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The southward extension of the Bangong-Nujiang Suture and the late Mesozoic tectonic affinity of the Tengchong Block have been subject to debate, and the Early Cretaceous magmatism in the eastern Tengchong Block provides a crucial window to address these issues. This paper reports comprehensive petrographic, geochemical, geochronological, and isotopic data of Early Cretaceous granitic rocks from the eastern Tengchong Block. Results show that these granitic rocks consist of monzogranites and granodiorites, with zircon U-Pb ages of 120.4–113.9 Ma. These granitic rocks are characterized by enrichments in large ion lithophile elements (e.g. Rb, U, K) and light rare earth elements, but depleted in high field strength elements (e.g. Nb, Ta, P, Ti), and have negative apatite εNd(t) values (−10.4 to −6.7) and negative zircon εHf(t) values (−11.7 to −1.2). The molar [Al2O3/(CaO + K2O + Na2O)] (A/CNK) values and whole-rock zircon saturated temperatures of the studied monzogranites of 1.04–1.09 and 714–799°C, respectively, indicate that they have I-type granite affinity. The presence of biotite indicative of I-type granite and the observation that P2O5 decrease with increasing SiO2 further indicated that the monzogranites have affinities of I-type granites. The petrography, geochemical and isotopic signatures of the studied monzogranites indicate that they originated from partial melting of mafic lower crustal rocks. The Na-rich granodiorites have elevated Na2O/K2O ratios and Na2O contents of 1.19–2.04 and 3.12–3.47 wt.%, respectively. These granodiorites also have relatively high Mg# values and the transition metal element Cr of 53.3–54.5 and up to 100 ppm, respectively. According to these isotopic and geochemical features and the occurrence of magnesiohornblende, we propose that the Na-rich granodiorites were derived from partial melting of ancient basaltic lower crust, with certain inputs of mantle materials in the magma source. Considering these results as well as published data, we finally propose that the Tengchong Block was likely the southeastern extension of the Lhasa Block and that these Early Cretaceous granitic rocks were formed in the setting of the volcanic arc due to westward subduction of the Bangong-Nujiang Tethys oceanic lithosphere beneath the Tengchong Block. [ABSTRACT FROM AUTHOR]

Various magmatisms during the subduction-collision process are crucial to reveal the long-term tectonic evolution of the eastern Central Asian Orogenic Belt. In this paper, we present major and trace elements of whole-rock, zircon U-Pb dating and Hf isotope of the Shanmen pluton. Results imply that the Shanmen pluton consists of quartz diorite and mylonitic granite, with zircon U-Pb ages of 263.7–259.6 Ma. The studied quartz diorite contains high Sr/Y (51.19–90.87) and (La/Yb)N (7.82–13.62) ratios, and belongs to adakitic rocks. Coupled with the positive εHf(t) values of +5.71 to +12.8 with no obvious Eu anomaly, we propose that quartz diorite is the product of the interaction between different degrees of slab melt and the overlying mantle wedge. In contrast, the mylonitic granite has lower MgO (0.28 wt% – 0.47 wt%) contents and positive εHf(t) values of +7.79 to +10.15, indicating an affinity with I-type granite originated by partial melting of the intermediate-basic lower crust. The geochemical characteristics and lithological assemblages, along with the Permian magmatic rocks in the Changchun-Kaiyuan area displaying arc rocks affinity, propose their formation is related to the southward subduction of the Paleo-Asian Ocean (PAO). Based on this study and previous evidence, we lean towards adopting a middle-late Permian slab break-off model, wherein the PAO did not close until the late Permian. [ABSTRACT FROM AUTHOR]

The Central Asian Orogenic Belt (CAOB) is the largest accretionary orogenic belt in the world and its formation involved a complicated process of arc–continent collision. Large‐scale Mesozoic volcanic activity in the Great Xing'an Range (GXAR) in northeastern China, which constitutes part of the eastern CAOB, has received much recent research attention. However, the petrogenesis and formation mechanism of the late Mesozoic igneous rocks remain enigmatic. This paper investigates the geochronology, petrogenesis, and formation mechanism of late Mesozoic magmatic rocks in the Kelihe area of the GXAR based on zircon U–Pb dating, petrology, and geochemistry. Late Mesozoic magmatism in the Kelihe area occurred during the Late Jurassic (165–155 Ma) and Early Cretaceous (130–120 Ma). These igneous rocks generated by this magmatism are characterized by high SiO2 (69.97–75.49 wt%) and low MgO (0.11–0.68 wt%), Cr (10–30 ppm), Co (0.2–2.6 ppm), and Ni (0.5–1.6 ppm) contents. Trace elements show enrichment in Rb, Th, U, Zr, and K, and depletion in Ba, P, Nb, and Ti. These features indicate that the rocks were derived from partial melting of the crust. Furthermore, the rhyolites have high Na2O (5.02–5.44 wt%) and K2O (3.94–4.88 wt%) contents, similar to those of melts formed by the partial melting of basaltic crust. Combining the present results with the findings of previous studies, it is inferred that the Mesozoic igneous rocks formed in a post‐collisional extensional setting related to lithospheric thinning and asthenospheric upwelling after the closure of the Mongol–Okhotsk Ocean. [ABSTRACT FROM AUTHOR]

Simple Summary: The dark black chafer, Holotrichia parallela, which is widely distributed all over the world, is an economically important pest in agriculture and forestry. In the north part of China, this beetle causes serious damage to the peanut plant. Much attention has been paid to olfactory perception of volatile compounds from supplemental nutrition hosts by H. parallela prior to sexual maturation. However, volatile compounds attractive to this beetle from the peanut plant have not been identified yet. In this study, we collected the volatile compounds from peanut seedlings by dynamic headspace adsorption and identified twelve electrophysiologically active compounds responsible for the attraction of H. parallela to the peanut. Among the eight chemically identified compounds, β-caryophyllene and hexanal significantly attracted both sexes of H. parallela when tested individually in the field. A blend of β-caryophyllene and hexanal at a ratio of 2:1 was most attractive to the beetles. The addition of the remaining compounds to the binary mixture did not increase the attractiveness. The findings of this study reveal that β-caryophyllene and hexanal can be potentially used for development of effective attractants for management of H. parallela. Holotrichia parallela (Coleoptera: Scarabaeidae: Melolonthinae) is a notorious pest of many crops, especially peanuts. In this study, volatiles from peanut plants were analyzed using both gas chromatographic-electroantennographic detection (GC-EAD) and gas chromatography/mass spectrometry (GC/MS) techniques, and tested for adult attraction with field trapping bioassays in Hebei Province, China. GC-EAD analyses indicated that H. parallela antennae strongly responded to twelve GC peaks, including eight identified compounds, (Z)-β-ocimene, hexanal, 6-methyl-5-hepten-2-one, nonanal, dihydromyrcenol, linalool, β-caryophyllene, methyl salicylate, and four unidentified compounds. When tested individually in field conditions from 24 to 31 July, 2020, β-caryophyllene and hexanal significantly attracted both sexes of H. parallela, whereas all other compounds were unattractive. A blend of β-caryophyllene and hexanal at a ratio of 2:1, close to the natural ratio of these two compounds from the intact peanut plant, was most attractive to the beetles. The remaining identified compounds, (Z)-β-ocimene, 6-methyl-5-hepten-2-one, nonanal, dihydromyrcenol, linalool, and methyl salicylate had no synergistic effects on H. parallela attraction when tested in combination with the blend of β-caryophyllene and hexanal. These results demonstrated that β-caryophyllene and hexanal in the volatiles from peanut plants have strong attraction to H. parallela. These two compounds have the potential to be used for monitoring H. parallela and its management programs. [ABSTRACT FROM AUTHOR]

Importance: Lymphopenia is common and correlates with poor clinical outcomes in patients with coronavirus disease 2019 (COVID-19)., Objective: To determine whether a therapy that increases peripheral blood leukocyte and lymphocyte cell counts leads to clinical improvement in patients with COVID-19., Design, Setting and Participants: Between February 18 and April 10, 2020, we conducted an open-label, multicenter, randomized clinical trial at 3 participating centers in China. The main eligibility criteria were pneumonia, a blood lymphocyte cell count of 800 per μL (to convert to ×109/L, multiply by 0.001) or lower, and no comorbidities. Severe acute respiratory syndrome coronavirus 2 infection was confirmed with reverse-transcription polymerase chain reaction testing., Exposures: Usual care alone, or usual care plus 3 doses of recombinant human granulocyte colony-stimulating factor (rhG-CSF, 5 μg/kg, subcutaneously at days 0-2)., Main Outcomes and Measures: The primary end point was the time from randomization to improvement of at least 1 point on a 7-category disease severity score., Results: Of 200 participants, 112 (56%) were men and the median (interquartile range [IQR]) age was 45 (40-55) years. There was random assignment of 100 patients (50%) to the rhG-CSF group and 100 (50%) to the usual care group. Time to clinical improvement was similar between groups (rhG-CSF group median of 12 days (IQR, 10-16 days) vs usual care group median of 13 days (IQR, 11-17 days); hazard ratio, 1.28; 95% CI, 0.95-1.71; P = .06). For secondary end points, the proportion of patients progressing to acute respiratory distress syndrome, sepsis, or septic shock was lower in the rhG-CSF group (rhG-CSF group, 2% vs usual care group, 15%; difference, -13%; 95%CI, -21.4% to -5.4%). At 21 days, 2 patients (2%) had died in the rhG-CSF group compared with 10 patients (10%) in the usual care group (hazard ratio, 0.19; 95%CI, 0.04-0.88). At day 5, the lymphocyte cell count was higher in the rhG-CSF group (rhG-CSF group median of 1050/μL vs usual care group median of 620/μL; Hodges-Lehmann estimate of the difference in medians, 440; 95% CI, 380-490). Serious adverse events, such as sepsis or septic shock, respiratory failure, and acute respiratory distress syndrome, occurred in 29 patients (14.5%) in the rhG-CSF group and 42 patients (21%) in the usual care group., Conclusion and Relevance: In preliminary findings from a randomized clinical trial, rhG-CSF treatment for patients with COVID-19 with lymphopenia but no comorbidities did not accelerate clinical improvement, but the number of patients developing critical illness or dying may have been reduced. Larger studies that include a broader range of patients with COVID-19 should be conducted., Trial Registration: Chinese Clinical Trial Registry: ChiCTR2000030007.

Background: During the outbreak of coronavirus disease 2019 (COVID-19), consistent and considerable differences in disease severity and mortality rate of patients treated in Hubei province compared to those in other parts of China have been observed. We sought to compare the clinical characteristics and outcomes of patients being treated inside and outside Hubei province, and explore the factors underlying these differences., Methods: Collaborating with the National Health Commission, we established a retrospective cohort to study hospitalised COVID-19 cases in China. Clinical characteristics, the rate of severe events and deaths, and the time to critical illness (invasive ventilation or intensive care unit admission or death) were compared between patients within and outside Hubei. The impact of Wuhan-related exposure (a presumed key factor that drove the severe situation in Hubei, as Wuhan is the epicentre as well the administrative centre of Hubei province) and the duration between symptom onset and admission on prognosis were also determined., Results: At the data cut-off (31 January 2020), 1590 cases from 575 hospitals in 31 provincial administrative regions were collected (core cohort). The overall rate of severe cases and mortality was 16.0% and 3.2%, respectively. Patients in Hubei (predominantly with Wuhan-related exposure, 597 (92.3%) out of 647) were older (mean age 49.7 versus 44.9 years), had more cases with comorbidity (32.9% versus 19.7%), higher symptomatic burden, abnormal radiologic manifestations and, especially, a longer waiting time between symptom onset and admission (5.7 versus 4.5 days) compared with patients outside Hubei. Patients in Hubei (severe event rate 23.0% versus 11.1%, death rate 7.3% versus 0.3%, HR (95% CI) for critical illness 1.59 (1.05-2.41)) have a poorer prognosis compared with patients outside Hubei after adjusting for age and comorbidity. However, among patients outside Hubei, the duration from symptom onset to hospitalisation (mean 4.4 versus 4.7 days) and prognosis (HR (95%) 0.84 (0.40-1.80)) were similar between patients with or without Wuhan-related exposure. In the overall population, the waiting time, but neither treated in Hubei nor Wuhan-related exposure, remained an independent prognostic factor (HR (95%) 1.05 (1.01-1.08))., Conclusion: There were more severe cases and poorer outcomes for COVID-19 patients treated in Hubei, which might be attributed to the prolonged duration of symptom onset to hospitalisation in the epicentre. Future studies to determine the reason for delaying hospitalisation are warranted., Competing Interests: Conflict of interest: Wen-hua Liang has nothing to disclose. Conflict of interest: Wei-jie Guan has nothing to disclose. Conflict of interest: Cai-chen Li has nothing to disclose. Conflict of interest: Yi-min Li has nothing to disclose. Conflict of interest: Heng-rui Liang has nothing to disclose. Conflict of interest: Yi Zhao has nothing to disclose. Conflict of interest: Xiao-qing Liu has nothing to disclose. Conflict of interest: Ling Sang has nothing to disclose. Conflict of interest: Ru-chong Chen has nothing to disclose. Conflict of interest: Chun-li Tang has nothing to disclose. Conflict of interest: Tao Wang has nothing to disclose. Conflict of interest: Wei Wang has nothing to disclose. Conflict of interest: Qi-hua He has nothing to disclose. Conflict of interest: Zi-sheng Chen has nothing to disclose. Conflict of interest: Sook-San Wong has nothing to disclose. Conflict of interest: Mark Zanin has nothing to disclose. Conflict of interest: Jun Liu has nothing to disclose. Conflict of interest: Xin Xu has nothing to disclose. Conflict of interest: Jun Huang has nothing to disclose. Conflict of interest: Jian-fu Li has nothing to disclose. Conflict of interest: Li-min Ou has nothing to disclose. Conflict of interest: Bo Cheng has nothing to disclose. Conflict of interest: Shan Xiong has nothing to disclose. Conflict of interest: Zhan-hong Xie has nothing to disclose. Conflict of interest: Zheng-yi Ni has nothing to disclose. Conflict of interest: Yu Hu has nothing to disclose. Conflict of interest: Lei Liu has nothing to disclose. Conflict of interest: Hong Shan has nothing to disclose. Conflict of interest: Chun-liang Lei has nothing to disclose. Conflict of interest: Yi-xiang Peng has nothing to disclose. Conflict of interest: Li Wei has nothing to disclose. Conflict of interest: Yong Liu has nothing to disclose. Conflict of interest: Ya-hua Hu has nothing to disclose. Conflict of interest: Peng has nothing to disclose. Conflict of interest: Jian-ming Wang has nothing to disclose. Conflict of interest: Ji-yang Liu has nothing to disclose. Conflict of interest: Zhong Chen has nothing to disclose. Conflict of interest: Gang Li has nothing to disclose. Conflict of interest: Zhi-jian Zheng has nothing to disclose. Conflict of interest: Shao-qin Qiu has nothing to disclose. Conflict of interest: Jie Luo has nothing to disclose. Conflict of interest: Chang-jiang Ye has nothing to disclose. Conflict of interest: Shao-yong Zhu has nothing to disclose. Conflict of interest: Lin-ling Cheng has nothing to disclose. Conflict of interest: Feng Ye has nothing to disclose. Conflict of interest: Shi-yue Li has nothing to disclose. Conflict of interest: Jin-ping Zheng has nothing to disclose. Conflict of interest: Nuo-fu Zhang has nothing to disclose. Conflict of interest: Nan-shan Zhong has nothing to disclose. Conflict of interest: Jian-xing He has nothing to disclose., (Copyright ©ERS 2020.)

Background: The coronavirus disease 2019 (COVID-19) outbreak is evolving rapidly worldwide., Objective: To evaluate the risk of serious adverse outcomes in patients with COVID-19 by stratifying the comorbidity status., Methods: We analysed data from 1590 laboratory confirmed hospitalised patients from 575 hospitals in 31 provinces/autonomous regions/provincial municipalities across mainland China between 11 December 2019 and 31 January 2020. We analysed the composite end-points, which consisted of admission to an intensive care unit, invasive ventilation or death. The risk of reaching the composite end-points was compared according to the presence and number of comorbidities., Results: The mean age was 48.9 years and 686 (42.7%) patients were female. Severe cases accounted for 16.0% of the study population. 131 (8.2%) patients reached the composite end-points. 399 (25.1%) reported having at least one comorbidity. The most prevalent comorbidity was hypertension (16.9%), followed by diabetes (8.2%). 130 (8.2%) patients reported having two or more comorbidities. After adjusting for age and smoking status, COPD (HR (95% CI) 2.681 (1.424-5.048)), diabetes (1.59 (1.03-2.45)), hypertension (1.58 (1.07-2.32)) and malignancy (3.50 (1.60-7.64)) were risk factors of reaching the composite end-points. The hazard ratio (95% CI) was 1.79 (1.16-2.77) among patients with at least one comorbidity and 2.59 (1.61-4.17) among patients with two or more comorbidities., Conclusion: Among laboratory confirmed cases of COVID-19, patients with any comorbidity yielded poorer clinical outcomes than those without. A greater number of comorbidities also correlated with poorer clinical outcomes., Competing Interests: Conflict of interest: Wei-jie Guan has nothing to disclose. Conflict of interest: Wen-hua Liang has nothing to disclose. Conflict of interest: Yi Zhao has nothing to disclose. Conflict of interest: Heng-rui Liang has nothing to disclose. Conflict of interest: Zi-sheng Chen has nothing to disclose. Conflict of interest: Yi-min Li has nothing to disclose. Conflict of interest: Xiao-qing Liu has nothing to disclose. Conflict of interest: Ru-chong Chen has nothing to disclose. Conflict of interest: Chun-li Tang has nothing to disclose. Conflict of interest: Tao Wang has nothing to disclose. Conflict of interest: Chun-quan Ou has nothing to disclose. Conflict of interest: Li has nothing to disclose. Conflict of interest: Ping-yan Chen has nothing to disclose. Conflict of interest: Ling Sang has nothing to disclose. Conflict of interest: Wei Wang has nothing to disclose. Conflict of interest: Jian-fu Li has nothing to disclose. Conflict of interest: Cai-chen Li has nothing to disclose. Conflict of interest: Li-min Ou has nothing to disclose. Conflict of interest: Bo Cheng has nothing to disclose. Conflict of interest: Shan Xiong has nothing to disclose. Conflict of interest: Zheng-yi Ni has nothing to disclose. Conflict of interest: Jie Xiang has nothing to disclose. Conflict of interest: Yu Hu has nothing to disclose. Conflict of interest: Lei Liu has nothing to disclose. Conflict of interest: Hong Shan has nothing to disclose. Conflict of interest: Chun-liang Lei has nothing to disclose. Conflict of interest: Yi-xiang Peng has nothing to disclose. Conflict of interest: Li Wei has nothing to disclose. Conflict of interest: Yong Liu has nothing to disclose. Conflict of interest: Ya-hua Hu has nothing to disclose. Conflict of interest: Peng has nothing to disclose. Conflict of interest: Jian-ming Wang has nothing to disclose. Conflict of interest: Ji-yang Liu has nothing to disclose. Conflict of interest: Zhong Chen has nothing to disclose. Conflict of interest: Gang Li has nothing to disclose. Conflict of interest: Zhi-jian Zheng has nothing to disclose. Conflict of interest: Shao-qin Qiu has nothing to disclose. Conflict of interest: Jie Luo has nothing to disclose. Conflict of interest: Chang-jiang Ye has nothing to disclose. Conflict of interest: Shao-yong Zhu has nothing to disclose. Conflict of interest: Lin-ling Cheng has nothing to disclose. Conflict of interest: Feng Ye has nothing to disclose. Conflict of interest: Shi-yue Li has nothing to disclose. Conflict of interest: Jin-ping Zheng has nothing to disclose. Conflict of interest: Nuo-fu Zhang has nothing to disclose. Conflict of interest: Nan-shan Zhong reports grants from the National Health Commission and Dept of Science and Technology of Guangdong Province, during the conduct of the study. Conflict of interest: Jian-xing He has nothing to disclose., (Copyright ©ERS 2020.)