A novel handheld robotic-assisted system for unicompartmental knee arthroplasty: surgical technique and early survivorship.

Technology, including robotics, has been developed for use in unicompartmental knee arthroplasty (UKA) to improve accuracy and precision of bone preparation, implant positioning, and soft tissue balance. The NAVIO™ System (Smith and Nephew, Pittsburgh, PA, United States) is a handheld robotic system that assists surgeons in planning implant positioning based on an individual patient\u27s anatomy and then preparing the bone surface to accurately achieve the plan. The surgical technique is presented herein. In addition, initial results are presented for 128 patients (mean age 64.7 years; 57.8% male) undergoing UKA with NAVIO. After a mean of follow-up period of 2.3 years, overall survivorship of the knee implant was 99.2% (95% confidence interval 94.6-99.9%). There was one revision encountered during the study, which was due to persistent soft tissue pain, without evidence of loosening, subsidence, malposition or infection. These initial results suggest a greater survivorship than achieved in the same follow-up time intervals in national registries and cohort studies, though further follow-up is needed to confirm whether this difference is maintained at longer durations

Motion‐Compensated Transform Coding

Interframe Hybrid Transform/dpcm Coders Encode Television Signals by Taking a Spatial Transform of a Block of Picture Elements in a Frame and Predictively Coding the Resulting Coefficients using the Corresponding Coefficients of the Spatial Block at the Same Location in the Previous Frame. These Coders Can Be Made More Efficient for Scenes Containing Objects in Translational Motion by First Estimating the Translational Displacement of Objects and Then using Coefficients of a Spatially Displaced Block in the Previous Frame for Prediction. This Paper Presents Simulation Results for Such Motion‐compensated Transform Coders using Two Algorithms for Estimating Displacements. the First Algorithm, Which is Developed in a Companion Paper, Recursively Estimates the Displacements from the Previously Transmitted Transform Coefficients, Thereby Eliminating the Need to Transmit the Displacement Estimates. the Second Algorithm, Due to Limb and Murphy, Estimates Displacements by Taking Ratios of Accumulated Frame Difference and Spatial Difference Signals in a Block. in This Scheme, the Displacement Estimates Are Transmitted to the Receiver. Computer Simulations on Two Typical Real‐life Sequences of Frames Show that Motion‐compensated Coefficient Prediction Results in Coder Bit Rates that Are 20 to 40 Percent Lower Than Conventional Interframe Transform Coders using Frame Difference of Coefficients. Comparisons of Bit Rates for Approximately the Same Picture Quality Show that the Two Methods of Displacement Estimation Are Quite Similar in Performance with a Slight Preference for the Scheme with Recursive Displacement Estimation. © 1979 the Bell System Technical Journa

Interframe Television Coding using Gain and Displacement Compensation

This Paper Presents Algorithms for Predicting Luminance Changes in Successive Television Frames. the Changes Can Result When Objects in a TV Scene Move or When Illumination Varies. by a Gradient Search Technique, Which Seeks to Minimize a Functional of the Interframe Prediction Error, We Estimate Two Parameters Associated with These Luminance Changes—displacement and Gain. using the Estimates of These Parameters, We Also Develop, for Interframe Coding, Adaptive Predictors and a Segmentor to Determine Which Pels Need to Be Transmitted. We Describe Several Coder Variations and Compare Them by Computer Simulations using Three Substantially Different Scene Sequences. for These Sequences, Gain Compensation with Improved Segmentation Reduced the Bit Rate of a Conditional Replenishment Encoder by 50.7, 11.1, and 39.3 Percent. Displacement Compensation Reduced the Bit Rate by 61.0, 24.8, and 14.5 Percent. Combined Gain and Displacement Compensation Reduced the Bit Rate by 63.4, 32.2, and 44.6 Percent. © 1980 the Bell System Technical Journa

Model-Based Deconvolution of Cell Cycle Time-Series Data Reveals Gene Expression Details at High Resolution

In both prokaryotic and eukaryotic cells, gene expression is regulated across the cell cycle to ensure “just-in-time” assembly of select cellular structures and molecular machines. However, present in all time-series gene expression measurements is variability that arises from both systematic error in the cell synchrony process and variance in the timing of cell division at the level of the single cell. Thus, gene or protein expression data collected from a population of synchronized cells is an inaccurate measure of what occurs in the average single-cell across a cell cycle. Here, we present a general computational method to extract “single-cell”-like information from population-level time-series expression data. This method removes the effects of 1) variance in growth rate and 2) variance in the physiological and developmental state of the cell. Moreover, this method represents an advance in the deconvolution of molecular expression data in its flexibility, minimal assumptions, and the use of a cross-validation analysis to determine the appropriate level of regularization. Applying our deconvolution algorithm to cell cycle gene expression data from the dimorphic bacterium Caulobacter crescentus, we recovered critical features of cell cycle regulation in essential genes, including ctrA and ftsZ, that were obscured in population-based measurements. In doing so, we highlight the problem with using population data alone to decipher cellular regulatory mechanisms and demonstrate how our deconvolution algorithm can be applied to produce a more realistic picture of temporal regulation in a cell