Fibrosis Associated with Retroperitoneal Abscess after Multimodal Treatment of Cervical Carcinoma - A Case Report and Brief Review of the Literature.

Background: The multimodal treatment options for cervical carcinoma are represented by either radical hysterectomy associated with pelvic lymph node dissection, pelvic radiation therapy or chemotherapy. Inflammatory and post-neoplasia fibrosis associated with post-radiation fibrosis syndrome (RFS) and lymphedema may cause severe complications and quality of life alteration. Case report: Here we present a case of a 40-year-old woman, seven months after completing standard treatment for squamous cervical cancer FIGO IIA1 with a negative impact on the quality of life due to an important abdominal and retroperitoneal fibrosis leading to significant gastrointestinal symptoms. Over a year, a symptomatic intraabdominal collection and a retroperitoneal abscess were managed in the surgery department by percutaneous drainage and exploratory laparotomy. Bowel obstruction, abscessed pelvic tumor, left colocutaneous and colocolic fistula, intra-abdominal adhesions and left uretero-hydronephrosis were found. Postoperatively, the evolution was unfavorable with upper gastrointestinal bleeding probably due to entero-mesenteric fistula followed by death. Conclusion: Fibrosis can contribute to unfavorable clinical evolution with multiple complications and difficult management. Intra- and retroperitoneal fibrosis, neoplasia and post radiation enteropathy associated with pelvic inflammatory disease make the surgical approach difficult. Diagnosis of retroperitoneal abscess may be challenging due to nonspecific symptoms.

Analyzing Sustainable 3D Printing Processes: Mechanical, Thermal, and Crystallographic Insights.

In this study, the objective was to optimize energy consumption in the fused deposition modeling (FDM) 3D printing process via a detailed analysis of printing parameters. By utilizing thermal analysis techniques, this research aimed to identify lower printing temperatures that could lead to reduced energy usage. Experimental analysis was conducted using a three-level L9 Taguchi orthogonal array, which involved a systematic combination of different extruder temperatures and cooling fan capacities. Furthermore, the research incorporated differential scanning calorimetry (DSC) and X-ray diffraction (XRD) methods to analyze the thermal properties and crystallinity of the 3D-printed specimens. The results indicated that temperature was a key factor affecting crystallinity, with samples printed at 190 °C and 60% fan capacity showing the highest mean values. By conducting a multi-objective desirability analysis, the optimal conditions for maximizing ultimate tensile strength (UTS), tensile modulus, and elongation at break while minimizing energy consumption for PLA 3D-printed samples were determined to be a temperature of 180 °C and a fan speed of 80%.

Modernizing the NEURON Simulator for Sustainability, Portability, and Performance.

The need for reproducible, credible, multiscale biological modeling has led to the development of standardized simulation platforms, such as the widely-used NEURON environment for computational neuroscience. Developing and maintaining NEURON over several decades has required attention to the competing needs of backwards compatibility, evolving computer architectures, the addition of new scales and physical processes, accessibility to new users, and efficiency and flexibility for specialists. In order to meet these challenges, we have now substantially modernized NEURON, providing continuous integration, an improved build system and release workflow, and better documentation. With the help of a new source-to-source compiler of the NMODL domain-specific language we have enhanced NEURON's ability to run efficiently, via the CoreNEURON simulation engine, on a variety of hardware platforms, including GPUs. Through the implementation of an optimized in-memory transfer mechanism this performance optimized backend is made easily accessible to users, providing training and model-development paths from laptop to workstation to supercomputer and cloud platform. Similarly, we have been able to accelerate NEURON's reaction-diffusion simulation performance through the use of just-in-time compilation. We show that these efforts have led to a growing developer base, a simpler and more robust software distribution, a wider range of supported computer architectures, a better integration of NEURON with other scientific workflows, and substantially improved performance for the simulation of biophysical and biochemical models.