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Background The impetus for policies promoting medical data sharing in China has gained significant traction. Nonetheless, the present legal and ethical framework governing the research use of medical data in China, is characterized by a more restrictive rather than permissive approach. The proportion of Chinese medical data being leveraged for scientific research still has room for improvement at present, indicating a significant untapped potential for advancing medical knowledge and improving healthcare outcomes. Building upon this research, we aim to delve deeper into the challenges researchers encounter in the sharing of medical data through focus group interviews. Methods We conducted two focus group interviews study with researchers representing diverse disciplines to explore their perspectives on 21 June 2021 and 28 July 2021. A total of seventeen researchers willingly participated in this study, representing various professional backgrounds. Similar codes were merged. Research team discussions were also utilized to select interviewees’ statements that were regarded as typical or representative. Results The respondents demonstrated a strong understanding that medical data should not be disseminated arbitrarily, recognizing the importance of sharing data in compliance with laws. Through the interview, we found that although respondents stressed the importance of careful consideration regarding if and when this information can be responsibly released, none of the respondents raised the issue of necessitating consent from data subjects for the research use of medical data. This observation sharply contrasts with the stringent separate consent provisions for secondary data use outlined in the PIPL. Conclusions The findings from the focus group studies shed light on researchers’ barriers and ethical challenges towards medical data sharing for scientific research, highlighting their deep concern for data security and cautious approach to sharing. The key objectives aimed at facilitating and enabling the reuse of medical data encompass enhancing interoperability, harmonizing data standards, improving data quality, safeguarding privacy, ensuring informed consent, incentivizing patients, and establishing explicit regulations pertaining to data access and utilization.

In recent years, natural polysaccharides have received growing attention and interest in view of their values in food, medical, cosmetics and other fields. Eleutherococcus senticosus ( E. senticosus ) is a medicine and food homologous plant that possess anti-tumor, anti-inflammatory, central nervous system and cardiovascular protection, anti-radiation, enhancement of human microcirculation, improvement of physical fatigue effects, mainly based on lignans, flavonoids and coumarin types. E. senticosus polysaccharides (ESPS), act as a kind of polysaccharide extracted and isolated from the root and rhizome of E. senticosus , have been found in many applications of medicine and food for their unique biological activity. Nevertheless, the existing studies are mostly concerned with small molecules of E. senticosus , less attention is paid to polysaccharides. Moreover, the types and structural characterization of ESPS reported in existing literature were also not summarized. In this paper, the research progress of ESPS is reviewed from the aspects of extraction, separation, structural characterization and biological activity, future perspectives from points of efficient extraction, resource utilization and quality control standards were also proposed, which provide reference for the further development and utilization of ESPS.

Early detection has the potential to reduce cancer mortality, but an effective screening test must demonstrate asymptomatic cancer detection years before conventional diagnosis in a longitudinal study. In the Taizhou Longitudinal Study (TZL), 123,115 healthy subjects provided plasma samples for long-term storage and were then monitored for cancer occurrence. Here we report the preliminary results of PanSeer, a noninvasive blood test based on circulating tumor DNA methylation, on TZL plasma samples from 605 asymptomatic individuals, 191 of whom were later diagnosed with stomach, esophageal, colorectal, lung or liver cancer within four years of blood draw. We also assay plasma samples from an additional 223 cancer patients, plus 200 primary tumor and normal tissues. We show that PanSeer detects five common types of cancer in 88% (95% CI: 80–93%) of post-diagnosis patients with a specificity of 96% (95% CI: 93–98%), We also demonstrate that PanSeer detects cancer in 95% (95% CI: 89–98%) of asymptomatic individuals who were later diagnosed, though future longitudinal studies are required to confirm this result. These results demonstrate that cancer can be non-invasively detected up to four years before current standard of care. Patients whose disease is diagnosed in its early stages have better outcomes. In this study, the authors develop a non invasive blood test based on circulating tumor DNA methylation that can potentially detect cancer occurrence even in asymptomatic patients.

Objectives Carcinoma-associated fibroblasts (CAFs) have been known to promote cancer progression by modifying the primary tumor microenvironment. We aimed to elucidate the intercellular communication between CAFs and secondary organs in salivary adenoid cystic carcinoma (SACC) metastasis. Methods Pre-metastatic and metastatic animal models of SACC were established using extracellular vesicles (EVs) from CAFs and SACC cells. Lung fibroblasts (LFs) were treated with EVs and their transcriptomic alterations were identified by RNA sequencing. ITRAQ were performed to analyze EV cargos. TC I-15 was used to inhibit EV uptake by LFs and SACC lung metastasis in vivo. Results Here, we show that CAF EVs induced lung pre-metastatic niche formation in mice and consequently increased SACC lung metastasis. The pre-metastatic niche induced by CAF EVs was different from that induced by SACC EVs. CAF EVs presented a great ability for matrix remodeling and periostin is a potential biomarker characterizing the CAF EV-induced pre-metastatic niche. We found that lung fibroblast activation promoted by CAF EVs was a critical event at the pre-metastatic niche. Integrin α2β1 mediated CAF EV uptake by lung fibroblasts, and its blockage by TC I-15 prevented lung pre-metastatic niche formation and subsequent metastasis. Plasma EV integrin β1 was considerably upregulated in the mice bearing xenografts with high risk of lung metastasis. Conclusions We demonstrated that CAF EVs participated in the pre-metastatic niche formation in the lung. Plasma EV integrin β1 might be a promising biomarker to predict SACC metastasis at an early stage. An integrated strategy targeting both tumor and stromal cells is necessary to prevent SACC metastasis.

Increasing attention has been attracted by exosomes in blood-based diagnosis because cancer cells release more exosomes in serum than normal cells and these exosomes overexpress a certain number of cancer-related biomarkers. However, capture and biomarker analysis of exosomes for clinical application are technically challenging. In this study, we developed a microfluidic chip for immunocapture and quantification of circulating exosomes from small sample volume and applied this device in clinical study. Circulating EpCAM-positive exosomes were measured in 6 cases breast cancer patients and 3 healthy controls to assist diagnosis. A significant increase in the EpCAM-positive exosome level in these patients was detected, compared to healthy controls. Furthermore, we quantified circulating HER2-positive exosomes in 19 cases of breast cancer patients for molecular classification. We demonstrated that the exosomal HER2 expression levels were almost consistent with that in tumor tissues assessed by immunohistochemical staining. The microfluidic chip might provide a new platform to assist breast cancer diagnosis and molecular classification.

Background Cerebral palsy (CP) is a kind of disability that influences motion, and children with CP also exhibit depression-like behaviour. Inflammation has been recognized as a contributor to CP and depression, and some studies suggest that the gut-brain axis may be a contributing factor. Our team observed that Saccharomyces boulardii (S. boulardii) could reduce the inflammatory level of rats with hyperbilirubinemia and improve abnormal behaviour. Both CP and depression are related to inflammation, and probiotics can improve depression by reducing inflammation. Therefore, we hypothesize that S. boulardii may improve the behaviour and emotions of spastic CP rats through the gut-brain axis pathway. Methods Our new rat model was produced by resecting the cortex and subcortical white matter. Seventeen-day-old CP rats were exposed to S. boulardii or vehicle control by gastric gavage for 9 days, and different behavioural domains and general conditions were tested. Inflammation was assessed by measuring the inflammatory markers IL-6 and TNF-α. Hypothalamic–pituitary–adrenal (HPA) axis activity was assessed by measuring adrenocorticotropic hormone and corticosterone in the serum. Changes in the gut microbiome were detected by 16S rRNA. Results The hemiplegic spastic CP rats we made with typical spastic paralysis exhibited depression-like behaviour. S. boulardii treatment of hemiplegic spastic CP rats improves behaviour and general conditions and significantly reduces the level of inflammation, decreases HPA axis activity, and increases gut microbiota diversity. Conclusions The model developed in this study mimics a hemiplegic spastic cerebral palsy. Damage to the cortex and subcortical white matter of 17-day-old Sprague–Dawley (SD) rats led to spastic CP-like behaviour, and the rats exhibited symptoms of depression-like behaviour. Our results indicate that S. boulardii might have potential in treating hemiplegic spastic CP rat models or as an add-on therapy via the gut-brain axis pathway.

Background Psittacosis, which is also known as parrot fever, is Chlamydia psittaci (C. psittaci) caused infectious disease . The clinical manifestations vary from asymptomatic infection to severe atypical pneumonia or even fatal meningitis. Early recognition of psittacosis is difficult because of its nonspecific clinical manifestations. Culture and gene probe techniques for C. psittaci are not available for routine clinical use, which makes the diagnosis difficult too. Although psittacosis has increasingly been recognized and reported in recent years, cure of severe pneumonia complicated with meningitis, with etiologic diagnosis aided by the use of metagenomic next-generation sequencing (mNGS), is still uncommon. So, it is necessary to report and review such potentially fatal case. Case presentation This report describes a 54-year-old woman with C. psittaci caused severe atypical pneumonia and meningitis. She presented with symptoms of fever, dry cough and dyspnea, accompanied by prominent headache. Her condition deteriorated rapidly to respiratory failure and lethargy under the treatment of empirical antibacterial agents, and was treated with invasive mechanical ventilation soon. She denied contact with birds, poultry or horses, but unbiased mNGS of both the bronchoalveolar lavage fluid (BALF) and the cerebrospinal fluid (CSF) identified sequence reads corresponding to C. psittaci infection, and there was no sequence read corresponding to other probable pathogens. Combined use of targeted antimicrobial agents of tetracyclines, macrolides and fluoroquinolones was carried out, and the patient’s condition improved and she was discharged home 28 days later. Her status returned close to premorbid condition on day 60 of follow-up. Conclusions When clinicians come across a patient with atypical pneumonia accompanied by symptoms of meningitis, psittacosis should be taken into consideration. mNGS is a promising detection method in such condition and is recommended.

Traffic time series anomaly detection has been intensively studied for years because of its potential applications in intelligent transportation. However, classical traffic anomaly detection methods often overlook the evolving dynamic associations between road network nodes, which leads to challenges in capturing the long-term temporal correlations, spatial characteristics, and abnormal node behaviors in datasets with high periodicity and trends, such as morning peak travel periods. In this paper, we propose a mirror temporal graph autoencoder (MTGAE) framework to explore anomalies and capture unseen nodes and the spatiotemporal correlation between nodes in the traffic network. Specifically, we propose the mirror temporal convolutional module to enhance feature extraction capabilities and capture hidden node-to-node features in the traffic network. Morever, we propose the graph convolutional gate recurrent unit cell (GCGRU CELL) module. This module uses Gaussian kernel functions to map data into a high-dimensional space, and enables the identification of anomalous information and potential anomalies within the complex interdependencies of the traffic network, based on prior knowledge and input data. We compared our work with several other advanced deep-learning anomaly detection models. Experimental results on the NYC dataset illustrate that our model works best compared to other models for traffic anomaly detection.

Background Astragalus membranaceus var. mongholicus (Astragalus), acknowledged as a pivotal “One Root of Medicine and Food”, boasts dual applications in both culinary and medicinal domains. The growth and metabolite accumulation of medicinal roots during the harvest period is intricately regulated by a transcriptional regulatory network. One key challenge is to accurately pinpoint the harvest date during the transition from conventional yield content of medicinal materials to high and to identify the core regulators governing such a critical transition. To solve this problem, we performed a correlation analysis of phenotypic, transcriptome, and metabolome dynamics during the harvesting of Astragalus roots. Results First, our analysis identified stage-specific expression patterns for a significant proportion of the Astragalus root genes and unraveled the chronology of events that happen at the early and later stages of root harvest. Then, the results showed that different root developmental stages can be depicted by co-expressed genes of Astragalus. Moreover, we identified the key components and transcriptional regulation processes that determine root development during harvest. Furthermore, through correlating phenotypes, transcriptomes, and metabolomes at different harvesting periods, period D (Nov.6) was identified as the critical period of yield and flavonoid content increase, which is consistent with morphological and metabolic changes. In particular, we identified a flavonoid biosynthesis metabolite, isoliquiritigenin, as a core regulator of the synthesis of associated secondary metabolites in Astragalus. Further analyses and experiments showed that HMGCR , 4CL , CHS , and SQLE , along with its associated differentially expressed genes, induced conversion of metabolism processes, including the biosynthesis of isoflavones and triterpenoid saponins substances, thus leading to the transition to higher medicinal materials yield and active ingredient content. Conclusions The findings of this work will clarify the differences in the biosynthetic mechanism of astragaloside IV and calycosin 7-O-β-D-glucopyranoside accumulation between the four harvesting periods, which will guide the harvesting and production of Astragalus.

Extracellular vesicles (EVs) are important intercellular mediators regulating health and diseases. Conventional methods for EV surface marker profiling, which was based on population measurements, masked the cell-to-cell heterogeneity in the quantity and phenotypes of EV secretion. Herein, by using spatially patterned antibody barcodes, we realized multiplexed profiling of single-cell EV secretion from more than 1,000 single cells simultaneously. Applying this platform to profile human oral squamous cell carcinoma (OSCC) cell lines led to a deep understanding of previously undifferentiated single-cell heterogeneity underlying EV secretion. Notably, we observed that the decrement of certain EV phenotypes (e.g., CD63+EV) was associated with the invasive feature of both OSCC cell lines and primary OSCC cells. We also realized multiplexed detection of EV secretion and cytokines secretion simultaneously from the same single cells to investigate the multidimensional spectrum of cellular communications, from which we resolved tiered functional subgroups with distinct secretion profiles by visualized clustering and principal component analysis. In particular, we found that different cell subgroups dominated EV secretion and cytokine secretion. The technology introduced here enables a comprehensive evaluation of EV secretion heterogeneity at single-cell level, which may become an indispensable tool to complement current singlecell analysis and EV research.