Deep learning-based discriminant model for wearable sensing gait pattern

In order to effectively improve the accuracy of identifying the gait pattern of wearable sensing data, this paper proposes a new model for deep learning gait mode discrimination that integrates convolutional neural network and long short-term memory neural network, which makes full use of the convolutional neural network to obtain the most local spatial characteristics of data and the long short-term memory neural network to obtain the inherent characteristics of the data, and effectively excavates the hidden high-dimensional, nonlinear, time-space gait characteristics of random wearable sensing timing gait data that are closely related to gait pattern changes, to improve the classification performance of gait mode. The effectiveness of the proposed model in this paper is evaluated using the HAR dataset from University of California UCI database. The experiment results showed that the proposed model in this paper can effectively obtain the time-space gait characteristics embedded in the wearable sensor gait data, and the classification accuracy can reach 91.45%, the precision rate 91.54%, and the recall rate 91.53%, and the classification performance is significantly better than that of the traditional machine learning model, which provides a new solution for accurately identifying the gait mode of wearable sensor data

Finanční analýza společnosti McDonald’s

Financial analysis is a process of selecting, evaluation and interpreting financial data. It is an aspect of the overall business finance function that involves examining historical data to gain information about the current and future financial health of a company. Financial analysis can be applied in a wide variety of situations to give business managers the information they need to make critical decisions. The ability to understand financial data is essential for any business manager. Finance is the language of business. Business goals and objectives are set in financial terms and their outcomes are measured in financial terms. Among the skills required to understand and manage a business is fluency in the language of finance—the ability to read and understand financial data as well as present information in the form of financial reports. The objective of this thesis is to analyze the financial situation of McDonald's between 2012 and 2016. McDonald's is an American fast food company, founded in 1940 as a restaurant operated by Richard and Maurice McDonald, originating in Southern California. And it is also the world's largest fast food chain, serving over 69 million customers daily in over 100 countries across approximately 36,900 outlets as of 2016. Thesis is divided into five parts. The first chapter is introduction. The second chapter is description of the financial analysis methodology. The third chapter is financial characterization of McDonald's. The fourth chapter is financial analysis of financial characterization of McDonald's. And the last chapter is summarization.Financial analysis is a process of selecting, evaluation and interpreting financial data. It is an aspect of the overall business finance function that involves examining historical data to gain information about the current and future financial health of a company. Financial analysis can be applied in a wide variety of situations to give business managers the information they need to make critical decisions. The ability to understand financial data is essential for any business manager. Finance is the language of business. Business goals and objectives are set in financial terms and their outcomes are measured in financial terms. Among the skills required to understand and manage a business is fluency in the language of finance—the ability to read and understand financial data as well as present information in the form of financial reports.154 - Katedra financídobř

AF17 Facilitates Dot1a Nuclear Export and Upregulates ENaC-Mediated Na+ Transport in Renal Collecting Duct Cells

Our previous work in 293T cells and AF17-/- mice suggests that AF17 upregulates expression and activity of the epithelial Na+ channel (ENaC), possibly by relieving Dot1a-AF9-mediated repression. However, whether and how AF17 directly regulates Dot1a cellular distribution and ENaC function in renal collecting duct cells remain unaddressed. Here, we report our findings in mouse cortical collecting duct M-1 cells that overexpression of AF17 led to preferential distribution of Dot1a in the cytoplasm. This effect could be blocked by nuclear export inhibitor leptomycin B. siRNA-mediated depletion of AF17 caused nuclear accumulation of Dot1a. AF17 overexpression elicited multiple effects that are reminiscent of aldosterone action. These effects include 1) increased mRNA and protein expression of the three ENaC subunits (α, β and γ) and serum- and glucocorticoid inducible kinase 1, as revealed by real-time RT-qPCR and immunoblotting analyses; 2) impaired Dot1a-AF9 interaction and H3 K79 methylation at the αENaC promoter without affecting AF9 binding to the promoter, as evidenced by chromatin immunoprecipitation; and 3) elevated ENaC-mediated Na+ transport, as analyzed by measurement of benzamil-sensitive intracellular [Na+] and equivalent short circuit current using single-cell fluorescence imaging and an epithelial Volt-ohmmeter, respectively. Knockdown of AF17 elicited opposite effects. However, combination of AF17 overexpression or depletion with aldosterone treatment did not cause an additive effect on mRNA expression of the ENaC subunits. Taken together, we conclude that AF17 promotes Dot1a nuclear export and upregulates basal, but not aldosterone-stimulated ENaC expression, leading to an increase in ENaC-mediated Na+ transport in renal collecting duct cells

Hemoglobin level is negatively associated with sarcopenia and its components in Chinese aged 60 and above

Introduction: Sarcopenia and low hemoglobin level are common in older adults. Few studies have evaluated the association between hemoglobin level and sarcopenia and with inconsistent findings. The multifaceted effects of sarcopenia on the human body and the high prevalence of anemia in the Chinese population make it necessary to explore the association between the two. Methods: Using the China Health and Retirement Longitudinal Study (CHARLS), we explored the association between hemoglobin with sarcopenia and its components in the Chinese population aged 60 and above. Multivariate logistic and Cox proportional hazards models were constructed to examine the association of hemoglobin level with sarcopenia and sarcopenia components in individuals aged 60 years or above. The subgroup analysis covered residence, body mass index level, drinking status, and smoking status were conducted. The possible difference of associations between sexes was also explored. Results: With a total of 3,055 people, the hemoglobin concentration in people without sarcopenia, possible sarcopenia, and sarcopenia are 14.34 ± 2.22, 14.64 ± 2.27, and 13.58 ± 2.02 g/dl, respectively. Cross-sectional analysis showed strong evidence that hemoglobin was negatively associated with sarcopenia [Odds Ratio (OR) = 0.95, 95% Confidence Interval (CI): 0.90–0.99] and low height-adjusted appendicular skeletal muscle mass (OR = 0.91, 95% CI: 0.86–0.97). On average, a per 1 g/dl higher hemoglobin level was associated with 5% lower odds of sarcopenia (OR = 0.95, 95% CI: 0.90–0.98). The cohort study of 1,022 people demonstrated a statistically significant negative association of hemoglobin level with low physical performance [Hazard Ratio (HR) = 0.92, 95% CI: 0.85–0.99], merely with sarcopenia (HR = 0.92, 95% CI: 0.84–1.00) and skeletal muscle mass (HR = 0.95, 95% CI: 0.80–1.00). Sex-specific analysis suggested hemoglobin's association with sarcopenia, muscle mass, and physical performance in all sexes, with weaker magnitudes in females. Hemoglobin in urban residents and people with high body mass index (BMI) has a larger magnitude of the negative association with sarcopenia. Discussion: Hemoglobin level associates with sarcopenia, muscle mass, and physical performance in the Chinese population aged 60 and above, with sex-specific, residence-specific, and BMI-specific effects

Construction and comprehensive analysis of a curoptosis-related lncRNA signature for predicting prognosis and immune response in cervical cancer

Cuproptosis (copper-ion-dependent cell death) is an unprogrammed cell death, and intracellular copper accumulation, causing copper homeostasis imbalance and then leading to increased intracellular toxicity, which can affect the rate of cancer cell growth and proliferation. This study aimed to create a newly cuproptosis-related lncRNA signature that can be used to predict survival and immunotherapy in patients with cervical cancer, but also to predict prognosis in patients treated with radiotherapy and may play a role in predicting radiosensitivity. First of all, we found lncRNAs associated with cuproptosis between cervical cancer tumor tissues and normal tissues. By LASSO-Cox analysis, overlapping lncRNAs were then used to construct lncRNA signatures associated with cuproptosis, which can be used to predict the prognosis of patients, especially the prognosis of radiotherapy patients, ROC curves and PCA analysis based on cuprotosis-related lncRNA signature and clinical signatures were developed and demonstrated to have good predictive potential. In addition, differences in immune cell subset infiltration and differences in immune checkpoint expression between high-risk and low-risk score groups were analyzed, and we investigated the relationship between this signature and tumor mutation burden. In summary, we constructed a lncRNA prediction signature associated with cuproptosis. This has important clinical implications, including improving the predictive value of cervical cancer patients and providing a biomarker for cervical cancer

Integrated transcriptomic and metabolomic analysis reveals the metabolic programming of GM-CSF- and M-CSF- differentiated mouse macrophages

Macrophages play a critical role in the inflammatory response and tumor development. Macrophages are primarily divided into pro-inflammatory M1-like and anti-inflammatory M2-like macrophages based on their activation status and functions. In vitro macrophage models could be derived from mouse bone marrow cells stimulated with two types of differentiation factors: GM-CSF (GM-BMDMs) and M-CSF (M-BMDMs), to represent M1- and M2-like macrophages, respectively. Since macrophage differentiation requires coordinated metabolic reprogramming and transcriptional rewiring in order to fulfill their distinct roles, we combined both transcriptome and metabolome analysis, coupled with experimental validation, to gain insight into the metabolic status of GM- and M-BMDMs. The data revealed higher levels of the tricarboxylic acid cycle (TCA cycle), oxidative phosphorylation (OXPHOS), fatty acid oxidation (FAO), and urea and ornithine production from arginine in GM-BMDMs, and a preference for glycolysis, fatty acid storage, bile acid metabolism, and citrulline and nitric oxide (NO) production from arginine in M-BMDMs. Correlation analysis with the proteomic data showed high consistency in the mRNA and protein levels of metabolic genes. Similar results were also obtained when compared to RNA-seq data of human monocyte derived macrophages from the GEO database. Furthermore, canonical macrophage functions such as inflammatory response and phagocytosis were tightly associated with the representative metabolic pathways. In the current study, we identified the core metabolites, metabolic genes, and functional terms of the two distinct mouse macrophage populations. We also distinguished the metabolic influences of the differentiation factors GM-CSF and M-CSF, and wish to provide valuable information for in vitro macrophage studies

FBXO5 acts as a novel prognostic biomarker for patients with cervical cancer

Background: Cervical cancer (CC) remains one of the most common and deadly malignancies in women worldwide. FBXO5, a protein-coding gene, is highly expressed in a variety of primary tumors and promotes tumor progression, however, its role and prognostic value in CC remain largely unknown.Methods: A key differential gene, FBXO5, was screened according to WGCNA based on immunohistochemical assays of clinical samples, multiple analyses of the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases, including survival analysis, tumor mutational burden, GO, KEGG, tumor immune infiltration, and chemotherapeutic drug sensitivity, to explore the expression and prognostic value of FBXO5 in CC. The migration and invasiveness of cervical cancer cells following FBXO5 knockdown and overexpression were examined using wound healing and transwell assays, and the viability of cancer cells was assessed using CCK8 and EdU assays.Results:FBXO5 was discovered to be substantially expressed in CC tissues using data from our CC cohort and the TCGA database, and a survival analysis indicated FBXO5 as a predictive factor for poor overall survival in CC patients. In vitro, CC cells were more inclined to proliferate, migrate, and invade when FBXO5 was upregulated as opposed to when it was knocked down