System integration of magnetic medical microrobots: from design to control

Magnetic microrobots are ideal for medical applications owing to their deep tissue penetration, precise control, and flexible movement. After decades of development, various magnetic microrobots have been used to achieve medical functions such as targeted delivery, cell manipulation, and minimally invasive surgery. This review introduces the research status and latest progress in the design and control systems of magnetic medical microrobots from a system integration perspective and summarizes the advantages and limitations of the research to provide a reference for developers. Finally, the future development direction of magnetic medical microrobot design and control systems are discussed

BLAT: Bootstrapping Language-Audio Pre-training based on AudioSet Tag-guided Synthetic Data

Compared with ample visual-text pre-training research, few works explore audio-text pre-training, mostly due to the lack of sufficient parallel audio-text data. Most existing methods incorporate the visual modality as a pivot for audio-text pre-training, which inevitably induces data noise. In this paper, we propose BLAT: Bootstrapping Language-Audio pre-training based on Tag-guided synthetic data. We utilize audio captioning to generate text directly from audio, without the aid of the visual modality so that potential noise from modality mismatch is eliminated. Furthermore, we propose caption generation under the guidance of AudioSet tags, leading to more accurate captions. With the above two improvements, we curate high-quality, large-scale parallel audio-text data, based on which we perform audio-text pre-training. Evaluation on a series of downstream tasks indicates that BLAT achieves SOTA zero-shot classification performance on most datasets and significant performance improvement when fine-tuned on downstream tasks, suggesting the effectiveness of our synthetic data

Building Interpretable Interaction Trees for Deep NLP Models

This paper proposes a method to disentangle and quantify interactions among words that are encoded inside a DNN for natural language processing. We construct a tree to encode salient interactions extracted by the DNN. Six metrics are proposed to analyze properties of interactions between constituents in a sentence. The interaction is defined based on Shapley values of words, which are considered as an unbiased estimation of word contributions to the network prediction. Our method is used to quantify word interactions encoded inside the BERT, ELMo, LSTM, CNN, and Transformer networks. Experimental results have provided a new perspective to understand these DNNs, and have demonstrated the effectiveness of our method

Coupling Artificial Neurons in BERT and Biological Neurons in the Human Brain

Linking computational natural language processing (NLP) models and neural responses to language in the human brain on the one hand facilitates the effort towards disentangling the neural representations underpinning language perception, on the other hand provides neurolinguistics evidence to evaluate and improve NLP models. Mappings of an NLP model's representations of and the brain activities evoked by linguistic input are typically deployed to reveal this symbiosis. However, two critical problems limit its advancement: 1) The model's representations (artificial neurons, ANs) rely on layer-level embeddings and thus lack fine-granularity; 2) The brain activities (biological neurons, BNs) are limited to neural recordings of isolated cortical unit (i.e., voxel/region) and thus lack integrations and interactions among brain functions. To address those problems, in this study, we 1) define ANs with fine-granularity in transformer-based NLP models (BERT in this study) and measure their temporal activations to input text sequences; 2) define BNs as functional brain networks (FBNs) extracted from functional magnetic resonance imaging (fMRI) data to capture functional interactions in the brain; 3) couple ANs and BNs by maximizing the synchronization of their temporal activations. Our experimental results demonstrate 1) The activations of ANs and BNs are significantly synchronized; 2) the ANs carry meaningful linguistic/semantic information and anchor to their BN signatures; 3) the anchored BNs are interpretable in a neurolinguistic context. Overall, our study introduces a novel, general, and effective framework to link transformer-based NLP models and neural activities in response to language and may provide novel insights for future studies such as brain-inspired evaluation and development of NLP models

Nitrate and Nitrite Promote Formation of Tobacco-Specific Nitrosamines via Nitrogen Oxides Intermediates during Postcured Storage under Warm Temperature

Tobacco-specific nitrosamines (TSNAs) are carcinogenic and are present in cured tobacco leaves. This study was designed to elucidate the mechanisms of TSNAs formation under warm temperature storage conditions. Results showed that nitrogen oxides (NOx) were produced from nitrate and nitrite in a short period of time under 45 ∘ C and then reacted with alkaloids to form TSNAs. Nitrite was more effective than nitrate in promoting TSNAs formation during 45 ∘ C storage which may be due to the fact that nitrite can produce a large amount of NOx in comparison with nitrate. Presence of activated carbon effectively inhibited the TSNAs formation because of the adsorption of NOx on the activated carbon. The results indicated that TSNAs are derived from a gas/solid phase nitrosation reaction between NOx and alkaloids. Nitrate and nitrite are major contributors to the formation of TSNAs during warm temperature storage of tobacco

Global trends and performances in diabetic retinopathy studies: A bibliometric analysis

ObjectiveThe objective of this study is to conduct a comprehensive bibliometric analysis to identify and evaluate global trends in diabetic retinopathy (DR) research and visualize the focus and frontiers of this field.MethodsDiabetic retinopathy-related publications from the establishment of the Web of Science (WOS) through 1 November 2022 were retrieved for qualitative and quantitative analyses. This study analyzed annual publication counts, prolific countries, institutions, journals, and the top 10 most cited literature. The findings were presented through descriptive statistics. VOSviewer 1.6.17 was used to exhibit keywords with high frequency and national cooperation networks, while CiteSpace 5.5.R2 displayed the timeline and burst keywords for each term.ResultsA total of 10,709 references were analyzed, and the number of publications continuously increased over the investigated period. America had the highest h-index and citation frequency, contributing to the most influence. China was the most prolific country, producing 3,168 articles. The University of London had the highest productivity. The top three productive journals were from America, and Investigative Ophthalmology Visual Science had the highest number of publications. The article from Gulshan et al. (2016; co-citation counts, 2,897) served as the representative and symbolic reference. The main research topics in this area were incidence, pathogenesis, treatment, and artificial intelligence (AI). Deep learning, models, biomarkers, and optical coherence tomography angiography (OCTA) of DR were frontier hotspots.ConclusionBibliometric analysis in this study provided valuable insights into global trends in DR research frontiers. Four key study directions and three research frontiers were extracted from the extensive DR-related literature. As the incidence of DR continues to increase, DR prevention and treatment have become a pressing public health concern and a significant area of research interest. In addition, the development of AI technologies and telemedicine has emerged as promising research frontiers for balancing the number of doctors and patients

Variants in the SNCA Locus Are Associated With the Progression of Parkinson's Disease

Background: Genetic factors have a well-known influence on Parkinson's disease (PD) susceptibility; however, no previous studies have investigated the influence of SNCA mutations on the natural history of PD using a prospective follow-up study. The aim of this study was to assess the risk factors of variation of SNCA on the prognosis symptoms of PD patients.Methods: Fifty PD patients were recruited with 38 v-PSG confirmed PD+RBD patients, and the median follow-up period was 30 months. All patients underwent a comprehensive clinical evaluation at baseline and follow-up, and six SNPs of SNCA (rs356165, rs3857053, rs1045722, rs894278, rs356186, and rs356219) were analyzed. Cox proportional hazards regression models and Kaplan–Meier plot analysis were used to assess the associations between the SNCA variation and the primary and secondary progression outcomes.Results: Based on the clinical assessment, we found that hyposmia was substantially easier to aggravate. Regression analysis showed that patients with the T allele of rs1045722 and the G allele of rs356219 presented a 34 and 20% decreased risk of progression to the H-Y stage, respectively (p = 0.022; p = 0.005). While for rs894278, G allele patients showed a 47% decreased risk of olfactory dysfunction (p = 0.029). Further subgroup analysis showed that PD+RBD patients with rs356219/G exhibited a 30% and 20% decreased risk of progression on the H-Y stage and MoCA score (p = 0.038; p = 0.045).Conclusions: Our results indicated that genetic variation in SNCA may contribute to variability natural progression of PD and could possibly be used as a prognostic marker

The Metabolism of Polysaccharide from Atractylodes macrocephala

An active polysaccharide from the rhizome of Atractylodes macrocephala Koidz (PAM) was identified to improve and adjust disordered intestinal flora. High-performance gel permeation chromatography (HPGPC) and gas chromatography-mass spectrometry (GC-MS) were employed to identify the components of PAM as rhamnose, glucose, mannose, xylose, and galactose at a ratio of 0.03 : 0.25 : 0.15 : 0.41 : 0.15. PAM metabolized in gastrointestinal tract when incubated with artificial gastric and intestinal juices. Anaerobic incubation of PAM on intestinal flora confirmed that PAM promoted the ability of intestinal bacteria to digest reducing sugar. Based on the Shannon index and similarity coefficient index of enterobacterial repetitive intergenic consensus-PCR (ERIC-PCR) fingerprinting of the total intestinal bacteria DNA, we concluded that PAM can significantly improve disordered intestinal flora and may be used as an oral adjuvant to regulate intestinal flora

Pharmacokinetics, Tissue Distribution and Excretion of Isoalantolactone and Alantolactone in Rats after Oral Administration of Radix Inulae Extract

Radix Inulae is endemic to China and has been used in traditional medicine to treat upper body pain, emesis and diarrhoea, and to eliminate parasites. Here, an UPLC-MS/MS method was developed and applied to study the pharmacokinetics, distribution and excretion of isoalantolactone and alantolactone, which are two main active sesquiterpene lactones in Radix Inulae, in Sprague-Dawley rats following oral administration of total Radix Inulae extract. Isoalantolactone, alantolactone and osthole (internal standard) were prepared using acetonitrile precipitation, and the separation of isoalantolactone and alantolactone was achieved by isocratic elution using water (containing 0.1% formic acid) and acetonitrile as the mobile phase using a ZORBAX Eclipse Plus C18 column. The total run time was 6.4 min. The present study showed poor absorption of isoalantolactone and alantolactone in vivo. The apparent Cmax, Tmax, T1/2 and total exposure (AUC0–12h) in rat plasma were 37.8 ng/mL, 120 min, 351.7 min and 6112.3 ng-min/mL for isoalantolactone and 25.9 ng/mL, 90 min, 321.0 min and 4918.9 ng-min/mL for alantolactone, respectively. It was shown that the highest concentration was achieved in the small intestine and feces clearance was shown to be the dominant elimination pathway of the lactones