Differentiating the relationships between traditional and new media use and sleep quality during the COVID-19 pandemic: roles of psychological distress and age.

Background: Numerous studies have consistently demonstrated a decline in sleep quality during the COVID-19 pandemic. The primary objective of this study is to explore the impact of engaging with pertinent epidemic information through the media amid the COVID-19 crisis on individuals' sleep quality and the underlying mechanisms through which this influence operates. Methods: An online cross-sectional study design was employed. A total of 1,063 British adults (36.2% males; M age = 38.85, SD age = 13.36, ranging from 18 to 77 years old) participated in the study and completed our questionnaires, which included media usage frequency during the pandemic, the 10-item Kessler Psychological Distress Scale (K10), the Insomnia Severity Index (ISI), and the Ten-item Personality Inventory (TIPI). Results: Pearson's correlation analyses indicated that there was no significant correlation between COVID-19-related traditional media use (television, radio, newspaper) and psychological distress or sleep quality. However, exposure to information related to COVID-19 through new media use (Facebook, Tik Tok, Twitter) was correlated with greater psychological distress and poorer sleep quality. A moderated mediation analysis showed that psychological distress fully mediated the relationship between new media use and poor sleep, which was moderated by age, with the association between psychological distress and poor sleep quality being stronger among older adults. Conclusion: Exposure to information of COVID-19 via new (but not traditional) media use deteriorated sleep quality through greater psychological distress, and this relationship was stronger among older adults.

Advances in development of biomarkers for brain damage and ischemia.

Acquired brain injury is an urgent situation that requires rapid diagnosis and treatment. Magnetic resonance imaging (MRI) and computed tomography (CT) are required for accurate diagnosis. However, these methods are costly and require substantial infrastructure and specialized staff. Circulatory biomarkers of acute brain injury may help in the management of patients with acute cerebrovascular events and prevent poor outcome and mortality. The purpose of this review is to provide an overview of the development of potential biomarkers of brain damage to increase diagnostic possibilities. For this purpose, we searched the PubMed database of studies on the diagnostic potential of brain injury biomarkers. We also accessed information from Clinicaltrials.gov to identify any clinical trials of biomarker measurements for the diagnosis of brain damage. In total, we present 41 proteins, enzymes and hormones that have been considered as biomarkers for brain injury, of which 20 have been studied in clinical trials. Several microRNAs have also emerged as potential clinical biomarkers for early diagnosis. Combining multiple biomarkers in a panel, along with other parameters, is yielding promising outcomes.

Decoding depression: a comprehensive multi-cohort exploration of blood DNA methylation using machine learning and deep learning approaches.

The causes of depression are complex, and the current diagnosis methods rely solely on psychiatric evaluations with no incorporation of laboratory biomarkers in clinical practices. We investigated the stability of blood DNA methylation depression signatures in six different populations using six public and two domestic cohorts (n = 1942) conducting mega-analysis and meta-analysis of the individual studies. We evaluated 12 machine learning and deep learning strategies for depression classification both in cross-validation (CV) and in hold-out tests using merged data from 8 separate batches, constructing models with both biased and unbiased feature selection. We found 1987 CpG sites related to depression in both mega- and meta-analysis at the nominal level, and the associated genes were nominally related to axon guidance and immune pathways based on enrichment analysis and eQTM data. Random forest classifiers achieved the highest performance (AUC 0.73 and 0.76) in CV and hold-out tests respectively on the batch-level processed data. In contrast, the methylation showed low predictive power (all AUCs < 0.57) for all classifiers in CV and no predictive power in hold-out tests when used with harmonized data. All models achieved significantly better performance (>14% gain in AUCs) with pre-selected features (selection bias), with some of the models (joint autoencoder-classifier) reaching AUCs of up to 0.91 in the final testing regardless of data preparation. Different algorithmic feature selection approaches may outperform limma, however, random forest models perform well regardless of the strategy. The results provide an overview over potential future biomarkers for depression and highlight many important methodological aspects for DNA methylation-based depression profiling including the use of machine learning strategies.

Identifying proteomic risk factors for overall, aggressive, and early onset prostate cancer using Mendelian Randomisation and tumour spatial transcriptomics.

BACKGROUND: Understanding the role of circulating proteins in prostate cancer risk can reveal key biological pathways and identify novel targets for cancer prevention. METHODS: We investigated the association of 2002 genetically predicted circulating protein levels with risk of prostate cancer overall, and of aggressive and early onset disease, using cis-pQTL Mendelian randomisation (MR) and colocalisation. Findings for proteins with support from both MR, after correction for multiple-testing, and colocalisation were replicated using two independent cancer GWAS, one of European and one of African ancestry. Proteins with evidence of prostate-specific tissue expression were additionally investigated using spatial transcriptomic data in prostate tumour tissue to assess their role in tumour aggressiveness. Finally, we mapped risk proteins to drug and ongoing clinical trials targets. FINDINGS: We identified 20 proteins genetically linked to prostate cancer risk (14 for overall [8 specific], 7 for aggressive [3 specific], and 8 for early onset disease [2 specific]), of which the majority replicated where data were available. Among these were proteins associated with aggressive disease, such as PPA2 [Odds Ratio (OR) per 1 SD increment = 2.13, 95% CI: 1.54-2.93], PYY [OR = 1.87, 95% CI: 1.43-2.44] and PRSS3 [OR = 0.80, 95% CI: 0.73-0.89], and those associated with early onset disease, including EHPB1 [OR = 2.89, 95% CI: 1.99-4.21], POGLUT3 [OR = 0.76, 95% CI: 0.67-0.86] and TPM3 [OR = 0.47, 95% CI: 0.34-0.64]. We confirmed an inverse association of MSMB with prostate cancer overall [OR = 0.81, 95% CI: 0.80-0.82], and also found an inverse association with both aggressive [OR = 0.84, 95% CI: 0.82-0.86] and early onset disease [OR = 0.71, 95% CI: 0.68-0.74]. Using spatial transcriptomics data, we identified MSMB as the genome-wide top-most predictive gene to distinguish benign regions from high grade cancer regions that comparatively had five-fold lower MSMB expression. Additionally, ten proteins that were associated with prostate cancer risk also mapped to existing therapeutic interventions. INTERPRETATION: Our findings emphasise the importance of proteomics for improving our understanding of prostate cancer aetiology and of opportunities for novel therapeutic interventions. Additionally, we demonstrate the added benefit of in-depth functional analyses to triangulate the role of risk proteins in the clinical aggressiveness of prostate tumours. Using these integrated methods, we identify a subset of risk proteins associated with aggressive and early onset disease as priorities for investigation for the future prevention and treatment of prostate cancer. FUNDING: This work was supported by Cancer Research UK (grant no. C8221/A29017).

Genetic variants of LEAP2 are associated with anthropometric traits and circulating insulin-like growth factor-1 concentration: A UK Biobank study.

AIM: To test the hypothesis that liver-expressed antimicrobial peptide 2 (LEAP2) genetic variants might influence the susceptibility to human obesity. METHODS: Using data from the UK Biobank, we identified independent LEAP2 gene single nucleotide polymorphisms (SNPs) and examined their associations with obesity traits and serum insulin-like growth factor-1 (IGF-1) concentration. These associations were evaluated for both individual SNPs and after combining them into a genetic risk score (GRSLEAP2) using linear and logistic regression models. Sex-stratified analyses were also conducted. RESULTS: Five SNPs showed positive associations with obesity-related traits. rs57880964 was associated with body mass index (BMI) and waist-to-hip ratio adjusted for BMI (WHRadjBMI), in the total population and among women. Four independent SNPs were positively associated with higher serum IGF-1 concentrations in both men and women. GRSLEAP2 was associated with BMI and WHRadjBMI only in women and with serum IGF-1 concentration in both sexes. CONCLUSIONS: These findings reveal sex-specific associations between key LEAP2 gene variants and several obesity traits, while also indicating a strong independent association of LEAP2 variants with serum IGF-1 concentration.

Depression proteomic profiling in adolescents with transcriptome analyses in independent cohorts.

Introduction: Depression is a major global burden with unclear pathophysiology and poor treatment outcomes. Diagnosis of depression continues to rely primarily on behavioral rather than biological methods. Investigating tools that might aid in diagnosing and treating early-onset depression is essential for improving the prognosis of the disease course. While there is increasing evidence of possible biomarkers in adult depression, studies investigating this subject in adolescents are lacking. Methods: In the current study, we analyzed protein levels in 461 adolescents assessed for depression using the Development and Well-Being Assessment (DAWBA) questionnaire as part of the domestic Psychiatric Health in Adolescent Study conducted in Uppsala, Sweden. We used the Proseek Multiplex Neuro Exploratory panel with Proximity Extension Assay technology provided by Olink Bioscience, followed by transcriptome analyses for the genes corresponding to the significant proteins, using four publicly available cohorts. Results: We identified a total of seven proteins showing different levels between DAWBA risk groups at nominal significance, including RBKS, CRADD, ASGR1, HMOX2, PPP3R1, CD63, and PMVK. Transcriptomic analyses for these genes showed nominally significant replication of PPP3R1 in two of four cohorts including whole blood and prefrontal cortex, while ASGR1 and CD63 were replicated in only one cohort. Discussion: Our study on adolescent depression revealed protein-level and transcriptomic differences, particularly in PPP3R1, pointing to the involvement of the calcineurin pathway in depression. Our findings regarding PPP3R1 also support the role of the prefrontal cortex in depression and reinforce the significance of investigating prefrontal cortex-related mechanisms in depression.

Identifying therapeutic targets for cancer among 2074 circulating proteins and risk of nine cancers.

Circulating proteins can reveal key pathways to cancer and identify therapeutic targets for cancer prevention. We investigate 2,074 circulating proteins and risk of nine common cancers (bladder, breast, endometrium, head and neck, lung, ovary, pancreas, kidney, and malignant non-melanoma) using cis protein Mendelian randomisation and colocalization. We conduct additional analyses to identify adverse side-effects of altering risk proteins and map cancer risk proteins to drug targets. Here we find 40 proteins associated with common cancers, such as PLAUR and risk of breast cancer [odds ratio per standard deviation increment: 2.27, 1.88-2.74], and with high-mortality cancers, such as CTRB1 and pancreatic cancer [0.79, 0.73-0.85]. We also identify potential adverse effects of protein-altering interventions to reduce cancer risk, such as hypertension. Additionally, we report 18 proteins associated with cancer risk that map to existing drugs and 15 that are not currently under clinical investigation. In sum, we identify protein-cancer links that improve our understanding of cancer aetiology. We also demonstrate that the wider consequence of any protein-altering intervention on well-being and morbidity is required to interpret any utility of proteins as potential future targets for therapeutic prevention.

Hydroxymethylglutaryl-CoA reductase activity is essential for mitochondrial ß-oxidation of fatty acids to prevent lethal accumulation of long-chain acylcarnitines in the mouse liver.

BACKGROUND AND PURPOSE: Statins are competitive inhibitors of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase (HMGCR), and exert adverse effects on mitochondrial function, although the mechanisms underlying these effects remain unclear. We used a tamoxifen-induced Hmgcr-knockout (KO) mouse model, a multi-omics approach and mitochondrial function assessments to investigate whether decreased HMGCR activity impacts key liver energy metabolism pathways. EXPERIMENTAL APPROACH: We established a new mouse strain using the Cre/loxP system, which enabled whole-body deletion of Hmgcr expression. These mice were crossed with Rosa26Cre mice and treated with tamoxifen to delete Hmgcr in all cells. We performed transcriptomic and metabolomic analyses and thus evaluated time-dependent changes in metabolic functions to identify the pathways leading to cell death in Hmgcr-KO mice. KEY RESULTS: Lack of Hmgcr expression resulted in lethality, due to acute liver damage caused by rapid disruption of mitochondrial fatty acid ß-oxidation and very high accumulation of long-chain (LC) acylcarnitines in both male and female mice. Gene expression and KO-related phenotype changes were not observed in other tissues. The progression to liver failure was driven by diminished peroxisome formation, which resulted in impaired mitochondrial and peroxisomal fatty acid metabolism, enhanced glucose utilization and whole-body hypoglycaemia. CONCLUSION AND IMPLICATIONS: Our findings suggest that HMGCR is crucial for maintaining energy metabolism balance, and its activity is necessary for functional mitochondrial ß-oxidation. Moreover, statin-induced adverse reactions might be rescued by the prevention of LC acylcarnitine accumulation.

Social support predicted subsequent subjective well-being during the COVID-19 pandemic: a prospective study.

BACKGROUND: Subjective well-being (SWB) is associated with social support in cross-sectional studies. However, it remains unclear whether and how social support predicts SWB longitudinally, especially during the COVID-19 contingency. METHODS: By adopting a prospective design, the current work addressed this research question in a sample of 594 participants from the U.K. The data were collected via the online platform, Prolific, at two time points (June, 2020 and August, 2021) with a 14-month interval. Descriptive analysis and a moderated mediation model were conducted to test the proposed hypotheses. RESULTS: Baseline social support was a significant predictor of subjective well-being (SWB) 14 months later, even after controlling for baseline SWB and other covariates such as personality traits. Additionally, affect balance (i.e., the affective component of SWB) fully mediated the link between baseline social support and subsequent life satisfaction (i.e., the cognitive component of SWB). Moreover, household income moderated this relationship, indicating a stronger mediation for individuals with lower monthly household income. CONCLUSION: The present work sheds light on the underlying mechanism and boundary condition of the association between social support and different components of SWB during the COVID-19 pandemic.

Differential change in alcohol consumption during the COVID-19 pandemic: the role of loneliness, socialization, and mental well-being.

Introduction: The COVID-19 pandemic led to a surge in mental health issues and psychological distress, disruption to work/studying conditions, and social isolation particularly among young adults. Changes in these factors are differentially associated with alcohol use. Moreover, the relationship between these factors are bidirectional and may have fluctuated throughout the different phases of the pandemic. However, studies focusing on young adults had conflicting results, short follow-up periods, and lacked comprehensive data to describe underlying mechanisms. Methods: 1067 young adults participated in repetitive measures termed wave 4 (2021) of the Survey of Adolescent Life in Västmanland Cohort "SALVe" Cohort. Of these, 889 also completed pre-pandemic measurements termed wave 3 (2018). Participants completed the Alcohol Use Disorders Identification Test (AUDIT) to evaluate alcohol consumption and harmful use. Cross-sectional associations between perceived changes in alcohol use and shift in individual, mental health, and work environment factors were examined using Chi-square tests. Logistic regression was utilized to identify pre-pandemic predictors of harmful consumption during the pandemic. Results: Harmful consumption decreased only in females following the COVID-19 pandemic. Participants who reported increased feelings of depression, anxiety, and loneliness were more likely to increase their alcohol use. Interestingly, the subgroup who felt less lonely and met their friends more often, as well as those who continued working/studying from their regular workplace also had an increased likelihood of higher consumption. Only pre-pandemic ADHD and delinquency symptoms predicted harmful alcohol consumption following the pandemic. Conclusion: Females reduced harmful alcohol consumption during the COVID-19 pandemic. While those who suffered the burden of social isolation and distress were more likely to increase their alcohol use, young adults who felt less lonely and met their friends more often also had a similar outcome. The relationship between loneliness and alcohol consumption among young adults is influenced by the social factors that may be facilitated by drinking.

Exploring sex differences: insights into gene expression, neuroanatomy, neurochemistry, cognition, and pathology.

Increased knowledge about sex differences is important for development of individualized treatments against many diseases as well as understanding behavioral and pathological differences. This review summarizes sex chromosome effects on gene expression, epigenetics, and hormones in relation to the brain. We explore neuroanatomy, neurochemistry, cognition, and brain pathology aiming to explain the current state of the art. While some domains exhibit strong differences, others reveal subtle differences whose overall significance warrants clarification. We hope that the current review increases awareness and serves as a basis for the planning of future studies that consider both sexes equally regarding similarities and differences.

The exposure to UV filters: Prevalence, effects, possible molecular mechanisms of action and interactions within mixtures.

Substances that can absorb sunlight and harmful UV radiation such as organic UV filters are widely used in cosmetics and other personal care products. Since humans use a wide variety of chemicals for multiple purposes it is common for UV filters to co-occur with other substances either in human originating specimens or in the environment. There is increasing interest in understanding such co-occurrence in form of potential synergy, antagonist, or additive effects of biological systems. This review focuses on the collection of data about the simultaneous occurrence of UV filters oxybenzone (OXYB), ethylexyl-methoxycinnamate (EMC) and 4-methylbenzylidene camphor (4-MBC) as well as other classes of chemicals (such as pesticides, bisphenols, and parabens) to understand better any such interactions considering synergy, additive effect and antagonism. Our analysis identified >20 different confirmed synergies in 11 papers involving 16 compounds. We also highlight pathways (such as transcriptional activation of estrogen receptor, promotion of estradiol synthesis, hypothalamic-pituitary-gonadal (HPG) axis, and upregulation of thyroid-hormone synthesis) and proteins (such as Membrane Associated Progesterone Receptor (MAPR), cytochrome P450, and heat shock protein 70 (Hsp70)) that can act as important key nodes for such potential interactions. This article aims to provide insight into the molecular mechanisms on how commonly used UV filters act and may interact with other chemicals.

STING inhibitors sensitize platinum chemotherapy in ovarian cancer by inhibiting the CGAS-STING pathway in cancer-associated fibroblasts (CAFs).

Chemotherapy resistance in ovarian cancer hampers cure rates, with cancer-associated fibroblasts (CAFs) playing a pivotal role. Despite their known impact on cancer progression and chemotherapy resistance, the specific mechanism by which CAFs regulate the tumor inflammatory environment remains unclear. This study reveals that cisplatin facilitates DNA transfer from ovarian cancer cells to CAFs, activating the CGAS-STING-IFNB1 pathway in CAFs and promoting IFNB1 release. Consequently, this reinforces cancer cell resistance to platinum drugs. High STING expression in the tumor stroma was associated with a poor prognosis, while inhibiting STING expression enhanced ovarian cancer sensitivity. Understanding the relevance of the CGAS-STING pathway in CAFs for platinum resistance suggests targeting STING as a promising combination therapy for ovarian cancer, providing potential avenues for improved treatment outcomes.

Synthesis of a Rivastigmine and Insulin Combinational Mucoadhesive Nanoparticle for Intranasal Delivery.

Efficient drug delivery remains a critical challenge for treating neurodegenerative diseases, such as Alzheimer's disease (AD). Using innovative nanomaterials, delivering current medications like acetylcholinesterase inhibitors to the brain through the intranasal route is a promising strategy for managing AD. Here, we developed a unique combinational drug delivery system based on N,N,N-trimethyl chitosan nanoparticles (NPs). These NPs encapsulate rivastigmine, the most potent acetylcholinesterase inhibitor, along with insulin, a complementary therapeutic agent. The spherical NPs exhibited a zeta potential of 17.6 mV, a size of 187.00 nm, and a polydispersity index (PDI) of 0.29. Our findings demonstrate significantly improved drug transport efficiency through sheep nasal mucosa using the NPs compared to drug solutions. The NPs exhibited transport efficiencies of 73.3% for rivastigmine and 96.9% for insulin, surpassing the efficiencies of the drug solutions, which showed transport efficiencies of 52% for rivastigmine and 21% for insulin ex vivo. These results highlight the potential of a new drug delivery system as a promising approach for enhancing nasal transport efficiency. These combinational mucoadhesive NPs offer a novel strategy for the simultaneous cerebral delivery of rivastigmine and insulin, which could prove helpful in developing effective treatments of AD and other neurodegenerative conditions.

Fluvastatin-induced myofibrillar damage is associated with elevated ROS, and impaired fatty acid oxidation, and is preceded by mitochondrial morphological changes.

Previously, we showed that fluvastatin treatment induces myofibrillar damage and mitochondrial phenotypes in the skeletal muscles of Drosophila. However, the sequential occurrence of mitochondrial phenotypes and myofibril damage remains elusive. To address this, we treated flies with fluvastatin for two and five days and examined their thorax flight muscles using confocal microscopy. In the two-day fluvastatin group, compared to the control, thorax flight muscles exhibited mitochondrial morphological changes, including fragmentation, rounding up and reduced content, while myofibrils remained organized in parallel. In the five-day fluvastatin treatment, not only did mitochondrial morphological changes become more pronounced, but myofibrils became severely disorganized with significantly increased thickness and spacing, along with myofilament abnormalities, suggesting myofibril damage. These findings suggest that fluvastatin-induced mitochondrial changes precede myofibril damage. Moreover, in the five-day fluvastatin group, the mitochondria demonstrated elevated H2O2 and impaired fatty acid oxidation compared to the control group, indicating potential mitochondrial dysfunction. Surprisingly, knocking down Hmgcr (Drosophila homolog of HMGCR) showed normal mitochondrial respiration in all parameters compared to controls or five-day fluvastatin treatment, which suggests that fluvastatin-induced mitochondrial dysfunction might be independent of Hmgcr inhibition. These results provide insights into the sequential occurrence of mitochondria and myofibril damage in statin-induced myopathy for future studies.

Conceptual foundations of acetylcarnitine supplementation in neuropsychiatric long COVID syndrome: a narrative review.

Post-acute sequelae of COVID-19 can present as multi-organ pathology, with neuropsychiatric symptoms being the most common symptom complex, characterizing long COVID as a syndrome with a significant disease burden for affected individuals. Several typical symptoms of long COVID, such as fatigue, depressive symptoms and cognitive impairment, are also key features of other psychiatric disorders such as myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and major depressive disorder (MDD). However, clinically successful treatment strategies are still lacking and are often inspired by treatment options for diseases with similar clinical presentations, such as ME/CFS. Acetylcarnitine, the shortest metabolite of a class of fatty acid metabolites called acylcarnitines and one of the most abundant blood metabolites in humans can be used as a dietary/nutritional supplement with proven clinical efficacy in the treatment of MDD, ME/CFS and other neuropsychiatric disorders. Basic research in recent decades has established acylcarnitines in general, and acetylcarnitine in particular, as important regulators and indicators of mitochondrial function and other physiological processes such as neuroinflammation and energy production pathways. In this review, we will compare the clinical basis of neuropsychiatric long COVID with other fatigue-associated diseases. We will also review common molecular disease mechanisms associated with altered acetylcarnitine metabolism and the potential of acetylcarnitine to interfere with these as a therapeutic agent. Finally, we will review the current evidence for acetylcarnitine as a supplement in the treatment of fatigue-associated diseases and propose future research strategies to investigate the potential of acetylcarnitine as a treatment option for long COVID.

Pre-prandial plasma liver-expressed antimicrobial peptide 2 (LEAP2) concentration in humans is inversely associated with hunger sensation in a ghrelin independent manner.

PURPOSE: The liver-expressed antimicrobial peptide 2 (LEAP2) is a newly recognized peptide hormone that acts via the growth hormone secretagogue receptor (GHSR) blunting the effects of ghrelin and displaying ghrelin-independent actions. Since the implications of LEAP2 are beginning to be elucidated, we investigated if plasma LEAP2 concentration varies with feeding status or sex and whether it is associated with glucose metabolism and appetite sensations. METHODS: We performed a single test meal study, in which plasma concentrations of LEAP2, ghrelin, insulin and glucose as well as visual analogue scales for hunger, desire to eat, prospective food consumption, fullness were assessed before and 60 min after breakfast in 44 participants (n = 21 females) with normal weight (NW) or overweight/obesity (OW/OB). RESULTS: Pre-prandial plasma LEAP2 concentration was ~ 1.6-fold higher whereas ghrelin was ~ 2.0-fold lower in individuals with OW/OB (p < 0.001) independently of sex. After adjusting for body mass index (BMI) and sex, pre-prandial plasma LEAP2 concentration displayed a direct relationship with BMI (ß: 0.09; 95%CI: 0.05, 0.13; p < 0.001), fat mass (ß: 0.05; 95%CI: 0.01, 0.09; p = 0.010) and glycemia (ß: 0.24; 95%CI: 0.05, 0.43; p = 0.021), whereas plasma ghrelin concentration displayed an inverse relationship with BMI and fat mass but not with glycemia. Postprandial plasma LEAP2 concentration increased ~ 58% in females with OW/OB (p = 0.045) but not in females with NW or in males. Pre-prandial plasma LEAP2 concentration displayed an inverse relationship with hunger score (ß: - 11.16; 95% CI: - 18.52, - 3.79; p = 0.004), in a BMI-, sex- and ghrelin-independent manner. CONCLUSIONS: LEAP2 emerges as a key hormone implicated in the regulation of metabolism and appetite in humans. TRIAL REGISTRATION: The study was retrospectively registered in clinicaltrials.gov (April 2023). CLINICALTRIALS: gov Identifier: NCT05815641.

Exploring biomarkers in trigeminal neuralgia patients operated with microvascular decompression: A comparison with multiple sclerosis patients and non-neurological controls.

BACKGROUND: Trigeminal neuralgia (TN) is a severe facial pain condition often associated with a neurovascular conflict. However, neuroinflammation has also been implicated in TN, as it frequently co-occurs with multiple sclerosis (MS). METHODS: We analysed protein expression levels of TN patients compared to MS patients and controls. Proximity Extension Assay technology was used to analyse the levels of 92 proteins with the Multiplex Neuro-Exploratory panel provided by SciLifeLab, Uppsala, Sweden. Serum and CSF samples were collected from TN patients before (n = 33 and n = 27, respectively) and after (n = 28 and n = 8, respectively) microvascular decompression surgery. Additionally, we included samples from MS patients (n = 20) and controls (n = 20) for comparison. RESULTS: In both serum and CSF, several proteins were found increased in TN patients compared to either MS patients, controls, or both, including EIF4B, PTPN1, EREG, TBCB, PMVK, FKBP5, CD63, CRADD, BST2, CD302, CRIP2, CCL27, PPP3R1, WWP2, KLB, PLA2G10, TDGF1, SMOC1, RBKS, LTBP3, CLSTN1, NXPH1, SFRP1, HMOX2, and GGT5. The overall expression of the 92 proteins in postoperative TN samples seems to shift towards the levels of MS patients and controls in both serum and CSF, as compared to preoperative samples. Interestingly, there was no difference in protein levels between MS patients and controls. CONCLUSIONS: We conclude that TN patients showed increased serum and CSF levels of specific proteins and that successful surgery normalizes these protein levels, highlighting its potential as an effective treatment. However, the similarity between MS and controls challenges the idea of shared pathophysiology with TN, suggesting distinct underlying mechanisms in these conditions. SIGNIFICANCE: This study advances our understanding of trigeminal neuralgia (TN) and its association with multiple sclerosis (MS). By analysing 92 protein biomarkers, we identified distinctive molecular profiles in TN patients, shedding light on potential pathophysiological mechanisms. The observation that successful surgery normalizes many protein levels suggests a promising avenue for TN treatment. Furthermore, the contrasting protein patterns between TN and MS challenge prevailing assumptions of similarity between the two conditions and point to distinct pathophysiological mechanisms.

Artificial Neural Network (ANN)-Based Pattern Recognition Approach Illustrates a Biphasic Behavioral Effect of Ethanol in Zebrafish: A High-Throughput Method for Animal Locomotor Analysis.

Variations in stress responses between individuals are linked to factors ranging from stress coping styles to the sensitivity of neurotransmitter systems. Many anxiolytic compounds can increase stressor engagement through the modulation of neurotransmitter systems and are used to investigate stress response mechanisms. The effect of such modulation may vary in time depending on concentration or environment, but those effects are hard to dissect because of the slow transition. We investigated the temporal effect of ethanol and found that ethanol-treated individual zebrafish larvae showed altered behavior that is different between drug concentrations and decreases with time. We used an artificial neural network approach with a time-dependent method for analyzing long (90 min) experiments on zebrafish larvae and found that individuals from the 0.5% group begin to show locomotor activity corresponding to the control group starting from the 60th minute. The locomotor activity of individuals from the 2% group after the 80th minute is classified as the activity of individuals from the 1.5% group. Our method shows three clusters of different concentrations in comparison with two clusters, which were obtained with the usage of a statistical approach for analyzing just the speed of fish movements. In addition, we show that such changes are not explained by basic behavior statistics such as speed and are caused by shifts in locomotion patterns.