The rising incidence of pancreatic diseases, including acute and chronic pancreatitis and various pancreatic neoplasms, poses a significant global health challenge. Pancreatic ductal adenocarcinoma (PDAC) for example, has a high mortality rate due to late‐stage diagnosis and its inaccessible location. Advances in imaging technologies, though improving diagnostic capabilities, still necessitate biopsy confirmation. Artificial intelligence, particularly machine learning and deep learning, has emerged as a revolutionary force in healthcare, enhancing diagnostic precision and personalizing treatment. This narrative review explores Artificial intelligence's role in pancreatic imaging, its technological advancements, clinical applications, and associated challenges. Following the PRISMA‐DTA guidelines, a comprehensive search of databases including PubMed, Scopus, and Cochrane Library was conducted, focusing on Artificial intelligence, machine learning, deep learning, and radiomics in pancreatic imaging. Articles involving human subjects, written in English, and published up to March 31, 2024, were included. The review process involved title and abstract screening, followed by full‐text review and refinement based on relevance and novelty. Recent Artificial intelligence advancements have shown promise in detecting and diagnosing pancreatic diseases. Deep learning techniques, particularly convolutional neural networks (CNNs), have been effective in detecting and segmenting pancreatic tissues as well as differentiating between benign and malignant lesions. Deep learning algorithms have also been used to predict survival time, recurrence risk, and therapy response in pancreatic cancer patients. Radiomics approaches, extracting quantitative features from imaging modalities such as CT, MRI, and endoscopic ultrasound, have enhanced the accuracy of these deep learning models. Despite the potential of Artificial intelligence in pancreatic imaging, challenges such as legal and ethical considerations, algorithm transparency, and data security remain. This review underscores the transformative potential of Artificial intelligence in enhancing the diagnosis and treatment of pancreatic diseases, ultimately aiming to improve patient outcomes and survival rates.

The study evaluated the evolution of the incidence of infections with Klebsiella in the County Clinical Emergency Hospital of Craiova (SCJUC), Romania. Also, we monitored antibiotic resistance over more than two years and detected changes in resistance to various antimicrobial agents. Our study included 2062 patients (823 women and 1239 men) hospitalised in SCJUC during the period 1st of September 2017 to 30 June 2019. In 458 patients (22.21%) from the 2062 total patients, the collected samples (1116) were positive and from those, we isolated 251 strains of Klebsiella spp. We conducted a longitudinal analysis of the prevalence of Klebsiella spp. over calendar months, which showed a prevalence in surgical wards that ranged between 5.25% and 19.49% in June 2018, while in medical wards the variation was much wider, between 5.15% and 17.36% in April 2018. Klebsiella spp. strains showed significant resistance to Amoxicillin/Clavulanate, Aztreonam and Cephalosporins such as Ceftriaxone, Ceftazidime and Cefepime. We examined the possible link with the consumption of antibiotics in the same month by performing a multiple linear regression analysis. The evolution of antibiotic resistance in Klebsiella was correlated with the variation of resistance in other bacteria, which suggests common resistance mechanisms in the hospital environment. By performing the regression for dependency between antibiotic resistance and antibiotic consumption, we observed some correlations between antibiotic consumption and the development of antibiotic resistance after 1, 2 and even 3 months (e.g., resistance to meropenem was influenced by the consumption in the hospital ward of imipenem 1 month and two months before, but only 1 month before by the consumption of meropenem). The clustering of strains showed filiation between multiresistant Klebsiella spp. strains isolated from specific patients from the ICU. The evolution of prevalence and antibiotic resistance in Klebsiella correlated with the resistance in other bacteria, which suggest common resistance mechanisms in the hospital environment, and also with the consumption of antibiotics.

Genetic research has shaped the inflammatory bowel disease (IBD) landscape identifying nearly two hundred risk loci. Nonetheless, the identified variants rendered only a partial success in providing criteria for the differential diagnosis between ulcerative colitis (UC) and Crohn’s disease (CD). Transcript levels from affected intestinal mucosa may serve as tentative biomarkers for improving classification and diagnosis of IBD. The aim of our study was to identify gene expression profiles specific for UC and CD, in endoscopically affected and normal intestinal colonic mucosa from IBD patients. We evaluated a panel of 84 genes related to the IBD-inflammatory pathway on 21 UC and 22 CD paired inflamed and not inflamed mucosa and on age-matched normal mucosa from 21 non-IBD controls. Two genes in UC (CCL11 and MMP10) and two in CD (C4BPB and IL1RN) showed an upregulation trend in both noninflamed and inflamed mucosa compared to controls. Our results suggest that the transcript levels of CCL11, MMP10, C4BPB, and IL1RN are candidate biomarkers that could help in clinical practice for the differential diagnosis between UC and CD and could guide new research on future therapeutic targets.

Inflammatory bowel disease development has been associated with several environmental factors, among which, diet can play a key role, probably due to a westernized lifestyle. However, its involvement in the pathogenesis of inflammatory bowel disease (IBD) is difficult to demonstrate. The aim of this study was to analyze dietary composition in a Romanian and Belgian population with IBD. an observational retrospective comparative study was performed using two European cohorts (Romanian and Belgian). The IBD group included 76 Romanian and 53 Belgian patients with an IBD diagnosis, while the control group included a total of 56 healthy people (35 Romanians and 21 Belgians). All subjects were interviewed and asked to fill in a questionnaire regarding diet. in the entire IBD cohort (Romanian + Belgian), a significantly increased consumption of sweets (OR 3.36 [95 % CI 1.6,7]), processed and high fat meat (OR 2.5 [95 % CI 1.4, 4.7], fried food (OR 9.5 [3.8, 23.6]), salt (OR 2.8 [1.5, 5.3]), ice cream (OR 3.25 [1.1, 9.8]), mayonnaise (OR 3.49 [1.1, 10.3]), margarine (OR 5.63 [1.64, 19.33]) and chips/nachos/other snacks (OR 2.3 [0.97, 5.73]) were found compared to the healthy control group. The intake of seeds, nuts (OR 0.26 [0.14, 0.52]) and yoghurt consumption (OR 0.44 [0.23, 0.83]) was lower in the IBD group compared to the control group. a westernized diet with increased consumption of sweets, processed food, high fat meat, fried food, salt, margarine, snacks, ice cream and mayonnaise seems to be a risk factor for IBD in Romanian and Belgian IBD patients. Intake of seeds, nuts and yoghurt may be a protective factor.

AFP (alpha-fetoprotein) levels are increased during the development of HCC (hepatocellular carcinoma); nonetheless, it can also be produced by non-tumoral hepatocytes in conditions of high cell turnover. Our study aims to provide additional data regarding the causes of elevated AFP in patients with liver cirrhosis due to hepatitis C virus (HCV) infection. We conducted an observational prospective cohort study that included 2068 patients with compensated cirrhosis and chronic hepatitis C genotype 1b infection. The two main inclusion criteria were the presence of advanced liver fibrosis - Metavir stage F4 - diagnosed by FibroMax testing, Fibroscan or liver biopsy, and the presence of detectable HCV RNA in the serum. Plasmatic AFP levels were determined through the electrochemiluminescence method, with a standard value ranging from 0 to 7 ng/ml. All data were obtained from the Romanian National Health Agency. The average AFP serum levels in patients with compensated cirrhosis without HCC were 9.4 ng/ml (range 0.5 ÷ 406 ng/ml); 30.1% of patients had significantly increased levels of AFP (>15 ng/ml). High values of serum AFP in patients with compensated liver cirrhosis without HCC was correlated with more advanced age (p<0.001), severe necroinflammatory activity detected by FibroMax (p<0.001), severe NASH (p<0.001), severe steatosis (p<0.001), low platelets (p<0.001), increased values of AST and ALT (p<0.001).