A Mesoporous Silica-loaded Multi-functional Hydrogel Enhanced Tendon Healing via Immunomodulatory and pro-regenerative Effects

Tendon injuries are pervasive orthopedic injuries encountered by the general population. Nonetheless, recovery after severe injuries such as Achilles tendon injury is limited. Consequently, there is a pressing need to devise interventions, including biomaterials, that foster tendon healing. Regrettably, tissue engineering treatments have faced obstacles in crafting appropriate tissue scaffolds and efficacious nanomedical approaches. To surmount these hurdles, we have pioneered an innovative injectable hydrogel (CP@SiO2), comprising puerarin and chitosan through in situ self-assembly, while concurrently delivering mesoporous silica nanoparticles for tendon healing. In our research, we employed CP@SiO2 hydrogel for the treatment of Achilles tendon injuries, conducting extensive in vivo and in vitro experiments to evaluate its efficacy. Our results show that CP@SiO2 hydrogel significantly promotes the proliferation and differentiation of tendon-derived stem cells. BrdU assay results indicated a 12% increase in cell growth rate compared to gel treatment. Additionally, PCR results showed an increase in the expression of genes related to tendon differentiation and stemness maintenance. Moreover, the hydrogel effectively mitigated inflammation by promoting M2 polarization and inhibiting M1 polarization, thus alleviating macrophage-induced inflammation. The hydrogel also accelerated the recovery of injured tendon function; biomechanical assessments revealed that at 28 days post-operation, the load-to-failure ratio of tendons in the CP@SiO2 group was 53.28N, surpassing the 32.06N of the model group. Furthermore, we conducted a comprehensive in vivo evaluation using a tendon injury model, which included detailed histological analysis and behavioral observations. Our findings indicate that this multifaceted injectable CP@SiO2 hydrogel constitutes a suitable bioactive material for tendon repair and presents a promising new strategy for the clinical management of tendon injuries. This article is protected by copyright. All rights reserved.

Development and validation of prediction models for papillary thyroid cancer structural recurrence using machine learning approaches

BACKGROUND

Although papillary thyroid cancer (PTC) patients are known to have an excellent prognosis, up to 30% of patients experience disease recurrence after initial treatment. Accurately predicting disease prognosis remains a challenge given that the predictive value of several predictors remains controversial. Thus, we investigated whether machine learning (ML) approaches based on comprehensive predictors can predict the risk of structural recurrence for PTC patients.

METHODS

A total of 2244 patients treated with thyroid surgery and radioiodine were included. Twenty-nine perioperative variables consisting of four dimensions (demographic characteristics and comorbidities, tumor-related variables, lymph node (LN)-related variables, and metabolic and inflammatory markers) were analyzed. We applied five ML algorithms-logistic regression (LR), support vector machine (SVM), extreme gradient boosting (XGBoost), random forest (RF), and neural network (NN)-to develop the models. The area under the receiver operating characteristic (AUC-ROC) curve, calibration curve, and variable importance were used to evaluate the models' performance.

RESULTS

During a median follow-up of 45.5 months, 179 patients (8.0%) experienced structural recurrence. The non-stimulated thyroglobulin, LN dissection, number of LNs dissected, lymph node metastasis ratio, N stage, comorbidity of hypertension, comorbidity of diabetes, body mass index, and low-density lipoprotein were used to develop the models. All models showed a greater AUC (AUC = 0.738 to 0.767) than did the ATA risk stratification (AUC = 0.620, DeLong test: P < 0.01). The SVM, XGBoost, and RF model showed greater sensitivity (0.568, 0.595, 0.676), specificity (0.903, 0.857, 0.784), accuracy (0.875, 0.835, 0.775), positive predictive value (PPV) (0.344, 0.272, 0.219), negative predictive value (NPV) (0.959, 0.959, 0.964), and F1 score (0.429, 0.373, 0.331) than did the ATA risk stratification (sensitivity = 0.432, specificity = 0.770, accuracy = 0.742, PPV = 0.144, NPV = 0.938, F1 score = 0.216). The RF model had generally consistent calibration compared with the other models. The Tg and the LNR were the top 2 important variables in all the models, the N stage was the top 5 important variables in all the models.

CONCLUSIONS

The RF model achieved the expected prediction performance with generally good discrimination, calibration and interpretability in this study. This study sheds light on the potential of ML approaches for improving the accuracy of risk stratification for PTC patients.

TRIAL REGISTRATION

Retrospectively registered at www.chictr.org.cn (trial registration number: ChiCTR2300075574, date of registration: 2023-09-08).

[Mid-term efficacy evaluation of ABO incompatible living relative kidney transplantation based on protocol biopsy]

Objective: To evaluate the mid-term efficacy of ABO incompatible living donor kidney transplantation (ABOi-KT) based on the results of routine renal biopsy for transplantation. Methods: Retrospective collection of clinical data from 23 pairs of ABOi-KT donors and recipients at the First Affiliated Hospital of Sun Yat-sen University from July 2015 to November 2021. ABOi-KT was performed on recipients after desensitization treatment, and the results of routine kidney transplant biopsy at 1 week, 1 month, 3 months, 6 months, and 12 months after surgery were analyzed. Combined with blood type antibody levels and renal function recovery, the mid-term efficacy of ABOi-KT was evaluated. Results: Among the 23 recipients, there were 19 males and 4 females; age range from 19 to 47 years old [(29.6±6.7) years old], all underwent ABOi-KT successfully after receiving desensitization treatment. The follow-up time was (44.6±22.4) months, of which 22 cases were followed up for more than 1 year. The incidence rates of rejection reactions at 1 week, 1 month, 3 months, 6 months, and 12 months after surgery were 15.0% (3/20), 11.1% (1/9), 7.7% (1/13), 25.0% (3/12), and 12.5% (1/8), respectively. For receptors with rejection reactions, targeted anti-rejection therapy was performed based on clinical symptoms and various indicators. Borderline T cell mediated rejection (TCMR) can be converted to mild tubular inflammation after anti-rejection treatment. The positive rate of complement C4d in peritubular capillaries was 95.0% (19/20) one week after surgery, and the positive rate of complement C4d was 100% at 3 and 12 months after surgery. The cumulative survival rates at 1, 3, 5, and 7 years after surgery were all 100%. The cumulative survival rates at 1, 3, 5, and 7 years after kidney transplantation were 100%, 93.3%, 84.0%, and 84.0%, respectively. Except for 2 recipients who underwent transplantation in 2017 and experienced kidney failure at 30 and 49 months after surgery, all other transplanted kidneys survived. Conclusions: The results of routine renal transplant biopsy show that ABOi-KT has a good mid-term therapeutic effect. The pathological changes of ABOi-KT can be dynamically observed through routine renal transplant biopsy and targeted treatment for rejection reactions can be provided accordingly.

[Identifying Novel Coronavirus Pneumonia With CT Images: A Deep Learning Approach With Detail Upsampling and Attention Guidance]

Objective

To construct a deep learning-based target detection method to help radiologists perform rapid diagnosis of lesions in the CT images of patients with novel coronavirus pneumonia (NCP) by restoring detailed information and mining local information.

Methods

We present a deep learning approach that integrates detail upsampling and attention guidance. A linear upsampling algorithm based on bicubic interpolation algorithm was adopted to improve the restoration of detailed information within feature maps during the upsampling phase. Additionally, a visual attention mechanism based on vertical and horizontal spatial dimensions embedded in the feature extraction module to enhance the capability of the object detection algorithm to represent key information related to NCP lesions.

Results

Experimental results on the NCP dataset showed that the detection method based on the detail upsampling algorithm improved the recall rate by 1.07% compared with the baseline model, with the AP50 reaching 85.14%. After embedding the attention mechanism in the feature extraction module, 86.13% AP50, 73.92% recall, and 90.37% accuracy were achieved, which were better than those of the popular object detection models.

Conclusion

The feature information mining of CT images based on deep learning can further improve the lesion detection ability. The proposed approach helps radiologists rapidly identify NCP lesions on CT images and provides an important clinical basis for early intervention and high-intensity monitoring of NCP patients.

Relative importance of triglyceride glucose index combined with body mass index in predicting recovery from prediabetic state to normal fasting glucose: a cohort analysis based on a Chinese physical examination population

BACKGROUND

Prediabetes is a high-risk state for diabetes, and numerous studies have shown that the body mass index (BMI) and triglyceride-glucose (TyG) index play significant roles in risk prediction for blood glucose metabolism. This study aims to evaluate the relative importance of BMI combination with TyG index (TyG-BMI) in predicting the recovery from prediabetic status to normal blood glucose levels.

METHODS

A total of 25,397 prediabetic subjects recruited from 32 regions across China. Normal fasting glucose (NFG), prediabetes, and diabetes were defined referring to the American Diabetes Association (ADA) criteria. After normalizing the independent variables, the impact of TyG-BMI on the recovery or progression of prediabetes was analyzed through the Cox regression models. Receiver Operating Characteristic (ROC) curve analysis was utilized to visualize and compare the predictive value of TyG-BMI and its constituent components in prediabetes recovery/progression.

RESULTS

During the average observation period of 2.96 years, 10,305 individuals (40.58%) remained in the prediabetic state, 11,278 individuals (44.41%) recovered to NFG, and 3,814 individuals (15.02%) progressed to diabetes. The results of multivariate Cox regression analysis demonstrated that TyG-BMI was negatively associated with recovery from prediabetes to NFG and positively associated with progression from prediabetes to diabetes. Further ROC analysis revealed that TyG-BMI had higher impact and predictive value in predicting prediabetes recovering to NFG or progressing to diabetes in comparison to the TyG index and BMI. Specifically, the TyG-BMI threshold for predicting prediabetes recovery was 214.68, while the threshold for predicting prediabetes progression was 220.27. Additionally, there were significant differences in the relationship of TyG-BMI with prediabetes recovering to NFG or progressing to diabetes within age subgroups. In summary, TyG-BMI is more suitable for assessing prediabetes recovery or progression in younger populations (< 45 years old).

CONCLUSIONS

This study, for the first time, has revealed the significant impact and predictive value of the TyG index in combination with BMI on the recovery from prediabetic status to normal blood glucose levels. From the perspective of prediabetes intervention, maintaining TyG-BMI within the threshold of 214.68 holds crucial significance.

Identification of ipsilateral supraclavicular lymph node metastasis in breast cancer based on LASSO regression with a high penalty factor

Aiming at the problems of small sample size and large feature dimension in the identification of ipsilateral supraclavicular lymph node metastasis status in breast cancer using ultrasound radiomics, an optimized feature combination search algorithm is proposed to construct linear classification models with high interpretability. The genetic algorithm (GA) is used to search for feature combinations within the feature subspace using least absolute shrinkage and selection operator (LASSO) regression. The search is optimized by applying a high penalty to the L1 norm of LASSO to retain excellent features in the crossover operation of the GA. The experimental results show that the linear model constructed using this method outperforms those using the conventional LASSO regression and standard GA. Therefore, this method can be used to build linear models with higher classification performance and more robustness.

A nomogram to preoperatively predict the aggressiveness of non-functional pancreatic neuroendocrine tumors based on CT features

OBJECTIVES

To develop a nomogram to predict the aggressiveness of non-functional pancreatic neuroendocrine tumors (NF-pNETs) based on preoperative computed tomography (CT) features.

METHODS

This study included 176 patients undergoing radical resection for NF-pNETs. These patients were randomly divided into the training (n = 123) and validation sets (n = 53). A nomogram was developed based on preoperative predictors of aggressiveness of the NF-pNETs which were identified by univariable and multivariable logistic regression analysis. The aggressiveness of NF-pNETs was defined as a composite measure including G3 grading, N+, distant metastases, and/ or disease recurrence.

RESULTS

Altogether, the number of patients with highly aggressive NF-pNETs was 37 (30.08 %) and 15 (28.30 %) in the training and validation sets, respectively. Multivariable logistic regression analysis identified that tumor size, biliopancreatic duct dilatation, lymphadenopathy, and enhancement pattern were preoperative predictors of aggressiveness. Those variables were used to develop a nomogram with good concordance statistics of 0.89 and 0.86 for predicting aggressiveness in the training and validation sets, respectively. With a nomogram score of 59, patients with NF-pNETs were divided into low-aggressive and high-aggressive groups. The high-aggressive group had decreased overall survival (OS) and disease-free survival (DFS). Moreover, the nomogram showed good performance in predicting OS and DFS at 3, 5, and 10 years.

CONCLUSION

The nomogram integrating CT features helped preoperatively predict the aggressiveness of NF-pNETs and could potentially facilitate clinical decision-making.

Comprehensive split TEV based protein-protein interaction screening reveals TAOK2 as a key modulator of Hippo signalling to limit growth

The conserved Hippo signalling pathway plays a crucial role in tumour formation by limiting tissue growth and proliferation. At the core of this pathway are tumour suppressor kinases STK3/4 and LATS1/2, which limit the activity of the oncogene YAP1, the primary downstream effector. Here, we employed a split TEV-based protein-protein interaction screen to assess the physical interactions among 28 key Hippo pathway components and potential upstream modulators. This screen led us to the discovery of TAOK2 as pivotal modulator of Hippo signalling, as it binds to the pathway's core kinases, STK3/4 and LATS1/2, and leads to their phosphorylation. Specifically, our findings revealed that TAOK2 binds to and phosphorylates LATS1, resulting in the reduction of YAP1 phosphorylation and subsequent transcription of oncogenes. Consequently, this decrease led to a decrease in cell proliferation and migration. Interestingly, a correlation was observed between reduced TAOK2 expression and decreased patient survival time in certain types of human cancers, including lung and kidney cancer as well as glioma. Moreover, in cellular models corresponding to these cancer types the downregulation of TAOK2 by CRISPR inhibition led to reduced phosphorylation of LATS1 and increased proliferation rates, supporting TAOK2's role as tumour suppressor gene. By contrast, overexpression of TAOK2 in these cellular models lead to increased phospho-LATS1 but reduced cell proliferation. As TAOK2 is a druggable kinase, targeting TAOK2 could serve as an attractive pharmacological approach to modulate cell growth and potentially offer strategies for combating cancer.

[Analysis of the current status and related factors of human papillomavirus infection among community-dwelling women aged 18-24 years without a history of vaccination in Shanghai City]

Objective: To understand the status of human papillomavirus (HPV) infection among young women without a history of vaccination in Shanghai, and analyze the related factors of HPV infection in this population. Methods: A total of 2 660 women aged 18-24 years old who had made an appointment for HPV vaccine at 36 community health service centers in Shanghai from July 2022 to February 2023 were selected as the study subjects. Basic information (including demographic characteristics, previous disease history, female menstrual and reproductive history, sexual life history, etc.) was collected by a self-filling electronic questionnaire. Cervical secretions were detected by HPV nucleic acid typing. The multivariate logistic regression model was used to analyze the factors related to high-risk HPV (HR-HPV) infection in the target population. Results: The age of the subjects was (23±1) years old, and the infection rate of HPV was 14.51% (386 cases), among which the infection rates of HR-HPV and low-risk HPV were 13.53% (360 cases) and 1.84% (49 cases), respectively. The main subtypes of HR-HPV infection were HPV52, 16, 58, 39 and 66. The multivariate logistic regression model analysis showed that compared with the control group, the OR (95%CI) values for HR-HPV infection in the group of married, earned less than 2 000 yuan/month, drank alcohol occasionally, gynecological disease history, had two or more sexual partners in the past year, and did not know whether the partners had other sexual partners were 0.41 (0.25-0.66), 0.39 (0.21-0.70), 1.45 (1.13-1.86), 1.29 (1.00-1.66), 2.18-5.18 (1.02-16.05), and 1.82 (1.31-2.54), respectively. Conclusion: The infection rate of HPV among women aged 18-24 years old in Shanghai remains at a high level. The main subtypes of HR-HPV infection are HPV52, 16, 58, 39 and 66. The marital status, economic income level, drinking status, gynecological disease history and sexual life history are related to HR-HPV infection.

Gender perspective on the association between liver enzyme markers and non-alcoholic fatty liver disease: insights from the general population

Objective

Every distinct liver enzyme biomarker exhibits a strong correlation with non-alcoholic fatty liver disease (NAFLD). This study aims to comprehensively analyze and compare the associations of alanine aminotransferase (ALT), aspartate aminotransferase (AST), and gamma-glutamyl transferase (GGT) with NAFLD from a gender perspective.

Methods

This study was conducted on 6,840 females and 7,411 males from the NAGALA cohort. Multivariable logistic regression analysis was used to compare the associations between liver enzyme markers and NAFLD in both genders, recording the corresponding adjusted odds ratios (ORs) and 95% confidence intervals (CIs). Receiver operating characteristic (ROC) curves were used to evaluate the accuracy of individual liver enzyme markers and different combinations of them in identifying NAFLD.

Results

Liver enzyme markers ALT, AST, and GGT were all independently associated with NAFLD and exhibited significant gender differences (All P-interaction<0.05). In both genders, ALT exhibited the most significant association with NAFLD, with adjusted standardized ORs of 2.19 (95% CI: 2.01-2.39) in males and 1.60 (95% CI: 1.35-1.89) in females. Additionally, ROC analysis showed that ALT had significantly higher accuracy in identifying NAFLD than AST and GGT in both genders (Delong P-value < 0.05), and the accuracy of ALT in identifying NAFLD in males was higher than that in females [Area under the ROC curve (AUC): male 0.79, female 0.77]. Furthermore, out of the various combinations of liver enzymes, ALT+GGT showed the highest accuracy in identifying NAFLD in both genders, with AUCs of 0.77 (95% CI: 0.75-0.79) in females and 0.79 (95% CI: 0.78-0.81) in males.

Conclusion

Our study revealed significant gender differences in the associations of the three commonly used liver enzyme markers with NAFLD. In both genders, the use of ALT alone may be the simplest and most effective tool for screening NAFLD, especially in males.

Alanine aminotransferase to high- density lipoprotein cholesterol ratio is positively correlated with the occurrence of diabetes in the Chinese population: a population-based cohort study

Objective

Both alanine aminotransferase (ALT) and high-density lipoprotein cholesterol (HDL-C) are closely related to glucose homeostasis in the body, and the main objective of this study was to investigate the association between ALT to HDL-C ratio (ALT/HDL-C ratio) and the risk of diabetes in a Chinese population.

Methods

The current study included 116,251 participants who underwent a healthy physical examination, and the study endpoint was defined as a diagnosis of new-onset diabetes. Multivariate Cox regression models and receiver operator characteristic curves were used to assess the association of the ALT/HDL-C ratio with diabetes onset.

Results

During the average observation period of 3.10 years, a total of 2,674 (2.3%) participants were diagnosed with new-onset diabetes, including 1,883 (1.62%) males and 791 (0.68%) females. After fully adjusting for confounding factors, we found a significant positive association between the ALT/HDL-C ratio and the risk of diabetes [Hazard ratios 1.06, 95% confidence intervals: 1.05, 1.06], and this association was significantly higher in males, obese individuals [body mass index ≥ 28 kg/m2] and individuals aged < 60 years (All P interaction < 0.05). In addition, the ALT/HDL-C ratio was significantly better than its components ALT and HDL-C in predicting diabetes in the Chinese population.

Conclusion

There was a positive relationship between ALT/HDL-C ratio and diabetes risk in the Chinese population, and this relationship was significantly stronger in males, obese individuals, and individuals younger than 60 years old.

The newly proposed Metabolic Score for Visceral Fat is a reliable tool for identifying non-alcoholic fatty liver disease, requiring attention to age-specific effects in both sexes

Objective

The newly proposed Metabolic Visceral Fat Score (METS-VF) is considered a more effective measure for visceral adipose tissue (VAT) than other obesity indicators. This study aimed to reveal the association between METS-VF and non-alcoholic fatty liver disease (NAFLD), and its variations across age groups within both sexes.

Methods

Data from 14,251 medical examiners in the NAGALA project were employed in this study. 3D fitted surface plots were constructed based on multivariate logistic regression models to visualize the isolated and combined effects of aging and METS-VF on NAFLD. Receiver operating characteristic curve (ROC) analysis was conducted to compare the diagnostic performance of METS-VF with other VAT surrogate markers in predicting NAFLD.

Results

The results of multivariate logistic regression analysis showed that each unit increase in METS-VF was independently associated with a 333% and 312% increase in the odds of NAFLD in males and females, respectively. Additionally, the 3D fitted surface plot showed that age significantly influenced the association between METS-VF and the odds of NAFLD in both sexes, as follows: (i) In males, when METS-VF was less than 6.2, the METS-VF-related odds of NAFLD increased gradually with age in the 20-45 age group, reached a plateau in the 45-65 age group, and then decreased in the group above 65 years old; however, when male METS-VF exceeded 6.2, aging and METS-VF combined to further increase the odds of NAFLD in all age groups, particularly in the 45-65 age group. (ii) In females, aging seemed to reduce METS-VF-related odds of NAFLD in the 18-40 age group, but significantly increased it in the 40-60 age group, particularly for those with higher METS-VF levels. Further ROC analysis revealed that compared to other VAT surrogate markers, METS-VF showed the highest diagnostic accuracy for NAFLD in females, especially in those under 45 years of age [area under the curve (AUC) = 0.9256].

Conclusions

This study firstly revealed a significant positive correlation between METS-VF and the odds of NAFLD, with METS-VF surpassing other VAT surrogate markers in NAFLD diagnosis. Moreover, age significantly influenced the METS-VF-related odds of NAFLD and METS-VF's diagnostic efficacy for NAFLD in both sexes.

[Relationship between the neutrophil-to-lymphocyte ratio and estimated glomerular filtration rate in patients with primary aldosteronism: a cross-sectional study]

Objective: To investigate the associations between neutrophil-to-lymphocyte ratio (NLR) and estimated glomerular filtration rate (eGFR) in patients with primary aldosteronism (PA). Methods: This study was a cross-sectional study. Consecutive patients diagnosed with PA and admitted to the Second Affiliated Hospital of Nanchang University from October 2017 to April 2022 were enrolled. General information, blood routine, renal function, and other clinical data of the patients were collected. Based on the median NLR of the enrolled patients, NLR Collapse

Key Words Collapse

MESH Headings

• Humans
• Female
• Male
• Neutrophils
• Glomerular Filtration Rate
• Cross-Sectional Studies
• Lymphocytes
• Hyperaldosteronism/diagnosis
• Hyperlipidemias

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Grants

• 3226090026, 81960088 National Natural Science Foundation of China

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Affiliation(s)

N Li Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
J Qiu Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
N P Liang Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
M B Wu Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
X T Zhang Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
H Zhang Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
Y F Dong Cardiovascular Department, Second Affiliated Hospital of Nanchang University, Nanchang 330006, China Key Laboratory of Molecular Biology in Jiangxi Province, Nanchang 330006, China

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The predictive significance of lipid accumulation products for future diabetes in a non-diabetic population from a gender perspective: an analysis using time-dependent receiver operating characteristics

Objective

The increasing prevalence of diabetes is strongly associated with visceral adipose tissue (VAT), and gender differences in VAT remarkably affect the risk of developing diabetes. This study aimed to assess the predictive significance of lipid accumulation products (LAP) for the future onset of diabetes from a gender perspective.

Methods

A total of 8,430 male and 7,034 female non-diabetic participants in the NAGALA (NAfld in the Gifu Area, Longitudinal Analysis) program were included. The ability of LAP to assess the risk of future new-onset diabetes in both genders was analyzed using multivariate Cox regression. Subgroup analysis was conducted to explore the impact of potential modifiers on the association between LAP and diabetes. Additionally, time-dependent receiver operator characteristics (ROC) curves were used to assess the predictive power of LAP in both genders for new-onset diabetes over the next 2-12 years.

Results

Over an average follow-up of 6.13 years (maximum 13.14 years), 373 participants developed diabetes. Multivariate Cox regression analysis showed a significant gender difference in the association between LAP and future diabetes risk (P-interaction<0.05): the risk of diabetes associated with LAP was greater in females than males [hazard ratios (HRs) per standard deviation (SD) increase: male 1.20 (1.10, 1.30) vs female 1.35 (1.11, 1.64)]. Subgroup analysis revealed no significant modifying effect of factors such as age, body mass index (BMI), smoking history, drinking history, exercise habits, and fatty liver on the risk of diabetes associated with LAP (All P-interaction <0.05). Time-dependent ROC analysis showed that LAP had greater accuracy in predicting diabetes events occurring within the next 2-12 years in females than males with more consistent predictive thresholds in females.

Conclusions

This study highlighted a significant gender difference in the association between LAP and future diabetes risk. The risk of diabetes associated with LAP was greater in females than in males. Furthermore, LAP showed superior predictive ability for diabetes at different time points in the future in females and had more consistent and stable predictive thresholds in females, particularly in the medium and long term.

MRI-based radiomics analysis of bladder cancer: prediction of pathological grade and histological variant

AIM

To develop magnetic resonance imaging (MRI)-based radiomics models for the prediction of the pathological grade and histological variant of bladder cancer.

MATERIALS AND METHODS

A total of 227 patients who underwent bladder MRI and had histopathologically confirmed grades and variants were included retrospectively from January 2017 to March 2022. They were assigned to a training set (n=131) and a testing set (n=96) based on the MRI system. MRI-based radiomics features were extracted from manually segmented volumes of interest from high-b-value DWI images and ADC maps. The radiomics models were trained with all possible pipelines in the training set. One optimal model was selected using the fivefold cross-validation method and verified by the testing set according to the pathological results. Univariate and multivariate analyses were performed to identify the significant clinical and imaging factors for developing clinical-radiomics models.

RESULTS

The radiomics model for grade prediction had area under the curve (AUC) values of 0.784, 0.786, and 0.733 in the training, cross-validation, and testing sets, respectively. The radiomics model for variant prediction had AUC values of 0.748, 0.757, and 0.789 in the training, cross-validation, and testing sets, respectively. The performance of the clinical-radiomics model was significantly improved compared with the radiomics models alone for the total dataset (AUC for grade: 0.846 versus 0.756; AUC for variant: 0.810 versus 0.757, p<0.05).

CONCLUSION

MRI-based radiomics models could be used to predict the pathological grade and histological variants of bladder cancer with relatively good performance.

Application of the Ion Chamber Array in Magnetic Resonance Accelerator QA

PURPOSE/OBJECTIVE(S)

The magnetic resonance accelerator (MR-Linac) is gradually widely used due to high-quality soft tissue contrast and real-time tracking. However, the special dosimetry characteristics and wide field sizes of MR-Linac increase the QA difficulty with conventional measurement method. The purpose of this study was to confirm an ion chamber array could be used for measuring the beam quality, the profiles, as well as the positioning accuracy of all MLC leaves efficiently, by comparing results with the conventional method. To propose a new QA approach for solving the common problem in data acquisition caused by the wide fields of MR-Linac.

MATERIALS/METHODS

The research was based on a MR-Linac fixed with 1.5T MR and 7MeV energy photon beam. The conventional QA method adopted the MR water tank with a gantry angle of 0°and an SSD of 133.5 cm, both microdiamond and ionization chamber detector were used to acquire the dose profiles (PDD, inline, crossline and diagonal). Field sizes 1 × 1 cm2, 2 × 2 cm2, 3 × 3 cm2, 5 × 5 cm2, 10 × 10 cm2, 15 × 15 cm2, 22 × 22 cm2, 40 × 22 cm2,57 × 22 cm2 were measured with depth 13mm, 50mm, 100mm for vertical beam. As for the wide fields (larger than 15 × 15 cm2), two profiles of x axis (one from left to right, the other from right to left) needed to be gathered and then stitched into one final profile. A boot phantom with an ionization chamber detector was used for measuring beam quality. We defined the profiles measured by conventional method as the baseline. An ion chamber array was adopted to acquire TPR, PDD, profiles and MLC positioning, comparing to the conventional method. The center of ion chamber array was placed to the isocenter of MR-Linac, the array could move to the right and left offset positions through engaging the pin into correct hole of QA platform, such 'once positioning and twice movements' operation could finish within 3 minutes. The central detector of the ion chamber array was used for measuring beam quality. TPRs for different depths were acquired by stacking solid water on the ion chamber array. As for the profiles, we could get the final profile by 'once positioning and twice movements' efficiently. As for the positioning accuracy of MLC leaves, firstly the central leaf pair was put on y = 0 to measure 'open profile' under the open field. Then we moved the MLC leaves to different positions to get the n profile (n for different leaf positions). The ratio of n profile to open profile could show the positioning accuracy of MLC.

RESULTS

We adopted 2D gamma (1mm / 2%) to compare the profiles between the ion chamber array and the conventional method, the results were within 98%. The beam quality consistency of ion chamber array comparing to the wedge tank was within 1% according to daily measurement. The ion chamber array could reflect the MLC positioning differences, the sensitivity was 0.5 mm.

CONCLUSION

The ion chamber array showed a convenient QA method both for the dosimetry and for the MLC positioning accuracy which did reduce the overall measurement time, it was recommended for daily and monthly QA for MR-Linac.

Performance Evaluation in Automatic Plan Generation for Ethos Intelligent Optimization Engine

PURPOSE/OBJECTIVE(S)

To evaluate the automatic optimization performance and clinical feasibility of the Intelligent Optimization Engine (IOE) of Ethos online adaptive radiotherapy platform.

MATERIALS/METHODS

Eleven patients with cervical cancer treated with Halcyon accelerator were retrospectively selected. All the patients manually planned with four full arc volume rotating intensity modulated radiotherapy (VMAT) (Manual-4Arc), and the prescription dose was 45 Gy/25F. All patient images and structures were imported into Ethos simulator, and clinical goals were added appropriately based on clinical requirements. The target coverage was normalized to 95%. 7F, 9F, 12F IMRT plans and 2Arc, 3Arc VMAT plans were automatically generated by IOE. Dosimetric index comparisons were made among the Manual-4Arc plans and five group IOE generated plan to evaluate the automatic optimization performance of IOE.

RESULTS

In terms of hot dose area, for PTV, D1% of IMRT-12F plans was the lowest, and there were significant differences between IMRT-12F plans and Manual-4Arc plans (46.936 ± 0.241 vs 48.639 ± 2.395, p = 0.004); In terms of target coverage, the CTVs of all groups meet clinical requirements. Although the Ethos online adaptive plans have been normalized during planning, the PTV coverage is slightly insufficient (12F: 94.913 ± 0.154; 9F: 94.585 ± 1.148). For OARs close to target, such as bladder, V30Gy, V40Gy and Dmean have significant differences among the six group plans. The order of bladder dose is basically followed by IMRT-12F

CONCLUSION

The plans automatically generated by Ethos IOE can achieve similar performance as the manual plan, and the automatically generated IMRT-12F and 9F plans are preferred for clinical use.

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Key Words Collapse

MESH Headings Collapse

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Affiliation(s)

Z Wang Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
B Yang Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
X Meng Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
Y Liang Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
T Pang Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
J Qiu Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China

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The newly proposed alanine aminotransferase to high-density lipoprotein cholesterol ratio has shown effectiveness in identifying non-alcoholic fatty liver disease

Objective

Alanine aminotransferase (ALT) and high-density lipoprotein cholesterol (HDL-C) are important predictive factors for non-alcoholic fatty liver disease (NAFLD). The aim of this study was to analyze the association between the ALT/HDL-C ratio and NAFLD.

Methods

We conducted a retrospective analysis of data from 14,251 individuals participating in the NAGALA project's health screening program. The presence of NAFLD was diagnosed based on the participants' alcohol consumption status and liver ultrasonography images. Multivariable logistic regression models were used to assess the association between the ALT/HDL-C ratio and NAFLD. Receiver operating characteristic (ROC) analysis was performed to determine and compare the effectiveness of ALT, HDL-C, the aspartate aminotransferase to HDL-C (AST/HDL-C) ratio, the gamma-glutamyl transferase to HDL-C (GGT/HDL-C) ratio and the ALT/HDL-C ratio in identifying NAFLD.

Results

We observed a significant positive association between the ALT/HDL-C ratio and the prevalence of NAFLD. For each standard deviation (SD) increase in the ALT/HDL-C ratio, the adjusted odds ratio (OR) for NAFLD among the participants was 3.05 [95% confidence interval (CI): 2.63, 3.53], with the highest quartile of ALT/HDL-C ratio having a 9.96-fold increased risk compared to the lowest quartile. In further subgroup analyses stratified by gender, age, and waist circumference (WC), we observed a significantly higher risk of NAFLD associated with the ALT/HDL-C ratio among individuals aged ≥45 years, males, and those who were abdominal obesity. Furthermore, based on the results of ROC analysis, we found that the ALT/HDL-C ratio [area under the curves (AUC): 0.8553] was significantly superior to ALT, HDL-C, AST/HDL-C ratio and GGT/HDL-C ratio in identifying NAFLD (All Delong P<0.05); the threshold of suggested ALT/HDL-C ratio for identifying NAFLD was 15.97.

Conclusion

This population-based study demonstrates a positive association between the ALT/HDL-C ratio and NAFLD. The ALT/HDL-C ratio can effectively identify individuals with NAFLD.

Assessing the usefulness of a newly proposed metabolic score for visceral fat in predicting future diabetes: results from the NAGALA cohort study

Objective

Visceral adipose tissue assessment holds significant importance in diabetes prevention. This study aimed to explore the association between the newly proposed Metabolic Score for Visceral Fat (METS-VF) and diabetes risk and to further assess the predictive power of the baseline METS-VF for the occurrence of diabetes in different future periods.

Methods

This longitudinal cohort study included 15,464 subjects who underwent health screenings. The METS-VF, calculated using the formula developed by Bello-Chavolla et al., served as a surrogate marker for visceral fat obesity. The primary outcome of interest was the occurrence of diabetes during the follow-up period. Established multivariate Cox regression models and restricted cubic spline (RCS) regression models to assess the association between METS-VF and diabetes risk and its shape. Receiver operating characteristic (ROC) curves were used to compare the predictive power of METS-VF with body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), and visceral adiposity index (VAI) for diabetes, and time-dependent ROC analysis was conducted to assess the predictive capability of METS-VF for the occurrence of diabetes in various future periods.

Results

During a maximum follow-up period of 13 years, with a mean of 6.13 years, we observed that the cumulative risk of developing diabetes increased with increasing METS-VF quintiles. Multivariable-adjusted Cox regression analysis showed that each unit increase in METS-VF would increase the risk of diabetes by 68% (HR 1.68, 95% CI 1.13, 2.50), and further RCS regression analysis revealed a possible non-linear association between METS-VF and diabetes risk (P for non-linearity=0.002). In addition, after comparison by ROC analysis, we found that METS-VF had significantly higher predictive power for diabetes than other general/visceral adiposity indicators, and in time-dependent ROC analysis, we further considered the time-dependence of diabetes status and METS-VF and found that METS-VF had the highest predictive value for predicting medium- and long-term (6-10 years) diabetes risk.

Conclusion

METS-VF, a novel indicator for assessing visceral adiposity, showed a significantly positive correlation with diabetes risk. It proved to be a superior risk marker in predicting the future onset of diabetes compared to other general/visceral adiposity indicators, particularly in forecasting medium- and long-term diabetes risk.

Atomic Layer Deposition of Tantalum Oxide Films on 3D-Printed Ti6Al4V Scaffolds with Enhanced Osteogenic Property for Orthopedic Implants

There is an evident advantage in personalized customization of orthopedic implants by 3D-printed titanium (Ti) and its alloys. However, 3D-printed Ti alloys have a rough surface structure caused by adhesion powders and a relatively bioinert surface. Therefore, surface modification techniques are needed to improve the biocompatibility of 3D-printed Ti alloy implants. In the present study, porous Ti6Al4V scaffolds were manufactured by a selective laser melting 3D printer, followed by sandblasting and acid-etching treatment and atomic layer deposition (ALD) of tantalum oxide films. SEM morphology and surface roughness tests confirmed that the unmelted powders adhered on the scaffolds were removed by sandblasting and acid-etching. Accordingly, the porosity of the scaffold increased by about 7%. Benefiting from the self-limitation and three-dimensional conformance of ALD, uniform tantalum oxide films were formed on the inner and outer surfaces of the scaffolds. Zeta potential decreased by 19.5 mV after depositing tantalum oxide films. The in vitro results showed that the adhesion, proliferation, and osteogenic differentiation of rat bone marrow mesenchymal stem cells on modified Ti6Al4V scaffolds were significantly enhanced, which may be ascribed to surface structure optimization and the compatibility of tantalum oxide. This study provides a strategy to improve the cytocompatibility and osteogenic differentiation of porous Ti6Al4V scaffolds for orthopedic implants.

[Analysis of the direct economic burden of measles cases and its influencing factors in Shanghai from 2017 to 2019]

Objective: To analyze the direct economic burden caused by measles cases in Shanghai from 2017 to 2019 and its influencing factors. Methods: A total of 161 laboratory-confirmed measles cases reported from January 1, 2017, to December 31, 2019, in Shanghai were included in the study through the "Measles Surveillance Information Reporting and Management System" of the "China Disease Surveillance Information Reporting and Management System". Through telephone follow-up and consulting hospital data, the basic information of population, medical treatment situation, medical treatment costs and other information were collected, and the direct economic burden of cases was calculated, including registration fees, examination fees, hospitalization fees, medical fees and other disease treatment expenses, as well as transportation and other expenses of cases. The multiple linear regression model was used to analyze the main influencing factors of the direct economic burden. Results: The age of 161 measles cases M (Q₁, Q₃) was 28.21 (13.33, 37.00) years. Male cases (56.52%) were more than female cases (43.48%). The largest number of cases was≥18 years old (70.81%). The total direct economic burden of 161 measles cases was 540 851.14 yuan, and the per capita direct economic burden was 3 359.32 yuan. The direct economic burden M (Q₁, Q₃) was 873.00 (245.01, 4 014.79) yuan per person. The results of multiple linear regression model analysis showed that compared with other and unknown occupations, central areas and non-hospitalized cases, the direct economic burden of measles cases was higher in scattered children, childcare children, students, and cadre staff in the occupational distribution, suburban areas and hospitalized, with the coefficient of β (95%CI) values of 0.388 (0.150-0.627), 0.297 (0.025-0.569), 0.327 (0.148-0.506) and 1.031 (0.853-1.209), respectively (all P values<0.05). Conclusion: The direct economic burden of some measles cases in Shanghai is relatively high. Occupation, area of residence and hospitalization are the main factors influencing the direct economic burden of measles cases.

Automated detection of hippocampal sclerosis using real-world clinical MRI images

Background

Hippocampal sclerosis (HS) is the most common pathological type of temporal lobe epilepsy (TLE) and one of the important surgical markers. Currently, HS is mainly diagnosed manually by radiologists based on visual inspection of MRI, which greatly relies on MRI quality and physician experience. In clinical practice, non-thin MRI scans are often used due to the time and efficiency needed for the acquisition. However, these scans can be difficult for junior physicians to interpret accurately. Thus, the rapid and accurate diagnosis of HS using real-world MRI images in clinical settings is a challenging task.

Objective

Our aim was to explore the feasibility of using computer vision methods to diagnose HS on real-world clinical MRI images and to provide a reference for future clinical applications of artificial intelligence methods to aid in detecting HS.

Methods

We proposed a deep learning algorithm called "HS-Net" to discriminate HS using real-world clinical MRI images. First, we delineated and segmented a region of interest (ROI) around the hippocampus. Then, we utilized the fractional differential (FD) method to enhance the textures of the ROIs. Finally, we used a small-sample image classification method based on transfer learning to fine-tune the feature extraction part of a pretrained model and added two fully connected layers and an output layer. In the study, 96 TLE patients with HS confirmed by postoperative pathology and 89 healthy controls were retrospectively enrolled. All subjects were cross-validated, and models were evaluated for performance, robustness, and clinical utility.

Results

The HS-Net model achieved an area under the curve (AUC) of 0.894, an accuracy of 82.88%, an F1-score of 84.08% in the test cohort based on real, routine, clinical T2-weighted fluid attenuated inversion recovery (FLAIR) sequence MRI images. Additionally, the AUC, accuracy and F1 scores of our model all increased by around 3 percentage points when the inputs were augmented with the ROIs of the textures enhanced using the FD method.

Conclusions

Our computational model has the potential to be used for the diagnosis of HS in real clinical MRI images, which could assist physicians, particularly junior physicians, in improving the accuracy of discrimination.

[A preliminary report of laparoscopic extraperitoneal colostomy anterior to posterior sheath of rectus abdominis-transversus abdominis to prevent parastomal hernia]

Objective: To examine the preliminary effect of laparoscopic extraperitoneal colostomy anterior to posterior sheath of rectus abdominis-transversus abdominis for the prevention of parastomal hernia after abdominoperineal resection for rectal cancer. Methods: This study is a prospective case series study. From June 2021 to June 2022, patients with low rectal cancer underwent laparoscopic abdominoperineal resection combined with extraperitoneal colostomy anterior to posterior sheath of rectus abdominis-transversus abdominis at the First Department of General Surgery, Shaanxi Provincial People's Hospital were enrolled. The clinical data and postoperative CT images of patients were collected to analyze the incidence of surgical complication and parastomal hernia. Results: Totally 6 cases of patient were enrolled, including 3 males and 3 females, aging 72.5 (19.5) years (M(IQR)) (range: 55 to 79 years). The operation time was 250 (48) minutes (range: 190 to 275 minutes), the stoma operation time was 27.5 (10.7) minutes (range: 21 to 37 minutes), the bleeding volume was 30 (35) ml (range: 15 to 80 ml). All patients were cured and discharged without surgery-related complications. The follow-up time was 136 (105) days (range: 98 to 279 days). After physical examination and abdominal CT follow-up, no parastomal hernia occurred in the 6 patients up to this article. Conclusions: A method of laparoscopic extraperitoneal colostomy anterior to posterior sheath of rectus abdominis-transversus abdominis is established. Permanent stoma can be completed with this method safely. It may have a preventive effect on the occurrence of parastomal hernia, which is worthy of further study.

Prediction of Suicidal Behaviors in the Middle-aged Population: Machine Learning Analyses of UK Biobank

BACKGROUND

Suicidal behaviors, including suicide deaths and attempts, are major public health concerns. However, previous suicide models required a huge amount of input features, resulting in limited applicability in clinical practice.

OBJECTIVE

We aimed to construct applicable models (ie, with limited features) for short- and long-term suicidal behavior prediction. We further validated these models among individuals with different genetic risks of suicide.

METHODS

Based on the prospective cohort of UK Biobank, we included 223 (0.06%) eligible cases of suicide attempts or deaths, according to hospital inpatient or death register data within 1 year from baseline and randomly selected 4460 (1.18%) controls (1:20) without such records. We similarly identified 833 (0.22%) cases of suicidal behaviors 1 to 6 years from baseline and 16,660 (4.42%) corresponding controls. Based on 143 input features, mainly including sociodemographic, environmental, and psychosocial factors; medical history; and polygenic risk scores (PRS) for suicidality, we applied a bagged balanced light gradient-boosting machine (LightGBM) with stratified 10-fold cross-validation and grid-search to construct the full prediction models for suicide attempts or deaths within 1 year or between 1 and 6 years. The Shapley Additive Explanations (SHAP) approach was used to quantify the importance of input features, and the top 20 features with the highest SHAP values were selected to train the applicable models. The external validity of the established models was assessed among 50,310 individuals who participated in UK Biobank repeated assessments both overall and by the level of PRS for suicidality.

RESULTS

Individuals with suicidal behaviors were on average 56 years old, with equal sex distribution. The application of these full models in the external validation data set demonstrated good model performance, with the area under the receiver operating characteristic (AUROC) curves of 0.919 and 0.892 within 1 year and between 1 and 6 years, respectively. Importantly, the applicable models with the top 20 most important features showed comparable external-validated performance (AUROC curves of 0.901 and 0.885) as the full models, based on which we found that individuals in the top quintile of predicted risk accounted for 91.7% (n=11) and 80.7% (n=25) of all suicidality cases within 1 year and during 1 to 6 years, respectively. We further obtained comparable prediction accuracy when applying these models to subpopulations with different genetic susceptibilities to suicidality. For example, for the 1-year risk prediction, the AUROC curves were 0.907 and 0.885 for the high (>2nd tertile of PRS) and low (<1st) genetic susceptibilities groups, respectively.

CONCLUSIONS

We established applicable machine learning-based models for predicting both the short- and long-term risk of suicidality with high accuracy across populations of varying genetic risk for suicide, highlighting a cost-effective method of identifying individuals with a high risk of suicidality.

Assessing temporal differences of baseline body mass index, waist circumference, and waist-height ratio in predicting future diabetes

Objective

Obesity is the prominent modifiable risk factor known to influence the occurrence and progression of diabetes other than age, and the objective of this study was to evaluate and compare the predictive value of three simple baseline anthropometric indicators of obesity, body mass index (BMI), waist circumference (WC), and waist-height ratio (WHtR), for the occurrence of diabetes at different time points in the future.

Methods

The study subjects were 12,823 individuals with normoglycemic at baseline who underwent health screening and had measurements of BMI, WC, and WHtR. The outcome of interest was new-onset diabetes during follow-up. Time-dependent receiver operator characteristics (ROC) curves of baseline BMI, WC, and WHtR for predicting the risk of diabetes in the next 2 to 12 years were constructed and their area under the ROC curves (AUCs) and corresponding optimal threshold values were calculated for each time point, which were used to compare the accuracy and stability of the above three indicators for predicting the occurrence of diabetes in different future periods.

Results

During a median follow-up period of 7.02 years, with a maximum follow-up of 13 years, 320 new-onset diabetes were recorded. After adjusting for confounders and comparing standardized hazard ratios (HRs), WC was shown to be the best simple anthropometric indicator of obesity reflecting diabetes risk in all models, followed by WHtR. Time-dependent ROC analysis showed that WC had the highest AUC in predicting the occurrence of diabetes in the short term (2-5 years), and WHtR had the highest AUC in predicting the occurrence of diabetes in the medium to long term (6-12 years), while in any time point, both WC and WHtR had higher AUC than BMI in predicting future diabetes. In addition, we found relatively larger fluctuations in the thresholds of BMI and WC for predicting diabetes over time, while the thresholds of WHtR consistently remained between 0.47-0.50; comparatively speaking, WHtR may have greater application value in predicting future diabetes.

Conclusions

Our analysis sustained that central obesity is a more important predictor of diabetes, and in clinical practice, we proposed measuring WHtR as a useful tool for predicting future diabetes.

An injectable hydrogel combining medicine and matrix with anti-inflammatory and pro-angiogenic properties for potential treatment of myocardial infarction

One of the main illnesses that put people's health in jeopardy is myocardial infarction (MI). After MI, damaged or dead cells set off an initial inflammatory response that thins the ventricle wall and degrades the extracellular matrix. At the same time, the ischemia and hypoxic conditions resulting from MI lead to significant capillary obstruction and rupture, impairing cardiac function and reducing blood flow to the heart. Therefore, attenuating the initial inflammatory response and promoting angiogenesis are very important for the treatment of MI. Here, to reduce inflammation and promote angiogenesis in infarcted area, we report a new kind of injectable hydrogel composed of puerarin and chitosan via in situ self-assembly with simultaneous delivery of mesoporous silica nanoparticles (CHP@Si) for myocardial repair. On the one hand, puerarin degraded from CHP@Si hydrogel modulated the inflammatory response via inhibiting M1-type polarization of macrophages and expression of pro-inflammatory factors. On the other hand, silica ions and puerarin released from CHP@Si hydrogel showed synergistic activity to improve the cell viability, migration and angiogenic gene expression of HUVECs in both conventional and oxygen/glucose-deprived environments. It suggests that this multifunctional injectable CHP@Si hydrogel with good biocompatibility may be an appropriate candidate as a bioactive material for myocardial repair post-MI.

A cancer cell membrane coated, doxorubicin and microRNA co-encapsulated nanoplatform for colorectal cancer theranostics

Endogenous microRNAs (miRNA) in tumors are currently under exhaustive investigation as potential therapeutic agents for cancer treatment. Nevertheless, RNase degradation, inefficient and untargeted delivery, limited biological effect, and currently unclear side effects remain unsettled issues that frustrate clinical application. To address this, a versatile targeted delivery system for multiple therapeutic and diagnostic agents should be adapted for miRNA. In this study, we developed membrane-coated PLGA-b-PEG DC-chol nanoparticles (m-PPDCNPs) co-encapsulating doxorubicin (Dox) and miRNA-190-Cy7. Such a system showed low biotoxicity, high loading efficiency, and superior targeting ability. Systematic delivery of m-PPDCNPs in mouse models showed exceptionally specific tumor accumulation. Sustained release of miR-190 inhibited tumor angiogenesis, tumor growth, and migration by regulating a large group of angiogenic effectors. Moreover, m-PPDCNPs also enhanced the sensitivity of Dox by suppressing TGF-β signal in colorectal cancer cell lines and mouse models. Together, our results demonstrate a stimulating and promising m-PPDCNPs nanoplatform for colorectal cancer theranostics.

[Application of the "virtual-real combination" experimental teaching model in Human Parasitology teaching: a case study of comprehensive schistosome experiments]

Information technology has become an important driver to facilitate higher education developments in the context of new medical sciences. A new "virtual-real combination" experimental teaching model was designed and created through integrating information technology with experimental teaching by Experimental Teaching Center of Basic Medical Sciences and Department of Pathogen Biology, Nanjing Medical University and was applied in Human Parasitology teaching, which achieved satisfactory teaching effectiveness. This new model showed effective to deepen the understanding of the basic human parasitology knowledge, improve the operative skills, and cultivate the moral literacy and comprehensive capability among medical students. This report presents the teaching protocols and implementation, teaching effectiveness and evaluation, and experiences of comprehensive schistosome experiments.

The evolution of marsupial social organization

It is generally believed that marsupials are more primitive than placentals mammals and mainly solitary living, representing the ancestral form of social organization of all mammals. However, field studies have observed pair and group-living in marsupial species, but no comparative study about their social evolution was ever done. Here, we describe the results of primary literature research on marsupial social organization which indicates that most species can live in pairs or groups and many show intra-specific variation in social organization. Using Bayesian phylogenetic mixed-effects models with a weak phylogenetic signal of 0.18, we found that solitary living was the most likely ancestral form (35% posterior probability), but had high uncertainty, and the combined probability of a partly sociable marsupial ancestor (65%) should not be overlooked. For Australian marsupials, group-living species were less likely to be found in tropical rainforest, and species with a variable social organization were associated with low and unpredictable precipitation representing deserts. Our results suggest that modern marsupials are more sociable than previously believed and that there is no strong support that their ancestral state was strictly solitary living, such that the assumption of a solitary ancestral state of all mammals may also need reconsideration.

Wavelet transformation can enhance computed tomography texture features: a multicenter radiomics study for grade assessment of COVID-19 pulmonary lesions

Background

This study set out to develop a computed tomography (CT)-based wavelet transforming radiomics approach for grading pulmonary lesions caused by COVID-19 and to validate it using real-world data.

Methods

This retrospective study analyzed 111 patients with 187 pulmonary lesions from 16 hospitals; all patients had confirmed COVID-19 and underwent non-contrast chest CT. Data were divided into a training cohort (72 patients with 127 lesions from nine hospitals) and an independent test cohort (39 patients with 60 lesions from seven hospitals) according to the hospital in which the CT was performed. In all, 73 texture features were extracted from manually delineated lesion volumes, and 23 three-dimensional (3D) wavelets with eight decomposition modes were implemented to compare and validate the value of wavelet transformation for grade assessment. Finally, the optimal machine learning pipeline, valuable radiomic features, and final radiomic models were determined. The area under the receiver operating characteristic (ROC) curve (AUC), calibration curve, and decision curve were used to determine the diagnostic performance and clinical utility of the models.

Results

Of the 187 lesions, 108 (57.75%) were diagnosed as mild lesions and 79 (42.25%) as moderate/severe lesions. All selected radiomic features showed significant correlations with the grade of COVID-19 pulmonary lesions (P<0.05). Biorthogonal 1.1 (bior1.1) LLL was determined as the optimal wavelet transform mode. The wavelet transforming radiomic model had an AUC of 0.910 in the test cohort, outperforming the original radiomic model (AUC =0.880; P<0.05). Decision analysis showed the radiomic model could add a net benefit at any given threshold of probability.

Conclusions

Wavelet transformation can enhance CT texture features. Wavelet transforming radiomics based on CT images can be used to effectively assess the grade of pulmonary lesions caused by COVID-19, which may facilitate individualized management of patients with this disease.

A Multifunctional Cascade Bioreactor Based on a Layered Double Oxides Composite Hydrogel for Synergetic Tumor Chemodynamic/Starvation/Photothermal Therapy

The field of nanomedicine-catalyzed tumor therapy has achieved a lot of progress; however, overcoming the limitations of the tumor microenvironment (TME) to achieve the desired therapeutic effect remains a major challenge. In this study, a nanocomposite hydrogel (GH@LDO) platform combining the nanozyme CoMnFe-layered double oxides (CoMnFe-LDO) and natural enzyme glucose oxidase (GOX) was engineered to remodel the TME to enhance tumor catalytic therapy. The CoMnFe-LDO is a nanozyme that can convert endogenous H₂O₂ into reactive oxygen species (ROS) and O₂ to achieve chemodynamic therapy (CDT) and alleviate the hypoxic microenvironment. Meanwhile, GOX can catalyze the conversion of glucose and O₂ to gluconic acid and H₂O₂, which not only represses the ATP production of tumor cells to achieve starvation therapy (ST), but also decreases the pH value of TME and supplies extra H₂O₂ to enhance the CDT effect. Furthermore, this well-designed CoMnFe-LDO possessed a high photothermal conversion efficiency (66.63%), which could promote the generation of ROS to enhance the CDT effect and achieve photothermal therapy (PTT) under near-infrared light irradiation. The GH@LDO hydrogel cascade reaction overcomes the limitation of the TME and achieves satisfactory CDT/ST/PTT synergetic effects in vitro and in vivo. This work provides a new strategy for remodeling the TME using nanomedicine to achieve precise tumor cascaded catalytic therapy. STATEMENT OF SIGNIFICANCE: At present, the focus of tumor therapy has begun to shift from monotherapy to combination therapy for improving the overall therapeutic effect. In this study, we synthesized a CoMnFe-layered double oxide (CoMnFe-LDO) nanozyme composed of multiple transition metal oxides, which demonstrated improved peroxidase and oxidase activities as well as favorable photothermal conversion capability. The CoMnFe-LDO nanozyme was compounded with an injectable GH hydrogel crosslinked by glucose oxidase (GOX) and peroxidase (HRP). This nanocomposite hydrogel overcame the limitations of weak acidity, H₂O₂, and O₂ levels in the tumor microenvironment (TME) and achieved synergetic chemodynamic therapy (CDT), starvation therapy (ST), and photothermal therapy (PTT) effects based on the cascaded catalytic actions of CoMnFe-LDO and GOX to H₂O₂ and glucose.

A superlattice composite of Zn-Fe layered double hydroxide and graphene oxide for antitumor application

A superlattice composite of Zn-Fe layered double hydroxide and graphene oxide was fabricated on the titanium surface and showed lamellar morphology. It was found for the first time that this superlattice composite could inhibit cell adhesion and proliferation, and cause cell death of the cholangiocarcinoma cell line RBE cells in vitro and show tumor inhibition effect in vivo.

Abdominal obesity phenotypes are associated with the risk of developing non-alcoholic fatty liver disease: insights from the general population

Background

The diversity of obesity-related metabolic characteristics generates different obesity phenotypes and corresponding metabolic diseases. This study aims to explore the correlation of different abdominal obesity phenotypes with non-alcoholic fatty liver disease (NAFLD).

Methods

The current study included 14,251 subjects, 7411 males and 6840 females. Abdominal obesity was defined as waist circumference ≥ 85 cm in males and ≥ 80 cm in females; according to the diagnostic criteria for metabolic syndrome recommended by the National Cholesterol Education Program Adult Treatment Panel III, having more than one metabolic abnormality (except waist circumference criteria) was defined as metabolically unhealthy. All subjects were divided into 4 abdominal obesity phenotypes based on the presence ( +) or absence (− ) of metabolically healthy/unhealthy (MH) and abdominal obesity (AO) at baseline: metabolically healthy + non-abdominal obesity (MH⁻AO⁻); metabolically healthy + abdominal obesity (MH⁻AO⁺); metabolically unhealthy + non-abdominal obesity (MH⁺AO⁻); metabolically unhealthy + abdominal obesity (MH⁺AO⁺). The relationship between each phenotype and NAFLD was analyzed using multivariate logistic regression.

Results

A total of 2507 (17.59%) subjects in this study were diagnosed with NAFLD. The prevalence rates of NAFLD in female subjects with MH⁻AO⁻, MH⁻AO⁺, MH⁺AO⁻, and MH⁺AO⁺ phenotypes were 1.73%, 24.42%, 7.60%, and 59.35%, respectively. Among male subjects with MH⁻AO⁻, MH⁻AO⁺, MH⁺AO⁻, and MH⁺AO⁺ phenotypes, the prevalence rates were 9.93%, 50.54%, 25.49%, and 73.22%, respectively. After fully adjusting for confounding factors, with the MH⁻AO⁻ phenotype as the reference phenotype, male MH⁻AO⁺ and MH⁺AO⁺ phenotypes increased the risk of NAFLD by 42% and 47%, respectively (MH⁻AO⁺: OR 1.42, 95%CI 1.13,1.78; MH⁺AO⁺: OR 1.47, 95%CI 1.08,2.01); the corresponding risks of MH⁻AO⁺ and MH⁺AO⁺ in females increased by 113% and 134%, respectively (MH⁻AO⁺: OR 2.13, 95%CI 1.47,3.09; MH⁺AO⁺: OR 2.34, 95%CI 1.32,4.17); by contrast, there was no significant increase in the risk of NAFLD in the MH⁺AO⁻ phenotype in both sexes.

Conclusions

This first report on the relationship of abdominal obesity phenotypes with NAFLD showed that both MH⁻AO⁺ and MH⁺AO⁺ phenotypes were associated with a higher risk of NAFLD, especially in the female population. These data provided a new reference for the screening and prevention of NAFLD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-022-02393-9.

Mechanical Force Induced Self-Assembly of Chinese Herbal Hydrogel with Synergistic Effects of Antibacterial Activity and Immune Regulation for Wound Healing

Skin wounds, especially infected chronic wounds, have attracted worldwide attention due to the high prevalence and poor treatment outcomes. Hydrogel dressings with antibacterial ability and immune regulation property are urgently required. Herein, inspired by the grinding treatment of traditional Chinese medicine, mechanical force is introduced to promote the effective molecular collision and accelerate the self-assembly of chitosan (CS) and puerarin (PUE) for fabricating Chinese-herb-based hydrogels. The antibacterial rate of CS@PUE (C@P) hydrogel is more than 95%, and the wound closed rate is twice that of the control group. Interestingly, the rational design of C@P hydrogels with different PUE ratios enables a refined control over hydrogel formation, nanofiber appearance, viscoelastic, physicochemical, and biological properties. The extraordinary antibacterial ability of C@P hydrogels may originate from the nanofiber structure and the improved zeta potential on account of the orientation of amino groups in CS . Thus, the synergistically antibacterial and immune regulation properties of C@P hydrogels kill bacteria and relieve inflammation in the wound bed, ensuring the anti-infection effect, and boosting wound healing. In addition to providing a universal mechanosynthesis of PUE-based hydrogel for wound healing, this finding is expected to increase the attention paid to Chinese herbal medicines in the construction of biomaterials.

Preparation of PEG/ZIF-8@HF drug delivery system for melanoma treatment via oral administration

Melanoma is one of the highly malignant tumors whose incidence and fatality rates have been increased year by year. However, in addition to early surgical resection, there still lacks specific targeted drugs and treatment strategies. In this study, it was discovered that hinokiflavone (HF) encapsulated in zeolitic imidazolate framework-8 (ZIF-8) exhibited a superior anti-melanoma effect in vitro and in vivo. HF was encapsulated in ZIF-8 through a one-step synthesis method, and polyethylene glycol (PEG-2000) was used to optimize the size and dispersion of the drug-loaded complex (PEG/ZIF-8@HF). The results show that the prepared PEG/ZIF-8@HF has a high encapsulation efficiency (92.12%) and can achieve selective drug release in an acidic microenvironment. The results of in vitro anti-melanoma experiments indicate that PEG/ZIF-8@HF shows up-regulation of reactive oxygen species (ROS) levels and can restrain the migration and invasion of B16F10 cells. Moreover, in vivo animal experiments further confirm that PEG/ZIF-8@HF shows anti-tumor effect by up-regulating the pro-apoptotic proteins caspase-3 and caspase-8, and down-regulating the migration-promoting invasion protein MMP-9. This study developed a safe and effective oral administration of HF based on the high-efficiency delivery ZIF-8 system, which provides an effective treatment strategy for melanoma.

Brain charts for the human lifespan

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

Association of body mass index with risk of prediabetes in Chinese adults: a population-based cohort study

Aims/Introduction

Overweight and obesity in adults are strongly associated with an increased risk of prediabetes, and this study set out to gain a better understanding of the optimal body mass index (BMI) range for assessing the risk of prediabetes in the Chinese population.

Materials and Methods

The cohort study included 100,309 Chinese adults who underwent health screening. Participants were divided into six groups based on the cut‐off point for BMI recommended by the World Health Organization (underweight: <18.5 kg/m², normal‐weight: 18.5–24.9 kg/m², pre‐obese: 25.0–29.9 kg/m², obese class I: 30.0–34.9 kg/m², obese class II: 35.0–39.9 kg/m², and obese class III ≥40 kg/m²). The association of BMI with prediabetes and the shape of the correlation were modeled using multivariate Cox regression and restricted cubic spline regression, respectively.

Results

In the multivariate Cox regression model, with normal weight as the control group, underweight people had a lower risk of developing prediabetes, whereas obese and pre‐obese people had a higher risk of prediabetes. Additionally, in the restricted cubic spline model, we found that the association of BMI with prediabetes follows a positive dose–response relationship, but does not conform to the pattern of obesity paradox. Among the general population in China, a BMI of 23.03 kg/m² might be a potential intervention threshold for prediabetes.

Conclusions

The national cohort study found that the association of BMI with prediabetes follows a positive dose–response relationship, rather than a pattern of obesity paradox. For Chinese people with normal weight, more attention should be paid to glucose metabolism when BMI exceeds 23.03 kg/m².

Genetic findings of Sanger and nanopore single-molecule sequencing in patients with X-linked hearing loss and incomplete partition type III

Background

POU3F4 is the causative gene for X-linked deafness-2 (DFNX2), characterized by incomplete partition type III (IP-III) malformation of the inner ear. The purpose of this study was to investigate the clinical characteristics and molecular findings in IP-III patients by Sanger or nanopore single-molecule sequencing.

Methods

Diagnosis of IP-III was mainly based on clinical characteristics including radiological and audiological findings. Sanger sequencing of POU3F4 was carried out for these IP-III patients. For those patients with negative results for POU3F4 Sanger sequencing, nanopore long-read single-molecule sequencing was used to identify the possible pathogenic variants. Hearing intervention outcomes of hearing aids (HAs) fitting and cochlear implantation (CI) were also analyzed. Aided pure tone average (PTA) was further compared between two groups of patients according to their different locations of POU3F4 variants: in the exon region or in the upstream region.

Results

In total, 18 male patients from 14 unrelated families were diagnosed with IP-III. 10 variants were identified in POU3F4 by Sanger sequencing and 6 of these were reported for the first time (p.Gln181*, p.Val215Gly, p.Arg282Gln, p.Gln316*, c.903_912 delins TGCCA and p.Arg205del). Four different deletions that varied from 80 to 486 kb were identified 876–1503 kb upstream of POU3F4 by nanopore long-read single-molecule sequencing. De novo genetic mutations occurred in 21.4% (3/14) of patients with POU3F4 mutations. Among these 18 patients, 7 had bilateral HAs and 10 patients received unilateral CI. The mean aided PTA for HAs and CI users were 41.1 ± 5.18 and 40.3 ± 7.59 dB HL respectively. The mean PTAs for patients with the variants located in the exon and upstream regions were 39.6 ± 6.31 versus 43.0 ± 7.10 dB HL, which presented no significant difference (p = 0.342).

Conclusions

Among 14 unrelated IP-III patients, 28.6% (4/14) had no definite mutation in exon region of POU3F4. However, possible pathogenic deletions were identified in upstream region of this gene. De novo genetic mutations occurred in 21.4% (3/14) of patients with POU3F4 mutation. There was no significant difference of hearing intervention outcomes between the IP-III patients with variants located in the exon region and in the upstream region.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13023-022-02235-7.

Comparison of dyslipidemia incidence in Chinese early-stage breast cancer patients following different endocrine therapies: A population-based cohort study

BACKGROUND

There is lack of large-scale real-world research evidence showing the impact of endocrine therapy on blood lipids in Chinese breast cancer patients, especially those with premenopausal breast cancer. Based on a large breast cancer cohort at West China Hospital, we aimed to compare the risk of dyslipidemia between premenopausal and postmenopausal women based on the endocrine therapy used.

METHODS

A total of 1,883 early-stage breast cancer (EBC) patients who received endocrine monotherapy [selective estrogen receptor modulator (SERM) and aromatase inhibitor (AI), with or without ovarian function suppression] with normal blood lipid levels at baseline were retrospectively included between October 2008 and April 2017. Dyslipidemia was defined as an abnormality in cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein, and total cholesterol (TC) levels. The risk accumulation function was used to calculate the incidence of dyslipidemia in order to assess the absolute risk, while the multivariate Cox regression model was used to calculate the relative risk of dyslipidemia between the groups.

RESULTS

Patients with EBC were followed up for 60 months to monitor their blood lipid levels. The accumulated 5-year incidence of dyslipidemia in postmenopausal patients was higher than that in premenopausal patients (adjusted HR [95% confidence interval], 1.25 [1.01-1.56], 41.7% vs. 31.2%, p = 0.045). In premenopausal patients, the risk of abnormal TC was significantly higher in the OFS+AI group compared with that in the SERM group (adjusted HR [95% CI], 6.24 [3.19-12.20], p < 0.001, 5-year abnormal rates: 21.5% vs. 2.4%), and that of abnormal LDL-C level also increased (adjusted HR [95% CI], 10.54 [3.86-28.77], p < 0.001, 5-year abnormal rates: 11.1% vs. 0.9%). In postmenopausal patients, the risk of abnormal TC or LDL-C levels showed a similar trend in the AI and SERM groups.

CONCLUSIONS

In addition to postmenopausal patients, dyslipidemia is also common in premenopausal Chinese patients with EBC who received endocrine therapy. Irrespective of menopausal status, AI treatment increases the risk of TC/LDL-C dyslipidemia than SERM treatment.

[Enlightment of routine vaccination under the prevention and control of COVID-19 based on the circulating event of type Ⅲ vaccine-derived poliovirus in Shanghai]

Since the Global Polio Eradication Initiative was launched by the World Health Assembly in 1988, significant progress has been made in global polio prevention and control. But the occurrence of vaccine-associated paralytic poliomyelitis cases and vaccine-derived poliovirus related cases have become a major challenge during the post-polio era. While coronavirus disease 2019(COVID-19) has brought serious disease burden and economic burden to all countries in the world, prevention and control of vaccine-preventable infectious diseases such as polio should not be neglected under the background of the global common fight against COVID-19. Taking the type Ⅲ VDPV cycle event in Shanghai as an example, the paper discussed how to do a good job of routine inoculation under the prevention and control of COVID-19 to strictly prevent the outbreak of vaccine-preventable infectious diseases.

RNA editing regulates lncRNA splicing in human early embryo development

RNA editing is a co- or post-transcriptional modification through which some cells can make discrete changes to specific nucleotide sequences within an RNA molecule after transcription. Previous studies found that RNA editing may be critically involved in cancer and aging. However, the function of RNA editing in human early embryo development is still unclear. In this study, through analyzing single cell RNA sequencing data, 36.7% RNA editing sites were found to have a have differential editing ratio among early embryo developmental stages, and there was a great reprogramming of RNA editing rates at the 8-cell stage, at which most of the differentially edited RNA editing sites (99.2%) had a decreased RNA editing rate. In addition, RNA editing was more likely to occur on RNA splicing sites during human early embryo development. Furthermore, long non-coding RNA (lncRNA) editing sites were found more likely to be on RNA splicing sites (odds ratio = 2.19, P = 1.37×10-8), while mRNA editing sites were less likely (odds ratio = 0.22, P = 8.38×10-46). Besides, we found that the RNA editing rate on lncRNA had a significantly higher correlation coefficient with the percentage spliced index (PSI) of lncRNA exons (R = 0.75, P = 4.90×10-16), which indicated that RNA editing may regulate lncRNA splicing during human early embryo development. Finally, functional analysis revealed that those RNA editing-regulated lncRNAs were enriched in signal transduction, the regulation of transcript expression, and the transmembrane transport of mitochondrial calcium ion. Overall, our study might provide a new insight into the mechanism of RNA editing on lncRNAs in human developmental biology and common birth defects.

Standardization of a SNP panel for parentage verification and identification in the domestic cat (Felis silvestris catus)

The domestic cat (Felis silvestris catus) is a valued companion animal throughout the world. Over 60 different cat breeds are accepted for competition by the cat fancy registries in different countries. Genetic markers, including short tandem repeats and SNPs, are available to evaluate and manage levels of inbreeding and genetic diversity, population and breed structure relationships, and individual identification for forensic and registration purposes. The International Society of Animal Genetics (ISAG) hosts the Applied Genetics in Companion Animals Workshop, which supports the standardization of genetic marker panels and genotyping for the identification of cats via comparison testing. SNP panels have been in development for many species, including the domestic cat. An ISAG approved core panel of SNPs for use in cat identification and parentage analyses is presented. SNPs (n = 121) were evaluated by different university-based and commercial laboratories using 20 DNA samples as part of the ISAG comparison testing procedures. Different SNP genotyping technologies were examined, including DNA arrays, genotyping-by-sequencing and mass spectroscopy, to select a robust and efficient panel of 101 SNPs as the ISAG core panel for cats. The SNPs are distributed across all chromosomes including two on the X chromosome and an XY pseudo-autosomal sexing marker (zinc-finger XY; ZFXY). A population study demonstrated that the markers have an average polymorphic information content of 0.354 and a power of exclusion greater than 0.9999. The SNP panel should keep testing affordable while also allowing for the development of additional panels to monitor health, phenotypic traits, hybrid cats and highly inbred cats.