Miracle-dz/UniFAR-FTUs huggingface dataset:
3D modeling and characterization of a calorimetric flow rate sensor for sweat rate sensing applications

Sweat-based physiological monitoring has been intensively explored in the last decade with the hopes of developing real-time hydration monitoring devices. Although the content of sweat (electrolytes, lactate, urea, etc.) provides significant information about the physiology, it is also very important to know the rate of sweat at the time of sweat content measurements because the sweat rate is known to alter the concentrations of sweat compounds. We developed a calorimetric based flow rate sensor using PolydimethylSiloxane that is suitable for sweat rate applications. Our simple approach on using temperature-based flow rate detection can easily be adapted to multiple sweat collection and analysis devices. Moreover, we have developed a 3D finite element analysis model of the device using COMSOL Multiphysics™ and verified the flow rate measurements. The experiment investigated flow rate values from 0.3 μl/min up to 2.1 ml/min, which covers the human sweat rate range (0.5 μl/min–10 μl/min). The 3D model simulations and analytical model calculations covered an even wider range in order to understand the main physical mechanisms of the device. With a verified 3D model, different environmental heat conditions could be further studied to shed light on the physiology of the sweat rate.Sweat-based physiological monitoring has been intensively explored in the last decade with the hopes of developing real-time hydration monitoring devices. Although the content of sweat (electrolytes, lactate, urea, etc.) provides significant information about the physiology, it is also very important to know the rate of sweat at the time of sweat content measurements because the sweat rate is known to alter the concentrations of sweat compounds. We developed a calorimetric based flow rate sensor using PolydimethylSiloxane that is suitable for sweat rate applications. Our simple approach on using temperature-based flow rate detection can easily be adapted to multiple sweat collection and analysis devices. Moreover, we have developed a 3D finite element analysis model of the device using COMSOL Multiphysics™ and verified the flow rate measurements. The experiment investigated flow rate values from 0.3 μl/min up to 2.1 ml/min, which covers the human sweat rate range (0.5 μl/min–10 μl/min). The 3D model simul.
Automated IoT Device Identification Based on Full Packet Information Using Real-Time Network Traffic

In an Internet of Things (IoT) environment, a large volume of potentially confidential data might be leaked from sensors installed everywhere. To ensure the authenticity of such sensitive data, it is important to initially verify the source of data and its identity. Practically, IoT device identification is the primary step toward a secure IoT system. An appropriate device identification approach can counteract malicious activities such as sending false data that trigger irreparable security issues in vital or emergency situations. Recent research indicates that primary identity metrics such as Internet Protocol (IP) or Media Access Control (MAC) addresses are insufficient due to their instability or easy accessibility. Thus, to identify an IoT device, analysis of the header information of packets by the sensors is of imperative consideration. This paper proposes a combination of sensor measurement and statistical feature sets in addition to a header feature set using a classification-based device identification framework. Various machine Learning algorithms have been adopted to identify different combinations of these feature sets to provide enhanced security in IoT devices. The proposed method has been evaluated through normal and under-attack circumstances by collecting real-time data from IoT devices connected in a lab setting to show the system robustness.
Repeated transarterial chemoembolization with epirubicin-loaded superabsorbent polymer microspheres vs. conventional transarterial chemoembolization for hepatocellular carcinoma

The aim of the present study was to evaluate the long-term outcomes and the impact of repeated conventional transarterial chemoembolization (C-TACE) and transarterial chemoembolization with epirubicin-loaded superabsorbent polymer embolics (SAP-TACE) on liver function in TACE-naïve patients with unresectable hepatocellular carcinoma (HCC). Overall, 155 consecutive patients with HCC received either C-TACE or SAP-TACE. The first cohort (n=71), treated between 2011 and 2014, received C-TACE; the second cohort (n=84), treated between 2014 and 2016, received SAP-TACE. Overall survival and deterioration of liver function were compared between the two cohorts. The 1-, 2- and 3-year overall survival rates and median survival times were 74, 50, 35% and 26 months in the C-TACE cohort and 75, 60, 39% and 28 months in the SAP-TACE cohort, respectively. There were no significant differences between the two groups (P=0.289). Age <70 years, Child-Pugh class A, alpha-fetoprotein <400 ng/ml and des-gamma-carboxy prothrombin <1,000 mAU/ml were identified as favorable prognostic factors in multivariate analysis. In the subgroup of patients with a Child-Pugh score of 5, survival was 29 months for C-TACE vs. 55 months for SAP-TACE (P<0.05). In the C-TACE cohort, the median Child-Pugh score was 6 after 3 cycles and 7 after 5 cycles of TACE, and the score worsened significantly (before vs. 3 cycles, P<0.05; before vs. 5 cycles, P<0.05). In the SAP-TACE cohort, the median Child-Pugh score was 6 after 3 and 5 cycles of TACE, and the score did not worsen during the treatment cycles. There were no differences in overall survival between repeated C-TACE and SAP-TACE in TACE-naïve patients with HCC. However, liver function deterioration was more evident in patients treated with C-TACE than in those treated with SAP-TACE.
Generation of Augmented Capillary Network Optical Coherence Tomography Image Data of Human Skin for Deep Learning and Capillary Segmentation

The segmentation of capillaries in human skin in full-field optical coherence tomography (FF-OCT) images plays a vital role in clinical applications. Recent advances in deep learning techniques have demonstrated a state-of-the-art level of accuracy for the task of automatic medical image segmentation. However, a gigantic amount of annotated data is required for the successful training of deep learning models, which demands a great deal of effort and is costly. To overcome this fundamental problem, an automatic simulation algorithm to generate OCT-like skin image data with augmented capillary networks (ACNs) in a three-dimensional volume (which we called the ACN data) is presented. This algorithm simultaneously acquires augmented FF-OCT and corresponding ground truth images of capillary structures, in which potential functions are introduced to conduct the capillary pathways, and the two-dimensional Gaussian function is utilized to mimic the brightness reflected by capillary blood flow seen in real OCT data. To assess the quality of the ACN data, a U-Net deep learning model was trained by the ACN data and then tested on real in vivo FF-OCT human skin images for capillary segmentation. With properly designed data binarization for predicted image frames, the testing result of real FF-OCT data with respect to the ground truth achieved high scores in performance metrics. This demonstrates that the proposed algorithm is capable of generating ACN data that can imitate real FF-OCT skin images of capillary networks for use in research and deep learning, and that the model for capillary segmentation could be of wide benefit in clinical and biomedical applications.
Perception and Demands of Pregnant and Breastfeeding Women Regarding Their Role as Participants in Environmental Research Studies

A significant proportion of scientific studies consider pregnant and breastfeeding women as vulnerable subjects. The objective of this study was to analyse the perception of pregnant and breastfeeding women regarding their participation in environmental research studies. Our work is a descriptive and interpretative observational study that has been developed under the qualitative research paradigm following a phenomenological and ethnographic perspective. The study involved 173 women selected intentionally in two Spanish autonomous communities. To obtain the primary data, we relied upon 111 interviews, four focused ethnographies and eight focus groups. The data encoding and analysis was carried out with the help of NVivo 12 software (QSR International, Boston, MA, USA). We evidenced the need of pregnant and breastfeeding women for more detailed and accurate information on the risk of environmental pollutant exposure during their crucial life stage. In addition, these women claimed for a more participatory role in research studies. Pregnant and breastfeeding women in Spain ask for greater interaction with researchers and propose a dialogical relationship between valid partners. We conclude that our pregnant and breastfeeding women claim more research focused on their collective, as well as clearer, more accessible and structured information on the risks of exposure to environmental contaminants. In addition, they do not want to simply be informants; rather, they ask to be active and empowered members by providing their opinions and arguments throughout the research process.
Detection of SARS-COV-2 Proteins Using an ELISA Test

The coronavirus disease 2019 (COVID-19) global pandemic created an unprecedented public health emergency. Early recognition of an infected person and disruption of the transmission pathway are the keys to controlling this major public health threat around the world. The scientifically reliable screening method is an RT-PCR test that is performed on an ororhinopharyngeal swab in the laboratory. In the current severe SARS-CoV-2 pandemic, it is necessary to identify devices for rapid diagnosis to reduce the spread of the disease. The aim of this study was to provide a qualitative, rapid, sensitive, and specific method for a diagnosis of SARS-CoV-2 infection based on the recognition of specific antigens of the SARS-CoV-2 virus. The device was built by assembling commercially available and custom-made semi-finished products. The method was performed in environments outside the laboratory, i.e., “patient side,” with an immediate chemocolorimetric response or with a digital reader using an ELISA method.
Pathophysiological In Vitro Profile of Neuronal Differentiated Cells Derived from Niemann-Pick Disease Type C2 Patient-Specific iPSCs Carrying the NPC2 Mutations c.58G>T/c.140G>T

Niemann-Pick type C2 (NP-C2) disease is a rare hereditary disease caused by mutations in the NPC2 gene. NPC2 is a small, soluble protein consisting of 151 amino acids, primarily expressed in late endosomes and lysosomes (LE/LY). Together with NPC1, a transmembrane protein found in these organelles, NPC2 accomplishes the exclusion of cholesterol; thus, both proteins are essential to maintain cellular cholesterol homeostasis. Consequently, mutations in the NPC2 or NPC1 gene result in pathophysiological accumulation of cholesterol and sphingolipids in LE/LY. The vast majority of Niemann-Pick type C disease patients, 95%, suffer from a mutation of NPC1, and only 5% display a mutation of NPC2. The biochemical phenotype of NP-C1 and NP-C2 appears to be indistinguishable, and both diseases share several commonalities in the clinical manifestation. Studies of the pathological mechanisms underlying NP-C2 are mostly based on NP-C2 animal models and NP-C2 patient-derived fibroblasts. Recently, we established induced pluripotent stem cells (iPSCs), derived from a donor carrying the NPC2 mutations c.58G>T/c.140G>T. Here, we present a profile of pathophysiological in vitro features, shared by NP-C1 and NP-C2, of neural differentiated cells obtained from the patient specific iPSCs. Profiling comprised a determination of the NPC2 protein level, detection of cholesterol accumulation by filipin staining, analysis of oxidative stress, and determination of autophagy. As expected, the NPC2-deficient cells displayed a significantly reduced amount of NPC2 protein, and, accordingly, we observed a significantly increased amount of cholesterol. Most notably, NPC2-deficient cells displayed only a slight increase of reactive oxygen species (ROS), suggesting that they do not suffer from oxidative stress and express catalase at a high level. As a site note, comparable NPC1-deficient cells suffer from a lack of catalase and display an increased level of ROS. In summary, this cell line provides a valuable tool to gain deeper understanding, not only of the pathogenic mechanism of NP-C2, but also of NP-C1.
Fungal Genomic Resources for Strain Identification and Diversity Analysis of 1900 Fungal Species

Identification and diversity analysis of fungi is greatly challenging. Though internal transcribed spacer (ITS), region-based DNA fingerprinting works as a “gold standard” for most of the fungal species group, it cannot differentiate between all the groups and cryptic species. Therefore, it is of paramount importance to find an alternative approach for strain differentiation. Availability of whole genome sequence data of nearly 2000 fungal species are a promising solution to such requirement. We present whole genome sequence-based world’s largest microsatellite database, FungSatDB having >19M loci obtained from >1900 fungal species/strains using >4000 assemblies across globe. Genotyping efficacy of FungSatDB has been evaluated by both in-silico and in-vitro PCR. By in silico PCR, 66 strains of 8 countries representing four continents were successfully differentiated. Genotyping efficacy was also evaluated by in vitro PCR in four fungal species. This approach overcomes limitation of ITS in species, strain signature, and diversity analysis. It can accelerate fungal genomic research endeavors in agriculture, industrial, and environmental management.
hTERT Downregulation Attenuates Resistance to DOX, Impairs FAK-Mediated Adhesion, and Leads to Autophagy Induction in Breast Cancer Cells

Telomerase is known to contribute to telomere maintenance and to provide cancer cell immortality. However, numerous reports are showing that the function of the enzyme goes far beyond chromosome ends. The study aimed to explore how telomerase downregulation in MCF7 and MDA-MB-231 breast cancer cells affects their ability to survive. Consequently, sensitivity to drug resistance, proliferation, and adhesion were assessed. The lentiviral-mediated human telomerase reverse transcriptase (hTERT) downregulation efficiency was performed at gene expression and protein level using qPCR and Western blot, respectively. Telomerase activity was evaluated using the Telomeric Repeat Amplification Protocol (TRAP) assay. The study revealed that hTERT downregulation led to an increased sensitivity of breast cancer cells to doxorubicin which was demonstrated in MTT and clonogenic assays. During a long-term doubling time assessment, a decreased population doubling level was observed. Interestingly, it did not dramatically affect cell cycle distribution. hTERT downregulation was accompanied by an alteration in β1-integrin- and by focal adhesion kinase (FAK)-driven pathways together with the reduction of target proteins phosphorylation, i.e., paxillin and c-Src. Additionally, autophagy activation was observed in MDA-MB-231 cells manifested by alternations in Atg5, Beclin 1, LC3II/I ratio, and p62. These results provide new evidence supporting the possible therapeutic potential of telomerase downregulation leading to induction of autophagy and cancer cells elimination.
Fecal Calprotectin and Eosinophil-Derived Neurotoxin in Children with Non-IgE-Mediated Cow’s Milk Protein Allergy

Our aim is to assess the efficacy of fecal calprotectin (fCP) and fecal eosinophil-derived neurotoxin (fEDN) as diagnostic markers of cow’s milk protein allergy (CMPA) and for monitoring the infants’ response to a non-IgE mediated cow’s milk protein (CMP)-free diet. We prospectively recruited infants aged 0 to 9 months. Stool samples were taken from 30 infants with CMPA, 19 with mild functional gastrointestinal disorders, 28 healthy infants, and 28 children who presented mild infections. Despite the fact that levels of fCP and fEDN in CMPA infants were higher than in healthy infants at month 0, differences for both parameters did not reach statistical significance (p-value 0.119 and 0.506). After 1 month of an elimination diet, no statistically significant differences in fCP with basal levels were found (p-values 0.184) in the CMPA group. We found a high variability in the fCP and fEDN levels of young infants, and discrepancies in individual behavior of these markers after a CMP-free diet was started. It seems that neither fCP nor fEDN levels are helpful to discriminate between healthy infants and those with signs or symptoms related to non-IgE-mediated CMPA. Additionally, it is debatable if on an individual basis, fCP or fEDN levels could be used for clinical follow-up and dietary compliance monitoring. However, prospective studies with larger populations are needed to draw robust conclusions.
SUPPORTED ZIEGLER-NATTA CATALYSTS FOR ETHYLENE SLURRY POLYMERIZATION AND CONTROL OF MOLECULAR WEIGHT DISTRIBUTION OF POLYETHYLENE

The effect of chemical composition of highly active supported Ziegler-Natta catalysts with controlled morphology on the MWD of PE has been studied. It was shown the variation of transition metal compound in the MgCl2-supported catalyst affect of MWD of PE produced in broad range: Vanadium-magnesium catalyst (VMC) produce PE with broad and bimodal MWD (Mw/Mn = 14−21). MWD of PE, produced over titanium-magnesium catalyst (TMC) is narrow or medium depending on Ti content in the catalyst (Mw/Mn = 3.1−4.8). The oxidation state of the initial titanium compounds in TMC has only slight effect on MWD of PE produced. Based on MWD data of PE heterogeneity of active centers of TMC and VMC was studied. The results of resolution of experimental GPC curves into Flory components indicated three Flory components are sufficient to describe MWD curve of PE, produced with TMC; six Flory components are required in the case of VMC. In the case of copolymerization of ethylene with 1-hexene over TMC the addition of 1-hexene leads to decrease of MW and to slight effect on Mw/Mn values. On the contrary the strong effect of 1-hexene on MWD of PE produced over VMC was found: the introduction of 1-hexene results in considerable broadening of MWD due to the shifting of the main MWD peak to low MW region. At that comonomer doesn't affect the position of high molecular weight shoulder. The results indicate that some of active centers of VMC producing high MW polymer are not active in the reaction of chain transfer with comonomer.
Development of a Numerical Model to Predict the Dielectric Properties of Heterogeneous Asphalt Concrete

Ground-penetrating radar (GPR) has been used for asphalt concrete (AC) pavement density prediction for the past two decades. Recently, it has been considered as a method for pavement quality control and quality assurance. A numerical method to estimate asphalt pavement specific gravity from its dielectric properties was developed and validated. A three-phase numerical model considering aggregate, binder, and air void components was developed using an AC mixture generation algorithm. A take-and-add algorithm was used to generate the uneven air-void distribution in the three-phase model. The proposed three-phase model is capable of correlating pavement density and bulk and component dielectric properties. The model was validated using field data. Two methods were used to calculate the dielectric constant of the AC mixture, including reflection amplitude and two-way travel time methods. These were simulated and compared when vertical and longitudinal heterogeneity existed within the AC pavement layers. Results indicate that the reflection amplitude method is more sensitive to surface thin layers than the two-way travel time methods. Effect of air-void content, asphalt content, aggregate gradation, and aggregate dielectric constants on the GPR measurements were studied using the numerical model.
Relationships between Structure and Antioxidant Capacity and Activity of Glycosylated Flavonols

The antioxidant capacity (AC) and antioxidant activity (AA) of three flavonols (FLV), aglycones and their glycosylated derivatives were evaluated using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) assays in various solvents. Findings confirmed that the glycosylation at the 3-position (3-glycosylation) always decreased the AC under most conditions due to substitution of the 3-position hydroxyl group and glycoside disruption in the molecular planarity. The 7-glycosylated derivatives did not have the above effects, thus generally exhibited ACs similar to their aglycones. Glycosylation decreased the AA of kaempferol and isorhamnetin for both assays in methanol, 3-glycosylation inhibited quercetin AA in the ABTS assay. In the DPPH assay, the AA of 3-glycosylated quercetin was significantly higher than quercetin. Using LC–MS/MS analysis, we found that quercetin and quercetin-7-glucoside underwent dimerization during the antioxidant reaction, potentially leading to a decline in AAs. However, 3-glycoside substitution may have hindered dimer formation, thereby allowing the FLVs to retain strong free radical scavenging abilities.
Development and Validation of a SYBR Green Real Time PCR Protocol for Detection and Quantification of Nervous Necrosis Virus (NNV) Using Different Standards

Simple Summary In the present report, we designed a reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR) for the detection and quantification of the nervous necrosis virus (NNV), a fish virus of great importance in Mediterranean aquaculture. The advantage of this procedure with respect to others is that it ensures the correct diagnosis of any viral type, at extremely low viral loads, thanks to a limit of detection lower than in previous methods, and demonstrates a better diagnostic sensitivity and specificity than PCR and cell culture isolation. Furthermore, this is the first time that an RT-qPCR procedure has been validated for the quantification of NNV, ensuring the reliability of the quantification, regardless of the calibration standard chosen. Therefore, its use would enable the comparison of data between different laboratories. Abstract The nervous necrosis virus (NNV) is a threat to fish aquaculture worldwide, especially in Mediterranean countries. Fast and accurate diagnosis is essential to control it, and viral quantification is required to predict the level of risk of new viral detections in field samples. For both, reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR) is used by diagnostic laboratories. In the present study, we developed an RT-qPCR procedure for the diagnosis and simultaneous quantification of NNV isolates from any of the four genotypes. The method proved to be highly sensitive in terms of crude virus titer: 5.56–9.88 TCID50/mL (tissue culture infectious dose per mL), depending on the viral strain, and averaging 8.8 TCID50/mL or 0.08 TCID50/reaction. Other standards also yielded very low detection limits: 16.3 genome copies (cps) of purified virus per mL, 2.36 plasmid cps/mL, 7.86 in vitro synthetized RNA cps/mL, and 3.16 TCID50/mL of virus from infected tissues. The diagnostic parameters evaluated in fish samples were much higher in comparison to cell culture isolation and nested PCR. In addition, the high repeatability and reproducibility of the procedure, as well as the high coefficient of determination (R2) of all the calibration curves with any type of standard tested, ensure the high reliability of the quantification of NNV using this RT-qPCR procedure, regardless of the viral type detected and from the type of standard chosen.