Biosafety and toxicity assessment of transgenic cotton-harboring insecticide and herbicide tolerant genes on albino mice.

Introduction: Genetic engineering has revolutionized agriculture by transforming biotic and abiotic stress-resistance genes in plants. The biosafety of GM crops is a major concern for consumers and regulatory authorities. Methodology: A 14-week biosafety and toxicity analysis of transgenic cotton, containing 5 transgenes ((Cry1Ac, Cry2A, CP4 EPSPS, VIP3Aa, and ASAL)), was conducted on albino mice. Thirty mice were divided into three groups (Conventional, Non-transgenic, without Bt, and transgenic, containing targeted crop) according to the feed given, with 10 mice in each group, with 5 male and 5 female mice in each group. Results: During the study, no biologically significant changes were observed in the non-transgenic and transgenic groups compared to the control group in any of the study's parameters i.e. increase in weight of mice, physiological, pathological, and molecular analysis, irrespective of the gender of the mice. However, a statistically significant change was observed in the hematological parameters of the male mice, while no such change was observed in the female study group mice. The expression analysis, however, of the TNF gene increases many folds in the transgenic group as compared to the non-transgenic and conventional groups. Conclusion: Overall, no physiological, pathological, or molecular toxicity was observed in the mice fed with transgenic feed. Therefore, it can be speculated that the targeted transgenic crop is biologically safe. However, more study is required to confirm the biosafety of the product on the animal by expression profiling.

Assessment of historical and projected changes in extreme temperatures of Balochistan, Pakistan using extreme value theory.

The fundamental consequences of global warming include an upsurge in the intensity and frequency of temperature extremes. This study provides an insight into historical trends and projected changes in extreme temperatures on annual and seasonal scales across "Balochistan, Pakistan". Historical trends are analyzed through the Mann Kendal test, and extreme temperatures (Tmax and Tmin) are evaluated using generalized extreme value (GEV) distribution for historical period (1991-2020) from the observational data and the two projected periods as near-future (2041-2070) and far-future (2071-2100) using a six-member bias-corrected ensemble of regional climate models (RCMs) projections from the coordinate regional downscaling experiment (CORDEX) based on the worst emission scenario (RCP8.5). The evaluation of historical temperature trends suggests that Tmax generally increase on yearly scale and give mixed signals on seasonal scale (winter, spring, summer, and autumn); however, Tmin trends gave mixed signals at both yearly and seasonal scale. Compared to the historical period, the return levels are generally expected to be higher for Tmax and Tmin during the both projection periods in the order as far-future > near-future > historical on yearly and seasonal basis; however, the changes in Tmin are more evident. Station-averaged anomalies of + 1.9 °C and + 3.6 °C were estimated in 100-year return levels for yearly Tmax for near-future and far-future, respectively, while the anomalies in Tmin were found to be + 3.5 °C and + 4.8 °C which suggest the intensified heatwaves but milder colder extreme in future. The findings provide guidance on improved quantification of changing frequencies and severity in temperature extremes and the associated impacts.

Analysis and experimental assessment of an optimized SERS substrate used to detect thiabendazole in apples with high sensitivity.

Pesticides that linger in the environment and ecosystems for an extended period can cause severe and dangerous health problems in humans. To detect pesticides in foods, the development of high-sensitivity and quick screening technologies was required. This research investigated the performance of Au@Ag NPs with varying thicknesses of the silver shell for detecting trace quantities of thiabendazole (TBZ) in apples using surface-enhanced Raman spectroscopy (SERS). The Au@Ag NPs were synthesized by coating 32 nm gold seeds with different thicknesses of silver shell ranging from 2.4 to 8.7 nm, achieved by adjusting the incorporation of AgNO3 and ascorbic acid. The optimized Au@Ag NPs with a 7.3 nm silver shell demonstrated outstanding SERS activity, high sensitivity, and a detection limit of 0.05 µg/mL for TBZ. The R2 values, representing the goodness of fit, were found to be 0.990 and 0.986 for standard and real TBZ samples, respectively, indicating a strong correlation between the measured signal and the TBZ concentration. The recovery analysis showed a reliable and accurate detection capability (96 to 105%), suggesting good reliability and accuracy of the SERS-based detection using the optimal Au@Ag NPs. Overall, this research highlights the potential of SERS with optimal Au@Ag NPs for rapid and effective monitoring of pesticides in the food industry.

AI and machine learning for soil analysis: an assessment of sustainable agricultural practices.

Sustainable agricultural practices help to manage and use natural resources efficiently. Due to global climate and geospatial land design, soil texture, soil-water content (SWC), and other parameters vary greatly; thus, real time, robust, and accurate soil analytical measurements are difficult to be developed. Conventional statistical analysis tools take longer to analyze and interpret data, which may have delayed a crucial decision. Therefore, this review paper is presented to develop the researcher's insight toward robust, accurate, and quick soil analysis using artificial intelligence (AI), deep learning (DL), and machine learning (ML) platforms to attain robustness in SWC and soil texture analysis. Machine learning algorithms, such as random forests, support vector machines, and neural networks, can be employed to develop predictive models based on available soil data and auxiliary environmental variables. Geostatistical techniques, including kriging and co-kriging, help interpolate and extrapolate soil property values to unsampled locations, improving the spatial representation of the data set. The false positivity in SWC results and bugs in advanced detection techniques are also evaluated, which may lead to wrong agricultural practices. Moreover, the advantages of AI data processing over general statistical analysis for robust and noise-free results have also been discussed in light of smart irrigation technologies. Conclusively, the conventional statistical tools for SWCs and soil texture analysis are not enough to practice and manage ergonomic land management. The broader geospatial non-numeric data are more suitable for AI processing that may soon help soil scientists develop a global SWC database.

Deep Learning Models for Automated Assessment of Breast Density Using Multiple Mammographic Image Types.

Recently, convolutional neural network (CNN) models have been proposed to automate the assessment of breast density, breast cancer detection or risk stratification using single image modality. However, analysis of breast density using multiple mammographic types using clinical data has not been reported in the literature. In this study, we investigate pre-trained EfficientNetB0 deep learning (DL) models for automated assessment of breast density using multiple mammographic types with and without clinical information to improve reliability and versatility of reporting. 120,000 for-processing and for-presentation full-field digital mammograms (FFDM), digital breast tomosynthesis (DBT), and synthesized 2D images from 5032 women were retrospectively analyzed. Each participant underwent up to 3 screening examinations and completed a questionnaire at each screening encounter. Pre-trained EfficientNetB0 DL models with or without clinical history were optimized. The DL models were evaluated using BI-RADS (fatty, scattered fibroglandular densities, heterogeneously dense, or extremely dense) versus binary (non-dense or dense) density classification. Pre-trained EfficientNetB0 model performances were compared using inter-observer and commercial software (Volpara) variabilities. Results show that the average Fleiss' Kappa score between-observers ranged from 0.31-0.50 and 0.55-0.69 for the BI-RADS and binary classifications, respectively, showing higher uncertainty among experts. Volpara-observer agreement was 0.33 and 0.54 for BI-RADS and binary classifications, respectively, showing fair to moderate agreement. However, our proposed pre-trained EfficientNetB0 DL models-observer agreement was 0.61-0.66 and 0.70-0.75 for BI-RADS and binary classifications, respectively, showing moderate to substantial agreement. Overall results show that the best breast density estimation was achieved using for-presentation FFDM and DBT images without added clinical information. Pre-trained EfficientNetB0 model can automatically assess breast density from any images modality type, with the best results obtained from for-presentation FFDM and DBT, which are the most common image archived in clinical practice.

Surveillance and Assessment of Risk Factors for Newcastle Disease Virus from Live Bird Retail Stalls in Lahore District of Pakistan.

Live bird markets (LBMs) in Asian countries are considered hubs for the spread of several poultry viruses. In Pakistan, there is a lack of uniformity in practices used in LBMs, which leads to the spread of poultry diseases. A cross-sectional survey was conducted in June-October 2017 to determine the circulation of Newcastle disease virus (NDV) in chickens being sold in live bird retail stalls (LBRSs) and to identify potential risk factors associated with estimated prevalence. A total of 189 stalls (n = 1134 birds) distributed in eight administrative towns of Lahore were visited. A pool of six oropharyngeal swabs was collected from each stall and tested by real-time reverse transcriptase PCR for the presence of NDV. Forty-two out of 189 swabs were found positive with an overall prevalence of 22.22% (95% confidence interval [Cl]: 16.88%-28.67%). Data for 11 potential risk factors acquired through questionnaires were analyzed by survey-weighted logistic regression and prevalence odds ratios (ORs) for associated risk factors were calculated. A final multivariable model identified three risk factors for NDV prevalence in LBRSs, including trading other poultry breeds alongside broilers (OR = 2.41; 95% confidence interval [CI] = 1.5-6.1), purchasing birds from mixed sources (OR = 3.12; 95% CI = 1.4-11.9), and number of birds sold per day (OR = 6.32; 95% CI = 1.9-23.5). Additionally, 24 selected samples were sequenced and phylogenetic analysis of the complete fusion gene (1662 bp) revealed that all isolates belonged to Subgenotype VII.2. This study provides important information on the epidemiology of NDV in Pakistan and highlights the importance of implementing surveillance and biosecurity practices in LBRSs.

Vigilancia y evaluación de factores de riesgo para el virus de la enfermedad de Newcastle en puestos de venta al menudeo de aves vivas en el distrito de Lahore en Pakistán. Los mercados de aves vivas (LBM, por sus siglas en inglés) en los países asiáticos se consideran centros de propagación de varios virus aviares. En Pakistán, existe una falta de uniformidad en las prácticas utilizadas en los mercados de aves vivas, lo que conduce a la propagación de enfermedades avícolas. Se realizó una encuesta transversal de junio a octubre del 2017 para determinar la circulación del virus de la enfermedad de Newcastle (NDV) en pollos que se venden en puestos minoristas de aves vivas y para identificar posibles factores de riesgo asociados con la prevalencia estimada. Se visitó un total de 189 puestos (n = 1134 aves) distribuidos en ocho ciudades administrativas de Lahore. Se recolectó un grupo de seis hisopos orofaríngeos de cada puesto y se analizó mediante transcripción reversa y PCR en tiempo real para detectar la presencia del virus de Newcastle. Cuarenta y dos de los 189 hisopos resultaron positivos con una prevalencia general del 22.22 % (intervalo de confianza [IC] del 95 % = 16.88­28.67). Los datos para 11 factores de riesgo potenciales adquiridos a través de cuestionarios se analizaron mediante regresión logística ponderada por encuesta y se calcularon las razones de probabilidad (OR) de prevalencia para los factores de riesgo asociados. Un modelo multivariable final identificó tres factores de riesgo para la prevalencia del virus de Newcastle en puestos minoristas de aves vivas, incluido el comercio de otras razas de aves de corral junto con pollos de engorde (OR = 2.41; IC del 95 % = 1.5­6.1), la compra de aves de fuentes mixtas (OR = 3.12; IC del 95 % = 1.4 ­11.9), y número de aves vendidas por día (OR = 6.32; IC 95% = 1.9­23.5). Además, se secuenciaron 24 muestras seleccionadas y el análisis filogenético del gene de fusión completo (1662 pb) reveló que todos los aislamientos pertenecían al subgenotipo VII.2. Este estudio brinda información importante sobre la epidemiología del virus de Newcastle en Pakistán y destaca la importancia de implementar prácticas de vigilancia y bioseguridad en los en puestos minoristas de aves vivas.

Assessment of wheat productivity responses and soil health dynamics under brackish ground water.

The continuous use of brackish groundwater for irrigation is detrimental for soil and crop attributes. A three-year research study was designed for the wheat crop to assess the effects of brackish groundwater on crop yield and soil health under a surface irrigation system. Three sites were selected in different cropping zones of Pakistan. The treatments comprised of irrigation with moderately brackish water having 0.8, 1.3 & 2.7 dSm-1 of salinity and canal water. The results indicated that EC, SAR, bicarbonates, Ca2+ and Mg2+ levels increased in the soil for consecutive years and this increase was more at site S3 followed by S2 and S1. As soil depth is concerned, the increase was more pronounced in upper layers of soil (0-15 cm) as compared to 15-30 cm depth. Growth and yield were also affected by the consecutive use of this water, the number of plants, plant height, the number of spikes per plant, and yield was reduced at all the three sites. However, the impact was less pronounced at the site S1 whereas S3 was the most affected one. Grain weight and dry matter weight were observed to be maximum at S1. Water productivity was also calculated for all the three sites. Maximum water productivity was observed at S1 followed by S2 & S3. It was concluded that the continuous use of brackish water would have an adverse effect on crop yield and subsequently, soil health is also affected by it significantly.

Variability of Breast Density Assessment and the Need for Additional Imaging: A Comparison between Computed Mammography and Digital Mammography.

OBJECTIVE: To determine the variability of breast density assessment and the need for additional imaging using computed radiography (CR) mammography versus digital radiography (DR) mammography. STUDY DESIGN: Cohort study. PLACE AND DURATION OF STUDY: Department of Radiology, The Aga Khan University Hospital, Karachi from March to June 2018. METHODOLOGY: Patients who underwent screening CR mammography, followed by DR mammography a year later, were selected. Only disease-free individuals were included in the study. Evaluation of breast density was done subjectively, using the breast imaging reporting and data system (BI-RADS) by two independent experienced radiologists. Statistical analysis was performed using the Wilcox Signed Rank-sum test to compare both modalities. Fisher Exact method was used to compare the need for ultrasound imaging.   Results: A total of 295 patients were included in the study. The mean age of the patients was 52.76 ± 0.64 years. There was a significant difference in the change of breast density when comparing both modalities (Z= -11.839, p <0.001). A statistically significant reduction in the need for further breast ultrasound was observed after DR mammography than with CR mammography (p <0.001).  Conclusion: Use of DR mammography, especially in patients with dense breast parenchyma, is a better screening tool overall. It translates to better feasibility for the radiologist and is more economical for the patient. DR mammography decreases unnecessary imaging and leads to better visualisation, thus providing a more accurate categorisation of breast density. Key Word: Computed radiography mammography, Breast density, Screening, Breast cancer, Digital mammography, Ultrasound.

Hyperspectral Near-Infrared Image Assessment of Surface-Acetylated Solid Wood.

Visualization of acetic anhydride flow and its heterogeneity within the wood block necessitates the development of a reliable and robust analytical method. Hyperspectral imaging has the potential to acquire a continuous spectrum of chemical analytes at different spectral channels in terms of pixels. The large set of chemical data (3-dimensional) can be expanded into relevant information in a multivariate fashion. We quantified gradients in acetylation degree over cross sections of Scots pine sapwood caused by a one-sided flow of acetic anhydride into wood blocks using near-infrared hyperspectral imaging. A principal component analysis (PCA) model was used to decompose the high-dimensional data into orthogonal components. Moreover, a partial least-squares (PLS) hyperspectral image regression model was developed to quantify heterogeneity in acetylation degree that was affected by the flow of acetic anhydride through wood blocks and into the tracheid cell walls. The model was validated and optimized with an external test data set and a prediction map using the root-mean-squared error of an individual predicted pixel. The model performance parameters are well suited, and prediction of the acetylation degree at the image level was complemented with confocal Raman imaging of selected areas on the microlevel. NIR image regression showed that the acetylation degree was determined not only by the time-dependent flow of the acetic anhydride through the wood macropores but also by the diffusion of the anhydride into the wood cell walls. Thereby, thin-walled earlywood sections were acetylated faster than the thick-walled latewood sections. Our results demonstrate the suitability of near-infrared imaging as a tool for quality control and process optimization at the industrial scale.

Occurrence of Aflatoxin M1 in raw and processed milk and assessment of daily intake in Lahore, Multan cities of Pakistan.

In this survey aflatoxin, M1 was quantified in raw and processed milk from various areas of two big cities of Punjab province, i.e. Lahore and Multan. The results indicated that approximately 90% of the raw milk samples collected from Lahore city was contaminated with aflatoxin M1. Similarly, around 92% of the raw milk samples collected from Multan city was contaminated with aflatoxin M1. All samples of processed milk and tea whiteners were contaminated and 56% of the contaminated processed milk samples and 66% of the contaminated tea whitener samples were violating the maximum limits. The dietary exposure data of AFM1 among six different groups was calculated, which indicated that the male children population was the most vulnerable group to AFM1, up to 6.68 ng L-1 per day and the least affected one was the female group above 20 years of age with 1.13 ng L-1 per day.

Knowledge, attitude, and practices regarding infection control measures among medical students.

OBJECTIVE: To assess the knowledge, attitude and reported practices of medical students regarding infection control measures. METHODS: The cross-sectional, questionnaire-based study was conducted at one public and one private medical university in Karachi from January to February 2016. The students enrolled were in their clinical years of the Bachelor of Medicine, Bachelor of Surgery course and their knowledge, attitude and practice were measured regarding infection control measures. SPSS 19 was used to analyse data. RESULTS: There were 413 medical students with a mean age of 21.78±1.10 years. Overall, 206(49.9%) students were from the private university and 207(50.1%) from the public institution. Students from the private institution had better knowledge compared to those from the public institution regarding hand hygiene (p<0.001), needlestick injuries (p<0.001) and surgical scrubbing (p=0.007), as well as better reported practices regarding hand hygiene (p<0.001) and surgical scrubbing (p=0.001). CONCLUSIONS: Knowledge and practices of medical students regarding the method of surgical scrubbing and needlestick injury protocols in particular needed improvement.