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As central agents in the cultural dialogue between China and Europe in the 17th century, Christian Chinese communities represent a rich and fascinating source, offering a unique intercultural perspective on the intellectual, cultural, and religious world of late Ming and early Qing China. What did these communities look like? How did they come into being and maintain their significance as a community? By utilising stories depicting scenes of Christian ritual practices in local Chinese contexts between the 1620s and 1640s, collected by a late Ming Christian convert from Fujian, this article delves into the life of Chinese Christian communities, specifically focusing on the dimension of ritual practice. It shows how rituals played a key role in the formation of these communities, not only in keeping them alive, but also in continually redefining their significance for their members.

Summary: Knowledge about the impact of different dissolved oxygen (DO) on the composition and function of gut bacteria of aquatic insects is largely unknown. Herein, we constructed freshwater environments with different DOs (hypoxia: 2.50 ± 0.50, normoxia: 7.00 ± 0.50, and hyperoxia: 13.00 ± 0.50 mg/L) where aquatic firefly Aquatica leii larvae lived for three months. Their gut flora was analyzed using the combination of 16S rRNA amplicon sequencing and metagenomics. The results showed no difference in alpha diversity of the gut flora between A. leii inhabiting various DOs. However, the relative abundance of several bacterial lineages presented significant changes, such as Pseudomonas. In addition, bacterial genes with an altered relative abundance in response to various DOs were primarily related to metabolism. The alteration of these functions correlated with the DO change. This is the first to uncover structure of gut flora under various DOs in aquatic insect larvae.

As a global phenomenon, mobile phone addiction has become an increasingly common issue among Chinese university students. Although previous research explored the link between mobile phone addiction and mental health, the possible mechanism underlying the above association is unclear. We administered a cross-sectional survey to 585 participants from two universities in Kunming, southwest China, from October 2021 to January 2022. Our results suggested that mobile phone addiction was negatively associated with mental health, and sleep quality partially mediated the relationship between mobile phone addiction and mental health. Furthermore, perceived social support positively moderated the direct effect of sleep quality on mental health, as well as the indirect effect of mobile phone addiction on mental health. These findings provide a new insight into the underlying mechanism by which mobile phone addiction affects university students’ mental health. The results emphasize a necessary task for administrators, health workers, and family members to attach importance to the overuse of mobile phones among university students.

Background: Epidemiological studies about the effect of essential metal mixture on fasting plasma glucose (FPG) levels among elderly people are sparse. The object of this study was to examine the associations of single essential metals and essential metal mixture with FPG levels in Chinese community-dwelling elderly people. Methods: The study recruited 2348 community-dwelling elderly people in total. Inductively coupled plasma-mass spectrometry was adopted to detect the levels of vanadium (V), selenium (Se), magnesium (Mg), cobalt (Co), calcium (Ca), and molybdenum (Mo) in urine. The relationships between single essential metals and essential metal mixture and FPG levels were evaluated by linear regression and Bayesian kernel machine regression (BKMR) models, respectively. Results: In multiple-metal linear regression models, urine V and Mg were negatively related to the FPG levels (β = − 0.016, 95 % CI: − 0.030 to − 0.003 for V; β = − 0.021, 95 % CI: − 0.033 to − 0.009 for Mg), and urine Se was positively related to the FPG levels (β = 0.024, 95 % CI: 0.014–0.034). In BKMR model, the significant relationships of Se and Mg with the FPG levels were also found. The essential metal mixture was negatively associated with FPG levels in a dose-response pattern, and Mg had the maximum posterior inclusion probability (PIP) value (PIP = 1.0000), followed by Se (PIP = 0.9968). Besides, Co showed a significant association with decreased FPG levels in older adults without hyperlipemia and in women. Conclusions: Both Mg and Se were associated with FPG levels, individually and as a mixture. The essential metal mixture displayed a linear dose-response relationship with reduced FPG levels, with Mg having the largest contribution to FPG levels, followed by Se. Further prospective investigations are necessary to validate these exploratory findings.

Background The past nearly 20-year period has seen a sudden increase in the use of artificial intelligence (AI) in esophageal cancer research, and an emergence of many systematic reviews and meta-analyses of the research. However, most of the reviews and meta-analyses only address a single aspect in summary, making it difficult for researchers to gain a comprehensive understanding of the latest developments and research hotspots in the field. Objective To perform a bibliometric analysis of the use of AI in esophageal cancer research, and the development, hotspots and emerging trend in this field. Methods All literature in English regarding esophageal cancer research using AI included in the Science Citation Index Expanded database of the Web of Science Core Collection was searched from 2000-01-01 to 2022-04-06. Microsoft Excel 2019, CiteSpace (5.8R3-64bit) and VOSviewer (1.6.18) were used to analyze the literature for annual number of publications, country, author, institution, co-citation and keywords. Results Nine hundred and eighteen studies were retrieved, with a total of 23 490 times of being cited. The number of studies published between 2000 and 2016 grew slowly (from 6 to 40), but increased rapidly between 2017 and 2022 (from 62 to 216). Sixty countries, 118 institutions and 5 979 authors were involved in the studies. China (306 articles), the United States (238 articles) and the United Kingdom (113 articles) ranked the top three in terms of number of studies published. The top three institutions in terms of intensity of cooperation were University of Amsterdam (TLS=72), Catherine Hospital (TLS=64) and Eindhoven University of Technology (TLS=53). The top three authors in terms of number of publications were Jacques J G H M Bergman from the Netherlands (n=16), Tomohiro Tada from Japan (n=12), and Fons Van Der Sommen from the Netherlands (n=12). There were 39 962 co-cited authors and 42 992 co-cited studies. Thirty-three burst keywords were identified: the major burst keywords were p53 and mutations in 2001-2008 (early stage), and were esophageal cancer classification, new examination techniques (tomography), differentiation, identification and comparison between esophageal cancer and other cancers in 2013-2018 (middle stage), and were deep learning, convolutional neural network, and machine learning in esophageal cancer examination and diagnosis applications in 2019-2022 (late stage). Among which deep learning had the highest burst intensity (burst intensity of 13.89) . Conclusion AI application in esophageal cancer research has entered a new phase, moving gradually from genes and mutations toward accurate examination, diagnosis, and treatment. The latest major burst keywords in recent years (2019-2022) are deep learning, convolutional neural network, and machine learning in esophageal cancer examination and diagnosis. The future challenges to the use of AI in esophageal cancer research may include individual data collection, data quality assurance, data processing specifications, AI code reproduction, and reliability assurance of AI-assisted diagnostic decision-making.

With the rapid development of social economy and the continuous improvement of people’s living standards, the demand for foods of animal origin is also increasing. The problem of veterinary drug residues in foods of animal origin has attracted more and more attention. Meanwhile, higher requirements have been raised for the supervision and inspection of veterinary drug residues. High-resolution mass spectrometry (HRMS) is a powerful tool to retrieve compounds, which can enable the non-targeted screening and confirmation of a variety of veterinary drugs without the use of standards. HRMS is an important technical means for risk monitoring and high-throughput screening of veterinary drug residues, making up for the weaknesses of triple quadrupole mass spectrometry such as poor universality and no ability to screen unknown compounds. This review summarizes the application of liquid chromatography-high resolution mass spectrometry (LC-HRMS) in the field of veterinary drug residue detection from the year 2018 to 2021, and systematically demonstrates the advantages and characteristics of HRMS. With the popularization of HRMS and the development of detection technologies, HRMS will be widely used in the field of veterinary drug residue detection as a routine method.

Nowadays, communication networks are becoming increasingly complex. This paper aims to demonstrate an effective method to achieve the intelligent planning for network base stations (BSs). The various parameters such as BS coordinates (x, y), the collaboration of multiple types of BS, and the density of BS construction are taken as design parameters for BS placement. We construct the objective function using the lowest total cost and the total minimum workload of BS to 90%. To solve the problem of siting planning with large data volume and mixed placement of multiple BS, we propose a new practical three-step model for BS siting planning: (I) roughly selecting the alternative coordinates for the BS using the DBSCAN algorithm; (II) correcting and further refining the alternative BS coordinates using the K-means algorithm; (III) determining the optimal BS construction solution to meet the requirements using simulated annealing algorithm (SAA). The real data of a $2500\times 2500$ area have been used for the simulation test. The simulation result shows that BS placement covers 90.03% of the workload, confirming that the proposed method can handle site planning for large orders of magnitude of data and use a mix of BS to achieve the best economics for the demand. This paper provides basic support for future research on network site optimization.

Alzheimer’s disease is known as one of the “top ten killers in the world”. Due to lack of effective therapy at present， early pathological changes have captivated widespread attention. Axonal transport dysfunction has been reported as an early pathological feature of many neurodegenerative diseases. However， multiple factors can cause axonal transport dysfunction. In this article， the relationship between axonal transport dysfunction caused by kinesins， microtubules and mitochondria and Alzheimer’s disease was discussed， aiming to provide new ideas for the prevention and treatment of Alzheimer’s disease by in-depth study on axonal transport mechanism of neure.

High amylase level is a typical sign of acute pancreatitis. However， it can also be found in other diseases. In the article， a case of persistent elevation of amylase level for over 1 year was reported. A 66-year-old male patient suffered from bullous pemphigoid complicated with diabetes mellitus for 3 years. After bullous pemphigoid treatment 8 months ago， he presented with elevated amylase level ranging from 556 to 1106 U/L， serum lipase level between 62 U/L and 73 U/L and urine amylase level between 553 U/L and 1162 U/L， respectively. The renal amylase clearance rate /creatinine clearance ratio was 0.8% （