[MAX germline mutation-associated pheochromocytoma-paraganglioma syndrome: multiple endocrine neoplasia type 5].

The individualized precision management of hereditary pheochromocytoma (PHEO) and paraganglioma (PGL) syndromes (PPGLs) based on molecular diagnosis and molecular subtype is becoming more popular. The newly discovered MAX germline mutation-associated PPGLs are autosomally dominant and rare. To raise awareness and explore the effective management of individual diagnosis and treatment, the relevant literature published between January 2011 and February was systematically reviewed. There were a total of 101 patients in the 77 families, involving all 5 exons, containing 44 types of MAX germline mutations and mostly concentrated in exons 3 and 4 (64.4%), the main mutations were nonsense mutations and missense mutations (73.2%), and some were large fragment deletions or insertions, intron variant, gene fusion mutations were relatively infrequent. Furthermore, about 10% of the patients had a paternal parent-of-origin effect. Among the 101 patients, 96 (95.0%) developed PHEO including 15 metastatic PHEO, 61 bilateral PHEO and 35 unilateral PHEO. The age of diagnosis was (31.7±10.9) years (range: 13 to 80 years). The male to female ratio was 1.2∶1. Eleven were accompanied with chest and abdominal PGL. Eight (7.9%) were accompanied by functional pituitary adenoma. And 12 (11.9%) developed other neuroendocrine tumors (NET), of which 8 were accompanied by PHEO, including 4 hyperparathyroidism, 1 gangliocytoma and neuroblastoma, 1 pancreatic NET, 1 medullary thyroid carcinoma and 1 C cell hyperplasia. Six presented concomitant non-NET, including 1 tongue squamous cell carcinoma, 1 papillary thyroid carcinoma, 1 prostate cancer, 1 renal oncocytoma, 1 breast cancer with renal oncocytoma, and 1 thoracic chondrosarcoma with multifocal adenocarcinoma of lung. The remaining 5 cases (5.0%), including 4 other NET (2 ganglioblastoma, 1 abdominal neuroblastoma and 1 pancreatic NET) and 1 asymptomatic child, did not present PHEO. The MAX germline mutation may cause a novel multiple endocrine neoplasia, which can be described as type 5. A comprehensive baseline assessment of neural crest cell-derived diseases such as PPGL, pituitary adenoma, hyperparathyroidism, and/or gangliocytoma (neuroblastoma) was recommended for all people with MAX germline mutations, and the risk of bilateral and/or metastatic PHEO should also be considered. In contrast, patients with PPGLs combined with other NET, such as functional pituitary adenoma, should undergo genetic testing and pedigree screening that includes at least the MAX gene.

[Interpretation of specification for service of cancer screening for workers].

As the backbone force of China's social and economic construction, the health status of workers is closely related to the nation's productivity and social development. Currently, cancers have become one of the major diseases threatening the health of workers. However, there are still many shortcomings in the cancer screening services for the workers. To standardize cancer screening services for workers, ensure the quality of screening services, and improve the overall screening effectiveness, 19 institutions, including Peking Union Medical College Hospital of the Chinese Academy of Medical Sciences, have jointly formulated the Group Standard "Specification for service of cancer screening for workers (T/CHAA 023-2023)". This standard follows the principles of "legality, scientific rigor, advancement, and feasibility" and combines the frontier scientific advances in cancer screening. It clarifies the relevant requirements for service principles, service design, service delivery, service management, service evaluation, and improving worker cancer screening. Implementing this group standard will help connect the common screening needs of workers, employers, and cancer screening service providers, standardize the screening process, improve screening quality, and ultimately increase the early diagnosis rate and survival rate of cancer patients. Consequently, this group standard will help safeguard workers' health rights and interests, ensure the labor force resources, promote the comprehensive coordinated and sustainable development of society, and contribute to realizing the "Healthy China 2030" strategic policy.

Terahertz in vivo imaging of human skin: Toward detection of abnormal skin pathologies.

Terahertz (THz) imaging has long held promise for skin cancer detection but has been hampered by the lack of practical technological implementation. In this article, we introduce a technique for discriminating several skin pathologies using a coherent THz confocal system based on a THz quantum cascade laser. High resolution in vivo THz images (with diffraction limited to the order of 100 µm) of several different lesion types were acquired and compared against one another using the amplitude and phase values. Our system successfully separated pathologies using a combination of phase and amplitude information and their respective surface textures. The large scan field (50 × 40 mm) of the system allows macroscopic visualization of several skin lesions in a single frame. Utilizing THz imaging for dermatological assessment of skin lesions offers substantial additional diagnostic value for clinicians. THz images contain information complementary to the information contained in the conventional digital images.

NRG Oncology Assessment of Artificial Intelligence Deep Learning-Based Auto-segmentation for Radiation Therapy: Current Developments, Clinical Considerations, and Future Directions.

Deep learning neural networks (DLNN) in Artificial intelligence (AI) have been extensively explored for automatic segmentation in radiotherapy (RT). In contrast to traditional model-based methods, data-driven AI-based models for auto-segmentation have shown high accuracy in early studies in research settings and controlled environment (single institution). Vendor-provided commercial AI models are made available as part of the integrated treatment planning system (TPS) or as a stand-alone tool that provides streamlined workflow interacting with the main TPS. These commercial tools have drawn clinics' attention thanks to their significant benefit in reducing the workload from manual contouring and shortening the duration of treatment planning. However, challenges occur when applying these commercial AI-based segmentation models to diverse clinical scenarios, particularly in uncontrolled environments. Contouring nomenclature and guideline standardization has been the main task undertaken by the NRG Oncology. AI auto-segmentation holds the potential clinical trial participants to reduce interobserver variations, nomenclature non-compliance, and contouring guideline deviations. Meanwhile, trial reviewers could use AI tools to verify contour accuracy and compliance of those submitted datasets. In recognizing the growing clinical utilization and potential of these commercial AI auto-segmentation tools, NRG Oncology has formed a working group to evaluate the clinical utilization and potential of commercial AI auto-segmentation tools. The group will assess in-house and commercially available AI models, evaluation metrics, clinical challenges, and limitations, as well as future developments in addressing these challenges. General recommendations are made in terms of the implementation of these commercial AI models, as well as precautions in recognizing the challenges and limitations.

Feature selection based on unsupervised clustering evaluation for predicting neoadjuvant chemoradiation response for patients with locally advanced rectal cancer.

Accurate response prediction allows for personalized cancer treatment of locally advanced rectal cancer (LARC) with neoadjuvant chemoradiation. In this work, we designed a convolutional neural network (CNN) feature extractor with switchable 3D and 2D convolutional kernels to extract deep learning features for response prediction. Compared with radiomics features, convolutional kernels may adaptively extract local or global image features from multi-modal MR sequences without the need of feature predefinition. We then developed an unsupervised clustering based evaluation method to improve the feature selection operation in the feature space formed by the combination of CNN features and radiomics features. While normal process of feature selection generally includes the operations of classifier training and classification execution, the process needs to be repeated many times after new feature combinations were found to evaluate the model performance, which incurs a significant time cost. To address this issue, we proposed a cost effective process to use a constructed unsupervised clustering analysis indicator to replace the classifier training process by indirectly evaluating the quality of new found feature combinations in feature selection process. We evaluated the proposed method using 43 LARC patients underwent neoadjuvant chemoradiation. Our prediction model achieved accuracy, area-under-curve (AUC), sensitivity and specificity of 0.852, 0.871, 0.868, and 0.735 respectively. Compared with traditional radiomics methods, the prediction models (AUC = 0.846) based on deep learning-based feature sets are significantly better than traditional radiomics methods (AUC = 0.714). The experiments also showed following findings: (1) the features with higher predictive power are mainly from high-order abstract features extracted by CNN on ADC images and T2 images; (2) both ADC_Radiomics and ADC_CNN features are more advantageous for predicting treatment responses than the radiomics and CNN features extracted from T2 images; (3) 3D CNN features are more effective than 2D CNN features in the treatment response prediction. The proposed unsupervised clustering indicator is feasible with low computational cost, which facilitates the discovery of valuable solutions by highlighting the correlation and complementarity between different types of features.

Prediction of Radiation Treatment Response for Locally Advanced Rectal Cancer via a Longitudinal Trend Analysis Framework on Cone-Beam CT.

Locally advanced rectal cancer (LARC) presents a significant challenge in terms of treatment management, particularly with regards to identifying patients who are likely to respond to radiation therapy (RT) at an individualized level. Patients respond to the same radiation treatment course differently due to inter- and intra-patient variability in radiosensitivity. In-room volumetric cone-beam computed tomography (CBCT) is widely used to ensure proper alignment, but also allows us to assess tumor response during the treatment course. In this work, we proposed a longitudinal radiomic trend (LRT) framework for accurate and robust treatment response assessment using daily CBCT scans for early detection of patient response. The LRT framework consists of four modules: (1) Automated registration and evaluation of CBCT scans to planning CT; (2) Feature extraction and normalization; (3) Longitudinal trending analyses; and (4) Feature reduction and model creation. The effectiveness of the framework was validated via leave-one-out cross-validation (LOOCV), using a total of 840 CBCT scans for a retrospective cohort of LARC patients. The trending model demonstrates significant differences between the responder vs. non-responder groups with an Area Under the Curve (AUC) of 0.98, which allows for systematic monitoring and early prediction of patient response during the RT treatment course for potential adaptive management.

Bioinformatics screening of gene expression profile and diagnostic application of meningeal carcinoma.

OBJECTIVE: The aim of this study was to research gene expression profiles and diagnostic applications of meningeal carcinoma based on bioinformatics. MATERIALS AND METHODS: We used the Gene Expression Omnibus (GEO) database to obtain the GSE43290 dataset based on the expression data of normal meninges and meningiomas consisting of 51 samples divided into two groups (47 samples of meningioma tumors and four samples of normal meninges). We used the GEO2R tool to identify differentially expressed genes (DEGs) by setting the log2 fold change as greater than two and an adjusted p-value lower than 0.05. We used the database for annotation, visualization and integrated discovery (DAVID) to perform gene ontology, biological pathways and functional annotation of the DEGs. A search Tool for the Retrieval of Interacting Gene database (STRING) was used to obtain Protein-Protein Interaction (PPI) and modular networks based on the Markov clustering algorithm. RESULTS: Our study identified 358 significant DEGs, of which 343 were downregulated genes while 15 were upregulated. Five significant hub genes (CXCL8, AGT, CXCR4, CXCL12 and CXCL2) were associated with various biological pathways, molecular functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The DEGs were enriched in biological pathways of chemokine-mediated signaling, positive regulation of leukocyte chemotaxis, second messenger-mediated signaling, induction of positive chemotaxis, CXCR chemokine receptor binding and activities of cytokines. CONCLUSIONS: These hub genes and pathways could be targeted in clinical research to discover new treatments for meningeal carcinoma.

[Plurihormonal PIT1-lineage pituitary neuroendocrine tumors: a clinicopathological study].

Objective: To investigate the clinicopathological characteristics of plurihormonal PIT1-lineage pituitary neuroendocrine tumors. Methods: Forty-eight plurihormonal PIT1-lineage tumors were collected between January 2018 and April 2022 from the pathological database of Sanbo Brain Hospital, Capital Medical University. The related clinical and imaging data were retrieved. H&E, immunohistochemical and special stains were performed. Results: Out of the 48 plurihormonal PIT1-lineage tumors included, 13 cases were mature PIT1-lineage tumors and 35 cases were immature PIT1-lineage tumors. There were some obvious clinicopathological differences between the two groups. Clinically, the mature plurihormonal PIT1-lineage tumor mostly had endocrine symptoms due to increased hormone production, while a small number of immature PIT1-lineage tumors had endocrine symptoms accompanied by low-level increased serum pituitary hormone; patients with the immature PIT1-lineage tumors were younger than the mature PIT1-lineage tumors; the immature PIT1-lineage tumors were larger in size and more likely invasive in imaging. Histopathologically, the mature PIT1-lineage tumors were composed of large eosinophilic cells with high proportion of growth hormone expression, while the immature PIT1-lineage tumors consisted of chromophobe cells with a relatively higher expression of prolactin; the mature PIT1-lineage tumors had consistently diffuse cytoplasmic positive staining for keratin, while the immature PIT1-lineage tumors had various expression for keratin; the immature PIT1-lineage tumors showed more mitotic figures and higher Ki-67 proliferation index; in addition, 25.0% (12/48) of PIT1-positive plurihormonal tumors showed abnormal positive staining for gonadotropin hormones. There was no significant difference in the progression-free survival between the two groups (P=0.648) by Kaplan-Meier analysis. Conclusions: Plurihormonal PIT1-lineage tumor belongs to a rare type of PIT1-lineage pituitary neuroendocrine tumors, most of which are of immature lineage. Clinically increased symptoms owing to pituitary hormone secretion, histopathologically increased number of eosinophilic tumor cells with high proportion of growth hormone expression, diffusely cytoplasmic keratin staining and low proliferative activity can help differentiate the mature plurihormonal PIT1-lineage tumors from the immature PIT1-lineage tumors. The immature PIT1-lineage tumors have more complicated clinicopathological characteristics.

[Application of intraoperative optical coherence tomography in deep lamellar keratoplasty].

Objective: To evaluate the clinical application value of intraoperative optical coherence tomography (iOCT) in deep anterior lamellar keratoplasty (DALK) using the big-bubble technique to bare Descemet's membrane. Methods: Retrospective case series. Clinical data of 92 patients (92 eyes) with monocular stromal corneal diseases who underwent big-bubble DALK in the Eye Hospital of Shandong First Medical University from January 2020 to August 2021 were collected. There were 53 males and 39 females. The average age was (53.2±16.0) years old. All patients underwent iOCT scanning to determine the location and depth of the injection needle after initial removal of the corneal lesion, to observe the integrity of the recipient bed, Descemet's membrane, after complete lesion removal, and to observe the adhesion between the corneal graft and the recipient bed and check folds on the recipient bed after suturing of the corneal graft. The intraoperative perforation of Descemet's membrane, postoperative thickness of the cornea and the recipient bed, visual acuity, and corneal astigmatism were recorded. Results: By iOCT, the thickness of the recipient bed was found to be about 1/2 of the corneal thickness and relatively uniform in all directions in 62 eyes (67.4%), so the sterile air was injected from the center of the recipient bed to separate it from the stromal layer. In 30 eyes (32.6%) with an uneven thickness of the recipient bed, the sterile air was injected from the paracentral area of the recipient bed. Under the guidance of iOCT scanning, 89 eyes (96.7%) did not experience any perforation of Descemet's membrane during surgery. The Descemet's membrane folds in the central 5-mm area of the recipient bed was observed and flattened in 20 eyes with the assistance of iOCT scanning. The postoperative corneal thickness was (578.95±108.26) µm, and the recipient bed thickness was (36.06±23.11) µm. The best corrected visual acuity of all patients at 6 months after surgery was 0.57±0.25 logMAR, which was significantly better than that before surgery (1.61±1.27 logMAR; P<0.001). The average corneal astigmatism at 6 months after surgery was (2.72±2.44) diopters. Conclusions: The application of iOCT scanning in DALK surgery assisted by the big-bubble method can provide safe guidance for surgeons to adopt correct surgical procedures, decrease the risk of Descemet's membrane perforation, reduce the recipient bed folds, and facilitate corneal interlayer adhesion, thereby improving the visual prognosis.

MRI-Guided Radiation Therapy for Prostate Cancer: The Next Frontier in Ultrahypofractionation.

Technological advances in MRI-guided radiation therapy (MRIgRT) have improved real-time visualization of the prostate and its surrounding structures over CT-guided radiation therapy. Seminal studies have demonstrated safe dose escalation achieved through ultrahypofractionation with MRIgRT due to planning target volume (PTV) margin reduction and treatment gating. On-table adaptation with MRI-based technologies can also incorporate real-time changes in target shape and volume and can reduce high doses of radiation to sensitive surrounding structures that may move into the treatment field. Ongoing clinical trials seek to refine ultrahypofractionated radiotherapy treatments for prostate cancer using MRIgRT. Though these studies have the potential to demonstrate improved biochemical control and reduced side effects, limitations concerning patient treatment times and operational workflows may preclude wide adoption of this technology outside of centers of excellence. In this review, we discuss the advantages and limitations of MRIgRT for prostate cancer, as well as clinical trials testing the efficacy and toxicity of ultrafractionation in patients with localized or post-prostatectomy recurrent prostate cancer.

Predicting Overall Survival for Patients with Malignant Mesothelioma Following Radiotherapy via Interpretable Machine Learning.

PURPOSE/OBJECTIVES: Malignant pleural mesothelioma (MPM) is a rare but aggressive cancer arising from the cells of the thoracic pleura with a poor prognosis. We aimed to develop a model, via interpretable machine learning (ML) methods, predicting overall survival for MPM following radiotherapy based on dosimetric metrics as well as patient characteristics. MATERIALS/METHODS: Sixty MPM (37 right, 23 left) patients treated on a Tomotherapy unit between 2013 and 2018 were retrospectively analyzed. All patients received 45 Gy (25 fractions). The multivariable Cox regression (Cox PH) model and Survival Support Vector Machine (sSVM) were applied to build predictive models of overall survival (OS) based on clinical, dosimetric, and combined variables. RESULTS: Significant differences in dosimetric endpoints for critical structures, i.e., the lung, heart, liver, kidney, and stomach, were observed according to target laterality. The OS was found to be insignificantly different (p = 0.18) between MPM patients who tested left- and right-sided, with 1-year OS of 77.3% and 75.0%, respectively. With Cox PH regression, considering dosimetric variables for right-sided patients alone, an increase in PTV_Min, Total_Lung_PTV_Mean, Contra_Lung_Volume, Contra_Lung_V20, Esophagus_Mean, and Heart_Volume had a greater hazard to all-cause death, while an increase in Total_Lung_PTV_V20, Contra_Lung_V5, and Esophagus_Max had a lower hazard to all-cause death. Considering clinical variables alone, males and increases in N stage had greater hazard to all-cause death; considering both clinical and dosimetric variables, increases in N stage, PTV_Mean, PTV_Min, and esophagus_Mean had greater hazard to all-cause death, while increases in T stage and Heart_V30 had lower hazard to all-cause-death. In terms of C-index, the Cox PH model and sSVM performed similarly and fairly well when considering clinical and dosimetric variables independently or jointly. CONCLUSIONS: Clinical and dosimetric variables may predict the overall survival of mesothelioma patients, which could guide personalized treatment planning towards a better treatment response. The identified predictors and their impact on survival offered additional value for translational application in clinical practice.

[Analysis of the characteristics of viral infections in children with diarrhea in Beijing from 2018 to 2022].

Objective: To explore the characteristics of viral infections in children with diarrhea in Beijing from 2018 to 2022. Methods: Real-time PCR and enzyme-linked immunosorbent assay were used to detect viral nucleic acid of Norovirus (NoV), Sappovirus (SaV), Astrovirus (AstV), Enteric Adenovirus (AdV) or antigen of Rotavirus (RV) in 748 stool samples collected from Beijing Capital Institute of Pediatrics from January 2018 to December 2021. Subsequently, the reverse transcription PCR or PCR method was used to amplify the target gene of the positive samples after the initial screening, followed by sequencing, genotyping and evolution analysis, so as to obtain the characteristics of these viruses. Phylogenetic analysis was performed using Mega 6.0. Results: From 2018 to 2021, the overall detection rate of the above five common viruses was 37.6%(281/748)in children under 5 years old in Beijing. NoV, Enteric AdV and RV were still the top three diarrhea-related viruses, followed by AstV and SaV, accounting for 41.6%, 29.2%, 27.8%, 8.9% and 7.5%, respectively. The detection rate of co-infections with two or three diarrhea-related viruses was 4.7% (35/748). From the perspective of annual distribution, the detection rate of Enteric AdV was the highest in 2021, while NoV was predominant in the other 4 years. From the perspective of genetic characteristics, NoV was predominant by GⅡ.4, and after the first detection of GⅡ.4[P16] in 2020, it occupied the first two gene groups together with GⅡ.4[P31]. Although the predominant RV was G9P[8], the rare epidemic strain G8P[8] was first detected in 2021. The predominant genotypes of Enteric AdV and AstV were Ad41 and HAstV-1. SaV was sporadic spread with a low detection rate. Conclusion: Among the diarrhea-related viruses infected children under 5 years of age in Beijing, the predominant strains of NoV and RV have changed and new sub-genotypes have been detected for the first time, while the predominant strains of AstV and Enteric AdV are relatively stable.

A subregion-based survival prediction framework for GBM via multi-sequence MRI space optimization and clustering-based feature bundling and construction.

Aiming at accurate survival prediction of Glioblastoma (GBM) patients following radiation therapy, we developed a subregion-based survival prediction framework via a novel feature construction method on multi-sequence MRIs. The proposed method consists of two main steps: (1) a feature space optimization algorithm to determine the most appropriate matching relation derived between multi-sequence MRIs and tumor subregions, for using multimodal image data more reasonable; (2) a clustering-based feature bundling and construction algorithm to compress the high-dimensional extracted radiomic features and construct a smaller but effective set of features, for accurate prediction model construction. For each tumor subregion, a total of 680 radiomic features were extracted from one MRI sequence using Pyradiomics. Additional 71 geometric features and clinical information were collected resulting in an extreme high-dimensional feature space of 8231 to train and evaluate the survival prediction at 1 year, and the more challenging overall survival prediction. The framework was developed based on 98 GBM patients from the BraTS 2020 dataset under five-fold cross-validation, and tested on an external cohort of 19 GBM patients randomly selected from the same dataset. Finally, we identified the best matching relationship between each subregion and its corresponding MRI sequence, a subset of 235 features (out of 8231 features) were generated by the proposed feature bundling and construction framework. The subregion-based survival prediction framework achieved AUCs of 0.998 and 0.983 on the training and independent test cohort respectively for 1 year survival prediction, compared to AUCs of 0.940 and 0.923 for survival prediction using the 8231 initial extracted features for training and validation cohorts respectively. Finally, we further constructed an effective stacking structure ensemble regressor to predict the overall survival with the C-index of 0.872. The proposed subregion-based survival prediction framework allow us to better stratified patients towards personalized treatment of GBM.

[Association between HULC gene locus rs7763881 polymorphism and recurrence and metastasis after radical resection in hepatocellular carcinoma].

Objective: To investigate the association between the expression of long non-coding RNA genes and the HULC rs7763881 polymorphism, recurrence, and metastasis after radical resection in patients with hepatocellular carcinoma (HCC). Methods: Paraffin tissue samples were selected from 426 cases diagnosed with HCC between January 2004 to January 2012. The expression of different genotypes of HULC gene locus rs7763881 in paraffin tissues was detected by PCR, and the association between different genotype expressions and clinical case characteristics of HCC [gender, age, TNM stage, alpha-fetoprotein, tumor maximum diameter (cm), vascular invasion, tumor capsule, tumor grade] was analyzed. Cox proportional risk regression model was used to analyze the correlation between different genotypes and clinicopathological features, prognosis, and recurrence. Survival analysis between different genotypes was performed using the Kaplan-Meier method for a parallel log-rank test. Results: There were 27 (6.3%) cases in the whole group who lost to follow-up. A total of 399 (93.7%) specimens were included in the study, and 105 (26.3%), 211 (52.9%) and 83 (20.8%) were included in the rs77638881 AA, AC, and CC genotypes, respectively. Kaplan-Meier curve showed that the postoperative overall survival and recurrence-free survival rate were significantly higher in patients with the AA than AC/CC genotype (P < 0.05). Univariate analysis showed that the AC/CC genotype was closely related to tumor vascular invasion and recurrence or metastasis of HCC (P < 0.05). Cox multivariate analysis results showed that patients with the AA genotype were taken as references, and the results showed that the risk of recurrence and metastasis in patients with the CA/CC genotype increased to varying degrees, with statistical significance (P < 0.05). Conclusion: The rs7763881 polymorphic loci located on the HULC gene are closely related to HCC recurrence and metastasis after radical resection. Thus, it may be an indicator for evaluating HCC recurrence and metastasis.

["Graded early warning system" of RET germline mutation carriers in MEN2A/MEN2B families and total thyroidectomy (report of 7 cases)].

Objective: To explore the reasonable time of prophylactic thyroidectomy for RET gene carriers in multiple endocrine neoplasia(MEN) 2A/2B families. Methods: From May 2015 to August 2021, RET gene carriers in MEN2A/MEN2B families were dynamically followed up at the Department of Thyroid Head and Neck Surgery, Beijing Tongren Hospital of Capital Medical University. The high-risk patients were encouraged to undergo prophylacitc total thyroidectomy according to the principle of "graded early warning system", namely the evaluation of gene detection, calcitonin value and ultrasound examination successively. Seven cases underwent the surgery, including 3 males and 4 females, aged from 7 to 29 years. According to the risk stratification listed in the guidelines of the American Thyroid Association in 2015, there were 2 cases of the highest risk, 2 cases of the high risk and 3 cases of the modest risk. Calcitonin index remained within the normal range in 3 cases and elevated in 4 cases before operation. All 7 patients underwent thyroidectomy with lymph node dissection of the level Ⅵ performed in 4 patients. Results: The time from suggestion to operation was 2 to 37 months, with an average of 15.1 months. The 6 patients were medullary thyroid carcinoma and 1 case with C-cell hyperplasia. The follow-up time was 2 to 82 months, with an average of 38.4 months. Postoperative serum calcitonin levels of all cases decreased to normal level, with biochemical cure. There was no sign of recurrence on ultrasound examination. All 7 patients had no serious complications, no obvious thyroid dysfunction. Their height, weight and other indicators of pediatric patients were similar to those of their peers, with normal growth and development. Conclusion: For healthy people with MEN2A/MEN2B family history, prophylactic thyroidectomy can be carried out selectively based on the comprehensive evaluation of "graded early warning system" with strict screening and close monitoring.

[Protective effect of anti-idiopathic pulmonary fibrosis drug Pirfenidone and Sufenidone (SC1011) on pulmonary injury induced by tuberculosis in a mouse tuberculosis model].

Objective: To evaluate the protective effect of anti-idiopathic pulmonary fibrosis (IPF) marketed drug Pirfenidone and its clinical drug Sufenidone (SC1011) against lung injury in a mouse tuberculosis model. Methods: C57BL/6 mouse model of tuberculosis was established. A total of 75 C57BL/6 mice were infected with 1×107 CFU/ml H37Rv suspension by aerosol and randomly divided into untreated (n=9) group, isoniazid+rifampicin+pyrazinamide (HRZ) group (n=22), PFD+HRZ group (n=22), and SC1011+HRZ group (n=22). C57BL/6 mice were infected with H37Rv by aerosol for 6 weeks and then treated. Seven mice in each treatment group were weighed, sacrificed, dissected and observed for lung and spleen lesions at 4 and 8 weeks of treatment. HE staining and Masson staining were used to assess degree of lung injury and fibrosis, respectively. ELISA was used to assess the IFN-γ/TNF-α content in the serum of mice in each treatment group after 4 weeks of treatment. Hydroxyproline (HYP) content in lung tissue was measured by alkaline hydrolysis; meanwhile, CFU counts were used to assess the bacterial load in the lung and spleen of mice in each treatment group and the recurrence of spleen and lung tissue after 12 weeks of drug withdrawal. Results: At 8 weeks, the HYP content in the lung tissue was (630±58), (635±17), and (840±70) µg/mg in the PFD+HRZ, SC1011+HRZ, and HRZ treatment group, respectively (P<0.05).At 8 weeks, the proportion of Masson staining blue-stained area, that was, positive area, in lung tissue was 16.65%±1.82%, 10.01%±2.16%, and 21.36%±3.21%, respectively (F=27.11, P<0.001).The lung injury scores by HE staining at 8 weeks were (5.00±0.50), (5.00±0.47), and (6.89±0.99) points, respectively (F=19.81, P<0.001).The results of 4-week ELISA showed that the levels of TNF-α and IFN-γ in the serum of the SC1011+HRZ-treated group were lower than those of the HRZ-treated group (all P<0.05).The degree of lung injury and fibrosis in PFD+HRZ and SC1011+HRZ treatment groups were lower than those in HRZ treatment group (all P<0.001). The number of viable bacteria in the lung tissue of mice treated with PFD+HRZ, SC1011+HRZ, and HRZ for 4 weeks was lower than that of mice untreated [(1.82±0.10), (1.91±0.05), (1.79±0.17) vs. (5.27±0.07) lg(CFU+1)/ml, all P<0.05)]. And the aseptic transformation of the spleen of mice was achieved in each treatment group at 8 weeks of administration. After 12 weeks of drug withdrawal, the recurrence of lung infection in the SC1011+HRZ treatment group was 3/7 lower than 5/7 in the HRZ treatment group (P>0.05); the recurrence of spleen infection in the SC1011+HRZ treatment group was 1/7 lower than 5/7 in the HRZ treatment group (P>0.05).Pulmonary infection recurred more frequently in PFD+HRZ 6/7 versus HRZ 5/7 (P>0.05). Conclusions: PFD/SC1011, when combined with HRZ, reduced lung injury and reduced secondary fibrosis in pulmonary tuberculosis in C57BL/6 mice. SC1011 combined with HRZ has no significant short-term therapeutic effect on MTB, but may reduce its recurrence rate in long-term treatment, especially in reducing the recurrence rate of mouse spleen.

[Clinicopathological features of patients with RET fusion-positive non-small cell lung cancer].

Objective: To investigate the clinicopathological features, treatment and prognosis of patients with RET fusion positive non-small cell lung cancer (NSCLC). Methods: A total of 1 089 NSCLCs were retrieved at Affiliated Hospital of Jiangnan University from August 2018 to April 2020. In all cases, multiple gene fusion detection kits (fluorescent PCR method) were used to detect the gene status of RET, EGFR, ALK, ROS1, KRAS, BRAF and HER2; and immunohistochemical method was used to detect the expression of PD-L1 and mismatch repair related proteins. The correlation between RET-fusion and patients' age, gender, smoking history, tumor stage, grade, pathologic type, and PD-L1, mismatch repair related protein expression was analyzed. Results: There were 22 cases (2.02%) detected with RET fusion-positive in 1 089 NSCLC patients, in which 11 males and 11 females; and the median age was 63.5 years. There were 20 adenocarcinomas, including 11 acinar predominant adenocarcinoma (APA), five solid predominant adenocarcinoma (SPA) and four lepidic predominant adenocarcinoma (LPA); There were one case each of squamous cell carcinoma (non-keratinizing type) and sarcomatoid carcinoma (pleomorphic carcinoma). There were 6 and 16 patients with RET fusion-positive who were in stage Ⅰ-Ⅱ and Ⅲ-Ⅳ respectively, and 16 cases with lymph node metastasis, 11 cases with distant metastasis. Among RET fusion-positive cases, one was detected with HER2 co-mutation. The tumor proportion score of PD-L1≥1% in patients with RET fusion positive lung cancer was 54.5% (12/22). Defects in mismatch repair protein expression were not found in patients with RET fusion positive NSCLC. Four patients with RET fusions positive (two cases of APA and two cases of SPA) received pratinib-targeted therapy, and two showed benefits from this targeted therapy. Conclusions: The histological subtypes of RET fusions positive NSCLC are more likely to be APA or SPA. RET fusion-positive NSCLC patients are associated with advanced clinical stage, lymph node metastases, and they may benefit from targeted therapy with RET-specific inhibitors.

A survival prediction model via interpretable machine learning for patients with oropharyngeal cancer following radiotherapy.

PURPOSE: To explore interpretable machine learning (ML) methods, with the hope of adding more prognosis value, for predicting survival for patients with Oropharyngeal-Cancer (OPC). METHODS: A cohort of 427 OPC patients (Training 341, Test 86) from TCIA database was analyzed. Radiomic features of gross-tumor-volume (GTV) extracted from planning CT using Pyradiomics, and HPV p16 status, etc. patient characteristics were considered as potential predictors. A multi-level dimension reduction algorithm consisting of Least-Absolute-Selection-Operator (Lasso) and Sequential-Floating-Backward-Selection (SFBS) was proposed to effectively remove redundant/irrelevant features. The interpretable model was constructed by quantifying the contribution of each feature to the Extreme-Gradient-Boosting (XGBoost) decision by Shapley-Additive-exPlanations (SHAP) algorithm. RESULTS: The Lasso-SFBS algorithm proposed in this study finally selected 14 features, and our prediction model achieved an area-under-ROC-curve (AUC) of 0.85 on the test dataset based on this feature set. The ranking of the contribution values calculated by SHAP shows that the top predictors that were most correlated with survival were ECOG performance status, wavelet-LLH_firstorder_Mean, chemotherapy, wavelet-LHL_glcm_InverseVariance, tumor size. Those patients who had chemotherapy, with positive HPV p16 status, and lower ECOG performance status, tended to have higher SHAP scores and longer survival; who had an older age at diagnosis, heavy drinking and smoking pack year history, tended to lower SHAP scores and shorter survival. CONCLUSION: We demonstrated predictive values of combined patient characteristics and imaging features for the overall survival of OPC patients. The multi-level dimension reduction algorithm can reliably identify the most plausible predictors that are mostly associated with overall survival. The interpretable patient-specific survival prediction model, capturing correlations of each predictor and clinical outcome, was developed to facilitate clinical decision-making for personalized treatment.