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.
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 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.
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.
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.
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.
Discriminating the distance of a sound source from oneself contributes to the representation of the bodily self and may interact with the analysis of its self-relevance, but the mechanisms underlying the relationship between spatial and content processing remain underexplored. The present study investigated whether the self-relevance of a sound (own vs. unfamiliar first names) influenced listeners' discrimination of source distance from themselves for sounds simulated in peripersonal and extrapersonal space. Distance discrimination was also assessed in a stimulus-centered task, in which listeners judged distances relative to an external auditory reference rather than to their own body. In the body-centered task, performance was better for self-relevant than for non-self-relevant stimuli in the extrapersonal space. In the stimulus-centered task, no comparable own-name effect was revealed under the present design. These findings suggest that spatial and semantic content processes may interact under specific conditions rather than operating fully independently.
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.
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.
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.
Diagnostic stewardship-performing the right test for the right patient at the right time-improves diagnostic accuracy and reduces healthcare resource waste. Various stewardship interventions have been introduced, yet their effects dissipate without systematic, sustained monitoring. One-time education and isolated system controls consistently show effect attenuation over time, and inappropriate ordering practices rapidly rebound once active oversight ceases. To date, the literature has focused on monitoring within single institutions; integration with population-level surveillance systems remains underexplored. This review proposes a framework linking institutional-level and system-level monitoring. At the institutional level, key performance indicators such as tests per patient-day and test-to-test ratios, combined with dashboard visualization, statistical process control charts, and cyclical audit-and-feedback structures, enable continuous surveillance of ordering patterns and drive behavioral change. Root cause analysis of monitoring data can identify specific drivers of over-ordering, and machine learning approaches show promise for predicting both overutilization and underutilization. These institutional tools, however, cannot track patients across facilities or assess population-level test appropriateness. At the system level, health insurance claims and administrative data enable macroscopic monitoring across entire populations. National experiences from Korea, Canada, and the United States demonstrate that ordering code pattern analysis can systematically identify inappropriate utilization-and that the structural design of reimbursement systems is more effective than voluntary recommendations in controlling low-value testing. The inherent limitation of claims data-the absence of test result values-can be partially overcome through linkage with other administrative databases. Bridging these two levels requires healthcare data standards and interoperability infrastructure, including Logical Observation Identifiers Names and Codes (LOINC), Nomenclature for Properties and Units (NPU), Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT), and Fast Healthcare Interoperability Resources (FHIR), yet practical barriers such as mapping quality variability, privacy constraints, and standardization costs persist. The scope of monitoring should extend beyond test ordering to encompass the entire total testing process, engaging diverse stakeholders across the testing continuum. With multidisciplinary workforce development, artificial intelligence-based clinical decision support, value-based reimbursement models, and rigorous multi-center studies, diagnostic stewardship monitoring can evolve into sustainable healthcare infrastructure that serves both individual patient safety and population health.
Tibetan medicine calcite (the traditional Chinese medicine name is "Nanhanshuishi") is a commonly used mineral medicine. However, calcite comes from many places, and the quality of medicine is uneven. Therefore, it is particularly important to develop an accurate and efficient method to identify the origin calcite. A total of 32 calcite samples from four different geographical areas were collected from three different provinces in southwest China. The C/O/Sr stable isotope ratios and 45 trace elements were determined using isotope ratio mass spectrometer and ICP-MS. At the same time, the trace elements and isotope information of calcite were analyzed by statistical methods. The results revealed that δ18O, δ13C, 87Sr/86Sr, and trace elements provided useful information for the identification of calcite from the four regions. Moreover, the application of multivariate statistical approaches, including the CA, PCA, and PLS-DA, to explore the ability of C/O/Sr stable isotopes and trace elements for determining the geographical origins of calcite identified a significant difference (p < 0.05) in the stable isotope ratios from different regions. PLS-DA has more accurate differentiation due to the supervision of elements. The present findings suggest that the C/O/Sr stable isotopes and trace elements can be potentially applied in the authentication of different geographical origins of calcite.
Gephyrocharax atracaudatus is a rare freshwater fish in Panama. This study provides a comprehensive analysis of the mitochondrial genome of G. atracaudatus, highlighting its gene composition, codon usage, evolutionary pressures, and phylogenetic relationships. The findings reveal unique evolutionary patterns and divergence times of G. atracaudatus that enhance the understanding of the genetic diversity within Characiformes. The increasing availability of genomic data has prompted taxonomic revisions for numerous Characiformes species, encompassing corrections to species names, subfamily, and family classifications. This study reconfirmed the classification of G. atracaudatus as "Gephyrocharax, Stevardiinae, Stevardiidae, Characiformes". A cross-analysis model for species differentiation and tracking was established using divergence time comparison and phylogenetic analysis. The results show that G. atracaudatus, Hyphessobrycon roseus and Pristella maxillaris converge on one branch, indicating that the genetic relationship may be the most similar, and it occurred approximately 90.45 Mya in the Cretaceous. This study establishes a robust model framework for understanding the evolution of G. atracaudatus, and correctly determines the biological classification status of G. atracaudatus, providing basic data support for clarifying the evolution mode of Characiformes.
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.
Sorghum consumption has potential health-promoting effects for consumers. This study identified sorghum-containing grain-based food products available in major supermarkets in China and Australia. A total of 1,692 products were audited in Shenzhen, China and Illawarra, Australia, in 2023/24. Breakfast cereals and snack bars were evaluated in both countries, while flours, pastas, and noodles were evaluated only in Australia. Information on ingredients, including the presence of sorghum, food format, brand, product name, wholegrain/gluten-free labelling was recorded. In China, sorghum was found in 4.3% (12/279) of breakfast cereals, with only 1/12 sorghum-containing breakfast cereals listed sorghum in the first position of the ingredient list. Sorghum was found in 2.0% (9/458) of snack bars and was listed as either 'sorghum' (n = 3) or 'sorghum flour' (n = 6). In Australia, sorghum was found in 22/356 (6.2%) breakfast cereals, 9/285 (3.2%) snack bars, and was absent from all flours, pastas, and noodles. Most sorghum-containing cereals were extruded (36.4%) and labelled gluten-free (16/22, 73%) or wholegrain (14/22, 64%). Sorghum-containing snack bars, notably oat-bake and muesli bars, were mostly made from sorghum flour and flakes. Sorghum appeared in the first position in the ingredient list in 2/22 (9.1%) of breakfast cereals, and in the third or higher position for all snack bars. Among the breakfast cereal and snack bar subcategories analyzed, there were no significant differences in sorghum utilization between China and Australia (Fisher's Exact Tests, p < 0.05), except for oat bake snack bars (higher in China, p = 0.0265). Overall, the audit data suggests that sorghum is not widely incorporated as an ingredient in common grain-based food products available to consumers in major Chinese and Australian supermarkets. Greater awareness of its potential consumer health benefits is needed to drive utilization of sorghum grain in foods across different markets.
A yellow strain, designated YCB016T, was isolated from rhizosphere soil of Camellia oleifera Abel collected from Xingning city, Guangdong Province, PR China. The strain was aerobic, rod-shaped, without flagella. Phylogenetic analysis of 16S rRNA gene revealed strain YCB016T showed the highest similarities of 98.9% and 98.2% to Trinickia terrae 7GSK02T, Trinickia mobilis DHG64T and Trinickia fusca GDMCC 1.1449T, respectively. The phylogenomic tree revealed strain YCB016T formed a clade with Trinickia violacea DHOD12T. The major cellular fatty acids of strain YCB016T included C16:0, C17:0 cyclo, C19:0 cyclo ɷ8c and summed feature 8. The major polar lipids were phosphatidylethanolamine, diphosphatidylglycerol, phosphatidylglycerol and hydroxyphosphatidylethanolamine. The predominant respiratory quinone was ubiquinone-8. The average nucleotide identities (ANI) and the digital DNA-DNA hybridization (dDDH) values among strain YCB016T and all 11 species of the genus Trinickia were 77.7-92.8% and 22.3-50.4%, respectively, which are interspersed on the intra-species cutoff values. The draft genome size of strain YCB016T was 7.3 Mbp with a DNA G + C content of 63.5%. Based on phenotypic, chemotaxonomic, phylogenetic analysis, genomic DNA G + C content, ANI and dDDH values, strain YCB016T represents a novel species of the genus Trinickia, for which the name Trinickia camelliae sp. nov. is proposed. The type strain is YCB016T (= GDMCC 1.3849T = JCM 36232T). Additionally, strain YCB016T produced siderophore, cellulase and lipase whereas T. fusca GDMCC 1.1449T produced siderophore and indoleacetic acid (IAA). The Trinickia symbiotica JPY-345T and Trinickia caryophylli DSM 50341T contained nifH and nifD genes while other species did not. The nodD gene was present in all species. Collectively, the genus Trinickia exhibited potential plant growth-promoting activities.