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Retinopathy of prematurity (ROP) is a treatable cause of blindness in neonates. In Pakistan, ROP is often not recognized early because screening and treatment programs are not yet in place in most neonatal units, even in tertiary care hospitals. It is hoped that this report will help inform medical professionals of the magnitude of the problem and help to design appropriate management strategies. The aim was to determine the frequency of ROP in premature and very low birth weight (BW) neonates (BW<1500 g and gestational age (GA) <32 weeks). Cross-sectional study. Neonatal intensive care unit (NICU) of a tertiary care hospital in Karachi, Pakistan. From June 2009 to May 2010. Neonates with a Birth weight (BW) <1500 g and Gestational Age (GA) <32 weeks who were admitted to the NICU and received an eye examination, or were referred for a ROP eye examination as an outpatient, were included in the study. GA was estimated from intrauterine ultrasound findings. Neonates with major congenital malformations, syndromes or congenital cataracts or tumors of the eyes, and those that died before the eye examination or did not attend the out patients department for an eye examination, were excluded. The neonatal eye examination was performed by a trained ophthalmologist at 4 or 6 weeks of age. Out of 86 neonates, ROP was identified in nine neonates (10.5%) at the first eye examination. ROP was significantly associated with BW (P = 0.037), GA (P = 0.033), and chronological age (P<0.001). we identified ROP in 10.5% of neonates at first eye examination. Significant associations between ROP and a GA<32 weeks and a BW<1500 g were also observed.we also stress that serial follow-up of neonates at risk for ROP is important when making a final diagnosis.

Background Tetanus in newborns, is an under-reported public health problem and a major cause of mortality in developing countries. This study aimed to determine the predictors and outcome of tetanus in newborn infants in the slums of Bin-Qasim town, Karachi, Pakistan. Methods We conducted a case–control study at primary health care centers of slums of Bin-Qasim town, area located adjacent to Bin Qasim seaport in Karachi, from January 2003 to December 2013. Cases were infants aged ≤30 days with tetanus, as defined by the World Health Organization. Controls were newborn infants aged ≤30 days without Tetanus, who were referred for a checkup or minor illnesses. The case to control ratio was 1:2. Results We analyzed 26 cases and 52 controls. The case fatality was 70.8%. We identified four independent predictors of Tetanus in newborns: maternal education (only religious education with no formal education OR 51.95; 95% CI 3.69–731), maternal non-vaccination (OR 24.55; 95% CI 1.01–131.77), lack of a skilled birth attendant (OR 44.00; 95% CI 2.30–840.99), and delivery at home (OR 11.54; 95% CI 1.01–131.77). Conclusions We identified several potentially modifiable socio-demographic risk factors for Tetanus in newborns, including maternal education and immunization status, birth site, and lack of a skilled birth attendant. Prioritization of these risk factors could be useful for planning preventive and cost-effective measures.

Network security has developed as a critical research subject as a result of the Rapid advancements in the development of Internet and communication technologies over the previous decades. The expansion of networks and data has caused cyber-attacks on the systems, making it difficult for network security to detect breaches effectively. Current Intrusion Detection Systems (IDS) have several flaws, including their inability to prevent attacks on their own, the requirement for a professional engineer to administer them, and the occurrence of false alerts. As a result, a plethora of new attacks are being created, making it harder for network security to properly detect breaches. Despite the best efforts, IDS continues to struggle with increasing detection accuracy while lowering false alarm rates and detecting new intrusions. Therefore, network intrusion detection enhancement by preprocessing and generation of highly reliable algorithms is the main focus nowadays. Machine learning (ML) based IDS systems have recently been implemented as viable solutions for quickly detecting intrusions across the network. In this study, we use a combined data analysis technique with four Robust Machine learning ensemble algorithms, including the Voting Classifier, Bagging Classifier, Gradient Boosting Classifier, and Random Forest-based Bagging algorithm along with the proposed Robust genetic ensemble classifier. For each algorithm, a model is created and tested using a Network Dataset. To assess the performance of both algorithms in terms of their ability to anticipate the anomaly occurrence, graphs of performance rates have been evaluated. The suggested algorithm outperformed other methods as it shows the lowest values of mean square error (MSE) and mean absolute error (MAE). The experiments were conducted on the Network traffic dataset available on Kaggle, on the Python platform, which has limited samples. The proposed method can be applied in the future with more machine learning ensemble classifiers and deep learning techniques.

Ciprofol, a newer entrant with similarities to propofol, has shown promise with a potentially improved safety profile, making it an attractive alternative for induction of general anesthesia. This meta-analysis aimed to assess the safety and efficacy of ciprofol compared with propofol during general anesthesia induction. A comprehensive literature search was conducted using PubMed, Clinical Trial.gov, and Cochrane Library databases from inception to July 2023 to identify relevant studies. All statistical analyses were conducted using R statistical software version 4.1.2. Thirteen Randomized Controlled Trials (RCTs) encompassing a total of 1998 participants, were included in our analysis. The pooled analysis indicated that Ciprofol was associated with a notably lower incidence of pain upon injection [RR: 0.15; 95% CI: 0.10 to 0.23; I^2 = 43%, p < 0.0000001] and was non-inferior to propofol in terms of anesthesia success rate [RR: 1.00; 95% CI: 0.99 to 1.01; I^2 = 0%; p = 0.43]. In terms of safety, the incidence of hypotension was significantly lower in the ciprofol group [RR:0.82; 95% CI:0.68 to 0.98; I^2 = 48%; p = 0.03]. However, no statistically significant differences were found for postoperative hypertension, bradycardia, or tachycardia. In conclusion, Ciprofol is not inferior to Propofol in terms of its effectiveness in general anesthesia. Ciprofol emerges as a valuable alternative sedative with fewer side effects, especially reduced injection pain, when compared to Propofol. Propofol, frequently utilized as an anesthetic, provides swift onset and quick recovery. However, it has drawbacks such as a narrow effective dosage range and a high occurrence of adverse effects, particularly pain upon injection. Ciprofol, a more recent drug with propofol-like properties, has demonstrated promise and may have an improved safety profile, making it a compelling alternative for inducing general anesthesia. This meta-analysis compared the safety and effectiveness of Ciprofol with Propofol for general anesthesia induction in a range of medical procedures, encompassing thirteen Randomized Controlled Trials (RCTs) and 1998 individuals. The pooled analysis indicated that Ciprofol was associated with a notably lower incidence of pain upon injection [RR: 0.15; 95% CI: 0.10 to 0.23; I^2 = 43%, p < 0.0000001] and was non-inferior to propofol in terms of anesthesia success rate [RR: 1.00; 95% CI: 0.99 to 1.01; I^2 = 0%; p = 0.43]. In terms of safety, the incidence of hypotension was significantly lower in the ciprofol group [RR:0.82; 95% CI:0.68 to 0.98; I^2 = 48%; p = 0.03]. However, no statistically significant differences were found for hypertension, bradycardia, or tachycardia. In conclusion, ciprofol is equally effective at inducing and maintaining general anesthesia as propofol. When compared to propofol, ciprofol is a better alternative sedative for operations including fiberoptic bronchoscopy, gynecological procedures, gastrointestinal endoscopic procedures, and elective surgeries because it has less adverse effects, most notably less painful injections. •Our meta-analysis found that Ciprofol was associated with a significantly lower incidence of injection-related pain compared to Propofol.•Ciprofol also demonstrated a lower risk of hypotension during general anesthesia induction when compared to Propofol, indicating improved safety.•However, there were no statistically significant differences between Ciprofol and Propofol in terms of hypertension, bradycardia, or tachycardia events during induction, suggesting a comparable cardiovascular safety profile.

The sixth-generation (6G) wireless communication network is expected to integrate the terrestrial, aerial, and maritime communications into a robust network which would be more reliable, fast, and can support a massive number of devices with ultra-low latency requirements. The researchers around the globe are proposing cutting edge technologies such as artificial intelligence (AI)/machine learning (ML), quantum communication/quantum machine learning (QML), blockchain, tera-Hertz and millimeter waves communication, tactile Internet, non-orthogonal multiple access (NOMA), small cells communication, fog/edge computing, etc., as the key technologies in the realization of beyond 5G (B5G) and 6G communications. In this article, we provide a detailed overview of the 6G network dimensions with air interface and associated potential technologies. More specifically, we highlight the use cases and applications of the proposed 6G networks in various dimensions. Furthermore, we also discuss the key performance indicators (KPI) for the B5G/6G network, challenges, and future research opportunities in this domain.

Plants are the primary source of food for world’s population. Diseases in plants can cause yield loss, which can be mitigated by continual monitoring. Monitoring plant diseases manually is difficult and prone to errors. Using computer vision and artificial intelligence (AI) for the early identification of plant illnesses can prevent the negative consequences of diseases at the very beginning and overcome the limitations of continuous manual monitoring. The research focuses on the development of an automatic system capable of performing the segmentation of leaf lesions and the detection of disease without requiring human intervention. To get lesion region segmentation, we propose a context-aware 3D Convolutional Neural Network (CNN) model based on CANet architecture that considers the ambiguity of plant lesion placement in the plant leaf image subregions. A Deep CNN is employed to recognize the subtype of leaf lesion using the segmented lesion area. Finally, the plant’s survival is predicted using a hybrid method combining CNN and Linear Regression. To evaluate the efficacy and effectiveness of our proposed plant disease detection scheme and survival prediction, we utilized the Plant Village Benchmark Dataset, which is composed of several photos of plant leaves affected by a certain disease. Using the DICE and IoU matrices, the segmentation model performance for plant leaf lesion segmentation is evaluated. The proposed lesion segmentation model achieved an average accuracy of 92% with an IoU of 90%. In comparison, the lesion subtype recognition model achieves accuracies of 91.11%, 93.01 and 99.04 for pepper, potato and tomato plants. The higher accuracy of the proposed model indicates that it can be utilized for real-time disease detection in unmanned aerial vehicles and offline to offer crop health updates and reduce the risk of low yield.

The naturopathic treatment of obesity is a matter of keen interest to develop efficient natural pharmacological routes for disease management with low or negligible toxicity and side effects. For this purpose, optimized ultrasonicated hydroethanolic extracts of Taraxacum officinale were evaluated for antiobesity attributes. The 2,2-diphenyl-1-picrylhydrazyl method was adopted to evaluate antioxidant potential. Porcine pancreatic lipase inhibitory assay was conducted to assess the in vitro antiobesity property. Ultra-high performance chromatography equipped with a mass spectrometer was utilized to profile the secondary metabolites in the most potent extract. The 60% ethanolic extract exhibited highest extract yield (25.05 ± 0.07%), total phenolic contents (123.42 ± 0.007 mg GAE/g DE), total flavonoid contents (55.81 ± 0.004 RE/g DE), DPPH-radical-scavenging activity (IC50 = 81.05 ± 0.96 µg/mL) and pancreatic lipase inhibitory properties (IC50 = 146.49 ± 4.24 µg/mL). The targeted metabolite fingerprinting highlighted the presence of high-value secondary metabolites. Molecular-binding energies computed by docking tool revealed the possible contribution towards pancreatic lipase inhibitory properties of secondary metabolites including myricetin, isomangiferin, icariside B4, kaempferol and luteolin derivatives when compared to the standard drug orlistat. In vivo investigations revealed a positive impact on the lipid profile and obesity biomarkers of obese mice. The study presents Taraxacum officinale as a potent source of functional bioactive ingredients to impart new insights into the existing pool of knowledge of naturopathic approaches towards obesity management.

Sharpless asymmetric dihydroxylation is an important reaction in the enantioselective synthesis of chiral vicinal diols that involves the treatment of alkene with osmium tetroxide along with optically active quinine ligand. Sharpless introduced this methodology after considering the importance of enantioselectivity in the total synthesis of medicinally important compounds. Vicinal diols, produced as a result of this reaction, act as intermediates in the synthesis of different naturally occurring compounds. Hence, Sharpless asymmetric dihydroxylation plays an important role in synthetic organic chemistry due to its undeniable contribution to the synthesis of biologically active organic compounds. This review emphasizes the significance of Sharpless asymmetric dihydroxylation in the total synthesis of various natural products, published since 2020.

Soil salinity is one of the primary problem for agricultural crops which causes a great loss in crop production in Pakistan and worldwide. Various approaches have been implemented to overcome salinity problem. Assembly of crops for the enhancement of salt tolerance is a good strategy to achieve cost-effective yields. Cucumber is considered as one of the leading vegetable crop around the world for the nourishment of human being as source of nutrients, minerals, and vitamins. Screening of 12 cucumber genotypes using some physiological indices, that is, seedling germination stress tolerance index, plant height stress tolerance index, root length stress tolerance index, shoot and root dry weight stress tolerance index, and shoot and root fresh weight stress tolerance index were performed for the identification of salt tolerance. Using the above characteristics genotypes, Valley and HC-999 were categorized as tolerant, Safaa and Debra as medium tolerant, while Thamin-II identified as medium sensitive and NSC-CM1 and Akbar are classified as sensitive genotypes of cucumber. According to the current study findings, the screened cucumber genotypes for salinity tolerance can also be suggested to farmers for the improved production and yield of crop at saline soil.

Citrus canker (CC), caused by one of the most destructive subfamilies of the bacterial phytopathogen Xanthomonas citri subsp. Citri (Xcc), poses a serious threat to the significantly important citrus fruit crop grown worldwide. This has been the subject of ongoing epidemiological and disease management research. Currently, five different forms have been identified of CC, in which Canker A (Xanthomonas citri subsp. citri) being the most harmful and infecting the majority of citrus cultivars. Severe infection symptoms include leaf loss, premature fruit drop, dieback, severe fruit blemishing or discoloration, and a decrease in fruit quality. The infection spreads rapidly through wind, rain splash, and warm and humid climates. The study of the chromosomal and plasmid DNA of bacterium has revealed the evolutionary pattern among the pathovars, and research on the Xcc genome has advanced our understanding of how the bacteria specifically recognize and infect plants, spread within the host, and propagates itself. Quarantine or exclusion programs, which prohibit the introduction of infected citrus plant material into existing stock, are still in use. Other measures include eliminating sources of inoculum, using resistant hosts, applying copper spray for protection, and implementing windbreak systems. The main focus of this study is to highlight the most recent developments in the fields of Xcc pathogenesis, epidemiology, symptoms, detection and identification, host range, spread, susceptibility, and management. Additionally, it presents an analysis of the economic impact of this disease on the citrus industry and suggests strategies to reduce its spread, including the need for international collaboration and research to reduce the impact of this disease on the global citrus industry.