Search

Abstract Background Osteoarthritis (OA) of the knee is a prevalent chronic degenerative joint condition that is having a growing impact on a global scale., posing a challenge in diagnosis which is often reliant on time-consuming and error-prone visual analysis by physicians. There is a critical need for an automated, efficient, and accurate diagnostic method to improve early detection and treatment. Methods We developed a novel Convolutional Neural Network (CNN) module, Dense Multi-Scale (DMS), an advancement over Multi-Scale Convolution (MSC). This module utilizes dense connections in convolutions of varying sizes (1 × 1, 3 × 3, 5 × 5) and across layers, enhancing feature reuse and complexity recognition, thereby improving recognition capabilities. Dense connections also facilitate deeper network architecture and mitigate gradient vanishing problems. We compared our model with a standard baseline model and validated it using an unseen-data test set. Results The DMS model exhibited exceptional performance in unseen-data tests, achieving 73.00% average accuracy (ACC) and 92.73% area under the curve (AUC), surpassing the baseline model’s (DenseNet) 63.52% ACC and 88.76% AUC. This highlights the DMS model’s superior predictive capability for knee OA. Conclusion The DMS model presents a significant advancement in predicting and grading knee OA, holding substantial clinical importance. It promises to aid radiologists in accurate diagnosis and grading, and in choosing appropriate treatments, thereby reducing misdiagnosis and patient burden.

Abstract Objective To investigate the value of 7E instructional model in the teaching of nursing students in nursing clinical probation. Methods One hundred and fifty-nine nursing undergraduates of the class of 2018 who were on probation in our hospital from November 2020 to June 2021 were selected as the control group by convenience sampling, and the traditional teaching model was adopted; an additional 171 nursing undergraduates of the class of 2019 who were on clinical probation in the same hospital from November 2021 to June 2022 were selected as the experimental group, and the 7E instructional model was adopted, including elicit, engagement, exploration, explain, elaborate, evaluate and extend. Results After the intervention, the experimental group was higher than the control group in theoretical knowledge scores (59.47 ± 4.51 VS 54.11 ± 8.46), practical skills scores (19.62 ± 1.36 VS 19.14 ± 1.24) and total course scores (90.13 ± 2.98 VS 84.67 ± 4.47); total scores of learning motivation (30.57 ± 5.24 VS 29.41 ± 4.77), learning cooperation ability (20.35 ± 4.41 VS 19.02 ± 4.25), information literacy (23.14 ± 4.36 VS 21.12 ± 3.95) and self-regulated learning ability (114.00 ± 19.72 VS 109.07 ± 18.61); total scores of viewpoint acquisition (43.58 ± 5.21 VS 42.16 ± 5.10), emotional care (33.41 ± 4.54 VS 32.09 ± 4.47), transposition thinking (13.04 ± 2.97 VS 11.56 ± 2.43) and empathy ability (89.03 ± 13.87 VS 85.81 ± 13.55); and total scores of positive attitudes toward communication skills (55.39 ± 7.03 VS 51.54 ± 6.54), with a statistically significant difference (P

Abstract This study evaluates the applicability of three thermal comfort indices—Physiologically Equivalent Temperature (PET), Standard Effective Temperature (SET), and Universal Thermal Climate Index (UTCI)—in various outdoor environments on the campus of Xi’an University, China. Meteorological data were collected on sunny days using a portable weather station at a height of 1.5 m, and subjective questionnaires were administered to 25 healthy university students over three months to gather Thermal Sensation Votes (TSV) and Thermal Comfort Votes (TCV). The study was conducted at four distinct outdoor locations: a lakeside area (Location 1), a shaded path (Location 2), a sports field (Location 3), and a plaza (Location 4). PET, SET, and UTCI values were calculated from the collected data using Rayman software. The analysis revealed significant differences in thermal comfort across the four locations, with the highest proportion of subjects feeling hot at the sports field (54.4%) and the highest proportion feeling cold at the lakeside (39%). The shaded path had the highest proportion of subjects feeling comfortable (79.4%), while the lakeside had the lowest (60.1%). The results indicated that SET underestimated thermal sensation at Locations 1, 3, and 4, necessitating calibration. PET was suitable for Locations 2, 3, and 4 but failed to reflect the thermal sensation at Location 1 due to prolonged sun exposure. In contrast, UTCI demonstrated applicability across all locations. To enhance accuracy, revised indices SET’ and PET’ were formulated using the mean-median method, providing more precise thermal comfort assessments. These findings underscore the limitations of SET and PET under specific conditions and highlight the robustness of UTCI, offering valuable insights for urban planning and design aimed at improving outdoor thermal comfort and well-being.

Abstract Background Unfavourable lipid and glucose levels may play a crucial role in the pathogenesis of gestational diabetes mellitus (GDM). However, there is a lack of prospective studies on the relationship between lipid profiles, lipid ratios and GDM during pregnancy. Aims To prospectively investigate the relationship between lipid profile and lipid ratios in early and mid-pregnancy and their pattern of change from early to mid-pregnancy and the risk of GDM. Methods This nested case-control study was based on maternal and child healthcare hospitals from Fujian Province, China. We included pregnant women who delivered in the hospital from January 2021 to June 2023. Lipid profiles (TC, TG, ApoA1, ApoB, HDL-c, LDL-c) and fasting glucose were measured before 14 weeks of gestation and between 20 and 28 weeks of gestation, and lipid ratios (triglyceride glucose index, TG/HDL-c and TC/HDL-c) was constructed. Logistic regression was used to assess the relationship between lipid profile, lipid ratios and GDM. Results Of 1586 pregnant women, 741 were diagnosed with GDM. After adjusting for potential confounders, TG, ApoA1, ApoB, LDL-c, triglyceride glucose index, TG/HDL-c, and TC/HDL-c in early pregnancy were positively associated with the risk of GDM (odds ratios [95% CI] for extreme interquartile comparisons were 2.040 (1.468–2.843), 1.506 (1.091–2.082), 1.529 (1.110–2.107), 1.504 (1.086–2.086), 1.952 (1.398–2.731), 2.127 (1.526–2.971), and 2.370 (1.700-3.312), all trend P

Objective: Opera Heritage in China is a rich and diverse cultural tradition passed down through generations. Today, Opera Heritage remains an essential part of Chinese culture and is celebrated through performances, festivals, and other cultural events. Efforts are being made to preserve and promote Opera Heritage through innovative technologies and approach such as digital archives, virtual reality, and community-based heritage management. Analysis: In this study, we suggested the SMART model that seeks to integrate these technologies and approaches into the preservation and promotion of Opera Heritage, ensuring that this rich cultural tradition can be enjoyed by future generations. We employed an ‘opera heritage’ using the Smart model in this study. In this research, "Smart Heritage" was defined as heritage experiences that used the word "Smart Heritage" or "similar terms" to describe the smart model. Findings: Opera Heritage analysis paid close attention to cutting-edge tools to record developments that showcase technical independence. Due to language barriers, this article could only interpret a clear convergence between SMART and opera heritage protection. For China's Opera Heritage to be properly archived and protected, a holistic and cooperative strategy that incorporates cutting-edge technologies and community-based heritage management practises are essential. Conclusion:Innovating technologies such as virtual reality and digital archives have been employed in efforts to promote and preserve China's rich Opera Heritage. This study emphasises the necessity for an extensive strategy for the efficient preservation and protection of Opera Heritage and suggests the SMART model to incorporate these methods. Doi: 10.28991/HIJ-2024-05-02-09 Full Text: PDF

Abstract Objective To explore the application effect of procedural pathways combined with information management in the construction of nursing staff skills training system. Methods This was a quasi-experimental study with a control group and an experimental group. A total of 300 newly admitted nurses or nurses who required training within three years of admission were selected as the experimental group, and 267 nurses who were trained in the same hospital during the same period in 2020 were selected as the control group. The experimental group received skills training using a system that combines procedural pathways with information management, while the control group received traditional teaching mode. The outcome measures included theoretical score, operation score, nurse competency, patient satisfaction, and nursing-related adverse events. The data were analyzed using t-test, chi-square test, and rank-sum test. Results The experimental group had higher scores in theoretical assessment, skills assessment, nurse competency, and patient satisfaction, and lower incidence of nursing-related adverse events than the control group (P

Abstract Background The spread of the coronavirus has led to significant anxiety among university students, resulting in various mental health problems that could potentially impact their academic performance. Method To examine the mediating role of emotional regulation and online social support in the relationships between COVID-19 psychological pressures, depression, and the fear of missing out (FoMO) among young adult university students, a cross-sectional research design was employed using an online survey. The sample consisted of 521 full-time university students from China, currently enrolled in undergraduate and postgraduate programs. Results Findings revealed that more than half (55.09%, n=287) of the university students experienced COVID-19 psychological pressures. These pressures directly contributed to increased levels of depression (β = 0.339, p < .001) and fear of missing out (β = 0.236, p < .001). Moreover, online social support and emotional regulation exhibited partial mediating effects on the association between COVID-19 psychological pressures, depression, and the fear of missing out. The results indicated that COVID-19 psychological pressures were linked to higher levels of depressive symptoms and a greater fear of missing out among university students. Conclusions However, the provision of timely and adequate online social support, as well as the implementation of emotional regulation strategies, mitigated the negative effects of the pandemic on students' social and emotional well-being. Consequently, this led to reduced levels of depression and fear of missing out.

The utilization of hydrogen-enriched liquefied petroleum gas (LPG) is an effective means of reducing carbon emissions, but the special physical and chemical properties of hydrogen have raised concerns among the public. To delve into the intricate chemical kinetic mechanisms governing the inhibitory effect of CO2 on the explosion of hydrogen-enriched LPG, this study systematically investigated the influence of varying CO2 concentrations (3%, 6%, and 9%) on the explosion characteristics of hydrogen-enriched LPG (hydrogen ratio ranging from 0 to 0.5) within a 20 L spherical explosion chamber. Subsequently, a chemical kinetic analysis was conducted, focusing on the explosion reaction dynamics of the H2/LPG/CO2/Air mixture, encompassing temperature sensitivity assessments and the production rates of key free radicals. The findings reveal that although hydrogen incorporation does not significantly alter the maximum explosion pressure of LPG, it markedly accelerates the explosion reaction rate, posing a challenge for CO2 in effectively inhibiting the explosion of hydrogen-enriched LPG. CO2 functions as a stabilizing third body within the reaction system, diminishing the collision frequency among free radicals, hydrogen molecules, hydrocarbon molecules, and oxygen molecules, thereby slowing down the reaction rate. As the proportion of hydrogen increases, the concentration of ·H radicals, known for their high reactivity, escalates, rapidly completing the propagation phase of the chain reaction and intensifying the overall generation rates of critical free radicals, including ·H, ·O, and ·OH. Notably, the key reaction H+O2⇋O+OH, which governs the reaction temperature, undergoes significant enhancement, further accelerating the explosion reaction rate and ultimately diminishing the inhibitory efficacy of CO2 against the hydrogenated LPG explosion. Furthermore, as the amount of hydrogen added increases, hydrogen’s competitiveness for oxygen within the reaction system markedly improves, attenuating the oxidation of hydrocarbons. Concurrently, the alkane recombination reaction, exemplified by C3H6+CH3(+M)⇋sC4H9(+M), is strengthened. These insights provide valuable understanding of the complex interactions and mechanisms during the explosion of hydrogen-enriched LPG in the presence of CO2, with implications for the safe application of hydrogen-enriched LPG.

Introduction Electronic cigarette use has become increasingly popular, with potential consequences for reproductive health. We aimed to investigate the effects of different components of e-liquid on the ovary and compare the impact of low nicotine concentration e-liquids (LN e-liquids) and high nicotine concentration e-liquids (HN e-liquids) on ovarian toxicity. Methods A total of 378 rat ovaries were divided into seven groups, including control (no intervention), nicotine (0.05 mg/mL), flavoring (0.25 μL/mL), propylene glycol (PG) (2.5 μL/mL), vegetable glycerin (VG) (2.0 μL/mL), LN e-liquid (0.05 mg nicotine + 0.25 μL flavoring + 2.5 μL PG + 2.0 μL VG + 0.25 μL distilled water/mL medium) and HN e-liquid groups (0.05 mg nicotine + 0.05 μL flavoring + 0.5 μL PG + 0.4 μL VG + 0.05 μL distilled water/mL medium). After three hours of in vitro culture, ovarian morphology, oxidation levels [superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSH-Px) and malondialdehyde (MDA)], and apoptosis levels [factor related apoptosis (Fas), Cyt-c, Caspase-9, Caspase-3] were analyzed. Results Our findings indicate that nicotine has limited impact on the ovary, while flavoring, PG, and VG all cause ovarian damage including morphological damage, disruption of oxidative balance and promotion of apoptosis, with VG having the most significant effect. Moreover, LN e-liquids may lead to more severe ovarian damage than HN e-liquids at an equal intake of total nicotine. Conclusions Our study highlights that in e-liquid formula, nicotine has a limited effect on the ovaries, but flavoring, PG, and VG all cause damage to the ovaries, with VG the most damaging. At a consistent level of total nicotine intake, e-liquids with low nicotine concentrations cause more damage to the ovaries than those with high nicotine concentrations. These findings contribute to a better understanding of the impact of e-liquids on ovarian health and have important implications for public health policy.

To investigate the distribution, contamination status, and antibiotic resistance of Listeria monocytogenes in four types of retail poultry meat, including chicken, duck, goose, and pigeon, sold in Jiading District, Shanghai, a total of 236 retail poultry meat samples were collected, and L. monocytogenes isolates were obtained for identification and antibiotic susceptibility testing against 14 common antibiotics. Forty-one L. monocytogenes isolates were detected from the 236 retail poultry meat samples, with detection rates of 24.47%, 19.44%, 14.75%, and 4.44% in chicken, goose, duck, and pigeon meat, respectively. Among refrigerated, frozen, and room temperature samples, refrigerated poultry had the highest detection rate at 25.40%, while frozen poultry had the lowest at 13.33%. The detection rate of L. monocytogenes in chicken meat differed significantly between the storage temperatures, while no significant differences were found for other poultry types. No significant differences in detection rates were observed between different retail locations or packaging methods. Isolates exhibited complete resistance to cefoxitin (FOX) and increasing resistance over time to tetracycline (TET) and clindamycin (CLI), while low levels of resistance were found for penicillin (PEN), oxacillin (OXA), and erythromycin (ERY). Resistance to ERY and TET suggests the potential for multidrug resistance. Significant differences in antibiotic resistance profiles were observed among L. monocytogenes from the various poultry types. In summary, contamination status and antibiotic resistance profiles differed among retail chicken, duck, goose, and pigeon meat sold and the resistance rate of strains continues to increase in Jiading District, Shanghai. Targeted control measures should be implemented to reduce the emergence of resistant strains, as retail conditions had minimal impact on L. monocytogenes prevalence in poultry meat.

Side-scan sonar (SSS) image sample augmentation plays an important role in improving the effect of deep-learning-based underwater target detection. However, the existing sample augmentation methods for cross-domain conversion always result in weak representativeness of the augmented samples since the targets in the nondomain images are similar but not exactly the same as the actual underwater target to be detected. In this article, an augmentation method for SSS image samples of underwater targets based on the cross-domain mapping relationship of images of the same object is proposed. A physical model of the actual underwater target was first constructed using three-dimensional printing. A series of optical images and SSS images of underwater targets can be obtained by using the actual measurement of underwater targets under different conditions. To achieve the augmentation of SSS target samples, a single-cycle-consistency network structure with a channel and spatial attention and generative adversarial networks with least squares loss was designed for efficient and robust conversion of information between optical and SSS acoustic samples. To verify the effectiveness of the proposed method in generating high-quality samples, underwater targets were detected using the detection model trained by the generated samples. The experimental results revealed that the proposed method achieved impressive performance with a more than 5.8% improvement in average precision value for zero-sample underwater mine target detection and 4.3% for few-sample shipwreck target detection, compared with using only real SSS data.

Hyperspectral image classification using deep learning techniques has received great attention in recent years, considering the powerful spatial feature mining ability of deep learning. Fully convolutional network is an effective deep learning architecture that exploits spatial contextual information through a hierarchical convolutional structure. However, it often ignores the relationships between samples of the same category and different categories within the global context. Therefore, a fully convolutional spectral–spatial fusion network based on supervised contrastive learning (FCSCL) is proposed for hyperspectral image classification to enhance the separability between different categories and class aggregation among the same category. In the FCSCL framework, the spectral–spatial fusion classification network is developed to capture subtle spectral variations and spatial patterns by adaptively fusing the features extracted by the spectral branch and spatial branch. To improve intraclass compactness and interclass separability, the SCL module is integrated into the FCSCL framework. The positive and negative sample pairs are constructed by the designed hard example pairs sampling strategy. These constructed sample pairs are used to guide the network to learn more discriminative feature representations that pixels of the same category are closer to each other and pixels of different categories are pushed further apart in the feature space. The experiments using three public hyperspectral datasets verify the effectiveness of the FCSCL algorithm, and the FCSCL method achieves better classification performance.

IntroductionOral cancer, a predominant malignancy in developing nations, represents a global health challenge with a five-year survival rate below 50%. Nonetheless, substantial reductions in both its incidence and mortality rates can be achieved through early detection and appropriate treatment. Crucial to these treatment plans and prognosis predictions is the identification of the pathological type of oral cancer.MethodsToward this end, fiber-optic Raman spectroscopy emerges as an effective tool. This study combines Raman spectroscopy technology with deep learning algorithms to develop a portable intelligent prototype for oral case analysis. We propose, for the first time, a multi-task network (MTN) Raman spectroscopy classification model that utilizes a shared backbone network to simultaneously achieve different clinical staging and histological grading diagnoses.ResultsThe developed model demonstrated accuracy rates of 94.88%, 94.57%, and 94.34% for tumor staging, lymph node staging, and histological grading, respectively. Its sensitivity, specificity, and accuracy compare closely with the gold standard: routine histopathological examination.DiscussionThus, this prototype proposed in this study has great potential for rapid, non-invasive, and label-free pathological diagnosis of oral cancer.

Abstract The blast crisis (BC) is the final deadly phase of chronic myeloid leukemia (CML), which remains a major challenge in clinical management. However, the underlying molecular mechanism driving blastic transformation remains unclear. Here, we show that ASF1A, an essential activator, enhanced the transformation to CML-BC by mediating cell differentiation arrest. ASF1A expression was aberrantly increased in bone marrow samples from CML-BC patients compared with newly diagnosed CML-chronic phase (CP) patients. ASF1A inhibited cell differentiation and promoted CML development in vivo. Mechanistically, we identified ASF1A as a coactivator of the Notch transcriptional complex that induces H3K56ac modification in the promoter regions of Notch target genes, and subsequently enhanced RBPJ binding to these promoter regions, thereby enhancing Notch signaling activation to mediate differentiation arrest in CML cells. Thus, our work suggests that targeting ASF1A might represent a promising therapeutic approach and a biomarker to detect disease progression in CML patients.

In various ecosystems and human societies, living organisms and systems often exhibit cooperative and synchronous behaviors during survival. Recently, co-evolutionary models of cooperation and synchronization have shed light on the underlying mechanisms driving such behaviors, offering an intriguing avenue for studying these phenomena. However, current research predominantly focuses on a point-strategy decision mode, where each individual is limited to taking the same actions towards its neighbors. Such an assumption implies that an individual is unable to differentiate its neighbors and adjust its strategy accordingly, making it difficult to capture the complexity and diversity of interactive behaviors observed in reality. To this end, we introduce the interaction mode based on the edge-strategy and investigate how synchronization and cooperation co-evolve under interaction diversity. Specifically, we explore a scenario in which individuals can adopt different strategic decisions toward their neighbors based on their differences, thereby extending the traditional point strategy. Our research clarifies the positive role of interaction diversity in alleviating the evolutionary Kuramoto’s dilemma. Moreover, it provides new insights and ideas for comprehending the influence of edge-strategy on the co-evolution of cooperative and synchronous behaviors.

Introduction Electronic cigarettes (e-cigarettes) have recently become popular as an alternative to conventional cigarettes. The aim of this study is to investigate the effects of e-cigarette refill liquid (e-liquid) on follicular development and estrogen secretion in rats and whether it is related to the Hippo signaling pathway, a pathway that can regulate follicle growth. Methods Ovaries from 21- and 35-day-old rats were divided into three groups: control (no intervention), 0.05 mg, and 0.5 mg (e-liquids containing 0.5 mg and 5 mg of nicotine/kg). The rates were cultured for three hours in vitro . At the end of culture, HE staining was performed to observe the follicle morphology and calculate the percentage of normal follicles, and the expression of Yes-associated protein (YAP, target factors of the Hippo signaling pathway) and CYP19 (aromatase, a key enzyme in estrogen synthesis) were observed by immunohistochemistry. Western blotting was performed to detect the expression levels of CYP19, YAP, phosphorylated YAP (PYAP), large tumor suppressor 2 (LATS2, factors upstream of YAP in the Hippo signaling pathway), and phosphorylated LATS2 (PLATS2). Estrogen concentrations were determined using ELISA. Results HE staining showed that the percentage of normal follicles decreased, and immunohistochemistry showed that the expression of CYP19 and YAP significantly decreased after e-liquid intervention. ELISA showed that the estrogen concentration in the ovaries decreased after e-liquid intervention. Western blot results indicated that CYP19, LATS2, and YAP expression, decreased after e-liquid intervention, but PLATS2 and PYAP expression increased. Conclusions We found that the e-liquids may impair the development of rat ovarian follicles and reduce estrogen secretion through Hippo signaling pathway.

In this study, based on the traditional hot water extraction-ethanol precipitation method for fucoidan, the ethanol-free extraction process of kelp fucoidan was studied in accordance with the difference in the fucose contents and sulfate groups of fucoidans and their beneficial biological activities. Three extraction methods including hot water extraction-ethanol precipitation method, hot water extraction-acid precipitation method, and hot water extraction-acid precipitation-enzymatic hydrolysis assisted extraction method, were applied to prepare fucoidans, and three fucoidan samples (sample 1, sample 2 and sample 3) were obtained, respectively. Fucose and sulfuric acid group-contents and biological activities (antioxidant, antibacterial activities) analysis results showed that the contents of fucose and sulfate groups in fucoidan (sample 3) prepared by hot water extraction-acid precipitation-enzymatic assisted hydrolysis method were 41.10%±0.87% and 24.90%±0.15%, respectively, which were significantly higher than the Trade Standard requirements of fucoidan (SC/T 3404-2012), samples 1 and sample 2. Meanwhile, the sample 3 also had the best antioxidant and antibacterial activities in three fucoidan samples. The Response surface methodology (RSM) was used to optimize the key process conditions of hot water extraction-acid precipitation-enzymatic hydrolysis assisted extraction of fucoidan. The best extraction process parameters were obtained as follows: Extraction temperature was 90℃, extraction time was 2.0 h, liquid material ratio was 40:1 mL/g, and the extraction yield reached 9.65%±0.11%. In this study, raction rate of fucoidan and the biological activity of fucoidan prepared by hot water extraction-acid precipitation-enzymatic assisted hydrolysis method were significantly higher than those prepared by hot water extraction-ethanol precipitation method and hot water extraction-acid precipitation method, therefore, the hot water extraction-acid precipitation-enzymatic assisted hydrolysis method digestion would be a good process to effectively replace the hot water extraction-ethanol precipitation method for fucoidan extraction.

With the development trend of an aging society, Alzheimer’s disease (AD) has become an urgent problem in the field of medicine worldwide. Cognitive impairment in AD patients leads to a decline in the ability to perform daily living and abnormalities in behavior and personality, causing abnormal psychiatric symptoms, which seriously affect the daily life of patients. Currently, mainly drug therapy is used for AD patients in the clinic, but a large proportion of patients will experience drug efficacy not working, and even some drugs bring severe sleep disorders. Acupuncture, with its unique concept and treatment method, has been validated through a large number of experiments and proved its reliability of acupuncture in the treatment of AD. Many advances have been made in the study of the neurobiological mechanisms of acupuncture in the treatment of AD, further demonstrating the good efficacy and unique advantages of acupuncture in the treatment of AD. This review first summarizes the pathogenesis of AD and then illustrates the research progress of acupuncture in the treatment of AD, which includes the effect of acupuncture on the changes of biochemical indicators in AD in vivo and the specific mechanism of action to exert the therapeutic effect. Changes in relevant indicators of AD similarly further validate the effectiveness of acupuncture treatment. The clinical and mechanistic studies of acupuncture in the treatment of AD are intensified to fit the need for social development. It is believed that acupuncture will achieve new achievements in the treatment of AD as research progresses.

Abstract Background Synaptophysin (SYN), chromogranin A (CGA), CD56 and insulinoma-associated protein 1 (INSM1) are proposed neuroendocrine (NE) markers used for diagnosis of pulmonary NE tumors. These NE markers have been identified in subsets of non-NE tumors requiring differential diagnosis, thus we sought to explore new NE markers. Methods We evaluated the immunohistochemical expression of SOX11, a transcription factor involved in neurogenesis, in pulmonary NE tumors and large cell carcinomas (LCCs). Results We found that SOX11 showed a sensitivity similar to INSM1 and CGA, and less than SYN and CD56 in small cell lung carcinomas (SCLCs) and large cell neuroendocrine carcinomas (LCNECs). While SOX11 is more specific than the other four markers for diagnosis of high-grade neuroendocrine carcinomas (HG-NECs) because 1) None of LCCs (0/63), the most challenging non-NE tumor type for differential diagnosis due to overlapped morphology with LCNECs displayed SOX11 positivity. While expression of at least one of SYN, CGA, CD56 or INSM1 was identified in approximately 60% (18/30) of LCCs. 2) SOX11 was only expressed in 1 of 37 carcinoid tumors in contrast to diffuse expression of SYN, CGA, CD56 and INSM1. In HG-NECs, we noticed that SOX11 was a good complementary marker for SCLC diagnosis as it was positive in 7 of 18 SYN−/CGA−/CD56− SCLCs and 3 of 8 SYN−/CGA−/CD56−/INSM1− SCLCs, and SOX11 positivity in 4 of 6 SYN−/CGA−/CD56− cases previously diagnosed as LCCs with NE morphology provides additional evidence of NE differentiation for reclassification into LCNECs, which was further confirmed by electromicroscopical identification of neurosecretory granules. We also found SOX11 expression cannot predict the prognosis in patients with HG-NECs. Conclusions Therefore, SOX11 is a useful complementary transcriptional NE marker for diagnosis and differential diagnosis of SCLC and LCNEC.

Abstract Background PCV3 is a pathogen associated with porcine dermatitis and nephropathy syndrome (PDNS)-like clinical signs, reproductive failure, and cardiac and multiorgan inflammation, which was newly identified in 2016 in sows in USA. Recently, PCV3 has also been identified from several non-porcine species like (cattle, dog, wild boar, deer, mice and ticks). However, PCV3 infection in donkey is not well established. Since 2019, 300 blood samples were collected from female donkey, which was characterized by abortion and sterility, in Liaocheng city of China. Results In the present study, an investigation of PCV3 in donkey blood samples was undertaken employing by real time PCR. Positive rates of PCV3 in donkeys reach to 21.0 %. In addition, one full-length PCV3 genome sequence was obtained, and it had a highest identity with porcine circovirus 3 PCV3/CN/Nanjing2017 strain and is clustered to PCV3a genotype based on ORF2 sequences. Conclusions This is the first report of detection of PCV3 from female donkeys presenting reproductive failure in large-scale donkey farms, China. In addition, the PCV3 strain identified in this study shared the closest relationship with those from porcine, suggesting that PCV3 may be transmitted from pigs to donkeys. Totally, PCV3 infection in donkey should be concerned although the association between it and reproductive failure are not better understood.

The economic progress of China cannot be denied; however, deteriorating environmental quality is the primary concern to be addressed. Since the last few years, China’s legislators have intended to facilitate green transformation by sustaining natural resources and ensuring renewable energy consumption. Therefore, this study explores the impact of renewable energy, natural resource green innovation, and economic growth on ecological footprints in China. The bootstrap autoregressive distributed lag (ARDL) model has been deployed by taking the quarterly data ranging between 1990Q1 and 2020Q4. The results reveal that by enhancing green innovation, China can transform its economy into a clean environment. Similarly, the effective utilization of renewable energy consumption is indispensable to reducing the ecological footprint in the long run. Moreover, the Error Correction Term (ECT) is significantly negative, confirming a stable long-run equilibrium relationship between model variables. Similar results are found in the short run; however, the marginal impact of all variables is stronger in the long run. It implies that long-term planning is imperative in China for optimal benefits from renewable energy and green technologies.

The study investigates the nexus of CO2 emissions, tourism, fossil fuels, and GDP growth using China’s data from 1970 to 2019. The research applied the upset U-molded EKC and the ARDL -models to calculate the time series stationarity variables. The results showed that in the initial enlargement phases, a sophisticated GDP adversely impacts CO2 emissions, then a higher GDP positively influences CO2 emissions. The development of tourism, use of fossil fuels (coal and oil), and population growth show an important influence on CO2 emissions but the use of gas and electricity has little effect on CO2 emissions. In contrast, foreign direct investment besides population development had little effect on increasing CO2 emissions. Retreating foreign direct investment, strengthening the use of sustainable electricity, and improving transportation for explorers, especially the green tourism business, are excellent ways to reduce environmental degradation in China.

Climatic extremes, such as heat waves, are increasing in frequency, intensity and duration under anthropogenic climate change. These extreme events pose a great threat to many organisms, and especially ectotherms, which are susceptible to high temperatures. In nature, many ectotherms, such as insects, may seek cooler microclimates and ’ride out´ extreme temperatures, especially when these are transient and unpredictable. However, some ectotherms, such as web-building spiders, may be more prone to heat-related mortality than more motile organisms. Adult females in many spider families are sedentary and build webs in micro-habitats where they spend their entire lives. Under extreme heat, they may be limited in their ability to move vertically or horizontally to find cooler microhabitats. Males, on the other hand, are often nomadic, have broader spatial distributions, and thus might be better able to escape exposure to heat. However, life-history traits in spiders such as the relative body size of males and females and spatial ecology also vary across different taxonomic groups based on their phylogeny. This may make different species or families more or less susceptible to heat waves and exposure to very high temperatures. Selection to extreme temperatures may drive adaptive responses in female physiology, morphology or web site selection in species that build small or exposed webs. Male spiders may be better able to avoid heat-related stress than females by seeking refuge under objects such as bark or rocks with cooler microclimates. Here, we discuss these aspects in detail and propose research focusing on male and female spider behavior and reproduction across different taxa exposed to temperature extremes.

Identifying whether and how merger and acquisition (M&A) goodwill influences corporate technology innovation is a critical topic in the context of growing M&A activities. Based on the panel data of 2,634 Chinese non-financial listed companies from 2007 to 2019, this paper adopts multiple linear regression and the Bootstrap method to investigate the impact of M&A goodwill on corporate technological innovation and the mechanism through which M&A goodwill affects technological innovation. The results show that: (1) There is a significant negative correlation between M&A goodwill and technological innovation input, with financial constraints acting as the main channels. (2) Non-private corporations enjoy a higher level of financing capacity in terms of debt and equity compared with private corporations, resulting in the absence of the disincentive effect of M&A goodwill on corporate technological innovation inputs, despite the fact that M&A activities also cause massive resource consumption. (3) Stock pledges by controlling shareholders are effective in alleviating the negative impact of M&A goodwill on technological innovation inputs. Furthermore, our results highlight that simple stock pledge measures capture a significant influence of alleviating financing constraints, thereby decreasing the adverse impact of M&A, and hence need to be adequately considered in future M&A and innovation studies. While enriching the literature on the economic consequences of M&A and the research on stock pledge, this paper also provides micro-evidence for an in-depth understanding of the effect of M&A goodwill on technological innovation.

BackgroundThe alternative usage of promoters provides a way to regulate gene expression, has a significant influence on the transcriptome, and contributes to the cellular transformation of cancer. However, the function of alternative promoters (APs) in hepatocellular carcinoma (HCC) has not been systematically studied yet. In addition, the potential mechanism of regulation to the usage of APs remains unclear. DNA methylation, one of the most aberrant epigenetic modifications in cancers, is known to regulate transcriptional activity. Whether DNA methylation regulates the usage of APs needs to be explored. Here, we aim to investigate the effects of DNA methylation on usage of APs in HCC.MethodsPromoter activities were calculated based on RNA-seq data. Functional enrichment analysis was implemented to conduct GO terms. Correlation tests were used to detect the correlation between promoter activity and methylation status. The LASSO regression model was used to generate a diagnostic model. Kaplan–Meier analysis was used to compare the overall survival between high and low methylation groups. RNA-seq and whole-genome bisulfite sequencing (WGBS) in HCC samples were performed to validate the correlation of promoter activity and methylation.ResultsWe identified 855 APs in total, which could be well used to distinguish cancer from normal samples. The correlation of promoter activity and DNA methylation in APs was observed, and the APs with negative correlation were defined as methylation-regulated APs (mrAPs). Six mrAPs were identified to generate a diagnostic model with good performance (AUC = 0.97). Notably, the majority of mrAPs had CpG sites that could be used to predict clinical outcomes by methylation status. Finally, we verified 85.6% of promoter activity variation and 92.3% of methylation changes in our paired RNA-seq and WGBS samples, respectively. The negative correlation between promoter activity and methylation status was further confirmed in our HCC samples.ConclusionThe aberrant methylation status plays a critical role in the precision usage of APs in HCC, which sheds light on the mechanism of cancer development and provides a new insight into cancer screening and treatment.

Abstract Background Previous studies have documented the therapeutic value of computed tomography (CT)‐guided percutaneous microwave ablation (MWA) for early‐stage non‐small cell lung cancer (NSCLC). However, few studies have focused on patients aged 80 years and older. This retrospective study aimed to evaluate the safety and clinical outcomes of CT‐guided percutaneous MWA in patients aged 80 years and older with early‐stage peripheral NSCLC. Methods A retrospective analysis of 63 patients aged 80 years and older with cT1a‐2bN0M0 peripheral NSCLC who underwent CT‐guided percutaneous MWA was performed between January 2008 and January 2018 at 11 hospitals in Shandong Province, China. Results The median follow‐up time was 21.0 months. The overall median survival time was 50 months. The cancer‐specific median survival time was not reached in five years. The one‐, two‐, three‐, four‐, and five‐year overall survival rates were 97.1%, 92.6%, 63.4%, 54.4%, and 32.6%, respectively. The one‐, two‐, and three‐year cancer‐specific survival (CSS) rates were 97.9%, 97.9%, and 69.4%, respectively. The four‐ and five‐year CSS rates were not achieved. A total of 14 patients (22.2%) had local progression. The one‐, two‐, three‐, four‐, and five‐year local control rates were 88.8%, 78.8%, 70.3%, 63.9%, and 63.9%, respectively. The mortality rate was 0% within 30 days after the procedure. Major complications included pneumothorax requiring drainage (21.1%), pulmonary infection (4.2%), and pleural effusions requiring drainage (2.8%). Conclusions CT‐guided percutaneous MWA is a safe and effective modality for treating patients aged 80 years and older with early‐stage peripheral NSCLC.

This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1186/s13046-019-1046-x.

With the rapid development of the social economy, people’s demand for energy is increasing. Global warming has made people pay more attention to the importance of energy saving and emission reduction. The power grid is the system responsible for the transmission and distribution of electric energy. Therefore, in the context of energy saving and emission reduction, there are higher requirements for substations in the power grid. For this reason, an intelligent switch with built-in electronic voltage transformer is designed. The concept and key technical characteristics of the electronic voltage transformer intelligent switch are introduced; the overall design scheme of the built-in electronic voltage transformer intelligent switch is expounded; the hardware and software system of the device is designed; the management and control strategy of the design device is such as transformer tangent control, voltage and reactive control; and the operating system is ported. Finally, the simulation test of the system proves that the system has high effectiveness and stability. The research can provide reference for the realization of efficient, economic, stable, safe, and environmentally friendly distribution of power in a power grid.

Ovarian cancer remains the most lethal gynecological malignant tumor, with relapse occurring in approximately 70% of advanced cases. Anlotinib is an oral small-molecule multi-targeted tyrosine kinase inhibitor that can resist neoangiogenesis and inhibit tumor growth. Previous research demonstrated clinical antitumor activity of anlotinib in various cancers. We report the case of an elderly woman with advanced ovarian cancer who received anlotinib after failure of multiple-line chemotherapy. A partial response was observed after six cycles of anlotinib monotherapy, with a reduction in the size of the metastases and significantly decreased serum CA125 levels from 1832.7 U/mL to 118.7 U/mL. She continued to take anlotinib, with a progression-free survival time of more than 4 months. Only mild hypertension was observed during the treatment. Anlotinib monotherapy may be a novel therapeutic option for patients with advanced ovarian cancer.

Abstract Background Early invasion and metastasis are responsible for the dismal prognosis of pancreatic ductal adenocarcinoma (PDAC), and epithelial-to-mesenchymal transition (EMT) is recognized as a crucial biological progress in driving tumor invasion and metastasis. The transcription factor FOXO3a is inactivated in various types of solid cancers and the loss of FOXO3a is associated with EMT and tumor metastasis. In this study, we sought to explore whether SPRY2, a regulator of receptor tyrosine kinase (RTK) signaling, is involved in FOXO3a-mediated EMT and metastasis in PDAC. Methods Immunohistochemistry was performed in 130 paired PDAC tissues and paracarcinomatous pancreatic tissues. Cell proliferation and apoptosis were assessed by cell counting kit and flow cytometry, while cell migration and invasion were evaluated with wound healing and transwell assays. The changes in mRNA and protein levels were estimated by qRT-PCR and western blot. BALB/c nude mice xenograft model was established to evaluate tumorigenesis and metastasis in vivo. Results FOXO3a expression was remarkably reduced in PDAC tissues, and correlated with metastasis-associated clinicopathologic characteristics and poor prognosis in patients with PDAC. In addition to the promotion of proliferation and suppression of apoptosis, knockdown of FOXO3a or SPRY2 induced EMT and promoted the migration and invasion of PDAC cells via activation of the β-catenin/TCF4 pathway. Moreover, silencing of SPRY2 reversed the suppressor effects induced by FOXO3a overexpression on EMT-associated migration and invasion of PDAC cells, while blockade of β-catenin reversed the effects of SPRY2 loss. FOXO3a knockdown decreased SPRY2 protein stability, whereas SPRY2 knockdown enhanced β-catenin protein stability. In vivo, FOXO3a knockdown promoted the tumorigenic ability and metastasis of PDAC cells. Conclusions Our study suggests that knockdown of FOXO3a induces EMT and promotes metastasis of PDAC by activation of the β-catenin/TCF4 pathway through SPRY2. Thus, FOXO3a may represent a candidate therapeutic target in PDAC.

Interferometric synthetic aperture radar (InSAR) is an effective technology for generating high-precision digital elevation models (DEMs). However, the vertical accuracy of InSAR DEMs is limited by the contradiction between height measurement sensitivity and phase unwrapping reliability in terms of normal baseline length as well as data voids caused by layover or shadow effects. In order to alleviate these two unfavorable factors, in this study, a novel InSAR DEM fusion method with guided filter is developed and assessed with multiple bistatic TanDEM-X InSAR data pairs of different normal baselines acquired from different orbits. Unlike the widely used fusion method based on pixel-by-pixel weighted average, the guided-filter-based method incorporates local spatial context information into the fusion and can thus effectively alleviate the noise effect and automatically fill in data voids. As a result of the local edge-preserving capability of the guided filter, the proposed fusion method can preserve terrain details by maintaining gradient consistency and introducing terrain features as guidance image. Furthermore, the proposed fusion method is computationally efficient owing to the linear time complexity of guided filter. The experimental results show that the fused DEM with guided filter can depict terrain details well and smooth the “salt-and-pepper” noise and fill in almost all of the data voids. The root mean square error (RMSE) of the fused InSAR DEM with guided filter is lower than those of the weighted average fused InSAR DEM and the TanDEM-X DEM released by the German Aerospace Center (DLR), thus validating the effectiveness of the fusion method proposed in this study.

For InSAR topographic mapping, multi-baseline InSAR height estimation is known to be an effective way to facilitate phase unwrapping by significantly increasing the ambiguity intervals and maintaining good height measurement sensitivity, especially in mountainous areas. In this paper, an efficient multi-baseline SAR interferometry approach based on maximum likelihood estimation is developed for refined topographic mapping in mountainous areas. In the algorithm, maximum likelihood (ML) height estimation is used to measure the topographic details and avoid the complicated phase unwrapping process. In order to be well-adapted to the mountainous terrain conditions, the prior height probability is re-defined to take the local terrain conditions and neighboring height constraint into consideration in the algorithm. In addition, three strategies are used to optimize the maximum likelihood height estimation process to obtain higher computational efficiency, so that this method is more suitable for spaceborne InSAR data. The strategies include substituting a rational function model into the complicated conversion process from candidate height to interferometric phase, discretizing the continuous height likelihood probability, and searching for the maximum likelihood height with a flexible step length. The experiment with simulated data is designed to verify the improvement of the ML height estimation accuracy with the re-defined prior height distribution. Then the optimized processing procedure is tested with the multi-baseline L-band ALOS/PALSAR data covering the Mount Tai area in China. The height accuracy of the generated multi-baseline InSAR DEM can meet both standards of American DTED-2 and Chinese national 1:50,000 DEM (mountain) Level 2.