The enhanced reliability of higher national institute of health stroke scale thresholds over the conventional 6-point scale.

INTRODUCTION: It is still uncertain if higher thresholds on National Institute of Health Stroke Scale (NIHSS) are better predictors of large infarctions than the conventional 6-point cutoff. METHODS: We used 6-point and higher NIHSS thresholds including 8, 9, and 10-point to predict relative infarct areas, expressed as percentage of the affected hemisphere on axial brain computed tomography images, beginning at 5% with 5% increments each time until reaching the 40% cutoff for large infarctions, or achieving 100% sensitivity. Results were compared using area under the receiver operating characteristic curves (AUROC). RESULTS: We enrolled 151 patients of acute ischemic stroke (Mean age: 62.88 years ± 12.71; Female: 48.34%). 77 patients (50.99%) exhibited left hemisphere strokes, while 74 (49%) had right hemisphere involvement. Sensitivity values of the 6-point for infarcts measuring 5%, 10%, 20%, 30%, and 40% were 62%, 64%, 77%, 82%, and 100%, respectively. At 40% infarct-size, 8-point achieved comparable results (52%, 55%, 69%, 76%, 100%), closely aligning with the 9-point (50%, 53%, 69%, 76%, 100%). The10-point was slightly trailing behind in sensitivity at 40% infarct-core (96%). Moreover, higher thresholds exhibited improved false-positive rates (FPR). At 40% infarct size, the FPRs of 6, 8, 9, and 10 points were 39%, 27%, 27%, and 21% respectively. Higher thresholds had augmented AUROC values (0.86, 0.86, 0.89) as compared to the 6-point (0.80). Logistic regression identified 14-point as definitive cutoff for large infarctions. CONCLUSION: Higher thresholds can better differentiate small and medium infarcts as true-negatives and substantially reduce false-positive referrals for mechanical thrombectomy.

Auscultation-Based Pulmonary Disease Detection through Parallel Transformation and Deep Learning.

Respiratory diseases are among the leading causes of death, with many individuals in a population frequently affected by various types of pulmonary disorders. Early diagnosis and patient monitoring (traditionally involving lung auscultation) are essential for the effective management of respiratory diseases. However, the interpretation of lung sounds is a subjective and labor-intensive process that demands considerable medical expertise, and there is a good chance of misclassification. To address this problem, we propose a hybrid deep learning technique that incorporates signal processing techniques. Parallel transformation is applied to adventitious respiratory sounds, transforming lung sound signals into two distinct time-frequency scalograms: the continuous wavelet transform and the mel spectrogram. Furthermore, parallel convolutional autoencoders are employed to extract features from scalograms, and the resulting latent space features are fused into a hybrid feature pool. Finally, leveraging a long short-term memory model, a feature from the latent space is used as input for classifying various types of respiratory diseases. Our work is evaluated using the ICBHI-2017 lung sound dataset. The experimental findings indicate that our proposed method achieves promising predictive performance, with average values for accuracy, sensitivity, specificity, and F1-score of 94.16%, 89.56%, 99.10%, and 89.56%, respectively, for eight-class respiratory diseases; 79.61%, 78.55%, 92.49%, and 78.67%, respectively, for four-class diseases; and 85.61%, 83.44%, 83.44%, and 84.21%, respectively, for binary-class (normal vs. abnormal) lung sounds.

A comprehensive computational study to explore promising natural bioactive compounds targeting glycosyltransferase MurG in Escherichia coli for potential drug development.

Peptidoglycan is a carbohydrate with a cross-linked structure that protects the cytoplasmic membrane of bacterial cells from damage. The mechanism of peptidoglycan biosynthesis involves the main synthesizing enzyme glycosyltransferase MurG, which is known as a potential target for antibiotic therapy. Many MurG inhibitors have been recognized as MurG targets, but high toxicity and drug-resistant Escherichia coli strains remain the most important problems for further development. In addition, the discovery of selective MurG inhibitors has been limited to the synthesis of peptidoglycan-mimicking compounds. The present study employed drug discovery, such as virtual screening using molecular docking, drug likeness ADMET proprieties predictions, and molecular dynamics (MD) simulation, to identify potential natural products (NPs) for Escherichia coli. We conducted a screening of 30,926 NPs from the NPASS database. Subsequently, 20 of these compounds successfully passed the potency, pharmacokinetic, ADMET screening assays, and their validation was further confirmed through molecular docking. The best three hits and the standard were chosen for further MD simulations up to 400 ns and energy calculations to investigate the stability of the NPs-MurG complexes. The analyses of MD simulations and total binding energies suggested the higher stability of NPC272174. The potential compounds can be further explored in vivo and in vitro for promising novel antibacterial drug discovery.

The outcomes and complications of percutaneous interventions in chronic total coronary occlusion.

BACKGROUND: The limited availability of complex coronary intervention facilities and qualified operators, due to the high cost associated with chronic total occlusion (CTO) percutaneous intervention (PCI) equipment and a shortage of necessary skills, has led to a scarcity of capable medical centers in Pakistan. This study seeks to examine the outcomes and potential complications associated with CTO PCI procedures conducted at the Cardiac Catheterization Laboratories of a prominent national institute in Pakistan, which handles a large volume of cases. RESULTS: Three hundred and six patients were included in the study in the study period of six months. The mean age was 59.49 (± 9.16) years: 256 (83.66%) were male and 50 (16.34%) were female. CTO was successfully re-vascularized in 237 (77.5%) with a complication rate of 13.7%. Two hundred and ninety-eight (97.39%) patients underwent an antegrade approach, while RCA was the most common target vessel (47.71%). Diabetes was the only significant associated risk factor with CTO PCI failure (30.43% vs. 30.43%, P-value = 0.015). CONCLUSION: We achieved an excellent procedural success rate with a low complication rate. CTO procedural failure is associated with a higher complication rate, and diabetes is among the risk factors that lead to higher procedural failure.

Design, synthesis and evaluation of novel norfloxacin analogs as potent anticancer and antioxidant agents.

Aim: To synthesize a novel series of norfloxacin analogs and to evaluate biological activity. Methodology: Novel norfloxacin analogs were synthesized and characterized by NMR and mass spectrometry. Antiproliferative and antioxidant properties were studied. Results: Compound 2f was the most potent against HeLa cell-line with 100% inhibition of cell viability IC50 = 3.1 ± 0.2 µM. All compounds exhibit moderate to excellent antioxidant properties. Docking study demonstrates higher binding affinity of compounds with respective anticancer (B-cell lymphoma-2) and (tyrosinase) antioxidant targets. In silico absorption, distribution, metabolism and excretion profile of compounds proves all synthesized compounds follow Lipinski's rule of drug likeness, non toxic and possess passive gastrointestinal absorption. Conclusion: The biological profile suggest that the synthesized norfloxacin analogs can be a novel scaffold for future anticancer drug development.

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Targeted treatment for biofilm-based infections using PEGylated tobramycin.

Chronic infections often involve biofilm-based bacteria, in which the biofilm results in significant resistance against antimicrobial agents and prevents eradication of the infection. The physicochemical barrier presented by the biofilm matrix is a major impediment to the delivery of many antibiotics. Previously, PEGylation has been shown to improve antibiotic penetration into biofilms in vitro. In these studies, PEGylating tobramycin was investigated both in vitro and in vivo. Two distinct PEGylated tobramycin molecules were synthesized (mPEG-SA-Tob and mPEG-AA-Tob). Then, in a P. aeruginosa biofilm in vitro model, we found that mPEG-SA-Tob can operate as a prodrug and showed 7 times more effectiveness than tobramycin (MIC80: 14 µM vs.100 µM). This improved biofilm eradication is attributable to the fact that mPEG-SA-Tob can aid tobramycin to penetrate through the biofilm and overcome the alginate-mediated antibiotic resistance. Finally, we used an in vivo biofilm-based chronic pulmonary infection rat model to confirm the therapeutic impact of mPEG-SA-Tob on biofilm-based chronic lung infection. mPEG-SA-Tob has a better therapeutic impact than tobramycin in that it cannot only stop P. aeruginosa from multiplying in the lungs but can also reduce inflammation caused by infections and prevent a recurrence infection. Overall, our findings show that PEGylated tobramycin is an effective treatment for biofilm-based chronic lung infections.