Miracle-dz/UniFAR-FTUs huggingface dataset:
PDK1 Inhibitor BX795 Improves Cisplatin and Radio-Efficacy in Oral Squamous Cell Carcinoma by Downregulating the PDK1/CD47/Akt-Mediated Glycolysis Signaling Pathway

Background: Oral squamous cell carcinoma (OSCC) has a high prevalence and predicted global mortality rate of 67.1%, necessitating better therapeutic strategies. Moreover, the recurrence and resistance of OSCC after chemo/radioresistance remains a major bottleneck for its effective treatment. Molecular targeting is one of the new therapeutic approaches to target cancer. Among a plethora of targetable signaling molecules, PDK1 is currently rising as a potential target for cancer therapy. Its aberrant expression in many malignancies is observed associated with glycolytic re-programming and chemo/radioresistance. Methods: Furthermore, to better understand the role of PDK1 in OSCC, we analyzed tissue samples from 62 patients with OSCC for PDK1 expression. Combining in silico and in vitro analysis approaches, we determined the important association between PDK1/CD47/LDHA expression in OSCC. Next, we analyzed the effect of PDK1 expression and its connection with OSCC orosphere generation and maintenance, as well as the effect of the combination of the PDK1 inhibitor BX795, cisplatin and radiotherapy in targeting it. Results: Immunohistochemical analysis revealed that higher PDK1 expression is associated with a poor prognosis in OSCC. The immunoprecipitation assay indicated PDK1/CD47 binding. PDK1 ligation significantly impaired OSCC orosphere formation and downregulated Sox2, Oct4, and CD133 expression. The combination of BX795 and cisplatin markedly reduced in OSCC cell’s epithelial-mesenchymal transition, implying its synergistic effect. p-PDK1, CD47, Akt, PFKP, PDK3 and LDHA protein expression were significantly reduced, with the strongest inhibition in the combination group. Chemo/radiotherapy together with abrogation of PDK1 inhibits the oncogenic (Akt/CD47) and glycolytic (LDHA/PFKP/PDK3) signaling and, enhanced or sensitizes OSCC to the anticancer drug effect through inducing apoptosis and DNA damage together with metabolic reprogramming. Conclusions: Therefore, the results from our current study may serve as a basis for developing new therapeutic strategies against chemo/radioresistant OSCC.
Trip Purposes Mining From Mobile Signaling Data

With the widespread application of mobile phones, it has become possible to study human mobility and travel behaviors based on cellular network data. Contrary to call detail records, the data is triggered by mobile cellular signaling and can provide fine-grained information about users’ daily routines. However, it does not explicitly provide semantic details about traveling traces, e.g., trip purposes. In this paper, we propose a methodological framework to handle large-scale cellular network data and discover the underlying trip purposes in an unsupervised way. We first devise heuristic rules to identify home/work purposes. Then, a flexible latent Dirichlet allocation (LDA) model is presented to discover the activities for remaining trips, in which each trip is depicted by four attributes, i.e. arrival time, age group, stay duration, and the point of interest tag for the destination. Experimental results show that the proposed method can identify diverse trip purposes by explaining their structures over trip attributes and outperform baselines in terms of log-likelihood and perplexity. We also analyze the difference between the automatically discovered trip purposes and those estimated from household census, and the analyzed results demonstrate the feasibility of our proposed method.
A Comprehensive Review of HLA and Severe Cutaneous Adverse Drug Reactions: Implication for Clinical Pharmacogenomics and Precision Medicine

Human leukocyte antigen (HLA) encoded by the HLA gene is an important modulator for immune responses and drug hypersensitivity reactions as well. Genetic polymorphisms of HLA vary widely at population level and are responsible for developing severe cutaneous adverse drug reactions (SCARs) such as Stevens–Johnson syndrome (SJS), toxic epidermal necrolysis (TEN), drug reaction with eosinophilia and systemic symptoms (DRESS), maculopapular exanthema (MPE). The associations of different HLA alleles with the risk of drug induced SJS/TEN, DRESS and MPE are strongly supportive for clinical considerations. Prescribing guidelines generated by different national and international working groups for translation of HLA pharmacogenetics into clinical practice are underway and functional in many countries, including Thailand. Cutting edge genomic technologies may accelerate wider adoption of HLA screening in routine clinical settings. There are great opportunities and several challenges as well for effective implementation of HLA genotyping globally in routine clinical practice for the prevention of drug induced SCARs substantially, enforcing precision medicine initiatives.
Facile Synthesis of Copper Oxide-Cobalt Oxide/Nitrogen-Doped Carbon (Cu2O-Co3O4/CN) Composite for Efficient Water Splitting

Herein, we report a copper oxide-cobalt oxide/nitrogen-doped carbon hybrid (Cu2O-Co3O4/CN) composite for electrochemical water splitting. Cu2O-Co3O4/CN is synthesized by an easy two-step reaction of melamine with Cu2O-Co3O4/CN composite. The designed composite is aimed to solve energy challenges by producing hydrogen and oxygen via electrochemical catalysis. The proposed composite offers some unique advantages in water splitting. Carbon imparts superior conductivity, while the water oxidation abilities of Cu2O and Co3O4 are considered to constitute a catalyst. The synthesized composite (Cu2O-Co3O4/CN) is characterized by SEM, EDS, FTIR, TEM, and AFM in terms of the size, morphology, shape, and elemental composition of the catalyst. The designed catalyst’s electrochemical performance is evaluated via linear sweep voltammetry (LSV) and cyclic voltammetry (CV). The Cu2O-Co3O4/CN composite shows significant electrocatalytic activity, which is further improved by introducing nitrogen doped carbon (current density 10 mA cm−2, onset potential 91 mV, and overpotential 396 mV).
Moving Target Defense Based on Adaptive Forwarding Path Migration for Securing the SCADA Network

Static characteristics of supervisory control and data acquisition (SCADA) system are often exploited to perform malicious activities on smart grids. Most of the time, the success of cyberattacks begins with the profiling of the target system and follows by the analysis of the limited resources. To alleviate the asymmetry between attack and defense, network-based moving target defense (MTD) techniques have been applied in the network system to defend against cyberattacks by constructing a dynamic attack surface to the adversary. In this paper, we propose a novel MTD technique based on adaptive forwarding path migration (AFPM) that focuses on improving the defense capability and optimizing the network performance of path mutation. Considering the transient problems present in path mutation caused by the dynamic switching of the forwarding path, we formalize the mutation constraints based on the satisfiability modulo theory (SMT) to select the mutation path. Considering the limited defense capability of path mutation owing to the traditional mutation selection mechanism, we design the mutation path generation algorithm based on the network security capacity matrix to obtain an optimal combination of mutation path and mutation period. Finally, we compare and analyze various cyber defense techniques used in the SCADA network and demonstrate experimentally that our MTD technique can prevent more than 92% of passive monitoring under specified conditions while ensuring the quality of service (QoS) to be almost the same as the static network.
The SKBR3 Cell-Membrane Proteome: Role in Aberrant Cancer Cell Proliferation and Resource for Precision Medicine Applications

The plasma membrane proteome resides at the interface between the extra- and intra-cellular environment and through its various roles in signal transduction, immune recognition, nutrient transport, and cell-cell and cell-matrix interactions plays an absolutely critical role in determining the fate of a cell. Our work was aimed at exploring the landscape of the cancer cell-membrane proteome responsible for sustaining uncontrolled cell proliferation, and its intrinsic resources for enabling detection and therapeutic interventions. SKBR3/HER2+ breast cancer cells were used as a model system and mass spectrometry for characterizing the proteome. The number of identified cell-membrane proteins exceeded 2,000, with ~1,300 being matched by two or more unique peptides. Classification in four major categories, i.e., proteins with receptor or enzymatic activity, CD antigens, transporters, and cell adhesion proteins, uncovered overlapping roles in biological processes that drive cell growth, apoptosis, differentiation, immune response, adhesion and migration, as well as capabilities for signaling crosstalk and alternate pathways for proliferation. The large number of tumor markers (>50) and putative drug targets (>100) exposed a vast potential for yet unexplored detection and targeting opportunities, whereas the presence of 15 antigen immunological markers enabled an assessment of epithelial, mesenchymal or stemness characteristics. Serum-starved cells displayed altered processes related to mitochondrial OXPHOS/ATP synthesis, protein folding and localization, while serum-treated cells exhibited attributes that support tissue invasion and metastasis. Altogether, our findings advance the understanding of the biological triggers that sustain aberrant cancer cell proliferation, survival and development of resistance to therapeutic drugs, and reveal the vast innate opportunities for guiding immunological profiling and precision medicine applications aimed at target selection or drug discovery.
Halophiles

Halophiles are extremophilic salt-loving microorganisms that can survive in an extremely high level of salinity (10-30% NaCl). They belong to all three groups (i.e., bacteria, archaea, and eukaryotes). Halophiles tolerate high salt concentration due to unique cellular adaptations like salt-in strategy, compatible solute strategy, and enzyme adaptations. The chapter describes the classification, physiology, ecology, and mechanisms of adaptations and biotechnological applications of halophiles.
CLASSIFICATION OF STAGES OF ALZHEIMER’S DISEASE USING DEEP RESIDUAL NEURAL NETWORK

—Alzheimer’s disease is a sort of neurological disorder that causes the brain to shrink (atrophy) and the death of brain cells.Though Alzheimer’s disease (AD) has no immediate cure, a correct early diagnosis is vital for both the patient and social care. We have proposed a Convolutional Neural Network-based architecture for the diagnosis of the Alzheimer’s disease.The Training and testing is carried out with Magnetic resonance imaging (MRI) dataset obtained from Kaggle.These images are pre-processed and segmented using a UNet model, the segmented image is further optimized using Adam optimizer. It is then trained and classiﬁed using the Residual Neural Network(ResNet50) model which produces a 4-way classiﬁer to classify Alzheimer’s (AD),based on it’s stages.The suggested approach can be used to accurately diagnose the disease based on the positive results obtained.As a consequence, new ﬁndings for disease multiclass classiﬁcation are obtained.
Predicting Elections

This chapter covers the major types of election forecasting, as they have been applied in the United States and other democracies. For the most part, electoral forecasts have relied on three approaches. In the order in which they have emerged, these are prediction markets, pre-election polls, and structural models. In the last few years, Google searches, Facebook, and Twitter have also been exploited by election forecasters. The handbook chapter describes the various methods and evaluates their successes and failures. Of particular interest is the widespread failure of nearly all approaches to predict the election of Donald Trump. The postmortem is still ongoing. It remains to be seen what can be done to make election forecasting more accurate and thus more trustworthy.
Dynamic Wireless Charging of Medium Power and Speed Electric Vehicles

For a broad range of industrial, service, and household electric vehicles, dynamic charging is a viable option for energy replenishing that could reduce the size of the onboard energy storage, remove range limitations, and increase operating time. For these systems, timely detection of an approaching vehicle and the detection of strong coupling conditions between transmitter and receiver coils are of prime interest. A novel method is proposed in this article, which utilizes the existing embedded transmitter coil and power electronics modules to establish a precise detection system based on the power footprint of a traveling receiver. Next, a control algorithm is proposed to control charger activation and deactivation time accurately and deliver the required energy during the maximum coupling of the coils. The proposed sigmoid-curve-based control algorithm achieves a robust, speed-independent, smooth transition between two states while providing fast dynamics for aligned and misaligned conditions. Finally, a novel approach to test high-speed dynamic charging in laboratory conditions based on the receiver emulator is developed and used for experimental validation. The vehicle detection and control techniques have been validated through simulations and experimentally on a speed-controlled dynamic charging test station for a wide speed range. The proposed method does not require any additional hardware, sensing devices, or high-speed communication between the vehicle and the charging infrastructure.
5 Post-processing methods for passivity enforcement

: Many physical systems are passive (or dissipative): they are unable to generate energy on their own, but they can store energy in some form while exchanging power with the surrounding environment. This chapter describes the most prominent approaches for ensuring that Reduced Order Models are passive, so that their math-ematical representation satisfies an appropriate dissipativity condition. The main focus is on Linear and Time-Invariant (LTI) systems in state-space form. Different conditions for testing passivity of a given LTI model are discussed, including Linear Matrix Inequalities (LMIs), Frequency-Domain Inequalities, and spectral conditions on associated Hamiltonian matrices. Then we describe common approaches for perturbing a given non-passive system to enforce its passivity. Various examples from electronic applications are used to demonstrate both theory and algorithm performance.
PLUMMETING CONSUMERS' BRAND SWITCHING BEHAVIOUR USING A HOLISTIC PRODUCT STRATEGY IN THE ZIMBABWEAN COLA INDUSTRY

The study was driven by the need to elevate consumers switching costs so as to minimise consumer churning behaviour. The purpose of this study was to examine the effect of the product strategy on consumers brand switching intention behaviour. A marketing orientation of managing a product from a holistic approach was adopted and that was informed by previous theoretical modelling. The study followed a quantitative approach in the cola industry in Zimbabwe. Data was collected using questionnaires from a sample size of 432 respondents. Structural Equation Modeling (SEM) - Amos Graphics was used to analyse data. The study confirmed that a holistic approach to product strategy is statistically significant in minimising churning behaviour of customers. Product availability and product quality were inversely influencing behavioural intention to switch brands whilst product price recorded a significant positive impact. Product range had an insignificant association with consumer attrition. The study concluded that consumers switching behaviour can be managed through a well implemented product strategy. To plummet brand switching behaviour, the study recommends effective product pricing, effective product distribution and improvements in product quality.
Blood cell gene expression profiles: A narrative review of biomarkers and effects of low-dose ionizing radiation exposure

Ionizing radiation (IR) is a ubiquitous environmental agent whose effects on organisms are well known. This review provides a summary about definitions and man-made low-dose ionizing radiation (LDIR) sources and dosimeters used in radiation protection. Moreover, the main purpose of this article was to overview the pro-oncogenic effects of LDIR, and to provide experimental evidence that reinforce the use of gene expression data as biomarkers of LDIR effects. Our review showed that basic studies on biological response to LDIR are considered priority. Further, understanding occupational exposure to LDIR may provide valuable information to organize the prevention and prevent from the onset of long-term health effects in radiation workers. Currently, the biodosimetry-based assessment in certain high-risk occupational groups may be performed by using peripheral blood cells as samples for testing and validation of biomarkers specificity and sensitivity. Most of the studies on this topic are aimed at establishing new biomarkers and approaches to biological dosimetry, for allowing non-invasive monitoring of long-term health effects of LDIR. Analysis on changes in gene-expression, which is an early specific biological response to LDIR, could provide rapid estimates of individual dose in occupational cohorts, improving the management of periodical medical examination in subjects exposed to LDIR sources. Journal of Health and Social Sciences 2021; 6,3:349-366 The Italian Journal for Interdisciplinary Health and Social Development
RELAȚIA DINTRE FACTORII DE PERSONALITATE BIG FIVE ȘI DEPENDENȚA DE GAMING

As we can see the significant increase in the number of video games on the market, but also an increase in the number of people who choose to relax in a virtual world at the expense of reality. In this context, present study has the primary objective of discovering whether any of the Big Five personality components can predict gaming addiction. A total of 137 respondents aged between 10 and 55 participated in the data collection. As a result of the data analysis, the neuroticism factor explains 28% of the gaming addiction variable (R2 = .28, p <0.01) and the introversion factor variance explains 4% of the gaming addiction variable (R2 = .04, p <0.05). The rest of the personality factors did not correlate significantly with the gaming addiction variable. The types of video games did not moderate the relationship between emotional stability and gaming addiction.
CCL3 Promotes Proliferation of Colorectal Cancer

Background: Chemokines and their receptors can be expressed on the surface of inflammatory cells and malignant tumor cells in the body. Tumor cells can participate in directional organ metastasis by means of the ‘navigation effect’ of chemokines. Recent studies have found that chemokine C-C motif chemokine ligand 3 (CCL3) plays an important role in the invasion and metastasis of malignant tumors. Determining the effect of chemokine CCL3 and the related cytokine network on colorectal cancer is helpful in developing new therapeutic targets and anti-tumor drugs, as well as improving the survival rate of patients. Methods: In this study, protein chip technology was used to examine colorectal cancer tissue samples and identify the key factors of chemokine CCL3 and the toll-like receptors/nuclear factor-κB (TLR/NF-κB) pathway in cancer and metastatic lymph nodes. In addition, we used lentiviral vector technology for transfection to construct interference and overexpression cell lines. The aim of this experiment was to analyze the mechanism of CCL3 and TNF receptor associated factor 6 (TRAF6)/NF-κB pathway-related factors and their effect on the proliferation of colon cancer cells. Finally, the expression and significance of CCL3 in colorectal cancer tissues and its correlation with clinical pathology were studied by immunohistochemistry. Results: The results confirmed that CCL3 and C-C motif chemokine receptor 5 (CCR5) were expressed in adjacent tissues, colorectal cancer tissues, and metastatic cancer. The expression level was correlated with clinical stage and nerve invasion. Conclusions: The expression of chemokine CCL3 and receptor CCR5 was positively correlated with the expression of TRAF6 and NF-κB, and could promote the proliferation, invasion, and migration of colorectal cancer cells through TRAF6 and NF-κB.
Enzyme Assisted Extraction, Purification and Structure Analysis of the Polysaccharides from Naked Pumpkin Seeds

Enzyme assisted extraction was used to extract the polysaccharides from pumpkin seeds (PSP) and the extraction parameters were optimized by response surface methodology (RSM). Under the optimum experimental parameters: Extraction temperature of 60 °C, extraction time of 43 min, enzyme concentration of 2.5%, and pH of 6.0, the yield of PSP was 3.22 ± 0.04%, which was in close agreement with the predicted value (3.24%). After further purification on anion exchange column and gelfiltration column, a novel purified polysaccharide (PSPE) with molecular weight of 16,700 g/mol was obtained. PSPE was mainly composed of mannose, galactose and glucose in the molar ratio of 1.00:3.84:1.62. NMR spectra analysis showed that the major backbone of PSPE consisted of →4)-α-d-Glcp-(1→, →4)-β-d-Manp-(1→, →3,6)-β-d-Glap-(1→, and β-d-galactose.
Queue Management Benchmark for Modelling Patients' Flow in Nigerian Public Hospitals

Although queue management in hospitals is widely researched, little is known about the benchmark for modelling patients flow in terms of the optimal number of servers required for effective service delivery. This study applied the queuing theory to the Nigerian public hospitals by setting a benchmark for modelling patients flow. A mixture of survey and observation was adopted to garner data for 30 days from patients in six public hospitals in Nigeria. Data were subjected to performance analysis via the Temporary Ordered Routine Algorithm. The computed performance values were further compared with their acceptable benchmarks for multi-server queues through the General Purpose System Simulator. We found the queuing system in the select hospitals not in congruence with the system performance benchmark; the mean service rate in each facility was low compared to the mean arrival rate; and the simulated number of doctors for were below the modelled benchmark. Managerial implications of findings were discussed.
Tear Film Stability After Primary Pterygium Excision Combined with Limbal Stem Cell Transplantation is Superior to Amniotic Membrane Transplantation: A Meta-Analysis

Purpose To evaluate the tear film stability after primary pterygium excision combined with Limbal stem cell transplantation (LSCT) or amniotic membrane transplantation (AMT). Methods We searched the PubMed, EMBASE, Web of Science, Cochrane Library, CNKI, Wan Fang and VIP databases for all studies on tear film stability after primary pterygium excision combined with LSCT or AMT. The mean difference (MD) and 95% confidence interval (CI) were calculated for outcomes using the fixed effect or random effect model.Results Seven studies with a total of 531 eyes were enrolled in our meta-analysis, which revealed that comparison between the LSCT group and the AMT group: Ocular Surface Disease Index (OSDI) 3 months postoperatively (MD=-5.16, 95%CI:-6.48,-3.85, P＜0.05), Tear break-up time (BUT) 1 or 3 months postoperatively (1 month: MD=0.30, 95%CI:-0.66,1.26, P=0.54; 3 months: MD=1.30, 95%CI:-0.13,2.72, P=0.07), Schirmer I test 1 or 3 months postoperatively (1 month: MD=0.05, 95%CI:-0.41,0.51, P=0.82; 3 months: MD=1.41, 95%CI:0.81,2.02, P＜0.05), Corneal fluorescein staining (CFS) score 1 month postoperatively (MD=-0.49, 95%CI:-1.29,0.31, P=0.23). Conclusion Primary pterygium excision combined with LSCT is associated with better tear film stability changes than AMT.