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Clarifying the nutritional and antioxidant characteristics of introduced mulberry leaves aids development and utilization in Hexi region, China. The main nutrients and functional components of fruit and leaf mulberries, and correlations between antioxidant capacities of their leaf extracts, were investigated. Crude protein, crude fat, reduced sugar, and ash contents of leaf mulberry were significantly higher than those of fruit mulberry (P0.05). Flavonoid concentrations in leaf mulberry (50.57 mg.g−1) were significantly higher than in fruit mulberry (46.96 mg.g−1) (PCa>Mg>Na>Fe. Leaf mulberry K, Mn, Zn, Cu and Ni contents were higher than those in fruit mulberry, while the opposite holds for Ca, Mg, Na and Fe contents. The Index for Nutritional Quality (INQ) of Na, crude fat, and reduced sugar contents in fruit and leaf mulberry leaves were1. Additionally, nutrition equivalent (NEU) from leaf mulberry exceeds that of fruit mulberry. Flavones and polysaccharides in fruit mulberry have higher DPPH radical clearance activity than leaf mulberry, but flavonoids in leaf mulberry had higher radical clearance of ABTS+ than fruit mulberry. There was little difference in polysaccharide clearance of ABTS+ between the two cultivars. Highly significant positive correlations (correlation coefficients ranging 0.899~0.991) in flavonoid, rutin, polyphenol and polysaccharide content DPPH radical scavenging exist between the two cultivars. There was no significant difference in the ABTS+ free radical scavenging rate. The nutritional function and antioxidant activity of leaf mulberry exceed those of fruit mulberry, which was more suitable for the Hexi region.

Abstract Fruit acidity significantly influences fruit flavor, but the specific impact of soil pH on fruit acidity remains unclear. This study investigated the effects of various soil pH levels on fruit acidity and citric acid (CA) metabolism in lemon (Citrus limon L.). High soil pH (pH 8) decreased total soluble solids concentrations in lemon fruits, while low soil pH (pH 4) increased titratable acid and CA concentrations. Although low soil pH reduced the synthesis of CA due to the decreased citrate synthase and phosphoenolpyruvate carboxylase activities, the elevated fruit acidity under low soil pH conditions is not directly related to CA synthesis. Instead, low soil pH was found to suppress the activity of cytosolic aconitase (Cyt-ACO), an iron-dependent enzyme, indicating a potential role for CA degradation inhibition in low soil pH-induced CA accumulation. Furthermore, low soil pH significantly reduced cytosolic iron (Cyt-Fe) concentration, which was positively correlated with Cyt-ACO activity. In conclusion, low soil pH contributes to increasing fruit acidity in lemon, partially by inhibiting CA degradation due to the reduced Cyt-Fe concentrations. Our work unravels the influence of soil pH on CA accumulation and provides important clues for modulating CA levels through microelement fertilization in citrus.

Summary: Dendritic cells (DCs) express high levels of PD-L1 in the tumor microenvironment. However, the physiological functions of PD-L1 on DCs remain incompletely understood. Here, we explored the roles of PD-L1 signaling during immunogenic chemotherapy. We found that antitumor efficacy was dramatically reduced in the absence of PD-L1 on DCs. Chemotherapy reshaped the tumor immune microenvironment, particularly the DC compartment. In the absence of PD-L1, DCs were more susceptible to the cytotoxicity induced by chemotherapy. Mechanistically, loss of PD-L1 led to the downregulation of SLC7A11, resulting in increased lipid peroxidation that caused DCs to succumb to ferroptosis and dampened antitumor immune responses. Mice with Pdl1-deficient DCs were less efficient at priming T cells during chemotherapy. In cancer patients, a higher level of PD-L1 on DCs correlated with better prognosis after immunogenic chemotherapy. Collectively, these findings reveal an underappreciated role of PD-L1 in orchestrating DC survival, which is critical during chemoimmunotherapy.

The aim of this study was to investigate the global epidemiological trends in the incidence and deaths of acute respiratory infections (ARIs), encompassing both upper respiratory infections (URIs) and lower respiratory infections (LRIs), from 1990 to 2021. Using data from the Global Burden of Disease study 2021 (GBD 2021), we utilized the average annual percentage change (AAPC) to examine the trends in the age-standardized incidence rate and deaths rate (ASIR and ASDRs) of URIs and LRIs. In 2021, the global ASIR of URIs and LRIs were 166,770.73 (95 % UI: 148,098.16–189,487.93) per 100,000 and 4283.61 (95 % UI: 4057.03–4524.89) per 100,000, respectively. The highest ASIR of URIs occurred in high-sociodemographic index (SDI) regions (232744.64, 95 % UI: 206887.07–261694.81) per 100,000, whereas LRIs occurred in low-SDI regions (9261.1, 95 % UI: 8741.61–9820.86) per 100,000. In 2021, the global ASDRs of URIs and LRIs were 0.28 (95 % UI: 0.09–0.61) per 100,000 and 28.67 (95 % UI: 25.92–31.07) per 100,000, respectively. The highest ASDRs of both URIs and LRIs were observed in low-SDI regions, with 1.1 (95 % UI: 0.08–2.78) per 100,000 and 70.68 (95 % UI: 62.56–78.62) per 100,000, respectively. From 1990 to 2021, the global ASIR for URIs and LRIs decreased, with AAPCs of −0.17 % (95 % CI: 0.17 % to −0.16 %) and −1.28 % (95 % CI: −1.37 % to −1.22 %), respectively. The global ASDRs also decreased (−3.39 % for URIs; −2.46 % for LRIs). However, during the COVID-19 pandemic, the ASIR of URIs increased in many countries, especially in high-SDI regions (rate difference before and during the COVID-19 pandemic in ASIR was 2210.19 per 100,000.) and low-SDI regions (rate difference in ASIR: 111.26 per 100,000). The global incidence and deaths related to ARIs have decreased over the past 32 years. However, it remains a significant public health concern, particularly due to the notable incidence of URIs in high SDI regions and the deaths associated with both URIs and LRIs in low SDI regions. Furthermore, an increase in the incidence of URIs was observed in both high- and low-SDI regions during the COVID-19 pandemic, highlighting the need for increased attention.

In this article, we provided a comprehensive overview and in-depth analysis of global patterns and temporal trends in years lived with disability (YLDs) for musculoskeletal (MSK) disorders in individuals aged ≥70. Data on YLDs for MSK disorders in individuals aged ≥70 were obtained from the Global Burden of Disease 2019. The average annual percentage change (AAPC) was calculated to assess the temporal trends in the YLDs rate of MSK disorders. A Bayesian Age-Period-Cohort model was used to predict the YLDs rate up to the year 2040. In 2019, the global rate of YLDs for MSK disorders in individuals aged ≥70 were 4819.81 (95 % UI: 3402.91 - 6550.77) per 100,000 persons. The YLDs rate of MSK disorders in female was 1.36 times higher than that in male, and was highest in high SDI regions. From 1990 to 2019, the global YLDs rate showed a slightly downward trend (AAPC = −0.04 %, 95 % CI: −0.06 % to −0.03 %), while it significantly increased in high, low-middle, low SDI regions. Tobacco and high body mass index were the primary risk factors worldwide, while in low SDI regions, occupational risks emerged as the predominant factors. Up to 2040, the global YLDs rate of MSK disorders are expected to increase by 1.78 %, with 36.39 %, 20.66 %, 18.96 % and 5.32 % growth in other MSK disorders, rheumatoid arthritis, neck pain and osteoarthritis. MSK disorders are a significant and continuously growing public health concern among older adults. Tailored interventions should be developed for older adults, taking into account the variations across distributions, trends, and risk factors in terms of sex and SDI levels.

At present, on the one hand, domestic enterprises carry out digital transformation one after another due to the pressure of survival and development, and on the other hand, due to environmental regulations, enterprises are facing the pressure of carbon emission reduction. This paper discusses the impact of enterprises’ digital transformation on carbon emissions and finds that enterprises’ digital transformation will increase carbon emissions, mainly because technological progress will bring about more extensive use of computers in production services, and the use of fossil energy will increase carbon emissions before the energy structure is effectively improved. Even if enterprises’ digital transformation can improve of total factor productivity, it is difficult to offset the increase in carbon emissions caused by the use of more fossil energy. In addition, it is also found that for state-owned enterprises, the carbon emission pressure brought about by digital transformation is higher than that of non-state-owned enterprises; environmental regulation can significantly restrain carbon emissions. This study reveals the real impact of enterprises’ digital transformation on carbon emissions and provides a direction for enterprises to implement digital transformation and carbon emission reduction.

Abstract Background Foreign bodies (FBs) are a common emergency in medical institutions, that can occur in any area and among people of any age, which are common public health problems. Understanding the epidemiological characteristics of FBs is crucial for their prevention and control. The purpose of this study was to analyze the epidemiological characteristics of FBs worldwide through the data from the Global Burden of Disease Study 2019 (GBD 2019). Methods We obtained data from the GBD 2019, which is an important public database to understand the disease burden of FBs. Joinpoint was used to analyze temporal trends in the incidence and death trends of FBs, which is widely used to study the long-term temporal trend of the burden of diseases. SaTScan was used to detect spatial-temporal clusters of pulmonary aspiration and foreign body in the airway (PAFBA), which is based on a Poisson model, scanning the number of people and diseases in the study area to obtain the spatial-temporal clusters of diseases. Results Globally, the age-standardized incidence rate (ASIR) and the age-standardized death rate (ASDR) of FBs in 2019 were 869.23/100,000 (679.92/100,000-1120.69/100,000) and 1.55/100,000 (1.41/100,000-1.67/100,000), respectively. The ASIR and ASDR showed downtrends with average annual percent changes (AAPCs) of -0.31% and − 1.47% from 1990 to 2019. Of note, the ASIR showed an uptrend during 2010–2019, especially in high, high-middle, and middle SDI regions. Stratified analysis by age group showed that ASIR increased in each age group in recent years. From 1990 to 2019, the ASDR in the over-70 age group showed an uptrend worldwide, especially in high and high-middle SDI regions. In different types of FBs, the ASDR of PAFBA was the highest. The death burden of PAFBA was mainly clustered in 82 countries during 1993–2007, such as Canada, Cuba, and Mexico. Conclusion The most important goal is to improve public awareness and emergency knowledge of FBs through publicity methods, such as the internet or offline activities, and to improve laws and regulations. Additionally, different age groups need different targeted measures, such as strengthening the care of children, caring for elderly individuals, improving necessary monitoring programs and reporting systems, conducting effective hazard assessments, and publicity and education activities.

Objective: Understanding the global patterns of respiratory syncytial virus (RSV) is crucial for developing effective prevention and control strategies. Methods: Data on RSV-related burden were extracted from the Global Burden of Disease 2019. Joinpoint regression models were used to assess the global temporal trends of RSV and further stratified analyses were conducted according to the Socio-demographic Index (SDI), which is a composite measure of income, education, and total fertility. Age-period-cohort model was used to evaluate age, period, and cohort effects. Results: In 2019, the global age-standardized rate of mortality (ASMR) and disability-adjusted life years (ASR-DALYs) of RSV were 4.79/100,000 (95% uncertainty interval [95% UI]: 1.82/100,000-9.32/100,000) and 218.34/100,000 (95% UI: 92.06/100,000-376.80/100,000), respectively. The burden of RSV was higher in men than women. The highest ASMR (10.26/100,000, 3.80/100,000-20.16/100,000) and ASR-DALYs (478.71/100,000, 202.40/100,000-840.85/100,000) were reported in low-SDI region. Although mortality and DALYs rates in all age groups declined globally, the pace of decline was not uniform across age groups. Mortality rate in the elderly over 70 years surpassed that in children under 5 years in 2019. Conclusion: This study highlights the need for targeted interventions to reduce the burden of RSV, particularly in low-SDI region, and among the elderly over 70 years.

Summary: Subtype interference has a significant impact on the epidemiological patterns of seasonal influenza viruses (SIVs). We used attributable risk percent [the absolute value of the ratio of the effective reproduction number (Rₑ) of different subtypes minus one] to quantify interference intensity between A/H1N1 and A/H3N2, as well as B/Victoria and B/Yamagata. The interference intensity between A/H1N1 and A/H3N2 was higher in southern China 0.26 (IQR: 0.11–0.46) than in northern China 0.17 (IQR: 0.07–0.24). Similarly, interference intensity between B/Victoria and B/Yamagata was also higher in southern China 0.14 (IQR: 0.07–0.24) than in norther China 0.10 (IQR: 0.04–0.18). High relative humidity significantly increased subtype interference, with the highest relative risk reaching 20.59 (95% CI: 6.12–69.33) in southern China. Southern China exhibited higher levels of subtype interference, particularly between A/H1N1 and A/H3N2. Higher relative humidity has a more pronounced promoting effect on subtype interference.

Background: Measles and rubella are vaccine-preventable diseases targeted for elimination in most World Health Organization regions, and China is considered to have momentum towards measles elimination. Therefore, this study aimed to assess the population immunity levels against measles and rubella in Zhejiang Province in China in order to provide valuable insights for informing future public health measures and contributing to the ongoing global campaign against these diseases. Materials and methods: A cross-sectional serological survey was conducted in 2022. A total of 2740 blood samples were collected from healthy individuals spanning the age range of 0–59 years, representing diverse demographic strata across 11 prefectures in Zhejiang Province in China. The sera were tested for measles and rubella IgG antibodies to determine positivity rates and geometric mean concentrations (GMCs). Results: The overall positivity rate for the measles IgG antibody was 85.3%, with a GMC of 588.30 mIU/mL. The positivity rate for the rubella IgG antibody was 70.9%, and the GMC was 35.30 IU/mL. Measles IgG antibody positivity rates across the 0–11 months, 12–23 months, 24–35 months, 3–5 years, 6–9 years, 10–14 years, 15–19 years, 20–29 years, and 30–59 years age groups were 63.1%, 92.5%, 97.0%, 94.0%, 85.8%, 77.3%, 86.9%, 84.9%, and 88.7%, respectively (trend χ2 = 118.34, p < 0.001). Correspondingly, rubella antibody positivity rates for these same age brackets were 55.9%, 87.9%, 94.7%, 88.2%, 69.9%, 54.2%, 72.6%, 67.5%, and 74.3% (trend χ2 = 199.18, p < 0.001). Both univariate and multivariate analyses consistently demonstrated that age, immunization history, and differing economic levels were significant factors contributing to variations in antibody levels. Conclusions: The seroprevalence of measles and rubella was lower than that required for herd immunity. Periodic vaccination campaigns should be launched to increase immunity.

Objectives: This study aimed to investigate region-specific epidemiologic characteristics of influenza and influenza transmission zones (ITZs). Methods: Weekly influenza surveillance data of 156 countries from 1996 to 2021 were obtained using FluNet. Joinpoint regression was used to describe global influenza virus trends, and clustering analyses were used to classify the ITZs. Results: The global median average positive rate for total influenza virus was 16.19% (interquartile range: 11.62-25.70%). Overall, three major subtypes (influenza H1, H3, and B viruses) showed alternating epidemics. Notably, the proportion of influenza B viruses increased significantly from July 2020 to June 2021, reaching 62.66%. The primary peaks of influenza virus circulation in the north were earlier than those in the south. Global influenza virus circulation was significantly characterized by seven ITZs, including ''Northern America'' (primary peak: week 10), ''Eastern & Southern-Asia'' (primary peak: week 10), ''Europe'' (primary peak: week 11), ''Asia-Europe'' (primary peak: week 12), ''Southern-America'' (primary peak: week 30), ''Oceania-Melanesia-Polynesia'' (primary peak: week 39), and ''Africa'' (primary peak: week 46). Conclusion: Global influenza virus circulation was significantly characterized by seven ITZs that could be applied to influenza surveillance and warning.

Objectives: Influenza vaccination is an effective method for preventing influenza virus infection. Herein, we performed a meta-analysis to quantify global influenza vaccination rates (IVRs) and the factors influencing its uptake in the general population, individuals with chronic diseases, pregnant women, and healthcare workers. Methods: Related articles were obtained from online databases and screened according to the inclusion criteria. The pooled IVRs were calculated using the random effects model. Subgroup analyses and multivariate meta-regression were performed to determine the factors associated with influenza vaccine uptake. Results: We included 522 studies from 68 countries/regions. Most studies were conducted in the European region (247 studies), followed by the Western Pacific (135 studies) and American regions (100 studies). The IVRs with 95% confidence intervals (CIs) in the general population were lower (24.96%, 23.45%-26.50%) than in individuals with chronic diseases (41.65%, 40.08%-43.23%), healthcare workers (36.57%, 33.74%-39.44%), and pregnant women (25.92%, 23.18%-28.75%). The IVRs in high-income countries/regions were significantly higher than that in middle-income countries/regions. A free national or regional vaccination policy, perception of influenza vaccine efficacy and disease severity, a recommendation from healthcare workers, and having a history of influenza vaccination were positive factors for vaccine uptake (P

IntroductionSeveral studies have reported on hepatitis E virus (HEV) prevalence in various regions of China, but the results vary widely. Herein, we conducted a systematic review and meta-analysis to assess the seroprevalence, RNA-positive rate, genotype distribution of HEV in China, and its risk factors.MethodsWe included 208 related studies involving 1,785,569 participants published between 1997 and 2022. Random-effects models were used to pool prevalence, and subgroup analyses were conducted by population, gender, age, study period, regions, and rural–urban distribution. The meta regression models and pooled odds ratios (OR) were performed to identify risk factors for HEV infections.ResultsThe pooled anti-HEV IgG, IgM, and Ag seroprevalence, and RNA detection rates in China from 1997 to 2022 were 23.17% [95% confidence interval (CI): 20.23–26.25], 0.73% (95% CI: 0.55–0.93), 0.12% (95% CI: 0.01–0.32), and 6.55% (95% CI: 3.46–12.05), respectively. The anti-HEV IgG seropositivity was higher in the occupational population (48.41%; 95% CI: 40.02–56.85) and older adult aged 50–59 years (40.87%; 95% CI: 31.95–50.11). The dominant genotype (GT) of hepatitis E in China was GT4. Notably, drinking non-tap water (OR = 1.82; 95% CI: 1.50–2.20), consumption of raw or undercooked meat (OR = 1.47; 95% CI: 1.17–1.84), and ethnic minorities (OR = 1.50; 95% CI: 1.29–1.73) were risk factors of anti-HEV IgG seroprevalence.DiscussionsOverall, the prevalence of hepatitis E was relatively high in China, especially among older adults, ethnic minorities, and humans with occupational exposure to pigs. Thus, there is a need for preventive measures, including HEV infection screening and surveillance, health education, and hepatitis E vaccine intervention in high-risk areas and populations.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42023397036.

Abstract Background Rotavirus is the leading global pathogen of diarrhea-associated mortality and poses a great threat to public health in all age groups. This study aimed to explore the global burden and 30-year change patterns of rotavirus infection-associated deaths. Methods Based on the Global Burden of Disease 2019 Study (GBD 2019), we analyzed the age-standardized death rate (ASDR) of rotavirus infection by sex, geographical region, and sociodemographic index (SDI) from 1990 to 2019. A Joinpoint regression model was used to analyze the global trends in rotavirus infection over the 30 years, SaTScan software was used to detect the spatial and temporal aggregations, and a generalized linear model to explore the relationship between sociodemographic factors and death rates of rotavirus infection. Results Globally, rotavirus infection was the leading cause of diarrheal deaths, accounting for 19.11% of deaths from diarrhea in 2019. Rotavirus caused a higher death burden in African, Oceanian, and South Asian countries in the past three decades. The ASDR of rotavirus declined from 11.39 (95% uncertainty interval [95% UI] 5.46–19.48) per 100,000 people in 1990 to 3.41 (95% UI 1.60–6.01) per 100,000 people in 2019, with an average annual percentage change (AAPC) (− 4.07%, P

The human papillomavirus (HPV) vaccine reduces the prevalence of genital warts and the cancers they are associated with in males. However, the vaccination of males has always been neglected. Here, we performed a meta-analysis to comprehend the acceptability of the HPV vaccine in men and the factors impacting vaccination intentions. We searched PubMed, Web of Science, Embase, Ovid, CNKI, and Wan Fang up to 5 July 2023 for studies that reported HPV vaccine acceptance among men. A random effects model was used to obtain the pooled acceptance rate, and subgroup analysis was performed. Then, the influencing factors of HPV vaccination in males were analyzed. A total of 57 studies with 32,962 samples were included in the analysis. The overall acceptance rate of the HPV vaccine in general men was 47.04% (95% confidence interval [95%CI]: 39.23–54.93%), and 62.23% (95% CI: 52.93–71.10%) among those whose sexual orientation contained men. HPV vaccine acceptance rates differed significantly between the two populations (p = 0.01). The population with a medical background (46.23%, 95% CI: 40.28–52.24%) was more willing to be vaccinated. In comparison to the employed population (66.93%, 95% CI: 48.79–82.81%) and the unemployed (68.44%, 95% CI: 52.82–82.23%), vaccination acceptance rates were lower among students (47.35%, 95% CI: 37.00–57.81%) (p = 0.04). The most significant barriers to vaccination were perceived low risk of infection for themselves (45.91%, 95% CI: 31.73–60.43%), followed by vaccine cost (43.46%, 95% CI: 31.20–56.13%). Moreover, the recommendations from medical professionals (60.90%, 95%CI: 44.23–76.37%) and sexual partners (60.09%, 95%CI: 27.11–88.67%) were significant factors in promoting vaccination. Overall, acceptance of the HPV vaccine among general men was at a lower level, despite being slightly higher among men with a same-sex orientation. Popularizing knowledge about diseases and vaccines, encouraging medical professionals to recommend vaccines to men, or reducing the cost of vaccines may promote HPV vaccination.

IntroductionAs an important pathogen causing diarrheal diseases, the burden and change in the death rate of norovirus-associated diseases (NADs) globally are still unknown.MethodsBased on global disease burden data from 1990 to 2019, we analyzed the age-standardized death rate (ASDR) of NADs by age, region, country, and Socio-Demographic Index (SDI) level. The discrete Poisson model was applied in the analysis of NADs' spatiotemporal aggregation, the Joinpoint regression model to analyze the trend of death burden of NADs over 30 years, and a generalized linear model to identify the risk factors for the death rate from NADs.ResultsThe ASDR of NADs significantly decreased by a factor of approximately 2.7 times, from 5.02 (95% CI: 1.1, 11.34) in 1990 to 1.86 (95% CI: 0.36, 4.16) in 2019 [average annual percent change (AAPC) = −3.43, 95% CI: −3.56, −3.29]. The death burden of NADs in 2019 was still highest in African regions despite a great decline in recent decades. However, the ASDR in high SDI countries presented an uptrend [0.12 (95% CI: 0.03, 0.26) in 1990 and 0.24 (95% CI: 0.03, 0.53) in 2019, AAPC = 2.52, 95% CI: 2.02–3.03], mainly observed in the elderly over 70 years old. Compared to children under 5 years old, the 2019 death rate of elderly individuals over 80 years old was much higher in high SDI countries. The generalized linear model showed that factors of the number of physicians (RR = 0.67), the proportions of children under 14 years old (RR = 1.21), elderly individuals over 65 years old (RR = 1.13), educational level (RR = 1.03) and urbanization proportion (RR = 1.01) influenced the ASDR of NADs.ConclusionsThe death burden of NADs has remained high in developing regions over the last three decades and has increased among the elderly in countries with high SDI levels, even though the global trend in NAD-associated deaths has decreased significantly in the past three decades. More effective public health policies against NADs need to be implemented in high SDI regions and for the elderly.

Lemon is an important economic crop in the world and can bloom several times each year. The Dehong prefecture of Yunnan province is one of the main lemon-producing areas in China, and is a suitable area for planting high-quality lemons in China. However, the hot and rainy summers in Yunnan are not conducive to flower bud differentiation, which leads to low lemon yield. Therefore, normal flower bud differentiation is important to guarantee lemon production and quality. In this study, we selected some lemon trees for a pot experiment, and we sprayed the lemon leaves with gibberellin and paclobutrazol to regulate lemon flower formation. We set four separate concentration gradients for each regulator: 50, 100, 150, and 200 mg/L. The PBZ concentration gradients were 200, 400, 600, and 1200 mg/L. After the experiment, we determined and analyzed the morphological index and fruit quality of the lemon trees. The results showed that under the same cultivation and management conditions, spraying paclobutrazol substantially inhibited the growth of lemon shoots, increased the fruit setting rate, and improved the fruit yield. However, gibberellin considerably reduced the number of lemon flowering branches and promoted the vegetative growth of the lemons. When the concentration of paclobutrazol was 600 mg/L, the amount of lemon fruits reached the maximum, which remarkably increased the titratable acid and soluble solids contents of the fruit and ultimately increased the fruit quality compared with the control. Altogether, selecting the appropriate concentration of regulators to control the flowering and fruit setting of fruit trees is important and has value in guiding actual production.

Potato common scab, an economically important disease worldwide, is caused by pathogenic Streptomyces strains mainly through the effects of thaxtomin. The cello-oligosaccharides binding protein CebE is proposed as a gateway to the pathogenic development of Streptomyces scabiei. In this study, two functional CebE encoding genes, GEO5601 and GEO7671, were identified in pathogenic Streptomyces sp. AMCC400023. With a higher binding affinity towards signal molecules, the deletion of GEO5601 severely impaired thaxtomin-producing capacity and reduced the strain’s pathogenicity. Transcriptional analysis confirmed that CebE5601 is also responsible for the import and provision of carbon sources for cell growth. With lower binding affinity, the pathogenicity island (PAI)-localized CebE7671 may assume a new function of mediating the biological process of sporulation, given the significantly impaired formation of ΔGEO7671 spores. The mechanisms of action of CebE proteins unraveled in Streptomyces sp. AMCC400023 will help pave the way for more effective prevention of the potato common scab disease.

Perovskite solar cells (PSCs) are attracting much attention and are on the way to commercialization. However, some modules are subject to reverse bias in actual fields, so it is meaningful to investigate the reverse-bias behavior of PSCs. Herein, an in-situ temperature and current measurement technique was developed. Intriguingly, some hot spots were observed and then quickly disappeared in the reverse biased PSCs, along with the simultaneous increase in the current and local temperature. Also, the potential mechanism has been revealed and analyzed. An abnormal bulge in the perovskite film was found at the hot spot. Accordingly, the appearance and disappearance of hot spots were perfectly explained by band bending and tunneling current caused by ion accumulation. Additionally, statistical analysis suggested that sparkling hot spots were related to reverse voltage and efficiencies of PSCs. The research provides a great significance for the study of PSCs under reverse bias.

In hyperspectral image (HSI) classification, convolutional neural networks (CNNs) have been widely employed and achieved promising performance. However, CNN-based methods face difficulties in achieving both accurate and efficient HSI classification due to their limited receptive fields and deep architectures. To alleviate these limitations, we propose an effective HSI classification network based on multi-head self-attention and spectral-coordinate attention (MSSCA). Specifically, we first reduce the redundant spectral information of HSI by using a point-wise convolution network (PCN) to enhance discriminability and robustness of the network. Then, we capture long-range dependencies among HSI pixels by introducing a modified multi-head self-attention (M-MHSA) model, which applies a down-sampling operation to alleviate the computing burden caused by the dot-product operation of MHSA. Furthermore, to enhance the performance of the proposed method, we introduce a lightweight spectral-coordinate attention fusion module. This module combines spectral attention (SA) and coordinate attention (CA) to enable the network to better weight the importance of useful bands and more accurately localize target objects. Importantly, our method achieves these improvements without increasing the complexity or computational cost of the network. To demonstrate the effectiveness of our proposed method, experiments were conducted on three classic HSI datasets: Indian Pines (IP), Pavia University (PU), and Salinas. The results show that our proposed method is highly competitive in terms of both efficiency and accuracy when compared to existing methods.

Infrared thermography (IRT), is one of the most interesting techniques to identify different kinds of defects, such as delamination and damage existing for quality management of material. Objective detection and segmentation algorithms in deep learning have been widely applied in image processing, although very rarely in the IRT field. In this paper, spatial deep-learning image processing methods for defect detection and identification were discussed and investigated. The aim in this work is to integrate such deep-learning (DL) models to enable interpretations of thermal images automatically for quality management (QM). That requires achieving a high enough accuracy for each deep-learning method so that they can be used to assist human inspectors based on the training. There are several alternatives of deep Convolutional Neural Networks for detecting the images that were employed in this work. These included: 1. The instance segmentation methods Mask–RCNN (Mask Region-based Convolutional Neural Networks) and Center–Mask; 2. The independent semantic segmentation methods: U-net and Resnet–U-net; 3. The objective localization methods: You Only Look Once (YOLO-v3) and Faster Region-based Convolutional Neural Networks (Fast-er-RCNN). In addition, a regular infrared image segmentation processing combination method (Absolute thermal contrast (ATC) and global threshold) was introduced for comparison. A series of academic samples composed of different materials and containing artificial defects of different shapes and nature (flat-bottom holes, Teflon inserts) were evaluated, and all results were studied to evaluate the efficacy and performance of the proposed algorithms.

Abstract Background Patients with locally advanced rectal cancer generally have different response rates to preoperative neoadjuvant chemo-radiotherapy. This study investigated the value of the apparent diffusion coefficient (ADC) as a predictor to forecast the response to neoadjuvant chemo-radiotherapy in patients with locally advanced rectal cancer. Methods Ninety-one locally advanced rectal cancer patients who underwent neoadjuvant chemo-radiotherapy between 2015 and 2018 were enrolled. Diffusion-weighted magnetic resonance imaging was performed before treatment and within 4 weeks after the completion of neoadjuvant chemo-radiotherapy. Mean ADC values of regions of interest were evaluated by two radiologists. The tumor response was evaluated according to RESCIST 1.1. The cut-off value for the mean ADC and increasing percentage (ΔADC%) after neoadjuvant chemo-radiotherapy was calculated using the receiver operating characteristic curve. The response rate of pre-ADC and ΔADC% above/below the cut-off values was determined using the chi-square test, respectively. Primary tumor progression-free survival (PFS) was analyzed using the Kaplan–Meier method, based on the pre-ADC and ΔADC% cut-off values. Results The cut-off value of mean pre-ADC and ΔADC% was 0.94 × 10–3 mm2/s (80.36% sensitivity, 74.29% specificity) and 26.0% (73.21% sensitivity, 77.14% specificity), respectively. Lower mean pre-ADC values were related to a better response rate (83.3% vs 29.7%, P

Background: Aneurysmal subarachnoid hemorrhage (SAH) is a devastating disease. Anterior communicating artery (ACoA) aneurysm is the most frequent location of intracranial aneurysms. The purpose of this study is to predict the clinical outcome at discharge after rupture of ACoA aneurysms using the random forest machine learning technique.Methods: A total of 607 patients with ruptured ACoA aneurysms were included in this study between December 2007 and January 2016. In addition to basic clinical variables, 12 aneurysm morphologic parameters were evaluated. A multivariate logistic regression analysis was performed to determine the independent predictors of poor outcome. Of the 607 patients, 485 patients were randomly selected for training and the remaining for internal testing. The random forest model was developed using the training data set. An additional 202 patients from February 2016 to December 2017 were collected for externally validating the model. The prediction performance of the random forest model was compared with two radiologists.Results: Patients' age (odds ratio [OR] = 1.04), ventilated breathing status (OR = 4.23), World Federation of Neurosurgical Societies (WFNS) grade (OR = 2.13), and Fisher grade (OR = 1.50) are significantly associated with poor outcome. None of the investigated morphological parameters of ACoA aneurysm is an independent predictor of poor outcome. The developed random forest model achieves sensitivities of 78.3% for internal test and 73.8% for external test. The areas under receiver operating characteristic (ROC) curve of the random forest model were 0.90 for the internal test and 0.84 for the external test. Both sensitivities and areas under ROC curves of our model are superior to those of two raters in both internal and external tests.Conclusions: The random forest model presents good performance in predicting the outcome after rupture of ACoA aneurysms, which may aid in clinical decision making.

Ceramic-coated materials used in different engineering sectors are the focus of world-wide interest and have generated a need for inspection techniques that detect very small structural anomalies. Non-destructive testing is increasingly being used to evaluate coating thickness and to test for coating flaws. The main pros of non-destructive testing is that the tested object remains intact and available for continued use afterward. This paper reports on an integrated, non-destructive testing approach that combines infrared thermography and acousto-ultrasonics to evaluate advanced aerospace sandwich structure materials with the aim of exploring any potential for detecting defects of more than one type. Combined, these two techniques successfully detected fabrication defects, including inclusions and material loss.