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  1. Fulltext Cubitus Valgus with Tardy Ulnar Nerve Palsy - Functional Outcome of Milch Osteotomy without Anterior Transposition of Ulnar Nerve
    Gupta RK, Khiyani R, Majumdar KP, Potalia R
    Malays Orthop J, 2020 Jul;14(2):120-125.
    PMID: 32983386 DOI: 10.5704/MOJ.2007.021
    Introduction: To assess the results of Milch osteotomy in terms of deformity correction and functional outcome in the absence of ulnar nerve transposition.

    Material and Methods: Nine patients with cubitus valgus deformity greater than 20° with tardy ulnar nerve palsy (TUNP) operated between 2012 and 2017 were evaluated. Correction by Milch osteotomy and fixation was done in each case, without osteosynthesis of the non-union lateral condyle humerus or transposition of the ulnar nerve. At one year post-operatively, carrying angle, elbow function (Mayo Elbow Performance Score) and ulnar nerve symptoms were assessed.

    Results: The mean carrying angle pre-operatively was 30.8° on the affected side which improved to a mean of 8.3° postoperatively with an average correction of 22.5°. The mean elbow flexion pre-operatively was 129.4° which improved to 133.3° post-operatively. The mean preoperative MEP score was 76.7 which improved to a mean of 92.2 post-operatively (p < 0.01). TUNP recovered completely in all the patients.

    Conclusion: Milch osteotomy is an effective procedure for cubitus valgus deformity correction and its associated tardy ulnar nerve palsy without a decrease in elbow ROM. Correction of even severe valgus deformities without concurrent anterior transposition of the ulnar nerve is likely to improve ulnar nerve symptoms.

  2. Fulltext Estimation of Andrographolides and Gradation of Andrographis paniculata Leaves Using Near Infrared Spectroscopy Together With Support Vector Machine
    Sing D, Banerjee S, Jana SN, Mallik R, Dastidar SG, Majumdar K, et al.
    Front Pharmacol, 2021;12:629833.
    PMID: 34025404 DOI: 10.3389/fphar.2021.629833
    Andrographis paniculata (Burm. F) Nees, has been widely used for upper respiratory tract and several other diseases and general immunity for a historically long time in countries like India, China, Thailand, Japan, and Malaysia. The vegetative productivity and quality with respect to pharmaceutical properties of Andrographis paniculata varies considerably across production, ecologies, and genotypes. Thus, a field deployable instrument, which can quickly assess the quality of the plant material with minimal processing, would be of great use to the medicinal plant industry by reducing waste, and quality grading and assurance. In this paper, the potential of near infrared reflectance spectroscopy (NIR) was to estimate the major group active molecules, the andrographolides in Andrographis paniculata, from dried leaf samples and leaf methanol extracts and grade the plant samples from different sources. The calibration model was developed first on the NIR spectra obtained from the methanol extracts of the samples as a proof of concept and then the raw ground samples were estimated for gradation. To grade the samples into three classes: good, medium and poor, a model based on a machine learning algorithm - support vector machine (SVM) on NIR spectra was built. The tenfold classification results of the model had an accuracy of 83% using standard normal variate (SNV) preprocessing.
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