Miracle-dz/UniFAR-FTUs huggingface dataset:
New tools for high‐throughput expression of fungal secretory proteins in Saccharomyces cerevisiae and Pichia pastoris

Heterologous protein expression in yeast, mostly in Saccharomyces cerevisiae and Pichia pastoris, is a well‐established and widely used technique. It typically requires the construction of an expression vector in Escherichia coli containing the foreign gene and its subsequent transformation into yeast. Although simple, this procedure has important limitations for the expression of large numbers of proteins, that is, for the generation of protein libraries. We describe here the development of a novel system for the easy and fast expression of heterologous proteins both in S. cerevisiae and in P. pastoris, under the control of the GAL1 and AOX1 promoters respectively. Expression in S. cerevisiae requires only the transformation of yeast cells with an unpurified PCR product carrying the gene to be expressed, and the expression of the same gene in P. pastoris requires only the isolation of the plasmid generated in S. cerevisiae and its transformation into this second yeast, thus making this system suitable for high‐throughput projects. The system has been tested by the extracellular expression of 30 secretory fungal proteins.
Phase 1 Safety and Pharmacokinetics Study of MK-2048/Vicriviroc (MK-4176)/MK-2048A Intravaginal Rings

BACKGROUND Vaginal rings (VR) containing antiretroviral (ARV) drugs can be utilized for prevention of human immunodeficiency virus (HIV) with potential for improved adherence compared to daily pills. Combination ARV VRs could improve efficacy. METHODS MTN-027, a single-blind, randomized, placebo-controlled trial in 48 women, evaluated VRs containing MK-2048 (30 mg) and vicriviroc (VCV, 182 mg), alone or in combination, and placebo used continuously for 28 days. Safety was assessed by recording adverse events. Drug concentrations were quantified in plasma, vaginal fluid, cervical tissue, and rectal fluid. Cervical tissue was utilized for ex vivo HIV inhibition analysis. RESULTS There was no difference in related genitourinary adverse events between treatment arms compared to placebo. VCV and MK-2048 released from single or combination VRs both achieved peak concentrations in vaginal fluids, which were substantially higher compared to plasma (200× for VCV, 30× for MK-2048) and rectal fluid. In an ex vivo challenge assay, the antiviral activity of VCV and/or MK-2048 was not correlated with tissue-associated drug concentrations. Most women (77%) were fully adherent to 28 days of continuous VR use and found the VR acceptable. CONCLUSIONS VCV and/or MK-2048 containing VRs were safe and acceptable. Both VCV and MK-2048 were quantifiable in all matrixes tested with peak compartmental drug concentrations similar for single and combination drug VRs. Tissue-associated VCV and/or MK-2048 did not correlate with inhibition of HIV infection. These data highlight the need to assess adequacy of drug dosing in the VR and measuring genital tissue drug concentrations to develop more precise concentration-response relationships.
Reinforcement Learning Meets Hybrid Zero Dynamics: A Case Study for RABBIT

The design of feedback controllers for bipedal robots is challenging due to the hybrid nature of its dynamics and the complexity imposed by high-dimensional bipedal models. In this paper, we present a novel approach for the design of feedback controllers using Reinforcement Learning (RL) and Hybrid Zero Dynamics (HZD). Existing RL approaches for bipedal walking are inefficient as they do not consider the underlying physics, often requires substantial training, and the resulting controller may not be applicable to real robots. HZD is a powerful tool for bipedal control with local stability guarantees of the walking limit cycles. In this paper, we propose a non traditional RL structure that embeds the HZD framework into the policy learning. More specifically, we propose to use RL to find a control policy that maps from the robot’s reduced order states to a set of parameters that define the desired trajectories for the robot’s joints through the virtual constraints. Then, these trajectories are tracked using an adaptive PD controller. The method results in a stable and robust control policy that is able to track variable speed within a continuous interval. Robustness of the policy is evaluated by applying external forces to the torso of the robot. The proposed RL framework is implemented and demonstrated in OpenAI Gym with the MuJoCo physics engine based on the well-known RABBIT robot model.
Detecting Truthful and Useful Consumer Reviews for Products using Opinion Mining

Individuals and organizations rely heavily on social media these days for consumer reviews in their decision-making on purchases. However, for personal gains such as profit or fame, people post fake reviews to promote or de-mote certain target products as well as to deceive the reader. To get genuine user experiences and opinions, there is a need to detect such spam or fake reviews. This paper presents a study that aims to detect truthful, useful reviews and ranks them. An effective supervised learning technique is proposed to detect truthful and useful reviews and rank them, using a ‘deceptive’ classifier, ‘useful’ classifier, and a ‘ranking’ model respectively. Deceptive and non-useful consumer reviews from online review communities such as amazon.com and Epinions.com are used. The proposed method first uses the ‘deceptive’ classifier to find truthful reviews followed by the ‘useful’ classifier to find whether a review is useful or not. Manually labeling individual reviews is very difficult and time consuming. We incorporate a dictionary that makes it easy to label reviews. We present the experimental results of our proposed approach us-ing our dictionary with ‘deceptive’ classifier and ‘useful’ classifier.
Mount St. Helens Retrospective: Lessons Learned Since 1980 and Remaining Challenges

Since awakening from a 123-year repose in 1980, Mount St. Helens has provided an opportunity to study changes in crustal magma storage at an active arc volcano—a process of fundamental importance to eruption forecasting and hazards mitigation. There has been considerable progress, but important questions remain unanswered. Was the 1980 eruption triggered by an injection of magma into an upper crustal reservoir? If so, when? How did magma rise into the edifice without producing detectable seismicity deeper than 2.5 km or measurable surface deformation beyond the volcano’s north flank? Would precursory activity have been recognized earlier if current monitoring techniques had been available? Despite substantial improvements in monitoring capability, similar questions remain after the dome-forming eruption of 2004–8. Did additional magma accumulate in the reservoir between the end of the 1980–86 eruption and the start of the 2004–8 eruption? If so, when? What is the significance of a relative lull in seismicity and surface deformation for several years prior to the 2004–8 eruption onset? How did magma reach the surface without producing seismicity deeper than 2 km or measurable deformation more than a few hundred meters from the vent? Has the reservoir been replenished since the eruption ended, and is it now primed for the next eruption? What additional precursors, if any, should be expected? This paper addresses these questions, explores possible answers, and identifies unresolved issues in need of additional study. The 1980–86 and 2004–8 eruptions could have resulted from “second boiling” during crystallization of magma long-resident in an upper crustal reservoir, rather than from injection of fresh magma from below. If reservoir pressurization and magma ascent were slow enough, resulting strain might have been accommodated by viscoelastic deformation, without appreciable seismicity or surface deformation, until rising magma entered a brittle regime within 2–2.5 km of the surface. Given the remarkably gas-poor nature of the 2004–8 dome lava, future eruptive activity might require a relatively long period of quiescence and reservoir pressurization or a large injection of fresh magma—an event that arguably has not occurred since the Kalama eruptive period (C.E. 1479–1720).
MUC16 mutations improve patients’ prognosis by enhancing the infiltration and antitumor immunity of cytotoxic T lymphocytes in the endometrial cancer microenvironment

ABSTRACT The incidence and mortality rates of endometrial cancer are increasing during recent years. CA125 (gene symbol MUC16) is a well-known diagnostic and prognostic serum marker of endometrial cancer. High serum CA125 level is associated with poor prognosis. MUC16 is one of the most frequently mutated genes in endometrial cancer. However, the potential relationship and underlying mechanism between MUC16 mutations and endometrial cancer patients’ prognosis and disease progression remain unclear. In present study, we analyzed the whole exome sequencing data, RNA sequencing data and patients’ clinical information in TCGA database and demonstrated that MUC16 mutational status was an independent prognostic factor for endometrial cancer patients. Patients with somatic MUC16 mutations had a prolonged overall survival time. MUC16 mutations promoted patients’ antitumor immune responses. Cytotoxic immune cells mediated pathways were enriched in endometrial cancer samples with MUC16 mutations. Elevation of two pathways, NO2-dependent IL 12 pathway in NK cells and T cytotoxic cell surface molecules, significantly correlated with a higher rate of MUC16 mutations and a significantly favorable patients’ prognosis. An increased level of cytotoxic T lymphocytes, not NK cells, infiltration was observed in the tumor microenvironment of patients with MUC16 mutations. High expression of molecular markers of T cells and CD8+ T cells associated with a higher rate of MUC16 mutations and a better patients’ prognosis. These findings may provide deeper insight into potential endometrial cancer immunotherapy approaches.
Neutrophils instruct homeostatic and pathological states in naive tissues

Immune protection relies on the capacity of neutrophils to infiltrate challenged tissues. Naive tissues, in contrast, are believed to remain free of these cells and protected from their toxic cargo. Here, we show that neutrophils are endowed with the capacity to infiltrate multiple tissues in the steady-state, a process that follows tissue-specific dynamics. By focusing in two particular tissues, the intestine and the lungs, we find that neutrophils infiltrating the intestine are engulfed by resident macrophages, resulting in repression of Il23 transcription, reduced G-CSF in plasma, and reinforced activity of distant bone marrow niches. In contrast, diurnal accumulation of neutrophils within the pulmonary vasculature influenced circadian transcription in the lungs. Neutrophil-influenced transcripts in this organ were associated with carcinogenesis and migration. Consistently, we found that neutrophils dictated the diurnal patterns of lung invasion by melanoma cells. Homeostatic infiltration of tissues unveils a facet of neutrophil biology that supports organ function, but can also instigate pathological states.
Associations Between Manual Dexterity and Language Ability in School-Age Children.

Purpose We aimed to determine whether individual differences in manual dexterity are associated with specific language skills (nonword repetition, receptive vocabulary, and receptive grammar) after controlling for nonverbal abilities (visual-spatial working memory and intelligence). Method We assessed manual dexterity using the pegboard task and examined relationships with verbal and nonverbal abilities in a diverse community sample of children (N = 63, mean age = 8;2 [year;months], range: 6;0-10;8) varying in language ability (Comprehensive Evaluation of Language Fundamentals-Fourth Edition core language score M = 105, range: 62-126; Semel, Wiig, & Secord, 2003). Results Correlational analyses indicated significant relationships between manual dexterity and performance on tests of nonword repetition, receptive vocabulary, receptive grammar, and nonverbal intelligence, after controlling for multiple comparisons. In regression analyses, manual dexterity remained a significant predictor of nonword repetition after controlling for nonverbal abilities and age. In contrast, manual dexterity was no longer significant in predicting receptive vocabulary or grammar when nonverbal intelligence was included as a factor in the model. Conclusions These findings build on prior work implicating poor fine motor control in child language disorders by identifying a robust relationship between manual dexterity and nonword repetition. Relationships between manual dexterity and receptive language abilities appear to be indirect and mediated by nonword repetition. For clinicians, the results underscore the importance of screening children with poor fine motor control for concomitant language impairments.
The Importance of Statistical Power Calculations

When planning research, collecting data, or interpreting an analysis, a crucial research design consideration is the size of the study sample. Typically, all of the individuals in a certain population of interest cannot be evaluated, so a researcher must rely on examining a sample of individuals to make inferences about the population they represent. For example, to understand the benefit of a new drug to prevent migraine, a researcher cannot possibly give the drug or a placebo to all individuals in the world who have migraine. Instead, the researcher will evaluate a sample of individuals with migraine and give the drug or placebo to everyone in this sample. Still, how large does this sample need to be before we can claim to know something about how it works in the population? The answer to this question can be found in statistical power calculations. Statistical power calculations are an integral aspect of determining the size of a sample in evaluating research using null hypothesis testing. As outlined below, when designing a study, an effect size is postulated to exist (eg, a 20% group difference in treatment response), and a study is designed to examine this effect size in relation to a null hypothesis that usually depicts the absence of an effect (eg, a 0% treatment response). Using this effect size and several other analytical assumptions, investigators can calculate a sample size that will allow them to have a good chance of finding statistically significant differences in their sample, even with sampling error that is always encountered when a sample is drawn from a population. For example, the investigators think that their new drug will have a 20% group difference in the population, but due to sampling error, any individual sample drawn from that population likely will exhibit subtle differences from this expected rate. A statistical power calculation takes this into consideration to inform a researcher on the needed sample size to obtain a suitable chance of detecting a hypothesized effect size.
Daratumumab induces CD38 internalization and impairs myeloma cell adhesion

ABSTRACT Daratumumab (Dara), a human immunoglobulin G1 kappa (IgG1κ) monoclonal anti-CD38 antibody, has been approved by the U.S. Food and Drug Administration for the treatment of relapsed multiple myeloma (MM) as a single agent as well as in combination with immunomodulatory drugs (IMiDs) and proteasome inhibitors (PI). Although the scientific rationale behind the use of Dara in combination with IMiDs has been extensively explored, the molecular mechanisms underlying Dara-PI regimens have not yet been investigated. Here, we demonstrate that CD38 on the surface of MM cells is rapidly internalized after Dara treatment; we also show that Dara treatment impairs MM cell adhesion, an effect that can be rescued by using the endocytosis inhibitor Dynasore. Finally, we show that Dara potentiates bortezomib (BTZ) killing of MM cells in vitro and in vivo, independent of its function as an immune activator. In conclusion, our data show that Dara impairs MM cell adhesion, which results in an increased sensitivity of MM to proteasome inhibition.
Faster R-CNN for Robust Pedestrian Detection Using Semantic Segmentation Network

Convolutional neural networks (CNN) have enabled significant improvements in pedestrian detection owing to the strong representation ability of the CNN features. However, it is generally difficult to reduce false positives on hard negative samples such as tree leaves, traffic lights, poles, etc. Some of these hard negatives can be removed by making use of high level semantic vision cues. In this paper, we propose a region-based CNN method which makes use of semantic cues for better pedestrian detection. Our method extends the Faster R-CNN detection framework by adding a branch of network for semantic image segmentation. The semantic network aims to compute complementary higher level semantic features to be integrated with the convolutional features. We make use of multi-resolution feature maps extracted from different network layers in order to ensure good detection accuracy for pedestrians at different scales. Boosted forest is used for training the integrated features in a cascaded manner for hard negatives mining. Experiments on the Caltech pedestrian dataset show improvements on detection accuracy with the semantic network. With the deep VGG16 model, our pedestrian detection method achieves robust detection performance on the Caltech dataset.
Effects of consecutive monoculture of sweet potato on soil bacterial community as determined by pyrosequencing

Soil bacteria play key roles in determining soil health and plant growth. In this study, four sweet potato fields that had been consecutively monocultured for 1, 2, 3, and 4 years were used to investigate the effect of monoculture on soil physicochemical properties and soil bacterial communities. The results revealed that continuous cropping led to a significant decline in soil pH, soil organic carbon, and soil bacterial abundance. Miseq pyrosequencing analysis of 16S rRNA genes revealed that Proteobacteria and Bacteroidetes were the main phyla in the sweet potato monoculture soils, comprising up to 66.24% of the total sequences. The relative abundances of beneficial bacteria, including Actinobacteria, Gemmatimonadetes, Firmicutes, Xanthomonadaceae, Rhodospirillaceae, and Syntrophobacteraceae, as well as their subgroups at the genus and operational taxonomic unit (OTU) levels, decreased considerably as the number of continuous cropping years increased. In contrast, the number of potentially pathogenic bacteria, such as Acidobacteria, Sphingomonadaceae, and Pedobacter accumulated with increasing years. The results also showed the alterations to the bacterial community in the sweet potato monoculture soils were mainly driven by soil pH and soil organic matter. Overall, the decline in soil quality after successive sweet potato monoculture can be attributed to the imbalance in soil properties and soil microbes, including the decrease in soil pH and soil organic carbon, and the enrichment of pathogenic bacteria at the expense of plant‐beneficial bacteria.
Effects of health‐related quality of life on health service utilisation in patients with colorectal neoplasms

This study was to assess the impact of HRQOL on health service utilisation using four different count data models. The HRQOL was measured using the Short-Form Six-Dimension instrument and the functional assessment of cancer therapy-colorectal whereas health service utilisation was measured by the number of monthly clinical consultations and the number of monthly hospitalisation. Different count data models (Poisson's regression, negative binomial regression, zero-inflated Poisson's regression and zero-inflated negative binomial regression) were used to assess the association between HRQOL and health service utilisation. A performance comparison was made between the models. Goodness-of-fit statistics (the Pearson's chi-squared test statistic, the Akaike and Bayesian information criteria) were used to determine the best-fitting model. The negative binomial model performed the best in assessing the association between HRQOL measures and health service utilisation in patients with colorectal neoplasm and thus recommended. Physical well-being of patients was negatively and significantly associated with the monthly rate of health service utilisation after controlling for patient demographics. Both physical and function well-beings of patients were negatively and significantly associated with the number of monthly hospitalisations. If the data for the condition-specific FACT-C are not available, SF-6D showed a very strong negative relationship with health service utilisation. Such models can be used to guide the allocation of clinical resources and funding for the care of colorectal cancer patients.
Morphological and Molecular Identification of Phlebotomus mascittii Grassi, 1908 Populations from Slovenia

Abstract The Transphlebotomus subgenus has been drawing attention in last decade due to the uncertain vector capacity and cryptic life history of the group. During a 2015 entomological survey, Phlebotomine flies were collected in western locations of Slovenia, with a total of 22 specimens of the Transphlebotomus subgenus collected. In addition to morphological identifications, we confirmed the presence of Phlebotomus mascittii Grassi, 1908 (Diptera: Psychodidae) by nucleotide sequences of the mitochondrial cytochrome b gene. During the study, we found that P. mascittii is most abundant in the area of coastal–karst region of Slovenia, while in rare occasions can also be collected in Northeastern part of the country, near the Austrian border. Vector competence of P. mascitii, like all other member species of the Transphlebotomus subgenus, is unclear, but potential to transmit Leishmania (Kinetoplastida: Trypanosomatidae) pathogens or phleboviruses is strongly suspected.
Leveraging Cognitive Computing for Gender and Emotion Detection

In this paper we present a tool that performs two tasks: given an input image, ﬁrst, (i) it detects whether the image corresponds to a male or female person and then (ii), it further recognizes which emotion the face expression of the detected person is conveying. We mapped the two tasks as multi-label classiﬁcations. The ﬁrst one aims at identifying if the input image contains one of the following four categories: one male person, one female person, a group of both male and female persons or if the image does not contain any person. The second task is triggered whether the image has been recognized to belong to one of the ﬁrst two classes and aims at detecting whether that image is conveying one among six diﬀerent emotions: sadness, anger, surprise, happiness, disgust, fear. For both the problems, Microsoft Cognitive Services have been leveraged to extract tags from the input image. Tags are text elements that have been adopted to form the vectorial space model, using the bag of words model, that has been fed to the machine learning clas-siﬁers for the prediction tasks. For both tasks, we manually annotated 3000 images, which have been extracted from students who agreed using our system and providing their Facebook pictures for our analysis. Our evaluation uses Naive Bayes and Random Forest classiﬁers and with a 10-fold cross-validation reached satisfactory accuracies both for the two tasks and for the combination of them. Finally, our system works on-line and has been integrated with social media. In that way, any visitors logged in to Facebook through its APIs, is allowed to quickly classify any of their photos.