Miracle-dz/UniFAR-FTUs huggingface dataset:
SeMPI: a genome-based secondary metabolite prediction and identification web server

Abstract The secondary metabolism of bacteria, fungi and plants yields a vast number of bioactive substances. The constantly increasing amount of published genomic data provides the opportunity for an efficient identification of gene clusters by genome mining. Conversely, for many natural products with resolved structures, the encoding gene clusters have not been identified yet. Even though genome mining tools have become significantly more efficient in the identification of biosynthetic gene clusters, structural elucidation of the actual secondary metabolite is still challenging, especially due to as yet unpredictable post-modifications. Here, we introduce SeMPI, a web server providing a prediction and identification pipeline for natural products synthesized by polyketide synthases of type I modular. In order to limit the possible structures of PKS products and to include putative tailoring reactions, a structural comparison with annotated natural products was introduced. Furthermore, a benchmark was designed based on 40 gene clusters with annotated PKS products. The web server of the pipeline (SeMPI) is freely available at: http://www.pharmaceutical-bioinformatics.de/sempi.
A 35-dBm OIP3 CMOS Constant Bandwidth PGA With Extended Input Range and Improved Common-Mode Rejection

An improved CMOS second generation current conveyor with adaptive control circuit (ACC) is proposed, and is used to build a highly linear transconductance–transimpedance programmable gain amplifier (PGA). This PGA is fabricated in a 0.18-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> CMOS technology and draws a 0.58-mA current from a supply of 1.8 V. It achieves a 0–14-dB-gain range within a roughly constant bandwidth of 30 MHz when driving a capacitor load of 2 pF. Enhanced linearity, extended input range, and improved common-mode rejection are achieved due to the employ of the proposed ACC. In addition, gain peaking is less prone to appear as the proposed ACC contributes a significant reduction in <inline-formula> <tex-math notation="LaTeX">${X}$ </tex-math></inline-formula> terminal parasitic capacitance.
Gene Expression Signatures That Predict Radiation Exposure in Mice and Humans

Background The capacity to assess environmental inputs to biological phenotypes is limited by methods that can accurately and quantitatively measure these contributions. One such example can be seen in the context of exposure to ionizing radiation. Methods and Findings We have made use of gene expression analysis of peripheral blood (PB) mononuclear cells to develop expression profiles that accurately reflect prior radiation exposure. We demonstrate that expression profiles can be developed that not only predict radiation exposure in mice but also distinguish the level of radiation exposure, ranging from 50 cGy to 1,000 cGy. Likewise, a molecular signature of radiation response developed solely from irradiated human patient samples can predict and distinguish irradiated human PB samples from nonirradiated samples with an accuracy of 90%, sensitivity of 85%, and specificity of 94%. We further demonstrate that a radiation profile developed in the mouse can correctly distinguish PB samples from irradiated and nonirradiated human patients with an accuracy of 77%, sensitivity of 82%, and specificity of 75%. Taken together, these data demonstrate that molecular profiles can be generated that are highly predictive of different levels of radiation exposure in mice and humans. Conclusions We suggest that this approach, with additional refinement, could provide a method to assess the effects of various environmental inputs into biological phenotypes as well as providing a more practical application of a rapid molecular screening test for the diagnosis of radiation exposure.
Lipid accumulation product index: a reliable marker of cardiovascular risk in polycystic ovary syndrome.

BACKGROUND Metabolic disturbances are common features of polycystic ovary syndrome (PCOS), which possibly enhance the risk of cardiovascular disease. The aim of this study was to assess the accuracy of lipid accumulation product (LAP) index as a marker of cardiovascular risk in PCOS patients. METHODS Case-control study including 51 PCOS patients aged between 14 and 35 years and 44 body mass index (BMI) and age-matched controls. Measures included the LAP index, homeostasis model assessment (HOMA) index, glucose tolerance and plasma hormones, cholesterols and triglycerides. RESULTS LAP index was positively correlated with HOMA index in all subjects (r = 0.70; P < 0.001). Waist circumference (WC) (P = 0.002), HOMA index (P < 0.001) and LAP index (P = 0.035) were higher in PCOS patients than controls. On receiver operating characteristic curve analysis, an LAP index of 34.5 (sensitivity: 84%; specificity 79%) showed a better performance than non-high-density lipoprotein cholesterol, WC or BMI to identify insulin resistance (IR) in all subjects. In PCOS patients, the positive and negative predictive values for LAP > or = 34.5 were 91 and 74%, respectively, compared with 73 and 61%, respectively, for WC > or =80 cm, and 43 and 20%, respectively, for WC > or =88 cm. CONCLUSIONS We have confirmed that IR is more common in PCOS than BMI-matched control women. Furthermore, the LAP index, an easily obtainable measure, is associated with HOMA index and an LAP > or = 34.5 is an additional risk factor for cardiovascular disease in PCOS patients.
Endonuclease VIII-like 1 (NEIL1) promotes short-term spatial memory retention and protects from ischemic stroke-induced brain dysfunction and death in mice

Recent findings suggest that neurons can efficiently repair oxidatively damaged DNA, and that both DNA damage and repair are enhanced by activation of excitatory glutamate receptors. However, in pathological conditions such as ischemic stroke, excessive DNA damage can trigger the death of neurons. Oxidative DNA damage is mainly repaired by base excision repair (BER), a process initiated by DNA glycosylases that recognize and remove damaged DNA bases. Endonuclease VIII-like 1 (NEIL1) is a DNA glycosylase that recognizes a broad range of oxidative lesions. Here, we show that mice lacking NEIL1 exhibit impaired memory retention in a water maze test, but no abnormalities in tests of motor performance, anxiety, or fear conditioning. NEIL1 deficiency results in increased brain damage and a defective functional outcome in a focal ischemia/reperfusion model of stroke. The incision capacity on a 5-hydroxyuracil–containing bubble substrate was lower in the ipsilateral side of ischemic brains and in the mitochondrial lysates of unstressed old NEIL1-deficient mice. These results indicate that NEIL1 plays an important role in learning and memory and in protection of neurons against ischemic injury.
Craniosynostosis in 10q26 deletion patients: A consequence of brain underdevelopment or altered suture biology?

Approximately a hundred patients with terminal 10q deletions have been described. They present with a wide range of clinical features always accompanied by delayed development, intellectual disability and craniofacial dysmorphisms. Here, we report a girl and a boy with craniosynostosis, developmental delay and other congenital anomalies. Karyotyping and molecular analysis including Multiplex Ligation dependent probe amplification (MLPA) and Array Comparative Genomic Hybridization (aCGH) were performed in both patients. We detected a 13.1 Mb pure deletion at 10q26.12‐q26.3 in the girl and a 10.9 Mb pure deletion at 10q26.13‐q26.3 in the boy, both encompassing about 100 genes. The clinical and molecular findings in these patients reinforce the importance of the DOCK1 smallest region of overlap I (SRO I), previously suggested to explain the clinical signs, and together with a review of the literature suggest a second 3.5 Mb region important for the phenotype (SRO II). Genotype‐phenotype correlations and literature data suggest that the craniosynostosis is not directly related to dysregulated signaling in suture development, but may be secondary to alterations in brain development instead. Further, genes at 10q26 may be involved in the molecular crosstalk between brain and cranial vault. © 2015 Wiley Periodicals, Inc.
External validity & non-probability sampling

Sir, Apropos of the article on determinants of Indian physicians satisfaction and dissatisfaction from their job published recently1, the authors deserve credit for their efforts. As the title and the conclusions suggest, the aim was to study the job satisfaction and dissatisfaction levels among Indian physicians and compare it with levels across the world. The authors conclude that “the pattern of high proportion of satisfaction of the Indian physicians reported was similar to the physicians’ satisfaction working particularly in the developed countries”. I have a few concerns here as the methodology used for the purpose of this study may score low on external validity and, therefore, making a conclusion based on non-probability (convenience sampling in this case) sampling may not be correct. This keeping in view the fact that the two institutions chosen for the purpose of this study are not actually representative of institutions across India. One of the institutions chosen is a postgraduate institute only and fully autonomous and the second institution is a central government medical college. Now compare these institutions with other medical institutions across India [private, government (State and central), undergraduate, and undergraduate and postgraduate both, autonomous and non-autonomous, rural and urban] and we can understand the limits in generalizing the findings of this study to medical colleges across India. The question that needs to be addressed here is to what extent the results of a study conducted in one setting can be generalized to other settings. As pointed above, the situation in this study is not representative of other settings. Further, this representativeness can be expressed in two ways: experimental realism and mundane realism. Experimental realism is the degree to which participants’ psychological experience of a situation is representative of the experience they would have in other situations2. As is obvious, working in the above mentioned institutions is psychologically very different from other institutions across India. Experimental realism asks: Are participants feeling time pressure, or social rejection, or conformity pressure at levels similar to others? Mundane realism is the degree to which the physical setting in a study superficially resembles other physical settings2, again questionable in this study. Though the study has been done wonderfully well in its limited settings but may not be used as a surrogate for Indian physicians.
AI^2: Training a Big Data Machine to Defend

We present AI2, an analyst-in-the-loop security system where Analyst Intuition (AI) is put together with state-of-the-art machine learning to build a complete end-to-end Artificially Intelligent solution (AI). The system presents four key features: a big data behavioral analytics platform, an outlier detection system, a mechanism to obtain feedback from security analysts, and a supervised learning module. We validate our system with a real-world data set consisting of 3.6 billion log lines and 70.2 million entities. The results show that the system is capable of learning to defend against unseen attacks. With respect to unsupervised outlier analysis, our system improves the detection rate in 2.92× and reduces false positives by more than 5×.
Text Snippets from the DomGraph

We explore the idea that the Document-Object Model tree of an HTML page | absent any semantic or heuristic interpretations of the tags and their positions | provides cues about the importance of the information it contains. This hypothesis is evaluated by constructing a DomGraph, i.e., a network of the DOM trees of pages connected by their hyperlinks, and using it in a snippet-extraction technique. In this process, we also address technical issues related to the processing of the resultant very large graph. Snippets produced by this technique are compared in a user study to those extracted by a reasonable and simple baseline method, and found to be clearly preferred by users.
Cervical human papillomavirus detection is not affected by menstrual phase

Objectives In many settings, human papillomavirus (HPV) DNA testing already plays an important role in cervical cancer screening. It is unclear whether hormonal fluctuations associated with menstrual phase or oral contraceptive (OC) use have any effect on HPV detection. We evaluated the effects of OC use and timing of cervical sampling in relation to women's last menstrual period (LMP) on HPV detection, and viral load in the Brazilian Ludwig–McGill cohort study. Methods Women in the cohort were followed every 4–6 months, and at each clinic visit they were asked to complete a questionnaire and to provide a cervical sample for HPV testing. Specimens from 6093 patient visits (n=2209 women) were categorised according to date of LMP into four distinct phases: follicular (days 5–9), midcycle (days 10–15), luteal (days 16–22), or late luteal (days 23–31). Results Compared with follicular phase (referent group), HPV detection did not differ according to reported LMP for midcycle (OR=1.14, 95% CI 0.95 to 1.37), luteal (OR=1.03, 95% CI 0.85 to 1.25), or late luteal menstrual phase (OR=1.01, 95% CI 0.83 to 1.24), and was also not influenced by OC use. Analyses restricted to high-risk HPV types (grouped) and HPVs 16 and 18 (separately), produced similar non-significant associations. For HPV-positive samples, we found that the menstrual phase did not influence the total viral load. Conclusions These results indicate HPV detection is not associated with menstrual phase. Our findings suggest that standardising the timing of specimen collection for HPV testing is not necessary.
Intrusion Detection System in Cloud Computing Environment

The Cloud computing system can be easily threatened by various attacks, because most of the cloud computing systems provide service to so many people who are not proven to be trustworthy. Due to their distributed nature, cloud computing environment are easy targets for intruders[1]. There are various Intrusion Detection Systems having various specifications to each. Cloud computing have two approaches i.e. Knowledge-based IDS and Behavior-Based IDS to detect intrusions in cloud computing. Behavior-Based IDS assumes that an intrusion can be detected by observing a deviation from normal to expected behavior of the system or user[2]s. Knowledgebased IDS techniques apply knowledge accumulated about specific attack . Knowledge-based IDS can’t detect unknown attacks, but it uses rules and monitors a stream of event s to find malicious characteristics and set the new rules for unknown attacks. In this paper we proposed a system is to detect intrusions in the cloud computing using Behavior-based approach and knowledge-based approach. If first approach unable to detect the data, second approach again verifies the data and compare it with the signatures within the database. In the proposed system definitely we will have very low false positive alarm.
Meaning and the Mental Lexicon

This paper presents a network model of the mental lexicon and its formation. Models of word meaning typically postulate a network of nodes with connection strengths, or distances, that reflect semantic similarity, but seldom explain how the network is formed or how it could be represented in the brain. The model presented here is an attempt to address these questions. The network organizes semantically similar words into clusters when exposed to sequentially presented text. Lexical co-occurrence information is calculated and used to create a hierarchical semantic representation. The output is similar to semantic networks first described by [Collins and Loftus, 1975], but is created automatically.
Association Between Opioid Abuse/Dependence and Outcomes in Hospitalized Heart Failure Patients

Opioid use is associated with unintentional and intentional overdose and is one of the leading causes of emergency room visits and accidental deaths. However, the association between opioid abuse/dependence and outcomes in hospitalized patients has not been well studied. Congestive heart failure (HF) is the fourth most common cause of hospitalization in the United States. The purpose of this study was to examine the effect of opioid abuse/dependence on outcomes in patients hospitalized with HF. We queried the 2002–2010 Nationwide Inpatient Sample databases to identify all patients aged 18 years and older admitted with the primary diagnosis of HF. Multivariate logistic regression analysis was used to compare the frequency of hospital-acquired conditions (HACs) and in-hospital mortality between patients with and without a history of opioid abuse/dependence. Of 9,993,240 patients with HF, 29,014 had a history of opioid abuse or dependence. Opioid abusers/dependents were likely to be younger men of poor socioeconomic background with self pay or Medicaid as their primary payer. They had a lower prevalence of dyslipidemia, diabetes mellitus, coronary artery disease, prior myocardial infarction, and peripheral vascular disease (P < 0.001 for all). They were more likely to be smokers and have chronic pulmonary disease, depression, liver disease, and obesity (P < 0.001 for all). Patients with a history of opioid abuse/dependence had lower incidence of HACs (14.8% vs. 16.5%, adjusted odds ratio: 0.71, P < 0.001) and lower in-hospital mortality (1.3% vs. 3.6%, adjusted odds ratio: 0.64, P < 0.001) as compared with patients without prior opioid abuse/dependence. In conclusion, among adult patients aged 18 years and older hospitalized with HF, opioid abuse/dependence was associated with lower frequency of HACs and lower in-hospital mortality.
True Cramer-Rao bound for timing recovery from a bandlimited linearly Modulated waveform with unknown carrier phase and frequency

This paper derives the Cramer-Rao bound (CRB) related to the estimation of the time delay of a linearly modulated bandpass signal with unknown carrier phase and frequency. We consider the following two scenarios: joint estimation of the time delay, the carrier phase, and the carrier frequency; and joint estimation of the time delay and the carrier frequency irrespective of the carrier phase. The transmit pulse is a bandlimited square-root Nyquist pulse. For each scenario, the transmitted symbols constitute either an a priori known training sequence or an unknown random data sequence. In spite of the presence of random data symbols and/or a random carrier phase, we obtain a relatively simple expression of the CRB, from which the effect of the constellation and the transmit pulse are easily derived. We show that the penalty resulting from estimating the time delay irrespective of the carrier phase decreases with increasing observation interval. However, the penalty, caused by not knowing the data symbols a priori, cannot be reduced by increasing the observation interval. Comparison of the true CRB to existing symbol synchronizer performance reveals that decision-directed timing recovery is close to optimum for moderate-to-large signal-to-noise ratios.
Biofidelic Piezoresistive Sandwich Composites

Nengda Jiang MSAE, Embry-Riddle Aeronautical University, August 2018. Biofidelic Piezoresistive Sandwich Composites. Silicone based biofidelic surrogates are being used in many biomedical applications; e.g. to understand the body injury mechanisms, evaluate protective equipment like helmets and armors. Apart from matching the mechanical behavior of bodily tissues, there is an increasing requirement for these materials to be electrically conductive and piezoresistive to facilitate direct instrumentation. Carbon nanotubes (CNTs) are a possible filler to impart electrical conductivity and piezoresistivity to silicone biofidelic materials. A sandwich structure of silicone and CNT sheet, comprising two dielectric facesheets and a highly conductive core layer has added advantages of raising the dielectric permittivity and suppressing dielectric loss. In this thesis, a fabrication methodology was developed for a proprietary blend of two-part silicone/CNT sheet sandwich composite with biofidelic mechanical properties corresponding to that of white matter of human brain tissue. The mechanical and electromechanical behavior of these sandwich composites was characterized using resistivity measurements, tensile tests and dynamic mechanical analysis (DMA). The composition of the two-part silicone in this composite was varied to obtain electrical conductivity and piezoresistivity while retaining the mechanical properties of the white matter. Interestingly, the mechanical and electromechanical performance of the composite varied between first loading and subsequent loadings during the testing. The effect of a second filler addition: graphite platelets (GP) on the properties of silicone nanocomposite
Differential Response of Myeloid-Derived Suppressor Cells to the Nonsteroidal Anti-Inflammatory Agent Indomethacin in Tumor-Associated and Tumor-Free Microenvironments

Myeloid-derived suppressor cells (MDSCs) are key regulatory cells that control inflammation and promote tumor-immune escape. To date, no specific immunomodulatory drug has proven efficacy in targeting the expansion and/or function of these cells in different pathophysiologic settings. In this study, we identified a context-dependent effect of the nonsteroidal anti-inflammatory drug indomethacin (IND) on MDSCs, depending on whether they were derived from tumor microenvironments (TME) or from tumor-free microenvironments (TFME). Treatment of mice bearing the LP07 lung adenocarcinoma with IND inhibited the suppressive activity of splenic MDSCs, which restrained tumor growth through mechanisms involving CD8+ T cells. The same effect was observed when MDSCs were treated with IND and conditioned media from LP07 tumor cells in vitro. However, in the absence of a tumor context, IND enhanced the intrinsic suppressive function of MDSCs and amplified their protumoral activity. In a model of autoimmune neuroinflammation, IND-treated MDSCs differentiated in TFME attenuated inflammation, whereas IND-treated MDSCs differentiated in TME aggravated clinical symptoms and delayed resolution of the disease. Mechanistically, IND reduced arginase activity as well as NO and reactive oxygen species production in MDSCs differentiated in TME but not in TFME. Moreover, expression of the C/EBP-β transcription factor isoforms correlated with the suppressive activity of IND-treated MDSCs. Our study unveils the dual and context-dependent action of IND, a drug that serves both as an anti-inflammatory and anticancer agent, which differentially affects MDSC activity whether these cells are derived from TME or TFME. These results have broad clinical implication in cancer, chronic inflammation and autoimmunity.