Protocol for integrating tissue clearing and light-sheet imaging to analyze cancer initiation in mosaic analysis with double markers mouse models.

Mosaic analysis with double markers (MADM) mouse models closely mimic the clonal origin of human cancers by generating sporadic, GFP-labeled cancer-initiating cells. Traditional clonal analysis pipelines are labor intensive, hindering throughput and disrupting the 3D architecture. Here, we present a protocol that integrates tissue clearing and light-sheet imaging to analyze pre-malignant clones in whole-mount MADM-labeled tissues. We describe steps for generating mosaic-labeled cancer mouse models, tissue harvesting, fixation, and clearing. We then detail procedures for light-sheet imaging and clonal size analysis. For complete details on the use and execution of this protocol, please refer to Zeng et al.1,2.

The effect of rehabilitation time on functional recovery after arthroscopic rotator cuff repair: a systematic review and meta-analysis.

Objective: We compared the effects of early and delayed rehabilitation on the function of patients after rotator cuff repair by meta-analysis to find effective interventions to promote the recovery of shoulder function. Methods: This meta-analysis was registered in PROSPERO (CRD42023466122). We manually searched the randomized controlled trials (RCTs) in the Cochrane Library, Pubmed, Cochrane Library, EMBASE, the China National Knowledge Infrastructure (CNKI), the China VIP Database (VIP), and the Wanfang Database to evaluate the effect of early and delayed rehabilitation after arthroscopic shoulder cuff surgery on the recovery of shoulder joint function. Review Manager 5.3 software was used to analyze the extracted data. Then, the PEDro scale was employed to appraise the methodological quality of the included research. Results: This research comprised nine RCTs and 830 patients with rotator cuff injuries. According to the findings of the meta-analysis, there was no discernible difference between the early rehabilitation group and the delayed rehabilitation group at six and twelve months after the surgery in terms of the VAS score, SST score, follow-up rotator cuff healing rate, and the rotator cuff retear rate at the final follow-up. There was no difference in the ASES score between the early and delayed rehabilitation groups six months after the operation. However, although the ASES score in the early rehabilitation group differed significantly from that in the delayed rehabilitation group twelve months after the operation, according to the analysis of the minimal clinically important difference (MCID), the results have no clinical significance. Conclusions: The improvement in shoulder function following arthroscopic rotator cuff surgery does not differ clinically between early and delayed rehabilitation. When implementing rehabilitation following rotator cuff repair, it is essential to consider the paradoxes surrounding shoulder range of motion and tendon anatomic healing. A program that allows for flexible progression based on the patient's ability to meet predetermined clinical goals or criteria may be a better option.

The CREB1/WNK1 axis promotes the tumorigenesis of ovarian cancer via regulating HIF-1.

The aim of this study was to explore the functions and molecular mechanisms of the WNK lysine deficient protein kinase 1 (WNK1) in the development of ovarian cancer. Firstly, loss- and gain-of-function assays were carried out and subsequently cell proliferation, apoptosis, invasion and migration were detected. Furthermore, WNK1 action on glucose uptake, lactate production and adenosine triphosphate (ATP) level were assessed. The roles of WNK1 on cisplatin resistance were explored using CCK-8, colony formation, and flow cytometry in vitro. Immunohistochemistry, Western blot and qRT-PCR were conducted to determine the protein and mRNA expression. Additionally, tumor growth in vivo was also monitored. We found that the overexpression of WNK1 predicted a bad prognosis of ovarian cancer patients. WNK1 enhanced the malignant behavior and facilitated glycolysis of ovarian cancer cells. Moreover, WNK1 increased cisplatin resistance in ovarian cancer cells. Mechanistically, we found that WNK1 expression was promoted by CREB1 at the transcriptional level. And CREB1 could facilitate ovarian cancer cells malignant behavior through target upregulating WNK1. Besides, we also showed that WNK1 facilitated the malignant behavior by accelerating HIF-1 expression. In xenograft tumor tissues, the downregulation of WNK1 significantly reduced HIF-1α expression. These data demonstrated that the CREB1/WNK1 axis could promote the tumorigenesis of ovarian cancer via accelerating HIF-1 expression, suggesting that the CREB1/WNK1 axis could be a potential target during the therapy of ovarian cancer.

Open-Top Patterned Hydrogel-Laden 3D Glioma Cell Cultures for Creation of Dynamic Chemotactic Gradients to Direct Cell Migration.

The laminar flow profiles in microfluidic systems coupled to rapid diffusion at flow streamlines have been widely utilized to create well-controlled chemical gradients in cell cultures for spatially directing cell migration. However, within hydrogel-based closed microfluidic systems of limited depth (≤0.1 mm), the biomechanical cues for the cell culture are dominated by cell interactions with channel surfaces rather than with the hydrogel microenvironment. Also, leaching of poly(dimethylsiloxane) (PDMS) constituents in closed systems and the adsorption of small molecules to PDMS alter chemotactic profiles. To address these limitations, we present the patterning and integration of a PDMS-free open fluidic system, wherein the cell-laden hydrogel directly adjoins longitudinal channels that are designed to create chemotactic gradients across the 3D culture width, while maintaining uniformity across its ∼1 mm depth to enhance cell-biomaterial interactions. This hydrogel-based open fluidic system is assessed for its ability to direct migration of U87 glioma cells using a hybrid hydrogel that includes hyaluronic acid (HA) to mimic the brain tumor microenvironment and gelatin methacrylate (GelMA) to offer the adhesion motifs for promoting cell migration. Chemotactic gradients to induce cell migration across the hydrogel width are assessed using the chemokine CXCL12, and its inhibition by AMD3100 is validated. This open-top hydrogel-based fluidic system to deliver chemoattractant cues over square-centimeter-scale areas and millimeter-scale depths can potentially serve as a robust screening platform to assess emerging glioma models and chemotherapeutic agents to eradicate them.

A novel bispecific antibody drug conjugate targeting HER2 and HER3 with potent therapeutic efficacy against breast cancer.

Antibody drug conjugate (ADC) therapy has become one of the most promising approaches in cancer immunotherapy. Bispecific targeting could enhance the efficacy and safety of ADC by improving its specificity, affinity and internalization. In this study we constructed a HER2/HER3-targeting bispecific ADC (BsADC) and characterized its physiochemical properties, target specificity and internalization in vitro, and assessed its anti-tumor activities in breast cancer cell lines and in animal models. The HER2/HER3-targeting BsADC had a drug to antibody ratio (DAR) of 2.89, displayed a high selectivity against the target JIMT-1 breast cancer cells in vitro, as well as a slightly higher level of internalization than HER2- or HER3-monospecific ADCs. More importantly, the bispecific ADC potently inhibited the viability of MCF7, JIMT-1, BT474, BxPC-3 and SKOV-3 cancer cells in vitro. In JIMT-1 breast cancer xenograft mice, a single injection of bispecific ADC (3 mg/kg, i.v.) significantly inhibited the tumor growth with an efficacy comparable to that caused by combined injection of HER2 and HER3-monospecific ADCs (3 mg/kg for each). Our study demonstrates that the bispecific ADC concept can be applied to development of more potent new cancer therapeutics than the monospecific ADCs.

PCAO2: an ontology for integration of prostate cancer associated genotypic, phenotypic and lifestyle data.

Disease ontologies facilitate the semantic organization and representation of domain-specific knowledge. In the case of prostate cancer (PCa), large volumes of research results and clinical data have been accumulated and needed to be standardized for sharing and translational researches. A formal representation of PCa-associated knowledge will be essential to the diverse data standardization, data sharing and the future knowledge graph extraction, deep phenotyping and explainable artificial intelligence developing. In this study, we constructed an updated PCa ontology (PCAO2) based on the ontology development life cycle. An online information retrieval system was designed to ensure the usability of the ontology. The PCAO2 with a subclass-based taxonomic hierarchy covers the major biomedical concepts for PCa-associated genotypic, phenotypic and lifestyle data. The current version of the PCAO2 contains 633 concepts organized under three biomedical viewpoints, namely, epidemiology, diagnosis and treatment. These concepts are enriched by the addition of definition, synonym, relationship and reference. For the precision diagnosis and treatment, the PCa-associated genes and lifestyles are integrated in the viewpoint of epidemiological aspects of PCa. PCAO2 provides a standardized and systematized semantic framework for studying large amounts of heterogeneous PCa data and knowledge, which can be further, edited and enriched by the scientific community. The PCAO2 is freely available at https://bioportal.bioontology.org/ontologies/PCAO, http://pcaontology.net/ and http://pcaontology.net/mobile/.

RARPKB: A knowledge-guide decision support platform for personalized robot-assisted surgery in prostate cancer.

BACKGROUND: Robot-assisted radical prostatectomy (RARP) has emerged as a pivotal surgical intervention for the treatment of prostate cancer. However, the complexity of clinical cases, heterogeneity of prostate cancer, and limitations in physician expertise pose challenges to rational decision-making in RARP. To address these challenges, we aimed to organize the knowledge of previously complex cohorts and establish an online platform named the RARP Knowledge Base (RARPKB) to provide reference evidence for personalized treatment plans. MATERIALS AND METHODS: PubMed searches over the past two decades were conducted to identify publications describing RARP. We collected, classified, and structured surgical details, patient information, surgical data, and various statistical results from the literature. A knowledge-guided decision-support tool was established using MySQL, DataTable, ECharts, and JavaScript. ChatGPT-4 and two assessment scales were used to validate and compare the platform. RESULTS: The platform comprised 583 studies, 1589 cohorts, 1 911 968 patients, and 11 986 records, resulting in 54 834 data entries. The knowledge-guided decision support tool provide personalized surgical plan recommendations and potential complications on the basis of patients' baseline and surgical information. Compared with ChatGPT-4, RARPKB outperformed in authenticity (100% versus [vs.] 73%), matching (100% vs. 53%), personalized recommendations (100% vs. 20%), matching of patients (100% vs. 0%), and personalized recommendations for complications (100% vs. 20%). Post-use, the average System Usability Scale score was 88.88±15.03, and the Net Promoter Score of RARPKB was 85. The knowledge base is available at http://rarpkb.bioinf.org.cn. CONCLUSIONS: We introduced the pioneering RARPKB, the first knowledge base for robot-assisted surgery, with an emphasis on prostate cancer. RARPKB can assist in personalized and complex surgical planning for prostate cancer to improve its efficacy. RARPKB provides a reference for the future applications of artificial intelligence in clinical practice.

Performance of ChatGPT on Chinese national medical licensing examinations: a five-year examination evaluation study for physicians, pharmacists and nurses.

BACKGROUND: Large language models like ChatGPT have revolutionized the field of natural language processing with their capability to comprehend and generate textual content, showing great potential to play a role in medical education. This study aimed to quantitatively evaluate and comprehensively analysis the performance of ChatGPT on three types of national medical examinations in China, including National Medical Licensing Examination (NMLE), National Pharmacist Licensing Examination (NPLE), and National Nurse Licensing Examination (NNLE). METHODS: We collected questions from Chinese NMLE, NPLE and NNLE from year 2017 to 2021. In NMLE and NPLE, each exam consists of 4 units, while in NNLE, each exam consists of 2 units. The questions with figures, tables or chemical structure were manually identified and excluded by clinician. We applied direct instruction strategy via multiple prompts to force ChatGPT to generate the clear answer with the capability to distinguish between single-choice and multiple-choice questions. RESULTS: ChatGPT failed to pass the accuracy threshold of 0.6 in any of the three types of examinations over the five years. Specifically, in the NMLE, the highest recorded accuracy was 0.5467, which was attained in both 2018 and 2021. In the NPLE, the highest accuracy was 0.5599 in 2017. In the NNLE, the most impressive result was shown in 2017, with an accuracy of 0.5897, which is also the highest accuracy in our entire evaluation. ChatGPT's performance showed no significant difference in different units, but significant difference in different question types. ChatGPT performed well in a range of subject areas, including clinical epidemiology, human parasitology, and dermatology, as well as in various medical topics such as molecules, health management and prevention, diagnosis and screening. CONCLUSIONS: These results indicate ChatGPT failed the NMLE, NPLE and NNLE in China, spanning from year 2017 to 2021. but show great potential of large language models in medical education. In the future high-quality medical data will be required to improve the performance.

MSWIFA and cement cooperate in the disposal of soft soil - experimental study on silty sand and silty clay.

Municipal solid waste incineration fly ash (MSWIFA) can be reused as a positive additive to strengthen soft soil. In this study, MSWIFA was initially used as a supplementary solidification material in combination with ordinary Portland cement to prepare fly ash cement-stabilized soil (FACS) with silty sand and silty clay, respectively. The ratio of MWSIFA to total mass was 5%, 10%, and 15%, and the cement content was set as 10% and 15%. The mechanical properties of FACS were evaluated by unconfined compressive strength test. The heavy metal-leaching test was conducted to estimate the environmental risk of FACS. The scanning electron microscope was used to test the micro-structure of FACS. The X-ray diffraction was performed to analyze material composition of FACS. The result indicates that the collaborative solidification of soft soil with MSWIFA and cement is feasible. Regarding the silty clay, the FA had positive effects on the silty clay in the service age (between 50 and 100% with 15% MSWIFA), as the MSWIFA reformulated the initial silty clay structure, resulting in interconnection and pore fill between particles. It can be founded that C-S-H and ettringite are the main products of MSWIFA and cement hydration, which are formed by the hydration of C3S and C2S. Regarding the silty sand, the MSWIFA decreased the peak strength (between 35 and 48% with 15% MSWIFA) but increased the ductility of the stabilized cement. Under the same mix proportions, the leaching toxicities of Zn and Pb in FACS of silty clay were obviously lower than were those of silty sand. Generally, the leaching concentrations of tested metals under all the mix proportions were well below the limit value set by GB 18598-2019 for hazardous waste landfill. Thus, the reuse of MSWIFA in cement-stabilized soil would be one of the effective methods in soft soil treatment and solid waste reduction.

Bibliometric and visual analysis of spinal cord injury-associated macrophages from 2002 to 2023.

Background: Spinal cord injury (SCI) triggers motor, sensory, and autonomic impairments that adversely damage patients' quality of life. Its pathophysiological processes include inflammation, oxidative stress, and apoptosis, although existing treatment options have little success. Macrophages have a vital function in controlling inflammation in SCI, with their M1-type and M2-type macrophages dominating early inflammatory effects and late brain tissue repair and regeneration, respectively. However, there is a dearth of rigorous bibliometric study in this sector to explore its dynamics and trends. This study intends to examine the current status and trends of macrophage usage in SCI using bibliometric methodologies, which may drive novel therapeutic options. Methods: In this study, the Web of Science Core Collection (WOSCC) was utilized to collect publications and reviews on macrophages in SCI from 2002 to 2023. Bibliometrics and visualization analyses were performed by VOSviewer, CiteSpace, the R package "bibliometrix", and online analytic platforms. These analyses covered a variety of aspects, including countries and institutions, authors and co-cited authors, journals and co-cited journals, subject categories, co-cited references, and keyword co-occurrences, in order to provide insights into the research trends and hotspots in this field. Results: 1,775 papers were included in the study, comprising 1,528 articles and 247 reviews. Our research analysis demonstrates that the number of relevant studies in this sector is expanding, specifically the number of publications in the United States and China has risen dramatically. However, there are fewer collaborations between institutions in different nations, and international cooperation needs to be reinforced. Among them, Popovich PG became the leader in the field, and significant journals include Experimental Neurology, Journal of Neurotrauma, and Journal of Neuroscience. Research hotspots involve macrophage polarization, microglia, astrocytes, signaling, cytokines, inflammation, and neuroprotection. Conclusions: This analysis gives, for the first time, a comprehensive overview of bibliometric studies on macrophages in SCI over the past 20 years. This study not only gives an extensive picture of the knowledge structure but also indicates trends in the subject. The systematic summarization gives a complete and intuitive understanding of the link between spinal cord damage and macrophages and provides a great reference for future related studies.

Impact of apolipoprotein A1 on tumor immune microenvironment, clinical prognosis and genomic landscape in hepatocellular carcinoma.

Background: Current knowledge on apolipoprotein A1 (APOA1) in hepatocellular carcinoma (HCC) is fragmented and even contradictory. Multi-dimensional analyses are required to comprehensively elucidate its value and underlying mechanism. Methods: We collected 49 RNA-seq datasets, 40 cell line types data and 70 scRNA pan-cancer datasets public available, including 17 HCC datasets (1754 tumor samples), and enrolled 73 pairs of HCC tissue and 516 blood samples independently from our clinics. APOA1 impacting on the HCC tumor microenvironment (TME) was analyzed using intensive data mining. Methylation sequencing, flow cytometry, quantitative PCR, western blot, immunohistochemistry and clinical chemistry assays were conducted for wet experimental investigation. Results: The APOA1 ontology fingerprint indicated that it played various crucial biological roles in HCC, primarily involved in cholesterol efflux. Consistent findings at histology, serology, and clinical follow-up revealed that high APOA1 was a good prognosis indicator of HCC. Hypermethylation in the APOA1 promoter region was found in clinical samples which is in accordance with the reduction of APOA1 in HCC. The cell cycle, DNA replication, mismatch repair pathways, and tumor cell proliferation were less observed in the HCC APOA1high subgroup. The favorable immunoregulatory abilities of APOA1 showed interesting findings: a positive correlation between APOA1 and anti-tumor immune cells (NK, CD8+ T cells) and a negative association with immune cells exerting immunosuppressive effects, including M2 macrophages. Conclusion: This is an integrative multidimensional exploration of APOA1 using bioinformatics and experiments. Both the prognostic value and anti-tumor effects based on APOA1 panoramic exploration in the HCC TME demonstrate a new potential clinical target for HCC assessment and intervention in the future.

Highly Stable Amide-Functionalized Zirconium-Organic Frameworks: Synthesis, Structure, and Methane Storage Capacity.

With the development of crystalline porous materials toward methane storage, the stability issue of metal-organic framework (MOF) materials has caused great concern despite high working capacity. Considering the high stability of zirconium-based MOFs and effective functions of amide groups toward gas adsorption, herein, a series of UiO-66 type of Zr-MOFs, namely, Zr-fcu-H/F/CH3/OH, were successfully designed and synthesized by virtue of amide-functionalized dicarboxylate ligands bearing distinct side groups (i.e., -H, -F, -CH3, and -OH) and ZrCl4 in the presence of trifluoroacetic acid as the modulator. Single-crystal X-ray diffraction and topology analyses reveal that these compounds are archetypal fcu MOFs encompassing octahedral and tetrahedral cages, respectively. The N2 sorption isotherms and acid-base stability tests demonstrate that the materials possess not only relatively high surface areas, pore volumes, and appropriate pore sizes but also great hydrolytic stabilities ranging pH = 3-11. Furthermore, the volumetric methane storage working capacities of Zr-fcu-H, Zr-fcu-F, Zr-fcu-CH3, and Zr-fcu-OH at 298/273 K and 80 bar are 187/217, 175/193, 167/187, and 154/171 cm3 (STP) cm-3, respectively, which indicate that the zirconium-based crystalline porous materials are capable of storing relatively high amounts of methane.

Extracting laboratory test information from paper-based reports.

BACKGROUND: In the healthcare domain today, despite the substantial adoption of electronic health information systems, a significant proportion of medical reports still exist in paper-based formats. As a result, there is a significant demand for the digitization of information from these paper-based reports. However, the digitization of paper-based laboratory reports into a structured data format can be challenging due to their non-standard layouts, which includes various data types such as text, numeric values, reference ranges, and units. Therefore, it is crucial to develop a highly scalable and lightweight technique that can effectively identify and extract information from laboratory test reports and convert them into a structured data format for downstream tasks. METHODS: We developed an end-to-end Natural Language Processing (NLP)-based pipeline for extracting information from paper-based laboratory test reports. Our pipeline consists of two main modules: an optical character recognition (OCR) module and an information extraction (IE) module. The OCR module is applied to locate and identify text from scanned laboratory test reports using state-of-the-art OCR algorithms. The IE module is then used to extract meaningful information from the OCR results to form digitalized tables of the test reports. The IE module consists of five sub-modules, which are time detection, headline position, line normalization, Named Entity Recognition (NER) with a Conditional Random Fields (CRF)-based method, and step detection for multi-column. Finally, we evaluated the performance of the proposed pipeline on 153 laboratory test reports collected from Peking University First Hospital (PKU1). RESULTS: In the OCR module, we evaluate the accuracy of text detection and recognition results at three different levels and achieved an averaged accuracy of 0.93. In the IE module, we extracted four laboratory test entities, including test item name, test result, test unit, and reference value range. The overall F1 score is 0.86 on the 153 laboratory test reports collected from PKU1. With a single CPU, the average inference time of each report is only 0.78 s. CONCLUSION: In this study, we developed a practical lightweight pipeline to digitalize and extract information from paper-based laboratory test reports in diverse types and with different layouts that can be adopted in real clinical environments with the lowest possible computing resources requirements. The high evaluation performance on the real-world hospital dataset validated the feasibility of the proposed pipeline.

A genetic mosaic mouse model illuminates the pre-malignant progression of basal-like breast cancer.

Basal-like breast cancer (BLBC) is highly aggressive, and often characterized by BRCA1 and p53 deficiency. Although conventional mouse models enabled the investigation of BLBC at malignant stages, its initiation and pre-malignant progression remain understudied. Here, we leveraged a mouse genetic system known as mosaic analysis with double markers (MADM) to study BLBC initiation by generating rare GFP+Brca1, p53-deficient mammary cells alongside RFP+ wild-type sibling cells. After confirming the close resemblance of mammary tumors arising in this model to human BLBC at both transcriptomic and genomic levels, we focused our studies on the pre-malignant progression of BLBC. Initiated GFP+ mutant cells showed a stepwise pre-malignant progression trajectory from focal expansion to hyper-alveolarization and then to micro-invasion. Furthermore, despite morphological similarities to alveoli, hyper-alveolarized structures actually originate from ductal cells based on twin-spot analysis of GFP-RFP sibling cells. Finally, luminal-to-basal transition occurred exclusively in cells that have progressed to micro-invasive lesions. Our MADM model provides excellent spatiotemporal resolution to illuminate the pre-malignant progression of BLBC, and should enable future studies on early detection and prevention for this cancer.

Resampling-Detection-Network-Based Robust Image Watermarking against Scaling and Cutting.

Watermarking is an excellent solution to protect multimedia privacy but will be damaged by attacks such as noise adding, image filtering, compression, and especially scaling and cutting. In this paper, we propose a watermarking scheme to embed the watermark in the DWT-DCT composite transform coefficients, which is robust against normal image processing operations and geometric attacks. To make our scheme robust to scaling operations, a resampling detection network is trained to detect the scaling factor and then rescale the scaling-attacked image before watermark detection. To make our scheme robust to cutting operations, a template watermark is embedded in the Y channel to locate the cutting position. Experiments for various low- and high-resolution images reveal that our scheme has excellent performance in terms of imperceptibility and robustness.

An artificial intelligence method for predicting postoperative urinary incontinence based on multiple anatomic parameters of MRI.

Background: Deep learning methods are increasingly applied in the medical field; however, their lack of interpretability remains a challenge. Captum is a tool that can be used to interpret neural network models by computing feature importance weights. Although Captum is an interpretable model, it is rarely used to study medical problems, and there is a scarcity of data regarding MRI anatomical measurements for patients with prostate cancer after undergoing Robotic-Assisted Radical Prostatectomy (RARP). Consequently, predictive models for continence that use multiple types of anatomical MRI measurements are limited. Methods: We explored the energy efficiency of deep learning models for predicting continence by analyzing MRI measurements. We analyzed and compared various statistical models and provided reference examples for the clinical application of interpretable deep-learning models. Patients who underwent RARP at our institution between July 2019 and December 2020 were included in this study. A series of clinical MRI anatomical measurements from these patients was used to discover continence features, and their impact on continence was primarily evaluated using a series of statistical methods and computational models. Results: Age and six other anatomical measurements were identified as the top seven features of continence by the proposed model UINet7 with an accuracy of 0.97, and the first four of these features were also found by primary statistical analysis. Conclusions: This study fills the gaps in the in-depth investigation of continence features after RARP due to the limitations of clinical data and applicable models. We provide a pioneering example of the application of deep-learning models to clinical problems. The interpretability analysis of deep learning models has the potential for clinical applications.

Clinical observations in treatment of lower extremity varicose veins with trigger points acupuncture.

OBJECTIVES: To observe the effect of the acupuncture of myofascial trigger points (MTrPs) in the treatment of lower extremity varicose veins (LEVVs). METHODS: Overall, 260 patients with LEVVs participated in this study. LEVVs were selected based on diagnostic criteria of Clinical, Etiology, Anatomy, and Pathophysiology levels 2-5 and classified into six types on the basis of their anatomical positions. The MTrPs in the lower extremities were localized in accordance with the classification of LEVVs and treated by MTrPs acupuncture combined with self-massage and self-stretching. The interval between each treatment was 2 weeks to 1 month, depending on needling pain tolerance of each patient. An in-house evaluation was used to estimate the proportion of varicose veins in the lower limbs and their accompanying symptoms. The treatment effect was evaluated before each treatment and at 1-year follow-up. RESULTS: The mean evaluation score of LEVVs before the treatment course was 3.66 ± 1.19. After the course, this reduced to 1.18 ± 0.97, with the following response rates: 85% for excellent and good and 15% for medium. After 1-year follow-up, the mean evaluation score of all patients was 1.11 ± 0.92, with the following response rates: 87% for excellent and good, and 13% for medium. CONCLUSIONS: In some patients, MTrP acupuncture could cure LEVVs and its accompanying symptoms. These LEVVs are probably caused by fascia tension as a pre-pathology induced by the MTrPs.

Large-Scale Biomedical Relation Extraction Across Diverse Relation Types: Model Development and Usability Study on COVID-19.

BACKGROUND: Biomedical relation extraction (RE) is of great importance for researchers to conduct systematic biomedical studies. It not only helps knowledge mining, such as knowledge graphs and novel knowledge discovery, but also promotes translational applications, such as clinical diagnosis, decision-making, and precision medicine. However, the relations between biomedical entities are complex and diverse, and comprehensive biomedical RE is not yet well established. OBJECTIVE: We aimed to investigate and improve large-scale RE with diverse relation types and conduct usability studies with application scenarios to optimize biomedical text mining. METHODS: Data sets containing 125 relation types with different entity semantic levels were constructed to evaluate the impact of entity semantic information on RE, and performance analysis was conducted on different model architectures and domain models. This study also proposed a continued pretraining strategy and integrated models with scripts into a tool. Furthermore, this study applied RE to the COVID-19 corpus with article topics and application scenarios of clinical interest to assess and demonstrate its biological interpretability and usability. RESULTS: The performance analysis revealed that RE achieves the best performance when the detailed semantic type is provided. For a single model, PubMedBERT with continued pretraining performed the best, with an F1-score of 0.8998. Usability studies on COVID-19 demonstrated the interpretability and usability of RE, and a relation graph database was constructed, which was used to reveal existing and novel drug paths with edge explanations. The models (including pretrained and fine-tuned models), integrated tool (Docker), and generated data (including the COVID-19 relation graph database and drug paths) have been made publicly available to the biomedical text mining community and clinical researchers. CONCLUSIONS: This study provided a comprehensive analysis of RE with diverse relation types. Optimized RE models and tools for diverse relation types were developed, which can be widely used in biomedical text mining. Our usability studies provided a proof-of-concept demonstration of how large-scale RE can be leveraged to facilitate novel research.

Association Between Urinary Bisphenols and Body Composition Among American Adults: Cross-Sectional National Health and Nutrition Examination Survey Study.

BACKGROUND: Bisphenol A (BPA), bisphenol S (BPS), and bisphenol F (BPF) are widely used in various consumer products. They are environmental contaminants with estrogenic properties that have been linked to various health outcomes. Understanding their impact on body composition is crucial for identifying potential health risks and developing preventive strategies. However, most current studies have only focused on their relationship with BMI. OBJECTIVE: This study aimed to investigate the association between urinary levels of BPA, BPS, and BPF and body composition, including BMI, lean mass, and fat mass, in a large population-based sample. METHODS: We conducted a cross-sectional analysis using data from the National Health and Nutrition Examination Survey 2003-2016. Body composition data were assessed using dual-energy X-ray absorptiometry, which provided precise measurements of lean mass, fat mass, and other indicators. We used multivariate linear regression models to estimate the associations, adjusting for potential confounders such as age, gender, race, socioeconomic factors, and lifestyle variables. RESULTS: The results revealed significant associations between bisphenol exposure and body composition. After adjusting for covariates, BPS showed a positive association with BMI, with quartiles 3 and 4 having 0.91 (95% CI 0.34-1.48) and 1.15 (95% CI 0.55-1.74) higher BMI, respectively, compared with quartile 1 (P<.001). BPA was negatively associated with total lean mass (TLM) and appendicular lean mass, with quartiles 2, 3, and 4 having -7.85 (95% CI -11.44 to -4.25), -12.33 (95% CI -16.12 to -8.54), and -11.08 (95% CI -15.16 to -7.01) lower TLM, respectively, compared with quartile 1 (P<.001). BPS was negatively associated with TLM, with quartiles 3 (ß=-10.53, 95% CI -16.98 to -4.08) and 4 (ß=-11.14, 95% CI -17.83 to -4.45) having significantly lower TLM (P=.005). Both BPA and BPS showed a positive dose-response relationship with trunk fat (BPA: P=.002; BPS: P<.001) and total fat (BPA: P<.001; BPS: P=.01). No significant association was found between BPF and any body composition parameter. CONCLUSIONS: This large-sample study highlights the associations between urinary levels of BPA and BPS and alterations in body composition, including changes in lean mass, fat mass, and regional fat distribution. These findings underscore the importance of understanding the potential health risks associated with bisphenol exposure and emphasize the need for targeted interventions to mitigate adverse effects on body composition.

Three-port transoral robotic thyroidectomy without axillary incision: A preliminary report of 20 cases in China.

Objective: Transoral scarless thyroid surgery has proven to be a popular alternative to traditional approaches. Transoral robotic thyroidectomy (TORT) has been reported using ports on the lower lip and axilla. Avoiding axillary incision can further reduce scars on the armpit. Here, we present our preliminary data from the initial 20 consecutive patients to explore the feasibility of three-port TORT without axillary incision. Methods: From September 2017 to June 2019, we performed TORT at Beijing United Family Hospital using three intraoral ports without axillary incision via the da Vinci Si system with three robotic arms. The outcomes of the procedure were retrospectively reviewed. Results: Among 20 patients (mean age 30 ± 7 years; mean tumor size 1.64 ± 0.96 cm), 16 patients underwent unilateral thyroid lobectomy and four had total thyroidectomy with or without central neck dissection. Eighteen patients had papillary thyroid carcinomas (PTC), one had a follicular thyroid carcinoma, and one had a thyroid adenoma. The mean surgical time was 221 ± 68 min. The mean number of retrieved central lymph nodes in the PTC patients was 5.6 ± 5. There was no permanent vocal cord palsy or hypocalcemia postoperatively. One patient had transient vocal cord palsy, which resolved within 1 week. Paresthesia of the lower lip and the chin was observed in nine patients, and one patient had a first-degree burn of the skin flap due to the lens. Conclusion: Three-port TORT without axillary incision is feasible for selected patients and would be a potential alternative for remote-access thyroid surgery to avoid leaving scars on the neck or the armpit.