Research trends and frontier hotspots of TRPV1 based on bibliometric and visualization analyses.

Background: Transient receptor potential vanilloid type1 (TRPV1) is a non-selective cation channel with multiple activation mechanisms, which has received increasing attention since it was first cloned in 1997. Methods: We used bibliometric and visualization analyses to evaluate the theme trends and knowledge structure of TRPV1 research-papers on TRPV1 from 2002 to 2022 obtained from the Web of Science Core Collection. VOSviewer and CiteSpace were used to analyze authors, institutions, countries, co-cited references, and keywords. Results: A total of 7413 papers were included. The main research area of TRPV1 was neuroscience; the most published country was the United States, and the University of California, San Francisco, had the highest centrality. Two major collaborative sub-networks were formed between the authors. The distribution of keywords shows that TRPV1 was initially studied extensively, and the recent studies focused on TRPV1 structure and diseases. "Oxidative stress," "TRPV1 structure," "cancer," and "model" have been the research hotspots in recent years. Conclusions: This research provides valuable information for the study of TRPV1. Disease research was focused on pain, cancer, and neurodegenerative diseases. Both agonists and antagonists of TRPV1 are gradually being used in clinical practice, and acupuncture was effective in treating TRPV1-mediated inflammatory pain. TRPV1 is involved in classical endogenous cannabis system signaling, and new signaling pathways continue to be revealed.

Research status and hotspots in the surgical treatment of tremor in Parkinson's disease from 2002 to 2022: a bibliometric and visualization analysis.

Objective: This study aims to investigate the research status and hotspots of surgical treatment for tremor in Parkinson's disease (PD) from 2002 to 2022, utilizing bibliometric and visual analysis. Additionally, it aims to offer insights into future research trends in this field. Methods: This study collected publications on the surgical treatment of tremor in PD from 2002 to 2022 using the Web of Science (WOS) database. CiteSpace, VOSviewer, and Scimago Graphica were employed to quantify the number of publications and analyze the bibliographic information networks, including the contributions of countries/cities, authors, keywords, and co-cited references. Results: A total of 2,815 publications were included in the study, revealing that 541 scientific institutions experienced an increase in publications from 2002 to 2022. Michael Okun emerged as the most productive author, and the United States emerged as the leading hub for research. The study identified 772 keywords. Noteworthy citation bursts and long-term activity were observed in pallidotomy, bilateral stimulation, and focused ultrasound thalamotomy. The top 10 highly co-cited references comprised eight deep brain stimulation (DBS) studies (including two follow-up studies and six randomized controlled trials), one randomized controlled trial on focused ultrasound, and one consensus on tremor. Conclusion: This study uses an in-depth and systematic bibliometric and visualization analysis to visualize the evolution of research and identify emerging hotspots. The identified hotspots are as follows: Firstly, DBS has received significant attention and widespread recognition as a surgical treatment for tremor in PD. Secondly, there are various key aspects to consider in DBS, such as operative indications, operative targets, and surgical protocols. Lastly, magnetic resonance-guided focused ultrasound (MRgFUS) has emerged as a promising treatment option in the surgical management of tremor in Parkinson's disease. This research also provides insights into the phenomenon of these hotspots, offering valuable prompts and reminders for further research.

Assessing systemic vascular resistance using arteriolar pulse transit time based on multi-wavelength photoplethysmography.

Objective.Sympathetic nerve activity affects blood pressure by contracting the arteriole, which can increase systemic vascular resistance (SVR). Consequently, SVR is a key factor affecting blood pressure. However, a method for measuring SVR continuously is lacking. This paper formulated and experimentally validated a method that uses the arteriolar pulse transmit time (aPTT) to track changes in SVR.Approach.multi-wavelength photoplethysmogram (PPG), electrocardiogram (ECG), and galvanic skin response (GSR) data were simultaneously gathered using a measurement system designed by this study. Blood perfusion was monitored by laser Doppler. Least mean square (LMS) is an adaptive filtering algorithm. Our LMS-based algorithm formulated in this study was used to calculate the aPTT from the multi-wavelength PPGs. A cold stimulation experiment was conducted to verify the relationship between aPTT determined by algorithm and arteriole vasodilation. An emotinal stimulation experiment conducted, in which GSR was employed to further verify the relationship between aPTT and SVR. Twenty healthy young participants were asked to watch movie clips, which excited their sympathetic nerves. The dynamic time warping (DTW) distance is applied to evaluate between correlation of GSR and aPTT.Main results.The changes in aPTT was extracted using our LMS-based method. During the recovery period after cold stimulation, aPTT decreased with the average slope of -0.2080, while blood perfusion increased with the average slope of 0.7046. Meanwhile, 70% participants' DTW distances median between aPTT and GSR were significantly smaller than that between PTT and GSR during emotion stimulation.Significance.Our method uses aPTT, a continuous measurable parameter, to closely reflect SVR, as verified through experiments.

Real-Time Multiple Gesture Recognition: Application of a Lightweight Individualized 1D CNN Model to an Edge Computing System.

The human-machine interface (HMI) detects electrophysiological signals from the subject and controls the machine based on the signal information. However, most applications are still only in the testing stage and are generally unavailable to the public. In recent years, researchers have been devoted to making wearable HMI devices smarter and more comfortable. In this study, a wearable, intelligent eight-channel electromyography (EMG) signal-based system was designed to recognize 21 types of gestures. An analog front end (AFE) integrated chip (IC) was developed to detect the EMG signals, and an integrated EMG signal acquisition device integrating an elastic armband was fabricated. An SIAT database of 21 gestures was established by collecting EMG gesture signals from 10 volunteers. A lightweight 1D CNN model was constructed and subjected to individualized training by using the SIAT database. The maximum signal recognition accuracy was 89.96%, and the average model training time was 14 min 13 s. Given its small size, the model can be applied on lower-performance edge computing devices and is expected to be applied to smartphone terminals in the future. The source code is available at https://github.com/Siat-F9/EMG-Tools.

The algal selenoproteomes.

BACKGROUND: Selenium is an essential trace element, and selenocysteine (Sec, U) is its predominant form in vivo. Proteins that contain Sec are selenoproteins, whose special structural features include not only the TGA codon encoding Sec but also the SECIS element in mRNA and the conservation of the Sec-flanking region. These unique features have led to the development of a series of bioinformatics methods to predict and research selenoprotein genes. There have been some studies and reports on the evolution and distribution of selenoprotein genes in prokaryotes and multicellular eukaryotes, but the systematic analysis of single-cell eukaryotes, especially algae, has been very limited. RESULTS: In this study, we predicted selenoprotein genes in 137 species of algae by using a program we previously developed. More than 1000 selenoprotein genes were obtained. A database website was built to record these algae selenoprotein genes ( www.selenoprotein.com ). These genes belong to 42 selenoprotein families, including three novel selenoprotein gene families. CONCLUSIONS: This study reveals the primordial state of the eukaryotic selenoproteome. It is an important clue to explore the significance of selenium for primordial eukaryotes and to determine the complete evolutionary spectrum of selenoproteins in all life forms.

[Research rules of famous veteran traditional Chinese medicine practitioners in treating infertility].

To explore the medication rules of famous veteran traditional Chinese medicine practitioners in treating infertility based on medical cases of infertility collected from book series of Hundred Traditional Chinese Medicine Clinicians of Hundred Years in China and Prescription Proven by Traditional Chinese Medicine Masters. Researchers extracted the information of prescriptions from these cases according to the inclusion and exclusion criteria. Then, Excel 2010, SPSS Clementine(ver.12.0) and SPSS(ver. 22.0) were adopted respectively for frequency analysis, association rules analysis, cluster analysis and factor analysis. Cluster analysis was carried out by Ochiai algorithm of binary variable data, which was a systematic clustering method. And principal component analysis was used for factor analysis. Besides, KMO test and Bartlett spherical test were used for factor adaptation test. Finally, 151 medical cases and 396 prescriptions were included in total. A total of 60 kinds of frequently used herbs were identified according to the results of frequency analysis for medication, they were mainly used for activating blood and resolving stasis, tonifying and clearing heat respectively. The association rules analysis found out 25 drug pair association rules and 14 3-drug combination association rules. A total of 15 medicine groups were extracted by cluster analysis. KMO test and Bartlett spherical test indicated that the method was suitable for factor analysis, and 21 common factors were respectively extracted by factor analysis. Association rules indicated the characteristics of the therapeutic methods, like tonifying Qi and replenishing blood. The famous veteran traditional Chinese medicine practitioners utilized modified Siwu Decoction for tonifying blood and preferred Atractylodis Macrocephalae Rhizoma(Baizhu) for tonifying Qi. The results of both cluster analysis and factor analysis demonstrated the characteristics of the therapies for tonifying kidney, activating blood, tonifying spleen and dispelling dampness. In addition, factor analysis could reflect the therapies for nourishing Yin, tonifying kidney, warming the meridian, dissipating cold, nourishing blood and dispelling blood stasis. These results of analysis comprehensively showed out the medication characteristics of famous veteran traditional Chinese medicine practitioners of strictly following the pathogenesis, making good use of classical formulas and providing proper compatibility. In conclusion, data mining techniques(including frequency analysis, association rules analysis, cluster analysis and factor analysis) were used to comprehensively analyze the medication rules of famous veteran traditional Chinese medicine practitioners in treating infertility, which is helpful for guiding the clinical practice of treating infertility with traditional Chinese medicine.

[Famous veteran traditional Chinese medicine doctors' medication rules in treating spermatorrhea].

To explore famous veteran traditional Chinese medicine( TCM) doctors' medication rules in treating spermatorrhea based on the medical cases about spermatorrhea collected from Hundred TCM Clinical Doctors of Hundred Years in China and Proven Cases and National Medical Master Test Case. Researchers extracted such data as medicinal and therapies from these cases according to the inclusion and exclusion criteria. Then,Excle 2010,SPSS Clementine 12. 0 and SPSS 22. 0 were adopted respectively for frequency analysis,association rules analysis,cluster analysis and factor analysis. Cluster analysis was carried out by Ochiai algorithm of binary variable data,one of the systematic clustering methods. And principal component analysis was used for factor analysis. Finally,27 medical cases and 41 prescriptions were included in total. The frequency analysis showed that the most common therapy was the astringent therapy( n = 28),which was followed by the tonifying method,tranquilizing method,heat-clearing method,damp-dispelling method and Qiregulating method. The top three kinds of high-frequency traditional Chinese medicines were Poria,Ostreae Concha and Dioscoreae Rhizoma. The association rules analysis found out 11 association rules of medicine pairs,23 association rules of medicine combinations of the three kinds of herbs and 6 association rules of medicine combinations of five kinds of herbs. Among them,the representatives were Rubi Fructus→Fossilia Ossis Mastodi,Rehmanniae Radix Praeparata + Corni Fructus→Dioscoreae Rhizoma,and Pinelliae Rhizoma→Citri Reticulatae Pericarpium,which showed the therapeutic characteristics of astringing,tonifying the kidney and replenishing essence,fortifying the spleen and dispelling dampness. Moreover,7 medicine groups with relevance were extracted from the tree map generated by cluster analysis,including " Phellodendri Chinensis Cortex and Anemarrhenae Rhizoma" and " Angelicae Sinensis Radix,Rehmanniae Radix,Bupleuri Radix and Glycyrrhizae Radix et Rhizoma",which demonstrated the effects of nourishing Yin and purging fire,tonifying and soothing the liver. Besides,totally 12 common factors were obtained according to factor analysis,including 14 drug combinations,like " Amomi Fructus,Anemarrhenae Rhizoma and Phellodendri Chinensis Cortex" and " Nelumbinis Stamen,Moutan Cortex,Poria and Scrophulariae Radix",which indicated the compatibility characteristics of tonifying the spleen and purging fire,dispelling dampness and clearing heat. In conclusion,data mining techniques( including frequency analysis,association rules analysis,cluster analysis and factor analysis) were used to comprehensively analyze the famous veteran TCM doctors' medication rules in treating spermatorrhea,which was helpful for guiding the clinical practice of treating spermatorrhea in TCM.

Identification and characterization of a novel multifunctional placenta specific protein 8 in Dugesia japonica.

Placenta specific protein 8 (Plac8) has been well studied in vertebrates, yet little is known in invertebrates. In this study, a novel Plac8 from the planarian Dugesia japonica was identified and its functions in immune responses and development were characterized. Our results show that Djplac8 was expressed in the pharynx, epidermis and intestine of intact adult planarian. The expression of DjPlac8 increased significantly upon lipopolysaccharide (LPS) challenge, and inhibited the growth of the Gram-negative bacteria (Escherichia coli and Pseudomonas aeruginosa), suggesting the role of Plac8 in immune response. Spatial and temporal expression and distribution of DjPlac8 mRNA in regenerated planarians indicates that DjPlac8 was mainly expressed in the pharynx. In situ hybridization also revealed the elevated expression of the DjPlac8 gene in the embryonic pharynx, germ band and parenchyma cells, indicating an important role in embryonic development of D. japonica. When DjPlac8 was deactivated by RNA interference-mediated knockdown, the head of planarians underwent abnormal development. In summary, we identified DjPlac8 as a novel multifunctional protein that plays essential roles in immune response and development of planarians.