Serum biomarker levels predict disability progression in patients with primary progressive multiple sclerosis.

BACKGROUND: We aimed to investigate the potential of serum biomarker levels to predict disability progression in a multicentric real-world cohort of patients with primary progressive multiple sclerosis (PPMS). METHODS: A total of 141 patients with PPMS from 18 European MS centres were included. Disability progression was investigated using change in Expanded Disability Status Scale (EDSS) score over three time intervals: baseline to 2 years, 6 years and to the last follow-up. Serum levels of neurofilament light chain (sNfL), glial fibrillar acidic protein (sGFAP) and chitinase 3-like 1 (sCHI3L1) were measured using single-molecule array assays at baseline. Correlations between biomarker levels, and between biomarkers and age were quantified using Spearman's r. Univariable and multivariable linear models were performed to assess associations between biomarker levels and EDSS change over the different time periods. RESULTS: Median (IQR) age of patients was 52.9 (46.4-58.5) years, and 58 (41.1%) were men. Median follow-up time was 9.1 (7.0-12.6) years. Only 8 (5.7%) patients received treatment during follow-up. sNfL and sGFAP levels were moderately correlated (r=0.43) and both weakly correlated with sCHI3L1 levels (r=0.19 and r=0.17, respectively). In multivariable analyses, levels of the three biomarkers were associated with EDSS changes across all time periods. However, when analysis was restricted to non-inflammatory patients according to clinical and radiological parameters (n=64), only sCHI3L1 levels remained associated with future EDSS change. CONCLUSIONS: Levels of sNfL, sGFAP and sCHI3L1 are prognostic biomarkers associated with disability progression in patients with PPMS, being CHI3L1 findings less dependent on the inflammatory component associated with disease progression.

Response to Fingolimod in Multiple Sclerosis Patients Is Associated with a Differential Transcriptomic Regulation.

Fingolimod is an immunomodulatory sphingosine-1-phosphate (S1P) analogue approved for the treatment of relapsing-remitting multiple sclerosis (RRMS). The identification of biomarkers of clinical responses to fingolimod is a major necessity in MS to identify optimal responders and avoid the risk of disease progression in non-responders. With this aim, we used RNA sequencing to study the transcriptomic changes induced by fingolimod in peripheral blood mononuclear cells of MS-treated patients and their association with clinical response. Samples were obtained from 10 RRMS patients (five responders and five non-responders) at baseline and at 12 months of fingolimod therapy. Fingolimod exerted a vast impact at the transcriptional level, identifying 7155 differentially expressed genes (DEGs) compared to baseline that affected the regulation of numerous signaling pathways. These DEGs were predominantly immune related, including genes associated with S1P metabolism, cytokines, lymphocyte trafficking, master transcription factors of lymphocyte functions and the NF-kB pathway. Responder and non-responder patients exhibited a differential transcriptomic regulation during treatment, with responders presenting a higher number of DEGs (6405) compared to non-responders (2653). The S1P, NF-kB and TCR signaling pathways were differentially modulated in responder and non-responder patients. These transcriptomic differences offer the potential of being exploited as biomarkers of a clinical response to fingolimod.

Applicability of probabilistic graphical models for early detection of SARS-CoV-2 reactive antibodies after SARS-CoV-2 vaccination in hematological patients.

Prior studies of antibody response after full SARS-CoV-2 vaccination in hematological patients have confirmed lower antibody levels compared to the general population. Serological response in hematological patients varies widely according to the disease type and its status, and the treatment given and its timing with respect to vaccination. Through probabilistic machine learning graphical models, we estimated the conditional probabilities of having detectable anti-SARS-CoV-2 antibodies at 3-6 weeks after SARS-CoV-2 vaccination in a large cohort of patients with several hematological diseases (n= 1166). Most patients received mRNA-based vaccines (97%), mainly Moderna® mRNA-1273 (74%) followed by Pfizer-BioNTech® BNT162b2 (23%). The overall antibody detection rate at 3 to 6 weeks after full vaccination for the entire cohort was 79%. Variables such as type of disease, timing of anti-CD20 monoclonal antibody therapy, age, corticosteroids therapy, vaccine type, disease status, or prior infection with SARS-CoV-2 are among the most relevant conditions influencing SARS-CoV-2-IgG-reactive antibody detection. A lower probability of having detectable antibodies was observed in patients with B-cell non-Hodgkin's lymphoma treated with anti-CD20 monoclonal antibodies within 6 months before vaccination (29.32%), whereas the highest probability was observed in younger patients with chronic myeloproliferative neoplasms (99.53%). The Moderna® mRNA-1273 compound provided higher probabilities of antibody detection in all scenarios. This study depicts conditional probabilities of having detectable antibodies in the whole cohort and in specific scenarios such as B cell NHL, CLL, MM, and cMPN that may impact humoral responses. These results could be useful to focus on additional preventive and/or monitoring interventions in these highly immunosuppressed hematological patients.

Effect of Expanded Hemodialysis with Theranova® in Patients with COVID-19.

INTRODUCTION: Cytokine storm control is the main target for improving severe COVID-19 by using immunosuppressive treatment. Effective renal replacement therapy (RRT) could give us an advantage removing cytokines in patients with RRT requirements superimposed on COVID-19. METHODS: This is a prospective observational study in COVID-19 patients who required hemodialysis (HD). Patients were assigned to online hemodiafiltration (OL-HDF) and expanded HD (HDx) according to Brescia group recommendations. We measured several cytokines, ß2 microglobulin and albumin levels pre/post-dialysis and on 1st-2nd week. We compared levels among both techniques and control group (HD without COVID-19). RESULTS: We included 26 patients: 18 with COVID-19 on RRT (5 of them had acute kidney injury [AKI]) and 8 controls. We confirm higher cytokine levels in COVID-19 patients than controls and even higher in patients with AKI than in those with chronic kidney disease. Most cytokines raised during HD session, except IL-10 and TNFα. IL-10 was eliminated by any dialysis technique, while clearance of TNFα was higher in the HDx group. HDx achieved a deeper normalization of cytokines and ß2 microglobulin reduction. Mortality was higher in the OL-HDF group than the HDx group. DISCUSSION: Not all cytokines behave equally along HD session. The following characteristics should be taken into account, such as intrinsic kinetic profile during a HD session. HDx seems to get better performance, probably due to the combination of different factors; however, we did not reach statistical significance due to the small sample size, dropout, and reduction of AKI incidence during the 2nd pandemic wave. CONCLUSION: HDx appears to provide better clearance for TNFα and ß2 microglobulin during HD session and associates lower mortality. We propose the HDx technique for COVID-19 patients with RRT requirements since it seems to be safe and more effective than OL-HDF. Further studies are still needed, but we hope that our preliminary data may help us in future pandemic waves of SARS-CoV-2 or other viruses still to come.

Neurofilament light chain and oligoclonal bands are prognostic biomarkers in radiologically isolated syndrome.

The prognostic role of cerebrospinal fluid molecular biomarkers determined in early pathogenic stages of multiple sclerosis has yet to be defined. In the present study, we aimed to investigate the prognostic value of chitinase 3 like 1 (CHI3L1), neurofilament light chain, and oligoclonal bands for conversion to clinically isolated syndrome and to multiple sclerosis in 75 patients with radiologically isolated syndrome. Cerebrospinal fluid levels of CHI3L1 and neurofilament light chain were measured by enzyme-linked immunosorbent assay. Uni- and multivariable Cox regression models including as covariates age at diagnosis of radiologically isolated syndrome, number of brain lesions, sex and treatment were used to investigate associations between cerebrospinal fluid CHI3L1 and neurofilament light chain levels and time to conversion to clinically isolated syndrome and multiple sclerosis. Neurofilament light chain levels and oligoclonal bands were independent risk factors for the development of clinically isolated syndrome (hazard ratio = 1.02, P = 0.019, and hazard ratio = 14.7, P = 0.012, respectively) and multiple sclerosis (hazard ratio = 1.03, P = 0.003, and hazard ratio = 8.9, P = 0.046, respectively). The best cut-off to classify cerebrospinal fluid neurofilament light chain levels into high and low was 619 ng/l, and high neurofilament light chain levels were associated with a trend to shorter time to clinically isolated syndrome (P = 0.079) and significant shorter time to multiple sclerosis (P = 0.017). Similarly, patients with radiologically isolated syndrome presenting positive oligoclonal bands converted faster to clinically isolated syndrome and multiple sclerosis (P = 0.005 and P = 0.008, respectively). The effects of high neurofilament light chain levels shortening time to clinically isolated syndrome and multiple sclerosis were more pronounced in radiologically isolated syndrome patients with ≥37 years compared to younger patients. Cerebrospinal fluid CHI3L1 levels did not influence conversion to clinically isolated syndrome and multiple sclerosis in radiologically isolated syndrome patients. Overall, these findings suggest that cerebrospinal neurofilament light chain levels and oligoclonal bands are independent predictors of clinical conversion in patients with radiologically isolated syndrome. The association with a faster development of multiple sclerosis reinforces the importance of cerebrospinal fluid analysis in patients with radiologically isolated syndrome.

Cannabinoid Receptors, Mental Pain and Suicidal Behavior: a Systematic Review.

PURPOSE OF REVIEW: The current serotonin-based biological model of suicidal behavior (SB) may be too simplistic. There is emerging evidence that other biomarkers and biological systems may be involved in SB pathophysiology. The literature on the endocannabinoid (EC) systems and SB is limited. The objective of the present article is to review all available information on the relationship between cannabinoid receptors (CB1 and CB2 receptors), and SB and/or psychological pain. RECENT FINDINGS: Our review is limited by the small number and heterogeneity of studies identified: (1) an autopsy study describing elevated levels of CB1 receptor activity in the prefrontal cortex and suicide in both depression and alcoholism and (2) studies supporting the involvement of both CB1 and CB2 receptors in the regulation of neuropathic pain and stress-induced analgesia. We conclude that cannabinoid receptors, particularly CB1 receptors, may become promising targets for the development of novel therapeutic tools for the treatment of SB.

A machine learning approach to identify groups of patients with hematological malignant disorders.

BACKGROUND AND OBJECTIVE: Vaccination against SARS-CoV-2 in immunocompromised patients with hematologic malignancies (HM) is crucial to reduce the severity of COVID-19. Despite vaccination efforts, over a third of HM patients remain unresponsive, increasing their risk of severe breakthrough infections. This study aims to leverage machine learning's adaptability to COVID-19 dynamics, efficiently selecting patient-specific features to enhance predictions and improve healthcare strategies. Highlighting the complex COVID-hematology connection, the focus is on interpretable machine learning to provide valuable insights to clinicians and biologists. METHODS: The study evaluated a dataset with 1166 patients with hematological diseases. The output was the achievement or non-achievement of a serological response after full COVID-19 vaccination. Various machine learning methods were applied, with the best model selected based on metrics such as the Area Under the Curve (AUC), Sensitivity, Specificity, and Matthew Correlation Coefficient (MCC). Individual SHAP values were obtained for the best model, and Principal Component Analysis (PCA) was applied to these values. The patient profiles were then analyzed within identified clusters. RESULTS: Support vector machine (SVM) emerged as the best-performing model. PCA applied to SVM-derived SHAP values resulted in four perfectly separated clusters. These clusters are characterized by the proportion of patients that generate antibodies (PPGA). Cluster 1, with the second-highest PPGA (69.91%), included patients with aggressive diseases and factors contributing to increased immunodeficiency. Cluster 2 had the lowest PPGA (33.3%), but the small sample size limited conclusive findings. Cluster 3, representing the majority of the population, exhibited a high rate of antibody generation (84.39%) and a better prognosis compared to cluster 1. Cluster 4, with a PPGA of 66.33%, included patients with B-cell non-Hodgkin's lymphoma on corticosteroid therapy. CONCLUSIONS: The methodology successfully identified four separate patient clusters using Machine Learning and Explainable AI (XAI). We then analyzed each cluster based on the percentage of HM patients who generated antibodies after COVID-19 vaccination. The study suggests the methodology's potential applicability to other diseases, highlighting the importance of interpretable ML in healthcare research and decision-making.

Cancer-Related Fatigue and Circulating Biomarkers in Breast Cancer Survivors.

PURPOSE: Cancer-related fatigue (CRF) is the most common and disruptive symptom experienced by cancer survivors and because of its frequency and severity is especially worrisome in breast cancer survivors (BCS). Despite a great deal of research, the mechanisms underlying CRF have not been determined. The present study aims to describe associations between CRF in BCS and different blood biomarkers. METHODS: A descriptive and cross-sectional study was conducted. A set of biomarkers assessing inflammation were measured in BCS: C-reactive protein (CRP), neutrophil-lymphocyte ratio (NLR), IL-1ß, IL-6, IL-8, IL-10, tumor necrosis factor (TNF); HPA axis dysfunction (cortisol), autonomic dysfunction (noradrenaline); oxidative stress (8-OH deoxyguanosine); insulin resistance markers (insulin, IGF-I, IGFBP3) and sexual hormones (estrogens, progesterone, testosterone). RESULTS: NLR (p = .00) and cortisol (p = .02) were positive and negatively associated with CRF, respectively. The rest of the blood markers were not associated with CRF. CONCLUSION: Our results increase the evidence on pathophysiological mechanisms driving CRF in BCS. However, longitudinal studies are needed to explore the role of these factors as potential causal mechanisms.

Association of Complement Factors With Disability Progression in Primary Progressive Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: The complement system is known to play a role in multiple sclerosis (MS) pathogenesis. However, its contribution to disease progression remains elusive. The study investigated the role of the complement system in disability progression of patients with primary progressive MS (PPMS). METHODS: Sixty-eight patients with PPMS from 12 European MS centers were included in the study. Serum and CSF levels of a panel of complement components (CCs) were measured by multiplex enzyme-linked immunosorbent assay at a baseline time point (i.e., sampling). Mean (SD) follow-up time from baseline was 9.6 (4.8) years. Only one patient (1.5%) was treated during follow-up. Univariable and multivariable logistic regressions adjusted for age, sex, and albumin quotient were performed to assess the association between baseline CC levels and disability progression in short term (2 years), medium term (6 years), and long term (at the time of the last follow-up). RESULTS: In short term, CC played little or no role in disability progression. In medium term, an elevated serum C3a/C3 ratio was associated with a higher risk of disability progression (adjusted OR 2.30; 95% CI 1.17-6.03; p = 0.040). By contrast, increased CSF C1q levels were associated with a trend toward reduced risk of disability progression (adjusted OR 0.43; 95% CI 0.17-0.98; p = 0.054). Similarly, in long term, an elevated serum C3a/C3 ratio was associated with higher risk of disability progression (adjusted OR 1.81; 95% CI 1.09-3.40; p = 0.037), and increased CSF C1q levels predicted lower disability progression (adjusted OR 0.41; 95% CI 0.17-0.86; p = 0.025). DISCUSSION: Proteins involved in the activation of early complement cascades play a role in disability progression as risk (elevated serum C3a/C3 ratio) or protective (elevated CSF C1q) factors after 6 or more years of follow-up in patients with PPMS. The protective effects associated with C1q levels in CSF may be related to its neuroprotective and anti-inflammatory properties.

Identification of fatty acid amide hydrolase as a metastasis suppressor in breast cancer.

Clinical management of breast cancer (BC) metastasis remains an unmet need as it accounts for 90% of BC-associated mortality. Although the luminal subtype, which represents >70% of BC cases, is generally associated with a favorable outcome, it is susceptible to metastatic relapse as late as 15 years after treatment discontinuation. Seeking therapeutic approaches as well as screening tools to properly identify those patients with a higher risk of recurrence is therefore essential. Here, we report that the lipid-degrading enzyme fatty acid amide hydrolase (FAAH) is a predictor of long-term survival in patients with luminal BC, and that it blocks tumor progression and lung metastasis in cell and mouse models of BC. Together, our findings highlight the potential of FAAH as a biomarker with prognostic value in luminal BC and as a therapeutic target in metastatic disease.

Impact of Non-Thermal Technologies on the Quality of Nuts: A Review.

Nuts are widely consumed worldwide, mainly due to their characteristic flavor and texture, ease of consumption, and their functional properties. In addition, consumers increasingly demand natural or slightly processed foods with high quality. Consequently, non-thermal treatments are a viable alternative to thermal treatments used to guarantee safety and long shelf life, which produce undesirable changes that affect the sensory quality of nuts. Non-thermal treatments can achieve results similar to those of the traditional (thermal) ones in terms of food safety, while ensuring minimal loss of bioactive compounds and sensory properties, thus obtaining a product as similar as possible to the fresh one. This article focuses on a review of the main non-thermal treatments currently available for nuts (cold plasma, high pressure, irradiation, pulsed electric field, pulsed light, ultrasound and ultraviolet light) in relation to their effects on the quality and safety of nuts. All the treatments studied have shown promise with regard to the inhibition of the main microorganisms affecting nuts (e.g., Aspergillus, Salmonella, and E. coli). Furthermore, by optimizing the treatment, it is possible to maintain the organoleptic and functional properties of these products.

C-Reactive Protein Is Associated with Physical Fitness in Breast Cancer Survivors.

Background: Physical fitness (PF) is an expression of the physiological functioning of multiple body components. PF is an important prognostic factor in terms of cardiovascular mortality, cancer mortality, and all-cause mortality. PF has been related to some biomarkers in the general population but not in breast cancer survivors (BCS). Purpose: To evaluate the effects of PF on biomarkers potentially related to physical activity (PA) in a sample of BCS. Methods: Cross-sectional study. A total of 84 BCS (mean age 54) who had finished their treatment were recruited. Different components of PF were evaluated, namely body composition (anthropometry), cardiorespiratory fitness (one-mile walk test), muscular (handgrip and sit-to-stand timed test), and motor (gait speed) components. Sexual hormones, inflammation, and insulin resistance biomarkers were measured. Results: C-Reactive Protein (CRP) was associated with every component of physical fitness: cardiorespiratory fitness (p-value = 0.002), muscular (sit-to-stand timed test, p-value = 0.002) and motor (gait speed, p-value = 0.004) components, and body composition (body mass index, p-value = 0.003; waist, p-value < 0.000; and waist-to-hip index, p-value = 0.012). CRP also was associated with "poor physical condition," a constructed variable that encompasses all components of physical fitness (p-value < 0.001). Insulin was associated with cardiorespiratory fitness and gait speed (p-values = 0.002 and 0.024, respectively). Insulin-like Growth Factor-1 was negatively associated with waist perimeter and waist-to-hip ratio. Conclusions: CRP can also be considered an indicator of poor PF in BCS. Implications for cancer survivors: in case of elevation of CRP indicating cardiovascular risk, health professionals should recommend lifestyle changes to improve BCS physical condition.

Polymorphisms in ACE, ACE2, AGTR1 genes and severity of COVID-19 disease.

BACKGROUND: Infection by the SARS-Cov-2 virus produces in humans a disease of highly variable and unpredictable severity. The presence of frequent genetic single nucleotide polymorphisms (SNPs) in the population might lead to a greater susceptibility to infection or an exaggerated inflammatory response. SARS-CoV-2 requires the presence of the ACE2 protein to enter in the cell and ACE2 is a regulator of the renin-angiotensin system. Accordingly, we studied the associations between 8 SNPs from AGTR1, ACE2 and ACE genes and the severity of the disease produced by the SARS-Cov-2 virus. METHODS: 318 (aged 59.6±17.3 years, males 62.6%) COVID-19 patients were grouped based on the severity of symptoms: Outpatients (n = 104, 32.7%), hospitalized on the wards (n = 73, 23.0%), Intensive Care Unit (ICU) (n = 84, 26.4%) and deceased (n = 57, 17.9%). Comorbidity data (diabetes, hypertension, obesity, lung disease and cancer) were collected for adjustment. Genotype distribution of 8 selected SNPs among the severity groups was analyzed. RESULTS: Four SNPs in ACE2 were associated with the severity of disease. While rs2074192 andrs1978124showed a protector effectassuming an overdominant model of inheritance (G/A vs. GG-AA, OR = 0.32, 95%CI = 0.12-0.82; p = 0.016 and A/G vs. AA-GG, OR = 0.37, 95%CI: 0.14-0.96; p = 0.038, respectively); the SNPs rs2106809 and rs2285666were associated with an increased risk of being hospitalized and a severity course of the disease with recessive models of inheritance (C/C vs. T/C-T/T, OR = 11.41, 95% CI: 1.12-115.91; p = 0.012) and (A/A vs. GG-G/A, OR = 12.61, 95% CI: 1.26-125.87; p = 0.0081). As expected, an older age (OR = 1.47), male gender (OR = 1.98) and comorbidities (OR = 2.52) increased the risk of being admitted to ICU or death vs more benign outpatient course. Multivariable analysis demonstrated the role of the certain genotypes (ACE2) with the severity of COVID-19 (OR: 0.31, OR 0.37 for rs2074192 and rs1978124, and OR = 2.67, OR = 2.70 for rs2106809 and rs2285666, respectively). Hardy-Weinberg equilibrium in hospitalized group for I/D SNP in ACE was not showed (p<0.05), which might be due to the association with the disease. No association between COVID-19 disease and the different AGTR1 SNPs was evidenced on multivariable, nevertheless the A/A genotype for rs5183 showed an higher hospitalization risk in patients with comorbidities. CONCLUSIONS: Different genetic variants in ACE2 were associated with a severe clinical course and death groups of patients with COVID-19. ACE2 common SNPs in the population might modulate severity of COVID-19 infection independently of other known markers like gender, age and comorbidities.

Exploring the potential relationship between collagen cross-linking and impaired myocardial relaxation in Marfan syndrome: An observational study using serum biomarkers.

BACKGROUND: Increased collagen cross-linking (CCL) has been described in hypertensive cardiomyopathy by means of reduced serum ratio of serum carboxyterminal telopeptide of collagen type I (CITP) to matrix metalloproteinase-1 (MMP1). Previous studies have demonstrated the existence of primary impaired diastole in patients with Marfan syndrome (MFS), but little is known about the pathophysiology of this condition. METHODS: 60 MFS patients (without previous cardiovascular surgery or significant valvular regurgitation) and 24 healthy controls (age and sex-matched) were enrolled. All participants underwent a comprehensive transthoracic echocardiographic study, including left atrial and left ventricular speckle-tracking strain analysis. CITP and MMP1 were measured in peripheral blood. RESULTS: All participants had normal diastolic function according to guidelines. Peak left atrial strain in the reservoir phase (LASr) was significantly reduced in the MFS cohort compared to controls (32.2 ± 9.4 vs 43.9 ± 7.0%; p < 0.001). Serum CITP and CITP:MMP1 ratio were lower among MFS patients, showing significant correlations with LASr (R = 0.311; p = 0.020 and R = 0.437; p = 0.001, respectively). The MFS cohort was divided into quartiles of LASr. MFS patients in the lowest quartile of LASr (<26%) had significantly lower values of CITP:MMP1 ratio compared to the other quartiles. CONCLUSIONS: The analysis of serum biomarkers revealed the presence of increased CCL in association with reduced LASr in the MFS cohort. Our results suggest that excessive CCL may play a role in the development of primary myocardial impairment in these patients. Future studies are needed to confirm our findings and evaluate the prognostic role of CCL markers in the MFS population.

Anticorrosion and Cytocompatibility Assessment of Graphene-Doped Hybrid Silica and Plasma Electrolytic Oxidation Coatings for Biomedical Applications.

Magnesium AZ31 alloy substrates were coated with different coatings, including sol-gel silica-reinforced with graphene nanoplatelets, sol-gel silica, plasma electrolytic oxidation (PEO), and combinations of them, to improve cytocompatibility and control the corrosion rate. Electrochemical corrosion tests, as well as hydrogen evolution tests, were carried out using Hanks' solution as the electrolyte to assess the anticorrosion behavior of the different coating systems in a simulated body fluid. Preliminary cytocompatibility assessment of the different coating systems was carried out by measuring the metabolic activity, deoxyribonucleic acid quantification, and the cell growth of premyoblastic C2C12-GFP cell cultures on the surface of the different coating systems. Anticorrosion behavior and cytocompatibility were improved with the application of the different coating systems. The use of combined PEO + SG and PEO + SG/GNP coatings significantly decreased the degradation of the specimens. The monolayer sol-gel coatings, with and without GNPs, presented the best cytocompatibility improvement.

Retinal degeneration in mice and humans with neuronal ceroid lipofuscinosis type 8.

BACKGROUND: Ceroid lipofuscinosis type 8 belongs to a heterogenous group of vision and life-threatening neurodegenerative diseases, neuronal ceroid lipofuscinosis (NCL). Effective therapy is limited to a single drug for treatment of ceroid lipofuscinosis type 2, necessitating animal disease models to facilitate further therapeutic development. Murine models are advantageous for therapeutic development due to easy genetic manipulation and rapid breeding, however appropriate genetic models need to be identified and characterized before being used for therapy testing. To date, murine models of ocular disease associated with ceroid lipofuscinosis type 8 have only been characterized in motor neuron degeneration mice. METHODS: Cln8-/- mice were produced by CRISPR/Cas9 genome editing through the International Mouse Phenotyping Consortium. Ophthalmic examination, optical coherence tomography, electroretinography, and ocular histology was performed on Cln8-/- mice and controls at 16 weeks of age. Quantification of all retinal layers, retinal pigmented epithelium, and the choriocapillaris was performed using images acquired with ocular coherence tomography and planimetry of histologic sections. Necropsy was performed to investigate concurrent systemic abnormalities. Clinical correlation with human patients with CLN8-associated retinopathy is provided. RESULTS: Retinal degeneration characterized by retinal pigment epithelium mottling, scattered drusen, and retinal vascular attenuation was noted in all Cln8-/- mice. Loss of inner and outer photoreceptor segment demarcation was noted on optical coherence tomography, with significant thinning of the whole retina (P=1e-9), outer nuclear layer (P=1e-9), and combined photoreceptor segments (P=1e-9). A global reduction in scotopic and photopic electroretinographic waveforms was noted in all Cln8-/- mice. Slight thickening of the inner plexiform layer (P=0.02) and inner nuclear layer (P=0.004), with significant thinning of the whole retina (P=0.03), outer nuclear layer (P=0.01), and outer photoreceptor segments (P=0.001) was appreciated on histologic sections. Scattered lipid vacuoles were noted in splenic red pulp of all Cln8-/- mice, though no gross systemic abnormalities were detected on necropsy. Retinal findings are consistent with those seen in patients with ceroid lipofuscinosis type 8. CONCLUSIONS: This study provides detailed clinical characterization of retinopathy in adult Cln8-/- mice. Findings suggest that Cln8-/- mice may provide a useful murine model for development of novel therapeutics needed for treating ocular disease in patients with ceroid lipofuscinosis type 8.

CSF Chitinase 3-Like 2 Is Associated With Long-term Disability Progression in Patients With Progressive Multiple Sclerosis.

OBJECTIVE: This study aimed to identify long-term prognostic protein biomarkers associated with disease progression in patients with progressive multiple sclerosis (MS). METHODS: CSF samples were collected from a discovery cohort of 28 patients with progressive MS who participated in a clinical trial with interferon beta. Patients were classified into high and low disability progression phenotypes according to numeric progression rates (NPR) and step-based progression rates (SPR) after a mean follow-up time of 12 years. Protein abundance was measured by shotgun proteomics. Selected proteins from the discovery cohort were quantified by parallel reaction monitoring in CSF samples from an independent validation cohort of 41 patients with progressive MS classified also into high and low disability progression phenotypes after a mean follow-up time of 7 years. RESULTS: Of 2,548 CSF proteins identified in the discovery cohort, 10 were selected for validation based on their association with long-term disability progression: SPATS2-like protein, chitinase 3-like 2 (CHI3L2), plasma serine protease inhibitor, metallothionein-3, phospholipase D4, beta-hexosaminidase, neurexophilin-1, adipocyte enhancer-binding protein 1, cathepsin L1, and lipopolysaccharide-binding protein. Only CHI3L2 was validated, and patients with high disability progression exhibited significantly higher CSF protein levels compared with patients with low disability progression (p = 0.03 for NPR and p = 0.02 for SPR). CHI3L2 levels showed good performance to discriminate between high and low disability progression in patients with progressive MS (area under the curve 0.73; sensitivity 90% and specificity 63%). CONCLUSIONS: Although further confirmatory studies are needed, we propose CSF CHI3L2 as a prognostic protein biomarker associated with long-term disability progression in patients with progressive MS. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that high CSF CHI3L2 levels identified higher disability progression in patients with progressive MS.

Evaluation of Pulsed Light to Inactivate Brettanomyces bruxellensis in White Wine and Assessment of Its Effects on Color and Aromatic Profile.

Brettanomyces bruxellensis is a wine spoilage yeast that could be inactivated by pulsed light (PL); however, this technology may induce changes in the quality of this alcoholic drink. The present research aimed to determine the potential of PL to inactivate B. bruxellensis inoculated in white wine and to assess the effect of this technology on the color and aromatic profile of the wine. For this, a cocktail of B. bruxellensis strains was inoculated into the wine and its inactivation by PL was determined and fitted to a microbial inactivation model. Along with this, the effect of PL on instrument-measured color, and the volatile compounds of the wine were evaluated by GC/MS and descriptive sensory analysis, respectively. B. bruxellensis was inactivated according to the Geeraerd model including the tail effect, with a maximum inactivation of 2.10 log reduction at 10.7 J/cm2; this fluence was selected for further studies. PL affected wine color but the total color difference was below the just noticeable difference at 10.7 J/cm2. The concentration of 13 out of 15 volatile compounds decreased due to the PL, which was noticeable by the panel. It is not clear if these compounds were photolyzed or volatilized in the open reactor during treatment. In conclusion, PL is able to inactivate B. bruxellensis in white wine but the treatment impairs the volatile profile. The use of a closed reactor under turbulent flow is recommended for disaggregating yeast clumps that may cause the tailing of the inactivation curve, and to avoid the possible escape of volatile compounds during treatment.

Machine Learning for Mortality Analysis in Patients with COVID-19.

This paper analyzes a sample of patients hospitalized with COVID-19 in the region of Madrid (Spain). Survival analysis, logistic regression, and machine learning techniques (both supervised and unsupervised) are applied to carry out the analysis where the endpoint variable is the reason for hospital discharge (home or deceased). The different methods applied show the importance of variables such as age, O2 saturation at Emergency Rooms (ER), and whether the patient comes from a nursing home. In addition, biclustering is used to globally analyze the patient-drug dataset, extracting segments of patients. We highlight the validity of the classifiers developed to predict the mortality, reaching an appreciable accuracy. Finally, interpretable decision rules for estimating the risk of mortality of patients can be obtained from the decision tree, which can be crucial in the prioritization of medical care and resources.

Serum endocannabinoid levels in suicide attempters: A pilot study.

The search for a biomarker for suicide risk is a longstanding pursuit in clinical psychiatry. Literature addressing the role of endocannabinoids in suicide attempters (SA) is sparse. This cross-sectional study is aimed at comparing 8 AM serum concentrations of 4 endogenous cannabinoids (anandamide, AEA; 2-arachidonoylglycerol, 2-AG; N-palmitoiletanolamida, PEA; and oleoylethanolamide, OEA) in 30 suicide attempters (SA) and 12 psychiatric controls (PC). 8 AM AEA and PEA serum levels were higher in SA compared to PC without controlling for cannabis use (n = 42) (3.58 ± 5.77 vs. 1.62 ± 2.49, F = 3.04, P = 0.089; and 3.31 ± 4.82 vs. 1.21 ± 1.20, F = 6.22, p = 0.017, respectively). Serum ACTH was higher in PC compared to SA (32.11 ± 21.60 vs. 20.05 ± 9.96, F = 9.031, p = 0.0.005). After controlling for cannabis use in the urine test (n = 28), 8 AM AEA and PEA serum levels remained higher in SA compared to PC (4.57 ± 6.38 vs. 0.64 ± 1.11, F = 4.852, P = 0.037; and 4.35 ± 5.46 vs. 1.21 ± 1.25, F = 4.125, p = 0.053, respectively). The present study offers preliminary evidence about the role of AEA and PEA in suicidal behavior (SB). Furthermore, in the context of the mental pain model of SB, our findings suggest that some endocannabinoids may play a role in the pathophysiology of SB. Our pilot study deserves replication by other studies with bigger sample sizes.