Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of turbulent transport and dissipation closures in second-order modeling

Abstract We show that the turbulence statistics from our (96)3 large-eddy-simulation (LES) studies of a convective boundary layer are in excellent agreement with those from the Deardorff–Willis laboratory convection tank. Using these LES data, we evaluate contemporary parameterizations for turbulent transport and dissipation in second-order closure models of the convective boundary layer. The gradient-diffusion parameterization for turbulent transport fares poorly, due in large part to the direct influence of buoyancy. This leads to poor predictions of the vertical profiles of some turbulence statistics. We also find that the characteristic length scales for the mechanical and thermal dissipation rates typically used in second-order closure models are a factor of 2–3 too small; this leads to underpredictions of turbulence kinetic energy levels. Finally, we find that the flux and variance budgets for conservative scalars are substantially different in top-down and bottom-up diffusion. In order to reproduce.
Synergistic impact of nanomaterials and plant probiotics in agriculture: A tale of two-way strategy for long-term sustainability

Modern agriculture is primarily focused on the massive production of cereals and other food-based crops in a sustainable manner in order to fulfill the food demands of an ever-increasing global population. However, intensive agricultural practices, rampant use of agrochemicals, and other environmental factors result in soil fertility degradation, environmental pollution, disruption of soil biodiversity, pest resistance, and a decline in crop yields. Thus, experts are shifting their focus to other eco-friendly and safer methods of fertilization in order to ensure agricultural sustainability. Indeed, the importance of plant growth-promoting microorganisms, also determined as “plant probiotics (PPs),” has gained widespread recognition, and their usage as biofertilizers is being actively promoted as a means of mitigating the harmful effects of agrochemicals. As bio-elicitors, PPs promote plant growth and colonize soil or plant tissues when administered in soil, seeds, or plant surface and are used as an alternative means to avoid heavy use of agrochemicals. In the past few years, the use of nanotechnology has also brought a revolution in agriculture due to the application of various nanomaterials (NMs) or nano-based fertilizers to increase crop productivity. Given the beneficial properties of PPs and NMs, these two can be used in tandem to maximize benefits. However, the use of combinations of NMs and PPs, or their synergistic use, is in its infancy but has exhibited better crop-modulating effects in terms of improvement in crop productivity, mitigation of environmental stress (drought, salinity, etc.), restoration of soil fertility, and strengthening of the bioeconomy. In addition, a proper assessment of nanomaterials is necessary before their application, and a safer dose of NMs should be applicable without showing any toxic impact on the environment and soil microbial communities. The combo of NMs and PPs can also be encapsulated within a suitable carrier, and this method aids in the controlled and targeted delivery of entrapped components and also increases the shelf life of PPs. However, this review highlights the functional annotation of the combined impact of NMs and PPs on sustainable agricultural production in an eco-friendly manner.
Sex and gender role differences on stress, depression, and anxiety symptoms in response to the COVID-19 pandemic over time

Introduction Stress, depression, and anxiety symptoms have been reported during the pandemic, with important inter-individual differences. Past cross-sectional studies have found that sex and gender roles may contribute to the modulation of one's vulnerability to develop such symptoms. This longitudinal study aimed to examine the interaction of sex and psychological gender roles on stress, depression, and anxiety symptoms in adults during the COVID-19 pandemic. Methods Following the confinement measures in March 2020 in Montreal, stress, depression, and anxiety symptoms were assessed every 3 months (from June 2020 to March 2021) with the Depression, Anxiety and Stress Scale among 103 females and 50 males. Femininity and masculinity scores were assessed with the Bem Sex Role Inventory before the pandemic and were added as predictors along with time, sex, and the interactions between these variables using linear mixed models. Results We observed similar levels of depressive symptoms between males and females, but higher levels of stress and anxious symptoms in females. No effects of sex and gender roles on depressive symptoms were found. For stress and anxiety, an interaction between time, femininity, and sex was found. At the beginning of the pandemic, females with high femininity had more stress symptoms than males with high femininity, whereas females with low femininity had more anxiety symptoms 1 year after the confinement measures compared to males with low femininity. Discussion These findings suggest that sex differences and psychological gender roles contribute to heterogeneous patterns of stress and anxiety symptoms over time in response to the COVID-19 pandemic.
Multiparametric MRI radiomics fusion for predicting the response and shrinkage pattern to neoadjuvant chemotherapy in breast cancer

Purpose During neoadjuvant chemotherapy (NACT), breast tumor morphological and vascular characteristics are usually changed. This study aimed to evaluate the tumor shrinkage pattern and response to NACT by preoperative multiparametric magnetic resonance imaging (MRI), including dynamic contrast-enhanced MRI (DCE-MRI), diffuse weighted imaging (DWI) and T2 weighted imaging (T2WI). Method In this retrospective analysis, female patients with unilateral unifocal primary breast cancer were included for predicting tumor pathologic/clinical response to NACT (n=216, development set, n=151 and validation set, n=65) and for discriminating the tumor concentric shrinkage (CS) pattern from the others (n=193; development set, n=135 and validation set, n=58). Radiomic features (n=102) of first-order statistical, morphological and textural features were calculated on tumors from the multiparametric MRI. Single- and multiparametric image-based features were assessed separately and were further combined to feed into a random forest-based predictive model. The predictive model was trained in the testing set and assessed on the testing dataset with an area under the curve (AUC). Molecular subtype information and radiomic features were fused to enhance the predictive performance. Results The DCE-MRI-based model showed higher performance (AUCs of 0.919, 0.830 and 0.825 for tumor pathologic response, clinical response and tumor shrinkage patterns, respectively) than either the T2WI or the ADC image-based model. An increased prediction performance was achieved by a model with multiparametric MRI radiomic feature fusion. Conclusions All these results demonstrated that multiparametric MRI features and their information fusion could be of important clinical value for the preoperative prediction of treatment response and shrinkage pattern.
Integrating machine learning and single-cell trajectories to analyze T-cell exhaustion to predict prognosis and immunotherapy in colon cancer patients

Introduction The incidence of colon adenocarcinoma (COAD) has recently increased, and patients with advanced COAD have a poor prognosis due to treatment resistance. Combining conventional treatment with targeted therapy and immunotherapy has shown unexpectedly positive results in improving the prognosis of patients with COAD. More study is needed to determine the prognosis for patients with COAD and establish the appropriate course of treatment. Methods This study aimed to explore the trajectory of T-cell exhaustion in COAD to predict the overall survival and treatment outcome of COAD patients. Clinical data were derived from the TCGA-COAD cohort through "UCSC", as well as the whole genome data. Prognostic genes driving T-cell trajectory differentiation were identified on the basis of single-cell trajectories and univariate Cox regression. Subsequently, T-cell exhaustion score (TES) was created by iterative LASSO regression. The potential biological logic associated with TES was explored through functional analysis, immune microenvironment assessment, immunotherapy response prediction, and in vitro experiments. Results Data showed that patients with significant TES had fewer favorable outcomes. Expression, proliferation, and invasion of COAD cells treated with TXK siRNA were also examined by cellular experiments. Both univariate and multivariate Cox regression indicated that TES was an independent prognostic factor in patients with COAD; in addition, subgroup analysis supported this finding. Functional assay revealed that immune response and cytotoxicity pathways are associated with TES, as the subgroup with low TES has an active immune microenvironment. Furthermore, patients with low TES responded better to chemotherapy and immunotherapy. Conclusion In this study, we systematically explored the T-cell exhaustion trajectory in COAD and developed a TES model to assess prognosis and provide guidelines for the treatment decision. This discovery gave rise to a fresh concept for novel therapeutic procedures for the clinical treatment of COAD.
Risk factors and characteristics influencing humoral response to COVID-19 vaccination in patients after allogeneic stem cell transplantation

Introduction Vaccination against severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) is approved and recommended for immunocompromised patients such as patients after allogeneic stem cell transplantation (allo-SCT). Since infections represent a relevant cause of transplant related mortality we analyzed the advent of immunization to SARS-CoV-2 vaccination in a bicentric population of allogeneic transplanted patients. Methods We retrospectively analyzed data of allo-SCT recipients in two German transplantation centers for safety and serologic response after two and three SARS-CoV-2 vaccinations. Patients received mRNA vaccines or vector-based vaccines. All patients were monitored for antibodies against SARS-CoV2-spike protein (anti-S-IgG) with an IgG ELISA assay or an EIA Assay after two and three doses of vaccination. Results A total of 243 allo-SCT patients underwent SARS-CoV-2 vaccination. The median age was 59 years (range 22-81). While 85% of patients received two doses of mRNA vaccines, 10% had vector-based vaccines and 5% received a mixed vaccination. The two vaccine doses were well tolerated with only 3% patients developing a reactivation of graft versus host disease (GvHD). Overall, 72% of patients showed a humoral response after two vaccinations. In the multivariate analysis age at time of allo-SCT (p=0.0065), ongoing immunosuppressive therapy (p= 0.029) and lack of immune reconstitution (CD4-T-cell counts <200/μl, p< 0.001) were associated with no response. Sex, intensity of conditioning and the use of ATG showed no influence on seroconversion. Finally, 44 out of 69 patients that did not respond after the second dose received a booster and 57% (25/44) showed a seroconversion. Discussion We showed in our bicentric allo-SCT patient cohort, that a humoral response could be achieve after the regular approved schedule, especially for those patients who underwent immune reconstitution and were free from immunosuppressive drugs. In over 50% of the initial non-responders after 2-dose vaccination, a seroconversion can be achieved by boostering with a third dose.
Oral vinorelbine and continuous low doses of cyclophosphamide in pediatric rhabdomyosarcoma: a real-world study

Introduction: Metronomic maintenance therapy (MMT) has significantly improved the survival of patients with high-risk rhabdomyosarcoma in clinical trials. However, there remains a lack of relevant data on its effectiveness in real-world situations. Methods: We retrospectively retrieved data of 459 patients < 18 years of age diagnosed with rhabdomyosarcoma at Sun Yat-sen University Cancer Center from January 2011 to July 2020 from our database. The MMT regimen was oral vinorelbine 25–40 mg/m2 for twelve 4-week cycles on days 1, 8, and 15, and oral cyclophosphamide 25–50 mg/m2 daily for 48 consecutive weeks. Results: A total of 57 patients who underwent MMT were included in the analysis. The median follow-up time was 27.8 (range: 2.9–117.5) months. From MMT to the end of follow-up, the 3-year PFS and OS rates were 40.6% ± 6.8% and 58.3% ± 7.2%, respectively. The 3-year PFS was 43.6% ± 11.3% in patients who were initially diagnosed as low- and intermediate-risk but relapsed after comprehensive treatment (20/57), compared with 27.8% ± 10.4% in high-risk patients (20/57) and 52.8% ± 13.3% in intermediate-risk patients who did not relapse (17/57). The corresponding 3-year OS for these three groups was 65.8% ± 11.4%, 50.1% ± 12.9%, and 55.6% ± 13.6%, respectively. Conclusion: We present a novel study of MMT with oral vinorelbine and continuous low doses of cyclophosphamide in real-world pediatric patients with RMS. Our findings showed that the MMT strategy significantly improved patient outcomes and may be an effective treatment for high-risk and relapsed patients.
Protective effect of ursodeoxycholic acid on COVID-19 in patients with chronic liver disease

Objective Ursodeoxycholic acid (UDCA) may reduce susceptibility to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection by downregulating angiotensin-converting enzyme 2 (ACE2), based on recent experimental investigation. This study aimed to determine the potential protective effect of UDCA against SARS-CoV-2 infection in patients with chronic liver disease. Methods Patients with chronic liver disease receiving UDCA (taking UDCA ≥1 month) at Beijing Ditan Hospital between January 2022 and December 2022 were consecutively enrolled. These patients were matched in a 1:1 ratio to those with liver disease not receiving UDCA during the same period by using a propensity score matching analysis with nearest neighbor matching algorithm. We conducted a phone survey of coronavirus disease 2019 (COVID-19) infection during the early phase of the pandemic liberation (from 15 December 2022 to 15 January 2023). The risk of COVID-19 was compared in two matched cohorts of 225 UDCA users and 225 non-UDCA users based on patient self-report. Results In the adjusted analysis, the control group was superior to the UDCA group in COVID-19 vaccination rates and liver function indicators, including γ-glutamyl transpeptidase and alkaline phosphatase (p < 0.05). UDCA was associated with a lower incidence of SARS-CoV-2 infection (UDCA 85.3% vs. control 94.2%, p = 0.002), more mild cases (80.0% vs. 72.0%, p = 0.047), and shorter median time from infection to recovery (5 vs. 7 days, p < 0.001). Logistic regression analysis showed that UDCA was a significant protective factor against COVID-19 infection (OR: 0.32, 95%CI: 0.16–0.64, p = 0.001). Furthermore, diabetes mellitus (OR: 2.48, 95%CI: 1.11–5.54, p = 0.027) and moderate/severe infection (OR: 8.94, 95%CI: 1.07–74.61, p = 0.043) were more likely to prolong the time from infection to recovery. Conclusion UDCA therapy may be beneficial in reducing COVID-19 infection risk, alleviating symptoms, and shortening the recovery time in patients with chronic liver disease. However, it should be emphasized that the conclusions were based on patient self-report rather than classical COVID-19 detection by experimental investigations. Further large clinical and experimental studies are needed to validate these findings.
Interleukin 36 receptor-inducible matrix metalloproteinase 13 mediates intestinal fibrosis

Background Fibrostenotic disease is a common complication in Crohn’s disease (CD) patients hallmarked by transmural extracellular matrix (ECM) accumulation in the intestinal wall. The prevention and medical therapy of fibrostenotic CD is an unmet high clinical need. Although targeting IL36R signaling is a promising therapy option, downstream mediators of IL36 during inflammation and fibrosis have been incompletely understood. Candidate molecules include matrix metalloproteinases which mediate ECM turnover and are thereby potential targets for anti-fibrotic treatment. Here, we have focused on understanding the role of MMP13 during intestinal fibrosis. Methods We performed bulk RNA sequencing of paired colon biopsies taken from non-stenotic and stenotic areas of patients with CD. Corresponding tissue samples from healthy controls and CD patients with stenosis were used for immunofluorescent (IF) staining. MMP13 gene expression was analyzed in cDNA of intestinal biopsies from healthy controls and in subpopulations of patients with CD in the IBDome cohort. In addition, gene regulation on RNA and protein level was studied in colon tissue and primary intestinal fibroblasts from mice upon IL36R activation or blockade. Finally, in vivo studies were performed with MMP13 deficient mice and littermate controls in an experimental model of intestinal fibrosis. Ex vivo tissue analysis included Masson’s Trichrome and Sirius Red staining as well as evaluation of immune cells, fibroblasts and collagen VI by IF analysis. Results Bulk RNA sequencing revealed high upregulation of MMP13 in colon biopsies from stenotic areas, as compared to non-stenotic regions of patients with CD. IF analysis confirmed higher levels of MMP13 in stenotic tissue sections of CD patients and demonstrated αSMA+ and Pdpn+ fibroblasts as a major source. Mechanistic experiments demonstrated that MMP13 expression was regulated by IL36R signaling. Finally, MMP13 deficient mice, as compared to littermate controls, developed less fibrosis in the chronic DSS model and showed reduced numbers of αSMA+ fibroblasts. These findings are consistent with a model suggesting a molecular axis involving IL36R activation in gut resident fibroblasts and MMP13 expression during the pathogenesis of intestinal fibrosis. Conclusion Targeting IL36R-inducible MMP13 could evolve as a promising approach to interfere with the development and progression of intestinal fibrosis.
FDXR drives primary and endocrine-resistant tumor cell growth in ER+ breast cancer via CPT1A-mediated fatty acid oxidation

Background The majority of breast cancers (BCs) expressing estrogen receptor (ER) have shown endocrine resistance. Our previous study demonstrated that ferredoxin reductase (FDXR) promoted mitochondrial function and ER+ breast tumorigenesis. But the underlying mechanism is not clear. Methods Liquid chromatography (LC) tandem mass spectrometry (MS/MS)-based metabolite profiling was utilized to reveal the metabolites regulated by FDXR. RNA microarray was utilized to determine the potential downstream targets of FDXR. Seahorse XF24 analyzer was performed to analyze the FAO-mediated oxygen consumption rate (OCR). Q-PCR and western blotting assays were used to measure expression levels of FDXR and CPT1A. MTS, 2D colony formation and anchorage-independent growth assays were used to evaluate the effects of FDXR or drug treatments on tumor cell growth of primary or endocrine-resistant breast cancer cells. Results We found that depletion of FDXR inhibited fatty acid oxidation (FAO) by suppressing CPT1A expression. Endocrine treatment increased the expression levels of both FDXR and CPT1A. Further, we showed that depletion of FDXR or FAO inhibitor etomoxir treatment reduced primary and endocrine-resistant breast cancer cell growth. Therapeutically, combining endocrine therapy with FAO inhibitor etomoxir synergistically inhibits primary and endocrine-resistant breast cancer cell growth. Discussion We reveal that the FDXR-CPT1A-FAO signaling axis is essential for primary and endocrine-resistant breast cancer cell growth, thus providing a potential combinatory therapy against endocrine resistance in ER+ breast cancer.
Empirical identification of the inverse model of a squeeze-film damper bearing using neural networks and its application to a nonlinear inverse problem

The identification of nonlinear squeeze-film damper (SFD) bearings, typically used in aero-engines, has so far focused on their forward model (i.e. displacement input/force output). The contributions of this paper are the non-parametric identification of the inverse model of the SFD bearing (force input/displacement output) from empirical data, and its application to a nonlinear inverse rotor-bearing problem. This work is motivated by the need for a reliable substitute for internal instrumentation, to enable the identification of rotor unbalance using vibration data from externally mounted sensors, in applications where the rotor is inaccessible under operating conditions and there is no adequate linear connection between rotor and casing. The identification of the inverse model is fundamentally different from that of the forward model due to the need to account for system memory. A suitably trained Recurrent Neural network (RNN) is shown to be capable of identifying the inverse model of an actual SFD through two validation studies. In the first study, the RNN model satisfactorily predicted the SFD journal’s displacement time histories for given periodic time histories of the Cartesian SFD forces, although it could not predict the user-applied static offset in the SFD since it was not trained to do so. This was no limitation for the second study where, for both centred and non-centred SFD conditions, the RNN proved to be a reliable substitute for actual instrumentation as part of the inverse problem solution process for identifying the amplitudes and phases of the external excitation forces on a simple test rig.