Zeba Haque

Biomedical Science research, by its very nature, generates colossal volumes of data ranging from genomics to medical imaging, that is both complex and diverse. It demands a lot of time and expertise to translate that data into meaningful interpretations to be applied on the bedside. AI algorithms on the other hand, possess the exceptional ability to examine this wealth of information, uncovering patterns and relationships. It has been claimed that it may elude even the most astute human minds¹ in some areas of social sciences. The interpretation of data in the field of Biomedical research, however, remains debatable². Nonetheless, it can accelerate the pace of scientific discovery, enabling researchers to identify novel therapeutic targets, understand disease mechanisms, and develop innovative treatments. Moreover, the resounding question that echoes across laboratories and research institutions globally is not whether AI can be employed in biomedical research, but instead, how extensively we can tap into its complete potential. The integration of AI into Biomedical Sciences is yet not free from its set of challenges. Privacy concerns and ethical considerations related to data usage must be diligently addressed. Additionally, robust validation and transparency in AI models are essential to ensure their reliability and safety³. continue...

Objective: To compare leptin levels in newly-diagnosed treatment-naive epileptic patients and healthy controls. Method: This case-control study was conducted from January 10 to September 15, 2022, at the Dow University of Health Sciences, Karachi, and comprised newly-diagnosed epileptic patients age 12-35years who had no comorbidity. The subjects were enrolled from the Neurology out-patient department of Civil Hospital, Karachi. Healthy individuals matched for age, gender and body mass index were also enrolled as controls. Blood samples were collected between 8am and 10am for the evaluation of serum leptin levels using enzyme-linked immunosorbent assay. Data was analysed using SPSS 26. Results: Of the 100 subjects, 64(64%) were males and 36(36%) were females. There were 50(50%) cases with mean age 19.34±5.65 years, and 50(50%) controls with mean age 19.76±5.67 (p=0.614). 100% of 50 individuals in control group did not have any family history of epilepsy,while 18% of cases (9) reported a positive family history. Mean leptin level in cases was 31.03±19.37 compared to 5.25±4.03 in the controls (pConclusion: Serum leptin levels were elevated in newly-diagnosed epileptic patients compared to healthy controls. Key Words: Epilepsy, Leptin, Leptin resistance.

Treating periodontitis with metronidazole (MET) as an adjunct to scaling root planing (SRP) is suggested to have inconsistent effects on insulin resistance (IR) in type 2 diabetes mellitus (T2DM). This paper will present the effects of MET, in addition to SRP, on the homeostatis model assessment of IR (HOMA-IR). A three-arm clinical trial was conducted and analyses were performed on T2DM participants with periodontitis (n = 74) who completed follow-up visits at 3 and 6 months after the intervention. The observed between-group and within-group mean changes in IR were found using ANOVA with repeated measures, followed by a post-hoc analysis, and a p-value of ≤0.05 was considered significant. Between-group analyses showed no difference in the HOMA-IR at 3 months, but at 6 months the difference was significant (p = 0.046). Within-group analyses showed that the HOMA-IR was significantly reduced in both test groups (p ≤ 0.05) over the period of time. Adjunct use of MET may result in a sudden short-term lowering of the HOMA-IR level within 3 months that may not be retained over 6 months when compared to the sustained lowering of the HOMA-IR levels in T2DM when intervened with SRP without MET.

Background: Treating periodontitis through non-surgical periodontal therapy (NSPT) may improve glycemic control in type-2 Diabetes Mellitus (T2DM) patients. However, the evidence to maintain this improvement beyond four months is insufficient. Hence, this trial was conducted to assess clinical efficacy of NSPT on glycemic control in T2DM patients. Methods: This three-arm randomized controlled trial recruited 150 known T2DM participants (35–65 years), suffering from moderate to severe periodontitis, having HbA1c level ≥ 6.5% at baseline. Participants were followed up at 3 and 6 months. Intervention for test group-1 included scaling and root planing (SRP) with metronidazole (MET) and oral hygiene instructions (OHI). Test group-2 was intervened with SRP + OHI and control group with OHI only. Stata v. 14 was used to observe inter and intragroup mean changes in glycemic [glycated hemoglobin (HbA1c), fasting blood glucose (FBG)] and periodontal variables [bleeding on probing (BOP), periodontal pocket depth (PPD), clinical attachment loss (CAL)] using ANOVA and RMANOVA. Proportion of change in outcome variable (HbA1c) was assessed between treatment groups using chi-square test. Change was considered significant at p-value ≤ 0.05. Results: A significant reduction was observed in BOP, PPD, CAL, HbA1c and FBG over time [p < 0.05]. Significant reductions were observed in same variables in both test groups in comparison to control arm [p < 0.05]. No change between the two test groups was observed [p > 0.05]. Conclusion: Scaling and root planing improves glycemic control of T2DM patients independently of the use of MET. Therefore, SRP after every 6 months may be suggested and included as a part of overall diabetes management for patients suffering from T2DM. Clinical trial registration NCT 03,343,366 [Date of Registration: 17/11/2017]

The original version of this article unfortunately contained a typo in the author name. The co-author name should be Ahsan Ehtesham instead it was published as Ahsan Ehtisham.