The endoplasmic reticulum (ER) is a crucial neuronal organelle involved in protein synthesis, calcium homeostasis, and metabolic support, essential for neuronal function and plasticity. Understanding its three-dimensional (3D) architecture is key to elucidating functional organization. Using SBF-SEM and AI-assisted segmentation, we established a quantitative framework to characterize ER and mitochondrial scaling within 35 peripheral nervous system (PNS) myelinated axons. Analysis of individual organelle morphometrics revealed a strong power-law relationship between surface area and volume for both mitochondria (R² = 0.949) and ER (R² = 0.949). The resulting exponents were super-isometric (k_Mito = 0.85, k_ER = 0.73), suggesting structural plasticity that prioritizes membrane surface expansion. A key finding was the distinction between size and number regulation: mitochondrial and ER volumes were negligibly correlated (r ≈ 0.03), implying independent size regulation. However, organelle abundance (counts) showed a strong positive correlation (r = 0.79), maintaining an extremely low Bonferroni-adjusted Q value (8.1 ×10^-9), suggesting coordinated control of organelle number in response to axonal size. Axonal populations were heterogeneous, with larger axons consistently containing more ER elements (r = 0.59) and mitochondria (r = 0.69). Furthermore, a low correlation of axon length with organelle content supports the idea that regulation is primarily a local phenomenon tied to cross-sectional size. These findings provide a quantitative basis for understanding how ER and mitochondria structurally adapt to axonal size, laying the groundwork for future research into how these scaling relationships influence neuronal metabolic health and contribute to neurological disease.

Background: According to newly published studies, patients with Coronavirus Disease 2019 (COVID-19) have significantly lower serum 25-hydroxyvitamin D 25(OH)D levels than those without the SARS-CoV-2 infection. Vitamin D insufficiency may be a predictor of poor prognosis in COVID-19 patients. Vitamin D supplementation is related to improved clinical outcomes in terms of intensive care unit (ICU) admission and death, particularly in individuals with moderate-to-severe forms of COVID-19 requiring hospitalization. Materials and methods: This placebo-controlled five-day study was performed on 100 hospitalized COVID-19 patients with vitamin D insufficiency randomized into two groups. Vitamin D in the form of a sublingual sprayable microemulsion (LYL love your life® sunD3 LYLmicro™) was given three times daily after breakfast, lunch, and dinner (daily dose 12,000 IU) to 52 patients with blood vitamin D levels below 30 ng/ml. 48 patients in the control group received a placebo spray in the same daily regiment. Results: We observed a statistically significant increase by 8.6 ng/ml in median vitamin D level after five days of high-dose vitamin D3 spray therapy. 90.2% of subjects reached normal serum levels of vitamin D. There was a strong correlation between changes in vitamin D and C-reactive protein (CRP) levels in individuals with moderately severe disease (p<0.05), while mild and severe cases showed no statistical significance comparing case and control groups. There were no statistically significant changes in ferritin and interleukin-6 (IL-6) levels. Conclusions: In this study, we demonstrated the possibility to rapidly increase circulating levels of vitamin D just in 5 days of high-dose intervention and found a statistically significant decrease of CRP levels in patients with moderately severe COVID-19. We were not able to detect statistically significant changes in ferritin and IL-6 levels during the 5-day vitamin D intervention.

Automated analysis of peripheral nerve ultrastructure is bottlenecked by heterogeneous electron microscopy (EM) datasets, where varying staining protocols and resolutions create domain shifts that confound deep learning. To address this, we developed a generalized segmentation pipeline. Using a custom pre-processing workflow (CLAHE and noise suppression) integrated into ZEISS Arivis Pro, we standardized inputs across three disparate domains: traditional osmium-based Palade, lanthanide-based “green” Uranyl-free method, and low-resolution Ellisman preparations. A U-Net trained on a highly constrained 15-image composite dataset achieved peak internal Intersection over Union (IoU) scores >0.95 for myelin and Schwann cells. Crucially, during open-world, zero-shot inference on an expanded independent testing cohort (N = 40), the model sustained robust Dice Similarity Coefficients of 0.854 for myelin and 0.597 for mitochondria. This demonstrates that integrating classical image standardization with deep learning effectively mitigates EM domain gaps, enabling comprehensive 3D multi-organelle reconstructions from challenging data. To ensure transparency and community utility, the pre-trained models and standardization scripts are provided in a public, open-access repository. Ultimately, this pipeline supports the transition to sustainable, non-toxic EM protocols and provides a robust pathway for unlocking historical clinical archives for automated organellomics.

Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system with a complex etiology involving genetic and environmental factors. Genome-wide association studies have identified several genetic variants associated with MS susceptibility, including the XRCC1 gene involved in DNA base excision repair. Environmental factors such as exposure to nitric oxide have also been linked to MS development and progression. This study aims to investigate the potential association between these factors, including patient demographic descriptors and biochemical markers, to better understand the mechanisms underlying MS. This scientific article discusses the results of statistical analysis of biomarkers in relation to multiple sclerosis (MS). Our findings reveal significant associations between various factors, such as levels of nitric oxide (NO) and serum nitrite levels, NO and plasma malondialdehyde (MDA) levels, nitrite and nitrate levels in serum, and nitrite and MDA levels in plasma. It also suggests a potential association between XRCC1 rs25487 T > C locus deviation from Hardy-Weinberg equilibrium and MS in the population of Latvia. Furthermore, XRCC1 rs25487 T > C is found to be statistically significantly associated with DNA damage in peripheral blood mononuclear cells (PBMNC) and potentially associated with levels of NO. Additionally, PARP1 rs1136410 A > G is linked to plasma levels of MS patients. Finally, the study finds that XRCC1 rs25487 T > C is associated with both plasma nitrite levels and serum malondialdehyde (MDA) levels of MS patients, with the rare allele T specifically correlated with the latter.