Miracle-dz/UniFAR-FTUs huggingface dataset:
Dexamethasone differentially depletes tumour and peripheral blood lymphocytes and can impact the efficacy of chemotherapy/checkpoint blockade combination treatment

ABSTRACT Dexamethasone is a synthetic glucocorticoid commonly used for the prevention and management of side effects in cancer patients undergoing chemotherapy. While it is effective as an anti-emetic and in preventing hypersensitivity reactions, dexamethasone depletes peripheral blood lymphocytes and impacts immune responses. The effect of dexamethasone on the number and quality of tumour-infiltrating leukocytes has not been reported. To address this, we calibrated the dose in two different strains of mice to achieve the same extent of peripheral blood lymphocyte depletion observed in patients with cancer. Doses that caused analogous depletion of T and B lymphocytes and NK cells from the peripheral blood, elicited no change in these populations within the tumour. The expression of immune checkpoint molecules PD-1, OX40, GITR and TIM3 on tumour-infiltrating lymphocytes was not altered. We found that dexamethasone had a small but significant deleterious impact on weakly efficacious chemoimmunotherapy but had no effect when the protocol was highly efficacious. Based on these results, we predict that dexamethasone will have a modest negative influence on the overall effectiveness of chemoimmunotherapy treatment.
lncRNA-CCDC26, as a novel biomarker, predicts prognosis in acute myeloid leukemia

The aim of the present study was to examine the expression and clinical significance of long non-coding RNA (lncRNA)-CCDC26 in patients with acute myeloid leukemia (AML), and to investigate the potential functions of CCDC26. The Gene Expression Omnibus database and reverse transcription-quantitative polymerase chain reaction analysis were used to detect the expression levels of CCDC26 in patients with AML and healthy volunteers. Clinical data for 93 patients with AML were collected to analyze the clinical significance of CCDC26. Weighted gene co-expression network analysis (WGCNA), a protein-protein interaction (PPI) network, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to examine the functions of CCDC26. The expression levels of CCDC26 in the initially diagnosed and relapsed patients with AML were significantly upregulated compared with the control group. The upregulated expression level of CCDC26 in patients with AML was significantly associated with age, anemia, risk stratification and remission. Furthermore, patients with a high CCDC26 expression level had a poorer overall survival (P=0.0105). In addition, the area under the curve (AUC)1year and AUC2year of CCDC26 for overall survival were 0.722 and 0.686, respectively. WGCNA, PPI network and KEGG pathway analysis revealed that CCDC26 was involved in the regulation of a number of biological processes. lncRNA-CCDC26 may serve as a novel biomarker for monitoring the progression and predicting the clinical outcome of AML.
Hand gesture recognition using sparse autoencoder-based deep neural network based on electromyography measurements

Hand gesture recognition has recently grown as a powerful technical means in human-machine interaction field for control the appliances such as in home automation. However, the accuracy recognition of diverse hand gestures is still in the early stage for real-world application. In this paper, we present a new gesture recognition framework which is capable of classifying ten different hand gestures based on the input signals from surface electromyography (sEMG) sensors. The multi-channel signals of a hand motion are simultaneously captured and transmitted to a PC via Bluetooth wireless protocol. The proposed recognition framework composes of three main steps: gesture sequence segmentation, feature extraction by sparse autoencoder, and deep neural network (DNN) based classification. The advantage of the proposed approach is the automated abstract feature extraction based on sparse autoencoder method. Combined with the DNN classification technique, we could achieve a better recognition performance tested on the dataset consisting of ten types of hand gestures compared with other classification methods.
Speech Synthesis for Text-Based Editing of Audio Narration

Recorded audio narration plays a crucial role in many contexts including online lectures, documentaries, demo videos, podcasts, and radio. However, editing audio narration using conventional software typically involves many painstaking low-level manipulations. Some state of the art systems allow the editor to perform select, cut, copy and paste operations in the text transcript of the narration and apply the changes to the waveform accordingly. However such interfaces do not support the ability to synthesize new words not appearing in the transcript. While it is possible to build a high fidelity speech synthesizer based on samples of a new voice, to operate well they typically require a large amount of voice data as input as well as substantial manual annotation. This thesis presents a speech synthesizer tailored for text-based editing of narrations. The basic idea is to synthesize the input word in a different voice using a standard pre-built speech synthesizer and then transform the voice to the desired voice using voice conversion. Unfortunately, conventional voice conversion does not produce synthesis with sufficient quality for the stated application. Hence, this thesis introduces new voice conversion techniques that synthesize words with high individuality and clarity. Three methods are proposed: the first approach is called CUTE, a data-driven voice conversion method based on frame-level unit selection and exemplar features. The second method called VoCo is built on CUTE but with several improvements that help the synthesized word blend more seamlessly into the context where it is inserted Both CUTE and VoCo select sequences of audio frames from the voice samples and stitch them together to approximate the voice being converted. The third method improves over VoCo with deep neural networks. It involves two networks: FFTNet generates high quality waveforms based on acoustic features, and TimbreNet transforms the acoustic feature of the generic synthesizer voice to that of a human voice. iii
Prevalence of Syphilis among Pregnant Women Attending Antenatal Care Clinic, Sede Muja District, South Gondar, Northwest Ethiopia

Background Syphilis is a disease caused by bacteria called Treponema pallidum. Major rout of transmission of this bacterium was through sexual and contact with mucocutaneous lesion. Untreated syphilis during pregnancy can greatly affect pregnancy outcome, resulting in spontaneous abortion and stillbirth. Objective The objective of the study was to determine the seroprevalence of syphilis and associated factors among pregnant women attending antenatal care unit at Sede Muja district, Northern Ethiopia. Methods and Materials Facility based cross-sectional study was conducted from November 2018 to January 2019 in two health centers from Sede Muja district, Northwest Ethiopia. The study included a total of 210 participants. The entire participants were recruited by systematic random sampling method after proportional allocation of the sample size in the two health centers. Sociodemographic and clinical data were collected by semistructured questioner. Two milliliter of blood was collected to determine seroprevalence of syphilis using VDRL test method. The data was analyzed by using SPSS version 21. The association between independent and dependent variables was determined using chi-square. P-value less than 0.05 was considered as statistically significant. Result Seroprevalence of syphilis was found to be 1.9% (95 CI, 0.5-3.5%). Women with multiple sexual partners and late trimester of pregnancy during first ANC visit were found to be significantly associated with seropositive syphilis. Conclusion Syphilis remains a major problem in the study area. Seroprevalence of syphilis was significantly associated with women who have multiple sexual partners and late first ANC visit attendees in the study area. Therefore it is recommended to give health education about syphilis etiology and transmission as well as creating awareness about the importance of early ANC visit and follow-up regarding syphilis prevention.
Biochemical Alteration and Immunohistochemical Characterization of Lymphoid Cells Involved in Type 2 Diabetes Mellitus

T cells are crucial for the inflammation development of metabolic disorder and insulin resistance and the cytokines of T cells are considered as an excellent evaluating tools for the immune system activity in many diseases. As cytokine profile associates with the development of type-2 diabetes mellitus (T2-DM) is well understood the link between this disease and the involved immune cells still unclear. Therefore, it was hypothesized that Th1 pathway is disrupted in the pathogenesis of type 2DM. As such, we aimed to evaluate IL-12, which induces Th1 pathway, and IL-2 which mediates Th1 function. Paraffin-embedded sections of peripheral blood lymphocytes with T2-DM patients were stained with antibodies against CD4 and CD8. Computerized image analysis was used to calculate areas of stained lymphocytes taken from diabetic and control patients. Clinical data and blood samples were collected from Eighty-one (37.6±13.9 years old) diabetic Egyptian patients and 103 (40.5±12.7 years old) of normal control volunteer to evaluate the level of serum interleukin IL-2 and IL-12 in their blood by using ELISA technique. Routine laboratory analysis, including fasting blood glucose, CRP, lipid profile, fasting insulin, and CBC for each patient were measured. Immunohistochmical results in 2DM showed an increase in the numbers of CD8+ cells with a decrease in the numbers of CD4+ cells displayed. Diabetic patients showed decreased and increased values of IL-2 and IL_12, respectively as compared to control values. Conclusion: This data indicate the importance of these two cytokines in the pathogenesis of type-2 Diabetes mellitus. Article history: Received: March 18, 2019 Revised: April 5, 2019 Accepted: April 11, 2019
Sole‐ground contact and sitting leg position influence suprahyoid and sternocleidomastoid muscle activity during swallowing of liquids

Clinically, the stable sole‐ground contact in the diet is considered as important for achieving safe swallows in the dysphagic patients. However, the effects of varied sole‐ground contacts on swallow‐related muscles activities remain unclear. The aim of this study was to investigate the effects of sole‐ground contacts on the muscle activities during swallow for various materials; 26 healthy adult subjects participated in this study. Three different sole‐ground contact conditions were investigated; sole‐ground contact with knees bent to 90° (KB 90°), sole‐ground contact with knees bent to 135° (KB 135°), and sole‐ground off the floor (Off). Participants swallowed four bolus materials (saliva, 5‐ml water, 10‐ml water, and 5‐ml yogurt) in each sole‐ground contact condition. The muscular activities of the suprahyoid (SH) muscle and the sternocleidomastoid muscle during swallowing were detected and recorded using surface electromyography. The sole‐ground contact pressure was evaluated using the data acquisition system. Duration of SH during 10‐ml water swallow for Off was significantly longer than that for KB 90°. Duration of SH during 5‐ml yogurt swallow for Off was significantly longer than that for KB 90°. Integration of SH during 10‐ml water swallow for Off was significantly greater than that for KB 135°. Integration of SH during 5‐ml yogurt swallow for Off was significantly greater than that for KB 90°. No significant differences were found in peak of SH. Sole‐ground contact conditions had significant effect on swallow‐related muscles activities. The stable sitting positions might be more advantageous for performing effective swallows compared with less stable sitting positions.
Bit error rate performance of underwater channels for OFDM data

In underwater acoustic communication, the energy received is a combination of energies contributed by different rays traversing through different paths due to multiple reflections of the waves at the boundaries, which results in Inter Symbol Interference (ISI). Orthogonal Frequency Division Multiplexing (OFDM), which is a multicarrier modulation technique, is widely employed nowadays. Its advantages include resilience to Inter Symbol Interference, immunity to selective fading, simpler channel equalization, etc. Sea trials being very expensive, underwater acoustic communication scenario can be simulated with any of the available toolboxes. In the simulation studies, Bellhop has been used for generating the channel impulse response based on the assumed environmental conditions. In this paper, OFDM performance has been simulated in underwater communication scenario using 16-QAM and 16-PSK modulation methods. From the simulation studies, it has been observed that 16-QAM based OFDM offers lower bit error rates than that for the 16-PSK based OFDM.
Advanced polymer-based drug delivery systems for chemotherapy

The research in this thesis attempts to help reduce the side effects of current cancer treatments via targeted drug delivery. This was achieved by developing advanced polymer-based delivery systems for chemotherapeutic agents by using different techniques such as: electrohydrodynamic techniques, which include electrospinning and electrospraying, in addition to spray drying. The fabrication of fibres and particles was achieved using single fluid electospinning and electrospraying as well as to side-by-side structures and triaxial fibres. Chapter 1 is a brief introduction of cancer and its current treatments where their benefits and limitations are critically discussed. Then, the importance and advantages of drug delivery systems in cancer therapeutics are explored. Finally, the fabrication of these delivery systems by electrospinning and spray drying is reviewed. After a detailed overview of the research field, the scientific gaps are identified and the overall aims of the experimental work on this thesis are outlined. In Chapter 2, electrospinning and electrospraying techniques were used to generate drug-loaded Janus fibres and particles made of polyvinylpyrrolidone (PVP) by using a side-by-side spinneret. A photo-chemotherapeutic formulation was created by using rose bengal and carmofur, where the formulation created by electrospraying achieved a high selectivity towards lung cancer cells. Chapter 3 describes the production of formulations in the form of fibres or particles composed of a polyvinylpyrrolidone (PVP) matrix and tristearin (GTS) by electrohydrodynamic techniques. These precursor formulations were used as templates to fabricate aqueous-dispersible, drug loaded SLNs. Indomethacin (BCS class 2), and 5FU a chemotherapeutic agent were used. Chapter 4, builds on the work from Chapter 3, and details the scale-up production of the polymer-based templates to create SLNs, it also compares the electrohydrodynamic techniques with spray drying. Chapter 5 focuses on using triaxial electospinning to create a template which upon hydration self-assembles in snowman Janus nanoparticles. These Janus nanoparticles create a photo chemotherapy formulation, which constitutes of a micelle containing hematoporphyrin and a liposome entrapping carmofur.
The Scale and Characteristics Strength of SURF Feature Points Adaptive Matching Algorithm

In order to improve the matching precision of the SURF image feature points, we study the relationship among the scale of the SURF feature points, the characteristics of strength and matching precision. Then, a feature point matching algorithm of SURF image feature is proposed, which is adaptive to the feature point scale and characteristic strength. On the basis research of the scale and characteristics strength of SURF feature points, we found that the larger the scale of feature points set, the lower the matching precision will be; and the higher the intensity of characteristic, the matching precision are higher, but the number is less. Therefore, the using of the adaptive algorithm which can match the different scales of feature points with different characteristics strength threshold can keep the balance between the feature point matching precision and the quantity of matching feature points pairs, and realize the high precision of SURF feature points matching. The experimental shows that, compared with the traditional algorithm of SURF, this algorithm can obtain more precise matching feature points pairs.
Assessment of ranking algorithms in complex networks

A particularly helpful search of a network such as the Internet or a citation network not only finds nodes that satisfy some criteria but also ranks those nodes for importance to create what amounts to a “reading list”. In the recent past, there has been a large interest across a number of research communities in the analysis of complex networks. The selected set of pages from the World Wide Web can be modeled as a directed graph, where nodes are designated as individual pages, and the links as a connection between them. As the number of webpages to be ranked is in the billions, the computation is time-consuming and can take several days or more. Algorithms like PageRank, HITS, SALSA and their modifications has a challenge to deal with the size of the processed data. The need for accelerated algorithms is clear. This article presents the characteristics of three best known ranking algorithms and the assumptions for new algorithm development with first test runs.
Wireless sensor network-based improved NPW leakage detection algorithm for real-time application in pipelines

With increasing population in South Africa coupled with improved standard of living, the demand for water has increased dramatically in the past few years. To meet this demand and for effective water supply, the water loss through leakages of pipelines transporting this resource needs to be reduced. This paper briefly elaborates on work in progress employing wireless sensor networks (WSNs) to an improved negative pressure wave method for real-time leakage monitoring of a water pipeline network. Keywords— Leakage detection techniques, pipelines, water loss,
Mutation Spectrum of Cancer-Associated Genes in Patients With Early Onset of Colorectal Cancer

Background: Colorectal cancer (CRC) incidence is rising worldwide, as well as in the Republic of Kazakhstan, while its occurrence is also increasing in the younger population. Hereditary forms associated with the development of colon and rectal cancer and early-onset CRC have never been studied in the population of Kazakhstan. The aim of this research was to investigate the spectrum of CRC-related gene mutations to determine which mutations cause early onset of CRC in the Kazakhstan population. Methods: The study included 125 unrelated patients from Kazakhstan (range 17–50 years in age) with early onset CRC. Genomic DNA was obtained from peripheral blood of the patients. Next-generation sequencing was performed using the TruSightCancer Kit on the MiSeq platform. The Studio Variant was used to annotate and interpret genetic variants. Results: Bioinformatics analysis of Next-generation sequencing data revealed 11,152 variants from 85 genes, of them, 3,790 missense, 6,254 synonymous variants, 44 3′UTR variants, 10 frameshift variants, five stop-gain variants, four in-frame deletions, two splice donors, one splice acceptor variant, and 1,042 intron or non-coding variants. APC, BRCA2/1, ALK, BRIP1, EGFR, FANCA, FANCD2, FANCI, HNF1A, MEN1, NSD1, PMS2, RECQL4, RET, SLX4, WRN, and XPC genes mutated most often. According to the ACMG guidelines and LOVD/ClinVar databases, 24 variants were pathogenic (10 frameshifts, five missenses, five stop-gain, one in-frame deletion, and three splice-site mutations), and 289 were VUS with population frequency <1%, 131 of them were attributed as deleterious. In the study, 50% of all pathogenic mutations found in Kazakhstani patients with early CRC onset were identified in the subgroups with a family history of CRC and primary multiple tumors. In APC, pathogenic mutations were most often (21%). Conclusion: Pathogenic and likely pathogenic mutations were found in 20 (16%) out of 125 patients. Eight novel pathogenic mutations detected in FANCI, APC, BMPR1, ATM, and DICER1 genes have not been reported in previous literature. Given the high frequency and wide spectrum of mutations, NGS analysis must be carried out in families with a history of CRC/CRC-related cancers with the purpose to identify cause-effective mutations, clarify the clinical diagnosis, and prevent the development of the disease in other family members.
Programming Spreadsheets in Natural Language: Design of a Natural Language User Interface

—In this paper, we present the idea to use the nat-ural language as the user interface for programming tasks. Programming languages assist with repetitive tasks that involve the use of conditionals, loops and statements. However, users can easily describe tasks in their natural language. We aim to develop a Natural Language User Interface that enables users to describe algorithms, including statements, loops, and conditionals. For this, we extend our current spreadsheet system to support control ﬂows. Although far from perfect, this research might lead to fundamental changes in computer use. With natural language, programming would become available to everyone. We believe that it is a reasonable approach for end-user software engineering and will, therefore, overcome the present bottleneck of IT proﬁcients.
Freezing of sputum as a way to improve the applicability of sputum studies

Rationale: Sputum examination is a valuable research tool to study airway diseases, but the requirement to process the samples within 2 hours of their collection poses limitations to its wider applicability. A way to bypass this hurdle would be to freeze the sample at the time of collection and to examine it at a later stage. Methods and Subjects: We developed a protocol for freezing of sputum upon collection by adding dimethylsulfoxide to it. We tested the reproducibility of cell counts in frozen samples and in fresh portions from the same sputum specimens. We took sputum from 41 asthmatics (18 males) with different levels of control of their disease: 19 of the samples were spontaneously produced and 22 were induced with hypertonic saline. Results: Significant correlations (p<0.05) were established between the total cell counts, the relative and absolute number of neutrophils, eosinophils and macrophages in the paired fresh and frozen sputum samples. Cell viability in frozen sputum was slightly but consistently lower. Only one frozen sample had viability < 50%. Outcomes in paired samples from induced sputum had better reproducibility than the spontaneous ones. Conclusion: Examination of frozen sputum samples does not change total cell counts and differential cell counts, despite consistently affecting cell viability compared with fresh sputum cellularity. Still cell viability in frozen sputum was above 50% in all but one examined specimens.
Intention Classification for Retrieval of Health Questions

Healthcare professionals have edited many health questions (HQs) and their answers for healthcare consumers on the Internet. The HQs provide both readable and reliable health information, and hence retrieval of those HQs that are relevant to a given question is essential for health education and promotion through the Internet. However, retrieval of relevant HQs needs to be based on the recognition of the intention of each HQ, which is difficult to be done by predefining syntactic and semantic rules. We thus model the intention recognition problem as a text classification problem, and develop two techniques to improve a learning-based text classifier for the problem. The two techniques improve the classifier by location-based and area-based feature weightings, respectively. Experimental results show that, the two techniques can work together to significantly improve a Support Vector Machine classifier in both the recognition of HQ intentions and the retrieval of relevant HQs.