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Abstract Background While physicians are considered to be more susceptible to developing depressive symptoms, empirical data are lacking. The study aims to compare the risk of depressive symptoms between emergency physicians and the general population in China based on national data. Methods This was a national cross-sectional study. 10 457 emergency physicians and 101 120 participants from the general population were investigated from July 2018 to August 2018 and January 2019 to February 2019, respectively. PHQ-9 was used to measure depressive symptoms, and a score ≥ 10 indicates major depression. Propensity score matching was adopted to balance the characteristics between emergency physicians and the general population. Multinomial logistic regression model was used to examine the association between occupational groups and the severity of depressive symptoms. Binary logistic regression model was performed to explore the risk factors of major depression among emergency physicians. Results The prevalence of major depression among emergency physicians was 35.7%, whereas among the general population was 13.9%. Emergency physicians had a 3.65 times higher risk of major depression than the general population. And emergency physician was significantly associated with mild (OR: 3.12, 95% CI 2.95–3.30), moderate (OR: 4.94, 95% CI 4.60–5.30), moderately severe (OR: 9.48, 95% CI 8.61–10.44), and severe depressive symptoms (OR: 14.18, 95% CI 12.47–16.13) compared with none depressive symptoms. Even after matching, the results remained consistent. Factors associated with major depression among emergency physicians included bachelor degree or above (OR: 1.22, 95% CI 1.06–1.40), worked long years (OR: 1.26, 95% CI 1.08–1.46 for 1–5 years; OR: 1.56, 95% CI 1.32–1.84 for ≥ 6 years), experienced workplace violence (OR: 2.51, 95% CI 2.16–2.94), worked more night shifts per month (OR: 1.33, 95% CI 1.16–1.51 for 6–10 times; OR: 1.83, 95% CI 1.58–2.11 for ≥ 11 times), smoked (OR: 1.64, 95% CI 1.47–1.84), and effort-reward imbalance (OR: 4.18, 95% CI 3.62–4.85). Conclusions Emergency physicians had a higher risk of depressive symptoms than the general population. There is a need for greater awareness of the mental health issues faced by emergency physicians.

Objective To investigate the ability of radiological parameter canal bone ratio (CBR) to assess bone mineral density and to differentiate between patients with primary and multiple osteoporotic vertebral compression fracture (OVCF). Methods A retrospective analysis was conducted on OVCF patients treated at our hospital. CBR was measured through full-spine x-rays. Patients were categorized into primary and multiple fracture groups. Receiver operating characteristic curve analysis and area under the curve (AUC) calculation were used to assess the ability of parameters to predict osteoporosis and multiple fractures. Predictors of T values were analyzed by multiple linear regression, and independent risk factors for multiple fractures were determined by multiple logistic regression analysis. Results CBR showed a moderate negative correlation with dual-energy x-ray absorptiometry T values (r = -0.642, p < 0.01). Higher CBR (odds ratio [OR], -6.483; 95% confidence interval [CI], -8.234 to -4.732; p < 0.01) and lower body mass index (OR, 0.054; 95% CI, 0.023–0.086; p < 0.01) were independent risk factors for osteoporosis. Patients with multiple fractures had lower T values (mean ±standard deviation [SD]: -3.76 ±0.73 vs. -2.83 ±0.75, p < 0.01) and higher CBR (mean ±SD: 0.54 ±0.07 vs. 0.46 ±0.06, p < 0.01). CBR had an AUC of 0.819 in predicting multiple fractures with a threshold of 0.53. T values prediction had an AUC of 0.816 with a threshold of -3.45. CBR > 0.53 was an independent risk factor for multiple fractures (OR, 14.66; 95% CI, 4.97–43.22; p < 0.01). Conclusion CBR is negatively correlated with bone mineral density (BMD) and can be a novel opportunistic BMD assessment method. It is a simple and effective measurement index for predicting multiple fractures, with predictive performance not inferior to T values.

Abstract The compound NS5806 is a Kv4 channel modulator. This study investigated the chronic effects of NS5806 on cardiac hypertrophy induced by transverse aortic constriction (TAC) in mice in vivo and on neonatal rat ventricular cardiomyocyte hypertrophy induced by endothelin-1 (ET-1) in vitro. Four weeks after TAC, NS5806 was administered by gavage for 4 weeks. Echocardiograms revealed pronounced left ventricular (LV) hypertrophy in TAC-treated mice compared with sham mice. NS5806 attenuated LV hypertrophy, as manifested by the restoration of LV wall thickness and weight and the reversal of contractile dysfunction in TAC-treated mice. NS5806 also blunted the TAC-induced increases in the expression of cardiac hypertrophic and fibrotic genes, including ANP, BNP and TGF-β. Electrophysiological recordings revealed a significant prolongation of action potential duration and QT intervals, accompanied by an increase in susceptibility to ventricular arrhythmias in mice with cardiac hypertrophy. However, NS5806 restored these alterations in electrical parameters and thus reduced the incidence of mouse sudden death. Furthermore, NS5806 abrogated the downregulation of the Kv4 protein in the hypertrophic myocardium but did not influence the reduction in Kv4 mRNA expression. In addition, NS5806 suppressed in vitro cardiomyocyte hypertrophy. The results provide novel insight for further ion channel modulator development as a potential treatment option for cardiac hypertrophy.

Abstract Background Clear cell odontogenic carcinoma (CCOC) is an odontogenic carcinoma characterized by sheets and islands of vacuolated and clear cells. The diagnosis of atypical CCOC can pose a challenge when tumor cells deviate from their characteristic clear morphology, even with the aid of genetic profiling for CCOC identification. Case presentation In this manuscript, we detailed the inaugural instance of a recurrently recurring clear cell odontogenic carcinoma (CCOC) with pronounced squamous differentiation in a 64-year-old male. The primary tumor in this individual initially displayed a biphasic clear cell phenotype. However, subsequent to the third recurrence, the clear tumor cells were entirely supplanted by epidermoid cells characterized by eosinophilic cytoplasm, vesicular chromatin, and prominent nucleoli. Notable aggressive attributes such as necrosis, conspicuous cytological malignancy, perineural dissemination, and vascular invasion were noted. Additionally, the tumor progressed to manifest lung metastases. The tumor cells exhibited positive immunoreactivity for AE1/AE3, KRT19, Pan-CK, EMA, P40, P63, CK34βE12, and P53, while they tested negative for CK35βH11, KRT7, S-100, and neuroendocrine markers. The Ki-67 proliferation index was calculated at an average of 15%. Furthermore, FISH analysis unveiled the presence of the EWSR1::ATF1 gene fusion. Conclusions This case illustrated a rare and aggressive case of CCOC characterized by significant squamous differentiation upon recurrence of the tumor.

Abstract College students represent a burgeoning force in mass entrepreneurship, underscoring the critical need to nurture their entrepreneurial endeavors. This study adopts a quantitative method, surveying 33,660 Chinese college students engaged in entrepreneurial activities. It examines the impact of various entrepreneurial policies and regional entrepreneurship spirit on these students’ decision-making processes. The findings reveal a positive correlation between entrepreneurial policies and entrepreneurial decision-making among college students, with regional entrepreneurship spirit serving as a mediator. Gender influences the relationship between regional entrepreneurship spirit and entrepreneurial decision-making, primarily moderating the effects of supply-based and environmentally-oriented policies. Entrepreneurship must be deeply integrated within China’s unique social networks and informal institutional frameworks. The moderating influence of gender also highlights differing policy impacts among various student groups. This research contributes to the enhancement and understanding of the policy support mechanism’s effect on college students and underscores the necessity for precise implementation of entrepreneurship policies tailored to college students.

Abstract Background Early detection of patients at risk of falling is crucial. This study was designed to develop and internally validate a novel risk score to classify patients at risk of falls. Methods A total of 334 older people from a fall clinic in a medical center were selected. Least absolute shrinkage and selection operator (LASSO) regression was used to minimize the potential concatenation of variables measured from the same patient and the overfitting of variables. A logistic regression model for 1-year fall prediction was developed for the entire dataset using newly identified relevant variables. Model performance was evaluated using the bootstrap method, which included measures of overall predictive performance, discrimination, and calibration. To streamline the assessment process, a scoring system for predicting 1-year fall risk was created. Results We developed a new model for predicting 1-year falls, which included the FRQ-Q1, FRQ-Q3, and single-leg standing time (left foot). After internal validation, the model showed good discrimination (C statistic, 0.803 [95% CI 0.749–0.857]) and overall accuracy (Brier score, 0.146). Compared to another model that used the total FRQ score instead, the new model showed better continuous net reclassification improvement (NRI) [0.468 (0.314–0.622), P

Autoimmune diseases comprise a large group of conditions characterized by a complex pathogenesis and significant heterogeneity in their clinical manifestations. Advances in sequencing technology have revealed that in addition to genetic susceptibility, various epigenetic mechanisms including DNA methylation and histone modification play critical roles in disease development. The emerging field of epigenetics has provided new perspectives on the pathogenesis and development of autoimmune diseases. Aberrant epigenetic modifications can be used as biomarkers for disease diagnosis and prognosis. Exploration of human epigenetic profiles revealed that patients with autoimmune diseases exhibit markedly altered DNA methylation profiles compared with healthy individuals. Targeted cutting-edge epigenetic therapies are emerging. For example, DNA methylation inhibitors can rectify methylation dysregulation and relieve patients. Histone deacetylase inhibitors such as vorinostat can affect chromatin accessibility and further regulate gene expression, and have been used in treating hematological malignancies. Epigenetic therapies have opened new avenues for the precise treatment of autoimmune diseases and offer new opportunities for improved therapeutic outcomes. Our review can aid in comprehensively elucidation of the mechanisms of autoimmune diseases and development of new targeted therapies that ultimately benefit patients with these conditions.

Tumor microenvironment (TME) immune cells and gastric mucosal microbiome constitute two vital elements of tumor tissue. Increasing evidence has elucidated their clinicopathological significance in predicting outcomes and therapeutic efficacy. However, comprehensive characterization of immune cell-associated microbiome signatures in the TME is still in the early stages of development. Here, we characterized the gastric mucosa microbiome and its associations with immune-activated related transcripts (IATs) in 170 GC tumor tissues and matched non-tumor tissues using 16s rRNA gene sequencing and quantitative reverse transcription-PCR. Microbial diversity and richness were significantly higher in GC tumor tissues than in non-tumor tissues. Differences in microbial composition between the groups were evident, with Firmicutes, Proteobacteria, Bacteroidota, Campilobacterota, Actinobacteria, Fusobacteriota, Verrucomicrobiota, Acidobacteriota, and Cyanobacteria being the dominant phyla in the gastric mucosal microbiota. Microbial interaction network analysis revealed distinctive centralities of oral bacteria (such as Fusobacterium, Porphyromonas, Prevotella, etc.) in both tumor and normal mucosae networks, suggesting their significant influence on GC microbial ecology. Furthermore, we analyzed the expression of IATs (CXCL9, CXCL10, GZMA, GZMB, PRF1, CD8A, IFNG, TBX2, and TNF) and characterized IAT-relevant gastric microbiome signatures in GC patients. Our results showed that the expression of CXCL9, CXCL10, GZMA, GZMB, PRF1 and IFNG was significantly higher in tumor tissues than in adjacent normal tissues in GC patients. Notably, high expression of IATs in tumor tissues was associated with improved survival in GC patients and could serve as a powerful predictor for disease-free survival. Additionally, analysis of IAT levels and mucosal microbiota diversity revealed a correlation between higher IAT expression and increased microbiota richness and evenness in the IATs high group, suggesting potential interactions between mucosal microbiota and tumor immunopathology. Spearman correlation analysis showed positive associations between IAT expression and specific mucosal bacterial species. Notably, Akkermansia muciniphila demonstrated potential involvement in modulating GZMB expression in the GC mucosal microenvironment. These findings underscore the importance of mucosal microbiota alterations in GC and suggest potential therapeutic targets focusing on modulating the tumor microbiota for improved clinical outcomes. The detailed characterization of these elements has profound implications for both treatment and survival prediction in GC. We observed that microbial diversity and richness were significantly higher in GC tumor tissues compared to non-tumor tissues. These differences highlight the unique microbial landscape of GC tumors and suggest that the microbiome could influence tumor development and progression. Importantly, our study demonstrated that high expression levels of IATs in GC tumor tissues were associated with improved patient survival. This suggests that IATs not only reflect immune activation but also serve as valuable biomarkers for predicting disease-free survival. The potential of IATs as predictive markers underscores their utility in guiding therapeutic strategies and personalizing treatment approaches. Moreover, the correlation between higher IAT expression and increased microbiota richness and evenness suggests that a diverse and balanced microbiome may enhance immune responses and contribute to better clinical outcomes. These findings highlight the critical need to consider mucosal microbiota alterations in GC management. Targeting the tumor microbiota could emerge as a promising therapeutic strategy, potentially leading to more effective treatments and improved patient outcomes. Understanding and modulating the microbiome’s role in GC opens new avenues for innovative therapeutic interventions and personalized medicine.

IntroductionThis study investigates the experiences of leading Chinese companies in environmental conservation under varying extreme climate conditions, focusing on the role of artificial intelligence (AI) and governmental assistance.MethodsA survey was conducted involving 200 participants to assess recognition and endorsement of AI’s role in environmental protection and to explore the adoption of AI technologies by firms for enhancing environmental management practices.ResultsThe survey revealed widespread recognition of Tencent’s green initiatives and strong support for AI’s role in environmental protection. Many firms are considering adopting AI technologies to optimize energy management, deploy intelligent HVAC systems, and improve the operations of data centers and smart lighting systems.DiscussionThe findings highlight a strong belief in AI’s potential to advance environmental protection efforts, with a call for increased governmental support to foster this development. The study underscores the importance of a partnership between businesses and governments to leverage AI for environmental sustainability, contributing significantly to conservation efforts.

Abstract Background To investigate the impact of wearing spectacle lenses with highly aspherical lenslets (HAL) for 3 years and the impact of switching from single-vision lenses (SVL) to HAL on choroidal thickness (ChT). Methods Fifty-one participants who had already worn HAL for 2 years continued wearing them for an additional year (HAL group). Further, 50 and 41 participants who had worn spectacle lenses with slightly aspherical lenslets (SAL) and SVL for 2 years, respectively, switched to wearing HAL for another year (SAL-HAL and SVL-HAL groups). Additionally, 48 new participants aged 10–15 years were enrolled to wear SVL at the third year (new-SVL group). ChT was measured every 6 months throughout the study. Results Significant differences were observed in the changes in ChT among the four groups at the third year (all P 0.05). When comparing the changes in ChT for 3 years among the HAL, SAL-HAL, and SVL-HAL groups, significant differences were found before switching to HAL, but these differences were abolished after all participants switched to HAL. Conclusions Compared to those in the SVL group, choroid thinning was significantly inhibited in all the HAL groups. Wearing HAL for 3 years no longer had a choroidal thickening effect but could still inhibit choroidal thinning compared to wearing SVL. Trial registration The study was registered at the Chinese Clinical Trial Registry (ChiCTR1800017683), http://www.chictr.org.cn/showproj.aspx?proj=29789 .

Abstract Background Diarrheal diseases caused by viral agents have led to a great morbidity, mortality, and economic loss in global pig industry. Porcine epidemic diarrhea virus (PEDV), transmissible gastroenteritis virus (TGEV), porcine deltacoronavirus (PDCoV), and group A porcine rotavirus (RVA) are main causative agents of swine viral diarrhea with similar clinical signs on Chinese farms and their co-infection is also common. However, it is still lack of a convenient method to detect these four agents. Methods A TaqMan multiplex qPCR method was developed to detect PEDV, TGEV, PDCoV, and RVA, simultaneously. This method was then applied to investigate 7,342 swine fecal samples or rectal swabs, as well as 1,246 swine intestinal samples collected from 2075 farms in China in 2022. Results Minimum detection limits of this method were 3 copies/µL for PEDV, 4 copies/µL for TGEV, 8 copies/µL for RVA, and 8 copies/µL for PDCoV, suggesting a good sensitivity. No signals were observed by using this method detecting other viral agents commonly prevalent in pigs, which is suggestive of a good specificity. Application of this method on investigating clinical samples demonstrated a relatively high positive rate for PEDV (22.21%, 1907/8588) and RVA (44.00%, 3779/8588). In addition, co-infection between PEDV and RVA was observed on 360 investigated farms, accounting for 17.35% (360/2075) of the farms where co-infection events were screened. Conclusions A TaqMan multiplex qPCR method targeting PEDV, TGEV, PDCoV, and RVA was developed in this study. This method demonstrated a good specificity and sensitivity on investigating these four common viruses responsible for viral diarrhea on Chinese pig farms, which represents a convenient method for the monitoring and differential diagnosis of swine viral diarrhea.

Solid solution strengthened ferritic ductile iron (SSFDI) exhibits improved mechanical properties compared to conventional ductile cast iron (DCI) grades, however, its potential widespread application is hindered by unpredictable brittle fracture which might be attributed to microstructural silicon segregation and associated superstructure formation. The aim of the present study is therefore to deepen the understanding on the effect of local silicon segregation on the mechanical properties of SSFDI, which is crucial especially for the common applications of DCI in cyclically loaded structures. Micropillar compression tests were carried out on three different casts to investigate the solution strengthening effect of silicon in the ferritic matrix. An almost perfect linear relationship between critical resolved shear stress (CRSS) and global silicon content was found. It was also found that the variation of CRSS with silicon content corresponds well to the variation of the macroscopic yield limits (under tension and compression) with global silicon content of different SSFDI alloys. This indicates that the ferritic matrix dominates the yield limit of the DCI alloys investigated in this study, while the morphology of the graphite nodules plays a minor role under monotonic loading conditions.

BackgroundThe long-term impact of COVID-19 on the mental health and well-being of college students, specifically trends over time after full removal of COVID-19 restrictions, has not been well-studied.MethodsFour consecutive cross-sectional surveys were conducted in December 2022 (N = 689), March 2023 (N = 456), June 2023 (N = 300), and November 2023 (N = 601) at a university in Sichuan Province, China.ResultsThe proportion of students with COVID-19 panic decreased from 95.1 to 77.3% (p

Abstract Intraperitoneal dissemination is the main method of epithelial ovarian cancer (EOC) metastasis, which is related to poor prognosis and a high recurrence rate. Circular RNAs (circRNAs) are a novel class of endogenous RNAs with covalently closed loop structures that are implicated in the regulation of tumor development. In this study, hsa_circ_0001546 is downregulated in EOC primary and metastatic tissues vs. control tissues and this phenotype has a favorable effect on EOC OS and DFS. hsa_circ_0001546 can directly bind with 14‐3‐3 proteins to act as a chaperone molecule and has a limited positive effect on 14‐3‐3 protein stability. This complex recruits CAMK2D to induce the Ser324 phosphorylation of Tau proteins, changing the phosphorylation status of Tau bound to 14‐3‐3 and ultimately forming the hsa_circ_0001546/14‐3‐3/CAMK2D/Tau complex. The existence of this complex stimulates the production of Tau aggregation, which then induces the accumulation of lipid peroxides (LPOs) and causes LPO‐dependent ferroptosis. In vivo, treatment with ferrostatin‐1 and TRx0237 rescued the inhibitory effect of hsa_circ_0001546 on EOC cell spreading. Therefore, based on this results, ferroptosis caused by Tau aggregation occurs in EOC cells, which is not only in Alzheimer's disease‐ or Parkinson's disease‐related cells and this kind of ferroptosis driven by the hsa_circ_0001546/14‐3‐3/CAMK2D/Tau complex is LPO‐dependent rather than GPX4‐dependent is hypothesized.

Rapid simultaneous detection of multi-component adulteration markers can improve the accuracy of identification of gutter cooking oil in edible oil, which is made possible by broad-spectrum antibody (bs-mAb). This study used capsaicinoids (CPCs) and gingerol derivatives (GDs) as adulteration markers, and two broad-spectrum haptens (bs-haptens) were designed and synthesized based on a reverse design strategy of molecular docking. Electrostatic potential (ESP) and monoclonal antibodies (mAbs) preparation verified the strategy's feasibility. To further investigate the recognition mechanism, five other reported antigens and mAbs were also used. Finally, the optimal combination (Hapten 5-OVA/1-F12) and key functional groups (f-groups) were determined. The half maximal inhibitory concentration (IC50) for CPCs-GDs was between 88.13 and 499.16 ng/mL. Meanwhile, a preliminary lateral flow immunoassay (LFIA) study made practical monitoring possible. The study provided a theoretical basis for the virtual screening of bs-haptens and simultaneous immunoassay of multiple exogenous markers to monitor gutter oil rapidly and accurately.

A novel scheme for generating full-duty-cycle triangular and square pulses based on an optoelectronic oscillator (OEO) is proposed and experimentally demonstrated. The scheme can generate a tuneable fundamental tone corresponding to the repetition rate of the pulses without any external radio frequency source. The “Vernier effect” is realised using two chirped fibre Bragg gratings, which can effectively improve the side-mode suppression ratio. The oscillation frequency is tuned from 2.5 to 6 GHz in an experiment to verify the theory, and the phase noise of the generated fundamental tone is measured to be −115 dBc/Hz at an offset frequency of 10 kHz. By appropriately setting the gain of the OEO loop, the power of the first- and third-order harmonics can be adjusted to meet the required power ratio. Periodical triangular pulses with repetition rates of 5 GHz, 6 GHz and square pulses with repetition rates of 2.5 GHz, 5 GHz were successfully generated. The root–mean–square errors are measured as 0.026 and 0.083 at a repetition rate of 5 GHz.

Abstract Background Male patients with papillary thyroid carcinoma (PTC) tend to have poorer prognosis compared to females, partially attributable to a higher rate of lymph node metastasis (LNM). Developing a precise predictive model for LNM occurrence in male PTC patients is imperative. While preliminary predictive models exist, there is room to improve accuracy. Further research is needed to create optimized prognostic models specific to LNM prediction in male PTC cases. Methods We conducted a comprehensive search of publicly available microarray datasets to identify candidate genes continuously upregulated or downregulated during PTC progression in male patients only. Univariate Cox analysis and lasso regression were utilized to construct an 11-gene signature predictive of LNM. TIPARP emerged as a key candidate gene, which we validated at the protein level using immunohistochemical staining. A prognostic nomogram incorporating the signature and clinical factors was developed based on the TCGA cohort. Results The 11-gene signature demonstrated good discriminative performance for LNM prediction in training and validation datasets. High TIPARP expression associated with advanced stage, high T stage, and presence of LNM. A prognostic nomogram integrating the signature and clinical variables reliably stratified male PTC patients into high and low recurrence risk groups. Conclusions We identified a robust 11-gene signature and prognostic nomogram for predicting LNM occurrence in male PTC patients. We propose TIPARP as a potential contributor to inferior outcomes in males, warranting further exploration as a prognostic biomarker and immunotherapeutic target. Our study provides insights into the molecular basis for gender disparities in PTC.

Abstract Non-alcoholic fatty liver disease (NAFLD) as a chronic disease especially in Western countries, is still a tough question in the clinical therapy. With the rising prevalence of various chronic diseases, liver transplantation is expected to be the most common therapy after the next 10 years. However, there is still no approved drug for NAFLD, and targeted therapy for NAFLD is urgent. Exosomes as a kind of extracellular vesicle are cell-derived nanovesicles, which play an essential role in intercellular communication. Due to complex cell–cell interactions in the liver, exosomes as therapeutic drugs or drug delivery vesicles may be involved in physiological or pathological processes in NAFLD. Compared with other nanomaterials, exosomes as a cell-free therapy, are not dependent on cell number limitation, which means can be administered safely in high doses. Apart from this, exosomes with the advantages of being low-toxic, high stability, and low-immunological are chosen for targeted therapy for many diseases. In this review, firstly we introduced the extracellular vesicles, including the biogenesis, composition, isolation and characterization, and fundamental function of extracellular vesicles. And then we discussed the modification of extracellular vesicles, cargo packing, and artificial exosomes. Finally, the extracellular vesicles for the therapies of NAFLD are summarized. Moreover, we highlight therapeutic approaches using exosomes in the clinical treatment of NAFLD, which provide valuable insights into targeting NAFLD in the clinical setting. Graphical Abstract Video Abstract

Background: Menopause in women marks the knot of reproductive life, and menopause is defined as the last menstrual period in a woman, but this is caused by the failure of the ovarian reserve. The average age of natural menopause in the general population of women has remained around 50–52 years. Premature ovarian insufficiency (POI) is a debilitating clinical syndrome that manifests as a decline in ovarian function in women under 40. This condition is a prominent cause of female infertility. Summary: POI is a debilitating condition that not only wreaks havoc on patients’ physical and mental well-being but also imposes substantial mental, psychological, and economic burdens, particularly on women. In addition to diminished fertility, individuals afflicted with POI face an elevated risk of developing debilitating conditions such as osteoporosis and cardiovascular disease. The etiologies of POI are highly heterogeneous, and it can be caused by spontaneous genetic defects or induced by autoimmune diseases, infections, and iatrogenic or environmental factors. Alarmingly, idiopathic POI, a subtype characterized by an unknown etiology, accounts for more than half of all POI cases. Currently, clinical interventions for POI primarily consist of hormone replacement therapy. Fertility preservation methods are cryopreservation of embryos, oocytes, and ovarian tissue. Immunological interventions, gene editing techniques, and stem cell-based therapies are being explored to unravel the diverse etiologies and underlying mechanisms of POI, thereby enabling the identification of optimal therapeutic interventions. These innovative approaches offer unprecedented opportunities to advance the field of reproductive medicine. Key Messages: The main aim of this paper was to offer a succinct summary of the latest research breakthroughs concerning the elucidation of the mechanisms governing the origin and management of POI.

This study aimed to compare the changes in physicochemical properties of the starch isolated from three banana cultivars (Musa AAA group, Cavendish subgroup; Musa ABB group, Pisang Awak subgroup; Musa AA group, Huangdijiao subgroup) at five different maturity stages. The results revealed both similarities and significant differences in micromorphology and physicochemical characteristics of the three banana varieties during different growth stages. Apparent amylose content and particle size of the three starches increased with the ripeness of banana. Light microscopy and scanning electron microscopy revealed that starch particles of the three starches had different microscopic characteristics, and that banana starch morphology was basically unchanged at various growth stages. Moreover, the pasting and thermal properties of the banana starches were significantly different at various growth stages. The resistant starch content of the three banana cultivars was about 80% at all growth stages. Musa AAA group, Cavendish subgroup had the highest resistant starch content at stage Ⅴ. This study provides insights into the starch changes of three banana cultivars during ripening.

To clarify the characteristic odor of compounds present in duck meat, especially reheating after storage, the effect of duck breast cooked at three temperatures (90 °C, 100 °C, 105 °C) and reheating after 7 days of storage was studied. Electronic nose analysis and sensory evaluation revealed a significant increase (p

Standards play significant roles in the development of technology and economics, while the cooperation between drafters directly determines the quality of standard systems. The cooperation prediction is a significant while challenging problem for seeking new cooperation chances between drafting units due to their differences in experience and professional ability. In this study, an integrated artificial intelligence method is proposed for cooperation prediction using the link prediction method, text analysis, and network modeling. Specifically, we develop a multi-layer standard network formed by standard citation relationships and cooperation relationships between drafters. Then, a set of novel metrics is designed for predicting the cooperation between drafters considering the knowledge, experience, and professional capability. These metrics are further integrated into a neural network to improve the prediction accuracy. The priorities of our method in terms of prediction accuracy are verified with realistic data of Chinese environmental health standards. The prediction results provide strong support for the selection of drafters and further optimize the structure of standard systems.

Climate classification plays a fundamental role in understanding climatic patterns, particularly in the context of a changing climate. This study utilized hourly meteorological data from 36 major cities in China from 2011 to 2021, including 2 m temperature (T2), relative humidity (RH), and precipitation (PRE). Both original hourly sequences and daily value sequences were used as inputs, applying two non-hierarchical clustering methods (k-means and k-medoids) and four hierarchical clustering methods (ward, complete, average, and single) for clustering. The classification results were compared using two clustering evaluation indices: the silhouette coefficient and the Calinski–Harabasz index. Additionally, the clustering was compared with the Köppen–Geiger climate classification based on the maximum difference in intra-cluster variables. The results showed that the clustering method outperformed the Köppen–Geiger climate classification, with the k-medoids method achieving the best results. Our research also compared the effectiveness of climate classification using two variables (T2 and PRE) versus three variables, including the addition of hourly RH. Cluster evaluation confirmed that incorporating the original sequence of hourly T2, PRE, and RH yielded the best performance in climate classification. This suggests that considering more meteorological variables and using hourly observation data can significantly improve the accuracy and reliability of climate classification. In addition, by setting the class numbers to two, the clustering methods effectively identified climate boundaries between northern and southern China, aligning with China’s traditional geographical division along the Qinling–Huaihe River line.

Abstract Abnormal expression of the potassium channel tetramerization domain containing 12 (KCTD12) is closely related to the occurrence and development of various tumors, but a pan-cancer analysis of KCTD12 has not yet been conducted. We explored the association between KCTD12 and more than 30 human malignancies using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. First, the mRNA and protein levels of KCTD12 were examined and their correlations with tumor stage and survival were explored. Second, we analyzed the infiltration of CD8+ and CD4+ T cells and cancer-associated fibroblasts in tumors and explored the correlation between KCTD12 expression and tumor cell stemness, genomic heterogeneity, and diagnostic specificity. Finally, we explored the molecular mechanisms associated with KCTD12 using KEGG/GO analysis. The results showed that KCTD12 mRNA and protein expression levels decreased in most tumors was significantly associated with the prognosis of tumor patients, and the phosphorylation level of KCTD12 decreased in several tumors, such as S200 and T196, pancreatic adenocarcinoma (PAAD), lung adenocarcinoma (LUAD), and breast invasive cancer (BRCA). The expression of KCTD12 was positively correlated with the degree of cancer-associated fibroblasts infiltration in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), head and neck squamous cell carcinoma (HNSC), PAAD, and stomach adenocarcinoma (STAD). The relationship between KCTD12 expression and CD8+ and CD4+ T cell infiltration was also clarified. KCTD12 showed high diagnostic sensitivity for various types of tumors and may be involved in tumor cell biology by affecting tumor cell stemness, tumor burden, and other characteristics. Finally, we analyzed the molecular functions of KCTD12 and possible KEGG/GO signaling pathways. In this study, we developed a biological marker for diagnosis, prognosis, and immune infiltration of the pan-cancers.

With the increasing renewable energy and expanding trans-regional transmission, higher requirements are placed on the outage maintenance scheduling for high-voltage power transmission networks. In this paper, a bi-level multi-area joint maintenance scheduling optimization model is established for high-voltage transmission lines taking into account the consumption of renewable energy under two-level market environment. This model is able to achieve the following in terms of the maintenance scheduling: (i) It adapts to the optimization objectives and modes of different electricity spot markets between and within areas; (ii) The goals of maintenance willingness and consumption of renewable energy are balanced; (iii) By using the Kuhn–Tucker method, the bi-level model is transformed into a single-level mixed integer programming problem with complementarity constraints for the purpose of solving. The method proposed in this paper is verified by numerical examples, which reveal how the proposed model can improve the capability of multi-area power system to accommodate renewable energy and better arrange the maintenance resources.

Abstract Self-experience consistency has an important effect on life satisfaction; however, the underlying mechanism of this relationship remains unclear. This study aims to examine why self-experience consistency is related to increased life satisfaction. To do so, we investigated the relationships between self-experience consistency, the need for relatedness, Zhong-yong thinking, and life satisfaction in a sample of 456 undergraduate students. We also tested a moderated mediation model examining Zhong-yong thinking as a moderator. The results suggest that self-experience consistency related to life satisfaction was due, in part, to an increased need for relatedness. However, interpretation of this finding is limited by the use of cross-sectional data. Furthermore, Zhong-yong thinking moderated the self-experience consistency—need for relatedness link, such that the link was stronger for individuals with high/moderate levels of Zhong-yong thinking. Overall, these findings address a major gap in the positive psychology literature. Finally, implications for research are discussed.

Background: Drug-drug interactions (DDIs) are a major but preventable cause of adverse drug reactions. There is insufficient information regarding DDIs in lung transplant recipients.Objective: This study aimed to determine the prevalence of potential DDIs (pDDIs) in intensive care unit (ICU) lung transplant recipients, identify the real DDIs and the most frequently implicated medications in this vulnerable population, and determine the risk factors associated with pDDIs.Methods: This retrospective cross-sectional study included lung transplant recipients from January 2018 to December 2021. Pertinent information was retrieved from medical records. All prescribed medications were screened for pDDIs using the Lexicomp® drug interaction software. According to this interaction software, pDDIs were classified as C, D, or X (C = monitor therapy, D = consider therapy modification, X = avoid combination). The Drug Interaction Probability Scale was used to determine the causation of DDIs. All statistical analysis was performed in SPSS version 26.0.Results: 114 patients were qualified for pDDI analysis, and total pDDIs were 4051. The most common type of pDDIs was category C (3323; 82.0%), followed by D (653; 16.1%) and X (75; 1.9%). Voriconazole and posaconazole were the antifungal medicine with the most genuine DDIs. Mean tacrolimus concentration/dose (Tac C/D) before or after co-therapy was considerably lower than the Tac C/D during voriconazole or posaconazole co-therapy (p < 0.001, p = 0.027). Real DDIs caused adverse drug events (ADEs) in 20 patients. Multivariable logistic regression analyses found the number of drugs per patient (OR, 1.095; 95% CI, 1.048–1.145; p < 0.001) and the Acute Physiology and Chronic Health Evaluation II (APACHE Ⅱ) score (OR, 1.097; 95% CI, 1.021–1.179; p = 0.012) as independent risk factors predicting category X pDDIs.Conclusion: This study revealed a high incidence of both potential and real DDIs in ICU lung transplant recipients. Immunosuppressive drugs administered with azole had a high risk of causing clinically significant interactions. The number of co-administered drugs and APACHE Ⅱ score were associated with an increased risk of category × drug interactions. Close monitoring of clinical and laboratory parameters is essential for ensuring successful lung transplantation and preventing adverse drug events associated with DDIs.

IntroductionUpper extremity deficits (UED) is a common and impactful complication among stroke survivors. Virtual reality (VR)-based rehabilitation holds potential for enhancing rehabilitation intensity and engagement by stimulating tasks. While several clinical studies have examined the effectiveness and safety of VR-based rehabilitation, there is a need for further research to improve consistency in outcomes.Materials and methodsThe study will incorporate randomized controlled trials (RCTs) concerning the effects of VR-based rehabilitation on upper extremity (UE) function in stroke survivors. A comprehensive search of databases including PubMed, Embase, Cochrane Library, Web of Science, Scopus, Cinahl, China National Knowledge Infrastructure (CNKI), Wan-fang, and Chinese Biology Medicine Database will be performed from inception to the start of the study. Primary outcomes will focus on upper limb motor function assessments such as the Fugl-Meyer Upper Extremity (FMUE), Box and Block Test (BBT), Wolf Motor Function Test (WMFT), and Action Research Arm Test (ARAT). Secondary outcomes related to activities of daily living will include the Barthel Index (BI) and Functional Independence Measure (FIM). Research selection, data extraction, and quality assessment will be independently conducted by two researchers. The recently revised Cochrane risk of bias tool will be employed to evaluate study quality. Meta-regression and subgroup analyses will be utilized to identify effective therapy delivery modes and patterns. The assessment, development, and evaluation of recommendations approach will be applied to achieve a robust conclusion.DiscussionThis study provides a rigorous synthesis to evaluate optimal parameters-specifically intensity and duration-for VR-based rehabilitation interventions aimed at enhancing UE function in stroke survivors. Our secondary objective is to assess the impact of these parameters on rehabilitation outcomes. We anticipate an accurate, transparent, and standardized review process that will yield evidence-based recommendations for integrating VR technology into treating upper extremity dysfunction in stroke patients, offering clinicians effective strategies to enhance upper limb function.

In the actual production of duck meat, the cooking time for marinated and sliced duck products is around 30 min. Before consumption, it is recommended to use a water bath for reheating at 75 °C for 10 min. However, many consumers reflect that after reheating, there will be an unpleasant smell, affecting the quality of food. Therefore, to investigate the effects of lipid oxidation on the duck odorous smell during heat treatment and reheating, lipid oxidation, sensory evaluation and lipidomics were performed on raw duck meat, 90 °C processed, and reheated cooked duck meat stored at 4 ± 1 °C for 3 and 7 days, respectively. The results showed that the duck odorous smell increased after heat treatment and reheating. A total of 26 lipid subclasses and 519 lipid molecules were identified in duck meat based on lipidomics. Phosphatidylcholine (PC) and phosphatidylethanolamine (PE) in duck meat phospholipids played an important role in the production of duck odorous smell. These findings may contribute in reducing duck odorous smell by targeted inhibition of lipid oxidation.

Rational regulation of reactive oxygen species (ROS) plays a vital importance in maintaining homeostasis of living biological systems. For ROS-related pathologies, chemotherapy technology derived from metal nanomaterials currently occupies a pivotal position. However, they suffer from inherent issues such as complicated synthesis, batch-to-batch variability, high cost, and potential biological toxicity caused by metal elements. Here, we reported for the first time that dual-action 3,5-dihydroxy-1-ketonaphthalene-structured small-molecule enzyme imitator (DHKNase) exhibited 2-edged ROS regulation, catering to the execution of physiology-beneficial ROS destiny among diverse pathologies in living systems. Based on this, DHKNase is validated to enable remarkable therapeutic effects in 2 classic disease models, including the pathogen-infected wound-healing model and the dextran sulfate sodium (DSS)-caused inflammatory bowel disease (IBD). This work provides a guiding landmark for developing novel natural small-molecule enzyme imitator and significantly expands their application potential in the biomedical field.

Introduction: Mesenchymal stem cells (MSCs) possess a high degree of self-renewal capacity and in vitro multi-lineage differentiation potential. Decellularized materials have garnered considerable attention due to their elevated biocompatibility, reduced immunogenicity, excellent biodegradability, and the ability to partially mimic the in vivo microenvironment conducive to cell growth. To address the issue of mesenchymal stem cells losing their stem cell characteristics during two-dimensional (2D) cultivation, this study established three-dimensional cell carriers modified with lung decellularized extracellular matrix and assessed its impact on the life activities of mesenchymal stem cells.Methods: This study employed PET as a substrate material, grafting with polydopamine (PDA), and constructing a decellularized extracellular matrix (dECM) coating on its surface, thus creating the PET/PDA/dECM three-dimensional (3D) composite carrier. Subsequently, material characterization of the cellular carriers was conducted, followed by co-culturing with human umbilical cord mesenchymal stem cells in vitro, aiming to investigate the material’s impact on the proliferation and paracrine activity of mesenchymal stem cells.Results and Discussion: Material characterization demonstrated successful grafting of PDA and dECM materials, and it had complete hydrophilicity, high porosity, and excellent mechanical properties. The material was rich in various ECM proteins (collagen I, collagen IV , laminin, fibronectin, elastin), indicating good biocompatibility. In long-term in vitro cultivation (14 days) experiments, the PET/PDA/dECM three-dimensional composite carrier significantly enhanced adhesion and proliferation of human umbilical cord-derived mesenchymal stem cells (HUCMSCs), with a proliferation rate 1.9 times higher than that of cells cultured on tissue culture polystyrene (TCPS) at day 14. Furthermore, it effectively maintained the stem cell characteristics, expressing specific antigens for HUCMSCs. Through qPCR, Western blot, and ELISA experiments, the composite carrier markedly promoted the expression and secretion of key cell factors in HUCMSCs. These results demonstrate that the PET/PDA/dECM composite carrier holds great potential for scaling up MSCs’ long-term in vitro cultivation and the production of paracrine factors.

In this paper, two novel methodologies of employing machine learning (here, the type-2 fuzzy system) are presented to control a multiagent system in which the agents are flexible joint robots. In the previous methods, the static mode controller has been investigated, which has little flexibility and cannot measure all the states of the system, but in the method presented in this paper, we can eliminate these disadvantages. The control signal is consisting of feedback from the output and the estimated states of the system. In the first method, the control signal coefficients are calculated from the linear matrix inequality (LMI), followed by a type-2 fuzzy system that adds the compensation signal to the control signal. In the second method, the type-2 fuzzy system is directly used to estimate the control signal coefficients which do not employ LMI. Both methods have their disadvantages and benefits, so in general, one of these two methods cannot be considered superior. To prove the effectiveness of the two proposed methods, a topology with four robots has been considered. Both proposed methods have been evaluated for controlling the angle and speed of the robot link. Also, another simulation was made without using the fuzzy system to verify the importance of our methods. Simulation results indicate the proper efficiency of proposed methods, especially in presence of uncertainty in the system.

In the contemporary digital economy, economic development increasingly relies on the innovation and dissemination of knowledge. Academic entrepreneurship, as a direct channel for knowledge dissemination into the marketplace, is significantly influenced by digital technology. Consequently, how to improve academic entrepreneurial ability has become a hot research topic. This study is grounded in the theory of reciprocal determinism within the context of the digital economy. We use the “2019 China Digital Economy Development Index White Paper” and collect data from 1843 survey questionnaires in China to conduct empirical research with a ridge regression model. It primarily focuses on the following individual factors and social environmental factors on academic entrepreneurial ability of teachers (AEAT): digital economy (DE), organizational support (OS), policy environment (PE), and personal learning growth (PLG). First, the findings show that the DE, OS, PE, and PLG have a significant positive impact on improving AEAT. Second, the results also indicate that social environmental factors relative to personal factors will have a greater impact. Finally, this study not only presents the first attempt to establish a connection between DE and AEAT but also holds significant managerial implications for enhancing AEAT within the context of the DE. Despite the increasing body of literature on academic entrepreneurship, the research domain pertaining specifically to AEAT remains fragmented and lacks comprehensive theoretical development. There is a pressing need for more systematic and thorough investigations to unveil the black box of factors influencing AEAT in the context of the DE.

High silicon alloyed ductile cast iron (Si-DCI) can show unpredictable brittle fracture which currently prevents a widespread application of this material. The brittleness is associated with local superstructure formation due to silicon segregation which influences the deformation mechanisms of the matrix phase. In order to understand the effect of silicon segregation on the mechanical properties of Si-DCI under monotonous loading, three alloys with different cooling conditions were examined and micromechanical simulations were carried out by using the phenomenological crystal plasticity model. Here, the segregation profiles were determined through multi phase field simulations. The influence of segregation on the mechanical properties was only evident from the model but not from the experimental results. The simulated results show that the toughness of Si-DCI decreases with stronger silicon segregation when ductile damage is considered.

IntroductionCognitive impairment (CI) is a common degenerative condition in the older population. However, the current methods for assessing CI are not based on brain functional state, which leads to delayed diagnosis, limiting the initiatives towards achieving early interventions.MethodsA total of one hundred and forty-nine community-dwelling older adults were recruited. Montreal Cognitive Assessment (MoCA) and Mini-Mental State Exam (MMSE) were used to screen for CI, while brain functional was assessed by brain functional state measurement (BFSM) based on electroencephalogram. Bain functional state indicators associated with CI were selected by lasso and logistic regression models (LRM). We then classified the CI participants based on the selected variables using hierarchical clustering analysis.ResultsEighty-one participants with CI detected by MoCA were divided into five groups. Cluster 1 had relatively lower brain functional states. Cluster 2 had highest mental task-switching index (MTSi, 13.7 ± 3.4), Cluster 3 had the highest sensory threshold index (STi, 29.9 ± 7.7), Cluster 4 had high mental fatigue index (MFi) and cluster 5 had the highest mental refractory period index (MRPi), and external apprehension index (EAi) (21.6 ± 4.4, 35.4 ± 17.7, respectively). Thirty-three participants with CI detected by MMSE were divided into 3 categories. Cluster 1 had the highest introspective intensity index (IIi, 63.4 ± 20.0), anxiety tendency index (ATi, 67.2 ± 13.6), emotional resistance index (ERi, 50.2 ± 11.9), and hypoxia index (Hi, 41.8 ± 8.3). Cluster 2 had the highest implicit cognitive threshold index (ICTi, 87.2 ± 12.7), and cognitive efficiency index (CEi, 213.8 ± 72.0). Cluster 3 had higher STi. The classifications both showed well intra-group consistency and inter-group variability.ConclusionIn our study, BFSM-based classification can be used to identify clinically and brain-functionally relevant CI subtypes, by which clinicians can perform personalized early rehabilitation.

PurposeTOPBP1 interacting checkpoint and replication regulator (TICRR), a hub gene of the Cdk2-mediated initiation step of DNA replication, has been shown an essential role in tumorigenesis by accelerating the DNA replication of tumor cells.MethodsRT-qPCR was used to detect the mRNA expression of TICRR in LUAD tumors and adjacent normal tissues. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database of LUAD were acquired to analyze the critical role of TICRR expression in survival prognosis and clinicopathology characters in LUAD. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were performed using the R package. The correlation of TICRR expression with immune cell infiltration, RNA epigenetic modification, DNA damage repair (DDR) pathway, and cell metabolism of LUAD was further explored to verify significant conclusions.ResultsTICRR was significantly upregulated in most cancer types, including LUAD, lung squamous cell carcinoma (LUSC), and others. Cox regression analysis indicated the overexpression of TICRR was associated with poor survival in several cancers. In LUAD, TICRR expression was positively correlated with tumor stage and was increased in smoking, male, and high tumor mutational burden (TMB) patients. Enrichment analysis revealed that TICRR could influence tumor proliferation and prognosis via activating pathways involving cell cycle, DNA repair, DNA replication, cysteine metabolism, oxidative phosphorylation, and ubiquitin-mediated proteolysis pathways. Interestingly, high TICRR expression correlated with DDR pathway signature (34 genes), 37 m6A/m5C regulated genes, and some metabolism-regulated genes. Silencing the TICRR gene affects cysteine metabolism and modifies cancer-related pathways, with decreased cell cycle and increased B/T cell receptor signaling. Our TICRR risk model accurately predicts LUAD patient prognosis, validated across GEO datasets, and is integrated with clinical characteristics via a nomogram, facilitating personalized treatment strategies and enhancing patient management.ConclusionsTaken together, TICRR has emerged as a promising prognostic biomarker in lung adenocarcinoma (LUAD), with implications in immune activation, cell cycle regulation, RNA modification, and tumor energy metabolism. These findings suggest that TICRR could serve as a viable therapeutic target and a reliable prognostic indicator for LUAD.

AbstractLimited Sexual and Reproductive Health (SRH) knowledge among China’s youth is a considerable challenge that impacts not only China but also the global progression towards sustainable development goals. This study aims to offer a comprehensive understanding of China’s sex education policy, its evolution in recent years, and the role played by domestic and international actors in the policy-making process. A combination of quantitative and qualitative methodologies were employed to investigate the current state and historical progression of China’s sex education policy. The findings reveal a significant correlation between the government’s emphasis on sex education and several key indicators, including the incidence of abortion, the level of gender equality, and the development of the education system. The study also identifies several roadblocks hampering the comprehensive development of sex education in China, and recommends the establishment of a dedicated cross-ministerial institution to enhance collaboration and guide the development of comprehensive sex education in China.

ABSTRACTScandium is the best alloying element to improve the mechanical properties of industrial Al-Si-Mg casting alloys. Most literature reports devote to exploring/designing optimal Sc additions in different commercial Al-Si-Mg casting alloys with well-defined compositions. However, no attempt to optimize the contents of Si, Mg, and Sc has been made due to the great challenge of simultaneous screening in high-dimensional composition space with limited experimental data. In this paper, a novel alloy design strategy was proposed and successfully applied to accelerate the discovery of hypoeutectic Al-Si-Mg-Sc casting alloys over high-dimensional composition space. Firstly, high-throughput CALculation of PHAse Diagrams (CALPHAD) solidification simulations of ocean of hypoeutectic Al-Si-Mg-Sc casting alloys over a wide composition range were performed to establish the quantitative relation ‘composition-process-microstructure’. Secondly, the relation ‘microstructure-mechanical properties’ of Al-Si-Mg-Sc hypoeutectic casting alloys was acquired using the active learning technique supported by key experiments designed by CALPHAD and Bayesian optimization samplings. After a benchmark in A356-xSc alloys, such a strategy was utilized to design the high-performance hypoeutectic Al-xSi-yMg alloys with optimal Sc additions that were later experimentally validated. Finally, the present strategy was successfully extended to screen the optimal contents of Si, Mg, and Sc over high-dimensional hypoeutectic Al-xSi-yMg-zSc composition space. It is anticipated that the proposed strategy integrating active learning with high-throughput CALPHAD simulations and key experiments should be generally applicable to the efficient design of high-performance multi-component materials over high-dimensional composition space.

Abstract Chrysanthemum (Chrysanthemum morifolium Ramat.) is a globally important ornamental plant with great economic, cultural, and symbolic value. However, research on chrysanthemum is challenging due to its complex genetic background. Here, we report a near-complete assembly and annotation for C. morifolium comprising 27 pseudochromosomes (8.15 Gb; scaffold N50 of 303.69 Mb). Comparative and evolutionary analyses reveal a whole-genome triplication (WGT) event shared by Chrysanthemum species approximately 6 million years ago (Mya) and the possible lineage-specific polyploidization of C. morifolium approximately 3 Mya. Multilevel evidence suggests that C. morifolium is likely a segmental allopolyploid. Furthermore, a combination of genomics and transcriptomics approaches demonstrate the C. morifolium genome can be used to identify genes underlying key ornamental traits. Phylogenetic analysis of CmCCD4a traces the flower colour breeding history of cultivated chrysanthemum. Genomic resources generated from this study could help to accelerate chrysanthemum genetic improvement.

Esophageal cancer (EC) is a fatal digestive disease with a poor prognosis and frequent lymphatic metastases. Nevertheless, reliable biomarkers for EC diagnosis are currently unavailable. Accordingly, we have performed a comparative proteomics analysis on cancer and paracancer tissue-derived exosomes from eight pairs of EC patients using label-free quantification proteomics profiling and have analyzed the differentially expressed proteins through bioinformatics. Furthermore, nano-flow cytometry (NanoFCM) was used to validate the candidate proteins from plasma-derived exosomes in 122 EC patients. Of the 803 differentially expressed proteins discovered in cancer and paracancer tissue-derived exosomes, 686 were up-regulated and 117 were down-regulated. Intercellular adhesion molecule-1 (CD54) was identified as an up-regulated candidate for further investigation, and its high expression in cancer tissues of EC patients was validated using immunohistochemistry, real-time quantitative PCR (RT-qPCR), and western blot analyses. In addition, plasma-derived exosome NanoFCM data from 122 EC patients concurred with our proteomic analysis. The receiver operating characteristic (ROC) analysis demonstrated that the AUC, sensitivity, and specificity values for CD54 were 0.702, 66.13%, and 71.31%, respectively, for EC diagnosis. Small interference (si)RNA was employed to silence the CD54 gene in EC cells. A series of assays, including cell counting kit-8, adhesion, wound healing, and Matrigel invasion, were performed to investigate EC viability, adhesive, migratory, and invasive abilities, respectively. The results showed that CD54 promoted EC proliferation, migration, and invasion. Collectively, tissue-derived exosomal proteomics strongly demonstrates that CD54 is a promising biomarker for EC diagnosis and a key molecule for EC development.

BackgroundColorectal cancer (CRC) is a prevalent malignancy with diverse molecular characteristics. The NGS-based approach enhances our comprehension of genomic landscape of CRC and may guide future advancements in precision oncology for CRC patients.MethodIn this research, we conducted an analysis using Next-Generation Sequencing (NGS) on samples collected from 111 individuals who had been diagnosed with CRC. We identified somatic and germline mutations and structural variants across the tumor genomes through comprehensive genomic profiling. Furthermore, we investigated the landscape of driver mutations and their potential clinical implications.ResultsOur findings underscore the intricate heterogeneity of genetic alterations within CRC. Notably, BRAF, ARID2, KMT2C, and GNAQ were associated with CRC prognosis. Patients harboring BRAF, ARID2, or KMT2C mutations exhibited shorter progression-free survival (PFS), whereas those with BRAF, ARID2, or GNAQ mutations experienced worse overall survival (OS). We unveiled 80 co-occurring and three mutually exclusive significant gene pairs, enriched primarily in pathways such as TP53, HIPPO, RTK/RAS, NOTCH, WNT, TGF-Beta, MYC, and PI3K. Notably, co-mutations of BRAF/ALK, BRAF/NOTCH2, BRAF/CREBBP, and BRAF/FAT1 correlated with worse PFS. Furthermore, germline AR mutations were identified in 37 (33.33%) CRC patients, and carriers of these variants displayed diminished PFS and OS. Decreased AR protein expression was observed in cases with AR germline mutations. A four-gene mutation signature was established, incorporating the aforementioned prognostic genes, which emerged as an independent prognostic determinant in CRC via univariate and multivariate Cox regression analyses. Noteworthy BRAF and ARID2 protein expression decreases detected in patients with their respective mutations.ConclusionThe integration of our analyses furnishes crucial insights into CRC’s molecular characteristics, drug responsiveness, and the construction of a four-gene mutation signature for predicting CRC prognosis.

In this paper, a Genetic-Artificial Bee Colony Algorithm (G-ABCA) for mechanism optimization synthesis is proposed to improve the accuracy of the dimensional synthesis of the 4-bar mechanism. Firstly, the plane coordinate of the 4-bar mechanism was determined. Then, the relevant design parameters of the link motion were analyzed. The objective function was constructed to minimize the position error between the actual trajectory of the mechanism and the target trajectory, constraints of the 4-bar plane mechanism were added. Then, by means of the improved artificial bee colony algorithm, the length, size and angle variables of the 4-bar mechanism were optimized. The parameters of the classical case were optimized. Finally, the optimization results of the algorithm were simulated for the optimized parameters of the 4-bar mechanism. The results were compared to other optimization algorithms. The results show that the trajectory error obtained by the improved artificial bee colony algorithm is smaller and the optimization effect of the parameters of the 4-bar mechanism is better. The proposed algorithm improves the crossover rate between food sources, extends the population optimization space, improves the local search ability and prevents the premature convergence of the genetic algorithm. The validity and accuracy of the method are proved, which provides a theoretical basis for the in-depth study of the trajectory error of the 4-bar mechanism.

Summary: Metastasis is the leading cause of high ovarian-cancer-related mortality worldwide. Three major processes constitute the whole metastatic cascade: invasion, intravasation, and extravasation. Tumor cells often reprogram their metabolism to gain advantages in proliferation and survival. However, whether and how those metabolic alterations contribute to the invasiveness of tumor cells has yet to be fully understood. Here we performed a genome-wide CRISPR-Cas9 screening to identify genes participating in tumor cell dissemination and revealed that PTGES3 acts as an invasion suppressor in ovarian cancer. Mechanistically, PTGES3 binds to phosphofructokinase, liver type (PFKL) and generates a local source of prostaglandin E2 (PGE2) to allosterically inhibit the enzymatic activity of PFKL. Repressed PFKL leads to downgraded glycolysis and the subsequent TCA cycle for glucose metabolism. However, ovarian cancer suppresses the expression of PTGES3 and disrupts the PTGES3-PGE2-PFKL inhibitory axis, leading to hyperactivation of glucose oxidation, eventually facilitating ovarian cancer cell motility and invasiveness.

Background and objective Small cell lung cancer (SCLC) with high c-Myc expression is prone to relapse and metastasis, leading to extremely low survival rate. Cyclin-dependent kinases 4 and 6 (CDK4/6) inhibitor Abemaciclib plays a key role in the treatment of tumors, but the effects and mechanisms on SCLC remain unclear. This study was to analyze the effect and molecular mechanism of Abemaciclib in inhibiting proliferation, migration and invasion of SCLC with high c-Myc expression, with a view to expanding a new direction for reducing the recurrence and metastasis. Methods Proteins interacting with CDK4/6 were predicted using the STRING database. The expressions of CDK4/6 and c-Myc in 31 cases of SCLC cancer tissues and paired adjacent normal tissues were analyzed by immunohistochemistry. The effects of Abemaciclib on the proliferation, invasion and migration of SCLC were detected by CCK-8, colony formation assay, Transwell and migration assay. Western blot was used to detect the expressions of CDK4/6 and related transcription factors. Flow cytometry was used to analyze the effects of Abemaciclib on the cell cycle and checkpoint of SCLC. Results The expression of CDK4/6 was associated with c-Myc by STRING protein interaction network. c-Myc can directly modalize achaete-scute complex homolog 1 (ASCL1), neuronal differentiation 1 (NEUROD1) and Yes-associated protein 1 (YAP1). Moreover, CDK4 and c-Myc regulate the expression of programmed cell death ligand 1 (PD-L1). Immunohistochemistry showed that the expressions of CDK4/6 and c-Myc in cancer tissues were higher than those in adjacent tissues(P

Human-object interaction (HOI) detection is an advanced task in the field of computer vision and is crucial for deep scene understanding. However, current HOI detection models face serious challenges in the following aspects: first, they overly rely on appearance features and neglect the local details of human-object interactions; second, the training cost of the existing detection model is quite high. To overcome these challenges, this study proposes a Parallel Multi-Head Graph Attention Network (PMGAT) model for detecting human-object interaction correlations. First, the close relationship between facial landmarks and body keypoints with objects is recognized, thereby introducing a local feature module to construct a relational graph model between facial keypoints, body keypoints, and objects. A multi-head graph attention network was utilized to accurately capture the interaction correlations between keypoints, addressing the issue of neglecting local details. Furthermore, the global feature module is designed to extract absolute spatial pose features and relative spatial pose features based on the positions of human keypoints relative to objects, enabling a more in-depth extraction of interactions between humans and objects. To reduce the training cost of the model, it adopts a multi-branch parallel structure and employs a multi-threaded multi-GPU scheme for parallel training acceleration. The empirical results demonstrate that the PMGAT model outperforms the current state-of-the-art ViPLO method in terms of mAP on the V-COCO and HICO-DET datasets. On V-COCO, it exhibits a notable improvement of up to 0.8% mAP over ViPLO, while on the more demanding HICO-DET, the improvement reaches up to 1.47% mAP. Furthermore, PMGAT stands out for its minimal training time compared to existing approaches. Overall, these results corroborate the dual augmentation of PMGAT in accuracy and training efficiency.

Objective: To explore the impact of lactic acid bacteria on the quality of yeast-fermented multigrain bread. Methods: It was detected the changes of pH value, fermentation volume and rheological properties of multigrain dough fermented with lactic acid bacterias in different proportions (0, 0.03%, 0.06%, 0.09%, 0.12%). Changes of the hardness, stickiness and chewiness of multigrain bread, as well as specific volume, sensory quality and flavors were analyzed. Results: The pH value of the fermented multigrain dough fermented with lactic acid bacteria was reduced. The dough volume fermented with 0.03%~0.12% lactic acid bacteria, increasing from 50.00% to 88.12%, which was higher than yeast fermentation (increasing 48.51%). The storage modulus (G') and loss modulus (G") of dough decreased with lactic acid bacteria powder. The values of G' and G" decreased by 33.33% and 30.00% respectively, with 0.06% lactic acid bacteria powder. The textural properties including hardness, stickiness and chewiness of the multigrain bread fermented with 0.06% lactic acid bacteria were reduced, while elasticity improved significantly(P

Abstract Background Chrysanthemum seticuspe has emerged as a model plant species of cultivated chrysanthemums, especially for studies involving diploid and self-compatible pure lines (Gojo-0). Its genome was sequenced and assembled into chromosomes. However, the genome annotation of C. seticuspe still needs to be improved to elucidate the complex regulatory networks in this species. Results In addition to the 74,259 mRNAs annotated in the C. seticuspe genome, we identified 18,265 novel mRNAs, 51,425 novel lncRNAs, 501 novel miRNAs and 22,065 novel siRNAs. Two C-class genes and YABBY family genes were highly expressed in disc florets, while B-class genes were highly expressed in ray florets. A WGCNA was performed to identify the hub lncRNAs and mRNAs in ray floret- and disc floret-specific modules, and CDM19, BBX22, HTH, HSP70 and several lncRNAs were identified. ceRNA and lncNAT networks related to flower development were also constructed, and we found a latent functional lncNAT–mRNA combination, LXLOC_026470 and MIF2. Conclusions The annotations of mRNAs, lncRNAs and small RNAs in the C. seticuspe genome have been improved. The expression profiles of flower development-related genes, ceRNA networks and lncNAT networks were identified, laying a foundation for elucidating the regulatory mechanisms underlying disc floret and ray floret formation.