Efficacy of different interventions on the morbidity of the palatal donor area after free gingival graft and connective tissue graft: A systematic review

This review aimed to evaluate the efficacy of different interventions used on the palatal donor area in the treatment of postoperative pain after free gingival graft and connective tissue graft techniques, and their impact in the oral-health related quality of life (OHRQOL). This study was conducted according to PRISMA. A search was conducted in four electronic databases and the grey literature. The interventions found were grouped according to biological plausibility and mechanisms of action: Mechanical Barriers; Topical Drugs; Hemostatic Agents; Other Therapies (photobiomodulation, ozonotherapy and others). Fifty-four studies were included and 43 different interventions were reported. The most commonly reported intervention was collagen hemostatic sponge, either alone or combined with other interventions, followed by platelet-rich fibrin and photobiomodulation. Postoperative pain evaluation using the Visual Analogue Scale (VAS) generally indicated that interventions improved pain over time. However, comparing the superiority of interventions is challenging, as studies often combine different interventions with different mechanisms of action. OHRQOL also showed improvement over time, but the comparison between interventions is limited, since few studies used a validated tool. The methodological diversity among studies is considerable, requiring a cautious interpretation of individual studies.

Readability, accuracy and appropriateness and quality of AI chatbot responses as a patient information source on root canal retreatment: A comparative assessment

AIM

This study aimed to assess the readability, accuracy, appropriateness, and overall quality of responses generated by large language models (LLMs), including ChatGPT-3.5, Microsoft Copilot, and Gemini (Version 2.0 Flash), to frequently asked questions (FAQs) related to root canal retreatment.

METHODS

Three LLM chatbots-ChatGPT-3.5, Microsoft Copilot, and Gemini (Version 2.0 Flash)-were assessed based on their responses to 10 patient FAQs. Readability was analyzed using seven indices, including Flesch reading ease score (FRES), Flesch-Kincaid grade level (FKGL), Simple Measure of Gobbledygook (SMOG), gunning FOG (GFOG), Linsear Write (LW), Coleman-Liau (CL), and automated readability index (ARI), and compared against the recommended sixth-grade reading level. Response quality was evaluated using the Global Quality Scale (GQS), while accuracy and appropriateness were rated on a five-point Likert scale by two independent reviewers. Statistical analyses were conducted using one-way ANOVA, Tukey or Games-Howell post-hoc tests for continuous variables. Spearman's correlation test was used to assess associations between categorical variables.

RESULTS

All chatbots generated responses exceeding the recommended readability level, making them suitable for readers at or above the 10th-grade level. No significant difference was found between ChatGPT-3.5 and Microsoft Copilot, while Gemini produced significantly more readable responses (p < 0.05). Gemini demonstrated the highest proportion of accurate (80 %) and high-quality responses (80 %) compared to ChatGPT-3.5 and Microsoft Copilot.

CONCLUSIONS

None of the chatbots met the recommended readability standards for patient education materials. While Gemini demonstrated better readability, accuracy, and quality, all three models require further optimization to enhance accessibility and reliability in patient communication.

Breast cancer survival in Ethiopia: a systematic review and meta-analysis of rates and predictors

BACKGROUND

Evidence on breast cancer survival and factors affecting survival is crucial for evaluating treatment effectiveness and formulating breast cancer control strategies. Although original research has been conducted on the survival rate of breast cancer patients and their determinants in Ethiopia, there is a shortage of comprehensive scientific evidence. The present study systematically reviewed literature on the survival rate of breast cancer patients and the predictors of survival in Ethiopia.

METHODS

A comprehensive search was conducted in the PubMed, HINARI, Global Index Medicus, and Google Scholar databases up to August 26, 2024. Without any design restrictions, studies on breast cancer patients that measured survival at different time points in Ethiopia were included. The results are summarized in a table, the survival rates are pooled, and risk factors are narratively synthesized. To assess the risk of bias, the Newcastle Ottawa Scale was utilized. Heterogeneity between studies was assessed using the I2 statistic. Potential publication bias was assessed using a funnel plot. To examine robustness, a leave-one-out sensitivity analysis was performed.

RESULTS

The pooled survival rates in the first, second, third, fifth, and sixth years were 90%, 70%, 68%, 46%, and 44%, respectively. Advanced age, lower socioeconomic status, late clinical stage, delayed diagnosis, higher histological grade, metastasis, lymph node involvement, presence of comorbidity, tumor size, and estrogen receptor positive were factors that increased the risk of mortality in the included studies.

CONCLUSION

Survival rate of breast cancer patients in later time including fifth and sixth years was comparably lower than other countries. It is crucial to raise awareness about breast cancer screening, early diagnosis, and therapy initiation to increase the survival rate of breast cancer patients in Ethiopia. In addition, it is important to emphasize the risky population groups, which includes those with lower socioeconomic status and advanced clinical parameters.

Peroral Endoscopic Myotomy and Functional Lumen Imaging Probe

Esophageal motor disorders (EMDs) encompass a spectrum of conditions characterized by abnormal motility patterns leading to impaired bolus transit through the esophagus. These disorders can generally be categorized as dysfunction of the esophagogastric junction, dysfunction of peristalsis, or a combination of both. A thorough clinical history focusing on classic symptoms is imperative to guide the diagnostic approach and interpretation of testing appropriately. High-resolution manometry is the cornerstone diagnostic modality for EMDs as it allows for interrogation of esophageal pressure dynamics in real time by measuring peristaltic activity of the esophageal body and the relaxation of the lower esophageal sphincter.

Hepatitis B virus genotype distribution and mutation patterns: Insights and clinical implications for hepatitis B virus positive patients

Hepatitis B virus (HBV) infection is still a major worldwide health concern, contributing to chronic liver disorders like hepatocellular carcinoma (HCC). This review comprehensively analyzes HBV genotype distribution, mutation patterns, and their clinical implications, focusing on diagnostic and therapeutic strategies for HBV-positive patients. The discussion begins with HBV virology, emphasizing its capacity for chronic hepatitis and its association with severe liver complications, notably HCC. Understanding HBV genotypes (A-J) and their distinct geographic distributions is crucial, as genotype variations influence disease progression and treatment responses. Genotypes like C are particularly linked to heightened HCC risk, highlighting the need for genotype-specific management strategies. The genomic structure of HBV, consisting of four open reading frames (ORFs) encoding essential viral proteins, is detailed, with emphasis on mutations within these ORFs influenced by host immune responses and antiviral therapies. These mutations contribute to viral resistance and virulence, impacting treatment outcomes through alterations in viral replication dynamics. Clinical implications are explored through genotype-specific impacts on disease outcomes and treatment approaches. Genotype and mutation analysis guide personalized treatment regimens, optimizing therapeutic efficacy while minimizing adverse effects and preventing drug resistance. Diagnostic molecular techniques such as polymerase chain reaction and sequencing are pivotal in genotype and mutation detection, facilitating tailored treatment decisions.

The sports nutrition knowledge of large language model (LLM) artificial intelligence (AI) chatbots: An assessment of accuracy, completeness, clarity, quality of evidence, and test-retest reliability

BACKGROUND

Generative artificial intelligence (AI) chatbots are increasingly utilised in various domains, including sports nutrition. Despite their growing popularity, there is limited evidence on the accuracy, completeness, clarity, evidence quality, and test-retest reliability of AI-generated sports nutrition advice. This study evaluates the performance of ChatGPT, Gemini, and Claude's basic and advanced models across these metrics to determine their utility in providing sports nutrition information.

MATERIALS AND METHODS

Two experiments were conducted. In Experiment 1, chatbots were tested with simple and detailed prompts in two domains: Sports nutrition for training and Sports nutrition for racing. Intraclass correlation coefficient (ICC) was used to assess interrater agreement and chatbot performance was assessed by measuring accuracy, completeness, clarity, evidence quality, and test-retest reliability. In Experiment 2, chatbot performance was evaluated by measuring the accuracy and test-retest reliability of chatbots' answers to multiple-choice questions based on a sports nutrition certification exam. ANOVAs and logistic mixed models were used to analyse chatbot performance.

RESULTS

In Experiment 1, interrater agreement was good (ICC = 0.893) and accuracy varied from 74% (Gemini1.5pro) to 31% (ClaudePro). Detailed prompts improved Claude's accuracy but had little impact on ChatGPT or Gemini. Completeness scores were highest for ChatGPT-4o compared to other chatbots, which scored low to moderate. The quality of cited evidence was low for all chatbots when simple prompts were used but improved with detailed prompts. In Experiment 2, accuracy ranged from 89% (Claude3.5Sonnet) to 61% (ClaudePro). Test-retest reliability was acceptable across all metrics in both experiments.

CONCLUSIONS

While generative AI chatbots demonstrate potential in providing sports nutrition guidance, their accuracy is moderate at best and inconsistent between models. Until significant advancements are made, athletes and coaches should consult registered dietitians for tailored nutrition advice.

Prevention of shivering post spinal anesthesia: Ondansetron vs. Nefopam ‒ a prospective randomized controlled trial

BACKGROUND

Post Spinal Anesthesia Shivering (PSAS) is common and linked to increased morbidity.While various methods exist to prevent it, no study has compared Nefopam and Ondansetron. This study aims to compare Ondansetron and Nefopam in preventing PSAS.

METHODS

A prospective, randomized, controlled, double-blind trial was conducted in the operating room of a tertiary university hospital from April 5, 2021 to April 30, 2022. It included patients aged between 18 and 65 years scheduled for surgery under spinal anesthesia. Patients received either 8 mg of Ondansetron or 20 mg of Nefopam administered intravenously over 30 minutes before spinal anesthesia. Main outcome measures included the number and grades of shivering episodes post spinal anesthesia at 15-minute intervals until post anesthesia care unit discharge. Secondary outcomes included number of episodes of hypotension, bradycardia, nausea and/or vomiting. Tympanic temperature and pain at the injection site were also recorded.

RESULTS

The study included 150 patients, evenly divided between the two groups. The Ondansetron group had a higher incidence of shivering compared to the Nefopam group (23.9% vs. 16%; p = 0.038), as well as higher incidences of hypotension (16% vs. 5.3%; p = 0.035) and bradycardia (13.3% vs. 2.7%; p = 0.016). The Ondansetron group had a significantly lower incidence of nausea and vomiting (12% vs. 1.3%; p = 0.010). More patients in the Nefopam group (45.3%) reported pain during drug infusion.

CONCLUSIONS

Nefopam seems to be more effective than Ondansetron in preventing PSAS with fewer cardiovascular side effects. However, Ondansetron reduces the incidence of nausea and vomiting and causes no pain during administration.

Rectal diclofenac versus indomethacin for prevention of post-ERCP pancreatitis (DIPPP): a multicentre, double-blind, randomised, controlled trial

BACKGROUND

Recent meta-analyses suggested diclofenac may be superior to indomethacin in preventing post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP). The aim of our study was to compare the efficacy of 100 mg rectal indomethacin versus diclofenac on PEP incidences.

DESIGN

This multicentre, double-blinded, randomised controlled trial was conducted in nine tertiary centres in China. Patients with low and high risk for PEP and native papilla were randomly allocated (1:1) to receive 100 mg diclofenac or 100 mg indomethacin rectally before ERCP. The primary outcome was the occurrence of PEP defined by the Cotton consensus. The intention-to-treat principle was conducted for the analysis.

RESULTS

The trial was terminated early for futility after the predetermined first interim analysis. Between June 2023 and May 2024, 1204 patients were randomised into the diclofenac group (n=600) or indomethacin group (n=604). Baseline characteristics were balanced. The primary outcome occurred in 53 patients (8.8%) of 600 patients allocated to the diclofenac group and 37 patients (6.1%) of 604 patients allocated to the indomethacin group (relative risk 1.44; 95% CI 0.96 to 2.16, p=0.074). PEP occurred in 35 (14.2%) of 247 high-risk patients in the diclofenac group and 26 (9.8%) of 266 high-risk patients in the indomethacin group (p=0.124). PEP incidences were also comparable in low-risk patients between the two groups (18/353 (5.1%) vs 11/338 (3.3%), p=0.227). Other ERCP-related complications did not differ between the two groups.

CONCLUSION

Pre-procedure 100 mg rectal diclofenac was not superior to the same dose of rectal indomethacin regarding preventing PEP. These findings supported current clinical practice guidelines of 100 mg indomethacin or diclofenac for PEP prophylaxis in patients without contraindications.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov (NCT05947461).

Accuracy, consistency, and contextual understanding of large language models in restorative dentistry and endodontics

OBJECTIVE

This study aimed to evaluate and compare the performance of several large language models (LLMs) in the context of restorative dentistry and endodontics, focusing on their accuracy, consistency, and contextual understanding.

METHODS

The dataset was extracted from the national educational archives of the Collège National des Enseignants en Odontologie Conservatrice (CNEOC) and includes all chapters from the reference manual for dental residency applicants. Multiple-choice questions (MCQs) were selected following a review by three independent academic experts. Four LLMs were assessed: ChatGPT-3.5, ChatGPT-4 (OpenAI), Claude-3 (Anthropic), and Mistral 7B (Mistral AI). Model accuracy was determined by comparing responses with expert-provided answers. Consistency was measured through robustness (the ability to provide identical responses to paraphrased questions) and repeatability (the ability to provide identical responses to the same question). Contextual understanding was evaluated based on the model's ability to categorise questions correctly and infer terms from definitions. Additionally, accuracy was reassessed after providing the LLMs with the relevant full course chapter.

RESULTS

A total of 517 MCQs and 539 definitions were included. ChatGPT-4 and Claude-3 demonstrated significantly higher accuracy and repeatability than Mistral 7B, with ChatGPT-4 showing the greater robustness. Advanced LLMs displayed high accuracy in presenting dental content, although performance varied on closely related concepts. Supplying course chapters generally improved response accuracy, though inconsistently across topics.

CONCLUSION

Even the most advanced LLMs, such as ChatGPT-4 and Claude 3, achieve moderate performance and require cautious use due to inconsistencies in robustness. Future studies should focus on integrating validated content and refining prompt engineering to enhance the educational and clinical utility of LLMs.

CLINICAL SIGNIFICANCE

The findings underscore the potential of advanced LLMs and context-based prompting in restorative dentistry and endodontics.

Machine Learning Accurately Predicts Need for Critical Care Support in Patients Admitted to Hospital for Community-Acquired Pneumonia

OBJECTIVES

Hospitalized community-acquired pneumonia (CAP) patients are admitted for ventilation, vasopressors, and renal replacement therapy (RRT). This study aimed to develop a machine learning (ML) model that predicts the need for such interventions and compare its accuracy to that of logistic regression (LR).

DESIGN

This retrospective observational study trained separate models using random-forest classifier (RFC), support vector machines (SVMs), Extreme Gradient Boosting (XGBoost), and multilayer perceptron (MLP) to predict three endpoints: eventual use of invasive ventilation, vasopressors, and RRT during hospitalization. RFC-based models were overall most accurate in a derivation COVID-19 CAP cohort and were validated in one COVID-19 CAP and two non-COVID-19 CAP cohorts.

SETTING

This study is part of the Community-Acquired Pneumonia: Toward InnoVAtive Treatment (CAPTIVATE) Research program.

PATIENTS

Two thousand four hundred twenty COVID-19 and 1909 non-COVID-19 CAP patients over 18 years old hospitalized and not needing invasive ventilation, vasopressors, and RRT on the day of admission were included.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Performance was evaluated with area under the receiver operating characteristic curve (AUROC) and accuracy. RFCs performed better than XGBoost, SVM, and MLP models. For comparison, we evaluated LR models in the same cohorts. AUROC was very high ranging from 0.74 to 0.95 in predicting ventilation, vasopressors, and RRT use in our derivation and validation cohorts. ML used and variables such as Fio2, Glasgow Coma Scale, and mean arterial pressure to predict ventilator, vasopressor use, creatinine, and potassium to predict RRT use. LR was less accurate than ML, with AUROC ranging 0.66 to 0.8.

CONCLUSIONS

A ML algorithm more accurately predicts need of invasive ventilation, vasopressors, or RRT in hospitalized non-COVID-19 CAP and COVID-19 patients than regression models and could augment clinician judgment for triage and care of hospitalized CAP patients.

Performance of Artificial Intelligence Chatbots in Responding to Patient Queries Related to Traumatic Dental Injuries: A Comparative Study

BACKGROUND/AIM

Artificial intelligence (AI) chatbots have become increasingly prevalent in recent years as potential sources of online healthcare information for patients when making medical/dental decisions. This study assessed the readability, quality, and accuracy of responses provided by three AI chatbots to questions related to traumatic dental injuries (TDIs), either retrieved from popular question-answer sites or manually created based on the hypothetical case scenarios.

MATERIALS AND METHODS

A total of 59 traumatic injury queries were directed at ChatGPT 3.5, ChatGPT 4.0, and Google Gemini. Readability was evaluated using the Flesch Reading Ease (FRE) and Flesch-Kincaid Grade Level (FKGL) scores. To assess response quality and accuracy, the DISCERN tool, Global Quality Score (GQS), and misinformation scores were used. The understandability and actionability of the responses were analyzed using the Patient Education Materials Assessment Tool for Printed Materials (PEMAT-P) tool. Statistical analysis included Kruskal-Wallis with Dunn's post hoc test for non-normal variables, and one-way ANOVA with Tukey's post hoc test for normal variables (p < 0.05).

RESULTS

The mean FKGL and FRE scores for ChatGPT 3.5, ChatGPT 4.0, and Google Gemini were 11.2 and 49.25, 11.8 and 46.42, and 10.1 and 51.91, respectively, indicating that the responses were difficult to read and required a college-level reading ability. ChatGPT 3.5 had the lowest DISCERN and PEMAT-P understandability scores among the chatbots (p < 0.001). ChatGPT 4.0 and Google Gemini were rated higher for quality (GQS score of 5) compared to ChatGPT 3.5 (p < 0.001).

CONCLUSIONS

In this study, ChatGPT 3.5, although widely used, provided some misleading and inaccurate responses to questions about TDIs. In contrast, ChatGPT 4.0 and Google Gemini generated more accurate and comprehensive answers, making them more reliable as auxiliary information sources. However, for complex issues like TDIs, no chatbot can replace a dentist for diagnosis, treatment, and follow-up care.

Evaluating the influence of prompt formulation on the reliability and repeatability of ChatGPT in implant-supported prostheses

Language models (LLMs) such as ChatGPT are widely available to any dental professional. However, there is limited evidence to evaluate the reliability and reproducibility of ChatGPT-4 in relation to implant-supported prostheses, as well as the impact of prompt design on its responses. This constrains understanding of its application within this specific area of dentistry. The purpose of this study was to evaluate the performance of ChatGPT-4 in generating answers about implant-supported prostheses using different prompts. Thirty questions on implant-supported and implant-retained prostheses were posed, with 30 answers generated per question using general and specific prompts, totaling 1800 answers. Experts assessed reliability (agreement with expert grading) and repeatability (response consistency) using a 3-point Likert scale. General prompts achieved 70.89% reliability, with repeatability ranging from moderate to almost perfect. Specific prompts showed higher performance, with 78.8% reliability and substantial to almost perfect repeatability. The specific prompt significantly improved reliability compared to the general prompt. Despite these promising results, ChatGPT's ability to generate reliable answers on implant-supported prostheses remains limited, highlighting the need for professional oversight. Using specific prompts can enhance its performance. The use of a specific prompt might improve the answer generation performance of ChatGPT.

A Bibliometric Review of Person-Centered Care Research 2010-2024

Background/Objectives: Person-centered care (PCC) has become a pivotal concept in healthcare. At present, no published studies have assessed the PCC field using bibliometric tools. This study aimed to identify hot spots, trends, and developmental trajectories within the PCC field. Methods: Publications related to PCC from 2010 to 2024 were extracted from the Web of Science core collection database and analyzed by the Bibliometrix package from RStudio. Results: A total of 5837 studies were analyzed. The analysis revealed steady growth in PCC research, with the United Kingdom, Australia, and the USA leading in publication numbers. Frequent keywords included patient-centered care, PCC, and qualitative research. The thematic shift from patient-centered care to PCC highlights a growing emphasis on individual healthcare needs and values. The evolution of research themes related to PCC has varied across different time periods, with communication, quality improvement, multimorbidity, and chronic disease remaining underdeveloped during 2020-2024, indicating that these themes are key focuses for future research. Emerging keywords over the past five years-value-based healthcare; deep learning; telehealth; and COVID-19-suggest new research directions. Conclusions: This study provides a detailed overview of the PCC research landscape, highlighting key areas of focus and identifying potential directions for future research. The findings suggest a dynamic field with a growing emphasis on individualized care and the integration of new methodologies and themes to address current healthcare challenges.

Identifying zoonotic risks: molecular insights into Cryptosporidium and Enterocytozoon bieneusi in pediatric cancer patients in Ahvaz, 2024

Opportunistic infections remain a major cause of morbidity and mortality among patients with immunodeficiency and malignancy. Cryptosporidium spp. and microsporidia, particularly Enterocytozoon bieneusi, are obligate intracellular parasites that can lead to severe complications and even death in immunocompromised individuals.In this cross-sectional study, 60 stool samples were collected from pediatric oncology patients aged 5-18 years who were hospitalized at Baghaei 2 Hospital in Ahvaz, southwestern Iran, in 2024. Following DNA extraction, molecular analysis was performed to detect the presence of Cryptosporidium spp. and E. bieneusi. For genotyping, amplification and sequencing of the 60-kDa glycoprotein (gp60) gene for Cryptosporidium spp. and the internal transcribed spacer (ITS) region for E. bieneusi were conducted. A total of 16 samples (26.6%) tested positive for either C. hominis or E. bieneusi. Co-infection with both pathogens was identified in two patients (3%). Statistical analysis revealed no significant association between gender and parasitic infection (P = 0.166), nor between the type of malignancy and presence of protozoa (P = 0.717). Genotyping of E. bieneusi showed the presence of BEB6, CHG3, D, and I genotypes, with BEB6 being the most prevalent. Subtyping of C. hominis revealed the presence of the IeA11G3T3 subtype. Overall, the molecular findings demonstrated a prevalence rate 26.6 % of parasitic infection among the studied population, with E. bieneusi being predominant. The detection of potentially zoonotic genotypes, particularly BEB6, underscores the likelihood of zoonotic transmission routes in these patients.

Temporal Association Between ChatGPT-Generated Diarrhea Synonyms in Internet Search Queries and Emergency Department Visits for Diarrhea-Related Symptoms in South Korea: Exploratory Study

BACKGROUND

Diarrhea, a common symptom of gastrointestinal infections, can lead to severe complications and is a major cause of emergency department (ED) visits.

OBJECTIVE

This study explored the temporal association between internet search queries for diarrhea and its synonyms and ED visits for diarrhea-related symptoms.

METHODS

We used data from the National Emergency Department Information System (NEDIS) and NAVER (Naver Corporation), South Korea's leading search engine, from January 2017 to December 2021. After identifying diarrhea synonyms using ChatGPT, we compared weekly trends in relative search volumes (RSVs) for diarrhea, including its synonyms and weekly ED visits. Pearson correlation analysis and Granger causality tests were used to evaluate the relationship between RSVs and ED visits. We developed an Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX) model to further predict these associations. This study also examined the age-based distribution of search behaviors and ED visits.

RESULTS

A significant correlation was observed between the weekly RSV for diarrhea and its synonyms and weekly ED visits for diarrhea-related symptoms (ranging from 0.14 to 0.51, P<.05). Weekly RSVs for diarrhea synonyms, such as "upset stomach," "watery diarrhea," and "acute enteritis," showed stronger correlations with weekly ED visits than weekly RSVs for the general term "diarrhea" (ranging from 0.20 to 0.41, P<.05). This may be because these synonyms better reflect layperson terminology. Notably, weekly RSV for "upset stomach" was significantly correlated with weekly ED visits for diarrhea and acute diarrhea at 1 and 2 weeks before the visit (P<.05). An ARIMAX model was developed to predict weekly ED visits based on weekly RSVs for diarrhea synonyms with lagged effects to capture their temporal influence. The age group of <50 years showed the highest activity in both web-based searches and ED visits for diarrhea-related symptoms.

CONCLUSIONS

This study demonstrates that weekly RSVs for diarrhea synonyms are associated with weekly ED visits for diarrhea-related symptoms. By encompassing a nationwide scope, this study broadens the existing methodology for syndromic surveillance using ED data and provides valuable insights for clinicians.

The mediating effect of resilience and job satisfaction on the relationship between critical care nurses' stress-and task performance: findings to improve nursing care

BACKGROUND

Critical care nurses (CCNs) are exposed to stress, which may affect their performance. Resilience and job satisfaction are important factors in improving adaptation and work performance.

AIMS

This study aimed to ascertain the mediating effect of resilience and job satisfaction on the relationship between critical care nurses' stressand task performance among CCNs in Hail City, Saudi Arabia.

METHODS

A cross-sectional correlational design was used in critical and intensive care units in all governmental hospitals in Hail City, Saudi Arabia, from March to May 2024 for the 352 CCNs using a convenience sample selection method. Data were collected using the Global Satisfaction Scale, the Brief Nursing Stress Scale, the Task Performance Scale, and the Brief Resilience Scale. Multiple linear regression was used to identify key variables affecting nurses' task performance and job satisfaction. Path analysis was performed using AMOS 23.0, to ascertain the direct and indirect impacts of CCNs' task performance.

RESULTS

The results indicated that those who were non-Saudi, held bachelor's degrees, were registered nurses or supervisors, had less stress, and had more resilience were significant factors of higher task performance scores, whereas irregular shift duration was a factor of lower task performance scores (p < .05). Stress had an indirect negative impact on task performance through resilience and job satisfaction (β=-0.052, p < .001 and β=-0.115, p < .001, respectively). Furthermore, stress had a significant negative direct effect on task performance (β=-280, p < .001), with a total effect of (β=-0.447, p < .001).

CONCLUSION

Nurses' stress, resilience, job satisfaction, and task performance were intertwined with critical care nursing. Strategies are needed to implement effective programs for improving nurse resilience and well-being satisfaction, and to examine the multifaceted elements that impact nursing work in the harsh nursing critical care environment.

NURSING IMPLICATIONS

The results highlight the importance of organizational support, such as training and resources for resilience building, in alleviating stress and enhancing critical care nurses' overall satisfaction and performance.

CLINICAL TRIAL NUMBER

Not applicable.

Assessment of various artificial intelligence applications in responding to technical questions in endodontic surgery

BACKGROUND

The objective of this study was to evaluate the performance of ScholarGPT, ChatGPT-4o and Google Gemini in responding to queries pertaining to endodontic apical surgery, a subject that demands advanced specialist knowledge in endodontics.

METHODS

A total of 30 questions, including 12 binary and 18 open-ended queries, were formulated based on information on endodontic apical surgery taken from a well-known endodontic book called Cohen's pathways of the pulp (12th edition). The questions were posed by two different researchers using different accounts on the ScholarGPT, ChatGPT-4o and Gemini platforms. The responses were then coded by the researchers and categorised as 'correct', 'incorrect', or 'insufficient'. The Pearson chi-square test was used to assess the relationships between the platforms.

RESULTS

A total of 5,400 responses were evaluated. Chi-square analysis revealed statistically significant differences between the accuracy of the responses provided applications (χ² = 22.61; p < 0.05). ScholarGPT demonstrated the highest rate of correct responses (97.7%), followed by ChatGPT-4o with 90.1%. Conversely, Gemini exhibited the lowest correct response rate (59.5%) among the applications examined.

CONCLUSIONS

ScholarGPT performed better overall on questions about endodontic apical surgery than ChatGPT-4o and Gemini. GPT models based on academic databases, such as ScholarGPT, may provide more accurate information about dentistry. However, additional research should be conducted to develop a GPT model that is specifically tailored to the field of endodontics.

Characteristics of hepatitis B virus surface protein and occult hepatitis B infection in infants with immunoprophylaxis failure from Indonesia

Perinatal hepatitis B virus (HBV) infection carries a significant risk of chronicity and complications while making infected people reservoirs for further transmission. Hepatitis B immunization in infants, with or without hepatitis B immune globulin (HBIG), has proven effective in preventing mother-to-child transmission. Nevertheless, some newborns of mothers with high viremia testing positive for hepatitis B e antigen (HBeAg) may not benefit from HBV immunoprophylaxis. Nineteen (10.2 %) of 186 infants born to HBV-infected mothers were HBV DNA-positive. HBV genotypes, serotypes, and hepatitis B surface antigen (HBsAg) sequences were comparable in most mother-cord blood-infant sample pairings, indicating that the infants' HBV strains originated from their mothers. Three (15.3 %) infants had overt HBV infection, whereas 16 (84.2 %) had occult HBV infection (OBI). The HBV isolates from infants exhibited 26 mutations: 38.5 % in the 'a' determinant and 61.5 % in the rest of HBsAg. Mutations were identified in B-cell and T-cell epitopes, impairing humoral and cellular responses to detect or neutralize the virus. This rendered immunoprophylaxis and diagnostics ineffective while inducing tolerance to the infection. HBV strains with these mutations can persist and cause complications, but they can be transmitted undetected by HBsAg tests commonly used in community healthcare. This study reveals the risk of HBV transmission from HBsAg mutant-infected mothers to newborns despite having received the birth dose with HBIG and complete hepatitis B vaccination.

Global Burden of Rare Cancers: Insights from GLOBOCAN 2022 Estimates

Background: Rare cancers, defined as those with an incidence rate of fewer than 6 cases per 100,000 individuals, contribute to a substantial portion of the global cancer burden. Despite their impact, they receive less attention than more common malignancies, leading to challenges in early detection, treatment strategies, and research funding. This study aims to assess the global incidence and mortality patterns of rare cancers in 2022 to better understand their contribution to the overall cancer burden and regional disparities. Methods: We conducted a comprehensive analysis using 2022 GLOBOCAN estimates to assess the global incidence and mortality of rare cancers. The study included 24 major rare cancers, such as bladder cancer, leukemia, non-Hodgkin lymphoma, esophageal cancer, and pancreatic cancer. Age-standardized rates (ASRs) were calculated to compare cancer burden across continents, and absolute case and death counts were reported. Results: In 2022, rare cancers accounted for 26.7% of all new cancer cases (5,347,784 cases) and 30% of all cancer-related deaths (2,959,369 deaths) worldwide. Bladder cancer was the most common rare cancer, with an incidence rate of 5.58 per 100,000, followed by non-Hodgkin lymphoma (5.57) and leukemia (5.26). Mortality rates were highest for pancreatic, esophageal, and brain cancers, reflecting their aggressive nature and limited treatment options. Significant regional disparities were observed, with Europe and North America reporting the highest incidence rates for bladder cancer and leukemia, while Asia bore the largest absolute burden of rare cancers. Conclusions: Rare cancers represent a considerable share of the global cancer burden, with notable geographic variations in incidence and mortality. These findings underscore the need for improved early detection, expanded treatment access, and targeted research efforts to address disparities and improve outcomes for patients with rare cancers worldwide.

The Impact of Language Variability on Artificial Intelligence Performance in Regenerative Endodontics

BACKGROUND

Regenerative endodontic procedures (REPs) are promising treatments for immature teeth with necrotic pulp. Artificial intelligence (AI) is increasingly used in dentistry; thus, this study evaluates the reliability of AI-generated information on REPs, comparing four AI models against clinical guidelines.

METHODS

ChatGPT-4o, Claude 3.5 Sonnet, Grok 2, and Gemini 2.0 Advanced were tested with 20 REP-related questions from the ESE/AAE guidelines and expert consensus. Questions were posed in Turkish and English, with or without prompts. Two specialists assessed 640 AI-generated answers via a four-point rubric. Inter-rater reliability and response accuracy were statistically analyzed.

RESULTS

Inter-rater reliability was high (0.85-0.97). ChatGPT-4o showed higher accuracy with English prompts (p < 0.05). Claude was more accurate than Grok in the Turkish (nonprompted) and English (prompted) conditions (p < 0.05). No model reached ≥80% accuracy. Claude (English, prompted) scored highest; Grok-Turkish (nonprompted) scored lowest.

CONCLUSIONS

The performance of AI models varies significantly across languages. English queries yield higher accuracy. While AI shows potential for REPs information, current models lack sufficient accuracy for clinical reliance. Cautious interpretation and validation against guidelines are essential. Further research is needed to enhance AI performance in specialized dental fields.

Artificial Intelligence Chatbots as Sources of Implant Dentistry Information for the Public: Validity and Reliability Assessment

This study assessed the reliability and validity of responses from three chatbot systems-OpenAI's GPT-3.5, Gemini, and Copilot-concerning frequently asked questions (FAQs) in implant dentistry posed by patients.Twenty FAQs were prompted to three chatbots in three different times utilizing their respective application programming interfaces. The responses were assessed for validity (low and high threshold) and reliability by two prosthodontic consultants using a five-point Likert scale.The test of normality was utilized using the Shapiro-Wilk test. Differences between different chatbots regarding the quantitative variables in a given (fixed) time point and between the same chatbots in different time points were assessed using Friedman's two-way analysis of variance by ranks, followed by pairwise comparisons. All statistical analyses were conducted using the SPSS (Statistical Package for Social Sciences) Version 26.0 software program.GPT-3.5 provided the longest responses, while Gemini was the most concise. All chatbots advised consulting dental professionals more frequently. Validity was high under the low-threshold test but low under the high-threshold test, with Copilot scoring the highest. Reliability was high for all, with Gemini achieving perfect consistency.Chatbots showed consistent and generally valid responses with some variability in accuracy and details. While the chatbots demonstrated a high degree of reliability, their validity-especially under high-threshold criterion-remains limited. Improvements in accuracy and comprehensiveness are necessary for more effective use in providing information about dental implants.

Artificial intelligence in pediatric dental trauma: do artificial intelligence chatbots address parental concerns effectively?

BACKGROUND

This study focused on two Artificial Intelligence chatbots, ChatGPT 3.5 and Google Gemini, as the primary tools for answering questions related to traumatic dental injuries. The aim of this study to evaluate the reliability, understandability, and applicability of the responses provided by these chatbots to commonly asked questions from parents of children with dental trauma.

METHODS

The case scenarios were developed based on frequently asked questions that parents commonly ask their dentists or Artificial Intelligence chatbots regarding dental trauma in children. The quality and accuracy of the information obtained from the chatbots were assessed using the DISCERN Instrument. The understandability and actionability of the responses obtained from the Artificial Intelligence chatbots were assessed using the Patient Education Materials Assessment Tool for Printed Materials. In statistical analysis; categorical variables were analyzed in terms of frequency and percentage. For numerical variables, skewness and kurtosis values were calculated to assess normal distribution.

RESULTS

Both Artificial Intelligence chatbots performed similarly, although Google Gemini provided higher quality and more reliable responses. Based on the mean scores, ChatGPT 3.5 had a higher understandability. Both chatbots demonstrated similar levels of performance in terms of actionability.

CONCLUSION

Artificial Intelligence applications can serve as a helpful starting point for parents seeking information and reassurance after dental trauma. However, they should not replace professional dental consultations, as their reliability is not absolute. Parents should use Artificial Intelligence applications as complementary resources and seek timely professional advice for accurate diagnosis and treatment.

Myosteatosis and the survival of patients with hepatocellular carcinoma: a meta-analysis

Myosteatosis, characterized by fat infiltration into skeletal muscle, is increasingly recognized as a prognostic factor in hepatocellular carcinoma (HCC), although the results were not consistent. This meta-analysis aimed to summarize impact on overall survival (OS) and progression-free survival (PFS) in patients with HCC.A systematic search of PubMed, Embase, and Web of Science was conducted to identify observational studies reporting survival outcomes in HCC patients with and without myosteatosis. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated using a random-effects model. A total of 24 retrospective cohort studies involving 7436 HCC patients were included. Myosteatosis was significantly associated with poorer OS (HR: 1.60, 95% CI: 1.40-1.83, p < 0.001, I2 = 65%) and PFS (HR: 1.53, 95% CI: 1.33-1.76, p < 0.001, I2 = 36%). Subgroup analysis revealed a stronger association in Asian studies (HR: 1.74 for OS; 1.57 for PFS) compared to European studies (HR: 1.08 for OS; 1.05 for PFS). The prognostic impact remained significant regardless of anticancer treatment type, myosteatosis assessment method, sex-specific or universal cutoff values, and follow-up duration (p for subgroup differences all > 0.05). The results remained significant in studies adjusting for sarcopenia (HR: 1.89 for OS; 1.50 for PFS). Meta-regression analyses did not suggest any of the following variables may affect the results, including sample size, mean ages of the patients, proportions of men, follow-up durations, and study quality scores (p all > 0.05).Myosteatosis is independently associated with worse survival in HCC patients, particularly in Asian populations. These findings highlight the significance of assessing muscle quality as a prognostic factor in HCC.

The association between lifelines diet score and metabolic associated fatty liver disease: a case-control study

Introduction

Adherence to a healthy dietary pattern is a fundamental recommendation for the prevention of Metabolic Associated Fatty Liver Disease (MAFLD); however, conclusive evidence regarding the optimal dietary pattern remains elusive.

Objectives

The Lifelines Diet Score (LLDS) is a novel, evidence-based scoring system designed to evaluate diet quality. However, despite the extensive research on dietary patterns and liver health, the specific relationship between the LLDS and MAFLD remains underexplored. This study aims to investigate the association between LLDS and MAFLD, providing insights into how dietary adherence, as measured by LLDS, may influence the risk and prevalence of MAFLD.

Methods

This case-control study enrolled 215 individuals who had recently been diagnosed with MAFLD and 430 healthy controls at King Khalid University Hospital. All participants were aged between 20 and 60 years, with data collection occurring from February 2023 to January 2025. The dietary intake of the participants was assessed through the utilization of a validated semi-quantitative food frequency questionnaire, which comprised a total of 168 distinct food items. Logistic regression was used to estimate the association between LLDS and MAFLD.

Results

Out of 645 participants, 215 newly diagnosed MAFLD patients and 430 healthy controls were analyzed. After stratifying participants based on LLDS tertiles, those in the highest LLDS group had a 78% lower odds of MAFLD than those in the lowest tertile (odds ratio (OR): 0.22; 95% Confidence interval (CI): 0.12-0.36, p for trend <0.001). The association remained robust even after adjustment for major confounders. These findings highlight a novel and robust association between LLDS and MAFLD, providing evidence for dietary pattern assessment in liver health research.

Conclusion

Our study strengthens the evidence that adherence to a healthy dietary pattern (as measured by LLDS) is associated with a lower MAFLD risk, even after accounting for major confounders. However, further research integrating genetic and molecular data is needed to refine personalized dietary recommendations for MAFLD prevention.

Worldwide Impact of Upper Gastrointestinal Disease in Familial Adenomatous Polyposis

Familial adenomatous polyposis (FAP) is the most common hereditary colorectal adenomatous polyposis and cancer syndrome which has historically been associated with a near absolute risk of colorectal cancer. However, the morbidity and mortality from colorectal cancer has been greatly diminished by pre-symptomatic genetic testing which identifies affected individuals and by appropriately timed, risk-reducing surgery of the colorectum. Following colorectal surgery, cancer risk beyond the retained rectum or ileal pouch includes other gastrointestinal organs, especially those of the upper gastrointestinal tract. While genotype-phenotype correlations exist for the severity of colonic polyposis, they have not been demonstrated for upper gastrointestinal tract manifestations. We reviewed the impact of ethnicity on the upper gastrointestinal manifestations of FAP by a comparison of published data in patients with FAP from Asian and Western countries. Our main findings demonstrate that following risk-reducing surgery to mitigate colorectal cancer risk, patients with FAP remain at increased risk for upper gastrointestinal polyposis and cancer. The duodenal and gastric phenotype differs between patients with FAP from the West and the East, and all should be followed in a multidisciplinary surveillance program. Following risk-reducing surgery to mitigate colorectal cancer risk, patients with familial adenomatous polyposis remain at increased risk for upper gastrointestinal polyposis and cancer. The duodenal and gastric phenotype differs between patients with FAP from the West and the East, and all should be followed in a multidisciplinary surveillance program.

Combining lipidomics and machine learning to identify lipid biomarkers for nonsyndromic cleft lip with palate

Nonsyndromic cleft lip with palate (nsCLP) is a common birth defect disease. Current diagnostic methods comprise fetal ultrasound images, which are mainly limited by fetal position and technician skills. We aimed to identify reliable maternal serum lipid biomarkers to diagnose nsCLP. Eight-feature selection methods were used to assess the dysregulated lipids from untargeted lipidomics in a discovery cohort. The robust rank aggregation algorithm was applied on these selected lipids. The data were subsequently processed using 7 classification models to retrieve a panel of 35 candidate lipid biomarkers. Potential lipid biomarkers were evaluated using targeted lipidomics in a validation cohort. Seven classification models and multivariate analyses were constructed to identify the lipid biomarkers for nsCLP. The diagnostic model achieved high performance with 3 lipids in determining nsCLP. A panel of 3 lipid biomarkers showed great potential for nsCLP diagnosis. FA (20:4) and LPC (18:0) were also significantly downregulated in early serum samples from the nsCLP group in the additional validation cohort. We demonstrate the applicability and robustness of a machine-learning algorithm to analyze lipidomic data for efficient and reliable biomarker screening.

Survival status and predictors of mortality among patients with breast cancer in Ethiopia: a systematic review and meta-analysis

OBJECTIVES

This study aimed to evaluate survival outcomes and identify key mortality predictors among patients with breast cancer in Ethiopia.

STUDY DESIGN

A systematic review and meta-analysis.

STUDY PARTICIPANTS

The study used 11 primary studies, involving a total of 4131 participants.

DATA SOURCES

We searched PubMed, Embase, Web of Science, Scopus and Google Scholar until 7 March 2025, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

All observational studies that had reported the survival status and/or at least one predictor of mortality of women patients with breast cancer were considered.

DATA EXTRACTION AND SYNTHESIS

Three independent reviewers (HA, HKN and DGA) used a structured data extraction form to extract the data. To compute the pooled survival and mortality rates, the survival rates at different observation periods and the mortality rates reported in the included studies were extracted.

RESULTS

Eleven studies were analysed. All studies were of good quality based on Newcastle-Ottawa Scale. However, heterogeneity was high (I² = 98.2%, p=0.00). Funnel plots showed significant publication bias. The Grading of Recommendations, Assessment, Development, and Evaluations assessment indicated moderate certainty for mortality rates and predictors, limited by heterogeneity and regional data gaps. The pooled mortality rate was 36% (95% CI: 25% to 46%). The survival rates at 1, 3 and 5 years were 85% (95% CI: 75% to 96%), 66% (95% CI: 48% to 84%) and 22% (95% CI: 1% to 43%), respectively. Key mortality predictors included advanced clinical stage (Adjusted Hazard Ratio (AHR): 4.14; CI: 2.53 to 6.78), rural residence (AHR: 1.65; 95% CI: 1.27 to 2.14), positive lymph node status (AHR: 2.85; 95% CI: 1.50 to 5.44), no hormonal therapy (AHR: 2.02; 95% CI: 1.59 to 2.56), histologic grade III (AHR: 1.76; 95% CI: 1.29 to 2.41), hormone receptor negativity (AHR: 1.54; 95% CI: 1.05 to 2.25) and comorbidities (AHR: 2.24; 95% CI: 1.41 to 3.56).

CONCLUSION

Breast cancer in Ethiopia poses a high mortality rate primarily due to late-stage diagnosis, rural residency, histologic grade III, positive lymph node status and comorbidities. To improve survival outcomes, it is crucial to expand access to early screening, particularly in rural areas, implement comprehensive treatment protocols and strengthen healthcare infrastructure to address these critical factors.

PROSPERO REGISTRATION NUMBER

CRD42024575074.

Investigation of cagA, dupA and babA genes among clinical Helicobacter pylori isolates collected from patients suffering from H. pylori gastric disease using real-time PCR

BACKGROUND

Helicobacter pylori (H. pylori) infection causes chronic gastritis and can lead to severe gastrointestinal diseases, including stomach ulcers, stomach cancer, and mucosa-associated lymphoid tissue (MALT) lymphoma. This infection affects about half of the world's population, with varying prevalence based on location and hygiene standards. Determining the importance of H. pylori pathogenic genes in predicting clinical outcomes is crucial, especially considering high rates of stomach cancer in Middle Eastern and Asian populations. The main aim of this study was to determine the frequency of the babA, cagA, and dupA pathogenic genes in H. pylori isolates obtained from patients with gastrointestinal diseases.

METHODS

A urease test was conducted on 111 biopsies from the antrum of patients undergoing endoscopies at Tehran hospitals. Following this, an extraction kit was used, and the Real-time PCR technique determined the frequency of the babA, cagA, and dupA genes.

RESULTS

Out of 111 stomach biopsies, 70 tested positive for H. pylori. Molecular analysis showed that the frequency of babA, cagA, and dupA genes was 51 (72.8 %), 35 (50 %), and 26 (37.14 %), respectively.

CONCLUSION

The results showed that babA and cagA genes were identified with a higher abundance among patients and the findings suggest that the presence of these genes could be considered a risk indicator for exacerbation of gastrointestinal disease. Additionally, the dupA gene was found with lower frequency, which is less likely to play a significant role in pathogenicity compared to other genes. This study could help develop more effective prevention and treatment methods in the future.

Intravenous and subcutaneous vedolizumab for moderately to severely active ulcerative colitis in Iran: a model-based cost-effectiveness evaluation

OBJECTIVE

To evaluate the cost-effectiveness of intravenous and subcutaneous vedolizumab compared to infliximab for moderately to severely active ulcerative colitis (UC) from an Iranian societal perspective.

METHODS

A decision-analytic cost-utility model was developed using a decision tree and a Markov model. Direct and indirect costs were calculated. Treatment effectiveness and health state utility values were extracted from published literature. Effects were estimated using quality-adjusted life-years (QALYs). Costs and QALYs were projected over a lifetime and discounted at 3% per year. Deterministic and probabilistic sensitivity analyses were performed to evaluate uncertainties.

RESULTS

In base-case analysis, infliximab was associated with $28,888.5 costs and 15.17 QALYs. Vedolizumab was associated with 15.34 QALYs and costs of $27,916.90 for IV (induction and maintenance) and $28,200.40 for IV (induction) followed by SC (maintenance). The ICERs were estimated at -$5673.3/QALY and -$4,017.8/QALY, remaining negative across all sensitivity analyses. The cost of infliximab and vedolizumab and the probability of response to vedolizumab during maintenance were the key determinants of cost-effectiveness.

CONCLUSIONS

Vedolizumab (both IV and SC) resulted in reduced costs and improved QALYs compared to infliximab for moderate to severe UC in Iran. Therefore, we recommended including vedolizumab in the Iranian national formulary as a cost-effective treatment strategy.

Information from digital and human sources: A comparison of chatbot and clinician responses to orthodontic questions

INTRODUCTION

This study aimed to investigate whether artificial intelligence (AI)-based chatbots can be used as reliable adjunct tools in orthodontic practice by evaluating chatbot responses and comparing them to those of clinicians with varying levels of knowledge.

METHODS

Large language model-based chatbots (ChatGPT-4, ChatGPT-4o, Microsoft Copilot, Google Gemini 1.5 Pro, and Claude 3.5 Sonnet) and clinicians (dental students, general dentists, and orthodontists; n = 30) were included. The groups were asked 40 true and false questions, and the accuracy rate for each question was assessed by comparing it to the predetermined answer key. The total score was converted into a percentage. The Kruskal-Wallis test and Dunn's multiple comparison tests were used to compare accuracy rates. The consistency of the answers given by chatbots at 3 different times was assessed by Cronbach α.

RESULTS

The accuracy ratio scores for students were significantly lower than Microsoft Copilot (P = 0.029), Claude 3.5 Sonnet (P = 0.023), ChatGPT-4o (P = 0.005), and orthodontists (P = 0.001). For dentists, the accuracy ratio scores were found to be significantly lower than ChatGPT-4o (P = 0.019) and orthodontists (P = 0.001). The accuracy rate of ChatGPT-4o was closest to that of orthodontists, whereas the accuracy rates of ChatGPT-4, Microsoft Copilot, Claude 3.5 Sonnet, and Google Gemini 1.5 Pro were lower than orthodontists but higher than general dentists. Although ChatGPT-4 demonstrated a high degree of consistency in its responses, evidenced by a high Cronbach α value (α = 0.867), ChatGPT-4o (α = 0.256) and Claude 3.5 Sonnet (α = 0.256) were the least consistent chatbots.

CONCLUSIONS

The study found that orthodontists had the highest accuracy rate, whereas AI-based chatbots had a higher accuracy rate compared with dental students and general dentists. However, ChatGPT-4 gave the most consistent answers, whereas ChatGPT-4o and Claude 3.5 Sonnet showed the least consistency. AI-based chatbots can be useful for patient education and general orthodontic guidance, but a lack of consistency in responses can lead to the risk of misinformation.

Genomics and integrative clinical data machine learning scoring model to ascertain likely Lynch syndrome patients

BACKGROUND

Lynch syndrome (LS) screening methods include multistep molecular somatic tumor testing to distinguish likely-LS patients from sporadic cases, which can be costly and complex. Also, direct germline testing for LS for every diagnosed solid cancer patient is a challenge in resource limited settings. We developed a unique machine learning scoring model to ascertain likely-LS cases from a cohort of colorectal cancer (CRC) patients.

METHODS

We used CRC patients from the cBioPortal database (TCGA studies) with complete clinicopathologic and somatic genomics data. We determined the rate of pathogenic/likely pathogenic variants in five (5) LS genes (MLH1, MSH2, MSH6, PMS2, EPCAM), and the BRAF mutations using a pre-designed bioinformatic annotation pipeline. Annovar, Intervar, Variant Effect Predictor (VEP), and OncoKB software tools were used to functionally annotate and interpret somatic variants detected. The OncoKB precision oncology knowledge base was used to provide information on the effects of the identified variants. We scored the clinicopathologic and somatic genomics data automatically using a machine learning model to discriminate between likely-LS and sporadic CRC cases. The training and testing datasets comprised of 80% and 20% of the total CRC patients, respectively. Group regularisation methods in combination with 10-fold cross-validation were performed for feature selection on the training data.

RESULTS

Out of 4800 CRC patients frorm the TCGA datasets with clinicopathological and somatic genomics data, we ascertained 524 patients with complete data. The scoring model using both clinicopathological and genetic characteristics for likely-LS showed a sensitivity and specificity of 100%, and both had the maximum accuracy, area under the curve (AUC) and AUC for precision-recall (AUCPR) of 1. In a similar analysis, the training and testing models that only relied on clinical or pathological characteristics had a sensitivity of 0.88 and 0.50, specificity of 0.55 and 0.51, accuracy of 0.58 and 0.51, AUC of 0.74 and 0.61, and AUCPR of 0.21 and 0.19, respectively.

CONCLUSIONS

Simultaneous scoring of LS clinicopathological and somatic genomics data can improve prediction and ascertainment for likely-LS from all CRC cases. This approach can increase accuracy while reducing the reliance on expensive direct germline testing for all CRC patients, making LS screening more accessible and cost-effective, especially in resource-limited settings.

The epidemiological trends and projected future of primary sclerosing cholangitis by 2040: An updated meta-analysis and modeling study

BACKGROUND AND AIMS

Primary sclerosing cholangitis (PSC) exhibits varying incidence and prevalence rates across different regions; however, comprehensive global studies examining its geographic distribution and future trends are scarce. This study presents an updated meta-analysis through 2024 and projects the global and regional prevalence of PSC from 2024 to 2040 using an illness-death multi-state model.

METHODS

We conducted a thorough systematic search across multiple databases to identify all primary studies published until 2024 that reported on the incidence, prevalence, and mortality rates of PSC in various regions. Using the gathered data, we developed an illness-death model to forecast the future prevalence of PSC, covering the years 2024-2040.

RESULTS

Our meta-analysis revealed that the global pooled incidence and prevalence rates of PSC are 0.65 and 7.52 per 100,000 persons, respectively. Projections indicate that the global prevalence of PSC will rise to 22.98 cases per 100,000 (95% CI: 21.0-24.95), corresponding to an overall increase of 28.3%. Specifically, North America is forecasted to experience a 5.45% increase in PSC cases, reaching 24.76 cases per 100,000 (95% CI: 19.63-29.88), while Western Europe is anticipated to see a more pronounced rise of 28.79%, resulting in a prevalence of 21.48 cases per 100,000 (95% CI: 18.3-24.65) by 2040.

CONCLUSIONS

Our findings indicate a substantial rise in the number of individuals affected by PSC in recent years and estimate a significant future burden of the disease.

Evaluating Large Language Models in Addressing Patient Questions on Endodontic Pain: A Comparative Analysis of Accessible Chatbots

INTRODUCTION

Patients increasingly use large language models for health-related information, but their reliability and usefulness remain controversial. Continuous assessment is essential to evaluate their role in patient education. This study evaluates the performance of ChatGPT-3.5 and Gemini in answering patient inquiries about endodontic pain.

METHODS

A total of 62 frequently asked questions on endodontic pain were categorized into etiology, symptoms, management, and incidence. Responses from ChatGPT 3.5 and Gemini were assessed using standardized tools, including the Global Quality Score (GQS), Completeness, Lack of false information, Evidence supported, Appropriateness and Relevance reliability tool, and readability indices (Flesch-Kincaid and Simple Measure of Gobbledygook).

RESULTS

Compared to Gemini, ChatGPT 3.5 responses scored significantly higher in terms of overall quality (GQS: 4.67-4.9 vs 2.5-4, P < .001) and reliability (Completeness, Lack of false information, Evidence supported, Appropriateness and Relevance: 23.5-23.6 vs 19.35-22.7, P < .05). However, it required a higher reading level (Simple Measure of Gobbledygook: 14-17.6) compared to Gemini (8.7-11.3, P < .001). Gemini's responses were more readable (6th-7th grade level) but lacked depth and completeness.

CONCLUSION

While ChatGPT 3.5 outperformed Gemini in quality and reliability, its complex language reduced accessibility. In contrast, Gemini's simpler language enhanced readability but sacrificed comprehensiveness. These findings highlight the need for professional oversight in integrating artificial intelligence-driven tools into healthcare communication to ensure accurate, accessible, and empathetic patient education.

Dietary inflammatory index and the risk of esophageal cancer: a systematic review and meta-analysis

BACKGROUND AND AIM

It is well-recognized that inflammation is an adaptive pathophysiological response in many types of cancer. Research on nutrition's critical role in inflammation, a risk factor for all forms of cancer, is growing. The dietary inflammatory index (DII) was created lately to assess if a diet is pro- or anti-inflammatory in terms of inflammation. Indeed, several studies have demonstrated the correlation between DII and the risk of several cancer types. This meta-analysis set out to look into the relationship between DII and the different forms of esophageal cancer.

METHOD

PubMed, Cochrane library, Embase, Scopus, and Web of Science databases were searched up to May 2024 to retrieve relevant articles. RAYYAN intelligent tool for systematic reviews was incorporated for the screening of studies. Original articles written in English Studies that investigated the inflammatory index of diet in individuals who developed esophageal cancer were included in this study.STATA v18 software was used to conduct the meta-analysis. Egger's test for publication bias assessment was implemented. Newcastle Ottawa scale was used to evaluate the qualities of the included studies. A plot digitizer was used to extract digital data.

RESULT

A total of 13 studies were included in the systematic review, with 6 studies contributing to the meta-analysis, comprising 10,150 participants. The participants were categorized into high and low DII groups, with the low DII group (n = 3,403) serving as the reference. The meta-analysis demonstrated a significant association between high DII and increased risk of esophageal cancer. Specifically, individuals in the high DII group were 29% more likely to develop esophageal cancer, with a pooled odds ratio (OR) of 1.29 (95% Confidence Interval [CI]: 1.16-1.43), as calculated using a random-effects model. Moderate heterogeneity was observed (I2 > 50%). Egger's test indicated evidence of publication bias (p < 0.05). Subgroup and sensitivity analyses confirmed the robustness of this association across populations and study designs.

CONCLUSION

our study concludes that a higher level of DII is associated with a higher risk of esophageal cancer development. This study suggests that modifying inflammatory properties of dietary patterns can reduce the risk of incidence of esophageal cancer.

Discovery of 1-phenyl-1,2,3-triazole ureas as dual VEGFR-2/JNK-1 type II kinase inhibitors targeting pancreatic cancer

In oncology, pancreatic cancer (PC) continues to be a problem that requires creative approaches to therapy. This research aims to create dual kinase inhibitors that target VEGFR-2 and JNK-1, two important factors in the angiogenesis and progression of PC. We found compounds with promising anticancer action using phenyltriazolyl piperazine/(piperidine) carboxamides (PTPCs) and phenyltriazolyl phenylureas (PTPUs). Compound 12b was the most effective in inhibiting VEGFR-2 (IC50: 46 nM) and JNK-1 (IC50: 35 nM) and showed the highest activity against PANC-1 cancer cells (IC50: 1.05 μM). Furthermore, 12b altered the caspase-3, Bcl-2, and Bax apoptotic markers. The binding interactions of 12b with target kinases were discovered by in silico investigations. This study emphasizes how dual kinase inhibitors may be a viable way to improve the effectiveness of cancer treatments and deal with resistance mechanisms.

Unraveling the Serum Protein Landscape in Celiac Disease: Current Evidence and Future Directions

BACKGROUND

Celiac disease (CD) is a chronic autoimmune disorder characterized by an abnormal immune response to gluten, leading to intestinal inflammation and various clinical manifestations. Serum proteins are increasingly recognized as potential biomarkers in CD, reflecting inflammation, malabsorption, and immune activation.

OBJECTIVE

This review aims to elucidate the role of serum proteins in the pathogenesis, diagnosis, and management of CD, emphasizing their potential as noninvasive biomarkers and therapeutic targets.

METHODS

A comprehensive review of current literature was conducted, focusing on key serum proteins such as albumin, transthyretin (TTR), transferrin, β2-microglobulin (β2M), C-reactive protein (CRP), and immunoglobulins. Their alterations in CD and their relevance to disease activity, nutritional status, and treatment response were examined.

RESULTS

CD-related inflammation leads to increased acute-phase proteins (e.g., CRP) and decreased transport proteins (e.g., albumin, TTR, transferrin), contributing to malnutrition and anemia. TTR serves as a sensitive marker of nutritional status, while transferrin levels correlate with iron deficiency, a common CD complication. Immunoglobulin profiles reflect immune responses to gluten. These proteins provide insights into CD pathophysiology and offer potential utility for diagnosis and monitoring.

CONCLUSION

Serum proteins represent promising biomarkers for CD diagnosis and management, with potential for integration into clinical practice. Further research is necessary to validate their utility in routine patient care and explore their role in personalized therapeutic strategies.

Self-efficacy as a psychological resource in the management of stress suffered by ICU nurses during the COVID-19 pandemic: A prospective study on emotional exhaustion

BACKGROUND

Intensive care unit (ICU) nurses have experienced a high degree of stress during the COVID-19 pandemic. While the literature on the consequences on emotional symptomatology is abundant, studies on the protective psychosocial variables that have contributed to buffering these consequences are scarcer.

AIM

This study analyses the role of self-efficacy as a protective personality trait in ICU nurses during the COVID-19 pandemic, using a moderated mediation model that begins with the stress and anxiety experienced at the onset of the pandemic and concludes with the emotional exhaustion experienced 6 months later.

STUDY DESIGN

Prospective longitudinal study with two data collection periods during the COVID-19 pandemic: (1) from 5 May to 21 June 2020 and (2) a follow-up 6 months after the state of alarm finalized (January-April 2021). These were both very stressful periods for ICU staff because of the COVID-19 pandemic. This study was conducted with 129 ICU nurses (a non-probabilistic convenience sample in the Spanish health care system). Socio-demographic, occupational and psychosocial variables (i.e. stress, anxiety, self-efficacy and emotional exhaustion) were assessed. Descriptive analyses, Pearson correlations, covariate analyses (i.e. Student's t-test, one-factor ANOVA) and moderated mediation analyses were carried out (SPSS PROCESS macro, model 7). STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) reporting guidelines were followed.

RESULTS

It shows that the higher the self-efficacy score, the lower the effect of stress on anxiety (p < .001); likewise, the moderating role of self-efficacy was equally valid for the whole final model (F = 8.790, p < .001), showing self-efficacy to be a good buffer for emotional exhaustion derived from the stress suffered in the ICU.

CONCLUSIONS

Self-efficacy (i.e. the belief of being able to do certain tasks successfully) is shown to be a highly relevant trait to enhance among ICU nurses during the COVID-19 pandemic, allowing them to manage work stress effectively and thus buffering the development of anxiety in the short term and emotional exhaustion in the long term.

RELEVANCE TO CLINICAL PRACTICE

Our results point to the need to assess and take action on self-efficacy in ICU nurses in highly stressful situations such as the COVID-19 pandemic. As a psychological variable, self-efficacy refers to beliefs and therefore has to be trained by evidence-based psychological techniques, such as cognitive behavioural therapy. In addition, previous literature has pointed out that previous experience or specific training is an influential (although not a determining) factor in self-efficacy, so specialization for ICU nurses could also be considered.

Performance of 4 Artificial Intelligence Chatbots in Answering Endodontic Questions

INTRODUCTION

Artificial intelligence models have shown potential as educational tools in healthcare, such as answering exam questions. This study aimed to assess the performance of 4 prominent chatbots: ChatGPT-4o, MedGebra GPT-4o, Meta LIama 3, and Gemini Advanced in answering multiple-choice questions (MCQs) in endodontics.

METHODS

The study utilized 100 MCQs, each with 4 potential answers. These MCQs were obtained from 2 well-known endodontic textbooks. The performance of the above chatbots regarding choosing the correct answers was assessed twice with a 1-week interval.

RESULTS

The stability of the performance in the 2 rounds was highest for ChatGPT-4o, followed by Gemini Advanced and Meta Llama 3. MedGebra GPT-4o provided the highest percentage of true answers in the first round (93%) followed by ChatGPT-4o in the second round (90%). Meta Llama 3 provided the lowest percentages in the first (73%) and second rounds (75%). Although the performance of MedGebra GPT-4o was the best in the first round, it was less stable upon the second round (McNemar P > .05; Kappa = 0.725, P < .001).

CONCLUSIONS

ChatGPT-4o and MedGebra GPT-4o answered a high fraction of endodontic MCQs, while Meta LIama 3 and Gemini Advanced showed lower performance. Further training and development are required to improve their accuracy and reliability in endodontics.

Risk factors of anxiety, depression, stress, job burnout, and characteristics of sleep disorders in critical care nurses: An observational study

AIM/OBJECTIVE

The aim of this study was to determine risk factors and associations between anxiety, depression, stress, and job burnout and describe sleep disorders in critical care nurses.

SETTING

Data were collected in six intensive care units.

METHODS

A descriptive cross-sectional design was used. Multivariate and univariate regressions were used to determine significant risk factors. Significance levels were established at p <0.05. We use Depression Anxiety Stress Scales to determine anxiety, depression, and stress. Work burnout was detected using the Maslach Burnout Inventory scale, and sleep quality was determined by the Pittsburgh Sleep Quality Index.

RESULTS

A total of 140 critical care nurses were included. The female gender was associated with high levels of anxiety (odds ratio [OR] = 3.03; 95% confidence interval [CI] = [1.12-8.23]; p = 0.029), depression (OR = 10.55; 95% CI = [2.17-51.19]; p = 0.003), and stress (OR = 2.87; 95% CI = [1.02-8.07]; p = 0.045). Multivariate regression showed that critical care nurses with intention of leaving were exposed to high levels of anxiety (OR = 3.65; 95% CI = [1.40-9.53]; p = 0.008), depression (OR = 6.79; 95% CI = [2.01-22.95]; p = 0.002), stress [OR = 4.13; 95% CI = [1.49-11.45]; p = 0.006), and burnout (OR = 4.15; 95% CI = [1.63-10.56]; p = 0.003). Sleep quality is influenced by high latency, low duration, the use of medications, and daytime dysfunction.

CONCLUSION

Females were exposed to a higher risk of developing mental health problems such as anxiety, depression, and stress than men. The intention to leave was an independent predictor of anxiety, depression, and stress. Characteristics such as high sleep latency, low duration, use of medications, and daytime dysfunction have a negative impact on sleep quality. Early detection of mental health would allow nursing managers to implement nonpharmacological preventive interventions to improve well-being at work.

Chronically increased osteoclastogenesis in adult celiac disease patients does not hinder improvement in bone health induced by gluten-free diet: Role of vitamin D, OPG and IL-6

The etiology of bone loss in celiac disease (CeD) remains a clinical challenge, with uncertainties present such as the extent of involvement of malabsorption and inflammation-induced osteoresorption processes in development of osteopenia/osteoporosis (OPN/OP), or reasons for failure to achieve healthy bone mass (BMD) even after long-term gluten-free diet (GFD) treatment. This observational prospective study explores the in vitro osteoclastogenic potential of peripheral blood precursors originating from adult active (newly diagnosed and untreated) celiac disease patients (aCeD) and describes the longitudinal changes in osteoclastogenesis after long-term adherence to GFD. To find connections between in vitro observations and in vivo bone metabolism changes, serum levels of 25(OH)D3, PTH, bCTX, PINP, CRP, IL-6, RANKL and OPG were measured before and after GFD and levels of these markers were correlated with the rate of osteoclastogenesis in vitro. OPG and IL-6 showed associations with BMD and/or presence of OPN/OP. Patients after GFD (CeD-GFD) exhibited improved BMD and increased serum 25(OH)D3 levels, alongside reduced bCTX and PINP levels. Compared to healthy donors, aCeD osteoclast genesis in vitro was higher and, surprisingly, remained elevated even in CeD-GFD patients. Negative correlation was found between osteoclastogenesis rate and serum OPG in aCeD, while osteoclastogenesis rate positively correlated with PTH in CeD-GFD. These results highlight OPG as marker for risk of OPN/OP in CeD and suggest that improvement of BMD after GFD is a result of uncoupling between bone metabolism and osteoresorptive action of osteoclasts after GFD.

Uncovering the role of TREM-1 in celiac disease: In silico insights into the recognition of gluten-derived peptides and inflammatory mechanisms

BACKGROUND

Celiac disease (CD) is a chronic enteropathy characterized by a permanent intolerance to gluten. While CD has been associated with heightened T cell responses and the involvement of distinct innate immunity components, the role of the triggering receptor expressed on myeloid cells (TREM) family in this disease remains unclear. Thus, as TREM-1 has already been implicated in other inflammatory bowel diseases, and given its role in the amplification of inflammation, we hypothesized that it might play a role in the pathophysiology of CD.

METHODS AND RESULTS

the STRING tool was used to predict protein-protein interaction networks between TREM-1 and CD signaling pathways. Then, molecular docking and molecular dynamics simulations were conducted to explore potential interactions between TREM-1 and different peptides derived from alpha-gliadin (25-mer, 33-mer and p31-43). Finally, we used transcriptomic data, available from public repositories, to assess TREM1 gene expression, and genes involved in its signaling pathway, in CD patients. Our results found an association between TREM-1 and CD markers, with STRING analysis, and the in silico simulations suggesting that the receptor might recognize the alpha-gliadin peptides, with the TREM-1/p31-43 interaction as the most likely interaction to occur biologically. Furthermore, TREM1 and its signaling pathway were increased in patients with active CD, while in those in clinical remission, the expression levels were similar to healthy controls.

CONCLUSIONS

collectively, our findings suggest that TREM-1 might recognize alpha-gliadin derived peptides, and TREM-1's activation may contribute to the intestinal inflammation observed in CD.

Mucin 5AC as a Biomarker for Sessile Serrated Lesions: Results From a Systematic Review and Meta-Analysis

INTRODUCTION

Sessile serrated lesions (SSLs) are a class of colon polyps challenging to detect through current screening methods but highly associated with colon cancer. To improve detection, we sought a biomarker sensitive for SSLs. Recent endoscopic and histopathologic studies suggest that SSLs are associated with alterations in intestinal mucin expression, but the frequency with which this occurs is not known.

METHODS

We performed a meta-analysis of available pathologic studies comparing mucin expression on SSLs to normal colonic mucosa, tubular adenomas, villous adenomas, traditional serrated adenomas (TSAs), and hyperplastic polyps (HPs). We searched Medline, Pubmed, and Embase and found 440 publications in this topic, and 18 total studies met inclusion.

RESULTS

We found that MUC5AC expression was more common in SSLs compared to normal colonic mucosa (OR = 82.9, P < 0.01), tubular adenoma (OR = 11, P < 0.01), and TSAs (OR = 3.6, P = 0.04). We found no difference in MUC5AC expression between SSLs versus HPs (OR = 2.1, P = 0.09) and no difference in MUC5AC expression between left colon and right colon HPs, with an OR = 1.8, P = 0.23.

DISCUSSION

We found that MUC5AC expression was found commonly on villous adenoma, SSLs, and TSAs while the frequency on colon cancers declined. MUC5AC is also upregulated in inflammatory bowel disease and in response to intestinal infections. MUC5AC expression highlights the potential of mucins as useful biomarkers, though not specific to SSLs. Further research into the clinical utility of MUC5AC as a pathologic or fecal biomarker could enhance SSL detection.

Relationship between death anxiety and resilience among critical care nurses in Oman

BACKGROUND

Critical care nurses encounter numerous work-related stressors that might lead to depression and anxiety. Areas with higher patient mortality can lead to burnout, higher turnover and death anxiety. The possession of resilience and good attitudes towards mental health is of utmost importance for nurses, given their role as influential figures within society.

AIM

The aim of this study was to examine the relationship between death anxiety and resilience among critical care nurses in Oman.

STUDY DESIGN

This study employed a cross-sectional design with convenience sampling, sending 300 invitations via a URL link on a popular social media platform for critical care nurses in Oman. Out of 218 responses, the initial response rate was 72.7%. After data cleansing to remove incomplete and illegible submissions, the final sample consisted of 183 nurses who completed the Templer Death Anxiety Scale and the Connor-Davidson Resilience Scale (CD-RISC). The survey was conducted in December 2023.

RESULTS

The study found that the mean death anxiety and resilience scores were 38.23 (SD = 6.96) and 37.62 (SD = 5.32), respectively. Most of the participants exhibited a low level of death anxiety and a moderate level of resilience. The results of this study found a significant proportional correlation between death anxiety and resilience among critical care nurses in Oman (p = .000); nurses with a higher degree of resilience were shown to be significantly correlated with a lower level of death anxiety. The results showed that resilience explained 14.9% of the variation in death anxiety.

CONCLUSIONS

The research in Oman reveals that critical care nurses in the country experience moderate death fear. This anxiety stems from the demanding nature of their profession, which involves providing care for critically ill patients in high-pressure environments. Factors such as cultural and religious beliefs and educational attainment are also influencing this anxiety. Resilience is positively associated with the ability to confront challenges with courage, and a positive correlation exists between resilience and death anxiety. This suggests that nurses with higher resilience may also experience higher death anxiety because of their profession's inherent responsibilities and decision-making.

RELEVANCE TO CLINICAL PRACTICE

The study on critical care nurses in Oman highlights that workplace stress and high death anxiety negatively impact their well-being and patient care quality. Factors like job demands, cultural beliefs and education influence these experiences, with resilience playing a key role in coping. Enhancing resilience and coping strategies can improve care quality and reduce turnover in nursing.

Global status of research on quality of life in pancreatic cancer patients: A bibliometric and network analysis from 2005-2024

BACKGROUND

Pancreatic cancer (PC) is a major global health challenge, with rising incidence and mortality rates, particularly in high-socio-demographic index regions. Given its high mortality and significant morbidity, research on patient quality of life (QoL) has gained momentum, addressing symptom burdens, psychological distress, and treatment-related outcomes. Bibliometric analysis provides a valuable approach to mapping research trends, identifying key contributors, and forecasting future directions.

OBJECTIVE

This study aimed to map global research on QoL in pancreatic cancer patients, highlighting key findings, challenges, and future directions through bibliometric analysis over the past two decades.

METHODS

Data for this study were collected from the Web of Science Core Collection (WoSCC) database, using specific search strategies to retrieve relevant documents on the quality of life in pancreatic cancer patients. The data were analysed using the Bibliometrix R package to create knowledge maps and visualize research trends, collaborations, and emerging hotspots in the field.

RESULTS

A total of 819 articles on pancreatic cancer and quality of life were identified, with an average citation count of 47.13 per article, highlighting moderate academic impact. The research revealed a growing trend in collaborative efforts, with an average of 9.42 co-authors per article and 16 % international collaborations. The United States emerged as the leading contributor, with 203 publications and the highest citation count, followed by France and the United Kingdom.

CONCLUSION

This bibliometric analysis highlights the growing volume of pancreatic cancer and quality of life research, with a steady annual growth rate of 6.9 % and increasing collaboration, especially from the United States. However, despite the rising number of publications, a decline in citation impact for recent studies suggests a need for continued innovation in therapeutic strategies to improve clinical outcomes.

Exploring the potential of machine learning in gastric cancer: prognostic biomarkers, subtyping, and stratification

BACKGROUND

Advancements in the management of gastric cancer (GC) and innovative therapeutic approaches highlight the significance of the role of biomarkers in GC prognosis. Machine-learning (ML)-based methods can be applied to identify the most important predictors and unravel their interactions to classify patients, which might guide prioritized treatment decisions.

METHODS

A total of 140 patients with histopathological confirmed GC who underwent surgery between 2011 and 2016 were enrolled in the study. The inspired modification of the partial least squares (SIMPLS)-based model was used to identify the most significant predictors and interactions between variables. Predictive partition analysis was employed to establish the decision tree model to prioritize markers for clinical use. ML models have also been developed to predict TNM stage and different subtypes of GC. Latent class analysis (LCA) and principal component analysis (PCA) were carried out to cluster the GC patients and to find a subgroup of survivors who tended to die.

RESULTS

The findings revealed that the SIMPLS method was able to predict the mortality of GC patients with high predictabilities (Q2 = 0.45-0.70). The analysis identified MMP-7, P53, Ki67, and vimentin as the top predictors. Correlation analysis revealed different patterns of prognostic markers in the non-survivor and survivor cohorts and different GC subtypes. The main prediction models were verified via other ML-based analyses, with a high area under the curve (AUC) (0.84-0.99), specificity (0.82-0.99) and sensitivity (0.87-0.99). Patients were classified into three clusters of mortality risk, which highlighted the most significant mortality predictors. Partition analysis prioritizes the most significant predictors P53 ≥ 6, COX-2 > 2, vimentin > 2, Ki67 ≥ 13 in mortality of patients (AUC = 0.85-0.90).

CONCLUSION

The present study highlights the importance of considering multiple variables and their interactions to predict the prognosis of mortality and stage in GC patients through ML-based techniques. These findings suggest that the incorporation of molecular biomarkers may enhance patient prognosis compared to relying solely on clinical factors. Furthermore, they demonstrate the potential for personalized medicine in GC treatment by identifying high-risk patients for early intervention and optimizing therapeutic strategies. The partition analysis technique offers a practical tool for identifying cutoffs and prioritizing markers for clinical application. Additionally, providing Clinical Decision Support systems with predictive tools can assist clinicians and pathologists in identifying aggressive cases, thereby improving patient outcomes while minimizing unnecessary treatments. Overall, this study contributes to the ongoing efforts to improve patient outcomes by advancing our comprehension of the intricate nature of GC.

Exploring the bioactive components and mechanism of Biling Weitong Granules in chronic gastric ulcer repair through network analysis and experimental verification

Biling Weitong Granules (BLWTG) is a clinical formula employed for treating epigastric pain, yet its pharmacodynamic components and mechanisms against chronic gastric ulcers (GU) remain inadequately understood. The objective of this study was to investigate the targets and mechanisms of BLWTG and its bioactive components in chronic GU. Chronic GU model was induced in SD rats through acetic acid injection, and administered BLWTG post-induction. The macroscopic ulcer appearance, microscopic histology, mucosal growth, vascular promoting factors, myeloperoxidase, and inflammatory factors in gastric tissue were assessed. Network analysis was used to predict the potential core targets and pathways. Further, bioactive components were screened based on cell model, identified by HPLC-QTOF-MS and validated in vivo. The results showed that BLWTG effectively mitigated pathological damage, achieving a 63.32% ulcer healing rate. Network analysis and experimental verification showed that the effectiveness of BLWTG stemmed from its capacity lower oxidative stress and inflammation, boost antioxidant levels, and promote the synthesis of gastric mucosal protective factors and repair. Further, the primary active fraction of BLWTG was ethyl acetate fraction, which increased the ulcer healing rate to 75.04%. Among the 55 compounds identified in the ethyl acetate fraction of BLWTG, evodiamine, dehydroevodiamine, berberine and tetrahydropalmatine may represent the active components responsible for facilitating the regeneration and repair of GU. In conclusion, BLWTG and its bioactive components significantly promote healing in rat models of chronic GU, providing a scientific basis for further applications of BLWTG in treating chronic GU.

The impact of Zataria multiflora on oxidative stress biomarkers and ulcerative colitis symptoms: A multicenter, triple-blind, placebo-controlled clinical trial

BACKGROUND

Oxidative stress plays a crucial role in the pathogenesis of ulcerative colitis (UC), contributing to mucosal damage and inflammation. Zataria multiflora possesses antioxidant properties, yet clinical evidence regarding its effects in UC remains limited. This study aimed to evaluate the impact of Z. multiflora extract on oxidative stress markers and disease severity in UC patients.

METHODS

In this triple-blind, randomized, placebo-controlled trial, 92 patients with mild-to-moderate UC were randomly assigned to receive either Z. multiflora extract (6 mg/kg/day) or a placebo for two months. Oxidative stress markers, including malondialdehyde (MDA), total antioxidant capacity (TAC), superoxide dismutase (SOD), and thiol groups (SH), were measured before and after treatment. Disease severity was assessed using the Partial Simple Clinical Colitis Activity Index (P-SCCAI).

RESULTS

Z. multiflora supplementation significantly increased TAC (p = 0.01), SOD (p = 0.02), and SH (p = 0.01) levels, indicating enhanced antioxidant defenses. However, MDA levels did not significantly decrease (p = 0.06). Clinically, the Z. multiflora group exhibited significant improvements in bowel frequency (p < 0.001), urgency of defecation (p < 0.001), general well-being (p < 0.001), and final P-SCCAI scores (p < 0.001) compared to the placebo group.

CONCLUSION

Z. multiflora supplementation improved antioxidant markers and alleviated UC symptoms, though MDA levels remained unchanged. These findings suggest its potential as a complementary therapy for UC. Further large-scale, long-term studies are warranted to confirm its efficacy and optimize dosing.

Global aspects of celiac disease and food allergy

Celiac disease and food-allergy are both food-related chronic immune disorders with a common pathogenic link being breakdown in the gut tolerance to otherwise innocuous food antigens. Notwithstanding the similarities, there are significant differences in the pathogenesis of both disorders, which translates to variations in clinical presentations, diagnostic tools and disease epidemiology. The past few decades have witnessed a global increase in prevalence and incidence of both disorders, driven both by true rise due to epidemiological factors and unmasking of previously undiagnosed disease due to better diagnostics and health seeking behavior, related to economic factors. Worldwide as more cases are diagnosed, disparities in healthcare and resources available for disease management are increasingly becoming more relevant but are infrequently discussed. In this review we will discuss the global epidemiology of celiac disease and food allergy, their epidemiological risk factors and future directions for their improved diagnosis and management.