The relationship between health literacy and the adoption of COVID-19 preventive behaviors: A cross-sectional study in Iran.

BACKGROUND AND AIM: Health literacy (HL) is one of the effective factors in controlling the COVID-19 epidemic. Considering the high prevalence of COVID-19 disease, the present study aimed to determine the relationship between HL and the adoption of COVID-19 preventive behaviors. MATERIALS AND METHODS: This was a descriptive-cross sectional study conducted on 214 students selected by simple random sampling method in Esfarayen Faculty of Medical Sciences, Iran, in 2022. The data included demographic and background characteristics, health literacy for Iranian Adults (HELIA), and a valid and reliable questionnaire to measure COVID-19 preventive behaviors. The data were analyzed using SPSS 23, descriptive statistics, and ordinal logistic regression tests. RESULTS: The mean and standard deviation of the scores of adoption of COVID-19 preventive behaviors and HL among students were 18.18) 4.02(out of 25 and 72.14) and 12.75 (out of 100, respectively. The results of the logistic regression test showed that the HL (P = 0.003), gender (P<0.001), mother's education (P = 0.039), educational level (P = 0.031), smoking (P = 0.032), and physical activity (P = 0.007) were effective factors in adopting preventive behaviors. CONCLUSION: Adopting preventive behaviors against COVID-19 was lower among students with lower levels of health literacy, male students, students with less physical activity, students with illiterate mothers, undergraduate students, and finally smokers. Therefore, it is necessary to pay more attention to these students in designing educational programs. It is suggested to carry out more extensive studies to clarify the effect of HL on the adoption of COVID-19 preventive behaviors.

Evaluation of a novel integrated membrane biological aerated filter for water reclamation: A practical experience.

The use of treated wastewater in addition to solving the problem of water shortage, can increase soil fertility and reduce the use of chemical fertilizers. We aim to provide a high-quality effluent to feed membrane system, reduce treatment costs and enhance the efficiency of wastewater recycling. All experiments were conducted on a novel integrated membrane biological aerated filter (IMBAF) consisting of a down flow cylindrical biological aerated filter (BAF) filled by silica and a novel sand-coated polystyrene granules (SCP), followed by ultrafiltration (UF) and reverse osmosis (RO) membranes. IMBAF reactor, with 73.6 L volume, was operated for 270 days (in three 90-day stages) with different conditions of returning backwash water. Accordingly, BAF generated high quality water for feeding UF membrane with 94.2%, 68%, 54.4%, 91.2%, and 99.95% of turbidity, 5-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), oil and grease (O&G), fecal coliform (FC) removal, respectively. At the end of stage 3, 99.88% of influent was recycled by UF and only 0.12% was disposed of as sludge. The BAF and UF module efficiently promote the quality of water entering RO system. After 75 days of continuous operation, the increase in trans-membrane pressure (TMP) and also decrease in RO membrane permeability were about 14% and 9.4%, respectively, indicating low clogging of the membrane. The use of BAF structure designed in this study increases the wastewater recycling rate, decreases membrane clogging and thereby reduces the costs of concentrate disposal and chemical cleaning.

Automatic microscopic diagnosis of diseases using an improved UNet++ architecture.

Anthrax is a severe infectious disease caused by the Bacillus anthracis bacterium. This paper aims to design and implement a fast and reliable system based on microscopic image processing of patient tissue samples for the automatic diagnosis of anthrax and other tissues diseases, metastasis detection, patient prognosis, etc. An improved UNet++ architecture is proposed to segment microscopic images of patient tissue samples. The proposed model combines multi-scale features by adding skip connections in two paths; the forward path from the encoder to the decoder and the decoder path to the output. These new connections improve the performance of the UNet++. Integration of the squeeze and excitation-inception blocks in the new skip connections provides the network with features at different scales with different kernel sizes. Several convolutional networks are used as the backbone to extract powerful representations in the encoder section. The use of batch normalization, dropout technique, and LRelu activation function in this model accelerates convergence and increases the generalization power of the model. To overcome the problem of data imbalance of different classes, a weighted hybrid loss function is proposed, which further improved segmentation efficiency. The semantic segmentation results are converted to the instance segmentation using the marker-based watershed algorithm. Experimental results show that despite many challenges of microscopic image analysis, the proposed model is a reliable system for the automatic diagnosis of anthrax and other tissues diseases. It produces better results than state-of-the-art architectures.

Cutaneous adverse reactions of COVID-19 vaccines: A systematic review.

Numerous vaccines are under clinical development and implementation for the prevention of severe course and lethal outcomes of coronavirus disease 2019 (COVID-19). This systematic review aims to summarize and integrated the findings of studies regarding cutaneous side effects of COVID-19 vaccines. This systematic review conducted by searching the scientific databases of PubMed, Scopus, Science direct, and Web of knowledge from the beginning of the COVID-19 to May 10, 2021. Articles were reviewed and analyzed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. Seventeen studies on cutaneous side effects of COVID-19 vaccines were included after the screening of search results based on to the eligibility criteria. The results showed that the most common injection site reactions and delayed large local reactions, arising from all vaccine types, were redness/erythema (39%), followed by: itchiness (28%), urticarial rash (17%) on the neck, upper limbs, and trunk, morbilliform eruptions (6.5%), Pityriasis rosea (3%), swelling, and burning, and so forth. Most cutaneous reactions occurred in women (84%), and middle-aged people, after the first dose of vaccine, with the onset ranged from 1 to 21 days after vaccination. In addition, cutaneous reactions were generally self-limiting, and needed little or no therapeutic intervention, that were not regarded as a barrier to injecting a second dose. In conclusion, severe cutaneous side effects are very rare and approved vaccines have satisfactory safety profiles. Therefore, mild or moderate cutaneous reactions should not discourage people from vaccination. In certain groups such as patients with allergies and a history of local injection reactions, pre-vaccination counseling and assurance, also use of appropriate medications may be helpful. However, more studies are needed to investigate the side effect profile of all COVID-19 vaccines.

Greedy Autoaugment for classification of mycobacterium tuberculosis image via generalized deep CNN using mixed pooling based on minimum square rough entropy.

Although tuberculosis (TB) is a disease whose cause, epidemiology and treatment are well known, some infected patients in many parts of the world are still not diagnosed by current methods, leading to further transmission in society. Creating an accurate image-based processing system for screening patients can help in the early diagnosis of this disease. We provided a dataset containing1078 confirmed negative and 469 positive Mycobacterium tuberculosis instances. An effective method using an improved and generalized convolutional neural network (CNN) was proposed for classifying TB bacteria in microscopic images. In the preprocessing phase, the insignificant parts of microscopic images are excluded with an efficient algorithm based on the square rough entropy (SRE) thresholding. Top 10 policies of data augmentation were selected with the proposed model based on the Greedy AutoAugment algorithm to resolve the overfitting problem. In order to improve the generalization of CNN, mixed pooling was used instead of baseline one. The results showed that employing generalized pooling, batch normalization, Dropout, and PReLU have improved the classification of Mycobacterium tuberculosis images. The output of classifiers such as Naïve Bayes-LBP, KNN-LBP, GBT-LBP, Naïve Bayes-HOG, KNN-HOG, SVM-HOG, GBT-HOG indicated that proposed CNN has the best results with an accuracy of 93.4%. The improvements of CNN based on the proposed model can yield promising results for diagnosing TB.

Comparing Serum Levels of Vitamin D and Zinc in Novel Coronavirus-Infected Patients and Healthy Individuals in Northeastern Iran, 2020.

BACKGROUND: COVID-19 infection has recently become a pandemic disease around the world, and its risk factors have not fully evaluated. This study aimed to compare the serum vitamin D (Vit D) and zinc levels in patients infected with novel coronavirus and healthy volunteers (HVs). METHODS: This was a single-center, cross-sectional study conducted on 56 patients (32 severe cases and 24 nonsevere) admitted to the COVID-19 ward and 46 HVs living in Esfarayen City, North Khorasan Province of Iran. Serum levels of Vit D and zinc in admitted patients to the COVID-19 ward and HVs were measured. RESULTS: The average levels of serum Vit D in severe cases, nonsevere cases, and HVs were 31.03 ± 15.49, 37.25 ± 18.49, and 39.33 ± 14.83, respectively (P = 0.05). Moreover, the average concentrations of serum zinc in severe cases, nonsevere cases, and HVs were 31.03 ± 15.49, 37.25 ± 18.49, and 39.33 ± 14.83, respectively (P = 0.01). Mortality rate, reinfection (for 5 months), and length of hospital stay in severe cases were higher than in nonsevere cases (P > 0.05). CONCLUSIONS: Results showed that severe cases had lower levels of Vit D than did other groups and were marginally significant. Also, severe cases had a significantly low level of zinc when compared with nonsevere cases and HVs. Levels of Vit D and zinc can affect the incidence of COVID-19 infection.

Automatic Bacillus anthracis bacteria detection and segmentation in microscopic images using UNet+.

Anthrax is one of the important diseases in humans and animals, caused by the gram-positive bacteria spores called Bacillus anthracis. The disease is still one of the health problems of developing countries. Due to fatigue and decreased visual acuity, microscopic diagnosis of diseases by humans may not be of good quality. In this paper, for the first time, a system for automatic and rapid diagnosis of anthrax disease simultaneously with detection and segmentation of B. anthracis bacteria in microscopic images has been proposed based on artificial intelligence and deep learning techniques. Two important architectures of deep neural networks including UNet and UNet++ have been used for detection and segmentation of the most important component of the image i.e. bacteria. Automated detection and segmentation of B. anthracis bacteria offers the same level of accuracy as the human diagnostic specialist and in some cases outperforms it. Experimental results show that these deep architectures especially UNet++ can be used effectively and efficiently to automate B. anthracis bacteria segmentation of microscopic images obtained under different conditions. UNet++ produces outstanding results despite the many challenges in this field, such as high image dimension, image artifacts, object crowding, and overlapping. We conducted our experiments on a dataset prepared privately and achieved an accuracy of 97% and the dice score of 0.96 on the patch test images. It also tested on whole raw images and a recall of 98% and accuracy of 97% is achieved, which shows excellent performance in the bacteria segmentation task. The low cost and high speed of diagnosis and no need for a specialist are other benefits of the proposed system.

A new DNA vaccine expressing HspX-PPE44-EsxV fusion antigens of Mycobacterium tuberculosis induced strong immune responses.

OBJECTIVES: Infection with tuberculosis (TB) is regarded as a major health issue. Due to the emergence of antibiotic resistance during TB treatment, prevention via vaccination is one of the most effective ways of controlling the infection. DNA vaccines are developed at a greater pace due to their ability in generating a long-lasting immune response, higher safety compared to the live vaccines, and relatively lower cost of production. In the present study, we evaluated a new DNA vaccine encoding the fusion HspX-PPE44-EsxV antigens, separately, and in combination with Bacillus Calmette-Guérin (BCG) administration, in a prime-boost method in mice. MATERIALS AND METHODS: A novel DNA vaccine encoding HspX-PPE44-EsxV fusion antigen of Mycobacterium tuberculosis was constructed, and RT-PCR and Western blot analysis were performed to verify the expression of the antigen. Female BALB/c mice were divided into five groups (PBS, BCG, pcDNA3.1 (+) vector, pDNA/HspX-PPE44-EsxV vaccine, and the BCG-prime boost groups). In order to evaluate the immunogenicity of the recombinant vector, BALB/c mice were injected with 100 µg of pDNA at 2-week intervals. Then, cytokine assay was conducted using eBioscience ELISA kits (Ebioscience, AUT) according to manufacturers' instructions to evaluate the concentrations of IL-4, IL-12, TGF-ß, and IFN-γ. RESULTS: The concentrations of INF-γ, IL-12, and TGF-beta were significantly increased compared to the control groups (P<0.001). INF-γ and IL-12 production were increased significantly in pDNA/HspX-PPE44-EsxV+BCG group compared to pDNA/HspX-PPE44-EsxV group (P<0.001). CONCLUSION: This study showed that the present DNA vaccine could induce a high level of specific cytokines in mice. It was also shown that using this DNA vaccine in a BCG prime-boost protocol can produce significant amounts of IFN-γ, IL-12, and TGF-ß.

The roles of latency-associated antigens in tuberculosis vaccines.

Tuberculosis (TB) is a re-emerging disease and is caused by Mycobacterium tuberculosis (M. tuberculosis). TB is currently one of the leading causes of morbidity and mortality, worldwide. The only available vaccine against TB infection, Bacillus Calmette-Guérin (BCG), fails to adequately protect against reactivation of latent infections in adults. Furthermore, recently developed subunit vaccines, which are in various stages of clinical trials, are all prophylactic vaccines based on proteins expressed in replicating stage of M. tuberculosis and they are not preventive of reactivation of latent TB infection. Thus, an appropriate subunit post-exposure vaccine needs to be developed to control all forms of TB infection. To produce a multi-stage subunit vaccine, scientists should combine the early secreted M. tuberculosis antigens with latency antigens. For this purpose, some latency proteins are known which could be important antigens in the production of specific humoral and cellular immune responses in latent M. tuberculosis infected individuals. Several studies have evaluated the immunogenicity of these proteins in improving the TB vaccines. The present study is a comprehensive review of several studies on the role of the latency antigens in the development of TB vaccines. Overall, the studies indicate that the latency-associated antigens including the resuscitation-promoting factors, the Dormancy of survival regulon (DosR) proteins and the starvation stimulant proteins are potential candidates for the development of subunit vaccines against TB infection.

Diversity of aminoglycoside modifying enzymes and 16S rRNA methylases in Acinetobacter baumannii and Acinetobacter nosocomialis species in Iran; wide distribution of aadA1 and armA.

PURPOSE: Acinetobacter baumannii-calcoaceticus complex (ABC) make a great burden on health-care systems due to hospital-acquired infections and antibacterial resistance. Aminoglycoside in combination with other antibacterials used as treatment options. However, ABC species overcome this class of antibacterials in different ways. This study provides a comprehensive report on the distribution of aminoglycoside modifying enzymes (AMEs) and 16S rRNA methylase in Acinetobacter baumannii and Acinetobacter nosocomialis isolated from various provinces in Iran. METHODS: During six month of study, from eight referral centers in seven provinces across the country, Iran, 178 A. baumannii and 43 A. nosocomialis isolates were collected. The minimum inhibitory concentration of amikacin, gentamicin, netilmicin, kanamycin and tobramycin were measured by microbroth dilution method. AMEs and 16S rRNA methylase variants were sought by PCR. RESULTS: High rates of resistance were seen in all centers. MIC50 and MIC90 for all A. baumannii and A. nosocomialis isolates from different centers were > 512 mg/L. The most frequent AME was ant(3″)-Ia (aadA1) in both of A. baumannii (74.1%) and A. nosocomialis (86%). armA was detected in A. baumannii and A. nosocomialis at the frequency of 41.6% and 67.4%, respectively. rmtA, B, C, D, aac(3)-Ia (aacC1) and aac(6')-Im were not detected, neither in A. baumannii nor A. nosocomialis. Moreover, aac(6')-Ih was only found in A. baumannii isolates. The distribution of some of the ARGs was limited to a definite center. CONCLUSION: The overall high-level carriage of ARGs in Acinetobacter species may limited usage of this class of antibacterials as a treatment option.

Heterologous Expression, Purification, and Characterization of the HspX, Ppe44, and EsxV Proteins of Mycobacterium tuberculosis.

BACKGROUND: Subunit vaccines are appropriate vaccine candidates for the prevention of some infections. In this study, three immunogenic proteins of Mycobacterium tuberculosis, including HspX, Ppe44, and EsxV as a new construction, were expressed alone and as a fusion protein to develop a new vaccine candidate against tuberculosis infection. METHODS: To make the fusion protein, the three genes were linked together by AEAAAKEAAAKA linkers and inserted into pET21b and pET32b vectors. Escherichia coli (E. coli) Top10 cells were transformed with the plasmid, and the purified plasmid was used to transform E. coli BL21 cells. Protein expression was induced with IPTG. After optimizing protein expression, the recombinant proteins were purified by Ni-NTA chromatography. Protein purification was confirmed by SDS-PAGE and Western blotting with an anti-poly histidine-peroxidase monoclonal antibody against the 6His-tags at the proteins' C termini. RESULTS: Directional cloning was confirmed by polymerase chain reaction (PCR), restriction enzyme digestion, and sequencing. The highest expression of the tri-fusion protein and HspX were obtained by the addition of 0.2 mM of IPTG to E. coli BL-21 cells at 37 °C and 18 h of incubation. For Ppe44 and EsxV, the optimum expression conditions were 18 °C and 16 h of incubation. SDS-PAGE and Western blots confirmed that the desired proteins were produced. CONCLUSION: The three desired proteins and the fusion protein were successfully expressed and the conditions for optimum expression determined. These recombinant proteins will be evaluated as vaccine candidates against tuberculosis. Further studies are needed to evaluate the abilities of these proteins to induce strong immunological responses.

Aluminum hydroxide nanoparticles show strong activity to stimulate Th-1 immune response against tuberculosis.

Many materials such as aluminum hydroxide have been tried as adjuvants to compensate low inherent immunogenicity of subunit vaccines. The aim of this study was to evaluate the specific immune response following the administration of aluminum hydroxide nanoparticles with EsxV antigen. The physiochemical properties of the nanoparticle were characterized in vitro. After subcutaneous immunization, cytokine secretion patterns including IFN-gama,IL-4, and TGF-beta levels were measured by indirect enzyme linked immunosorbent assay (ELISA). Aluminum hydroxide-NPs were demonstrated excellent effects to raise of IFN-γ secretion in compare to EsxV alone. Administration of aluminum hydroxide nanoparticles stimulates strong cellular immune response and could be considered as appropriate adjuvant against TB infection.

Construction of a Novel DNA Vaccine Candidate Encoding an HspX-PPE44-EsxV Fusion Antigen of Mycobacterium tuberculosis.

BACKGROUND: Mycobacterium tuberculosis is the causative agent of tuberculosis (TB). Bacille Calmette-Guerin (BCG) vaccine, is not effective in adults, therefore, many efforts have been made to produce an effective adult TB vaccine. The aim of this study was to develop a new tuberculosis DNA vaccine candidate encoding a recombinant HspX-PPE44-EsxV fusion antigen of M. tuberculosis. METHODS: A fusion DNA segment consisting of HspX, linker, PPE44, linker, and EsxV, after codon optimization, was designed. The fusion DNA was cloned and its sequence confirmed. Then, expression of a recombinant pcDNA3.1 (+)/HspX-PPE44-EsxV plasmid in Chinese hamster ovary (CHO) cells was verified by RT-PCR and Western-blot analysis. RESULTS: A 1968 bp band in RT-PCR and a 68 kDa band on Western-blot analysis confirmed transcription and expression of recombinant hspX-ppe44-esxV in eukaryotic cells. CONCLUSION: A recombinant DNA segment encoding the HspX-PPE44-EsxV fusion antigen of M. tuberculosis was constructed and considered to be tested as a new TB DNA vaccine candidate.