Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Environmental Variables in Waste Stabilization Ponds' Morphodynamics

In management of helminth infections and transmission, the correct prediction of sludge accumulation patterns in waste stabilization ponds (WSP) is important as sedimented eggs are associated with sludge depth. However, sedimentation in WSP is complicated by the non-stationary nature of the inputs and environmental factors such as weather variables, that are mostly site specific. This paper investigates sludge accumulation patterns in the Buguruni WSP (in Dar es Salaam, Tanzania) and the role that wind and increased run-off during rainy season play. Sludge depths were measured twice; in January 2017 and January 2018. Higher sludge depths were observed close to the inlet, indicating that more helminth eggs may be recovered in the sludge around this area. A sedimentation model set in Delft3D successfully reproduced the sludge accumulation pattern near the inlet, with wind and inflow characteristics as the major driving factors. The pond inlet receives more solids and water during the rain season as a result of defective pipes and manholes, and simulations show that this has significant impacts on sludge accumulation. Improved sludge depth measurement and wind and discharge data will improve modelled sludge accumulation patterns to capture those away from the inlet. Our research has shown that neglecting maintenance of the pond, as well as the sewer system has potential severe health and environmental effects, impacting communities downstream of the WSP. This research also shows the important role that numerical modelling can play in sustainable management of WSP.
AI-Assisted Forward Modeling of Biological Structures

The rise of machine learning and deep learning technologies have allowed researchers to automate image classification. We describe a method that incorporates automated image classification and principal component analysis to evaluate computational models of biological structures. We use a computational model of the kinetochore to demonstrate our artificial-intelligence (AI)-assisted modeling method. The kinetochore is a large protein complex that connects chromosomes to the mitotic spindle to facilitate proper cell division. The kinetochore can be divided into two regions: the inner kinetochore, including proteins that interact with DNA; and the outer kinetochore, comprised of microtubule-binding proteins. These two kinetochore regions have been shown to have different distributions during metaphase in live budding yeast and therefore act as a test case for our forward modeling technique. We find that a simple convolutional neural net (CNN) can correctly classify fluorescent images of inner and outer kinetochore proteins and show a CNN trained on simulated, fluorescent images can detect difference in experimental images. A polymer model of the ribosomal DNA locus serves as a second test for the method. The nucleolus surrounds the ribosomal DNA locus and appears amorphous in live-cell, fluorescent microscopy experiments in budding yeast, making detection of morphological changes challenging. We show a simple CNN can detect subtle differences in simulated images of the ribosomal DNA locus, demonstrating our CNN-based classification technique can be used on a variety of biological structures.
Understanding Personal Carers' Experiences of Caring for Older People in Pain

Pain is a complex phenomenon that can be challenging for staff working in residential aged care facilities (RACFs) (Fisher et al., 2002; Twycross, 2-002). A high prevalence of pain reported by older individuals has been reported and suggests that further study in this area is warranted (Higgins, Madjar & Walton, 2004). Research suggests that a significant barrier to effective pain management in the elderly is the provision of primary care by care staff who have little or no education about pain, pain assessment or pain management (Allcock, McGarry & Elkan, 2002). Studies have identified personal carers as being in a unique position to improve pain management, because of their working relationship with residents (Ferrell, 1996; Horgas & Dunn, 2001). However, there is a lack ofliterature which specifically examines personal carers' perspectives of providing care to residents in pain on a
Heat Stress Challenges in Marathon vs. Ultra-Endurance Running

Several studies have investigated the effect of hot and humid ambient conditions on running exercise up to the marathon. However, studies on exercise longer than marathon are sparse. Events exceeding 6 h can be defined as ultra-endurance and have variable characteristics (e.g., distance, elevation profile, technical difficulty, altitude, night running) making hazardous the transposition of the current knowledge obtained in marathon to ultra-endurance running. Thus, the aim of this manuscript was to discuss the potential differences between marathon and ultra-endurance running in terms of heat stress challenges. The high running intensity (especially for the fastest runners), the urban context with high albedo effect materials, and the hot self-generated microclimate in mass-participation events (especially for the average to slow runners) are specific risk factors associated with marathon running in hot environments. Uphill running/walking (sometimes with poles), exotic destination with long-haul travel, desert environment and the necessity to sustain thermoregulatory and sweating responses for several days are risk factors more specific to ultra-endurance running. These differences call for specific research on the effect of hot ambient conditions in ultra-endurance disciplines to create appropriate recommendations.
Exogenous Nitric Oxide and Phosphorus Stress Affect the Mycorrhization, Plant Growth, and Associated Microbes of Carya illinoinensis Seedlings Colonized by Tuber indicum

In the artificial cultivation of truffles, ectomycorrhizal colonization level, host plant quality, and the associated microbes in the rhizosphere soil are vitally important. To explore the effects of nitric oxide (NO) and phosphorus (P) stress on the early symbiosis of truffles and host plants, different concentrations of exogenous NO donor sodium nitroprusside (SNP) and P were applied to Carya illinoinensis seedlings inoculated with the Chinese black truffle (Tuber indicum). The growth of T. indicum-mycorrhized seedlings and their mycorrhizal colonization rate were investigated. Additionally, the denitrifying bacterial community harboring NO reductase (norB) genes and the fungal community in the rhizosphere of the host were analyzed by high-throughput sequencing. The results showed that the colonization rate of T. indicum was significantly influenced by SNP treatments and P stress, with the highest level being obtained when the SNP was 100 μmol/L under low P stress (5 μmol/L). Treatment with 100 μmol/L SNP alone also increased the colonization rate of T. indicum and had positive effects on the plant height, stem circumference, biomass, root-shoot ratio and root POD activity of the seedlings at different times after inoculation. Under low P stress, the 100 μmol/L SNP increased the richness of the norB-type denitrifying bacterial community. Interestingly, the diversity and richness of norB-type denitrifying bacteria were significantly positively correlated with the colonization rate of T. indicum. SNP treatments under low P stress altered the abundance of some dominant taxa such as Alphaproteobacteria, Gammaproteobacteria, Pseudomonas, Ensifer, and Sulfitobacter. Evaluation of the fungal community in the rhizosphere revealed that 100 μmol/L SNP treatment alone had no noticeable effect on their richness and diversity, but it did shape the abundance of some fungi. Buellia, Podospora, Phaeoisaria, Ascotaiwania, and Lophiostoma were more abundant following exogenous NO application, while the abundance of Acremonium, Monographella, and Penicillium were decreased. Network analysis indicated that T. indicum was positively and negatively correlated with some fungal genera when treated with 100 μmol/L SNP. Overall, these results revealed how exogenous NO and P stress influence the symbiosis of truffles and host plants, and indicate that application of SNP treatments has the potential for ectomycorrhizal synthesis and truffle cultivation.
A Novel Fully-Human Potency-Matched Dual Cytokine-Antibody Fusion Protein Targets Carbonic Anhydrase IX in Renal Cell Carcinomas

Certain cytokines synergize in activating anti-cancer immunity at the site of disease and it may be desirable to generate biopharmaceutical agents, capable of simultaneous delivery of cytokine pairs to the tumor. In this article, we have described the cloning, expression and characterization of IL2-XE114-TNFmut, a dual-cytokine biopharmaceutical featuring the sequential fusion of interleukin-2 (IL2) with the XE114 antibody in scFv format and a tumor necrosis factor mutant (TNFmut). The fusion protein recognized the cognate antigen (carbonic anhydrase IX, a marker of hypoxia and of renal cell carcinoma) with high affinity and specificity. IL2-XE114-TNFmut formed a stable non-covalent homotrimeric structure, displayed cytokine activity in in vitro tests and preferentially localized to solid tumors in vivo. The product exhibited a partial growth inhibition of murine CT26 tumors transfected for carbonic anhydrase IX. When administered to Cynomolgus monkey as intravenous injection, IL2-XE114-TNFmut showed the expected plasma concentration of ~1500 ng/ml at early time points, indicating the absence of any in vivo trapping events, and a half-life of ~2 hours. IL2-XE114-TNFmut may thus be considered as a promising biopharmaceutical for the treatment of metastatic clear-cell renal cell carcinoma, since these tumors are known to be sensitive to IL2 and to TNF. Contribution to the field There is a growing interest in the antibody-based targeted delivery of pro-inflammatory cytokines for tumor therapy, which may be complementary or alternative to immune checkpoint inhibitors for immunotherapeutic applications. In this article, we have described a novel fusion protein, featuring antibody moieties specific to carbonic anhydrase IX, as well as interleukin-2 and tumor necrosis factor as pro-inflammatory cytokines, which combines the ability to recognize a tumor-associated antigen on the surface of renal cell carcinomas with the simultaneous display of two potent therapeutic payloads. The newly developed product (termed IL2-XE114-TNFmut) exhibited favorable biochemical characteristics, the ability to preferentially localize at the tumor site, a cancer growth inhibition activity and a suitable pharmacokinetic profile in Cynomolgus monkey. IL2-XE114-TNFmut may therefore represent an attractive candidate for the immunotherapy of renal cell carcinoma.
Iterative Learning Control for Motion Trajectory Tracking of a Circular Soft Crawling Robot

Soft robots have recently received much attention with their infinite degrees of freedoms and continuously deformable structures, which allow them to adapt well to the unstructured environment. A new type of soft actuator, namely, dielectric elastomer actuator (DEA) which has several excellent properties such as large deformation and high energy density is investigated in this study. Furthermore, a DEA-based soft robot is designed and developed. Due to the difficulty of accurate modeling caused by nonlinear electromechanical coupling and viscoelasticity, the iterative learning control (ILC) method is employed for the motion trajectory tracking with an uncertain model of the DEA. A D2 type ILC algorithm is proposed for the task. Furthermore, a knowledge-based model framework with kinematic analysis is explored to prove the convergence of the proposed ILC. Finally, both simulations and experiments are conducted to demonstrate the effectiveness of the ILC, which results show that excellent tracking performance can be achieved by the soft crawling robot.
Executive Function in Autism Spectrum Disorder: History, Theoretical Models, Empirical Findings, and Potential as an Endophenotype

This review presents an outline of executive function (EF) and its application to autism spectrum disorder (ASD). The development of the EF construct, theoretical models of EF, and limitations in the study of EF are outlined. The potential of EF as a cognitive endophenotype for ASD is reviewed, and the Research Domain Criteria (RDoC) framework is discussed for researching EF in ASD given the multifaceted factors that influence EF performance. A number of executive-focused cognitive models have been proposed to explain the symptom clusters observed in ASD. Empirical studies suggest a broad impairment in EF, although there is significant inter-individual variability in EF performance. The observed heterogeneity of EF performance is considered a limiting factor in establishing EF as a cognitive endophenotype in ASD. We propose, however, that this variability in EF performance presents an opportunity for subtyping within the spectrum that can contribute to targeted diagnostic and intervention strategies. Enhanced understanding of the neurobiological basis that underpins EF performance, such as the excitation/inhibition hypothesis, will likely be important. Application of the RDoC framework could provide clarity on the nature of EF impairment in ASD with potential for greater understanding of, and improved interventions for, this disorder.
Reactivation of the Unconditioned Stimulus Inhibits the Return of Fear Independent of Cortisol

Reconsolidation is the post-retrieval stabilization of memories, a time-limited process during which reactivated (i.e., retrieved) memories can be updated with new information, become stronger or weaker, depending on the specific treatment. We have previously shown that the stress hormone cortisol has an enhancing effect on the reconsolidation of fear memories in men. This effect was specific, i.e., limited to the conditioned stimulus (CS) that was reactivated, and did not generalize to other previously reinforced, but not reactivated CS. Based on these results, we suggested that cortisol plays a critical role in the continuous strengthening of reactivated emotional memories, contributing to their persistence and robustness. In the current study, we aimed to achieve a more generalized reconsolidation enhancement using an alternative reactivation method, i.e., by a low-intensity unconditioned stimulus (UCS) presentation instead of the more common unreinforced CS presentation. In previous studies, UCS reactivation was shown to lead to a more generalized reconsolidation effect. Therefore, we hypothesized that the combination of cortisol treatment and UCS reactivation would lead to an enhanced fear memory reconsolidation, which would generalize from previously reinforced CS to stimuli that resemble it. We tested 75 men in a 3-day fear conditioning paradigm: fear acquisition training on day 1; UCS reactivation/no reactivation and pharmacological treatment (20 mg hydrocortisone/placebo) on day 2; extinction training, reinstatement and test (of original and modified stimuli) on day 3. In contrast to our hypothesis, UCS reactivation prevented the return of fear [observed in skin conductance responses (SCR)] regardless of the pharmacological manipulation: while reinstatement to the original CS was found in the no-reactivation group, both reactivation groups (cortisol and placebo) showed no reinstatement. As the only methodological difference between our previous study and the current one was the reactivation method, we focus on UCS reactivation as the main explanation for these unexpected findings. We suggest that the robust prediction error generated by the UCS reactivation method (as opposed to CS reactivation), combined with the lower UCS intensity, has by itself weakened the emotional value of the UCS, thus preventing the return of fear to the CS that was associated with it. We call for future research to support these findings and to examine the potential of this reactivation method, or variations thereof, as a tool for therapeutic use.
Fast, scalable and accurate finite-element based ab initio calculations using mixed precision computing: 46 PFLOPS simulation of a metallic dislocation system

Accurate large-scale first principles calculations based on density functional theory (DFT) in metallic systems are prohibitively expensive due to the asymptotic cubic scaling computational complexity with number of electrons. Using algorithmic advances in employing finite-element discretization for DFT (DFT-FE) in conjunction with efficient computational methodologies and mixed precision strategies, we delay the onset of this cubic scaling by significantly reducing the computational prefactor while increasing the arithmetic intensity and lowering the data movement costs. This has enabled fast, accurate and massively parallel DFT calculations on large-scale metallic systems on both many-core and heterogeneous architectures, with time-to-solution being an order of magnitude faster than state-of-the-art plane-wave DFT codes. We demonstrate an unprecedented sustained performance of 46 PFLOPS (27.8% peak FP64 performance) on a dislocation system in Magnesium containing 105,080 electrons using 3,800 GPU nodes of Summit supercomputer, which is the highest performance to-date among DFT codes.
Nomogram to Predict Internal Mammary Lymph Nodes Metastasis in Patients With Breast Cancer

Background: Numerous studies have showed that internal mammary lymph node (IMLN) metastasis is an important adverse prognostic factor in patients with breast cancer (BC), however, there are no available prediction model for the preoperative diagnosis of IMLN metastasis. Methods: Data from 102 breast cancer patients treated with IMLN operation were used to establish and calibrate a nomogram for IMLN status based on multivariate logistic regression. Prediction performance of this model was further validated with a second set of 50 patients with BC. Discrimination of the predict model was assessed by the C-index, and calibration assessed by calibration plots. Moreover, we conducted the decision curve analysis (DCA) to evaluate the clinical value of the nomogram. Finally, the survival status of patients in different risk groups based on nomogram were also compared. Results: The final multivariate regression model included tumor location, lymph vascular invasion (LVI), and pathological axillary lymph node stage (pALN stage). A nomogram was developed as a graphical representation of the model and had good calibration and discrimination in both sets (with C-index of 0.86 and 0.83 for the training and validation set, respectively). Moreover, the DCA showed the clinical usefulness of our constructed nomogram. False negative (FN) in low risk group classified by nomogram (FN-LR-nomogram) did not significantly impact adjuvant treatment decision making, and more importantly, patients with FN-LR-nomogram had recurrence-free survival equivalent to patients with pathologically ture negative in low risk group classified by nomogram (TN-LR-nomogram). Conclusions: As a non-invasive prediction tool, our nomogram shows favorable predictive accuracy for IMLN metastasis in patients with BC and can serve as a basis to integrate future molecular markers for its clinical application.
Integrating the Ribonucleic Acid Sequencing Data From Various Studies for Exploring the Multiple Sclerosis-Related Long Noncoding Ribonucleic Acids and Their Functions

Multiple sclerosis (MS) is a chronic fatal central nervous system (CNS) disease involving in complex immunity dysfunction. Recently, long noncoding RNAs (lncRNAs) were discovered as the important regulatory factors for the pathogenesis of MS. However, these findings often cannot be repeated and confirmed by the subsequent studies. We considered that the small-scale samples or the heterogeneity among various tissues may result in the divergence of the results. Currently, RNA-seq has become a powerful approach to quantify the abundances of lncRNA transcripts. Therefore, we comprehensively collected the MS-related RNA-seq data from a variety of previous studies, and integrated these data using an expression-based meta-analysis to identify the differentially expressed lncRNA between MS patients and controls in whole samples and subgroups. Then, we performed the Jensen-Shannon (JS) divergence and cluster analysis to explore the heterogeneity and expression specificity among various tissues. Finally, we investigated the potential function of identified lncRNAs for MS using weighted gene co-expression network analysis (WGCNA) and gene set enrichment analysis (GSEA), and 5,420 MS-related lncRNAs specifically expressed in the brain tissue were identified. The subgroup analysis found a small heterogeneity of the lncRNA expression profiles between brain and blood tissues. The results of WGCNA and GSEA showed that a potential important function of lncRNAs in MS may be involved in the regulation of ribonucleoproteins and tumor necrosis factor cytokines receptors. In summary, this study provided a strategy to explore disease-related lncRNAs on genome-wide scale, and our findings will be benefit to improve the understanding of MS pathogenesis.
Canine Primary Intracranial Cancer: A Clinicopathologic and Comparative Review of Glioma, Meningioma, and Choroid Plexus Tumors

In the dog, primary intracranial neoplasia represents ~2–5% of all cancers and is especially common in certain breeds including English and French bulldogs and Boxers. The most common types of primary intracranial cancer in the dog are meningioma, glioma, and choroid plexus tumors, generally occurring in middle aged to older dogs. Much work has recently been done to understand the characteristic imaging and clinicopathologic features of these tumors. The gross and histologic landscape of these tumors in the dog compare favorably to their human counterparts with many similarities noted in histologic patterns, subtype, and grades. Data informing the underlying molecular abnormalities in the canine tumors have only begun to be unraveled, but reveal similar pathways are mutated between canine and human primary intracranial neoplasia. This review will provide an overview of the clinicopathologic features of the three most common forms of primary intracranial cancer in the dog, delve into the comparative aspects between the dog and human neoplasms, and provide an introduction to current standard of care while also highlighting novel, experimental treatments that may help bridge the gap between canine and human cancer therapies.