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Background: The effectiveness of post-exposure prophylaxis (PEP) depends on participants adherence, making it crucial to assess and compare regimen options to enhance human immunodeficiency virus (HIV) prophylaxis strategies. However, no prospective study in China has shown that the completion rate and adherence of single-tablet regimens in HIV PEP are higher than those of multi-tablet preparations. Therefore, this study aimed to assess the completion rate and adherence of two HIV PEP regimens. Methods: In this single-center, prospective, open-label cohort study, we included 179 participants from May 2022 to March 2023 and analyzed the differences in the 28-day medication completion rate, adherence, safety, tolerance, and effectiveness of bictegravir/emtricitabine/tenofovir alafenamide (BIC/FTC/TAF) and tenofovir disoproxil fumarate, emtricitabine, and dolutegravir (TDF/FTC + DTG). Results: The PEP completion rate and adherence were higher in the BIC/FTC/TAF group than in the TDF/FTC + DTG group (completion rate: 97.8% vs. 82.6%, P = 0.009; adherence: 99.6 ± 2.82% vs. 90.2 ± 25.29%, P = 0.003). The incidence of adverse reactions in the BIC/FTC/TAF and TDF/FTC + DTG groups was 15.2% and 10.3% (P = 0.33), respectively. In the TDF/FTC + DTG group, one participant stopped PEP owing to adverse reactions (1.1%). No other participants stopped PEP due to adverse events. Conclusions: BIC/FTC/TAF and TDF/FTC + DTG have good safety and tolerance as PEP regimens. BIC/FTC/TAF has a higher completion rate and increased adherence, thus, is recommended as a PEP regimen. These findings emphasize the importance of regimen choice in optimizing PEP outcomes. Trial registration: The study was registered in the Chinese Clinical Trial Registry (registration number: ChiCTR2200059994(2022-05-14), https://www.chictr.org.cn/bin/project/edit?pid=167391). [ABSTRACT FROM AUTHOR]

Introduction: Bictegravir/emtricitabine/tenofovir alafenamide (BIC/FTC/TAF) and dolutegravir plus lamivudine (DTG + 3TC) are well tolerated and effective in clinical trials. This study aimed to evaluate the safety and efficacy of these two schemes in a real-world setting and to obtain the first dataset for switching to BIC/FTC/TAF and DTG + 3TC in a Chinese population. Methods: This retrospective single-center cohort study in China included participants who switched to DTG + 3TC or BIC/FTC/TAF between January 2020 and February 2023. The main endpoint was the proportion of participants with HIV-1 RNA levels of ≥ 50 copies/mL. Safety, tolerance, and the incidence of low-level viremia (LLV) were evaluated. Results: A total of 525 participants were included, 454 of whom were included in the PP analysis. At week 48, the proportions of participants with HIV-1 RNA ≥ 50 copies/mL were 4.4% (10/225) for DTG + 3TC and 6.1% (14/229) for BIC/FTC/TAF; virological efficacy did not differ significantly between the two groups. Consistent results were obtained in an intent-to-treat (ITT) analysis. The incidences of LLV were 3.6% (7/193) and 4.9% (10/206), respectively. During the study, none of the participants stopped taking drugs because of a lack of efficacy or adverse reactions. Conclusions: Both regimens are well tolerated and effective for switching HIV-1 infection therapy. However, the detection of genotypic drug resistance should be considered when baseline virological non-suppression is observed. [ABSTRACT FROM AUTHOR]

Background: Prospective studies examining long‐term therapeutic outcomes of the Bictegravir/Emtricitabine/Tenofovir Alafenamide (BIC/FTC/TAF) regimen in human immunodeficiency virus (HIV) infection remain limited. This study assessed the actual efficacy and safety of BIC/FTC/TAF in HIV‐infected individuals in southwest China. Methods: This was a single‐center, prospective study enrolling ART‐naïve (n = 32) and ART‐experienced (n = 177) HIV‐infected patients administered BIC/FTC/TAF treatment between March 2022 and August 2022. The data were collected until February 28, 2023. Virological reactions and adverse events to the treatment were recorded, and patient subjective feelings in the form of Electronic Patient Reporting Outcome (ePRO) were collected. The primary endpoint was the rate of patients with HIV viral load <50 copies/mL at Week 24. Results: At Week 24, 87.5% and 95.5% of ART‐naïve and ART‐experienced HIV patients had a viral load <50 copies/mL, respectively. CD4 cell counts in ART‐naïve and ART‐experienced patients increased significantly by 163.5 cells/μL (p =.002) and 55.0 cells/μL (p =.022), respectively. By Week 24, no patients had discontinued the BIC/FTC/TAF treatment due to adverse events. Based on ePRO data, ART‐naïve and ART‐experienced patients at Week 24 had stable disease symptom burden, quality of life, and depression level after treatment with BIC/FTC/TAF. Conclusion: BIC/FTC/TAF reduces the viral load in ART‐naïve patients with high viral load as well as ART‐experienced patients with residual viremia. The patient's subjective experience was maintained stable after treatment with BIC/FTC/TAF. This study also revealed a very low incidence for BIC/FTC/TAF drug‐related side effects. [ABSTRACT FROM AUTHOR]

The average grade of iron ore is low in China, and it is significant for the effective utilization of iron ore to obtain grades. In the paper, the high-precision model was constructed based on the spectrum of hematite and the multiple hidden layers extreme learning machine with random values and dense connection, which took the output of all previous layers as the input of each hidden layer. It has achieved high precision during the detection of the total iron content for hematite, which meets the requirements for the construction and development of new green and intelligent mines. [ABSTRACT FROM AUTHOR]

Intensive anthropogenic activities have led to drastic changes in land use/land cover (LULC) and impacted the carbon storage in high-groundwater coal basins. In this paper, we conduct a case study on the Yanzhou Coalfield in Shandong Province of China. We further classify waterbodies by using the Google Earth Engine (GEE) to better investigate the process of LULC transformation and the forces driving it in four periods from 1985 to 2020 (i.e., 1985–1995, 1995–2005, 2005–2015, and 2015–2020). We modeled the spatiotemporal dynamics of carbon storage by using InVEST based on the transformation in LULC and its drivers, including mining (M), reclamation (R), urbanization and village relocation (U), and ecological restoration (E). The results indicate that carbon storage had depleted by 19.69 % (321099.06 Mg) owing to intensive transformations in LULC. The area of cropland shrank with the expansion of built-up land and waterbodies, and 56.31 % of the study area underwent transitions in land use in the study period. U was the primary driver of carbon loss while E was the leading driver of carbon gain. While the direct impact of M on carbon loss accounted for only 5.23 % of the total, it affected urbanization and led to village relocation. R led to the recovery of cropland and the reclamation of water for aquaculture, which in turn improved the efficiency of land use. However, it contributed only 2.09 % to the total increase in carbon storage. Numerous complicated and intertwined processes (211) drove the changes in carbon storage in the study area. The work here provides valuable information for decision-makers as well as people involved in reclamation and ecological restoration to better understand the link between carbon storage and the forces influencing it. The results can be used to integrate the goals of carbon sequestration into measures for land management. [Display omitted] • The carbon storage impacted by LULC driving processes in high groundwater coal basins was investigated. • 56.31 % of the study area has undergone land use transition during 1985–2020. • The carbon storage decreased by19.69 % during the study years. • Urbanization and village relocation was the primary driver of carbon loss, ecological restoration was the leading driver of carbon gain. [ABSTRACT FROM AUTHOR]

Underground coal mining leads to land subsidence, and the situation is particularly serious in the Coal-Grain Complex in eastern China, causing the crop production to be reduced or to be taken out. Backfilling with Yellow River sediment is one of the effective methods to solve the land subsidence in this area, but a key issue is how to select the optimal soil reconstruction profile so that the crop yield after backfilling and reclamation is unaffected. The main purpose of this study is to verify the feasibility of selecting the optimal soil reconstruction profile by rapid monitoring of crop growth and judging soil quality with the aid of unmanned aerial vehicle systems (UAVs). A control treatment and 13 experimental treatments were established for the study area. The control treatment consisted of using 30 cm topsoil and 90 cm subsoil and the topsoil is a proxy for native (undisturbed) soil from the study sites. All other treatments consisted of using varying combinations of subsoil and sediment overlain by 30 cm of topsoil. The vegetation indices from the UAV multispectral images, and the plant height and vegetation coverage from the UAV RGB images were used for estimation of the winter wheat biomass in a random forest regression. The results showed that the random forest regression model yielded accurate estimation of the aboveground biomass. Furthermore, knowledge of plant height and vegetation coverage improved the accuracy of prediction such that crop growth was well characterized. The optimal soil profile consisted of 0.3 m topsoil + 0.2 m subsoil + 0.2 m sediment + 0.2 m subsoil + 0.3 m sediment. A fast and effective airborne monitoring method for soil quality was established, thus providing greatly improved monitoring efficiency. [ABSTRACT FROM AUTHOR]

[Display omitted] • Soil organic carbon and labile organic carbon fractions decreased in the subsidence waterlogging areas. • The largest carbon depletion was observed in the 0–10 cm soil layer. • The liability of particulate organic carbon was highest among the three types of labile organic carbon fractions. • Labile organic carbon fractions were closely correlated with soil properties. • The shallow waterlogging area has the best carbon accumulation potential. The restoration of subsidence waterlogging areas has the potential to facilitate carbon accumulation in coal mining areas with high ground water tables. However, the soil organic carbon (SOC) and labile organic carbon (LOC) have not been sufficiently investigated in different types of subsidence waterlogging areas. In this study, SOC and LOC fractions, including light fraction organic carbon (LFOC), particulate organic carbon (POC), and dissolved organic carbon (DOC) within 0–50 cm soil profiles, were determined in a reference cropland (RC) and three types of subsidence waterlogging area in Xinglongzhuang Coal Mine, Shandong Province, China, including an aquaculture waterlogging area (AWA), deep waterlogging area (DWA) and shallow waterlogging area (SWA) with water depths of 1.8, 3.2, and 0.65 m, respectively. Compared with RC, SOC and LOC decreased by 4.13%, 25.03%, and 77.91% in SWA, DWA, and AWA, respectively. The largest depletion was in the 0–10 cm layer, indicating that there was a time lag for the recovery of the total functional pools of SOC after subsidence. The lability of POC was highest among the three types of LOC fractions, indicating that mining subsidence triggered soil redistribution and impacted on carbon accumulation. With comparatively little soil profile interference in DWA and SWA, the lability of LFOC and POC decreased with soil depth, while the DOC increased. There was a large discrepancy in AWA, with the lability of LOC fractions fluctuating because of soil disturbance by intensive engineering. The LOC fractions were closely associated and correlated with soil properties, especially total nitrogen (TN) and total phosphorus (TP). Restoration and management of the subsidence waterlogging areas have a vital impact on the SOC pool. It was concluded that shallow water and a natural geomorphology-based topography, with little soil disturbance, well-developed vegetation communities, and continuous monitoring of soil and water properties would facilitate the carbon accumulation process. [ABSTRACT FROM AUTHOR]

Coal resources play a strategic role in long-term development in China. However, underground mining activities in high groundwater table areas result in dramatic land use transition, putting both the ecosystem and the environment under great pressure. This paper examines the dynamic patterns of land use in high groundwater coal basins (HGCBs) using high-resolution Landsat TM (Thematic Mapper) data from 1985, 1995, 2005, 2010, and 2015, and socio-economic data from research institutes and government departments, and assesses the changes of ecosystem service value (ESV) by drawing a connection between the observed land use dynamics and the evaluation of ESV, based on the latest research of Xie et al. (2015) and some revisions adapted to the situation in the mining areas. The outcomes indicated that from 1985 to 2005, the ESV of the study area had a sustained growth, from 308.66 million RMB¥ in 1985–481.50 million RMB¥ in 2005. However, this growth has since stopped and turned into a decrease, with ESV dropping to 334.27 million RMB¥ in 2015. The reasons for the changes in ESV were analyzed: the large transition of construction land and farmland to waterbody caused by mining subsidence and restoration activities play a positive role, while the urbanization process in mining areas leading to the expansion of cities, and drought for the past 5 years leading to the shrinkage of waterbody, bring negative efforts to ESV. Based on the analysis above, some of the major implications were discussed. It is argued that the mining-induced land use transition will continue in the near future in HGCBs. Therefore, in order to fully consider the future landscape and thus optimize land use and extend urban development space it is necessary: to make pre-subsidence plans to maximize the farmland and ensure food security; to restore the secondary waterbody; to protect regional ecosystem service function and maintain its stability; and to make urban planning on the basis of subsidence prediction at every stage. Only in this way can HGCBs realize the sustainable use of ecological resources, as well as the integration of economic, social and ecologic benefits. [ABSTRACT FROM AUTHOR]

Eastern China has a long history of coal mining and a large number of coal mine sites have been abandoned in this region leaving a legacy of mining-related land subsidence, coal waste piles and brownfield sites. Furthermore, as a result of the historical planning approach in the region, many cities were built around coal mines. Therefore, the ecological restoration of abandoned mine land has become vital to the sustainable development in these cities. This paper uses the Datong coal mine site in Huainan as a case study to develop a detailed ecological restoration plan and functional division for an abandoned underground coal mine land by considering the local conditions and mining history, site assessment and integrated monitoring tools. [ABSTRACT FROM AUTHOR]

To address the global phenomenon of the salinisation of large land areas, a quantitative inversion model of the salinity of saline soils and soil visible–near-infrared (NIR) spectral data was developed by considering saline soils in Zhenlai County, Jilin Province, China as the research object. The original spectral data were first subjected to Savitzky–Golay (SG) smoothing, multiplicative scattering correction (MSC) pre-processing, and a combined transformation technique. The pre-processed spectral data were then analysed to construct the difference index (DI), ratio index (RI), and normalised difference index (NDI), and the Spearman rank correlation coefficient (r) between these three spectral indices and the salt content in the samples was calculated, while a combined spectral index (r > 0.8) was eventually selected as a sensitive spectral index. Finally, a quantitative inversion model for the salinity of saline soils was developed, and the model's accuracy was evaluated based on partial least squares regression (PLSR), the random forest (RF) algorithm, and the radial basis function (RBF) neural network algorithm. The results indicated that the inversion of soil salt content using the selected combination of spectral indices based on the RBF neural network algorithm was the most effective, with the prediction model yielding an R2 value of 0.950, a root mean square error (RMSE) of 1.014, and a relative percentage deviation (RPD) of 4.479, which suggested a good prediction effect. [ABSTRACT FROM AUTHOR]

• Pretreatment combined algorithms combining multiple mathematical transformations and dimensionality reduction algorithms to comprehensively process raw spectral data. • The advantage of this method is high accuracy". • A method for selecting the optimal Pretreatment combined algorithm is proposed and can accurately predict the accuracy of skarn-type iron ore. Iron ore grade determination is a key step in mining production, and its efficiency has a significant impact on mining efficiency and profitability. At present, the most commonly used method for ore grade determination is chemical analysis, which not only is expensive but also has a long assay cycle and lag effect relative to the ore allocation process and cannot effectively reduce the loss depletion rate of ore mining. Therefore, in situ iron ore grade data determination technology based on visible and near-infrared hyperspectral data analysis is an effective way to solve the above problems, but the poor quality of raw hyperspectral data and low accuracy of the ore grade inversion model are still one of the bottlenecks in the application of this technology. In this paper, 225 ore samples were collected from Hongling skarn-type iron ore in Chifeng, Inner Mongolia Autonomous Region, China. The visible and near-infrared hyperspectral data of the sample set and the grade data obtained from chemical analysis were used as data sources. The raw spectral data were first smoothed, and then the smoothed spectral data were processed using two algorithms, continuum removal (CR) and standard normal variate transform (SNV). Then, two dimensionality reduction algorithms, principal component analysis (PCA) and genetic algorithm (GA), were used to reduce the dimensionality of the spectral data before and after preprocessing, and the data sources were obtained after the four different preprocessing combination algorithms were processed. Finally, several quantitative inversion models were established based on the random forest algorithm and the backpropagation neural network (BPNN) algorithm. The stability, accuracy and credibility of the models were evaluated by four metrics: the coefficient of determination (R2), root mean square error (RMSE), residual prediction deviation(RPD) and mean relative error (MRE). The results showed that the quantitative inversion model (SNV-PCA-BPNN) established based on the BP neural network algorithm using the data processed by SNV and PCA for dimensionality reduction was the best, with an R2 of 0.99, an RMSE of 0.0048, an MRE of 1.10% and a RPD of 37.70, providing an effective method for the high-precision inversion of iron ore grades. [ABSTRACT FROM AUTHOR]

• The spectral data are pre-processed using three dimensionality reduction algorithms. • Optimize the parameters of the dimensionality reduction algorithm. • Establishment of a high-precision grade inversion model for Derni copper deposit. At present, chemical analysis is the main method for copper ore grade verification. Because of its long test cycle and lag effect relative to mining and ore blending processes, this approach cannot effectively reduce losses in mineral resource mining. An effective way to solve this problem is to conduct research on in situ grade determination methods for ore bodies based on visible-near-infrared hyperspectral grade modelling techniques. However, the accuracy of the modelling is seriously reduced by the large redundancy of hyperspectral data and the self-limiting nature of some machine learning methods. Therefore, the accurate selection of dimensionality reduction algorithms and machine learning algorithms determines the accuracy of the inverse model, and the setting of parameters such as dimensionality reduction, number of nearest neighbour points and number of hidden layers in neural networks is crucial. In this paper, 190 ore samples were collected from the open pit of the Derni copper deposit in Dawu town, Guoluo Tibetan Autonomous Prefecture, Qinghai Province, China. First, the visible-near-infrared spectral data for the sample set were obtained with an SVC HR-1024 spectrometer. The copper grade of the sample set was verified by chemical analysis. Three algorithms—the Laplacian eigenmap (LE), local tangent space alignment (LTSA) and local linear embedding (LLE)—were used to reduce the dimensionality of the original hyperspectral data. The original data and the three hyperspectral datasets after dimensionality reduction were used as data sources. Several Derni copper grade inversion models based on two machine learning algorithms, the backpropagation neural network and radial basis function (RBF) neural network, were developed. Finally, the coefficient of determination (R2), mean absolute error (MAE) and root mean square error (RMSE) were used to evaluate the accuracy of each model. The results show that the accuracy of the model built with spectral data processed by the dimension reduction algorithm is higher than that of the model constructed with the original spectral data. Among the above combined models, the LLE-RBF model has the highest inversion accuracy. The MAE of the model is 0.117%, the RMSE is 0.136, and R2 is 0.934. [ABSTRACT FROM AUTHOR]

In China, non-nucleoside reverse transcriptase inhibitors (NNRTIs) are integral to the antiretroviral therapy (ART) regimen for persons living with HIV (PWH), comprising over 80% of such treatments. To broaden treatment options and improve therapeutic effectiveness, Ainuovirine (ANV), a new NNRTI, was authorized for ART in 2021. Nevertheless, the clinical efficacy of ANV and its impact on blood biochemical markers remain somewhat underexplored. This study seeks to evaluate ANV's clinical performance in ART and its influence on relevant treatment parameters. A retrospective analysis was performed on 208 patients treated with an ANV-based regimen from July 2021 to July 2023, monitoring indicator changes from baseline to week 24. The primary endpoint was the proportion of participants achieving HIV-1 RNA levels of less than 50 copies/mL by week 24. Secondary endpoints involved assessing variations in CD4 + T cell counts and blood biochemical markers from baseline. These outcomes were also compared with data from 241 patients treated with an Efavirenz (EFV)-based regimen in the same time frame. The findings suggest that the ANV-based regimen is as effective as the EFV-based regimen in viral suppression ( p > .05) and offers superior improvements in lipid profiles, liver function, and immune system indicators, alongside fewer adverse reactions. These results affirm ANV's efficacy and safety as an antiretroviral therapy option, offering Acquired Immune Deficiency Syndrome patients a wider array of treatment possibilities and the potential for better treatment outcomes.

Objectives: To estimate anaemia prevalence and the associated factors among hospitalised people living with HIV (PLHIV) receiving antiretroviral therapy (ART)., Design: A cross-sectional study., Setting: PLHIV receiving ART and hospitalised in a specialised hospital for infectious disease in Guizhou Province, Southwest China, between 1 January 2018 and 31 March 2021., Participants: A total of 6959 hospitalised PLHIV aged ≥18 years and receiving ART were included in this study., Primary and Secondary Outcome Measures: Anaemia was diagnosed as a haemoglobin concentration <120 g/L for non-pregnant females and <130 g/L for males. Mild, moderate and severe anaemia were diagnosed as below the gender-specific lower limit of normal but ≥110 g/L, 80-110 g/L and <80 g/L, respectively., Results: The prevalence of anaemia was 27.5%, and that of mild, moderate and severe anaemia was 9.2%, 12.2% and 6.1%, respectively. Results from multivariate logistic regression showed that females had increased odds of anaemia (adjusted OR (aOR)=1.60, 95% CI: 1.42 to 1.81) compared with males. Widowed or divorced inpatients (anaemia: aOR=1.26, 95% CI: 1.08 to 1.47; severe anaemia: aOR=1.52, 95% CI: 1.16 to 1.97) and thrombocytopenia inpatients (anaemia: aOR=4.25, 95% CI: 3.54 to 5.10; severe anaemia: aOR=4.16, 95% CI: 3.24 to 5.35) had increased odds of anaemia and severe anaemia compared with their counterparts. Hepatitis C was associated with increased odds of severe anaemia (aOR=1.80, 95% CI: 1.11 to 2.92)., Conclusions: Anaemia was prevalent among hospitalised PLHIV. Female sex, those widowed or divorced, and thrombocytopenia were associated with increased odds of anaemia, and those widowed or divorced, thrombocytopenia and hepatitis C were associated with increased odds of severe anaemia. Determination of anaemia predictors, early detection and timely management of anaemia are crucial to prevent anaemia progression., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

The evolution of land-use spatial conflict is a comprehensive reflection of regional development and a common phenomenon in urbanization. The research on land-use spatial conflicts can provide theoretical basis and practical support for spatial control. The present study employs Tianjin as the research object, and ecological risk assessment model was improved based on landscape pattern analysis by selecting appropriate indicators that may bring conflict risk problems. The spatial conflict measurement model of land-use based on the coordination of human-land-landscape elements was preliminarily constructed. The spatial and temporal evolution of land-use spatial conflict degree, and spatial autocorrelation from 2000 to 2020 was preliminarily analyzed. Results showed that (1) the conflict measurement level of the model was verified by Google Earth remote sensing image platform and field survey, and the results were relatively consistent with the actual situation, which proves that this method was feasible. (2) The areas with low intensity of land-use conflict were mainly distributed in remote mountainous areas with less human activities, while the areas with high comprehensive conflict index were mainly distributed in the central urban area with more active human activities and urbanization, the urban fringe area, the water-land ecotone, and some landscape transition areas. (3) There was a close relationship between land use spatial conflict and land-use change. Areas with severe and frequent land-use changes were often areas with noticeable land-use conflict changes. In the period of high land-use change intensity and frequent land-use mode conversion, it was also a period of a large area where regional land-use conflict was enhanced. (4) The overall level of conflict showed an average trend year by year, and the high conflict fluctuates greatly with first rising and then falling, but the change range was small. Moderate conflict mainly showed a decreasing trend, with an extensive change range. The early stage of the mild conflict was relatively stable, and the later stage changed significantly., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)