Assessment of tuberculosis among male prisoners in Shiraz central prison, south of Iran.

Background: Prisons play an important role in the prevalence of Tuberculosis (TB) in a region. This study aimed to determine the situation of TB in high-risk male prisoners in Shiraz central prison of Fars province in southern Iran. Methods: This cross-sectional study (June-October 2018) was conducted on male prisoners in Shiraz central prison, southern Iran. According to 4 criteria, the prisoners were determined as high-risk prisoners for TB, and para clinical tests included three sputum samples and chest radiograph were performed for them. Then, the high risk and low risk participants were compared in terms of demographic characteristics and past medical history. Results: Among 2,995 prisoners, only 108 (3.6%) had at least one of the high-risk criteria. But after performing further TB tests for these prisoners, no prisoners with TB disease were found. The high-risk prisoners were statistically older than low-risk prisoners (38.30±9.74 vs. 35.17±9.62, P=0.001). Also, the length of incarceration was statistically different in both groups (P=0.002), and drug abuse was more in high-risk group (P<0.001). Moreover, high risk prisoners used cigarettes/day more (14.87±11.55 vs. 9.71±9.09, P<0.001), but both groups were not different in term of the marital status (P=0.519), educational level (P=0.662), job (P=0.39), and nationality (P=0.342). Conclusion: Our results showed that none of the high-risk prisoners for TB had positive test. The length of incarceration, drug abuse, smoking, as well as age were more in high-risk prisoners in comparing low risk group

Effects of medium and culture conditions on folate production by Streptococcus thermophilus BAA-250

The present study was conducted to investigate the effects of culture conditions on folate production by Streptococcus thermophilus BAA-250. Lactose (3g/L) and yeast extract (20g/L) were found to be the more suitable carbon and nitrogen sources for folate production by S. thermophilus BAA-250. para-aminobenzoic acid (pABA) higher than 1 µM had no significant effect on folate biosynthesis. The optimum pH for folate production was shown to be 7.0 with a folate yield and productivity of 54.53 (µg/L) and 2.27 (µg/L.h), respectively. Optimum folate production obtained in the presence of lactose and yeast extract in a controlled pH of 7 during batch fermentation in bioreactor. Kinetic studies indicated that folate production by S. thermophilus is growth-associated process

Modeling of Reference Crop Evapotranspiration in Wet and Dry Climates Using Data-Mining Methods and Empirical Equations

In the present study, performance of data-mining methods in modeling and estimating reference crop evapotranspiration (ETo) is investigated. To this end, different machine learning, including Artificial Neural Network (ANN), M5 tree, Multivariate Adaptive Regression Splines (MARS), Least Square Support Vector Machine (LS-SVM), and Random Forest (RF) are employed by considering different criteria including impacts of climate (eight synoptic stations in humid and dry climates), accuracy, uncertainty and computation time. Furthermore, to show the application of data-mining methods, their results are compared with some empirical equations, that indicated the superiority of data- mining methods. In the humid climate, it was demonstrated that M5 tree model is the best if only accuracy criterion is considered, and MARS is a better data-mining method by considering accuracy, uncertainty, and computation time criteria. While in the dry climate, the ANN has better results by considering accuracy and all other criteria. In the final step, for a comprehensive investigation of data-mining ability in ETo modeling, all data in humid and dry climates are combined. Results showed the highest accuracy by MARS and ANN models

Gum Tragacanth (GT): A Versatile Biocompatible Material beyond Borders

The use of naturally occurring materials in biomedicine has been increasingly attracting the researchers' interest and, in this regard, gum tragacanth (GT) is recently showing great promise as a therapeutic substance in tissue engineering and regenerative medicine. As a polysaccharide, GT can be easily extracted from the stems and branches of various species of Astragalus. This anionic polymer is known to be a biodegradable, non-allergenic, non-toxic, and non-carcinogenic material. The stability against microbial, heat and acid degradation has made GT an attractive material not only in industrial settings (e.g., food packaging) but also in biomedical approaches (e.g., drug delivery). Over time, GT has been shown to be a useful reagent in the formation and stabilization of metal nanoparticles in the context of green chemistry. With the advent of tissue engineering, GT has also been utilized for the fabrication of three-dimensional (3D) scaffolds applied for both hard and soft tissue healing strategies. However, more research is needed for defining GT applicability in the future of biomedical engineering. On this object, the present review aims to provide a state-of-the-art overview of GT in biomedicine and tries to open new horizons in the field based on its inherent characteristics

Comparative growth and physiological responses of tetraploid and hexaploid species of wheat to flooding stress

Present study is aimed to comparatively investigate the response of two ploidy levels of wheat including a tetraploid (Triticum turgidum L.) and a hexaploid (Triticum aestivum L.) wheat to different durations of flooding stress. Wheat seedlings were exposed to flooding stress for 0, 3, 6 and 9 days. Results showed that all flooding treatments significantly decreased the shoot and root length, and chlorophyll content of both species of wheat. The decrease in chlorophyll content of tetraploid wheat was more than that of hexaploid one. In both species, ADH activity of root was significantly increased under flooding stress, where the increase was more in hexaploid wheat. Flooding stress did not significantly affect root and shoot water content, root porosity, and shoot protein content of any wheat species. Tetraploid and hexaploid wheat used different mechanisms for better tolerance of flooding condition, where tetraploid wheat increased the proline content but in hexaploid wheat, an increase in soluble sugar content was observed.</p

Development of a bivalent protein-based vaccine candidate against invasive pneumococcal diseases based on novel pneumococcal surface protein A in combination with pneumococcal histidine triad protein D

Extensive efforts have been made toward improving effective strategies for pneumococcal vaccination, focusing on evaluating the potential of multivalent protein-based vaccines and overcoming the limitations of pneumococcal polysaccharide-based vaccines. In this study, we investigated the protective potential of mice co-immunization with the pneumococcal PhtD and novel rPspA proteins against pneumococcal sepsis infection. The formulations of each antigen alone or in combination were administered intraperitoneally with alum adjuvant into BALB/c mice three times at 14-day intervals. The production of antigen-specific IgG, IgG1 and IgG2a subclasses, and IL-4 and IFN-γ cytokines, were analyzed. Two in vitro complement- and opsonophagocytic-mediated killing activities of raised antibodies on day 42 were also assessed. Finally, the protection against an intraperitoneal challenge with 106 CFU/mouse of multi-drug resistance of Streptococcus pneumoniae ATCC49619 was investigated. Our findings showed a significant increase in the anti-PhtD and anti-rPspA sera IgG levels in the immunized group with the PhtD+rPspA formulation compared to each alone. Moreover, the results demonstrated a synergistic effect with a 6.7- and 1.3- fold increase in anti-PhtD and anti-rPspA IgG1, as well as a 5.59- and 1.08- fold increase in anti-PhtD and anti-rPspA IgG2a, respectively. Co-administration of rPspA+PhtD elicited a mixture of Th-2 and Th-1 immune responses, more towards Th-2. In addition, the highest complement-mediated killing activity was observed in the sera of the immunized group with PhtD+rPspA at 1/16 dilution, and the opsonophagocytic activity was increased from 74% to 86.3%. Finally, the survival rates showed that mice receiving the rPspA+PhtD formulation survived significantly longer (100%) than those receiving protein alone or PBS and exhibited the strongest clearance with a 2 log10 decrease in bacterial load in the blood 24h after challenge compared to the control group. In conclusion, the rPspA+PhtD formulation can be considered a promising bivalent serotype-independent vaccine candidate for protection against invasive pneumococcal infection in the future

Predictive models for Alzheimer's disease diagnosis and MCI identification: The use of cognitive scores and artificial intelligence algorithms

The paper presents a comprehensive study on predictive models for Alzheimer's disease (AD) and mild cognitive impairment (MCI) diagnosis, implementing a combination of cognitive scores and artificial intelligence algorithms. The research includes detailed analyses of clinical and demographic variables such as age, education, and various cognitive and functional scores, investigating their distributions and correlations with AD and MCI. The study utilizes several machine-learning classifiers, comparing their performance through metrics like accuracy, precision, and area under the ROC curve (AUC). Key findings include the influence of gender on AD prevalence, the potential protective effect of education, and the significance of functional decline and cognitive performance scores in the models. The results demonstrate the effectiveness of ensemble methods and the robustness of the models across different data subsets, highlighting the potential of artificial intelligence in enhancing diagnostic accuracy for Alzheimer's disease and mild cognitive impairment

Effect of extrinsic and intrinsic parameters on inulinase production by Aspergillus niger ATCC 20611

Background: Inulinase is a versatile enzyme from glycoside hydrolase family which targets the \u3b2-2, 1 linkage of fructopolymers. In the present study, the effect of medium composition and culture conditions on inulinase production by Aspergillus niger ATCC 20611 was investigated in shake-flasks. Results: The highest extracellular inulinase (3199 U/ ml) was obtained in the presence of 25% (w/v) sucrose, 0.5% (w/v) meat extract, 1.5% (w/v) NaNO3 and 2.5 mM (v/v) Zn2+, at initial pH of 6.5, temperature 35\ubaC and 6% (v/v) of spores suspension in the agitation speed of 100 rpm. Surfactants showed an inhibitory effect on enzyme production. The optimum temperature for inulinase activity was found to be 50\ubaC. TLC analysis showed the presence of both exo- and endo-inulinase. Conclusion: Sucrose, Zn2+, and aeration were found to be the most effective elements in inulinase production by A. niger ATCC 20611. TLC analysis also showed that the crude enzyme contained both endo and exoinulinases. The strain is suggested as a potential candidate for industrial enzymatic production of fructose from inulin

Effects of medium and culture conditions on folate production by Streptococcus thermophilus BAA-250.

The present study was conducted to investigate the effects of culture conditions on folate production by Streptococcus thermophilus BAA-250. Lactose (3g/L) and yeast extract (20g/L) were found to be the more suitable carbon and nitrogen sources for folate production by S. thermophilus BAA-250. para-aminobenzoic acid (pABA) higher than 1 µM had no significant effect on folate biosynthesis. The optimum pH for folate production was shown to be 7.0 with a folate yield and productivity of 54.53 (µg/L) and 2.27 (µg/L.h), respectively. Optimum folate production obtained in the presence of lactose and yeast extract in a controlled pH of 7 during batch fermentation in bioreactor. Kinetic studies indicated that folate production by S. thermophilus is growth-associated process

An energy-aware and Q-learning-based area coverage for oil pipeline monitoring systems using sensors and Internet of Things

Pipelines are the safest tools for transporting oil and gas. However, the environmental effects and sabotage of hostile people cause corrosion and decay of pipelines, which bring financial and environmental damages. Today, new technologies such as the Internet of Things (IoT) and wireless sensor networks (WSNs) can provide solutions to monitor and timely detect corrosion of oil pipelines. Coverage is a fundamental challenge in pipeline monitoring systems to timely detect and resolve oil leakage and pipeline corrosion. To ensure appropriate coverage on pipeline monitoring systems, one solution is to design a scheduling mechanism for nodes to reduce energy consumption. In this paper, we propose a reinforcement learning-based area coverage technique called CoWSN to intelligently monitor oil and gas pipelines. In CoWSN, the sensing range of each sensor node is converted to a digital matrix to estimate the overlap of this node with other neighboring nodes. Then, a Q-learning-based scheduling mechanism is designed to determine the activity time of sensor nodes based on their overlapping, energy, and distance to the base station. Finally, CoWSN can predict the death time of sensor nodes and replace them at the right time. This work does not allow to be disrupted the data transmission process between sensor nodes and BS. CoWSN is simulated using NS2. Then, our scheme is compared with three area coverage schemes, including the scheme of Rahmani et al., CCM-RL, and CCA according to several parameters, including the average number of active sensor nodes, coverage rate, energy consumption, and network lifetime. The simulation results show that CoWSN has a better performance than other methods