Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Immune-Related lncRNA Signature for Prognosis and Response to Immunotherapy in Cutaneous Melanoma

Background Cutaneous melanoma is a highly malignant skin tumor, and most patients have a poor prognosis. In recent years, immunotherapy has assumed an important role in the treatment of advanced cutaneous melanoma, but only a small percentage of patients benefit from immunotherapy. A growing number of studies have demonstrated that the prognosis of patients with cutaneous melanoma is closely related to long non-coding RNA and the tumor immune microenvironment. Methods We downloaded RNA expression data and immune-related gene lists of cutaneous melanoma patients separately from The Cancer Genome Atlas database and ImmPort website and identified immune-related lncRNAs by co-expression analysis. The prognostic model was constructed by applying least absolute shrinkage and selection operator regression, and all patients were classified into high- and low-risk groups according to the risk score of the model. We evaluated the differences between the two groups in terms of survival outcomes, immune infiltration, pathway enrichment, chemotherapeutic drug sensitivity and immune checkpoint gene expression to verify the impact of lncRNA signature on clinical prognosis and immunotherapy efficacy. Results By correlation analysis and LASSO regression analysis, we constructed an immune-related lncRNA prognostic model based on five lncRNA: HLA-DQB1-AS1, MIR205HG, RP11-643G5.6, USP30-AS1 and RP11-415F23.4. Based on this model, we plotted Kaplan–Meier survival curves and time-dependent ROC curves and analyzed its ability as an independent prognostic factor for cutaneous melanoma in combination with clinicopathological features. The results showed that these lncRNA signature was an independent prognostic factor of cutaneous melanoma with favorable prognostic ability. Our results also show a higher degree of immune infiltration, higher expression of immune checkpoint-associated genes, and better outcome of immunotherapy in the low-risk group of the lncRNA signature. Conclusion The 5 immune-related lncRNA signatures constructed in our study can predict the prognosis of cutaneous melanoma and contribute to the selection of immunotherapy.
Novel Anti-Tubulin Compounds from Trigonella foenum-graecum Seeds; Insights into In-vitro and Molecular Docking Studies

Background Fenugreek, also known as Trigonella foenum-graecum L, is a natural plant that belongs to the Fabaceae family and has been known as a promising source of bioactive compounds. It has been widely used as traditional medicine since it has shown to lower blood glucose, manage cholesterol levels and further aid in the prevention and treatment of cancer. Herein, we aim to evaluate the anticancer activity of methanolic fenugreek seed extract against several cancer cell lines. Methods We sought to investigate the phytochemical classes present in multiple fenugreek seeds extracts using HPLC-DAD followed by LC/MS, predict and investigate anticancer activity using PASS online webserver, the CellTiter-Glo assay, evaluate ADME properties, and perform molecular docking for all bioactive compounds via Maestro software. Results Multiple extracts exhibited distinct phytochemical classes that demonstrated different biological activities. Fenugreek methanolic extract contains flavonoid chemical class, which showed the highest anticancer activity against the HCT8 cell line of colorectal cancer (IC50 of 8.83 μg/mL), followed by KAIMRC1 breast cancer cell line (IC50 of 35.06 μg/mL), HL60 leukemia cell line (37.80 μg/mL), MDA-MB-231 breast cancer cell line (38.51 μg/mL), and lastly, HCT116 colorectal cancer cell line with IC50 of 56.03 μg/mL. In contrast, the chloroform extract was inactive. The molecular docking study for all the bioactive compounds suggested that flavonoids F6 (−9.713 and −12.132), F7 (−10.166 and −12.411), and F11 (−10.084 and −13.516) possess the highest docking scores through SP and XP scores, respectively. Conclusion The obtained results confirm that the bioactive compounds present in fenugreek seeds exhibit anticancer activity against several cancer cells that can mediate via tubulin polymerization inhibition. Although our study has evaluated the anticancer potential of Trigonella foenum-graecum as a promising natural source for new anticancer agents, fenugreek biological activity needs further research and investigations on their mechanism of action and toxicity profile.
Effect of the hydrophobicity of fumed silica particles and the nature of oil on the structure and rheological behavior of Pickering emulsions

Abstract We studied the efficiency of Aerosil® fumed silica particles to emulsify oils with water. Pickering emulsions were prepared using 1%wt of particles displaying different degrees of hydrophobicity. 0.1 Pa.s polydimethylsiloxane and paraffin oils were used to investigate the effect of the oil polarity and a 0.02 Pa.s polydimethylsiloxane was used to check the effect of the viscosity on the structure and the rheological behavior. Macroscopic stability and emulsion composition were studied by visual observations. The emulsion structure and particle localization at the droplet interface were observed by confocal laser scanning microscopy (CLSM). Rheological properties of particle suspensions and emulsions were studied. More hydrophobic particles led to water-in-oil emulsions with a lower elastic modulus and a lower emulsified volume fraction that decreased with the oil viscosity regardless the particles hydrophobicity. CSLM shows a particles localization at the droplet interface and evidences a network of particles in the continuous phase. The emulsion features are discussed in terms of the physicochemical characteristics of the particles, their ability to disperse in the oil phase and the viscosity of the latter. In addition, we show that the rheology of the particle suspensions is a relevant indication for their affinity with the liquid phases. Graphical Abstract
Colorectal Cancer in Uganda: A 10-Year, Facility-Based, Retrospective Study

Introduction Colorectal cancer (CRC) is the most common type of gastrointestinal malignancies and the third leading cause of cancer-related deaths for both sexes worldwide. Although the burden of CRC is highest in developed countries, reports are indicating a rise in the incidence of early-onset CRC in developing countries. In this study, we aimed to determine the prevalence of CRC among patients hospitalized with lower gastrointestinal complaints at a tertiary health facility in Uganda. Methods We conducted a 10-year retrospective chart review of patients admitted to Mulago National Referral Hospital in Kampala, Uganda, between 1st January 2010 and 31st December 2020. We reviewed all charts of patients admitted to the lower gastrointestinal tract (GIT) ward. Charts with grossly missing data, pediatric patients, and those from other non-lower GIT specialties were excluded. Results Data of 1476 unique eligible patients were analyzed. Of these,138 had a diagnosis of CRC (prevalence: 9.3%, 95% confidence interval (95% CI): 6.5–11.7%). Among patients with CRC, the female:male ratio was 1:1. The most common site for CRC was the rectum (59.8%, n= 79). For the 138 participants with CRC, 44 had staging data with 72.8% (n=32) having advanced disease, that is, stage 3 or 4. Factors independently associated with CRC were age ≥50 years (adjusted odds ratio (aOR): 4.3, 95% CI: 2.6–7.1, p < 0.001), female sex (aOR: 1.8, 95% CI: 1.2 −2.8, p = 0.005), being widowed (aOR: 2.5, 95% CI: 1.3–5.0, p = 0.006), and presence of any risk factor for CRC (aOR: 5.3, 95% CI: 2.9–9.9, p < 0.001). Conclusion CRC is relatively common among patients hospitalized with lower GIT complaints, particularly among women and those with known risk factors for CRC. Awareness creation and screening programs should be instituted to allow early diagnosis of CRC in our setting.
Root and Shoot Contribution to Carbon and Nitrogen Inputs in the Topsoil Layer in No-Tillage Crop Systems under Subtropical Conditions

ABSTRACT Recycling of carbon (C) and nitrogen (N) from plants into soils is decisive for maintaining soil organic matter and soil fertility. Therefore, we quantified plant biomass and C and N in the shoots and roots from the topsoil layer for a wide range of annual crops grown under subtropical conditions. We grew 26 species, 13 main crops, and 13 cover crops, in the field in standard sowing arrangements. Root biomass was recovered from the 0.00-0.20 m soil layer at [. ]
Understanding an evolving pandemic: An analysis of the clinical time delay distributions of COVID-19 in the United Kingdom

Understanding and monitoring the epidemiological time delay dynamics of SARS-CoV-2 infection provides insights that are key to discerning changes in the phenotype of the virus, the demographics impacted, the efficacy of treatment, and the ability of the health service to manage large volumes of patients. This paper analyses how the pandemic has evolved in the United Kingdom through the temporal changes to the epidemiological time delay distributions for clinical outcomes. Using the most complete clinical data presently available, we have analysed, through a doubly interval censored Bayesian modelling approach, the time from infection to a clinical outcome. Across the pandemic, for the periods that were defined as epidemiologically distinct, the modelled mean ranges from 8.0 to 9.7 days for infection to hospitalisation, 10.3 to 15.0 days for hospitalisation to death, and 17.4 to 24.7 days for infection to death. The time delay from infection to hospitalisation has increased since the first wave of the pandemic. A marked decrease was observed in the time from hospitalisation to death and infection to death at times of high incidence when hospitals and ICUs were under the most pressure. There is a clear relationship between age groups that is indicative of the youngest and oldest demographics having the shortest time delay distributions before a clinical outcome. A statistically significant difference was found between genders for the time delay from infection to hospitalisation, which was not found for hospitalisation to death. The results by age group indicate that younger demographics that require clinical intervention for SARS-CoV-2 infection are more likely to require earlier hospitalisation that leads to a shorter time to death, which is suggestive of the largely more vulnerable nature of these individuals that succumb to infection. The distinction found between genders for exposure to hospitalisation is revealing of gender healthcare seeking behaviours.
Postprandial plasma glucose excursion is associated with an atherogenic lipid profile in individuals with type 2 diabetes mellitus: A cross-sectional study

Coronary heart disease (CHD) is a prevalent complication of type 2 diabetes mellitus (T2DM). The atherogenic low-density lipoprotein (LDL) cholesterol is an established risk factor of cardiovascular disease, and evidence also suggests that postprandial plasma glucose (PPG) levels closely delineate CHD mortality in diabetes. The investigators hypothesized that postprandial plasma glucose excursion (PPGE), defined as the difference between 2-hour PPG and fasting plasma glucose (FPG), may be associated with plasma LDL cholesterol levels in patients with T2DM. This study enrolled diabetic participants for whom FPG and lipid profile were sampled after a 12-hour fast, followed by PPG sampling two hours after consuming a standard meal with 75 grams of carbohydrates. The study enrolled 379 participants who were divided into PPGE tertiles according to the difference between their 2-hour PPG and FPG. Participants in the highest PPGE tertile had considerably greater plasma LDL cholesterol levels than patients in the lowest tertile (126.7 mg/dL vs. 99.5 mg/dL, P <0.001). Linear regression analysis also demonstrated that the PPGE was positively correlated with plasma LDL cholesterol levels (β coefficient: 0.165, P < 0.001). Postprandial glucose excursion positively correlated with plasma LDL cholesterol levels in individuals with T2DM. Participants with raised PPGE harbored greater LDL cholesterol levels than those with lower postprandial glucose fluctuations. Therefore, postprandial glucose excursion is associated with an atherogenic lipid profile and may be a modifiable risk factor of diabetic CHD.
Internal Medicine Residents’ Perceptions of the Learning Environment of a Residency Training Program in Ethiopia: a Mixed Methods Study

Introduction The learning environment is an important determinant of the quality of medical education. Having a good learning climate leads to improved learning process, satisfaction with education, and helps achieve the goals of the curriculum. Assessment of the quality of learning environment helps with the identification of areas that need improvement. The aim of this study was to assess the learning environment of internal medicine training program in Ethiopia. Methods A mixed methods study using a cross-sectional survey using Postgraduate Hospital Educational Environment Measure and a qualitative study using a focus group discussion was done on internal medicine residents from December 2020 to May 2021. Comparison of quantitative data was done using Mann–Whitney U-Test and Kruskal–Wallis H-test. P-value <0.05 was considered statistically significant. Results A total of 100 residents participated in the study. The overall total mean score of the responses of the participants was 70.87 (±19.8) with mean perceptions of role autonomy, perceptions of teaching and perceptions of social support of 25.9 (±7.1), 27.1 (10.2) and 17.9 (±5.1), respectively. These values suggest the presence of plenty of problems in the program. Higher mean scores were reported by males and by earlier years of residency. Ten residents participated in the focus group discussion. Four recurring themes that negatively affect learning environment were identified and included excessive workload, inadequate teaching activity, non-conducive hospital physical environment and lack of diagnostic and therapeutic modalities. Conclusion The internal medicine residency learning environment has many challenges that need immediate attention and follow-up.
On the Relationship between Heterophily and Robustness of Graph Neural Networks

Empirical studies on the robustness of graph neural networks (GNNs) have suggested a relation between the vulnerabilities of GNNs to adversarial attacks and the increased presence of heterophily in perturbed graphs (where edges tend to connect nodes with dissimilar features and labels). In this work, we formalize the relation between heterophily and robustness, bridging two topics previously investigated by separate lines of research. We theoretically and empirically show that for graphs exhibiting homophily (low heterophily), impactful structural attacks always lead to increased levels of heterophily, while for graph with heterophily the change in the homophily level depends on the node degrees. By leveraging these insights, we deduce that a design principle identiﬁed to signiﬁcantly improve predictive performance under heterophily—separate aggregators for ego-and neighbor-embeddings—can also inherently offer increased robustness to GNNs. Our extensive empirical analysis shows that GNNs adopting this design alone can achieve signiﬁcantly improved empirical and certiﬁable robustness compared to the best-performing unvaccinated model. Furthermore, models with this design can be readily combined with explicit defense mechanisms to yield improved robustness with up to 18.33% increase in performance under attacks compared to the best-performing vaccinated model.
Learning Equivariances and Partial Equivariances from Data

Group equivariant Convolutional Neural Networks (G-CNNs) constrain features to respect the chosen symmetries, and lead to better generalization when these symmetries appear in the data. However, if the chosen symmetries are not present, group equivariant architectures lead to overly constrained models and worse performance. Frequently, the distribution of the data can be
A nonlinear, non-dispersive energy balance for surfzone waves: infragravity wave dynamics on a sloping beach

Abstract A fully nonlinear non-dispersive energy balance for surfzone waves is derived based on the nonlinear shallow water equations to study the nearshore dynamics of infragravity (IG) waves. Based on simulations of waves on a relatively moderate and mild beach slope with a non-hydrostatic wave-flow model (SWASH), the new theory shows that spatial gradients in IG energy flux are nearly completely balanced by the combined effect of bottom stresses and predominantly nonlinear triad interactions. The new balance confirms many features of existing weakly nonlinear theories, and yields an improved description in the inner surfzone where waves become highly nonlinear. A gain of IG energy flux throughout the shoaling and outer surfzones is driven by triad interactions between IG waves and pairs of sea-swell (SS) waves. The IG energy flux decreased in the inner surfzone, primarily through an energy cascade to the swell-band and superharmonic frequencies where wave energy is ultimately dissipated. Dissipation by bottom friction was weak on both slopes. The IG wave breaking, characterized by triads between three IG or two IG waves and one SS wave, was significant only deep inside the surfzone of the mild slope. Even though IG waves broke on the mild slope, nonlinear interactions between IG waves and pairs of SS waves were responsible for at least half of the net IG flux loss.
Stable marriage in the eyes of the law∗

We present a framework to study household consumption under the assumption of marital stability in the presence of divorce legislation. Using this model, we derive nonparametric conditions that allow us to identify the intrahousehold consumption allocation. We study two integral dimensions of divorce legislation. First, we consider a regime governing divorce itself. The legislation either allows partners to divorce unilaterally at will or requires the mutual consent of both partners to dissolve the marriage. Second, for couples with children, we consider the implications of sole and joint custody arrangements for marital stability. Under sole custody, children reside with the custodian parent, whereas under joint custody, both parents equally share the responsibilities of children after the divorce. We illustrate the importance of these legislative aspects of divorce and marriage in the empirical identification of intrahousehold allocations through an application to household data from Russia. Our results suggest that a model incorporating divorce legislation better fits the data than a benchmark model without divorce legislation, especially for couples with children. Next, we show that ignoring the law-based implications results in notably different estimates of intrahousehold resource shares. For example, we find that a model without divorce legislation significantly underestimates the mother’s share of private consumption. Bias in the estimates of intrahousehold allocations can lead to misleading policy implications. We illustrate this by conducting a poverty analysis at the level of individual household members.
LARNet: Latent Action Representation for Human Action Synthesis

We present LARNet, a novel end-to-end approach for generating human action videos. A joint generative modeling of appearance and dynamics to synthesize a video is very challenging and therefore recent works in video synthesis have proposed to decompose these two factors. However, these methods require a driving video to model the video dynamics. In this work, we propose a generative approach instead, which explicitly learns action dynamics in latent space avoiding the need of a driving video during inference. The generated action dynamics is integrated with the appearance using a recurrent hierarchical structure which induces motion at different scales to focus on both coarse as well as fine level action details. In addition, we propose a novel mix-adversarial loss function which aims at improving the temporal coherency of synthesized videos. We evaluate the proposed approach on four real-world human action datasets demonstrating the effectiveness of the proposed approach in generating human actions. Code available at https://github.com/aayushjr/larnet.
Local Existence and Uniqueness of Spatially Quasi-Periodic Solutions to the Generalized KdV Equation

In this paper, we study the existence and uniqueness of spatially quasi-periodic solutions to the generalized KdV equation (gKdV for short) on the real line with quasi-periodic initial data whose Fourier coefficients are exponentially decaying. In order to solve for the Fourier coefficients of the solution, we first reduce the nonlinear dispersive partial differential equation to a nonlinear infinite system of coupled ordinary differential equations, and then construct the Picard sequence to approximate them. However, we meet, and have to deal with, the difficulty of studying {\bf the higher dimensional discrete convolution operation for several functions}: \[\underbrace{c\times\cdots\times c}_{\mathfrak p~\text{times}}~(\text{total distance}):=\sum_{\substack{\clubsuit_1,\cdots,\clubsuit_{\mathfrak p}\in\mathbb Z^\nu\\ \clubsuit_1+\cdots+\clubsuit_{\mathfrak p}=~\text{total distance}}}\prod_{j=1}^{\mathfrak p}c(\clubsuit_j). \] In order to overcome it, we apply a combinatorial method to reformulate the Picard sequence as a tree. Based on this form, we prove that the Picard sequence is exponentially decaying and fundamental ({\color{red}i.e., a} Cauchy sequence). We first give a detailed discussion of the proof of the existence and uniqueness result in the case $\mathfrak p=3$. Next, we prove existence and uniqueness in the general case $\mathfrak p\geq 2$, which then covers the remaining cases $\mathfrak p\geq 4$. As a byproduct, we recover the local result from \cite{damanik16}. We exhibit the most important combinatorial index $\sigma$ and obtain a relationship with other indices, which is essential to our proofs in the case of general $\mathfrak p$.
Pacta sunt servanda: legal contracts in Stipula

There is a growing interest in running legal contracts on digital systems, at the same time, it is important to understand to what extent software contracts may capture legal content. We then undertake a foundational study of legal contracts and we distill four main features: agreement, permissions, violations and obligations. We therefore design Stipula, a domain specific language that assists lawyers in programming legal contracts through specific patterns. The language is based on a small set of abstractions that correspond to common patterns in legal contracts, and that are amenable to be executed either on centralized or on distributed systems. Stipula comes with a formal semantics and an observational equivalence, that provide for a clear account of the contracts' behaviour. The expressive power of the language is illustrated by a set of examples that correspond to template contracts that are often used in practice.
Transductive Robust Learning Guarantees

We study the problem of adversarially robust learning in the transductive setting. For classes $\mathcal{H}$ of bounded VC dimension, we propose a simple transductive learner that when presented with a set of labeled training examples and a set of unlabeled test examples (both sets possibly adversarially perturbed), it correctly labels the test examples with a robust error rate that is linear in the VC dimension and is adaptive to the complexity of the perturbation set. This result provides an exponential improvement in dependence on VC dimension over the best known upper bound on the robust error in the inductive setting, at the expense of competing with a more restrictive notion of optimal robust error.