Determining human-coronavirus protein-protein interaction using machine intelligence.

The Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) virus spread the novel CoronaVirus -19 (nCoV-19) pandemic, resulting in millions of fatalities globally. Recent research demonstrated that the Protein-Protein Interaction (PPI) between SARS-CoV-2 and human proteins is accountable for viral pathogenesis. However, many of these PPIs are poorly understood and unexplored, necessitating a more in-depth investigation to find latent yet critical interactions. This article elucidates the host-viral PPI through Machine Learning (ML) lenses and validates the biological significance of the same using web-based tools. ML classifiers are designed based on comprehensive datasets with five sequence-based features of human proteins, namely Amino Acid Composition, Pseudo Amino Acid Composition, Conjoint Triad, Dipeptide Composition, and Normalized Auto Correlation. A majority voting rule-based ensemble method composed of the Random Forest Model (RFM), AdaBoost, and Bagging technique is proposed that delivers encouraging statistical performance compared to other models employed in this work. The proposed ensemble model predicted a total of 111 possible SARS-CoV-2 human target proteins with a high likelihood factor ≥70%, validated by utilizing Gene Ontology (GO) and KEGG pathway enrichment analysis. Consequently, this research can aid in a deeper understanding of the molecular mechanisms underlying viral pathogenesis and provide clues for developing more efficient anti-COVID medications.

Forecasting adversities of COVID-19 waves in India using intelligent computing.

The second wave of the COVID-19 pandemic outburst triggered enormously all over India. This ill-fated and fatal brawl affected millions of Indian citizens, with many active and infected Indians struggling to recover from this deadly disease to date, leading to a grief situation. The present situation warrants developing a robust and sound forecasting model to evaluate the adversities of the epidemic with reasonable accuracy to assist officials in curbing this hazard. Consequently, we employed Auto-ARIMA, Auto-ETS, Auto-MLP, Auto-ELM, AM, MLP and proposed ELM methods for assessing accumulative infected COVID-19 individuals by the end of July 2021. We made 90 days of advanced forecasting, i.e., up to 24 July 2021, for the number of cumulative infected COVID-19 cases of India using all seven methods in 15 days' intervals. We fine-tuned the hyper-parameters to enhance the prediction performance of these models and observed that the proposed ELM model offers satisfactory accuracy with MAPE of 5.01, and it rendered better accuracy than the other six models. To comprehend the dataset's nature, five features are extracted. The resulting feature values encouraged further investigation of the models for an updated dataset, where the proposed model provides encouraging results.

Morphometric study of the thoracic vertebral pedicle in an Indian population.

STUDY DESIGN: Morphometric study of the thoracic vertebral pedicular parameters and comparison with the previous studies in the literature. OBJECTIVES: To define pedicular dimensions and screw placement in the Indian population. SUMMARY OF THE BACKGROUND DATA: Pedicular morphometric characteristics vary in different population groups. Thoracic pedicular screw fixation is being used more frequently with the advent of better imaging methods. Because of the small size and close proximity to the neurovascular structures, thoracic pedicle fixation has little margin of safety. METHODS: T1-T12 vertebral pedicles were studied in 18 cadavers by direct, roentgenographic, and computerized tomographic scan methods. The following parameters were studied: transverse diameter, transverse angle, sagittal diameter, sagittal angle, chord length, interpedicular distance, pedicle entrance point, and pedicle cortical thickness (medial and lateral). RESULTS.: Transverse diameter was more than 6 mm at both ends of the thoracic spine (T1, T2, T11, and T12). Between T3-T9 levels, it was less than 5 mm at some levels. The transverse angle was widest at T1 (30 degrees) and was less than 5 degrees from T5 to T12. Pedicles were directed cephalad in the sagittal plane at all thoracic levels. Sagittal angle was less than 12 degrees at all thoracic levels. Chord length was largest at T11 (37.3 mm) and smallest at T1 and T2 (29.9 mm). Interpedicular distance was 29 mm at T12 and 21.3 mm at T1. Medial pedicular cortex was thicker than lateral cortex at all levels. CONCLUSIONS: These results suggest that even a 4-mm screw should be used carefully at the midthoracic level; 5-mm screw seems to be safe at upper and lower thoracic spine. Because of very small sagittal and transverse angle at mid and lower thoracic levels, the pedicular screw should be inserted along almost perpendicular line in these planes; 25-mm and 30-mm screw length appears to be safe at upper thoracic and lower thoracic levels, respectively. Pedicle entrance point lies along the midtrans-verse line at upper thoracic levels and along the upper border of transverse process at lower thoracic levels.

Morphometric study of the lumbar pedicle in the Indian population as related to pedicular screw fixation.

STUDY DESIGN: A morphometric study of lumbar vertebral pedicular parameters in cadavers and comparison with previous studies in the literature was conducted. OBJECTIVES: To suggest dimensions for pedicular implants in the Indian population, and to improve the pedicular screw placement technique. SUMMARY OF BACKGROUND DATA: Detailed knowledge of pedicle morphometry is critical for proper placement of a transpedicular screw. The size and shape of the vertebral pedicle vary between different races. Morphometric studies have been conducted in white and nonwhite populations (e.g., Chinese, Koreans). METHODS: The vertebral pedicles at L1-L5 were studied in 20 cadavers by direct roentgenographic and computerized tomographic scan methods. The following parameters were studied: transverse diameter, transverse angle, sagittal diameter, sagittal angle, chord length, interpedicular distance, medial and lateral cortical thickness. RESULTS: Transverse diameter was largest at L5 (16.19 mm) and smallest at L1 (7.05 mm). The transverse angle was largest at L5 (29 degrees) and smallest at L1 (9 degrees). The pedicles were directed cranially in the sagittal plane at all lumber levels except L5. The sagittal angle was largest at L5 (29 degrees) and smallest at L1 (9 degrees). Chord length was largest at L2 (47.5 mm) and smallest at L1 (46.01 mm). The values of linear measurements were smaller in females at all levels. CONCLUSIONS: On the basis of this limited study in a subset of the Indian population, it appears that the transverse diameter and pedicle entrance point differ from those in the white population. The results suggest that a 5-mm screw would be safer in the upper lumbar levels (L1, L2), and 6-mm screw in the lower lumbar levels (L3-L5). The pedicle entrance point migrates laterally for lower lumbar levels, especially at L5. The medial pedicle cortex can be safely sounded while the pedicle is probed.