Peritoneal recurrence in gastric cancer after curative gastrectomy: risk factors and predictive score model.

Background: Peritoneal recurrence (PR) remains the most common pattern of relapse in gastric cancer (GC), even after curative resection. Given its dismal prognosis, the identification of risk factors for PR is essential for developing new treatment modalities and selecting a more appropriate subgroup of patients. This study aimed to evaluate the risk factors and survival outcomes of patients with GC who had PR and to develop a risk score to predict PR.

Anomalies of Inferior Vena Cava: Implications and Considerations in Retroperitoneal Surgical Procedures.

Anomalies of the inferior vena cava pose a great challenge to surgeons. Although uncommon, these congenital vascular malformations may have significant surgical implications. Awareness of their presence is essential to avoid inadvertent injury and major bleeding during retroperitoneal procedures.

TRANSHIATAL ESOPHAGECTOMY IS NOT ASSOCIATED WITH POOR QUALITY LYMPHADENECTOMY.

Background: Esophageal cancer neoadjuvant therapy followed by surgery increases the likelihood of treatment success.

Aim: To evaluate variables that can influence the number of retrieved lymph nodes, the number of retrieved metastatic lymph nodes and lymphnodal recurrence in esophagectomy after neoadjuvant chemoradiotherapy.

Methods: Patients of a single institute were evaluated after completion of trimodal therapy.

The effects of aging on neuropil structure in mouse somatosensory cortex-A 3D electron microscopy analysis of layer 1.

This study has used dense reconstructions from serial EM images to compare the neuropil ultrastructure and connectivity of aged and adult mice. The analysis used models of axons, dendrites, and their synaptic connections, reconstructed from volumes of neuropil imaged in layer 1 of the somatosensory cortex. This shows the changes to neuropil structure that accompany a general loss of synapses in a well-defined brain region.

NeuroMorph: a toolset for the morphometric analysis and visualization of 3D models derived from electron microscopy image stacks.

Serialelectron microscopy imaging is crucial for exploring the structure of cells and tissues. The development of block face scanning electron microscopy methods and their ability to capture large image stacks, some with near isotropic voxels, is proving particularly useful for the exploration of brain tissue. This has led to the creation of numerous algorithms and software for segmenting out different features from the image stacks.