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Despite a growing interest in animal welfare in production systems, research on fish welfare remains limited, particularly in commercial fisheries. Fish caught in fixed-net fisheries experience multiple stressors from the time of capture to mortality on deck considered detrimental to their welfare. We examined the impact of bottom-set gill nets and on-board handling on catch welfare using behavioural and physiological indicators. Vitality assessments were performed on four commercially important fish species on-board fishing vessels through a devised vitality scale that included behaviours, morphological condition and reflexes as indicators of welfare. Physiological stress parameters (Cortisol, Glucose, Lactate and Osmolality) were evaluated in blood collected on deck and analysed in relation to the vitality scores. The vitality at arrival on deck as well as the rate of decrease in vitality differed significantly amongst the tested species. Furthermore, Generalised Linear Models predicted that several biological, operational, and environmental variables significantly affect the extent of time the fish shows activity, and hence, on the welfare. Elevated average cortisol levels were found at all the vitality stages highlighting the stress experienced by fish due to the fishing process. The findings of this study enable us to recommend welfare-friendly methods in set-net fisheries to promote better fishing standards.

Virus-based biopharmaceutical products are used in clinical applications such as vaccines, gene therapy, and immunotherapy. However, their manufacturing remains a challenge, hampered by the lack of appropriate analytical tools for purification monitoring or characterization of the final product. This paper describes the implementation of a highly sensitive method, capillary electrophoresis (CE)-sodium dodecyl sulfate (SDS) combined with a laser-induced fluorescence (LIF) detector to monitor the impact of various bioprocess steps on the quality of different viral vectors. The fluorescence labelling procedure uses the (3-(2-furoyl) quinoline-2-carboxaldehyde dye, and the CE-SDS LIF method enables the evaluation of in-process besides final product samples. This method outperforms other analytical methods, such as SDS–polyacrylamide gel electrophoresis with Sypro Ruby staining, in terms of sensitivity, resolution, and high-throughput capability. Notably, this CE-SDS LIF method was also successfully implemented to characterize enveloped viruses such as Maraba virus and lentivirus, whose development as biopharmaceuticals is now restricted by the lack of suitable analytical tools. This method was also qualified for quantification of rAAV2 according to the International Council for Harmonisation guidelines. Overall, our work shows that CE-SDS LIF is a precise and sensitive analytical platform for in-process sample analysis and quantification of different virus-based targets, with a great potential for application in biomanufacturing.

Background/Objectives: Sarcopenia is an emergent prognostic biomarker in clinical oncology. Albeit increasingly defined through skeletal muscle index (SMI) thresholding, the literature cut-offs fail to discern heterogeneous baseline muscularity across populations. This study assesses the prognostic impact of using cohort-specific SMI thresholds in a Portuguese metastatic non-small-cell lung cancer (mNSCLC) cohort. Methods: Retrospective study including mNSCLC patients treated between January 2017 and December 2022. ImageJ v1.54 g was used to assess cross-sectional CT imaging at the third lumbar vertebra (L3) and calculate L3SMI. Sarcopenia was defined both according to Prado et al. and L3SMI thresholds derived from receiver operating characteristic analysis. Overall survival (OS) was the primary endpoint. Secondary endpoints included first-line (1L) progression-free survival (PFS) and sarcopenia subgroup analysis regarding body mass index impact on OS. Results: The initial cohort included 197 patients. Mean age was 65 years (±11.31). Most tumors were adenocarcinomas (n = 165) and presented with metastasis (n = 154). SMI was evaluable in 184 patients: cohort-specific thresholds (<49.96 cm2/m2 for men; <34.02 cm2/m2 for women) yielded 46.74% sarcopenic patients (n = 86) versus 66.30% (n = 122) per the literature definition. Cohort-specific thresholds predicted both OS (12.75 versus 21.13 months, hazard ratio [HR] 1.654, p = 0.002) and PFS (7.92 versus 9.56 months, HR 1.503, p = 0.01). Among sarcopenic patients, overweight (HR 0.417, p = 0.01) and obesity (HR 2.723, p = 0.039) had contrasting impacts on OS. Conclusions: Amid reclassification of nearly one-fifth of the cohort, cohort-specific thresholds improved sarcopenia prognostication in mNSCLC. Homogeneity regarding both cancer treatment setting and ethnicity could be key to defining sarcopenia based on SMI.

Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16–36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10−7). These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources).

Predicting patient response to treatment and the onset of chemoresistance are still major challenges in oncology. Chemoresistance is deeply influenced by the complex cellular interactions occurring within the tumor microenvironment (TME), including metabolic crosstalk. We have previously shown that ex vivo tumor tissue cultures derived from ovarian carcinoma (OvC) resections retain the TME components for at least four weeks of culture and implemented assays for assessment of drug response. Here, we explored ex vivo patient-derived tumor tissue cultures to uncover metabolic signatures of chemosensitivity and/or resistance. Tissue cultures derived from nine OvC cases were challenged with carboplatin and paclitaxel, the standard-of-care chemotherapeutics, and the metabolic footprints were characterized by LC-MS. Partial least-squares discriminant analysis (PLS-DA) revealed metabolic signatures that discriminated high-responder from low-responder tissue cultures to ex vivo drug exposure. As a proof-of-concept, a set of potential metabolic biomarkers of drug response was identified based on the receiver operating characteristics (ROC) curve, comprising amino acids, fatty acids, pyrimidine, glutathione, and TCA cycle pathways. Overall, this work establishes an analytical and computational platform to explore metabolic features of the TME associated with response to treatment, which can leverage the discovery of biomarkers of drug response and resistance in OvC.

The intracellular misfolding and accumulation of alpha-synuclein into structures collectively called Lewy pathology (LP) is a central phenomenon for the pathogenesis of synucleinopathies, including Parkinson’s disease (PD) and dementia with Lewy bodies (DLB). Understanding the molecular architecture of LP is crucial for understanding synucleinopathy disease origins and progression. Here we used a technique called biotinylation by antibody recognition (BAR) to label total (BAR-SYN1) and pathological alpha-synuclein (BAR-PSER129) in situ for subsequent mass spectrometry analysis. Results showed superior immunohistochemical detection of LP following the BAR-PSER129 protocol, particularly for fibers and punctate pathology within the striatum and cortex. Mass spectrometry analysis of BAR-PSER129–labeled LP identified 261 significantly enriched proteins in the synucleinopathy brain when compared to nonsynucleinopathy brains. In contrast, BAR-SYN1 did not differentiate between disease and nonsynucleinopathy brains. Pathway analysis of BAR-PSER129–enriched proteins revealed enrichment for 718 pathways; notably, the most significant KEGG pathway was PD, and Gene Ontology (GO) cellular compartments were the vesicle, extracellular vesicle, extracellular exosome, and extracellular organelle. Pathway clustering revealed several superpathways, including metabolism, mitochondria, lysosome, and intracellular vesicle transport. Validation of the BAR-PSER129–identified protein hemoglobin beta (HBB) by immunohistochemistry confirmed the interaction of HBB with PSER129 Lewy neurites and Lewy bodies. In summary, BAR can be used to enrich for LP from formalin-fixed human primary tissues, which allowed the determination of molecular signatures of LP. This technique has broad potential to help understand the phenomenon of LP in primary human tissue and animal models.

Frontotemporal dementia is a heterogenous neurodegenerative disorder, with about a third of cases being genetic. Most of this genetic component is accounted for by mutations in GRN, MAPT, and C9orf72. In this study, we aimed to complement previous phenotypic studies by doing an international study of age at symptom onset, age at death, and disease duration in individuals with mutations in GRN, MAPT, and C9orf72. In this international, retrospective cohort study, we collected data on age at symptom onset, age at death, and disease duration for patients with pathogenic mutations in the GRN and MAPT genes and pathological expansions in the C9orf72 gene through the Frontotemporal Dementia Prevention Initiative and from published papers. We used mixed effects models to explore differences in age at onset, age at death, and disease duration between genetic groups and individual mutations. We also assessed correlations between the age at onset and at death of each individual and the age at onset and at death of their parents and the mean age at onset and at death of their family members. Lastly, we used mixed effects models to investigate the extent to which variability in age at onset and at death could be accounted for by family membership and the specific mutation carried. Data were available from 3403 individuals from 1492 families: 1433 with C9orf72 expansions (755 families), 1179 with GRN mutations (483 families, 130 different mutations), and 791 with MAPT mutations (254 families, 67 different mutations). Mean age at symptom onset and at death was 49·5 years (SD 10·0; onset) and 58·5 years (11·3; death) in the MAPT group, 58·2 years (9·8; onset) and 65·3 years (10·9; death) in the C9orf72 group, and 61·3 years (8·8; onset) and 68·8 years (9·7; death) in the GRN group. Mean disease duration was 6·4 years (SD 4·9) in the C9orf72 group, 7·1 years (3·9) in the GRN group, and 9·3 years (6·4) in the MAPT group. Individual age at onset and at death was significantly correlated with both parental age at onset and at death and with mean family age at onset and at death in all three groups, with a stronger correlation observed in the MAPT group (r=0·45 between individual and parental age at onset, r=0·63 between individual and mean family age at onset, r=0·58 between individual and parental age at death, and r=0·69 between individual and mean family age at death) than in either the C9orf72 group (r=0·32 individual and parental age at onset, r=0·36 individual and mean family age at onset, r=0·38 individual and parental age at death, and r=0·40 individual and mean family age at death) or the GRN group (r=0·22 individual and parental age at onset, r=0·18 individual and mean family age at onset, r=0·22 individual and parental age at death, and r=0·32 individual and mean family age at death). Modelling showed that the variability in age at onset and at death in the MAPT group was explained partly by the specific mutation (48%, 95% CI 35–62, for age at onset; 61%, 47–73, for age at death), and even more by family membership (66%, 56–75, for age at onset; 74%, 65–82, for age at death). In the GRN group, only 2% (0–10) of the variability of age at onset and 9% (3–21) of that of age of death was explained by the specific mutation, whereas 14% (9–22) of the variability of age at onset and 20% (12–30) of that of age at death was explained by family membership. In the C9orf72 group, family membership explained 17% (11–26) of the variability of age at onset and 19% (12–29) of that of age at death. Our study showed that age at symptom onset and at death of people with genetic frontotemporal dementia is influenced by genetic group and, particularly for MAPT mutations, by the specific mutation carried and by family membership. Although estimation of age at onset will be an important factor in future pre-symptomatic therapeutic trials for all three genetic groups, our study suggests that data from other members of the family will be particularly helpful only for individuals with MAPT mutations. Further work in identifying both genetic and environmental factors that modify phenotype in all groups will be important to improve such estimates. UK Medical Research Council, National Institute for Health Research, and Alzheimer's Society.

Neurofilament light chain (NfL) is a promising blood biomarker in genetic frontotemporal dementia, with elevated concentrations in symptomatic carriers of mutations in GRN, C9orf72, and MAPT. A better understanding of NfL dynamics is essential for upcoming therapeutic trials. We aimed to study longitudinal NfL trajectories in people with presymptomatic and symptomatic genetic frontotemporal dementia. We recruited participants from 14 centres collaborating in the Genetic Frontotemporal Dementia Initiative (GENFI), which is a multicentre cohort study of families with genetic frontotemporal dementia done across Europe and Canada. Eligible participants (aged ≥18 years) either had frontotemporal dementia due to a pathogenic mutation in GRN, C9orf72, or MAPT (symptomatic mutation carriers) or were healthy at-risk first-degree relatives (either presymptomatic mutation carriers or non-carriers), and had at least two serum samples with a time interval of 6 months or more. Participants were excluded if they had neurological comorbidities that were likely to affect NfL, including cerebrovascular events. We measured NfL longitudinally in serum samples collected between June 8, 2012, and Dec 8, 2017, through follow-up visits annually or every 2 years, which also included MRI and neuropsychological assessments. Using mixed-effects models, we analysed NfL changes over time and correlated them with longitudinal imaging and clinical parameters, controlling for age, sex, and study site. The primary outcome was the course of NfL over time in the various stages of genetic frontotemporal dementia. We included 59 symptomatic carriers and 149 presymptomatic carriers of a mutation in GRN, C9orf72, or MAPT, and 127 non-carriers. Nine presymptomatic carriers became symptomatic during follow-up (so-called converters). Baseline NfL was elevated in symptomatic carriers (median 52 pg/mL [IQR 24–69]) compared with presymptomatic carriers (9 pg/mL [6–13]; p<0·0001) and non-carriers (8 pg/mL [6–11]; p<0·0001), and was higher in converters than in non-converting carriers (19 pg/mL [17–28] vs 8 pg/mL [6–11]; p=0·0007; adjusted for age). During follow-up, NfL increased in converters (b=0·097 [SE 0·018]; p<0·0001). In symptomatic mutation carriers overall, NfL did not change during follow-up (b=0·017 [SE 0·010]; p=0·101) and remained elevated. Rates of NfL change over time were associated with rate of decline in Mini Mental State Examination (b=–94·7 [SE 33·9]; p=0·003) and atrophy rate in several grey matter regions, but not with change in Frontotemporal Lobar Degeneration-Clinical Dementia Rating scale score (b=–3·46 [SE 46·3]; p=0·941). Our findings show the value of blood NfL as a disease progression biomarker in genetic frontotemporal dementia and suggest that longitudinal NfL measurements could identify mutation carriers approaching symptom onset and capture rates of brain atrophy. The characterisation of NfL over the course of disease provides valuable information for its use as a treatment effect marker. ZonMw and the Bluefield project.