Lessons in clinical reasoning ‒ pitfalls, myths and pearls: a case of recurrent pancreatitis

Objectives Cognitive biases can result in clinical reasoning failures that can lead to diagnostic errors. Autobrewery syndrome is a rare, but likely underdiagnosed, condition in which gut flora ferment glucose, producing ethanol. It most frequently presents with unexplained episodes of inebriation, though more case studies are necessary to better characterize the syndrome. Case presentation This is a case of a 41-year old male with a past medical history notable only for frequent sinus infections, who presented with recurrent episodes of acute pancreatitis. In the week prior to his first episode of pancreatitis, he consumed four beers, an increase from his baseline of 1–2 drinks per month. At home, he had several episodes of confusion, which he attributed to fatigue. He underwent laparoscopic cholecystectomy and testing for genetic and autoimmune causes of pancreatitis, which were non-revealing. He was hospitalized 10 more times during that 9-month period for acute pancreatitis with elevated transaminases. During these admissions, he had elevated triglycerides requiring an insulin drip and elevated alcohol level despite abstaining from alcohol for the prior eight months. His alcohol level increased after consumption of complex carbohydrates, confirming the diagnosis of autobrewery syndrome. Conclusions Through integrated commentary on the diagnostic reasoning process, this case underscores how overconfidence can lead to premature closure and anchoring resulting in diagnostic error. Using a metacognitive overview, case discussants describe the importance of structured reflection and a standardized approach to early hypothesis generation to navigate these cognitive biases.

Ribosomal DNA revealed an extensive role of allopolyploidy in the radiation of Ulex L

We studied the phylogeny of Ulex L., a genus of spiny legumes, which its center of diversity in the Iberian Peninsula, using ribosomal DNA markers (rDNA), namely ETS, 5.8S and ITS (45S), and 5S intergenic spacer regions. One of the main findings was the presence of very different haplotypes in 5S-IGS genes and, to a less extent, in ETS and ITS, in seven polyploid taxa. We interpreted these results as an indication of hybrid origins and proposed allopolyploidy for U. argenteus ssp. subsericeus, U. australis ssp. australis, U. australis ssp. welwitschianus, U. densus, U. europaeus ssp. europaeus, U. europaeus ssp. latebracteatus, and U. jussiaei. These results reinforce an early hypothesis which stated that the radiation of Ulex occurred mainly by polyplodization.Phylograms showed two main clades, one grouping the hydrophilic U. gallii, U. breoganii and U. minor, and the other grouping the southern, xerophytic, taxa. The putative allopolyploids showed haplotypes, which grouped in both clades, indicating that allopolyploidy, occurred through hybridization from these hydrophilic and xerophytic lineages.The phylogenetic position of U. micranthus is not certain and it is discussed. The 5S-IGS showed to retain more polymorphisms than ETS gene or ITS markers. This result is compatible with the hypothesis that 5S rDNA region is less vulnerable to inter-loci concerted evolution than 45S, providing a more suitable marker for reconstructing histories of allopolyploid species. We discuss the taxonomic consequences of these results.

The Lean Discovery Process: the case of raiserve

Purpose Uncertainty in the early development of digital business startups can benefit from data-driven testing of hypotheses. Startups face uncertainty not only in product development, but also over the structure of the business model and the nature of the customer or market to address. The authors conceptualize a new model, the Lean Discovery Process (LDP), which focuses on market-based testing from the early business idea through to fully realized product stages of an innovation. The purpose of this paper is to highlight a methodology to help digital business reduce uncertainty and apply lean principles as early as possible in the development of a business concept. Design/methodology/approach Examining literature in lean startups, lean user experience and lean software development, the authors highlight underlying assumptions of existing lean models. The authors then examine the LDP using the case of raiserve, a social entrepreneurship startup that focuses on the management of cause-based voluntary service. Findings Existing literature focuses on product development against an assumed customer base. Early hypothesis testing can be applied to business concept development to substantially reduce cost and time to market. Research limitations/implications Further investigation of different forms of uncertainty in digital startups can open up opportunities to further apply lean methodologies. A more extensive empirical study to measure the potential impact is warranted. Originality/value The authors conceptualize the minimum viable customer and support early testing with concepts from market research and collective intelligence. The authors demonstrate early opportunities to apply lean principles and rigorous hypothesis testing in an LDP that results in significant reductions in time and expense of product development.

Guide Sign Analysis of Traffic Sign Data-Set Using Supervised Spiking Neuron Technique

In this paper, 20 guided traffic signs mostly displayed around Malacca area were selected as project databased. Early hypothesis was made as the error for each usable image will increased as more interference introduced to the original image used. Three types of conditions which are hidden region, image brightness and image rotation were selected as an experiment to analyze the performance of each sign used. Each condition will perform a specific error to generate their mean value and in the same, image recognition will take place in the matchup process. By focusing on the result, it produces hidden region critically ascending mean error value at 62.5% = 0.07 and has average value at others points. For image brightness effect, it shows a higher mean error value collected at less brightness points and non-stable pattern at 10% to 60% brightness. As for rotation upshot, the values show a critically ascending for error value at 22.5% and slightly increase at 2% to 5% rotation point. For the recognition process, at 6.25% hidden region, almost 70% of images are correctly matched to its own classes while at 62.5% hidden region only 40% of images are correctly matched to its own classes and leaving 2 images to outperform. For -40% brightness, 45% of images are correctly matched to its own classes while at 60% brightness 65% of images are correctly matched to its own classes and leaving 1 image to outperform. Lastly, at 2.5 degree rotation, 85% of images are correctly matched to its own classes while at 25° rotation, 45% of images are correctly matched to its own classes and leaving 2 images to outperform. Finally, the error forms will affect the final output response of the detected traffic signs used.

Warning Sign Analysis of Traffic Sign Data-Set Using Supervised Spiking Neuron Technique

In this paper, two types of conditions have been applied to analyze the performance of SNN towards usable traffic sign, which are hidden region and rotational effect. There are 20 warning traffic signs being focused on where there are regularly seen around Malacca area. These traffic sign needed to be embedded in this system as a databased to counter the output for mean error and recognition process for both conditions applied. Early hypothesis was design as the mean error and recognition process will degraded its performance as more intrusion get introduced in the system. For hidden region, the values show a critically rising error value at 62.5% = 0.123. While for mean error rotational effect, the values show an increasing abruptly for error value between 80 ̊ to 90 ̊ with 0.087% to 0.130%. For recognition process at 6.25% hidden region, 100% of images are correctly matchup to its own image. At 50% of hidden region, there is only 10% of image that able to be recognize while at 56.25% and 62.5% are leaving to outperform. At 10 ̊ rotation, 100% of images are perfectly recognized to its own image. At 60%, there is 30% of image able to recognize leaving others at 70%, 80% and 90% degrees rotation of images were outperformed. In view of element occasion driven handling, they open up new skylines for creating models with a colossal sum limit of recollecting and a solid capacity to quick adjustment. SNNs include another component, the transient hub, to the representation limit and the handling capacities of neural systems.

Ewing's sarcoma of the head and neck

CONTEXT: Ewing's sarcoma is a rare neoplasm, which usually arises in long bones of the limbs and in flat bones of the pelvis, with the involvement of head and neck bones being very unusual. CASE REPORT: a case of Ewing's sarcoma occurring in the mandible of a 35-year-old female. Pain and swelling of the tumor were the main complaints. The early hypothesis was an undifferentiated malignant neoplasm, possibly a sarcoma. The CT scan depicted an expansive lesion, encapsulated, with septa and characteristics of soft tissue, involving the left side of the mandible and extending to the surrounding tissues. The patient underwent surgical excision of the lesion, the definitive diagnosis of Ewing's sarcoma was established, and the patient commenced on radiotherapy.