Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolutionary Potential of Cis-Regulatory Mutations to Cause Rapid Changes in Transcription Factor Binding

Abstract Transcriptional regulation is crucial for all biological processes and well investigated at the molecular level for a wide range of organisms. However, it is quite unclear how innovations, such as the activity of a novel regulatory element, evolve. In the case of transcription factor (TF) binding, both a novel TF and a novel-binding site would need to evolve concertedly. Since promiscuous functions have recently been identified as important intermediate steps in creating novel specific functions in many areas such as enzyme evolution and protein–protein interactions, we ask here how promiscuous binding of TFs to TF-binding sites (TFBSs) affects the robustness and evolvability of this tightly regulated system. Specifically, we investigate the binding behavior of several hundred TFs from different species at unprecedented breadth. Our results illustrate multiple aspects of TF-binding interactions, ranging from correlations between the strength of the interaction bond and specificity, to preferences regarding TFBS nucleotide composition in relation to both domains and binding specificity. We identified a subset of high A/T binding motifs. Motifs in this subset had many functionally neutral one-error mutants, and were bound by multiple different binding domains. Our results indicate that, especially for some TF–TFBS associations, low binding specificity confers high degrees of evolvability, that is that few mutations facilitate rapid changes in transcriptional regulation, in particular for large and old TF families. In this study we identify binding motifs exhibiting behavior indicating high evolutionary potential for innovations in transcriptional regulation.
Transfer Learning with Deep Convolutional Neural Networks for Classifying Cellular Morphological Changes

The quantification and identification of cellular phenotypes from high-content microscopy images has proven to be very useful for understanding biological activity in response to different drug treatments. The traditional approach has been to use classical image analysis to quantify changes in cell morphology, which requires several nontrivial and independent analysis steps. Recently, convolutional neural networks have emerged as a compelling alternative, offering good predictive performance and the possibility to replace traditional workflows with a single network architecture. In this study, we applied the pretrained deep convolutional neural networks ResNet50, InceptionV3, and InceptionResnetV2 to predict cell mechanisms of action in response to chemical perturbations for two cell profiling datasets from the Broad Bioimage Benchmark Collection. These networks were pretrained on ImageNet, enabling much quicker model training. We obtain higher predictive accuracy than previously reported, between 95% and 97%. The ability to quickly and accurately distinguish between different cell morphologies from a scarce amount of labeled data illustrates the combined benefit of transfer learning and deep convolutional neural networks for interrogating cell-based images.
Imaging human keratinocytes grown on electrospun mats by scanning electron microscopy

Drying is a critical step in preparing cell samples for examination with scanning electron microscopy (SEM). The two commonly used drying procedures are the critical point drying (CPD) and the chemical drying using hexamethyldisilazane (HMDS drying). Here we compared the application of these procedures for the drying of HaCaT human keratinocyte cells grown on electrospun nylon mats. Both drying procedures allowed us to obtain images of the cells and characterize the microvilli on the cell surface. After HMDS drying the membrane was less damaged than after CPD. Both drying procedures could be used to investigate contact guidance–the substrate‐induced changes in cell shape. The aspect ratio of HaCaT cells grown on the aligned and random mats was 4.2 ± 2.8 and 1.5 ± 0.3, respectively.
Epidemiologic Analysis Along the Mevalonate Pathway Reveals Improved Cancer Survival in Patients Who Receive Statins Alone and in Combination With Bisphosphonates.

PURPOSE Cohort studies report associations between statin use and improved survival in patients with cancer. We used pharmacoepidemiologic methods to evaluate the survival of patients with cancer who received statins alone or in ostensibly synergistic drug combinations. MATERIALS AND METHODS Patients with cancer who were diagnosed from 2010 to 2013 were identified in a large health care claims database. The rate of all-cause death up to 1 year after diagnosis was compared by Cox proportional hazard regression. Sensitivity analyses included age stratification, statin type and intensity, and comparison with or without bisphosphonates and dipyridamole. RESULTS Among 312,907 identified patients with cancer, treatment groups included statin users (n = 65,440), nonstatin users who received medications that block cholesterol absorption (n = 9,289), and nonusers (n = 226,007). Statin use before diagnosis was associated with improved overall survival compared with no treatment (hazard ratio [HR], 0.85; 95% CI, 0.80 to 0.91) and specifically in patients with leukemia, lung, or renal cancers. Nonstatin users had increased overall survival compared with no treatment (HR, 0.73; 95% CI, 0.62 to 0.85); when stratified, this difference held true only for pancreatic cancer and leukemia. No differences were observed between statin and nonstatin groups. Bisphosphonate use alone had no effect (n = 4,528), but patients who used both statins and bisphosphonates (n = 4,090) had increased survival compared with no treatment (HR, 0.60; 95% CI, 0.45 to 0.81). The effect of the combination of dipyridamole and statin use (n = 651) was not significant compared with no treatment. CONCLUSION This study suggests that the combination of statins with drugs that affect isoprenylation, such as bisphosphonates, improves survival in patients with cancer. Consideration of pathway-specific pharmacology allows for hypotheses testing with the pharmacoepidemiologic approach. Prospective evaluation of these findings warrants clinical investigation and preclinical mechanistic studies.
Feeding cycle alters the biophysics and molecular expression of voltage‐gated Na+ currents in rat hippocampal CA1 neurones

The function of hippocampus as a hub for energy balance is a subject of broad and current interest. This study aims at providing more evidence on this regard by addressing the effects of feeding cycle on the voltage‐gated sodium (Na+) currents of acutely isolated Wistar rat hippocampal CA1 neurones. Specifically, by applying patch clamp techniques (whole cell voltage clamp and single channel in inside‐out patches) we assessed the influence of feeding and fasting conditions on the intrinsic biophysical properties of Na+ currents. Additionally, mass spectrometry and western blotting experiments were used to address the effect of feeding cycle over the Na+ channel population of the rat hippocampus. Na+ currents were recorded in neurones obtained from fed and fasted animals (here termed “fed neurones” and “fasted neurones”, respectively). Whole cell Na+ currents of fed neurones, as compared to fasted neurones, showed increased mean maximum current density and a higher “window current” amplitude. We demonstrate that these results are supported by an increased single channel Na+ conductance in fed neurones and, also, by a greater Nav1.2 channel density in plasma membrane‐enriched fractions of fed samples (but not in whole hippocampus preparations). These results imply fast variations on the biophysics and molecular expression of Na+ currents of rat hippocampal CA1 neurones, throughout the feeding cycle. Thus, one may expect a differentiated regulation of the intrinsic neuronal excitability, which may account for the role of the hippocampus as a processor of satiety information.
Update on the Management of Occupational Asthma and Work-Exacerbated Asthma

Work-related asthma is the most common occupational lung disease encountered in clinical practice. In adult asthmatics, work-relatedness can account for 15%–33% of cases, but delays in diagnosis remain common and lead to worse outcomes. Accurate diagnosis of asthma is the first step to managing occupational asthma, which can be sensitizer-induced or irritant-induced asthma. While latency has traditionally been recognized as a hallmark of sensitizer-induced asthma and rapid-onset a defining feature of irritant-induced asthma (as in Reactive Airway Dysfunction Syndrome), there is epidemiological evidence for irritant-induced asthma with latency from chronic moderate exposure. Diagnostic testing while the patient is still in the workplace significantly improves sensitivity. While specific inhalational challenges remain the gold-standard for the diagnosis of occupational asthma, they are not available outside of specialized centers. Commonly available tests including bronchoprovocation challenges and peak flow monitoring are important tools for practicing clinicians. Management of sensitizer-induced occupational asthma is notable for the central importance of removal from the causative agent: ideally, removal of the culprit agent; but if not feasible, this may require changes in the work process or ultimately, removal of the worker from the workplace. While workers' compensation programs may reduce income loss, these are not universal and there can be significant socio-economic impact from work-related asthma. Primary prevention remains the preferred method of reducing the burden of occupational asthma, which may include modification to work processes, better worker education and substitution of sensitizing agents from the workplace with safer compounds.
An Observational Study of Deep Learning and Automated Evaluation of Cervical Images for Cancer Screening.

Background Human papillomavirus vaccination and cervical screening are lacking in most lower resource settings, where approximately 80% of more than 500 000 cancer cases occur annually. Visual inspection of the cervix following acetic acid application is practical but not reproducible or accurate. The objective of this study was to develop a "deep learning"-based visual evaluation algorithm that automatically recognizes cervical precancer/cancer. Methods A population-based longitudinal cohort of 9406 women ages 18-94 years in Guanacaste, Costa Rica was followed for 7 years (1993-2000), incorporating multiple cervical screening methods and histopathologic confirmation of precancers. Tumor registry linkage identified cancers up to 18 years. Archived, digitized cervical images from screening, taken with a fixed-focus camera ("cervicography"), were used for training/validation of the deep learning-based algorithm. The resultant image prediction score (0-1) could be categorized to balance sensitivity and specificity for detection of precancer/cancer. All statistical tests were two-sided. Results Automated visual evaluation of enrollment cervigrams identified cumulative precancer/cancer cases with greater accuracy (area under the curve [AUC] = 0.91, 95% confidence interval [CI] = 0.89 to 0.93) than original cervigram interpretation (AUC = 0.69, 95% CI = 0.63 to 0.74; P < .001) or conventional cytology (AUC = 0.71, 95% CI = 0.65 to 0.77; P < .001). A single visual screening round restricted to women at the prime screening ages of 25-49 years could identify 127 (55.7%) of 228 precancers (cervical intraepithelial neoplasia 2/cervical intraepithelial neoplasia 3/adenocarcinoma in situ [AIS]) diagnosed cumulatively in the entire adult population (ages 18-94 years) while referring 11.0% for management. Conclusions The results support consideration of automated visual evaluation of cervical images from contemporary digital cameras. If achieved, this might permit dissemination of effective point-of-care cervical screening.
Exploring Comorbidity Within Mental Disorders Among a Danish National Population

Importance Individuals with mental disorders often develop comorbidity over time. Past studies of comorbidity have often restricted analyses to a subset of disorders and few studies have provided absolute risks of later comorbidity. Objectives To undertake a comprehensive study of comorbidity within mental disorders, by providing temporally ordered age- and sex-specific pairwise estimates between the major groups of mental disorders, and to develop an interactive website to visualize all results and guide future research and clinical practice. Design, Setting, and Participants This population-based cohort study included all individuals born in Denmark between January 1, 1900, and December 31, 2015, and living in the country between January 1, 2000, and December 31, 2016. The analyses were conducted between June 2017 and May 2018. Main Outcomes and Measures Danish health registers were used to identify mental disorders, which were examined within the broad 10-level International Statistical Classification of Diseases and Related Health Problems, 10th Revision, subchapter groups (eg, codes F00-F09 and F10-F19). For each temporally ordered pair of disorders, overall and lagged hazard ratios and 95% CIs were calculated using Cox proportional hazards regression models. Absolute risks were estimated using competing risks survival analyses. Estimates for each sex were generated. Results A total of 5 940 778 persons were included in this study (2 958 293 men and 2 982 485 women; mean [SD] age at beginning of follow-up, 32.1 [25.4] years). They were followed up for 83.9 million person-years. All mental disorders were associated with an increased risk of all other mental disorders when adjusting for sex, age, and calendar time (hazard ratios ranging from 2.0 [95% CI, 1.7-2.4] for prior intellectual disabilities and later eating disorders to 48.6 [95% CI, 46.6-50.7] for prior developmental disorders and later intellectual disabilities). The hazard ratios were temporally patterned, with higher estimates during the first year after the onset of the first disorder, but with persistently elevated rates during the entire observation period. Some disorders were associated with substantial absolute risks of developing specific later disorders (eg, 30.6% [95% CI, 29.3%-32.0%] of men and 38.4% [95% CI, 37.5%-39.4%] of women with a diagnosis of mood disorders before age 20 years developed neurotic disorders within the following 5 years). Conclusions and Relevance Comorbidity within mental disorders is pervasive, and the risk persists over time. This study provides disorder-, sex-, and age-specific relative and absolute risks of the comorbidity of mental disorders. Web-based interactive data visualization tools are provided for clinical utility.
Exposure to Aspergillus in Home and Healthcare Facilities’ Water Environments: Focus on Biofilms

Aspergillus conida are ubiquitous in the environment, including freshwater, water for bathing, and in drinking water. Vulnerable patients and those suffering from allergic diseases are susceptible to aspergillosis. Avoidance of Aspergillus is of paramount importance. Potential outbreaks of aspergillosis in hospital facilities have been described where the water supply has been implicated. Little is known regarding the risk of exposure to Aspergillus in water. How does Aspergillus survive in water? This review explores the biofilm state of Aspergillus growth based on recent literature and suggests that biofilms are responsible for the persistence of Aspergillus in domestic and healthcare facilities’ water supplies.
Integrated omics profiling reveals novel patterns of epigenetic programming in cancer-associated myofibroblasts

Abstract There is increasing evidence that stromal myofibroblasts play a key role in the tumour development however, the mechanisms by which they become reprogrammed to assist in cancer progression remain unclear. As cultured cancer-associated myofibroblasts (CAMs) retain an ability to enhance the proliferation and migration of cancer cells in vitro, it is possible that epigenetic reprogramming of CAMs within the tumour microenvironment may confer long-term pro-tumourigenic changes in gene expression. This study reports the first comparative multi-omics analysis of cancer-related changes in gene expression and DNA methylation in primary myofibroblasts derived from gastric and oesophageal tumours. In addition, we identify novel CAM-specific DNA methylation signatures, which are not observed in patient-matched adjacent tissue-derived myofibroblasts, or corresponding normal tissue-derived myofibroblasts. Analysis of correlated changes in DNA methylation and gene expression shows that different patterns of gene-specific DNA methylation have the potential to confer pro-tumourigenic changes in metabolism, cell signalling and differential responses to hypoxia. These molecular signatures provide new insights into potential mechanisms of stromal reprogramming in gastric and oesophageal cancer, while also providing a new resource to facilitate biomarker identification and future hypothesis-driven studies into mechanisms of stromal reprogramming and tumour progression in solid tumours.
Cellular prion protein neither binds to alpha-synuclein oligomers nor mediates their detrimental effects

α-Synuclein oligomers are crucial players in the pathogenesis of Parkinson's disease. Some mechanisms involved in α-synuclein oligomer detrimental effects include membrane damage, neuroinflammation and protein-protein interactions. Recently, the cellular prion protein (PrPC) emerged as an interactor of α-synuclein oligomers, apparently mediating their detrimental activities. Through direct in vivo and in vitro approaches we herein investigated the existence of a direct cross-talk between α-synuclein oligomers and PrPC. In vitro, we assessed α-synuclein oligomer toxicity by comparing the effect in Prnp+/+ versus PrPC knockout (Prnp0/0) hippocampal neurons. Through an in vivo acute mouse model, where α-synuclein oligomers injected intracerebroventricularly induce memory impairment and neuroinflammation, we verified whether these detrimental effects were preserved in Prnp0/0 mice. In addition, PrPC-α-synuclein oligomer direct binding was investigated through surface plasmon resonance. We found that PrPC was not mandatory to mediate α-synuclein oligomer detrimental effects in vitro or in vivo. Indeed, α-synuclein oligomer toxicity was comparable in Prnp+/+ and Prnp0/0 neurons and both Prnp+/+ and Prnp0/0 mice injected with α-synuclein oligomers displayed memory deficit and hippocampal gliosis. Moreover, surface plasmon resonance analyses ruled out PrPC-α-synuclein oligomer binding. Our findings indicate that PrPC neither binds α-synuclein oligomers nor mediates their detrimental actions. Therefore, it is likely that PrPC-dependent and PrPC-independent pathways co-exist in Parkinson's disease.
Fat‐fated microglial dysfunction

Patients with lysosomal storage disorders (LSDs) exhibit activated microglia in the brain, but the mechanisms underlying microglial activation and contribution to disease pathology are unclear. In this issue, Gabandé‐Rodríguez et al present intriguing data to suggest a protective function for microglia that is corrupted by sphingolipid lysosomal overload in Niemann‐Pick disease type A.
Variation of tolerance and accumulation to excess iron in 24 willow clones: Implications for phytoextraction

Abstract Willows (Salix spp.) are characterized by having large biomass, high tolerance to flooding, and strong metal accumulation ability, exhibiting great promise in the phytoremediation of iron (Fe) from contaminated sites. In this study, the variation of Fe tolerance and accumulation in 24 willow clones was investigated with two levels of Fe(II)-EDTA, 0.025 mM (control) and 2.0 mM (treatment) by hydroponic system for 21 days in a greenhouse. Visual symptoms of Fe toxicity were observed in the leaves and roots of Fe sensitive clones. Clonal comparisons showed a great variation in Fe tolerance, and the high levels of Fe reduced biomass productions of most clones. Tolerance indexes (TIs) varied about five-fold based on shoot dry biomass and about six-fold based on root dry biomass among clones. Clones also exhibited a wide variation in Fe concentrations (mg g–1 DW), ranged from 0.80 to 3.41 in leaves, from 5.40 to 10.51 in stems, and from 3.25 to 17.10 in roots under Fe treatments among clones. Large differences varied in the transport of Fe from roots to aerial parts among clones. The results highlighted the selection of Salix clones with high resistance to Fe toxicity and high Fe accumulation to improve phytoremediation efficacy.
Erythropoietin Protects Against Cognitive Impairment and Hippocampal Neurodegeneration in Diabetic Mice

Administration of erythropoietin (EPO) is neuroprotective against a variety of experimentally-induced neurological disorders. The aim was to determine if EPO protects against hippocampal neurodegeneration as well as impairment of cognition and motor performance, associated with long-term diabetes. BALB/c mice were randomly allocated between control, diabetic and EPO-treated diabetic groups. EPO-treated diabetic mice were administered EPO 0.05 U/kg/day i.p. three times/week for 10 weeks. Cognition was assessed by Morris water maze. Brain samples were processed for light microscopic evaluation of hippocampus. Controls showed gradual improvement of cognitive performance in water maze when comparing latency (p < 0.01) and distance swum to reach the platform (p = 0.001). There was a similar trend for improvement in EPO-treated diabetics (p < 0.001). Latency did not improve in diabetic animals indicating lack of learning (p = 0.79). In probe trials, controls and EPO-treated diabetics spent more time in the training quadrant than expected by chance (p < 0.001). Diabetics did not show memory recall behavior; performance was significantly worse than expected by chance (p = 0.023). In diabetics, there was neurodegeneration in hippocampus and reduction in number of granule cells (p < 0.01) in the dentate gyrus. EPO treatment improved these neurodegenerative changes and preserved numbers of granule cells (p < 0.1, compared to controls). Erythropoietin treatment is protective against cognitive deficits and hippocampal neurodegeneration in diabetic mice.
Fast Flow-Line-Based Analysis of Ultrasound Spectral and Vector Velocity Estimators

A new technique, termed FLUST (FlowLine Ultrasound Simulation Tool), is proposed as a computationally cheap alternative to simulations based on randomly positioned scatterers for the simulation of stationary blood velocity fields. In FLUST, the flow field is represented as a collection of flow lines. Point spread functions are first calculated at regularly spaced positions along the flow lines before realizations of single scatterers traversing the flow lines are generated using temporal interpolation. Several flow-line realizations are then generated by convolution with temporal noise filters, and finally, flow-field realizations are obtained by the summation of the individual flow-line realizations. Flow-field realizations produced by FLUST are shown to correspond well with conventional Field II simulations both quantitatively and qualitatively. The added value of FLUST is demonstrated by using the proposed simulation technique to obtain multiple realizations of realistic 3-D flow fields at a significantly reduced computational cost. This information is utilized for a performance assessment of different spectral and vector velocity estimators for carotid and coronary imaging applications. The computational load of FLUST does not increase substantially with the number of realizations or simulated frames, and for the examples shown, it is the fastest alternative when the total number of simulated frames exceeds 48. In the examples, the standard deviation and bias of the velocity estimators are calculated using 100 FLUST realizations, in which case the proposed method is two orders of magnitude faster than simulations based on random scatterer positions.