Background: s/Aims: To determine short-term and long-term outcomes after pancreas preserving total duodenectomy (PPTD). Methods: A case series and a complementary meta-analysis were conducted. All patients with (pre)neoplastic lesions of duodenum who underwent PPTD in a tertiary center for pancreatic surgery between May 2009 and October 2022 were included for the case series.All studies in the literature with a sample size of 10 or more patients reporting outcomes of PPTD were included for the meta-analysis. Results: A total of 439 patients (18 from case series and 421 from literature) were analyzed. Clavien-Dindo (CD) I complications in 2.9% (95% confidence interval [CI] 0.6%–5.2%), CD II complications in 21.1% (14.6%–27.6%), CD III complications in 18.1% (9.3%–26.9%), CD IV complications in 2.7% (0.5%–4.9%), and CD V complications in 2.2% (0.2%–4.2%) of patients were found. Probabilities of overall survival and recurrence-free survival at 15 years were 87% and 86%, respectively. There was no significant difference in the risk of mortality (odds ratio [OR]: 0.82, p = 0.830), total complications (OR: 0.77, p = 0.440), postoperative pancreatic fistula (OR: 0.43, p = 0.140), delayed gastric emptying (OR: 0.70, p = 0.450), or postoperative bleeding (OR: 0.97, p = 0.960) between PPTD and pancreaticoduodenectomy. Conclusions PPTD is safe and feasible for (pre)neoplastic lesions of duodenum not involving the pancreatic head. The risk of severe complications (CD > III) is low and long-term outcomes are favorable. Whether PPTD provides advantages over more radical techniques in terms of long-term outcomes remains controversial and requires further research.

Background: Pneumatization of turbinates, also known as concha bullosa (CB), is associated with nasal septal deviation and sinonasal pathologies. This study aims to evaluate the performance of deep learning models in detecting CB in coronal cone-beam computed tomography (CBCT) images. Methods: Standardized coronal images were obtained from 203 CBCT scans (83 with CB and 119 without CB) from the radiology archives of a dental teaching hospital. These scans underwent preprocessing through a hybridized contrast enhancement (CE) method using discrete wavelet transform (DWT). Of the 203 CBCT images, 162 were randomly assigned to the training set and 41 to the testing set. Initially, the images were enhanced using a CE technique before being input into pre-trained deep learning models, namely ResNet50, ResNet101, and MobileNet. The features extracted by each model were then flattened and input into a random forest (RF) classifier. In the subsequent phase, the CE technique was refined by incorporating DWT. Results: CE-DWT-ResNet101-RF demonstrated the highest performance, achieving an accuracy of 91.7% and an area under the curve (AUC) of 98%. In contrast, CE-MobileNet-RF recorded the lowest accuracy at 82.46% and an AUC of 92%. The highest precision, recall, and F1 score (all 92%) were observed for CE-DWT-ResNet101-RF. Conclusion Deep learning models demonstrated high accuracy in detecting CB in CBCT images. However, to confirm these results, further studies involving larger sample sizes and various deep learning models are required.

Inflammatory myofibroblastic tumor (IMT) of the soft tissues of the neck is a rare pathological entity. We present the case of a 32-year-old patient who had a painful, slowly enlarging mass in the neck’s soft tissues. Radiological examination revealed a well-defined, dense lesion. The mass was surgically removed through local excision. Immunohistological analysis confirmed the diagnosis of IMT. After nearly 2 years of follow-up, there was no evidence of recurrence or distant metastases. In conclusion, although IMT of the soft tissues of the neck is uncommon, it should be considered in the differential diagnosis of neck tumors. Further research is necessary to understand the pathogenetic mechanisms of IMT, which could lead to the development of more effective treatments for this tumor.

Purpose: This study evaluated the sensitivity, specificity, and accuracy of computed tomographic angiography (CTA) versus handheld Doppler (HHD) in detecting perforators for anterolateral thigh (ALT) flap surgery. Methods: This study was conducted on 20 patients randomly assigned to two groups from April 2023 to November 2024: One group received CTA and HHD, while the other group received only HHD. Perforators were evaluated for their number, location, and source and compared with intraoperative findings. Results: The sensitivity and specificity of CTA were 86.0% and 98.0%, respectively, while those of HHD were 81.0% and 86.5%. CTA exhibited an accuracy of 92.0% for perforator identification, whereas that of HHD was 83.5%. Conclusion CTA offers higher sensitivity, specificity, and accuracy in identifying ALT flap perforators than HHD. Its superior imaging capabilities can enable improved surgical planning, minimizing intraoperative challenges, reducing the risk of complications, and potentially increasing flap survival rates. As such, CTA could be considered a valuable standard tool in preoperative planning for ALT flap surgery, particularly in cases where anatomical variation poses a challenge.

Purpose: To assess clinical outcomes in patients undergoing surgical excision and eyelid reconstruction for malignancies. Methods: This 17-year retrospective study (2004–2021) analyzed patients with malignant eyelid tumors who underwent excision and reconstruction. Data on tumor type, size, location, surgical techniques, complications, and prognostic factors for recurrence were evaluated. Results: A total of 152 patients underwent surgical excision and reconstruction for eyelid malignancies. Basal cell carcinoma was the most common (52.6%), followed by sebaceous cell carcinoma (32.2%). Direct lid closure was the most frequent reconstructive method. Postoperative complications, including ectropion, entropion, and canalicular obstruction, were minimal but required additional surgery in some cases. Recurrence occurred in 13 patients. Lymph node involvement (odds ratio, 21.291; p = 0.004) and positive intraoperative frozen margins (odds ratio, 7.083; p = 0.018) were significant risk factors for local recurrence. Conclusions Surgical excision and reconstruction are effective treatments for eyelid malignancies, with techniques tailored to tumor size, location, and extension to ensure proper lid function. Lymph node involvement and positive intraoperative frozen margins are key predictors of local recurrence.

Background: Parkinson’s disease is a debilitating and the second most common neurodegenerative disorder with a high prevalence. Parkinson’s disease has a multifaceted etiology characterized by an altered redox state and an excessive inflammatory response. In this study, we investigated the potential neuroprotective properties of carvacrol in a haloperidol-induced Parkinson’s model. In female Sprague-Dawley rats, the animal Parkinson model was induced by intraperitoneally administering 1 mg / kg of haloperidol once daily for fifteen days. Carvacrol was administered at a dose of 25 and 50 mg / kg once daily for fifteen days before haloperidol administration. In order to further illustrate the vital role of the tumor necrosis factor (TNF-α) pathway, we administered 50 mg / kg of the TNF-α inhibitor thalidomide once daily for 15 days. Results: Our results showed that haloperidol-induced motor deficits, changed endogenous antioxidant enzymes, along with higher levels of inflammasome (NLRP3) and other inflammatory mediators. Moreover, increased levels of lipid peroxidase (LPO) indicated a significant rise in oxidative stress due to haloperidol. Moreover, carvacrol reduced these effects by preventing pyroptosis mediated by the inflammasome (NLRP3) and TNF-α. The administration of thalidomide mitigated oxidative stress and suppresses inflammatory pathways through the augmentation of the intrinsic antioxidant system. Further, co-treatment of carvacrol with thalidomide synergized the neuroprotective effect of carvacrol as demonstrated by various immunoassays and histology analyses. Conclusions Taken together, our findings suggest that carvacrol mitigated haloperidol-induced Parkinson-like symptoms, partially through the downregulation of TNF-α and NLRP3.

Zebrafish (Danio rerio) have emerged as an influential model for studying human epithelial pathology, particularly because of their genetic similarity to humans and their unique physiological traits. This review explores the structural and functional homology between zebrafish and human epithelial tissues in organs, such as the gastrointestinal system, liver, and kidneys. Zebrafish possess significant cellular and functional homology with mammals, which facilitates the investigation of various diseases, including inflammatory bowel disease, nonalcoholic fatty liver disease, and polycystic kidney disease. The advantages of using zebrafish as a model organism include rapid external development, ease of genetic manipulation, and advanced imaging capabilities, allowing for the real-time observation of disease processes. However, limitations exist, particularly concerning the lack of organs in zebrafish and the potential for incomplete phenocopy of human conditions. Despite these challenges, ongoing research in adult zebrafish promises to enhance our understanding of the disease mechanisms and regenerative processes. By revealing the similarities and differences in epithelial cell function and disease pathways, this review highlights the value of zebrafish as a translational model for advancing our knowledge of human health and developing targeted therapies.

Dyslipidemia is a major risk factor for cardiovascular disease, and its impact may be exacerbated when accompanied by metabolic dysfunction-associated steatotic liver disease (MASLD). The simultaneous management of these conditions poses multiple challenges for healthcare providers. Insulin resistance has been implicated in the pathogenesis of both dyslipidemia and MASLD, necessitating a holistic approach to managing dyslipidemia, glucose levels, body weight, and MASLD. This review explores the intricate pathophysiological relationship between MASLD and dyslipidemia. It also examines current guidance regarding the use of lipid-lowering agents (including statins, ezetimibe, fibrates, omega-3 polyunsaturated fatty acids, and proprotein convertase subtilisin/kexin type 9 inhibitors) as well as glucose-lowering medications (such as pioglitazone, glucagon-like peptide-1 receptor agonists, and sodium-glucose cotransporter 2 inhibitors) in patients with MASLD, with or without metabolic dysfunction-associated steatohepatitis (MASH), and dyslipidemia. Additionally, the review addresses the potential of emerging drugs to concurrently target both MASLD/MASH and dyslipidemia. Our hope is that a deeper understanding of the mechanisms underlying MASLD and dyslipidemia may assist clinicians in the management of these complex cases.

Purpose: This study aims to validate the use of ProAnalyst (Xcitex Inc.), a software for professional motion analysts to assess the performance of surgical interns while performing the peg transfer task in a simulator box for safe practice in real minimally invasive surgery. Methods: A correlation study was conducted in a multidisciplinary skills simulation lab at the Faculty of Medicine, Jordan University of Science and Technology from October 2019 to February 2020. Forty-one interns (i.e., novices and intermediates) were recruited and an expert surgeon participated as a reference benchmark. Videos of participants’ performance were analyzed through the ProAnalyst and Global Operative Assessment of Laparoscopic Skills (GOALS). Two results were s analyzed for correlation. Results: The motion analysis scores by Proanalyst were correlated with those by GOALS for novices (r=–0.62925, P=0.009), and Intermediates (r= –0.53422, P=0.033). Both assessment methods differentiated the participants’ performance based on their experience level. Conclusion The motion analysis scoring method with Proanalyst provides an objective, time-efficient, and reproducible assessment of interns’ performance, and comparable to GOALS. It may require initial training and set-up; however, it eliminates the need for expert surgeon judgment.

Purpose: This study was performed to assess the performance and accuracy of artificial intelligence (AI) in the detection and diagnosis of maxillary sinus pathologies using computed tomography (CT)/cone-beam computed tomography (CBCT) imaging. Materials and Methods: A comprehensive literature search was conducted across 4 databases: Google Scholar, BioMed Central (BMC), ProQuest, and PubMed. Combinations of keywords such as “DCNN,” “deep learning,” “convolutional neural network,” “machine learning,” “predictive modeling,” and “data mining” were used to identify relevant articles. The study included articles that were published within the last 5 years, written in English, available in full text, and focused on diagnostic accuracy. Results: Of an initial 530 records, 12 studies with a total of 3,349 patients (7,358 images) were included. All articles employed deep learning methods. The most commonly tested pathologies were maxillary rhinosinusitis and maxillary sinusitis, while the most frequently used AI models were convolutional neural network architectures, including ResNet and DenseNet, YOLO, and U-Net. DenseNet and ResNet architectures have demonstrated superior precision in detecting maxillary sinus pathologies due to their capacity to handle deeper networks without overfitting. The performance in detecting maxillary sinus pathology varied, with an accuracy ranging from 85% to 97%, a sensitivityof 87% to 100%, a specificity of 87.2% to 99.7%, and an area under the curve of 0.80 to 0.91. Conclusion AI with various architectures has been used to detect maxillary sinus abnormalities on CT/CBCT images, achieving near-perfect results. However, further improvements are needed to increase accuracy and consistency.