Finger pulp reconstruction with thenar flap: Aesthetic and functional outcome

Purpose: Fingertip injuries are common in industrial production activities as well as in domestic work. Loss of pulp hampers daily life activities. Functional and aesthetic aspects are important in fingertip reconstruction. The bone is usually exposed along with soft tissue loss. Therefore to reconstruct the pulp flap with adequate bulk is required. Methods: We reported a case series of 12 patients with the injury over the volar aspect of distal phalanx of the index or middle finger. In all cases, laterally based thenar flap was chosen. The flap donor site was closed primarily in most of cases, while 4 patients required skin graft. The flap was detached between 2-3 weeks. Functional assessment was done using static and dynamic 2-point discrimination and range of motion at each joint. The aesthetic outcome was assessed through questionnaire. The results were analyzed using the unpaired t-test (SPSS version 21). Results: Partial necrosis occurred in 2 cases while rest of flaps survived successfully. Static 2-point discrimination ranged from 6e10 mm, mean 8.6 mm; and dynamic 2-point discrimination ranged from 8-10 mm, mean 8.9 mm. The mean satisfaction score was (4.0 ± 0.55). Conclusion: Thenar flap is a good choice for reconstruction of the finger pulp as it provides the bulk with good functional and aesthetic outcome.     

Quantitative structure–activity relationship (QSAR) studies as strategic approach in drug discovery

Drug design is a process which is driven by technological breakthroughs implying advanced experimental and computational methods. Nowadays, the techniques or the drug design methods are of paramount importance for prediction of biological profile, identification of hits, generation of leads, and moreover to accelerate the optimization of leads into drug candidates. Quantitative structure–activity relationship (QSAR) has served as a valuable predictive tool in the design of pharmaceuticals and agrochemicals. From decades to recent research, QSAR methods have been applied in the development of relationship between properties of chemical substances and their biological activities to obtain a reliable statistical model for prediction of the activities of new chemical entities. Classical QSAR studies include ligands with their binding sites, inhibition constants, rate constants, and other biological end points, in addition molecular to properties such as lipophilicity, polarizability, electronic, and steric properties or with certain structural features. 3D-QSAR has emerged as a natural extension to the classical Hansch and Free–Wilson approaches, which exploit the three-dimensional properties of the ligands to predict their biological activities using robust chemometric techniques such as PLS, G/PLS, and ANN. This paper provides an overview of 1-6 dimension-based developed QSAR methods and their approaches. In particular, we present various dimensional QSAR approaches, such as comparative molecular field analysis (CoMFA), comparative molecular similarity analysis, Topomer CoMFA, self-organizing molecular field analysis, comparative molecule/pseudo receptor interaction analysis, comparative molecular active site analysis, and FLUFF-BALL, 4D-QSAR, and G-QSAR approaches.     

Optic nerve surface temperature during intradural anterior clinoidectomy: a comparison between high-speed diamond burr and ultrasonic bone curette

Ultrasonic bone curettes are increasingly used in cranial base surgery. The heat generated by these devices during anterior clinoidectomy has not been evaluated. The purpose of this study was to compare the optic nerve surface temperature during intradural anterior clinoidectomy using the drill and ultrasonic bone curette. Ten fresh cadaver heads were used. During intradural clinoidectomy and optic nerve unroofing with either a 2-mm diamond burr drill or ultrasonic bone curette, temperature was measured along the medial cisternal and proximal intracanalicular segments of the optic nerve. Additional experiments were performed to determine optimal ultrasonic bone curette settings for anterior clinoidectomy. At the lateral cisternal segment, peak and mean temperature were significantly higher with the ultrasonic bone curette (peak 38.8 vs 29.3 °C, p?=?0.03, mean 29.5 vs 22.6 °C, p?=?0.003). At the proximal intracanalicular segment, only peak temperature was significantly higher with the ultrasonic bone curette (peak 32.0 vs 23.5 °C, p?=?0.02, mean 26.9 vs 22.4 °C, p?=?0.07). Using standard company settings, room temperature irrigation fluid was heated by the oscillating tip to peak temperature 36.1 °C without drilling. In order to maintain emitted irrigation fluid at room temperature, optimal settings were power 70 %, cool irrigation (5 °C) at 40 mL/min. Using these settings, the ultrasonic bone curette generated optic nerve surface temperature measurements similar to the drill. Further work is necessary to translate these findings into the operating room.     

Naringin ameliorates gentamicin-induced nephrotoxicity and associated mitochondrial dysfunction,apoptosis and inflammation in rats: Possible mechanism of nephroprotection

Gentamicin-induced nephrotoxicity has been well documented, although its underlying mechanisms and preventive strategies remain to be investigated. The present study was designed to investigate the protective effect of naringin, a bioflavonoid, on gentamicin-induced nephrotoxicity and to elucidate the potential mechanism. Serum specific renal function parameters (blood urea nitrogen and creatinine) and histopathology of kidney tissues were evaluated to assess the gentamicin-induced nephrotoxicity. Renal oxidative stress (lipid peroxidation, protein carbonylation, enzymatic and non-enzymatic antioxidants), inflammatory (NF-kB [p65], TNF-α, IL-6 and MPO) and apoptotic (caspase 3, caspase 9, Bax, Bcl-2, p53 and DNA fragmentation) markers were also evaluated. Significant decrease in mitochondrial NADH dehydrogenase, succinate dehydrogenase, cytochrome c oxidase and mitochondrial redox activity indicated the gentamicin-induced mitochondrial dysfunction. Naringin (100 mg/kg) treatment along with gentamicin restored the mitochondrial function and increased the renal endogenous antioxidant status. Gentamicin induced increased renal inflammatory cytokines (TNF-α and IL-6), nuclear protein expression of NF-κB (p65) and NF-κB-DNA binding activity and myeloperoxidase (MPO) activity were significantly decreased upon naringin treatment. In addition, naringin treatment significantly decreased the amount of cleaved caspase 3, Bax, and p53 protein expression and increased the Bcl-2 protein expression. Naringin treatment also ameliorated the extent of histologic injury and reduced inflammatory infiltration in renal tubules. U-HPLS-MS data revealed that naringin co-administration along with gentamicin did not alter the renal uptake and/or accumulation of gentamicin in kidney tissues. These findings suggest that naringin treatment attenuates renal dysfunction and structural damage through the reduction of oxidative stress, mitochondrial dysfunction, inflammation and apoptosis in the kidney.     

A review on current advances in machine learning based diabetes prediction

Diabetes is a metabolic disorder comprising of high glucose level in blood over a prolonged period in the body as it is not capable of using it properly. The severe complications associated with diabetes include diabetic ketoacidosis, nonketotic hypersmolar coma, cardiovascular disease, stroke, chronic renal failure, retinal damage and foot ulcers. There is a huge increase in the number of patients with diabetes globally and it is considered a major health problem worldwide. Early diagnosis of diabetes is helpful for treatment and reduces the chance of severe complications associated with it. Machine learning algorithms (such as ANN, SVM, Naive Bayes, PLS-DA and deep learning) and data mining techniques are used for detecting interesting patterns for diagnosing and treatment of disease. Current computational methods for diabetes diagnosis have some limitations and are not tested on different datasets or peoples from different countries which limits the practical use of prediction methods. This paper is an effort to summarize the majority of the literature concerned with machine learning and data mining techniques applied for the prediction of diabetes and associated challenges. This report would be helpful for better prediction of disease and improve in understanding the pattern of diabetes. Consequently, the report would be helpful for treatment and reduce risk of other complications of diabetes.     

Development and validation of a questionnaire to assess socio-behavioural impact of COVID-19 on the general population

Background and aimThe aim of the study is to develop a valid and reliable tool to assess sociobehavioural changes due to COVID among the general population.MethodsThis mixed method study has two phases. Phase I for questionnaire development (literature review, focus group discussion, expert evaluation and pilot testing). Phase II for establishing construct validity via factor analysis and internal consistency via Cronbach’s ɑ by administering the questionnaire on 179 participants.ResultsA questionnaire comprising 33 questions and five domains was developed having Cronbach’s α of 0·82.ConclusionThe developed questionnaire is a concise, easy to administer and valid tool to assess socio-behavioural changes.