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Rong Yu,1,&ast; Chuan Liu,1,&ast; Jixiang Zhang,1,&ast; Jiao Li,1,&ast; Shan Tian,2 Fugui Ding,1 Zhengru Liu,3 Ting Wang,4 Zhongchun Liu,5 Changqing Jiang,6 Jie Shi,7 Kaichun Wu,8 Weiguo Dong1 1Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, 430060, People’s Republic of China; 2Department of Infectious Diseases, Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430000, People’s Republic of China; 3Department of Gastroenterology, First Affiliated Hospital of Kunming Medical University, Kunming, 650032, People’s Republic of China; 4Department of Gastroenterology, First Affiliated Hospital of Hainan Medical College, Haikou, 570102, People’s Republic of China; 5Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, 430060, People’s Republic of China; 6Department of Clinical Psychology, Beijing Anding Hospital, Capital Medical University, Beijing, 100088, People’s Republic of China; 7Department of Medical Psychology, Chinese People’s Liberation Army Rocket Army Characteristic Medical Center, Beijing, 100088, People’s Republic of China; 8Department of Gastroenterology, Xijing Hospital, Air Force Medical University, Xi’an, 710032, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Weiguo Dong, Department of Gastroenterology, Renmin Hospital of Wuhan University, No. 99 Zhangzhidong Road, Wuhan, Hubei Province, 430060, People’s Republic of China, Tel +86 027-88041911, Email dongweiguo@whu.edu.cn Kaichun Wu, Department of Gastroenterology, Xijing Hospital, Air Force Medical University, No. 127 West Changle Road, Xi’an, Shaanxi Province, 710032, People’s Republic of China, Tel +86 029-84771600, Email kaicwu@fmmu.edu.cnObjective: To explore the correlation between disease activity and anxiety, depression, sleep quality, and quality of life in patients with inflammatory bowel disease (IBD).Methods: The disease activity of IBD patients was evaluated by 66 gastroenterologists from 42 hospitals in 22 provinces in China from September 2021 to May 2022. Anxiety, depression, sleep quality and quality of life of IBD patients were investigated and statistically analyzed by different scales, including Generalized Anxiety Disorder 7-item Scale (GAD-7), Patient Health Questionnaire-9 (PHQ-9), Pittsburgh Sleep Quality Index (PSQI), and Inflammatory Bowel Disease Quality-of-Life Questionnaire (IBD-Q).Results: A total of 2478 IBD patients were included, of which 1532 (61.8%) were in active stage and 946 (38.2%) were in remission. The proportions of active IBD with anxiety, depression, sleep disturbance, and poor quality of life were 29.5%, 29.7%, 71.1%, and 50.1%, respectively, while the proportions of remission IBD with anxiety, depression, sleep disturbance, and poor quality of life were 19.1%, 24.4%, 69.3%, and 17.4%, respectively. IBD patients who also had anxiety, depression, sleep disturbances and poor quality of life had 80 cases (8.46%) in remission and 114 cases (7.44%) in active stage, with 54 cases (9.18%) in mild activity, 51 cases (6.95%) in moderate activity and 9 cases (4.49%) in severe activity. IBD patients with different disease activity levels differed in GAD-7 scores, PHQ-9 scores, PSQI scores, and IBD-Q scores (all P< 0.001). In IBD patients, anxiety, depression, and sleep disturbance, which interact with each other, can further aggravate their disease activity (all P< 0.001).Conclusion: Anxiety, depression, sleep disturbances, and quality of life are strongly correlated with disease activity in IBD patients, and IBD patients with psychological disturbances are most often in the active stage and have a poor quality of life.Keywords: inflammatory bowel disease, disease activity, anxiety, depression, sleep quality, quality of life, survey

The ability to rapidly and reliably screen for bacterial vaginosis (BV) during pregnancy is of great significance for maternal health and pregnancy outcomes. In this proof-of-concept study, we demonstrated the potential of carbon nanotube field-effect transistors (NTFET) in the rapid diagnostics of BV with the sensing of BV-related factors such as pH and biogenic amines. The fabricated sensors showed good linearity to pH changes with a linear correlation coefficient of 0.99. The pH sensing performance was stable after more than one month of sensor storage. In addition, the sensor was able to classify BV-related biogenic amine-negative/positive samples with machine learning, utilizing different test strategies and algorithms, including linear discriminant analysis (LDA), support vector machine (SVM), and principal component analysis (PCA). The biogenic amine sample status could be well classified using a soft-margin SVM model with a validation accuracy of 87.5%. The accuracy could be further improved using a gold gate electrode for measurement, with accuracy higher than 90% in both LDA and SVM models. We also explored the sensing mechanisms and found that the change in NTFET off current was crucial for classification. The fabricated sensors successfully detect BV-related factors, demonstrating the competitive advantage of NTFET for point-of-care diagnostics of BV.

Developing robust cell recognition strategies is important in biochemical research, but the lack of well-defined target molecules creates a bottleneck in some applications. In this paper, a carbon nanotube sensor array was constructed for the label-free discrimination of live and dead mammalian cells. Three types of carbon nanotube field-effect transistors were fabricated, and different features were extracted from the transfer characteristic curves for model training with linear discriminant analysis (LDA) and support-vector machines (SVM). Live and dead cells were accurately classified in more than 90% of samples in each sensor group using LDA as the algorithm. The recursive feature elimination with cross-validation (RFECV) method was applied to handle the overfitting and optimize the model, and cells could be successfully classified with as few as four features and a higher validation accuracy (up to 97.9%) after model optimization. The RFECV method also revealed the crucial features in the classification, indicating the participation of different sensing mechanisms in the classification. Finally, the optimized LDA model was applied for the prediction of unknown samples with an accuracy of 87.5-93.8%, indicating that live and dead cell samples could be well-recognized with the constructed model.

Accurately estimating prognosis based on clinicopathologic variables could improve risk stratification for patients with early-onset colorectal cancer (EOCRC). Our primary goal was to create and validate a survival nomogram with adequate performance for predicting overall survival (OS) in patients with EOCRC. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied to identify clinical features statistically related to OS. Then we established and internally validated a survival nomogram based on surveillance, epidemiology and end results (SEER) database (N=23813). A cohort of 77 patients with EOCRC from Renmin Hospital of Wuhan University (RHWU) was employed to detect the external validity of the survival nomogram. Moreover, we compared the predictive accuracy of survival nomogram with TNM stage, and also compared the OS between endoscopy and surgery groups before and after propensity score matching (PSM) among EOCRC patients with early stage (Tis-T1N0M0). We selected seven informative indexes (N stage, M stage, perineural invasion, chemotherapy, surgery primary site, summary stage and tumor grade) for the construction of the survival nomogram. Then the survival nomogram exhibited good discrimination with C-index of 0.829, 0.841 and 0.796 in the SEER training, SEER validation and RHWU validation sets, respectively. Calibration curves showed good concordance between the survival nomogram predictions and actual outcomes for 1-year, 3-year and 5-year OS. Furthermore, the survival nomogram was superior to risk stratification by TNM stage in predicting OS among patients with EOCRC. Early-stage patients treated with endoscopy showed similar survival to those with surgery before and after PSM. We proposed a survival nomogram based on the extensively used parameters to precisely predict OS in EOCRC patients. This survival nomogram will contribute to aid oncologists better risk stratification and prognostication for patients with EOCRC.

Purpose Coronavirus disease 2019 (COVID-19) has become a topic of concern worldwide; however, the impacts of type 2 diabetes mellitus (T2DM) on disease severity, therapeutic effect, and mortality of patients with COVID-19 are unclear. Methods All consecutive patients with COVID-19 admitted to the Renmin Hospital of Wuhan University from January 11 to February 6, 2020, were included in this study. Results A total of 663 patients with COVID-19 were included, while 67 patients with T2DM accounted for 10.1% of the total. Compared with patients with COVID-19 without T2DM, those with T2DM were older (aged 66 years vs 57 years; P < 0.001) and had a male predominance (62.7% vs 37.3%; P = 0.019) and higher prevalence of cardiovascular diseases (61.2% vs 20.6%; P < 0.001) and urinary diseases (9% vs 2.5%; P = 0.014). Patients with T2DM were prone to developing severe (58.2% vs 46.3%; P = 0.002) and critical COVID-19 (20.9% vs 13.4%; P = 0.002) and having poor therapeutic effect (76.1% vs 60.4%; P = 0.017). But there was no obvious difference in the mortality between patients with COVID-19 with and without T2DM (4.5% vs 3.7%; P = 0.732). Multivariate logistic regression analysis identified that T2DM was associated with poor therapeutic effect in patients with COVID-19 (odd ratio [OR] 2.99; 95% confidence interval [CI], 1.07-8.66; P = 0.04). Moreover, having a severe and critical COVID-19 condition (OR 3.27; 95% CI, 1.02-9.00; P = 0.029) and decreased lymphocytes (OR 1.59; 95% CI, 1.10-2.34; P = 0.016) were independent risk factors associated with poor therapeutic effect in patients with COVID-19 with T2DM. Conclusions T2DM influenced the disease severity and therapeutic effect and was one of the independent risk factors for poor therapeutic effect in patients with COVID-19.

ObjectivesAn outbreak of the highly contagious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has sickened thousands of people in China. The purpose of this study was to explore the early clinical characteristics of COVID-19 patients with cardiovascular disease (CVD).MethodsThis is a retrospective analysis of patients with COVID-19 from a single centre. All patients underwent real-time reverse transcription PCR for SARS-CoV-2 on admission. Demographic and clinical factors and laboratory data were reviewed and collected to evaluate for significant associations.ResultsThe study included 541 patients with COVID-19. A total of 144 (26.6%) patients had a history of CVD. The mortality of patients with CVD reached 22.2%, which was higher than that of the overall population of this study (9.8%). Patients with CVD were also more likely to develop liver function abnormality, elevated blood creatinine and lactic dehydrogenase (pConclusionsConsidering the high prevalence of CVD, a thorough CVD assessment at diagnosis and early intervention are recommended in COVID-19 patients with CVD. Patients with CVD are more vulnerable to deterioration.

Background Identifying the early-stage colon adenocarcinoma (ECA) patients who have lower risk cancer vs. the higher risk cancer could improve disease prognosis. Our study aimed to explore whether the glandular morphological features determined by computational pathology could identify high risk cancer in ECA via H&E images digitally. Methods 532 ECA patients retrospectively from 2 independent data centers, as well as 113 from The Cancer Genome Atlas (TCGA), were enrolled in this study. Four tissue microarrays (TMAs) were constructed across ECA hematoxylin and eosin (H&E) stained slides. 797 quantitative glandular morphometric features were extracted and 5 most prognostic features were identified using minimum redundancy maximum relevance to construct an image classifier. The image classifier was evaluated on D2/D3 = 223, D4 = 46, D5 = 113. The expression of Ki67 and serum CEA levels were scored on D3, aiming to explore the correlations between image classifier and immunohistochemistry data and serum CEA levels. The roles of clinicopathological data and ECAHBC were evaluated by univariate and multivariate analyses for prognostic value. Results The image classifier could predict ECA recurrence (accuracy of 88.1%). ECA histomorphometric-based image classifier (ECAHBC) was an independent prognostic factor for poorer disease-specific survival [DSS, (HR = 9.65, 95% CI 2.15–43.12, P = 0.003)]. Significant correlations were observed between ECAHBC-positive patients and positivity of Ki67 labeling index (Ki67Li) and serum CEA. Conclusion Glandular orientation and shape could predict the high risk cancer in ECA and contribute to precision oncology. Computational pathology is emerging as a viable and objective means of identifying predictive biomarkers for cancer patients.

Non-invasive detection and quantification of the stress hormone cortisol not only provide the assessment of stress level but also enable close monitoring of mental and physical health. In this work, we report two types of field-effect transistors (FETs) based on semiconducting single-walled carbon nanotubes (sc-SWCNTs) as selective cortisol sensors. In one FET device configuration cortisol antibody is directly attached to sc-SWCNTs, the other one is using gold nanoparticles (Au NPs) as linkers in between antibody and sc-SWCNTs to enhance the device conductance. We fabricated and characterized both device configurations to investigate how the nanomaterial interface to cortisol antibody influences the biosensor performance. We tested the sensors in artificial sweat and compared these two types of sensors in terms of limit of detection and sensitivity, and the results indicate that direct binding between antibody and sc-SWCNTs yields better biosensor characteristics.

BACKGROUND In recent years, emerging evidence has suggested that ulcerative colitis occurs as a consequence of an imbalance between oxidative stress and antioxidant capacity. The objective of this study was to investigate whether serum total bilirubin and serum uric acid levels were associated with ulcerative colitis. MATERIAL AND METHODS We conducted a retrospective case-control study which included 170 patients with ulcerative colitis and 200 healthy individuals. Concentrations of serum total bilirubin and serum uric acid were obtained from biochemical information and segregated into quartiles. Logistic regression analysis was adopted to explore the correlations between levels of the 2 biochemical markers and the risk of ulcerative colitis. RESULTS Compared with healthy controls, patients with ulcerative colitis exhibited lower levels of serum bilirubin (9.30 umol/L versus 12.49 umol/L respectively, P0.001). Multivariate logistic regression showed that the lowest quartile of total serum bilirubin was independently associated with the occurrence of ulcerative colitis (OR=2.56, 95%CI: 1.54-4.25, P0.001). Similarly, ulcerative colitis patients exhibited higher concentrations of serum uric acid (338 umol/L versus 300 umol/L respectively, P=0.041). Multivariate logistic regression showed that the highest quartile of serum uric acid was independently associated with ulcerative colitis risk (OR=1.20, 95%CI: 1.05-1.77, P=0.045). Furthermore, a negative association was observed between serum total bilirubin and serum uric acid in patients with ulcerative colitis. CONCLUSIONS Lower levels of serum total bilirubin and higher levels of serum uric acid are associated with ulcerative colitis patients compared to healthy controls.

Inductively coupled plasma mass spectrometry (ICP-MS) with the merits of high sensitivity and accuracy, strong tolerance to interference and multi-element simultaneous detection ability has shown its great potentials in the quantification of biomolecules with elemental labeling strategies in the past decade. Exogenous elemental tags play essential roles on the performance of ICP-MS based analytical strategies for biomolecules. In this review, the state of the art of ICP-MS based analytical techniques with exogenous tags for the quantification of biomolecules is provided. The basics of exogenous tags, such as the labeling strategies and classification of tags, are summarized, and the applications of ICP-MS based analytical techniques with elemental tags for the quantification of biomolecules (including proteins and nucleic acids) and cell analysis are discussed in detail. Finally, several prospects for the further development of this area are proposed.

Apoptosis is a main type of cell death in which caspase-3 plays a key role. In this work, a simple, fast and sensitive immunoassay for caspase-3 is established by using inductively coupled plasma mass spectrometry (ICP-MS) detection and signal enhancement gold nanoparticle (Au-NP) labelling of the secondary antibody (IgG). After the immunoreaction of caspase-3, primary antibody and Au-NP labeled IgG, the concentration of caspase-3 was determined by ICP-MS analysis of the Au-NPs released from the immunocomplex. Under the optimized conditions, a limit of detection (LOD, 3σ) of 0.42 ng mL(-1) (0.31 nM) was obtained for caspase-3, with a dynamic range of 1-200 ng mL(-1) and a relative standard deviation of 4.1% (c = 5 ng mL(-1), n = 11). The proposed method has good specificity towards caspase-3. To demonstrate the application potential of the proposed method, the cell lysates of Hg(2+)-induced HepG2 cells were analyzed, and it was found that the concentration of caspase-3 increased when increasing the incubation concentration of Hg(2+). This method is easy, sensitive and selective, and has excellent capability of tolerating a complex biological matrix, indicating the potential of the ICP-MS-based assay in the study of apoptosis.

Upconversion nanoparticles (UCNPs) have received increasing attention due to their unique optical properties. Recognizing that UCNPs are lanthanide-doped nanoparticles, we incorporated UCNPs into an immunoassay with inductively coupled plasma mass spectrometry (ICP-MS) detection for the determination of specific proteins, e.g., alpha-fetoprotein (AFP). The sensitivity of the assay was enhanced because of the ICP-MS detection of UCNPs that contained large numbers of lanthanide elemental tags. Conjugates of UCNPs and antibodies were prepared and the morphology of the conjugates was characterized by transmission electron microscopy. After a sandwich immunoreaction, the AFP was determined by the ICP-MS analysis of UCNPs. Under the optimized conditions, a limit of detection (3σ) of 0.31 ng mL−1 based on 89Y signal and 0.22 ng mL−1 based on 174Yb signal was obtained for AFP, with a dynamic range of 0.5–35 ng mL−1 and a relative standard deviation of 4.8% (c = 5 ng mL−1, n = 9). The developed method was applied to the determination of AFP in human serum and the recovery for the spiked sample was in the range of 98.6–123%. The proposed method is simple, rapid, selective and sensitive, and has a good tolerance for the complex biological matrix, indicating great potential for the application of UCNP in biological research as an elemental tag.

Rationale:Ulcerative colitis is a chronic and recurrent inflammatory disease involving the intestine. It is reported that about 40% of patients with ulcerative colitis have extraintestinal manifestations, where as the literature on neurological involvement as extraintestinal manifestation is