High-sensitivity immunoassay on interdigitated electrode to detect osteoporosis biological marker.

Osteoporosis is with porous bones, which refers to a decrease in the bone mineral density and weakens the bones to become brittle. Osteoporosis often progresses without any pain or symptoms until the bone fractures. Monitoring the condition of bone regularly helps to identify the bone that weakens at its earlier stages. In general, radiological techniques have been used to measure bone mineral density, are expensive, and the procedures are complicated. Therefore, researchers are focusing on the alternative method of biomarker quantification to identify bone mineral density. This research work was focused on quantifying the osteoporosis biomarker of C-terminal telopeptide of type I collagen (CTX-I) on an interdigitated electrode (IDE) sensor. Gold nanomaterial-modified anti-CTX-I antibody was attached to silica nanomaterial-decorated IDE and then identified by CTX-I interaction. Higher immobilization of antibodies was recorded on diamond-modified IDE through gold nanoparticles, and detected CTX-I as low as 0.5 pg/mL [y = 1.5507x - 0.9043 R2 = 0.9715], determined on a linear curve at the range 0.5-3.5 ng/mL. Further, specific identification of CTX-I was confirmed by control performances with osteopontin, IL-6, and anti-IgG antibody.

An Entity Extraction Pipeline for Medical Text Records Using Large Language Models: Analytical Study.

BACKGROUND: The study of disease progression relies on clinical data, including text data, and extracting valuable features from text data has been a research hot spot. With the rise of large language models (LLMs), semantic-based extraction pipelines are gaining acceptance in clinical research. However, the security and feature hallucination issues of LLMs require further attention. OBJECTIVE: This study aimed to introduce a novel modular LLM pipeline, which could semantically extract features from textual patient admission records. METHODS: The pipeline was designed to process a systematic succession of concept extraction, aggregation, question generation, corpus extraction, and question-and-answer scale extraction, which was tested via 2 low-parameter LLMs: Qwen-14B-Chat (QWEN) and Baichuan2-13B-Chat (BAICHUAN). A data set of 25,709 pregnancy cases from the People's Hospital of Guangxi Zhuang Autonomous Region, China, was used for evaluation with the help of a local expert's annotation. The pipeline was evaluated with the metrics of accuracy and precision, null ratio, and time consumption. Additionally, we evaluated its performance via a quantified version of Qwen-14B-Chat on a consumer-grade GPU. RESULTS: The pipeline demonstrates a high level of precision in feature extraction, as evidenced by the accuracy and precision results of Qwen-14B-Chat (95.52% and 92.93%, respectively) and Baichuan2-13B-Chat (95.86% and 90.08%, respectively). Furthermore, the pipeline exhibited low null ratios and variable time consumption. The INT4-quantified version of QWEN delivered an enhanced performance with 97.28% accuracy and a 0% null ratio. CONCLUSIONS: The pipeline exhibited consistent performance across different LLMs and efficiently extracted clinical features from textual data. It also showed reliable performance on consumer-grade hardware. This approach offers a viable and effective solution for mining clinical research data from textual records.

Multi-stimuli responsive photonic hydrogel based on a novel photonic crystal template containing gold nanorods.

Multi-stimuli responsive photonic hydrogels (MRPHs) fabricated by doping nanoparticles into hydrogels show promising potential value in the fields of visual detection and drug delivery. However, complicated surface chemical modification is selected to improve the compatibility between nanoparticles and a pre-gel solution of hydrogel. Herein, we developed a simple and convenient vertical deposition method to prepare a novel photonic crystal (PC) template containing gold nanorods (Au NRs) (Au NRs/PC template), which could respond to near-infrared (NIR) light due to the conversion capability of Au NRs from NIR light to heat. Additionally, carboxyl groups on the surface of polystyrene (PS) colloids endowed the Au NRs/PC template with pH-stimulus responsiveness. Based on the Au NRs/PC template, MRPH film was fabricated by infiltrating the pre-gel solution of poly(N-isopropylacrylamide) (PNIPAM) hydrogel into the gap of a 'sandwich' structure through capillary forces and then polymerizing at 25 °C for 24 h. The obtained MRPH film could respond to NIR light, pH and temperature. Under the irradiation of NIR light, only the irradiated position lost structural color while the film volume had no distinct change. With the increase of ambient temperature, the whole MRPH film completely lost structural color and shrank significantly, which was greatly different from the phenomenon irradiated by NIR light. Besides, the structural color of the MRPH film exhibited a red shift from green to orange-red as the pH increased. Overall, both the Au NRs/PC template and the MRPH film may have potential applications in visual detection, due to their multi-stimuli responsiveness.

Downregulation of TRIM21 contributes to hepatocellular carcinoma carcinogenesis and indicates poor prognosis of cancers.

The aim of our work is to clarify the clinical implication and functional role of tripartite motif 21 (TRIM21) in hepatocellular carcinoma (HCC). We validated that TRIM21 was downregulated in liver cancer samples by immunohistochemical (IHC) staining. We also demonstrated that its downregulation was associated with several clinicopathologic features such as tumor numbers, T stage, Barcelona Clinic Liver Cancer (BCLC) stage, and Cancer of the Liver Italian Program (CLIP) stage of HCC patients. Importantly, the expression of TRIM21 in tumor samples is significantly correlated with the prognosis of the patients. We further silenced TRIM21 in HCC cell HepG2 and LM3 and confirmed that TRIM21 silencing will promote cancer cell proliferation (CCK-8 assay), colony forming (plate colony-forming assay), migration (transwell assay), and the ability of antiapoptosis (annexin V-FITC/PI staining) in vitro. Then, we predicted gene sets influenced by TRIM21 by using bioinformatic tools. For the first time, we prove that TRIM21 is a potential tumor suppressor in HCC and its low expression indicates poor prognosis. Our findings provide useful insight into the mechanism of HCC origin and progression and offer clues to novel HCC therapies.

Polylactic acid electrospun membrane loaded with cerium nitrogen co-doped titanium dioxide for visible light-triggered antibacterial photocatalytic therapy.

Wound infection caused by multidrug-resistant bacteria poses a serious threat to antibiotic therapy. Therefore, it is of vital importance to find new methods and modes for antibacterial therapy. The cerium nitrogen co-doped titanium dioxide nanoparticles (N-TiO2, 0.05Ce-N-TiO2, 0.1Ce-N-TiO2, and 0.2Ce-N-TiO2) were synthesized using the hydrothermal method in this study. Subsequently, electrospinning was employed to fabricate polylactic acid (PLA) electrospun membranes loaded with the above-mentioned nanoparticles (PLA-N, PLA-0.05, PLA-0.1, and PLA-0.2). The results indicated that cerium and nitrogen co-doping tetrabutyl titanate enhanced the visible light photocatalytic efficiency of TiO2 nanoparticles and enabled the conversion of ultraviolet light into harmless visible light. The photocatalytic reaction under visible light irradiation induced the generation of ROS, which could effectively inhibit the bacterial growth. The antibacterial assay showed that it was effective in eliminating S. aureus and E. coli and the survival rates of two types of bacteria under 30 min of irradiation were significantly below 20% in the PLA-0.2 experimental group. Moreover, the bactericidal membranes also have excellent biocompatibility performance. This bio-friendly and biodegradable membrane may be applied to skin trauma and infection in future to curb drug-resistant bacteria and provide more alternative options for antimicrobial therapy.

Investigating the Impact of Prompt Engineering on the Performance of Large Language Models for Standardizing Obstetric Diagnosis Text: Comparative Study.

BACKGROUND: The accumulation of vast electronic medical records (EMRs) through medical informatization creates significant research value, particularly in obstetrics. Diagnostic standardization across different health care institutions and regions is vital for medical data analysis. Large language models (LLMs) have been extensively used for various medical tasks. Prompt engineering is key to use LLMs effectively. OBJECTIVE: This study aims to evaluate and compare the performance of LLMs with various prompt engineering techniques on the task of standardizing obstetric diagnostic terminology using real-world obstetric data. METHODS: The paper describes a 4-step approach used for mapping diagnoses in electronic medical records to the International Classification of Diseases, 10th revision, observation domain. First, similarity measures were used for mapping the diagnoses. Second, candidate mapping terms were collected based on similarity scores above a threshold, to be used as the training data set. For generating optimal mapping terms, we used two LLMs (ChatGLM2 and Qwen-14B-Chat [QWEN]) for zero-shot learning in step 3. Finally, a performance comparison was conducted by using 3 pretrained bidirectional encoder representations from transformers (BERTs), including BERT, whole word masking BERT, and momentum contrastive learning with BERT (MC-BERT), for unsupervised optimal mapping term generation in the fourth step. RESULTS: LLMs and BERT demonstrated comparable performance at their respective optimal levels. LLMs showed clear advantages in terms of performance and efficiency in unsupervised settings. Interestingly, the performance of the LLMs varied significantly across different prompt engineering setups. For instance, when applying the self-consistency approach in QWEN, the F1-score improved by 5%, with precision increasing by 7.9%, outperforming the zero-shot method. Likewise, ChatGLM2 delivered similar rates of accurately generated responses. During the analysis, the BERT series served as a comparative model with comparable results. Among the 3 models, MC-BERT demonstrated the highest level of performance. However, the differences among the versions of BERT in this study were relatively insignificant. CONCLUSIONS: After applying LLMs to standardize diagnoses and designing 4 different prompts, we compared the results to those generated by the BERT model. Our findings indicate that QWEN prompts largely outperformed the other prompts, with precision comparable to that of the BERT model. These results demonstrate the potential of unsupervised approaches in improving the efficiency of aligning diagnostic terms in daily research and uncovering hidden information values in patient data.

An early screening model for preeclampsia: utilizing zero-cost maternal predictors exclusively.

To provide a reliable, low-cost screening model for preeclampsia, this study developed an early screening model in a retrospective cohort (25,709 pregnancies) and validated in a validation cohort (1760 pregnancies). A data augmentation method (α-inverse weighted-GMM + RUS) was applied to a retrospective cohort before 10 machine learning models were simultaneously trained on augmented data, and the optimal model was chosen via sensitivity (at a false positive rate of 10%). The AdaBoost model, utilizing 16 predictors, was chosen as the final model, achieving a performance beyond acceptable with Area Under the Receiver Operating Characteristic Curve of 0.8008 and sensitivity of 0.5190. All predictors were derived from clinical characteristics, some of which were previously unreported (such as nausea and vomiting in pregnancy and menstrual cycle irregularity). Compared to previous studies, our model demonstrated superior performance, exhibiting at least a 50% improvement in sensitivity over checklist-based approaches, and a minimum of 28% increase over multivariable models that solely utilized maternal predictors. We validated an effective approach for preeclampsia early screening incorporating zero-cost predictors, which demonstrates superior performance in comparison to similar studies. We believe the application of the approach in combination with high performance approaches could substantially increase screening participation rate among pregnancies. Machine learning model for early preeclampsia screening, using 16 zero-cost predictors derived from clinical characteristics, was built on a 10-year Chinese cohort. The model outperforms similar research by at least 28%; validated on an independent cohort.

How Effective are Metal Nanotherapeutic Platforms Against Bacterial Infections? A Comprehensive Review of Literature.

The emergence of multidrug-resistant bacteria has been deemed a global crisis that affects humans worldwide. Novel anti-infection strategies are desperately needed because of the limitations of conventional antibiotics. However, the increasing gap between clinical demand and antimicrobial treatment innovation, as well as the membrane permeability obstacle especially in gram-negative bacteria fearfully restrict the reformation of antibacterial strategy. Metal-organic frameworks (MOFs) have the advantages of adjustable apertures, high drug-loading rates, tailorable structures, and superior biocompatibilities, enabling their utilization as drug delivery carriers in biotherapy applications. Additionally, the metal elements in MOFs are usually bactericidal. This article provides a review of the state-of-The-art design, the underlying antibacterial mechanisms and antibacterial applications of MOF- and MOF-based drug-loading materials. In addition, the existing problems and future perspectives of MOF- and MOF-based drug-loading materials are also discussed.

Tracing the evolving dynamics and research hotspots of microbiota and immune microenvironment from the past to the new era.

Gut microbiota can regulate many physiological processes within gastrointestinal tract and other distal sites. Dysbiosis may not only influence chronic diseases like the inflammatory bowel disease (IBD), metabolic disease, tumor and its therapeutic efficacy, but also deteriorate acute injuries. This article aims to review the documents in this field and summarize the research hotspots as well as developing processes. Gut microbiota and immune microenvironment-related documents from 1976 to 2022 were obtained from the Web of Science Core Collection database. Bibliometrics was used to assess the core authors and journals, most contributive countries and affiliations together with hotspots in this field and keyword co-occurrence analysis. Data were visualized to help comprehension. Nine hundred and twelve documents about gut microbiota and immune microenvironment were retrieved, and the annual publications increased gradually. The most productive author, country, and affiliation were "Zitvogel L," USA and "UNIV TEXAS MD ANDERSON CANC CTR," respectively. FRONTIERS IN IMMUNOLOGY, CANCERS, and INTERNATIONAL JOURNAL OF MOLECULAR SCIENCE were the periodicals with most publications. Keyword co-occurrence analysis identified three clusters, including gut microbiota, inflammation, and IBD. Combined with the visualized analysis of documents and keyword co-occurrence as well as literature reading, we recognized three key topics of gut microbiota: cancer and therapy; immunity, inflammation and IBD; acute injuries and metabolic diseases. This article revealed researches on gut microbiota and immune microenvironment were growing. More attention should be given to the latest hotspots like gut microbiota, inflammation, IBD, cancer and immunotherapy, acute traumas, and metabolic diseases.IMPORTANCEGut microbiota can regulate many physiological processes within gastrointestinal tract and other distal sites. Dysbiosis may not only influence chronic diseases like inflammatory bowel disease (IBD), metabolic disease, tumor and its therapeutic efficacy, but also deteriorate acute injuries. While the application of bibliometrics in the field of gut microbiota and immune microenvironment still remains blank, which focused more on the regulation of the gut microbiota on the immune microenvironment of different kinds of diseases. Here, we intended to review and summarize the presented documents in gut microbiota and immune microenvironment field by bibliometrics. And we revealed researches on gut microbiota and immune microenvironment were growing. More attention should be given to the latest hotspots like gut microbiota, inflammation, IBD, cancer and immunotherapy, acute traumas, and metabolic diseases.

Recent progress and perspectives on the relationship between hyperuricemia and periodontitis.

Periodontitis is one of the most prevalent diseases in oral cavity, which could not merely lead to the destruction of supporting or surrounding tooth structures but also affect the whole-body health such as the digestive and nervous systems. Epidemiological investigations suggested that in some developed countries, more than 45% or even 50% population were suffering from periodontitis. However, the prevalence increases with age remarkably and it is investigated that a high prevalence (>50%) is affecting the elderly who is over 65 years old. There is an increasing interest in the direct and indirect relationships between periodontitis and hyperuricemia. Currently, hyperuricemia has become the second major metabolic disease in modern society and the prevalence of hyperuricemia among adult males and females was 21.7% and 14.4% respectively. As an inflammatory disease associated with various systemic diseases, periodontitis may have certain connections with hyperuricemia. Partial existing research announced that hyperuricemia could act as an inhibitory factor for periodontitis, while other scholars presented that a high uric acid (UA) level was more likely to aggravate inflammatory immune response and lead to more serious tissue destruction. This article provides a detailed and comprehensive overview of the relationship underlying hyperuricemia and periodontitis in the molecular mechanisms. Given the impact of hyperuricemia, this review could provide insight into its comorbidities.

Antibacterial and anti-inflammatory ZIF-8@Rutin nanocomposite as an efficient agent for accelerating infected wound healing.

Essentially, wound healing is a complicated physiological process in which there exists an interaction between the organism's immune regulation and antimicrobial therapy. However, multiple drug-resistant bacteria implicated in chronic non-healing wound are not merely impeding the cure process, but more than a burden on economic and social development. Due to the inefficiency of conventional antibiotics, nanomedicine in the biomedical field is emerging as a prospective anti-infective therapy method. Herein, a novel nano-drug with antibacterial and anti-inflammatory characteristics was synthesized by loading Rutin into zeolitic imidazolate framework-8 (ZIF-8), abided by the principle of electrostatic adsorption. The synthetic ZIF-8 loaded Rutin (ZIF-8@Rutin) was affirmed by testing the changes in the diameter and chemical functional group. Interestingly, the ladened Rutin afforded nanocomposite with anti-inflammatory activity by its antioxidant capacity for the polarization of macrophages. Further, the prepared ZIF-8@Rutin exhibited highly effective antibacterial activity against Escherichia coli and Staphylococcus aureus in vitro. More importantly, it could shorten the infected wound healing process and alleviate the inflammation around the wound in vivo. Also, ZIF-8@Rutin had acceptable cytocompatibility. Thus, ZIF-8@Rutin may become a multifunctional nanomedicine with anti-inflammatory and bactericidal properties to promote infected wound healing.

Upconversion nanoparticles and its based photodynamic therapy for antibacterial applications: A state-of-the-art review.

Major medical advances in antibiotics for infectious diseases have dramatically improved the quality of life and greatly increased life expectancy. Nevertheless, the widespread and inappropriate exploitation of antibacterial agents has resulted in the emergence of multi-drug-resistant bacteria (MDR). Consequently, the study of new drugs for the treatment of diseases associated with multi-drug-resistant bacteria and the development of new treatments are urgently needed. Inspiringly, due to the advantages of a wide antimicrobial spectrum, fast sterilization, low resistance, and little damage to host tissues and normal flora, antibacterial photodynamic therapy (APDT), which is based on the interaction between light and a nontoxic photosensitizer (PS) concentrated at the lesion site to generate reactive oxygen species (ROS), has become one of the most promising antibacterial strategies. Recently, a burgeoning APDT based on a variety of upconversion nanoparticles (UCNPs) such as PS and near-infrared (NIR) light has been fully integrated in antibacterial applications and achieved excellent performances. Meanwhile, conjugated nanoparticles have been frequently reported in UCNP design, including surface-modified PS conjugates, antibiotic-PS conjugates, and dual or multiple antibacterial modal PS conjugates. This article provides an overview of the state-of-the-art design and bactericidal effects of UCNPs and their based APDTs. The first part discusses the design and mechanisms for UCNPs currently implemented in biomedicine. The second part focuses on the applications and antimicrobial effects of diverse APDT based on UCNPs in antibacterial-related infectious diseases.

FBXW7 deletion contributes to lung tumor development and confers resistance to gefitinib therapy.

Gefitinib, an epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI), is an effective treatment for non-small-cell lung cancer (NSCLC) with EGFR activating mutations, but inevitably, the clinical efficacy is impeded by the emergence of acquired resistance. The tumor suppressor gene FBXW7 modulates chemosensitivity in various human cancers. However, its role in EGFR-TKI therapy in NSCLC has not been well studied. Here, we demonstrate that the mice with deficient Fbxw7 have greater susceptibility to urethane-induced lung tumor development. Through analysis of The Cancer Genome Atlas data, we show that deletion of FBXW7 occurs in 30.9% of lung adenocarcinomas and 63.5% of lung squamous cell carcinomas, which significantly leads to decrease in FBXW7 mRNA expression. The reduction in FBXW7 mRNA level is associated with poor overall survival in lung cancer patients. FBXW7 knockdown dramatically promotes epithelial-mesenchymal transition, migration, and invasion in NSCLC cells. Moreover, with silenced FBXW7, EGFR-TKI-sensitive cells become resistant to gefitinib, which is reversed by the mammalian target of rapamycin inhibitor, rapamycin. Furthermore, xenograft mouse model studies show that FBXW7 knockdown enhances tumorigenesis and resistance to gefitinib. Combination of gefitinib with rapamycin treatment suppresses tumor formation of gefitinib-resistant (GR) FBXW7-knockdown cells. In conclusion, our findings suggest that loss of FBXW7 promotes NSCLC progression as well as gefitinib resistance and combination of gefitinib and rapamycin may provide an effective therapy for GR NSCLC.

HIV-1-Induced miR-146a Attenuates Monocyte Migration by Targeting CCL5 in Human Primary Macrophages.

MicroRNAs (miRNAs) are widely involved in immune regulation during virus infection. Several studies showed that the expression of miR-146a was increased in human immunodeficiency virus type I (HIV-1)-infected cells, but the definitive function of miR-146a in HIV-1 infection remains obscure. The production of chemokine (C-C motif) ligand 5 (CCL5) in macrophages has been reported to play an important role in HIV/AIDS-associated pathogenesis. In this study, we examined the effects of miR-146a on CCL5 regulation in HIV-1-infected macrophages. Gain and loss of function studies showed that CCL5 might be one of the miR-146a targets, as miR-146a mimic reduced, while miR-146a inhibitor increased CCL5 production in HIV-1-infected macrophages. In addition, we demonstrated that miR-146a reduced CCL5-induced monocyte migration. Our study provided evidence that miR-146a targets CCL5 3' untranslated regions, downregulates its release from macrophages, and affects monocyte migration consequently. These findings drew a novel layer of posttranscriptional control of the chemokine CCL5 by miR-146a during HIV infection, which might contribute to HIV pathogenesis.