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To help determine the unmet need for improved diagnostic tools to evaluate patients with nonspecific signs and/or symptoms (NSSS) and suspicion of cancer, we examined patient characteristics, diagnostic journey, and cancer incidence of patients with NSSS within The US Oncology Network (The Network), a secondary care community oncology setting. This retrospective, observational cohort study included patients aged ≥40 years with ≥1 NSSS in their problem list at their first visit within The Network (the index date) between 1 January 2016 and 31 December 2020. Patients were followed longitudinally with electronic health record data for initial cancer diagnosis, new noncancer diagnosis, death, end of study observation period, or 12 months, whichever occurred first. Of 103,984 patients eligible for inclusion, 96,722 presented with only 1 NSSS at index date; 6537/103,984 (6.3%) were diagnosed with 1 primary cancer within 12 months after the index date; 3825/6537 (58.5%) with hematologic malignancy, and 2712/6537 (41.5%) with solid tumor. Among patients diagnosed with cancer (n = 6774), the median time to cancer diagnosis after their first visit within The Network was 5.13 weeks. This study provides a real-world perspective on cancer incidence in patients with NSSS referred to a secondary care setting and highlights the unmet need for improved diagnostic tools to improve cancer outcomes.

Abstract Choroid plexus tumors (CPT) are rare and highly vascularized neoplasms that have three histologically confirmed diagnoses, including choroid plexus papilloma, atypical choroid plexus papilloma, and choroid plexus carcinoma (CPC). This study aimed to determine the epidemiology and survival of patients with CPTs and develop a nomogram to quantify the prognosis of the patients with CPT. Data of 808 patients who were diagnosed as CPT between 2000 and 2020 was obtained from the surveillance, epidemiology, and end results database. Descriptive analysis was used to assess the distribution and tumor-related characteristics of the patients with CPT. Independent prognostic factors for patients with CPT were identified by univariate and multivariate Cox regression analysis. The nomogram was established and evaluated by receiver operating characteristic curve, and decision curve analysis (DCA), calibration curves. The independent prognostic factors for patients with CPT are age, tumor size, surgery, chemotherapy, tumor number, pathologies, and race. For the prognostic nomogram, the area under the curve (AUC) of 60-, 120-, and 180-months were 0.855, 0.869 and 0.857 in the training set and 0.836, 0.864 and 0.922 in the test set. The DCA and calibration curve indicated the good performance of the nomogram. Patients with CPTs can be diagnosed at any age. Among the three histopathological tumors, patients with CPC had the worst prognosis. The nomogram was established to predict the prognosis of patients with CPT, which had satisfactory accuracy, and clinical utility may benefit for clinical decision-making.

Abstract Black carbon (BC) is a highly persistent yet poorly understood component of forest soil carbon reservoirs, while its inventory, distribution, and determining factors in forest soils on a large geographic scale remain unclear. Here, we characterized soil BC across 68 Chinese forest sites using benzene polycarboxylic acid method and developed machine learning (ML) models to predict and interpret potential impacts of soil organic matter (SOM) properties, soil physiochemical properties, meteorological conditions, wildfire history, and microbial diversity on BC. Results revealed that SOM properties were the most critical in predicting BC, complemented by the negative impact of mean annual temperature and alkaline mineral composition. The superior prediction accuracy for BC with higher condensed aromaticity (more benzene hexa‐ and penta‐carboxylic acid monomers) likely results from its simpler sources and greater resistance to transformation. This study introduces an effective ML model for predicting and interpreting soil BC inventory to better understand BC cycling.

The accumulation of rare earth elements (REEs) in the global environment poses a threat to plant health and ecosystem stability. Stomata located on leaves serve as the primary site for plant responses to REE-related threats. This study focused on lanthanum [La(III)], a prevalent REE in the atmospheric environment. Using interdisciplinary techniques, it was found that La(III) (≤80 µM) interfered with the fundamental rhythms of stomatal opening, related gene expression, and evapotranspiration in plants. Specifically, when exposed to low concentrations of La(III) (15 and 30 µM), the expression levels of six genes were increased, stomatal opening was enhanced, and the evapotranspiration rate was accelerated. The interference on stomatal rhythms was enhanced with higher concentrations of La(III) (60 and 80 µM), increasing the expression levels of six genes, stomatal opening, and evapotranspiration rate. To counter the interference of low concentrations of La(III) (15 and 30 μM), plants accelerated nutrient replenishment through La(III)-induced endocytosis, which the redundant nutrients enhanced photosynthesis. However, replenished nutrients failed to counter the disruption of plant biological rhythms at higher concentrations of La(III) (60 and 80 μM), thus inhibiting photosynthesis due to nutrient deficit. The interference of La(III) on these biological rhythms negatively affected plant health and ecosystem stability.

Abstract Reservoirs exert a profound influence on the cycling of dissolved organic matter (DOM) in inland waters by altering flow regimes. Biological incubations can help to disentangle the role that microbial processing plays in the DOM cycling within reservoirs. However, the complex DOM composition poses a great challenge to the analysis of such data. Here we tested if the interpretable machine learning (ML) methodologies can contribute to capturing the relationships between molecular reactivity and composition. We developed time‐specific ML models based on 7‐day and 30‐day incubations to simulate the biogeochemical processes in the Three Gorges Reservoir over shorter and longer water retention periods, respectively. Results showed that the extended water retention time likely allows the successive microbial degradation of molecules, with stochasticity exerting a non‐negligible effect on the molecular composition at the initial stage of the incubation. This study highlights the potential of ML in enhancing our interpretation of DOM dynamics over time.

Although strengths-based approaches have reaped substantial interest from researchers and practitioners alike, little attention was paid to strengths mindset. This study investigated the relationship between employee strengths mindset and positive affect and job performance (i.e., task performance and innovative behavior), and considered the mediating role of positive affect in the strengths mindset-job performance relationship. Data with a sample of 407 employees from different industries in China were collected using a time-lagged research design. Structural equation modeling analysis was employed to test our research hypotheses. Analytical results illustrated that strengths mindset positively relates to positive affect and job performance. More importantly, positive affect was found to significantly mediate the relationship of strengths mindset with task performance and innovative behavior. This study contributes to advancing strengths mindset theory and research, and identifies a new pathway for improving employee job performance., Author(s): He Ding [sup.1] , Jun Liu [sup.2] Author Affiliations: (1) grid.261049.8, 0000 0004 0645 4572, School of Economics and Management, North China Electric Power University, , No. 2, Bei [...]

Although strengths-based approaches in the workplace are able to bring out various positive outcomes, relatively little research has considered the dark sides of strengths-based approaches in the workplace. This study sought to examine whether perceived strengths-based human resource (HR) system as a specific form of strengths-based approaches is able to stimulate employees to execute unethical pro-organizational behavior (UPB) and considered the mediating role of organizational identification in the relationship. Data with a sample of 210 employees from various organizations in China were collected at three points in time. Structural equation modelling analysis was deployed to test our hypotheses. The authors found that perceived strengths-based HR system spurs UPB, and organizational identification acts as a mediator in the relationship between perceived strengths-based HR system and UPB. This study extends previous literature on strengths-based approaches in the workplace by considering its dark side and advances HR system and UPB theories and research., Author(s): He Ding [sup.1] , Jun Liu [sup.2] Author Affiliations: (1) grid.261049.8, 0000 0004 0645 4572, School of Economics and Management, North China Electric Power University, , No. 2, Bei [...]

Dissolved organic matter (DOM) is closely linked to human activities in drainage basins and plays a crucial role in maintaining ecosystem functioning and reflecting environmental quality. However, the impacts of climate and anthropogenic-induced changes on DOM in riverine systems under increasingly warming conditions still need to be better understood, particularly at large regional scales. To address this knowledge gap, we analyzed a dataset containing 386 published measurements for nine major Chinese river systems, examining dissolved organic carbon (DOC) concentrations and optical properties of chromophoric DOM (CDOM) under diverse environmental conditions, including mean air temperature, precipitation, surface solar radiation, population density, and land use. Our findings indicate that riverine DOC concentrations are significantly higher in northern China (at ∼46.8%) than in the south. This disparity is primarily due to the high input of soil erosion-induced DOM from drying-affected lands (57.0%), farmland (49.1%), and forests in the north. The high temperate and strong hydrological conditions would lead to DOM degradation easily in the riverine system in the south of China. Our study highlights that various climatic and anthropogenic factors, such as agriculture, vegetation coverage, soil erosion, surface solar radiation, and precipitation, individually or in combination, can affect DOM dynamics in river systems. Therefore, considering alterations in DOM dynamics resulting from climate and environmental changes is crucial for carbon-neutral policies and sustainable river ecosystem assessments.

To solve the problem of large sowing amount and poor sowing uniformity for millet, according to the physical characteristics of the millet seed and its sowing agronomic requirements, an electromagnetic vibration type fine and small-amount seeder was designed, and the main technical parameters of the seeder were determined, in order to realize the functions of furrow opening, electronically controlled seed metering, soil covering and pressing. Based on the principle of electromagnetic vibration, an electromagnetic vibration type seed metering device was designed to achieve uniform seeding of the millet seed with a small sowing amount; a seeding amount electronic control device was designed using an STM32 microcontroller, which realized the switching to sowing agronomic mode and the adjustment of the seeding amount with sowing operation speed; a vibration experimental bench was set up to simulate the vibration state of field operation, and studies on the seeding performance and vibration damping of the seed metering device by the isolation spring were carried out, as well as field sowing tests for verification. When the working voltage of the seed metering device is 80–160 V, the coefficients of variation for seeding uniformity per row and for total seeding uniformity are not greater than 3.57% and 2.39%, respectively, and the seed damage rate is less than 0.5%. The installation of isolation springs can increase the maximum vibration acceleration of the seed metering device by 10.61–28.20%, significantly reducing the impact of external vibrations on the seed metering device. Within the range of suitable sowing operation speeds, the electronic control device can meet the seeding amounts along with sowing operation speed in the 6, 7.5 and 9 kg/hm2 sowing agronomic modes, and the coefficient of variation for seeding uniformity per row, for total seeding uniformity and for sowing uniformity are not greater than 4.63%, 2.48% and 23.38%, respectively. This study provides a reference for the development of sowing machinery for millet crop.

Macrophage polarization is an essential process involved in immune regulation. In response to different microenvironmental stimulation, macrophages polarize into cells with different phenotypes and functions, most typically M1 (pro-inflammatory) and M2 (anti-inflammatory) macrophages. Iron-based nanoparticles have been widely explored and reported to regulate macrophage polarization for various biomedical applications. However, the influence factors and modulation mechanisms behind are complicated and not clear. In this review, we systemically summarized different iron-based nanoparticles that regulate macrophage polarization and function and discussed the influence factors and mechanisms underlying the modulation process. This review aims to deepen the understanding of the modulation of macrophage polarization by iron-based nanoparticles and expects to provide evidence and guidance for subsequent design and application of iron-based nanoparticles with specific macrophage modulation functions.

The Great Wall, as a globally important large-scale linear cultural heritage asset, is an example of the integration of architecture and landscape, demonstrating the interaction and feedback between heritage and the environment. In the context of advocating the holistic protection of cultural heritage and surroundings, this study utilizes landscape character assessment (LCA) to identify the landscape character of the Great Wall heritage area. Taking the heritage area of the Great Wall in Beijing, China, as an example, principal component analysis (PCA), two-step clustering, and the eCognition software were used to identify and describe the landscape character types, and the interaction mechanism between heritage and the environment was further explored through the reclassification process. A total of 20 landscape character types and 201 landscape character areas were identified in the study area, and a deep coupling relationship between heritage and the environment and cultural landscape spatial patterns were found in the core heritage area. The heritage and environmental character of linear heritage areas should be integrated so as to protect, manage, and plan cultural heritage areas at the landscape level. This study identifies and describes the character of the coupling of heritage and the environment in the Great Wall area for the first time, expands the types and methods of landscape character assessment, and carries out the exploration to combine natural and cultural elements of large-scale linear cultural heritage areas.