Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of trombiculid mites (Acari: Trombiculidae) on rodents from Chiloé Island and molecular evidence of infection with Orientia species

Background Scrub typhus is an emerging vector-borne zoonosis, caused by Orientia spp. and transmitted by larvae of trombiculid mites, called chiggers. It mainly occurs within a region of the Asia-Pacific called the tsutsugamushi triangle, where rodents are known as the most relevant hosts for the trombiculid vector. However, the reservoir(s) and vector(s) of the scrub typhus outside Asia-Pacific are unknown. The disease has recently been discovered on and is considered endemic for Chiloé Island in southern Chile. The aim of the present work was to detect and determine the prevalence of chiggers on different rodent species captured in probable sites for the transmission of orientiae responsible for scrub typhus on Chiloé Island in southern Chile and to molecularly examine collected chiggers for the presence of Orientia DNA. Methodology/Principal findings During the austral summer 2018, rodents were live-trapped in six sites and examined for chigger infestation. All study sites were rural areas on Chiloé Island, previously identified as probable localities where human cases acquired the scrub typhus. During a total of 4,713 trap-nights, 244 rodents of seven species were captured: the most abundant was Abrothrix olivacea. Chiggers were detected on all seven rodent species with a 55% prevalence rate. Chiggers showed low host specificity and varied according to site specific host abundance. Three genera of trombiculids were identified. Herpetacarus was the most abundant genus (93%), prevalent in five of the six sites. Infestation rates showed site specific differences, which were statistically significant using a GLM model with binomial errors. Molecular analyses proved that 21 of 133 (15.8%) mite pools were positive for Orientia species, all of them belonged to the genus Herpetacarus. Conclusions/Significance This study firstly reports the presence of different rodent-associated chigger mites positive for Orientia sp. , in a region endemic for scrub typhus in southern Chile. Herpetacarus and two other genera of mites were found with high infestation rates of rodents in sites previously identified as probable exposure of scrub typhus cases. A substantial percentage of mite pools were positive for Orientia DNA, suggesting that chigger mites serve as vectors and reservoirs of this emerging zoonosis in South America.
Progression of Meiosis Is Coordinated by the Level and Location of MAPK Activation Via OGR-2 in Caenorhabditis elegans

During meiosis, a series of evolutionarily conserved events allow for reductional chromosome division, which is required for sexual reproduction. Although individual meiotic processes have been extensively studied, we currently know far less about how meiosis is regulated and coordinated. In the Caenorhabditis elegans gonad, mitogen-activated protein kinase (MAPK) signaling drives oogenesis while undergoing spatial activation and deactivation waves. However, it is currently unclear how MAPK activation is governed and how it facilitates the progression of oogenesis. Here, we show that the oocyte and germline-related 2 (ogr-2) gene affects proper progression of oogenesis. Complete deletion of ogr-2 results in delayed meiotic entry and late spatial onset of double-strand break repair. Elevated levels of apoptosis are observed in this mutant, independent of the meiotic canonical checkpoints; however, they are dependent on the MAPK terminal member MPK-1/ERK. MPK-1 activation is elevated in diplotene in ogr-2 mutants and its aberrant spatial activation correlates with stages where meiotic progression defects are evident. Deletion of ogr-2 significantly reduces the expression of lip-1, a phosphatase reported to repress MPK-1, which is consistent with OGR-2 localization at chromatin in germ cells. We suggest that OGR-2 modulates the expression of lip-1 to promote the timely progression of meiosis through MPK-1 spatial deactivation.
Tailoring Photoluminescence from Si-Based Nanocrystals Prepared by Pulsed Laser Ablation in He-N2 Gas Mixtures

Using methods of pulsed laser ablation from a silicon target in helium (He)-nitrogen (N2) gas mixtures maintained at reduced pressures (0.5–5 Torr), we fabricated substrate-supported silicon (Si) nanocrystal-based films exhibiting a strong photoluminescence (PL) emission, which depended on the He/N2 ratio. We show that, in the case of ablation in pure He gas, Si nanocrystals exhibit PL bands centered in the “red - near infrared” (maximum at 760 nm) and “green” (centered at 550 nm) spectral regions, which can be attributed to quantum-confined excitonic states in small Si nanocrystals and to local electronic states in amorphous silicon suboxide (a-SiOx) coating, respectively, while the addition of N2 leads to the generation of an intense “green-yellow” PL band centered at 580 nm. The origin of the latter band is attributed to a radiative recombination in amorphous oxynitride (a-SiNxOy) coating of Si nanocrystals. PL transients of Si nanocrystals with SiOx and a-SiNxOy coatings demonstrate nonexponential decays in the micro- and submicrosecond time scales with rates depending on nitrogen content in the mixture. After milling by ultrasound and dispersing in water, Si nanocrystals can be used as efficient non-toxic markers for bioimaging, while the observed spectral tailoring effect makes possible an adjustment of the PL emission of such markers to a concrete bioimaging task.
To Tune or Not to Tune? Adapting Pretrained Representations to Diverse Tasks

While most previous work has focused on different pretraining objectives and architectures for transfer learning, we ask how to best adapt the pretrained model to a given target task. We focus on the two most common forms of adaptation, feature extraction (where the pretrained weights are frozen), and directly fine-tuning the pretrained model. Our empirical results across diverse NLP tasks with two state-of-the-art models show that the relative performance of fine-tuning vs. feature extraction depends on the similarity of the pretraining and target tasks. We explore possible explanations for this finding and provide a set of adaptation guidelines for the NLP practitioner.
On the Performance of Time Domain Displacement Estimators for Magnetomotive Ultrasound Imaging

In magnetomotive (MM) ultrasound (US) imaging, magnetic nanoparticles (NPs) are excited by an external magnetic field and the tracked motion of the surrounding tissue serves as a surrogate parameter for the NP concentration. MMUS procedures exhibit weak displacement contrasts due to small forces on the NPs. Consequently, precise US-based displacement estimation is crucial in terms of a sufficiently high contrast-to-noise ratio (CNR) in MMUS imaging. Conventional MMUS detection of the NPs is based on samplewise evaluation of the phase of the in-phase and quadrature (IQ) data, where a low signal-to-noise ratio (SNR) in the data leads to strong phase noise and, thus, to an increased variance of the displacement estimate. This paper examines the performance of two time-domain displacement estimators (DEs) for MMUS imaging, which differ from conventional MMUS techniques by incorporating data from an axial segment. The normalized cross correlation (NCC) estimator and a recursive Bayesian estimator, incorporating spatial information from neighboring segments, weighted by the local SNR, are adapted for the small MMUS displacement magnitudes. Numerical simulations of MM-induced, time-harmonic bulk and Gaussian-shaped displacement profiles show that the two time-domain estimators yield a reduced estimation error compared to the phase-shift-based estimator. Phantom experiments, using our recently proposed magnetic excitation setup, show a 1.9-fold and 3.4-fold increase of the CNR in the MMUS images for the NCC and Bayes estimator compared to the conventional method, while the amount of required data is reduced by a factor of 100.
Risk of cancer in infertile women: analysis of US claims data.

STUDY QUESTION Is female infertility associated with higher risk of cancer? SUMMARY ANSWER Although absolute risks are low, infertility is associated with higher risk of cancer compared to a group of non-infertile women. WHAT IS KNOWN ALREADY Infertile women are at higher risk of hormone-sensitive cancers. Information on risk of non-gynecologic cancers is rare and conflicting, and the effect of pregnancy on these risk associations is known for only a minority of cancer types. STUDY DESIGN, SIZE, DURATION Retrospective cohort analysis between 2003 and 2016 using an insurance claims database. PARTICIPANTS/MATERIALS, SETTING, METHODS In all, 64 345 infertile women identified by infertility diagnosis, testing or treatment were compared to 3 128 345 non-infertile patients seeking routine gynecologic care. Women with prior diagnosis of cancer or within 6 months of index event were excluded. Main outcomes were development of any malignancy and individual cancers as identified by ICD-9/ICD-10 codes. Results were adjusted for age at index date, index year, nulliparity, race, smoking, obesity, number of visits per year and highest level of education. MAIN RESULTS AND THE ROLE OF CHANCE Infertile women had an overall higher risk of developing cancer compared to non-infertile women (2.0 versus 1.7%, adjusted hazard ratio (aHR) = 1.18; CI: 1.12-1.24). In addition, the risk of uterine cancer (0.10 versus 0.06%, aHR = 1.78; CI: 1.39-2.28), ovarian cancer (0.14 versus 0.09%, aHR 1.64; CI: 1.33-2.01), lung cancer (0.21 versus 0.21%, aHR = 1.38; CI: 1.01-1.88), thyroid cancer (0.21 versus 0.16%, aHR = 1.29; CI: 1.09-1.53), leukemia (0.10 versus 0.06%, aHR = 1.55; CI: 1.21-1.98) and liver and gallbladder cancer (0.05 versus 0.03%, aHR = 1.59; CI: 1.11-2.30) were higher in infertile women compared to non-infertile women. In a subgroup analysis of women in each cohort who became pregnant and had a delivery during enrollment, the risk of uterine and ovarian cancer were similar between infertile and non-infertile women. In a subgroup analysis excluding women with PCOS and endometriosis from both cohorts, the risk of uterine cancer was similar between infertile and non-infertile women. LIMITATIONS, REASONS FOR CAUTION Absolute risk of cancer was low, average follow up for each individual was limited, and average age at index date was limited. Insurance databases have known limitations. WIDER IMPLICATIONS OF THE FINDINGS Using claims-based data, we report that infertile women may have a higher risk of certain cancers in the years after infertility evaluation; continued follow up should be considered after reproductive goals are achieved. STUDY FUNDING/COMPETING INTEREST(S) None.
On Moderating Software Crowdsourcing Challenges

Crowdsourcing divides a task into small pieces that are carried out by the crowd. In Software Engineering, crowdsourcing divides the software development tasks of to be carried out online by the crow and is simply called Software Crowdsourcing (SW CS). Most SW CS platforms support this emerging software development strategy and operate within a framework of competition among the crowd. Competitive SW CS platforms intentionally minimize communication and collaboration among the parties involved (customer, platform, and crowd) while they compete in the software development tasks. The goal of this paper is to investigate platform moderators in SW CS challenges. Platform moderators are individuals who work for the SW CS platforms to mediate customer and crowd. A qualitative analysis of the content of the communication forums hosted on the TopCoder platform was performed to analyze the messages exchanged by the platform moderators and the crowd. Our empirical results indicate that co-pilots enforce and, at the same time, extend the limitations of the documentation associated with the tasks to support crowd members, provide technical help to crowd members during the competitions, and engage the crowd in the challenges. Co-pilots are organized, work diligently, worrying about being fair, and, at the same time, seeking to find a balance between autonomy and dependency on the customer. We conclude by providing insights to improve the design of software crowdsourcing platforms.
Aberrant reward prediction errors in young adult at‐risk alcohol users

Previous studies suggest that individuals with substance use disorder have abnormally large responses to unexpected outcomes (reward prediction errors [RPEs]). However, there is much less information on RPE in individuals at risk of alcohol misuse, prior to neurobiological adaptations that might result from sustained alcohol use. Here, participants (mean age 23.77 years, range 18‐32 years) performed the electrophysiological monetary incentive delay task. This task involved responding to a target stimulus following reward incentive cues to win, or avoid losing, the cued reward while brain activity was recorded under 64‐channel EEG. The Alcohol Use Disorders Identification Test (AUDIT) was used to quantify at‐risk alcohol use, with high (n = 22, mean AUDIT score: 13.82) and low (n = 22, mean AUDIT score: 5.77) alcohol use groups. Trial‐by‐trial RPEs were estimated using a Rescorla‐Wagner reinforcement model based on behavioral data. A single‐trial analysis revealed that the feedback‐related negativity (FRN) and feedback P3 (fb‐P3) event‐related potential components were significantly modulated by RPEs. There was increased RPE‐related fb‐P3 amplitude for those in the high alcohol use group. Next, the mean amplitude of ERPs elicited by positive and negative RPEs were compared between groups. We found that high alcohol use participants had attenuated FRN amplitude in contrast with low alcohol use participants for both positive and negative RPEs but enhanced fb‐P3 for both positive and negative RPE. These results, with differences in RPE in an at‐risk group, suggest that RPE a potential vulnerability marker for alcohol use disorder.
Perspectives on Acceptance and Use of a Mobile Health Intervention for the Prevention of Atherosclerotic Cardiovascular Disease in Singapore: Mixed-Methods Study

Background Cardiovascular disease, including atherosclerotic cardiovascular disease (ASCVD), is a growing public health threat globally and many individuals remain undiagnosed, untreated, and uncontrolled. Simultaneously, mobile health (mHealth) interventions using short messaging service (SMS) have gained popularity globally. There is an opportunity for innovative approaches such as mHealth to encourage and enable adherence to medications for ASCVD and its risk factors. Objective This study aimed to understand mobile technology acceptance, use, and facilitating conditions among the study population ahead of the design of an mHealth intervention. Methods Using data from a mixed-methods study conducted in Singapore, we conducted a cross-sectional survey with 100 participants and in-depth, semistructured interviews with 20 patients. All participants were over the age of 40 years with ASCVD or its risk factors. Interviews were conducted in English and Mandarin and if needed translated to English. Nvivo 11 (QSR International) was used for analyses. Results Participants reported their perspectives on technology use and preferences, including low or sporadic mobile phone use and usability concerns including small screen and text size, among others; the benefit of previous mHealth use in creating a favorable opinion of SMS for health information; trust in both the source of mHealth SMS, as well as in treatment; the formation of habits; and fear of sequelae or death for facilitating intention to use an mHealth intervention and adhere to medication. We also highlighted a case that underscored the importance of the period after diagnosis in habit forming as an opportunity for an mHealth intervention. Conclusions We explored both technology- and adherence-related factors that influence a patient’s intention to use an mHealth intervention for adherence to ASCVD medication in Singapore. We highlighted the importance of identifying the right opportunity to engage with patients and promote an mHealth intervention for adherence, such as immediately following diagnosis when patients are establishing medication-taking habits.
Looking for the Devil in the Details: Learning Trilinear Attention Sampling Network for Fine-Grained Image Recognition

Learning subtle yet discriminative features (e.g., beak and eyes for a bird) plays a significant role in fine-grained image recognition. Existing attention-based approaches localize and amplify significant parts to learn fine-grained details, which often suffer from a limited number of parts and heavy computational cost. In this paper, we propose to learn such fine-grained features from hundreds of part proposals by Trilinear Attention Sampling Network (TASN) in an efficient teacher-student manner. Specifically, TASN consists of 1) a trilinear attention module, which generates attention maps by modeling the inter-channel relationships, 2) an attention-based sampler which highlights attended parts with high resolution, and 3) a feature distiller, which distills part features into an object-level feature by weight sharing and feature preserving strategies. Extensive experiments verify that TASN yields the best performance under the same settings with the most competitive approaches, in iNaturalist-2017, CUB-Bird, and Stanford-Cars datasets.
Diagnosing and Enhancing VAE Models

Although variational autoencoders (VAEs) represent a widely influential deep generative model, many aspects of the underlying energy function remain poorly understood. In particular, it is commonly believed that Gaussian encoder/decoder assumptions reduce the effectiveness of VAEs in generating realistic samples. In this regard, we rigorously analyze the VAE objective, differentiating situations where this belief is and is not actually true. We then leverage the corresponding insights to develop a simple VAE enhancement that requires no additional hyperparameters or sensitive tuning. Quantitatively, this proposal produces crisp samples and stable FID scores that are actually competitive with a variety of GAN models, all while retaining desirable attributes of the original VAE architecture. A shorter version of this work will appear in the ICLR 2019 conference proceedings (Dai and Wipf, 2019). The code for our model is available at this https URL TwoStageVAE.
Malnutrition among 6–59-Month-Old Children at District 2 Hospital, Ho Chi Minh City, Vietnam: Prevalence and Associated Factors

Objectives Childhood malnutrition is major health concern in many low- and middle-income countries, including Vietnam. It was a major risk factor for child mortality and adult ill-health. Malnutrition could increase the risk of serious infections; conversely current diseases also had a negative impact on the growth of child. This study, therefore, examines the prevalence of stunting and underweight among 6–59-month-old outpatient children in District 2 Hospital, Ho Chi Minh City, Vietnam. Methods A cross-sectional study involved a sample of 225 children aged 6–59 months who were randomly selected from the Outpatient Department in District 2 Hospital. Anthropometric measurements and blood test of children were taken to assess the nutritional status and anaemia. A structured questionnaire was also used to collect mothers' and children's characteristics to examine associated risk factors. Results The prevalence of stunting, underweight, overweight, and anaemia among children aged 6–59 months was 9.8%, 8.4%, 25.8%, and 30.7%, respectively. Underweight significantly correlated only to having breastfeeding in the first hour after birth (RR: 0.02; 95% CI: 0.01-0.17; p<0.001), while stunting was related to age of starting complementary foods from equal to/more than 6 months (RR=0.70, 95%CI=0.50-0.99, p<0.05) and normal birth weight (RR = 0.29, 95%CI = 0.15-0.56, p<0.001). Conclusions This study emphasized the importance of measuring the overall nutritional status for children, who have coexisting infectious diseases and anaemia. The high prevalence of malnutrition and anaemia underlined the need for routine screening as well as treatment of children. Additionally, health information strategies should be focused on young children feeding practices to minimize stunting and underweight.
Associations between antibiotic prescriptions and recurrent urinary tract infections in female college students

Abstract Urinary tract infections (UTIs) are common among college-aged women and often recur. Some antibiotics recommended to treat UTIs trigger dysbiosis of intestinal and vaginal microbiomes – where uropathogens originate, though few studies have investigated associations between these therapies with recurrent infections. We retrospectively analysed the electronic medical records of 6651 college-aged women diagnosed with a UTI at a US university student health centre between 2006 and 2014. Women were followed for 6 months for incidence of a recurrent infection. In a secondary analysis, associations in women whose experienced UTI recurrence within 2 weeks were also considered for potential infection relapse. Logistic regression was used to assess associations between infection recurrence or relapse and antibiotics prescribed, in addition to baseline patient characteristics including age, race/ethnicity, region of origin, year of encounter, presence of symptomology, pyelonephritis, vaginal coinfection and birth control consultation. There were 1051 instances of infection recurrence among the 6620 patients, indicating a prevalence of 16%. In the analysis of patient characteristics, Asian women were statistically more likely to experience infection recurrence whereas African American were less likely. No significant associations were identified between the antibiotic administered at the initial infection and the risk of infection recurrence after multivariable adjustment. Treatment with trimethoprim-sulphamethoxazole and being born outside of the USA were significantly associated with increased odds of infection relapse in the multivariate analysis. The results of the analyses suggest that treatment with trimethoprim-sulphamethoxazole may lead to an increased risk of UTI relapse, warranting further study.
Immunohistochemical Expression of Epidermal Growth Factor Receptor in Hepatocellular Carcinoma

Abstract Introduction: Epidermal growth factor receptor (EGFR) signaling plays an important role in various cancers, including hepatocellular carcinoma (HCC). We aimed to evaluate immunoexpression of EGFR in HCC and surrounding non-tumor liver tissue and to correlate it to multiple clinicopathologic data. Material and Methods: We analyzed 60 patients with HCC for multiple clinicopathologic characteristics and survival. Presence of the immunosignal and the percentage of positive tumor cells at the whole tumor tissue sample and adjacent cirrhotic liver tissue were semi-quantitatively determined. Results: Nineteen patients (31.67%) were female and 41 (68.33%) were male ranging in age from 31 to 85 years, median 61.88±10.51. Mean survival time for female patients was 8.86±1.76 months, for male 13.03±1.50 months and overall survival was 11.6051±1.19 months. The most patients had: T2 status (41.67%), no enlarged lymph nodes (90%), vascular invasion (63.33%) and well differentiated (43.33%) tumors. EGFR immunoexpression was determined in range from 0% to 100% in both tumor and non-tumor tissue with mean value of 39.58% in tumor and 86.86% in cirrhotic tissue (p<0.00). Higher percent of tumor EGFR positive cells were found in cases with higher T status, higher levels of AFP and poorly differentiated carcinoma, but not significantly. Lower percent of tumor EGFR positive cells were found in patients with vascular invasion and enlarged lymph nodes, but also not significantly. EGFR expression in tumor tissue significantly influenced survival of the patients (p<0.05). Conclusion: The study showed that expression of EGFR in lower percentage of tumor cells was associated to favorable prognosis, making it a potential prognostic marker and therapeutic target.