Development of a Software for Treat-To-Target Strategy Implementation and Increasing Quality of Life in Patients with Inflammatory Bowel Disease.

The management of each form of the inflammatory bowel disease (IBD), ulcerative colitis (UC) and Crohn's disease (CD), represents a challenge for the clinician and patient. The treatment paradigm was shifted from achievement of a symptomatic control of the disease, to the prevention of bowel damage, disease progression and disability, and better quality of life. These goals were related with the treat-to-target (T2T) strategies developed for a proper treatment optimization. The T2T strategy is based on the assessments of the biochemical markers (C-Reactive Protein-CRP and fecal calprotectin-FCAL), clinical targets (multiple clinical scoring systems), endoscopic targets (resolution of ulceration and friability, and histologic targets. Another objective of the treatment is the obtaining of a higher level of improvement for the patient's quality of life (QoL). One of the most reliable ways for a better management of IBD is represented by the IT instruments. In this respect, we developed under the auspices of RCCC (Romanian Club of Crohn's and Colitis) between 2018-2019 a new software for collecting medical data of IBD patients, according to STRIDE recommendations, in order to have continuous access to their evolutionary history and all therapeutically aspects. The software proved to be a valuable tool for clinician with a positive impact on clinical, economic, and patient-centred outcomes in IBD.

MR spectroscopy of the liver - a reliable non-invasive alternative for evaluating non-alcoholic fatty liver disease.

Non-alcoholic fatty liver disease (NAFLD) is one of the most common conditions worldwide that targets the liver parenchyma. NAFLD represents an intrahepatic triglyceride accumulation in the absence of excessive alcohol consumption and other diseases that affect the liver parenchyma. The current "gold standard" for evaluating the amount of intrahepatic fat is represented by liver biopsy, but many patients are reluctant and hardly accept undergoing this procedure due to its invasive nature. The current study addresses this aspect by evaluating the reliability of liver magnetic resonance spectroscopy (MRS) in diagnosing NAFLD, compared to the traditional invasive liver biopsy. The present study included a total of 38 patients based on several well-defined inclusion and exclusion criteria. We used the same NAFLD grading system for both liver MRS and liver biopsy: grade 0: <5% hepatocytes are affected; grade I: 5-33% hepatocytes are affected; grade II: 34-66% hepatocytes are affected; grade III: >66% hepatocytes are affected. Regarding the NAFLD grade, over three-quarters of patients were classified as grade I and grade II, with a strong predilection for men. The current results indicated a significant association between the NAFLD grade indicated by liver MRS and the NAFLD grade indicated by liver biopsy. At the end of our study, we recommend using liver MRS for evaluating and grading NAFLD in association with other parameters like serum triglycerides and body mass index grade as this protocol can enhance early detection and provide an accurate grading that will lead to a proper management of this disease.

Automated Gleason grading of prostate cancer using transfer learning from general-purpose deep-learning networks.

Two deep-learning algorithms designed to classify images according to the Gleason grading system that used transfer learning from two well-known general-purpose image classification networks (AlexNet and GoogleNet) were trained on Hematoxylin-Eosin histopathology stained microscopy images with prostate cancer. The dataset consisted of 439 images asymmetrically distributed in four Gleason grading groups. Mean and standard deviation accuracy for AlexNet derivate network was of 61.17±7 and for GoogleNet derivate network was of 60.9±7.4. The similar results obtained by the two networks with very different architecture, together with the normal distribution of classification error for both algorithms show that we have reached a maximum classification rate on this dataset. Taking into consideration all the constraints, we conclude that the resulted networks could assist pathologists in this field, providing first or second opinions on Gleason grading, thus presenting an objective opinion in a grading system which has showed in time a great deal of interobserver variability.

Microglial morphology determined with confocal and two-photon laser scanning microscopy.

Microglia are the first and main form of active immune defense in the nervous system. The immune status of microglia is directly correlated to their morphology. Therefore, microglia morphology is used to distinguish between active and surveilling microglia. For the actual paper, we used confocal laser scanning microscopy (cLSM) and two-photon laser scanning microscopy (2P-LSM), to investigate microglia morphology of 14-16 weeks old male, transgenic mice (n=6). After obtaining, in vivo and fixed tissue, single cells images, we manually tracked individually branch segments of normal microglia. The total number of branches and their overall length were analyzed. Additionally, the number and mean length of each branch order were measured. The overall microglia branching morphology was not different between the two acquisition methods. However, a higher number of fifth branches was observed using cLSM and 2P-LSM, in both fixed and in vivo tissue. Although results from the two methods are mainly comparable, small differences between them should be taken in consideration when formulating an activating∕surveilling conclusion that is purely based on pure microscopic findings. Furthermore, in our opinion, due to their highly dynamic nature, microglia should be carefully labeled as resting or active, taking also into consideration the imaging method used to obtain the data.