A deep learning dataset for sample preparation artefacts detection in multispectral high-content microscopy.

High-content image-based screening is widely used in Drug Discovery and Systems Biology. However, sample preparation artefacts may significantly deteriorate the quality of image-based screening assays. While detection and circumvention of such artefacts could be addressed using modern-day machine learning and deep learning algorithms, this is widely impeded by the lack of suitable datasets. To address this, here we present a purpose-created open dataset of high-content microscopy sample preparation artefact. It consists of high-content microscopy of laboratory dust titrated on fixed cell culture specimens imaged with fluorescence filters covering the complete spectral range. To ensure this dataset is suitable for supervised machine learning tasks like image classification or segmentation we propose rule-based annotation strategies on categorical and pixel levels. We demonstrate the applicability of our dataset for deep learning by training a convolutional-neural-network-based classifier.

Circulating plasma miR-23b-3p as a biomarker target for idiopathic Parkinson's disease: comparison with small extracellular vesicle miRNA.

Background: Parkinson's disease (PD) is an increasingly common neurodegenerative condition, which causes movement dysfunction and a broad range of non-motor symptoms. There is no molecular or biochemical diagnosis test for PD. The miRNAs are a class of small non-coding RNAs and are extensively studied owing to their altered expression in pathological states and facile harvesting and analysis techniques. Methods: A total of 48 samples (16 each of PD, aged-matched, and young controls) were recruited. The small extracellular vesicles (sEVs) were isolated and validated using Western blot, transmission electron microscope, and nanoparticle tracking analysis. Small RNA isolation, library preparation, and small RNA sequencing followed by differential expression and targeted prediction of miRNA were performed. The real-time PCR was performed with the targeted miRNA on PD, age-matched, and young healthy control of plasma and plasma-derived sEVs to demonstrate their potential as a diagnostic biomarker. Results: In RNA sequencing, we identified 14.89% upregulated (fold change 1.11 to 11.04, p < 0.05) and 16.54% downregulated (fold change -1.04 to -7.28, p < 0.05) miRNAs in PD and controls. Four differentially expressed miRNAs (miR-23b-3p, miR-29a-3p, miR-19b-3p, and miR-150-3p) were selected. The expression of miR-23b-3p was "upregulated" (p = 0.002) in plasma, whereas "downregulated" (p = 0.0284) in plasma-derived sEVs in PD than age-matched controls. The ROC analysis of miR-23b-3p revealed better AUC values in plasma (AUC = 0.8086, p = 0.0029) and plasma-derived sEVs (AUC = 0.7278, p = 0.0483) of PD and age-matched controls. Conclusion: We observed an opposite expression profile of miR-23b-3p in PD and age-matched healthy control in plasma and plasma-derived sEV fractions, where the expression of miR-23b-3p is increased in PD plasma while decreased in plasma-derived sEV fractions. We further observed the different miR-23b-3p expression profiles in young and age-matched healthy control.

An integrated pipeline for prediction of Clostridioides difficile infection.

With the expansion of electronic health records(EHR)-linked genomic data comes the development of machine learning-enable models. There is a pressing need to develop robust pipelines to evaluate the performance of integrated models and minimize systemic bias. We developed a prediction model of symptomatic Clostridioides difficile infection(CDI) by integrating common EHR-based and genetic risk factors(rs2227306/IL8). Our pipeline includes (1) leveraging phenotyping algorithm to minimize temporal bias, (2) performing simulation studies to determine the predictive power in samples without genetic information, (3) propensity score matching to control for the confoundings, (4) selecting machine learning algorithms to capture complex feature interactions, (5) performing oversampling to address data imbalance, and (6) optimizing models and ensuring proper bias-variance trade-off. We evaluate the performance of prediction models of CDI when including common clinical risk factors and the benefit of incorporating genetic feature(s) into the models. We emphasize the importance of building a robust integrated pipeline to avoid systemic bias and thoroughly evaluating genetic features when integrated into the prediction models in the general population and subgroups.

Fluorescence-tagged salivary small extracellular vesicles as a nanotool in early diagnosis of Parkinson's disease.

BACKGROUND: Parkinson's disease is generally asymptomatic at earlier stages. At an early stage, there is an extensive progression in the neuropathological hallmarks, although, at this stage, diagnosis is not possible with currently available diagnostic methods. Therefore, the pressing need is for susceptibility risk biomarkers that can aid in better diagnosis and therapeutics as well can objectively serve to measure the endpoint of disease progression. The role of small extracellular vesicles (sEV) in the progression of neurodegenerative diseases could be potent in playing a revolutionary role in biomarker discovery. METHODS: In our study, the salivary sEV were efficiently isolated by chemical precipitation combined with ultrafiltration from subjects (PD = 70, healthy controls = 26, and prodromal PD = 08), followed by antibody-based validation with CD63, CD9, GAPDH, Flotillin-1, and L1CAM. Morphological characterization of the isolated sEV through transmission electron microscopy. The quantification of sEV was achieved by fluorescence (lipid-binding dye-labeled) nanoparticle tracking analysis and antibody-based (CD63 Alexa fluor 488 tagged sEV) nanoparticle tracking analysis. The total alpha-synuclein (α-synTotal) in salivary sEVs cargo was quantified by ELISA. The disease severity staging confirmation for n = 18 clinically diagnosed Parkinson's disease patients was done by 99mTc-TRODAT-single-photon emission computed tomography. RESULTS: We observed a significant increase in total sEVs concentration in PD patients than in the healthy control (HC), where fluorescence lipid-binding dye-tagged sEV were observed to be higher in PD (p = 0.0001) than in the HC using NTA with a sensitivity of 94.34%. In the prodromal PD cases, the fluorescence lipid-binding dye-tagged sEV concentration was found to be higher (p = 0.008) than in HC. This result was validated through anti-CD63 tagged sEV (p = 0.0006) with similar sensitivity of 94.12%. We further validated our findings with the ELISA based on α-synTotal concentration in sEV, where it was observed to be higher in PD (p = 0.004) with a sensitivity of 88.24%. The caudate binding ratios in 99mTc-TRODAT-SPECT represent a positive correlation with sEV concentration (r = 0.8117 with p = 0.0112). CONCLUSIONS: In this study, for the first time, we have found that the fluorescence-tagged sEV has the potential to screen the progression of disease with clinically acceptable sensitivity and can be a potent early detection method for PD.

Rotational and translational drags of a Janus particle close to a wall and a lipid membrane.

HYPOTHESIS: Measuring rotational and translational Brownian motion of single spherical particles reveals dissipations due to the interaction between the particle and the environment. EXPERIMENTS: In this article, we show experiments where the in-plane translational and the two rotational drag coefficients of a single spherical Brownian particle can be measured. These particle drags are functions of the particle size and of the particle-wall distance, and of the viscous dissipations at play. We measure drag coefficients for Janus particles close to a solid wall and close to a lipid bilayer membrane. FINDINGS: For a particle close to a wall, we show that according to hydrodynamic models, particle-wall distance and particle size can be determined. For a particle partially wrapped by lipid membranes, in absence of strong binding interactions, translational and rotational drags are significantly larger than the ones of non-wrapped particles. Beside the effect of the membrane viscosity, we show that dissipations in the deformed membrane cap region strongly contribute to the drag coefficients.

Entry of microparticles into giant lipid vesicles by optical tweezers.

Entry of micro- or nanosized objects into cells or vesicles made of lipid membranes occurs in many processes such as entry of viruses into host cells, microplastics pollution, drug delivery, or biomedical imaging. Here we investigate the microparticle crossing of lipid membranes in giant unilamellar vesicles in the absence of strong binding interactions (e.g., streptavidin-biotin binding). In these conditions, we observe that organic and inorganic particles can always penetrate inside the vesicles provided an external piconewton force is applied and for relatively low membrane tensions. In the limit of vanishing adhesion, we identify the role of the membrane area reservoir and show that a force minimum exists when the particle size is comparable to the bendocapillary length.

Electrically controlled dual-mode polarization beam splitter using a nematic liquid crystal.

Polarization handling using an external source is highly desirable in applied optics and photonics to increase the degree of freedom of an optical system. Here we report an electrically controlled polarization beam splitter (PBS) by sandwiching the nematic liquid crystal (LC) between two equilateral prisms. The presented LC-PBS is operated in two different modes: non-splitting mode and polarization splitting mode. The externally applied voltage can switch the mode of the PBS, which makes the device active and flexible. The proposed electrically controlled PBS exhibits features such as bistability with highly stable modes, large splitting angle, wider operating range, and ease of fabrication with lower cost.

Osteogenic markers in peri-implant crevicular fluid in immediate and delayed-loaded dental implants: A randomized controlled trial.

INTRODUCTION: The study evaluates the levels of matrix metalloprotease-8 (MMP-8), and Cathepsin-K (CatK) in peri-implant crevicular fluid (PICF) among patients with immediate loaded (IL) and delayed-loaded (DL) implants at different time points to know the inflammation and osteogenic status. METHODS: The study population consisted of two groups (n = 25, each group) with a mean age of 28.7 ± 3.5 years, and PICF was collected. MMP-8 and CatK levels were quantified through ELISA. RESULTS: We observed the concentrations of inflammatory markers (MMP-8 and CatK) at three time points in the IL and DL groups. The mean concentration of MMP-8 in the IL group was 9468 ± 1230 pg/mL, 5547 ± 1088 pg/mL, and 7248 ± 1396 pg/mL at 2 weeks, 3 months, and 12 months, respectively; while in the DL group was 10 816 ± 779.7 pg/mL, 9531 ± 1245 pg/mL, and 9132 ± 1265 pg/mL at 2 weeks, 3 and 12 months, respectively. The mean concentration of Cat-K in the IL group was observed at 422.1 ± 36.46 pg/mL, 242.9 ± 25.87 pg/mL, and 469 ± 75.38 pg/mL at 2 weeks, 3, and 12 months, whereas in the DL group was 654.6 ± 152.9 pg/mL, 314.7 ± 28.29 pg/mL, and 539.8 ± 115.1 pg/mL at 2 weeks, 3 months and 12 months, respectively. CONCLUSION: In this study, the levels of CatK and MMP-8 levels decline at 12 months in both groups, and the IL group shows lower values compared to the DL group; however, no significant changes were observed after analyses were adjusted for multiple comparisons (p > 0.025). Therefore, there is not much difference observed in the inflammation process between immediate and delayed loading. (Clinical trial identifier: CTRI/2017/09/009668).

Development and validation of echocardiography-based machine-learning models to predict mortality.

BACKGROUND: Echocardiography (echo) based machine learning (ML) models may be useful in identifying patients at high-risk of all-cause mortality. METHODS: We developed ML models (ResNet deep learning using echo videos and CatBoost gradient boosting using echo measurements) to predict 1-year, 3-year, and 5-year mortality. Models were trained on the Mackay dataset, Taiwan (6083 echos, 3626 patients) and validated in the Alberta HEART dataset, Canada (997 echos, 595 patients). We examined the performance of the models overall, and in subgroups (healthy controls, at risk of heart failure (HF), HF with reduced ejection fraction (HFrEF) and HF with preserved ejection fraction (HFpEF)). We compared the models' performance to the MAGGIC risk score, and examined the correlation between the models' predicted probability of death and baseline quality of life as measured by the Kansas City Cardiomyopathy Questionnaire (KCCQ). FINDINGS: Mortality rates at 1-, 3- and 5-years were 14.9%, 28.6%, and 42.5% in the Mackay cohort, and 3.0%, 10.3%, and 18.7%, in the Alberta HEART cohort. The ResNet and CatBoost models achieved area under the receiver-operating curve (AUROC) between 85% and 92% in internal validation. In external validation, the AUROCs for the ResNet (82%, 82%, and 78%) were significantly better than CatBoost (78%, 73%, and 75%), for 1-, 3- and 5-year mortality prediction respectively, with better or comparable performance to the MAGGIC score. ResNet models predicted higher probability of death in the HFpEF and HFrEF (30%-50%) subgroups than in controls and at risk patients (5%-20%). The predicted probabilities of death correlated with KCCQ scores (all p < 0.05). INTERPRETATION: Echo-based ML models to predict mortality had good internal and external validity, were generalizable, correlated with patients' quality of life, and are comparable to an established HF risk score. These models can be leveraged for automated risk stratification at point-of-care. FUNDING: Funding for Alberta HEART was provided by an Alberta Innovates - Health Solutions Interdisciplinary Team Grant no. AHFMRITG 200801018. P.K. holds a Canadian Institutes of Health Research (CIHR) Sex and Gender Science Chair and a Heart & Stroke Foundation Chair in Cardiovascular Research. A.V. and V.S. received funding from the Mitacs Globalink Research Internship.

A neurodevelopmental epigenetic programme mediated by SMARCD3-DAB1-Reelin signalling is hijacked to promote medulloblastoma metastasis.

How abnormal neurodevelopment relates to the tumour aggressiveness of medulloblastoma (MB), the most common type of embryonal tumour, remains elusive. Here we uncover a neurodevelopmental epigenomic programme that is hijacked to induce MB metastatic dissemination. Unsupervised analyses of integrated publicly available datasets with our newly generated data reveal that SMARCD3 (also known as BAF60C) regulates Disabled 1 (DAB1)-mediated Reelin signalling in Purkinje cell migration and MB metastasis by orchestrating cis-regulatory elements at the DAB1 locus. We further identify that a core set of transcription factors, enhancer of zeste homologue 2 (EZH2) and nuclear factor I X (NFIX), coordinates with the cis-regulatory elements at the SMARCD3 locus to form a chromatin hub to control SMARCD3 expression in the developing cerebellum and in metastatic MB. Increased SMARCD3 expression activates Reelin-DAB1-mediated Src kinase signalling, which results in a MB response to Src inhibition. These data deepen our understanding of how neurodevelopmental programming influences disease progression and provide a potential therapeutic option for patients with MB.

Employing nanoparticle tracking analysis of salivary neuronal exosomes for early detection of neurodegenerative diseases.

Neurodegenerative diseases are a set of progressive and currently incurable diseases that are primarily caused by neuron degeneration. Neurodegenerative diseases often lead to cognitive impairment and dyskinesias. It is now well recognized that molecular events precede the onset of clinical symptoms by years. Over the past decade, intensive research attempts have been aimed at the early diagnosis of these diseases. Recently, exosomes have been shown to play a pivotal role in the occurrence and progression of many diseases including cancer and neurodegenerative diseases. Additionally, because exosomes can cross the blood-brain barrier, they may serve as a diagnostic tool for neural dysfunction. In this review, we detail the mechanisms and current challenges of these diseases, briefly review the role of exosomes in the progression of neurodegenerative diseases, and propose a novel strategy based on salivary neuronal exosomes and nanoparticle tracking analysis that could be employed for screening the early onset of neurodegenerative diseases.

Social isolation is linked to classical risk factors of Alzheimer's disease-related dementias.

Alzheimer's disease and related dementias is a major public health burden-compounding over upcoming years due to longevity. Recently, clinical evidence hinted at the experience of social isolation in expediting dementia onset. In 502,506 UK Biobank participants and 30,097 participants from the Canadian Longitudinal Study of Aging, we revisited traditional risk factors for developing dementia in the context of loneliness and lacking social support. Across these measures of subjective and objective social deprivation, we have identified strong links between individuals' social capital and various indicators of Alzheimer's disease and related dementias risk, which replicated across both population cohorts. The quality and quantity of daily social encounters had deep connections with key aetiopathological factors, which represent 1) personal habits and lifestyle factors, 2) physical health, 3) mental health, and 4) societal and external factors. Our population-scale assessment suggest that social lifestyle determinants are linked to most neurodegeneration risk factors, highlighting them as promising targets for preventive clinical action.

Dissociable brain structural asymmetry patterns reveal unique phenome-wide profiles.

Broca reported ~150 years ago that particular lesions of the left hemisphere impair speech. Since then, other brain regions have been reported to show lateralized structure and function. Yet, studies of brain asymmetry have limited their focus to pairwise comparisons between homologous regions. Here, we characterized separable whole-brain asymmetry patterns in grey and white matter structure from n = 37,441 UK Biobank participants. By pooling information on left-right shifts underlying whole-brain structure, we deconvolved signatures of brain asymmetry that are spatially distributed rather than locally constrained. Classically asymmetric regions turned out to belong to more than one asymmetry pattern. Instead of a single dominant signature, we discovered complementary asymmetry patterns that contributed similarly to whole-brain asymmetry at the population level. These asymmetry patterns were associated with unique collections of phenotypes, ranging from early lifestyle factors to demographic status to mental health indicators.

APOE alleles are associated with sex-specific structural differences in brain regions affected in Alzheimer's disease and related dementia.

Alzheimer's disease is marked by intracellular tau aggregates in the medial temporal lobe (MTL) and extracellular amyloid aggregates in the default network (DN). Here, we examined codependent structural variations between the MTL's most vulnerable structure, the hippocampus (HC), and the DN at subregion resolution in individuals with Alzheimer's disease and related dementia (ADRD). By leveraging the power of the approximately 40,000 participants of the UK Biobank cohort, we assessed impacts from the protective APOE ɛ2 and the deleterious APOE ɛ4 Alzheimer's disease alleles on these structural relationships. We demonstrate ɛ2 and ɛ4 genotype effects on the inter-individual expression of HC-DN co-variation structural patterns at the population level. Across these HC-DN signatures, recurrent deviations in the CA1, CA2/3, molecular layer, fornix's fimbria, and their cortical partners related to ADRD risk. Analyses of the rich phenotypic profiles in the UK Biobank cohort further revealed male-specific HC-DN associations with air pollution and female-specific associations with cardiovascular traits. We also showed that APOE ɛ2/2 interacts preferentially with HC-DN co-variation patterns in estimating social lifestyle in males and physical activity in females. Our structural, genetic, and phenotypic analyses in this large epidemiological cohort reinvigorate the often-neglected interplay between APOE ɛ2 dosage and sex and link APOE alleles to inter-individual brain structural differences indicative of ADRD familial risk.

Open-Source Biomedical Image Analysis Models: A Meta-Analysis and Continuous Survey.

Open-source research software has proven indispensable in modern biomedical image analysis. A multitude of open-source platforms drive image analysis pipelines and help disseminate novel analytical approaches and algorithms. Recent advances in machine learning allow for unprecedented improvement in these approaches. However, these novel algorithms come with new requirements in order to remain open source. To understand how these requirements are met, we have collected 50 biomedical image analysis models and performed a meta-analysis of their respective papers, source code, dataset, and trained model parameters. We concluded that while there are many positive trends in openness, only a fraction of all publications makes all necessary elements available to the research community.

Altered neural cell junctions and ion-channels leading to disrupted neuron communication in Parkinson's disease.

Parkinson's disease (PD) is a neurological disorder that affects the movement of the human body. It is primarily characterized by reduced dopamine levels in the brain. The causative agent of PD is still unclear but it is generally accepted that α-synuclein has a central role to play. It is also known that gap-junctions and associated connexins are complicated structures that play critical roles in nervous system signaling and associated misfunctioning. Thus, our current article emphasizes how, alongside α-synuclein, ion-channels, gap-junctions, and related connexins, all play vital roles in influencing multiple metabolic activities of the brain during PD. It also highlights that ion-channel and gap-junction disruptions, which are primarily mediated by their structural-functional changes and alterations, have a role in PD. Furthermore, we discussed available drugs and advanced therapeutic interventions that target Parkinson's pathogenesis. In conclusion, it warrants creating better treatments for PD patients. Although, dopaminergic replenishment therapy is useful in treating neurological problems, such therapies are, however, unable to control the degeneration that underpins the disease, thereby declining their overall efficacy. This creates an additional challenge and an untapped scope for neurologists to adopt treatments for PD by targeting the ion-channels and gap-junctions, which is well-reviewed in the present article.

Phylogenomics of the Phylum Proteobacteria: Resolving the Complex Relationships.

Proteobacteria is one of the largest and phenotypically most diverse divisions within the domain bacteria. Due to the economic importance, this phylum demands an urgent need for a clear and scientifically sound classification system to streamline their characterization. The goal of our study was to carefully reevaluate the current system of classification and suggest changes wherein necessary. Phylogenetic trees of 84 Proteobacteria were constructed using single gene-based phylogeny involving 16S rRNA genes and protein sequences of 85 conserved genes, whole genome-based phylogenetic tree using CVtree3.0, amino acid Identity matrix tree, and concatenated tree with aforementioned conserved genes. The results of our study confirm the polyphyletic relationship between Desulfurella acetivorans, a Deltaproteobacteria with Epsilonproteobacteria. The group Syntrophobacterales was found to be polyphyletic with respect to Desulfarculus baarsii and the group Thiotrichales was found to be splitting in different phylogenetic trees. Placement of phylogenetic groups belonging to Rhodocyclales, Oceonospirilalles, and Chromatiales is controversial and requires further study and revisions. Based on our analysis, we strongly support reclassification of Magnetococcales as a separate class Etaproteobacteria. From our results, we conclude that concatenated trees of conserved proteins are a more accurate method for phylogenetic analysis, as compared to other methods used.

Driven Engulfment of Janus Particles by Giant Vesicles in and out of Thermal Equilibrium.

The interaction between Janus colloids and giant lipid vesicles was experimentally investigated to elucidate the dynamics and mechanisms related to microparticle engulfment by lipid vesicles. Janus (Pt-SiO2 and Pt-MF, where MF is melamine formaldehyde) colloids do not spontaneously adhere to POPC or DOPC bilayers, but by applying external forces via centrifugation we were able to force the contact between the particles and the membranes, which may result in a partial engulfment state of the particle. Surface properties of the Janus colloids play a crucial role in the driven particle engulfment by vesicles. Engulfment of the silica and platinum regions of the Janus particles can be observed, whereas the polymer (MF) region does not show any affinity towards the lipid bilayer. By using fluorescence microscopy, we were able to monitor the particle orientation and measure the rotational dynamics of a single Janus particle engulfed by a vesicle. By adding hydrogen peroxide to the solution, particle self-propulsion was used to perform an active transport of a giant vesicle by a single active particle. Finally, we observe that partially engulfed particles experience a membrane curvature-induced force, which pushes the colloids towards the bottom where the membrane curvature is the lowest.

Effect of Moringa oleifera leaf extract on exercise and dexamethasone-induced functional impairment in skeletal muscles.

BACKGROUND: Chronic administration of steroids like dexamethasone produces symptoms including weight loss and skeletal muscle dysfunction. Similar events are reported in chronic or high-intensity exercises, that can lead to fatigue and muscle damage. OBJECTIVE: In the present study, the effect of Moringa oleifera leaf extract was evaluated against dexamethasone (Dex) and exercise (Exe)-induced muscle changes in rats. MATERIALS AND METHODS: Six groups each containing 6 rats, namely normal, Dex control, Exe Control, Dex + M. oleifera leaf extract (300mg/kgp.o.), Dex + Exe, Dex + Exe + M. oleifera leaf extract were assessed in the study. Dex was administered at 0.6 mg/kg i.p. daily for 7 days. Exercise was given for a total of 10 days after 30 minutes of dosing using treadmill equipment for 900 seconds at speed 18 m/min. Animals were assessed for variation in body weight, muscular endurance using treadmill, locomotor activity using actophotometer, motor coordination using rotarod on day zero, and day seven. Hemidiaphragm of rats were isolated and used for evaluation of the glucose uptake. Gastrocnemius muscle was isolated and subjected to hematoxylin and eosin staining. RESULTS: Dex and Exe control animals showed a significant decrease in skeletal muscle activity when compared to normal control animals in the actophotometer test. Improvement in endurance were seen in Dex + M. oleifera leaf extract, and Dex + exercise + M. oleifera leaf extract groups compared to Dex control group. Improvement in locomotor activity was seen in Dex group subjected to exercise and was significant when treated with M. oleifera leaf extract. Histology reports were in accordance with the functional parameters. CONCLUSION: M. oleifera leaf extract supplemented with exercise showed a reversal in the dexamethasone-induced functional impairment in skeletal muscles.

NIHSS 24 h After Mechanical Thrombectomy Predicts 90-Day Functional Outcome.

BACKGROUND: Mechanical thrombectomy (MT) for large vessel occlusion (LVO) ischemic stroke is a safe and effective treatment modality. The National Institute of Health Stroke Scale (NIHSS) 24 h after MT (24 h-NIHSS) was shown to serve as the strongest surrogate for 90-day functional outcome. Here, we seek to externally validate 24 h-NIHSS as predictor for 90-day functional outcome and explore additional variables in this context. METHODS: Patients treated for anterior LVO between February 2016 and August 2020 with premorbid mRS < 3 were included. Receiver operating characteristics were used to compare different NIHSS-related surrogates, such as baseline (B) NIHSS, 24 h-NIHSS, Δ­NIHSS and percent (%) change NIHSS to predict favorable function outcome (mRS 0-2). Additional analysis was performed to assess predictors associated with poor outcome despite reaching the best predictor threshold. RESULTS: A total of 337 eligible cases were identified. The 24 h-NIHSS outperformed B­NIHSS, Δ­NIHSS, and %­NIHSS in terms of 90-day mRS 0-2 prediction. A 24-NIHSS ≤ 8 was identified as the optimal binary threshold. Multivariable analysis demonstrated that 24-NIHSS ≤ 8 and younger patient age were independently associated with mRS 0-2. Despite achieving 24 h-NIHSS ≤ 8, 23/143 (16.1%) cases experienced poor outcome (mRS 4-6). Older age, higher baseline NIHSS, coexisting chronic kidney disease, and longer hospital stay were independent predictors for poor outcome despite achieving 24 h-NIHSS ≤ 8. CONCLUSION: An NIHSS of 8 or less 24 h after MT was validated to serve as an independent, strong surrogate for favorable functional outcome; however, cofactors such as older age, higher baseline NIHSS and coexisting comorbidities appear to mitigate this clinical adjunct.