Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel imaging techniques using 18F‐florbetapir PET/MRI can guide fascicular nerve biopsy in amyloid multiple mononeuropathy

Multiple mononeuropathy is a rare presentation of primary (AL) amyloidosis and nerve biopsy is usually needed for diagnosis. Conventional imaging is useful to identify proximal nerve involvement but may be inadequate. We report a patient with multiple mononeuropathy whose presentation was suggestive of AL amyloid neuropathy and in whom repeated tissue biopsies were negative for amyloid (including two sensory nerves and one muscle).
Crystalline water in gypsum is unavailable for cyanobacteria in laboratory experiments and in natural desert endolithic habitats

Huang et al. (1) describe a supposed mechanism of water extraction from gypsum by cyanobacteria sampled from endoliths inhabiting Ca sulfates in the Atacama Desert, and cultivated in the laboratory. The authors claim that the phase transformation from gypsum (CaSO4·2H2O) to anhydrite (CaSO4) (G→A) occurred under “dry conditions” in the contact zone between a “dry biofilm” and the gypsum, where only {011} planes of gypsum are transformed to anhydrite, supposedly providing water for cyanobacteria. This work (1) has a number of major conceptual problems, as follows. First, the authors show the presence of gypsum and/or anhydrite in the inoculated Ca sulfate samples using X-ray diffraction and, incompletely, by Fourier transform infrared spectroscopy techniques (2), and not by Raman (3) or transmission electron microscopy. Selected area electron diffraction (SAED) data in ref. 1 do not allow any mineral identification, due to their differences with … [↵][1]1To whom correspondence may be addressed. Email: j.wierzchos{at}mncn.csic. es or oartieda{at}unex.es. [1]: #xref-corresp-1-1
Small molecules targeting cyclooxygenase/prostanoid cascade in experimental brain ischemia: Do they translate?

Acute brain ischemia accounts for most of stroke cases and constitutes a leading cause of deaths among adults and permanent disabilities in survivors. Currently, the intravenous thrombolysis is the only available medication for ischemic stroke; mechanical thrombectomy is an emerging alternative treatment for occlusion of large arteries and has shown some promise in selected subsets of patients. However, the overall narrow treatment window and potential risks largely limit the patient eligibility. New druggable targets are needed to innovate the treatment of brain ischemia. As the rate‐limiting enzyme in the biosyntheses of prostanoids, cyclooxygenase (COX), particularly the inducible isoform COX‐2, has long been implicated in mechanisms of acute stroke‐induced brain injury and inflammation. However, the notion of therapeutically targeting COX has been diminished over the past two decades due to significant complications of the cardiovascular and cerebrovascular systems caused by long‐term use of COX‐2 inhibitor drugs. New treatment strategies targeting the downstream prostanoid signaling receptors regulating the deleterious effects of COX cascade have been proposed. As such, a large number of selective small molecules that negatively or positively modulate these important inflammatory regulators have been evaluated for neuroprotection and other beneficial effects in various animal models of brain ischemia. These timely preclinical studies, though not yet led to clinical innovation, provided new insights into the regulation of inflammatory reactions in the ischemic brain and could guide drug discovery efforts aiming for novel adjunctive strategies, along with current reperfusion therapy, to treat acute brain ischemia with higher specificity and longer therapeutic window.
Prediction of Malignant Breast Cancer Cases Using Ensemble Machine Learning: A Case Study of Pesticides Prone Area

Cancer of the female breast is one of the leading types of cancers worldwide. This paper presents a case study of Malwa Belt in India that has witnessed the proliferation in the overall mortality rate due to breast cancer. The paper researches mortality aspect of the disease and its association with the various risk parameters including demographic characteristics, percentage of pesticides residue present in the water and soil, life style of the women in the affected area, water intake, and the amount of pesticide exposure to the patient. The levels of organochlorine pesticides like DDT and its metabolites and isomers of HCH in blood, tumor and surrounding adipose are estimated. Additionally, an extent of exposure of the subjects to environmental pollutants like heavy metals (Lead, Copper, Iron, Zinc, Calcium, Selenium, and Chromium etc.)are also examined. For the obtained experimental data, an efficient ensemble machine learning based framework called Bagoost is proposed to predict the risk of breast cancer in Malwa women. The performance of the proposed machine learning model results in an accuracy of 98.21 percent, when empirically tested using K-fold cross validation over the real time data of malignant and benign cases and is established to be efficacious than the existing approaches.
Distinctive regulatory architectures of germline-active and somatic genes in C. elegans

RNA profiling has provided increasingly detailed knowledge of gene expression patterns, yet the different regulatory architectures that drive them are not well understood. To address this, we profiled and compared transcriptional and regulatory element activities across five tissues of Caenorhabditis elegans, covering ∼90% of cells. We find that the majority of promoters and enhancers have tissue-specific accessibility, and we discover regulatory grammars associated with ubiquitous, germline, and somatic tissue–specific gene expression patterns. In addition, we find that germline-active and soma-specific promoters have distinct features. Germline-active promoters have well-positioned +1 and −1 nucleosomes associated with a periodic 10-bp WW signal (W = A/T). Somatic tissue–specific promoters lack positioned nucleosomes and this signal, have wide nucleosome-depleted regions, and are more enriched for core promoter elements, which largely differ between tissues. We observe the 10-bp periodic WW signal at ubiquitous promoters in other animals, suggesting it is an ancient conserved signal. Our results show fundamental differences in regulatory architectures of germline and somatic tissue–specific genes, uncover regulatory rules for generating diverse gene expression patterns, and provide a tissue-specific resource for future studies.
VPTMdb: a viral posttranslational modification database

In viruses, posttranslational modifications (PTMs) are essential for their life cycle. Recognizing viral PTMs is very important for a better understanding of the mechanism of viral infections and finding potential drug targets. However, few studies have investigated the roles of viral PTMs in virus-human interactions using comprehensive viral PTM datasets. To fill this gap, we developed the first comprehensive viral posttranslational modification database (VPTMdb) for collecting systematic information of PTMs in human viruses and infected host cells. The VPTMdb contains 1240 unique viral PTM sites with 8 modification types from 43 viruses (818 experimentally verified PTM sites manually extracted from 150 publications and 422 PTMs extracted from SwissProt) as well as 13 650 infected cells' PTMs extracted from seven global proteomics experiments in six human viruses. The investigation of viral PTM sequences motifs showed that most viral PTMs have the consensus motifs with human proteins in phosphorylation and five cellular kinase families phosphorylate more than 10 viral species. The analysis of protein disordered regions presented that more than 50% glycosylation sites of double-strand DNA viruses are in the disordered regions, whereas single-strand RNA and retroviruses prefer ordered regions. Domain-domain interaction analysis indicating potential roles of viral PTMs play in infections. The findings should make an important contribution to the field of virus-human interaction. Moreover, we created a novel sequence-based classifier named VPTMpre to help users predict viral protein phosphorylation sites. VPTMdb online web server (http://vptmdb.com:8787/VPTMdb/) was implemented for users to download viral PTM data and predict phosphorylation sites of interest.
Tumor necrosis factor induced oxidative stress in the central nervous system contributes to sympathoexcitation in heart failure

vi CHAPTER 1. BACKGROUND 1 CYTOKINES AND CARDIOVASCULAR DISEASES 2 SYMPATHOEXCITATION AND HEART FAILURE 4 REACTIVE OXYGEN SPECIES AND HEART FAILURE 6 STATEMENT OF THE PROBLEM AND SPECIFIC AIMS 13 REFERENCES 14 CHAPTER 2. TNF-α BLOCKADE DECREASES OXIDATIVE STRESS IN THE PARAVENTRICULAR NUCLEUS AND ATTENUATES SYMPATHOEXCITATION IN HEART FAILURE RATS 23 INTRODUCTION 24 METHODS 26 RESULTS 31 DISCUSSION 37 REFERENCES 44 CHAPTER 3. CYTOKINE BLOCKADE ATTENUATES SYMPATHOEXCITATION IN HEART FAILURE: CROSS-TALK BETWEEN nNOS, AT-1R AND CYTOKINES IN THE HYPOTHALAMIC PARAVENTRICULAR NUCLEUS 49 INTRODUCTION 50 METHODS 51 RESULTS 55 DISCUSSION 62 REFERENCES 67 CHAPTER 4. TNF CONTRIBUTES TO SYMPATHOEXCITATION IN HEART FAILURE THROUGH MODULATION OF SUPEROXIDE AND NITRIC OXIDE IN THE CENTRAL NERVOUS SYSTEM 7
Spatiotemporal Scenario Generation of Traffic Flow Based on LSTM-GAN

In recent years, a surging development of vehicles and continuous enhancement of transportation infrastructures have been witnessed worldwide, leading to a remarkable growing of traffic flow data. The traffic data is highly valuable in today’s society, accurate modelling of traffic flow for the concerned areas can significantly benefit the government agencies, related commercial departments and individuals. Specifically, road users are allowed to make better traveling decisions, avoid traffic congestion, reduce carbon emissions and improve traffic operation efficiency. In order to estimate the possible traffic flow scenarios within a specific area for multiple horizons, we propose a scenario generation model based on sequential generative adversarial networks (LSTM-GAN) where the long short term memory (LSTM) network is incorporated to capture the temporal dynamics involved in traffic flows. Through game training, the spatiotemporal scenarios of traffic flow in line with the characteristics of observed road network traffic flow can be well generated. These traffic scenarios can be applied in the design and planning of road traffic system, as well as in the virtual training cases of intelligent driving.
Proposed Implementation of Blockchain in British Columbia’s Health Care Data Management

Background There are several challenges such as information silos and lack of interoperability with the current electronic medical record (EMR) infrastructure in the Canadian health care system. These challenges can be alleviated by implementing a blockchain-based health care data management solution. Objective This study aims to provide a detailed overview of the current health data management infrastructure in British Columbia for identifying some of the gaps and inefficiencies in the Canadian health care data management system. We explored whether blockchain is a viable option for bridging the existing gaps in EMR solutions in British Columbia’s health care system. Methods We constructed the British Columbia health care data infrastructure and health information flow based on publicly available information and in partnership with an industry expert familiar with the health systems information technology network of British Columbia’s Provincial Health Services Authorities. Information flow gaps, inconsistencies, and inefficiencies were the target of our analyses. Results We found that hospitals and clinics have several choices for managing electronic records of health care information, such as different EMR software or cloud-based data management, and that the system development, implementation, and operations for EMRs are carried out by the private sector. As of 2013, EMR adoption in British Columbia was at 80% across all hospitals and the process of entering medical information into EMR systems in British Columbia could have a lag of up to 1 month. During this lag period, disease progression updates are continually written on physical paper charts and not immediately updated in the system, creating a continuous lag period and increasing the probability of errors and disjointed notes. The current major stumbling block for health care data management is interoperability resulting from the use of a wide range of unique information systems by different health care facilities. Conclusions Our analysis of British Columbia’s health care data management revealed several challenges, including information silos, the potential for medical errors, the general unwillingness of parties within the health care system to trust and share data, and the potential for security breaches and operational issues in the current EMR infrastructure. A blockchain-based solution has the highest potential in solving most of the challenges in managing health care data in British Columbia and other Canadian provinces.
Exposure Assessment of a 5G indoor planar array antenna using Computational Dosimetry

The following work is focused on the assessment of exposure levels in indoor environment, taking account the innovations of the upcoming 5G network technology. More in details, it was analyzed the exposure caused by a 5G access point in a room, modelled with an indoor 8x8 planar array antenna. The working frequency of the planar array antenna was selected according to the frequency range that will be used firstly in Italian 5G networks and will be 3.7 GHz. The exposure levels were assessed using the Ella model from the Virtual family. The quantity analyzed will be the specific absorption rate in the head tissues.
Postharvest Attributes of “Washington Navel” Orange as Affected by Preharvest Foliar Application of Calcium Chloride, Potassium Chloride, and Salicylic Acid

ABSTRACT To evaluate the effects of preharvest foliar application of calcium chloride (CaCl2), potassium chloride (KCl), and salicylic acid (SA) on postharvest quantitative and qualitative attributes and storage life of “Washington navel” orange, an experiment was conducted during two consecutive years. Solutions including CaCl2 (1.5% and 3%), KCl (1.5% and 3%), SA (0.015%, 0.03% and 0.045%), and the combination of CaCl2, KCl, and SA were sprayed on the canopy at the end of the first stage of fruit growth one month after full bloom (fruit diameter was 20 mm) and repeated in late September. The fruits were harvested at commercial maturity stage and were stored at 5°C with 85 ± 5% relative humidity (RH) for 90 days. Quantitative and qualitative characteristics were assessed every month. Preharvest KCl treatment had no significant effect on measured parameters. However, CaCl2 and SA treatments had the most impact on the quantitative and qualitative characteristics, such as firmness and phenolic content of fruit during storage. The SA treatment enhanced fruit appearance and nutritional value compared to the control but could not prevent the weight loss during storage. The results showed that preharvest spray of CaCl2, KCl, SA, and their combination had positive effects on storability of “Washington navel” orange fruit during storage. However, the effect of Ca and SA was more. Application of Ca, K, and SA could be beneficial for orange postharvest instead of mixed elements fertilizers.
A Bayesian adaptive phase I/II platform trial design for pediatric immunotherapy trials

Immunotherapy is the most promising new cancer treatment for various pediatric tumors and has resulted in an unprecedented surge in the number of novel immunotherapeutic treatments that need to be evaluated in clinical trials. Most phase I/II trial designs have been developed for evaluating only one candidate treatment at a time, and are thus not optimal for this task. To address these issues, we propose a Bayesian phase I/II platform trial design, which accounts for the unique features of immunotherapy, thereby allowing investigators to continuously screen a large number of immunotherapeutic treatments in an efficient and seamless manner. The elicited numerical utility is adopted to account for the risk‐benefit trade‐off and to quantify the desirability of the dose. During the trial, inefficacious or overly toxic treatments are adaptively dropped from the trial and the promising treatments are graduated from the trial to the next stage of development. Once an experimental treatment is dropped or graduated, the next available new treatment can be immediately added and tested. Extensive simulation studies have demonstrated the desirable operating characteristics of the proposed design.
Repurposing Colchicine to Combat Residual Cardiovascular Risk: The LoDoCo2 Trial

Over the last decades, our understanding of inflammatory processes involved in atherogenesis advanced considerably, with elements of R. Virchow's concept on atherosclerosis as a chronic inflammation induced by cholesterol appearing highly topical. Indeed, the Canakinumab Anti-Inflammatory Thrombosis Outcomes Study (CANTOS) taught us that specifically targeted anti-inflammatory therapy can confer protection from recurrent cardiovascular (CV) events without affecting lipid levels.
DNA damage and health effects in juvenile haddock (Melanogrammus aeglefinus) exposed to PAHs associated with oil-polluted sediment or produced water

The research objective was to study the presence of DNA damages in haddock exposed to petrogenic or pyrogenic polyaromatic hydrocarbons (PAHs) from different sources: 1) extracts of oil produced water (PW), dominated by 2-ring PAHs; 2) distillation fractions of crude oil (representing oil-based drilling mud), dominated by 3-ring PAHs; 3) heavy pyrogenic PAHs, mixture of 4/5/6-ring PAHs. The biological effect of the different PAH sources was studied by feeding juvenile haddock with low doses of PAHs (0.3–0.7 mg PAH/kg fish/day) for two months, followed by a two-months recovery. In addition to the oral exposure, a group of fish was exposed to 12 single compounds of PAHs (4/5/6-ring) via intraperitoneal injection. The main endpoint was the analysis of hepatic and intestinal DNA adducts. In addition, PAH burden in liver, bile metabolites, gene and protein expression of CYP1A, GST activity, lipid peroxidation, skeletal deformities and histopathology of livers were evaluated. Juvenile haddock responded quickly to both intraperitoneal injection and oral exposure of 4/5/6-ring PAHs. High levels of DNA adducts were detected in livers three days after the dose of the single compound exposure. Fish had also high levels of DNA adducts in liver after being fed with extracts dominated by 2-ring PAHs (a PW exposure scenario) and 3-ring PAHs (simulating an oil exposure scenario). Elevated levels of DNA adducts were observed in the liver of all exposed groups after the 2 months of recovery. High levels of DNA adduct were found also in the intestines of individuals exposed to oil or heavy PAHs, but not in the PW or control groups. This suggests that the intestinal barrier is very important for detoxification of orally exposures of PAHs.
Transformations of Monoterpenes with the p-Menthane Skeleton in the Enzymatic System of Bacteria, Fungi and Insects

The main objective of this article was to present the possibilities of using the enzymatic system of microorganisms and insects to transform small molecules, such as monoterpenes. The most important advantage of this type of reaction is the possibility of obtaining derivatives that are not possible to obtain with standard methods of organic synthesis or are very expensive to obtain. The interest of industrial centers focuses mainly on obtaining particles of high optical purity, which have the desired biological properties. The cost of obtaining such a compound and the elimination of toxic or undesirable chemical waste is important. Enzymatic reactions based on enzymes alone or whole microorganisms enable obtaining products with a specific structure and purity in accordance with the rules of Green Chemistry.
Improving Deep Reinforcement Learning for Financial Trading Using Neural Network Distillation

Deep Reinforcement Learning (RL) is increasingly used for developing financial trading agents for a wide range of tasks. However, optimizing deep RL agents is known to be notoriously difficult and unstable, hindering the performance of financial trading agents. In this work, we propose a novel method for training deep RL agents, leading to better performing and more efficient RL agents. The proposed method works by first training a large and complex deep RL agent and then transferring the knowledge into a smaller and more efficient agent using neural network distillation. The ability of the proposed method to significantly improve deep RL for financial trading is demonstrated using experiments on a time series dataset consisting of Foreign Exchange (FOREX) trading pairs prices.
Prediction of driver variants in the cancer genome via machine learning methodologies

Abstract Sequencing technologies have led to the identification of many variants in the human genome which could act as disease-drivers. As a consequence, a variety of bioinformatics tools have been proposed for predicting which variants may drive disease, and which may be causatively neutral. After briefly reviewing generic tools, we focus on a subset of these methods specifically geared toward predicting which variants in the human cancer genome may act as enablers of unregulated cell proliferation. We consider the resultant view of the cancer genome indicated by these predictors and discuss ways in which these types of prediction tools may be progressed by further research.
Advanced interdisciplinary treatment protocol for pediatric obstructive sleep apnea including medical, surgical, and orthodontic care: a narrative review

ABSTRACT Objective To suggest an updated interdisciplinary treatment protocol for pediatric obstructive sleep apnea (POSA) based on the integration of craniofacial growth modification into medical and surgical sleep practice. Methods PubMed, Scopus, and Cochrane library were searched up to February 2020 using keywords. Among 184 articles, 80 studies were finally included. An integrated treatment protocol for POSA encompassing craniofacial skeletal management as well as medical and surgical care was attempted. Results A differential diagnostic workflow for identifying the phenotype of POSA was suggested, and a phenotype-based treatment protocol for POSA was proposed. Despite the lack of high level of evidence, timely skeletal growth modification in three dimensions using craniofacial growth potential could be valuable treatment for upper airway development in POSA patients with craniofacial phenotypic cause. Conclusion A novel precision treatment protocol will advance clinicians to determine the primary option or to apply the combined strategy for POSA patients.