Biomechanical evaluation of a central collinear entry reconstruction nail for femoral neck fracture prophylaxis.

INTRODUCTION: Reconstruction nails are commonly used to treat proximal femur fractures, with cephalic screw placement for femoral neck "prophylaxis" becoming standard practice. These implants are traditionally introduced through piriformis fossa (PF) or greater trochanter (GT) entry portals. A third "central collinear" (CC) portal has been proposed that allows entry along the femoral anatomic axis and central placement of cephalic screws. The present study aimed to quantify and compare the CC portal femoral neck strength with the two traditional (PF and GT) entry portals. MATERIALS AND METHODS: Eighteen cadaveric femur specimens (nine matched pairs) were divided into three groups using a balanced incomplete block design to control for variations in age and sex: (1) GT, (2) CC, and (3) PF entry points. Specimens and implants were cut to a standard length and instrumented with straight or valgus bend nails of appropriate laterality and two cephalic screws. Specimens were mounted on a custom jig replicating load distribution along the mechanical axis. A 100 N compressive preload was applied to the femoral head, followed by loading to failure at a rate of 10 mm/s until fracture, indicated by 30 % drop in axial force. RESULTS: THE THREE ENTRY POINTS DID NOT DIFFER IN LOAD-TO-FAILURE: GT (6378.7 ± 1494.9 N), P (6912.4 ± 4924.1 N) and CC (7044.2 ± 2911.4 N) (P = 0.948) or maximum displacement, stiffness, and toughness. Most PF specimens failed at the basicervical neck, whereas most GT specimens failed at the subcapital neck; these differences were not significant. CC specimens failed evenly split between subcapital and basicervical. CONCLUSION: There were no significant difference in femoral neck load-to-failure after placement of a reconstruction nail through a CC entry portal when compared to both GT and PF entry. Clinically, this suggests the CC entry portal is a viable option when clinical considerations warrant its use.

Multi-Target In-Silico modeling strategies to discover novel angiotensin converting enzyme and neprilysin dual inhibitors.

Cardiovascular diseases, including heart failure, stroke, and hypertension, affect 608 million people worldwide and cause 32% of deaths. Combination therapy is required in 60% of patients, involving concurrent Renin-Angiotensin-Aldosterone-System (RAAS) and Neprilysin inhibition. This study introduces a novel multi-target in-silico modeling technique (mt-QSAR) to evaluate the inhibitory potential against Neprilysin and Angiotensin-converting enzymes. Using both linear (GA-LDA) and non-linear (RF) algorithms, mt-QSAR classification models were developed using 983 chemicals to predict inhibitory effects on Neprilysin and Angiotensin-converting enzymes. The Box-Jenkins method, feature selection method, and machine learning algorithms were employed to obtain the most predictive model with ~ 90% overall accuracy. Additionally, the study employed virtual screening of designed scaffolds (Chalcone and its analogues, 1,3-Thiazole, 1,3,4-Thiadiazole) applying developed mt-QSAR models and molecular docking. The identified virtual hits underwent successive filtration steps, incorporating assessments of drug-likeness, ADMET profiles, and synthetic accessibility tools. Finally, Molecular dynamic simulations were then used to identify and rank the most favourable compounds. The data acquired from this study may provide crucial direction for the identification of new multi-targeted cardiovascular inhibitors.