Dr Mohammed Mahmoud Youssif

BACKGROUND: Hepatic exteriorization during Kasai portoenterostomy is usually associated with profound hypotension. This study aimed to assess the role of prophylactic norepinephrine infusion in maintaining blood pressure in infants undergoing Kasai portoenterostomy operation.

METHODS: Thirty-two infants scheduled for Kasai portoenterostomy operation were randomly assigned to one of two groups: Norepinephrine group: this group received prophylactic intraoperative norepinephrine infusion, Control group: this group received placebo saline infusion. The primary outcome was the incidence of hypotension during liver exteriorization, defined as a persistent reduction of the mean arterial pressure (MAP) ≥20% of the baseline reading requiring release of the liver. Other outcomes included: the frequency of stoppage of surgery and release of the liver, liver function variables, arterial blood gases parameters, total volume of intraoperative infused fluids, and incidence of bradycardia and hypertension.

RESULTS: The incidence of persistent hypotension (defined as the need for liver release after administering IV fluid and vasopressor boluses) during liver exteriorization, was 12.5% (2 patients) in the norepinephrine group compared to 75% (12 patients) in the control group, relative risk (95% confidence interval [CI]): 0.17 (0.04-0.63), p =  0.001. Rescue norepinephrine boluses were used in 3 patients (18.8%) in the norepinephrine group compared to 13 patients (81.3%) in the control group, relative risk (95% CI): 0.23 (0.08-0.66), p =  0.001.

CONCLUSION: Among infants with biliary atresia undergoing Kasai portoenterostomy operation, norepinephrine infusion significantly reduced the incidence of persistent severe hypotension during hepatic exteriorization requiring liver release.

CLINICAL TRIAL IDENTIFIER: NCT05521152. REGISTRATION URL: https://clinicaltrials.gov/study/NCT05521152.

Crop phenology describes the physiological development stages of crops from planting to harvest which is valuable information for decision makers to plan and adapt agricultural management strategies. In the era of big Earth observation data ubiquity, attempts have been made to accurately detect crop phenology using Remote Sensing (RS) and high resolution weather data. However, most studies have focused on large scale predictions of phenology or developed methods which are not adequate to help crop modeler communities on leveraging Sentinel-1 and Sentinal-2 data and fusing them with high resolution climate data, using a novel framework. For this, we trained a Machine Learning (ML) LightGBM model to predict 13 phenological stages for eight major crops across Germany at 20 m scale. Observed phenologies were taken from German national phenology network (German Meteorological Service; DWD) between 2017 and 2021. We proposed a thorough feature selection analysis to find the best combination of RS and climate data to detect phenological stages. At national scale, predicted phenology resulted in a reasonable precision of R2 > 0.43 and a low Mean Absolute Error of 6 days, averaged over all phenological stages and crops. The spatio-temporal analysis of the model predictions demonstrates its transferability across different spatial and temporal context of Germany. The results indicated that combining radar sensors with climate data yields a very promising performance for a multitude of practical applications. Moreover, these improvements are expected to be useful to generate highly valuable input for crop model calibrations and evaluations, facilitate informed agricultural decisions, and contribute to sustainable food production to address the increasing global food demand.

Nowadays, there is a strong interest in the scientific community in developing innovative methodologies within a green analytical chemistry framework. Herein, we introduce the first chromatographic approaches for the concurrent estimation of paracetamol (PAR), carbinoxamine (CRX), and pseudoephedrine (PSE) intended to relieve COVID-19 and common cold symptoms. The first method was thin layer chromatography (TLC) densitometry, which depends on the separation of the studied medications on TLC silica gel plates using ethyl acetate: methanol: ammonia (7.0: 3.0: 0.2, by volume) as the developing system, and were scanned at 208.0 nm. The data were linear in the ranges of 1-25 μg/band for PAR, 1-25 μg/band for PSE and 0.1-5 μg/band for CRX. The second method was reversed-phase high-performance liquid chromatography separation on a Kromasil C18 column using a mixture of 0.01 M phosphate buffer containing 0.1% triethylamine (pH 3.5) adjusted with orthophosphoric acid and ethanol at a flow rate of 1.0 mL/min in a gradient program. The separated peaks were detected at 215.0 nm over a concentration range of 10-250 μg/mL for PAR, 5-35 μg/mL for PSE, and 0.5-25 μg/mL for CRX. Both approaches were validated according to International Conference on Harmonization (ICH) guidelines. Finally, the impact of these methods on the environment was evaluated by many tools.

A green developed spectrofluorimetric method has been applied for Antazoline (ANT) and Xylometazoline (XLO) determination in both pharmaceutical formulation and pure form. The developed method is synchronous spectrofluorimetry coupled with the second derivative mathematical tool for the determination of antazoline and xylometazoline in their dosage form. The developed method depends on reacting the cited drugs with dansyl chloride, a suitable derivatizing agent, to generate highly fluorescent derivatives. The products formed were measured at emission wavelengths; 703.0 and 712.0 nm after being excited at wavelengths; 350.0 and 355.0 nm for antazoline and xylometazoline, respectively. Synchronous spectrofluorimetry coupled with second derivative mathematical tool was developed and optimized using fluorescence data manager software generating second derivative peak amplitudes at 556.5 nm for antazoline and 598.0 nm for xylometazoline. Linear responses have been represented over a wide range of concentration 0.5-12.0 µg/mL for antazoline and 0.1-10.0 µg/mL for xylometazoline, correspondingly. Method validation was successfully applied. Additionally, statistical comparison of developed method with official ones has been carried out where no significant difference was found. Evaluation of the method's greenness was proven using several assessment tools. Indeed, the method developed is found to be precise, sensitive, and discriminating to assess the cited drugs for regular analysis.