Miracle-dz/UniFAR-FTUs huggingface dataset:
Chromophorylation of cyanobacteriochrome Slr1393 from Synechocystis sp. PCC 6803 is regulated by protein Slr2111 through allosteric interaction

Cyanobacteriochromes (CBCRs) are photochromic proteins in cyanobacteria that act as photosensors. CBCRs bind bilins as chromophores and sense nearly the entire visible spectrum of light, but the regulation of the chromophorylation of CBCRs is unknown. Slr1393 from Synechocystis sp. PCC 6803 is a CBCR containing three consecutive GAF (cGMP phosphodiesterase, adenylyl cyclase, and FhlA protein) domains, of which only the third one (Slr1393g3) can be phycocyanobilin-chromophorylated. The protein Slr2111 from Synechocystis sp. PCC 6803 includes a cystathionine β-synthase (CBS) domain pair of an as yet unknown function at its N terminus. CBS domains are often characterized as sensors of cellular energy status by binding nucleotides. In this work, we demonstrate that Slr2111 strongly interacts with Slr1393 in vivo and in vitro, which generates a complex in a 1:1 molar ratio. This tight interaction inhibits the chromophorylation of Slr1393g3, even if the chromophore is present. Instead, the complex stability and thereby the chromophorylation of Slr1393 are regulated by the binding of nucleotides (ATP, ADP, AMP) to the CBS domains of Slr2111 with varying affinities. It is demonstrated that residues Asp-53 and Arg-97 of Slr2111 are involved in nucleotide binding. While ATP binds to Slr2111, the association between the two proteins gets weaker and chromophorylation of Slr1393 are enabled. In contrast, AMP binding to Slr2111 leads to a stronger association, thereby inhibiting the chromophorylation. It is concluded that Slr2111 acts as a sensor of the cellular energy status that regulates the chromophorylation of Slr1393 and thereby its function as a light-driven histidine kinase.
Miniature Uncooled and Unchopped Fiber Optic Infrared Thermometer for Application to Cutting Tool Temperature Measurement

A new infrared thermometer, sensitive to wavelengths between 3 μm and 3.5 μm, has been developed. It is based on an Indium Arsenide Antimony (InAsSb) photodiode, a transimpedance amplifier, and a sapphire fiber optic cable. The thermometer used an uncooled photodiode sensor and received infrared radiation that did not undergo any form of optical chopping, thereby, minimizing the physical size of the device and affording its attachment to a milling machine tool holder. The thermometer is intended for applications requiring that the electronics are located remotely from high-temperature conditions incurred during machining but also affording the potential for use in other harsh conditions. Other example applications include: processes involving chemical reactions and abrasion or fluids that would otherwise present problems for invasive contact sensors to achieve reliable and accurate measurements. The prototype thermometer was capable of measuring temperatures between 200 °C and 1000 °C with sapphire fiber optic cable coupling to high temperature conditions. Future versions of the device will afford temperature measurements on a milling machine cutting tool and could substitute for the standard method of embedding thermocouple wires into the cutting tool inserts. Similarly, other objects within harsh conditions could be measured using these techniques and accelerate developments of the thermometer to suit particular applications.
CIAhelper: towards change impact analysis in delta-oriented software product lines

Change is inevitable for software systems to deal with the evolving environment surrounding them, and applying changes requires careful design and implementation not to break existing functionalities. Evolution in software product lines (SPLs) is more complex compared to evolution for individual products: a change applied to a single feature might affect all the products in the whole product family. In this paper we present an approach for change impact analysis in delta-oriented programming (DOP), an existing language aimed at supporting SPLs. We propose the CIAHelper tool to identify dependencies within a DOP program, by analyzing the semantics of both the code artifacts and variability models to construct a directed dependency graph. We also consider how the source code history could be used to enhance the recall of detecting the affected artifacts given a change proposal. We evaluate our approach by means of five case studies on two different DOP SPLs.
Variability of the circulation processes in the Lower Volga Region on the background of global climate trends

In this article we consider variability of the character of atmospheric circulation during different periods of climatic variability in the Lower Volga region as part of the Atlantic-Eurasian hemisphere sector. Variability of the circulation regime is analyzed with the involvement of the regional typification of synoptic processes by V. L. Arkhangelsky - E. A. Polyanskaya. It is shown that during the phase of the second wave of global warming compared to the period of stabilization in the South-East of the Russian Plain we actually see the decrease of the polarfront cyclones occurrence frequency, the increase of cyclones frequency on the Arctic front and the intrusion of Arctic anticyclones. The revealed character of synoptic processes changes is reflected in the reconstructions of geopotential fields at the middle level of the troposphere. The climatically meaningful conclusion was also made about the stabilizing role of the atmospheric circulation and the formation of the specific features of the climatic variability that does not have analogues in the period of regular meteorological observations.
The role of diversity in data‐driven analysis of multi‐subject fMRI data: Comparison of approaches based on independence and sparsity using global performance metrics

Data‐driven methods have been widely used in functional magnetic resonance imaging (fMRI) data analysis. They extract latent factors, generally, through the use of a simple generative model. Independent component analysis (ICA) and dictionary learning (DL) are two popular data‐driven methods that are based on two different forms of diversity—statistical properties of the data—statistical independence for ICA and sparsity for DL. Despite their popularity, the comparative advantage of emphasizing one property over another in the decomposition of fMRI data is not well understood. Such a comparison is made harder due to the differences in the modeling assumptions between ICA and DL, as well as within different ICA algorithms where each algorithm exploits a different form of diversity. In this paper, we propose the use of objective global measures, such as time course frequency power ratio, network connection summary, and graph theoretical metrics, to gain insight into the role that different types of diversity have on the analysis of fMRI data. Four ICA algorithms that account for different types of diversity and one DL algorithm are studied. We apply these algorithms to real fMRI data collected from patients with schizophrenia and healthy controls. Our results suggest that no one particular method has the best performance using all metrics, implying that the optimal method will change depending on the goal of the analysis. However, we note that in none of the scenarios we test the highly popular Infomax provides the best performance, demonstrating the cost of exploiting limited form of diversity.
Scleral remodelling in myopia and its manipulation: a review of recent advances in scleral strengthening and myopia control

The biological mechanisms of eye growth and refractive development are increasingly well characterised, a result of many careful studies that have been carried out over many years. As the outer coat of the eye, the sclera has the ultimate impact on the restraint or facilitation of eye growth, thus any changes in its biochemistry, ultrastructure, gross morphology and/or biomechanical properties are critical in refractive error development and, in particular, the development of myopia. The current review briefly revisits our basic understanding of the structure and biomechanics of the sclera and how these are regulated and modified during eye growth and myopia development. The review then applies this knowledge in considering recent advances in our understanding of how the mechanisms of scleral remodelling may be manipulated or controlled, in order to constrain eye growth and limit the development of myopia, in particular the higher degrees of myopia that lead to vision loss and blindness. In doing so, the review specifically considers recent approaches to the strengthening of the sclera, through collagen cross-linking, scleral transplantation, implantation or injection of biomaterials, or the direct therapeutic targeting and manipulation of the biochemical mechanisms known to be involved in myopia development. These latest approaches to the control of scleral changes in myopia are, where possible, placed in the context of our understanding of scleral biology, in order to bring a more complete understanding of current and future therapeutic interventions in myopia, and their consequences.
Visualizing phosphatidylcholine via mass spectrometry imaging: relevance to human health

ABSTRACT Introduction: Mass spectrometry imaging (MSI) techniques are nowadays widely used to obtain spatially resolved metabolite information from biological tissues. Since (phospho)lipids occur in all animal tissues and are very sensitively detectable, they are often in the focus of such studies. This particularly applies for phosphatidylcholines (PC) which are very sensitively detectable as positive ions due to the permanent positive charge of their choline headgroup. Areas covered: After a short introduction of lipid species occurring in biological systems and approaches normally used to obtain spatially resolved mass spectra (with the focus on matrix-assisted laser desorption/ionization coupled to time-of-flight (MALDI-TOF) MSI) a survey will be given which diseases have so far been characterized by changes of the PC composition. Expert commentary: Since PC species are very sensitively detectable by MS, sensitivity is not a major issue. However, spatial resolution is still limited and cellular dimensions can be hardly resolved by MALDI-TOF MSI, which is a critical point of the available approaches. Due to lacks of reproducibility and standardization further development is required.
Pleiotropic Effects of Metformin on Cancer

Metformin (MTF) is a natural compound derived from the legume Galega officinalis. It is the first line antidiabetic drug for type 2 diabetes (T2D) treatment. One of its main antidiabetic effects results from the reduction of hepatic glucose release. First scientific evidence for the anticancer effects of MTF was found in animal research, published in 2001, and some years later a retrospective observational study provided evidence that linked MTF to reduced cancer risk in T2D patients. Its pleiotropic anticancer effects were studied in numerous in vitro and in vivo studies at the molecular and cellular level. Although the majority of these studies demonstrated that MTF is associated with certain anticancer properties, clinical studies and trials provided a mixed view on its beneficial anticancer effects. This review emphasizes the pleiotropic effects of MTF and recent progress made in MTF applications in basic, preclinical, and clinical cancer research.
Control of DNA Replication Initiation by Ubiquitin

Eukaryotic cells divide by accomplishing a program of events in which the replication of the genome is a fundamental part. To ensure all cells have an accurate copy of the genome, DNA replication occurs only once per cell cycle and is controlled by numerous pathways. A key step in this process is the initiation of DNA replication in which certain regions of DNA are marked as competent to replicate. Moreover, initiation of DNA replication needs to be coordinated with other cell cycle processes. At the molecular level, initiation of DNA replication relies, among other mechanisms, upon post-translational modifications, including the conjugation and hydrolysis of ubiquitin. An example is the precise control of the levels of the DNA replication initiation protein Cdt1 and its inhibitor Geminin by ubiquitin-mediated proteasomal degradation. This control ensures that DNA replication occurs with the right timing during the cell cycle, thereby avoiding re-replication events. Here, we review the events that involve ubiquitin signalling during DNA replication initiation, and how they are linked to human disease.
Commencing Nutrient Supplements before Full Enteral Feed Volume Achievement Is Beneficial for Moderately Preterm to Late Preterm Low Birth Weight Babies: A Prospective, Observational Study

The aim of this study was to observe after following a routine change in the feeding protocol whether the earlier introduction of nutrient supplements improved nutritional outcomes in moderately preterm to late preterm low birth weight (LBW) babies. In this prospective observational study, LBW babies between 31 and 39 weeks’ gestation admitted to a Special Care Nursery were assigned to two groups (F80, n = 45, F160, n = 42) upon commencing nutrient supplement at total fluid intake achievement of 80 or 160 mL/kg/day. Outcomes included weight, protein intake, biochemical markers, feeding intolerance, and length of stay (LOS). F80 nutrient supplements commenced before F160 (2.8 vs. 6.7 days, p < 0.0001) and lasted longer (15.2 vs. 12.2 days, p < 0.03). Weight gain velocity and LOS were similar. F80 mean protein intake during the first 10 days was higher (3.38 vs. 2.74 g/kg/day, p < 0.0001). There were fewer infants with protein intake <3 g/kg/day in the F80 group (8% vs. 65%, p < 0001). F80 babies regained birthweight almost two days earlier (7.5 vs. 9.4 days, p < 0.01). Weight gain Z-scores revealed an attenuation of the trend towards lower weight percentiles in the F80 group. Feeding intolerance was decreased for F80 (24.4% vs. 47.6%, p < 0.03). There were no adverse outcomes. Earlier nutrient supplementation for LBW babies lifts mean protein intake to above 3 g/kg/day and reduces both the duration of post-birth weight loss and incidence of feeding intolerance.
Pain Deterioration Within 1 Year Predicts Future Decline of Walking Ability: A 7-Year Prospective Observational Study of Elderly Female Patients With Knee Osteoarthritis Living in a Rural District

Introduction: Knee osteoarthritis (KOA) is commonly a main cause of locomotive syndrome. Consequently, appropriate timing of intervention is clinically important. Materials and Method: Fifty female patients of a primary care clinic in a rural district fulfilled the criteria for KOA and were recruited and underwent knee medical checkups. They initially underwent physical examination bilaterally of knees by an orthopedic surgeon, radiological evaluation, and they answered the outcome of Japanese Knee Osteoarthritis Measurement (JKOM). They were asked to answer JKOM 1 and 7 years after the initial checkup. Fourteen patients were lost to follow-up due to death or moving to a nursing home. Thirty-six patients were finally included and divided into 2 age-matched groups according to walking ability at the 7-year follow-up: group A, walking ability did not decline (n = 24), and group B, walking ability did decline (n = 12). The walking ability was measured as per ordinal classification as: 5 (walking without any aid), 4 (walking with a crutch), 3 (walking using walker), 2 (walking only possible in parallel bars), and 1 (wheelchair). We completed between-group comparisons of each of the 3 subsections of the JKOM (pain, limitation in mobility related to daily activity, and restriction of participation in social life and health perception), during each period. Results: There were significant differences in JKOM pain score (12.9 vs 18.3, P = .0058) and total score (41.3 vs 55.8, P = .0093) between the groups at 1-year follow-up, even though base scores did not differ. Discussion: Clinicians should pay attention to changes in perceived knee pain and should not continue prolonged conservative therapy in patients exhibiting rapid deterioration. Conclusion: Female patients with KOA whose pain deteriorated within 1 year may require early intervention to prevent future decline in walking ability.
Family Patterns and Suicidal and Violent Behavior among Adolescent Girls—Genogram Analysis

An increase in extreme self-destructive and aggressive behaviors in adolescents has been observed in recent years. Therapeutic effectiveness seems to depend on an adequate recognition of factors that might increase the risk of extreme destructive behaviors. The aim of this study was to identify the family patterns that should draw therapeutic attention due to their importance for suicidal or violent behaviors in adolescent girls. The study involved 140 participants, aged 13–17, including 40 girls after suicide attempts, 40 girls using violence, and 60 girls without destructive behavior at all. The Genograms were used to assess the family structure, relationships between family members, and family projections. The data was analyzed by polynomial logistic regression, analysis of variance, and discriminant analysis. Emotional distance and hidden projections (related to diseases) were the most significant predictors of suicidal behaviors in the studied adolescent girls. Alcohol abuse by significant family members, especially by male family members, and a lesser role of hidden projections, were the most significant predictors of violent behaviors. Interventions designed to reduce risk of destructive behaviors among adolescents need to take account of the specific family patterns.
Teaching software product lines: a snapshot of current practices and challenges (journal-first abstract)

This extended abstract summarizes our article entitled "Teaching Software Product Lines: A Snapshot of Current Practices and Challenges" published in the ACM Transactions on Computing Education, vol. 18 in 2017 (http://doi.acm.org/10.1145/3088440). The article reports on three initiatives we have conducted with scholars, educators, industry practitioners, and students to understand the connection between software product lines and education and to derive recommendations for educators to continue improving the state of practice of teaching SPLs.
Role of polymorphonuclear neutrophils in the reperfused ischemic brain: insights from cell-type-specific immunodepletion and fluorescence microscopy studies

Polymorphonuclear neutrophil granulocytes (PMNs) are part of the early post-ischemic immune response that orchestrates the removal of infarcted brain tissue. PMNs contribute to secondary brain injury in experimental stroke models. In human patients, high PMN-to-lymphocyte ratios in peripheral blood are predictive of poor stroke outcome. Following earlier studies indicating that the cerebral microvasculature forms an efficient barrier that impedes PMN brain entry even under conditions of ischemia, more recent studies combining intravital two-photon microscopy and ex vivo immunohistochemistry unequivocally demonstrated the accumulation of PMNs in the ischemic brain parenchyma. In the meantime, transgenic mouse lines, such as mice expressing Cre-recombinase and the red fluorescent reporter protein tdTomato under the highly granulocyte-specific locus for the gene Ly6G (so-called Catchup mice), have become available that allow study of dynamic interactions of PMNs with brain parenchymal cells. These mice will further help us understand how PMNs promote brain injury and disturb brain remodeling and plasticity.
Bronchovascular injury associated with clinically significant hemoptysis after CT-guided core biopsy of the lung: Radiologic and histopathologic analysis

Objective To evaluate bronchovascular injuries as the causative occurrence for clinically significant hemoptysis after percutaneous transthoracic needle biopsy (PTNB). Materials and methods We included 111 consecutive patients who experienced hemoptysis after cone beam CT (CBCT)-guided PTNB from January 2014 through January 2017. Clinically significant hemoptysis was defined as hemoptysis causing hemodynamic instability or oxygen desaturation greater than 10% of baseline. The lesion characteristics were evaluated on CT images. The penetration of bronchovascular structures along the trajectory of the introducer needle and potential penetration at the firing of the biopsy gun were assessed on CBCT images. The cutting injury of bronchovascular structures was histopathologically assessed in biopsy specimens. The associated factors for clinically significant hemoptysis were assessed using logistic regression analyses. Results Seventeen patients (15.3%; 95%CI, 9.7%-23.2%) had clinically significant hemoptysis. On univariate analysis, the open bronchus sign (P = .004), nodule consistency (P = .012), potential penetration of a pulmonary vessel or bronchus 1 mm or larger at firing (P = .008 and P = .038, respectively), and a cutting injury of a pulmonary vessel 1 mm or larger (P = .007) or a bronchial structure (P = .041) were associated with clinically significant hemoptysis. Multivariate analysis found the following significant associated factors: potential penetration of a pulmonary vessel 1 mm or larger at firing (OR, 3.874; 95%CI, 1.072–13.997; P = .039) and cutting injury of a pulmonary vessel 1 mm or larger (OR, 6.920; 95%CI, 1.728–27.711; P = .006) or a bronchial structure (OR 4.604; 95%CI, 1.194–17.755; P = .027). Conclusion Potential penetration and cutting injury of bronchovascular structures 1mm or larger at firing were independently associated with clinically significant hemoptysis after PTNB.
An end-to-end deep learning architecture for extracting protein–protein interactions affected by genetic mutations

Abstract The BioCreative VI Track IV (mining protein interactions and mutations for precision medicine) challenge was organized in 2017 with the goal of applying biomedical text mining methods to support advancements in precision medicine approaches. As part of the challenge, a new dataset was introduced for the purpose of building a supervised relation extraction model capable of taking a test article and returning a list of interacting protein pairs identified by their Entrez Gene IDs. Specifically, such pairs represent proteins participating in a binary protein–protein interaction relation where the interaction is additionally affected by a genetic mutation—referred to as a PPIm relation. In this study, we explore an end-to-end approach for PPIm relation extraction by deploying a three-component pipeline involving deep learning-based named-entity recognition and relation classification models along with a knowledge-based approach for gene normalization. We propose several recall-focused improvements to our original challenge entry that placed second when matching on Entrez Gene ID (exact matching) and on HomoloGene ID. On exact matching, the improved system achieved new competitive test results of 37.78% micro-F1 with a precision of 38.22% and recall of 37.34% that corresponds to an improvement from the prior best system by approximately three micro-F1 points. When matching on HomoloGene IDs, we report similarly competitive test results at 46.17% micro-F1 with a precision and recall of 46.67 and 45.59%, respectively, corresponding to an improvement of more than eight micro-F1 points over the prior best result. The code for our deep learning system is made publicly available at https://github.com/bionlproc/biocppi_extraction.