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.

Arboviruses have always been a significant public health concern. Metagenomic surveillance has expanded the number of novel, often unclassified arboviruses, especially mosquito-borne and mosquito-specific viruses. This report presents the first description of a novel single-stranded RNA virus, Wanghe virus, identified from mosquitoes that were collected in Shandong Province in 2022. In this study, a total of 4,795 mosquitoes were collected and then divided into 105 pools according to location and species. QRT-PCR and nested PCR were performed to confirm the presence of Wanghe virus, and its genomic features and phylogenetic relationships were further analyzed. Our results revealed that Wanghe virus was detected in 9 out of the 105 mosquito pools, resulting in a minimum infection rate (MIR) of 0.19 % (9/4,795). One complete genome sequence and three viral partial sequences were obtained from the Wanghe virus-positive pools. Pairwise distance analysis indicated that these amplified sequences shared high nucleotide identity. Phylogenetic analysis demonstrated that Wanghe virus is most closely related to Guiyang Solinvi-like virus 3, which belongs to Solinviviridae. Further analyses indicated that Wanghe virus is a new, unclassified member of Solinviviridae.

Droughts and heat waves exhibit synergistic effects and are among the world\'s most costly disasters. To explore the spatiotemporal differences and formation mechanisms of the combined vulnerability to droughts and heat waves in Shandong Province over the past 20 years, a vulnerability scoping diagram (VSD) model with three dimensions-exposure, sensitivity, and adaptability-was constructed to assess and compare the combined vulnerability to high-temperature and drought events, considering economic and social conditions. The results showed that (1) over the past 20 years, heat waves and droughts have increased in Shandong Province. The number of high-temperature events significantly increased in the west and decreased along the eastern coast, and drought change was characterized by an increase in the south and a decrease in the north. (2) The combined exposure to summer droughts and heat waves in Shandong Province showed a significant increasing trend (P < 0.05) at a rate of approximately 0.072/10a; the combined sensitivity significantly decreased (P < 0.05) at a rate of approximately 0.137/10a, and the combined adaptability continued to increase at a rate of approximately 0.481/10a. (3) The combined vulnerability to summer droughts and heat waves in the western inland area of Shandong Province was high and gradually decreased toward the southeastern coast. The overall decrease trend was nonsignificant with a decrease of approximately 0.126/10a, and the decline rate decreased from northwest to southeast, in which Laiwu, Yantai, Jinan, and Zibo cities exhibited a significant decreasing trend (P < 0.05). Although the compound vulnerability of Shandong Province has decreased insignificantly, the frequency of combined drought and heat wave events has increased, and the combined vulnerability will increase in the future.

PM2.5 remote sensing data was applied in this study, and Theil-Sen Median trend analysis and the Mann-Kendall significance test were utilized to analyze the temporal and spatial variation in PM2.5 in the Shandong Province from 2000 to 2021. The influencing power of the influencing factors on the spatial differentiation of PM2.5 concentration in the Shandong Province was detected at the provincial-city-county levels based on Geo-detector data. The results showed that:① on the temporal scale, the mean ρ(PM2.5)in the Shandong Province ranged from 38.15 to 88.63 μg·m-3 from 2000 to 2021, which was slightly higher than the secondary limit of inhalable particulate matter (35 μg·m-3) in the Ambient Air Quality Standards. On the interannual scale, 2013 was the peak year for the variation in ρ(PM2.5) with a value of 83.36 μg·m-3, according to which the trend of PM2.5 concentrations in the Shandong Province was divided into two phases:a continuous increase and a rapid decrease. On the seasonal scale, PM2.5 concentration presented the distribution characteristics of \"low in summer and high in winter and moderate in spring and autumn\" and the U-shaped change rule of first decreasing and then increasing. ② On the spatial scale, the PM2.5 concentration in the Shandong Province presented a spatial distribution pattern of \"high in the west and low in the east.\" The areas with high PM2.5 concentration were distributed in the western area of the Shandong Province, whereas the areas with low PM2.5 concentration were distributed in the eastern peninsula region. The spatial variation in the changing trend of PM2.5 concentration showed significant spatial heterogeneity, and the extremely significant decrease was mainly distributed in the eastern peninsula region. ③ The results of factor detection showed that climate factor was an important factor affecting the spatial differentiation of PM2.5 concentration in the Shandong Province. Mean temperature had the highest influence on the spatial differentiation of PM2.5 concentration in the Shandong Province, with a q value of 0.512. Provincial-city-county multi-scale detection results showed that the influencing factors affecting the spatial differentiation of PM2.5 concentration and their influencing power differed at different spatial scales. At the provincial scale, mean temperature, sunshine duration, and slope were the main factors affecting the spatial differentiation of PM2.5 concentration. At the city level, precipitation, elevation, and relative humidity were the main factors affecting the spatial differentiation of PM2.5. At the county level, precipitation, mean temperature, and sunshine duration were the main factors affecting the spatial variation in PM2.5 concentration.

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.

BACKGROUND: Hepatitis C threatens human health and brings a heavy economic burden. Shandong Province is the second most populous province in China and has uneven regional economic development. Therefore, we analyzed the incidence rate trend and regional differences of hepatitis C in Shandong Province from 2004 to 2021.
METHODS: The monthly and annual incidence rates of hepatitis C in Shandong Province from 2022 to 2030 were predicted by fitting Autoregressive Integrated Moving Average model (ARIMA), Long Short-Term Memory (LSTM) and ARIMA-LSTM combined model.
RESULTS: From 2004 to 2021, annual new cases of hepatitis C in Shandong Province increased from 635 to 5834, with a total of 61,707 cases. The incidence rate increased from 0.69/100 thousand in 2004 to 6.40/100 thousand in 2019, with a slight decrease in 2020 and 2021. The average annual incidence rate was 3.47/100 thousand. In terms of regional distribution, the hepatitis C incidence rate in Shandong Province was generally high in the west and low in the east. It is estimated that the hepatitis C incidence rate in Shandong Province will be 9.21 per 100 thousand in 2030.
CONCLUSIONS: The hepatitis C incidence rate in Shandong Province showed an increasing trend from 2004 to 2019 and a decreasing trend in 2020 and 2021. Significant regional variations in incidence rate existed. An upward trend in incidence rate is predicted from 2022 to 2030. It is necessary to strengthen the prevention and control of hepatitis C to achieve the goal of eliminating viral hepatitis by 2030.

To explore the resource components and availability of different parts of Panax quinquefolium in Shandong province, the paper employed the non-targeted metabolomics technology based on ultra-high performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS) to analyze the metabolites and their metabolic pathways in the root, fibril, stem, and leaf of P. quinquefolium. The content of seven ginsenosides and polysaccharides in different parts was determined by high performance liquid chromatography(HPLC) and ultraviolet-visible spectrophotometry(UV-Vis). The results showed that the metabolites were mainly sugars, glycosides, organic acids, amino acids and their derivatives, terpenoids, etc. The total abundance of metabolites followed the trend of leaf > root > fibril > stem. Most of the differential metabolites were concentrated in phenylpropane biosynthesis, flavonoid biosynthesis, citric acid cycle, and amino acid biosynthesis. The leaf contained high levels of sugars, glycosides, amino acids and their derivatives, and flavonoids; the root was rich in terpenoids, volatile oils, vitamins, and lignin; the fibril contained rich organic acids; and the stem had high content of nucleotides and their derivatives. The content of ginsenosides Re and Rb_1 was significantly higher in the root; the content of ginsenosides Rg_1, Rg_2, Rd, F_(11), and polysaccharide was significantly higher in the leaf; and the content of ginsenoside Rb_2 was significantly higher in the stem. We analyzed the resource components and availability of different parts of P. quinquefolium, aiming to provide basic information for the comprehensive development and utilization of P. quinquefolium resources in Shandong province.

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.