W dosing and those who switched to EID in parallel-arm analyses (adjusted Q4W-EID difference = 0.51 pg/mL; p = 0.60) or pre- and post-switch analyses (adjusted difference = 0.96 pg/mL; p = 0.10). Conclusion: These sNfL biomarker results suggest that the effectiveness of natalizumab is maintained in patients who switch from Q4W dosing to EID. [ABSTRACT FROM AUTHOR]

The article reports on the research about the capability of bacteria to transform the soil into a geological battery. Researchers have found out that soil bacteria create networks of tiny wires linking individual bacterial cells into a web-like electrical circuit. The study reveals that the wires enable the bacteria to eliminate electrons during metabolism, transporting them to distant electron dumps. According to geochemist Yuri Gorby, the soil might act as a gigantic circuit built by microbes to power their metabolic systems. Gorby states that the bacteria spit out unwanted electrons into the circuit after taking nutrients for energy.