The High-Affinity Chymotrypsin Inhibitor Eglin C Poorly Inhibits Human Chymotrypsin-Like Protease: Gln192 and Lys218 Are Key Determinants.

Eglin C, a small protein from the medicinal leech, has been long considered a general high-affinity inhibitor of chymotrypsins and elastases. Here, we demonstrate that eglin C inhibits human chymotrypsin-like protease (CTRL) weaker by several orders of magnitude than other chymotrypsins. In order to identify the underlying structural aspects of this unique deviation, we performed comparative molecular dynamics simulations on experimental and AlphaFold model structures of bovine CTRA and human CTRL. Our results indicate that in CTRL, the primary determinants of the observed weak inhibition are amino-acid positions 192 and 218 (using conventional chymotrypsin numbering), which participate in shaping the S1 substrate-binding pocket and thereby affect the stability of the protease-inhibitor complexes.

The safety of early pharmacological venous thromboembolism prophylaxis in patients with traumatic intracranial haemorrhage: a systematic review and meta-analysis.

INTRODUCTION: In patients with traumatic intracranial haemorrhage (tICH) there is significant risk of both venous thromboembolism (VTE) and haemorrhage progression. There is a paucity of literature to inform the timing of pharmacological thromboprophylaxis (PTP) initiation. AIM: This meta-analysis aims to summarise the current literature on the timing of PTP initiation in tICH. METHODS: This meta-analysis followed the Methodological Expectations of Cochrane Intervention Reviews checklist and the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. Following the literature search, studies were matched against the criteria for inclusion. Data from included studies was pooled, analysed using random-effect analysis and presented as forest plots of risk ratios, except one result reported as difference of means. The ROBINS-I tool was used to assess the risk of bias in the studies. The GRADE approach was taken to assess the quality of included studies. Heterogeneity of studies was assessed using Tau∧2. Funnel plots were generated and used in conjunction with Harbord's test and Rucker's arcsine to assess for small-study effect including publication bias. RESULTS: A total of 9927 ICH patients who received PTP were included from 15 retrospective observational cohort studies, 4807 patients received early PTP, the remaining 5120 received late PTP. The definition of early was dependent on the study but no more than 72-hours after admission. The mean age of the included cohort was 45.3 (std dev ±9.5) years, and the proportion of males was 71%. Meta-analysis indicated that there was a significant difference between early and late groups for the rate of VTE (RR, 0.544; p = 0.000), pulmonary embolus (RR, 0.538; p = 0.004), deep vein thrombosis (RR, 0.484; p = 0.000) and the intensive care unit length of stay (difference of means, -2.021; 95% CI, -2.250, -1.792; p = 0.000; Tau∧2 = 0.000), favouring the early group. However, the meta-analysis showed no significant difference between the groups for the rate of mortality (RR, 1.008; p = 0.936), tICH progression (RR, 0.853; p = 0.157), and neurosurgical intervention (RR, 0.870; p = 0.480). CONCLUSION: These findings indicated that early PTP appears to be safe and effective in patients with tICH.

Lung vascular changes as biomarkers of severity in systemic sclerosis-associated interstitial lung disease.

OBJECTIVES: It has recently become possible to assess lung vascular and parenchymal changes quantitatively in thoracic CT images using automated software tools. We investigated the vessel parameters of patients with SSc, quantified by CT imaging, and correlated them with interstitial lung disease (ILD) features. METHODS: SSc patients undergoing standard of care pulmonary function testing and CT evaluation were retrospectively evaluated. CT images were analysed for ILD patterns and total pulmonary vascular volume (PVV) extents with Imbio lung texture analysis. Vascular analysis (volumes, numbers and densities of vessels, separating arteries and veins) was performed with an in-house developed software. A threshold of 5% ILD extent was chosen to define the presence of ILD, and commonly used cut-offs of lung function were adopted. RESULTS: A total of 79 patients [52 women, 40 ILD, mean age 56.2 (s.d. 14.2) years, total ILD extent 9.5 (10.7)%, PVV/lung volume % 2.8%] were enrolled. Vascular parameters for total and separated PVV significantly correlated with functional parameters and ILD pattern extents. SSc-associated ILD (SSc-ILD) patients presented with an increased number and volume of arterial vessels, in particular those between 2 and 4 mm of diameter, and with a higher density of arteries and veins of <6 mm in diameter. Considering radiological and functional criteria concomitantly, as well as the descriptive trends from the longitudinal evaluations, the normalized PVVs, vessel numbers and densities increased progressively with the increase/worsening of ILD extent and functional impairment. CONCLUSION: In SSc patients CT vessel parameters increase in parallel with ILD extent and functional impairment, and may represent a biomarker of SSc-ILD severity.

Substrate specificity of human chymotrypsin-like protease (CTRL) characterized by phage display-selected small-protein inhibitors.

Chymotrypsin-like protease (CTRL) is one of the four chymotrypsin isoforms expressed in the human exocrine pancreas. Human genetic and experimental evidence indicate that chymotrypsins B1, B2, and C (CTRB1, CTRB2 and CTRC) are important not only for protein digestion but also for protecting the pancreas against pancreatitis by degrading potentially harmful trypsinogen. CTRL has not been reported to play a similar role, possibly due to its low abundance and/or different substrate specificity. To address this problem, we investigated the specificity of the substrate-binding groove of CTRL by evolving the substrate-like canonical loop of the Schistocerca gregaria proteinase inhibitor 2 (SGPI-2), a small-protein reversible chymotrypsin inhibitor to bind CTRL. We found that phage-associated SGPI-2 variants with strong affinity to CTRL were similar to those evolved previously against CTRB1, CTRB2 or bovine chymotrypsin A (bCTRA), indicating comparable substrate specificity. When tested as recombinant proteins, SGPI-2 variants inhibited CTRL with similar or slightly weaker affinity than bCTRA, confirming that CTRL is a typical chymotrypsin. Interestingly, an SGPI-2 variant selected with a Thr29His mutation in its reactive loop was found to inhibit CTRL strongly, but it was digested rapidly by bCTRA. Finally, CTRL was shown to degrade human anionic trypsinogen, however, at a much slower rate than CTRB2, suggesting that CTRL may not have a significant role in the pancreatic defense mechanisms against inappropriate trypsinogen activation and pancreatitis.

Molecular Dynamics Simulation as a Tool to Identify Mutual Synergistic Folding Proteins.

Mutual synergistic folding (MSF) proteins belong to a recently emerged subclass of disordered proteins, which are disordered in their monomeric forms but become ordered in their oligomeric forms. They can be identified by experimental methods following their unfolding, which happens in a single-step cooperative process, without the presence of stable monomeric intermediates. Only a limited number of experimentally validated MSF proteins are accessible. The amino acid composition of MSF proteins shows high similarity to globular ordered proteins, rather than to disordered ones. However, they have some special structural features, which makes it possible to distinguish them from globular proteins. Even in the possession of their oligomeric three-dimensional structure, classification can only be performed based on unfolding experiments, which are frequently absent. In this work, we demonstrate a simple protocol using molecular dynamics simulations, which is able to indicate that a protein structure belongs to the MSF subclass. The presumption of the known atomic resolution quaternary structure is an obvious limitation of the method, and because of its high computational time requirements, it is not suitable for screening large databases; still, it is a valuable in silico tool for identification of MSF proteins.

Combined miRNA and SERS urine liquid biopsy for the point-of-care diagnosis and molecular stratification of bladder cancer.

BACKGROUND: Bladder cancer (BC) has the highest per-patient cost of all cancer types. Hence, we aim to develop a non-invasive, point-of-care tool for the diagnostic and molecular stratification of patients with BC based on combined microRNAs (miRNAs) and surface-enhanced Raman spectroscopy (SERS) profiling of urine. METHODS: Next-generation sequencing of the whole miRNome and SERS profiling were performed on urine samples collected from 15 patients with BC and 16 control subjects (CTRLs). A retrospective cohort (BC = 66 and CTRL = 50) and RT-qPCR were used to confirm the selected differently expressed miRNAs. Diagnostic accuracy was assessed using machine learning algorithms (logistic regression, naïve Bayes, and random forest), which were trained to discriminate between BC and CTRL, using as input either miRNAs, SERS, or both. The molecular stratification of BC based on miRNA and SERS profiling was performed to discriminate between high-grade and low-grade tumors and between luminal and basal types. RESULTS: Combining SERS data with three differentially expressed miRNAs (miR-34a-5p, miR-205-3p, miR-210-3p) yielded an Area Under the Curve (AUC) of 0.92 ± 0.06 in discriminating between BC and CTRL, an accuracy which was superior either to miRNAs (AUC = 0.84 ± 0.03) or SERS data (AUC = 0.84 ± 0.05) individually. When evaluating the classification accuracy for luminal and basal BC, the combination of miRNAs and SERS profiling averaged an AUC of 0.95 ± 0.03 across the three machine learning algorithms, again better than miRNA (AUC = 0.89 ± 0.04) or SERS (AUC = 0.92 ± 0.05) individually, although SERS alone performed better in terms of classification accuracy. CONCLUSION: miRNA profiling synergizes with SERS profiling for point-of-care diagnostic and molecular stratification of BC. By combining the two liquid biopsy methods, a clinically relevant tool that can aid BC patients is envisaged.

A Transfer Learning Approach on the Optimization of Edge Detectors for Medical Images Using Particle Swarm Optimization.

Edge detection is a fundamental image analysis task, as it provides insight on the content of an image. There are weaknesses in some of the edge detectors developed until now, such as disconnected edges, the impossibility to detect branching edges, or the need for a ground truth that is not always accessible. Therefore, a specialized detector that is optimized for the image particularities can help improve edge detection performance. In this paper, we apply transfer learning to optimize cellular automata (CA) rules for edge detection using particle swarm optimization (PSO). Cellular automata provide fast computation, while rule optimization provides adaptability to the properties of the target images. We use transfer learning from synthetic to medical images because expert-annotated medical data is typically difficult to obtain. We show that our method is tunable for medical images with different properties, and we show that, for more difficult edge detection tasks, batch optimization can be used to boost the quality of the edges. Our method is suitable for the identification of structures, such as cardiac cavities on medical images, and could be used as a component of an automatic radiology decision support tool.

Butterfly Effect in Chaotic Image Segmentation.

The exploitation of the important features exhibited by the complex systems found in the surrounding natural and artificial space will improve computational model performance. Therefore, the purpose of the current paper is to use cellular automata as a tool simulating complexity, able to bring forth an interesting global behaviour based only on simple, local interactions. We show that, in the context of image segmentation, a butterfly effect arises when we perturb the neighbourhood system of a cellular automaton. Specifically, we enhance a classical GrowCut cellular automaton with chaotic features, which are also able to improve its performance (e.g., a Dice coefficient of 71% in case of 2D images). This enhanced GrowCut flavor (referred to as Band-Based GrowCut) uses an extended, stochastic neighbourhood, in which randomly-selected remote neighbours reinforce the standard local ones. We demonstrate the presence of the butterfly effect and an increase in segmentation performance by numerical experiments performed on synthetic and natural images. Thus, our results suggest that, by having small changes in the initial conditions of the performed task, we can induce major changes in the final outcome of the segmentation.

SERS-based quantification of albuminuria in the normal-to-mildly increased range.

The lack of an accurate point-of-care detection system for microalbuminuria represents an important unmet medical need that contributes to the morbidity and mortality of patients with kidney diseases. In this proof-of-concept study, we used SERS spectroscopy to detect urinary albumin concentrations in the normal-to-mildly increased albuminuria range, a strategy that could be useful for the early diagnosis of renal impairment due to uncontrolled hypertension, cardiovascular disease or diabetes. We analyzed 27 urine samples by SERS, using iodide-modified silver nanoparticles and we could discriminate between groups with high and low albumin concentrations with an overall accuracy of 89%, 93% and 89%, using principal component analysis-linear discriminant analysis and cut-off values of 3, 6 and 10 µg mL-1 for urinary albumin concentrations, respectively. We achieved a detection limit of 3 µg mL-1 for human serum albumin based on the 1002 cm-1 SERS band, attributed to the ring breathing vibration of phenylalanine. Our detection limit is similar to that of the immunoturbidimetric assays and around one order of magnitude below the detection limit of urinary dipsticks used to detect microalbuminuria. We used principal least squares regression for building a spectral model for quantifying albumin. Using an independent prediction set, the R2 and root mean squared error of prediction between predicted and reference values of human serum albumin concentrations were 0.982 and 2.82, respectively. Here, we show that direct SERS spectroscopy has the sensitivity required for detecting clinically relevant concentrations of urinary albumin, a strategy that could be used in the future for the point-of-care screening of microalbuminuria.

Activated prostaglandin D2 receptors on macrophages enhance neutrophil recruitment into the lung.

BACKGROUND: Prostaglandin (PG) D2 is an early-phase mediator in inflammation, but its action and the roles of the 2 D-type prostanoid receptors (DPs) DP1 and DP2 (also called chemoattractant receptor-homologous molecule expressed on T(H)2 cells) in regulating macrophages have not been elucidated to date. OBJECTIVE: We investigated the role of PGD2 receptors on primary human macrophages, as well as primary murine lung macrophages, and their ability to influence neutrophil action in vitro and in vivo. METHODS: In vitro studies, including migration, Ca(2+) flux, and cytokine secretion, were conducted with primary human monocyte-derived macrophages and neutrophils and freshly isolated murine alveolar and pulmonary interstitial macrophages. In vivo pulmonary inflammation was assessed in male BALB/c mice. RESULTS: Activation of DP1, DP2, or both receptors on human macrophages induced strong intracellular Ca(2+) flux, cytokine release, and migration of macrophages. In a murine model of LPS-induced pulmonary inflammation, activation of each PGD2 receptor resulted in aggravated airway neutrophilia, tissue myeloperoxidase activity, cytokine contents, and decreased lung compliance. Selective depletion of alveolar macrophages abolished the PGD2-enhanced inflammatory response. Activation of PGD2 receptors on human macrophages enhanced the migratory capacity and prolonged the survival of neutrophils in vitro. In human lung tissue specimens both DP1 and DP2 receptors were located on alveolar macrophages along with hematopoietic PGD synthase, the rate-limiting enzyme of PGD2 synthesis. CONCLUSION: For the first time, our results show that PGD2 markedly augments disease activity through its ability to enhance the proinflammatory actions of macrophages and subsequent neutrophil activation.