Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative histopathology and immunohistochemistry of human and canine mammary tumors

This study aimed at establishing aspects of comparison between canine and human mammary gland tumors. In order to achieve that, 44 specimens of canine mammary tumors and 70 specimens of human breast tumors were examined in order to state points of similarity in morphology, cells of origin, behavior and existence of tissue markers. We found that the ratio of benign to malignant forms was 4.5% to 95.5% in canine samples and 45.7% to 54.3% in human samples. In both species, malignant tumors composed of infiltrating ductal cells were in the forefront despite dissimilarity in nomenclature. Other kinds of lower rate of existence included, invasive micro-papillary carcinoma, mucinous carcinoma and invasive comedo-carcinoma which have displayed similar morphology and terminology in both species. Chondroid and squamous differentiation were found in human and canine specimens. In human samples, fibro-adenoma mounted up to 30 out of 32 benign tumors (93.8%). Her-2 and Ki-67 were detected in the specimens of both species but ER was detected in human specimens only. Our findings suggest a significant degree of resemblance between certain mammary tumor in canine and human. Such findings are in support of employing dogs in research investigation for human mammary tumors.
Local strategies and delivery systems for the treatment of malignant gliomas

Abstract Glioma is one of the most common type of malignant tumours with high morbidity and mortality rates. Due to the particular features of the brain, such as blood–brain barrier or blood–tumour barrier, therapeutic agents are ineffective by systemic administration. The tumour inevitably recurs and devitalises patients. Herein, an overview of the localised gliomas treatment strategies is provided, including direct intratumoural/intracerebral injection, convection-enhanced delivery, and the implant of biodegradable polymer systems. The advantages and disadvantages of each therapy are discussed. Subsequently, we have reviewed the recent developments of therapeutic delivery systems aimed at transporting sufficient amounts of antineoplastic drugs into the brain tumour sites while minimising the potential side effects. To treat gliomas, localised and controlled delivery of drugs at their desired site of action is preferred as it reduces toxicity and increases treatment efficiency. Simultaneously, various drug delivery systems (DDS) have been used to enhance drug delivery to the brain. Use of non-conventional DDS for localised therapy has greatly expanded the spectrum of drugs available for the treatment of malignant tumours. Use smart DDS via localised delivery strategies, in combination with radiotherapy and multiple drug loading would serve as a promising approach to treat gliomas.
BAMM gives misleading rate estimates in simulated and empirical datasets

In a previous paper, we used simulations and empirical data to show that BAMM (Bayesian Analysis of Macroevolutionary Mixtures) can give misleading estimates of rates and rate shifts. In simulations, BAMM underestimated rate shifts across every tree analyzed, and assigned incorrect rates to most clades in most trees. In empirical analyses, BAMM behaved as expected from simulations, and assigned different rates to clades when clades were analyzed alone versus across the tree (i.e., with rate heterogeneity). Rabosky recently criticized our paper, focusing primarily on the idea that our comparison of BAMM to another approach (method‐of‐moments estimators of Magallón and Sanderson, or MS estimators) was unfair to BAMM. Here, we provide further evidence that BAMM gives misleading rate estimates in empirical studies. We then describe how Rabosky's rown method comparisons were either acknowledged as being problematic or were described inaccurately (to favor BAMM). Finally, we show that the MS estimators can perform well when rates vary over time, despite untested assertions that they require constant rates to be accurate. Many other methods are available for analyzing diversification rates: we argue that BAMM should be avoided for estimating both diversification rates and rate shifts.
A survey of data transfer and storage techniques in prevalent cryptocurrencies and suggested improvements

This thesis focuses on aspects related to the functioning of the gossip networks underlying three relatively popular cryptocurrencies: Ethereum, Nano and IOTA. We look at topics such as automatic discovery of peers when a new node joins the network, bandwidth usage of a node, message passing protocols and storage schemas and optimizations for the shared ledger. We believe this is a topic that is often overlooked in works about blockchains and cryptocurrencies. Vulnerabilities and inefficiencies attain a higher significance than ones in a regular open source project because of the rather direct financial implications of these projects. Barring Bitcoin, a network that has been around for nearly 10 years, no other project has substantial documentation for its operational details other than scattered and sparse pages in the source code repositories. Almost all of the content described here has been extracted by studying the source code of the reference implementations of these projects. We evaluate the use of Invertible Bloom Lookup Tables and the Graphene protocol to decrease block propagation times and bandwidth usage of certain messages. We perform realistic simulations that show significant improvements. We provide a complete implementation of Graphene in Geth, Ethereum's main node software and test this implementation against the main Ethereum blockchain. We also crawled the chosen cryptocurrency networks for publicly visible nodes and provide an Autonomous System-level breakdown of these nodes with the end goal of estimating the ease of performing attacks such as BGP hijacks and their impact. Code written for implementing Graphene in Geth, performing various simulations and for other miscellaneous tasks has been uploaded to Github at this https URL.
Computational resources associating diseases with genotypes, phenotypes and exposures

Abstract The causes of a disease and its therapies are not only related to genotypes, but also associated with other factors, including phenotypes, environmental exposures, drugs and chemical molecules. Distinguishing disease-related factors from many neutral factors is critical as well as difficult. Over the past two decades, bioinformaticians have developed many computational resources to integrate the omics data and discover associations among these factors. However, researchers and clinicians are experiencing difficulties in choosing appropriate resources from hundreds of relevant databases and software tools. Here, in order to assist the researchers and clinicians, we systematically review the public computational resources of human diseases related to genotypes, phenotypes, environment factors, drugs and chemical exposures. We briefly describe the development history of these computational resources, followed by the details of the relevant databases and software tools. We finally conclude with a discussion of current challenges and future opportunities as well as prospects on this topic.
VerIDeep: Verifying Integrity of Deep Neural Networks through Sensitive-Sample Fingerprinting

Deep learning has become popular, and numerous cloud-based services are provided to help customers develop and deploy deep learning applications. Meanwhile, various attack techniques have also been discovered to stealthily compromise the model's integrity. When a cloud customer deploys a deep learning model in the cloud and serves it to end-users, it is important for him to be able to verify that the deployed model has not been tampered with, and the model's integrity is protected. We propose a new low-cost and self-served methodology for customers to verify that the model deployed in the cloud is intact, while having only black-box access (e.g., via APIs) to the deployed model. Customers can detect arbitrary changes to their deep learning models. Specifically, we define \texttt{Sensitive-Sample} fingerprints, which are a small set of transformed inputs that make the model outputs sensitive to the model's parameters. Even small weight changes can be clearly reflected in the model outputs, and observed by the customer. Our experiments on different types of model integrity attacks show that we can detect model integrity breaches with high accuracy ($>$99\%) and low overhead ($<$10 black-box model accesses).
Using Randomness to Improve Robustness of Machine-Learning Models Against Evasion Attacks

Machine learning models have been widely used in security applications such as intrusion detection, spam filtering, and virus or malware detection. However, it is well-known that adversaries are always trying to adapt their attacks to evade detection. For example, an email spammer may guess what features spam detection models use and modify or remove those features to avoid detection. There has been some work on making machine learning models more robust to such attacks. However, one simple but promising approach called {\em randomization} is underexplored. This paper proposes a novel randomization-based approach to improve robustness of machine learning models against evasion attacks. The proposed approach incorporates randomization into both model training time and model application time (meaning when the model is used to detect attacks). We also apply this approach to random forest, an existing ML method which already has some degree of randomness. Experiments on intrusion detection and spam filtering data show that our approach further improves robustness of random-forest method. We also discuss how this approach can be applied to other ML models.
Timing of adolescent emotional disclosures: The role of maternal emotions and adolescent age.

Adolescent disclosure is a positive feature of parent-adolescent relationships, though disclosure to parents typically declines across adolescence. However, little is known about parental emotions that facilitate or inhibit real-time adolescent disclosures about their emotions and how parents respond to such disclosures during parent-adolescent interactions. The present study tested (1) whether maternal emotions were associated with the time to adolescents' spontaneous emotional disclosures and (2) whether these associations varied as a function of adolescent age. Adolescents (N = 49, Mage = 14.84 years) and their mothers participated in a 10-min conflict discussion. Adolescent emotional disclosures and maternal emotions were coded moment-to-moment. Results from survival analysis demonstrated that older adolescents whose mothers expressed high levels of negative affect or high levels of validation were more likely to make emotional disclosures earlier in the discussion than were older adolescents whose mothers expressed low negative affect or low validation. There were no differences in associations between maternal emotions and the timing of emotional disclosures for younger adolescents. Findings suggest that a range of maternal emotions (validation and negative affect) might be features of high-quality mother-adolescent relationships in older adolescence, when parent-adolescent relationships are more egalitarian and negative emotions may be more readily expressed. Implications for applying observational methodologies and dynamic statistical techniques to the adolescent disclosure literature are discussed. (PsycINFO Database Record
Analyzing of Molecular Networks for Human Diseases and Drug Discovery

Molecular networks represent the interactions and relations of genes/proteins, and also encode molecular mechanisms of biological processes, development and diseases. Among the molecular networks, protein-protein Interaction Networks (PINs) have become effective platforms for uncovering the molecular mechanisms of diseases and drug discovery. PINs have been constructed for various organisms and utilized to solve many biological problems. In human, most proteins present their complex functions by interactions with other proteins, and the sum of these interactions represents the human protein interactome. Especially in the research on human disease and drugs, as an emerging tool, the PIN provides a platform to systematically explore the molecular complexities of specific diseases and the references for drug design. In this review, we summarized the commonly used approaches to aid disease research and drug discovery with PINs, including the network topological analysis, identification of novel pathways, drug targets and sub-network biomarkers for diseases. With the development of bioinformatic techniques and biological networks, PINs will play an increasingly important role in human disease research and drug discovery.
Double methylation of tRNA-U54 to 2′-O-methylthymidine (Tm) synergistically decreases immune response by Toll-like receptor 7

Abstract Sensing of nucleic acids for molecular discrimination between self and non-self is a challenging task for the innate immune system. RNA acts as a potent stimulus for pattern recognition receptors including in particular human Toll-like receptor 7 (TLR7). Certain RNA modifications limit potentially harmful self-recognition of endogenous RNA. Previous studies had identified the 2′-O-methylation of guanosine 18 (Gm18) within tRNAs as an antagonist of TLR7 leading to an impaired immune response. However, human tRNALys3 was non-stimulatory despite lacking Gm18. To identify the underlying molecular principle, interferon responses of human peripheral blood mononuclear cells to differentially modified tRNALys3 were determined. The investigation of synthetic modivariants allowed attributing a significant part of the immunosilencing effect to the 2′-O-methylthymidine (m5Um) modification at position 54. The effect was contingent upon the synergistic presence of both methyl groups at positions C5 and 2’O, as shown by the fact that neither Um54 nor m5U54 produced any effect alone. Testing permutations of the nucleobase at ribose-methylated position 54 suggested that the extent of silencing and antagonism of the TLR7 response was governed by hydrogen patterns and lipophilic interactions of the nucleobase. The results identify a new immune-modulatory endogenous RNA modification that limits TLR7 activation by RNA.
Umbelliferone as a Small Molecular Peroxidase Mimic towards Sensitive Detection of H_2O_2 and Glucose

In this work, umbelliferone, a kind of coumarin derivative, was proved to exhibit peroxidase-like activity that could catalyze the oxidation of 3,3′,5,5′-tetramethylbenzidine (TMB) in the presence of hydrogen peroxide to generate a blue-colored oxide (oxTMB). The catalytic mechanism is similar to that of native enzymes ( e.g . horseradish peroxidase, HRP) and nanozymes, which follow the Michaelis–Menten kinetics behavior. Meanwhile, the 7-hydroxyl group of umbelliferone plays a significant role in the peroxidase-like activity. Compared with enzymes and nanozymes, this small molecular mimic enzyme possesses the advantages of low cost, simple molecular structures, small molecular weight and high stability against harsh conditions. Based on the favorable peroxidase mimetic activity of umbelliferone, a convenient, practical and sensitive H_2O_2 and glucose detection method was successfully established. This work not only opens some new inspirations into seeking for novel molecular enzyme mimetics with excellent catalytic activities, but also provides promising assays for clinical diagnosis.
Ionization chamber dosimetry based on 60Co absorbed dose to water calibration for diagnostic kilovoltage x-ray beams

The purpose of this study was to develop a new ionization chamber dosimetry formalism for diagnostic kilovoltage x-ray beams based on a 60Co absorbed dose-to-water calibration coefficient . To validate the new chamber dosimetry, 39 fluence spectra of kilovoltage x-rays were calculated, using a SpekCalc program, for Al half-value-layer (Al-HVL) values of 1.4–8.5 mm and tube voltages of 50–137.6 kVp. We used these spectra to calculate the beam quality conversion factor for kilovoltage x-ray beams Qx to a 60Co beam for a PTW 30013 Farmer® ionization chamber in a reference geometrical setup (depth = 1 cm in water, field size = 20 × 20 cm2). The absorbed dose to water for kilovoltage x-rays was obtained using and . Meanwhile, the water surface dose based on the air kerma calibration coefficient NK was obtained using a Monte Carlo-calculated correction factor CF (corresponding to in AAPM TG-61) for the 39 x-ray fluence spectra. The absorbed dose based on was validated by comparing the water surface dose for the 39 x-ray fluence spectra with the water surface dose based on NK. The water surface dose based on was obtained using Monte Carlo-calculated percentage depth doses. For Al-HVL ranging from 1.4 to 8.5 mm, ranged from 0.884 to 0.956 and CF ranged from 1.264 to 1.663. The water surface dose based on for the x-ray fluence spectra was 1.0% higher on average than that based on NK, except for Al-HVLs of 1.4 and 1.5 mm and 1% was within their uncertainty ranges. Therefore, it is possible to use the absorbed dose-to-water value based on instead of on NK. With the new chamber dosimetry, the chamber reading can be easily converted to the absorbed dose using and the calculated .
Band selection with Higher Order Multivariate Cumulants for small target detection in hyperspectral images

In the small target detection problem a pattern to be located is on the order of magnitude less numerous than other patterns present in the dataset. This applies both to the case of supervised detection, where the known template is expected to match in just a few areas and unsupervised anomaly detection, as anomalies are rare by definition. This problem is frequently related to the imaging applications, i.e. detection within the scene acquired by a camera. To maximize available data about the scene, hyperspectral cameras are used; at each pixel, they record spectral data in hundreds of narrow bands. The typical feature of hyperspectral imaging is that characteristic properties of target materials are visible in the small number of bands, where light of certain wavelength interacts with characteristic molecules. A target-independent band selection method based on statistical principles is a versatile tool for solving this problem in different practical applications. Combination of a regular background and a rare standing out anomaly will produce a distortion in the joint distribution of hyperspectral pixels. Higher Order Cumulants Tensors are a natural `window' into this distribution, allowing to measure properties and suggest candidate bands for removal. While there have been attempts at producing band selection algorithms based on the 3 rd cumulant's tensor i.e. the joint skewness, the literature lacks a systematic analysis of how the order of the cumulant tensor used affects effectiveness of band selection in detection applications. In this paper we present an analysis of a general algorithm for band selection based on higher order cumulants. We discuss its usability related to the observed breaking points in performance, depending both on method order and the desired number of bands. Finally we perform experiments and evaluate these methods in a hyperspectral detection scenario.
Prevalence, incidence and predictors of volunteer community health worker attrition in Kwale County, Kenya

Introduction In underserved populations, the contribution of community health workers (CHWs) is vital to the healthcare systems. Attrition of these workers causes critical breakdowns in the delivery of essential services to these populations. Literature on reasons for attrition is limited, although some have been identified in studies on sustainability of CHW programmes. These factors are, however, likely to be influenced by context. We measured CHW attrition and its predictors in a rural area in Kenya. Methods We conducted a nested case–control study and focus group discussions among CHWs involved in a maternal and child health project. A training register of 1005 CHWs was used to sample and follow CHWs for attrition. Incidence of CHW attrition was calculated using a Poisson model. Separately, we used logistic regression to determine predictors of CHW attrition. Results Of the 1005 CHWs, 498 (49.6%) had left the project by the time of the study. The incidence of attrition was 46.8/1000 person-years (95% CI 38.7 to 56.5). In the case–control study, lack of interest in peer organisation membership (OR 5.3; 95% CI 1.3 to 20.6) was associated with attrition. Absence of refresher training (OR 4.0; 95% CI 2.2 to 7.1) and receiving no feedback from supervisors (OR 2.0; 95% CI 1.0 to 3.9) were also associated with attrition. Discordance in expectations and perceived heavy workload were also identified as key reasons for attrition in the qualitative study. Conclusion This study estimates high prevalence and incidence of CHW attrition in Kwale County, Kenya. Ongoing training, feedback and peer support are also important in enhancing retention of CHWs. Additionally, expectations regarding the roles and benefits of involvement in CHW work should be communicated clearly, and workload should be kept reasonable or negotiated with the CHWs.
Society of Interventional Radiology Reporting Standards for Thoracic Central Vein Obstruction: Endorsed by the American Society of Diagnostic and Interventional Nephrology (ASDIN), British Society of Interventional Radiology (BSIR), Canadian Interventional Radiology Association (CIRA), Heart Rhythm 

Society of Interventional Radiology Reporting Standards for Thoracic Central Vein Obstruction: Endorsed by the American Society of Diagnostic and Interventional Nephrology (ASDIN), British Society of Interventional Radiology (BSIR), Canadian Interventional Radiology Association (CIRA), Heart Rhythm Society (HRS), Indian Society of Vascular and Interventional Radiology (ISVIR), Vascular Access Society of the Americas (VASA), and Vascular Access Society of Britain and Ireland (VASBI)
Schizosaccharomyces pombe Pol II transcription elongation factor ELL functions as part of a rudimentary super elongation complex

Abstract ELL family transcription factors activate the overall rate of RNA polymerase II (Pol II) transcription elongation by binding directly to Pol II and suppressing its tendency to pause. In metazoa, ELL regulates Pol II transcription elongation as part of a large multisubunit complex referred to as the Super Elongation Complex (SEC), which includes P-TEFb and EAF, AF9 or ENL, and an AFF family protein. Although orthologs of ELL and EAF have been identified in lower eukaryotes including Schizosaccharomyces pombe, it has been unclear whether SEC-like complexes function in lower eukaryotes. In this report, we describe isolation from S. pombe of an ELL-containing complex with features of a rudimentary SEC. This complex includes S. pombe Ell1, Eaf1, and a previously uncharacterized protein we designate Ell1 binding protein 1 (Ebp1), which is distantly related to metazoan AFF family members. Like the metazoan SEC, this S. pombe ELL complex appears to function broadly in Pol II transcription. Interestingly, it appears to have a particularly important role in regulating genes involved in cell separation.