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Mutations causing amyotrophic lateral sclerosis (ALS) strongly implicate ubiquitously expressed regulators of RNA processing. To understand the molecular impact of ALS-causing mutations on neuronal development and disease, we analysed transcriptomes during in vitro differentiation of motor neurons (MNs) from human control and patient-specific VCP mutant induced-pluripotent stem cells (iPSCs). We identify increased intron retention (IR) as a dominant feature of the splicing programme during early neural differentiation. Importantly, IR occurs prematurely in VCP mutant cultures compared with control counterparts. These aberrant IR events are also seen in independent RNAseq data sets from SOD1- and FUS-mutant MNs. The most significant IR is seen in the SFPQ transcript. The SFPQ protein binds extensively to its retained intron, exhibits lower nuclear abundance in VCP mutant cultures and is lost from nuclei of MNs in mouse models and human sporadic ALS. Collectively, we demonstrate SFPQ IR and nuclear loss as molecular hallmarks of familial and sporadic ALS. Intron retention (IR) can increase protein diversity and function, and yet unregulated IR may be detrimental to cellular health. This study shows that aberrant IR occurs in ALS and finds nuclear loss of an RNA-binding protein called SFPQ as a new molecular hallmark in this devastating condition.

Histopathological analysis of tissue sections is invaluable in neurodegeneration research. However, cell‐to‐cell variation in both the presence and severity of a given phenotype is a key limitation of this approach, reducing the signal to noise ratio and leaving unresolved the potential of single‐cell scoring for a given disease attribute. Here, we tested different machine learning methods to analyse high‐content microscopy measurements of hundreds of motor neurons (MNs) from amyotrophic lateral sclerosis (ALS) post‐mortem tissue sections. Furthermore, we automated the identification of phenotypically distinct MN subpopulations in VCP‐ and SOD1‐mutant transgenic mice, revealing common morphological cellular phenotypes. Additionally we established scoring metrics to rank cells and tissue samples for both disease probability and severity. By adapting this paradigm to human post‐mortem tissue, we validated our core finding that morphological descriptors robustly discriminate ALS from control healthy tissue at single cell resolution. Determining disease presence, severity and unbiased phenotypes at single cell resolution might prove transformational in our understanding of ALS and neurodegeneration more broadly. With their novel pipeline for automated segmentation, profiling and identification of phenotypically distinct motor neuron subpopulations in ALS pathological tissue sections, Hageman et al. report that morphological descriptors strongly discriminate ALS from control healthy tissue at the single‐cell level.

PurposeIn critically ill patients, acute kidney injury (AKI) is a devastating problem often associated with adverse outcomes. Depending on the conventional markers for diagnosis of AKI, an undesirable delay in the diagnosis and initiation of treatment has occurred. Thus, it is challenging to find a biomarker for early diagnosis of AKI. We sought to evaluate urinary YKL-40 as a biomarker for early diagnosis of AKI among critically ill patients compared with conventional markers and to assess its relation to the severity of AKI.MethodsThirty-six patients without AKI at the time of ICU admission who enrolled in this prospective cohort study had the following measured: serum creatinine as well as urine YKL-40 at admission and thereafter at 4 time intervals (0, 12, and 24 ± 48 h) (therefore, we studied 94 urine samples in 36 patients). Urine YKL-40 was quantified by enzyme-linked immunosorbent assay (ELISA). AKI was defined using the Kidney Disease Improving Global Outcomes (KDIGO) criteria, which include three stages (1, 2, and 3) of progressive renal dysfunction.ResultsIn this study, 18 (50%) patients developed AKI within 48–72 h. Moreover, urine YKL-40 increased significantly within 12 h in patients who developed AKI (n = 18, 11.75 ± 1.94), but not in non-AKI patients (n = 18, 5.66 ± 3.42) ng/ml (P < 0.001) and, at the same time, we did not find any significant difference in the serum creatinine levels between the two groups. In addition, AKI group showed rising levels with KIDGO classes.ConclusionIn this pilot study we found that urinary YKL-40 can be used as a valuable and noninvasive marker for early diagnosis of AKI among critically ill patients in ICU as compared to conventional markers and its level is increasing with the severity of AKI classes. However, the small sample size is important limitation. Therefore, large multicenter studies may be needed to confirm it.

A distinctive isolate was discovered and visually recognized as a member of the genus Didymella during a routine examination of Coelomycetes isolated from diverse fruit juices. Based on sequencing of the internal transcribed spacer (ITS), the fungus was identified as Didymella keratinophila since it showed a 100% identity to the type strain. The strain thrived and produced keratinase and collagenase enzymes by hydrolyzing native chicken feathers in submerged fermentation (SmF). After 10 days of fermentation at 30 °C, pH 9 using sodium nitrate as a nitrogen supply produced the highest keratinase activity of 8780 ± 620 U/mL/min, while pH 6 and beef extract produced the maximum collagenase activity of 11,230 ± 1290 U/mL/min. The partially-purified keratinase enzyme worked best at pH 7.0 and 45 °C, exhibiting a specific activity of 44,903 ± 1555 U/mg protein. The activity of the partially-purified collagenase enzyme was excellent at pH 6.0 at 35 °C, generating 15,753 ± 110 U/mg enzyme-specific activity. Mn2+ and K+ were the most efficient inhibitors of keratinases and collagenase, respectively. Both EDTA and metal ions significantly decreased the activity of keratinase and collagenase. This report identified a workable supplier of collagenase and keratinase enzymes derived from chicken feathers, offering a reliable way to exploit and manage these wastes for obtaining high-value products.

The association between epicardial fat thickness and coronary artery disease (CAD) has been evaluated previously using echocardiography. Recently, multidetector computed tomography (MDCT), as a valuable tool in cardiovascular CT imaging, can improve characterization of CAD and give a more accurate volumetric quantitation of EF. The purpose of our study was to evaluate the relationship between the epicardial fat volume and CAD using multi-detector row CT. Out of the studied 120 patients, 22 patients were negative for CAD, while 98 patients had positive CAD. There was significant difference between both groups as regard epicardial fat volume (p < 0.001), and good relation was found between the amount of epicardial fat volume and coronary calcium score, number of affected vessel, plaque burden and degree of stenosis (p = < 0.001). EAT volume was larger in the presence of obstructive CAD and atheromatous plaques. These data suggest that EAT is associated with the development of coronary atherosclerosis and potentially the most dangerous types of plaques.

Neuroprotection seeks to halt cell death after brain ischemia and has been shown to be possible in laboratory studies. However, neuroprotection has not been successfully translated into clinical practice, despite voluminous research and controlled clinical trials. We suggested these failures may be due, at least in part, to the lack of a general theory of cell injury to guide research into specific injuries. The nonlinear dynamical theory of acute cell injury was introduced to ameliorate this situation. Here we present a revised nonautonomous nonlinear theory of acute cell injury and show how to interpret its solutions in terms of acute biomedical injuries. The theory solutions demonstrate the complexity of possible outcomes following an idealized acute injury and indicate that a “one size fits all” therapy is unlikely to be successful. This conclusion is offset by the fact that the theory can (1) determine if a cell has the possibility to survive given a specific acute injury, and (2) calculate the degree of therapy needed to cause survival. To appreciate these conclusions, it is necessary to idealize and abstract complex physical systems to identify the fundamental mechanism governing the injury dynamics. The path of abstraction and idealization in biomedical research opens the possibility for medical treatments that may achieve engineering levels of precision.

Many clinically relevant forms of acute injury, such as stroke, traumatic brain injury, and myocardial infarction, have resisted treatments to prevent cell death following injury. The clinical failures can be linked to the currently used inductive models based on biological specifics of the injury system. Here we contrast the application of inductive and deductive models of acute cell injury. Using brain ischemia as a case study, we discuss limitations in inductive inferences, including the inability to unambiguously assign cell death causality and the lack of a systematic quantitative framework. These limitations follow from an overemphasis on qualitative molecular pathways specific to the injured system. Our recently developed nonlinear dynamical theory of cell injury provides a generic, systematic approach to cell injury in which attractor states and system parameters are used to quantitatively characterize acute injury systems. The theoretical, empirical, and therapeutic implications of shifting to a deductive framework are discussed. We illustrate how a deductive mathematical framework offers tangible advantages over qualitative inductive models for the development of therapeutics of acutely injured biological systems.

Amyotrophic lateral sclerosis (ALS) is an adult-onset neurodegenerative disease affecting upper and lower motor neurons, characterised by muscle weakness rapidly leading to paralysis and death. Astrocytes respond to various insults by undergoing profound structural, molecular and functional changes called reactive astrogliosis. Reactive astrocytes are known to be implicated in ALS, although the mechanism controlling reactive transformation is unknown. So far, an astrocyte reactive state that favours an inflammatory phenotype has been reported in mouse models and human post-mortem tissue of ALS. In my thesis, I first demonstrate that hiPSCs-derived astrocytes undergo deleterious reactive transformation in response to tumor necrosis factor-alpha (TNF-α), interleukin 1α (IL-1α) and complement component1, subcomponent (C1q) but not to Lipopolysaccharides (LPS). I then characterised the reactive state in hiPSC-derived astrocytes from patients with VCP or SOD1 at a basal state and identified a distinct reactive profile of each mutation. The work in the thesis reveals that early reactive transformation can occur autonomously in human ALS astrocytes and with a striking degree of molecular and functional heterogeneity when comparing different disease-causing mutations. Looking into the mechanism underlying the diverse reactive states, the thesis shows decreased intron retention as a common alternative splicing mechanism in ALS astrocytes, associated with increased expression of transcripts regulating reactivity. This mechanism could potentially be targeted for therapeutic intervention. In parallel, recognizing the complex relationship between inflammation and ALS, this thesis examines how human astrocytes respond to extrinsic proinflammatory cues and ultimately how such responses might be perturbed or exacerbated in ALS. RNA binding proteins (RBPs) have been shown to play a key role in the pathogenesis of a variety of neurodegenerative disorders including ALS. Nuclear to cytoplasmic mislocalization and accumulation of RBPs has been identified as a pathological hallmark of the disease. This thesis combines the findings on RBP localisation with inflammatory responses, to explore how intrinsic mutation or/and extrinsic inflammation cues affect the localisation and ultimately the role of disease associated-RBPs in healthy and ALS astrocytes, to further our understanding of how pathogenic mechanisms may be interacting. Collectively, the work presented in this thesis shows the multiple layers of astrocytes reactive transformation in ALS.

A distinctive isolate was discovered and visually recognized as a member of the genus Didymella during a routine examination of Coelomycetes isolated from diverse fruit juices. Based on sequencing of the internal transcribed spacer (ITS), the fungus was identified as Didymella keratinophila since it showed a 100% identity to the type strain. The strain thrived and produced keratinase and collagenase enzymes by hydrolyzing native chicken feathers in submerged fermentation (SmF). After 10 days of fermentation at 30 °C, pH 9 using sodium nitrate as a nitrogen supply produced the highest keratinase activity of 8780 ± 620 U/mL/min, while pH 6 and beef extract produced the maximum collagenase activity of 11,230 ± 1290 U/mL/min. The partially-purified keratinase enzyme worked best at pH 7.0 and 45 °C, exhibiting a specific activity of 44,903 ± 1555 U/mg protein. The activity of the partially-purified collagenase enzyme was excellent at pH 6.0 at 35 °C, generating 15,753 ± 110 U/mg enzyme-specific activity. Mn[sup.2+] and K[sup.+] were the most efficient inhibitors of keratinases and collagenase, respectively. Both EDTA and metal ions significantly decreased the activity of keratinase and collagenase. This report identified a workable supplier of collagenase and keratinase enzymes derived from chicken feathers, offering a reliable way to exploit and manage these wastes for obtaining high-value products.