Ambient fine particulate matter and daily mortality: a comparative analysis of observed and estimated exposure in 347 cities.

BACKGROUND: Model-estimated air pollution exposure products have been widely used in epidemiological studies to assess the health risks of particulate matter with diameters of ≤2.5 µm (PM2.5). However, few studies have assessed the disparities in health effects between model-estimated and station-observed PM2.5 exposures. METHODS: We collected daily all-cause, respiratory and cardiovascular mortality data in 347 cities across 15 countries and regions worldwide based on the Multi-City Multi-Country collaborative research network. The station-observed PM2.5 data were obtained from official monitoring stations. The model-estimated global PM2.5 product was developed using a machine-learning approach. The associations between daily exposure to PM2.5 and mortality were evaluated using a two-stage analytical approach. RESULTS: We included 15.8 million all-cause, 1.5 million respiratory and 4.5 million cardiovascular deaths from 2000 to 2018. Short-term exposure to PM2.5 was associated with a relative risk increase (RRI) of mortality from both station-observed and model-estimated exposures. Every 10-µg/m3 increase in the 2-day moving average PM2.5 was associated with overall RRIs of 0.67% (95% CI: 0.49 to 0.85), 0.68% (95% CI: -0.03 to 1.39) and 0.45% (95% CI: 0.08 to 0.82) for all-cause, respiratory, and cardiovascular mortality based on station-observed PM2.5 and RRIs of 0.87% (95% CI: 0.68 to 1.06), 0.81% (95% CI: 0.08 to 1.55) and 0.71% (95% CI: 0.32 to 1.09) based on model-estimated exposure, respectively. CONCLUSIONS: Mortality risks associated with daily PM2.5 exposure were consistent for both station-observed and model-estimated exposures, suggesting the reliability and potential applicability of the global PM2.5 product in epidemiological studies.

Pain Intensity and Satisfaction of Pain Relief in Discharged Cancer Patients: A Large Sample Study in China.

BACKGROUND: Many studies have focused on the quality of pain management in hospitalized patients with cancer pain, while what happens after discharge remains unclear. AIM: The purpose of this study was to investigate the pain intensity and satisfaction of pain relief among a large sample of Chinese patients with cancer pain after discharge. DESIGN: Cross-sectional, descriptive, correlational research. SETTINGS AND SAMPLE: ABOUT: 1,013 patients were recruited in a tertiary cancer hospital, and their residence addresses were distributed in 6 geographical regions, including 26 provinces, municipalities, and autonomous regions. METHODS: The 1,013 patients with cancer pain were discharged from the wards of a national cancer hospital in China from July 2020 to October 2021. A nurse in the pain clinic followed the patients based on a whole-process information system and collected the data after the cancer pain patients were discharged. The study methods followed the STROBE guidelines. RESULTS: The average age of 1,013 discharged patients was 61.30 (±12.56) years. Moderate and severe background pain (BGP) was reported in 749 patients (73.94%), and more than 3 instances of breakthrough pain (BTP) in the past 24 hours were reported in 541 patients (53.41%). More severe BGP was associated with more frequent BTP (p < .01). In addition, there were 572 patients (56.47%) whose satisfaction with pain relief was lower than 70%. More severe BGP was associated with a lower satisfaction degree (r = -0.796, p < .01). CONCLUSIONS: Pain among discharged Chinese patients with cancer is poorly managed, and there is a low degree of satisfaction with pain relief. Nurses can do more work to assist cancer patients in managing pain more effectively by ensuring they have a plan to report and manage pain after discharge.

Effect of different strains on quality characteristics of soy yogurt: Physicochemical, nutritional, safety features, sensory, and formation mechanism.

The purpose of the study was to explore effect of four different strains on quality characteristics of soy yogurt. The results showed that four strains were all related to the genus Lactobacillus and N1 was Lacticaseibacillus rhamnosus, N2 was Lacticaseibacillus paracasei, N3 was Lacticaseibacillus plantarum, and N4 was Lacticaseibacillus acidophilus. The result analysis of biochemical, sensory, nutritional, functional and safety properties of fermentation process and end products showed that the soy yogurt fermented with L. rhamnosus N1 had the highest isoflavone content and the lowest phytic acid content; the soy yogurt fermented with L. paracasei N2 had the highest content of free amino acids and oligosaccharides, the lowest content of trypsin inhibitors; the soy yogurt fermented with L. plantarum N3 had the lowest oil content; the soy yogurt fermented with L. acidophilus N4 had optimal functional properties. In summary, N4 was suitable as a fermentation strain for soymilk.

Fine-grained image classification on bats using VGG16-CBAM: a practical example with 7 horseshoe bats taxa (CHIROPTERA: Rhinolophidae: Rhinolophus) from Southern China.

BACKGROUND: Rapid identification and classification of bats are critical for practical applications. However, species identification of bats is a typically detrimental and time-consuming manual task that depends on taxonomists and well-trained experts. Deep Convolutional Neural Networks (DCNNs) provide a practical approach for the extraction of the visual features and classification of objects, with potential application for bat classification. RESULTS: In this study, we investigated the capability of deep learning models to classify 7 horseshoe bat taxa (CHIROPTERA: Rhinolophus) from Southern China. We constructed an image dataset of 879 front, oblique, and lateral targeted facial images of live individuals collected during surveys between 2012 and 2021. All images were taken using a standard photograph protocol and setting aimed at enhancing the effectiveness of the DCNNs classification. The results demonstrated that our customized VGG16-CBAM model achieved up to 92.15% classification accuracy with better performance than other mainstream models. Furthermore, the Grad-CAM visualization reveals that the model pays more attention to the taxonomic key regions in the decision-making process, and these regions are often preferred by bat taxonomists for the classification of horseshoe bats, corroborating the validity of our methods. CONCLUSION: Our finding will inspire further research on image-based automatic classification of chiropteran species for early detection and potential application in taxonomy.

Huperzine A ameliorates neurological deficits after spontaneous subarachnoid hemorrhage through endothelial cell pyroptosis inhibition.

Spontaneous subarachnoid hemorrhage (SAH) is a kind of hemorrhagic stroke which causes neurological deficits in survivors. Huperzine A has a neuroprotective effect, but its role in SAH is unclear. Therefore, we explore the effect of Huperzine A on neurological deficits induced by SAH and the related mechanism. In this study, Evans blue assay, TUNEL staining, immunofluorescence, western blot analysis, and ELISA are conducted. We find that Huperzine A can improve neurological deficits and inhibit the apoptosis of nerve cells in SAH rats. Huperzine A treatment can improve the upregulation of brain water content, damage of blood-brain barrier, fibrinogen and matrix metalloprotein 9 expressions and the downregulation of ZO-1 and occludin expressions induced by SAH. Huperzine A inhibit the expressions of proteins involved in pyroptosis in endothelial cells in SAH rats. The increase in MDA content and decrease in SOD activity in SAH rats can be partly reversed by Huperzine A. The ROS inducer H 2O 2 can induce pyroptosis and inhibit the expressions of ZO-1 and occludin in endothelial cells, which can be blocked by Huperzine A. In addition, the increase in the entry of p65 into the nucleus in endothelial cells can be partly reversed by Huperzine A. Huperzine A may delay the damage of blood-brain barrier in SAH rats by inhibiting oxidative stress-mediated pyroptosis and tight junction protein expression downregulation through the NF-κB pathway. Overall, Huperzine A may have clinical value for treating SAH.

Advancements in hospice and palliative care in China: A five-year review.

In response to the challenges posed by an aging population, an increasing cancer incidence, and the growing demand for hospice care services, China has actively promoted the development of hospice and palliative care, achieving significant progress in the past five years. This article provides a retrospective analysis of the efforts and accomplishments in the field of hospice and palliative care in China, focusing on government policy support, quality standards and regulations, drug management, health provider training, and public education. Additionally, the study explores the current issues and challenges in the field.

The Concentration of Lactoferrin in Breast Milk Correlates with Maternal Body Mass Index and Parity.

Background: Lactoferrin (LF) is a multifunctional glycoprotein found in human milk and body fluids, which has been shown to play a vital role in regulating the immunity and supporting the intestinal health of infants. Aim: This study evaluated the association between maternal/parturient factors and LF concentration in the breast milk of Chinese mothers. Methods: 207 breast milk samples were collected from healthy mothers with in the first year of lactation. Maternal and parturient information was collected for these participants through questionnaires. The content of lactoferrin in breast milk was detected by liquid chromatography, and macronutrient concentration in breast milk was measured by human milk analyzer in only 109 samples. Results: Our findings demonstrated that the LF content was much higher within the first month of lactation than it was after that period (p < 0.05). When compared with normal and lean mothers, the LF content of obese mothers was considerably higher (p < 0.05). The parity and LF content showed a favorable correlation. The proportion of LF to total protein tended to decrease as lactation progressed. Protein, fat, dry matter, and energy content were significantly positively correlated with LF content (p < 0.001). Conclusion: Early breast milk tends to have a higher level of LF, and the change of LF concentration in breast milk is associated with the parity and body mass index of the mother.

Estimates of global mortality burden associated with short-term exposure to fine particulate matter (PM2·5).

BACKGROUND: The acute health effects of short-term (hours to days) exposure to fine particulate matter (PM2·5) have been well documented; however, the global mortality burden attributable to this exposure has not been estimated. We aimed to estimate the global, regional, and urban mortality burden associated with short-term exposure to PM2·5 and the spatiotemporal variations in this burden from 2000 to 2019. METHODS: We combined estimated global daily PM2·5 concentrations, annual population counts, country-level mortality rates, and epidemiologically derived exposure-response functions to estimate the mortality attributable to short-term PM2·5 exposure from 2000 to 2019, in the continental regions and in 13 189 urban centres worldwide at a spatial resolution of 0·1°â€ˆ× 0·1°. We tested the robustness of our mortality estimates with different theoretical minimum risk exposure levels, lag effects, and exposure-response functions. FINDINGS: Approximately 1 million (95% CI 690 000-1·3 million) premature deaths per year from 2000 to 2019 were attributable to short-term PM2·5 exposure, representing 2·08% (1·41-2·75) of total global deaths or 17 (11-22) premature deaths per 100 000 population. Annually, 0·23 million (0·15 million-0·30 million) deaths attributable to short-term PM2·5 exposure were in urban areas, constituting 22·74% of the total global deaths attributable to this cause and accounting for 2·30% (1·56-3·05) of total global deaths in urban areas. The sensitivity analyses showed that our worldwide estimates of mortality attributed to short-term PM2·5 exposure were robust. INTERPRETATION: Short-term exposure to PM2·5 contributes a substantial global mortality burden, particularly in Asia and Africa, as well as in global urban areas. Our results highlight the importance of mitigation strategies to reduce short-term exposure to air pollution and its adverse effects on human health. FUNDING: Australian Research Council and the Australian National Health and Medical Research Council.

Is model-estimated PM2.5 exposure equivalent to station-observed in mortality risk assessment? A literature review and meta-analysis.

Model-estimated air pollution exposure assessments have been extensively employed in the evaluation of health risks associated with air pollution. However, few studies synthetically evaluate the reliability of model-estimated PM2.5 products in health risk assessment by comparing them with ground-based monitoring station air quality data. In response to this gap, we undertook a meticulously structured systematic review and meta-analysis. Our objective was to aggregate existing comparative studies to ascertain the disparity in mortality effect estimates derived from model-estimated ambient PM2.5 exposure versus those based on monitoring station-observed PM2.5 exposure. We conducted searches across multiple databases, namely PubMed, Scopus, and Web of Science, using predefined keywords. Ultimately, ten studies were included in the review. Of these, seven investigated long-term annual exposure, while the remaining three studies focused on short-term daily PM2.5 exposure. Despite variances in the estimated Exposure-Response (E-R) associations, most studies revealed positive associations between ambient PM2.5 exposure and all-cause and cardiovascular mortality, irrespective of the exposure being estimated through models or observed at monitoring stations. Our meta-analysis revealed that all-cause mortality risk associated with model-estimated PM2.5 exposure was in line with that derived from station-observed sources. The pooled Relative Risk (RR) was 1.083 (95% CI: 1.047, 1.119) for model-estimated exposure, and 1.089 (95% CI: 1.054, 1.125) for station-observed sources (p = 0.795). In conclusion, most model-estimated air pollution products have demonstrated consistency in estimating mortality risk compared to data from monitoring stations. However, only a limited number of studies have undertaken such comparative analyses, underscoring the necessity for more comprehensive investigations to validate the reliability of these model-estimated exposure in mortality risk assessment.

Intervention on Mathematics Self-Efficacy: Solution-Focused Brief Therapy.

Purpose: Research has demonstrated a strong correlation between mathematics self-efficacy and math performance. Middle school children are increasingly receiving solution-focused brief therapy (SFBT), which is a type of psychotherapy. The study intends to use SFBT intervention to improve mathematics self-efficacy of students and to determine whether SFBT intervention was effective. To examine whether Rasch model can be used to evaluate students' mathematics self-efficacy. Methods: This study intends to use Radar chart, Rasch model, Line chart to measure the variations of mathematics self-efficacy of three 8th graders (n=3) during SFBT intervention. Results: Radar chart and Rasch model demonstrated a general increment in the mathematics self-efficacy of two pupils, while another one decreased. Additionally, three students showed a decline in their mathematics self-efficacy on particular mathematical problems using a line chart. Conclusion: Overall, students with varied degrees of self-efficacy in math benefited from SFBT interventions, which partially supports the usefulness of SFBT as a tool for assessing students' mathematics self-efficacy. It supported that Rasch model can reflected the changes in students' mathematics self-efficacy. This study provides guidance for measuring the improvement of students' academic self-efficacy through SFBT intervention using Rasch model.

Tropical cyclone-specific mortality risks and the periods of concern: A multicountry time-series study.

BACKGROUND: More intense tropical cyclones (TCs) are expected in the future under a warming climate scenario, but little is known about their mortality effect pattern across countries and over decades. We aim to evaluate the TC-specific mortality risks, periods of concern (POC) and characterize the spatiotemporal pattern and exposure-response (ER) relationships on a multicountry scale. METHODS AND FINDINGS: Daily all-cause, cardiovascular, and respiratory mortality among the general population were collected from 494 locations in 18 countries or territories during 1980 to 2019. Daily TC exposures were defined when the maximum sustained windspeed associated with a TC was ≥34 knots using a parametric wind field model at a 0.5° × 0.5° resolution. We first estimated the TC-specific mortality risks and POC using an advanced flexible statistical framework of mixed Poisson model, accounting for the population changes, natural variation, seasonal and day of the week effects. Then, a mixed meta-regression model was used to pool the TC-specific mortality risks to estimate the overall and country-specific ER relationships of TC characteristics (windspeed, rainfall, and year) with mortality. Overall, 47.7 million all-cause, 15.5 million cardiovascular, and 4.9 million respiratory deaths and 382 TCs were included in our analyses. An overall average POC of around 20 days was observed for TC-related all-cause and cardiopulmonary mortality, with relatively longer POC for the United States of America, Brazil, and Taiwan (>30 days). The TC-specific relative risks (RR) varied substantially, ranging from 1.04 to 1.42, 1.07 to 1.77, and 1.12 to 1.92 among the top 100 TCs with highest RRs for all-cause, cardiovascular, and respiratory mortality, respectively. At country level, relatively higher TC-related mortality risks were observed in Guatemala, Brazil, and New Zealand for all-cause, cardiovascular, and respiratory mortality, respectively. We found an overall monotonically increasing and approximately linear ER curve of TC-related maximum sustained windspeed and cumulative rainfall with mortality, with heterogeneous patterns across countries and regions. The TC-related mortality risks were generally decreasing from 1980 to 2019, especially for the Philippines, Taiwan, and the USA, whereas potentially increasing trends in TC-related all-cause and cardiovascular mortality risks were observed for Japan. CONCLUSIONS: The TC mortality risks and POC varied greatly across TC events, locations, and countries. To minimize the TC-related health burdens, targeted strategies are particularly needed for different countries and regions, integrating epidemiological evidence on region-specific POC and ER curves that consider across-TC variability.

Altered brain function in classical trigeminal neuralgia patients: ALFF, ReHo, and DC static- and dynamic-frequency study.

The present study aimed to clarify the brain function of classical trigeminal neuralgia (CTN) by analyzing 77 CTN patients and age- and gender-matched 73 healthy controls (HCs) based on three frequency bands of the static and dynamic amplitude of low-frequency fluctuation, regional homogeneity, and degree centrality (sALFF, sReHo, sDC, dALFF, dReHo, and dDC). Compared to HCs, the number of altered brain regions was different in three frequency bands, and the classical frequency band was most followed by slow-4 in CTN patients. Cerrelellum_8_L (sReHo), Cerrelellum_8_R (sDC), Calcarine_R (sDC), and Caudate_R (sDC) were found only in classical frequency band, while Precuneus_L (sALFF) and Frontal_Inf_Tri_L (sReHo) were found only in slow-4 frequency band. Except for the above six brain regions, the others overlapped in the classical and slow-4 frequency bands. CTN seriously affects the mental health of patients, and some different brain regions are correlated with clinical parameters. The static and dynamic indicators of brain function were complementary in CTN patients, and the changing brain regions showed frequency specificity. Compared to slow-5 frequency band, slow-4 is more consistent with the classical frequency band, which could be valuable in exploring the pathophysiology of CTN.

Temporal change of serum xanthine oxidase levels and its relation to clinical outcome of severe traumatic brain injury: a prospective cohort study.

Xanthine oxidase (XO) may be involved in the induction of oxidative stress and inflammation. We measured serum XO levels at multiple days to determine whether it is associated with the severity and prognosis of severe traumatic brain injury (sTBI). In this prospective cohort study, we quantified serum XO levels in 112 sTBI patients and 112 controls. Serum XO levels of patients were measured at admission and at days 1, 3, 5, 7, and 10 after sTBI. Extended Glasgow outcome scale scores of 1-4 at post-trauma 180 days were defined as a poor prognosis. Multivariate analysis was employed to determine the relationship between poor prognosis and serum XO levels at multiple days. Serum XO levels were significantly increased at admission among patients, afterwards elevated gradually, peaked at day 3, and then diminished gradually until day 10, and were substantially higher during 10 days in patients than in controls. Serum XO levels at 6 different days were all correlated with admission Rotterdam computed tomography (CT) scores and Glasgow coma scale (GCS) scores. Serum XO levels at 6 different days were all substantially higher in patients with poor prognosis than in those with good prognosis. Serum XO levels at days 7 and 10, but not at days 1, 3, and 5, had significantly lower area under receiver operating characteristic (AUC) than those at admission. Serum XO levels at admission and at days 1 and 3, but not at day 5, were independently associated with 180-day poor prognosis. Prognostic prediction model containing GCS scores, Rotterdam CT scores, and serum XO levels at admission (or at days 1 and 3) showed substantially higher AUC than GCS scores and Rotterdam CT scores alone. The models were visually described using nomograms, which were comparatively stable under calibration curve and were relatively of clinical benefit under decision curve. Elevated serum XO levels during early period of sTBI are more closely associated with trauma severity and clinical adverse outcomes, assuming that serum XO may serve as a potential prognostic biomarker in sTBI.

A prospective cohort study on serum A20 as a prognostic biomarker of aneurysmal subarachnoid hemorrhage.

BACKGROUND: A20 may be a neuroprotective factor. Herein, we aimed to investigate whether serum A20 levels were associated with disease severity, delayed cerebral ischemia (DCI), and outcome after aneurysmal subarachnoid hemorrhage (aSAH). METHODS: In this prospective cohort study containing 112 aSAH patients and 112 controls, serum A20 levels were quantified. At 90 d poststroke, Modified Rankin Scale (MRS) scores ≥3 were defined as a poor outcome. All correlations and associations were assessed using multivariate analysis. RESULTS: Compared with controls, there was a significant elevation of serum A20 levels in patients (median 123.7 pg/mL vs. 25.8 pg/mL; P<0.001). Serum A20 levels were independently correlated with Hunt-Hess scores (ß 9.854; 95% confidence interval [95% CI] 2.481-17.227, P=0.009) and modified Fisher scores (ß 10.349, 95% CI 1.273-19.424, P=0.026). Independent associations were found between serum A20 levels and poor outcome (odds ratio [OR] 1.015, 95% CI 1.000-1.031, P=0.047) and DCI (OR 1.018, 95% CI 1.001-1.035, P=0.042). Areas under the curve for predicting poor outcome and DCI were 0.771 (95% CI 0.682-0.845) and 0.777 (95% CI 0.688-0.850), respectively. Serum A20 levels ≥128.15 pg/mL predicted poor outcome, with a sensitivity of 73.9% and specificity of 74.2%, and A20 levels ≥160.55 pg/mL distinguished the risk of DCI with 65.5% sensitivity and 89.2% specificity. Its ability to predict poor outcome and DCI was similar to those of Hunt-Hess scores and modified Fisher scores (both P>0.05). CONCLUSION: Enhanced serum A20 levels are significantly associated with stroke severity and poor clinical outcome after aSAH, implying that serum A20 may be a potential prognostic biomarker for aSAH.

A fast and accurate identification model for Rhinolophus bats based on fine-grained information.

Bats are a crucial component within ecosystems, providing valuable ecosystem services such as pollination and pest control. In practical conservation efforts, the classification and identification of bats are essential in order to develop effective conservation management programs for bats and their habitats. Traditionally, the identification of bats has been a manual and time-consuming process. With the development of artificial intelligence technology, the accuracy and speed of identification work of such fine-grained images as bats identification can be greatly improved. Bats identification relies on the fine features of their beaks and faces, so mining the fine-grained information in images is crucial to improve the accuracy of bats identification. This paper presents a deep learning-based model designed for the rapid and precise identification of common horseshoe bats (Chiroptera: Rhinolophidae: Rhinolophus) from Southern China. The model was developed by utilizing a comprehensive dataset of 883 high-resolution images of seven distinct Rhinolophus species which were collected during surveys conducted between 2010 and 2022. An improved EfficientNet model with an attention mechanism module is architected to mine the fine-grained appearance of these Rhinolophus. The performance of the model beat other classical models, including SqueezeNet, AlexNet, VGG16_BN, ShuffleNetV2, GoogleNet, ResNet50 and EfficientNet_B0, according to the predicting precision, recall, accuracy, F1-score. Our model achieved the highest identification accuracy of 94.22% and an F1-score of 0.948 with low computational complexity. Heat maps obtained with Grad-CAM show that our model meets the identification criteria of the morphology of Rhinolophus. Our study highlights the potential of artificial intelligence technology for the identification of small mammals, and facilitating fast species identification in the future.

Global population exposure to landscape fire air pollution from 2000 to 2019.

Wildfires are thought to be increasing in severity and frequency as a result of climate change1-5. Air pollution from landscape fires can negatively affect human health4-6, but human exposure to landscape fire-sourced (LFS) air pollution has not been well characterized at the global scale7-23. Here, we estimate global daily LFS outdoor fine particulate matter (PM2.5) and surface ozone concentrations at 0.25° × 0.25° resolution during the period 2000-2019 with the help of machine learning and chemical transport models. We found that overall population-weighted average LFS PM2.5 and ozone concentrations were 2.5 µg m-3 (6.1% of all-source PM2.5) and 3.2 µg m-3 (3.6% of all-source ozone), respectively, in 2010-2019, with a slight increase for PM2.5, but not for ozone, compared with 2000-2009. Central Africa, Southeast Asia, South America and Siberia experienced the highest LFS PM2.5 and ozone concentrations. The concentrations of LFS PM2.5 and ozone were about four times higher in low-income countries than in high-income countries. During the period 2010-2019, 2.18 billion people were exposed to at least 1 day of substantial LFS air pollution per year, with each person in the world having, on average, 9.9 days of exposure per year. These two metrics increased by 6.8% and 2.1%, respectively, compared with 2000-2009. Overall, we find that the global population is increasingly exposed to LFS air pollution, with socioeconomic disparities.

Structural Properties of Quinoa Protein Isolate: Impact of Neutral to High Alkaline Extraction pH.

In this work, we extracted proteins from white quinoa cultivated in the northeast of Qinghai-Tibet plateau using the method of alkaline solubilization and acid precipitation, aiming to decipher how extraction pH (7-11) influenced extractability, purity and recovery rate, composition, multi-length scale structure, and gelling properties of quinoa protein isolate (QPI). The results showed that protein extractability increased from 39 to 58% with the increment of pH from 7 to 11 whereas protein purity decreased from 89 to 82%. At pH 7-11, extraction suspensions and QPI showed the similar major bands in SDS-PAGE with more minor ones (e.g., protein fractions at > 55 or 25-37 kDa) in suspensions. Extraction pH had limited effect on the secondary structure of QPI. In contrast, the higher-order structures of QPI were significantly affected, e.g., (1) emission maximum wavelength of intrinsic fluorescence increased with extraction pH; (2) surface hydrophobicity and the absolute value of zeta-potential increased with increasing extraction pH from 7 to 9, and then markedly decreased; (3) the particle size decreased to the lowest value at pH 9 and then increased to the highest value at pH 11; and (4) denaturation temperature of QPI had a large decrease with increasing extraction pH from 7/8 to 9/10. Besides, heat-set QPI gels were formed by loosely-connected protein aggregates, which were strengthened with increasing extraction pH. This study would provide fundamental data for industrial production of quinoa protein with desired quality.