Virtual Screening, Docking and DFT Study of PRMT5

Subathra S 조선대학교 기초과학연구원 2022 조선자연과학논문집 Vol.15 No.4

Structure Prediction of Gasdermin a Receptor by Homology Modelling

Subathra Selvam 조선대학교 기초과학연구원 2023 조선자연과학논문집 Vol.16 No.3

Machine learning Anti-inflammatory Peptides Role in Recent Drug Discovery

Subathra Selvam 조선대학교 기초과학연구원 2024 조선자연과학논문집 Vol.17 No.1

Several anti-inflammatory small molecules have been found in the process of the inflammatory response, and these small molecules have been used to treat some inflammatory and autoimmune diseases. Numerous tools for predicting anti-inflammatory peptides (AIPs) have emerged in recent years. However, conducting experimental validations in the lab is both resource-intensive and time-consuming. Current therapies for inflammatory and autoimmune disorders often involve nonspecific anti-inflammatory drugs and immunosuppressants, often with potential side effects. AIPs have been used in treating inflammatory illnesses like Alzheimer's disease and can limit the expression of inflammatory promoters. Recent advances in adverse incident predictions (AIPs) have been made, but it is crucial to acknowledge limitations and imperfections in existing methodologies.

Morphology of middle cerebral artery using computed tomography angiographic study in a tertiary care hospital

Urvi Sharma,Suman Verma,Subathra Adithan 대한해부학회 2023 Anatomy & Cell Biology Vol.56 No.3

Increased tortuosity of vessel is associated with high incidence of plaque formation leading to atherosclerosis. Surgical procedures are done after analyzing morphology of middle cerebral artery (MCA). However, literature describing MCA morphology using computed tomography angiography (CTA) is limited, so this study was planned to determine its incidence in Indian population. Datasets of CTA from 289 patients (180 males and 109 females), average age: 49.29±16.16 years (range: 11 to 85 years), from a tertiary care hospital were systematically reviewed for morphology of MCA. Cases involving aneurysms and infarcts were excluded. Four shapes of MCA were recognized: straight, U, inverted U, and S-shaped. MCA was straight in 44% (254/578), U-shaped in 37% (215/578), S shaped in 15% (89/578) and inverted U-shaped in 3% (20/578) cases. In males, MCA was straight in 46% (166/360), U-shaped in 37% (134/360), S-shaped in 16% (58/360) and inverted U-shaped in 4% (14/360) cases. In females, MCA was straight in 42% cases (92/218), U-shaped in 37% (81/218), S-shaped in 17% (36/218) and inverted U-shaped in 4% (9/218). On comparing shape with various age groups using chi square test, Ushaped (P≤0.001) and S-shaped (P=0.003) MCA were found to be statistically significant. The incidence of straight shape washigher in advanced age group (>60 years). Knowledge of MCA shape will be useful for clinicians and surgeons in successful endovascular recanalization. Also, this data would help surgeons during neurointerventional procedures.

Focalization of thrombosis and therapeutic perspectives: a memoir

S. Merlyn Keziah,C. Subathra Devi 경희대학교 융합한의과학연구소 2018 Oriental Pharmacy and Experimental Medicine Vol.18 No.4

The main aim of the review is to recapitulate the effects of thrombotic diseases, clotting disorders, and the methodology of prospecting a range of thrombolytics from various sources and thrombolytic therapies. Thrombolytic medications are administered to infringe dangerous clots inside blood vessels when there is deprivation in this haemostatic balance. Certain bioactive compounds present in herbs, plant leaves, roots and fruits exhibit thrombolytic activities. Serine proteases, metalloproteases and some cysteine proteases possess thrombolytic properties. These proteases are found in plants, humans, animals and microbes as well. Thrombolytics which are of clinical importance are discussed in this article along with its variants and biological sources exhibiting thrombolytic activity. Alternative therapies followed in recent days are also discussed, including future prospects of research on thrombolytics. Knowledge of thrombolytic biodiversity plays a decisive role in choosing safe, economic and effective thrombolytics for scale up and commercialization.

Sentinel Node Biopsy Examination for Breast Cancer in a Routine Laboratory Practice: Results of a Pilot Study

Khoo, Joon-Joon,Ng, Chen-Siew,Sabaratnam, Subathra,Arulanantham, Sarojah Asian Pacific Journal of Cancer Prevention 2016 Asian Pacific journal of cancer prevention Vol.17 No.3

Background: Examination of sentinel lymph node (SLN) biopsies provides accurate nodal staging for breast cancer and plays a key role in patient management. Procurement of SLNs and the methods used to process specimens are equally important. Increasing the level of detail in histopathological examination of SLNs increases detection of metastatic tumours but will also increase the burden of busy laboratories and thus may not be carried out routinely. Recommendation of a reasonable standard in SLN examination is required to ensure high sensitivity of results while maintaining a manageable practice workload. Materials and Methods: Twenty-four patients with clinically node-negative breast cancer were recruited. Combined radiotracer and blue dye methods were used for identification of SLNs. The nodes were thinly sliced and embedded. Serial sectioning and immunohistochemical (IHC) staining against AE1/AE3 were performed if initial H&E sections of the blocks were negative. Results: SLNs were successfully identified in all patients. Ten cases had nodal metastases with 7 detected in SLNs and 3 detected only in axillary nodes (false negative rate, FNR=30%). Some 5 out of 7 metastatic lesions in the SLNs (71.4%) were detected in initial sections of the thinly sliced tissue. Serial sectioning detected the remaining two cases with either micrometastases or isolated tumour cells (ITC). Conclusions: Thin slicing of tissue to 3-5mm thickness and serial sectioning improved the detection of micro and macro-metastases but the additional burden of serial sectioning gave low yield of micrometastases or ITC and may not be cost effective. IHC validation did not further increase sensitivity of detection. Therefore its use should only be limited to confirmation of suspicious lesions. False negative cases where SLNs were not involved could be due to skipped metastases to non-sentinel nodes or poor technique during procurement, resulting in missed detection of actual SLNs.

Distinguishing benign from malignant pelvic mass utilizing an algorithm with HE4, menopausal status, and ultrasound findings

Sarikapan Wilailak,Karen KL Chan,Chi-An Chen,남주현,Kazunori Ochiai,Tar-Choon Aw,Subathra Sabaratnam,Sudarshan Hebbar,Jaganathan Sickan,Beth A Schodin,Chuenkamon Charakorn,Walfrido W Sumpaico 대한부인종양학회 2015 Journal of Gynecologic Oncology Vol.26 No.1

Results: A total of 414 women with a pelvic mass were enrolled in the study, of which 328 had documented ultrasound findings. The risk prediction model that contained HE4, menopausal status, and ultrasound findings exhibited the best performance compared to models with CA-125 alone, or a combination of CA-125 and HE4. This model classified 77.2% of women with ovarian cancer as medium or high risk, and 86% of women with benign disease as very-low, low, or medium-low risk. This model exhibited better sensitivity than ROMA, but ROMA exhibited better specificity. Both models performed better than CA-125 alone. Objective: The purpose of this study was to develop a risk prediction score for distinguishing benign ovarian mass from malignant tumors using CA-125, human epididymis protein 4 (HE4), ultrasound findings, and menopausal status. The risk prediction score was compared to the risk of malignancy index and risk of ovarian malignancy algorithm (ROMA). Methods: This was a prospective, multicenter (n=6) study with patients from six Asian countries. Patients had a pelvic mass upon imaging and were scheduled to undergo surgery. Serum CA-125 and HE4 were measured on preoperative samples, and ultrasound findings were recorded. Regression analysis was performed and a risk prediction model was developed based on the significant factors. A bootstrap technique was applied to assess the validity of the HE4 model. Results: A total of 414 women with a pelvic mass were enrolled in the study, of which 328 had documented ultrasound findings. The risk prediction model that contained HE4, menopausal status, and ultrasound findings exhibited the best performance compared to models with CA-125 alone, or a combination of CA-125 and HE4. This model classified 77.2% of women with ovarian cancer as medium or high risk, and 86% of women with benign disease as very-low, low, or medium-low risk. This model exhibited better sensitivity than ROMA, but ROMA exhibited better specificity. Both models performed better than CA-125 alone. Conclusion: Combining ultrasound with HE4 can improve the sensitivity for detecting ovarian cancer compared to other algorithms.