Mono/Multi-material Characterization Using Hyperspectral Images and Multi-Block Non-Negative Matrix Factorization

Plastic sorting is a very essential step in waste management, especially due to the presence of multilayer plastics. These monomaterial and multimaterial plastics are widely employed to enhance the functional properties of packaging, combining beneficial properties in thickness, mechanical strength, and heat tolerance. However, materials containing multiple polymer species need to be pretreated before they can be recycled as monomaterials and therefore should not end up in monomaterial streams. Industry 4.0 has significantly improved materials sorting of plastic packaging in speed and accuracy compared to manual sorting, specifically through Near Infrared Hyperspectral Imaging (NIRHSI) that provides an automated, fast, and accurate material characterization, without sample preparation. Identification of multimaterials with HSI however requires novel dedicated approaches for chemical pattern recognition. Non negative Matrix Factorization, NMF, is widely used for the chemical resolution of hyperspectral images. Chemically relevant model constraints may make it specifically valuable to identify multilayer plastics through HSI. Specifically, Multi Block Non Negative Matrix Factorization (MBNMF) with correspondence among different chemical species constraint may be used to evaluate the presence or absence of particular polymer species. To translate the MBNMF model into an evidence based sorting decision, we extended the model with an F test to distinguish between monomaterial and multimaterial objects. The benefits of our new approach, MBNMF, were illustrated by the identification of several plastic waste objects

Systematic reduction of Hyperspectral Images for high-throughput Plastic Characterization

Hyperspectral Imaging (HSI) combines microscopy and spectroscopy to assess the spatial distribution of spectroscopically active compounds in objects, and has diverse applications in food quality control, pharmaceutical processes, and waste sorting. However, due to the large size of HSI datasets, it can be challenging to analyze and store them within a reasonable digital infrastructure, especially in waste sorting where speed and data storage resources are limited. Additionally, as with most spectroscopic data, there is significant redundancy, making pixel and variable selection crucial for retaining chemical information. Recent high-tech developments in chemometrics enable automated and evidence-based data reduction, which can substantially enhance the speed and performance of Non-Negative Matrix Factorization (NMF), a widely used algorithm for chemical resolution of HSI data. By recovering the pure contribution maps and spectral profiles of distributed compounds, NMF can provide evidence-based sorting decisions for efficient waste management. To improve the quality and efficiency of data analysis on hyperspectral imaging (HSI) data, we apply a convex-hull method to select essential pixels and wavelengths and remove uninformative and redundant information. This process minimizes computational strain and effectively eliminates highly mixed pixels. By reducing data redundancy, data investigation and analysis become more straightforward, as demonstrated in both simulated and real HSI data for plastic sorting

Concomitant granule cell neuronopathy in patients with natalizumab-associated PML

Granule cell neuronopathy (GCN) is a rare JC virus infection of the cerebellar granule cell neurons in immunocompromised patients. On brain imaging, GCN is characterized by cerebellar atrophy which can be accompanied by infratentorial white matter lesions. The objective of this study is to investigate the prevalence of MRI findings suggestive of GCN in a large natalizumab-associated progressive multifocal leukoencephalopathy (PML) cohort. MRI scans from before, at the time of, and during follow-up after diagnosis of PML in 44 natalizumab-treated MS patients, and a control group of 25 natalizumab-treated non-PML MS patients were retrospectively reviewed for imaging findings suggestive of GCN. To assess and quantify the degree of cerebellar atrophy, we used a 4 grade rating scale. Three patients in the PML group showed imaging findings suggestive of GCN and none in the control group. In two of these PML patients, cerebellar atrophy progressed from grade 0 at the time of diagnosis of isolated supratentorial PML to grade 1 and 2 after 2.5 and 3 months, respectively, in the absence of infratentorial white mater lesions. The third patient had grade 1 cerebellar atrophy before diagnosis of infra- and supratentorial PML, and showed progression of cerebellar atrophy to grade 2 in the 3 months following PML diagnosis. None of the other eight patients with infratentorial PML lesions developed cerebellar atrophy suggestive of GCN. Three cases with imaging findings suggestive of GCN were detected among 44 natalizumab-associated PML patients. GCN may, therefore, be more common than previously considered in natalizumab-associated PML patients

Self-reported work productivity in people with multiple sclerosis and its association with mental and physical health

PURPOSE: This study aimed to identify mental health, physical health, demographic and disease characteristics relating to work productivity in people with multiple sclerosis (MS). METHODS: In this cross-sectional study, 236 employed people with MS (median age = 42 years, 78.8% female) underwent neurological and neuropsychological assessments. Additionally, they completed questionnaires inquiring about work productivity (presenteeism: reduced productivity while working, and absenteeism: loss of productivity due to absence from work), mental and physical health, demographic and disease characteristics. Multiple linear and logistic regression analyses were performed with presenteeism and absenteeism as dependent variables, respectively. RESULTS: A model with mental and physical health factors significantly predicted presenteeism F(11,202) = 11.33, p < 0.001, R2 = 0.38; a higher cognitive (p < 0.001) and physical impact (p = 0.042) of fatigue were associated with more presenteeism. A model with only mental health factors significantly predicted absenteeism; χ2(11)=37.72, p < 0.001, with R2 = 0.27 (Nagelkerke) and R2 = 0.16 (Cox and Snell). Specifically, we observed that more symptoms of depression (p = 0.041) and a higher cognitive impact of fatigue (p = 0.011) were significantly associated with more absenteeism. CONCLUSIONS: In people with MS, both cognitive and physical impact of fatigue are positively related to presenteeism, while symptoms of depression and cognitive impact of fatigue are positively related to absenteeism.Implications for rehabilitationMultiple sclerosis (MS) affects people of working age, significantly interfering with work productivity.Higher cognitive and physical impact of fatigue were associated with more presenteeism in workers with MS.A higher cognitive impact of fatigue and more depressive symptoms were associated with absenteeism in workers with MS.Occupational and healthcare professionals should be aware of the impact of both physical and mental health on work productivity in workers with MS

Activity-based probes for functional interrogation of retaining β-glucuronidases

Humans express at least two distinct β-glucuronidase enzymes that are involved in disease: exo-acting β-glucuronidase (GUSB), whose deficiency gives rise to mucopolysaccharidosis type VII, and endo-acting heparanase (HPSE), whose overexpression is implicated in inflammation and cancers. The medical importance of these enzymes necessitates reliable methods to assay their activities in tissues. Herein, we present a set of β-glucuronidase-specific activity-based probes (ABPs) that allow rapid and quantitative visualization of GUSB and HPSE in biological samples, providing a powerful tool for dissecting their activities in normal and disease states. Unexpectedly, we find that the supposedly inactive HPSE proenzyme proHPSE is also labeled by our ABPs, leading to surprising insights regarding structural relationships between proHPSE, mature HPSE, and their bacterial homologs. Our results demonstrate the application of β-glucuronidase ABPs in tracking pathologically relevant enzymes and provide a case study of how ABP-driven approaches can lead to discovery of unanticipated structural and biochemical functionality

High quality of SARS-CoV-2 molecular diagnostics in a diverse laboratory landscape through supported benchmark testing and External Quality Assessment

A two-step strategy combining assisted benchmark testing (entry controls) and External Quality Assessments (EQAs) with blinded simulated clinical specimens to enhance and maintain the quality of nucleic acid amplification testing was developed. This strategy was successfully applied to 71 diagnostic laboratories in The Netherlands when upscaling the national diagnostic capacity during the SARS-CoV-2 pandemic. The availability of benchmark testing in combination with advice for improvement substantially enhanced the quality of the laboratory testing procedures for SARS-CoV-2 detection. The three subsequent EQA rounds demonstrated high quality testing with regard to specificity (99.6% correctly identified) and sensitivity (93.3% correctly identified). Even with the implementation of novel assays, changing workflows using diverse equipment and a high degree of assay heterogeneity, the overall high quality was maintained using this two-step strategy. We show that in contrast to the limited value of Cq value for absolute proxies of viral load, these Cq values can, in combination with metadata on strategies and techniques, provide valuable information for laboratories to improve their procedures. In conclusion, our two-step strategy (preparation phase followed by a series of EQAs) is a rapid and flexible system capable of scaling, improving, and maintaining high quality diagnostics even in a rapidly evolving (e.g. pandemic) situation.</p

High quality of SARS-CoV-2 molecular diagnostics in a diverse laboratory landscape through supported benchmark testing and External Quality Assessment

A two-step strategy combining assisted benchmark testing (entry controls) and External Quality Assessments (EQAs) with blinded simulated clinical specimens to enhance and maintain the quality of nucleic acid amplification testing was developed. This strategy was successfully applied to 71 diagnostic laboratories in The Netherlands when upscaling the national diagnostic capacity during the SARS-CoV-2 pandemic. The availability of benchmark testing in combination with advice for improvement substantially enhanced the quality of the laboratory testing procedures for SARS-CoV-2 detection. The three subsequent EQA rounds demonstrated high quality testing with regard to specificity (99.6% correctly identified) and sensitivity (93.3% correctly identified). Even with the implementation of novel assays, changing workflows using diverse equipment and a high degree of assay heterogeneity, the overall high quality was maintained using this two-step strategy. We show that in contrast to the limited value of Cq value for absolute proxies of viral load, these Cq values can, in combination with metadata on strategies and techniques, provide valuable information for laboratories to improve their procedures. In conclusion, our two-step strategy (preparation phase followed by a series of EQAs) is a rapid and flexible system capable of scaling, improving, and maintaining high quality diagnostics even in a rapidly evolving (e.g. pandemic) situation.</p

Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons. A cross-ancestry genome-wide association meta-analysis of amyotrophic lateral sclerosis (ALS) including 29,612 patients with ALS and 122,656 controls identifies 15 risk loci with distinct genetic architectures and neuron-specific biology

Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons. A cross-ancestry genome-wide association meta-analysis of amyotrophic lateral sclerosis (ALS) including 29,612 patients with ALS and 122,656 controls identifies 15 risk loci with distinct genetic architectures and neuron-specific biology

Novel genetic loci underlying human intracranial volume identified through genome-wide association

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five novel loci for intracranial volume and confirmed two known signals. Four of the loci are also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρgenetic=0.748), which indicated a similar genetic background and allowed for the identification of four additional loci through meta-analysis (Ncombined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, Parkinson’s disease, and enriched near genes involved in growth pathways including PI3K–AKT signaling. These findings identify biological underpinnings of intracranial volume and provide genetic support for theories on brain reserve and brain overgrowth