MEK-mediated CHPF2 phosphorylation promotes colorectal cancer cell proliferation and metastasis by activating NF-κB signaling.

The cytokine tumor necrosis factor (TNF) plays a crucial role in the proliferation and metastasis of colorectal cancer (CRC) cells, but the underlying mechanisms remain poorly understood. Here, we report that chondroitin polymerizing factor 2 (CHPF2) promotes CRC cell proliferation and metastasis mediated by TNF, independently of its enzymatic activity. CHPF2 is highly expressed in CRC, and its elevated expression is associated with poor prognosis of CRC patients. Mechanistically, upon TNF stimulation, CHPF2 is phosphorylated at the T588 residue by MEK, enabling CHPF2 to interact with both TAK1 and IKKα. This interaction enhances the binding of TAK1 and IKKα, leading to increased phosphorylation of the IKK complex and activation of NF-κB signaling. As a result, the expression of early growth factors (EGR1) is upregulated to promote CRC cell proliferation and metastasis. In contrast, introduction of a phospho-deficient T588A mutation in CHPF2 weakened the interaction between CHPF2 and TAK1, thus impairing NF-κB signaling. CHPF2 T588A mutation reduced the ability of CHPF2 to promote the proliferation and metastasis of CRC in vitro and in vivo. Furthermore, the NF-κB RELA subunit promotes CHPF2 expression, further amplifying TNF-induced NF-κB signaling activation. These findings identify a moonlighting function of CHPF2 in promoting tumor cell proliferation and metastasis and provide insights into the mechanism by which CHPF2 amplifies TNF-mediated NF-κB signaling activation. Our study provides a molecular basic for the development of therapeutic strategies for CRC treatment.

A Convolutional Neural Network for Automated Detection of Cervical Ossification of the Posterior Longitudinal Ligament using Magnetic Resonance Imaging.

STUDY DESIGN: Retrospective cohort study. OBJECTIVE: We aimed to develop and validate a convolutional neural network (CNN) model to distinguish between cervical ossification of posterior longitudinal ligament (OPLL) and multilevel degenerative spinal stenosis using Magnetic Resonance Imaging (MRI) and to compare the diagnostic ability with spine surgeons. SUMMARY OF BACKGROUND DATA: Some artificial intelligence models have been applied in spinal image analysis and many of promising results were obtained; however, there was still no study attempted to develop a deep learning model in detecting cervical OPLL using MRI images. MATERIALS AND METHODS: In this retrospective study, 272 cervical OPLL and 412 degenerative patients underwent surgical treatment were enrolled and divided into the training (513 cases) and test dataset (171 cases). CNN models applying ResNet architecture with 34, 50, and 101 layers of residual blocks were constructed and trained with the sagittal MRI images from the training dataset. To evaluate the performance of CNN, the receiver operating characteristic curves of 3 ResNet models were plotted and the area under the curve were calculated on the test dataset. The accuracy, sensitivity, and specificity of the diagnosis by the CNN were calculated and compared with 3 senior spine surgeons. RESULTS: The diagnostic accuracies of our ResNet34, ResNet50, and ResNet101 models were 92.98%, 95.32%, and 97.66%, respectively; the area under the curve of receiver operating characteristic curves of these models were 0.914, 0.942, and 0.971, respectively. The accuracies and specificities of ResNet50 and ResNet101 models were significantly higher than all spine surgeons; for the sensitivity, ResNet101 model achieved better values than that of the 2 surgeons. CONCLUSION: The performance of our ResNet model in differentiating cervical OPLL from degenerative spinal stenosis using MRI is promising, better results were achieved with more layers of residual blocks applied.

Biological informed graph neural network for tumor mutation burden prediction and immunotherapy-related pathway analysis in gastric cancer.

Tumor mutation burden (TMB) has emerged as an essential biomarker for assessing the efficacy of cancer immunotherapy. However, due to the inherent complexity of tumors, TMB is not always correlated with the responsiveness of immune checkpoint inhibitors (ICIs). Thus, refining the interpretation and contextualization of TMB is a requisite for enhancing clinical outcomes. In this study, we conducted a comprehensive investigation of the relationship between TMB and multi-omics data across 33 human cancer types. Our analysis revealed distinct biological changes associated with varying TMB statuses in STAD, COAD, and UCEC. While multi-omics data offer an opportunity to dissect the intricacies of tumors, extracting meaningful biological insights from such massive information remains a formidable challenge. To address this, we developed and implemented the PGLCN, a biologically informed graph neural network based on pathway interaction information. This model facilitates the stratification of patients into subgroups with distinct TMB statuses and enables the evaluation of driver biological processes through enhanced interpretability. By integrating multi-omics data for TMB prediction, our PGLCN model outperformed previous traditional machine learning methodologies, demonstrating superior TMB status prediction accuracy (STAD AUC: 0.976 ± 0.007; COAD AUC: 0.994 ± 0.007; UCEC AUC: 0.947 ± 0.023) and enhanced interpretability (BA-House: 1.0; BA-Community: 0.999; BA-Grid: 0.994; Tree-Cycles: 0.917; Tree-Grids: 0.867). Furthermore, the biological interpretability inherent to PGLCN identified the Toll-like receptor family and DNA repair pathways as potential combined biomarkers in conjunction with TMB status in gastric cancer. This finding suggests a potential synergistic targeting strategy with immunotherapy for gastric cancer, thus advancing the field of precision oncology.

Influence of Group Training Based on Psychological Capital Theory on Nursing Staff's Occupational Benefits and Job Satisfaction in an Infusion Preparation Center.

Context: While they play an increasingly important role in medication safety, nursing staff in an infusion preparation center also face high work intensity and high occupational-exposure risks. Psychological capital for nurses manifests as ab ability to overcome difficulties; nurses' perceptions of occupational benefits can enable them to think and function in a constructive and rational way in a clinical environment; and job satisfaction can influence the nursing quality. Objective: The study intended to investigate and analyze the influence of group training based on psychological capital theory on the nursing staff's psychological capital, occupational benefits, and job satisfaction in an infusion preparation center. Design: The research team performed a prospective, randomized controlled study. Setting: The study took place at the First Medical Center of the Chinese People's Liberation Army (PLA) General Hospital in Beijing, People's Republic of China. Participants: Participants were 54 nurses working in the infusion preparation center at the hospital between September 2021 and November 2021. Intervention: The research team randomly divided the participants into an intervention and a control group, each with 27 participants, using a random number list. Nurses in the intervention group received group training based on the psychological capital theory, while those in the control group received a routine psychological intervention. Outcome Measures: At baseline and postintervention, the study compared the scores for psychological capital, occupational benefits, and job satisfaction between the two groups. Results: At baseline, no statistically significant differences existed between the intervention and control groups on their scores related to psychological capital, occupational benefits, or job satisfaction. Postintervention, the intervention group's scores were significantly higher (1) for psychological capital-hope (P = .004), resilience (P = .000), optimism (P = .001), self-efficacy (P = .000) and total psychological capital score (P = .000); (2) for occupational benefits-career perception (P = .021), sense of belonging to a team (P = .040), and career benefit total score (P = .013); and (3) for job satisfaction-occupational recognition (P = .000), personal development (P = .001), relationships with colleagues (P = .004), the work itself (P = .003), workload (P = .036), management (P = .001), family and work balance (P = .001), and total score for job satisfaction (P = .000). Postintervention, no significant differences existed between the groups (P > .05): (1) for occupational benefits-identity of relatives and friends, self-growth, or nurse-patient relationships or (2) for job satisfaction-salary and benefits. Conclusions: Implementing group training based on psychological capital theory can improve the psychological capital, occupational benefits, and job satisfaction of nurses in the infusion preparation center.

A new perspective to promote sustainable low-carbon consumption: The influence of informational incentive and social influence.

In the era of internet-based information, how to promote sustainable low-carbon consumption by residents through information incentives and social influence is a pressing question that needs to be solved urgently. This study develops an explanatory model to explain how information incentives and social influence affect sustainable low-carbon consumption by residents. Data were collected from residents by large-scale online surveys in China. Partial least squares (PLS) regression was used to evaluate the model in its theory-mediated model scope to make it better than multiple regression. The empirical results show that purchase behavior, daily use behavior, waste disposal behavior, and public participation behavior define sustainable low-carbon consumption behavior; information incentives and social influence are two important predictors for low-carbon consumption behavior; at the level of information motivation, emotional information has a greater impact on low-carbon consumption behavior than rational information; and at the level of social influence, the influence of peer imitation is greater than that of endorsements and social norms. This study provides interesting insights into the important role of information and social networks for promoting low-carbon consumption behavior. Finally, we propose an information-based guidance policy to promote low-carbon consumption behavior based on social influence.

Characterization of the complete chloroplast genome of Peltoboykinia tellimoides (Saxifragaceae).

Peltoboykinia tellimoides, which is distributed in Japan and China, is the type species of Peltoboykinia. In this study, we sequenced and assembled the complete chloroplast (cp) genome of P. tellimoides and reconstructed the phylogeny of Saxifragaceae based on the whole cp genome sequences. The cp genome of P. tellimoides was 156,274 bp in length, comprising a pair of inverted repeat regions (25,099 bp) separated by a large single copy region (88,109 bp) and a small single copy region (17,967 bp). The genome encoded 112 unique genes consisting of 78 different protein-coding genes, 30 transfer RNA and four ribosomal RNA genes, with 16 duplicated genes in the inverted repeats. Phylogenetic analysis indicated that P. tellimoides together with three Chrysosplenium species formed a high support clade, which was sister to Micranthes melanocentra.

Exploring development and evolutionary trends in carbon offset research: a bibliometric perspective.

This study proposes a bibliometric measure to visualize and analyze the research status and development trend of carbon offset based on 1,581 articles over the period 1900-2019. The main findings include (1) carbon offset research turned into a rapid growth after 2009; (2) environmental studies, environmental science, economics, and energy fuels are the top four research domains in publication; (3) Energy Policy, Ecological Economics and Science are the top three journals in terms of citation impact; (4) climate change, impact, emission, CO2 emission, and policy are shown to be the most frequently used keywords; (5) the top 10 cited articles cover the following five essential aspects: individual carbon offset behavior; forest and land carbon offset; transportation carbon offset; international trade carbon offset; and eco-system service-related carbon offset; (6) eight research hotspots were identified including forest carbon sequestration program, understanding carbon and uncertainty market, policy design, biomass development, Chinese province, increasing adoption, and ecosystem service commodification. These findings suggest that the carbon offset research has been evolved from the theoretical exploration at the early stage to a more diversified conversion of research outputs at the practical level in recent years. Interdisciplinary research towards individual and organizational carbon offset behaviors in a broader context of socio-economic development and cooperation among various agents is the emphasis and direction for future study.

Second primary oral squamous cell carcinoma after radiotherapy: a retrospective cohort study.

BACKGROUND: The purpose of the present study was to investigate the clinicopathological characteristics and prognostic factors of second primary oral squamous cell carcinoma after radiotherapy for head and neck cancer. METHODS: The clinicopathological characteristics of 48 second primary oral squamous cell carcinoma patients with a history of radiotherapy for head and neck cancer were retrospectively analyzed by Kaplan-Meier survival analysis and Cox proportional hazards model, including gender, age, alcohol consumption, smoking, clinical stage, margin status, regional lymph node status, tumor differentiation and treatment mode. RESULTS: The second primary oral squamous cell carcinoma mostly occurred on the tongue [18/48], buccal [12/48] and gingiva [10/48], and the 3- and 5-year overall survival (OS) was 60.3% and 39.4%, respectively. Margin status and extranodal extension were significantly associated with OS, while only margin status was found to be an independent prognostic factor of OS in the Cox proportional hazards model (P=0.003, HR =3.976, 95% CI: 1.596-9.904). CONCLUSIONS: Oral squamous cell carcinoma patients underwent radiotherapy for head and neck cancer show poor survival outcomes. Margin status is an independent prognostic factor of second primary oral squamous cell carcinoma.

The evolution of a collaboration network and its impact on innovation performance under the background of government-funded support: an empirical study in the Chinese wind power sector.

To accelerate the transformation and application of basic research results, the Chinese government has repeatedly mentioned in a government work report that it is necessary to support research and innovation collaborations between knowledge research institutions and enterprises. However, few studies have focused on the evolution of collaborations between these organizations and the impact of collaborations on innovation performance (IP) in the field of renewable energy under the background of government-funded support (GFS). Based on scientific publications, we construct a GFS collaboration network in the wind power field to investigate the evolution of network structure characteristics, attribute proximity variables, and applied research collaboration (ARC), and we study the impact of network evolution on the IP of actors. The results show that the focal actor of the collaboration network prefers to engage in ARC with partners who are familiar and have the same knowledge base in different provinces. This collaboration tendency will reduce geographical proximity and increase the direct ties, indirect ties, technological proximity, and ARC of the ego network. Among them, direct ties have an inverted U-shaped effect on IP, geographical proximity has a significantly negative impact on IP, and the remaining variables have positive impacts on IP. Taken together, when the direct ties is within a certain range, these collaboration tendencies in a GFS collaboration network positively affect the IP of research institutions and enterprises.

Validation of Gene Profiles for Analysis of Regional Lymphatic Metastases in Head and Neck Squamous Cell Carcinoma.

The progress of Head and Neck Squamous Cell Carcinoma (HNSCC) is dependent on both cancer stem cells (CSCs) and immune suppression. This study was designed to evaluate the distribution of CSCs and the characteristic immune suppression status in HNSCC primary tumors and lymph nodes. A total of 303 lymph nodes from 25 patients, as well as tumor and adjacent normal tissue samples, were evaluated by a quantitative PCR assay of the markers of CSCs and the characteristic immune suppression. Expressions of selected genes in The Cancer Genome Atlas (TCGA) datasets were also analyzed. In the primary tumors, we found that expressions of CSCs markers (ALDH1L1, PECAM1, PROM1) were down-regulated, while immune suppression markers FOXP3, CD47, EGFR, SOX2, and TGFB1 were up-regulated significantly when compared to that in adjacent normal tissues. In the lymph nodes, expressions of both CSCs, and immune suppression markers were upregulated significantly compared with that in primary tumors. The mRNA expression of selected CSCs and immune suppression markers exhibited the highest expression in the level II of metastasis, then declined in the level III and remained constant at a reduced value in levels IV and V of metastases. These results reveal a comprehensive understanding of the unique genetic characteristics associated with metastatic loci and potential routes of lymphatic dissemination of HNSCC, which helps to explain why the level II has a high incidence of lymph node metastasis, and why skip metastasis straight to the level IV or level V is rarely found in the clinic.

The Influence of Information Intervention Cognition on College Students' Energy-Saving Behavior Intentions.

Based on the theory of planned behavior, this research examines the influence of different types of information on the behavioral intentions of college students in the context of perceived behavioral control (perceived self-efficacy and perceptual control) as mediating variables. The results showed that: (1) Different types of information intervention factors have different effects on perceptual self-efficacy and perceptual control; the influence degree of economic cost has the strongest effect, followed by group pressure, while the influence degree of publicity and education has the weakest effect. However, policy intervention has no statistically significant effect on both of them (perceived self-efficacy and perceptual control). (2) Two variables, perceived self-efficacy and perceptual control, serve as mediators between information intervention factors and energy-saving behavior intention. (3) Individual characteristic factors have significant moderating effects on each path in the model of information intervention-perceived behavior control-intention. Finally, suggestions are made on how to encourage college students to more effectively save energy.

Can environmental innovation benefit from outward foreign direct investment to developed countries? Evidence from Chinese manufacturing enterprises.

Environmental innovation is an important way to low-carbon economic growth. Outward foreign direct investment (OFDI) can produce reverse technology transfer to promote innovation. This study aims to examine whether OFDI to developed countries can transfer reverse green technology and promote the environmental innovation of manufacturing enterprises in emerging economies (EEs). Based on the technology gap theory, resource bricolage theory, resource-based view, and Potter hypothesis, this study constructs a conceptual model including the direct effect of OFDI on environmental innovation and the moderating effects of the knowledge level of the host country, multinational strategy, absorptive capacity, and environmental regulation. To verify the model, we also use a panel dataset of 424 Chinese manufacturing enterprises during 2010-2017, and the results indicate that OFDI to developed countries can produce reverse green technology transfer and promote parent companies' environmental innovation. The knowledge level of the host country and multinational strategy can further improve the impacts on environmental product innovation. However, absorptive capacity and environmental regulation in EEs do not play a significant moderating role. Consequently, this study expands the application scope of existing theories and enriches the theoretical basis of the relationship between OFDI and environmental innovation.

Analysis of pharmacological mechanisms and targets mining of Wuzi-Yanzong-Wan for treating non-obstructive oligoasthenospermia.

As a classical traditional Chinese medicine, Wuzi-Yanzong-Wan (WZYZW) has been widely applied for several centuries to treat non-obstructive oligoasthenozoospermia (NOA), although its pharmacological mechanisms remain largely unknown. In this study, both plasma and urine metabolomics profiling was first analysed to explore the therapeutic mechanisms of WZYZW in NOA rats induced by removal of the unilateral testicle. Then, 106 identified compounds comprising WZYZW (our previous work), for which putative targets were discovered using systems pharmacology, were systematically analysed via mRNA microarrays to validate their putative targets. Finally, metabolomics-tested WZYZW-regulated metabolites were connected with validated targets using Spearman correlation analysis to further confirm the targets from a biological perspective. The results suggested that WZYZW plays key roles in modulating the concentrations of 18 metabolites in the metabolism of amino acids, lipids and so on, normalizing the metabolic phenotype and regulating metabolic disorders. Moreover, 27 targets of WZYZW (23 compounds) against NOA were validated, and metabolomics-tested metabolites were also found to be significantly related to these identified targets, suggesting that these targets and compounds are worthy of further research. This work offers the first systematic investigation of the efficacy of WZYZW against NOA and illustrates a practicable approach for explaining the molecular mechanisms of multicomponent drugs.

Cidec differentially regulates lipid deposition and secretion through two tissue-specific isoforms.

Lipid metabolism has important roles in animal growth, development, and reproduction. As a regulator of lipid metabolism, CIDEc promotes unilocular development of lipid droplets and stimulates intracellular lipid deposition, and has two isoforms, CIDEc-l and CIDEc-s. CIDEc-l has ten more N-terminal amino acids than CIDEc-s. However, the functions of two isoforms are largely unknown. In this study, the expression profiles of two isoforms in Bama pigs differed, with cidec-l dominant in the liver and small intestine, and cidec-s dominant in muscle and adipose tissue. Fasting and consuming a high-fat diet resulted in changes in the expression of the two isoforms that were closely related to changes in blood and muscle triglyceride (TG) concentrations. Comparison of gene expression and TG concentration suggested that CIDEc-l accelerated lipid secretion and that CIDEc-s promoted lipid deposition, implying that the two isoforms had different functions. Study In vitro confirmed that CIDEc-s stimulated lipid deposition in C2C12 muscle cells and CIDEc-l promoted lipid secretion in HepG2 liver cells. The results showed that two tissue-specific CIDEc isoforms had different roles in lipid deposition and secretion. They may be potential targets for regulation of fat content.

A developmental toxicity assay of Carpesii Fructus on zebrafish embryos/larvae.

Carpesii Fructus, the dried fruit of Carpesium abrotanoides L., has been used as a traditional Chinese medicine for centuries to kill intestinal parasites in children. It has been recorded as a mildly toxic medicine in the Chinese pharmacopoeia. However, little proof of its toxicology has been reported in modern pharmacology. This study investigated for the first time its developmental toxicity on zebrafish embryos/larvae from 6 to 96 h post-fertilization (hpf). In addition, the enzymes and genes associated with oxidative stress and apoptosis were tested to investigate the potential toxicologic mechanism preliminarily. The observation of toxicologic endpoints showed the developmental toxicity of Carpesii Fructus. Pericardial edema, yolk sac edema, bleeding tendency, and enlarged yolk were the most commonly occurring morphological changes observed in our study. According to the results of acridine orange staining and morphological observation, the developing heart was speculated to be the target organ of toxicity. Furthermore, Carpesii Fructus exposure changed the activities of defense enzymes, increased malondialdehyde (MDA) content, decreased caspase-3 activity, and altered mRNA levels of related genes (ogg1, p53, Cu/Zn-Sod, Mn-Sod, and Cat↓; Gpx↑) in zebrafish larvae, indicating that oxidative stress and additional apoptosis should have roles in the developmental toxicity of Carpesii Fructus. This is the first study that provides proof of modern pharmacology on the teratogenicity and possible toxicologic mechanism of Carpesii Fructus.

The Extraction Model of Paddy Rice Information Based on GF-1 Satellite WFV Images.

In the present, using the characteristics of paddy rice at different phenophase to identify it by remote sensing images is an efficient way in the information extraction. According to the remarkably properties of paddy rice different from other vegetation, which the surface of paddy fields is with a large number of water in the early stage, NDWI (normalized difference water index) which is used to extract water information can reasonably be applied in the extraction of paddy rice at the early stage of the growth. And using NDWI ratio of two phenophase can expand the difference between paddy rice and other surface features, which is an important part for the extraction of paddy rice with high accuracy. Then using the variation of NDVI (normalized differential vegetation index) in different phenophase can further enhance accuracy of paddy rice information extraction. This study finds that making full advantage of the particularity of paddy rice in different phenophase and combining two indices (NDWI and NDVI) associated with paddy rice can establish a reasonable, accurate and effective extraction model of paddy rice. This is also the main way to improve the accuracy of paddy rice extraction. The present paper takes Lai'an in Anhui Province as the research area, and rice as the research object. It constructs the extraction model of paddy rice information using NDVI and NDWI between tillering stage and heading stage. Then the model was applied to GF1-WFV remote sensing image on July 12, 2013 and August 30, 2013. And it effectively extracted out of paddy rice distribution in Lai'an and carried on the mapping. At last, the result of extraction was verified and evaluated combined with field investigation data in the study area. The result shows that using the extraction model can quickly and accurately obtain the distribution of rice information, and it has the very good universality.