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Abstract The issue of transgender education and equality has long been neglected in Pakistan, leading to a lack of awareness and acceptance of the transgender community. The present study focuses on the joint effort of the government, print media, and citizens toward breaking the stigma and promoting transgender education and equality. This study employed a mixed-methods approach, combining qualitative content analysis of articles from three prominent Pakistani media outlets with a quantitative public opinion survey to evaluate the extent of media coverage and public attitudes toward transgender education and equality. This coverage helped create awareness and understanding of the transgender community. The government also took significant steps (Transgender Act 2018) by passing policies favoring the transgender community. Furthermore, the study showed that citizens have a positive attitude toward transgender equality, a sign of creating an inclusive society. The study also concluded that joint efforts between the government, print media, and citizens can help people break the stigma and promote transgender education and equality. This approach will pave the way for a more inclusive society that recognizes and values the rights of all individuals, regardless of their gender identity.

Abstract The role of enterprise dormitories as the main living arrangements of Chinese migrant workers who are registered as rural residents but make their living in cities in pursuit of urbanisation cannot be ignored. However, the existing research on living spaces and the urban integration of migrant workers lacks sufficient focus on enterprise dormitories. Using the logit model to examine representative data on the Pearl River Delta and Yangtze River Delta areas and applying a national dataset taken from the China Migrants Dynamic Survey, we analyse how enterprise dormitories affect the urban integration of migrant workers across the different migration stages in this paper. The research results reveal that there are two migration stages in the urban integration of migrant workers. In the individual migration stage, based on the production target, enterprises accommodate migrant workers as a means of reducing their labour costs by increasing the labour time input of migrant workers. Moreover, in the family migration stage, enterprise dormitories are conducive to the low-cost integration of migrant workers into urban society, but they negatively affect further family migration because of the insufficient family living space that they provide. This research offers the intellectual foundation required for not only resolving the contradiction between the family reunification of migrant workers and their employment situation but also for the optimisation of housing policy.

Abstract Climate change is a challenge for global sustainable development. The transportation sector contributes considerably to global greenhouse gas emissions. In China, it accounts for about 10% of total CO2 emissions with high mitigation potential. Public transit systems can save energy and reduce carbon emissions. Carbon-inclusive action based on digital technology is becoming the primary measure for promoting green transit in China. To understand the level and nature of the public’s awareness of green transit and identify potential pathways to change their behaviors toward green transit, this study collected 7369 questionnaires nationwide and examined the public’s behavior and preferences regarding green transportation and their attitudes toward digital technologies that support green transportation, in the first such study in the Chinese context. The study found that (1) most respondents understand and accept the concept of green transportation, especially younger respondents, under the age of 39; (2) convenience, safety, and weather are the most important factors considered; (3) digital tools provide innovative and interesting options for public participation in green mobility. The government, social organizations, enterprises, and various stakeholders must strive to foster consensus and collaborative participation. This involves partnering with digital technology enterprises and establishing emission reduction standards for low-carbon living, particularly in the realm of green transportation.

Abstract This study investigates the impact of strategic human resource management (SHRM) on fostering green innovation and enhancing environmental performance among employees in the Asia-Pacific region. In the context of intensifying competition in the industrial sector, it is essential to understand how SHRM influences employees’ innovative capabilities and their alignment with environmental goals. Our research suggests that effective SHRM strategies can significantly increase self-efficacy and stimulate green innovation, thus reinforcing the alignment between individual and organizational environmental objectives. To empirically test these hypotheses, we conducted a survey of 487 employees and used Smart-PLS 4.0 for structural equation modeling. This method allowed us to examine both the mediating and moderating effects within our model. The results indicate that self-efficacy mediates the relationship between SHRM practices and green innovation, while person-organization fit significantly moderates the relationship between green innovation and environmental performance. This study offers novel insights into how SHRM can promote environmental consciousness and innovation within organizations. By underscoring the roles of self-efficacy and person-organization fit, our research enriches the broader scholarly dialog on strategic human resource management and its environmental implications.

Abstract Corruption and anti-corruption efforts are intertwined with political and economic concerns. From an economic and political perspective, as the government strives to enhance its governance capabilities, it becomes crucial to consider the costs of anti-corruption supervision and the losses incurred from corruption. This evaluation is essential for formulating a scientifically sound anti-corruption strategy that maximizes government benefits. To address this issue, the paper presents a model that incorporates levels of supervision and associated costs. The findings reveal that in the case of homogeneous officials, the optimal level of supervisory input, which maximizes government benefit, is nearly zero when per capita income is low due to budgetary constraints on anti-corruption control. However, as per capita income reaches a certain threshold, the optimal level of supervisory input suddenly rises to its maximum and decreases as per capita income increases. Alternatively, if the government adopts a zero-tolerance approach towards corruption and provides adequate remuneration to its employees, ensuring that all competent authorities can resist corruption, then corruption can be eliminated. Moreover, when officials exhibit heterogeneity in terms of their honesty levels, certain conditions give rise to a middle per capita income range, resulting in an optimal level of supervisory input that leads to a phenomenon known as “partial corruption.” During this phase, the wages paid by the government to its employees promote honesty, preventing them from engaging in corruption. However, they are unable to curb the corrupt activities of more dishonest officials. To some extent, this model also explains the challenges associated with eradicating corruption in several middle-income countries.

Abstract Intellectual property rights (IPRs) have become increasingly important for firms in today’s knowledge-based economy, as evidenced by the strong growth in their use. The vital role of IPRs has motivated research into their association with firm performance. However, few firm-level studies have been conducted in developing countries. Moreover, empirical studies on the use of IPR bundles and their economic performance are scarce. To fill this gap, this study first illuminates how the joint use of different IPRs varies with firm characteristics, second, it analyses the association of such joint use with firm performance, based on a constructed large dataset that merges firm-level information from China’s Annual Survey of Industrial Enterprises with data on IPR filings from the China National Intellectual Property Administration. Results indicate that the joint use of different IPRs is strongly correlated with the industrial sector and firm size. Firms that use IPR bundles also have much greater economic performance than those that rely only on single types, indicating the existing complementarity between these rights. This study advances the understanding of the relationship between IPRs and firm performance and emphasises the complementary effect between different types of IPRs, demonstrating the significance of utilising various intellectual property mechanisms fully to increase firms’ competitive advantages.

Long bristles facilitate seed dispersal and protect seeds from herbivores. Early domesticated Setaria italica cultivars had long bristles, but most of the modern cultivars have short bristles. Little is known about the molecular regulatory mechanisms underlying the bristle length trait of S. italica. We generated a segregating population derived from a cross between a long bristle (Z-45) and a short bristle (Z-47) cultivars. A quantitative trait locus (QTL) was identified at 35–40 Mb on chromosome 1 using QTL-seq. In addition, we found that 351-bp transposable element insertion in the Seita.1G316900 promoter was linked to the short bristle trait, which can be used in marker-assisted selection in crop breeding. In addition, some evidences were also found for Seita.1G338900 to play a role in regulation of bristle length. In summary, we hypothesize that Seita.1G316900 and Seita.1G338900 could be candidate genes for bristle length in S. italica. But further functional analysis of these genes are required. [ABSTRACT FROM AUTHOR]

Abstract Early embryonic arrest and fragmentation (EEAF) is a common phenomenon leading to female infertility, but the genetic determinants remain largely unknown. The Moloney sarcoma oncogene (MOS) encodes a serine/threonine kinase that activates the ERK signaling cascade during oocyte maturation in vertebrates. Here, we identified four rare variants of MOS in three infertile female individuals with EEAF that followed a recessive inheritance pattern. These MOS variants encoded proteins that resulted in decreased phosphorylated ERK1/2 level in cells and oocytes, and displayed attenuated rescuing effects on cortical F‐actin assembly. Using oocyte‐specific Erk1/2 knockout mice, we verified that MOS‐ERK signal pathway inactivation in oocytes caused EEAF as human. The RNA sequencing data revealed that maternal mRNA clearance was disrupted in human mature oocytes either with MOS homozygous variant or with U0126 treatment, especially genes relative to mitochondrial function. Mitochondrial dysfunction was observed in oocytes with ERK1/2 deficiency or inactivation. In conclusion, this study not only uncovers biallelic MOS variants causes EEAF but also demonstrates that MOS‐ERK signaling pathway drives human oocyte cytoplasmic maturation to prevent EEAF.

Abstract Cellular RNA is decorated with over 170 types of chemical modifications. Many modifications in mRNA, including m6A and m5C, have been associated with critical cellular functions under physiological and/or pathological conditions. To understand the biological functions of these modifications, it is vital to identify the regulators that modulate the modification rate. However, a high‐throughput method for unbiased screening of these regulators is so far lacking. Here, we report such a method combining pooled CRISPR screen and reporters with RNA modification readout, termed CRISPR integrated gRNA and reporter sequencing (CIGAR‐seq). Using CIGAR‐seq, we discovered NSUN6 as a novel mRNA m5C methyltransferase. Subsequent mRNA bisulfite sequencing in HAP1 cells without or with NSUN6 and/or NSUN2 knockout showed that NSUN6 and NSUN2 worked on non‐overlapping subsets of mRNA m5C sites and together contributed to almost all the m5C modification in mRNA. Finally, using m1A as an example, we demonstrated that CIGAR‐seq can be easily adapted for identifying regulators of other mRNA modification.

Objective: Melanoma, with its high degree of malignancy, stands as one of the most dangerous skin cancers and remains the primary cause of death from skin cancer. With studies demonstrating the potential of traditional Chinese medicine to intervene and treat melanoma, we turned our attention to celastrol. Celastrol is a triterpene compound extracted from the traditional Chinese medicine derived from Tripterygium wilfordii. Previous studies have shown that celastrol exerts inhibitory effects on various malignant tumors, including melanoma. Hence, our goal was to clarify the impact of celastrol on cell viability, apoptosis, and cell cycle progression by elucidating its effects on the PI3K/AKT/mTOR pathway. Methods: CCK-8 and wound healing assays were used to determine the effect of celastrol on the viability and migration of B16-F10 cells. Changes in cell apoptosis, cell cycle, reactive oxygen species (ROS), and mitochondrial membrane potential were detected by flow cytometry. PI3K/AKT/mTOR pathway proteins and HIF-α mRNA expression in B16-F10 cells were detected by western blotting and qPCR. Moreover, the addition of a PI3K activator demonstrated that celastrol could inhibit the function of B16-F10 cells via the PI3K/AKT/mTOR pathway. Results: Celastrol inhibited the viability and migration of B16-F10 cells. Through the inhibition of the PI3K/AKT/mTOR pathway down-regulates the expression of HIF-α mRNA, thereby causing an increase of ROS in cells and a decrease in the mitochondrial membrane potential to promote cell apoptosis and cell cycle arrest. The inhibitory effect of celastrol on B16-F10 cells was further demonstrated by co-culturing with a PI3K activator. Conclusion: Celastrol inhibits the function of B16-F10 cells by inhibiting the PI3K/AKT/mTOR cellular pathway and regulating the expression of downstream HIF-α mRNA. [ABSTRACT FROM AUTHOR]

Lithium niobate thin film frequency doubler has extensive applications in the preparation of classical and quantum sources. In this study, we successfully fabricated microdisk resonators with a quality factor of 2.2×105 in reverse-polarization dual-layer x-cut lithium niobate for the first time. Based on the modal phase matching condition, efficient second harmonic generation with a record normalized conversion efficiency of ∼56000% W−1 and cascaded third harmonic generation with an efficiency of ∼6500% W−2 were obtained in the microdisk resonator. Compared with the periodically poled lithium niobate microcavity, the complex domain structure preparation processes are avoided. Our work provides a scheme for achieving highly efficient second-order nonlinear effects in non-periodically poled microcavities. [ABSTRACT FROM AUTHOR]

Snap-off events are one of the most common and essential phenomena in two-phase flow in porous media. This paper uses the scanning results of a siltstone slice to construct a two-dimensional heterogeneous pore network structure to visualise microscopic snap-off phenomena and displacement processes accurately. The relationship between snap-off events and the non-wetting phase saturation was studied using two-phase flow displacement experiments. Results show that although the non-wetting phase snap-off events benefit freeing the trapped non-wetting phase in the microchannels, high-frequency snap-off events are the main reason for trapping the non-wetting phase during the displacement process, eventually leading to residuals. The frequency of non-wetting phase snap-off events in the pore network structure can be reduced to lower the non-wetting phase saturation and reduce the non-wetting phase residuals by increasing the displacement fluid viscosity, reducing the surface tension coefficient between the phases and increasing the flow rate. [ABSTRACT FROM AUTHOR]

China's energy-intensive industries utilize the leading proportion of coal to meet the demand for its industrial outputs, while on the other hand, these industries also assure the provision of livelihood to millions of people, and capping the share of coal consumption for these industries can adversely affect the industrial and economic growth of China. Thus, to achieve the Pareto improvement between environmental pollution and industrial output growth, it is essential to comprehend the patterns of coal consumption in these industries. Hence, the present research intended to analyze the potential drivers of coal consumption by applying a joint LMDI, DEA, and the production theoretical decomposition approach. Findings indices that, first, industrial output growth was the crucial driver to simulate the industrial coal consumption, while the potential coal intensity and coal technology changes exhibited the reverse effect. Second, the coal inputs and industrial output efficiency, along with the improvements in technological gaps, were found to be the imperative factors in decelerating coal consumption. Third, the energy industrial group was discovered to have more potentials of coal conversation as compared to the non-energy industrial group. Moreover, results also indicated that coal pure technical efficiency is accelerating coal growth, which revealed that coal can be saved by enhancing coal allocative efficiency. These findings laid the empirical ground to design a feasible coal conservation policy for achieving the imperative goals of environmental protection without compromising industrial output growth. [ABSTRACT FROM AUTHOR]

It is well known that there is a pinning effect of oxygen vacancies. The migration rate of an oxygen vacancy in crystalline ceramics is lower than the rate of spontaneous polarization, which limits the improvement of piezoelectric properties. In this work, Pr and Ce elements were introduced into position A of Na0.5Bi4.5Ti4O15 to improve the piezoelectric properties of Na0.5Bi4.2-xCexPr0.3Ti4Oy ceramics. The Ce-doping effectively modulated the content of oxygen vacancies by different doping amounts so that the difficulty of domain inversion caused by oxygen vacancy motion was reduced and insufficient polarization was improved. As a result, the best piezoelectric properties (d33 = 22 pC/N) and low dielectric loss (tan δ = 0.003) were achieved at 10 KHz under 200°C with a substitution of 0.025 mol in Na0.5Bi4.2-xCexPr0.3Ti4Oy ceramics. The high dielectric constants and low dielectric loss greatly improve the energy conversion efficiency, so this ceramic has great prospects in the application of medium- and high-frequency ultrasonic transducers. [ABSTRACT FROM AUTHOR]

Medical imaging techniques, such as mammography, ultrasound and magnetic resonance imaging, plays an integral role in the detection and characterization of breast cancer. Although computers are believed to gain an important role in the assessment of medical images for breast evaluation for at least two decades, their impact on performance has not lived up to expectations yet. With the continuous and rapid development of computer science, artificial intelligence (AI) approaches, like machine learning and deep learning, have been introduced for the analysis of medical images. Because of the remarkable advances in data extraction and analysis in medical imaging compared to conventional feature-based techniques, AI has reignited the interest in automated breast image interpretation. Extensive research is conducted on accurate detection and classification of breast lesions, and more specifically, the predictive and prognostic features of breast cancer by radiomics. Radiomics exploits the fact that image data is nowadays numerical and can also be used to generate quantitative biomarkers. In this comprehensive review, we cover the progress, application and challenge of radiomics and AI in breast cancer diagnosis in recent years, as well as the impact and significance of AI on future breast cancer research. [ABSTRACT FROM AUTHOR]

When the existing visual SLAM (simultaneous localization and mapping) algorithms are applied to dynamic environments, the pose error estimated by the system often increases sharply, or even the algorithm fails due to the interference of dynamic objects. To adapt to dynamic scenes, a dynamic object processing part needs to be added to the system. However, some existing processing methods lead to reduced real-time performance, which is not conducive to the real-time localization and navigation of mobile robots. To solve the above problems, an RGB-D SLAM system is proposed in this paper for indoor dynamic environments. The system designs an adaptive semantic segmentation tracking algorithm to meet the requirements of localization accuracy and real-time performance in dynamic scenes. First, a lightweight semantic segmentation network is used to provide a priori information about the object. According to this prior information and the motion state of the object in the previous scene, each feature point is assigned a motion level and is classified as a static point, movable static point, or dynamic point. Then, whether the current frame needs semantic segmentation is adaptively determined according to the motion level information of the feature points. Some appropriate feature points (static points) are selected for initial pose estimation, and then, secondary optimization of the pose is performed according to the results of weighted static constraints. In order to verify the effectiveness of the proposed algorithm, experiments are carried out on the TUM RGB-D dynamic scene dataset and compared with ORB-SLAM2 and other SLAM algorithms for dynamic environments. The results show that the proposed algorithm performs well on most datasets, and the positioning accuracy in indoor dynamic environments can be improved by 90.57% compared with the ORB-SLAM2 algorithm. In addition, a 3D semantic map of static backgrounds in dynamic scenes has been established, using dense point cloud maps to visualize 3D scene information, and incorporating semantic information to label objects in the scene, to guide advanced tasks such as robot navigation and enhance the usability of the system. [ABSTRACT FROM AUTHOR]

Purpose: About one-fifth of newly diagnosed cancer patients are parents to young children. These patients are at higher risk of psychosocial stress and inability to attend treatment due to having to balance their own healthcare needs with childcare duties. This study aims to explore the impact of childcare on cancer parents and elicit their perspectives on potential supports. The results could help inform the implementation of suitable childcare programs to remove this barrier in accessing care. Methods: Patients at a large Canadian cancer treatment center were screened by oncologists for having minor children at home. Secure electronic surveys were then distributed to consenting participants. Domains surveyed included patient demographics, childcare burden, impact on treatment, and preference for childcare supports. Results: The mean age of correspondents was 43.9 (range 33–54), 46 patients (92%) were female, and breast cancer was the most common primary tumor. The median number of children per correspondent was two, and their mean age was 8.4. Balancing childcare with cancer treatment had a significant impact on self-reported stress levels for most correspondents. Twenty (40%) participants had to reschedule and 7 (14%) participants missed at least one appointment due to childcare conflicts. During the COVID-19 pandemic, access to childcare resources decreased while childcare responsibilities increased. Three-quarters of correspondents reported that a flexible childcare would make it easier for them to adhere to appointment schedules. Conclusion: Childcare is a significant psychosocial barrier for patients accessing cancer care. Our results indicate that most parents undergoing treatment may benefit from hospital-based childcare services. [ABSTRACT FROM AUTHOR]

A MoO2/Mo2C hybrid catalyst supported on N-doped carbon (Mo2C/MoO2@NC) was successfully prepared, which is featured with moderate mesoporosity, uniform metallic nanoparticles, and rich oxygen-vacancies. It showed excellent efficiency (99% imine yield) and good reusability for oxidative self-coupling of benzylamine to N-benzylbenzaldimine under mild conditions (85 °C, 3 h, 1 bar O2). In addition, the catalyst Mo2C/MoO2@NC also exhibited a universal applicability for oxidative coupling of other primary amines to imines with impressive conversion and satisfying target product selectivity. This method provides an efficient and environment friendly strategy for catalytic synthesis of complex imines from primary amines. [ABSTRACT FROM AUTHOR]

Background: Runt-related transcription factor-2 (Runx2) has been considered an inducer to improve bone repair ability of mesenchymal stem cells (MSCs). Methods and results: Twenty-four rabbits were used to establish Osteonecrosis of the femoral head (ONFH) and randomly devided into four groups: Adenovirus Runx2 (Ad-Runx2) group, Runx2-siRNA group, MSCs group and Model group. At 1 week after model establishment, the Ad-Runx2 group was treated with 5 × 107 MSCs transfected through Ad-Runx2, the Runx2-siRNA group was treated with 5 × 107 MSCs transfected through Runx2-siRNA, the MSCs group was injected with 5 × 107 untreated MSCs, and the Model group was treated with saline. The injection was administered at 1 week and 3 weeks after model establishment. The expression of bone morphogenetic protein 2 (BMP-2), Runx2 and Osterix from the femoral head was detected at 3 and 6 weeks after MSCs being injected, and Masson Trichrome Staining, Gross Morphology, X-ray and CT images observation were used to evaluate the repair effect of ONFH. The data revealed that the expression of BMP-2, Runx2 and Osterix in the Runx2-siRNA group was reduced at 3 weeks compared with the MSCs group, and then the expression further reduced at 6 weeks, but was still higher than the Model group besides Osterix; The expression of these three genes in the Ad-Runx2 group was higher than in the MSCs group. Masson Trichrome Staining, Gross Morphology and X-ray and CT images observation revealed that necrotic femoral head of the MSCs group was more regular and smooth than the Runx2-siRNA group, which has a collapsed and irregular femoral head. In the Ad-Runx2 group, necrotic femoral head was basically completely repaired and covered by rich cartilage and bone tissue. Conclusions: Overexpression of Runx2 can improve osteoblastic phenotype maintenance of MSCs and promote necrotic bone repair of ONFH. [ABSTRACT FROM AUTHOR]

The anthocyanin glycosides in potato tubers not only give potato bright color and high nutritional value, but also have pharmacological effects such as antioxidant, blood pressure-lowering, lipid-lowering and immunity-boosting. However, the overall expression pattern of genes involved in anthocyanin synthesis or regulation in potato tubers remains unclear. In this study, the anthocyanin content of four potato varieties (B, R, Y and W)was measured and the regulatory genes of anthocyanin synthesis in different potato cultivars were identified by comparative transcriptomic approaches. The results showed that a total of 82.6 G of filtered data were obtained from the 12 sequencing libraries, of which 82.23–87.66% of clean fragments were covered to the reference genome. A total of 42,793 genes were found in the 12 libraries, of which 3765 were novel genes. Finally, through strict threshold screening, three groups of 3638 (B), 4295 (R) and 3594 (Y) DEGs were obtained(FDR < 0.05 and |log2FC|>1), respectively. GO analysis showed that DEGs were mainly enriched in cell (GO: 0005623), metabolic process (GO: 0008152), catalytic activity (GO: 0003824) and other entries. KEGG analysis revealed that the DEGs were significantly enriched in metabolic pathways (ko01100), phenylalanine metabolism (ko00360), photosynthesis (ko00195). In addition, some anthocyanin synthesis genes (e.g. CHS, bHLH and MYB) were highly induced or repressed in different cultivars. This study provided a theoretical basis for the study ofthe regulatory genes of anthocyanin formation in potato and a scientific reference for breeding high-quality potato cultivars. [ABSTRACT FROM AUTHOR]

Colored potatoes are rich in anthocyanins and polyphenols, which have high nutritional and health values. miRNAs are closely linked to growth and development, metabolic regulation and various stress response activities in plants. However, the mechanism by which miRNAs regulate potato color remains unclear. In this study, 12 transcriptomic libraries were constructed using a comparative transcriptomics approach to mine miRNAs and their targets associated with anthocyanin formation in potato by comparing anthocyanin levels in four potato varieties. These analyses yielded 167.3 M clean reads and identified 5358 miRNAs, of which 4199 were newly discovered. Relative to group W (LK99), 1235, 1533 and 921 differentially expressed miRNAs (DEmiRNAs) were obtained by the stringent identification threshold in groups B (Black kingkong), R (Red beauty) and Y (Longshu No.7), respectively, and 236 shared DEmiRNAs were screened. Some important miRNAs and target genes were screened by combined analysis, such as miR858, miR172, miR156, miR157, APS1, ABCB4, SPL, RPP13, etc. Several key regulatory pathways were identified by functional annotation analysis, such as metabolic pathways, secondary metabolic pathways, glutathione metabolism, phenylalanine metabolism and cysteine and methionine metabolism. These results provide a comprehensive insight into the miRNAs that regulate potato color formation and will provide a scientific basis for developing colorful or functional potatoes. [ABSTRACT FROM AUTHOR]

Non-small-cell lung cancer (NSCLC) remains the major cause of cancer-related death. Immune checkpoint inhibition has become the cornerstone treatment for NSCLC. Cuproptosis is a newly identified form of cell death relying on mitochondrial respiration that might play a role in shaping tumor immune microenvironment (TIME). The clinical significance of cuproptosis-related genes (CRGs) remains unclear and warrant investigation. The current study extracted RNA sequencing profiles and corresponding clinical information from six aggregated datasets from the Gene Expression Omnibus (GEO) repository as the training set, and from The Cancer Genome Atlas (TCGA) database as the testing set. Cuproptosis-related immune genes (CRIMGs) were obtained through coexpression analysis, univariate Cox regression analysis, and LASSO analysis for overall survival (OS) association analysis. Consensus clustering was employed to divide the subjects into clusters. Stepwise multivariate Cox regression was used to establish the prognostic CRIMG_score from the CRIMGs. A 17-gene prediction signature was established that informed patients' OS both in the training and testing datasets (p < 0.001). The predictive value of the signature in terms of immunotherapeutic responses was assessed in two publicly available NSCLC immunotherapy datasets (POPLAR and OAK studies) and an internal dataset from Sun Yat-sen University Cancer Center (ORIENT-11 study). Patients in the high-risk group displayed worse survival, a characteristic suppressive tumor immune microenvironment, and low immunotherapeutic benefits compared to those in the low-risk group. Collectively, the CRIMG_score established herein could serve as a promising indicator of prognosis and immunotherapeutic response in patients with NSCLC. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic brought considerable change to the practice of radiotherapy. In the meantime, patients are increasingly turning to online resources for health information, with YouTube being one of the biggest platforms. However, little is known about what information is being disseminated to cancer patients about radiotherapy in the context of COVID-19. Therefore, this study aims to characterize and assess YouTube videos on radiotherapy during COVID-19. A YouTube search using the terms "Radiation therapy COVID-19", "Radiation therapy coronavirus", "Radiotherapy COVID-19", and "Radiotherapy coronavirus" was completed using a clear-cache web browser. The top 50 videos were collected from each search. After applying pre-determined exclusion criteria, each video was assessed for general parameters, source, and content. Two raters were used to ensure interrater reliability. One hundred five unique videos resulted from the four searches. Ninety-eight per cent were published in the last year. The median video length was 6 min and 54 s, and the median number of views was 570. Most videos were from the USA (58%). The majority of videos were published by a commercial channel (31%), non-profit organization (28%), or healthcare facility (26%). Forty-two per cent of the videos covered a topic related to radiotherapy during the pandemic. Bias was identified in 6% of videos. YouTube information on radiotherapy during COVID-19 is non-specific and can be misleading. The results of this study highlight the need for healthcare providers to proactively address patient information needs and guide them to appropriate sources of information. [ABSTRACT FROM AUTHOR]

A mechanochemical treatment and subsequent high temperature annealing strategy was developed for the synthesis of nitrogen-doped carbon supported cobalt catalysts. The as-prepared Co/NC800 catalyst was demonstrated for efficient and selective hydrogenation of furfural into furfuryl-based alcohols and amines with good to excellent yields under optimum conditions. [ABSTRACT FROM AUTHOR]

N-Methylene conjugate of (–)-cytisine and (4',7-dihydroxy-3'-methoxy)isoflavone, extracted from Sophora alopecuroides L., has been designed and synthesized in 7 steps with 50.6% with respect to the starting ketone. The neuroprotective effect of the conjugate has been investigated for the first time. The results showed that it could significantly promote in vitro viability of neural stem cells of Sprague–Dawley rats in a concentration-dependent manner (both p < 0.01). When the loading was 0.4 mg/kg, the conjugate could increase the number of new neurons in the hippocampal dentate gyrus in transgenic 5xFAD mice (p < 0.05). It is suggested that the conjugate plays an important role in neuroprotective process, which might prove useful for the development of new drugs for the treatment of neurological diseases. [ABSTRACT FROM AUTHOR]

Feature selection is an indispensable step in the data preprocessing stage of data mining and pattern recognition. In some numerical small sample data, it is often high dimensional in nature. Some traditional information-theoretic-based feature selection algorithms, however, neglect to judge the dependency correlation and redundancy among these high-dimensional features. How to dynamically find the dependent correlated features among features becomes an urgent problem to be solved. This paper proposes a feature selection algorithm using dynamic weighted conditional mutual information (DWCMI). Firstly, the algorithm uses the interaction information to calculate the coefficient for determining the interaction redundancy between features and between features and class labels. Secondly, the value of this coefficient is used to dynamically adjust the size of the weights of the maximum classification information and to find the dependency-related features between features. Finally, DWCMI is validated against six other feature selection algorithms on two classifiers using 12 different datasets with classification accuracy metrics (Precision_macro, Recall_macro and F1_macro). The experimental results show that the DWCMI method can effectively select relevant features and interaction features in small sample data, thus improving the quality of the feature subset and increasing the classification accuracy. [ABSTRACT FROM AUTHOR]

Objectives: Chronic obstructive pulmonary disease (COPD) is underdiagnosed globally. The present study aimed to develop weakly supervised deep learning (DL) models that utilize computed tomography (CT) image data for the automated detection and staging of spirometry-defined COPD. Methods: A large, highly heterogeneous dataset was established, consisting of 1393 participants retrospectively recruited from outpatient, inpatient, and physical examination center settings of four large public hospitals in China. All participants underwent both inspiratory chest CT scans and pulmonary function tests. CT images, spirometry data, demographic information, and clinical information of each participant were collected. An attention-based multi-instance learning (MIL) model for COPD detection was trained using CT scans from 837 participants. External validation of the COPD detection was performed with 620 low-dose CT (LDCT) scans acquired from the National Lung Screening Trial (NLST) cohort. A multi-channel 3D residual network was further developed to categorize GOLD stages among confirmed COPD patients. Results: The attention-based MIL model used for COPD detection achieved an area under the receiver operating characteristic curve (AUC) of 0.934 (95% CI: 0.903, 0.961) on the internal test set and 0.866 (95% CI: 0.805, 0.928) on the LDCT subset acquired from the NLST. The multi-channel 3D residual network was able to correctly grade 76.4% of COPD patients in the test set (423/553) using the GOLD scale. Conclusions: The proposed chest CT-DL approach can automatically identify spirometry-defined COPD and categorize patients according to the GOLD scale. As such, this approach may be an effective case-finding tool for COPD diagnosis and staging. Key Points: • Chronic obstructive pulmonary disease is underdiagnosed globally, particularly in developing countries. • The proposed chest computed tomography (CT)–based deep learning (DL) approaches could accurately identify spirometry-defined COPD and categorize patients according to the GOLD scale. • The chest CT-DL approach may be an alternative case-finding tool for COPD identification and evaluation. [ABSTRACT FROM AUTHOR]

With the real-time recording of the health care system, real-time monitoring of user trajectory data can effectively protect the health and health of the body. In order to accurately establish the spatial position trajectory data prediction model, a space trajectory data prediction model based on variable space chaotic particle swarm optimization (CPSO)-optimized least squares support vector machine (LSSVM) is proposed. Firstly, aiming at the problem that particle swarm optimization (PSO) is easy to fall into local optimum, the global optimization performance of PSO algorithm is improved by using variable space chaos search strategy and particle out-of-bounds mirror processing strategy. Numerical simulation experiments verify the superiority of improved particle swarm optimization algorithm. Based on the CPSO algorithm, the hyper parameters of the CPSO-optimized least squares support vector machine (CPSO-LSSVM) are proposed to improve the prediction accuracy of the model. Finally, using GeoLife and T-Drive dataset as the research object, the CPSO-LSSVM spatial position prediction model is established by using the trajectory data of the dataset. The simulation experiment verifies that the CPSO-LSSVM positional space prediction model has higher prediction accuracy and more strong generalization ability to accurately and effectively predict spatial location. [ABSTRACT FROM AUTHOR]

This paper selects the core content of recently released Market Patterns and Investment Insights of China's Digital Content Industry in 2020–2021, and this series of reports has been published in four consecutive volumes (2015, 2017–2018, 2019–2020, 2021–2022). Based on the latest developments of the digital content industry in China, this paper probes into the market development, competitive landscape, investment and financing volume, investment hotspots, policies and public opinion environment of 10 sub-sectors, including online games, animation, online videos, short videos, live streaming, online music, digital reading, news & information apps, online education, and knowledge payment, provides an insight into the status quo of China's digital content industry in 2020–2021 and ten major development trends of the industry. Furthermore, the investment value of 10 sub-sectors is assessed from two dimensions—internal factors and external factors, with a total of 7 primary indicators and 11 secondary indicators, and the results are compared with those of the previous two editions to observe market changes. Research conclusions are as follows: (1) From the perspective of development trends: the scale expansion of China's digital content industry has slowed down; short videos continue to increase; user value operation becomes a new test under routine pandemic prevention and control; the competitive landscape among sub-sectors tends to be stable; leading enterprises expand their business territory via investment, merger and acquisition (M&A) for the integration of upstream and downstream industrial chain. (2) From the results of investment value assessment and investment trends: live streaming and online games lead the way of investment forward in the digital content industry, thanks to their mature cash realization model and huge market space, with the investment value ranking rising to the top two; in the video field, vertical content creation of short video, online video-related intelligent technology and digital marketing are worthy of attention; and in the digital reading field, focus can be placed on original content creation and novel/comic reading platforms. [ABSTRACT FROM AUTHOR]

Ag nanoparticles (NPs) were introduced into Er3+/Tm3+ codoped tellurite glasses prepared using melt-quenching and heat-treated techniques. The glass samples were characterized by the differential scanning calorimeter (DSC), X-ray diffraction (XRD), transmission electron microscopy (TEM) and photoluminescence to reveal the Ag NPs induced broadband near-infrared band emission enhancement of Er3+/Tm3+ ions. The studied glasses possessed good thermal stability with ΔT larger than 137 °C. For glass sample heat-treated at 360 °C for 6 h, the nucleated Ag NPs in near-spherical shape with an average diameter about 6.5 nm dispersed in the glass matrix. Under the excitation of 808 nm laser diode (LD), the broadband near-infrared fluorescence emission extending from 1 350 nm to 1 620 nm, owing to the combined contributions from the 3H4→3F4 transition of Tm3+ at 1.47 μm band and the 4I13/2→4I15/2 transition of Er3+ at 1.53 μm band, improved significantly with the introduction of Ag NPs, which is mainly attributed to the increased local electric field. The present results indicate that Er3+/Tm3+/Ag NPs codoped tellurite glass with good thermal stability is a promising glass material for broadband fiber amplifiers of WDM transmission systems. [ABSTRACT FROM AUTHOR]

Key message: MANNANASE7 gene inBrassica napus L. encodes a hemicellulose which located at cell wall or extracellular space and dehiscence-resistance can be manipulated by altering the expression ofMANNANASE7. Silique dehiscence is an important physiological process in plant reproductive development, but causes heavy yield loss in crops. The lack of dehiscence-resistant germplasm limits the application of mechanized harvesting and greatly restricts the rapeseed (Brassica napus L.) production. Hemicellulases, together with cellulases and pectinases, play important roles in fruit development and maturation. The hemicellulase gene MANNANASE7 (MAN7) was previously shown to be involved in the development and dehiscence of Arabidopsis (Arabidopsis thaliana) siliques. Here, we cloned BnaA07g12590D (BnMAN7A07), an AtMAN7 homolog from rapeseed, and demonstrate its function in the dehiscence of rapeseed siliques. We found that BnMAN7A07 was expressed in both vegetative and reproductive organs and significantly highly expressed in leaves, flowers and siliques where the abscission or dehiscence process occurs. Subcellular localization experiment showed that BnMAN7A07 was localized in the cell wall. The biological activity of the BnMAN7A07 protein isolated and purified through prokaryotic expression system was verified to catalyse the decomposition of xylan into xylose. Phenotypic studies of RNA interference (RNAi) lines revealed that down-regulation of BnMAN7A07 in rapeseed could significantly enhance silique dehiscence-resistance. In addition, the expression of upstream silique development regulators is altered in BnMAN7A07-RNAi plants, suggesting that a possible feedback regulation mechanism exists in the regulation network of silique dehiscence. Our results demonstrate that dehiscence-resistance can be manipulated by altering the expression of hemicellulase gene BnMAN7A07, which could provide an available genetic resource for breeding practice in rapeseed which is beneficial to mechanized harvest. [ABSTRACT FROM AUTHOR]

Recent studies have revealed that proper exercise can reduce the risk of chronic disease and is beneficial to the body. Peptides have been shown to play an important role in various pathological processes, including cardiovascular diseases. However, little is known about the role of exercise-induced peptides in cardiovascular disease. We aimed to explore the function and mechanism of TAG-23 peptide in reperfusion injury and oxidative stress. Treatment with TAG-23 peptide significantly improved cell viability, the mitochondrial membrane potential, and ROS levels and reduced LDH release, the apoptosis rate and caspase 3 activation in vitro. In vivo, TAG-23 ameliorated MI and heart failure induced by I/R or DOX treatment. Pull-down assays showed that TAG-23 can bind to PKG . The TAG-23-PKG complex inhibited PKG degradation through the UPS. We also identified cCbl as the E3 ligase of PKG and found that the interaction between these proteins was impaired by TAG-23 treatment. In addition, we provided evidence that TAG-23 mediated Lys48-linked polyubiquitination and subsequent proteasomal degradation. Our results reveal that a novel exercise-induced peptide, TAG-23, can inhibit PKG degradation by serving as a competitive binding peptide to attenuate the formation of the PKG–cCbl complex. Treatment with TAG-23 may be a new therapeutic approach for reperfusion injury. [ABSTRACT FROM AUTHOR]

Polychlorinated biphenyls (PCBs) are released into the environment from a wide range of sources. The aim of the present study was to investigate the effect of the PCBs extracted from the Zhanjiang mangrove sediments on the immune function of zebrafish. The sediments were collected from 3 mangrove forest points in Zhanjiang (Guangdong Province, China), and the results showed that PCB153 was detected in the sediments of the Guangdong Zhanjiang Mangrove National Nature Reserve (MNNR) and Gaoqiao Mangrove Reserve (GMR), while PCB101, PCB112, PCB155, and PCB198 were detected in the sediments of the Leizhou Peninsula (LP). The zebrafish were exposed to different concentrations of PCBs, i.e., control group, positive control group (Aroclor1254; 10 μg/L), low dose group (LD; 0.6 μg/L), medium-dose group (MD; 3.0 μg/L) and high dose group (HD; 15 μg/L) for 14 days. As compared to the control group, the liver index increased significantly in all PCB treated groups. The liver tissue structure was destroyed in all PCB-treated groups as compared to the control group. In addition, the relative mRNA expression of the target genes (IL-1β, IL-8, and TNF-α) was significantly expressed in each concentration group. Therefore, these findings suggest that exposure of zebrafish to PCBs can destroy the liver histology and increase the liver index and mRNA expression of inflammatory cytokines in a dose and time-dependent manner. [ABSTRACT FROM AUTHOR]

The recommendation system recommends information and services to users by collecting and analyzing user behaviors. Many current studies have shown that recommendation algorithms that integrate social network information can effectively improve recommendation performance. Most of the existing social recommendation algorithms assume that the trust relationship between users is singular and homogeneous. These social recommendation algorithms generally ignore two problems: (i) in a network of trust relationships, each user has various friends and trust relationships, which have an impact on user ratings. (ii) each user with different social status, which influences also affects the ratings between users. Propose a social network recommendation algorithm (Social Strength Trust Recommendation Algorithm, SSTRA) in this paper. Firstly, the algorithm uses the different out-degree and in-degree relationships among different users to calculate the different trust strengths of each user in social networks; secondly, it calculates the social influence of different users through the social ranking algorithm (SocailRank); thirdly, it will be based on the trust strength relationship of social networks and the social influence of users are integrated into the probability matrix factorization model. This method can achieve the purpose of optimizing recommendation results. The experimental results compared on the CiaoDVD dataset show that: Compared with the SocialMF, SoRec, RSTE, PMF, and Trust algorithms, the average MAE has increased by 1.33%, 1.69%, 4.88%, 11.17% and 220.41%, and the average RMSE has increased by 1.47%, 1.9%, 5.06%, 7.27%, 217.55%. The experimental results compared on the Ciao dataset show that: Compared with the SocialMF, SoRec, RSTE, PMF, and Trust algorithms, the average MAE is increased by 4.83%, 5.05%, 1.96%, 5.58%, 143.39%, and the average RMSE is increased by 1.76%, 2.17%, 2.1%, 2.38%, 151.1%. Experimental results show that the algorithm has obvious advantages in recommendation accuracy. [ABSTRACT FROM AUTHOR]

Remarkable progress has been achieved on microseismic signal denoising in recent years, which is the basic component for rock-burst detection. However, its denoising effectiveness remains unsatisfactory. To extract the effective microseismic signal from polluted noisy signals, a novel microseismic signal denoising method that combines the variational mode decomposition (VMD) and permutation entropy (PE), which we denote as VMD—PE, is proposed in this paper. VMD is a recently introduced technique for adaptive signal decomposition, where K is an important decomposing parameter that determines the number of modes. VMD provides a predictable effect on the nature of detected modes. In this work, we present a method that addresses the problem of selecting an appropriate K value by constructing a simulation signal whose spectrum is similar to that of a mine microseismic signal and apply this value to the VMD—PE method. In addition, PE is developed to identify the relevant effective microseismic signal modes, which are reconstructed to realize signal filtering. The experimental results show that the VMD—PE method remarkably outperforms the empirical mode decomposition (EMD)—VMD filtering and detrended fluctuation analysis (DFA)—VMD denoising methods of the simulated and real microseismic signals. We expect that this novel method can inspire and help evaluate new ideas in this field. [ABSTRACT FROM AUTHOR]

Given an undirected graph G = (V , E) , the k-path partition problem is to find a collection of vertex-disjoint paths containing at most k vertices to cover all the vertices of V. The objective is to minimize the number of paths in the collection. For the k-path partition problem with k ≥ 3 , we propose a simple local search algorithm, whose approximation ratio improves on the best-known approximation algorithm in Chen (in: Chen, Li, Zhang (eds) Frontiers of algorithmics, Springer, Cham, 2022) for every k ≥ 4 , especially for k = 4 , 5 , 6 , 7 . In addition, we give examples to show that our algorithm is tight when k is odd. When k is even, we give almost tight examples. [ABSTRACT FROM AUTHOR]

The mid-infrared (mid-IR) is a strategically important band for numerous applications ranging from night vision to biochemical sensing. Here we theoretically analyzed and experimentally realized a Huygens metasurface platform capable of fulfilling a diverse cross-section of optical functions in the mid-IR. The meta-optical elements were constructed using high-index chalcogenide films deposited on fluoride substrates: the choices of wide-band transparent materials allow the design to be scaled across a broad infrared spectrum. Capitalizing on a two-component Huygens’ meta-atom design, the meta-optical devices feature an ultra-thin profile (λ0/8 in thickness) and measured optical efficiencies up to 75% in transmissive mode for linearly polarized light, representing major improvements over state-of-the-art. We have also demonstrated mid-IR transmissive meta-lenses with diffraction-limited focusing and imaging performance. The projected size, weight and power advantages, coupled with the manufacturing scalability leveraging standard microfabrication technologies, make the Huygens meta-optical devices promising for next-generation mid-IR system applications. [ABSTRACT FROM AUTHOR]

The microwave electrodeless lamp UV photocatalysis (MWUV) integrated with iron carbon micro-electrolysis (ME) was applied to degrade reactive brilliant red X-3B. In the present study, the removal rate of X-3B by MWUV/ME was 95%, which was significantly higher than 56% of MWUV and 62% of ME system. The experiment results demonstrated a synergistic effect in MWUV/ME system, wherein the ME system played an important role in color removal and the formation of ·OH in photocatalysis contributed most for the mineralization of X-3B and its intermediates. The removal efficiency of TOC was 32%, 7.5%, and 59.5% under MWUV, ME, and MWUV/ME processes at the end of the reaction, respectively. The Fe3+ existed in the system was an enhancer of producing ·OH via self-generation of ·OH by UV irradiation or improving the separation of electron-hole in photocatalysis by capturing the electrons. Therefore, the combined treatment of MWUV and ME system has the potential of synergistic effect compared to the separate process. Lowering the initial solution pH and increasing the iron filing dosage and dissolved oxygen were beneficial for the enhancement of degradation efficiency. The inorganic anions showed a diversity influencing the degradation of X-3B. NO3−, CO32−, and SO42− (at higher concentration) promoted the degradation reaction, while Cl− had non-significant effect. [ABSTRACT FROM AUTHOR]

These authors contributed equally: Zhuo-Qi Liu, Ping-Yang Zhu.Correction to: Scientific Datahttps://doi.org/10.1038/s41597-024-03812-0, published online 28 August 2024In this article the author name Zhuo-Qi Liu was incorrectly written as Zhou-Qi Liu. The original article has been corrected.By Zhuo-Qi Liu; Ping-Yang Zhu; Ni-Tong Xu; Yi Wan; Jin-Li Zhang; Xun Zhou; Yu-Xuan Ye; Hong-Xing Xu and Hai-Jun XuReported by Author; Author; Author; Author; Author; Author; Author; Author; Author [Extracted from the article]

Due to its potential application in signal analysis and image processing, quaternionic Fourier analysis has received increasing attention. This paper addresses quaternionic subspace Gabor frames under the condition that the products of time-frequency shift parameters are rational numbers. We characterize subspace quaternionic Gabor frames in terms of quaternionic Zak transformation matrices. For an arbitrary subspace Gabor frame, we give a parametric expression of its Gabor duals of type I and type II, and characterize the uniqueness Gabor duals of type I and type II. And as an application, given a Gabor frame for the whole space L 2 (R 2 , H) , we give a parametric expression of its all Gabor duals, and derive its unique Gabor dual of type II. Some examples are also provided. [ABSTRACT FROM AUTHOR]

Although the digital content industry (DCI) has been booming in recent years, there is no generally accepted definition of the industry. On the basis of reviewing prior studies on the subject, this paper traces the origin of the concept, explains the meaning of the industry, summarizes why some commonly-seen definitions were concluded, looks at their similarities and differences, and defines the relationship between DCI with other similar concepts like content industry, creative industry, copyright industry, information industry and information service industry. The paper then proposes the authors' understanding of DCI—an industrial cluster where cultural creation integrates with the information technology in various areas. [ABSTRACT FROM AUTHOR]

The dynamics, duration, and nature of immunity produced during SARS-CoV-2 infection are still unclear. Here, we longitudinally measured virus-neutralising antibody, specific antibodies against the spike (S) protein, receptor-binding domain (RBD), and the nucleoprotein (N) of SARS-CoV-2, as well as T cell responses, in 25 SARS-CoV-2-infected patients up to 121 days post-symptom onset (PSO). All patients seroconvert for IgG against N, S, or RBD, as well as IgM against RBD, and produce neutralising antibodies (NAb) by 14 days PSO, with the peak levels attained by 15-30 days PSO. Anti-SARS-CoV-2 IgG and NAb remain detectable and relatively stable 3-4 months PSO, whereas IgM antibody rapidly decay. Approximately 65% of patients have detectable SARS-CoV-2-specific CD4+ or CD8+ T cell responses 3-4 months PSO. Our results thus provide critical evidence that IgG, NAb, and T cell responses persist in the majority of patients for at least 3-4 months after infection. [ABSTRACT FROM AUTHOR]

With the continuous development of Internet technology, data gradually present a complicated and high-dimensional trend. These high-dimensional data have a large number of redundant features and irrelevant features, which bring great challenges to the existing machine learning algorithms. Feature selection is one of the important research topics in the fields of machine learning, pattern recognition and data mining, and it is also an important means in the data preprocessing stage. Feature selection is to look for the optimal feature subset from the original feature set, which would improve the classification accuracy and reduce the machine learning time. The traditional feature selection algorithm tends to ignore the kind of feature which has a weak distinguishing capacity as a monomer, whereas the feature group's distinguishing capacity is strong. Therefore, a new dynamic interaction feature selection (DIFS) algorithm is proposed in this paper. Initially, under the theoretical framework of interactive information, it redefines the relevance, irrelevance and redundancy of the features. Secondly, it offers the computational formulas for calculating interactive information. Finally, under the eleven data sets of UCI and three different classifiers, namely, KNN, SVM and C4.5, the DIFS algorithm increases the classification accuracy of the FullSet by 3.2848% and averagely decreases the number of features selected by 15.137. Hence, the DIFS algorithm can not only identify the relevance feature effectively, but also identify the irrelevant and redundant features. Moreover, it can effectively improve the classification accuracy of the data sets and reduce the feature dimensions of the data sets. [ABSTRACT FROM AUTHOR]

Objective: To develop a fully automated AI system to quantitatively assess the disease severity and disease progression of COVID-19 using thick-section chest CT images. Methods: In this retrospective study, an AI system was developed to automatically segment and quantify the COVID-19-infected lung regions on thick-section chest CT images. Five hundred thirty-one CT scans from 204 COVID-19 patients were collected from one appointed COVID-19 hospital. The automatically segmented lung abnormalities were compared with manual segmentation of two experienced radiologists using the Dice coefficient on a randomly selected subset (30 CT scans). Two imaging biomarkers were automatically computed, i.e., the portion of infection (POI) and the average infection HU (iHU), to assess disease severity and disease progression. The assessments were compared with patient status of diagnosis reports and key phrases extracted from radiology reports using the area under the receiver operating characteristic curve (AUC) and Cohen's kappa, respectively. Results: The dice coefficient between the segmentation of the AI system and two experienced radiologists for the COVID-19-infected lung abnormalities was 0.74 ± 0.28 and 0.76 ± 0.29, respectively, which were close to the inter-observer agreement (0.79 ± 0.25). The computed two imaging biomarkers can distinguish between the severe and non-severe stages with an AUC of 0.97 (p value < 0.001). Very good agreement (κ = 0.8220) between the AI system and the radiologists was achieved on evaluating the changes in infection volumes. Conclusions: A deep learning–based AI system built on the thick-section CT imaging can accurately quantify the COVID-19-associated lung abnormalities and assess the disease severity and its progressions. Key Points: • A deep learning–based AI system was able to accurately segment the infected lung regions by COVID-19 using the thick-section CT scans (Dice coefficient ≥ 0.74). • The computed imaging biomarkers were able to distinguish between the non-severe and severe COVID-19 stages (area under the receiver operating characteristic curve 0.97). • The infection volume changes computed by the AI system were able to assess the COVID-19 progression (Cohen's kappa 0.8220). [ABSTRACT FROM AUTHOR]

Background: The majority of GISTs express mutationally activated KIT. Imatinib and sunitinib are approved KIT-inhibiting therapies. Their efficacy is usually hampered by the acquired multiple secondary drug-resistance KIT mutations. The most problematic resistance subset is GISTs with acquisition of secondary mutations in the KIT activation loop. Here, we establish the spectrum of activity of dasatinib against a comprehensive collection of clinically relevant KIT mutants associated with drug-sensitive and drug-resistant GIST. Methods: The cellular and in vitro activities of tyrosine kinase inhibitors (TKIs) against mutant KIT were assessed using a panel of engineered and GIST-derived cell lines. The in vivo activities of dasatinib were determined using TKI-resistant xenograft models. Results: In engineered and GIST-derived cell lines, dasatinib potently inhibited KIT with primary mutations in exon 11 or 9 and a range of secondary imatinib-resistant mutations in exons 13 and 14, encoding the ATP-binding pocket, and in exons 17 and 18, encoding the activation loop, with the exception of a substitution at codon T670. Our data show that dasatinib is more potent than imatinib or sunitinib at inhibiting the activity of drug-resistant KIT mutants. Dasatinib also induces regression in GIST-derived xenograft models containing these secondary mutations. A major determinant of the efficacy of dasatinib for the treatment of advanced GIST is the activity of this inhibitor against KIT mutants. Conclusion: Dasatinib shows efficacy in cancer models, inhibiting a wide range of oncogenic primary and drug-resistant KIT mutants. These results have implications for the further development of dasatinib precision therapy in GIST patients. [ABSTRACT FROM AUTHOR]

This paper uses the core contents of the recently published book titled Market Patterns and Investment Insights of China's Digital Content Industry in 2020, which is authored by a team at the Chinese Academy of Press and Publication (CAPP) and is one of the most authoritative report about China's digital content industry. Analyzing the latest development of this industry, this paper re-defines it and focuses on ten segments—online game, animation, online video, short video, streaming, online music, digital reading, news APP, online education and knowledge payment. This paper estimates their investment value on two dimensions (internal and external), including seven level-1 indicators and eleven level-2 ones, and obtains the investment value ranking list of the segments. It systematically expounds the status quo and characteristics of Chinese digital content industry in such aspects as market development, conversion rate, competition, investment and financing tendency, relevant policies and traditional mainstream media reports, and predicts ten market trends. The paper comes to the following conclusion: ① In terms of investment value: short video and online video have the highest score in ten segments; ② Regarding investment prospects: video content, original content, vertical IP incubation are worth the most attention; ③ Regarding prospects, Chinese digital content industry is in the stage of expansion, with short video performing the best and entering the stage of "intensive cultivation", while content payment may lead a new round of growth. [ABSTRACT FROM AUTHOR]