Miracle-dz/UniFAR-FTUs huggingface dataset:
Perspective of Adults With Neurofibromatosis 1 and Cutaneous Neurofibromas

Objective To assess the perspectives of adults with neurofibromatosis 1 (NF1) regarding cutaneous neurofibroma (cNF) morbidity, treatment options, and acceptable risk–benefit ratio to facilitate the design of patient-centered clinical trials. Methods An online survey developed by multidisciplinary experts and patient representatives of the Response Evaluation in Neurofibromatosis and Schwannomatosis (REiNS) cNF Working Group was distributed to adults with NF1 (n = 3,734) in the largest international database of individuals with any form of NF. Eligibility criteria included self-reported NF1 diagnosis, age ≥18 years, ≥1 cNF, and ability to read English. Results A total of 548 adults with NF1 responded to the survey. Respondents ranked appearance, number, and then location as the most bothersome features of raised cNF. Seventy-five percent of respondents considered a partial decrease of 33%–66% in the number or size of cNF as a meaningful response to experimental treatments. Most respondents (48%–58%) were willing to try available cNF treatments but were not aware of options outside of surgical removal. Regarding experimental agents, respondents favored topical, then oral medications. Most individuals (>65%) reported being “very much” or “extremely willing” to try experimental treatments, especially those with the highest cNF burden. Many respondents were not willing to tolerate side effects like nausea/vomiting (51%) and rash (46%). The greatest barriers to participation in cNF clinical trials were cost of participation and need to take time off work. Conclusions Most adults with NF1 are willing to consider experimental therapies for treatment of cNF. These data will guide the design of patient-centered clinical trials for adults with cNF.
Blocking Bacterial Naphthohydroquinone Oxidation and ADP-Ribosylation Improves Activity of Rifamycins against Mycobacterium abscessus

Rifampicin is an effective drug for treating tuberculosis (TB) but is not used to treat Mycobacterium abscessus infections due to poor in vitro activity. While rifabutin, another rifamycin, has better anti-M. abscessus activity, its activity is far from the nanomolar potencies of rifamycins against Mycobacterium tuberculosis. ABSTRACT Rifampicin is an effective drug for treating tuberculosis (TB) but is not used to treat Mycobacterium abscessus infections due to poor in vitro activity. While rifabutin, another rifamycin, has better anti-M. abscessus activity, its activity is far from the nanomolar potencies of rifamycins against Mycobacterium tuberculosis. Here, we asked (i) why is rifabutin more active against M. abscessus than rifampicin, and (ii) why is rifabutin’s anti-M. abscessus activity poorer than its anti-TB activity? Comparative analysis of naphthoquinone- versus naphthohydroquinone-containing rifamycins suggested that the improved activity of rifabutin over rifampicin is linked to its less readily oxidizable naphthoquinone core. Although rifabutin is resistant to bacterial oxidation, metabolite and genetic analyses showed that this rifamycin is metabolized by the ADP-ribosyltransferase ArrMab like rifampicin, preventing it from achieving the nanomolar activity that it displays against M. tuberculosis. Based on the identified dual mechanism of intrinsic rifamycin resistance, we hypothesized that rifamycins more potent than rifabutin should contain the molecule’s naphthoquinone core plus a modification that blocks ADP-ribosylation at its C-23. To test these predictions, we performed a blinded screen of a diverse collection of 189 rifamycins and identified two molecules more potent than rifabutin. As predicted, these compounds contained both a more oxidatively resistant naphthoquinone core and C-25 modifications that blocked ADP-ribosylation. Together, this work revealed dual bacterial metabolism as the mechanism of intrinsic resistance of M. abscessus to rifamycins and provides proof of concept for the repositioning of rifamycins for M. abscessus disease by developing derivatives that resist both bacterial oxidation and ADP-ribosylation.
Arboviral diseases and poverty in Alabama, 2007–2017

Mosquito-borne viruses cause diseases of great public health concern. Arboviral disease case distributions have complex relationships with socioeconomic and environmental factors. We combined information about socio-economic (population, and poverty rate) and environmental (precipitation, and land use) characteristics with reported human cases of arboviral disease in the counties of Alabama, USA, from 2007–2017. We used county level data on West Nile virus (WNV), dengue virus (DENV), chikungunya virus (CHIKV), Zika virus (ZIKV), California serogroup virus, Eastern equine encephalitis virus, and Saint Louis encephalitis virus to provide a detailed description of their spatio-temporal pattern. We found a significant spatial convergence between incidence of WNV and poverty rate clustered in the southern part of Alabama. DENV, CHIKV and ZIKV cases showed a different spatial pattern, being mostly located in the northern part, in areas of high socioeconomic status. The results of our study establish that poverty-driven inequities in arboviral risk exist in the southern USA, and should be taken into account when planning prevention and intervention strategies.
DNA methylome and transcriptome landscapes of cancer-associated fibroblasts reveal a smoking-associated malignancy index.

Unlike the better-studied aberrant epigenome in the tumor, the clinicopathologic impact of DNA methylation in the tumor microenvironment (TME), especially the contribution from cancer-associated fibroblast (CAF), remains elusive. CAFs exhibit profound patient-to-patient tumorigenic heterogeneity. We ask whether such heterogeneity may be exploited to quantify the level of TME malignancy or not. We developed a robust and efficient methylome/transcriptome co-analysis system for CAFs and paired normal fibroblasts (NFs) from non-small-cell lung cancer patients. We found 14,781 CpG sites of CAF/NF differential methylation, of which 3,707 sites showed higher methylation changes in ever-smokers than in non-smokers. Concomitant CAF/NF differential gene expression analysis pinpointed to a subset of 54 smoking-associated CpG sites with strong methylation-regulated gene expression. A methylation index that summarizes the beta-values of these CpGs was built for NF/CAF discrimination (MIND) with high sensitivity and specificity. The potential of MIND in detecting pre-malignancy across individual patients was shown. MIND succeeded in predicting tumor recurrence in multiple lung cancer cohorts without reliance on patient survival data, suggesting that the malignancy level of TME may be effectively graded by this index. Precision TME grading may provide additional pathological information to guide cancer prognosis and open up more options in personalized medicine.
L-WNK1 is required for BK channel activation in intercalated cells

BK channels expressed in intercalated cells (ICs) in the aldosterone-sensitive distal nephron (ASDN) mediate flow-induced K+ secretion. In the ASDN of mice and rabbits, IC BK channel expression and activity increase with a high K+ diet. In cell culture, the long isoform of the kinase WNK1 (L-WNK1) increases BK channel expression and activity. Apical L-WNK1 expression is selectively enhanced in ICs in the ASDN of rabbits on a high K+ diet, suggesting that L-WNK1 contributes to BK channel regulation by dietary K+. We examined the role of IC L-WNK1 expression in enhancing BK channel activity in response to a high K+ diet. Mice with an IC-selective deletion of L-WNK1 (IC-L-WNK1-KO) and littermate control mice were placed on a high K+ (5% K+ as KCl) diet for at least 10 days. IC-L-WNK1-KO mice exhibited higher blood K+ concentrations ([K+]) than controls. BK channel-dependent whole-cell currents in ICs from cortical collecting ducts of high K+ fed IC-L-WNK1-KO mice were reduced compared to controls. Six-hour urinary K+ excretion in response a saline load was similar in IC-L-WNK1-KO mice and controls. The observations that IC-L-WNK1-KO mice have higher blood [K+] and reduced IC BK channel currents are consistent with impaired urinary K+ secretion, and suggest that IC L-WNK1 has a role in the renal adaptation to a high K+ diet.
IL-15 Gene Polymorphism in Celiac Disease Patients and Their Siblings.

BACKGROUND Celiac disease (CD) is an immune-mediated enteropathy characterized by lifelong gluten intolerance. Interleukin-15 (IL- 15) is a proinflammatory cytokine that is considered a key component in the immune reaction triggered by gluten. Our aim of this study was to evaluate the influence of IL-15 gene polymorphisms on CD development and clinical presentation. METHODS The study was enrolled-with 90 CD patients (49 female/41 male, median years of age 11), their 38 siblings (20 female/18 male, median years of age 8), and 99 healthy controls (66 female/33 male, median years of age 13). Their demographic findings, symptoms, and signs histopathological grade, Human Leukocyte Antigen (HLA) types were recorded. IL-15 gene polymorphisms rs2857261, rs10519613, and rs1057972 were analyzed through PCR. RESULTS There was a significantly higher frequency of GG genotype in rs2857972 polymorphisms and TT genotype in rs1057972 polymorphisms in celiac families compared to controls [41% vs. 23% (P = .0008), 36% vs. 11% (P = .001), respectively]. Without considering their HLA status, there was not any difference between celiacs and healthy siblings. However, when stratified according to their HLADQ2 status, rs2857972 GG polymorphism was 1.5 times prominent in celiacs than siblings at homozygous state, whereas rs1057972 TT genotype was found to be 2.5 times prominent in celiac siblings at heterozygous state. There was no association between these polymorphisms and clinical presentation. CONCLUSION rs2857972 GG and rs1057972 TT variants of IL 15 are more prominent in celiac families than controls. However, the impact of IL-15 gene polymorphism on CD development is dependent on HLADQ2 status.
Nutrient cycling drives plant community trait assembly and ecosystem functioning in a tropical mountain biodiversity hotspot.

Community trait assembly in highly diverse tropical rainforests is still poorly understood. Based on more than a decade of field measurements in a biodiversity hotspot of southern Ecuador, we implemented plant trait variation and improved soil organic matter dynamics in a widely used dynamic vegetation model (LPJ-GUESS) to explore the main drivers of community assembly along an elevational gradient. In the model (LPJ-GUESS-NTD, Nutrient-Trait Dynamics), each plant individual can possess different trait combinations, and the community trait composition emerges via ecological sorting. Further model developments include plant growth limitation by phosphorous (P) and mycorrhizal nutrient uptake. The new model version reproduced the main observed community trait shift and related vegetation processes along the elevational gradient, but only if nutrient limitations to plant growth were activated. In turn, when traits were fixed, low productivity communities emerged due to reduced nutrient-use efficiency. Mycorrhizal nutrient uptake, when deactivated, reduced NPP by between 61 - 72% along the gradient. Our results strongly suggest that the elevational temperature gradient drives community assembly and ecosystem functioning indirectly through its effect on soil nutrient dynamics, and vegetation traits. This illustrates the importance of considering these processes to yield realistic model predictions.
Fossil dermal denticles reveal the preexploitation baseline of a Caribbean coral reef shark community

Significance How abundant were sharks on Caribbean coral reefs before human impact? To explore this question, we recovered fossilized shark dermal denticles (scales) from a ∼7,000-y-old reef in western Caribbean Panama and compared them with denticles found on modern reefs in the same area. Our data suggest that sharks were over three times more numerous before humans began using marine resources in the area and that shark communities were compositionally different in the past, containing a higher proportion of fast-swimming, pelagic sharks. This reconstruction of preexploitation shark communities using fossil denticle assemblages demonstrates their potential to help contextualize recent declines in shark abundance, examine the ecological consequences of those declines, and guide shark management. Preexploitation shark baselines and the history of human impact on coral reef–associated shark communities in the Caribbean are poorly understood. We recovered shark dermal denticles from mid-Holocene (∼7 ky ago) and modern reef sediments in Bocas del Toro, Caribbean Panama, to reconstruct an empirical shark baseline before major human impact and to quantify how much the modern shark community in the region had shifted from this historical reference point. We found that denticle accumulation rates, a proxy for shark abundance, declined by 71% since the mid-Holocene. All denticle morphotypes, which reflect shark community composition, experienced significant losses, but those morphotypes found on fast-swimming, pelagic sharks (e.g., families Carcharhinidae and Sphyrnidae) declined the most. An analysis of historical records suggested that the steepest decline in shark abundance occurred in the late 20th century, coinciding with the advent of a targeted shark fishery in Panama. Although the disproportionate loss of denticles characterizing pelagic sharks was consistent with overfishing, the large reduction in denticles characterizing demersal species with low commercial value (i.e., the nurse shark Ginglymostoma cirratum) indicated that other stressors could have exacerbated these declines. We demonstrate that the denticle record can reveal changes in shark communities over long ecological timescales, helping to contextualize contemporary abundances and inform shark management and ecology.
Development and Validation of Image-Based Deep Learning Models to Predict Surgical Complexity and Complications in Abdominal Wall Reconstruction.

Importance Image-based deep learning models (DLMs) have been used in other disciplines, but this method has yet to be used to predict surgical outcomes. Objective To apply image-based deep learning to predict complexity, defined as need for component separation, and pulmonary and wound complications after abdominal wall reconstruction (AWR). Design, Setting, and Participants This quality improvement study was performed at an 874-bed hospital and tertiary hernia referral center from September 2019 to January 2020. A prospective database was queried for patients with ventral hernias who underwent open AWR by experienced surgeons and had preoperative computed tomography images containing the entire hernia defect. An 8-layer convolutional neural network was generated to analyze image characteristics. Images were batched into training (approximately 80%) or test sets (approximately 20%) to analyze model output. Test sets were blinded from the convolutional neural network until training was completed. For the surgical complexity model, a separate validation set of computed tomography images was evaluated by a blinded panel of 6 expert AWR surgeons and the surgical complexity DLM. Analysis started February 2020. Exposures Image-based DLM. Main Outcomes and Measures The primary outcome was model performance as measured by area under the curve in the receiver operating curve (ROC) calculated for each model; accuracy with accompanying sensitivity and specificity were also calculated. Measures were DLM prediction of surgical complexity using need for component separation techniques as a surrogate and prediction of postoperative surgical site infection and pulmonary failure. The DLM for predicting surgical complexity was compared against the prediction of 6 expert AWR surgeons. Results A total of 369 patients and 9303 computed tomography images were used. The mean (SD) age of patients was 57.9 (12.6) years, 232 (62.9%) were female, and 323 (87.5%) were White. The surgical complexity DLM performed well (ROC = 0.744; P < .001) and, when compared with surgeon prediction on the validation set, performed better with an accuracy of 81.3% compared with 65.0% (P < .001). Surgical site infection was predicted successfully with an ROC of 0.898 (P < .001). However, the DLM for predicting pulmonary failure was less effective with an ROC of 0.545 (P = .03). Conclusions and Relevance Image-based DLM using routine, preoperative computed tomography images was successful in predicting surgical complexity and more accurate than expert surgeon judgment. An additional DLM accurately predicted the development of surgical site infection.
Assessing clinicians’ Post-Exposure Prophylaxis recommendations for rabies virus exposures in Hunan Province, China

Background Timely and appropriate administration of post-exposure prophylaxis (PEP) is an essential component of human rabies prevention programs. We evaluated patient care at rabies clinics in a high-risk county in Hunan Province, China to inform strategies needed to achieve dog-mediated human rabies elimination by 2030. Methods We collected information on PEP, staff capacity, and service availability at the 17 rabies clinics in the high-risk county during onsite visits and key staff interviews. Additionally, we conducted observational assessments at five of these clinics, identified through purposive sampling to capture real-time information on patient care during a four-week period. Wound categories assigned by trained observers were considered accurate per national guidelines for comparison purposes. We used the kappa statistic and an alpha level of 0.05 to assess agreement between observers and clinic staff. Results In 2015, the 17 clinics provided PEP to 5,261 patients. Although rabies vaccines were available at all 17 clinics, rabies immune globulin (RIG) was only available at the single urban clinic in the county. During the assessment period in 2016, 196 patients sought care for possible rabies virus exposures. According to observers, 88 (44%) patients had category III wounds, 104 (53%) had category II wounds and 4 (2%) had category I wounds. Observers and PEP clinic staff agreed on approximately half of the assigned wound categories (kappa = 0.55, p-value< 0.001). Agreement for the urban county-level CDC clinic (kappa = 0.93, p-value<0.001) was higher than for the township clinics (kappa = 0.16, p-value = 0.007). Using observer assigned wound categories, 142 (73%) patients received rabies vaccinations and RIG as outlined in the national guidelines. Conclusion Rabies PEP services were available at each town of the project county; however, gaps between clinical practice and national rabies guidelines on the use of PEP were identified. We used these findings to develop and implement a training to rabies clinic staff on wound categorization, wound care, and appropriate use of PEP. Additional risk-based approaches for evaluating human rabies virus exposures may be needed as China progresses towards elimination.
Long-Term Stability of Short-Term Intensive Language–Action Therapy in Chronic Aphasia: A 1–2 year Follow-Up Study

Background. Intensive aphasia therapy can improve language functions in chronic aphasia over a short therapy interval of 2–4 weeks. For one intensive method, intensive language–action therapy, beneficial effects are well documented by a range of randomized controlled trials. However, it is unclear to date whether therapy-related improvements are maintained over years. Objective. The current study aimed at investigating long-term stability of ILAT treatment effects over circa 1–2 years (8–30 months). Methods. 38 patients with chronic aphasia participated in ILAT and were re-assessed at a follow-up assessment 8–30 months after treatment, which had been delivered 6–12.5 hours per week for 2–4 weeks. Results. A standardized clinical aphasia battery, the Aachen Aphasia Test, revealed significant improvements with ILAT that were maintained for up to 2.5 years. Improvements were relatively better preserved in comparatively young patients (<60 years). Measures of communicative efficacy confirmed improvements during intensive therapy but showed inconsistent long-term stability effects. Conclusions. The present data indicate that gains resulting from intensive speech–language therapy with ILAT are maintained up to 2.5 years after the end of treatment. We discuss this novel finding in light of a possible move from sparse to intensive therapy regimes in clinical practice.
Adsorption/Desorption of Organic Acids onto Different Adsorbents for Their Recovery from Fermentation Broths

Activated carbon and a weak base resin were used as adsorbents for organic acids of relevance in green chemistry. Equilibrium adsorption studies in single and binary systems of acetic, propionic and butyric acids were carried out using various solvents (water, ethanol, and n-propanol) and equilibrium isotherm models were tested. The resin had a higher adsorption capacity than the activated carbon (about 35 %). Data on adsorption of binary systems suggested competition between the acids and a chain size dependence. In the studies using organic solvents, the resin showed a higher adsorption capacity than the activated carbons. This work showed the importance of conducting a complete and integrated study of an adsorption process including both adsorption and desorption steps. The use of resin with n-propanol as eluent achieved the best recovery in the simulated purification of propionic acid.
A sensitivity analysis of probability maps in deep‐learning‐based anatomical segmentation

Abstract Purpose Deep‐learning‐based segmentation models implicitly learn to predict the presence of a structure based on its overall prominence in the training dataset. This phenomenon is observed and accounted for in deep‐learning applications such as natural language processing but is often neglected in segmentation literature. The purpose of this work is to demonstrate the significance of class imbalance in deep‐learning‐based segmentation and recommend tuning of the neural network optimization objective. Methods An architecture and training procedure were chosen to represent common models in anatomical segmentation. A family of 5‐block 2D U‐Nets were independently trained to segment 10 structures from the Cancer Imaging Archive's Head‐Neck‐Radiomics‐HN1 dataset. We identify the optimal threshold for our models according to their Dice score on the validation datasets and consider perturbations about the optimum. A measure of structure prominence in segmentation datasets is defined, and its impact on the optimal threshold is analyzed. Finally, we consider the use of a 2D Dice objective in addition to binary cross entropy. Results We observe significant decreases in perceived model performance with conventional 0.5‐thresholding. Perturbations of as little as ±0.05 about the optimum threshold induce a median reduction in Dice score of 11.8% for our models. There is statistical evidence to suggest a weak correlation between training dataset prominence and optimal threshold (Pearson r=0.92 and p≈10‐4). We find that network optimization with respect to the 2D Dice score itself significantly reduces variability due to thresholding but does not unequivocally create the best segmentation models when assessed with distance‐based segmentation metrics. Conclusion Our results suggest that those practicing deep‐learning‐based contouring should consider their postprocessing procedures as a potential avenue for improved performance. For intensity‐based postprocessing, we recommend a mixed objective function consisting of the traditional binary cross entropy along with the 2D Dice score.