Reduced responsiveness to hearing one's own name is a core early behavioral predictor of autism spectrum disorder (ASD). This behavioral maker reflects atypicalities in self-related and social auditory processing, that are foundational to the development of social communication. To better understand the underlying neural mechanism of this alteration, the current study investigated neural correlates of auditory own-name processing in a sample of toddlers with ASD and typically developing (TD) controls using an auditory novelty oddball paradigm. Participants included 54 toddlers (30 ASD, 24 TD; 2-4 years) who passively listened to five auditory stimuli consisted of pure tones (500Hz and 1000Hz) and name types (self, familiar and stranger names). An auditory novelty oddball paradigm was utilized to assess neural response to standard and deviant stimuli, as well as to the different name types. Event-related potentials (ERPs) were recorded to measure neural activity during the stimulus processing. Compared to TD controls, autistic toddlers showed reduced late MMN to deviant tones that was infrequently presented relative to standard tones; Analysis of ERP components during own-name processing revealed atypical neural response pattern: autistic toddlers exhibited enhanced central P3a coupled with decreased LDN amplitudes to one's own-name relative to other names, and lack of parietal LPP effect typically observed in response to one's own-name. Our findings provide insight into the neural mechanisms underlying altered own-name processing in toddlers with ASD. These results suggest preserved early attentional capture of self-relevant salience, but atypical higher-order cognitive functioning during self-related and social auditory processing in toddlers with ASD.
Polyendocrine metabolic ovarian syndrome (PMOS), previously named polycystic ovary syndrome (PCOS), affects one in eight women. However, the term PCOS is inaccurate, implying pathological ovarian cysts, obscuring diverse endocrine and metabolic features, and contributing to delayed diagnosis, fragmented care, and stigma, while curtailing research and policy framing. Building on an international mandate for change, we outline an unprecedented, rigorous, multistep global consensus process for the name change. Funding and governance were established with engagement of 56 leading academic, clinical, and patient organisations. Using iterative global surveys (with responses from 14 360 people with PCOS and multidisciplinary health professionals from all world regions), modified Delphi methods, nominal group technique workshops, and marketing and implementation analyses, we identified principles prioritising scientific accuracy, clarity, stigma avoidance, cultural appropriateness, and implementation feasibility. An accurate new name was prioritised over retaining the PCOS acronym or a generic name. Implementation approaches prioritised evolution rather than transformation. Preferred terms were polyendocrine, metabolic, and ovarian, reflecting the condition's multisystem pathophysiology, and polyendocrine metabolic ovarian syndrome was the consensus new name. Accuracy was improved by omitting cysts and by capturing endocrine, metabolic, and ovarian dysfunction. A co-designed global implementation strategy, including a transition period, education, and alignment with health systems and disease classification, is under way.
Although LOINC is widely adopted, clinical laboratory test names are frequently recorded in non-standardized free-formats, often involving mixed Persian-English terminology, in Iran. This study presents an intelligent service for automated mapping of mixed-language clinical laboratory test names to LOINC. A dataset of 1,400 local laboratory test names and codes was extracted from a hospital information system. All records were manually mapped to LOINC by two experts as the gold standard. The data were split into training (70%) and testing (30%) sets. After data preprocessing, an N-Gram-based similarity approach with adjustable thresholds was developed for automated mapping. System outputs were evaluated against expert-assigned LOINC codes. At low similarity thresholds (<0.4), the system achieved near-complete coverage but low accuracy. Performance improved substantially with higher thresholds. At similarity thresholds between 0.7 and 0.8, approximately 78% of records were correctly mapped automatically. At a threshold of 0.8, agreement with the expert coder reached 0.84, with both precision and sensitivity of 0.86. The proposed approach demonstrates that accurate automated LOINC mapping is feasible for Persian-English mixed-language laboratory data. This work addresses a critical gap in multilingual laboratory data interoperability in real-world health information systems.
Achieving interoperability with HL7 FHIR in practice requires creating a FHIR Implementation Guide (IG). Between the many IGs at international, national, and local levels, incompatibilities are inevitable. For example, one IG requiring a field to be filled in while another explicitly forbids it. The same application, such as a FHIR server or FHIR facade, must then handle inherently incompatible resource structures. We use Germany as a real-world failure case: three competing IGs (basisprofile-de, KBV-Basis-Profile, and ISiK), which were not aligned during development, have become mandatory; many organizations must implement all three for the same patient. We systematically compare KBV Base 1.x and ISiK Basismodul v2, identifying hard structural conflicts including closed versus open slicing on Condition.onset[x] and disjoint address and name type constraints on Patient, Practitioner, and RelatedPerson. We show one possible technical response: we cannot resolve the fact that FHIR disallows one resource from conforming to all three IGs at once, but our namespace-based data management in Neo4j is designed to allow storing data without redundancy and delivering the same patient in three different formats depending on which profile the client requests. Future work includes integrating this model with FHIR profile comparison tooling, evaluating performance at scale, and aligning with HL7 Europe EHDS implementation guides as they mature.
We showed recently that the adenosine system and nitric oxide (NO) can interact differently in the control of renal function in normoglycaemia (NG) versus streptozotocin-induced diabetes (DM). Herein, we investigated if this relationship is modulated by dietary betaine (Bet, food compound possessing antioxidant and anti-inflammatory properties), to examine if adenosine receptor signalling in NG and DM females is altered by chronic Bet supplementation. The effects of intravenous infusion of theophylline, non-selective adenosine receptor antagonist, were examined in anaesthetised Sprague-Dawley female rats, pretreated for 2 weeks with Bet alone or combined with 4-day NO synthesis blockade with L-NAME (Bet + L-NAME). Renal blood flow (RBF, ultrasound artery probe), perfusion of the cortex, outer (OM-BF) and inner medulla (IM-BF; laser-Doppler technique), and tissue NO signal (selective electrode) were determined along with renal excretion. Bet and Bet + L-NAME decreased baseline RBF irrespective of glycaemia, whereas Bet lowered (NG) or elevated (DM) basal OM-BF; Bet + L-NAME treatment abolished these effects. Baseline sodium excretion decreased after Bet and Bet + L-NAME in NG only. Bet modified theophylline effects: IM-BF was lowered in DM rats, while tissue NO changes shown in the control were modified: NO increased in NG and decreased in DM. In NG, these effects were abolished by Bet + L-NAME. Bet pretreatment did not alter diuresis, natriuresis and kaliuresis, but after Bet + L-NAME these parameters increased (NG) or decreased (DM). Dietary Bet has the potential to affect renal medullary blood circulation; however, the eventual effect depends on glycaemia. Bet can modify renal functional changes induced by the interplay of the adenosine and NO systems, both in rats with normoglycaemia and streptozotocin diabetes.
Digitizing electrocardiogram (ECG) images into structured time-series data is critical for clinical analysis, but it remains challenging due to the lack of standardized datasets, especially under realistic scenarios like overlapping waveforms. We introduce SynthECG, an open-source Python framework to generate four synthetic ECG datasets tailored for deep learning tasks, including ECG digitization, YOLO-based lead and lead name detection, and U-Net-based waveform segmentation. The framework supports customizable parameters (e.g., dataset size, lead layout, and visual style) and allows generating up to 21,799 images for multi-lead datasets and 261,588 for single-lead segmentation. Notably, it introduces a novel mechanism to simulate overlapping waveforms from adjacent leads while preserving clean segmentation masks. Using our framework, we generated four open-access datasets: (1) 2000 ECG images in various lead configurations paired with time-series signals for ECG digitization, (2) 2000 ECG images in various lead configurations with YOLO-format annotations for detecting lead regions and lead names, (3) 20,000 cropped single-lead images with pixel-level segmentation masks (normal variant), and (4) 102 cropped single-lead images with overlapping waveforms from adjacent leads (overlapping variant). We validated these datasets through two case studies: digitization using a non-ML algorithm (mean squared error: 0.002, ρ: 0.93, signal-to-noise ratio [SNR]: 7.36 dB, SNRmed: 37.86 dB) and lead/name detection using YOLOv8. Our open-source framework enables the generation of large-scale, customizable ECG image datasets to support key deep learning-based tasks, including digitization under normal and overlapping conditions, as well as lead region and lead name detection. The full datasets and code are publicly available at: https://doi.org/10.5281/zenodo.15484519 and https://github.com/rezakarbasi/ecg-image-and-signal-dataset.
We identified a case of illegitimacy according to the International Code of Nomenclature of Prokaryotes in a recent article that revisited the taxonomic boundaries of the species within the Streptococcus mitis-oralis complex. A new subspecies name S. mitis subsp. carlssonii Kilian et al. 2025 was mistakenly proposed for S. mitis cluster II without considering that its circumscription also contains the nomenclatural types of two validly published names, Streptococcus hohhotensis Li et al. 2024 and Streptococcus humanilactis Guo et al. 2024. To rectify this, we proposed a replacement name as S. mitis subsp. hohhotensis (Li et al. 2024) comb. nov. by adopting the earliest legitimate epithet for this particular circumscription.
The imperative to re-analyze existing public sequencing data is central to modern biology, driven by new hypotheses and advanced analytical methods. However, this effort is critically hampered by the profound heterogeneity of repository data, particularly the non-standardized, free-text descriptions of biological experiments. This lack of structural and semantic homogeneity prevents systematic search, integration, and comparative analysis, effectively locking away the full potential of accumulated datasets. Advances in Natural Language Processing (NLP) offer a pivotal pathway to overcome this bottleneck by transforming unstructured text into computable, homogeneous information. The integrated Entrez database system, maintained by the National Center for Biotechnology Information (NCBI), provides sophisticated programmatic access via an API to primary sequencing data and its associated metadata, including detailed experimental descriptions. This interface enables researchers to identify and retrieve relevant data through keyword searches, including those based on gene names, and to apply modern NLP techniques to transform textual metadata into structured information. The output is formatted data ready for integration into local databases, accompanied by a systematic list of links for downloading primary files. The Alembic software package offers a comprehensive and automated solution for the entire workflow. Designed as a locally deployable client-server system, Alembic incorporates state-of-the-art transformer-based AI algorithms for analyzing the biomedical text that accompanies sequencing data. Its core utilizes the openly available AIONER platform, which is built upon the PubMedBERT model trained on the PubMed repository, to ensure efficient and accurate recognition of biomedical named entities (e. g., genes, diseases). This provides users with structured and meaningful keyword search results. By delivering a curated list of datasets, Alembic streamlines the path from search to analysis. Researchers can efficiently identify high-value targets and obtain a complete package of metadata and primary data to construct a tailored local repository. This positions Alembic as a universal solution that overcomes the fragmented approach of existing tools, offering an integrated workflow for diverse public sequencing data. Развитие технологий высокопроизводительного секвенирования и методов анализа больших данных создает устойчивую потребность в повторном анализе накопленной в открытых репозиториях гетерогенной информации. Серьезной проблемой при этом остается преобладание свободного текстового описания биологических экспериментов, что затрудняет продуктивный поиск, систематизацию и дальнейшее использование соответствующих наборов данных. Прогресс в области искусственного интеллекта, особенно в развитии методов обработки естественного языка (natural language processing, NLP), обуславливает новые методологические возможности для эффективного решения этой задачи. Интегрированная система баз данных Entrez, поддерживаемая Национальным центром биотехнологической информации США (NCBI), предоставляет развитый и надежный доступ как к исходным данным секвенирования, так и к сопутствующей метаинформации, включающей детальное описание параметров экспериментов, через программный интерфейс (application programming interface, API). Это позволяет идентифицировать и загружать данные секвенирования и соответствующие им метаданные с описаниями экспериментов, используя поиск по ключевым словам и различным терминам, таким, например, как имена генов, в репозиториях; преобразовывать и систематизировать текстовые описания с применением современных NLP-методов и обеспечивать исследователям структурированную информацию для интеграции в локальные базы данных и форматированный перечень ссылок для загрузки исходных данных. Программный пакет Alembic предлагает комплексное решение для поиска и загрузки данных, автоматизируя все указанные этапы. Платформа использует клиент-серверную архитектуру и предназначенa для локальной установки. Для анализа биомедицинских текстов, сопровождающих данные секвенирования, в Alembic интегрированы современные алгоритмы искусственного интеллекта на основе архитектуры трансформеров. В частности, используется имеющаяся в открытом доступе платформа AIONER, обученная на данных репозитория PubMed с помощью модели PubMedBERT. Такой подход обеспечивает эффективное распознавание именованных сущностей (named entity recognition, NER) биомедицинского характера (гены, заболевания и др.), предоставляя пользователю структурированные результаты поиска по ключевым словам. Формируемый пакетом список дает возможность исследователю анализировать результаты, отбирать наиболее релевантные наборы данных и получать всю необходимую информацию (включая исходные данные) для создания локального репозитория, ориентированного на конкретную исследовательскую задачу. В отличие от имеющихся аналогов, Alembic является универсальным решением для интеграции данных из репозиториев открытого доступа и работы с разнородными типами данных секвенирования.
Mutual exclusivity (ME), the tendency that young children have to select a novel object upon hearing a novel label, gives children a basis to select a referent for an unknown label. However, this strategy may not be relevant to bilinguals who learn multiple labels for most objects. Although previous research showed that bilinguals are better than monolinguals in accepting second labels for familiar objects, these studies explicitly labelled the familiar objects with a novel name, leaving open the question of whether children implicitly accept lexical overlap in ambiguous naming situation. We investigated to what extent monolingual and bilingual children associate a novel label with a familiar, name-known object when a novel object is present using a tablet-based referent selection task. Subsequently, we examined whether children retained the novel word-object association as well as whether they formed associations between the novel labels and the familiar, name-known objects. We tested 123 monolingual and 131 bilingual children between 3 and 10 years of age. We found that monolinguals and bilinguals relied on ME but bilinguals to a lesser extent than monolinguals. Monolinguals retained novel word-object associations but not the associations between novel words and familiar objects, while bilinguals retained the associations between novel words and familiar objects but not novel word-object associations. Our study extends the proposition that bilinguals are open to lexical overlap even in ambiguous referent selection situations. Our findings thus indicate that the influence of language experience on children's word-learning strategies persists throughout the first decade of life.
Associative memory is essential for daily functioning; however, VR interventions in this domain are limited. The present study examined associative memory in different modalities and investigated the effects of culture on performance and response time in a virtual environment. Twenty-two healthy younger adults from Italy and Ghana (ages 18-26) completed eight training trial sessions on object-name matching and object-sound matching tasks in a virtual environment. Performance improved progressively across trials in both tasks, with greater accuracy and faster response times in the object-name task than in the object-sound task. Cross-cultural comparisons revealed no significant performance differences between the Ghanaians and Italians. However, the Italians completed both tasks significantly faster than the Ghanaians. The findings of the present study indicate that associative memory is culturally invariant, whereas response-time differences may reflect cultural influences on processing strategies. Overall, this study supports the use of VR as a culturally adaptable platform for associative memory assessment and training.
The reactive thiol group of cysteine (Cys) acts as a nucleophile and undergoes many cysteine post-translational modifications (Cys-PTMs). Cys-PTMs, called protein redox switch, contribute to various cellular and physiological processes, including reactive oxygen species (ROS)-induced signalling, ROS mitigation, and scavenging. Consolidation of Cys-PTMs into a database would facilitate the mechanistic elucidation of biological processes and therapeutic applications. The existing databases store information on cysteine motifs, oxidation states, a few of the Cys-PTMs, etc., specific to species or kingdoms, and lack general applicability. There was no mention of the impact of the protein microenvironments and cellular localizations on the Cys-PTMs. The current study reports a database containing 7 Cys-PTMs (disulphide, S-nitrosylation, S-palmitoylation, S-glutathionylation, S-sulphenylation, metal-binding, and thioether), 11 features, 33 06 395 UniProt IDs, and 1 14 56 639 cysteine residues, across the taxonomy, encompassing cellular organelles, enzyme classes, sequence motifs, protein structures, and microenvironments. The maximum number of cysteine residues is reported here compared to 16 contemporary cysteine databases. Twenty-one types of metal-binding cysteines and thioether modifications are reported for the first time. Enzyme classes, cellular localization, taxonomic preferences, and microenvironment around Cys-PTMs were systematically analysed and curated, indicating the pathogenic involvement of those Cys-PTMs. The database has a web access (https://cysdbase.bits-hyderabad.ac.in/) and a programmatic access via GitHub link (https://github.com/devhimd19/CysDBase). The query inputs to the repositories are UniProt ID, biological pathway, location, or genus name. Query outputs are 11 biological features, namely, protein name, Cys-PTMs, cysteine residue number, cysteine sequence motif, cell organelle, biological pathway, protein microenvironment (buried fraction and relative hydrophobicity [rHpy]), EC number and enzyme class, secondary structure, organism, and PubMed ID.
Background/Objectives: Body Protection Compound-157 (BPC 157) is a stable gastric pentadecapeptide with cytoprotective, pro-angiogenic, and nitric oxide (NO)-modulating properties that has gained increasing attention for its therapeutic potential. Although vasodilatory effects have been demonstrated in animal models, functional evidence in human arterial tissue remains limited. This study investigated the effects of BPC 157 on vascular tone in human internal mammary artery (IMA) rings and evaluated the contribution of endothelial NO signaling. Methods: Residual IMA segments obtained from elective coronary artery bypass graft surgeries (n = 12) were dissected into endothelium-intact and endothelium-denuded rings. Following equilibration, the rings were challenged by phenylephrine (PheE; 3 × 10-6 M) to induce contraction. Cumulative concentration-response curves of BPC 157 (0.01-1 mg/mL) for five consecutive doses were constructed. The involvement of NO was assessed by BPC 157 dose-response curves in the nitric oxide synthase (NOS) inhibitor Nω-nitro-L-arginine methyl ester (L-NAME; 10-6 M) pre-incubated rings. Maximum force of contraction, area under the curve, maximum response (Emax), and negative logarithm of the half-maximal effective concentration (pEC50) values were analyzed. Results: BPC 157 produced a concentration-dependent reduction in PheE-induced contraction in both groups, with significantly greater relaxation in endothelium-intact rings (p < 0.05). L-NAME increased contractile responsiveness in intact rings and attenuated BPC 157-induced relaxation. Under NOS inhibition, differences between groups progressively diminished and concentration-response curves converged at higher concentrations. Emax analysis demonstrated that endothelial integrity markedly enhanced maximal vasorelaxation, whereas this advantage was largely abolished after NOS inhibition. Conclusions: BPC 157 induces concentration-dependent vasorelaxation in human arterial tissue, predominantly mediated via an endothelium-dependent NO pathway. Endothelial integrity primarily enhances maximal efficacy, while residual effects indicate additional mechanisms. These findings provide early mechanistic evidence for the vascular activity of BPC 157, although further molecular and in vivo studies are required to clarify its clinical relevance.
Food-drug interactions are common in orally administered therapies. In order to achieve optimal therapeutic efficacy and safety, it is important for patients to understand the most appropriate way to take their medications in accordance with their diet. To evaluate the impact of food on the oral bioavailability of novel cardiovascular and antidiabetic drugs, including sacubitril/valsartan, direct oral anticoagulants, sodium-glucose cotransporter-2 inhibitors, semaglutide, vericiguat, pitavastatin, and bempedoic acid. PubMed, Scopus, and Cochrane Library databases were searched from inception to May 2024, following the guidelines of the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) statement. The search strategy employed keywords including 'food drug interactions', 'food effect', 'bioavailability', and 'bioequivalence', combined with the names of the investigated drugs. Eligible publications comprised clinical pharmacokinetic studies and randomized clinical trials evaluating the effect of food on drug bioavailability. A total of 36 publications met the inclusion criteria. For most drugs, food was found to reduce the maximum concentration and delay the rate of absorption of the active substance without significantly affecting overall drug exposure. Therefore, these drugs can generally be administered regardless of meals. Semaglutide is recommended to be administered on an empty stomach, and pitavastatin demonstrated higher bioavailability in the fasted state. In contrast, vericiguat and higher doses of rivaroxaban are better absorbed when taken with food. For patients with swallowing difficulties, rivaroxaban, apixaban, and edoxaban may be crushed and administered either via a nasogastric tube or orally mixed with applesauce. For a substantial proportion of novel cardiovascular and antidiabetic therapies, dosing without strict regard to meals is supported by available evidence. This level of flexibility may facilitate patient adherence and contribute to improved therapeutic outcomes in clinical practice.
A Gram-stain-negative, strictly aerobic, rod-shaped bacterium, designated EGI 63066T, was isolated from a saline soil of Kalidium foliatum (Pall.), collected from Wujiaqu in Xinjiang, China. Strain EGI 63066T is a non-motile, rod-shaped bacterium; it forms pale yellow colonies on the marine agar and grows at 10-37 °C,at pH 6.0-9.0 and 0-10% (w/v) NaCl. The 16S rRNA sequences of the strain EGI 63066T and Galbibacter mesophilus Mok-17T, Robertkochia solimangrovi CL23T, Robertkochia sediminum 1368T and Galbibacter pacificus CMA-7T share sequence similarities of 92.80%, 91.85%, 91.79% and 91.79%, respectively. Higher average amino acid identity values with Galbibacter (72.10-76.90%) than with Robertkochia (69.40-70.30%) supported the assignment of strain EGI 63066T to the genus Galbibacter. Phylogenomic analysis based on core genes revealed that strain Galbibacter kalidii formed a stable clade with the four recognized species of the genus Galbibacter and the not validly published 'Joostella atrarenae' M1-2. The average nucleotide identity and digital DNA-DNA hybridization values between the strain EGI 63066T and members of the genus Galbibacter were 71.10-74.15% and 18.00-19.70%, respectively. The DNA G+C content of the genome for strain EGI 63066T based on genomic DNA was 39.0 mol%, and the genome size was 4.66 Mbp. The predominant fatty acids of strain EGI 63066T were iso-C15 : 0, iso-C15 : 1 G and summed feature 3 (C16 : 1 ω6c and/or C16 : 1 ω7c). The major respiratory quinone was menaquinone-6, and the major polar lipids were phosphatidylethanolamine, aminolipid, aminophospholipid and phospholipid. Compared to other species within the genus Galbibacter, EGI 63066T exhibits distinctive features, including the production of flexirubin-type pigments, CM-cellulose hydrolysis and whole-cell protein profiles. Based on the polyphasic taxonomic analysis, strain EGI 63066T represents a novel species of the genus Galbibacter, for which the name G. kalidii sp. nov. is proposed. The type strain is EGI 63066T (=JCM 36938T=CGMCC 1.19132T).
This activity is designed as a team building capstone exercise for new interns to review important content from intern orientation at an emergency medicine residency program. Medical students matriculate into residency with various backgrounds, medical knowledge base, and personalities. As they orient themselves into their respective specialties, interns are commonly taught using lectures and slide decks with varied and unclear effectiveness.1,2 It has been recommended that intern orientation should incorporate active learning, such as simulation as well as a collaborative environment to bolster retention and encourage teamwork.1,3 Escape rooms are becoming increasingly popular in medical education as an adjunct to traditional lecture-based learning that encourages collaboration amongst learners.4 We embraced this modality to create a capstone and teambuilding experience for our new interns that was delivered at the completion of our intern orientation activities. Topics taught in our intern orientation include resuscitation of the critically ill patient, airway management, acute coronary syndromes, EKG reading, basic ultrasound, stroke care, and foundational pediatric topics. In this activity, an escape room is used to recall and apply topics learned during the emergency medicine intern orientation, while also promoting teamwork and camaraderie amongst a new intern cohort. By the end of this small group exercise, learners will be able to:Identify first, second, and third-degree heart block on a 12-lead ECG.Recognize STEMI pattern on a 12-lead ECG.Categorize appropriate images that make up an EFAST exam for a trauma patient.Recall the proper management of a tension pneumothorax.Identify an organized approach to emergency department rapid-sequence intubation (RSI).Recognize acute otitis media (AOM).Locate the appropriate antibiotic and pediatric dose to treat acute otitis media via the Harriet Lane Handbook.Demonstrate how to apply evidence-based guidelines to a clinical case of neonatal pediatric fever.Recall common clinical findings of basilar skull fracture.Identify important concepts in the management of stroke syndromes.Recognize vital sign abnormalities that could indicate sepsis.Review important concepts related to the management of septic patients. The use of game-based learning or gamification has become increasingly popular within medical education as a form of active learning.5 There is a growing body of literature among health care professionals highlighting improvement in participants' skills and learning through games as well as the ability of this method in encouraging peer education and socialization.6-8 Escape rooms are a form of game-based learning employing various puzzles and settings specifically designed to meet educational objectives in an active learning environment.9 Recently, literature has shown that escape rooms can be an instrument to foster relationships amongst co-workers in addition to facilitating improved learning outcomes via active learning.10We developed an escape room to review and solidify important content from our intern orientation as well as to encourage teamwork and camaraderie on the last day of orientation. The intern class was divided into three teams, each with four participants. Each team selected their own team name and were informed during a pre-briefing that they would only be able to escape intern orientation by completing all six stations. A facilitator at each station timed the teams. The team with the fastest time was deemed the winner which was announced after a short debrief of the activity. All interns who participated in the escape room completed an anonymous online survey after the activity. The survey was designed to solicit feedback on the effectiveness of the activity in reviewing material taught during orientation as well as overall satisfaction with the escape room experience measured as a recommendation to continue the activity in the future. All twelve (100%) interns that attended the escape room completed the post participation survey. Ninety-two percent (11/12 interns) thought the activity was moderately to extremely effective in reviewing the content delivered during intern orientation and 100% (12/12 interns) recommended we continue the escape intern orientation activity for future classes. Representative free response comments soliciting general feedback on the activity included "Great event, do it again. Very interactive and fun." As well as "Great activity to tie in all that we learned this month. Very creative and clever! Also, a great team building opportunity as well." Intern orientation is a necessary, high-yield time for new doctors to learn foundational specialty and hospital specific topics.11 As educators are being challenged to move away from traditional classroom lecturing, gamification has emerged within medical education as an active learning tool to increase engagement, promote team building, provide immediate feedback, and make content more interesting.12 Escape rooms fall within a constructivist theory of learning because participants are challenged to incorporate existing knowledge to draw conclusions, ultimately unlocking their "escape."13Further, intern orientation is also a time of social gathering and team building. Because camaraderie is connected to wellbeing, it is highly valued in emergency medicine residencies.14 When interns matriculate into their residencies, social interactions are encouraged among the group. In our escape room activity, gamification is used to enhance social interaction in a way that encourages relationship building and teamwork. This is important as cohesiveness amongst the resident group is a key factor for their success in residency.15. Intern, emergency medicine, heart blocks, extended focused assessment with sonography in trauma (EFAST), rapid sequence intubation, pediatric fever, stroke, sepsis.
Residents lack confidence caring for children with severe neurological impairment (SNI). The novel personal history tool, SHINE (Self, Happy, Ill, Names, and Extra), was codeveloped by families and residents to strengthen residents' confidence in connecting with children with SNI and their families. To describe SHINE's use among residents and its impact on residents' burnout, meaningful work, and confidence in caring for children with SNI. Residents at an academic children's hospital in the United States received small-group teaching on the use of SHINE. Participants completed baseline, one-, and three-month post-intervention surveys, which included resident demographics; self-reported tool use; and resident burnout, meaningful work, and confidence in caring for children with SNI. Data were analyzed descriptively and using Pearson's chi-square tests. Briefly, 88% (n = 37/42) of eligible residents participated (25 interns [67%], 12 senior residents [32%]). After one month, respondents reported they found the tool helpful/very helpful (n = 11, 92%), were likely/very likely to continue using it (n = 11, 92%), and recommended it to future residents (n = 16, 100%). At baseline, residents reported low confidence caring for children with SNI (mean = 2.08, standard deviation (SD) : 0.84 on a 1 = low to 4 = high Likert scale). After one month, respondents reported improvements in (1) understanding the nonmedical needs of patients (mean increase: 0.71, SD: 0.85, p value = 0.006) and (2) understanding life outside the hospital (mean increase: 0.94, SD: 0.87, p value = 0.003). Respondents reporting higher use of the tool experienced larger gains. No significant differences were seen in burnout or meaningful work. SHINE may improve resident self-reported confidence in caring for children with SNI.
Crop diseases significantly reduce agricultural output and are a serious problem, especially in the parts of the world where diagnostic experts are not readily available. Deep learning has recently shown us that it is possible for a computer to identify plant diseases directly from images of the leaves. Nevertheless, to make such solutions available on the web or mobile devices one has to really think about how heavy the calculations will be, how easy the user interface should be, and also the limit on the data used. Here is a paper on a web-based applied deep learning system for disease detection in multiple crops. The system detects disease in eight crops Apple, Banana, Grape, Mango, Cauliflower, Tomato, Potato, and Corn with each crop having several disease classes and healthy samples. Three transfer-learning-based CNN architectures MobileNetV3, EfficientNetB4, and ResNet50 were compared for classification performance on the public datasets collected from PlantVillage, Kaggle, and Mendeley. Considering class-wise accuracy, prediction time, and deployment scenarios, MobileNetV3 was picked as the main model to be integrated into the system. To compensate for the differences in image quality often found in pictures taken by users, an optional super-resolution preprocessing step with Real-ESRGAN is added and quantitatively assessed. Disease prediction with spectral activation maps (Grad-CAM) enhances the model's interpretability by highlighting image areas where the disease is detected. The resulting model is embedded in a multilingual Progressive Web Application (PWA). The platform enables users to submit their crop images and receive predicted disease names and treatment options, which are generated by a Large Language Model (LLM) using structured disease metadata. The research acknowledges dataset bias and limitations in extrapolating from curated datasets to the general real-world setting although it reports very good performance of the method on the test sets. In summary, the system proposed here is intended as a practical digital agriculture decision-support tool that demonstrates deployment feasibility and raises a few issues for future validation at the field level and improvement.
During fieldwork in the western Tian Shan Mountain range, somewhat different forms of Allium fetisowii s.l. were observed in its eastern and western parts. A detailed morphological study using principal component analysis (PCA) revealed the presence of two well-separated taxa within A. fetisowii s.l. A molecular study based on nrITS and four plastid markers (trnL-trnF, rpl32-trnL, trnQ-rps16 spacers, and the rps16 intron) confirmed their status at the species level. Allium fetisowii Regel s. str. occurs in the eastern part, whereas the name A. simile Regel applies to the plants growing in the western part. Together with A. chychkanense, these species constitute section Longibidentata, which is supported by molecular data. The nomenclatural history of these three species is explained. A taxonomic conspectus is provided, the distribution is mapped, and an identification key is presented.
Fluid management is a core aspect of critical care, guiding decisions around the type, timing, and amount of fluid therapy. The administration of intravenous fluids aims to restore and maintain tissue perfusion, replace overt losses, and serve as a carrier for drug delivery. While fluid administration is often emphasised during the resuscitation phase, growing evidence highlights the risks associated with sustained positive fluid balance, including tissue oedema, organ dysfunction, and increased mortality. A clear understanding of the pathophysiological mechanisms underlying fluid homeostasis can support decision-making during fluid de-escalation. Recognising the role of the lymphatic system in interstitial fluid clearance, and its potential impairment during critical illness, may help guide appropriate timing and realistic expectations for fluid removal. Fluid de-escalation includes limiting fluids to daily physiological needs, and when excess fluid persists, active fluid removal using pharmacological or mechanical interventions may be required. Evidence supporting adjunctive measures, such as albumin, hypertonic saline, or compression techniques, remains limited. There is increasing interest in understanding whether treatment effects differ across patient phenotypes, and studies in patients with lung injury suggest this may also apply to fluid management strategies. In one study, hyperinflammatory patients appeared to benefit from a conservative fluid approach, while hypoinflammatory patients had worse outcomes, despite no overall difference in mortality between the strategies. These findings highlight the potential value of phenotype-guided fluid strategies. Although fluid de-escalation is clinically important, evidence on the optimal timing, volume, and duration of fluid removal remains limited. While individualized ICU care often incorporates real-time hemodynamic variables, current strategies rely heavily on clinical judgment in the absence of standardized criteria. It also remains unclear whether a degree of permissive hemodynamic instability might be acceptable for preventing or reversing fluid overload. Ultimately, weaning from fluid support should be seen as a continuous, individualized process. Ward round discussions should explicitly name fluid overload as a working diagnosis and recognise persistent fluid accumulation or difficulty in removal as a barrier to recovery, comparable to difficult weaning from mechanical ventilation or ICU-acquired weakness.
In males, prostate cancer (PCa) is one of the frequently diagnosed forms of cancer, with high clinical variability and limited treatment options for advanced cases. This receptor, which goes by the names Coagulation Factor II Receptor (F2R) and PAR1, belongs to the family of G-protein-linked membrane proteins and plays roles in both blood clotting processes and the development of malignancies. Whereas F2R has been associated with tumor progression in various malignancies, its specific involvement in PCa is not well understood. Here, we seek to examine the expression patterns and biological functions of F2R to better understand its impact on PCa progression. We systematically analyzed F2R expression in PCa using data from the TCGA database and clinical specimens. Functional experiments, including cell proliferation, invasion, and apoptosis assays, were conducted in PCa cell lines with F2R overexpression or knockdown. Bioinformatics analyses were performed to identify F2R-associated genes and signaling pathways. In vivo xenograft models were used to validate the oncogenic role of F2R. Our results demonstrated that F2R is significantly overexpressed in PCa tissues and correlates with advanced clinicopathological features such as higher T stage, nodal metastasis, and elevated Gleason scores. Functional studies revealed that F2R promotes PCa cell proliferation, invasion, and cell cycle progression while inhibiting apoptosis. Mechanistically, we identified collagen type VIII alpha 1 (COL8A1) as a key downstream effector of F2R, which activates the FAK/PI3K/AKT signaling pathway. In vivo experiments confirmed that F2R knockdown suppresses tumor growth and downregulates this signaling axis. This study highlights F2R as an important promoter in PCa progression and identifies the F2R-COL8A1-FAK/PI3K/AKT signaling axis as a potential molecular mechanism underlying tumor aggressiveness.