Raoultella species associated sepsis in children: A case series at a tertiary hospital, Karachi

Objective: To determine the clinical outcome and management options of gram-negative Raoultella species reported at a tertiary care pediatric Hospital in Karachi.Study design: Descriptive study.Place and duration of study: Pediatric and child Health department of The Aga Khan University Hospital from January 2017 to June 2020.Methodology: A retrospective chart review was done. Data was extracted for 20 patients with culture-positive Raoultella species. Study variables included demographic features, infection site, antibiotic sensitivities, Hospital duration, clinical outcome, and management options. Data were summarised using descriptive statistics and Kaplan-Meier plots using SPSS version 22.Results: A total of twenty-three site cultures positive with Raoultella species were isolated among 20 children with a wide array of clinical symptoms and disease severity. Predominantly the organism was isolated in blood with 12 positive cultures (60%). Eleven (55%) of the patients were females having a median age of 9.5 months. Multidrug-resistant (MDR) and extensively drug-resistant species (XDR) were isolated from eleven (47.8%) and ten (43.5%) culture sites respectively. Combination therapy of colistin or fosfomycin with carbapenem and tigecycline (triple regimen) was used in seven (35%) patients with severe sepsis. Microbiological clearance (sterility) was achieved in twelve (60%) children. Eight children (40%) died of MDR/XDR Raoultella associated sepsis.Conclusion: Highly resistant Raoultella species were associated with high mortality among reported cases, with a limited choice of antibiotics and combination therapy. The management of Raoultella species is required with a multi-specialty approach. Furthermore, strict antimicrobial stewardship measures are required to control an outbreak of MDR and XDR infections in Pakistan

Complementary feeding pattern and nutritional status of children

Objective: To determine the complementary feeding patterns and their association with malnutrition. Study design: Prospective observational study. Place and Duration of the Study: Outpatient clinics of Aga Khan University Hospital, Pakistan, from June to November 2019. Methodology: A total of 207 children from age six to twenty-four months, who presented in the outdoor clinics of the study place, were enrolled. Data were recorded in a predesigned data sheet adopted from the infant and young child feeding module. Chi-square test was applied post-stratification and a p-value of Results: Among a total of 207 children, 115 (55.6%) were males and 92 (44.4%) were females, with a mean age of 14.15 ± 5.6 months. Complementary feeding was started at an appropriate age in 124 (60%) children. Normal weight was seen in 133 (64.3%) children, while 73 (35.3%) were underweight. Stunting was presented in 44 (21.3%) children, whereas 163 (78.7%) children were of normal length. The most common reason for early initiation of complementary feeding was difficulty in continuing to breastfeed (n=50, 24.2%); the most common reason behind late complementary feeding was bottle feeding (n=45, 21.7%). Conclusion: Only sixty percent of mothers living in an urban setting started complementary feeding at an appropriate age. Various myths are counteracting complementary feeding practice

Machine learning based psychotic behaviors prediction from Facebook status updates

With the advent of technological advancements and the widespread Internet connectivity during the last couple of decades, social media platforms (such as Facebook, Twitter, and Instagram) have consumed a large proportion of time in our daily lives. People tend to stay alive on their social media with recent updates, as it has become the primary source of interaction within social circles. Although social media platforms offer several remarkable features but are simultaneously prone to various critical vulnerabilities. Recent studies have revealed a strong correlation between the usage of social media and associated mental health issues consequently leading to depression, anxiety, suicide commitment, and mental disorder, particularly in the young adults who have excessively spent time on social media which necessitates a thorough psychological analysis of all these platforms. This study aims to exploit machine learning techniques for the classification of psychotic issues based on Facebook status updates. In this paper, we start with depression detection in the first instance and then expand on analyzing six other psychotic issues (e.g., depression, anxiety, psychopathic deviate, hypochondria, unrealistic, and hypomania) commonly found in adults due to extreme use of social media networks. To classify the psychotic issues with the user's mental state, we have employed different Machine Learning (ML) classifiers i.e., Random Forest (RF), Support Vector Machine (SVM), Naïve Bayes (NB), and K-Nearest Neighbor (KNN). The used ML models are trained and tested by using different combinations of features selection techniques. To observe the most suitable classifiers for psychotic issue classification, a cost-benefit function (sometimes termed as ‘Suitability’) has been used which combines the accuracy of the model with its execution time. The experimental evidence argues that RF outperforms its competitor classifiers with the unigram feature set

Synthesis of PVP-capped trimetallic nanoparticles and their efficient catalytic degradation of organic dyes

The study proposes a simple and efficient way to synthesize a heterogeneous catalyst that can be used for the degradation of organic dyes. A simple and fast chemical process was employed to synthesize Au: Ni: Co tri-metal nanohybrid structures, which were used as a catalyst to eliminate toxic organic dye contamination from wastewater in textile industries. The catalyst's performance was tested by degrading individual dyes as well as mixtures of dyes such as methylene blue (MB), methyl orange (MO), methyl red (MR), and Rose Bengal (RB) at various time intervals. The experimental results show the catalytic high degradation efficiency of different dyes achieving 72-90% rates in 29 s. Moreover, the material displayed excellent recycling stability, maintaining its degradation efficiency over four consecutive runs without any degradation in performance. Overall, the findings of the study suggest that these materials possess efficient catalytic properties, opening avenues toward their use in clean energy alternatives, environmental remediation, and other biological applications