Co-aggregation with Apolipoprotein E modulates the function of Amyloid-ß in Alzheimer's disease.

Which isoforms of apolipoprotein E (apoE) we inherit determine our risk of developing late-onset Alzheimer's Disease (AD), but the mechanism underlying this link is poorly understood. In particular, the relevance of direct interactions between apoE and amyloid-ß (Aß) remains controversial. Here, single-molecule imaging shows that all isoforms of apoE associate with Aß in the early stages of aggregation and then fall away as fibrillation happens. ApoE-Aß co-aggregates account for ~50% of the mass of diffusible Aß aggregates detected in the frontal cortices of homozygotes with the higher-risk APOE4 gene. We show how dynamic interactions between apoE and Aß tune disease-related functions of Aß aggregates throughout the course of aggregation. Our results connect inherited APOE genotype with the risk of developing AD by demonstrating how, in an isoform- and lipidation-specific way, apoE modulates the aggregation, clearance and toxicity of Aß. Selectively removing non-lipidated apoE4-Aß co-aggregates enhances clearance of toxic Aß by glial cells, and reduces secretion of inflammatory markers and membrane damage, demonstrating a clear path to AD therapeutics.

A computational suite for the structural and functional characterization of amyloid aggregates.

We developed the aggregate characterization toolkit (ACT), a fully automated computational suite based on existing and widely used core algorithms to measure the number, size, and permeabilizing activity of recombinant and human-derived aggregates imaged with diffraction-limited and super-resolution microscopy methods at high throughput. We have validated ACT on simulated ground-truth images of aggregates mimicking those from diffraction-limited and super-resolution microscopies and showcased its use in characterizing protein aggregates from Alzheimer's disease. ACT is developed for high-throughput batch processing of images collected from multiple samples and is available as an open-source code. Given its accuracy, speed, and accessibility, ACT is expected to be a fundamental tool in studying human and non-human amyloid intermediates, developing early disease stage diagnostics, and screening for antibodies that bind toxic and heterogeneous human amyloid aggregates.

Super-resolution imaging unveils the self-replication of tau aggregates upon seeding.

Tau is a soluble protein interacting with tubulin to stabilize microtubules. However, under pathological conditions, it becomes hyperphosphorylated and aggregates, a process that can be induced by treating cells with exogenously added tau fibrils. Here, we employ single-molecule localization microscopy to resolve the aggregate species formed in early stages of seeded tau aggregation. We report that entry of sufficient tau assemblies into the cytosol induces the self-replication of small tau aggregates, with a doubling time of 5 h inside HEK cells and 1 day in murine primary neurons, which then grow into fibrils. Seeding occurs in the vicinity of the microtubule cytoskeleton, is accelerated by the proteasome, and results in release of small assemblies into the media. In the absence of seeding, cells still spontaneously form small aggregates at lower levels. Overall, our work provides a quantitative picture of the early stages of templated seeded tau aggregation in cells.

Risk factors predicting cervical spine fracture on CT in craniocervical trauma - retrospective study.

INTRODUCTION: The study identifies risk factors predicting cervical spine fracture on CT based on information in the referral form. METHODS: All patients aged over 18 years with a CT scan of the head and cervical spine completed at the University Hospital Brno in the year 2019 to exclude any fresh trauma were included in the retrospective study. The analyzed potential risk factors included gender, age over 65 years, unconsciousness or impaired consciousness, mechanism of injury, paresthesia or plegia suspected to be associated with trauma, cervical spine pain, other neurological symptomatology, presence of cervical collar, presence of intracranial hemorrhage on head CT, and presence of skull fracture on head CT. RESULTS: In total, a cervical or upper thoracic spine fracture was described in 51 of 1177 patients (4.3%). Statistically significant risk factors for cervical spine fracture on CT scan were identified as mechanism of injury similar to car accident or jumping into water (OR 2.52; p=0.004), pain of the cervical spine (OR 1.81; p.

A multi-modal wildfire prediction and early-warning system based on a novel machine learning framework.

Wildfires are increasingly impacting the environment and human health. Among the top 20 California wildfires, those in 2020-2021 burned more acres than the last century combined. Lack of an adequate early warning system impacts the health and safety of vulnerable populations disproportionately and widens the inequality gap. In this project, a multi-modal wildfire prediction and early warning system has been developed based on a novel spatio-temporal machine learning architecture. A comprehensive wildfire database with over 37 million data points was created, including the historical wildfires, environmental and meteorological sensor data from the Environmental Protection Agency, and geological data. The data was augmented into 2.53 km × 2.53 km square grids to overcome the sensor network coverage limitations. Leading and trailing indicators for the wildfires are proposed, classified, and tested. The leading indicators are correlated to the risks of wildfire conception, whereas the trailing indicators are correlated to the byproducts of the wildfires. Additionally, geological data was incorporated to provide additional information for better assessment on wildfire risks and propagation. Next, a novel U-Convolutional Long Short-Term Memory (ULSTM) neural network was developed to extract key spatial and temporal features of the dataset, specifically to address the spatial nature of the location of the wildfire and time-progression temporal nature of the wildfire evolution. Through iterative improvements and optimization, the final ULSTM network architecture, trained with data from 2012 to 2017, achieved >97% accuracy for predicting wildfires in 2018, as compared to ∼76% using traditional Convolutional Neural Network (CNN) techniques. The final model was applied to conduct a retrospective study for the 2018-2022 wildfire seasons, and successfully predicted 85.7% of wildfires >300 K acres in size. This technique could enable fire departments to anticipate and prevent wildfires before they strike and provide early warnings for at-risk individuals for better preparation, thereby saving lives, protecting the environment, and avoiding economic damages.

Biomarkers as prognostic and predictive factors in patients with hepatocellular carcinoma undergoing radiological oncological interventions.

BACKGROUND: Hepatocellular carcinoma is the most common malignant liver tumor in adults and thermal ablation and transarterial embolization are important methods of therapy. Thermal ablation can be used in early stages. Methods based on the transarterial approach, especially transarterial chemoembolization, play an important role in intermediate stage diseases. The success of procedures depends not only on the biological nature and the size of the tumor, on the technical design of the procedure and on the patient's response to treatment, but also on the molecular changes associated with these procedures. In addition to classic predictive and prognostic factors including age, patient comorbidities, Child-Pugh score, tumor characteristics, presence of large surrounding vessels, and portal vein thrombosis, molecular prognostic and predictive factors (serum biomarkers) are often mentioned in studies. Currently, only a-fetoprotein is routinely used as a prognostic biomarker; however, there are studies referring to new serum biomarkers that can potentially help to classical markers and imaging methods to determine the cancer prognosis and predict the success of therapy. These biomarkers most often include g-glutamyltranspeptidase, des- g-carboxyprothrombin, some types of microRNAs, inflammatory and hypoxic substances, whose serum levels are changed by the intervention therapies. Evaluation of these molecules could lead to the optimization of the medical intervention (choice of therapy method, timing of treatment) or change the management of patient follow-up after interventions. Although several biomarkers have shown promising results, most serum biomarkers still require validation in phase III studies. PURPOSE: The aim of this work is to present a comprehensive overview of classical and molecular biomarkers that could potentially help in the prognostic stratification of patients and better predict the success and effect of radiological intervention methods.

Automating the Standardized Cosmesis and Health Nasal Outcomes Survey Classification with Convolutional Neural Networks.

Importance: Currently, the aesthetic appearance and structure of the nose in a rhinoplasty patient is evaluated by a surgeon, without automation. Objective: To compare the assessment of convolutional neural networks (CNNs) (machine learning) and a rhinoplasty surgeon's impression of the nose before rhinoplasty. Methods: Preoperative nasal images were scored using a modified standardized cosmesis and health nasal outcomes survey (SCHNOS) questionnaire. Artificial intelligence (AI) models based on CNNs were developed and trained to classify patient nasal aesthetics into one of five categories, representing even intervals on the SCHNOS scoring scale. The models' performances were benchmarked against expert surgeon evaluation. Results: Two hundred thirty-five preoperative patient images were included in the study. The best-performing AI model achieved 61% accuracy and 0.449 average Matthews Correlation Coefficient on new patients. Conclusions: This pilot study suggests a proof-of-concept for AI to allow an automated patient assessment tool trained on preoperative patient images with a potential utility for counseling rhinoplasty patients.

Small soluble α-synuclein aggregates are the toxic species in Parkinson's disease.

Soluble α-synuclein aggregates varying in size, structure, and morphology have been closely linked to neuronal death in Parkinson's disease. However, the heterogeneity of different co-existing aggregate species makes it hard to isolate and study their individual toxic properties. Here, we show a reliable non-perturbative method to separate a heterogeneous mixture of protein aggregates by size. We find that aggregates of wild-type α-synuclein smaller than 200 nm in length, formed during an in vitro aggregation reaction, cause inflammation and permeabilization of single-liposome membranes and that larger aggregates are less toxic. Studying soluble aggregates extracted from post-mortem human brains also reveals that these aggregates are similar in size and structure to the smaller aggregates formed in aggregation reactions in the test tube. Furthermore, we find that the soluble aggregates present in Parkinson's disease brains are smaller, largely less than 100 nm, and more inflammatory compared to the larger aggregates present in control brains. This study suggests that the small non-fibrillar α-synuclein aggregates are the critical species driving neuroinflammation and disease progression.

The associations of CD4 count, CD4/CD8 ratio, and HIV viral load with survival from non-small cell lung cancer in persons living with HIV.

HIV status may influence survival from non-small cell lung cancer (NSCLC). Among NSCLC patients in the Bronx, NY, we assessed (1) associations of CD4 count, CD4/CD8 ratio and HIV viral load (VL) with survival and (2) prognostic factors among persons living with HIV (PLWH). We compared survival from NSCLC diagnosis (2004-2017) between HIV-negative persons (HIV-, n=2,881) and PLWH (n=88) accounting for clinical and sociodemographic factors. HIV-survival was also compared with PLWH, dichotomized by CD4 (<200 vs. ≥200cells/µL), CD4/CD8 (median, <0.43 vs. ≥0.43) and VL (<75 vs. ≥75copies/mL) at NSCLC diagnosis. Among PLWH, we assessed the relationships of CD4, CD4/CD8, and VL with survival, adjusting for age, sex, and cancer stage. PLWH with CD4< 200cells/µL had lower survival than HIV- [hazard ratio, 95% confidence interval [HR(95%CI)]=1.86(0.98-3.55)]. Survival was similar between PLWH with CD4≥ 200cells/µL and HIV- [HR(95%CI) = 0.90(0.61-1.33)]. Results were similar when categorizing PLWH by CD4/CD8 [vs. HIV-: low CD4/CD8: HR(95%CI) = 1.74(1.07-3.89); high CD4/CD8: HR(95%CI) = 0.63(0.37-1.07)] and VL [vs. HIV-: <75copies/mL: HR(95%CI) = 0.74(0.46-1.21), ≥75copies/mL: HR(95%CI) = 1.41(0.88-2.27)]. Among PLWH, CD4< 200cells/µL was associated with worse survival [vs. CD4≥ 200cells/µL: HR(95%CI) = 2.37(1.14-4.92)]. CD4, CD4/CD8, and VL may be prognostic markers for PLWH with NSCLC, suggesting immune status may be important in NSCLC survival among PLWH.

Super-resolution imaging reveals α-synuclein seeded aggregation in SH-SY5Y cells.

Aggregation of α-synuclein (α-syn) is closely linked to Parkinson's disease (PD) and the related synucleinopathies. Aggregates spread through the brain during the progression of PD, but the mechanism by which this occurs is still not known. One possibility is a self-propagating, templated-seeding mechanism, but this cannot be established without quantitative information about the efficiencies and rates of the key steps in the cellular process. To address this issue, we imaged the uptake and seeding of unlabeled exogenous α-syn fibrils by SH-SY5Y cells and the resulting secreted aggregates, using super-resolution microscopy. Externally-applied fibrils very inefficiently induced self-assembly of endogenous α-syn in a process accelerated by the proteasome. Seeding resulted in the increased secretion of nanoscopic aggregates (mean 35 nm diameter), of both α-syn and Aß. Our results suggest that cells respond to seed-induced disruption of protein homeostasis predominantly by secreting nanoscopic aggregates; this mechanism may therefore be an important protective response by cells to protein aggregation.

Experimental model of occluded biliary metal stent recanalization using irreversible electroporation via a tubular catheter.

PURPOSE: To demonstrate the feasibility of irreversible electroporation (IRE) for treating biliary metal stent occlusion in an experimental liver model. METHODS AND MATERIALS: IRE was performed using an expandable tubular IRE-catheter placed in nitinol stents in the porcine liver. A 3-electrode IRE-catheter was connected to an IRE-generator and one hundred 100µs pulses of constant voltage (300, 650, 1000, and 1300 V) were applied. Stent occlusion was simulated by insertion of liver tissue both ex vivo (n = 94) and in vivo in 3 pigs (n = 14). Three scenarios of the relationship between the stent, electrodes, and inserted tissue (double contact, single contact, and stent mesh contact) were studied. Electric current was measured and resistance and power calculated. Pigs were sacrificed 72 h post-procedure. Harvested samples (14 experimental, 13 controls) underwent histopathological analysis. RESULTS: IRE application was feasible at 300 and 650 V for the single and double contact setup in both ex vivo and in vivo studies. Significant differences in calculated resistance between double contact and single contact settings were observed (ex-vivo p ˂ 0.0001, in-vivo p = 0.02; Mann-Whitney). A mild temperature increase of the surrounding liver parenchyma was noted with increasing voltage (0.9-5.9 °C for 300-1000 V). The extent of necrotic changes in experimental samples in vivo correlated with the measured electric current (r2 = 0.39, p = 0.01). No complications were observed during or after the in-vivo procedure. CONCLUSION: Endoluminal IRE using an expandable tubular catheter in simulated metal stent occlusion is feasible. The relationship of active catheter electrodes to stent ingrowth tissue can be estimated based on resistance values.

Single-molecule visualization of DNA G-quadruplex formation in live cells.

Substantial evidence now exists to support that formation of DNA G-quadruplexes (G4s) is coupled to altered gene expression. However, approaches that allow us to probe G4s in living cells without perturbing their folding dynamics are required to understand their biological roles in greater detail. Herein, we report a G4-specific fluorescent probe (SiR-PyPDS) that enables single-molecule and real-time detection of individual G4 structures in living cells. Live-cell single-molecule fluorescence imaging of G4s was carried out under conditions that use low concentrations of SiR-PyPDS (20 nM) to provide informative measurements representative of the population of G4s in living cells, without globally perturbing G4 formation and dynamics. Single-molecule fluorescence imaging and time-dependent chemical trapping of unfolded G4s in living cells reveal that G4s fluctuate between folded and unfolded states. We also demonstrate that G4 formation in live cells is cell-cycle-dependent and disrupted by chemical inhibition of transcription and replication. Our observations provide robust evidence in support of dynamic G4 formation in living cells.

Imaging rRNA Methylation in Bacteria by MR-FISH.

Methylation of RNA is normally monitored in purified cell lysates using next-generation sequencing, gel electrophoresis, or mass spectrometry as readouts. These bulk methods require the RNA from ~104 to 107 cells to be pooled to generate sufficient material for analysis. Here we describe a method-methylation-sensitive RNA in situ hybridization (MR-FISH)-that assays rRNA methylation in bacteria on a cell-by-cell basis, using methylation-sensitive hybridization probes and fluorescence microscopy. We outline step-by-step protocols for designing probes, in situ hybridization, and analysis of data using freely available code.

Chemoembolization for Treatment of Hepatocellular Carcinoma - National Registry-Based Analysis.

BACKGROUND: To evaluate survival benefit in patient undergoing transarterial chemoembolization (TACE) for hepatocellular carcinoma (HCC) by national registry data analysis and comparison of regions with unequal usage of interventional radiology procedures. MATERIALS AND METHODS: A total of 4,343 patients with primary diagnosis of HCC between 2010-2016 were extracted from the databases of The Czech National Cancer Registry. The analysis was supported by data from the National Registry of Paid Health Services and the Death Records Database. Primary treatment option was categorized as liver resection, ablation, TACE and chemotherapy. The regional data analysis provided information of interventional radiology procedures frequency for primary treatment of HCC. The 14 main regions were symmetrically divided to group with well-developed interventional radiology service and low-developed interventional radiology service according the frequency of stage adjusted interventional radiology procedure usage (< 15%, > 15%). Kaplan-Meier and Cox regression were used for survival and hazard ratios (HR) analyses. RESULTS: Only 1,730 patients had assessed any primary treatment option, 16.5 % (285) were treated by TACE. Median of survival were significantly different in regions with well and low developed interventional radiology service for whole study population (13.2 vs. 6.5 months, p < 0.001), patients treated in regions with well-developed interventional radiology service had lower risk of death during treatment (HR 0.73; 0.66-0.81). The patient treated by TACE had median of survival 15.8 months (13.5-18.1), while the survival was not significantly different in region groups. CONCLUSION: The usage of anticancer therapies based on interventional radiology procedures is a huge factor influences the survival of HCC patient according population-based data. Studies gathering data from cancer register databases can provide further information on treatment effectiveness. This work was created at Masaryk University in the project „Oncological radiological interventions and their benefit in complex oncological treatment, comparison of dedicated oncological treatment results data of the Czech republic II“ (MUNI/A/1574/2018), supported by Ministry of Education, Youth and Sports. This publication was additionally suported by Ministry of Health grant No. 15-32484A. The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study. The Editorial Board declares that the manuscript met the ICMJE recommendation for biomedical papers. Submitted: 1. 3. 2019 Accepted: 4. 3. 2019.

Nanoscopic Characterisation of Individual Endogenous Protein Aggregates in Human Neuronal Cells.

The aberrant misfolding and subsequent conversion of monomeric protein into amyloid aggregates characterises many neurodegenerative disorders, including Parkinson's and Alzheimer's diseases. These aggregates are highly heterogeneous in structure, generally of low abundance and typically smaller than the diffraction limit of light (≈250 nm). To overcome the challenges these characteristics pose to the study of endogenous aggregates formed in cells, we have developed a method to characterise them at the nanometre scale without the need for a conjugated fluorophore. Using a combination of DNA PAINT and an amyloid-specific aptamer, we demonstrate that this technique is able to detect and super-resolve a range of aggregated species, including those formed by α-synuclein and amyloid-ß. Additionally, this method enables endogenous protein aggregates within cells to be characterised. We found that neuronal cells derived from patients with Parkinson's disease contain a larger number of protein aggregates than those from healthy controls.

α-synuclein oligomers interact with ATP synthase and open the permeability transition pore in Parkinson's disease.

Protein aggregation causes α-synuclein to switch from its physiological role to a pathological toxic gain of function. Under physiological conditions, monomeric α-synuclein improves ATP synthase efficiency. Here, we report that aggregation of monomers generates beta sheet-rich oligomers that localise to the mitochondria in close proximity to several mitochondrial proteins including ATP synthase. Oligomeric α-synuclein impairs complex I-dependent respiration. Oligomers induce selective oxidation of the ATP synthase beta subunit and mitochondrial lipid peroxidation. These oxidation events increase the probability of permeability transition pore (PTP) opening, triggering mitochondrial swelling, and ultimately cell death. Notably, inhibition of oligomer-induced oxidation prevents the pathological induction of PTP. Inducible pluripotent stem cells (iPSC)-derived neurons bearing SNCA triplication, generate α-synuclein aggregates that interact with the ATP synthase and induce PTP opening, leading to neuronal death. This study shows how the transition of α-synuclein from its monomeric to oligomeric structure alters its functional consequences in Parkinson's disease.

Circulating tumour DNA for monitoring colorectal cancer-a prospective cohort study to assess relationship to tissue methylation, cancer characteristics and surgical resection.

Background: Cell-free circulating tumour-derived DNA (ctDNA) can be detected by testing for methylated BCAT1 and IKZF1 DNA, which has proven sensitivity for colorectal cancer (CRC). A prospective correlative biomarker study between presence of methylated BCAT1 and IKZF1 in tissue and blood was conducted in cases with CRC to explore how detection of such ctDNA biomarkers relates to cancer characteristics, methylation in tissue and surgical resection of the primary cancer. Methods: Enrolled patients with invasive CRC had blood collected at diagnosis, prior to any treatment or surgery (peri-diagnostic sample). A subgroup of patients also had cancer and adjacent non-neoplastic tissue collected at surgical resection, as well as a second blood sample collected within 12 months of surgery (post-surgery sample). DNA was extracted from all samples and assayed for methylated BCAT1 and IKZF1 to determine the degree of methylation in tissue and the presence of ctDNA in blood. Results: Of 187 cases providing peri-diagnostic blood samples, tissue was available in 91, and 93 provided at least one post-surgery blood sample for marker analysis. Significant methylation of either BCAT1 or IKZF1 was seen in 86/91 (94.5%) cancer tissues, with levels independent of stage and higher than that observed in adjacent non-neoplastic specimens (P < 0.001). ctDNA methylated in BCAT1 or IKZF1 was detected in 116 (62.0%) cases at diagnosis and was significantly more likely to be detected with later stage (P < 0.001) and distal tumour location (P = 0.004). Of the 91 patients who provided pre-and post-surgery blood samples, 47 patients were ctDNA-positive at diagnosis and 35 (74.5%) became negative after tumour resection. Conclusion: This study has shown that BCAT1 and IKZF1 methylation are common events in CRC with almost all cancer tissues showing significant levels of methylation in the two genes. The presence of ctDNA in blood is stage-related and show rapid reversion to negative following surgical resection. Monitoring methylated BCAT1 and IKZF1 levels could therefore inform adequacy of surgical resection. Trial registration: Australian New Zealand Clinical Trial Registry number 12611000318987. Registered 25 March 2011.

Detecting RNA base methylations in single cells by in situ hybridization.

Methylated bases in tRNA, rRNA and mRNA control a variety of cellular processes, including protein synthesis, antimicrobial resistance and gene expression. Currently, bulk methods that report the average methylation state of ~104-107 cells are used to detect these modifications, obscuring potentially important biological information. Here, we use in situ hybridization of Molecular Beacons for single-cell detection of three methylations (m62A, m1G and m3U) that destabilize Watson-Crick base pairs. Our method-methylation-sensitive RNA fluorescence in situ hybridization-detects single methylations of rRNA, quantifies antibiotic-resistant bacteria in mixtures of cells and simultaneously detects multiple methylations using multicolor fluorescence imaging.

Validation of a Circulating Tumor-Derived DNA Blood Test for Detection of Methylated BCAT1 and IKZF1 DNA.

BACKGROUND: Colvera™ is a test that detects circulating tumor-derived DNA in patients with colorectal cancer by assaying for the presence of methylated BCAT1 and IKZF1 in blood. This study describes the analytical and clinical performance characteristics of the test. METHODS: Validation was performed in accordance with ISO15189 and National Pathology Accreditation Advisory Council requirements. Spiked samples including 264 plasma and 120 buffer samples were randomized, divided into 8 batches of 48 samples, and processed over 8 days using 2 equipment lines (each line consisting of a QIAsymphony SP/AS, QIACube HT, and LC480); 2 reagent batches; and 2 operators to determine limit of detection, selectivity/specificity, precision, reproducibility, ruggedness, and susceptibility to commonly known interfering substances. Clinical performance was validated by assaying 222 archived plasma samples from subjects (n = 26 with cancer) enrolled in a previous prospective trial. RESULTS: The limit of detection for Colvera was 12.6 pg/mL (95% CI, 8.6-23.9 pg/mL), which equates to 2 diploid genome copies per milliliter plasma. No statistically significant difference was determined between testing days (n = 8), instrumentation, operators, or reagent batches in precision studies for the methylation-specific assays. The assay performance was unaffected by 9 commonly known interference substances, variations in bisulfite conversion, or quantitative PCR settings (cycling temperatures, incubation times, and oligonucleotide concentrations). For this clinical cohort, sensitivity and specificity estimates for Colvera were 73.1% (19 of 26; 95% CI, 52.2-88.4) and 89.3% (175 of 196; 95% CI, 84.1-93.2), respectively. CONCLUSION: Colvera is a robust test and suitable for detection of circulating tumor-derived DNA by measuring levels of methylated BCAT1 and IKZF1 in human blood plasma.