Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of gut microbiota in gout: Is gut microbiota a potential target for gout treatment

Numerous studies have demonstrated that gut microbiota is essential for the host’s health because it regulates the host’s metabolism, endocrine, and immune systems. In recent years, increasing evidence has shown that gut microbiota plays a role in the onset and progression of gout. Changes in the composition and metabolism of the gut microbiota, result in abnormalities of uric acid degradation, increasing uric acid generation, releasing pro-inflammatory mediators, and intestinal barrier damage in developing gout. As a result, gout therapy that targets gut microbiota has drawn significant interest. This review summarized how the gut microbiota contributes to the pathophysiology of gout and how gout affects the gut microbiota. Additionally, this study explained how gut microbiota might serve as a unique index for the diagnosis of gout and how conventional gout treatment medicines interact with it. Finally, prospective therapeutic approaches focusing on gut microbiota for the prevention and treatment of gout were highlighted, which may represent a future avenue in gout treatment.
Verification of PCSWMM's LID processes and their scalability over time and space

Introduction This paper explores the scalability of PCSWMM's Low Impact Development (LID) modeling tools within the urban stormwater computer model. Methods The scalability is assessed for a variety of spatial and temporal scales and for event (50-year return storm) and continuous inputs (daily rainfall for an 11 month period), and with a focus on bioretention cells. The model is calibrated for a moderate to large scale, semi-urban watershed on Vancouver Island, British Columbia, Canada. Sensitivity analysis and specialized metrics are used to verify internal model processes at a variety of scales. Results With regard to spatial scaling, changes in flow path length and slope derived from Digital Elevation Models were the most impactful spatial information when modeling flood event and the model's surface layer was the dominant contributor to peak flowrate and volume mitigation by the bioretention cell. However, when modeling the continuous rainfall inputs, storage layer related parameters dominated model outputs. Aside from the soil layer's depth, soil layer parameters such as hydraulic conductivity, showed negligible influence on response to time series rainfall. Parameters that are kept static by the model such as vegetation cover, hydraulic conductivity and storage void ratio (but are naturally dynamic), were tested for their impact on response if allowed to change seasonally or with excessive loading. Runoff coefficients were greatly impacted by storage layer parameter dynamics with very little impact from vegetation. For event simulations, the berm height in the surface layer was the dominant player in reducing peak flow as well as total volume. An analysis to help illustrate sensitivity across spatial scales is proposed. Discussion The Spatial Dynamic Sensitivity Analysis shows that parameter sensitivity changes dynamically as LID implementation percentage changes. In particular, the clogging factor, which is a parameter associated with the storage layer, was highly influential for time series rainfall analysis. The LID model concepts in PCSWM seem appropriate for events because the surface layer dominates the response for very large storms. For smaller storms, continuous time series, and larger spatial scales, the model could be revised to better represent soil layer dynamics and vegetation cover, which were both currently inconsequential to the model's output.
SARS-CoV-2 epitopes inform future vaccination strategies

All currently approved COVID-19 vaccines utilize the spike protein as their immunogen. SARS-CoV-2 variants of concern (VOCs) contain mutations in the spike protein, enabling them to escape infection- and vaccination-induced immune responses to cause reinfection. New vaccines are hence being researched intensively. Studying SARS-CoV-2 epitopes is essential for vaccine design, as identifying targets of broadly neutralizing antibody responses and immunodominant T-cell epitopes reveal candidates for inclusion in next-generation COVID-19 vaccines. We summarize the major studies which have reported on SARS-CoV-2 antibody and T-cell epitopes thus far. These results suggest that a future of pan-coronavirus vaccines, which not only protect against SARS-CoV-2 but numerous other coronaviruses, may be possible. The T-cell epitopes of SARS-CoV-2 have gotten less attention than neutralizing antibody epitopes but may provide new strategies to control SARS-CoV-2 infection. T-cells target many SARS-CoV-2 antigens other than spike, recognizing numerous epitopes within these antigens, thereby limiting the chance of immune escape by VOCs that mainly possess spike protein mutations. Therefore, augmenting vaccination-induced T-cell responses against SARS-CoV-2 may provide adequate protection despite broad antibody escape by VOCs.
Is altitude a determinant of the health benefits of nature exposure? A systematic review and meta-analysis

Introduction Nature exposure is a widely accepted option for promoting public health owing to the recent surge of scientific evidence. However, the actual settings to facilitate this initiative is yet to be extensively reviewed. In this systematic review, we have aimed to provide an up-to-date summary of interventional studies investigating the psycho-physiological effects of forests and urban forests, including details on their physical settings, and investigate an effect-modifying role of altitude and summarize data on the magnitude and shape of the association. Methods A keyword search using five electronic academic databases (PubMed, Embase, PsycINFO, Web of Science, and Scopus) was conducted to identify relevant articles published in English from the inception year to the end of February 2022. The methodological quality was evaluated using the ROBINS-I or ROB2 tool, depending on the study design. Meta-regression and random effects model were jointly used to examine the relationship between altitude and health outcomes. Results We included 27 eligible studies and 31 cases extracted from 19 studies were used for the meta-analysis. In the meta-regression, we observed a non-linear association between altitude and psycho-physiological effects. Altitude had a positive quadratic association with anxiety (p < 0.000, adjusted R2 = 96.79%), depression (p < 0.000, adjusted R2 = 98.78%), and fatigue (p < 0.000, adjusted R2 = 64.74%) alleviating effects. Conversely, altitude demonstrated a negative non-linear association with the blood pressure-lowering effect (p = 0.009, adjusted R2 = 32.83%). Additionally, the thermal index (THI) and illuminance (lx) levels were significantly associated with effect sizes of psychological restoration. Discussion This review provides moderate-certainty evidence for an effect-modifying role of altitude. The meta-regression results suggested the optimal and minimal altitude ranges for psychological restoration and physiological relaxation, respectively. Despite some limitations, the study findings provide a significant basis for utilizing altitude, which is easily accessible and simple, to promote the health benefits of nature-based initiatives. Systematic review registration https://www.crd. york.ac. uk/prospero/display_record. php? ID=CRD42022310894, identifier: CRD42022310894.
L p -WASSERSTEIN DISTANCES ON STATE AND QUASI-STATE SPACES OF C ∗ -ALGEBRAS

We construct an analogue of the classical L p -Wasserstein distance for the state space of a C � -algebra. Given an abstract Lipschitz gauge on a C � -algebra A in the sense of Rieffel, one can define the classical L p -Wasserstein distance on the state space of each commutative C � -subalgebra of A. We consider a projective limit of these metric spaces, which appears to be the space of all quasi-linear states, equipped with a distance function. We call this distance the projective L p -Wasserstein distance. It is easy to show, that the state space of a C � -algebra is naturally embedded in the space of its quasi-linear states, hence, the introduced distance is defined on the state space as well. We show that this distance is reasonable and well-behaved. We also formulate a sufficient c for a Lipschitz gauge, such that the corresponding projective L p -Wasserstein distance metricizes the weak � -topology on the state space.
Scalable deep learning for watershed model calibration

Watershed models such as the Soil and Water Assessment Tool (SWAT) consist of high-dimensional physical and empirical parameters. These parameters often need to be estimated/calibrated through inverse modeling to produce reliable predictions on hydrological fluxes and states. Existing parameter estimation methods can be time consuming, inefficient, and computationally expensive for high-dimensional problems. In this paper, we present an accurate and robust method to calibrate the SWAT model (i.e., 20 parameters) using scalable deep learning (DL). We developed inverse models based on convolutional neural networks (CNN) to assimilate observed streamflow data and estimate the SWAT model parameters. Scalable hyperparameter tuning is performed using high-performance computing resources to identify the top 50 optimal neural network architectures. We used ensemble SWAT simulations to train, validate, and test the CNN models. We estimated the parameters of the SWAT model using observed streamflow data and assessed the impact of measurement errors on SWAT model calibration. We tested and validated the proposed scalable DL methodology on the American River Watershed, located in the Pacific Northwest-based Yakima River basin. Our results show that the CNN-based calibration is better than two popular parameter estimation methods (i.e., the generalized likelihood uncertainty estimation [GLUE] and the dynamically dimensioned search [DDS], which is a global optimization algorithm). For the set of parameters that are sensitive to the observations, our proposed method yields narrower ranges than the GLUE method but broader ranges than values produced using the DDS method within the sampling range even under high relative observational errors. The SWAT model calibration performance using the CNNs, GLUE, and DDS methods are compared using R 2 and a set of efficiency metrics, including Nash-Sutcliffe, logarithmic Nash-Sutcliffe, Kling-Gupta, modified Kling-Gupta, and non-parametric Kling-Gupta scores, computed on the observed and simulated watershed responses. The best CNN-based calibrated set has scores of 0.71, 0.75, 0.85, 0.85, 0.86, and 0.91. The best DDS-based calibrated set has scores of 0.62, 0.69, 0.8, 0.77, 0.79, and 0.82. The best GLUE-based calibrated set has scores of 0.56, 0.58, 0.71, 0.7, 0.71, and 0.8. The scores above show that the CNN-based calibration leads to more accurate low and high streamflow predictions than the GLUE and DDS sets. Our research demonstrates that the proposed method has high potential to improve our current practice in calibrating large-scale integrated hydrologic models.
Network analysis of associations between anthropometry, physical fitness, and sport-specific performance in young canoe sprint athletes: The role of age and sex

Introduction Anthropometric and physical fitness data can predict sport-specific performance (e.g., canoe sprint race time) in young athletes. Of note, inter-item correlations (i.e., multicollinearity) may exist between tests assessing similar physical qualities. However, multicollinearity among tests may change across age and/or sex due to age-/sex-specific non-linear development of test performances. Therefore, the present study aimed at analyzing inter-item correlations between anthropometric, physical fitness, and sport-specific performance data as a function of age and sex in young canoe sprint athletes. Methods Anthropometric, physical fitness, and sport-specific performance data of 618 male and 297 female young canoe sprint athletes (discipline: male/female kayak, male canoe) were recorded during a national talent identification program between 1992 and 2019. For each discipline, a correlation matrix (i.e., network analysis) was calculated for age category (U13, U14, U15, U16) and sex including anthropometrics (e.g., standing body height, body mass), physical fitness (e.g., cardiorespiratory endurance, muscle power), and sport-specific performance (i.e., 250 and 2,000-m on-water canoe sprint time). Network plots were used to explore the correlation patterns by visual inspection. Further, trimmed means (μtrimmed) of inter-item Pearson's correlations coefficients were calculated for each discipline, age category, and sex. Effects of age and sex were analyzed using one-way ANOVAs. Results Visual inspection revealed consistent associations among anthropometric measures across age categories, irrespective of sex. Further, associations between physical fitness and sport-specific performance were lower with increasing age, particularly in males. In this sense, statistically significant differences for μtrimmed were observed in male canoeists (p < 0.01, ξ = 0.36) and male kayakers (p < 0.01, ξ = 0.38) with lower μtrimmed in older compared with younger athletes (i.e., ≥U15). For female kayakers, no statistically significant effect of age on μtrimmed was observed (p = 0.34, ξ = 0.14). Discussion Our study revealed that inter-item correlation patterns (i.e., multicollinearity) of anthropometric, physical fitness, and sport-specific performance measures were lower in older (U15, U16) versus younger (U13, U14) male canoe sprint athletes but not in females. Thus, age and sex should be considered to identify predictors for sport-specific performance and design effective testing batteries for talent identification programs in canoe sprint athletes.
The diagnostic value of salivary cortisol and salivary cortisone in patients with suspected hypercortisolism

Background Diagnosing endogenous hypercortisolism remains a challenge, partly due to a lack of biochemical tests with good diagnostic accuracy. Objectives To evaluate the diagnostic value of salivary cortisol and cortisone in patients with suspected hypercortisolism. Methods Retrospective study including 155 patients with adrenal incidentaloma, and 54 patients with suspected Cushing´s syndrome (CS). Salivary samples were collected at home, at 11 p.m. , and at 8 a.m. following an over-night dexamethasone suppression test (DST). Salivary cortisol and cortisone were measured with liquid chromatography-tandem mass spectrometry. Results Ten of 155 patients with adrenal incidentaloma were considered to have autonomous cortisol secretion (ACS). Using previously established cut-offs, all patients with ACS had elevated plasma-cortisol (>50 nmol/L) following DST, 9/10 had elevated late-night salivary cortisone (>15 nmol/L) whereas only 4/10 had elevated late-night salivary cortisol (LNSC; >3 nmol/L) compared to 35%, 9% and 8%, respectively, of the 145 patients with non-functioning adrenal incidentaloma. Six (60%) patents with ACS had elevated salivary cortisol and cortisone at 8 a.m. following DST compared to 9% and 8%, respectively, of patients with non-functioning adrenal incidentaloma. One of 6 patients with overt CS had a normal LNSC and one had normal late-night salivary cortisone, while all had increased salivary cortisol and cortisone following DST. Conclusion LNSC is not sufficiently sensitive or specific to be used for screening patients with suspected hypercortisolism. Instead, late-night salivary cortisone seems to be a promising alternative in patients with adrenal incidentaloma and salivary cortisone at 8 a.m. following DST in patients with suspected CS. Larger studies are needed to confirm these findings.
Anterior cervical decompression and fusion surgery for cervicogenic headache: A multicenter prospective cohort study

Background Cervicogenic headache (CEH) has long been recognized as a referred pain deriving from pathological changes in the upper cervical nerves. However, previous clinical studies found that anterior lower cervical discectomy for the treatment of cervical myelopathy and/or radiculopathy can also help relieve associated headaches. To date, there is still a lack of large sample and prospective study to investigate the effect of anterior cervical decompression and fusion (ACDF) on CEH associated with cervical spondylosis. Methods A total of 656 patients with cervical radiculopathy and/or myelopathy were enrolled in three spinal centers. Among them, 221 patients who were diagnosed with CEH were collected in this study, and 204 completed a 1-year follow-up. The primary endpoint was headache intensity during a 12-month follow-up period measured by the numeric pain rating scale (NPRS). The secondary outcome measures included headache frequency, headache duration, and the neck disability index (NDI). Results Among all 204 patients with CEH who completed a 1-year follow-up, 166 received anterior cervical surgery (surgery group) and 38 received conservative treatment (conservative group). There were statistically significant lower NPRS in the surgical group during follow-up. Between-group differences showed that NPRS in the surgery group was significantly greater improvement at 1 month (2.8, 95% CI: 2.0, 3.6), 3 months (2.6, 95% CI: 1.8, 3.4), 6 months (2.4, 95% CI: 1.6, 3.2), and 12 months (1.5, 95% CI: 0.7, 2.4) (p < 0.05 for all). There were statistically significant lower NDI, less frequent headaches, and lower headache duration in the surgery group during follow-up (p < 0.05 for all). Conclusion This study indicates that ACDF can effectively relieve CEH associated with cervical myelopathy and/or radiculopathy.
The G protein subunit α1, CaGα1, mediates ethylene sensing of mango anthracnose pathogen Colletotrichum asianum to regulate fungal development and virulence and mediates surface sensing for spore germination

Mango is an important tropic fruit, but its production is highly restricted by anthracnose diseases. Mango anthracnose development is related to the fruit-ripening hormone ethylene, but how the pathogen senses ethylene and affects the infection remains largely unknown. In this study, mango pathogen Colletotrichum asianum strain TYC-2 was shown to sense ethylene to enhance spore germination, appressorium formation and virulence. Upon further analysis of ethylene sensing signaling, three histidine kinase genes (CaHKs) and a G-protein gene (CaGα1) were functionally characterized. Ethylene upregulated the expression of the three CaHKs but had no influence on CaGα1 expression. No function in ethylene sensing was identified for the three CaHKs. Ethylene enhanced spore germination and multiple appressorium formation of the wild-type TYC-2 but not CaGα1 mutants. TYC-2 has extremely low germination in water, where self-inhibition may play a role in ethylene sensing via CaGα1 signaling. Self-inhibitors extracted from TYC-2 inhibited spore germination of TYC-2 and CaGα1 mutants, but ethylene could not rescue the inhibition, indicating that the self-inhibition was not mediated by CaGα1 and had no interactions with ethylene. Interestingly, spore germination of CaGα1 mutants was significantly enhanced in water on hydrophobic but not hydrophilic surfaces, suggesting that CaGα1 is involved in surface sensing. In the pathogenicity assay, CaGα1 mutants showed less virulence with delayed germination and little appressorium formation at early infection on mango leaves and fruit. Transcriptome and qRT–PCR analyses identified several pathogenicity-related genes regulated by ethylene, indicating that ethylene may regulate TYC-2 virulence partially by regulating the expression of these genes.
Mulching in lowland hay meadows drives an adaptive convergence of above- and below-ground traits reducing plasticity and improving biomass: A possible tool for enhancing phytoremediation

We aimed to understand the effect of mulching (i.e., cutting and leaving the crushed biomass to decompose in situ) on above- and below-ground plant functional traits and whether this practice may be a potential tool for enhancing the phytoremediation of lowland hay meadows. To this aim, we evaluated at the community level seven years of mulching application in a PCBs and HMs soil-polluted Site of National Interest (SIN Brescia-Caffaro) through the analysis of the floristic composition and the above- and below-ground plant traits. We found that the abandonment of agricultural activities led to a marked increase in the soil organic carbon and pH, and the over-imposed mulching additionally induced a slight increase in soil nutrients. Mulching favored the establishment of a productive plant community characterized by a more conservative-resource strategy, a higher biomass development, and lower plasticity through an adaptative convergence between above- and below-ground organs. In particular, the analysis of the root depth distribution highlighted the key role of roots living in the upper soil layer (10 cm). Mulching did not show a significant effect on plant species known to be effective in terms of PCB phytoremediation. However, the mulching application appears to be a promising tool for enhancing the root web that functions as the backbone for the proliferation of microbes devoted to organic contaminants’ degradation and selects a two-fold number of plant species known to be metal-tolerant. However, besides these potential positive effects of the mulching application, favoring species with a higher biomass development, in the long term, may lead to a biodiversity reduction and thus to potential consequences also on the diversity of native species important for the phytoremediation.
An integrated approach for physical, economic, and demographic evaluation of coastal flood hazard adaptation in Santa Monica Bay, California

The increased risk of coastal flooding associated with climate-change driven sea level rise threatens to displace communities and cause substantial damage to infrastructure. Site-specific adaptation planning is necessary to mitigate the negative impacts of flooding on coastal residents and the built environment. Cost-benefit analyses used to evaluate coastal adaption strategies have traditionally focused on economic considerations, often overlooking potential demographic impacts that can directly influence vulnerability in coastal communities. Here, we present a transferable framework that couples hydrodynamic modeling of flooding driven by sea level rise and storm scenarios with site-specific building stock and census block-level demographic data. We assess the efficacy of multiple coastal adaptation strategies at reducing flooding, economic damages, and impacts to the local population. We apply this framework to evaluate a range of engineered, nature-based, and hybrid adaptation strategies for a portion of Santa Monica Bay, California. Overall, we find that dual approaches that provide protection along beaches using dunes or seawalls and along inlets using sluice gates perform best at reducing or eliminating flooding, damages, and population impacts. Adaptation strategies that include a sluice gate and partial or no protection along the beach are effective at reducing flooding around inlets but can exacerbate flooding elsewhere, leading to unintended impacts on residents. Our results also indicate trade-offs between economic and social risk-reduction priorities. The proposed framework allows for a comprehensive evaluation of coastal protection strategies across multiple objectives. Understanding how coastal adaptation strategies affect hydrodynamic, economic, and social factors at a local scale can enable more effective and equitable planning approaches.