Miracle-dz/UniFAR-FTUs huggingface dataset:
The evolutionary potential of the influenza A virus hemagglutinin is highly constrained by intersegment epistasis

The ongoing antigenic evolution of the influenza A virus (IAV) hemagglutinin (HA) gene limits efforts to effectively control the spread of the virus in the human population through vaccination. The factors that influence and constrain the evolutionary potential of the HA gene remain poorly understood. Efforts to understand the mechanisms that govern HA antigenic evolution typically examine the HA gene in isolation and ignore the importance of balancing HA receptor-binding activities with the receptor-destroying activities of the viral neuraminidase (NA) for maintaining viral fitness. We hypothesized that the need to maintain functional balance with NA significantly constrains the evolutionary potential of the HA gene. We used deep mutational scanning to show that variation in NA activity significantly reshapes the HA fitness landscape by modulating the overall mutational robustness of the HA protein. Consistent with this, we observe that different NA backgrounds support the emergence of distinct repertoires of HA escape variants under neutralizing antibody pressure. Our results reveal a critical role for intersegment epistatic interactions in shaping the evolutionary potential of the HA gene.
Homeostatic changes maintain the gain control of spinal motoneurones across the lifetime of C57BL/6J mice

Age-related changes in the excitability of spinal motoneurone have been observed in mouse models of neurodegenerative diseases affecting these neurones. How the excitability of spinal motoneurones change with healthy ageing in mice and how this compares with that seen in neurodegenerative diseases is unknown. Therefore, we performed in vivo intracellular recording from identified spinal motoneurones in C57BL/6 mice at three different ages (100, 300-400 and 600-750 days old). Behavioral tests confirmed a linear reduction in motor function across these ages (using the rotorod test). Significant differences were observed with respect to the features of individual somatic action potential with ageing including a decreased rate of rise and fall in aged mice. Surprisingly, the rate of rise of the action potential at the initial segment was altered in middle aged mice. Immunohistochemical labelling of the axon initial segment of the motoneurones confirmed structural changes occurring at middle age (decreased length and diameter) but returning to the earlier parameters in aged mice. To explore the effects on repetitive firing, this was tested across the age groups which showed surprising little difference as the mice aged, with a similar rheobase and I-f gain across all age groups (with the exception of a lower voltage threshold for action potential initiation in middle-aged mice). However, amplitudes of the after-hyperpolarization and the input resistance were both found to be significantly altered with age. We conclude that there are changes occurring in the intrinsic properties of spinal motoneurones that control their excitability over the lifetime of mice, although these do not develop in a linear fashion from young to old. We propose that these changes are homeostatic in nature and are able to compensate for one another to maintain a constant gain control across the lifetime.
Inferring Public Transport Access Distance from Smart Card Registration and Transaction Data

Access distance to public transport is an important metric for planning, modeling, and evaluating public transport networks and is often used in policy goals and statements. However, accurately measuring access (and egress) distance can be difficult. Estimates often rely either on aggregate inferences based on census data or on small samples of disaggregate data from travel diary surveys. When smart cards used for fare payment are also registered with home address information, they represent a new data source that can be used to infer access distances for a large sample of users, at a disaggregate level and at low cost, compared with travel diary surveys. This paper demonstrates the inference of access distance from smart card fare and transaction data for a large sample of London public transport journeys and compares the inferred access distributions to data from the London Travel Demand Survey, a travel diary survey. Possible instances of false inferences are considered and measures to eliminate false inferences are discussed. This access distance inference methodology allows for the analysis of variation in access distance across the network, and examples of this type of analysis are presented.
Multi-carrier Communications over Time-varying Acoustic Channels

of the Dissertation Multi-carrier Communications over Time-varying Acoustic Channels by Yashar M. Aval Doctor of Philosophy in Electrical and Computer Engineering Northeastern University, June 2015 Dr. Milica Stojanovic, Adviser Acoustic communication is an enabling technology for many autonomous undersea systems, such as those used for ocean monitoring, offshore oil and gas industry, aquaculture, or port security. There are three main challenges in achieving reliable high-rate underwater communication: the bandwidth of acoustic channels is extremely limited, the propagation delays are long, and the Doppler distortions are more pronounced than those found in wireless radio channels. In this dissertation we focus on assessing the fundamental limitations of acoustic communication, and designing efficient signal processing methods that cam overcome these limitations. We address the fundamental question of acoustic channel capacity (achievable rate) for single-input-multi-output (SIMO) acoustic channels using a per-path Rician fading model, and focusing on two scenarios: narrowband channels where the channel statistics can be approximated as frequencyindependent, and wideband channels where the nominal path loss is frequency-dependent. In each scenario, we compare several candidate power allocation techniques, and show that assigning uniform power across all frequencies for the first scenario, and assigning uniform power across a selected frequency-band for the second scenario, are the best practical choices in most cases, because the long propagation delay renders the feedback information outdated for power allocation based on the estimated channel response. We quantify our results using the channel information extracted form the 2010 Mobile Acoustic Communications Experiment (MACE’10) . Next, we focus on achieving reliable high-rate communication over underwater acoustic channels. Specifically, we investigate orthogonal frequency division multiplexing (OFDM) as the state-of-the-art technique for dealing with frequency-selective multipath channels, and propose a class of methods that compensate for the time-variation of the underwater acoustic channel. These methods are based on multiple-FFT demodulation, and are implemented as partial (P), shaped (S), fractional (F), and Taylor series expansion (T) FFT demodulation. They replace the conventional FFT
Deploying the ATLAS Metadata Interface (AMI) on the cloud with Jenkins

The ATLAS Metadata Interface (AMI) is a mature application of more than 15 years of existence. Mainly used by the ATLAS experiment at CERN, it consists of a very generic tool ecosystem for metadata aggregation and cataloguing. AMI is used by the ATLAS production system, therefore the service must guarantee a high level of availability. We describe our monitoring and administration systems, and the Jenkins-based strategy used to dynamically test and deploy cloud OpenStack nodes on demand.
Prediction of Tumor Mutation Load in Colorectal Cancer Histopathological Images Based on Deep Learning

Colorectal cancer (CRC) is one of the most prevalent malignancies, and immunotherapy can be applied to CRC patients of all ages, while its efficacy is uncertain. Tumor mutational burden (TMB) is important for predicting the effect of immunotherapy. Currently, whole-exome sequencing (WES) is a standard method to measure TMB, but it is costly and inefficient. Therefore, it is urgent to explore a method to assess TMB without WES to improve immunotherapy outcomes. In this study, we propose a deep learning method, DeepHE, based on the Residual Network (ResNet) model. On images of tissue, DeepHE can efficiently identify and analyze characteristics of tumor cells in CRC to predict the TMB. In our study, we used ×40 magnification images and grouped them by patients followed by thresholding at the 10th and 20th quantiles, which significantly improves the performance. Also, our model is superior compared with multiple models. In summary, deep learning methods can explore the association between histopathological images and genetic mutations, which will contribute to the precise treatment of CRC patients.
A Visualized Dynamic Prediction Model for Overall Survival in Elderly Patients With Pancreatic Cancer for Smart Medical Services

Background Pancreatic cancer (PC) is a highly malignant tumor of the digestive system. The number of elderly patients with PC is increasing, and older age is related to a worse prognosis. Accurate prognostication is crucial in treatment decisions made for people diagnosed with PC. However, an accurate predictive model for the prognosis of these patients is still lacking. We aimed to construct nomograms for predicting the overall survival (OS) of elderly patients with PC. Methods Patients with PC, older than 65 years old from 2010 to 2015 in the Surveillance, Epidemiology, and End Results database, were selected and randomly divided into training cohort (n = 4,586) and validation cohort (n = 1,966). Data of patients in 2016–2018 (n = 1,761) were used for external validation. Univariable and forward stepwise multivariable Cox analysis was used to determine the independent prognostic factors. We used significant variables in the training set to construct nomograms predicting prognosis. The performance of the models was evaluated for their discrimination and calibration power based on the concordance index (C-index), calibration curve, and the decision curve analysis (DCA). Results Age, insurance, grade, surgery, radiation, chemotherapy, T, N, and American Joint Commission on Cancer were independent predictors for OS and thus were included in our nomogram. In the training cohort and validation cohort, the C-indices of our nomogram were 0.725 (95%CI: 0.715–0.735) and 0.711 (95%CI: 0.695–0.727), respectively. The 1-, 3-, and 5-year areas under receiver operating characteristic curves showed similar results. The calibration curves showed a high consensus between observations and predictions. In the external validation cohort, C-index (0.797, 95%CI: 0.778–0.816) and calibration curves also revealed high consistency between observations and predictions. The nomogram-related DCA curves showed better clinical utility compared to tumor-node-metastasis staging. In addition, we have developed an online prediction tool for OS. Conclusions A web-based prediction model for OS in elderly patients with PC was constructed and validated, which may be useful for prognostic assessment, treatment strategy selection, and follow-up management of these patients.
Identification of an Epithelial-Mesenchymal Transition-Related Long Non-coding RNA Prognostic Signature to Determine the Prognosis and Drug Treatment of Hepatocellular Carcinoma Patients

Introduction Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with poor prognosis. Epithelial–mesenchymal transition (EMT) is crucial for cancer progression and metastasis. Thus, we aimed to construct an EMT-related lncRNA signature for predicting the prognosis of HCC patients. Methods Cox regression analysis and LASSO regression method were used to build an EMT-related lncRNAs risk signature based on TCGA database. Kaplan-Meier survival analysis was conducted to compare the overall survival (OS) in different risk groups. ROC curves and Cox proportional-hazards analysis were performed to evaluate the performance of the risk signature. RT-qPCR was conducted in HCC cell lines and tissue samples to detect the expression of some lncRNAs in this risk model. Furthermore, a nomogram involving the risk score and clinicopathological features was built and validated with calibration curves and ROC curves. In addition, we explored the association between risk signature and tumor immunity, somatic mutations status, and drugs sensitivity. Results Twelve EMT-related lncRNAs were obtained to construct the prognostic risk signature for patients with HCC. The Kaplan-Meier curve analysis revealed that patients in the high-risk group had worse overall survival (OS) than those in low-risk group. ROC curves and Cox regression analysis suggested the risk signature could predict HCC survival exactly and independently. The prognostic value of the risk model was confirmed in the testing and entire groups. We also found AC099850.3 and AC092171.2 were highly expressed in HCC cells and HCC tissues. The nomogram could accurately predict survival probability of HCC patients. Gene set enrichment analysis (GSEA) and gene ontology (GO) analysis showed that cancer-related pathways and cell division activity were enriched in high-risk group. The SNPs showed that the prevalence of TP53 mutations was significantly different between high- and low-risk groups; the TP53 mutations and the high TMB were both associated with a worse prognosis in patients with HCC. We also observed widely associations between risk signature and drugs sensitivity in HCC. Conclusion A novel EMT-related lncRNAs risk signature, including 12 lncRNAs, was established and identified in patients with HCC, which can accurately predict the prognosis of HCC patients and may be used to guide individualized treatment in the clinical practice.
Effects of Ultramicronized Palmitoylethanolamide on Mitochondrial Bioenergetics, Cerebral Metabolism, and Glutamatergic Transmission: An Integrated Approach in a Triple Transgenic Mouse Model of Alzheimer's Disease

The therapeutic potential of ultramicronized palmitoylethanolamide (um-PEA) was investigated in young (6-month-old) and adult (12-month-old) 3 × Tg-AD mice, which received um-PEA for 3 months via a subcutaneous delivery system. Mitochondrial bioenergetics, ATP homeostasis, and magnetic resonance imaging/magnetic resonance spectroscopy were evaluated in the frontal cortex (FC) and hippocampus (HIPP) at the end of um-PEA treatment. Glutamate release was investigated by in vivo microdialysis in the ventral HIPP (vHIPP). We demonstrated that chronic um-PEA treatment ameliorates the decrease in the complex-I respiration rate and the FoF1-ATPase (complex V) activity, as well as ATP content depletion in the cortical mitochondria. Otherwise, the impairment in mitochondrial bioenergetics and the release of glutamate after depolarization was not ameliorated by um-PEA treatment in the HIPP of both young and adult 3 × Tg-AD mice. Moreover, progressive age- and pathology-related changes were observed in the cortical and hippocampal metabolism that closely mimic the alterations observed in the human AD brain; these metabolic alterations were not affected by chronic um-PEA treatment. These findings confirm that the HIPP is the most affected area by AD-like pathology and demonstrate that um-PEA counteracts mitochondrial dysfunctions and helps rescue brain energy metabolism in the FC, but not in the HIPP.
Ulva prolifera Polysaccharide–Manganese Alleviates Inflammation and Regulates Microbiota Composition in Dextran Sulfate Sodium-Induced Colitis Mice

Manganese (Mn) deficiency exacerbates colitis symptoms, whereas diet supplemented with inorganic Mn merely maintains colon length in experimental colitis. In the present study, a new form of Mn, Ulva prolifera polysaccharide cheated-Mn (PMn) was used and its treatment effects on dextran sulfate sodium (DSS)-induced colitis were investigated. Male C57BL/6 mice were orally administrated with 3.5% DSS to induce colitis. Then, the colitis mice were treated with PBS or PMn for 7 days. The results showed that PMn administration help retrieve the body weight loss and intestinal morphology damage, and alleviate apoptosis and inflammatory responses in colitis mice. Moreover, PMn administration decreased intestinal infiltration as indicated by decreased concentration of myeloperoxidase and eosinophil peroxidase. Importantly, PMn retrieved the increased abundance of Firmicutes and the decreased abundance of Bacteroidetes caused by DSS, suggested its beneficial roles in regulating microbiota composition in mice with colon inflammation. Gut microbiota composition at the genus level in the mice administrated with PMn was similar to those in control mice, whereas they were clearly distinct from DSS-treated mice. These results support the potential therapeutic role of PMn in the treatment of intestinal colitis and microbes may play critical roles in mediating its effects.
Efficacy and Safety of a Polysaccharide-Based Natural Substance Complex in the Treatment of Obesity and Other Metabolic Syndrome Components: A Systematic Review

Introduction: Metabolic syndrome (MetS) is increasingly common in adults as well as in children and adolescents. However, preventing and treating MetS is one of the most pressing challenges for public health services worldwide. At present, the only approved treatments for MetS are dietary changes and physical activity, which are associated with a high rate of non-compliance. On the contrary, no drugs are licensed to treat metabolic syndrome, although a number of drugs are used to treat individual metabolic abnormalities, which increases the risk of adverse events, particularly in children. Policaptil Gel Retard® (PGR), an oral macromolecule complex based on polysaccharides, has been demonstrated to significantly reduce body weight, peak blood glucose (BG) levels, insulin levels, and lipid levels, providing an interesting non-pharmacological therapeutic option for MetS-associated metabolic abnormalities, especially in younger patients. Aims: To review available studies on the use of PGR in children, adolescents, or adults with obesity or metabolic syndrome. Methods: A systematic search of electronic databases for PGR and MetS. A total of six studies were identified and included. Results: Across four randomized clinical studies and one retrospective clinical study including a total of 359 obese children and adolescents with or without MetS and 157 overweight/obese adults with or without MetS and/or T2DM, a single dose of PGR resulted in a reduction in appetite and postprandial triglyceride levels in younger patients and peak postprandial BG levels in adults. Decreased lipid levels were observed in adults following a normocaloric diet who received PGR for 30 days. As a long-term treatment, in combination with a low-glycemic index diet with or without metformin, PGR resulted in reduced body mass index and waist circumference, improved insulin sensitivity with reduction of glucose-metabolism abnormalities, increased insulin reserve and, finally, an improved circulating lipid profile, regardless of age. No safety issues were reported. Conclusion: Policaptil Gel Retard® is an effective and safe non-pharmacological approach to improve the treatment of MetS-associated cardiovascular risk factors in children, adolescents, and adults.
Immune-Associated Gene Signatures Serve as a Promising Biomarker of Immunotherapeutic Prognosis for Renal Clear Cell Carcinoma

As the most common type of renal cell carcinoma (RCC), the renal clear cell carcinoma (ccRCC) is highly malignant and insensitive to chemotherapy or radiotherapy. Although systemic immunotherapies have been successfully applied to ccRCC in recent years, screening for patients who can benefit most from these therapies is still essential and challenging due to immunological heterogeneity of ccRCC patients. To this end, we implemented a series of deep investigation on the expression and clinic data of ccRCC from The Cancer Genome Atlas (TCGA) International Consortium for Cancer Genomics (ICGC). We identified a total of 946 immune-related genes that were differentially expressed. Among them, five independent genes, including SHC1, WNT5A, NRP1, TGFA, and IL4R, were significantly associated with survival and used to construct the immune-related prognostic differential gene signature (IRPDGs). Then the ccRCC patients were categorized into high-risk and low-risk subgroups based on the median risk score of the IRPDGs. IRPDGs subgroups displays distinct genomic and immunological characteristics. Known immunotherapy-related genes show different mutation burden, wherein the mutation rate of VHL was higher than 40% in the two IRPDGs subgroups, and SETD2 and BAP1 mutations differed most between two groups with higher frequency in the high-risk subgroup. Moreover, IRPDGs subgroups had different abundance in tumor-infiltrating immune cells (TIICs) with distinct immunotherapy efficacy. Plasma cells, regulatory cells (Tregs), follicular helper T cells (Tfh), and M0 macrophages were enriched in the high-risk group with a higher tumor immune dysfunction and rejection (TIDE) score. In contrast, the low-risk group had abundant M1 macrophages, mast cell resting and dendritic cell resting infiltrates with lower TIDE score and benefited more from immune checkpoint inhibitors (ICI) treatment. Compared with other biomarkers, such as TIDE and tumor inflammatory signatures (TIS), IRPDGs demonstrated to be a better biomarker for assessing the prognosis of ccRCC and the efficacy of ICI treatment with the promise in screening precise patients for specific immunotherapies.
The Rail-Guided Vehicles Industry in Italy, 1861–1913: The Burden of the Evidence

This paper presents the first annual estimates for the rail-guided vehicles industry in post-Unification Italy. Nationally, maintenance was naturally trend-dominated, while new construction followed a Kuznets cycle; overall, maintenance exceeded new construction, while freight cars represented the largest component of the latter. The limited production of locomotives over the initial decades seems tied to high raw material costs rather than to technical inadequacy. Regionally, new construction was concentrated in the industrial triangle, and in Campania; maintenance was more widely diffused, as repair work tended to follow local traffic, but it too was largely absent from the swath of mostly Southern regions without major urban centers.
Altered Metabolomics in Bipolar Depression With Gastrointestinal Symptoms

Objective Although gastrointestinal (GI) symptoms are very common in patients with bipolar disorder (BD), Few studies have researched the pathomechanism behind these symptoms. In the present study, we aim at elucidate the pathomechanism of GI symptoms in BD through metabolomic analysis. Method BD patients were recruited from Shanxi Bethune Hospital that divided into two groups, each group assessed with the 24-item Hamilton Depression Rating Scale (HAMD-24) according to the presence or absence of GI symptoms. Healthy controls were recruited from the medical examination center of the same hospital. Differential metabolites were identified and further analyzed using Metabo Analyst 3.0 to identify associated metabolic pathways. Results There were significantly higher HAMD-24 scores in the GI symptoms group than that of non-GI symptoms group (p = 0.007). Based on metabolomic analysis results, we found that the common disturbances metabolic pathway of both two patients groups was ketone body metabolism, and the unique disturbances metabolic pathways of BD with GI symptoms were fatty acid biosynthesis and tyrosine metabolism, and these changes were independent of dietary habits. Conclusion BD patients with GI symptoms exhibited disturbances in fatty acid and tyrosine metabolism, perhaps suggesting that the GI symptoms in BD patients are related to disturbances of the gut microbiome. Both groups of patients jointly exhibit disturbances of ketone body metabolism, which may serve as a biomarker for the pathogenesis of BD patients.