Miracle-dz/UniFAR-FTUs huggingface dataset:
How patients choose kidney transplant centers: A qualitative study of patient experiences

Little is known about how patients make the critical decision of choosing a transplant center. In the United States, acceptance criteria, waiting times, and mortality vary significantly by geography and center. We sought to understand patients' experiences and perspectives when selecting transplant centers. We included 82 kidney transplant patients in 20 semi‐structured interviews, nine focus groups with local candidates, and three focus groups with national recipients. Sites included two local transplant centers in Minneapolis, Minnesota, and national recipients from across the United States. Transcripts were analyzed by two researchers using a thematic analysis. Several themes emerged related to priorities and barriers when choosing a center. Patients were often unfamiliar with options, even with multiple local centers. Patients described being referred to a specific center by a trusted provider. Patients prioritized perceived reputation, comfort, and convenience. Insurance coverage was both a source of information and a barrier to options. Patients underestimated differences across centers and the effects on being waitlisted and receiving a transplant. Barriers in decision making included an overwhelming scope of information and difficulty locating information relevant to patients with unique medical needs. Informed decisions could be improved by the dissemination of understandable information better tailored to individual patient needs.
Sudden Wilt of Melons in Southern Israel: Fungal Agents and Relationship with Plant Development.

Fungi belonging to five genera, Monosporascus sp. , Pythium aphanidermatum, Rhizoctonia solani, Olpidium sp. , Fusarium solani, and F. proliferatum, were the species most frequently isolated from the root systems of wilted melon. Diseased plants were collected from 24 fields in the northern and central Arava region of southern Israel during the fall seasons of 1994 and 1995. In pathogenicity tests conducted under field conditions, in artificially inoculated microplots, the first wilt symptoms were observed at various stages of fruit maturation. High mortality levels (73 to 97%) were recorded for inoculation combinations in which Monosporascus sp. was involved. Inoculations with the other fungi listed resulted in lower incidences of wilt. The combination of F. solani and P. aphanidermatum resulted in higher mortality than that caused by each pathogen alone. Monosporascus sp. seems to be the primary pathogen, although other fungi could also induce wilt. The dry weight of plants grown in naturally infested soil ceased to accumulate 33 days after transplanting, in contrast to plants grown in methyl bromide-treated soil. At this stage, the first wilt symptoms were observed. Fruit load affected wilt incidence. At the end of the growing season, 98% mortality was recorded for plants having the normal fruit load (2.5 fruits per plant) compared with 75 and 12% for plants that had their fruits thinned to one or zero per plant, respectively.
MirrorGAN: Learning Text-To-Image Generation by Redescription

Generating an image from a given text description has two goals: visual realism and semantic consistency. Although significant progress has been made in generating high-quality and visually realistic images using generative adversarial networks, guaranteeing semantic consistency between the text description and visual content remains very challenging. In this paper, we address this problem by proposing a novel global-local attentive and semantic-preserving text-to-image-to-text framework called MirrorGAN. MirrorGAN exploits the idea of learning text-to-image generation by redescription and consists of three modules: a semantic text embedding module (STEM), a global-local collaborative attentive module for cascaded image generation (GLAM), and a semantic text regeneration and alignment module (STREAM). STEM generates word- and sentence-level embeddings. GLAM has a cascaded architecture for generating target images from coarse to fine scales, leveraging both local word attention and global sentence attention to progressively enhance the diversity and semantic consistency of the generated images. STREAM seeks to regenerate the text description from the generated image, which semantically aligns with the given text description. Thorough experiments on two public benchmark datasets demonstrate the superiority of MirrorGAN over other representative state-of-the-art methods.
Cutaneous Abnormalities in Chronic Kidney Disease Patients with and without Dialysis

Background: Chronic kidney disease (CKD) is increasingly prevalent worldwide. CKD may present with different cutaneous manifestations. Objectives: To evaluate the dermatological manifestations and compare these manifestations between patients with maintenance hemodialysis (MHD) and non-dialysis groups. Methods: It was a cross sectional study conducted in the Department of Nephrology, Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh from April 2013 to March 2014. A total of 150 hospital admitted CKD patients were evaluated for dermatological manifestations. Age, gender, haemoglobin level, 24-hours urinary total protein (UTP), serum creatinine, serum fasting lipid profile, estimated glomerular filtration rate (e-GFR) and dermatological manifestations of the study subjects were recorded accordingly. Inter-group comparisons were made between patients with and those without cutaneous abnormality. Results: Out of 150 study subjects, 99 (66%) were male and 51 (34%) were female, 69 (46%) patients were on MHD and 81 (54%) patients were without dialysis, their mean (±SD) age was 44.6 ± 12.3 year. A Total of 126 (84%) patients had cutaneous abnormalities; among them 69 (54.76%) were pre-dialytic and 57 (45.24%) were on MHD group. The mean (±SD) serum creatinine was relatively higher but haemoglobin level was significantly lower (p = 0.021), while UTP was significantly higher (p = 0.038) among patients with cutaneous abnormality. There was no relationship between lipid profile with cutaneous abnormality. Among 126 (84%) patients with cutaneous abnormality; pallor was the most common cutaneous abnormality (72%) followed by xerosis (68.66%), pruritus (65.33%), half and half nails (38.66%), pigmentation (33.33%), purpura/ecchymosis (16.66%), fungal infection (16%), ulcerative stomatitis (10.66%) and bacterial infection (10%). Pigmentation (52.6%), purpura (35.1%), ulcerative stomatitis (21.1%) and bacterial infection (19.3%) were significantly higher in MHD group. Among 69 (54.76%) predialytic patients; 11 (15.94%), 20 (28.98%) and 38 (55.07%) of them were on CKD stage-III, IV and V respectively. Conclusions: The dermatological disorders are frequent among CKD patients. Pallor, pruritus, xerosis, pigmentation and purpura are predominant changes. Pigmentation, purpura, ulcerative stomatitis and bacterial infection are significantly higher in MHD patients. Cutaneous abnormalities are more frequent in advance stages of CKD.
Impact of Long-Term Exposure to Wind Turbine Noise on Redemption of Sleep Medication and Antidepressants: A Nationwide Cohort Study

Background: Noise from wind turbines (WTs) is associated with annoyance and, potentially, sleep disturbances. Objectives: Our objective was to investigate whether long-term WT noise (WTN) exposure is associated with the redemption of prescriptions for sleep medication and antidepressants. Methods: For all Danish dwellings within a radius of 20-WT heights and for 25% of randomly selected dwellings within a radius of 20-to 40-WT heights, we estimated nighttime outdoor and low-frequency (LF) indoor WTN, using information on WT type and simulated hourly wind. During follow-up from 1996 to 2013, 68,696 adults redeemed sleep medication and 82,373 redeemed antidepressants, from eligible populations of 583,968 and 584,891, respectively. We used Poisson regression with adjustment for individual and area-level covariates. Results: Five-year mean outdoor nighttime WTN of ≥42 dB was associated with a hazard ratio (HR) = 1.14 [95% confidence interval (CI]: 0.98, 1.33) for sleep medication and HR = 1.17 (95% CI: 1.01, 1.35) for antidepressants (compared with exposure to WTN of <24 dB). We found no overall association with indoor nighttime LF WTN. In age-stratified analyses, the association with outdoor nighttime WTN was strongest among persons ≥65y of age, with HRs (95% CIs) for the highest exposure group (≥42 dB) of 1.68 (1.27, 2.21) for sleep medication and 1.23 (0.90, 1.69) for antidepressants. For indoor nighttime LF WTN, the HRs (95% CIs) among persons ≥65y of age exposed to ≥15 dB were 1.37 (0.81, 2.31) for sleep medication and 1.34 (0.80, 2.22) for antidepressants. Conclusions: We observed high levels of outdoor WTN to be associated with redemption of sleep medication and antidepressants among the elderly, suggesting that WTN may potentially be associated with sleep and mental health. https://doi.org/10.1289/EHP3909
Effect of Tornadoes on Local Labor Markets

In this paper, I examine the change in local labor markets caused by extreme tornadoes that occur in counties of the contiguous United States. I also investigate the effect these tornadoes have on neighboring counties and evaluate the labor market response in urban and rural counties separately as well. Using a generalized difference-in-difference approach on quarterly data spanning from 1975 to 2016, I find that violent tornadoes lead to persistently higher wage growth at the end of two years following the tornado. Reviewing the data by urban and rural counties shows that the effect is stronger for rural counties. Further, evaluating the response of labor markets by sectors reveals the industrial sectors that experience increased labor market activity. The response of the labor market varies based on the intensity of the tornado.
External Shocks, Trade Margins, and Macroeconomic Dynamics

This paper studies the role of the exchange rate regime for trade of new products. It first provides VAR evidence that a rise in external productivity shifts trade away from new products and more so in fixed regimes. Then, it presents a model with firm dynamics in line with this evidence. We argue that exchange rate policy can affect firms’ entry decisions with consequences for the competitiveness of a country’s exports well beyond the short run. In our setup, fixed exchange rates can foster the competitiveness of firms that trade new products, while flexible rates favor firms that produce mature products.
Cellular, molecular, and clinical mechanisms of action of deep brain stimulation—a systematic review on established indications and outlook on future developments

Deep brain stimulation (DBS) has been successfully used to treat movement disorders, such as Parkinson's disease, for more than 25 years and heralded the advent of electrical neuromodulation to treat diseases with dysregulated neuronal circuits. DBS is now superseding ablative techniques, such as stereotactic radiofrequency lesions. While serendipity has played a role in developing DBS as a therapy, research during the past two decades has shown that electrical neuromodulation is far more than a functional lesion that can be switched on and off. This understanding broadens the field to enable new types of stimulation, clinical indications, and research. This review highlights the complex effects of DBS from the single cell to the neuronal network. Specifically, we examine the electrical, cellular, molecular, and neurochemical mechanisms of DBS as applied to Parkinson's disease and other emerging applications.
Serum Amyloid P Component Binds Fungal Surface Amyloid and Decreases Human Macrophage Phagocytosis and Secretion of Inflammatory Cytokines

Macrophages are a key part of our innate immune system and are responsible for recognizing invading microbes, ingesting them, and sending appropriate signals to other immune cells. We have found that human macrophages can recognize invading yeast pathogens that have a specific molecular pattern of proteins on their surfaces: these proteins have structures similar to the structures of amyloid aggregates in neurodegenerative diseases like Alzheimer’s disease. However, this surface pattern also causes the fungi to bind a serum protein called serum amyloid P component (SAP). In turn, the SAP-coated yeasts are poorly recognized and seldom ingested by the macrophages, and the macrophages have a more tolerant and less inflammatory response in the presence of SAP. Therefore, we find that surface structures on the yeast can alter how the macrophages react to invading microbes. ABSTRACT In patients with invasive fungal diseases, there is often little cellular inflammatory response. We tested the idea that binding of the human constitutive plasma protein serum amyloid P component (SAP) (also called PTX2) to Candida albicans dampens the innate immune response to this fungus. Many pathogenic fungi have cell surface amyloid-like structures important for adhesion and biofilm formation. Human SAP bound to fungi that expressed functional cell surface amyloid, but SAP had minimal binding to fungi with reduced expression of cell surface amyloid. In the absence of SAP, phagocytosis of fungi by human macrophages was potentiated by expression of amyloid on the fungi. SAP binding to fungi inhibited their phagocytosis by macrophages. Macrophages pretreated with SAP displayed reduced fungal phagocytosis, reduced secretion of inflammatory cytokines (IFN-γ, IL-6, and TNF-α), and increased secretion of the anti-inflammatory cytokine IL-10. SAP bound to fungi or added to the medium upregulated the expression of the anti-inflammatory receptor CD206 on macrophages. These findings suggest that SAP bound to amyloid-like structures on fungal cells dampens the host cellular immune response in fungal diseases such as invasive candidiasis. IMPORTANCE Macrophages are a key part of our innate immune system and are responsible for recognizing invading microbes, ingesting them, and sending appropriate signals to other immune cells. We have found that human macrophages can recognize invading yeast pathogens that have a specific molecular pattern of proteins on their surfaces: these proteins have structures similar to the structures of amyloid aggregates in neurodegenerative diseases like Alzheimer’s disease. However, this surface pattern also causes the fungi to bind a serum protein called serum amyloid P component (SAP). In turn, the SAP-coated yeasts are poorly recognized and seldom ingested by the macrophages, and the macrophages have a more tolerant and less inflammatory response in the presence of SAP. Therefore, we find that surface structures on the yeast can alter how the macrophages react to invading microbes.
War-induced collapse and asymmetric recovery of large-mammal populations in Gorongosa National Park, Mozambique

How do large-mammal communities reassemble after being pushed to the brink of extinction? Few data are available to answer this question, as it is rarely possible to document both the decline and recovery of wildlife populations. Here we present the first in-depth quantitative account of war-induced collapse and postwar recovery in a diverse assemblage of large herbivores. In Mozambique’s Gorongosa National Park, we assembled data from 15 aerial wildlife counts conducted before (1968–1972) and after (1994–2018) the Mozambican Civil War (1977–1992). Pre-war total biomass density exceeded 9,000 kg km-2, but populations declined by >90% during the war. Since 1994, total biomass has substantially recovered, but species composition has shifted dramatically. Formerly dominant large herbivores—including elephant (Loxodonta africana), hippo (Hippopotamus amphibius), buffalo (Syncerus caffer), zebra (Equus quagga), and wildebeest (Connochaetes taurinus)—are now outnumbered by waterbuck (Kobus ellipsiprymnus) and other small to mid-sized antelopes. Waterbuck abundance has increased by an order of magnitude, with >55,000 individuals accounting for >74% of large-herbivore biomass in 2018. By contrast, elephant, hippo, and buffalo, which totaled 89% of pre-war biomass, now comprise just 23%. These trends mostly reflect natural population growth following the resumption of protection under the Gorongosa Restoration Project; reintroductions (465 animals of 7 species) accounted for a comparatively small fraction of the total numerical increase. Waterbuck are growing logistically, apparently as-yet unchecked by interspecific competition or predation (apex-carnivore abundance has been low throughout the post-war interval), suggesting a community still in flux. Most other herbivore populations have increased post-war, albeit at differing rates. Armed conflict remains a poorly understood driver of ecological change; our results demonstrate the potential for rapid post-war recovery of large-herbivore biomass, given sound protected-area management, but also suggest that restoration of community structure takes longer and may require active intervention.
Factors Influencing Falls in High- and Low-Risk Patients in a Tertiary Hospital in Korea

Objective The purpose of this study was to explore the characteristics and predictors of falls in high- and low-risk inpatients in a tertiary hospital in Korea. Methods Fallers' data were extracted from quality improvement reports and electronic health records from June 1, 2014, to May 31, 2015. Data on nonfallers matched by the length of hospitalization and medical departments of fallers were extracted from electronic health records. Participants were classified into a high- or a low-risk group based on their Morse Fall Scale score, fall risk–related symptoms, and medications known to increase fall risk. Characteristics of falls and risk factors were analyzed using descriptive statistics and logistic regression analysis, respectively. Results In the high-risk group, education, surgery, department, impaired mobility, intravenous catheter placement, use of ambulatory aid, gait disturbance, and some medications were significantly different between the fallers and nonfallers. From these variables, education, operation, department, intravenous catheter placement, gait disturbance, and use of narcotics, vasodilators, antiarrhythmics, and hypnotics were statistically significant factors for falls. In the low-risk group, sex, age, length of hospitalization, surgery, department, diagnosis, and mental status were significantly different between the fallers and nonfallers. From these, sex, age, length of hospitalization, surgery, and liver-digestive diseases were statistically significant factors for falls. Conclusions Characteristics and risk factors for falls differed between the risk groups. Fall prevention strategies need to be tailored to the risk groups and fall risk assessment tools need to be revised accordingly.
Pedestrian Trajectory Prediction in Extremely Crowded Scenarios

Pedestrian trajectory prediction under crowded circumstances is a challenging problem owing to human interaction and the complexity of the trajectory pattern. Various methods have been proposed for solving this problem, ranging from traditional Bayesian analysis to Social Force model and deep learning methods. However, most existing models heavily depend on specific scenarios because the trajectory model is constructed in absolute coordinates even though the motion trajectory as well as human interaction are in relative motion. In this study, a novel trajectory prediction model is proposed to capture the relative motion of pedestrians in extremely crowded scenarios. Trajectory sequences and human interaction are first represented with relative motion and then integrated to our model to predict pedestrians’ trajectories. The proposed model is based on Long Short Term Memory (LSTM) structure and consists of an encoder and a decoder which are trained by truncated back propagation. In addition, an anisotropic neighborhood setting is proposed instead of traditional neighborhood analysis. The proposed approach is validated using trajectory data acquired at an extremely crowded train station in Tokyo, Japan. The trajectory prediction experiments demonstrated that the proposed method outperforms existing methods and is stable for predictions of varying length even when the model is trained with a controlled short trajectory sequence.
The Level and Role of Interleukin-17 in Patients of Type 2 Diabetes Mellitus with and without Complications

Background: Type 2 Diabetes Mellitus (T2DM) is the most prevalent metabolic disorder in the world. Recent evidence however suggests that T2DM is not only a disease of metabolism, but also an inflammatory disorder and that inflammation also plays an important role in the pathogenesis of Diabetic complications. Our aim was to study the level of interleukin-17 (IL 17) in Indian populations with T2DM as an inflammatory marker and analyze its role in different diabetic complications. Methods: A total of consecutive 67 patients of T2DM were evaluated for clinical parameters fasting blood glucose (FBG), 2hr-post-prandial blood glucose (PPBG), lipid profile, HbA1c and plasma IL 17. They were divided into three groups—Patients of T2DM without any complications (group A; n = 24), T2DM with acute complications (group B; n = 20), T2DM with chronic complications (group C; n = 23) and compared with 23 healthy controls (group D). Results: Diabetic patients had a higher level of IL 17 as compared to the healthy controls. The level of IL 17 in complicated diabetics was higher than the patients with T2DM without complications. Multiple logistic regression analysis showed positive correlation of IL 17 with Diabetic Retinopathy and Diabetic Neuropathy. IL 17 also showed a positive Pearsons correlation with systolic blood pressure (SBP), diastolic blood pressure (DBP), serum triglycerides (TG), serum total cholesterol (TC), very low density lipoproteins (VLDL), low density lipoproteins (LDL), HbA1c and a negative correlation with HDL. Conclusion: Indian subjects with T2DM with or without complications had higher values of IL 17 as compared to healthy controls. Also diabetic neuropathy and diabetic retinopathy were positively correlated to levels of IL 17. Further levels of IL 17 were positively correlated to hypertension and dyslipidemia indicating a prevalent inflammatory state in our population of T2DM with and without complications.
Serological Detection of Ebola Virus Exposures in Native Non-human Primates of Southern Nigeria

Ebola viruses (family: Filoviridae) are the cause of Ebola virus disease (EVD), a highly fatal illness characterised by haemorrhagic fever syndrome in both humans and non-human primates (NHPs). West Africa was the epicentre of the 2013–2015 EVD epidemic which caused the death of over 11,000 people, including eight casualties in southern Nigeria. Antibodies to filoviruses have been detected among NHPs in some countries, but there is no documented evidence of exposures to filoviruses among NHPs in Nigeria. From August 2015 to February 2017, a total of 142 serum samples were obtained from individual captive and wild animals, belonging to 11 NHP species, in southern Nigeria, and screened for species-specific antibodies to filoviruses belonging to the species; Zaire ebolavirus [Ebola virus (EBOV)], Sudan ebolavirus [Sudan virus (SUDV)], and Marburg marburgvirus [Ravn virus (RAVV)]–using a modified filovirus species-specific ELISA technique. Of the sera tested, 2.1% (3/142) were positive for antibodies to EBOV. The entire 142 sera were negative for SUDV or RAVV. These findings point to the existence of natural exposures of NHPs in southern Nigeria to EBOV. There is need to discourage, the uncontrolled hunting of NHPs in Nigeria for public health safety.