Search Results (7)

Huntington’s disease (HD) is characterized by progressive striatal atrophy and complex proteomic changes in the central nervous system. Using the ultrasensitive Next-Gen Ultra-Sensitive Immunoassay (NULISA) proteomic platform, we analyzed cerebrospinal fluid (CSF) from 88 persons with HD to dissect the biological correlates of gray matter loss. Our findings reveal a distinct “Two-Track” model of pathology. The first track, marked by the axonal damage protein neurofilament light chain (NEFL), showed a strong inverse correlation with putamen volume (Pearson r = −0.53, p < 0.001), reinforcing its utility as a proxy for structural neurodegeneration. The second track was defined by a positive association between the immune regulator TNFRSF8 (CD30) and putamen volume (Pearson r = 0.36, p < 0.001), reflecting a decline in active immune-regulatory signaling as striatal atrophy advances. Given its established role in immune modulation, TNFRSF8 was pre-specified for follow-up to further interrogate this neuro-immune axis. Crucially, TNFRSF8 maintained an independent association with striatal volume (Beta = 0.24, p = 0.008) even after controlling for NEFL, genetic burden (CAG-Age Product score), and sex. Supplementary analyses confirmed that this structural–immune axis is localized specifically to the striatum—showing no association with generic structural control regions—and is driven by CAG repeat length rather than chronological aging. Furthermore, bidirectional mediation analysis supported an atrophy-driven model, where striatal volume statistically mediates the relationship between genetic burden and downstream immune dysregulation (p = 0.010). These results demonstrate that maladaptive immune signaling is a distinct pathological correlate in HD, separable from general cytoskeletal damage. This dual-axis framework warrants evaluation in larger longitudinal and interventional studies to guide future biomarker-driven patient stratification and target engagement. Full article

Persistent and chronic hyperglycaemia in Type II diabetic mellitus (DM) is known to cause oxidative stress, which exacerbates underlying metabolic disorders, contributing to the progression of complications such as diabetic peripheral neuropathy (DPN). Palm tocotrienol-rich fraction (TRF) is renowned for its potent antioxidative and neuroprotective properties and might have the potential to halt or mitigate the severity of DPN. This study aimed to investigate the effects of palm TRF on diabetic rats with peripheral neuropathy and to identify the correlation between plasma metabolomic alterations and DPN parameters. Male Sprague Dawley (SD) rats were randomly divided into normal control and DM groups in which Type II DM was induced using a high-fat diet and a low-dose streptozotocin (STZ) (35 mg/kg). Successful diabetic rats were randomly divided and received daily oral treatments of palm olein (vehicle), metformin (70 mg/kg), TRF (60 mg/kg), or a combination of TRF and metformin for 12 weeks. Behavioural parameters, serum biomarkers, and plasma metabolomic profiling were assessed at 0 (baseline) and 12 weeks of intervention. From the behavioural parameters, improvement in the symptoms of thermal hyperalgesia and mechanical allodynia was seen with TRF interventions, either alone or in combination with metformin. A significant reduction in the neurofilament light (NEFL) chain, accompanied by a notable increase in nerve growth factor (NGF) levels in the serum of treatment groups, was also observed. From the plasma samples, findings reveal that TRF increases metabolites related to neurotransmitter pathways (acetylcholine, choline, phenylalanine, tryptophan) and decreases inflammatory metabolites (kynurenine, prostaglandin) compared to untreated diabetic rats. These metabolites, except for prostaglandin, showed positive correlations with pain sensitivity. In contrast, prostaglandin showed opposite correlations with pain and nerve damage markers, suggesting its potential role in inflammation and axonal injury. Full article

Intraventricular hemorrhage (IVH) in preterm neonates presents a high risk for developing posthemorrhagic ventricular dilatation (PHVD), a severe complication that can impact survival and long-term outcomes. Early detection of PHVD before clinical onset is crucial for optimizing therapeutic interventions and providing accurate parental counseling. This study explores the potential of explainable machine learning models based on targeted liquid biopsy proteomics data to predict outcomes in preterm neonates with IVH. In recent years, research has focused on leveraging advanced proteomic technologies and machine learning to improve prediction of neonatal complications, particularly in relation to neurological outcomes. Machine learning (ML) approaches, combined with proteomics, offer a powerful tool to identify biomarkers and predict patient-specific risks. However, challenges remain in integrating large-scale, multiomic datasets and translating these findings into actionable clinical tools. Identifying reliable, disease-specific biomarkers and developing explainable ML models that clinicians can trust and understand are key barriers to widespread clinical adoption. In this prospective longitudinal cohort study, we analyzed 1109 liquid biopsy samples from 99 preterm neonates with IVH, collected at up to six timepoints over 13 years. Various explainable ML techniques—including statistical, regularization, deep learning, decision trees, and Bayesian methods—were employed to predict PHVD development and survival and to discover disease-specific protein biomarkers. Targeted proteomic analyses were conducted using serum and urine samples through a proximity extension assay capable of detecting low-concentration proteins in complex biofluids. The study identified 41 significant independent protein markers in the 1600 calculated ML models that surpassed our rigorous threshold (AUC-ROC of ≥0.7, sensitivity ≥ 0.6, and selectivity ≥ 0.6), alongside gestational age at birth, as predictive of PHVD development and survival. Both known biomarkers, such as neurofilament light chain (NEFL), and novel biomarkers were revealed. These findings underscore the potential of targeted proteomics combined with ML to enhance clinical decision-making and parental counseling, though further validation is required before clinical implementation. Full article

Adipose-derived mesenchymal stem cells (ADSCs), which tended to neurogenically differentiate spontaneously after achieving high confluence, were observed. Human ADSCs reaching 80% confluence were cultured in DMEM without an inducing factor for 24 h and then maintained in DMEM plus 1% FBS medium for 7 days. The neurogenic, adipogenic, and osteogenic genes of the factor-induced and confluence-initiated differentiation of the ADSCs and bone marrow-derived mesenchymal stem cells (BMSCs) at passages 3 to 5 were determined and compared using RT-qPCR, and the neurogenic differentiation was confirmed using immunofluorescent staining. In vitro tests revealed that the RNA and protein expression of neuronal markers, including class III β-tubulin (TUBB3), microtubule-associated protein 2 (MAP2), neurofilament medium polypeptide (NEFM), neurofilament heavy polypeptide (NEFH), and neurofilament light polypeptide (NEFL), had been enhanced in the confluence-initiated differentiation of the ADSCs. In addition, the expressions of neurotrophins, such as the nerve growth factor (NGF), brain-derived neurotrophic factor (BDNF), and glial cell-derived neurotrophic factor (GDNF), were also elevated in the confluence-initiated differentiation of the ADSCs. However, the confluent ADSCs did not show a tendency toward spontaneous adipogenic and osteogenic differentiation. Moreover, compared with the confluent ADSCs, the tendency of spontaneous neurogenic, adipogenic, and osteogenic differentiation of the confluent human bone marrow mesenchymal stem cells (BMSCs) was not observed. The results indicated that ADSCs had the potential to spontaneously differentiate into neuron-like cells during the confluent culture period; however, this tendency was not observed in BMSCs. Full article

Neurofilaments (NFs), a major cytoskeletal component of motor neurons, play a key role in the differentiation, establishment and maintenance of their morphology and mechanical strength. The de novo assembly of these neuronal intermediate filaments requires the presence of the neurofilament light subunit (NEFL), whose expression is reduced in motor neurons in amyotrophic lateral sclerosis (ALS). This study used zebrafish as a model to characterize the NEFL homologue neflb, which encodes two different isoforms via a splicing of the primary transcript (neflbE4 and neflbE3). In vivo imaging showed that neflb is crucial for proper neuronal development, and that disrupting the balance between its two isoforms specifically affects the NF assembly and motor axon growth, with resultant motor deficits. This equilibrium is also disrupted upon the partial depletion of TDP-43 (TAR DNA-binding protein 43), an RNA-binding protein encoded by the gene TARDBP that is mislocalized into cytoplasmic inclusions in ALS. The study supports the interaction of the NEFL expression and splicing with TDP-43 in a common pathway, both biologically and pathogenetically. Full article

The search to date for accurate protein biomarkers in acute ischemic stroke has taken into consideration the stage and/or the size of infarction, but has not accounted for the site of stroke. In the present study, multiple reaction monitoring using labeled reference peptide (LRP) following laser capture microdissection (LCM) is used to identify site-specific protein biomarker candidates. In middle cerebral artery occlusion (MCAO) rat models, both intact and infarcted brain tissue was collected by LCM, followed by on-film digestion and semi-quantification using triple-quadrupole mass spectrometry. Thirty-four unique peptides were detected for the verification of 12 proteins in both tissue homogenates and LCM-captured samples. Six insoluble proteins, including neurofilament light polypeptide (NEFL), alpha-internexin (INA), microtubule-associated protein 2 (MAP2), myelin basic protein (MBP), myelin proteolipid protein (PLP) and 2′,3′-cyclic-nucleotide 3′-phosphodiesterase (CNP), were found to be site-specific. Soluble proteins, such as neuron-specific enolase (NSE) and ubiquitin carboxyl-terminal hydrolase isozyme L1 (UCHL1), and some insoluble proteins, including neurofilament heavy polypeptide (NEFH), glial fibrillary acidic protein (GFAP), microtubule-associated protein tau (MAPT) and tubulin β-3 chain (TUBB3), were found to be evenly distributed in the brain. Therefore, we conclude that some insoluble protein biomarkers for stroke are site-specific, and would make excellent candidates for the design and analysis of relevant clinical studies in the future. Full article

MicroRNAs (miRNAs) are small non-coding RNAs that regulate the majority of the transcriptome at a post-transcriptional level. Because of this critical role, it is important to ensure that the assays used to determine their functionality are robust and reproducible. Typically, the reporter gene assay in cell-based systems has been the first-line method to study miRNA functionality. In order to overcome some of the potential errors in interpretation that can be associated with this assay, we have developed a detailed protocol for the luciferase reporter gene assay that has been modified for miRNAs. We demonstrate that normalization against the effect of the miRNA and cellular factors on the luciferase coding sequence is essential to obtain the specific impact of the miRNA on the 3'UTR (untranslated region) target. Our findings suggest that there is a real possibility that the roles for miRNA in transcriptome regulation may be misreported due to inaccurate normalization of experimental data and also that up-regulatory effects of miRNAs are not uncommon in cells. We propose to establish this comprehensive method as standard for miRNA luciferase reporter assays to avoid errors and misinterpretations in the functionality of miRNAs. Full article