Time to take HPV infection in colorectal cancer patients more seriously.

Background: The association between viral infections and colorectal cancer (CRC) remains an enigma in cancer research. Certain types of Human Papillomaviruses (hr-HPVs), known for their oncogenic properties, have been observed in particular CRC biopsies, further adding to the enigma surrounding this association. Materials and methods: This cross-sectional study was conducted on 40 confirmed cases of CRC adenocarcinoma. The presence and genotyping of HPV DNA in colorectal fresh tissue and urine samples was assessed using an HPV DNA hybridization kit. A subset of serum samples from both CRC cases and healthy volunteers was randomly chosen and subjected to western blot to investigate the presence of HPV16 E6/E7 oncoproteins carried by exosomes. Results: It was observed that 26/40 HPV-positive CRC patients demonstrated 7 times more chance to develop colorectal cancer when compared to those 8/40 normal tissue (odds ratio [OR] = 7.4; confidence interval [CI] 95% = 0.483156-0.793718; p < 0.001). Of 26 HPV-positive CRC patients, 14 urine samples were also showed HPV DNA positivity (p = 0.013). High-risk HPV16 was the most prevalent genotype detected in both 24/40 tumor and 12/40 urine samples (p < 0.001). The tumor sample of a male was HPV45, while another male's urine sample was HPV31. A female CRC patient had HPV83 in tumor and HPV56 in urine. Here, was the first detection of HPV83 in a CRC patient. Notably among 20 randomly selected serum exosome samples, one serum sample concurrently tested positive for both HPV16 E6 and E7 oncoproteins, and one sample tested positive for HPV16 E7 oncoprotein. Conclusion: High risk HPV DNA detection in CRC urine samples supports non-invasive screening tools. Detection of HPV16 E6 and E7 oncoproteins in exosomes from serum samples shows potential for non-invasive diagnostics. HPV's potential role in CRC development is also underscored. HPV vaccination should be implemented in low- and middle-income countries to prevent cancer.

Miniaturized Sniffing Device based on an Array of Fluorescent Carbon Quantum Dots and Metallic Nanoclusters Efficiently Identifies Hematologic Malignancy in Adults.

The study demonstrates the potential of an optical nose made by depositing an array of fluorescent nanomaterials on a paper substrate for the early detection of leukemia in adults. This is based on the fact that blood volatile organic compounds (VOCs) are useful leukemia biomarkers. The integrated design was miniaturized and comprised both sensing zones and a sample holding zone, which were installed on a small sheet of paper within a miniature cubic reaction chamber fabricated by using 3D printing technology. The sensing device, comprising seven fluorescent sensing elements, namely, metal nanoclusters, quantum dots, and carbon dots was capable of detecting VOCs in the blood headspace and providing a colorimetric signature that could discriminate between blood samples from healthy and cancerous individuals. A total of 70 new leukemia cases and 51 healthy controls aged 20-50 years were studied. The device required a 60 µL portion of the blood sample and reacted to blood VOCs after 3 h when kept at 50 °C. The imaging data from the device was processed by linear discriminant analysis, and the results confirmed efficient identification of patient samples from healthy samples with 100% accuracy. Overall, the array system is noninvasive (or minimally invasive), portable, fast, inexpensive, and requires only a small amount of blood sample.

Safety and immunogenicity of an inactivated SARS-CoV-2 vaccine (FAKHRAVAC®) in healthy adults aged 18-55 years: Randomized, double-blind, placebo-controlled, phase I clinical trial.

Background: The FAKHRAVAC®, an inactivated SARS-CoV-2 vaccine, was assessed for safety and immunogenicity. Methods and findings: In this double-blind, placebo-controlled, phase I trial, we randomly assigned 135 healthy adults between 18 and 55 to receive vaccine strengths of 5 or 10 µg/dose or placebo (adjuvant only) in 0-14 or 0-21 schedules. This trial was conducted in a single center in a community setting. The safety outcomes in this study were reactogenicity, local and systemic adverse reactions, abnormal laboratory findings, and Medically Attended Adverse Events (MAAE). Immunogenicity outcomes include serum neutralizing antibody activity and specific IgG antibody levels.The most frequent local adverse reaction was tenderness (28.9%), and the most frequent systemic adverse reaction was headache (9.6%). All adverse reactions were mild, occurred at a similar incidence in all six groups, and were resolved within a few days. In the 10-µg/dose vaccine group, the geometric mean ratio for neutralizing antibody titers at two weeks after the second injection compared to the placebo group was 9.03 (95% CI: 3.89-20.95) in the 0-14 schedule and 11.77 (95% CI: 2.77-49.94) in the 0-21 schedule. The corresponding figures for the 5-µg/dose group were 2.74 (1.2-6.28) and 5.2 (1.63-16.55). The highest seroconversion rate (four-fold increase) was related to the 10-µg/dose group (71% and 67% in the 0-14 and 0-21 schedules, respectively). Conclusions: FAKHRAVAC® is safe and induces a strong humoral immune response to the SARS-CoV-2 virus at 10-µg/dose vaccine strength in adults aged 18-55. This vaccine strength was used for further assessment in the phase II trial.Trial registrationThis study is registered with https://www.irct.ir; IRCT20210206050259N1.

Potential Use of the Cholesterol Transfer Inhibitor U18666A as a Potent Research Tool for the Study of Cholesterol Mechanisms in Neurodegenerative Disorders.

Cholesterol is an essential component of mammalian cell membranes and a precursor for crucial signaling molecules. The brain contains the highest level of cholesterol in the body, and abnormal cholesterol metabolism links to many neurodegenerative disorders. The results indicate that faulty cholesterol metabolism is a common feature among people living with neurodegenerative conditions. The researchers suggest that restoring cholesterol levels may become a beneficial new strategy in treating certain neurodegenerative conditions. Several neurodegenerative disorders, such as Alzheimer's disease (AD), Niemann-Pick type C (NPC) disease, and Parkinson's disease (PD), have been connected to abnormalities in brain cholesterol metabolism. Consequently, using a lipid research tool is vital to study further and understand the effect of lipids in neurodegenerative disorders such as NPC, AD, PD, and Huntington's disease (HD). U18666A, also known as 3-(2-(diethylamino) ethoxy) androst-5-en-17-one, is a pharmaceutical drug that suppresses cholesterol trafficking and is a well-known class-2 amphiphile. U18666A has performed many functions, allowing for essential discoveries in lipid studies and shedding light on the pathophysiology of neurodegenerative disorders. Additionally, U18666A prevented the downregulation of low-density lipoprotein (LDL) receptors that are induced by LDL and led to the buildup of cholesterol in lysosomes. Numerous studies show that U18666A impacts the function of cholesterol trafficking to control the metabolism and transport of amyloid precursor proteins (APPs). Treating cortical neurons with U18666A may provide a new in vitro model system for studying the underlying molecular process of NPC, AD, HD, and PD. In this article, we review the mechanism and function of U18666A as a vital tool for studying cholesterol mechanisms in neurological diseases related to abnormal cholesterol metabolism, such as AD, NPC, HD, and PD.

Genetically engineered E. coli invade epithelial cells and transfer their genetic cargo into the cells: an approach to a gene delivery system.

PURPOSE: Despite advances in gene therapy, the lack of safe and efficient gene delivery systems limited the clinical effectiveness of gene therapy. Due to the inherent potential of bacteria, they can be considered as a good option for the gene transfer system. This study aimed to create a genetically engineered bacterium capable of entering epithelial cells and transferring its genetic cargo to the cell's cytoplasm, eventually expressing the gene of interest in the cell. METHODS: The invasin (inv) gene from Yersinia pseudotuberculosis and the listeriolysin (hlyA) gene from Listeria monocytogenes were isolated by PCR assay and inserted into a pACYCDuet-1 vector. The recombinant plasmid was then transformed into E. coli strain BL21. Subsequently, pEGFP-C1 plasmids containing a CMV promoter were transformed into the engineered bacteria. Finally, the engineered bacteria containing the reporter genes were incubated with the HeLa and LNCaP cell lines. Fluorescence microscopy, flow cytometry, and TEM were used to monitor bacterial entry into the cells and gene expression. We used native E. coli strain BL21 as a control. RESULTS: A fluorescence microscope showed that, in contrast to the control group, the manipulated E. coli were able to penetrate the cells and transport the plasmid pEGFP-C1 to the target cells. Flow cytometry also showed fluorescence intensity of 54.7% in HeLa cells and 71% in LNCaP cells, respectively. In addition, electron micrographs revealed the presence of bacteria in the cell endosomes and in the cytoplasm of the cells. CONCLUSION: This study shows that genetically engineered E. coli can enter cells, transport cargo into cells, and induce gene expression in the target cell. In addition, flow cytometry shows that the gene transfer efficiency was sufficient for protein expression.

Mathematical model presenting to assess variations in heart rate of different age groups.

OBJECTIVE: Recently, older people's cardiovascular systems have been affected by aging-related changes. An electrocardiogram (ECG) provides information about cardiac health. Analyzing ECG signals can help doctors and researchers diagnose many deaths. Besides direct ECG analysis, some measurements can be extracted from the ECG signals, and one of the most important measurements is heart rate variability (HRV). Research and clinical domains can benefit from HRV measurement and analysis as a potential noninvasive tool for assessing autonomic nervous system activity. The HRV describes the variation between an ECG signal's RR intervals over time and the change in that interval over time. An individual's heart rate (HR) is a non-stationary signal, and its variation can indicate a medical condition or impending cardiac disease. Many factors, such as stress, gender, disease, and age, influence HRV. METHODS: The data for this study is taken from a standard database, the Fantasia Database, which contains 40 subjects, including two groups of 20 young subjects (21‒34 years old) and 20 older subjects (68‒85 years old). We used two non-linear methods, Poincare and Recurrence Quantification Analysis (RQA), to determine how different age groups affect HRV using Matlab and Kubios software. RESULTS: By analyzing some features extracted from this non-linear method based on a mathematical model and making a comparison, the results indicate that the SD1, SD2, SD1/SD2, and area of an ellipse (S) in Poincare will be lower in old people than in young people, but %REC, %DET, Lmean and Lmax will recur more often in older people than in younger ones. Poincare Plot and RQA show opposite correlations with aging. In addition, Poincaré's plot showed that young people have a greater range of changes than the elderly. CONCLUSION: According to the result of this study, heart rate changes can be reduced by aging, and ignoring this issue could lead to cardiovascular disease in the future (Tab. 3, Fig. 7, Ref. 55).

Detection of sepsis using biomarkers based on machine learning.

BACKGROUND: Sepsis is the second most common cause of death in patients with non-cardiovascular diseases admitted to the ICU. It is one of the top ten reasons for death among all hospitalized patients. This study aimed to compare the value of some blood parameters in diagnosing sepsis and investigate their relationship to select a more practical diagnostic method. METHODS: In this descriptive-analytical study, 208 patients with sepsis admitted to the ICU were selected. Then the physiological parameters of patients and normal individuals were measured. Data analysis was performed using the p value and effect size methods and MATLAB software. To classify the disease, the MLP, RBF, and KNN methods were used. RESULTS: The values of the HR, O2Sat, and SBP in patients with sepsis have changed significantly compared to NORMAL conditions. The classification results using different classifications showed that the values of specificity, sensitivity, and accuracy values in the classifier are more than MLP and RBF and equal to 98 %, 100 %, and 99 %, respectively. CONCLUSIONS: Clinically, accurate detection of sepsis and predicting the patients at risk of developing sepsis is useful for improving treatment. Given the significant differences between HR, O2Sat, and SBP between normal and sepsis patients in this study, it may be possible to use these tests as simple tests instead of the complement protein 3 (C3) and Procalcitonin (PCT) tests to diagnose sepsis in the ICU (Tab. 8, Fig. 10, Ref. 39). Text in PDF www.elis.sk Keywords: sepsis, physiological parameters, detection; feature extraction, statistical analysis.

EEG-biomarker theta/beta ratio and attentional quotients in adults who stutter: An electrophysiological and behavioral study.

INTRODUCTION: There is increasing evidence that connects developmental stuttering to attention. However, findings have represented contradiction. Therefore, this study was conducted to investigate the possible relationship between stuttering and attention in resting and undertask conditions. METHODS: In a cross-sectional study, 26 right-handed AWS (adults who stutter) and 25 matched fluent speakers were enrolled. Demographic data were collected, and the Beck anxiety inventory (BAI) was filled out for all participants. Then, QEEG was conducted, followed by IVA2. CPT test for all subjects. Finally, data were analyzed using SPSS software version 16. RESULTS: AWS indicated significantly weaker auditory focus attention in the task (p = .02) than the control group, while a similar resting-state EEG marker of attention was found between groups (p > .05). Moreover, attention was not correlated between the two conditions (p > .05). CONCLUSION: The EEG marker of attention did not necessarily designate the attentional performance of AWS under the task. Furthermore, attentional skills could be considered in the assessment and therapeutic programs of at least some groups of AWS.

Efficacy of drug regimen with and without oseltamivir in hospitalized patients with COVID-19: A retrospective study.

Introduction: Coronavirus disease 2019 (COVID-19) is the most critical issue in nowadays medicine. We aimed to evaluate the use and therapeutic outcomes of oseltamivir, an antiviral drug for patients with COVID-19. Materials and method: In an observational study conducted at Imam Khomeini Hospital in Amol, Iran, data for 544 patients with laboratory and CT scan result confirmed COVID-19 were retrospectively collected between February 24th and April 13th 2020. To compare the characteristics of patients based on gender, the chi-square test was used. Logistic regression was used to evaluate the effect of oseltamivir on the outcome of treatment. Logrank test were used to compare the length of hospital stay in people treated with oseltamivir and drugs other than oseltamivir. Results: Kaplan-Meier and logrank test showed no significant reduction in hospitalization time and survival rate following treatment with oseltamivir. However, a significant increase in lymphocytes count and reduction of C-reactive protein (CRP) level detected. Conclusion: Administration of oseltamivir for patients with COVID-19 didn't show any improvement in hospitalization duration and survival rate.

Introducción: la enfermedad por coronavirus 2019 (COVID-19) es el tema más crítico en la medicina actual. Nuestro objetivo fue evaluar el uso y los resultados terapéuticos de oseltamivir, un medicamento antiviral para pacientes con COVID-19. Materiales y método: en un estudio observacional realizado en el Hospital Imam Khomeini en Amol, Irán, los datos de 544 pacientes con resultados de laboratorio y tomografía computarizada confirmados de COVID-19 se recopilaron retrospectivamente entre el 24 de febrero y el 13 de abril de 2020. Para comparar las características de los pacientes en función del género se utilizó la prueba de chi-cuadrado. Se utilizó regresión logística para evaluar el efecto de oseltamivir en el resultado del tratamiento. Se utilizó la prueba de rango logarítmico para comparar la duración de la estancia hospitalaria en personas tratadas con oseltamivir y otros fármacos distintos del oseltamivir. Resultados: Kaplan­Meier y la prueba de rango logarítmico no mostraron una reducción significativa en el tiempo de hospitalización y la tasa de supervivencia después del tratamiento con oseltamivir. Sin embargo, se detectó un aumento significativo en el recuento de linfocitos y una reducción del nivel de proteína C reactiva (PCR). Conclusión: la administración de oseltamivir para pacientes con COVID-19 no mostró ninguna mejora en la duración de la hospitalización y la tasa de supervivencia.

The Treatment Dilemma of Arteriopathy in Takayasu Arteritis- A State-of-the-Art Approach.

Takayasu Arteritis (TA) is a chronic idiopathic granulomatous pan-arteritis affecting the pulmonary artery, the aorta, and its principal derived branches. The majority of TA patients are female (82.9%-97.0%). Due to the inflammatory character of the illness, arterial stenosis therapy must be treated differently than the atherosclerosis process. In this review paper, we outline a strategy using real-world challenging cases.

Modelling the probability of presence of Aedes aegypti and Aedes albopictus in Iran until 2070

Objective: To determine the suitable ecological habitats of Aedes (Ae.) aegypti and Ae. albopictus in Iran due to climate change by the 2070s. Methods: All data relating to the spatial distribution of Ae. aegypti and Ae. albopictus worldwide, which indicated the geographical coordinates of the collection sites of these mosquitoes, were extracted from online scientific websites and entered into an Excel file. The effect of climatic and environmental variables on these mosquitoes was evaluated using the MaxEnt model in the current and future climatic conditions in the 2030s, 2050s, and 2070s. Results: The most suitable areas for the establishment of Ae. aegypti are located in the southern and northern coastal areas of Iran, based on the model outputs. The modelling result for suitable ecological niches of Ae. albopictus shows that in the current climatic conditions, the southern half of Iran from east to west, and parts of the northern coasts are prone to the presence of this species. In the future, some regions, such as Gilan and Golestan provinces, will have more potential to exist/establish Ae. albopictus. Also, according to the different climate change scenarios, suitable habitats for this species will gradually change to the northwest and west of the country. The temperature of the wettest season of the year (Bio8) and average annual temperature (Bio1) were the most effective factors in predicting the model for Ae. aegypti and Ae. albopictus, respectively. Conclusions: It is required to focus on entomological studies using different collection methods in the vulnerable areas of Iran. The future modelling results can also be used for long-term planning to prevent the entry and establishment of these invasive Aedes vectors in the country.

Surface biophysical features fusion in remote sensing for improving land crop/cover classification accuracy.

Preparing up-to-date land crop/cover maps is important to study in order to achieve food security. Therefore, the aim of this study was to evaluate the impact of surface biophysical features in the land crop/cover classification accuracy and introduce a new fusion-based method with more accurate results for land crop/cover classification. For this purpose, multi-temporal images from Sentinel 1 and 2, and an actual land crop map prepared by Agriculture and Agri-Food Canada (AAFC) in 2019 were used for 3 test sites in Ontario, Canada. Firstly, surface biophysical features maps were prepared based on spectral indices from Sentinel 2 including Normalized Difference Vegetation Index (NDVI), Index-based Built-up Index (IBI), Wetness, Albedo, and Brightness and co-polarization (VV) and cross-polarization (VH) from Sentinel 1 for different dates. Then, different scenarios were generated; these included single surface biophysical features as well as a combination of several surface biophysical features. Secondly, land crop/cover maps were prepared for each scenario based on the Random Forest (RF). In the third step, based on the voting strategy, classification maps from different scenarios were combined. Finally, the accuracy of the land crop/cover maps obtained from each of the scenario was evaluated. The results showed that the average overall accuracy of land crop/cover maps obtained from individual scenario (one feature) including NDVI, IBI, Wetness, Albedo, Brightness, VV and VH were 66%, 68%, 63%, 60%, 57%, 62% and 58%, respectively, which by the surface biophysical features fusion, the overall accuracy of land crop/cover maps increased to 83%. Also, by combining the classification results obtained from different scenarios based on voting strategy, the overall accuracy increased to 89%. The results of this study indicate that the feature level-based fusion of surface biophysical features and decision level based fusion of land crop/cover maps obtained from various scenarios increases the accuracy of land crop/cover classification.

Mental arithmetic task detection using geometric features extraction of EEG signal based on machine learning.

BACKGROUND: Mental arithmetic analysis based on electroencephalogram (EEG) signals can help to understand some disorders such as attention deficit hyperactivity disorder, arithmetic disorder, or autism spectrum disorder in which learning is difficult. Most mental computation detection and classification systems rely on the characteristics of a single channel, however, the understanding of the connections between EEG channels, which certainly contains valuable information, is still evolving. The methods presented in this paper are the result of a research project that introduces an alternative method for better and faster receipt of information from the EEG signals of individuals, which are generally complex and nonlinear. METHODS: The EEGs of 66 healthy individuals were recorded in two rest modes and mental task a designed, with a sampling frequency of 500 Hz. To classify these two modes, we extracted features from our recordings to differentiate the EEG signals of these two groups in a single channel as well as combine possible channels. The new method that was proposed was the extraction of several geometric features from Poincaré design analysis, which used the necessary comparison t-test to determine brain differences, with a significance level of less than 0.05 in the state of mental calculations and facial rest. Also, an artificial neural network (ANN) has been used for automatic learning and diagnosis in the two mentioned modes. RESULTS: The results of this paper show that by using a combination of geometric properties (sides, angles, shortest distance, slope, and coefficients of the third-degree equation) using selected channels (FP1, F7, C4, O1) can achieve 100 % accuracy. The sensitivity reached 100 %. As well as 100 % feature. CONCLUSIONS: With the help of mental calculation, it is possible to diagnose, treat, rehabilitate and rehabilitation people who have lost the function of a part of their brain due to a disease in this field (Tab. 6, Fig. 15, Ref. 45).

Modeling the impact of the COVID-19 lockdowns on urban surface ecological status: A case study of Milan and Wuhan cities.

The COVID-19 pandemic has caused unprecedent negative impacts on our society, however, evidences show a reduction of anthropogenic pressures on the environment. Due to the high importance of environmental conditions on human life quality, it is crucial to model the impact of COVID-19 lockdown on environmental conditions. Consequently, the objective of this study was to model the impact of COVID-19 lockdown on the urban surface ecological status (USES). To this end, the Landsat-8 images of Milan for three pre-lockdown dates (Feb 13, 2018 (MD1), April 18, 2018 (MD2) and Feb 3, 2020 (MD3)) and one date over the lockdown (April 14, 2020 (MD4)), and Wuhan for three pre-lockdown dates (Dec 17, 2017 (WD1), March 23, 2018 (WD2) and Dec 7, 2019 (WD3)) and one lockdown date (Feb 9, 2020 (WD4)) were used. First, pressure-state-response (PSR) framework parameters including index-based built-up index (IBI), vegetation cover (VC), vegetation health index (VHI), land surface temperature (LST) and Wetness were calculated. Second, by combining the PSR framework parameters based on comprehensive ecological evaluation index (CEEI), the USES were modeled on different dates. Thirdly, the USES during the COVID-19 lockdown was compared with the USES for pre-lockdown. The mean (standard deviation) of CEEI for Milan on MD1, MD2, MD3 and MD4 were 0.52 (0.12), 0.60 (0.19), 0.57 (0.13) and 0.45 (0.16), respectively. Also, these values for Wuhan on WD1, WD2, WD3 and WD4 were 0.63 (0.14), 0.67 (0.15), 0.60 (0.13) and 0.57 (0.13), respectively. Due to the lockdowns, the mean CEEI of built-up, bare soil and green spaces for Milan and Wuhan decreased by [0.18, 0.02, 0.08], [0.13, 0.06, 0.05], respectively. During the lockdown period, the USES improved substantially due to the reduction of anthropogenic activities in the urban environment.

A novel method to quantify urban surface ecological poorness zone: A case study of several European cities.

A set of factors cause the Surface Ecological Status (SES) of urban areas to become largely different from the surrounding rural areas. Hence, the degree of poorness of SES in urban areas versus surrounding rural areas forms a zone, which is named Urban Surface Ecological Poorness Zone (USEPZ). The main objective of this study was to propose a new method to quantify USEPZ Intensity (USEPZI). To this end, Landsat-8 satellite images, water vapor products, and High Resolution Imperviousness Layer (HRIL) datasets of Budapest, Bucharest, Ciechanow, Hamburg, Lyon, Madrid, Porto, and Rome cities were used. Firstly, Single Channel (SC) algorithm, Tasseled cap transformation, and spectral indices were used to model the surface biophysical characteristics including Land Surface Temperature (LST), Wetness, Normalized Difference Vegetation Index (NDVI), and Normalized Difference Soil Index (NDSI). Then, SES was modeled based on the combination of surface biophysical characteristics using Remote Sensing-based Ecological Index (RSEI). Finally, the USEPZI was modeled based on the linear regression function obtained from RSEI-Impervious Surface Percentage (ISP) feature space. The spatial variability of the ISP, LST, NDVI, NDSI and Wetness of the selected cities was found to be heterogeneous. The coefficient of determination (R2) between RSEI and ISP values for Budapest, Bucharest, Ciechanow, Hamburg, Lyon, Madrid, Porto, and Rome cities were obtained to be 0.99, 0.97, 0.98, 0.99, 0.98, 0.99, 0.99, and 0.94, respectively. Also, the USEPZI values of these cities were 0.14, 0.31, 0.41, 0.26, 0.40, 0.81, 0.44 and 0.46, respectively. Our findings show that the significant differences in their SES and USEPZI are due to the surface biophysical characteristics. The USEPZI in the selected cities with humid climate conditions was higher than the selected cities in dry climate conditions. Also, the use of the RSEI-ISP feature space is quite useful in modeling USEPZI of cities in different conditions.

Molecular epidemiology of JC polyomavirus in HIV-infected patients and healthy individuals from Iran.

JC polyomavirus (JCPyV) is the causative agent for progressive multifocal leukoencephalopathy (PML) in immunocompromised patients. More than 40% of healthy population excretes JCPyV particles in their urine. As JCPyV is ubiquitous in human, the definition of genotype distribution can help trace population migration. In this study, to define the frequency of JCPyV in southwest of Iran, urine samples of 161 volunteers including 80 healthy individuals and 81 HIV-infected patients were collected. PCR assays and sequence analysis were performed using JCPyV-specific primers designed against VP1 coding region. JCPyV DNA was detected in 65 out of 81 urine samples (80.2%) of HIV-infected, and in 43 out of 80 urine samples (53.8%) of healthy individuals (P = 0.001). The shedding of JCPyV among HIV-infected patients revealed an age-related pattern while such relationship was not observed in healthy individuals group. The most common genotype found in this region was genotype 3A (80.8%), followed by genotype 2D (11.5%), 4 (3.8%), and 7 (3.8%). The frequency of JCPyV in the urine of HIV-infected patients was found significantly higher than in the healthy individuals (P = 0.001).

Spatial distribution of cutaneous anthrax in western Iran from 2009 to 2016: Geographic information system mapping for predicting risk of anthrax outbreaks

To explore the spatial accumulation of diseases and their aggravating factors are essential in all public health. This study attempts to use geographic information system (GIS) to provide more information about the incidence and future of anthrax. Methods: Patients were diagnosed with anthrax in Kurdistan Province from 2009 to 2016. Data was then exported into ArcGIS software version 9 and the required layers for years and areas were added.Final map for each year was drawn up, pointing out the hot spots and predicting its future pattern. Results: Most cases were reported in females (57 cases, 54.80 %), and the lower body limbs were most affected (63 cases, 60.57%). The highest numbers of incidences were related to the cities of Marivan, Saqez and Divandareh, with more concentration in the central parts of the province, rather than borderline areas. The highest percentage of the probable incidence of the disease was in Sanandaj (57.74%) with a potential susceptible area of 1 729.12 km

Recognition of Lung Volume Condition based on Phase Space Mapping Using Electrical Impedance Tomography.

The purpose of this paper is to identify differences between abnormal and normal lung signals gathered by an EIT device, which is a new, non-invasive system that seeks the electrical conductivity and permittivity inside a body. Lung performances in patients are investigated using Phase Space Mapping technique on Electrical EIT signals. The database used in this paper contains 82 registered records of 52 individuals with proper lung volume. The results of this paper show that as the delay parameter (τ) increases, the SD1 parameter of phase space mapping indicates a significant difference between normal and abnormal lung volumes. The value of the SD1 parameter with τ = 6 in the case that the lung volume is in a normal condition is 342.57 ± 32.75 while it is 156.71 ± 26.01 in non-optimal mode. This method can be used to identify the patients' lung volumes with chronic respiratory illnesses and is an accurate assessment of the diverse methods to treat respiratory system illnesses in addition to saving various therapeutic costs and dangerous consequences that are likely to occur by using improper treatment methods. It can also reduce the required treatment durations.

Normalizing land surface temperature for environmental parameters in mountainous and urban areas of a cold semi-arid climate.

Normalization of land surface temperature (LST) relative to environmental factors is of great importance in many scientific studies and applications. The purpose of this study was to develop physical models based on energy balance equations for normalization of satellite derived LST relative to environmental parameters. For this purpose, a set of remote sensing imagery, meteorological and climatic data recorded in synoptic stations, and soil temperatures measured by data loggers were used. For modeling and normalization of LST, a dual-source energy balance model (dual-EB), taking into account two fractions of vegetation and soil, and a triple -source energy balance model (triple-EB), taking into account three fractions of vegetation, soil and built-up land, were proposed with either regional or local optimization strategies. To evaluate and compare the accuracy of different modeling results, correlation coefficients and root mean square difference (RMSE) were computed between modeled LST and LST obtained from satellite imagery, as well as between modeled LST and soil temperature measured by data loggers. Further, the variance of normalized LST values was calculated and analyzed. The results suggested that the use of local optimization strategy increased the accuracy of the normalization of LST, compared to the regional optimization strategy. In addition, no matter the regional or local optimization strategy was employed, the triple-EB model out-performed consistently the dual-EB model for LST normalization. The results show the efficiency of the local triple-EB model to normalize LST relative to environmental parameters. The correlation coefficients were close to zero between all of the environmental parameters and the normalized LST. In other words, normalized LST was completely independent of the environmental parameters considered by this research.