Iron Deficiency Is Common after Restorative Proctocolectomy with Ileal Pouch-Anal Anastomosis in Patients with Ulcerative Colitis

Background: Micronutrient deficiencies may occur after restorative proctocolectomy (RPC) with ileal pouch-anal anastomosis (IPAA) in patients with ulcerative colitis (UC), largely due to malabsorption and/or pouch inflammation. Objectives: The objective of this study was to report the frequency of iron deficiency in patients with UC who underwent RPC with IPAA and identify associated risk factors. Methods: We conducted a retrospective chart review of patients with UC or IBD-unclassified who underwent RPC with IPAA at Mount Sinai Hospital between 2008 and 2017. Patients younger than 18 years of age at the time of colectomy were excluded. Descriptive statistics were used to analyze baseline characteristics. Medians with interquartile range (IQR) were reported for continuous variables, and proportions were reported for categorical variables. Iron deficiency was defined by ferritin <30 ng/mL. Logistic regression was used to analyze unadjusted relationships between hypothesized risk factors and the outcome of iron deficiency. Results: A total of 143 patients had iron studies a median of 3.0 (IQR 1.7–5.6) years after final surgical stage, of whom 73 (51.0%) were men. The median age was 33.5 (IQR 22.7–44.3) years. Iron deficiency was diagnosed in 80 (55.9%) patients with a median hemoglobin of 12.4 g/dL (IQR 10.9–13.3), ferritin of 14 ng/mL (IQR 9.0–23.3), and iron value of 44 μg/dL (IQR 26.0–68.8). Of these, 29 (36.3%) had a pouchoscopy performed within 3 months of iron deficiency diagnosis. Pouchitis and cuffitis were separately noted in 4 (13.8%) and 13 (44.8%) patients, respectively, and concomitant pouchitis-cuffitis was noted in 9 (31.0%) patients. Age, sex, anastomosis type, pouch duration, and history of pouchitis and/or cuffitis were not associated with iron deficiency. Conclusion: Iron deficiency is common after RPC with IPAA in patients with UC. Cuffitis is seen in the majority of patients with iron deficiency; however, iron deficiency may occur even in the absence of inflammation

Exploring Traffic Crash Narratives in Jordan Using Text Mining Analytics

This study explores traffic crash narratives in an attempt to inform and enhance effective traffic safety policies using text-mining analytics. Text mining techniques are employed to unravel key themes and trends within the narratives, aiming to provide a deeper understanding of the factors contributing to traffic crashes. This study collected crash data from five major freeways in Jordan that cover narratives of 7,587 records from 2018-2022. An unsupervised learning method was adopted to learn the pattern from crash data. Various text mining techniques, such as topic modeling, keyword extraction, and Word Co-Occurrence Network, were also used to reveal the co-occurrence of crash patterns. Results show that text mining analytics is a promising method and underscore the multifactorial nature of traffic crashes, including intertwining human decisions and vehicular conditions. The recurrent themes across all analyses highlight the need for a balanced approach to road safety, merging both proactive and reactive measures. Emphasis on driver education and awareness around animal-related incidents is paramount.</p

Visual Reasoning and Multi-Agent Approach in Multimodal Large Language Models (MLLMs): Solving TSP and mTSP Combinatorial Challenges

Multimodal Large Language Models (MLLMs) harness comprehensive knowledge spanning text, images, and audio to adeptly tackle complex problems. This study explores the ability of MLLMs in visually solving the Traveling Salesman Problem (TSP) and Multiple Traveling Salesman Problem (mTSP) using images that portray point distributions on a two-dimensional plane. We introduce a novel approach employing multiple specialized agents within the MLLM framework, each dedicated to optimizing solutions for these combinatorial challenges. We benchmarked our multi-agent model solutions against the Google OR tools, which served as the baseline for comparison. The results demonstrated that both multi-agent models—Multi-Agent 1, which includes the initializer, critic, and scorer agents, and Multi-Agent 2, which comprises only the initializer and critic agents—significantly improved the solution quality for TSP and mTSP problems. Multi-Agent 1 excelled in environments requiring detailed route refinement and evaluation, providing a robust framework for sophisticated optimizations. In contrast, Multi-Agent 2, focusing on iterative refinements by the initializer and critic, proved effective for rapid decision-making scenarios. These experiments yield promising outcomes, showcasing the robust visual reasoning capabilities of MLLMs in addressing diverse combinatorial problems. The findings underscore the potential of MLLMs as powerful tools in computational optimization, offering insights that could inspire further advancements in this promising field

A Survey: To Govern, Protect, and Detect Security Principles on Internet of Medical Things (IoMT)

The integration of medical equipment into the Internet of Things (IoT) led to the introduction of Internet of Medical Things (IoMT). Variation of IoT devices have been equipped in medical facilities. These devices provided convenience to healthcare provider since they can continuously monitor their patients in real-time, while allowing them to have greater physical flexibility and mobility. However, users of healthcare services (such as patients and medical staff) often are less concerned about security issues associated with IoT. These alleviate existing problems and jeopardize the lives of their patients by making them susceptible to attacks. Furthermore, IoMT applications have direct access to healthcare services because it handles sensitive patient information. Therefore, it is extremely important to preserve and establish the security and privacy of IoMT. This further justifies the need to investigate and address the related issues. Despite existing literature on security and privacy mechanisms, the domain still requires more attention. Therefore, this paper aims to discuss the security and privacy principles, as well as challenges associated with IoMT. Besides, a comprehensive analysis of privacy and security solutions for IoMT is also presented. In addition, we introduced a novel taxonomy of IoMT security and privacy based on cyber security principles such as &#x201C;govern,&#x201D; &#x201C;protect,&#x201D; and &#x201C;detect&#x201D;. In conclusion, this paper provides a discussion on existing challenges and future direction for researchers

Results of Hierarchical based on seven selected features.

<p>Results of Hierarchical based on seven selected features.</p

Feature ranking using IG on DMZ 1 DARPA 2000 dataset.

<p>Feature ranking using IG on DMZ 1 DARPA 2000 dataset.</p

Results of Hierarchical after feature ranking.

<p>Results of Hierarchical after feature ranking.</p

All features of DRAPA 2000 datasets.

<p>All features of DRAPA 2000 datasets.</p

List of attack steps (clusters) discovered on all dataset.

<p>List of attack steps (clusters) discovered on all dataset.</p