Assessment of Parents' Perceptions of Childhood Immunization: A Cross-Sectional Study from Pakistan.

Immunization is one of the most cost-effective public health interventions, with considerable impacts on people's health. Parents' perception of their knowledge, attitude, and satisfaction is an important factor, as they may be targeted by interventions for better immunization coverage. Therefore, this study aimed to assess parents' perceptions in terms of their knowledge, attitude, and satisfaction of the immunization of their children aged less than two years of age, in two cities of Pakistan. A descriptive cross-sectional study was conducted in the vicinity of Rawalpindi and Islamabad from March to August 2019. A semi-structured questionnaire was used for the data collection on a convenient sample of parents. The questionnaire was hand-delivered to the parents by data collectors. Descriptive and inferential statistics were used for data analysis via SPSS version 22. A total of n = 382 respondents were included in the data analysis. Statistically significant differences were found between the parents' knowledge scores and their education levels and monthly incomes (p < 0.05). Parents with master's education degrees and low monthly incomes had significantly better knowledge (p < 0.05). Additionally, 96.85% of the respondents believed that child immunization was important. In addition, more than half of the respondents (57.58%) thought that the affordability of vaccines was a principal factor for delays in immunization. Although the parents' knowledge regarding the immunization of their children was not adequate, they had positive perceptions toward it.

Quantitative trait loci (QTL) mapping for physiological and biochemical attributes in a Pasban90/Frontana recombinant inbred lines (RILs) population of wheat (Triticum aestivum) under salt stress condition.

Salt stress causes nutritional imbalance and ion toxicity which affects wheat growth and production. A population of recombinant inbred lines (RILs) were developed by crossing Pasban90 (salt tolerant) and Frontana (salt suceptible) for identification of quantitative trait loci (QTLs) for physiological traits including relative water content, membrane stability index, water potential, osmotic potential, total chlorophyll content, chlorophyll a, chlorophyll b and biochemical traits including proline contents, superoxide dismutase, sodium content, potassium content, chloride content and sodium/potassium ratio by tagging 202 polymorphic simple sequence repeats (SSR) markers. Linkage map of RILs comprised of 21 linkage group covering A, B and D genome for tagging and maped a total of 60 QTLs with major and minor effect. B genome contributed to the highest number of QTLs under salt stress condition. Xgwm70 and Xbarc361 mapped on chromosome 6B was linked with Total chlorophyll, water potential and sodium content. The increasing allele for all these QTLs were advanced from parent Pasban90. Current study showed that Genome B and D had more potentially active genes conferring plant tolerance against salinity stress which may be exploited for marker assisted selection to breed salinity tolerant high yielding wheat varieties.

Modulation of agronomic and nutritional response of Pleurotus eryngii strains by utilizing glycine betaine enriched cotton waste.

BACKGROUND: This study aimed to evaluate the possibility of cotton waste enrichment with glycine betaine (GB) for production of two strains (P9, P10) of king oyster (Pleurotus eryngii). Cotton waste was used as (100%) control (T0 = cotton waste) and augmented with various combinations of GB, (T1 = 2 mmol L-1 , T2 = 4 mmol L-1 , T3 = 6 mmol L-1 , T4 = 8 mmol L-1 and T5 = 10 mmol L-1 ). The response of king oyster to GB was evaluated by earliness, yield, biological efficiency (BE), minerals (nitrogen, phosphorus, potassium, zinc (Zn), copper (Cu), magnesium (Mg), manganese (Mn), iron (Fe), sodium (Na), calcium (Ca)), total sugars, total soluble solids, reducing sugars, non-reducing sugars, ascorbic acid, proximate (crude protein, carbohydrates, crude fibers, ash, fats) content of fruiting body and Fourier-transform infrared (FTIR) spectroscopy analysis compared with the control substrate (cotton waste). RESULTS: The earliness, yield, and BE were higher as compared to control substrate and increased with an augmentation in the concentration of GB within the cotton waste. Two strains showed (on dry weight basis) 33.9-54.9 mg g-1 nitrogen, 6.8-12.5 mg g-1 phosphorus, 16.9-25.1 mg g-1 potassium, 40.5-64.2 mg kg-1 Zn, 17.1-37.3 mg kg-1 Cu, 1174-1325 mg kg-1 Mg, 20.1-29.1 mg kg-1 Mn, 129-265 mg kg-1 Fe, 779-835 mg kg-1 Ca), 6.3%-11.3% total sugars, 7.3-14.9 °Brix total soluble solids, 2.1-7.3% reducing sugars, 10.4-18.1% crude protein, 3.6-4.4% crude fiber and 5.6-16.7 mg (100 g)-1 on various concentration of GB enrich cotton waste. Cotton waste enriched with GB significantly affected nutritional profile of king oyster mushroom. CONCLUSION: The results revealed that GB enriched cotton waste can be used as an innovative substrate to enhance the yield and quality of king oyster mushroom. © 2019 Society of Chemical Industry.

Development and Prospective Validation of a Machine Learning-Based Risk of Readmission Model in a Large Military Hospital.

BACKGROUND: Thirty-day hospital readmissions are a quality metric for health care systems. Predictive models aim to identify patients likely to readmit to more effectively target preventive strategies. Many risk of readmission models have been developed on retrospective data, but prospective validation of readmission models is rare. To the best of our knowledge, none of these developed models have been evaluated or prospectively validated in a military hospital. OBJECTIVES: The objectives of this study are to demonstrate the development and prospective validation of machine learning (ML) risk of readmission models to be utilized by clinical staff at a military medical facility and demonstrate the collaboration between the U.S. Department of Defense's integrated health care system and a private company. METHODS: We evaluated multiple ML algorithms to develop a predictive model for 30-day readmissions using data from a retrospective cohort of all-cause inpatient readmissions at Madigan Army Medical Center (MAMC). This predictive model was then validated on prospective MAMC patient data. Precision, recall, accuracy, and the area under the receiver operating characteristic curve (AUC) were used to evaluate model performance. The model was revised, retrained, and rescored on additional retrospective MAMC data after the prospective model's initial performance was evaluated. RESULTS: Within the initial retrospective cohort, which included 32,659 patient encounters, the model achieved an AUC of 0.68. During prospective scoring, 1,574 patients were scored, of whom 152 were readmitted within 30 days of discharge, with an all-cause readmission rate of 9.7%. The AUC of the prospective predictive model was 0.64. The model achieved an AUC of 0.76 after revision and addition of further retrospective data. CONCLUSION: This work reflects significant collaborative efforts required to operationalize ML models in a complex clinical environment such as that seen in an integrated health care system and the importance of prospective model validation.

Synthetic N-[(substitutedsulfamoyl)phenyl]acetamides as moderate chymotrypsin inhibitors.

A facile method has been implemented for the synthesis of different N-substituted sulfamoylacetamides by reacting 4-acetamidobenzenesulfonyl chloride (1) with different alkyl/aralkyl/aryl amines (2a-q) in basic aqueous media under controlled pH to afford -[(Substitutedsulfamoyl) phenyl]acetamides (3a-q) which were confirmed through spectral analysis like FT-IR, EIMS and 1H-NMR. Moreover, the synthesized derivatives were screened against α-Chymotrypsin. The enzyme inhibitory results revealed that most of the synthesized compounds were found to be moderate enzyme inhibitors.