Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Mice Model for Studying the Efficacy and IRAEs of Anti-CTLA4 Targeted Immunotherapy

Background Patient-derived orthotopic xenograft (PDOX) is a popular animal model for translational cancer research. Immunotherapy is a promising therapy against glioblastoma (GBM). However, the PDOX model is limited to evaluating immune-related events. Our study aims to establish GBM humanized PDOX (HPDOX) mice models to study the mechanism of anti-CTLA4 immunotherapy and immune-related adverse events (IRAEs). Methods HPDOX models were established by culturing GBM tissues and intracranially implanting them in NSG mice. Meanwhile, peripheral blood mononuclear cells (PBMCs) were separated from peripheral blood and of GBM patients and administrated in corresponding mice. The population of CD45+, CD3+, CD4+, CD8+, and regulatory T (Treg) cells was estimated in the peripheral blood or tumor. Results T cells derived from GBM patients were detected in HPDOX mice models. The application of anti-CTLA4 antibodies (ipilimumab and tremelimumab) significantly inhibited the growth of GBM xenografts in mice. Moreover, residual patient T cells were detected in the tumor microenvironment and peripheral blood of HPDOX mice and were significantly elevated by ipilimumab and tremelimumab. Additionally, Treg cells were decreased in mice with IRAEs. Lastly, the proportion of CD4+/CD8+ T cells dramatically increased after the administration of ipilimumab. And the degree of IRAEs may be related to CD56+ expression in HPDOX. Conclusions Our study established HPDOX mice models for investigating the mechanism and IRAEs of immunotherapies in GBM, which would offer a promising platform for evaluating the efficacy and IRAEs of novel therapies and exploring personalized therapeutic strategies.
Impacts of Seagrass on Benthic Microalgae and Phytoplankton Communities in an Experimentally Warmed Coral Reef Mesocosm

The effects of seagrass on microalgal assemblages under experimentally elevated temperatures (28°C) and CO2 partial pressures (pCO2; 800 μatm) were examined using coral reef mesocosms. Concentrations of nitrate, ammonium, and benthic microalgal chlorophyll a (chl-a) were significantly higher in seagrass mesocosms, whereas phytoplankton chl-a concentrations were similar between seagrass and seagrass-free control mesocosms. In the seagrass group, fewer parasitic dinoflagellate OTUs (e.g., Syndiniales) were found in the benthic microalgal community though more symbiotic dinoflagellates (e.g., Cladocopium spp.) were quantified in the phytoplankton community. Our results suggest that, under ocean acidification conditions, the presence of seagrass nearby coral reefs may (1) enhance benthic primary productivity, (2) decrease parasitic dinoflagellate abundance, and (3) possibly increase the presence of symbiotic dinoflagellates.
Validating the Strategic Deployment of Blackleg Resistance Gene Groups in Commercial Canola Fields on the Canadian Prairies

Blackleg, caused by the fungal pathogen Leptosphaeria maculans, is a serious threat to canola (Brassica napus L.) production in western Canada. Crop scouting and extended crop rotation, along with the use of effective genetic resistance, have been key management practices available to mitigate the impact of the disease. In recent years, new pathogen races have reduced the effectiveness of some of the resistant cultivars deployed. Strategic deployment and rotation of major resistance (R) genes in cultivars have been used in France and Australia to help increase the longevity of blackleg resistance. Canada also introduced a grouping system in 2017 to identify blackleg R genes in canola cultivars. The main objective of this study was to examine and validate the concept of R gene deployment through monitoring the avirulence (Avr) profile of L. maculans population and disease levels in commercial canola fields within the Canadian prairies. Blackleg disease incidence and severity was collected from 146 cultivars from 53 sites across Manitoba, Saskatchewan, and Alberta in 2018 and 2019, and the results varied significantly between gene groups, which is likely influenced by the pathogen population. Isolates collected from spring and fall stubble residues were examined for the presence of Avr alleles AvrLm1, AvrLm2, AvrLm3, AvrLm4, AvrLm5, AvrLm6, AvrLm7, AvrLm9, AvrLm10, AvrLm11, AvrLepR1, AvrLepR2, AvrLep3, and AvrLmS using a set of differential host genotypes carrying known resistance genes or PCR-based markers. The Simpson’s evenness index was very low, due to two dominant L. maculans races (AvrLm2-4-5-6-7-10-11 and AvrLm2-5-6-7-10-11) representing 49% of the population, but diversity of the population was high from the 35 L. maculans races isolated in Manitoba. AvrLm6 and AvrLm11 were found in all 254 L. maculans isolates collected in Manitoba. Knowledge of the blackleg disease levels in relation to the R genes deployed, along with the L. maculans Avr profile, helps to measure the effectiveness of genetic resistance.
Acupuncture for Breast Cancer: A Systematic Review and Meta-Analysis of Patient-Reported Outcomes

Abstract The present systematic review and meta-analysis was undertaken to evaluate the effects of acupuncture in women with breast cancer (BC), focusing on patient-reported outcomes (PROs). Methods A comprehensive literature search was carried out for randomized controlled trials (RCTs) reporting PROs in BC patients with treatment-related symptoms after undergoing acupuncture for at least four weeks. Literature screening, data extraction, and risk bias assessment were independently carried out by two researchers. Results Out of the 2, 524 identified studies, 29 studies representing 33 articles were included in this meta-analysis. At the end of treatment (EOT), the acupuncture patients’ quality of life (QoL) was measured by the QLQ-C30 QoL subscale, the Functional Assessment of Cancer Therapy-Endocrine Symptoms (FACT-ES), the Functional Assessment of Cancer Therapy–General/Breast (FACT-G/B), and the Menopause-Specific Quality of Life Questionnaire (MENQOL), which depicted a significant improvement. The use of acupuncture in BC patients lead to a considerable reduction in the scores of all subscales of the Brief Pain Inventory-Short Form (BPI-SF) and Visual Analog Scale (VAS) measuring pain. Moreover, patients treated with acupuncture were more likely to experience improvements in hot flashes scores, fatigue, sleep disturbance, and anxiety compared to those in the control group, while the improvements in depression were comparable across both groups. Long-term follow-up results were similar to the EOT results. Conclusions Current evidence suggests that acupuncture might improve BC treatment-related symptoms measured with PROs including QoL, pain, fatigue, hot flashes, sleep disturbance and anxiety. However, a number of included studies report limited amounts of certain subgroup settings, thus more rigorous, well-designed and larger RCTs are needed to confirm our results.
A Comparison of Microplastic in Fish From Australia and Fiji

Awareness surrounding plastic pollution has increased significantly in the past decade, leading to concerns on potential adverse effects on biota, including the consumption of microplastic by fish. Globally, plastic has been found in many species of fish, but little research has been undertaken in the southern hemisphere. We assessed the abundance and type of plastic in fish captured and sold for human consumption in Australia and Fiji. Fish (goatfish, sea mullet, paddletail, and common coral trout) had their gastrointestinal tracts dissected and microplastic quantified under a microscope. Plastic polymer types were confirmed using μ-FTIR. In Australia, plastic was found in 61.6% of fish gastrointestinal tracts, while in Fiji, 35.3% of fish had plastic. Fish from Australia had almost double the amount of plastic on average than fish caught in Fiji, with 1.58 (± 0.23) pieces per fish in Australia compared to 0.86 (± 0.14) in fish caught in Fiji. The types of plastic differed between countries, with fibers comprising 83.6% of microplastic pieces in fish from Australia whereas 50% of microplastic found in fish from Fiji was film. Polyolefin was the most abundant polymer type in both fibers from Australia and film from Fiji. We hypothesize variations in abundance and plastic type are a reflection of the population density and coastal geomorphology, but may also be a result of legislation and waste management strategies in the two countries. This work adds evidence to the pervasive presence of plastic in fish gastrointestinal tracts, reinforcing the urgent need for efficient plastic waste management, but also a better understanding of the impacts of microplastic on marine biota.
Exploring Impacts of River Discharge on Forage Fish and Predators Using Ecopath With Ecosim

The ecology of estuaries is shaped significantly by the extent of freshwater discharge which regulates abiotic processes and influences overall biological productivity. The Suwannee River Estuary of Florida’s Big Bend Coastline has historically been a productive and diverse estuarine ecosystem supported by significant freshwater inputs from the Suwannee River. In recent years, significant changes in land use and climatic conditions have resulted in lower discharges from the Suwannee. Our objectives were to explore the impact of freshwater inputs from the Suwannee River on the estuarine forage fish and sportfish communities downstream. We built a trophic-dynamic food web model in Ecopath with Ecosim to simulate different levels of discharge and evaluate how changes in discharge (drought and floods) would influence the trophic structure of the food web. Using the fitted model, we applied a series of different short-term and long-term flow projections under different climatic scenarios to evaluate impacts on fish functional groups and sportfish biomass. Simulations suggested that ecological production was more influenced by drought conditions than flood conditions. In our short-term scenarios, the drought simulations produced biomass changes that were approximately twice as substantial as the flood scenarios. When making comparisons to other published EwE models, we generally observed smaller changes in biomass production. Although this model focused on the influence of bottom-up effects, we observed strong top-down control of snook (Centropomus undecimalis) on the system. Several functional groups were particularly sensitive to changes in snook abundance which included spotted seatrout (Cynoscion nebulosus), sand seatrout (C. arenarius), and other members of the family Sciaenidae. Because snook have recently colonized the estuary, likely as a result of warmer winter temperatures, this finding has implications for climate change and natural resource management.
Functional Hyperconnectivity and Task-Based Activity Changes Associated With Neuropathic Pain After Spinal Cord Injury: A Pilot Study

Neuropathic pain (NP) is a devastating chronic pain condition affecting roughly 80% of the spinal cord injury (SCI) patient population. Current treatment options are largely ineffective and neurophysiological mechanisms of NP are not well-understood. Recent studies in neuroimaging have suggested that NP patients have differential patterns of functional activity that are dependent upon the neurological condition causing NP. We conducted an exploratory pilot study to examine functional activation and connectivity in SCI patients with chronic NP compared to SCI patients without NP. We developed a novel somatosensory attention task to identify short term fluctuations in neural activity related to NP vs. non-painful somatosensation using functional magnetic resonance imaging (fMRI). We also collected high-resolution resting state fMRI to identify connectivity-based correlations over time between the two groups. We observed increased activation during focus on NP in brain regions associated with somatosensory integration and representational knowledge in pain subjects when compared with controls. Similarly, NP subjects showed increased connectivity at rest in many of the same areas of the brain, with positive correlations between somatomotor networks, the dorsal attention network, and regions associated with pain and specific areas of painful and non-painful sensation within our cohort. Although this pilot analysis did not identify statistically significant differences between groups after correction for multiple comparisons, the observed correlations between NP and functional activation and connectivity align with a priori hypotheses regarding pain, and provide a well-controlled preliminary basis for future research in this severely understudied patient population. Altogether, this study presents a novel task, identifies regions of increased task-based activation associated with NP after SCI in the insula, prefrontal, and medial inferior parietal cortices, and identifies similar regions of increased functional connectivity associated with NP after SCI in sensorimotor, cingulate, prefrontal, and inferior medial parietal cortices. This, along with our complementary results from a structurally based analysis, provide multi-modal evidence for regions of the brain specific to the SCI cohort as novel areas for further study and potential therapeutic targeting to improve outcomes for NP patients.
Preoperative Prediction of Metastasis for Ovarian Cancer Based on Computed Tomography Radiomics Features and Clinical Factors

Background There is urgent need for an accurate preoperative prediction of metastatic status to optimize treatment for patients with ovarian cancer (OC). The feasibility of predicting the metastatic status based on radiomics features from preoperative computed tomography (CT) images alone or combined with clinical factors were investigated. Methods A total of 101 OC patients who underwent primary debulking surgery were enrolled. Radiomics features were extracted from the tumor volumes contoured on CT images with LIFEx package. Mann-Whitney U tests, least absolute shrinkage selection operator (LASSO), and Ridge Regression were applied to select features and to build prediction models. Univariate and regression analysis were applied to select clinical factors for metastatic prediction. The performance of models generated with radiomics features alone, clinical factors, and combined factors were evaluated and compared. Results Nine radiomics features were screened out from 184 extracted features to classify patients with and without metastasis. Age and cancer antigen 125 (CA125) were the two clinical factors that were associated with metastasis. The area under curves (AUCs) for the radiomics signature, clinical factors model, and combined model were 0.82 (95% CI, 0.66-0.98; sensitivity = 0.90, specificity = 0.70), 0.83 (95% CI, 0.67-0.95; sensitivity = 0.71, specificity = 0.8), and 0.86 (95% CI, 0.72-0.99, sensitivity = 0.81, specificity = 0.8), respectively. Conclusions Radiomics features alone or radiomics features combined with clinical factors are feasible and accurate enough to predict the metastatic status for OC patients.
Lopinavir/Ritonavir and Darunavir/Cobicistat in Hospitalized COVID-19 Patients: Findings From the Multicenter Italian CORIST Study

Background: Protease inhibitors have been considered as possible therapeutic agents for COVID-19 patients. Objectives: To describe the association between lopinavir/ritonavir (LPV/r) or darunavir/cobicistat (DRV/c) use and in-hospital mortality in COVID-19 patients. Study Design: Multicenter observational study of COVID-19 patients admitted in 33 Italian hospitals. Medications, preexisting conditions, clinical measures, and outcomes were extracted from medical records. Patients were retrospectively divided in three groups, according to use of LPV/r, DRV/c or none of them. Primary outcome in a time-to event analysis was death. We used Cox proportional-hazards models with inverse probability of treatment weighting by multinomial propensity scores. Results: Out of 3,451 patients, 33.3% LPV/r and 13.9% received DRV/c. Patients receiving LPV/r or DRV/c were more likely younger, men, had higher C-reactive protein levels while less likely had hypertension, cardiovascular, pulmonary or kidney disease. After adjustment for propensity scores, LPV/r use was not associated with mortality (HR = 0.94, 95% CI 0.78 to 1.13), whereas treatment with DRV/c was associated with a higher death risk (HR = 1.89, 1.53 to 2.34, E-value = 2.43). This increased risk was more marked in women, in elderly, in patients with higher severity of COVID-19 and in patients receiving other COVID-19 drugs. Conclusions: In a large cohort of Italian patients hospitalized for COVID-19 in a real-life setting, the use of LPV/r treatment did not change death rate, while DRV/c was associated with increased mortality. Within the limits of an observational study, these data do not support the use of LPV/r or DRV/c in COVID-19 patients.
High Mobility Group Box 1 Contributes to the Acute Rejection of Liver Allografts by Activating Dendritic Cells

Acute rejection induced by the recognition of donor alloantigens by recipient T cells leads to graft failure in liver transplant recipients. The role of high mobility group box 1 (HMGB1), an inflammatory mediator, in the acute allograft rejection of liver transplants is unknown. Here, rat orthotopic liver transplantation was successfully established to analyze the expression pattern of HMGB1 in liver allografts and its potential role in promoting the maturation of dendritic cells (DCs) to promote T cell proliferation and differentiation. Five and 10 days after transplantation, allografts showed a marked upregulation of HMGB1 expression accompanied by elevated levels of serum transaminase and CD3+ and CD86+ inflammatory cell infiltration. Furthermore, in vitro experiments showed HMGB1 increased the expressions of co-stimulatory molecules (CD80, CD83, and MHC class II) on bone marrow-derived DCs. HMGB1-pulsed DCs induced naive CD4+ T cells to differentiate to Th1 and Th17 subsets secreting IFN-γ and IL-17, respectively. Further in vivo experiments confirmed the administration of glycyrrhizic acid, a natural HMGB1 inhibitor, during donor liver preservation had therapeutic effects by reducing inflammation and hepatocyte damage reflected by a decline in serum transaminase and prolonged allograft survival time. These results suggest the involvement of HMBG1 in acute liver allograft rejection and that it might be a candidate therapeutic target to avoid acute rejection after liver transplantation.
Classification of Relaxation and Concentration Mental States with EEG

In this paper, we study the use of EEG (Electroencephalography) to classify between concentrated and relaxed mental states. In the literature, most EEG recording systems are expensive, medical-graded devices. The expensive devices limit the availability in a consumer market. The EEG signals are obtained from a toy-grade EEG device with one channel of output data. The experiments are conducted in two runs, with 7 and 10 subjects, respectively. Each subject is asked to silently recite a five-digit number backwards given by the tester. The recorded EEG signals are converted to time-frequency representations by the software accompanying the device. A simple average is used to aggregate multiple spectral components into EEG bands, such as α, β, and γ bands. The chosen classifiers are SVM (support vector machine) and multi-layer feedforward network trained individually for each subject. Experimental results show that features, with α+β+γ bands and bandwidth 4 Hz, the average accuracy over all subjects in both runs can reach more than 80% and some subjects up to 90+% with the SVM classifier. The results suggest that a brain machine interface could be implemented based on the mental states of the user even with the use of a cheap EEG device.
Lunar Pit Exploration and Mapping via Autonomous Micro-Rover

Lunar pits are windows to great unknowns beneath the surface of the Moon. The steep pit walls expose a vertical cross-section of stratified lunar crust, a natural historical record of the Moon's formation. The shadowed pit floors conceal possible entrances to caves or lava tube networks where astronauts might shelter from the hazards of the lunar surface. While orbital imagery has led to the discovery of more than 200 lunar pits, surface exploration is needed to capture the close-range, long exposures required to address questions of lunar formation and habitation. We envision an autonomous micro-rover for rapid surface exploration and in situ modeling of a lunar pit. We survey the specific autonomy, mapping, and roving technologies required, and we demonstrate the accuracy and coverage achievable by pit modeling in an evaluation performed at a terrestrial pit.
A Reconfigurable Multi-Modal SDR Transceiver for CubeSats

As the attention towards CubeSats increases due to their low manufacturing and launch costs, it becomes more and more relevant equipping them with Software-Defined-Radio (SDR) technologies to fulfill tasks for various scientific missions. The most recent state-of-the-art about small satellites is quickly moving toward this direction. To provide the highest degree of flexibility, we decided to build a basic baseband multicarrier infrastructure, exploiting the usual Fast-Fourier Transform (FFT) digital signal processing module. In such a way, we provide a software-defined transceiver capable at supporting all standard and non-standard multicarrier transmission waveforms, namely: OFDMA, SC-FDMA and MC-CDMA, but also capable at reconfiguring itself in single-carrier mode with Frequency-Domain Equalization (SC-FDE) and, if needed, even in single-carrier DS/CDMA mode. The dynamic reconfiguration of the receiver is enabled by a waveform recognition block, based on the analysis of the cross-correlation of the received signal in the time/frequency domain. After introducing the motivations and the state-of-the-art framework, the paper describes in detail the software architecture of the transceiver, implemented with open-source GNU Radio tools. Preliminary results will be then presented, aimed at assessing the performance of the proposed SDR-based transceiver. Finally, some considerations will be drawn, concerning with the concrete feasibility of the proposed SDR implementation in the framework of commercial low-cost digital signal processing platforms.
Short-Term Wind Speed Forecasting Based on Hybrid MODWT-ARIMA-Markov Model

Markov chains (MC) are statistical models used to predict very short to short-term wind speed accurately. Such models are generally trained with a single moving window. However, wind speed time series do not possess an equal length of behavior for all horizons. Therefore, a single moving window can provide reasonable estimates but is not an optimal choice. In this study, a forecasting model is proposed that integrates MCs with an adjusting dynamic moving window. The model selects the optimal size of the window based on a similar approach to the leave-one-out method. The traditional model is further optimized by introducing a self-adaptive state categorization algorithm. Instead of synthetically generating time series, the modified model directly predicts one-step ahead wind speed. Initial results indicate that adjusting the moving window MC prediction model improved the forecasting performance of a single moving window approach by 50%. Based on preliminary findings, a novel hybrid model is proposed integrating maximal overlap discrete wavelet transform (MODWT) with auto-regressive integrated moving average (ARIMA) and adjusting moving window MC. It is evident from the literature that MC models are suitable for predicting residual sequences. However, MCs were not considered as a primary forecasting model for the decomposition-based hybrid approach in any wind forecasting studies. The improvement of the novel model is, on average, 55% for single deep learning models and 30% for decomposition-based hybrid models.