UNASSIGNED: Scrub typhus, an acute febrile disease caused by Orientia tsutsugamushi, is transmitted to humans through infected chigger mites. We present a case of scrub typhus in a previously healthy man from Shandong Province diagnosed using next-generation sequencing (NGS) and PCR and review recent literature on NGS for scrub typhus diagnosis.
UNASSIGNED: NGS was utilized for testing whole blood collected on admission. Confirmatory testing was done by detecting IgM and IgG antibodies to Orientia in acute and convalescent sera by ELISA. Orientia 47-kDa protein gene TaqMan and standard PCR of the 56-kDa protein gene and Sanger sequencing were performed on eschar scab DNA.
UNASSIGNED: The NGS diagnosis was confirmed by 47-kDa protein gene TaqMan and sequencing of a fragment of the O. tsutsugamushi 56-kDa protein gene from the eschar scab. Analysis of this sequence and the NGS data indicated O. tsutsugamushi strain Cheeloo2020 is a novel genotype. Mapping of the NGS data against the O. tsutsugamushi Gilliam strain genome sequence identified 304 reads with high similarity.
UNASSIGNED: NGS is not only useful for multiplex diagnosis of scrub typhus, but also provides insight into the genetic diversity of O. tsutsugamushi. The common failure to submit sequences to databases makes it difficult to determine the minimal quantity and quality of NGS data being used for the positive identification of Orientia DNA in clinical specimens.

Soil organic carbon (SOC) is a crucial component of the global carbon cycle, playing a significant role in ecosystem health and carbon balance. In this study, we focused on assessing the surface SOC content in Shandong Province based on land use types, and explored its spatial distribution pattern and influencing factors. Machine learning methods including random forest (RF), extreme gradient boosting (XGBoost), and support vector machine (SVM) were employed to estimate the surface SOC content in Shandong Province using diverse data sources like sample data, remote sensing data, socio-economic data, soil texture data, topographic data, and meteorological data. The results revealed that the SOC content in Shandong Province was 8.78 g/kg, exhibiting significant variation across different regions. Comparing the model error and correlation coefficient, the XGBoost model showed the highest prediction accuracy, with a coefficient of determination (R²) of 0.7548, root mean square error (RMSE) of 7.6792, and relative percentage difference (RPD) of 1.1311. Elevation and Clay exhibited the highest explanatory power in clarifying the surface SOC content in Shandong Province, contributing 21.74% and 13.47%, respectively. The spatial distribution analysis revealed that SOC content was higher in forest-covered mountainous regions compared to cropland-covered plains and coastal areas. In conclusion, these findings offer valuable scientific insights for land use planning and SOC conservation.

Monitoring and predicting the regional groundwater storage (GWS) fluctuation is an essential support for effectively managing water resources. Therefore, taking Shandong Province as an example, the data from Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) is used to invert GWS fluctuation from January 2003 to December 2022 together with Watergap Global Hydrological Model (WGHM), in-situ groundwater volume and level data. The spatio-temporal characteristics are decomposed using Independent Components Analysis (ICA), and the impact factors, such as precipitation and human activities, which are also analyzed. To predict the short-time changes of GWS, the Support Vector Machines (SVM) is adopted together with three commonly used methods Long Short-Term Memory (LSTM), Singular Spectrum Analysis (SSA), Auto-Regressive Moving Average Model (ARMA), as the comparison. The results show that: (1) The loss intensity of western GWS is significantly greater than those in coastal areas. From 2003 to 2006, GWS increased sharply; during 2007 to 2014, there exists a loss rate - 5.80 ± 2.28 mm/a of GWS; the linear trend of GWS change is - 5.39 ± 3.65 mm/a from 2015 to 2022, may be mainly due to the effect of South-to-North Water Diversion Project. The correlation coefficient between GRACE and WGHM is 0.67, which is consistent with in-situ groundwater volume and level. (2) The GWS has higher positive correlation with monthly Global Precipitation Climatology Project (GPCP) considering time delay after moving average, which has the similar energy spectrum depending on Continuous Wavelet Transform (CWT) method. In addition, the influencing facotrs on annual GWS fluctuation are analyzed, the correlation coefficient between GWS and in-situ data including the consumption of groundwater mining, farmland irrigation is 0.80, 0.71, respectively. (3) For the GWS prediction, SVM method is adopted to analyze, three training samples with 180, 204 and 228 months are established with the goodness-of-fit all higher than 0.97. The correlation coefficients are 0.56, 0.75, 0.68; RMSE is 5.26, 4.42, 5.65 mm; NSE is 0.28, 0.43, 0.36, respectively. The performance of SVM model is better than the other methods for the short-term prediction.

To investigate the positivity rates and drug resistance characteristics of Mycobacterium tuberculosis (MTB) among suspected tuberculosis (TB) patients in Shandong Province, the second-largest population province in China.
A prospective, multi-center study was conducted from April 2022 to June 2023. Pathogen and drug resistance were identified using nucleotide matrix-assisted laser desorption ionization time-of-flight mass spectrometry (nucleotide MALDI-TOF MS).
Of 940 suspected TB patients included in this study, 552 cases were found to be infected with MTB giving an overall positivity rate of 58.72%. Total of 346 cases were resistant to arbitrary anti-TB drug (62.68%), with Zibo (76.47%), Liaocheng and Weihai (both 69.23%) ranking top three and TB treatment history might be a related factor. Monoresistance was the most common pattern (33.53%), with isoniazid the highest at 12.43%, followed by rifampicin at 9.54%. Further analysis of gene mutations conferring resistance revealed diverse types with high heteroresistance rate found in multiple anti-TB drugs.
A relatively high rate of MTB positivity and drug resistance was found in Shandong Province during and after the COVID-19 pandemic, indicating the need for strengthening rapid identification of species and drug resistance among suspected TB patients to guide better medication and minimize the occurrence of drug resistance.

As a major coastal economic province in the east of China, it is of great significance to clarify the temporal and spatial patterns of regional development in Shandong Province in recent years to support regional high-quality development. Nightlight remote sensing data can reveal the spatio-temporal patterns of social and economic activities on a fine pixel scale. We based the nighttime light patterns at three spatial scales in three geographical regions on monthly nighttime light remote sensing data and social statistics. Different cities and different counties in Shandong Province in the last 10 years were studied by using the methods of trend analysis, stability analysis and correlation analysis. The results show that: (1) The nighttime light pattern was generally consistent with the spatial pattern of construction land. The nighttime light intensity of most urban, built-up areas showed an increasing trend, while the old urban areas of Qingdao and Yantai showed a weakening trend. (2) At the geographical unit scale, the total nighttime light in south-central Shandong was significantly higher than that in eastern and northwest Shandong, while the nighttime light growth rate in northwest Shandong was significantly highest. At the urban scale, Liaocheng had the highest nighttime light growth rate. At the county scale, the nighttime light growth rate of counties with a better economy was lower, while that of counties with a backward economy was higher. (3) The nighttime light growth was significantly correlated with Gross Domestic Product (GDP) and population growth, indicating that regional economic development and population growth were the main causes of nighttime light change.

Hubei mosquito virus 2 (HMV2) is a novel mosquito virus that was first identified in 2016 in Hubei Province, China. Until now, HMV2 has been shown to be endemic in some areas of China and Japan, but its biological characteristics, epidemiology, and pathogenicity are not yet known. This report describes the detection of HMV2 in mosquitoes that were collected in Shandong Province in 2019 and presents the first isolation and molecular characterization of the virus. In this study, a total of 2,813 mosquitoes were collected and then divided into 57 pools, according to location and species. qRT-PCR and nested PCR were performed to confirm the presence of HMV2, and its genomic features, phylogenetic relationships, growth characteristics, and potential pathogenicity were further analyzed. The results showed that HMV2 was detected in 28 of the 57 mosquito pools and that the minimum infection rate (MIR) for HMV2 was 1.00% (28/2,813). A HMV2 strain and 14 viral partial sequences were obtained from the HMV2-positive pools, including one complete genome sequence. A phylogenetic analysis revealed that HMV2 from Shandong Province shared over 90% identity with other reported isolates and was closely related to the Culex inatomii luteo-like virus. IMPORTANCE Our study provided important epidemiological evidence for the epidemic of HMV2 in Shandong Province. Here, we report the first isolation and molecular characteristics of this virus and enrich our knowledge of the distribution of HMV2 in China.

BACKGROUND: Soil-transmitted helminths (STHs) were previously endemic in Shandong Province, China. This study aimed to analyze the STHs prevalence trend and the natural, social, and human cognitive and behavioural factors influencing the discrepancies between high and low infection levels from 2016 to 2020 in Shandong Province in eastern China.
METHODS: STHs surveillance data of Shandong Province from 2016 to 2020 were obtained from China Information Management System for Prevention and Control of Parasitic Diseases. STHs infections were detected by modified Kato-Katz method. Comprehensive information on the natural and social factors, STHs-related knowledge and behaviours were collected through questionnaire surveys. Retrospective spatial scan analysis was performed using SaTScan v10.1 to evaluate any identified spatial clusters of STHs infection for statistical significance and Bayes discriminant analysis was used to discriminate the high or low infection groups of the villages.
RESULTS: In total, 72,160 participants were involved in our survey from 2016 to 2020. The overall STHs prevalence rate was 1.13%, with the eastern region of Shandong Province having the highest rate (2.02%). The predominant species was T. trichiura, with the prevalence rate of 0.99% and the ≥ 70-year age group possessed the highest rate of 2.21%. The STHs prevalence rate showed an annual linear downward trend from 2016 to 2020 ([Formula: see text] = 127.600, P < 0.001). Respondents aged ≥ 60 years had the lowest awareness level of STHs-related prevention knowledge (all P < 0.05), and were the most likely to adopt the practice of fertilizing with fresh stool (χ2 = 28.354, P < 0.001). Furthermore, the southern region demonstrated the highest temperature and rainfall level and the lowest GNP and annual net income per capita (all P < 0.05).
CONCLUSIONS: There is a remarkable declining in STHs prevalence in Shandong Province from 2016 to 2020. However, the prevalence rates of STHs especially T. trichiura in the southern and eastern regions were still high, and the elderly were more susceptible to be infected with STHs owning to their low awareness level of STHS-related prevention knowledge and high adoption rate of dangerous production and living behaviours. Integrated approaches of health education, environment improvement and behaviour change should be strengthened to obtain a further reduction of STHs prevalence in China.

The aim of this study is to understand the current situation of university students\' participation in emergency education and its influencing factors in Shandong province, to improve the enthusiasm of university students\' involvement in emergency training and exercise activities, and to provide a reference for universities to carry out education on public health emergencies.
From April to May 2020, 6,630 university students were selected from six universities in Shandong province by stratified random sampling. Descriptive analysis, χ2 test, and logistic regression for statistical analysis were also used.
Overall, 35.5 and 55.8% of university students believed that it is necessary to participate in emergency education activities, and 65.8% of university students participated in emergency training and exercise activities. Through multivariate analysis, the results showed that university students who are men, sophomores, medical students, from within the province, the only child, have good health, take emergency education courses, think it is necessary to participate in emergency education, think the school attaches great importance to emergency education, believe that the professional teacher level to meet needs, know about public health emergencies, have received emergency education such as prevention and treatment of infectious diseases, and have a higher participation rate of emergency education and training activities.
The willingness of university students to participate in emergency education in Shandong province is high, but the willingness in emergency training and exercise activities is low. Gender, grade, profession, and students\' nationalities, whether it is only children, health, the school courses in emergency education situations, the value of emergency education, emergency education to participate, the degree of teachers\' professional level to meet the requirements, a public health emergency condition as well as the prevention and treatment of infectious diseases such as emergency education are the main influencing factors for university students\' participation in emergency training and exercise activities in Shandong province.

With its unique geographical location, the coastal zone has concentrated great advantages in resources, population and economy. However, with the deepening of marine resources development activities, a series of problems have emerged in the coastal zone, such as the gradual shortage of resources, the decline of environmental quality and the increase of ecological risks. The coastal zone ecosystem has shown a certain degradation trend. Maintaining the health of the coastal zone ecosystem has become the primary task of the sustainable development of the marine economy. Monitoring the coastal ecosystem carrying capacity, diagnosing the health status of the coastal ecosystem, effectively planning and managing the development and utilization of natural resources in the coastal zone, and controlling human activities related to the sea within the ecological carrying capacity and health limits of the coastal zone are of great significance to the sustainable development of society and economy in the coastal zone. In this study, the ecosystem health model, state space model and ecological health early warning principle were comprehensively applied to construct the coastal ecosystem health diagnosis framework of \"Carrying type →Early warning degree →Health level;\" The evaluation index system of coastal ecosystem carrying capacity was established; Taking Shandong Province as the empirical research object, the health status of the coastal ecosystem in Shandong Province was diagnosed by using the relevant data from 2007 to 2019. The empirical results show that: (1) From 2007 to 2013, the carrying capacity of the coastal ecosystem in Shandong Province was relatively good, in the state of \"loadable\" or \"critical overload,\" while from 2014 to 2019, the carrying capacity was poor, in the state of \"overload;\" (2) From 2007 to 2013, the early warning degree of coastal ecosystem health in Shandong Province was in the state of \"no alarm,\" \"light alarm,\" and \"medium alarm,\" and the health level was in the state of \"very healthy,\" \"healthy,\" and \"sub-health;\" from 2014 to 2019, the health warning level of the coastal ecosystem in Shandong Province was in the state of \"serious alarm\" and \"extremely serious alarm,\" and the health level was in the state of \"unhealthy\" and \"Morbid,\" and the health status was worrying; (3) The key influencing factors affecting the carrying capacity of the coastal ecosystem mainly included the output of marine mining, marine GDP, per capita marine production, total amount of main pollutants directly discharged into the sea, domestic tourist arrivals in coastal cities, area of marine nature reserves, proportion of class IV and inferior class IV seawater, average density of beach garbage in the monitoring area, number of medical and health institutions; Finally, some policy suggestions were put forward to improve the health of coastal ecosystem in Shandong Province. In the \"discussion\" part of this study, the consistency between the research results of this paper and the actual situation of the marine ecosystem in Shandong Province and the existing research results of the same kind is compared, and the applicability and limitations of the research methods in this paper are put forward, indicating that the research methods in this paper are more applicable to the comparative analysis under the same ideal value determination criteria.

Antibiotic-resistant pathogens pose high risks to human and animal health worldwide. In recent years, many studies have been carried out to investigate the role of gut microbiota as a pool of antibiotic resistance genes (ARGs) in human and animals. Both the structure and function of the gut bacterial community and related ARGs in pig remain unknown. In this study, we characterized the gut microbiomes and resistomes of fecal samples collected from sixteen pig farms located in sixteen cities of Shandong Province by metagenomic sequencing. Alpha diversity indicated that fecal samples from Dezhou (DZ) and Jinan (J) showed higher alpha diversity, and the lowest was from pig farms of Rizhao (RZ). Other pig farms showed similar alpha diversity. Besides, we found that the composition of gut bacterial among these pig farms varied greatly. Helcococcus massiliensis was the dominant bacterial species in pig farms of RZ and Zibo (ZB), while Prevotella sp. P5-92 occupied a superior proportion in Binzhou (BZ) and Yantai (YT). The proportion of Lactobacillus johnsonii was similar among farms of Qingdao (QD), Linyi (LY), Taian (TA), Weifang (WF), Weihai (WH), and YT. In total, 1112 ARGs were obtained and classified into 69 groups from 48 fecal samples. ARG abundance was higher in farms of Dongying (DY) and WH than others, while the lowest farms in BZ and ZB. Interestingly, it is found that BZ pig farm was exclusive, so the tetQ gene showed a higher abundance. In contrast, the load of APH(3\') - IIIa in fecal samples from DY, J-1, LC, WF, and WH was high. Meanwhile, the most relevant ARGs and the corresponding microbes were screened out. Our metagenomic sequencing data provides new insights into the abundance, diversity, and structure of bacterial community in pig farms. Meanwhile, we screened ARG-carrying bacteria and explored the correlation between ARGs and bacterial community, which provide a comprehensive view of the pig fecial ARGs and microbes in different farms of Shandong.