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Background: In clinical practice, digital subtraction angiography (DSA) is widely used to diagnose cerebrovascular disease based on detailed information about blood vessel structure. Challenges remain on accurately find blood vessel abnormalities in a time-limited manner. In this perspective, computer-aided analysis of DSA can assist clinicians in interpreting the images. Purpose: Provide a method for extracting cerebral blood vessels from DSA images. Materials and methods: In this work, we presented a new method for segmenting digital subtraction angiography (DSA) by incorporating both global and local information about an image to adaptively classify each pixel to the foreground and background. The method utilizes the global mean and standard deviation of an angiography and local mean and standard deviation within a sliding window to build two criteria. The two criteria contains both global and local characteristics about an image and individual pixels. The two criteria work together to reduce noise in segmentation and preserve valid details about the foreground. We tested the method on angiography and compared it with several widely used algorithms. Results: In total, there were 72 DSA images in our dataset. Compared to Otsu, Niblack, iNiblack, Sauvola, Wolf, and CNW, our method achieved the best overall performance. The accuracy, Dice coefficient (Dice), and intersection over union (IoU) are 0.9777, 0.8500, and 0.7440, respectively. Conclusion: The results demonstrated that our method can obtain good outcomes, especially in achieving a balance between extracting the correct foreground and reducing incorrect classifications, and had the best performance among the methods being compared with.

Abstract Background Canine distemper virus (CDV) is a pathogen with the capability of cross-species transmission. It has crossed the species barrier to infect many other species, and its host range is expanding. The reverse genetic platform, a useful tool for scientific research, allows the generation of recombinant viruses from genomic cDNA clones in vitro. Methods To improve the reverse genetic system of CDV, a plasmid containing three independent expression cassettes was constructed for co-expression of the N, P, and L genes and then transfected with a full-length cDNA clone of CDV into Vero cells. Results The results indicated that the established rescue system has the advantages of being more convenient, easy to control the transfection ratio, and high rescue efficiency compared with the conventional reverse genetics system. Conclusion This method not only reduces the number of transfection plasmids, but also improves the rescue efficiency of CDV, which could provide a reference for the recovery of other morbilliviruses.

IntroductionThe cardiothoracic ratio (CTR) based on postero-anterior chest X-rays (P-A CXR) images is one of the most commonly used cardiac measurement methods and an indicator for initially evaluating cardiac diseases. However, the hearts are not readily observable on P-A CXR images compared to the lung fields. Therefore, radiologists often manually determine the CTR’s right and left heart border points of the adjacent left and right lung fields to the heart based on P-A CXR images. Meanwhile, manual CTR measurement based on the P-A CXR image requires experienced radiologists and is time-consuming and laborious.MethodsBased on the above, this article proposes a novel, fully automatic CTR calculation method based on lung fields abstracted from the P-A CXR images using convolutional neural networks (CNNs), overcoming the limitations to heart segmentation and avoiding errors in heart segmentation. First, the lung field mask images are abstracted from the P-A CXR images based on the pre-trained CNNs. Second, a novel localization method of the heart’s right and left border points is proposed based on the two-dimensional projection morphology of the lung field mask images using graphics.ResultsThe results show that the mean distance errors at the x-axis direction of the CTR’s four key points in the test sets T1 (21 × 512 × 512 static P-A CXR images) and T2 (13 × 512 × 512 dynamic P-A CXR images) based on various pre-trained CNNs are 4.1161 and 3.2116 pixels, respectively. In addition, the mean CTR errors on the test sets T1 and T2 based on four proposed models are 0.0208 and 0.0180, respectively.DiscussionOur proposed model achieves the equivalent performance of CTR calculation as the previous CardioNet model, overcomes heart segmentation, and takes less time. Therefore, our proposed method is practical and feasible and may become an effective tool for initially evaluating cardiac diseases.

Background Anaemia is a severe and common complication in patients with aneurysmal subarachnoid haemorrhage (aSAH). Early intervention for at-risk patients before anaemia occurs is indicated as potentially beneficial, but no validated method synthesises patients’ complicated clinical features into an instrument. The purpose of the current study was to develop and externally validate a nomogram that predicted postacute phase anaemia after aSAH.Methods We developed a novel nomogram for aSAH patients to predict postacute phase anaemia (3 days after occurrence of aSAH, prior to discharge) on the basis of demographic information, imaging, type of treatment, aneurysm features, blood tests and clinical characteristics. We designed the model from a development cohort and tested the nomogram in external and prospective validation cohorts. We included 456 aSAH patients from The First Affiliated Hospital for the development, 220 from Sanmen People’s Hospital for external validation and a prospective validation cohort that included 13 patients from Hangzhou Red Cross Hospital. We assessed the performance of the nomogram via concordance statistics and evaluated the calibration of predicted anaemia outcome with observed anaemia occurrence.Results Variables included in the nomogram were age, treatment method (open surgery or endovascular therapy), baseline haemoglobin level, fasting blood glucose level, systemic inflammatory response syndrome score on admission, Glasgow Coma Scale score, aneurysm size, prothrombin time and heart rate. In the validation cohort, the model for prediction of postacute phase anaemia had a c-statistic of 0.910, with satisfactory calibration (judged by eye) for the predicted and reported anaemia outcome. Among forward-looking forecasts, our predictive model achieved an 84% success rate, which showed that it has some clinical practicability.Conclusions The developed and validated nomogram can be used to calculate individualised anaemia risk and has the potential to serve as a practical tool for clinicians in devising improved treatment strategies for aSAH.

Abstract Background The genus Sanicula L. is a unique perennial herb that holds important medicinal values. Although the previous studies on Sanicula provided us with a good research basis, its taxonomic system and interspecific relationships have not been satisfactorily resolved, especially for those endemic to China. Moreover, the evolutionary history of this genus also remains inadequately understood. The plastid genomes possessing highly conserved structure and limited evolutionary rate have proved to be an effective tool for studying plant phylogeny and evolution. Results In the current study, we newly sequenced and assembled fifteen Sanicula complete plastomes. Combined with two previously reported plastomes, we performed comprehensively plastid phylogenomics analyses to gain novel insights into the evolutionary history of this genus. The comparative results indicated that the seventeen plastomes exhibited a high degree of conservation and similarity in terms of their structure, size, GC content, gene order, IR borders, codon bias patterns and SSRs profiles. Such as all of them displayed a typical quadripartite structure, including a large single copy region (LSC: 85,074–86,197 bp), a small single copy region (SSC: 17,047–17,132 bp) separated by a pair of inverted repeat regions (IRs: 26,176–26,334 bp). And the seventeen plastomes had similar IR boundaries and the adjacent genes were identical. The rps19 gene was located at the junction of the LSC/IRa, the IRa/SSC junction region was located between the trnN gene and ndhF gene, the ycf1 gene appeared in the SSC/IRb junction and the IRb/LSC boundary was located between rpl12 gene and trnH gene. Twelve specific mutation hotspots (atpF, cemA, accD, rpl22, rbcL, matK, ycf1, trnH-psbA, ycf4-cemA, rbcL-accD, trnE-trnT and trnG-trnR) were identified that can serve as potential DNA barcodes for species identification within the genus Sanicula. Furthermore, the plastomes data and Internal Transcribed Spacer (ITS) sequences were performed to reconstruct the phylogeny of Sanicula. Although the tree topologies of them were incongruent, both provided strong evidence supporting the monophyly of Saniculoideae and Apioideae. In addition, the sister groups between Saniculoideae and Apioideae were strongly suggested. The Sanicula species involved in this study were clustered into a clade, and the Eryngium species were also clustered together. However, it was clearly observed that the sections of Sanicula involved in the current study were not respectively recovered as monophyletic group. Molecular dating analysis explored that the origin of this genus was occurred during the late Eocene period, approximately 37.84 Ma (95% HPD: 20.33–52.21 Ma) years ago and the diversification of the genus was occurred in early Miocene 18.38 Ma (95% HPD: 10.68–25.28 Ma). Conclusion The plastome-based tree and ITS-based tree generated incongruences, which may be attributed to the event of hybridization/introgression, incomplete lineage sorting (ILS) and chloroplast capture. Our study highlighted the power of plastome data to significantly improve the phylogenetic supports and resolutions, and to efficiently explore the evolutionary history of this genus. Molecular dating analysis explored that the diversification of the genus occurred in the early Miocene, which was largely influenced by the prevalence of the East Asian monsoon and the uplift of the Hengduan Mountains (HDM). In summary, our study provides novel insights into the plastome evolution, phylogenetic relationships, taxonomic framework and evolution of genus Sanicula.

IntroductionWith the acceleration of urbanization, human population and built surface in urban areas have increased rapidly, triggering numerous environmental problems. Identification of ecological security pattern (ESP) can be helpful to optimize the interaction and relationship between ecological conservation and socioeconomic development in a given region. In this study, taking Chengdu City as an example, a methodology was used to analyze the city’s ESP.MethodologyEcological sources were identified based on their ecological security values, which were derived from the spatio-temporal evaluation of ecosystem services and ecological health. The ecological resistance surface was revised with nighttime light index. Linkage Mapper combined with circuit theory was used to extracted ecological corridors and key ecological nodes.Results:The results showed that the mean values of ecological security in Chengdu City presented a downward and then upward trend from 2000 to 2018. In 2018, the ESP in Chengdu City was formed by 140 ecological sources with the total area of 8,819.78 km2, 302 ecological corridors with the area of 456.91 km2, as well as 61 pinch-points and 17 barrier points. The ecological sources in Chengdu City were mainly distributed in or nearby Longmen Mountain and Longquan Mountain, two flanks of the Chengdu Plain, and connected each other with hundreds of ecological corridors. Most of ecological sources and corridors were composited of forests in mountainous areas and linpan units (wooded lots) in rural plain areas. On the contrary, pinch-points and barrier points were mainly distributed in the districts nearby the metropolitan urban center.ConclusionFinally, this study proposed that constructing ESP must adopt a dynamic and holistic approach in considering the change of restoring ecosystems, shift of urban demands for ecosystem services and transformation of urban-rural land use/cover. Restoring and managing corridors sustainably are important for improving the ecological connectivity of all over ecological sources in a city, all of which together, if functioning well, could further support the realization of sustainable urbanization.

BackgroundCurrently, the incidence of cerebral palsy is high in newborns. However, the current methods for diagnosing and treating patients with cerebral palsy are complex and poorly targeted. Moreover, these studies lack the support of bibliometric analysis results.ObjectiveOur study focused on a bibliometric analysis of published papers on the diagnosis and treatment of patients with cerebral palsy. This study identified the primary authors, institutions, and countries involved in analyzing the status and trends of research on the diagnosis and treatment of patients with cerebral palsy. Additionally, the study also involved screening pathways related to cerebral palsy.MethodsThe PubMed database was searched for publications on the diagnosis and treatment of patients with cerebral palsy between 1990 and 2023. R v4.2.2 and VOSviewer v1.6.18 software tools were utilized to perform bibliometric analysis and visualization.ResultsThere were 1,965 publications on cerebral palsy diagnosis and 5,418 articles on the qualified treatment strategies, and the annual number of publications also increased. The United States dominated in this field of research. Gregory Y.H. Lip and Patrizio Lancellotti published the most number of papers. The Cleveland Clinic published the most number of papers in the field. According to the analysis of the co-occurrence of keywords, we found that the main research directions were age, sex, disease diagnosis, and treatment. Newly emerging research has focused mainly on heart failure, which is related to valvular heart disease.ConclusionThe findings presented in this study offer valuable insights into ongoing research and potential future directions pertaining to cerebral palsy. These insights can assist researchers in identifying suitable collaborators and enhancing their investigations aimed at identifying the underlying molecular mechanisms associated with cerebral palsy, encompassing its etiology, preventive measures, and therapeutic interventions.

The use of natural ventilation for cooling in summer in mild climate areas can positively improve the indoor thermal environment and thermal comfort. In this paper, Kunming, China was chosen as a case to study experimentally the natural ventilation effects on the residential thermal environment and thermal comfort in mild climate rural areas. The effects of natural ventilation on the indoor thermal environment and thermal comfort under the typical hottest sunny days in summer in Kunming were investigated with seven different combinations of ventilation methods with the opening/closing of doors/windows. The results show that natural ventilation can considerably improve the indoor thermal environment. Furthermore, the uniformity of indoor thermal environments at different heights was assessed. Additionally, the vertical temperature difference between the head and foot areas around the human body remained below 3 °C. Moreover, the adaptive predicted mean vote (APMV) model was used to evaluate the thermal comfort under natural ventilation, and values of APMV ranged from −0.84 to 0.84 under six scenarios, considering an acceptable temperature range based on occupant satisfaction rates of over 80%. This study's outcomes offer valuable insights for the design of self-built housing in the extensive rural areas within mild climate zones in China.

Purpose: The presence of lymphovascular invasion (LVI) influences the management and outcomes of patients with clinical stage IA lung adenocarcinoma. The objective was the development of a deep learning (DL) signature for the prediction of LVI and stratification of prognosis. Methods: A total of 2077 patients from three centers were retrospectively enrolled and divided into a training set (n = 1515), an internal validation set (n = 381), and an external set (n = 181). A -three-dimensional residual neural network was used to extract the DL signature and three models, namely, the clinical, DL, and combined models, were developed. Diagnostic efficiency was assessed by ROC curves and AUC values. Kaplan-Meier curves and Cox proportional hazards regression analyses were conducted to evaluate links between various factors and disease-free survival. Results: The DL model could effectively predict LVI, shown by AUC values of 0.72 (95 %CI: 0.68–0.76) and 0.63 (0.54–0.73) in the internal and external validation sets, respectively. The incorporation of DL signature and clinical-radiological factors increased the AUC to 0.74 (0.71–0.78) and 0.77 (0.70–0.84) in comparison with the DL and clinical models (AUC of 0.71 [0.68–0.75], 0.71 [0.61–0.81]) in the internal and external validation sets, respectively. Pathologic LVI, LVI predicted by both DL and combined models were associated with unfavorable prognosis (all p < 0.05). Conclusion: The effectiveness of the DL signature in the diagnosis of LVI and prognosis prediction in patients with clinical stage IA lung adenocarcinoma was demonstrated. These findings suggest the potential of the model in clinical decision-making.

More than half of the carbon pools in peatlands are stored in the soil layers below 30 cm, yet little is known about the carbon stabilizing factors at these depths. Although iron oxide minerals are considered to be important for stabilizing organic carbon (OC), their role in the preservation of OC in peatlands, especially in the deep layers, is poorly understood. Here, we collected 1 m soil profiles from six peatlands in Central and West China to quantitatively study the vertical distribution characteristics of iron-bound OC (Fe-bound OC), and the influencing physicochemical properties of the soil. The results showed that the content of reactive iron (FeR) was enriched in the top layer and decreased gradually with depth. While Fe-bound OC was positively correlated with FeR, its concentration did not decrease with depth in the peat profile. There were no obvious trends in the distributions of FeR and Fe-bound OC with water level fluctuations in the peat profile. In addition, the proportion of Fe-bound OC to soil organic carbon in the deep peat (31 to 100 cm) was equivalent to that in the surface peat (0 to 30 cm), indicating that iron oxide mineral provides comparable protection of OC in both layers. According to upper estimates of global peatland carbon storage (612 Pg), it could be predicted that 23.81 ± 11.75 Pg of OC is protected by association with FeR. These results indicated that iron oxide minerals are the effective ''rusty sink'' of OC sequestration in peatland, and a key factor for its long-term preservation. The results from this study make a valuable contribution to the carbon dynamics knowledgebase for peatlands, and provide a basis for improved predictive simulations.

Abstract Intense grazing may lead to grassland degradation on the Qinghai-Tibetan Plateau, but it is difficult to predict where this will occur and to quantify it. Based on a process-based ecosystem model, we define a productivity-based stocking rate threshold that induces extreme grassland degradation to assess whether and where the current grazing activity in the region is sustainable. We find that the current stocking rate is below the threshold in ~80% of grassland areas, but in 55% of these grasslands the stocking rate exceeds half the threshold. According to our model projections, positive effects of climate change including elevated CO2 can partly offset negative effects of grazing across nearly 70% of grasslands on the Plateau, but only in areas below the stocking rate threshold. Our analysis suggests that stocking rate that does not exceed 60% (within 50% to 70%) of the threshold may balance human demands with grassland protection in the face of climate change.

Summary: Climate change and human activities have intensified variations of water table depth (WTD) in wetlands around the world, which may strongly affect greenhouse gas emissions. Here, we analyzed how emissions of CO2, CH4, and N2O from the Zoige wetland on the Qinghai-Tibetan Plateau (QTP) vary with the WTD. Our data indicate that the wetland shows net positive global warming potential (11.72 tCO2-e ha−1 yr−1), and its emissions of greenhouse gases are driven primarily by WTD. Our analysis suggests that an optimal WTD exists, which at our study site was approximately 18 cm, for mitigating increases in global warming potential from the wetland. Our study provides insights into how climate change and human acitivies affect greenhouse gas emissions from alpine wetlands, and they suggest that water table management may be effective at mitigating future increases in emissions.

Summary: Pathologic visceral pleural invasion (VPI) in patients with early-stage lung cancer can result in the upstaging of T1 to T2, in addition to having implications for surgical resection and prognostic outcomes. This study was designed with the goal of establishing and validating a CT-based deep learning (DL) model capable of predicting VPI status and stratifying patients based on their prognostic outcomes. In total, 2077 patients from three centers with pathologically confirmed clinical stage IA lung adenocarcinoma were enrolled. DL signatures were extracted with a 3D residual neural network. DL model was able to effectively predict VPI status. VPI predicted by the DL models, as well as pathologic VPI, was associated with shorter disease-free survival. The established deep learning signature provides a tool capable of aiding the accurate prediction of VPI in patients with clinical stage IA lung adenocarcinoma, thus enabling prognostic stratification.

Abstract Background Peatlands contain about 500 Pg of carbon worldwide and play a dual role as both a carbon sink and an important methane (CH4) source, thereby potentially influencing climate change. However, systematic studies on peat properties, microorganisms, methanogenesis, and their interrelations in peatlands remain limited, especially in China. Therefore, the present study aims to investigate the physicochemical properties, archaeal community, and predominant methanogenesis pathways in three typical peatlands in China, namely Hani (H), Taishanmiao (T), and Ruokeba (R) peatlands, and quantitively determine their CH4 production potentials. Results These peatlands exhibited high water content (WC) and total carbon content (TC), as well as low pH values. In addition, R exhibited a lower dissolved organic carbon concentration (DOC), as well as higher total iron content (TFe) and pH values compared to those observed in T. There were also clear differences in the archaeal community between the three peatlands, especially in the deep peat layers. The average relative abundance of the total methanogens ranged from 10 to 12%, of which Methanosarcinales and Methanomicrobiales were the most abundant in peat samples (8%). In contrast, Methanobacteriales were mainly distributed in the upper peat layer (0–40 cm). Besides methanogens, Marine Benthic Group D/Deep-Sea Hydrothermal Vent Euryarchaeotic Group 1 (MBG–D/DHVEG–1), Nitrosotaleales, and several other orders of Bathyarchaeota also exhibited high relative abundances, especially in T. This finding might be due to the unique geological conditions, suggesting high archaeal diversity in peatlands. In addition, the highest and lowest CH4 production potentials were 2.38 and 0.22 μg g−1 d−1 in H and R, respectively. The distributions of the dominant methanogens were consistent with the respective methanogenesis pathways in the three peatlands. The pH, DOC, and WC were strongly correlated with CH4 production potentials. However, no relationship was found between CH4 production potential and methanogens, suggesting that CH4 production in peatlands may not be controlled by the relative abundance of methanogens. Conclusions The results of the present study provide further insights into CH4 production in peatlands in China, highlighting the importance of the archaeal community and peat physicochemical properties for studies on methanogenesis in distinct types of peatlands.

Due to their excellent mechanical strength, corrosion resistance, and ease of processing, carbon fiber and carbon-fiber-reinforced plastics are finding wide application in diverse fields, including aerospace, industry, and automobiles. This research explores the feasibility of integrating carbon fiber solutions into the rotors of 85-kilowatt electric vehicle interior permanent magnet synchronous motors. Two novel configurations are proposed: a carbon fiber wire-wound rotor and a carbon fiber injection-molded rotor. A finite element analysis compares the performance of these models against a basic designed rotor, considering factors like no-load back electromotive force, no-load voltage harmonics, cogging torque, load torque, torque ripple, efficiency, and manufacturing cost. Additionally, a comprehensive analysis of system efficiency and energy loss based on hypothetical electric vehicle parameters is presented. Finally, mechanical strength simulations assess the feasibility of the proposed carbon fiber composite rotor designs.

Through extensive data research and analysis, this paper comprehensively summarizes the status and key insights of global carbon dioxide capture and storage (CCS) development. It aims to gain a comprehensive understanding of the relevant policies, technologies, and security measures adopted by major countries in their CCS development processes. Furthermore, it explores the existing status and limitations of China’s offshore development efforts, while providing valuable recommendations for enhancing China’s offshore CCS initiatives, as well as serving as a reference for other nations worldwide. Offshore CCS plays a crucial role for China to achieve the development target of carbon peak and carbon neutrality, due to its energy structure and industrial distribution. While China possesses significant offshore CCS potential, achieving commercialization still requires substantial efforts. To facilitate the process and draw insights from successful experiences in other countries, this paper illustrates the characteristics and generalizes the experience of offshore CCS industry practices in America, Europe and Japan, respectively. Furthermore, it is recommended that a new round of investigation into offshore CCS potential be conducted, while promoting integrated collaboration between geological surveying and marine scientific research. Additionally, further research on industrial policies and green financial strategies should be undertaken.

Canine parainfluenza virus (CPIV) is a zoonotic virus that is widely distributed and is the main pathogen causing canine infectious respiratory disease (CIRD), also known as “kennel cough,” in dogs. The CPIV-V protein is the only nonstructural protein of the virus and plays an important role in multiple stages of the virus life cycle by inhibiting apoptosis, altering the host cell cycle and interfering with the interferon response. In addition, studies have shown that the V protein has potential applications in the field of immunotherapy in oncolytic virus therapy or self-amplifying RNA vaccines. In this review, the biosynthesis, structural characteristics and functions of the CPIV-V protein are reviewed with an emphasis on how it facilitates viral immune escape and its potential applications in the field of immunotherapy. Therefore, this review provides a scientific basis for research into the CPIV-V protein and its potential applications.

Peatlands store 20–30 % of the global soil carbon (C). Earthworms simultaneously increase net C stabilization and net C mineralization. But little is known about the impact of earthworm invasion on the C cycling in peat soils. Earthworm excreta, such as casts and mucus, have been shown to affect soil chemistry and microbes, the former representing gut process and the latter are secretions from earthworms as they dig burrows. Therefore, this study evaluates the separate effects of the presence of earthworms, casts, and mucus on the soil chemistry, soil microbial community, and the enzymes of peat soil. The results indicated that earthworms and their casts had significantly negative effects on peat soil dissolved organic C, microbial biomass C, pH and polyphenol oxidase, and had positive effects on phenolic matters, hydrolase activity, bacterial diversity, and metabolic functions. The effects of mucus on polyphenol oxidase, phenolic matters and bacterial evenness were similar to those of earthworms, but the effects on other soil properties were different. Earthworms and their excreta selectively promote or inhibit the survival of some soil bacteria, e.g., the relative abundance of Bacteroidetes was increased and Acidobacteria and Rokubacteria was reduced after earthworm entering. This research provides evidence that earthworms change soil properties primarily through gut processes (casts), indicates the negative effect of earthworms on peat soil C, and call for the monitoring of soil fauna in degraded peatland to protecting C stocks in peatlands.

Despite the natural abundance and promising properties of Si, there are few examples of crystalline Si-based catalysts. Here, the authors report an epitaxial growth method to construct Co single atoms on Si for light driven CO2 reduction to syngas.

Objective: To summarize and analyze the clinical data, computed tomography (CT) signs, and pathological features of bronchiolar adenoma, and to discuss the diagnostic value of bronchiolar adenoma. Methods: In total, 18 cases of pulmonary nodules diagnosed as bronchiolar adenoma via postoperative pathology from January 2020 to December 2020 were retrospectively collected, and the clinical data, chest CT signs, and postoperative pathological features of pulmonary nodules were analyzed. Results: Among the 18 cases, 16 had no clinical chest symptoms, and 2 had chest pain. The patients were 18~65 years old. The mean age was 51.8 years, and the median age (25％~75％ quantile) was 52 (49~59) years; 7 patients were male (39％), and 11 were females (61％). The average maximum slice diameter of bronchiolar adenoma was 11.1 mm, and the median diameter (25％~75％ quantile) was 8 (6~15) mm. There were 15 cases with lesion distance ≤10 mm from the pleura. CT showed that 8 cases were pure ground-glass nodules (pGGN), 7 cases were part-solid nodules (PSN), and 3 cases had simple cystic space. The mean CT value of bronchiolar adenomas presenting with pGGN was −690.7 HU. The median mean CT value (25％~75％ quantiles) was −717.5 (−722~ −681) HU. A spicule sign at the nodular margin was found in 6 of the 18 cases. Pleural traction around nodules was found in 7 cases, and bronchiectasis occurred in nodules in 5 cases. The postoperative gross pathological diameter of 18 nodules was 9.1 mm, and the median diameter (25％~75％ quantile) was 7 (6~9) mm. Pathological immunohistochemical antibody CK7 was positive in 18 cases; p40, p63, CK5/6, and TTF-1 were positive in 16 cases. Conclusions: Bronchiolar adenoma often occurs in middle-aged and older women. Preoperative CT diagnosis of subpleural nodules around 10 mm could indicate the disease, and immunohistochemical antibody CK7, p40, and other indicators are qualitative methods for diagnosing bronchiolar adenoma.

Objective: Cystic lung cancer is a rare type of lung cancer with special morphological manifestations on imaging that have not been completely recognized. This study aimed to improve the understanding and diagnosis of this lung cancer by analyzing its computed tomography (CT) features and clinicopathological findings. Methods: The clinical data, pathological types, and CT features of patients with cystic lung cancer who were diagnosed at our hospital between January 2015 and June 2021 were analyzed retrospectively. Results: We identified 44 cases (86.27%) of adenocarcinomas; these included 7 (13.73%) and 35 (68.63%) cases of microinvasive adenocarcinomas and invasive adenocarcinomas, respectively. Regarding the histological type, 11 (21.57%), 8 (15.69%), and 15 (29.41%) cases were of the adjoint, papillary, and acinar types, respectively. Two cases (3.92%) contained micropapillary components that accounted for more than 20% . Furthermore, one case (1.96%) was not classified, and in another case (1.96%), pathological examination after chemotherapy suggested an adenocarcinoma. Lymph node biopsy in one case (1.96%) suggested a metastatic lung adenocarcinoma. Squamous cell carcinoma was observed in five cases (9.80%); these included three (5.89%) and two (3.92%) cases of keratinizing and non-keratinizing squamous cell carcinomas, respectively. A large cell carcinoma and a high-grade mucoepidermoid carcinoma were observed in one case each (1.96%). A peripheral distribution was observed in 40 cases (80.30%). The mean diameter was 4.7± 2.7 cm. A cystic cavity with ground glass, cystic cavity with solid components, and cystic cavity with mixed components were observed in 20 (39.22%), 22 (43.14%), and 9 (17.65%) cases, respectively. According to the Mario classification, 24 (47.06%), 8 (15.69%), 9 (17.65%), and 10 (19.61%) cases were of types I, II, III, and IV, respectively. The cyst wall was uneven in 42 cases (82.35%); furthermore, a lobular lesion edge and the burr sign were observed in 28 (54.90%) and 14 (27.45%) cases, respectively. Moreover, 33 cases (64.71%) showed a separation within the lesions, while 36 cases (70.59%) had a smooth inner lesion wall. Regarding the relationship with the pleura, pleural traction and closed pleura were observed in 24 (47.06%) and 11 (21.57%) cases, respectively. The peripheral blood vessels passed through the lesion in eight cases (15.69%) and adhered closely to the edge of the lesion in 16 cases (31.37%). The surrounding bronchi passed through the lesion in eight cases (15.69%) and moved toward the edge of the lesion in 21 cases (41.18%). Conclusion: Cystic lung cancer has certain features on CT that can allow its suggestive diagnosis.

Carbon dioxide emissions from oxic-anoxic transitional soil layers in a drained peatland are less sensitive to warming than emissions from oxic surface and anoxic deep soil layers, according to a laboratory-based incubation experiment of Qinghai-Tibet Plateau peatland soils.

Summary: Background: Mediastinal neoplasms are typical thoracic diseases with increasing incidence in the general global population and can lead to poor prognosis. In clinical practice, the mediastinum's complex anatomic structures and intertype confusion among different mediastinal neoplasm pathologies severely hinder accurate diagnosis. To solve these difficulties, we organised a multicentre national collaboration on the basis of privacy-secured federated learning and developed CAIMEN, an efficient chest CT-based artificial intelligence (AI) mediastinal neoplasm diagnosis system. Methods: In this multicentre cohort study, 7825 mediastinal neoplasm cases and 796 normal controls were collected from 24 centres in China to develop CAIMEN. We further enhanced CAIMEN with several novel algorithms in a multiview, knowledge-transferred, multilevel decision-making pattern. CAIMEN was tested by internal (929 cases at 15 centres), external (1216 cases at five centres and a real-world cohort of 11 162 cases), and human–AI (60 positive cases from four centres and radiologists from 15 institutions) test sets to evaluate its detection, segmentation, and classification performance. Findings: In the external test experiments, the area under the receiver operating characteristic curve for detecting mediastinal neoplasms of CAIMEN was 0·973 (95% CI 0·969–0·977). In the real-world cohort, CAIMEN detected 13 false-negative cases confirmed by radiologists. The dice score for segmenting mediastinal neoplasms of CAIMEN was 0·765 (0·738–0·792). The mediastinal neoplasm classification top-1 and top-3 accuracy of CAIMEN were 0·523 (0·497–0·554) and 0·799 (0·778–0·822), respectively. In the human–AI test experiments, CAIMEN outperformed clinicians with top-1 and top-3 accuracy of 0·500 (0·383–0·633) and 0·800 (0·700–0·900), respectively. Meanwhile, with assistance from the computer aided diagnosis software based on CAIMEN, the 46 clinicians improved their average top-1 accuracy by 19·1% (0·345–0·411) and top-3 accuracy by 13·0% (0·545–0·616). Interpretation: For mediastinal neoplasms, CAIMEN can produce high diagnostic accuracy and assist the diagnosis of human experts, showing its potential for clinical practice. Funding: National Key R&D Program of China, National Natural Science Foundation of China, and Beijing Natural Science Foundation.

Seafloor spreading is an important cornerstone of the theory of plate tectonics. Asymmetric seafloor spreading and oceanic ridge jumps are common phenomena in this process and play important roles in controlling oceanic crust accretion, regional tectonics and geological geometric boundaries. As the largest marginal sea in the western Pacific, the South China Sea is an ideal laboratory for dissecting the Wilson cycle of small marginal sea-type ocean basins restricted by surrounding blocks and exploring the deep dynamic processes of confined small ocean basins. In recent years, a lot of research has been conducted on the spreading history of the South China Sea and has achieved fruitful results. However, the detailed dynamic mechanisms of asymmetric seafloor spreading and ridge jumps are still unclear. Therefore, this paper summarizes the basic understanding about the dynamic mechanisms of global asymmetric seafloor spreading and ridge jumps and reviews the related research results of asymmetric seafloor spreading and ridge jumps in the South China Sea. Previous studies have basically confirmed that seafloor spreading in the South China Sea started between ~32 and 34 Ma in the east sub-basin and ended at ~15 Ma in the northwest sub-basin, with at least once oceanic ridge jump in the east sub-basin. The current research mainly focuses on the age of the seafloor spreading in the South China Sea and the location, time and stage of the ridge jumps, but there are relatively few studies on high-resolution lithospheric structure across these ridges and the dynamic mechanism of oceanic ridge jumps. Based on the current research progress, we propose that further studies should focus on the lithosphere–asthenosphere scale in the future, suggesting that marine magnetotelluric and Ocean Bottom Seismometer (OBS) surveys should be conducted across the residual oceanic ridges to perform a detailed analysis of the tectonics magmatism in the east sub-basin to gain insights into the dynamic mechanisms of oceanic ridge jumps and asymmetric seafloor spreading, which can promote understanding of the tectonic evolution of the South China Sea and improve the classical plate tectonics theory that was constructed based on the open ocean basins.

During the Miocene, several reefs formed in the Beikang Basin, South China Sea, which may be potential targets for hydrocarbon exploration. This is due to the environment that developed as a result of the collision, splitting, and splicing of the Nansha Block, which was influenced by the Neogene expansion of the area. However, studies on the types, distribution, controlling factors, and evolution stages of these reefs are scarce. In this study, we used high-resolution seismic data and extensive well-drilling records to gain insights into the evolution of reefs in this particular area. Six distinct types of reefs, namely, the point reef, the platform-edge reef, the block reef, the bedded reef, the pinnacle reef, and the atoll reef, were identified based on our data. These reefs underwent four stages of development. During the initial stage, a few small-sized point reefs emerged in the basin and experienced significant growth during the early Middle Miocene. In the flourishing stage, the reefs predominantly thrived around the Central Uplift and Eastern Uplift areas. In the recession stage, the reefs began to deteriorate during the late Middle Miocene period as a result of the rapid increase in relative sea level caused by tectonic subsidence. In the submerged stage, since the Late Miocene, as the relative sea level continued to rise steadily over time, many reefs that had previously flourished surrounding the Central Uplift and Eastern Uplift areas became submerged underwater, with only a handful of atoll reefs surviving near islands located on the Eastern Uplift. This study indicated the presence of a significant number of well-preserved reefs in the Beikang Basin that have experienced minimal subsequent diagenesis and therefore exhibit high potential as reservoirs for oil and gas exploration.

Abstract Zoonotic malaria due to Plasmodium knowlesi infection in Southeast Asia is sometimes life-threatening. Post-mortem examination of human knowlesi malaria cases showed sequestration of P. knowlesi-infected red blood cells (iRBCs) in blood vessels, which has been proposed to be linked to disease severity. This sequestration is likely mediated by the cytoadhesion of parasite-iRBCs to vascular endothelial cells; however, the responsible parasite ligands remain undetermined. This study selected P. knowlesi lines with increased iRBC cytoadhesion activity by repeated panning against human umbilical vein endothelial cells (HUVECs). Transcriptome analysis revealed that the transcript level of one gene, encoding a Schizont Infected Cell Agglutination (SICA) protein, herein termed SICA-HUVEC, was more than 100-fold increased after the panning. Transcripts of other P. knowlesi proteins were also significantly increased, such as PIR proteins exported to the iRBC cytosol, suggesting their potential role in increasing cytoadhesion activity. Transgenic P. knowlesi parasites expressing Myc-fused SICA-HUVEC increased cytoadhesion activity following infection of monkey as well as human RBCs, confirming that SICA-HUVEC conveys activity to bind to HUVECs.

Advanced security applications require materials responsive to different stimuli with remarkable stability. Here, Sargent et al. introduce Ge homogenously into a silica scaffold and obtain a colourtuned germanium silicon oxide with ultra-long phosphorescence and delayed fluorescence across a broad temperature range.

Computed tomography (CT) has been the most effective modality for characterizing and quantifying chronic obstructive pulmonary disease (COPD). Radiomics features extracted from the region of interest in chest CT images have been widely used for lung diseases, but they have not yet been extensively investigated for COPD. Therefore, it is necessary to understand COPD from the lung radiomics features and apply them for COPD diagnostic applications, such as COPD stage classification. Lung radiomics features are used for characterizing and classifying the COPD stage in this paper. First, 19 lung radiomics features are selected from 1316 lung radiomics features per subject by using Lasso. Second, the best performance classifier (multi-layer perceptron classifier, MLP classifier) is determined. Third, two lung radiomics combination features, Radiomics-FIRST and Radiomics-ALL, are constructed based on 19 selected lung radiomics features by using the proposed lung radiomics combination strategy for characterizing the COPD stage. Lastly, the 19 selected lung radiomics features with Radiomics-FIRST/Radiomics-ALL are used to classify the COPD stage based on the best performance classifier. The results show that the classification ability of lung radiomics features based on machine learning (ML) methods is better than that of the chest high-resolution CT (HRCT) images based on classic convolutional neural networks (CNNs). In addition, the classifier performance of the 19 lung radiomics features selected by Lasso is better than that of the 1316 lung radiomics features. The accuracy, precision, recall, F1-score and AUC of the MLP classifier with the 19 selected lung radiomics features and Radiomics-ALL were 0.83, 0.83, 0.83, 0.82 and 0.95, respectively. It is concluded that, for the chest HRCT images, compared to the classic CNN, the ML methods based on lung radiomics features are more suitable and interpretable for COPD classification. In addition, the proposed lung radiomics combination strategy for characterizing the COPD stage effectively improves the classifier performance by 12% overall (accuracy: 3%, precision: 3%, recall: 3%, F1-score: 2% and AUC: 1%).

The resting HR is an upward trend with the development of chronic obstructive pulmonary disease (COPD) severity. Chest computed tomography (CT) has been regarded as the most effective modality for characterizing and quantifying COPD. Therefore, CT images should provide more information to analyze the lung and heart relationship. The relationship between HR variability and PFT or/and COPD has been fully revealed, but the relationship between resting HR variability and COPD radiomics features remains unclear. 231 sets of chest high-resolution CT (HRCT) images from "COPD patients" (at risk of COPD and stage I to IV) are segmented by the trained lung region segmentation model (ResU-Net). Based on the chest HRCT images and lung segmentation images, 231 sets of the original lung parenchyma images are obtained. 1316 COPD radiomics features of each subject are calculated by the original lung parenchyma images and its derived lung parenchyma images. The 13 selected COPD radiomics features related to the resting HR are generated from the Lasso model. A COPD radiomics features combination strategy is proposed to satisfy the significant change of the lung radiomics feature among the different COPD stages. Results show no significance between COPD stage Ⅰ and COPD stage Ⅱ of the 13 selected COPD radiomics features, and the lung radiomics feature Y1-Y4 (P > 0.05). The lung radiomics feature F2 with the dominant selected COPD radiomics features based on the proposed COPD radiomics features combination significantly increases with the development of COPD stages (P < 0.05). It is concluded that the lung radiomics feature F2 with the dominant selected COPD radiomics features not only can characterize the resting HR but also can characterize the COPD stage evolution.

PurposeThe study aimed to identify clinical prognostic factors affecting overall survival (OS) in patients with central neurocytoma (CN) and to determine independent prognostic factors in the subgroups of different treatment modalities using a retrospective analysis based on the SEER database from 2003 to 2019.Materials and methodsData regarding patients with CN, including basic clinical characteristics, treatment measures, and prognosis follow-up, were extracted from the SEER database. The prognostic variables for all patients were assessed using log-rank test as well as univariate and multivariate analyses based on the Cox proportional hazards model. The same statistical methods were used for analysis in different subgroups of gross total resection (GTR), subtotal resection (STR), no surgery, radiotherapy (RT), and no RT.ResultsIn total, 413 patients were enrolled in this study. Tumor size, primary site surgery, and RT were independent prognostic factors in all patients with CN. In subgroup analyses, RT was not an independent prognostic factor in patients with GTR. However, sex and race were independent prognostic factors in patients with STR. Additionally, tumor size was an independent prognostic factor in patients who did not undergo surgery. Furthermore, sex and primary site were independent prognostic factors in patients who received RT. Size and primary site surgery were independent prognostic factors in patients without RT.ConclusionIn our study, patients with small tumors or GTR or those who did not receive RT showed a better prognosis. GTR was the preferred treatment for CN. RT was not recommended for patients after GTR. Men and African American showed certain advantages after STR surgery. Tumors with a size of >4 cm were recommended for active treatment. In the RT subgroup, patients with tumors outside the ventricle or women had a poorer prognosis than those with tumors within the ventricle or men, respectively. These findings will help clinicians and patients understand the treatment and prognosis of CN visually and intuitively.

IntroductionBecause of persistent airflow limitation in chronic obstructive pulmonary disease (COPD), patients with COPD often have complications of dyspnea. However, as a leading symptom of COPD, dyspnea in COPD deserves special consideration regarding treatment in this fragile population for pre-clinical health management in COPD. Methods: Based on the above, this paper proposes a multi-modal data combination strategy by combining the local and global features for dyspnea identification in COPD based on the multi-layer perceptron (MLP) classifier.MethodsFirst, lung region images are automatically segmented from chest HRCT images for extracting the original 1,316 lung radiomics (OLR, 1,316) and 13,824 3D CNN features (O3C, 13,824). Second, the local features, including five selected pulmonary function test (PFT) parameters (SLF, 5), 28 selected lung radiomics (SLR, 28), and 22 selected 3D CNN features (S3C, 22), are respectively selected from the original 11 PFT parameters (OLF, 11), 1,316 OLR, and 13,824 O3C by the least absolute shrinkage and selection operator (Lasso) algorithm. Meantime, the global features, including two fused PFT parameters (FLF, 2), six fused lung radiomics (FLR, 6), and 34 fused 3D CNN features (F3C, 34), are respectively fused by 11 OLF, 1,316 OLR, and 13,824 O3C using the principal component analysis (PCA) algorithm. Finally, we combine all the local and global features (SLF + FLF + SLR + FLR + S3C + F3C, 5+ 2 + 28 + 6 + 22 + 34) for dyspnea identification in COPD based on the MLP classifier.ResultsOur proposed method comprehensively improves classification performance. The MLP classifier with all the local and global features achieves the best classification performance at 87.7% of accuracy, 87.7% of precision, 87.7% of recall, 87.7% of F1-scorel, and 89.3% of AUC, respectively.DiscussionCompared with single-modal data, the proposed strategy effectively improves the classification performance for dyspnea identification in COPD, providing an objective and effective tool for COPD management.

The eutrophic lake Dianchi, china, is a hotspot for methane (CH4) and nitrous oxide (N2O) emissions. However, the potential factors driving CH4 and N2O production in the riparian wetlands of Dianchi Lake remain unclear. In the current study, the potential CH4 and N2O production was evaluated using incubation experiments. The abundance and community structure of the methanogenic communities and denitrifying bacteria were measured using quantitative polymerase chain reaction and Illumina MiSeq sequencing. The results indicated that the potential CH4 and N2O production differed significantly among the riparian wetlands of Dianchi Lake, with rates of 0.26–17.65 μg/g.d and 0.09–1.30 ng/g.h, respectively. The soil mcrA, nirS and nosZ gene copies differed significantly among the riparian wetlands, whereas the soil narG and nirk genes did not. Soil methanogenic archaea in the riparian wetlands were dominated by the order Bathyarchaeia (2.36–45.97 %). Forty-one potential denitrifying bacterial genera were detected in soils from the riparian wetlands, among which the majority belonged to the Proteobacteria (31 genera; 1.54–37.78 %). The variation in CH4 production was mediated through soil AP, water NO3−-N and soil mcrA abundance, while water NH4+-N, soil TN and soil NH4+-N were the main factors regulating N2O production in the riparian wetlands of Dianchi Lake. Our study highlighted the important implication of pollution abatement to greenhouse gas emission reduction in the riparian wetland.

Volatile organic compounds (VOCs) are growing pollutants now that cause the serious environmental pollution and threaten human health. The functionalized ordered mesoporous silica (FOMS) has attracted considerable attention in adsorbing VOCs. In this paper, the molecular dynamics simulation was used to simulate the adsorption performance of FOMS on VOCs (acetone, ethyl acetate and toluene). After simulating different pore sizes (2 nm, 3 nm and 4 nm) adsorption performances of ordered mesoporous silica (OMS) on VOCs, OMS with a pore size of 4 nm was selected to further study the influence of functional groups (vinyl, methyl, and phenyl). The following law was obtained: the saturated adsorption capacities of vinyl-functionalized OMS (V-FOMS) to acetone, ethyl acetate and toluene were 3.045 mmol.g−1, 2.568 mmol.g−1 and 1.976 mmol.g−1 respectively; the saturated adsorption capacities of methyl-functionalized OMS (M-FOMS) to acetone, ethyl acetate and toluene were 2.798 mmol.g−1, 2.312 mmol.g−1 and 1.698 mmol.g−1 respectively; the saturated adsorption capacities of phenyl-functionalized OMS (P-FOMS) to acetone, ethyl acetate and toluene were 2.124 mmol.g−1, 1.941 mmol.g−1 and 1.539 mmol.g−1 respectively. These results show that the adsorption ability of FOMS for different adsorbates follows the sequence of acetone > ethyl acetate > toluene. Furthermore, the interaction between functional groups (vinyl, methyl and phenyl) in FOMS and VOCs was explored. It is found that the interaction between different functional groups and adsorbates is different (interaction energy effect). This interaction energy effect promotes FOMS to better adsorb VOCs. This work would provide fundamental understanding and guidance for the development of novel adsorption materials for the adsorption of VOCs.

Peatlands in Qinghai-Tibetan are degrading with climate change and human activities. Peatland degradation and climate change affect methane emissions. Methanogens are key functional microbes during methane production; however, knowledge of methanogens in degraded peatlands is lacking. Here, we investigated the effects of short-term (1 year) warming (OTC), drought (20%), and their combination on methanogens in the degraded peatlands on the Zoige Plateau of China via qPCR and clone library analysis. The results showed that Methanomicrobiales and Methanobacteriales were predominant in all the treatments. Non-metric multidimensional scaling (NMDS) and PERMANOVA analyses showed that the methanogenic community structure among the climate change treatments was not significantly different. The relative abundance of methanogen communities showed insignificant variation among the climate change treatments. The copy number and Shannon diversity of methanogens were significantly different within the climate change treatments, and drought significantly decreased the copy number of methanogens when compared to the control. The Redundancy analysis (RDA) results and correlation analysis showed that the environmental variables measured had no significant effect on methanogenic community structure and Shannon diversity. These results indicate that methanogens are insensitive to short-term climate change in degraded peatlands. This study provides insight into methane emissions from the Zoige Plateau peatlands by focusing on the possible responses of the methanogens to climate-driven changes.

A finite element analysis (FEA) model was developed for Euler and Timoshenko curved beam elements by incorporating trigonometric displacement distribution patterns. Local polar coordinate stiffness matrices were derived based on force-displacement relations and static equilibrium conditions. By employing the kinetic energy theorem and triangular displacement functions, an expression for the consistent mass matrix of a curved beam element was obtained. A coordinate transformation matrix for the curved beam element was established by relating the local polar coordinate system to the global polar coordinate system. Calculation programs were implemented in the Fortran language to evaluate the static–dynamic performance and natural frequency characteristics of curved beam bridges. The obtained results were then compared with those obtained using ANSYS solid models and “replace curve with straight” beam element models. The comparison demonstrated a strong agreement between the results of the Euler and Timoshenko curved beam element models and those of the ANSYS solid models. However, discrepancies were observed when comparing with the results of the “replace curve with straight” beam element model, particularly in terms of lateral static displacement. This discrepancy suggests that the characteristic matrix derived in this study accurately represents the stiffness and mass distribution of the curved beam, making it suitable for mechanical performance analysis of curved beam bridges. It should be noted that the “replace curve with straight” method overlooks the initial curvature and the bending–torsion coupling effects of a curved beam, resulting in calculation deviations. On the other hand, the use of curved beam elements in numerical analysis provides a simple and practical approach, which facilitates further research in areas such as vehicle–bridge coupling vibrations and seismic analysis of curved beam bridges.

PurposeThis study was launched to ascertain the independent prognostic factors influencing the overall survival (OS) prognosis of intracranial subependymoma and construct a prognostic model to predict OS time.Materials and methodsWe collected data from patients with intracranial subependymoma, including treatment data, follow-up data, and clinical and pathological characteristics from the SEER database within 2004 to 2016, and patients were randomly classified into training and validation cohorts. Univariate and multivariate analyses were applied to the training group through building a Cox proportional hazards model. According to the results of multivariate analysis, we established a nomogram to forecast the OS rate of the per-case patient graphically, then calculated the accuracy of verification in both training and validation cohorts by concordance index (C-index). Univariate and multivariate analyses were used for different subgroups of unoperated versus operated, gross total resection (GTR), subtotal resection (STR), and biopsy after using the propensity score matching (PSM) analyses.ResultsA total of 667 patients were enrolled, and we randomly assigned 535 patients (80.21%) into the training cohort and 132 patients (19.79%) into the validation cohort. Age [hazard ratio (HR) = 6.355; 95% confidence interval (CI), 2.240–18.029; p = 0.001] and sex (HR = 0.475; 95% CI, 0.232–0.974; p = 0.042) were the independent prognostic factors in the training cohort. On the basis of age and sex, the nomogram was established to predict the OS for every patient (C-index = 0.733 ± 0.065 in the training cohort and 0.850 ± 0.065 in the validation cohort), and calibration plots reflected the reliability of the nomogram. Age, gender, or laterality was the independent prognostic factor for OS in the different matched subgroups of unoperated versus operated, GTR, STR, and biopsy. Surgical treatment, race, year of diagnosis, insurance, tumor location, tumor size, pathology, tumor grade, and radiation were not statistically significantly different in OS for subependymoma in our research.ConclusionAge and sex were the independent prognostic variables for OS in intracranial subependymoma. According to our research, we should not be more inclined to choose conservative or surgical treatment. Nonetheless, the information that we present might be useful to suggest potential hypotheses to be tested in the clinical research setting.

Our paper proposes a method to measure lung parenchyma parameters from pulmonary window computed tomography images based on ResU-Net model including the CT value, the density, the lung volume, and the surface area of the lungs of healthy rats, to help promote the quantitative analysis of lung parenchyma parameters of rats in medical respiratory researches. Through the analysis of the lung parenchyma parameters of the control group and the treatment group, the law of change among the lung parenchyma parameters is given in our paper. After comparing and analyzing the lung parenchyma parameter CT value and the density of the two groups, it is discovered that the lung parenchyma parameter CT value and the density significantly increase in the treatment group which is after continuously inhaling the nebulization of contrast agents. The change of the lung volume with the surface area in both two groups conforms to the law of lung changes during breathing. The relationship between the lung volume and the CT value or the density is analyzed and it is concluded that the lung volume is negatively correlated with the CT value or the density.

Since its discovery, Porcine reproductive and respiratory syndrome (PRRS) has had a huge impact on the farming industry. The virus that causes PRRS is Porcine Reproductive and Respiratory Syndrome Virus (PRRSV), and because of its genetic diversity and the complexity of the immune response, the eradication of PRRS has been a challenge. To provide scientific references for PRRSV control and vaccine development, this study describes the processes of PRRSV-induced infection and escape, as well as the host adaptive immune response to PRRSV. It also discusses the relationship between PRRSV and the adaptive immune response.

Wetlands are vulnerable to climate change and human activities. However, the past changes caused by climate and human activities on net primary production (NPP) were unclear on the Zoige Plateau, which is on the Qinghai-Tibet Plateau. In this study, the impact of climatic and anthropogenic pressure on the NPP of wetlands on the Zoige Plateau from 1990 to 2015 was explored. We assessed and quantified the effects of climatic and anthropogenic factors on NPP using a simulated process model (LPJ_WHyMe) and a remote sensing model (CASA). Our simulations suggested that the annual average potential net primary production (NPPp) fluctuated during the study period and peaked in 2008 (347.37 g C m-2 year-1), while the total wetland NPPp peaked in 2000 (1.75 Tg C year-1). The results also showed that the annual average actual net primary production (NPPa) reached the lowest value of 206.04 g C m-2 year-1 in 2000. The total wetland NPPa ranged from 0.97 to 1.15 Tg C year-1 and continuously decreased over the study period. Our research revealed that human activities accounted for 22.37–36.45% of wetland NPP reduction over the study period. These results suggested that reducing human interventions can improve the NPP of wetlands. However, some of the negative effects of human activities have been offset by ecological restoration projects. These results provide a reference and scientific support for wetland protection and sustainable development.

BackgroundChronic obstructive pulmonary disease (COPD), a preventable lung disease, has the highest prevalence in the elderly and deserves special consideration regarding earlier warnings in this fragile population. The impact of age on COPD is well known, but the COPD risk of the aging process in the lungs remains unclear. Therefore, it is necessary to understand the COPD risk of the aging process in the lungs, providing an early COPD risk decision for adults.MethodsCOPD risk is evaluated for adults to make an early COPD risk decision from the perspective of lung radiomics features. First, the subjects are divided into four groups according to the COPD stages. Their ages are divided into eight equal age intervals in each group. Second, four survival Cox models are established based on the lung radiomics features to evaluate the risk probability from COPD stage 0 to suffering COPD and COPD stages. Finally, four risk ranks are defined by equally dividing the COPD risk probability from 0 to 1. Subsequently, the COPD risk at different stages is evaluated with varying age intervals to provide an early COPD risk decision.ResultsThe evaluation metrics area under the curve (AUC)/C index of four survival Cox models are 0.87/0.94, 0.84/0.83, 0.94/0.89, and 0.97/0.86, respectively, showing the effectiveness of the models. The risk rank levels up every 5 years for the subjects who had suffered COPD after 60. For the subjects with COPD stage 0, the risk rank of suffering COPD stage I levels up every 5 years after the age of 65 years, and the risk rank of suffering COPD stages II and III & IV levels up every 5 years after the age of 70 years.ConclusionOnce the age is above 60 years, the patients with COPD need to take action to prevent the progress and deterioration of COPD. Once the age is above 65 years, the patients with COPD stage 0 need to take precautions against COPD.