A two-phase approach to re-calibrating expensive computer simulation for sex-specific colorectal neoplasia development modeling.

BACKGROUND: Medical evidence from more recent observational studies may significantly alter our understanding of disease incidence and progression, and would require recalibration of existing computational and predictive disease models. However, it is often challenging to perform recalibration when there are a large number of model parameters to be estimated. Moreover, comparing the fitting performances of candidate parameter designs can be difficult due to significant variation in simulated outcomes under limited computational budget and long runtime, even for one simulation replication. METHODS: We developed a two-phase recalibration procedure. As a proof-of-the-concept study, we verified the procedure in the context of sex-specific colorectal neoplasia development. We considered two individual-based state-transition stochastic simulation models, estimating model parameters that govern colorectal adenoma occurrence and its growth through three preclinical states: non-advanced precancerous polyp, advanced precancerous polyp, and cancerous polyp. For the calibration, we used a weighted-sum-squared error between three prevalence values reported in the literature and the corresponding simulation outcomes. In phase 1 of the calibration procedure, we first extracted the baseline parameter design from relevant studies on the same model. We then performed sampling-based searches within a proper range around the baseline design to identify the initial set of good candidate designs. In phase 2, we performed local search (e.g., the Nelder-Mead algorithm), starting from the candidate designs identified at the end of phase 1. Further, we investigated the efficiency of exploring dimensions of the parameter space sequentially based on our prior knowledge of the system dynamics. RESULTS: The efficiency of our two-phase re-calibration procedure was first investigated with CMOST, a relatively inexpensive computational model. It was then further verified with the V/NCS model, which is much more expensive. Overall, our two-phase procedure showed a better goodness-of-fit than the straightforward employment of the Nelder-Mead algorithm, when only a limited number of simulation replications were allowed. In addition, in phase 2, performing local search along parameter space dimensions sequentially was more efficient than performing the search over all dimensions concurrently. CONCLUSION: The proposed two-phase re-calibration procedure is efficient at estimating parameters of computationally expensive stochastic dynamic disease models.

Exploring the information transmission properties of noise-induced dynamics: application to glioma differentiation.

BACKGROUND: Cells operate in an uncertain environment, where critical cell decisions must be enacted in the presence of biochemical noise. Information theory can measure the extent to which such noise perturbs normal cellular function, in which cells must perceive environmental cues and relay signals accurately to make timely and informed decisions. Using multivariate response data can greatly improve estimates of the latent information content underlying important cell fates, like differentiation. RESULTS: We undertake an information theoretic analysis of two stochastic models concerning glioma differentiation therapy, an alternative cancer treatment modality whose underlying intracellular mechanisms remain poorly understood. Discernible changes in response dynamics, as captured by summary measures, were observed at low noise levels. Mitigating certain feedback mechanisms present in the signaling network improved information transmission overall, as did targeted subsampling and clustering of response dynamics. CONCLUSION: Computing the channel capacity of noisy signaling pathways present great probative value in uncovering the prevalent trends in noise-induced dynamics. Areas of high dynamical variation can provide concise snapshots of informative system behavior that may otherwise be overlooked. Through this approach, we can examine the delicate interplay between noise and information, from signal to response, through the observed behavior of relevant system components.

Plyometric-based Training for Isokinetic Knee Strength and Jump Performance in Cricket Fast Bowlers.

Competitive cricket demands a high level of performance from fast bowlers. Ground reaction forces during the landing phase pose a risk for lower limb and lumbar spine injury. Good dynamic knee strength allows the knee to flex to absorb these forces and extend prior to ball release for maximum efficiency. Plyometric training has been shown to improve dynamic strength. There is a lack of literature on this subject for cricket. This study evaluated the effect of a combined plyometric and strength training program on isokinetic knee strength of fast bowlers. Forty-two professional fast bowlers were randomly assigned to a training group (n=21) and a control group (n=21). Both groups underwent isokinetic knee strength and vertical and standing broad-jump testing. Quadriceps and hamstring concentric and eccentric peak torques, bilateral strength asymmetries (BSAs), and dynamic control ratios (DCRs) were evaluated by isokinetic testing. The study group underwent 12 weeks of plyometric training, whereas the control group continued with their own training methods. The study group showed a significant improvement (p<0.05) in jump performance and eccentric strength. There was a reduction in the proportion of bowlers with poor BSA and DCR. Improving dynamic knee strength through plyometric training reduces injury risk and improves performance in cricket fast bowlers.

Understanding and Managing Metabolic Deficiencies Post Bariatric and Esophagectomy Surgeries: A Narrative Review of the Literature.

Gastrectomy and esophagectomy are the most performed surgeries in the treatment of both esophageal and gastric cancers. The type of esophagectomy depends on the type of malignancy, site of the tumor, criteria of resection, and field of resection. The three standard approaches to esophagectomy are the transhiatal approach, the left thoracoabdominal approach, and a three-stage procedure. The transhiatal approach involves abdominal and cervical incisions, while the left thoracoabdominal approach is a one-stage procedure that utilizes a single incision exposing the dissection field. The Ivor Lewis and McKeown esophagectomies are two-stage and three-stage surgeries that include laparotomy with right thoracotomy. Malabsorption often emerges as a significant postoperative complication following esophagectomy and gastrectomy surgeries. Malnutrition linked with these cancers has detrimental effects, including heightened rates of postoperative complications, elevated infection risks, delayed wound healing, reduced tolerance to treatment, diminished quality of life, and heightened mortality rates. Our narrative review summarizes and sheds light on solutions to treat malabsorption disorders and malnutrition after gastric bypass surgery. These solutions include methods such as adjustments, supplements, and treatment. Although more research is needed to confirm their effectiveness, these methods indicate potential for lowering the impact on patients' diets. By considering the beneficial implications of these effects and considering solutions, we aim to improve the management of these adverse effects, ultimately improving the overall health and postoperative outcomes of patients.

Lumbar Spine Injury in Indian Fast Bowlers: 3D Biomechanical Analysis and Prevention Strategies.

Background: Lumbar spine injuries are among the most common overuse injuries in a fast bowler. Among various causative factors, bowling action technique is a crucial one. Three-dimensional motion analysis has been accepted as a gold standard tool to identify incorrect techniques. Previous studies have identified key biomechanical variables associated with lumbar injury risk in fast bowlers. Despite the large popularity of the sport, there is limited information available on the subject in Indian fast bowlers. This study aims to analyse the lumbar spine injury risk in Indian fast bowlers with respect to key biomechanical variables, using 3D motion analysis. Methods: Forty-seven male first class fast bowlers underwent 3D motion analysis in an indoor biomechanics laboratory. Motion capture was done with 3D cameras and 2D video cameras, using a standard marker set. Data processing and analysis was done using proprietary software. Biomechanical variables associated with lumbar spine injury risk including lateral trunk flexion (LTF) and knee angle at front foot contact (KA at FFC) were measured, and peak vertical ground reaction forces (pVGRF) were simultaneously recorded using force plates. Descriptive analysis of the data was done. Results: 26% of bowlers had a high LTF, 29% had low KA at FFC and 43% had high pVGRF. Thus, a large proportion of bowlers in this study were at risk of lumbar spine injury with respect to the assessed variables. Conclusion: This highlights the role of 3D motion analysis in early identification of injurious techniques, which can be modified by coaching and training interventions to prevent injuries. This study thus has implications on coaching and training of fast bowlers in India.

Open, Laparoscopic, and Robotic Approaches to Treat Colorectal Cancer: A Comprehensive Review of Literature.

Surgery is usually required to treat colorectal cancer (CRC). Medical technology has advanced, providing various approaches to tackle this disease. Different surgeries are available, such as laparoscopic surgery, single-incision laparoscopic surgery, natural orifice transluminal endoscopic surgery, and robotic surgery. Laparoscopic surgery has several benefits including reduced blood loss and shorter recovery time. It can also improve lung function and minimize complications. However, it requires more time to perform and has a higher risk of complications during the procedure. Robotic surgery provides a three-dimensional view of the surgical area allowing for greater precision in rectal surgeries and access to difficult-to-reach pelvic regions. This method utilizes robotics technology which reduces surgical time and speeds up recovery for patients. There are various surgical options available for treating CRC; however, laparoscopic surgery and robotic surgery offer unique advantages despite their own drawbacks. As technology continues to evolve, medical techniques will continue improving existing methods while providing new options resulting in better outcomes for patients. Compared to laparoscopy, robotic surgery has a lower rate of operative conversions and a shorter learning curve. However, it also has some drawbacks, such as a longer docking time, lack of tactile sensation, and higher cost. Therefore, the choice of surgical method should depend on patient characteristics, surgeon preference and expertise, and available resources. Currently, specialized centers offer robotic surgeries which are more expensive and take longer compared to open and laparoscopic approaches. Nonetheless, they are considered safe and feasible when compared to traditional surgery. Short-term outcomes for robotic surgeries are better, while long-term postoperative complication rates remain similar. However, there is a need for additional well-defined randomized control trials conducted across multiple centers to validate the use of robotic surgery over open and laparoscopic approaches. Improving patient care and outcomes is the objective of this comprehensive literature overview on surgical approaches for CRC.

Design and manufacturing of roller bearing polymeric cages and development of a theoretical model for predicting the roller push-out force.

In the present work, polymeric cages with 18 different pocket geometries are developed to investigate the effects of geometrical parameters and material properties on the amount of roller push-out force. An experimental setup including a specialized injection molding tool is designed and fabricated and three sets of polymeric cages are manufactured using the selected materials (PA46, PA66, PPA). Force measurements are carried out five times on each pocket and three cages for each material are tested. Considering three different materials, a total of 810 force measurements are performed. A theoretical model is developed to predict the roller push-out forces in polymeric cages with different materials and pocket geometries. The model is developed by estimating the deformed region of the cage as a cantilever beam with a parabolic profile. An empirical coefficient is reposed in the model to compensate for the assumptions applied to the model. Experimental results showed that a fixed coefficient gives accurate results for all the geometries and materials, which confirms the validity of the approach adopted in this paper for modeling such problems. Considering the geometrical and material tolerances, force limits predicted by the model cover all the forces measured for a specific pocket with excellent accuracy and consistency.

Concentric shell gradient index metamaterials for focusing ultrasound in bulk media.

Focusing of ultrasound waves is criticalto a number ofclinical andindustrial applications including biomedical and underwater imaging,nondestructive evaluation and material processing. This paper discusses the use of a novel'add-on' gradient refractive index (GRIN) metamaterial structure made ofconcentric shells,to focus ultrasonic waves generated by conventional transducers. Analysis based on the Huygen's principle and numerical simulations is used to design the geometric and material properties of the proposed structure, whose working is demonstrated through experiments. Varying the shell material or thickness is shown to offer an elegant and straightforward way to tailor the focal spot inside the target material. The concentric-shell GRIN lens proposed here has a simple design, and has a potential to be used in dynamic focusing without advanced lenses or electronic steering.

Aerial Swarm Defense by StringNet Herding: Theory and Experiments.

This paper studies a defense approach against one or more swarms of adversarial agents. In our earlier work, we employed a closed formation ("StringNet") of defending agents (defenders) around a swarm of adversarial agents (attackers) to confine their motion within given bounds, and guide them to a safe area. The adversarial agents were assumed to remain close enough to each other, i.e., within a prescribed connectivity region. To handle situations when the attackers no longer stay within such a connectivity region, but rather split into smaller swarms (clusters) to maximize the chance or impact of attack, this paper proposes an approach to learn the attacking sub-swarms and reassign defenders toward the attackers. We use a "Density-based Spatial Clustering of Application with Noise (DBSCAN)" algorithm to identify the spatially distributed swarms of the attackers. Then, the defenders are assigned to each identified swarm of attackers by solving a constrained generalized assignment problem. We also provide conditions under which defenders can successfully herd all the attackers. The efficacy of the approach is demonstrated via computer simulations, as well as hardware experiments with a fleet of quadrotors.

Multiobjective Calibration of Disease Simulation Models Using Gaussian Processes.

Background. Developing efficient procedures of model calibration, which entails matching model predictions to observed outcomes, has gained increasing attention. With faithful but complex simulation models established for cancer diseases, key parameters of cancer natural history can be investigated for possible fits, which can subsequently inform optimal prevention and treatment strategies. When multiple calibration targets exist, one approach to identifying optimal parameters relies on the Pareto frontier. However, computational burdens associated with higher-dimensional parameter spaces require a metamodeling approach. The goal of this work is to explore multiobjective calibration using Gaussian process regression (GPR) with an eye toward how multiple goodness-of-fit (GOF) criteria identify Pareto-optimal parameters. Methods. We applied GPR, a metamodeling technique, to estimate colorectal cancer (CRC)-related prevalence rates simulated from a microsimulation model of CRC natural history, known as the Colon Modeling Open Source Tool (CMOST). We embedded GPR metamodels within a Pareto optimization framework to identify best-fitting parameters for age-, adenoma-, and adenoma staging-dependent transition probabilities and risk factors. The Pareto frontier approach is demonstrated using genetic algorithms with both sum-of-squared errors (SSEs) and Poisson deviance GOF criteria. Results. The GPR metamodel is able to approximate CMOST outputs accurately on 2 separate parameter sets. Both GOF criteria are able to identify different best-fitting parameter sets on the Pareto frontier. The SSE criterion emphasizes the importance of age-specific adenoma progression parameters, while the Poisson criterion prioritizes adenoma-specific progression parameters. Conclusion. Different GOF criteria assert different components of the CRC natural history. The combination of multiobjective optimization and nonparametric regression, along with diverse GOF criteria, can advance the calibration process by identifying optimal regions of the underlying parameter landscape.

Characterising model dynamics using sparse grid interpolation: Parameter estimation of cholera.

Sparse grid interpolation is a popular numerical discretization technique for the treatment of high dimensional, multivariate problems. We consider the case of using time-series data to calibrate epidemiological models from both phenomenological and mechanistic perspectives using this computational tool. By capturing the dynamics underlying both global and local spaces, our algorithm identifies potentially optimal regions of the parameter space and directs computational effort towards resolving the dynamics and resulting fits of these regions. We demonstrate how sparse grid interpolants can be effectively deployed to fit available data and discriminate between competing hypotheses to explain the current cholera epidemic in Yemen.

Investigation of Thermal and Thermomechanical Properties of Biodegradable PLA/PBSA Composites Processed via Supercritical Fluid-Assisted Foam Injection Molding.

Bio-based polymer foams have been gaining immense attention in recent years due to their positive contribution towards reducing the global carbon footprint, lightweighting, and enhancing sustainability. Currently, polylactic acid (PLA) remains the most abundant commercially consumed biopolymer, but suffers from major drawbacks such as slow crystallization rate and poor melt processability. However, blending of PLA with a secondary polymer would enhance the crystallization rate and the thermal properties based on their compatibility. This study investigates the physical and compatibilized blends of PLA/poly (butylene succinate-co-adipate) (PBSA) processed via supercritical fluid-assisted (ScF) injection molding technology using nitrogen (N2) as a facile physical blowing agent. Furthermore, this study aims at understanding the effect of blending and ScF foaming of PLA/PBSA on crystallinity, melting, and viscoelastic behavior. Results show that compatibilization, upon addition of triphenyl phosphite (TPP), led to an increase in molecular weight and a shift in melting temperature. Additionally, the glass transition temperature (Tg) obtained from the tanδ curve was observed to be in agreement with the Tg value predicted by the Gordon⁻Taylor equation, further confirming the compatibility of PLA and PBSA. The compatibilization of ScF-foamed PLA⁻PBSA was found to have an increased crystallinity and storage modulus compared to their physically foamed counterparts.