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Analytical validation of a LC-MS/MS based in vitro diagnostic kit for the quantification of L-tyrosine and taurocholic acid for liver fibrosis diagnosis
No full textBackground: FibraChek is a newly developed mass spectrometry (MS) assay kit approved by the National Medical Products Administration (NMPA) of China for quantifying L-tyrosine (Tyr) and taurocholic acid (TCA) in serum, aiding liver fibrosis diagnosis. This study aimed to assess its analytical performance. Methods: The analytical performance was investigated based on NMPA and CLSI guidelines. Method suitability in the clinical context was tested by analyzing clinical samples from liver fibrosis patients confirmed via liver biopsy. Results: The assay enables simultaneous determination of Tyr and TCA, demonstrating compliance with performance parameters such as linearity, dynamic range, limit of detection (LOD), limit of quantification (LOQ), recovery, repeatability, reproducibility, and stability. It validated a linear range of 20–1000 μmol/L for Tyr and 10.3–618 ng/ml for TCA, maintaining stability after 5 freeze-thaw cycles for 14 months. Components remained stable for up to 7 days at room temperature and 30 days at 2–8 °C. TCA and Tyr were stable for up to 36 months at −20 °C or −80 °C. The method effectively quantified Tyr and TCA in serum from liver fibrosis patients and healthy controls. Conclusions: This is the first MS-based assay for non-invasive liver fibrosis detection validated for clinical use, providing a rapid and reliable analytical protocol suitable for routine analysis.</p
Relational characteristics and dynamics between high-tech firms in the Pearl River Delta and the empowerment for technological innovation by Hong Kong
No full textThe perfection of the cross-border regional innovation system of the Pearl River Delta (PRD) and Hong Kong remarkably underpins the construction of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) towards an international technological innovation hub. This paper focuses on the relational characteristics of the usage of technological innovation functions and elements, including labor force, technology, and producer services from Hong Kong by high-technology firms in the PRD, and probes into the influencing factors by integrating the objective perspective on the impact of firm-level socioeconomic attributes and subjective perspective on the open interpretations on the reasons by using or not using technological innovation functions and elements from Hong Kong by various stakeholders in high-technology domains in the PRD. Key research findings are fourfold. First, Hong Kong’s technological innovation functions primarily ride on its institutional advantages under the “One Country, Two Systems” framework to empower high-technology firms in the PRD by expanding their international market, international business operation, and financing, but cross-border investment and entrepreneurship has retrieved to a relatively marginalized position. The degree of supply-demand relations of producer services is the highest, followed by labor force and technology. Second, Hong Kong-invested, large-sized, and long-standing high-technology firms in the PRD are more inclined to use technological innovation elements from Hong Kong, while domestic, small-and-medium-sized, and start-up high-technology firms in the PRD are in turn, gradually unhooked from the supply of technological innovation elements from Hong Kong. Third, Hong Kong enjoys both advantages and disadvantages in supplying labor forces, technologies, and producer services to high-technology firms in the PRD, with advantages in competitiveness, international linkages and visions, and disadvantages in high cost, lack of more profound mutual understanding between Hong Kong and the PRD, and the imperfect cooperation mechanisms. Fourth, interactions among the transitioning role of Hong Kong in the macro-level global and national economic development landscape, meso-level cross-border regional specificities under the “One Country, Two Systems” framework, and micro-level heterogeneous practices and capabilities of firms influence the usage of technological innovation functions and elements from Hong Kong by high-technology firms in the PRD.</p
π-Extended Heli(aminoborane)s with Highly Bright Circularly Polarized Luminescence and Narrowband Emission
No full textHelical molecular carbons (HMCs) possess high absorption/luminescence dissymmetry factors (gabs/glum) and significant luminescence quantum yield (Φlum), resulting in a high circularly polarized luminescence (CPL) brightness (BCPL), which is essential for the development of CPL materials for practical applications. Herein, we designed and synthesized a series of boron-nitrogen (BN)-doped HMCs, named π-extended heli(aminoborane)s (E[10]HAB-A, E[10]HAB-B and E[10]HAB-C), consisting of laterally π-extended [10]helicene skeleton with alternating N and B atoms at the inner rim. The aromaticity, electronic structures, and photophysical properties of E[10]HAB-A/B/C were systematically investigated through experiments and theoretical calculations. E[10]HAB-A/B/C displayed remarkable photophysical properties, including high molar extinction coefficient and bright narrowband emission. The isolated enantiomers of E[10]HAB-A/B/C exhibited intense circular dichroism (CD) and CPL, in which E[10]HAB-A shows gabs and glum values up to 0.024 and 0.017, simultaneously with high Φlum of 82 % and a narrow full width at half maximum of 16 nm. Accordingly, E[10]HAB-A exhibits a BCPL as high as 583 M−1 cm−1, which is the largest value among the reported BN-doped HMCs. Our study indicates that inner rim BN-doping and π-extension are effective strategies to achieve high Φlum and balanced glum values in HMCs
Understanding human brain function in real-world environments
No full textFunctional MRI is invaluable in understanding brain function, but findings are often of limited real-world relevance. Neuroimaging in more naturalistic environments could reveal crucial insights into how the brain processes cognition, emotional experiences, and social interactions in daily life.</p
Clinical significance of the tumor microenvironment on immune tolerance in gastric cancer
No full textIn the realm of oncology, the tumor microenvironment (TME)—comprising extracellular matrix components, immune cells, fibroblasts, and endothelial cells—plays a pivotal role in tumorigenesis, progression, and response to therapeutic interventions. Initially, the TME exhibits tumor-suppressive properties that can inhibit malignant transformation. However, as the tumor progresses, various factors induce immune tolerance, resulting in TME behaving in a state that promotes tumor growth and metastasis in later stages. This state of immunosuppression is crucial as it enables TME to change from a role of killing tumor cells to a role of promoting tumor progression. Gastric cancer is a common malignant tumor of the gastrointestinal tract with an alarmingly high mortality rate. While chemotherapy has historically been the cornerstone of treatment, its efficacy in prolonging survival remains limited. The emergence of immunotherapy has opened new therapeutic pathways, yet the challenge of immune tolerance driven by the gastric cancer microenvironment complicates these efforts. This review aims to elucidate the intricate role of the TME in mediating immune tolerance in gastric cancer and to spotlight innovative strategies and clinical trials designed to enhance the efficacy of immunotherapeutic approaches. By providing a comprehensive theoretical framework, this review seeks to advance the understanding and application of immunotherapy in the treatment of gastric cancer, ultimately contributing to improved patient outcomes
A functional anatomical shift from the lateral frontal pole to dorsolateral prefrontal cortex in emotion action control underpins elevated levels of anxiety: partial replication and generalization of Bramson et al., 2023
Get PDFBackground: Emotion control represents a promising intervention target for mental disorders. In a recent study Bramson et al. (2023) demonstrate a functional-anatomical shift from the lateral frontal pole (FPl) to the dorsolateral prefrontal cortex (DLPFC) in anxious individuals during emotional action control. However, findings of neuroimaging experiments are often limited regarding generalizability and reproducibility. The present study examined the robustness of the reported functional shift across samples, cultures and paradigms. Methods: We capitalized on large-scale task fMRI data (n = 250 participants) using an affective linguistic Go/NoGo paradigm to examine the anxiety-related shift between FPl and DLPFC during emotional action control. Additionally, context-dependent functional connectivity analyses were employed to examine anxiety-related differences and associations on the network level. Results: Non-anxious individuals engaged the left FPl while highly anxious individuals specifically recruited the DLPFC, but non-significant between-group differences were found (see also Bramson et al.). The secondary analyses revealed moderate evidence for the absence of left FPl activation in the high-anxious as well as for left DLPFC activation in the non-anxious group. Additionally, trait anxiety scores were positively correlated with left DLPFC activity but negatively correlated with left FPl activity across groups. Furthermore, we found a context-specific connectivity shift between the subgenual anterior cingulate cortex (sgACC) with the FPl and DLPFC specifically in highly anxious individuals. Conclusion: The results partially confirmed the anxiety-related shift as reported by Bramson and colleagues across paradigms and samples. The findings provide further support for the functional shift in anxiety and can inform target-based interventions of persistent emotional control deficits in anxiety disorders.published_or_final_versio
Bidirectional Higher-Rank Polymorphism with Intersection and Union Types
Get PDFModern mainstream programming languages, such as TypeScript, Flow, and Scala, have polymorphic type systems enriched with intersection and union types. These languages implement variants of bidirectional higher-rank polymorphic type inference, which was previously studied mostly in the context of functional programming. However, existing type inference implementations lack solid theoretical foundations when dealing with non-structural subtyping and intersection and union types, which were not studied before. In this paper, we study bidirectional higher-rank polymorphic type inference with explicit type applications, and intersection and union types and demonstrate that these features have non-trivial interactions. We first present a type system, described by a bidirectional specification, with good theoretical properties and a sound, complete, and decidable algorithm. This is helpful to identify a class of types that can always be inferred. We also explore variants incorporating practical features, such as handling records and inferring a larger class of types, which align better with real-world implementations. Though some variants no longer have a complete algorithm, they still enhance the expressiveness of the type system. To ensure rigor, all results are formalized in the Coq proof assistant.published_or_final_versio
The Role of Virtual Reality on Parkinson’s Disease Management: A Bibliometric and Content Analysis
No full textThe management of Parkinson’s disease (PD) has increasingly focused on innovative technologies, particularly virtual reality (VR), which has emerged as a significant tool for addressing neurological disorders. This bibliometric analysis summarizes current research trends and hotspots regarding VR applications in PD management. A comprehensive search of the Science Citation Index Expanded (SCIE) within the Web of Science Core Collection (WoSCC) identified 475 publications from 2000 to 2024. Key findings indicate a substantial increase in publication output, especially after 2013, driven by technological advancements and investments from major IT companies. Prominent research institutions and scholars from Australia, Israel, Italy, and Spain have led this field, exploring various VR applications for PD patients. The focus of VR therapy research has evolved from primarily addressing freezing of gait (FOG) to a broader range of functional impairments, including balance, postural control, upper limb motor, and cognitive function. This study provides valuable insights into the evolving landscape of clinical research on VR in PD management, highlighting global trends and potential areas for future investigation and application of VR therapies.link_to_subscribed_fulltex
Response to the Letter to the Editor: “A Deep Learning System to Predict Epithelial Dysplasia in Oral Leukoplakia”
No full textDeep learning with data transformation improves cancer risk prediction in oral precancerous conditions
Get PDFBackground: Oral cancer is the most common head and neck malignancy and may develop from oral leukoplakia (OL) and oral lichenoid disease (OLD). Machine learning classifiers using structured (tabular) data have been employed to predict malignant transformation in OL and OLD. However, current models require improved discrimination, and their frameworks may limit feature fusion and multimodal risk prediction. Therefore, this study investigates whether tabular-to-image data conversion and deep learning (DL) based on convolutional neural networks (CNNs) can improve malignant transformation prediction compared to traditional classifiers. Methods: This study used retrospective data of 1,010 patients with OL and OLD treated at Queen Mary Hospital, Hong Kong, from January 2003 to December 2023, to construct artificial intelligence-based models for oral cancer risk stratification in OL/OLD. Twenty-five input features and information on oral cancer development in OL/OLD were retrieved from electronic health records. Tabular-to-2D image data transformation was achieved by creating a feature matrix from encoded labels of the input variables arranged according to their correlation coefficient. Then, 2D images were used to populate five pre-trained DL models (VGG16, VGG19, MobileNetV2, ResNet50, and EfficientNet-B0). Area under the receiver operating characteristic curve (AUC), Brier scores, and net benefit of the DL models were calculated and compared to five traditional classifiers based on structured data and the binary epithelial dysplasia grading system (current method). Results: This study found that the DL models had better AUC values (0.893–0.955) and Brier scores (0.072–0.106) compared to the traditional classifiers (AUC: 0.887–0.941 and Brier score: 0.074–0.136) during validation. During internal testing, VGG16 and VGG19 had better AUC values and Brier scores than other CNNs (AUC: 0.998–1.00; Brier score: 0.036–0.044) and the best traditional classifier (random forest) (AUC: 0.906; Brier score: 0.153). Additionally, VGG16 and VGG19 models outperformed random forest in discrimination and calibration during external testing (AUC: 1.00 vs. 0.976; Brier score: 0.022–0.034 vs. 0.129). The best CNNs also had better discriminatory performance and calibration than binary dysplasia grading at internal and external testing. Overall, decision curve analysis showed that the optimal DL models with transformed data had a higher net benefit than random forest and binary dysplasia grading. Conclusion: Tabular-to-2D image data transformation may improve the use of structured input features for developing optimal intelligent models for oral cancer risk prediction in OL and OLD using convolutional networks. This approach may have the potential to robustly handle structured data in multimodal DL frameworks for oncological outcome prediction.published_or_final_versio