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BackgroundChatGPT is among the most popular large language models (LLMs), exhibiting proficiency in various standardized tests, including multiple-choice medical board examinations. However, its performance on otolaryngology–head and neck surgery (OHNS) certification examinations and open-ended medical board certification examinations has not been reported. ObjectiveWe aimed to evaluate the performance of ChatGPT on OHNS board examinations and propose a novel method to assess an AI model’s performance on open-ended medical board examination questions. MethodsTwenty-one open-ended questions were adopted from the Royal College of Physicians and Surgeons of Canada’s sample examination to query ChatGPT on April 11, 2023, with and without prompts. A new model, named Concordance, Validity, Safety, Competency (CVSC), was developed to evaluate its performance. ResultsIn an open-ended question assessment, ChatGPT achieved a passing mark (an average of 75% across 3 trials) in the attempts and demonstrated higher accuracy with prompts. The model demonstrated high concordance (92.06%) and satisfactory validity. While demonstrating considerable consistency in regenerating answers, it often provided only partially correct responses. Notably, concerning features such as hallucinations and self-conflicting answers were observed. ConclusionsChatGPT achieved a passing score in the sample examination and demonstrated the potential to pass the OHNS certification examination of the Royal College of Physicians and Surgeons of Canada. Some concerns remain due to its hallucinations, which could pose risks to patient safety. Further adjustments are necessary to yield safer and more accurate answers for clinical implementation.

BACKGROUND:. Ingestion and aspiration of caustic substances is a common problem in pediatrics and carries the risk of associated aspiration pneumonitis, laryngeal injury, and esophageal injury. Extracorporeal membrane oxygenation (ECMO) has been used to support adults with acute respiratory distress syndrome (ARDS) from aspiration of cement dust, however, literature outlining pediatric management in cases of alkali lung and airway injuries is lacking. CASE SUMMARY:. A 6-year-old boy presented with ARDS from cement aspiration requiring high-pressure ventilation. He had further complications of tracheal injury with subsequent pneumomediastinum secondary to the alkali burn. He required ECMO to facilitate repeat bronchoscopy for cement particle washout and to enable recovery from ARDS and tracheal injury. CONCLUSION:. This case highlights the need to perform early bronchoscopy and gastrointestinal endoscopy for injury assessment and foreign body removal in alkali burns. It also emphasizes the value of ECMO support for respiratory failure and facilitating bronchoalveolar lavage when it is not otherwise tolerated.

Abstract Background Inverted papilloma (IP) is an unusual type of benign tumor that has high recurrence rates and the potential to transform into squamous cell carcinomas (SCC). The mechanism of the transformation process from IP to IP-SCC is uncertain and there is no consensus regarding the best practice for IP-SCC detection. The goal of this study is to identify the best clinical methods to detect for IP-SCC. Methods An evidence-based review was performed using Medline and Ovid to obtain all articles up to October 10th, 2019 pertaining to identification of IP malignant transformation. All manuscripts discussing clinical methods or biomarkers were included. Results Based on clinical research studies, convoluted cerebriform pattern and apparent diffusion coefficient values on Magnetic Resonance Imaging (MRI) can help differentiate benign IP from SCC and increased SUVmax on PET/CT is associated with higher probability of malignancy although not as specific. No consensus about the best biomarker for IP-SCC has been reached among researchers and continues to be exploratory. Conclusion Endoscopy with biopsy is the gold standard practice to identify IP-SCC; however, MRI is the preferred imaging modality to recognize malignant transformation in cases where biopsy is difficult. Multiple biomarkers have shown positive results, but no single indicator with clinical significance for monitoring malignant transformation process has been found.

It is a continual and challenging problem to detect small defects in metallic structures for array eddy current testing (ECT) probes, which require the probe to have ultra-high resolution and sensitivity. However, the spatial resolution of an ECT array probe is limited by the size of the induction coils. Even if it is possible to increase the spatial resolution by using smaller coils, the sensitivity of the sensor also decreases. To obtain finer spatial resolution without sacrificing sensitivity, this paper proposes a resolution enhanced ECT array probe with four rows of coils attached to a flexible printed circuit board (FPCB). The distance between each two adjacent coils in a row is 2 mm and the position of each row is offset by 0.5 mm along the horizontal direction related to its prior row. The outputs of the four rows are aligned and interpolated in a line, and in this way the image resolution of the probe is increased to 0.5 mm. The probe is configured to operate with the differential setting, namely two differential coils operate simultaneously at each time. The currents in the two coils can be controlled to have the same flowing direction or opposite flowing direction, resulting in different distributions of the induced eddy current and two sets of output images. A patch-image model and an image fusion method based on discrete wavelet transforms are employed to suppress the noise and highlight the defects’ indications. Experimental results show that small defects with dimensions as small as length × width × depth = 1 mm × 0.1 mm × 0.3 mm on a 304 stainless-steel sample can be detected from the fused image, demonstrating that the probe has super sensitivity for small defects inspection.

A series of zeolite X/activated carbon (AC) composites were prepared from the same starting materials at various activation time. The corresponding modified samples were obtained by being treated with diluted NH4Cl solution. The relationship between porosity development, surface properties, and CH4/N2 adsorption performance was investigated. The increase of micropore volume is beneficial to the improvement of CH4 and N2 adsorption capacity, but more sensitive for CH4. In addition, the polar functional groups of zeolite X/AC composites may enhance CH4 adsorption capacity. More importantly, both developing micropore structure and surface modification contributed to enhance the adsorption selectivity αCH4/N2. As the optimum sample of these studies, HZAC(24) showed CH4 adsorption capacity of 17.3 cm3/g and the highest adsorption selectivity αCH4/N2 of 3.4. The CH4 and N2 adsorption isotherms of all samples can be well fitted by the Langmuir–Freundlich model. HZAC(24) showed an excellent cyclability of adsorption/desorption of CH4 with a neglectable capacity loss after subsequent cycles. Moreover, HZAC(24) displayed relatively rapid adsorption kinetics. These properties of zeolite X/AC composites are essential for the adsorptive separation of CH4 from N2 in the pressure swing adsorption (PSA) process.

Transformative technologies are enabling the construction of threedimensional (3D) maps of tissues with unprecedented spatial and molecularresolution. Over the next seven years, the NIH Common Fund Human BiomolecularAtlas Program (HuBMAP) intends to develop a widely accessible framework forcomprehensively mapping the human body at single-cell resolution by supportingtechnology development, data acquisition, and detailed spatial mapping. HuBMAPwill integrate its efforts with other funding agencies, programs, consortia,and the biomedical research community at large towards the shared vision of acomprehensive, accessible 3D molecular and cellular atlas of the human body, inhealth and various disease settings.

The gut microbiota constitutes a complex ecosystem, comprising trillions of microbes that have co-evolved with their host over hundreds of millions of years. Over the past decade, a growing body of knowledge has underscored the intricate connections among diet, gut microbiota, and human health. Bioactive polysaccharides (BPs) from natural sources like medicinal plants, seaweeds, and fungi have diverse biological functions including antioxidant, immunoregulatory, and metabolic activities. Their effects are closely tied to the gut microbiota, which metabolizes BPs into health-influencing compounds. Understanding how BPs and gut microbiota interact is critical for harnessing their potential health benefits. This review provides an overview of the human gut microbiota, focusing on its role in metabolic diseases like obesity, type II diabetes mellitus, non-alcoholic fatty liver disease, and cardiovascular diseases. It explores the basic characteristics of several BPs and their impact on gut microbiota. Given their significance for human health, we summarize the biological functions of these BPs, particularly in terms of immunoregulatory activities, blood sugar, and hypolipidemic effect, thus providing a valuable reference for understanding the potential benefits of natural BPs in treating metabolic diseases. These properties make BPs promising agents for preventing and treating metabolic diseases. The comprehensive understanding of the mechanisms by which BPs exert their effects through gut microbiota opens new avenues for developing targeted therapies to improve metabolic health. [ABSTRACT FROM AUTHOR]

The neural crest is an embryonic population of multipotent stem cells that form numerous defining features of vertebrates. Due to lack of reliable techniques to perform transcriptional profiling in intact tissues, it remains controversial whether the neural crest is a heterogeneous or homogeneous population. By coupling multiplex single molecule fluorescence in situ hybridization with machine learning algorithm based cell segmentation, we examine expression of 35 genes at single cell  resolution in vivo. Unbiased hierarchical clustering reveals five spatially distinct subpopulations within the chick dorsal neural tube. Here we identify a neural crest stem cell niche that centers around the dorsal midline with high expression of neural crest genes, pluripotency factors, and lineage markers. Interestingly, neural and neural crest stem cells express distinct pluripotency signatures. This Spatial Genomic Analysis toolkit provides a straightforward approach to study quantitative multiplex gene expression in numerous biological systems, while offering insights into gene regulatory networks via synexpression analysis.

Purpose: This study aimed to establish and validate a diagnostic nomogram for identifying false positives in the Xpert MTB/RIF (Xpert) for detection of rifampicin resistance (RIF-R). Patients and Methods: In this retrospective study, we collected basic patient characteristics and various clinical information from the electronic medical record database. Patients were randomly divided into training and validation groups in a 7:3 ratio. LASSO regression was used to screen variables and construct a diagnostic nomogram. The ROC curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the performance of the nomogram. Results: A total of 384 patients were included in the study, with 268 and 116 patients in the training and validation cohorts, respectively. Finally, probe mutations and probe delay were identified as the independent influencing factors. Using the mutation of probe E as a reference, probes A or C (OR = 51.07, P< 0.001), probe D (OR = 7.48, P< 0.001), and multiple probes (OR = 4.42, P=0.029) were identified as factors influencing false positives in Xpert for detection of RIF-R. Taking probe delay ΔCT < 4 as a reference, ΔCT (4– 5.9) (OR = 17.06, P=0.005) and ΔCT (6– 7.9) (OR = 36.67, P< 0.001) were noted to be the factors influencing false positives in Xpert for detection of RIF-R. Based on these two variables, we constructed a diagnostic nomogram. The area under the curve of the nomogram model was 0.847 and 0.850 for the training and validation groups, respectively. The calibration curves were consistent. The DCA revealed that the model achieved the greatest net benefit when the threshold probability was set between 6% and 71% in the training cohort and 6% and 70% in the validation cohort. Conclusion: The nomogram constructed can identify false positives in Xpert for detection of RIF-R and provides basis for clinicians to formulate diagnosis and treatment plans. [ABSTRACT FROM AUTHOR]