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Furui Zhai, Shanshan Mu, Yinghui Song, Min Zhang, Cui Zhang, Ze Lv Gynecological Clinic, Cangzhou Central Hospital, Cangzhou, Hebei, People’s Republic of ChinaCorrespondence: Furui Zhai, Gynecological Clinic, Cangzhou Central Hospital, 16 Xinhua West Road, Cangzhou, Hebei, 061001, People’s Republic of China, Email zfr860708@126.comBackground: High-grade cervical intraepithelial neoplasia (CIN2/3) is a precursor to invasive cervical cancer, necessitating effective management. While the Loop Electrosurgical Excision Procedure (LEEP) is a successful treatment, recurrence remains a significant concern. This study evaluates the predictive value of preoperative immune-inflammatory markers, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and systemic immune-inflammation index (SII), in assessing the risk of residual or recurrent CIN post-LEEP.Methods: A retrospective analysis was performed on 423 women who underwent LEEP for CIN2/3 at Cangzhou Central Hospital between 2016 and 2020. Cox proportional hazards regression models with restricted cubic splines were used to evaluate linear and non-linear associations between immune-inflammatory indices and recurrence risk. Multivariate models were adjusted for confounding factors, and subgroup analyses were conducted to test the robustness of the associations. Threshold non-linear fitting and saturation effect analyses were also performed to identify inflection points influencing residual or recurrent disease risk.Results: Significant differences in age, menopausal status, TCT results, HPV status, degrees of CIN and margin status were observed between recurrence and non-recurrence groups. NLR demonstrated a U-shaped relationship with recurrence risk, with a threshold effect. NLR values below 3.15 were associated with a reduced recurrence risk, while higher values increased the risk. PLR and SII showed a modest protective effect below their respective thresholds.Conclusion: Systemic inflammation plays a key role in CIN recurrence following LEEP. NLR serves as a valuable prognostic marker, highlighting the potential for personalised follow-up strategies. Further research is needed to confirm these findings and elucidate the underlying mechanisms.Keywords: cervical intraepithelial neoplasia, loop electrosurgical excision procedure, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, systemic immune-inflammation index, residual disease/recurrence

Furui Zhai, Shanshan Mu, Yinghui Song, Min Zhang, Cui Zhang, Ze Lv Gynecological Clinic, Cangzhou Central Hospital, Cangzhou, Hebei, People’s Republic of ChinaCorrespondence: Furui Zhai, Gynecological Clinic, Cangzhou Central Hospital, 16 Xinhua West Road, Cangzhou City, Hebei Province, People’s Republic of China, Tel +86-0317-2075783, Email zfr860708@126.comPurpose: Loop electrosurgical excision procedure (LEEP) for high-grade cervical intraepithelial neoplasia (CIN) carries significant risks of recurrence and persistence. This study compares the efficacy of a random survival forest (RSF) model with that of a conventional Cox regression model for predicting residual and recurrent high-grade CIN in premenopausal women after LEEP.Methods: Data from 458 premenopausal women treated for CIN2/3 at our hospital between 2016 and 2020 were analyzed. The RSF model incorporated demographic, pathological, and treatment-related variables. Feature selection utilizing LASSO and three other algorithms was performed to enhance the RSF model, which was further compared to a Cox regression model. Model performance was assessed using area under the curve (AUC), out-of-bag (OOB) error rates, and SHAP values to interpret predictor importance.Results: The RSF model showed superior performance compared to the Cox regression model, with AUC values of 0.767– 0.901 and peak predictive performance at 36 months post-LEEP. In contrast, the highest AUC achieved by Cox regression was 0.880. The RSF model also exhibited relatively lower OOB error rates, indicating better generalizability. Moreover, SHAP value analysis identified margin status and CIN severity as the most prominent predictors that directly affected risk predictions. Lastly, an online tool providing real-time predictions in clinical settings was successfully implemented using the RSF model.Conclusion: The RSF model outperformed the traditional Cox regression model in predicting residual and recurrent high-grade CIN risks post-LEEP. This model may be a more accurate clinical tool that facilitates improved personalized care and early interventions in gynecological oncology.Keywords: cervical intraepithelial neoplasia, residual/recurrent, random survival forest, Cox regression, premenopausal women

Furui Zhai, Shanshan Mu, Yinghui Song, Min Zhang, Cui Zhang, Ze Lv Gynecological Clinic, Cangzhou Central Hospital, Cangzhou City, Hebei Province, People’s Republic of ChinaCorrespondence: Furui Zhai, Department of Gynecological Clinic, Cangzhou Central Hospital, 16 Xinhua West Road, Cangzhou City, Hebei Province, People’s Republic of China, Tel +86-0317-2075783, Email zfr860708@126.comPurpose: This study aims to develop a machine learning (ML) model to predict the risk of residual or recurrent high-grade cervical intraepithelial neoplasia (CIN) after loop electrosurgical excision procedure (LEEP), addressing a critical gap in personalized follow-up care.Methods: A retrospective analysis of 532 patients who underwent LEEP for high-grade CIN at Cangzhou Central Hospital (2016– 2020) was conducted. In the final analysis, 99 women (18.6%) were found to have residual or recurrent high-grade CIN (CIN2 or worse) within five years of follow-up. Four feature selection methods identified significant predictors of residual or recurrent CIN. Eight ML algorithms were evaluated using performance metrics such as AUROC, accuracy, sensitivity, specificity, PPV, NPV, F1 score, calibration curve, and decision curve analysis. Fivefold cross-validation optimized and validated the model, and SHAP analysis assessed feature importance.Results: The XGBoost algorithm demonstrated the highest predictive performance with the best AUROC. The optimized model included six key predictors: age, ThinPrep cytologic test (TCT) results, HPV classification, CIN severity, glandular involvement, and margin status. SHAP analysis identified CIN severity and margin status as the most influential predictors. An online prediction tool was developed for real-time risk assessment.Conclusion: This ML-based predictive model for post-LEEP high-grade CIN provides a significant advancement in gynecologic oncology, enhancing personalized patient care and facilitating early intervention and informed clinical decision-making.Keywords: cervical intraepithelial neoplasia, loop electrosurgical excision procedure, residual or recurrent, machine learning, predictive modeling

Lanlan Zong,1,* Yanling Wang,1,* Shiyu Song,1 Huiqi Zhang,1 Shengcai Mu,1 Wenshang Liu,1 Yu Feng,1 Shumin Wang,1 Ziwei Tu,1 Qi Yuan,1 Luhui Li,2 Xiaohui Pu1 1School of Pharmacy and Henan Province Engineering Research Center of High Value Utilization to Natural Medical Resource in Yellow River Basin, Henan University, Kaifeng, Henan, 475004, People’s Republic of China; 2Medical school, Henan Technical Institute, Kaifeng, Henan, 475004, People’s Republic of China*These authors contributed equally to this workCorrespondence: Qi Yuan; Xiaohui Pu, Tel/Fax +86-371-23880680, Email kaifengYQ2017@163.com; pgh425@163.comIntroduction: Hepatoma is the leading cause of death among liver diseases worldwide. Modern pharmacological studies suggest that some natural monomeric compounds have a significant effect on inhibiting tumor growth. However, poor stability and solubility, and side effects are the main factors limiting the clinical application of natural monomeric compounds.Methods: In this paper, drug-co-loaded nanoself-assemblies were selected as a delivery system to improve the chemical stability and solubility of Tanshinone II A and Glycyrrhetinic acid, and to produce a synergetic anti-hepatoma effect.Results: The study suggested that the drug co-loaded nanoself-assemblies showed high drug loading capacity, good physical and chemical stability, and controlled release. In vitro cell experiments verified that the drug-co-loaded nanoself-assemblies could increase the cellular uptake and cell inhibitory activity. In vivo studies verified that the drug co-loaded nanoself-assemblies could prolong the MRT0-∞, increase accumulation in tumor and liver tissues, and show strong synergistic anti-tumor effect and good bio-safety in H22 tumor-bearing mice.Conclusion: This work indicates that natural monomeric compounds co-loaded nanoself-assemblies would be a potential strategy for the treatment of hepatoma.Graphical Abstract: Keywords: nanoself-assemblies, drug combination, glycyrrhetinic acid, tanshinone IIA, liver cancer

Yingying Du,1,* Shikui Mu,1,* Yan Liu,2 Yinghua Yuan,2 Yunlou Zhu,2 Lijie Ma,2 Qixing Wang,2 Zhengfang Zhu,2 Yuhao Liu,1 Sheng Wang1 1Department of Critical Care Medicine, Shanghai Tenth People’s Hospital, Tongji University, School of Medicine, Shanghai, 200072, People’s Republic of China; 2Department of Clinical Microbiology, Shanghai Tenth People’s Hospital, Tongji University, School of Medicine, Shanghai, 200072, People’s Republic of China*These authors contributed equally to this workCorrespondence: Sheng Wang; Yuhao LiuDepartment of Critical Care Medicine, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, 200072, People’s Republic of ChinaTel +86-21-6630 7153; +86-21-6630 7162Fax +86-21-6630 3983Email wangsheng@tongji.edu.cn; lyh-7906@163.comPurpose: This study retrospectively analyzed the genome characteristics of blaKPC-2 in multidrug-resistant Klebsiella pneumoniae collected from the ICU of a teaching hospital in Shanghai, China.Methods: From February 2018 to December 2019, 36 strains of multidrug-resistant Klebsiella pneumoniae were collected from the bronchoalveolar lavage fluid of critically ill patients. The genome of all isolates was obtained through the Illumina sequence, and single nucleotide polymorphisms of the blaKPC-2 gene were analyzed to explore blaKPC-2’s evolutionary characteristics. Different strains’ genetic relationships and homology were studied by constructing an evolutionary tree on a single copy orthologue. Pacbio combined Illumina sequence was conducted to evaluate the structure and potential mobility of drug-resistant plasmids of the strain KP-s26.Results: The distribution of resistance and virulence genes had little difference, but most strains had significant differences in the plasmid-encoded region. Most strains (31/36) carried the carbapenemase gene blaKPC-2, with no single nucleotide polymorphism in different strains. Extended-spectrum β-lactamase resistance genes, such as blaCTX-M and blaSHV, were found in the isolates, but no metallo-β-lactamases were detected. All strains with blaKPC-2 coexisted with chromosomal-associated fosfomycin resistance genes fosA6, and the coexistence of blaKPC-2 and blaCTX variants (blaCTX-M-15, blaCTX-M-65, and blaCTX-M-27) was also detected in 29/31 strains. The isolate KP-s26 carried five circular plasmids. pA and pB were conjugate plasmids, as they carried drug resistance genes and contained a complete IV secretion system.Conclusion: The blaKPC-2 carbapenemase gene is relatively conservative in the process of evolution; drug-resistant plasmids containing conjugated transfer elements contribute to the spreading of drug resistance. The coexistence of blaKPC-2 with fosA6 or blaCTX-M variants was associated with increased fosfomycin resistance and broad-spectrum β-lactam resistance, respectively.Clinical Trials Registration: Clinical Trials.gov Identifier: NCT03950544Keywords: Klebsiella pneumoniae, blaKPC-2, whole-genome sequencing, single nucleotide polymorphism, drug-resistant plasmids

Jing Zhao,1,&ast; Qing Zhao,1,&ast; Jing-Ze Lu,1 Dan Ye,1 Sheng Mu,1 Xiao-Di Yang,2 Wei-Dong Zhang,3,4 Bing-Liang Ma1 1Department of Pharmacology, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People’s Republic of China; 2Innovation Research Institute of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People’s Republic of China; 3Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People’s Republic of China; 4School of Pharmacy, Second Military Medical University, Shanghai, 200433, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Wei-Dong Zhang; Bing-Liang Ma Email wdzhangy@hotmail.com; bingliang.ma@hotmail.comPurpose: This study aimed to evaluate the pharmaceutical and pharmacokinetic effects of the natural nanoparticles (Nnps) isolated from Coptidis Rhizoma extract on berberine hydrochloride (BBR) and systematically explore the related mechanisms.Methods: Firstly, Nnps were isolated from Coptidis Rhizoma extract and then an Nnps-BBR complex was prepared. After qualitative and quantitative analysis in terms of size, Zeta potential, morphology, and composition of the Nnps and the Nnps-BBR complex, the effects of the Nnps on the crystallization of BBR were characterized. The effects of the Nnps on the solubility and dissolution of BBR were then evaluated. In addition, the effects of the Nnps on BBR in terms of cellular uptake, transmembrane transport, metabolic stability, and pharmacokinetics in mice were studied.Results: The Nnps had an average size of 166.6 ± 1.3 nm and Zeta potential of − 12.5 ± 0.2 mV. The Nnps were formed by denaturation of co-existing plant proteins with molecular weight < 30 kDa. The Nnps adsorbed or dispersed BBR, thereby promoting BBR transformation from crystal to amorphous form and improving its solubility and dissolution. The Nnps carried and promoted BBR uptake by human colonic adenocarcinoma (Caco-2) cells via caveolae-mediated endocytosis, reducing P-gp-mediated efflux of BBR in mice gut sacs and Madin-Darby canine kidney cells stably expressing the transporter P-gp (MDCK-MDR1) cells. Moreover, the Nnps improved BBR metabolic stability in mouse intestinal S9, promoting BBR intestinal absorption in mice, as shown by increased peak BBR concentration (Cmax, 1182.3 vs 310.2 ng/mL) and exposure level (AUC0– 12 h, 2842.8 vs 1447.0 ng·h/mL) in mouse portal vein. In addition, the Nnps increased BBR exposure level in mouse livers (95,443.2 vs 43,586.2 ng·h/g liver).Conclusion: The proteinaceous nanoparticles isolated from Coptidis Rhizoma extract can form a natural nano-drug delivery system with BBR, thereby significantly improving the pharmacokinetics of oral BBR.Keywords: natural nanoparticles, drug delivery system, pharmacokinetic synergy, berberine hydrochloride, herbal extract

Hui Zhang,1,* Yi Zhao,2,* Ping Zou,3 Shuanghong Lin,2 Shaoyu Mu,4 Qiansu Deng,5 Chunxue Du,1 Guanglan Zhou,1 Jiang Wu,2 Lu Gan2 1Department of Cardiology, Guizhou Provincial People’s Hospital, Guiyang, 550002, Guizhou, People’s Republic of China; 2Department of Nursing, Hubei NO.3 People’s Hospital of Jianghan University, Wuhan, People’s Republic of China; 3Department of Scholar Practitioner Program, School of Nursing, Nipissing University, Toronto, M6J 3S3, Ontario, Canada; 4Department of Nursing, Nursing College of Chongqing Medical University, Chongqing, 400016, People’s Republic of China; 5Department of Nursing, Chongqing Traditional Chinese Medicine Hospital, Chongqing, 400011, People’s Republic of China*These authors contributed equally to this workCorrespondence: Shuanghong LinDepartment of Nursing, Hubei NO.3 People’s Hospital of Jianghan University, Wuhan, People’s Republic of ChinaTel +8618771059373Email 18771059373@163.comBackground: Little is known about the associated factors with organizational citizenship behavior among Chinese nurses combating COVID-19. The aim of the present study was to investigate the relationships between autonomy, optimism, role conflict, work engagement, and organizational citizenship behavior based on moderated mediation models among Chinese nurses combating COVID-19.Methods: This cross-sectional study was performed on a sample of 368 nurses supporting the COVID-19 epidemic in Wuhan Leishenshan Hospital, China. According to the Job Demands-Resources model, two moderated mediation models were tested, in which autonomy/optimism was associated with organizational citizenship behavior through work engagement, when role conflict served as a moderator.Results: This current study found the mediating effect of work engagement and the moderating effect of role conflict on the relationship between autonomy/optimism and organizational citizenship behavior among nurses. Of note, nurses working in the COVID-19 epidemic viewed role conflict as challenge job demands rather than hindrance job demands.Conclusion: Based on the findings, organizational citizenship behavior can be affected by work engagement and role conflict. Nursing management is suggested to put emphasis on work engagement and role conflict among nurses supporting the COVID-19 epidemic.Keywords: the job demands-resources model, autonomy, optimism, organizational citizenship behavior, nurses, COVID-19

Xuan Qiu, Manjiang Li, Liqun Wu, Yang Xin, Siyu Mu, Tianxiang Li, Kangjian Song Liver Disease Center, The Affiliated Hospital of Qingdao University, Qingdao 266003, People’s Republic of ChinaCorrespondence: Liqun WuLiver Disease Center, The Affiliated Hospital of Qingdao University, No. 59 Haier Road, Laoshan District, Qingdao, Shandong 266003, People’s Republic of ChinaTel +86 15315328331Email wulq5810@126.comObjective: To investigate the effects of fatigue on the survival of patients with advanced hepatocellular carcinoma treated with sorafenib.Patients and Methods: A retrospective analysis of 182 cases of patients with advanced hepatocellular carcinoma treated with sorafenib in our hospital from October 1, 2008, to October 31, 2017, showed clinical and pathological data and follow-up results. The clinical and pathological data as well as follow-up results of 182 patients with advanced hepatocellular carcinoma treated with sorafenib in our hospital from October 1, 2008, to October 31, 2018, were retrospectively analyzed. All patients were treated for at least 3 months. Patients were divided into three groups: fatigue grade I (n=74), fatigue grade II (n=62), and fatigue grade III (n=46), according to National Cancer Institute common terminology criteria for adverse events (NCI CTCAE) version 5.0. Survival analysis between groups was performed by the Kaplan–Meier method (Log rank test), continuous variables were analyzed by t-test, and categorical variables were analyzed by chi-square test.Results: The overall survival (OS) of patients who were relieved of fatigue was 33.0± 9.3 months, whereas the OS of patients who were not relieved of fatigue was 15.0± 1.8 months (P< 0.000). Furthermore, the time to progress (TTP) of patients who were relieved of fatigue by resting was 20.3 ± 10.9 months compared to a TTP of 7.7 ± 1.0 months in patients who were not relieved of fatigue (P< 0.000).Conclusion: Patients, especially the elderly and infirm, were more susceptible to toxicity.Keywords: hepatocellular carcinoma, sorafenib, fatigue, survival

Haiyan Li,1 Zhenhua Yang,1 Shuang Zhang,1 Lin Xu,1 Yudong Wei,1 Jun Jiang,2 Luzelena Caro,3 Hwa-Ping Feng,3 Jacqueline B McCrea,3 Meng Li,2 Shuang Xie,2 Jiangdian Wang,2 Xu Min Zhao,2 Shengmei Mu2 1Drug Clinical Trial Center, Peking University Third Hospital, Beijing, People’s Republic of China; 2Department of Infectious Diseases, MSD (China) R&D, Beijing, People’s Republic of China; 3Department of Infectious Diseases, Merck & Co., Inc., Kenilworth, NJ, USACorrespondence: Haiyan LiDrug Clinical Trial Center, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191, People’s Republic of ChinaTel +86 108 226 6226Email haiyanli1027@hotmail.comPurpose: The burden of hepatitis C virus infection is particularly high in Asian countries, and new treatments are urgently needed. The purpose of this study was to characterize the pharmacokinetics (PK) and safety of the fixed-dose combination tablet of elbasvir/grazoprevir in healthy Chinese participants.Patient and Methods: In this Phase I, single-site, open-label, 3-period study in healthy Chinese adults, participants received a single tablet of elbasvir 50 mg/grazoprevir 100 mg, followed by blood sampling for up to 96 hrs (http://www.chinadrugtrials.org.cn/ CTR20160034; Protocol PN071). Participants then received 1 tablet daily for 10 days, followed by a minimum 10-day washout, after which participants received a single dose of 2 tablets (elbasvir 100 mg/grazoprevir 200 mg). Elbasvir and grazoprevir PK were assessed following single and multiple doses. Safety and tolerability were also evaluated.Results: Twelve participants (50% male) were enrolled in and completed the study. Following single-dose oral administration of elbasvir 50 mg/grazoprevir 100 mg or elbasvir 100 mg/grazoprevir 200 mg, the median Tmax was 3– 4 hrs and elimination half-life was 18 hrs (elbasvir) and 30 hrs (grazoprevir). Multiple-dose administration resulted in AUC0– 24 accumulation ratios of 1.58 (elbasvir) and 2.35 (grazoprevir). Both elbasvir 50 mg/grazoprevir 100 mg and 100 mg/200 mg regimens were generally well tolerated.Conclusion: Single-dose administration of elbasvir 50 mg/grazoprevir 100 mg or 100 mg/200 mg and once-daily administration of elbasvir 50 mg/grazoprevir 100 mg for 10 days has been adequately characterized, with PK values within the expected range, and was generally well tolerated in healthy Chinese male and female participants.Keywords: elbasvir, grazoprevir, healthy volunteers, hepatitis C virus, pharmacokinetics

The unoccupied electronic structure of the spin crossover molecule cobalt (II) N-(2-pyrazylcarbonyl)-2-pyrazinecarboxamide, [Co(dpzca)2] was investigated, using X-ray absorption spectroscopy (XAS) and compared with magnetometry (SQUID) measurements. The temperature dependence of the XAS and molecular magnetic susceptibility χmT are in general agreement for [Co(dpzca)2], and consistent with density functional theory (DFT). This agreement of magnetic susceptibility and X-ray absorption spectroscopy provides strong evidence that the changes in magnetic moment can be ascribed to changes in electronic structure. Calculations show the choice of Coulomb correlation energy U has a profound effect on the electronic structure of the low spin state, but has little influence on the electronic structure of the high spin state. In the temperature dependence of the XAS, there is also evidence of an X-ray induced excited state trapping for [Co(dpzca)2] at 15 K.

Calcified amorphous tumors (CATs) of the heart are rare non-neoplastic cardiac masses primarily found in the mitral valve or annulus. However, their exact pathogenesis remains unknown. In this case report, we describe the CT and MRI findings and differentiating features of cardiac a CAT in the left atrium of a 79-year-old female.

ObjectiveThis paper analyzes and models the core logic of a strike chain in terms of time sensitivity, reconfiguration and coverage, thereby providing model and method support for improving the dynamic management ability of naval combat resources under confrontation conditions. MethodsFirst, the typical combat platforms and elements related to the cross-domain cooperative combat of naval battlefields, such as escort ships, UAVs and unmanned boats, are abstracted into four types of resource nodes, namely detection, processing, decision-making and strike. Next, taking the shortest delay as the goal and considering constraints such as wide battlespace, low transmission rate between nodes and limited communication distance, the dynamic integration optimization mathematical model of the strike chain is established. A typical air defense scenario is then designed to demonstrate the shortest delay analysis of the strike chain and the destruction reconstruction analysis under the absence or attack of nodes, and quantitatively describe the changes of the shortest delay and sector coverage index of the reorganized strike chain under countermeasure conditions. Finally, based on a typical combat example of a Ukrainian unmanned cluster attack on the Black Sea Fleet, the ability of the fleet to resist the attack is analyzed on basis of the strike chain model. ResultsThe simulation results show that the model can be used to generate multiple strike chains with the shortest delays, and the responsibility division of each strike chain can be optimized, forming a multi-target killing network at sea. The destruction reconstruction of the strike chain often needs to pay such costs as increased delay and decreased sector coverage. The model can also be used to test anti-saturation attack ability under different formations.ConclusionsThis paper studies and validates the feasibility of analyzing the naval warfare system based on the strike chain model, and can provide theoretical model support for the subsequent design of future naval joint combat systems oriented to the killing network.

Abstract This study aimed to develop and evaluate a deep learning-based system for the automatic measurement of angles (specifically, Meary’s angle and calcaneal pitch) in weight-bearing lateral radiographs of the foot for flatfoot diagnosis. We utilized 3960 lateral radiographs, either from the left or right foot, sourced from a pool of 4000 patients to construct and evaluate a deep learning-based model. These radiographs were captured between June and November 2021, and patients who had undergone total ankle replacement surgery or ankle arthrodesis surgery were excluded. Various methods, including correlation analysis, Bland–Altman plots, and paired T-tests, were employed to assess the concordance between the angles automatically measured using the system and those assessed by clinical experts. The evaluation dataset comprised 150 weight-bearing radiographs from 150 patients. In all test cases, the angles automatically computed using the deep learning-based system were in good agreement with the reference standards (Meary’s angle: Pearson correlation coefficient (PCC) = 0.964, intraclass correlation coefficient (ICC) = 0.963, concordance correlation coefficient (CCC) = 0.963, p-value = 0.632, mean absolute error (MAE) = 1.59°; calcaneal pitch: PCC = 0.988, ICC = 0.987, CCC = 0.987, p-value = 0.055, MAE = 0.63°). The average time required for angle measurement using only the CPU to execute the deep learning-based system was 11 ± 1 s. The deep learning-based automatic angle measurement system, a tool for diagnosing flatfoot, demonstrated comparable accuracy and reliability with the results obtained by medical professionals for patients without internal fixation devices.

Abstract Super-enhancers are a class of DNA cis-regulatory elements that can regulate cell identity, cell fate, stem cell pluripotency, and even tumorigenesis. Increasing evidence shows that epigenetic modifications play an important role in the pathogenesis of various types of cancer. However, the current research is far from enough to reveal the complex mechanism behind it. This study found a super-enhancer enriched with abnormally active histone modifications in pancreatic ductal adenocarcinoma (PDAC), called DKK1-super-enhancer (DKK1-SE). The major active component of DKK1-SE is component enhancer e1. Mechanistically, AP1 induces chromatin remodeling in component enhancer e1 and activates the transcriptional activity of DKK1. Moreover, DKK1 was closely related to the malignant clinical features of PDAC. Deletion or knockdown of DKK1-SE significantly inhibited the proliferation, colony formation, motility, migration, and invasion of PDAC cells in vitro, and these phenomena were partly mitigated upon rescuing DKK1 expression. In vivo, DKK1-SE deficiency not only inhibited tumor proliferation but also reduced the complexity of the tumor microenvironment. This study identifies that DKK1-SE drives DKK1 expression by recruiting AP1 transcription factors, exerting oncogenic effects in PDAC, and enhancing the complexity of the tumor microenvironment.

Objective: To astablish a strong popularity, high sensitivity of six human milk oligosaccharides in dairy product by precolumn derivatization high performance liquid chromatography-fluorescence method. Methods: Aquatic product sample was precipitated with glacial acetic acid, filtration by using the filter paper. It was derived by 2-aminobenzamide solution. The extracts were centrifuged and filtered by using the organic filter membrane and analyzed by using a AdvanceBio Glycan Map column to be separated and detected，employing acetonitrile-50 mmol/L ammonium formate solution （pH 4.4） as the mobile phase for gradient elution. Results: Under the experimental conditions, six human milk oligosaccharides in dairy product were linear in the range of 1.00～400.0 mg/L, and the correlation coefficients were all over 0.999. The detection limit of the method was 4.1～10.9 mg/kg, the limits of quantification were 12.3～32.7 mg/kg, the mean recoveries rate was ranged from 71.3% to 90.2% with the intra-day precisions （n=6） in the range of 1.0%～6.3% and inter-day precisions （n=6） less than 10.0%. Conclusion: This method can meet the requirements of the daily detection of six human milk oligosaccharides due to its simplicity and sensitives.

A pilot plant of microbubble ozonation and biological treatment was used to treat chemical wastewater in depth, and its long-term operation performance was evaluated and predicted by a neural network model. The results showed that the chemical wastewater could be treated stably and effectively in the pilot plant, and the average removal rates of COD and UV254 in the phase of microbubble ozontion were 35.1% and 52.5%, respectively. The mass ratio of ozone dosage to influent COD amount was an important parameter influencing the operation performance, which should be controlled as 0.5 for better performance. The wastewater biodegradability could be improved effectively by microbubble ozonation, BOD5/COD could increase from 0.10 to 0.33 and the ratio of BOD5 generated amount to COD removed amount could reach to 37.23%. Then biological treatment was applied for the improved water, and the contribution of BOD5 removal to COD removal was more than 80% in biological treatment. Back propagation neural network (BPNN) was used to establish a prediction model of the effect of m on COD removal performance in microbubble ozonation, which showed a stable prediction ability with acceptable accuracy.

Abstract Background Cerebral organoids (COs) are the most advanced in vitro models that resemble the human brain. The use of COs as a model for Alzheimer’s disease (AD), as well as other brain diseases, has recently gained attention. This study aimed to develop a human AD CO model using normal human pluripotent stem cells (hPSCs) that recapitulates the pathological phenotypes of AD and to determine the usefulness of this model for drug screening. Methods We established AD hPSC lines from normal hPSCs by introducing genes that harbor familial AD mutations, and the COs were generated using these hPSC lines. The pathological features of AD, including extensive amyloid-β (Aβ) accumulation, tauopathy, and neurodegeneration, were analyzed using enzyme-linked immunosorbent assay, Amylo-Glo staining, thioflavin-S staining, immunohistochemistry, Bielschowsky’s staining, and western blot analysis. Results The AD COs exhibited extensive Aβ accumulation. The levels of paired helical filament tau and neurofibrillary tangle-like silver deposits were highly increased in the AD COs. The number of cells immunoreactive for cleaved caspase-3 was significantly increased in the AD COs. In addition, treatment of AD COs with BACE1 inhibitor IV, a β-secretase inhibitor, and compound E, a γ-secretase inhibitor, significantly attenuated the AD pathological features. Conclusion Our model effectively recapitulates AD pathology. Hence, it is a valuable platform for understanding the mechanisms underlying AD pathogenesis and can be used to test the efficacy of anti-AD drugs.

Abstract Esophageal squamous cell carcinoma (ESCC) remains an important health concern in developing countries. Patients with advanced ESCC have a poor prognosis and survival rate, and achieving early diagnosis remains a challenge. Metabolic biomarkers are gradually gaining attention as early diagnostic biomarkers. Hence, this multicenter study comprehensively evaluated metabolism dysregulation in ESCC through an integrated research strategy to identify key metabolite biomarkers of ESCC. First, the metabolic profiles were examined in tissue and serum samples from the discovery cohort (n = 162; ESCC patients, n = 81; healthy volunteers, n = 81), and ESCC tissue-induced metabolite alterations were observed in the serum. Afterward, RNA sequencing of tissue samples (n = 46) was performed, followed by an integrated analysis of metabolomics and transcriptomics. The potential biomarkers for ESCC were further identified by censoring gene-metabolite regulatory networks. The diagnostic value of the identified biomarkers was validated in a validation cohort (n = 220), and the biological function was verified. A total of 457 dysregulated metabolites were identified in the serum, of which 36 were induced by tumor tissues. The integrated analyses revealed significant alterations in the purine salvage pathway, wherein the abundance of hypoxanthine/xanthine exhibited a positive correlation with HPRT1 expression and tumor size. A diagnostic model was developed using two purine salvage–associated metabolites. This model could accurately discriminate patients with ESCC from normal individuals, with an area under the curve (AUC) (95% confidence interval (CI): 0.680–0.843) of 0.765 in the external cohort. Hypoxanthine and HPRT1 exerted a synergistic effect in terms of promoting ESCC progression. These findings are anticipated to provide valuable support in developing novel diagnostic approaches for early ESCC and enhance our comprehension of the metabolic mechanisms underlying this disease.

BackgroundPaeoniae Radix Rubra (PRR) has been used widely to promote blood circulation and eliminate blood stasis in China clinical practice owing to its extensive pharmacological effects. However, the “quality markers” (Q-markers) of the antioxidant effects remains unknown.ObjectTo explore the Q-markers of antioxidant activity based on multiple strategies, which would provide reference for the quality evaluation of PRR based on specific pharmacodynamic-oriented.MethodsFirstly, the “fingerprint” profiles of 15 batches of PRR were acquired and identified by ultrahigh performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UHPLC-Q-TOF MS/MS) and the common peaks extracted. Meanwhile, the MTT assay was used to evaluate the effect of 15 batches of PRR on H2O2-induced oxidative stress in HT-22 cells. The antioxidant activity of PRR was investigated simultaneously by superoxide dismutase (SOD), glutathione (GSH), and malondialdehyde (MDA) commercial kits. The relationship between common peaks and antioxidant indexes were constructed by grey relational analysis (GRA) and partial least squares-discriminant analysis (PLS-DA) for the identification of preselected Q-markers. Secondly, experimental verification was conducted to investigate the protective effect of the preliminary components on HT-22 cells undergoing oxidative stress. Finally, for the further validation of effectiveness of antioxidant Q-markers, network pharmacology was applied to explore potential targets, and the molecular docking technology was used to value the binding ability of the potential active components of PRR to the antioxidant targets.ResultsThirty-seven common peaks from 15 batches of PRR were identified qualitatively by UHPLC-Q-TOF MS/MS. The MTT assay showed that PRR could reduce the oxidative damage induced by H2O2 upon HT-22 cells according to the index of MDA, SOD and GSH. Eight potential antioxidant components were screened by spectrum-effect correlation analysis: paeoniflorin, galloylpaeoniflorin, albiflorin, 1,2,3,4,6-o-pentagalloylglucose, benzoylpaeoniflorin, pinocembrin, oleanic acid, and isorhamnetin-3-o-nehesperidine. Each of these preliminary components showed significant protections on cellular oxidative stress (P < 0.05). Interleukin-6 (IL-6), protein kinase B (AKT1), and tumor necrosis factor (TNF) were predicted to be the major potential targets of PRR, and the good binding ability were presented between the potential active components of PRR and each target as a whole.ConclusionEight components were identified as the antioxidant Q-markers of PRR based on an integrated multimodal strategy.

ObjectiveTo detect muscular system adverse reaction signals of sacubitril/valsartan treatment combined with statins (atorvastatin, rosuvastatin, simvastatin) to provide a reference for clinical administration.MethodsMultiplicative and additive models were used to mine the FDA’s spontaneous reports database to detect signals of drug-drug interactions between sacubitril/valsartan and statins. SAS 9.4 software was used to conduct statistical tests for suspicious signals to determine whether the signals were statistically significant.ResultsA total of 8,883,870 adverse reaction reports were analyzed. The combinations “sacubitril/valsartan - simvastatin - musculoskeletal muscle pain” had statistically significant correlation signals in both models (P < 0.05). The combination “sacubitril/valsartan - atorvastatin - myopathy” and “sacubitril/valsartan–simvastatin - myopathy” had statistically significant correlation signal in the multiplicative model (P < 0.05).ConclusionCompared with a single drug, coadministration of sacubitril/valsartan with atorvastatin may increase safety risks to myopathy, with simvastatin may increase safety risks to the musculoskeletal pain and myopathy, which should be closely monitored in clinical practice.

Abstract The Holocene temperature conundrum, the discrepancy between proxy-based Holocene global cooling and simulated global annual warming trends, remains controversial. Meanwhile, reconstructions and simulations show inconsistent spatial patterns of terrestrial temperature changes. Here we report Holocene alkenone records to address spatial patterns over mid-latitude Eurasia. In contrast with long-term cooling trends in warm season temperatures in northeastern China, records from southwestern Siberia are characterized by colder conditions before ~6,000 years ago, thus long-term warming trends. Together with existing records from surrounding regions, we infer that colder airmass might have prevailed in the interior of mid-latitude Eurasian continent during the early to mid-Holocene, perhaps associated with atmospheric response to remnant ice sheets. Our results challenge the proposed seasonality bias in proxies and modeled spatial patterns in study region, highlighting that spatial patterns of Holocene temperature changes should be re-considered in record integrations and model simulations, with important implications for terrestrial hydroclimate changes.

Abstract There are limited data available regarding the connection between hypertension and heavy metal exposure. The authors intend to establish an interpretable machine learning (ML) model with high efficiency and robustness that identifies hypertension based on heavy metal exposure. Our datasets were obtained from the US National Health and Nutrition Examination Survey (NHANES, 2013–2020.3). The authors developed 5 ML models for hypertension identification by heavy metal exposure, and tested them by 10 discrimination characteristics. Further, the authors chose the optimally performing model after parameter adjustment by Genetic Algorithm (GA) for identification. Finally, in order to visualize the model's ability to make decisions, the authors used SHapley Additive exPlanation (SHAP) and Local Interpretable Model‐Agnostic Explanations (LIME) algorithm to illustrate the features. The study included 19 368 participants in total. A best‐performing eXtreme Gradient Boosting (XGB) with GA for hypertension identification by 16 heavy metals was selected (AUC: 0.774; 95% CI: 0.772–0.776; accuracy: 87.7%). According to SHAP values, Barium (0.02), Cadmium (0.017), Lead (0.017), Antimony (0.008), Tin (0.007), Manganese (0.006), Thallium (0.004), Tungsten (0.004) in urine, and Lead (0.048), Mercury (0.035), Selenium (0.05), Manganese (0.007) in blood positively influenced the model, while Cadmium (−0.001) in urine negatively influenced the model. Study participants' hypertension associated with heavy metal exposure was identified by an efficient, robust, and interpretable GA‐XGB model with SHAP and LIME. Barium, Cadmium, Lead, Antimony, Tin, Manganese, Thallium, Tungsten in urine, and Lead, Mercury, Selenium, Manganese in blood are positively correlated with hypertension, while Cadmium in blood is negatively correlated with hypertension.

Abstract The Kellgren–Lawrence (KL) grading system is a scoring system for classifying the severity of knee osteoarthritis using X-ray images, and it is the standard X-ray-based grading system for diagnosing knee osteoarthritis. However, KL grading depends on the clinician’s subjective assessment. Moreover, the accuracy varies significantly depending on the clinician’s experience and can be particularly low. Therefore, in this study, we developed an ensemble network that can predict a consistent and accurate KL grade for knee osteoarthritis severity using a deep learning approach. We trained individual models on knee X-ray datasets using the most suitable image size for each model in an ensemble network rather than using datasets with a single image size. We then built the ensemble network using these models to overcome the instability of single models and further improve accuracy. We conducted various experiments using a dataset of 8260 images from the Osteoarthritis Initiative open dataset. The proposed ensemble network exhibited the best performance, achieving an accuracy of 76.93% and an F1-score of 0.7665. The Grad-CAM visualization technique was used to further evaluate the focus of the model. The results demonstrated that the proposed ensemble network outperforms existing techniques that have performed well in KL grade classification. Moreover, the proposed model focuses on the joint space around the knee to extract the imaging features required for KL grade classification, revealing its high potential for diagnosing knee osteoarthritis.

Abstract Background The pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) of breast cancer is closely related to a better prognosis. However, there are no reliable indicators to accurately identify which patients will achieve pCR before surgery, and a model for predicting pCR to NAC is required. Methods A total of 269 breast cancer patients in Shandong Cancer Hospital and Liaocheng People’s Hospital receiving anthracycline and taxane-based NAC were prospectively enrolled. Expression profiling using a 457 cancer-related gene sequencing panel (DNA sequencing) covering genes recurrently mutated in breast cancer was carried out on 243 formalin-fixed paraffin-embedded tumor biopsies samples before NAC from 243 patients. The unique personalized panel of nine individual somatic mutation genes from the constructed model was used to detect and analyze ctDNA on 216 blood samples. Blood samples were collected at indicated time points including before chemotherapy initiation, after the 1st NAC and before the 2nd NAC cycle, during intermediate evaluation, and prior to surgery. In this study, we characterized the value of gene profile mutation and circulating tumor DNA (ctDNA) in combination with clinical characteristics in the prediction of pCR before surgery and investigated the prognostic prediction. The median follow-up time for survival analysis was 898 days. Results Firstly, we constructed a predictive NAC response model including five single nucleotide variant (SNV) mutations (TP53, SETBP1, PIK3CA, NOTCH4 and MSH2) and four copy number variation (CNV) mutations (FOXP1-gain, EGFR-gain, IL7R-gain, and NFKB1A-gain) in the breast tumor, combined with three clinical factors (luminal A, Her2 and Ki67 status). The tumor prediction model showed good discrimination of chemotherapy sensitivity for pCR and non-pCR with an AUC of 0.871 (95% CI, 0.797–0.927) in the training set, 0.771 (95% CI, 0.649–0.883) in the test set, and 0.726 (95% CI, 0.556–0.865) in an extra test set. This tumor prediction model can also effectively predict the prognosis of disease-free survival (DFS) with an AUC of 0.749 at 1 year and 0.830 at 3 years. We further screened the genes from the tumor prediction model to establish a unique personalized panel consisting of 9 individual somatic mutation genes to detect and analyze ctDNA. It was found that ctDNA positivity decreased with the passage of time during NAC, and ctDNA status can predict NAC response and metastasis recurrence. Finally, we constructed the chemotherapy prediction model combined with the tumor prediction model and pretreatment ctDNA levels, which has a better prediction effect of pCR with the AUC value of 0.961. Conclusions In this study, we established a chemotherapy predictive model with a non-invasive tool that is built based on genomic features, ctDNA status, as well as clinical characteristics for predicting pCR to recognize the responders and non-responders to NAC, and also predicting prognosis for DFS in breast cancer. Adding pretreatment ctDNA levels to a model containing gene profile mutation and clinical characteristics significantly improves stratification over the clinical variables alone.

C4H7N5O, monoclinic, P21 (no. 4), a = 4.855(3) Å, b = 9.026(5) Å, c = 7.092(4) Å, β = 103.267(7)°, V = 302.5(3) Å3, Z = 2, R gt(F) = 0.0369, wR ref(F 2) = 0.0960, T = 296 K.