EFFECT OF DIFFERENT SOLVENTS ON THE CHEMICAL COMPOSITION AND ANTI-DIABETIC ACTIVITY OF ACACIA ARABICA AND ZIZYPHUS MAURITIANA

The current study was designed to investigate the effect of solvents on chemical composition and antidiabetic activity of Zizyphus mauritiana and Acacia Arabica extracts. Total five solvents were used for this purpose (100% methanol, 50% aqueous methanol, 100% ethanol, 50% aqueous ethanol and aqueous). The data obtained from the investigation was subjected to the statistical analysis by using analysis of variance technique. The present study revealed that maximum antioxidant activity was attributed to Acacia arabica (96.53 ± 0.46%) followed by Zizyphus mauritiana (94.33 ± 0.52% by 50% aqueous ethanol extracts). Maximum total phenolic content of both Zizyphus mauritiana and Acacia arabica (670.83 ± 1.46 mg GAE/100g and 934.34 ± 0.89 mg GAE/100g) were shown by 50% aqueous ethanol extracts while maximum total flavonoid content (146.36 ± 0.81 mg QE/100 g, 172.52 ± 0.99 mg QE/100 g) was exhibited by 50% aqueous ethanol extract. The maximum (IC 50= 49.63 ± 0.12 µg/mL) antidiabetic activity was found in aqueous extract of Acacia arabica while in Zizyphus mauritiana the aqueous extract indicated excellent (IC 50= 46.90 ± 0.23 µg/mL) antidiabetic activity

Extremely Preterm (23 Weeks) Vaginal Cephalic Delivery En Caul and Subsequent Postpartum Intraventricular Hemorrhage and Respiratory Distress: A Teaching Case.

En caul deliveries are defined as a fetus that is delivered completely contained within an amniotic sac and are considered to be less common than 1 in 80,000 live births. Vaginal en caul births compared to abdominal or cesarean are the rarest subtype. Most en caul births are associated with prematurity and low gravida. The combination of prematurity, high gravida, vaginal en caul birth, and severe postpartum complications has not previously been described. We report a woman with gravida of 12 delivering vaginally a neonate female en caul at the extremely preterm gestational age of 23 weeks. The neonate subsequently decompensated, underwent respiratory distress, and was diagnosed with a bilateral intraventricular hemorrhage. Owing to deteriorating status, supportive care was removed and the infant was pronounced dead 5 days after delivery

Development of Novel Experimental Infrastructure for Collecting High-Fidelity Experimental Data for Refrigerant to Air Heat Exchangers

Manufactures of fin-and-tube heat exchangers often employ predictive modelling tools in order to reduce development cost and time. These tools require high-fidelity experimental data to validate the accuracy of their predictions. To that end, this paper presents the design and development of a custom-designed pumped refrigerant loop to collect high-fidelity experimental data for fin-and-tube heat exchangers in three operating modes: (1) single-phase refrigerant, (2) evaporator, and (3) condenser mode. It is combined with a small-scale wind tunnel installed in a psychrometric chamber facility for the purpose of validating the recently developed discretized fin-and-tube heat exchanger models (Sarfraz et al., 2019a and 2019b). The pumped refrigerant loop is able to precisely control desired refrigerant test conditions, flowrate to each individual heat exchanger circuit, and has been sized in order to test heat exchanger coils up to a capacity of 5 tons (17.5 kW). A preliminary test plan and uncertainty analysis is presented for the first heat exchanger coil to be tested. The uncertainty analysis showed that the experiment will have the capability of measuring overall coil capacity within ±2%. A design of experiments is also presented, which suggests that 9 tests per coil is an adequate number for minimizing experimental effort. A preliminary experiment was performed which showed that the average air and refrigerant side capacities match to within 1.1% of each other. This provides evidence that the experimental setup has the capability to far exceed the 5% threshold set by ASHRAE Standard 33 (2016)

Prevalence of Muscle Dysmorphia and Associated Health Activities in Male Medical Students in Karachi, Pakistan

Background: Muscle Dysmorphia (MD) is a subtype of body dysmorphic disorder (BDD) and is currently classified under anxiety disorders (subheading: Obsessive-compulsive disorder) in DSM 5. MD is hypothesized to affect the self-esteem and social outlook of the younger generation. MD shows a higher rate in males and may influence their self-confidence rendering them more prone towards using steroids, supplementary proteins and other drugs to alter their physical outlooks as shown in previous studies. This problem has been on the rise lately due to revolutionary advancement in the media and film industry and the abrupt changes about the standards of physical good looks and body shapes. With the lack of studies done in our population, our study will be helpful to consider the prevalence of the disease in our setting and increase awareness in the general public and clinicians. We hope to help clinicians/ therapists find better options in managing the disease. Materials: We performed a cross-sectional study with a sample size of 246 medical school students in Karachi to collect data through self-administered questionnaires. We used the DSM 5 criteria for the diagnosis of BDD and additional questions on the presence of MD. Nutritional habits, exercise routines, use of supplements and drugs were also obtained for exploratory analysis. Results: Our study predicted the prevalence of MD to be 25%. Other main findings included statistical significant associations between MD and the thoughts and practice of steroid use for muscularity. Conclusion: MD is an underdiagnosed and often unrecognized disease that we believe has significant consequences for the young male population. Further work is needed on this in our part of the world. Our research, we believe, can be a stepping stone for further studies that would incorporate wider populations

Evaluation of Indole production and Tellurite reduction for speciation of Candida species and Trichosporon species

Background: Candidiasis is one of the commonest infections in man, along with Trichosporon infection. Conventional methods for identification are often delayed, which leads to delay in empirical therapy in these infections. Methods: We here describe two newer methods, i.e. Indole production and Tellurite reduction for identification of these two genera. Results: Both these tests, combined together, were equally good as compared to conventional identification techniques. Conclusion: Indole production and Tellurite reduction are useful tests to identify these common yeast pathogens in the laboratory

Atrx Deletion in Neurons Leads to Sexually Dimorphic Dysregulation of miR-137 and Spatial Learning and Memory Deficits.

ATRX gene mutations have been identified in syndromic and non-syndromic intellectual disabilities in humans. ATRX is known to maintain genomic stability in neuroprogenitor cells, but its function in differentiated neurons and memory processes remains largely unresolved. Here, we show that the deletion of neuronal Atrx in mice leads to distinct hippocampal structural defects, fewer presynaptic vesicles, and an enlarged postsynaptic area at CA1 apical dendrite-axon junctions. We identify male-specific impairments in long-term contextual memory and in synaptic gene expression, linked to altered miR-137 levels. We show that ATRX directly binds to the miR-137 locus and that the enrichment of the suppressive histone mark H3K27me3 is significantly reduced upon the loss of ATRX. We conclude that the ablation of ATRX in excitatory forebrain neurons leads to sexually dimorphic effects on miR-137 expression and on spatial memory, identifying a potential therapeutic target for neurological defects caused by ATRX dysfunction

Comparative efficacy of Levofloxacin and Prulifloxacin against Uropathogenic Escherichia coli and Klebsiella spp. from a tertiary care hospital and their correlation with expression of lipase and lecithinase

Background: Fluoroquinolone antibiotics are often used for treatment of urinary tract infections. Prulifloxacin is a newer fluoroquinolone antimicrobial, and a prodrug of Ulifloxacin. It has been approved for use in Urinary tract infections and respiratory tract infections in many countries, but comparative studies comparing its efficacy against that of Levofloxacin are rare. Objectives: Our study aimed at studying this comparative efficacy. Methods: E. coli and Klebsiella spp. were isolated and identified from urine samples and their antibiogram was seen in respect to Levofloxacin and Prulifloxacin by Diak diffusion method. Antibiogram results were correlated with lecithinase, lipase and protease activities of the bac teria. Results: Most of the E. coli isolates were resistant to Prulifloxacin, but is was mostly effective against Klebsiella spp. Conclusion: Prulifloxacin is not a good option for empirical treatment of urinary tract infection, especially those caused by E. coli

Dynamic Dual-Attentive Aggregation Learning for Visible-Infrared Person Re-identification

© 2020, Springer Nature Switzerland AG. Visible-infrared person re-identification (VI-ReID) is a challenging cross-modality pedestrian retrieval problem. Due to the large intra-class variations and cross-modality discrepancy with large amount of sample noise, it is difficult to learn discriminative part features. Existing VI-ReID methods instead tend to learn global representations, which have limited discriminability and weak robustness to noisy images. In this paper, we propose a novel dynamic dual-attentive aggregation (DDAG) learning method by mining both intra-modality part-level and cross-modality graph-level contextual cues for VI-ReID. We propose an intra-modality weighted-part attention module to extract discriminative part-aggregated features, by imposing the domain knowledge on the part relationship mining. To enhance robustness against noisy samples, we introduce cross-modality graph structured attention to reinforce the representation with the contextual relations across the two modalities. We also develop a parameter-free dynamic dual aggregation learning strategy to adaptively integrate the two components in a progressive joint training manner. Extensive experiments demonstrate that DDAG outperforms the state-of-the-art methods under various settings