Miracle-dz/UniFAR-FTUs huggingface dataset:
Lactoferrin Expression Is Not Associated with Late-Onset Sepsis in Very Preterm Infants

Background: Preterm infants are at a high risk of developing late-onset sepsis (LOS). Lactoferrin is one of the most abundant endogenous antimicrobial proteins expressed in breast milk, stools, and blood, and a candidate for preventive intervention. Large clinical trials have recently investigated whether enteral supplementation with bovine lactoferrin reduces LOS. Aim: To characterize lactoferrin levels in preterm infants with and without LOS during the first month of life. Methods: Very preterm and term infants were recruited and serial biosamples collected during the first month of life. Lactoferrin levels were determined by immunoassay in cord blood and peripheral blood on days 1, 7, 14, 21, and 28; in the stools on days 1 and 28; and in the mother’s breast milk on days 7 and 21. Furthermore, we assessed the capacity of the peripheral blood to release lactoferrin in response to an in vitro challenge with live Staphylococcus epidermidis, lipopolysaccharide, and fibroblast-stimulating lipopeptide 1. Results: Plasma lactoferrin levels were higher in cord blood and day 1 peripheral blood and declined during the first month of life. Plasma lactoferrin levels were similar in term infants and in preterm infants with (n = 32) and without LOS (n = 53). S. epidermidis-induced lactoferrin levels were lower following the sepsis episode. Conclusions: Endogenous lactoferrin expression in preterm infants does not appear to affect their risk of developing LOS. These findings are in line with the lack of benefit recently observed in large trials of enteral supplementation with bovine lactoferrin to prevent LOS.
Synchronous papillary thyroid carcinoma and breast ductal carcinoma

A 48-year-old woman was admitted to our hospital with a lump in her left breast. She was diagnosed with synchronous papillary thyroid carcinoma and breast ductal carcinoma. The patient underwent four cycles of neoadjuvant chemotherapy with epirubicin and cyclophosphamide, and one cycle of docetaxel. She then underwent left breast mastectomy and radical resection of thyroid cancer (total thyroidectomy and bilateral central group [levels VI and VII] lymph node dissection) at the same time. She was administered three cycles of chemotherapy with docetaxel and radiotherapy. The patient had no metastasis in the follow-up period. A literature search was performed to characterize the epidemiology, etiology, management, and prognosis of this condition. We speculate that hormone treatment could be a probable pathogenesis of synchronous breast and thyroid cancers.
Predation of a Mardo Antechinus flavipes leucogaster by a Southern Boobook, and Mobbing of Boobooks by Other Birds

A Southern Boobook Ninox novaeseelandiae was observed taking an adult Mardo (Yellow-footed Antechinus) Antechinus flavipes leucogaster. The Mardo is the largest vertebrate prey recorded, to date, taken by a Boobook in south-western Australia, although future analyses of diet will likely reveal that vertebrates are commonly taken. Mobbing of the Boobook by medium-sized birds also suggests that they regard it as a predator.
Plants endophytes: unveiling hidden agenda for bioprospecting toward sustainable agriculture

Abstract Endophytic microbes are present in nearly all of the plant species known to date but how they enter and flourish inside a host plant and display multiple benefits like plant growth promotion (PGP), biodegradation, and stress alleviation are still unexplored. Until now, the majority of the research has been conducted assuming that the host–endophyte interaction is analogous to the PGP microbes, although, studies related to the mechanisms of their infection, colonization as well as conferring important traits to the plants are limited. It would be fascinating to explore the role of these endophytic microbes in host gene expression, metabolism, and the modulation of phenotypic traits, under abiotic and biotic stress conditions. In this review, we critically focused on the following areas: (i) endophytic lifestyle and the mechanism of their entry into plant tissues, (ii) how endophytes modulate the immune system of plants and affect the genotypic and phenotypic expression of host plants under abiotic and biotic stress condition, and (iii) the role of omics and other integrated genomic approaches in unraveling complex host–endophyte signaling crosstalk. Furthermore, we discussed their role in phytoremediation of heavy metal stress and whole genomic analysis based on an understanding of different metabolic pathways these endophytes utilize to combat stress.
Effect of temperature and pressure on antimycobacterial activity of Curcuma caesia extract by supercritical fluid extraction method

Background: Supercritical fluid extraction (SFE) is an advanced technique using CO2as a solvent and plant-based drug exploration is a topic of growing interest. Curcuma caesia is a medicinal herb with many medicinal potential. Hence, in the present study, the effect of temperature (40°C–60°C) and pressure (10–20 MPa) on extraction yield and antimycobacterium potential of C. caesia Roxb. dry rhizome powder using supercritical fluid extraction method were evaluated. Methods: The extract of C. caesia by SFE was accomplished using temperature range (40°C–60°C) and pressure range (10–20 MPa). The chemical profile of the extracts were investigated by Gas Chromatography Mass Spectrometry (GCMS) and the antimycobacterial activity of the extracts were analyzed against Mycobacterium smegmatis strains MTCC06 and MTCC994. Compounds found in the extract were further checked by in silico analyses with two protein target 4DRE and 3UCI. Results: Extraction yield ranged from 3.0 to 5.6 g/25g dry substrate, with the highest value being achieved at 50°C and 15 MPa. The results of GCMS analyses revealed the presence of beta-elemene, curzerenone, boldenone, and 2-cyclohexen-1-one, 4-ethynyl-4-hydroxy-3, 5, 5-trimethyl in the extracts. The extract obtained at 50°C temperature and 15 MPa pressure showed the highest zone of inhibition against M. smegmatis strains MTCC06 and MTCC994, that is, 15.6 mm and 13.6 mm, respectively. Active constituents present in the extracts showed good binding energy with 4DRE and 3UCI by in silico analysis. Conclusion: This study identified the effect of temperature and pressure on yield C. caesia extract by SFE method. Furthermore, the effect of different extracts on antimycobacterial potential and docking study validated the antimycobacterial potential.
Older adults’ use of an online decision support system: Usability and stability of assistive technology recommendations

ABSTRACT Online decision support systems (DSS) may help older adults self-select assistive technology (AT) by offering recommendations. User interactions with DSSs may change the recommendations they receive. Objective: We evaluated recommendations stability and usability of an online DSS. Methods: Middle-aged and older adults (n = 43) were observed while using the DSS. The stability of DSS recommendations (ATs and advice) was compared between two time points, using a three-point scale: no, partial, or full agreement. Usability was coded, referencing ISO standards. Results: Half (51%) of participants received AT recommendations from the DSS in both sessions, with full (14%) or partial (12%) agreement. All but one participant received advice, and almost all of them had full (40%) or partial (56%) agreement between sessions. Many of the usability issues appear to be the result of the users inaccurately measuring their environment, challenges in understanding the questions being asked, and improperly making selections from the system. Discussion: Strict AT matching rules versus generic advice, and usability issues, likely reduced the matching rate and stability of AT recommendations. Conclusion: It appears that some users may require assistance with the system, and we suggest changes to the DSS format and content to improve stability and usability.
Updates on the treatment of adhesive capsulitis with hydraulic distension

Adhesive capsulitis of the shoulder joint is a common disease characterized by pain at the insertional area of the deltoid muscle and decreased range of motion. The pathophysiological process involves fibrous inflammation of the capsule and intraarticular adhesion of synovial folds leading to capsular thickening and contracture. Regarding the multidirectional limitation of motion, a limitation in external rotation is especially prominent, which is related to not only global fibrosis but also to a localized tightness of the anterior capsule. Ultrasound and magnetic resonance imaging studies can be applied to rule out other structural lesions in the diagnosis of adhesive capsulitis. Hydraulic distension of the shoulder joint capsule provides pain relief and an immediate improvement in range of motion by directly expanding the capsule along with the infusion of steroids. However, the optimal technique for hydraulic distension is still a matter of controversy, with regards to the infusion volume and rupture of the capsule. By monitoring the real-time pressure-volume profile during hydraulic distension, the largest possible fluid volume can be infused without rupturing the capsule. The improvement in clinical outcomes is shown to be greater in capsule-preserved hydraulic distension than in capsule-ruptured distension. Moreover, repeated distension is possible, which provides additional clinical improvement. Capsule-preserved hydraulic distension with maximal volume is suggested to be an efficacious treatment option for persistent adhesive capsulitis.
Predictive Value of Serum Albumin in Patients With Acute Coronary Syndrome

We read with the interest the article entitled “Prognostic Significance of Serum Albumin in Patients With Acute Coronary Syndrome” by Polat et al. In this observational, retrospective study, the investigators evaluated the prognostic value of serum albumin (SA) in patients hospitalized with acute coronary syndrome (ACS). Based on the study results, patients with SA level <3.5 g/dL were found to have a higher long-term mortality compared with those with SA level 3.5 g/dL. Serum albumin is the most abundant protein of the extracellular vascular space, and it is a negative acute phase reactant marker of inflammation. Until now, several studies have documented the prognostic value of SA in patients with stable coronary artery disease (CAD), ST elevation myocardial infarction, and pulmonary embolism. In this research, the authors also concluded that admission SA level was a strong and independent predictor of all-cause long-term mortality in patients with ACS. Although the research was interesting and well-conducted, we have some comments. In Table 1, we believe that the authors should provide more detailed information of the enrolled patients regarding history of CAD. For example, how many patients had a history of prior percutaneous coronary intervention (PCI) or aortocoronary bypass grafting (ACBG) and whether the patients with ACBG underwent redo-ACBG? In addition, we consider that patients with ACS included in the study should be categorized in regard to treatment strategy of PCI or ACBG to create more homogenous data and to exclude the possible confounding of treatment modality on SA level. Besides that, the authors presented limited data in terms of interventional findings of patients with ACS. Patients with the left anterior descending artery as the infarct-related artery usually have higher infarct area, thereby having low SA level. However, multivessel involvement in such patients might be another possible confounding factor that should be clarified in the study. Current European and North American guidelines recommend risk stratification of ACS cases using available risk scores, such as the thrombolysis in myocardial infarction (TIMI) score and the Global Registry of Acute Coronary Events (GRACE) score, to determine the in-hospital and 6-months risk of death and myocardial infarction in patients with ACS following an index event. Beside that, a recent study revealed that these scores had an adequate predictive power for long-term mortality in patients who were diagnosed and hospitalized with ACS. In the present study, the authors did not evaluate these widely accepted risk scores in their study. Therefore, we recommend to calculate these risk tools in the enrolled study participants. After that, the authors should perform some statistical analysis, such as reclassification tables, net reclassification improvement, and integrated discriminative improvement analysis, to assess an additional prognostic value of SA on TIMI or GRACE score in predicting all-cause mortality in patients with ACS.
Cdk1 negatively regulates the spindle localization of Prc1 in mouse oocytes

Chromosome segregation requires the formation of a bipolar spindle. The timely bipolarization of the acentrosomal spindle during meiosis I in mouse oocytes depends on the antiparallel microtubule crosslinker Prc1. How Prc1 is regulated in oocytes remains poorly understood. In this study, we show that the kinase Cdk1 negatively regulates the spindle localization of Prc1 in mouse oocytes. The acute inhibition of Cdk1 activity led to excessive localization of Prc1 at the spindle and kinetochores, whereas the overactivation of Cdk1 had opposite effects. The overexpression of Prc1 carrying mutations at Cdk1‐mediated phosphorylation sites increased its localization to the spindle, accelerated spindle bipolarization and caused spindle‐checkpoint‐dependent arrest at metaphase I. Overactivation of Cdk1 delayed spindle bipolarization, which was reversed by the overexpression of a phospho‐mutant form but not the wild‐type form of Prc1. These results suggest that Cdk1‐mediated phosphorylation negatively regulates Prc1 localization to ensure the timely bipolarization of the acentrosomal spindle during meiosis I in mammalian oocytes.
Neurohormonal Regulation of IKs in Heart Failure: Implications for Ventricular Arrhythmogenesis and Sudden Cardiac Death

Abstract Heart failure (HF) results in sustained alterations in neurohormonal signaling, including enhanced signaling through the sympathetic nervous system and renin‐angiotensin‐aldosterone system pathways. While enhanced sympathetic nervous system and renin‐angiotensin‐aldosterone system activity initially help compensate for the failing myocardium, sustained signaling through these pathways ultimately contributes to HF pathophysiology. HF remains a leading cause of mortality, with arrhythmogenic sudden cardiac death comprising a common mechanism of HF‐related death. The propensity for arrhythmia development in HF occurs secondary to cardiac electrical remodeling that involves pathological regulation of ventricular ion channels, including the slow component of the delayed rectifier potassium current, that contribute to action potential duration prolongation. To elucidate a mechanistic explanation for how HF‐mediated electrical remodeling predisposes to arrhythmia development, a multitude of investigations have investigated the specific regulatory effects of HF‐associated stimuli, including enhanced sympathetic nervous system and renin‐angiotensin‐aldosterone system signaling, on the slow component of the delayed rectifier potassium current. The objective of this review is to summarize the current knowledge related to the regulation of the slow component of the delayed rectifier potassium current in response to HF‐associated stimuli, including the intracellular pathways involved and the specific regulatory mechanisms.
Extracellular Vesicles Derived from Human Umbilical Cord Mesenchymal Stromal Cells Protect Cardiac Cells Against Hypoxia/Reoxygenation Injury by Inhibiting Endoplasmic Reticulum Stress via Activation of the PI3K/Akt Pathway

Endoplasmic reticulum (ER) stress is implicated in the pathogenesis of many diseases, including myocardial ischemia/reperfusion injury. We hypothesized that human umbilical cord mesenchymal stromal cells derived extracellular vesicles (HuMSC-EVs) could protect cardiac cells against hyperactive ER stress induced by hypoxia/reoxygenation (H/R) injury. The H/R model was generated using the H9c2 cultured cardiac cell line. HuMSC-EVs were extracted using a commercially available exosome isolation reagent. Levels of apoptosis-related signaling molecules and the degree of ER stress were assessed by western blot. The role of the PI3K/Akt pathway was investigated using signaling inhibitors. Lactate dehydrogenase leakage and 3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide (MTT) analysis were used for evaluating the therapeutic effects of HuMSC-EVs in vitro. The results showed that ER stress and the rate of apoptosis were increased in the context of H/R injury. Treatment with HuMSC-EVs inhibited ER stress and increased survival in H9c2 cells exposed to H/R. Mechanistically, the PI3K/Akt pathway was activated by treatment with HuMSC-EVs after H/R. Inhibition of the PI3K/Akt pathway by a specific inhibitor, LY294002, partially reduced the protective effect of HuMSC-EVs. Our findings suggest that HuMSC-EVs could alleviate ER stress–induced apoptosis during H/R via activation of the PI3K/Akt pathway.
Learning Segmentation from Object Color

We propose Color Shift GAN(CSGAN), a method that allows learning to segment an object class without the need for pixel-wise annotations. We exploit a single textual annotation of the basic object color per image to learn the semantics of an object class. By using only a textual basic color annotation of each object, we are able to drastically reduce labeling efforts. We created a dataset of 29,910 images of cars and annotated the basic color of their body works. Our model reaches 61.4 percent IoU on our test data. CSGAN trained with additional 128 pixel-wise annotations reaches 62.0 percent. By adding 45,150 unlabeled images to the training of CSGAN we are able to increase IoU to 65.0 percent without using a single pixel-wise annotation. This verifies that our weak objective is sufficient for learning segmentation.
Predicting Acute Kidney Injury after Surgery

Acute Kidney Injury (AKI) is a common complication after surgery. Recognition of patients at risk of AKI at an earlier stage is a priority for researchers and health care providers. The objective of this study is to develop machine learning prediction models of acute kidney injury (AKI) in patients who undergo surgery. The dataset used in this study consists of in-hospital patients’ data of five different cohorts coming from different major procedure types. This data was collected from the SunRiseClinical Manager (SCM) electronic medical records system that is used in the Calgary Zone, Alberta, Canada from 2008 to 2015 where the patients are >=18 years of age. Five classifiers were experimented with: support vector machine, random forest, logistic regression, k-nearest neighbors, and adaptive boosting. The area under the receiver operating characteristics curve (AUROC) ranged between 0.62-0.84 and sensitivity and specificity ranged between 0.81-0.83 and 0.43-0.85, respectively. Predictions from these models can facilitate early intervention in AKI treatment.
Simulation of Triple Gate Spin Field-Effect Transistor and its Applications to Digital Logic

The simulation of Triple Gate Spin-FET having Indium Arsenide as its channel material is performed using its mathematical model in this paper. The simulation results are validated using dc simulations. Later by setting the suitable channels and various other parameters like spin injection, spin detection etc., diverse logic functions are attained. the different inputs are given at the various gate terminals. The functions obtained are implemented using only one multi gate spin-FET. If the same functions would be implemented using conventional CMOS, the number of devices required will be much higher. The functions obtained are also proficient in terms of power and speed as paralleled to the design using VLSI CMOS. The performance of the proposed designed is compared to the already existent VLSI CMOS for the same logic functions in a table.
Anxiety and Depression Diagnosis Method Based on Brain Networks and Convolutional Neural Networks

At present, only professional doctors can use the professional scales to diagnose depression and anxiety in clinical practice. In recent years, the problems of detecting the presence of anxiety or depression using Electroencephalography (EEG) has received attention as a way to implement assistant diagnosis, and some researchers explored that there are differences in the degree of prefrontal lateralization and functional connectivity of brain networks between patients with anxiety and depression and normal people. In this paper, we proposed a new approach that combines functional connectivity of brain networks and convolutional neural networks (CNN) for EEG-based anxiety and depression recognition. EEG data are collected from subjects consisting ten healthy controls and ten patients with anxiety or depression. In this way, we achieved 67.67% classification accuracy. It points out the way to further explore the application of functional connectivity of brain networks and deep learning technology in EEG about patients with anxiety and depression.
Distributed Fog Computing Architecture for Real-Time Anomaly Detection in Smart Meter Data

The use of Fog Computing for real-time Big Data monitoring of power consumption is gaining popularity. In traditional systems, Cloud servers receive sensor Big Data, perform predictions and detect anomalies or any threat patterns and then raise the alarms. With exponentially increasing sensor data, Cloud servers are becoming impractical to process this data because of the issues of volume, velocity, variety, network bandwidth, real-time support and security issues. Fog Computing is introduced as a Distributed Computing paradigm that uses intermediate Computing infrastructure for processing to overcome the limitations of Cloud Computing. In this paper, we propose a hierarchically Distributed Fog Computing architecture to deploy machine learning based anomaly detection models for generating insights from the collected Smart meter sensor data from the household. The anomaly detection is divided into two steps: model training and anomaly detection. We perform detailed analysis and evaluation of the models using standard open datasets obtained from UCI machine learning repository. The results confirm the efficacy of our proposed architecture. We used open source framework and software for our experiments.
Modeling Thermal Death in the Mexican Fruit Fly (Diptera: Tephritidae)

A large set of mortality data for the Mexican fruit fly, Anastrepha ludens (Loew), from induced thermal stress was fit to 4 mathematical models that are used to estimatc thermal death points for quarantine level security. Two of the models, the probit and kinetic formulas, estimated death point intercepts in close agreement at the tail ends of survivorship curves. Based on the criteria of chi-square values, coefficients of determination, and confidence limits, the kinetic model had the best fit to the data. The complementary log−log model produced disparately lower death point intercepts with wider confidence limits compared with the other 3 models with the same data set.
Influence of organicseed priming on germination and seedling quality in bell pepper (Capsicum annuum L.)

An experiment was conducted to improve the germination and quality of seedling through seed priming of bell pepper cv California Wonder using 16 botanicals and animal by-products/wastes for 12 and 24 hours. Analysis of variance depicted significant differences among different treatments. The best germination and quality of seedlings were obtained through pre-sowing seed priming treatments of Melia azedarach leaf extract 10% followed by Eucalyptus leaf extract 10%, garlic clove extract 5%, cow urine 5% and cow dung extract 5% at seed soaking duration of 24 hours. Organic, non-toxic and eco-friendly natures of these treatments are added advantages.