Toward discovering a novel family of peptides targeting neuroinflammatory states of brain microglia and astrocytes

Microglia are immune-derived cells critical to the development and healthy function of the brain and spinal cord, yet are implicated in the active pathology of many neuropsychiatric disorders. A range of functional phenotypes associated with the healthy brain or disease states has been suggested from in vivo work and were modeled in vitro as surveying, reactive, and primed sub-types of primary rat microglia and mixed microglia/astrocytes. It was hypothesized that the biomolecular profile of these cells undergoes a phenotypical change as well, and these functional phenotypes were explored for potential novel peptide binders using a custom 7 amino acid-presenting M13 phage library (SX7) to identify unique peptides that bind differentially to these respective cell types. Surveying glia were untreated, reactive were induced with a lipopolysaccharide treatment, recovery was modeled with a potent anti-inflammatory treatment dexamethasone, and priming was determined by subsequently challenging the cells with interferon gamma. Microglial function was profiled by determining the secretion of cytokines and nitric oxide, and expression of inducible nitric oxide synthase. After incubation with the SX7 phage library, populations of SX7-positive microglia and/or astrocytes were collected using fluorescence-activated cell sorting, SX7 phage was amplified in Escherichia coli culture, and phage DNA was sequenced via next-generation sequencing. Binding validation was done with synthesized peptides via in-cell westerns. Fifty-eight unique peptides were discovered, and their potential functions were assessed using a basic local alignment search tool. Peptides potentially originated from proteins ranging in function from a variety of supportive glial roles, including synapse support and pruning, to inflammatory incitement including cytokine and interleukin activation, and potential regulation in neurodegenerative and neuropsychiatric disorders.

An Active Strategy to Reduce Residual Alkali for High-Performance Layered Oxide Cathode Materials of Sodium-Ion Batteries

Residual alkali is one of the biggest challenges for the commercialization of sodium-based layered transition metal oxide cathode materials since it can even inevitably appear during the production process. Herein, taking O3-type Na0.9Ni0.25Mn0.4Fe0.2Mg0.1Ti0.05O2 as an example, an active strategy is proposed to reduce residual alkali by slowing the cooling rate, which can be achieved in one-step preparation method. It is suggested that slow cooling can significantly enhance the internal uniformity of the material, facilitating the reintegration of Na+ into the bulk material during the calcination cooling phase, therefore substantially reducing residual alkali. The strategy can remarkably suppress the slurry gelation and gas evolution and enhance the structural stability. Compared to naturally cooled cathode materials, the capacity retention of the slowly cooled electrode material increases from 76.2% to 85.7% after 300 cycles at 1 C. This work offers a versatile approach to the development of advanced cathode materials toward practical applications.

Tuning the Solvation Structure in Water-Based Solution Enables Surface Reconstruction of Layered Oxide Cathodes toward Long Lifespan Sodium-Ion Batteries

Layered oxides of sodium-ion batteries suffer from severe side reactions on the electrode/electrolyte interface, leading to fast capacity degradation. Although surface reconstruction strategies are widely used to solve the above issues, the utilization of the low-cost wet chemical method is extremely challenging for moisture-sensitive Na-based oxide materials. Here, the solvation tuning strategy is proposed to overcome the deterioration of NaNi1/3Mn1/3Fe1/3O2 in water-based solution and conduct the surface reconstruction. When capturing the water molecules by the solvation structure of cations, here is Li+, the structural collapse and degradation of layered oxides in water-based solvents are greatly mitigated. Furthermore, Li(H2O)3EA+ promotes the profitable Li+/Na+ exchange to build a robust surface, which hampers the decomposition of electrolytes and the structural evolution upon cycling. Accordingly, the lifespan of Li-reinforced materials is prolonged to three times that of the pristine one. This work represents a step forward in understanding the surface reconstruction operated in a water-based solution for high-performance sodium layered oxide cathodes.

Comparison of Efficacy and Safety of Different Second-line Therapies for Patients With Advanced Thymic Carcinoma

AIMS

Thymic carcinoma (TC) is a rare form of highly invasive tumors. Currently, the standard first-line therapy involves paclitaxel plus carboplatin treatment, while the recommended regimen for second-line therapy remains uncertain. The purpose of this study is to explore the second-line mode of TC patients.

MATERIALS AND METHODS

We evaluated the outcome of subjects with advanced TC between 2009 and 2023 in three medical centers, retrospectively. Tumor response was evaluated according to the Response Evaluation Criteria in Solid Tumors, version 1.1 (RECIST v1.1). Kaplan-Meier was used for calculating Progression-free survival (PFS) and overall survival (OS). The factors affecting survival in the real world were evaluated by Cox analysis.

RESULTS

Totally 136 patients were included in this study, the median PFS (mPFS) for all subjects was 5.97 months, and the median OS (mOS) was 25.03 months. According to patient's treatment modes, they are divided into monotherapy (n = 95) and combination therapy (n = 41), PFS manifested the difference between two groups (5.17 vs. 9.00 months, P = 0.043). OS also indicated a significant distinction (22.50 vs. 38.00 months, P = 0.017). Furthermore, there was a significant difference in PFS between patients using immunotherapy combined with chemotherapy and those with antivascular therapy (8.57 vs. 13.10 months, P = 0.047).

CONCLUSION

In the second-line therapy for advanced TC, the efficacy of combination therapy was better than monotherapy, especially for immunotherapy combined with antivascular therapy.

[A survey on the current situation of serum vitamin A and vitamin D levels among children aged 2-<7 years of 20 cities in China]

Objective: To investigate serum vitamin A and vitamin D status in children aged 2-<7 years in 20 cities in China. Methods: A cross-sectional study was conducted. A total of 2 924 healthy children aged 2-<7 years were recruited from September 2018 to September 2019 from 20 cities in China, categorized by age groups of 2-<3 years, 3-<5 years, and 5-<7 years. The demographic and economic characteristics and health-related information of the enrolled children were investigated. Body weight and height were measured by professional staff members. The serum vitamin A and vitamin D levels were detected by high-performance liquid chromatography-tandem mass spectrometry. Chi-square test and Logistic regression were applied to analyze the association between vitamin A and vitamin D deficiency and insufficiency as well as their underlying impact factors. Results: The age of the 2 924 enrolled children was 4.33 (3.42, 5.17) years. There were 1 726 males (59.03%) and 1 198 females (40.97%). The prevalences of vitamin A and vitamin D deficiency in enrolled children were 2.19% (64/2 924) and 3.52% (103/2 924), respectively, and the insufficiency rates were 29.27% (856/2 924) and 22.20% (649/2 924), respectively. Children with both vitamin A and vitamin D deficiencies or insufficiencies were found in 10.50% (307/2 924) of cases. Both vitamin A (χ2=7.91 and 8.06, both P=0.005) and vitamin D (χ2=71.35 and 115.10, both P<0.001) insufficiency rates were higher in children aged 3-<5 and 5-<7 years than those in children aged 2-<3 years. Vitamin A and vitamin D supplementation in the last 3 months was a protective factor for vitamin A and D deficiency and insufficiency, respectively (OR=0.68 and 0.22, 95%CI 0.49-0.95 and 0.13-0.40, both P<0.05). The rates of vitamin A and D insufficiency was higher in children with annual household incomes <60 000 RMB than in those with annual household incomes ≥60 000 RMB (χ2=34.11 and 10.43, both P<0.01). Northwest and Southwest had the highest rates of vitamin A and vitamin D insufficiency in children aged 2-<7 yeas, respectively (χ2=93.22 and 202.54, both P<0.001). Conclusions: Among 20 cities in China, children aged 2-<7 years experience high rates of vitamin A and vitamin D insufficiency, which are affected by age, family economic level, vitamin A and vitamin D supplementation, and regional economic level. The current results suggest that high level of attention should be paid to vitamin A and vitamin D nutritional status of preschool children.

Intravesical chemotherapy synergize with an immune adjuvant by a thermo-sensitive hydrogel system for bladder cancer

Surgical resection remains the prefer option for bladder cancer treatment. However, the effectiveness of surgery is usually limited for the high recurrence rate and poor prognosis. Consequently, intravesical chemotherapy synergize with immunotherapy in situ is an attractive way to improve therapeutic effect. Herein, a combined strategy based on thermo-sensitive PLEL hydrogel drug delivery system was developed. GEM loaded PLEL hydrogel was intravesical instilled to kill tumor cells directly, then PLEL hydrogel incorporated with CpG was injected into both groins subcutaneously to promote immune responses synergize with GEM. The results demonstrated that drug loaded PLEL hydrogel had a sol-gel phase transition behavior in response to physiological temperature and presented sustained drug release, and the PLEL-assisted combination therapy could have better tumor suppression effect and stronger immunostimulating effect in vivo. Hence, this combined treatment with PLEL hydrogel system has great potential and suggests a clinically-relevant and valuable option for bladder cancer.

[Comparison of BCR::ABL (P210) mRNA levels detected by dPCR and qPCR methods in patients with chronic myeloid leukemia]

Objective: To compare digital polymerase chain reaction (dPCR) and real-time quantitative PCR (qPCR) measurements of BCR::ABL (P210) mRNA expression in patients with chronic myeloid leukemia (CML) . Methods: In this non-interventional, cross-sectional study, BCR::ABL (P210) mRNA was simultaneously measured by dPCR and qPCR in peripheral blood samples collected from patients with CML who underwent tyrosine kinase inhibitor therapy and who achieved at least a complete cytogenetic response from September 2021 to February 2023 at Peking University People's Hospital. The difference, correlation, and agreement between the two methods were evaluated using the Wilcoxon signed-rank test, Spearman's correlation, and Bland-Altman analysis, respectively. Results: In total, 459 data pairs for BCR::ABL mRNA expression measured by dPCR and qPCR from 356 patients with CML were analyzed. There was a significant difference in BCR::ABL mRNA expression between the two methods (P<0.001). When analyzed by the depth of the molecular response (MR), a significant difference only existed for patients with ≥MR4.5 (P<0.001). No significant difference was observed for those who did not achieve a major MR (no MMR; P=0.922) or for those who achieved a major MR (MMR; P=0.723) or MR4 (P=0.099). There was a moderate correlation between the BCR::ABL mRNA expression between the two methods (r=0.761, P<0.001). However, the correlation gradually weakened or disappeared as the depth of the MR increased (no MMR: r=0.929, P<0.001; MMR: r=0.815, P<0.001; MR4: r=0.408, P<0.001; MR4.5: r=0.176, P=0.176). In addition, the agreement in BCR::ABL mRNA expression between the two methods in those with MR4.5 was weaker than other groups (no MMR: ▉= 0.042, P=0.846; MMR:▉=0.054, P=0.229; MR4:▉=-0.020, P=0.399; MR4.5:▉=-0.219, P<0.001) . Conclusions: dPCR is more accurate than qPCR for measuring BCR::ABL (P210) mRNA expression in patients with CML who achieve a stable deep MR.

[Evaluation of the application value of seven tumor-associated autoantibodies in non-small cell lung cancer based on machine learning algorithms]

Objective: Based on the diagnostic model established and validated by the machine learning algorithm, to investigate the value of seven tumor-associated autoantibodies (TAABs), namely anti-p53, PGP9.5, SOX2, GAGE7, GBU4-5, MAGEA1 and CAGE antibodies in the diagnosis of non-small cell lung cancer (NSCLC) and to differentiate between NSCLC and benign lung nodules. Methods: This was a retrospective study of clinical cases. Model building queue: a total of 227 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from November 2018 to June 2021 were collected as the NSCLC group, and 120 cases of benign lung nodules, 122 cases of pneumonia and 120 healthy individuals were selected as the control groups. External validation queue: a total of 100 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from May 2022 to December 2022 were collected as the NSCLC group, and 36 cases of benign lung nodules, 32 cases of pneumonia and 44 healthy individuals were selected as the control groups. In addition, NSCLC was divided into early (stage 0-ⅠB) and mid-to-late (stage ⅡA-ⅢB) subgroups. The levels of 7-TAABs were detected by enzyme immunoassay, and serum concentrations of CEA and CYFRA21-1 were detected by electrochemiluminescence. Four machine learning algorithms, XGBoost, Lasso logistic regression, Naïve Bayes, and Support Vector Machine are used to establish classification models. And the best performance model was chosen based on evaluation metrics and a multi-indicator combination model was established. In addition, an online risk evaluation tool was generated to assist clinical applications. Results: Except for p53, the levels of rest six TAABs, CEA and CYFRA21-1 were significantly higher in the NSCLC group (P<0.05). Serum levels of anti-SOX2 [1.50 (0.60, 10.85) U/ml vs. 0.8 (0.20, 2.10) U/ml, Z=2.630, P<0.05] and MAGEA1 antibodies [0.20 (0.10, 0.43) U/ml vs. 0.10 (0.10, 0.20) U/ml, Z=2.289, P<0.05], CEA [3.13 (2.12, 5.64) ng/ml vs. 2.11 (1.25, 3.09) ng/ml, Z=3.970, P<0.05] and CYFRA21-1 [4.31(2.37, 7.14) ng/ml vs. 2.53(1.92, 3.48) ng/ml, Z=3.959, P<0.05] were significantly higher in patients with mid-to late-stage NSCLC than in early stages. XGBoost model was used to establish a multi-indicator combined detection model (after removing p53). 6-TAABs combined with CYFRA21-1 was the best combination model for the diagnosis of NSCLC and early NSCLC. The optimal diagnostic thresholds were 0.410, 0.701 and 0.744, and the AUC was 0.828, 0.757 and 0.741, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in model building queue, and the AUC was 0.760, 0.710 and 0.660, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in external validation queue. Conclusion: In the diagnosis of NSCLC, 6-TAABs is superior to that of traditional tumor markers CEA and CYFRA21-1, and can compensate for the shortcomings of traditional tumor markers. For the differential diagnosis of NSCLC and benign lung nodule, "6-TAABs+CYFRA21-1" is the most cost-effective combination, and plays an important role in prevention and screening for early lung cancer.

Performance of Adaptive Deep Learning Models for Dose Predictions on High-Quality Cone-Beam Computed Tomography Images

PURPOSE/OBJECTIVE(S)

Online plan generation remains a patient-specific and time-consuming process that can place a significant burden on clinics strained with staffing shortages. As previous research show that dose-volume histogram (DVH) prediction plays a crucial role in automatic treatment planning, the objective of this study is to assess the capability of adaptive deep learning models in predicting dose information in volumetric modulation radiotherapy plans using the high-quality CBCT images and contour information of organs-at-risk (OARs).

MATERIALS/METHODS

The relationship between dose-volume histograms (DVHs) in radiotherapy plans and the geometric information of organs-at-risk (OAR) and planning target volume (PTV) has been well established. To evaluate the performance of the current state-of-the-art convolutional neural network (CNN) models including VIT3D and Unet3D, and intuitive machine learning methods (i.e., SVM and MLP), we implemented those models for dose prediction and conducted a comprehensive analysis with treatment plans created from images acquired from patients who consented to participate an IRB-approved imaging study designed to evaluate the imaging performance of the system. In total, 20 plans created by certified medical dosimetrists were employed in this study, with 15 used for training the machine-learning models and the remaining 5 used for performance testing. Two evaluation metrics were used: 1) root mean square error (RMSE) of the predicted dose and true dose and 2) time spent on dose prediction.

RESULTS

The results of the analysis showed that the ViT-3D (Transformer) model had the lowest RMSE of 3.682 ±0.010, followed by the Unet-3D (CNN) model with an RMSE of. 3.973 ±0.021 The MLP model had an RMSE of 8.007 ±0.019 while the SVM model had the highest RMSE of 9.156 ±0.032. For a fair comparison, we use 4-fold cross validation (each has 15 training plans and 5 testing plans), and report the mean value with standard deviation. All models are optimized with Adam optimizer of a learning rate 0.01, and the training process is stopped after 100 epochs. These findings indicate that the ViT-3D (Transformer) model performed the best in terms of predicting the dose information in volumetric modulation radiotherapy plans based on the CBCT images and contour information of OARs. For tested plan which contains 81 CT images (512 × 512 resolution), the inference time to predict dose information with a general CPU machine (6-Core Intel Core i7) is about 1.5 minutes. With GPU resources, such as NVIDIA A100, the inference process can be finished within seconds.

CONCLUSION

The study demonstrated that current state-of-the-art machine-learning models can achieve promising accuracy in dose prediction using high-quality CBCT images. A well-trained machine-learning model could offer clinicians a quick and reliable prediction of the true dose to patients in the case of significant anatomical changes or provide patient-specific optimization objectives if replanning is warranted.

Accuracy of Electron Density and Planning Dosimetry in a Novel High-Quality CBCT Imaging System

PURPOSE/OBJECTIVE(S)

A high-quality Cone-Beam Computed Tomography (CBCT) imaging system has been FDA approved for imaging guidance and dose calculation in radiotherapy. This study aims to evaluate the accuracy of the relative electron density in CBCT images acquired in this CBCT imaging system in a phantom study and its dosimetric impact on treatment planning in a patient study.

MATERIALS/METHODS

Astoichiometric CT calibration was performed with a CIRS phantom (SunNuclear, Model 062M) to generate the HU-electron density curve for two tube voltages, 125kVp and 140 kVp, respectively. The phantom has a longitudinal length of 26.5 cm and is equipped with interchangeable inserts of various compositions, supplied by the vendor. Measurements were taken with solid water plates added to both ends of the phantom to allow adequate scattering and repeated for various clinical protocols with different combinations of tube voltages and exposures. The accuracy of the relative electron density of the CBCT imaging system was verified by comparing the calculated electron density from the Hounsfield Units (HU) measurements obtained from a Gammex phantom to the relative electron densities provided in vendor's specifications. To benchmark the relative electron density of the CBCT imaging system against a standard helical CT simulator, ten clinical plans that were created on CT simulation images were copied and recalculated on the CBCT images acquired immediately after the CT simulation, the latter of which was a standard procedure in current radiotherapy care for all patients who had given their consent to participate in the IRB-approved imaging study. The dose grids used in these calculations were 2.5mm x 2.5mm x 3mm. The Gamma passing rate was calculated using a standard 3mm/3% criterion with a 10% threshold.

RESULTS

Ourresults showed the difference between the averaged CBCT calibration curves acquired at tube voltages of 125 kVP and 140 kVp was less than 2%. The mean discrepancy of the relative electron densities from vendor's specification was 0.0045 with a range between -0.02 and 0.04. Relative electron densities in all inserts were within 2% from the vendor's specifications except the cortical bone insert. Gamma passing rate was between 96.02% and 98.49% with mean value of 97.4% and a standard deviation of 0.95%. We consider this reflects the fact that the CT simulation and CBCT imaging were performed in separated rooms, which resulted in slight anatomical deformation that could negatively impact the Gamma passing rate.

CONCLUSION

The CBCT imaging system provides sufficient accuracy of electron density for dose calculation, and the dose distribution calculated on the CBCT images is clinically equivalent to those calculated on helical CT images. The enhanced imaging quality of CBCT could further extend the role of imaging guidance to planning for adaptive radiotherapy, potentially reducing the need for re-simulation and interruptions in the radiotherapy course.

An In Silico study of a One-Day One-Machine Workflow for Definitive Radiotherapy Cases on a Novel Simulation and Treatment Platform

PURPOSE/OBJECTIVE(S)

The workflow in Radiotherapy (RT) has largely unchanged for the past three decades, despite increasing evidence suggesting that delayed access to RT, including the wait time between consultation, simulation, and treatment appointments, can negatively impact clinical outcomes. In this pilot study, we present preliminary results of an in silico study that demonstrate the feasibility of a novel RT platform, which integrates simulation into the treatment process and enables patients to receive immediate RT after their initial RT consultation.

MATERIALS/METHODS

A prospective clinical study has been approved to assess the capabilities of a novel RT platform with a high quality CBCT system for imaging guidance as well as planning. This new platform enables a novel clinical workflow that allows clinicians to review contours and plans created on diagnostic CT images prior to the initial RT consultation and allow them to approve new plans adapted on the actual simulation dataset acquired on the first treatment fraction. Four patients receiving standard of care RT (three abdomen and one thorax) consented for this study and underwent additional experimental CBCT simulation on the new platform in addition to their standard CT simulation. The CBCT simulation was taken in two setups: with a specific mold on a flat couch and without a mold on a curved couch. To demonstrate the equivalence of the new workflow to the current standard of care, the plan created on the most recent diagnostic CT images was compared to the plans adapted on the experimental simulation images and the standard CT simulation images, using a knowledge-based model. Contours were propagated from approved datasets to the new datasets through deformable image registration.

RESULTS

All experimental simulations were completed between 14 and 21 minutes with the assistance of two therapists. The contouring, editing, and replanning process took less than one hour in all cases, in line with our experience and peer-reviewed literature. Despite notable anatomical changes observed, the dose-volume histograms (DVH) were consistent, as shown in Table 1.

CONCLUSION

The novel workflow presented herein was feasible and demonstrates that the integration of simulation with image-guided RT on one single platform may unlock the potential of accelerating the RT workflow and reducing the wait time for treatment from weeks to hours.

Proton Online Adaptation Using Novel Cone-Beam Computed Tomography System

PURPOSE/OBJECTIVE(S)

Cone beam computed tomography (CBCT) has been used in clinic frequently to provide quick, online, and handy three-dimensional images. However, due to its significant artifacts and inaccurate Hounsfield values (HU), CBCT based online proton adaptation is infeasible. Recently, a novel in-room imaging solution was developed to allow larger images, better contrast and faster CBCT imaging acquisition. Our work demonstrated for the first time the feasibility of using this novel CBCT images for direct intensity modulated proton planning.

MATERIALS/METHODS

Three patients and three CIRS phantoms were scanned using novel imaging technique (CBCTp) for this work. CT curves were acquired by scanning a CIRS electron density phantom. Stopping power ratio was computed using the stoichiometric method. Proton plans were made on treatment simulation CT and further evaluated on CBCTp to compare the differences.

RESULTS

The table below shows three patients and three phantoms plan comparisons. Multiple sites and dose levels were studied. The planning target volume (PTV) coverage (D95%) and mean dose difference between simulation CT and CBCTp are 0.8% and 0.3%, correspondingly. Dosimetrically, phantom and patient plans are almost identical between two imaging techniques. Lung patient plan show the largest variation due to patient tumor change and the quality of breathing.

CONCLUSION

The novel and high quality of CBCT is feasible for direct proton planning with accurate CT calibration. It provides a reliable alternative solution for proton online adaptive therapy.

[Association between different obesity measurement indexes and serum C-reactive protein in adult women]

Objective: To explore the association of different obesity measurement indexes on serum C-reactive protein (CRP) in Chinese adult women. Methods: The data were obtained from baseline and follow-up surveys of the urban Breast Cancer Screening Program in Shuangliu District, Chengdu. A total of 441 adult women were included in the study. A questionnaire survey, physical examination, and laboratory testing were conducted on the subjects. Multivariate logistic regression model, two-level mixed effects logistic regression model, and restricted cubic spline method were used to investigate the linear and nonlinear correlation between different obesity measurement indexes and serum CRP in adult women. Results: For every 1 unit increase in BMI, waist circumference (WC), and adiposity, the risk of elevated serum CRP or exacerbation of chronic low-grade inflammation in adult women increased by 16.5%, 5.0%, and 11.1% (P<0.05), respectively. Both BMI and adiposity were nonlinear correlated with serum CRP. Using BMI=24.0 kg/m2 as the reference point, serum CRP level increased with the increase of BMI when BMI >24.0 kg/m2. Using adiposity=30% as the reference point, serum CRP level increased with the increase of adiposity when adiposity >30%. Conclusions: Overall, obesity reflected by BMI had the strongest association with serum CRP in adult women, followed by body fat content reflected by adiposity, and central obesity reflected by WC had the weakest association with CRP. Adult women with BMI >24.0 kg/m2 or adiposity >30% are at high risk for obesity-related inflammatory manifestations.

[Identification and 3D architecture analysis of the LIPC gene mutation in a pedigree with familial hypercholesterolemia-like phenotype]

Objective: To identify and analyze 3D architecture of the mutational sites of susceptible genes in a pedigree with familial hypercholesterolemia-like phenotype (FHLP). Methods: This is a case series study. A pedigree with suspected familial hypercholesterolemia was surveyed. The proband admitted in Beijing Anzhen Hospital in April 2019. Whole-exome sequencing was performed to determine the mutational sites of susceptible genes in the proband. Polymerase chain reaction (PCR) sequencing was used to verify the pathogenic variant on proband's relatives. The structural and functional changes of the proteins were analyzed and predicted by Discovery Studio 4.0 and PyMol 2.0. Results: The patients in the pedigree showed abnormal lipid profiles, especially elevated levels of total cholesterol(TC). The genetic screening detected the c.1330C>T SNP in the exon 8 of lipase C (LIPC) gene, this mutation leads to an amino acid substitution from arginine to cysteine at position 444 (Arg444Cys), in the proband and proband's father and brother. In this family, members with this mutation exhibited elevated TC, whereas lipid profile was normal from the proband's mother without this mutation. This finding indicated that LIPC: c.1330C>T mutation might be the mutational sites of susceptible genes. The analysis showed that Arg444Cys predominantly affected the ligand-binding property of the protein, but had a limited impact on catalytic function. Conclusion: LIPC: c.1330C>T is a new mutational site of susceptible genes in this FHLP pedigree.

[Comparison of diagnostic performance of Clear Cell Likelihood Score v1.0 and v2.0 for clear renal cell carcinoma]

OBJECTIVE

To compare the performance of Clear Cell Likelihood Score (ccLS) v1.0 and v2.0 in diagnosing clear cell renal cell carcinoma (ccRCC) from small renal masses (SRM).

METHODS

We retrospectively analyzed the clinical data and MR images of patients with pathologically confirmed solid SRM from the First Medical Center of the Chinese PLA General Hospital between January 1, 2018, and December 31, 2021, and from Beijing Friendship Hospital of Capital Medical University and Peking University First Hospital between January 1, 2019 and May 17, 2021. Six abdominal radiologists were trained for use of the ccLS algorithm and scored independently using ccLS v1.0 and ccLS v2.0. Random- effects logistic regression modeling was used to generate plot receiver operating characteristic curves (ROC) to evaluate the diagnostic performance of ccLS v1.0 and ccLS v2.0 for ccRCC, and the area under curve (AUC) of these two scoring systems were compared using the DeLong's test. Weighted Kappa test was used to evaluate the interobserver agreement of the ccLS score, and differences in the weighted Kappa coefficients was compared using the Gwet consistency coefficient.

RESULTS

In total, 691 patients (491 males, 200 females; mean age, 54 ± 12 years) with 700 renal masses were included in this study. The pooled accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ccLS v1.0 for diagnosing ccRCC were 77.1%, 76.8%, 77.7%, 90.2%, and 55.7%, as compared with 80.9%, 79.3%, 85.1%, 93.4%, 60.6% with ccLS v2.0, respectively. The AUC of ccLS v2.0 was significantly higher than that of ccLS v1.0 for diagnosis of ccRCC (0.897 vs 0.859; P < 0.01). The interobserver agreement did not differ significantly between ccLS v1.0 and ccLS v2.0 (0.56 vs 0.60; P > 0.05).

CONCLUSION

ccLS v2.0 has better performance for diagnosing ccRCC than ccLS v1.0 and can be considered for use to assist radiologists with their routine diagnostic tasks.

[Preliminary study on the effect of fecal microbiota transplantation on neurobehavior and gut microbiota of offspring rats exposed to arsenic]

Objective: To explore the effects of fecal microbiota transplantation (FMT) on neurobehavior and gut microbiota of arsenic-exposed offspring rats. Methods: In April 2021, Thirty-six SPF SD rats aged 8 weeks were seleted, rats were ranked by weight and divided into four groups according to randomized block design, namely control group, arsenic exposure group (As group) , arsenic+normal saline group (As+NaCl group) and As+FMT group, 6 females and 3 males in each group. Fecal microbiota fluid were provided by feces of rats in control group. Rats drank tap water containing 75 mg/L sodium arsenite for one week and then were caged together. The arsenic exposure was terminated until the pups were born. Female rats with vaginal plug were treated with fecal microbiota fluid via gavage during neurodevelopmental teratogenic window period. The volume of gavage was 1 ml/100 g with once every two days, for a total of three times. Weight alterations of offspring rats were recorded every week after weaning, and when offspring rats grew up for 6 weeks, Morris test and open field experiment was used to observe learning and memory abilities, as well as neurobehavioral performance of autonomous exploration and tension, respectively. 16S rDNA sequencing technology was used to detect microbiota diversities in fecal samples of rats in As group and As+FMT group. Results: Compared with the control group, the ratio of swimming distance and staying time in the target quadrant and the times of crossing the platform of rats in As group decreased significantly, and the motor distance, times entering central zone and the number of grid crossing of rats decreased significantly (P<0.05) . Compared with As group, the ratio of swimming distance in target quadrant, the motor distance in central zone and times entering central zone of rats in As+FMT group were evidently increased (P<0.05) . The analysis of fecal microbiota diversities showed that, at the phyla level, the relative abundance of Bacteroidetes in feces of rats in As+FMT group was higher than that in As group (68.34% vs 60.55%) , while the relative abundance of Firmicutes was lower than that in As group (28.02% vs 33.48%) . At the genus level, the relative abundance of Prevotella in As+FMT group was significantly higher than that in As group, becoming the dominant genus (42.08% vs 21.78%) . Additionally, compared with As group, a total of 22 genus were increased with 21 decreased genus in As+FMT group (P<0.05) . LEfSe analysis showed that dominant genuses in As+FMT group were Prevotella and UCG_005, and their relative abundance was significantly higher than that of As group (P<0.05) . Conclusion: FMT may alleviate the impaired learning and memory ability and anxiety like behavior of the offspring rats exposed to arsenic, and improve the disrupted gut microbiota.

Dynapenic Abdominal Obesity and Risk of Heart Disease among Middle-Aged and Older Adults: A Prospective Cohort Study

OBJECTIVES

The vicious cycle of dynapenia and abdominal obesity may have synergistic detrimental impacts on health. We aim to investigate the prospective association between dynapenic abdominal obesity and the risk of heart disease among middle-aged and older adults.

DESIGN

A prospective cohort study.

SETTING

English Longitudinal Study of Ageing, 2002-2019.

PARTICIPANTS

A total of 4734 participants aged 50 years and older were included.

MEASUREMENTS

Individuals were divided into non-dynapenia/non-abdominal obesity (ND/NAO), non-dynapenia/abdominal obesity (ND/AO), dynapenia/non-abdominal obesity (D/NAO), and dynapenia/abdominal obesity (D/AO) according to grip strength and waist circumference at baseline. The Cox proportional hazards models were used to obtain the hazard ratios (HRs) of incident heart disease associated with dynapenia and abdominal obesity after adjusting for potential confounding factors.

RESULTS

During a median follow-up of 9.5 years, 1040 cases of heart disease were recorded. Compared with ND/NAO group, the multivariable HRs were 1.05 (0.92, 1.21) for ND/AO group, 1.31 (0.96, 1.81) for D/NAO group, and 1.39 (1.03, 1.88) for D/AO group. The significant association of D/AO with incident heart disease was detected in women but not in men [HR = 1.55 (1.07, 2.24) and 1.06 (0.60, 1.88), respectively]. Among middle-aged adults, significant associations of D/NAO and D/AO with incident heart disease were observed [HR = 2.46 (1.42, 4.29) and 1.74 (1.02, 2.97), respectively].

CONCLUSION

Both D/NAO and D/AO might increase the risk of developing heart disease, highlighting the importance of dynapenia and obesity early screening for heart disease prevention.

Extracellular vesicles derived from mesenchymal stem cells confer protection against intervertebral disc degeneration through a microRNA-217-dependent mechanism

OBJECTIVE

Extracellular vesicles released by mesenchymal stem cells (MSC-EVs) can be applied to alleviate intervertebral disc degeneration (IVDD) by curbing apoptosis of nucleus pulposus cells (NPCs). The current study aims to evaluate the effect of MSC-EVs on NPC apoptosis and IVDD and the related regulatory mechanisms involving microRNA (miR)-217.

METHOD

Expression of miR-217 was examined in tumor necrosis factor-α (TNF-α)-induced NPCs and MSC-EVs, followed by identification in the relationship between miR-217, enhancer of zeste homolog 2 (EZH2) and forkhead box O-3 (FOXO3). After isolation of EVs from MSCs and subsequent co-culture with NPCs, we assessed effects of miR-217 on NPC viability, autophagy, senescence and apoptosis along with extracellular matrix (ECM) degradation. Further in vivo experiments were conducted in rat models of IVDD to substantiate the effect of miR-217 on IVDD.

RESULTS

Poor miR-217 expression was found in TNF-α-induced NPCs, while high miR-217 expression was identified in MSC-EVs (P < 0.05). MSC-EVs transferred miR-217 to NPCs and increased its expression, thus attenuating NPC apoptosis and ECM degradation (elevated collagen II and aggrecan but reduced MMP13 and ADAMTS5) (P < 0.05). miR-217 targeted EZH2, and EZH2 bound to the FOXO3 promoter and consequently downregulated its expression. FOXO3 restrained NPC apoptosis and ECM degradation by stimulating cell autophagy (P < 0.05). Furthermore, in vivo experimental results confirmed the suppressive role of miR-217 shuttled by MSC-EVs in IVDD.

CONCLUSION

Overall, the delivery of miR-217 may be a novel mechanism underlying the effect of MSC-EVs on NPC apoptosis and ECM degradation following IVDD.