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Effects of lake evaporation (EW) on basin evapotranspiration (ETB) and lake water storage change (△SW) at lake-basin scale have never been reported for most basins on the inner Tibetan Plateau (IB). In this study, EW of 117 large lakes in 95 closed lake-basins were estimated, and its effects on ETB and △SW over 2001-2018 were examined using several newly derived diagnostic equations from the aspects of EW amount, rate, trend slope and inter-annual variability. The significant increasing trend (0.29 ± 0.04 km3/a) in annual EW amount is mainly caused by increase (224.65 km2/a) in lake area (82.13%), and increase (2.12 ± 1.28 mm/a) in EW rate is responsible for the rest (17.87%). EW accounts for 23.16% ± 4.94% of the ETB (107.24 ± 21.90 km3) for the 95 basins, and its impact has increased significantly (0.20% ± 0.09%/a). The increasing trends of EW rate and lake area ratio (0.06%, P < 0.05) contributed 14.49% and 52.69% to the increase trend in ETB (0.85 mm/a), and their variances contributed 1.60% ~ 4.79% and 1.64% ~ 6.50% to ETB variance (155.44 ± 107.97 mm2), respectively. The contribution of EW, quasi lake inflow (RL, 23.48 km3), and lake surface precipitation (PW, 9.18 km3) to mean △SW (7.82 km3) are -43.02%, 40.84% and 15.96%, respectively. The increasing trends of the three components (EW, RL and PW) account for -58.02%, 29.59% and 12.39% of the decrease trend in annual △SW (-0.81 × 10 km3/a, P > 0.05), respectively., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Lake storage change serves as a unique indicator of natural climate change on the Tibetan Plateau (TP). However, comprehensive lake storage data, especially for lakes smaller than 10 km2, are still lacking in the region. In this dataset, we completed a census of annual relative lake volume (RLV) for 976 lakes, which are larger than 1 km2, on the endorheic basin of the Tibetan Plateau (EBTP) during 1989–2019 using Landsat imagery and digital terrain models. Our method first identifies individual lakes, determines their analysis extents and calculates annual lake area from Landsat imagery. It then derives lake area-elevation relationship, estimates lake surface elevation, and calculates RLV. Validation and comparison with several existing datasets indicate our data are more reliable and comprehensive. Our study complements existing lake datasets by providing a complete and long-term lake water volume change data for the region.

Background Since the outbreak of coronavirus disease 2019 (COVID‐19), clinical features have been analyzed in detail. However, coagulopathy in elderly COVID‐19 patients has been scarcely reported. Methods Coagulation parameters of 189 patients with COVID‐19 in Tongji hospital were retrospectively analyzed among age groups. Results Patients were divided into 2 groups: older group (≥65 years, n = 87) and younger group (, In this study, we summarized the characteristics of coagulopathy in different age groups with SARS‐CoV‐2 infection, and investigated the relations between coagulopathy and systemic inflammation in COVID‐19 patients.

To explore the role of thymosin drugs in the prevention of novel coronavirus disease (COVID-19), we analyzed the preventive effects of different medication timings on health medical staff, and then provided recommendations for pharmaceutical monitoring of thymus drugs. The hospital-based retrospective study analyzed 435 medical staffers, treated with or without thymosin drugs as preventive medicines in our hospital of Wuhan City, from January 25 to March 25, 2020. For the prophylactics, the medical staff was prevented from pre-exposure prophylaxis (risk prevention of exposure to COVID-19 patients before using thymosin drugs) and postexposure prophylaxis (risk prevention of exposure to COVID-19 patients after using thymosin drugs). The effectiveness and safety of thymosin drugs were studied in the prevention and control of COVID-19 application, in real-world data research for the application of the drug for COVID- 19. In a similar exposure environment, compared to medical staffers who did not take preventive medicine, the use of thymosin drugs, before exposure and after exposure had an insignificant effect, and the adverse drug reaction (ADR) was increased, especially when thymosin drugs were used together with α-interferon.

Actual evapotranspiration (AET) is a key factor in land-atmosphere interactions and a major hydrological cycle component. Variations in AET have resulted from a combination of climate change (CC) and human activities (HA). Quantifying the contributions of these two factors to AET dynamics is essential for better understanding hydrometeorological and ecohydrological processes under both natural and anthropogenic conditions. In this study, an analytical framework was adopted for AET variance analysis, and the influences of CC and HA on regional AET variabilities were separated by using this method. AET variance is determined by the variance in CC ( $${\sigma }_{AETc}^{2}$$ ) and HA ( $${\sigma }_{AETh}^{2}$$ ); the former is estimated through a synthesis of the variance/covariance of potential evapotranspiration (ET0) and precipitation (P), and the latter is determined from the residual between the total AET variance and $${\sigma }_{AETc}^{2}$$ . Based on a 36-year dataset (1980–2015), this framework is applied to the different regions of the Tao River Basin (TRB). The results reveal that climate was the primary factor influencing AET variance in most parts of the basin. Precipitation (P) dominated the $${\sigma }_{AETc}^{2}$$ and had a positive effect, while the interactions between P and ET0 tended to suppress this effect, especially in the semihumid areas of the TRB. The contribution rates of CC and HA to basin AET variance were estimated to be 0.76 and 0.24, respectively. The developed analytical framework and its application are beneficial to the management and exploitation of water resources from the perspective of basin ecohydrology.

Lakes are sensitive indicators of climate change in the Tibetan Plateau (TP), which have shown high temporal and spatial variability in recent decades. The driving forces for the change are still not entirely clear. This study examined the area change of the lakes greater than 1 km2 in the endorheic basins of the Tibetan Plateau (EBTP) using Landsat images from 1990 to 2019, and analysed the relationships between lake area and local and large-scale climate variables at different geographic scales. The results show that lake area in the EBTP has increased significantly from 1990 to 2019 at a rate of 432.52 km2·year−1. In the past 30 years, lake area changes in the EBTP have mainly been affected by local climate variables such as precipitation and temperature. At a large scale, Indian Summer Monsoon (ISM) has correlations with lake area in western sub-regions in the Inner Basin (IB). While Atlantic Multidecadal Oscillation (AMO) has a significant connection with lake area, the North Atlantic Oscillation (NAO) does not. We also found that abnormal drought (rainfall) brought by the El Niño/La Niña events are significantly correlated with the lake area change in most sub-regions in the IB.

The Tibetan Plateau, known as "the third pole of the Earth", is a region susceptible to climate change. With little human disturbance, lake storage changes serve as a unique indicator of climate change, but comprehensive lake storage data are rare in the region, especially for the lakes with an area less than 10 km2 which are the most sensitive to environmental changes. In this paper, we completed a census of annual lake volume change for 976 lakes larger than 1 km2 in the endorheic basin of the Tibetan Plateau (EBTP) during 1989–2019 using Landsat imagery and digital terrain models. Validation and comparison with several existing studies indicate that our data are more reliable. Lake volume in the EBTP exhibited a net increase of 193.45 km3 during the time period with an increasing rate of 6.45 km3 year−1. In general, the larger the lake area, the greater the lake volume change, though there are some exceptions. Lakes with an area less than 10 km2 have more severe volume change whether decreasing or increasing. This research complements existing lake studies by providing a comprehensive and long-term lake volume change data for the region. The dataset is available on Zenodo (https://doi.org/10.5281/zenodo.5543615, Wang et al., 2021).

Background Internet hospitals show great potential for adequately fulfilling people’s demands for high-quality outpatient services, and with the normalization of the epidemic prevention and control of COVID-19, internet hospitals play an increasingly important role in delivering health services to the public. However, the factors that influence patients’ intention to use the online inquiry services provided by internet hospitals remain unclear. Understanding the patients’ behavioral intention is necessary to support the development of internet hospitals in China and promote patients’ intention to use online inquiry services provided by internet hospitals during the prevention and control of the COVID-19 epidemic. Objective The purpose of this study is to identify the determinants of patients’ intention to use the online inquiry services provided by internet hospitals based on the theory of planned behavior (TPB). Methods The hypotheses of our research model were developed based on the TPB. A questionnaire was developed through patient interviews, verified using a presurvey, and used for data collection for this study. The cluster sampling technique was used to include respondents with chronic diseases. Structural equation modeling was used to test the research hypotheses. Results A total of 638 valid responses were received from patients with chronic diseases. The goodness-of-fit indexes corroborated that the research model was a good fit for the collected data. The model explained 45.9% of the variance in attitude toward the behavior and 60.5% of the variance in behavioral intention. Perceived behavioral control and perceived severity of disease had the strongest total effects on behavioral intention (β=.624, P=.004 and β=.544, P=.003, respectively). Moreover, perceived convenience, perceived information risk, emotional preference, and health consciousness had indirect effects on behavioral intention, and these effects were mediated by attitude toward the behavior. Among the four constructs, perceived convenience had the highest indirect effect on behavioral intention (β=.207; P=.001). Conclusions Perceived behavioral control and perceived severity of disease are the most important determinants of patients’ intention to use the online inquiry services provided by internet hospitals. Therefore, internet hospitals should further optimize the design of online service delivery and ensure a reasonable assembly of high-quality experts, which will benefit the promotion of patients’ adoption intention toward online inquiry services for health purposes. Perceived convenience, emotional preference, and perceived risks also have effects on behavioral intention. Therefore, the relevant quality control standards and regulations for internet hospitals should be further developed and improved, and the measures to protect personal information should be strengthened to ensure the patient safety. Our study supports the use of the TPB in explaining patients’ intention to use online inquiry services provided by internet hospitals.

Background Current guidelines for perioperative management of coronavirus disease 19 (COVID-19) are mainly based on extrapolated evidence or expert opinion. We aimed to systematically investigate how COVID-19 affects perioperative management and clinical outcomes, to develop evidence-based guidelines. Methods First, we conducted a rapid literature review in EMBASE, MEDLINE, PubMed, Scopus, and Web of Science (January 1 to July 1, 2020), using a predefined protocol. Second, we performed a retrospective cohort analysis of 166 women undergoing Caesarean section at Tongji Hospital, Wuhan during the COVID-19 pandemic. Demographic, imaging, laboratory, and clinical data were obtained from electronic medical records. Results The review identified 26 studies, mainly case reports/series. One large cohort reported greater mortality in elective surgery patients diagnosed after, rather than before surgery. Higher 30 day mortality was associated with emergency surgery, major surgery, poorer preoperative condition and surgery for malignancy. Regional anaesthesia was favoured in most studies and personal protective equipment (PPE) was generally used by healthcare workers (HCWs), but its use was poorly described for patients. In the retrospective cohort study, duration of surgery, oxygen therapy and hospital stay were longer in suspected or confirmed patients than negative patients, but there were no differences in neonatal outcomes. None of the 262 participating HCWs was infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) when using level 3 PPE perioperatively. Conclusions When COVID-19 is suspected, testing should be considered before non-urgent surgery. Until further evidence is available, HCWs should use level 3 PPE perioperatively for suspected or confirmed patients, but research is needed on its timing and specifications. Further research must examine longer-term outcomes. Clinical trial registration CRD42020182891 (PROSPERO).

BACKGROUND Internet hospitals show great potential for adequately fulfilling people’s demands for high-quality outpatient services, and with the normalization of the epidemic prevention and control of COVID-19, internet hospitals play an increasingly important role in delivering health services to the public. However, the factors that influence patients’ intention to use the online inquiry services provided by internet hospitals remain unclear. Understanding the patients’ behavioral intention is necessary to support the development of internet hospitals in China and promote patients’ intention to use online inquiry services provided by internet hospitals during the prevention and control of the COVID-19 epidemic. OBJECTIVE The purpose of this study is to identify the determinants of patients’ intention to use the online inquiry services provided by internet hospitals based on the theory of planned behavior (TPB). METHODS The hypotheses of our research model were developed based on the TPB. A questionnaire was developed through patient interviews, verified using a presurvey, and used for data collection for this study. The cluster sampling technique was used to include respondents with chronic diseases. Structural equation modeling was used to test the research hypotheses. RESULTS A total of 638 valid responses were received from patients with chronic diseases. The goodness-of-fit indexes corroborated that the research model was a good fit for the collected data. The model explained 45.9% of the variance in attitude toward the behavior and 60.5% of the variance in behavioral intention. Perceived behavioral control and perceived severity of disease had the strongest total effects on behavioral intention (β=.624, P=.004 and β=.544, P=.003, respectively). Moreover, perceived convenience, perceived information risk, emotional preference, and health consciousness had indirect effects on behavioral intention, and these effects were mediated by attitude toward the behavior. Among the four constructs, perceived convenience had the highest indirect effect on behavioral intention (β=.207; P=.001). CONCLUSIONS Perceived behavioral control and perceived severity of disease are the most important determinants of patients’ intention to use the online inquiry services provided by internet hospitals. Therefore, internet hospitals should further optimize the design of online service delivery and ensure a reasonable assembly of high-quality experts, which will benefit the promotion of patients’ adoption intention toward online inquiry services for health purposes. Perceived convenience, emotional preference, and perceived risks also have effects on behavioral intention. Therefore, the relevant quality control standards and regulations for internet hospitals should be further developed and improved, and the measures to protect personal information should be strengthened to ensure the patient safety. Our study supports the use of the TPB in explaining patients’ intention to use online inquiry services provided by internet hospitals.

Background Existing patient safety culture assessment tools are mostly developed in western countries and may not be suitable for Chinese primary health care institutions. Primary care plays an important role in China's medical system, and a targeted tool for its patient safety culture is urgently needed. Objective The aim of the study was to develop a dependable instrument to assess the patient safety culture in Chinese primary health care institutions. Methods Three phases were undertaken to develop the scale. The first phase developed a pilot scale by literature review, focus groups, and 2-round Delphi expert consultation. The second phase conducted a pilot survey. The third phase carried out a formal survey to test reliability and validity, involving 369 participants from 9 primary health care institutions. Results The final scale included 32 items under 7 dimensions. For reliability, the Cronbach α coefficients among dimensions varied from 0.754 to 0.926, and the Cronbach α for the scale was 0.940. For content validity, the corrected item-level content validity varied between 0.64 and 1, the scale-level content validity index/universal agreement was 0.625, and the scale-level content validity index/average was 0.93. For construct validity, the Spearman correlations of dimension-total score varied between 0.129 and 0.851, all Spearman correlations of the dimension-total score were greater than that of interdimensions and the Spearman correlations of item-total score ranged from 0.042 to 0.775. The results of the confirmatory factor analysis indicated that the model fitted well. Conclusions The Patient Safety Culture Scale for Chinese primary health care institutions demonstrated good reliability and acceptable validity; thus, it can be used as an assessment instrument for patient safety culture in Chinese primary health care institutions.

Ecosystem water use efficiency (WUE) is a key indicator that depicts the carbon-water coupling relationship in terrestrial ecosystems. Separating the effects of climate change and human activities to the variation in WUE are essential for water resources and ecosystem management, especially for fragile ecosystems such as the Tibetan Plateau (TP). In this study, we introduced an analytical framework that combined the attribution approach with the elastic coefficient separation method to assess the impact of climate change and human activities on WUE variation in the TP from 1982 to 2015. The results are the following: (1) the multiyear mean annual WUE over the TP was 0.65 g C·kg−1 H2O and had a slightly increasing trend with a slope of 0.004 g C·kg−1 H2O yr−1 with about 87% of the vegetated area showed increasing trend. (2) WUE was positively correlated with temperature, precipitation and air pressure. The northwest TP tends to be a water-limited condition, while the thermal stress is spatially universal in the TP, climate warming and wetting promoted the gross primary productivity (GPP) and WUE enhancement in the TP. (3) WUE was more sensitive to GPP, and variation in WUE was mainly contributed by GPP. Climate change and human activities tend to cause more variations in GPP rather than evapotranspiration (ET), but great differences exist for different regions and vegetation types. (4) There was a good consistency between the WUE variation calculated by the framework and the actual WUE variation (R2 = 0.95). Climate change dominated the increase of WUE in the TP with a contribution rate of 79.8%, while human activities tend to reduce WUE (−20.2%). Ecological projects played a positive role in the ecological restoration of the TP, but there may be other human activities, which caused ecological degradation, that may need more attention in future ecological protections.

Background: The outbreak of COVID-19 is a global concern Positive 2019-nCoV nucleic acid results were reported in discharged patients, arousing the question of

Climate variability and anthropogenic regulations are two interwoven factors in the ecohydrologic system across large basins. Understanding the roles that these two factors play under various hydrologic conditions is of great significance for basin hydrology and sustainable water utilization. In this study, we present an analytical approach based on coupling water balance method and Budyko hypothesis to derive effectiveness coefficients (ECs) of climate change, as a way to disentangle contributions of it and human activities to the variability of river discharges under different hydro-transitional situations. The climate dominated streamflow change ( Δ Q c ) by EC approach was compared with those deduced by the elasticity method and sensitivity index. The results suggest that the EC approach is valid and applicable for hydrologic study at large basin scale. Analyses of various scenarios revealed that contributions of climate change and human activities to river discharge variation differed among the regions of the study area. Over the past several decades, climate change dominated hydro-transitions from dry to wet, while human activities played key roles in the reduction of streamflow during wet to dry periods. Remarkable decline of discharge in upstream was mainly due to human interventions, although climate contributed more to runoff increasing during dry periods in the semi-arid downstream. Induced effectiveness on streamflow changes indicated a contribution ratio of 49% for climate and 51% for human activities at the basin scale from 1956 to 2015. The mathematic derivation based simple approach, together with the case example of temporal segmentation and spatial zoning, could help people understand variation of river discharge with more details at a large basin scale under the background of climate change and human regulations.

Fast-growing metal-accumulating woody plants are considered potential candidates for phytoremediation of metals. Tonglushan mining, one of the biggest Cu production bases in China, presents an important source of the pollution of environment. The sample was collected at Tonglushan ancient copper spoil heap. The aims were to measure the content of heavy metal in the soil and woody plants and to elucidate the phytoremediation potential of the plants. The result showed that soil Cu, Cd and Pb were the main contamination, the mean contents of which were 3166.73 mg/kg, 3.66 mg/kg and 137.06 mg/kg respectively, which belonged to severe contamination. Fourteen species from 14 genera of 13 families were collected and investigated; except for Ligutrum lucidum, the other 13 woody plants species were newly recorded in this area. In addition, to assess the ability of metal accumulation of these trees, we proposed accumulation index. Data suggested that Platanus × acerilolia, Broussonetia papyrifera, Ligutrum lucidum, Viburnum awabuki, Firmiana simplex, Robina pseudoacacia, Melia azedarach and Osmanthus fragrans exhibited high accumulated capacity and strong tolerance to heavy metals. Therefore, Platanus × acerilolia and Broussonetia papyrifera can be planted in Pb contaminated areas; Viburnum awabuki, Firmiana simplex, Robina pseudoacacia and Melia azedarach are the suitable trees for Cd contaminated areas; Viburnum awabuki, Melia azedarach, Ligutrum lucidum, Firmiana simplex, Osmanthus fragrans and Robina pseudoacacia are appropriate to Cu, Pb and Cd multi-metal contaminated areas.

ObjectiveThe purpose of our study is to develop a mental workload scale for physicians in China and assess the scale’s reliability and validity.DesignThe instrument was developed over three phases involving 396 physicians from different tiers of comprehensive public hospitals in China. In the first phase, an initial item pool was developed through a systematic literature review. The second phase consisted of two rounds of Delphi expert consultations and a pilot survey. The third phase tested the reliability and validity of the instrument.SettingPublic hospitals in China.ParticipantsA total of 396 physicians from different tiers of comprehensive public hospitals in China participated in this study in 2018.Primary and secondary outcome measuresCronbach’s α, content validity index, item-total score correlation coefficient, dimension-total score correlation coefficient and indices of confirmatory factor analysis.ResultsSix dimensions (mental demands, physical demands, temporal demands, perceived risk, frustration level and performance) and 12 items were identified in the instrument. For reliability, Cronbach’s α for the whole scale was 0.81. For validity, the corrected item-content validity index of each item ranged from 0.85 to 1, item-total score correlation coefficients ranged from 0.31 to 0.75, and the correlation coefficients between the dimensions and total score ranged from 0.37 to 0.72. The results of the confirmatory factor analysis showed that the goodness-of-fit indices of the scale were satisfactory.ConclusionThe instrument showed good reliability and validity, and it is useful for diagnosing the mental workload of physicians.

Highlights • Most of the patients with COVID-19 who need to be admitted to hospital are older. • Older patients with COVID-19 had much more co-morbidity, complications and mortality. • Age, SOFA score, APACHEⅡ score, platelet count＜125 × 109/L, d-dimer, creatinine＞133 μmol/L, interleukin-6, and lung consolidation on admission were independent risk factors for severe cases among older patients with COVID-19. • More attention should be paid to older patients with COVID-19., Objectives Much of the previous research on COVID-19 was based on all population. But substantial numbers of severe episodes occur in older patients. There is a lack of data about COVID-19 in older adults. The aims of this study were to analyze the clinical characteristics of older adult patients with COVID-19. Methods Retrospective study of older patients hospitalized with COVID-19 from February 1 st to March 31 st, 2020 was conducted in the Sino-French New City Branch of Tongjing Hospital in Wuhan, China. According to the degree of severity of COVID-19 during hospitalization, 312 older patients were divided into non-severe and severe cases. Results the mean age of the patients was 69.2 ± 7.3 years, and 47.4 % of patients had exposure history. 77.2 % of patients had a co-morbidity, with hypertension being the most common (57.1 %), followed by diabetes (38.8 %) and cardiovascular disease (29.8 %). Multivariable regression showed increasing odds of severe COVID-19 associated with age(OR 1.59, 95 %CI 1.13−2.08), SOFA score(OR 5.89, 95 %CI 3.48−7.96), APACHEⅡ score(OR 3.13, 95 %CI 1.85−5.62), platelet count＜125 × 109/L(OR 2.36, 95 %CI 1.03−4.14), d-dimer (OR 4.37, 95 %CI 2.58−7.16), creatinine＞133 μmol/L(OR 1.85, 95 %CI 1.12−3.04), interleukin-6(OR 4.32, 95 %CI 2.07−7.13), and lung consolidation(OR 1.94, 95 %CI 1.45−4.27) on admission. The most common complication was acute respiratory distress syndrome (35.6 %), followed by acute cardiac injury (33.0 %) and coagulation disorders (30.8 %). 91.7 % of patients were prescribed antiviral therapy, followed by immune globulin (52.9 %) and systemic glucocorticoids (43.6 %). 21.8 % of patients received invasive ventilation, 1.92 % for extracorporeal membrane oxygenation. The overall mortality was 6.73 %, and mortality of severe patients was 17.1 %, which was higher than non-severe patients (0.962 %). Conclusions Older patients with COVID-19 had much more co-morbidity, complications and mortality. More attention should be paid to older patients with COVID-19.

Deep learning methods have been developed and widely used in land use classification with remote sensing images. In addition, due to the different datasets used in different studies, there is a lack of direct comparison between different deep learning model applications in land use classification. The open source dataset DeepSat was used to build and test a convolutional neural network (CNN) model. The convolution kernels in the model were extracted to further study the specific features learned by the deep learning model. In addition, different CNN-based models were compared to explore the impacts of model structures on model accuracy. The major conclusions from the research are: (1) CNN model is effective in land use classification, with an accuracy of 0.9998 and 0.9991 for the SAT-4 and SAT-6 data, respectively; (2) CNN does have a “learning” ability that can extract the most critical and effective information from training datasets; and (3) for remote sensing land use classification, increasing the number of convolution kernels is better than adding more convolutional layers. Max pooling is better than average pooling. In addition, a localized response normalized layer can also improve model accuracy.

Hospitals are struggling to involve patients and learn from their experience. The risk factor of patient experience is increasingly recognized as a critical component in improving patient experience. Our study explored risk factors of negative patient experience in order to improve the health-service quality of public hospitals. We conducted a cross-sectional study in Hubei province, China. A total of 583 respondents were surveyed by the Outpatient Experience Questionnaire with good validity and reliability in July 2015. T-tests were conducted to compare the experience scores among different outpatient groups. Multiple linear regression was performed to determine the significant factors that influenced the outpatient experience. Outpatients between 18 and 44 years old had the lowest experience scores (65.89 ± 0.79), whereas outpatients completely paying out-of-pocket had the lowest experience scores (64.68 ± 0.81) among all participants. Outpatients with poor self-rated health status had the lowest experience scores (66.14 ± 1.61) among different self-rated health status groups. While age, type of payment, and self-rated health status were significantly risk factors that influenced outpatient experience in the multiple linear regression. Thus, health-care providers should pay more attention to outpatients who are young (age

We crossed Luyuan343, containing the Gossypium barbadense (GB) genomic component, with Lumianyan22, a high-yielding Gossypium hirsutum (GH) variety, to evaluate the introgressive exogenous genomic components that contribute to fiber quality in upland cotton. A total of 158 of 334 mapping simple sequence repeats (SSR) loci screened from 18,467 SSR primer pairs were identified as putative GB introgression loci. Twenty-four quantitative trait loci (QTLs) for fiber quality and lint percentage were detected by WinQTLCart 2.5 based on three phenotypic datasets collected over 2 years in two different locations. Of these QTLs, 20 were mapped in the introgression chromosomal regions; the GB alleles contributed to improved fiber quality at eight loci, which were located in the introgression segments of chromosome (Chr.) 3, Chr.7 and Chr.25. A total of eight digenic epistasis and nine significant QTL × environment (QE) interactions were identified by QTLNetwork-2.2. Fiber elongation was found to be most easily influenced by environment since all QTLs for this trait showed significant QE interaction with large effects. Fiber length, fiber strength, and lint percentage were scarcely affected by environment as no or minor QE interaction effects for these traits were detected. Genome-wide identification of the introgressive GB components and mapping of the fiber-related QTLs indentified in this study will be beneficial for the simultaneous marker-assistant selection of improved fiber quality and lint yield in upland cotton breeding.

The germplasm with exotic genomic components especially from Sea Island cotton (Gossypium barbadense L. Gb) is the dominant genetic resources to enhance fiber quality of upland cotton (G. hirsutum L., Gh). Due to low efficiency of phenotypic evaluation and selection on fiber quality, genetic dissection of favorable alleles using molecular markers is essential. Genetic dissection on putative Gb introgressions related to fiber traits were conducted by SSR markers with mapping populations derived from a cross between Luyuan343 (LY343), a superior fiber quality introgression line (IL) with genomic components from Gb, and an elite Upland cotton cv. Lumianyan#22 (LMY22). Among 82 polymorphic loci screened out from 4050 SSRs, 42 were identified as putative introgression alleles. A total of 29 fiber-related QTLs (23 for fiber quality and six for lint percentage) were detected and most of which clustered on the putative Gb introgression chromosomal segments of Chr.2, Chr.16, Chr.23 and Chr.25. As expected, a majority of favorable alleles of fiber quality QTLs (12/17, not considering the QTLs for fiber fineness) came from the IL parent and most of which (11/12) were conferred by the introgression genomic components while three of the six (3/6) favorable alleles for lint percentage came from the Gh parent. Validation of these QTLs using an F8 breeding population from the same cross made previously indicated that 13 out of 29 QTLs showed considerable stability. The results suggest that fiber quality improvement using the introgression components could be facilitated by marker-assisted selection in cotton breeding program.