Study on Gesture Recognition Method with Two-Stream Residual Network Fusing sEMG Signals and Acceleration Signals.

Currently, surface EMG signals have a wide range of applications in human-computer interaction systems. However, selecting features for gesture recognition models based on traditional machine learning can be challenging and may not yield satisfactory results. Considering the strong nonlinear generalization ability of neural networks, this paper proposes a two-stream residual network model with an attention mechanism for gesture recognition. One branch processes surface EMG signals, while the other processes hand acceleration signals. Segmented networks are utilized to fully extract the physiological and kinematic features of the hand. To enhance the model's capacity to learn crucial information, we introduce an attention mechanism after global average pooling. This mechanism strengthens relevant features and weakens irrelevant ones. Finally, the deep features obtained from the two branches of learning are fused to further improve the accuracy of multi-gesture recognition. The experiments conducted on the NinaPro DB2 public dataset resulted in a recognition accuracy of 88.25% for 49 gestures. This demonstrates that our network model can effectively capture gesture features, enhancing accuracy and robustness across various gestures. This approach to multi-source information fusion is expected to provide more accurate and real-time commands for exoskeleton robots and myoelectric prosthetic control systems, thereby enhancing the user experience and the naturalness of robot operation.

Patient's Healthy-Limb Motion Characteristic-Based Assist-As-Needed Control Strategy for Upper-Limb Rehabilitation Robots.

The implementation of a progressive rehabilitation training model to promote patients' motivation efforts can greatly restore damaged central nervous system function in patients. Patients' active engagement can be effectively stimulated by assist-as-needed (AAN) robot rehabilitation training. However, its application in robotic therapy has been hindered by a simple determination method of robot-assisted torque which focuses on the evaluation of only the affected limb's movement ability. Moreover, the expected effect of assistance depends on the designer and deviates from the patient's expectations, and its applicability to different patients is deficient. In this study, we propose a control method with personalized treatment features based on the idea of estimating and mapping the stiffness of the patient's healthy limb. This control method comprises an interactive control module in the task-oriented space based on the quantitative evaluation of motion needs and an inner-loop position control module for the pneumatic swing cylinder in the joint space. An upper-limb endpoint stiffness estimation model was constructed, and a parameter identification algorithm was designed. The upper limb endpoint stiffness which characterizes the patient's ability to complete training movements was obtained by collecting surface electromyographic (sEMG) signals and human-robot interaction forces during patient movement. Then, the motor needs of the affected limb when completing the same movement were quantified based on the performance of the healthy limb. A stiffness-mapping algorithm was designed to dynamically adjust the rehabilitation training trajectory and auxiliary force of the robot based on the actual movement ability of the affected limb, achieving AAN control. Experimental studies were conducted on a self-developed pneumatic upper limb rehabilitation robot, and the results showed that the proposed AAN control method could effectively estimate the patient's movement needs and achieve progressive rehabilitation training. This rehabilitation training robot that simulates the movement characteristics of the patient's healthy limb drives the affected limb, making the intensity of the rehabilitation training task more in line with the patient's pre-morbid limb-use habits and also beneficial for the consistency of bilateral limb movements.

Targeting O-GlcNAcylation in cancer therapeutic resistance: The sugar Saga continues.

O-linked-N-acetylglucosaminylation (O-GlcNAcylation), a dynamic post-translational modification (PTM), holds profound implications in controlling various cellular processes such as cell signaling, metabolism, and epigenetic regulation that influence cancer progression and therapeutic resistance. From the therapeutic perspective, O-GlcNAc modulates drug efflux, targeting and metabolism. By integrating signals from glucose, lipid, amino acid, and nucleotide metabolic pathways, O-GlcNAc acts as a nutrient sensor and transmits signals to exerts its function on genome stability, epithelial-mesenchymal transition (EMT), cell stemness, cell apoptosis, autophagy, cell cycle. O-GlcNAc also attends to tumor microenvironment (TME) and the immune response. At present, several strategies aiming at targeting O-GlcNAcylation are under mostly preclinical evaluation, where the newly developed O-GlcNAcylation inhibitors markedly enhance therapeutic efficacy. Here we systematically outline the mechanisms through which O-GlcNAcylation influences therapy resistance and deliberate on the prospects and challenges associated with targeting O-GlcNAcylation in future cancer treatments.

Prioritization of risk genes in colorectal cancer by integrative analysis of multi-omics data and gene networks.

Genome-wide association studies (GWASs) have identified over 140 colorectal cancer (CRC)-associated loci; however, target genes at the majority of loci and underlying molecular mechanisms are poorly understood. Here, we utilized a Bayesian approach, integrative risk gene selector (iRIGS), to prioritize risk genes at CRC GWAS loci by integrating multi-omics data. As a result, a total of 105 high-confidence risk genes (HRGs) were identified, which exhibited strong gene dependencies for CRC and enrichment in the biological processes implicated in CRC. Among the 105 HRGs, CEBPB, located at the 20q13.13 locus, acted as a transcription factor playing critical roles in cancer. Our subsequent assays indicated the tumor promoter function of CEBPB that facilitated CRC cell proliferation by regulating multiple oncogenic pathways such as MAPK, PI3K-Akt, and Ras signaling. Next, by integrating a fine-mapping analysis and three independent case-control studies in Chinese populations consisting of 8,039 cases and 12,775 controls, we elucidated that rs1810503, a putative functional variant regulating CEBPB, was associated with CRC risk (OR=0.90, 95%CI=0.86-0.93, P=1.07×10-7). The association between rs1810503 and CRC risk was further validated in three additional multi-ancestry populations consisting of 24,254 cases and 58,741 controls. Mechanistically, the rs1810503 A to T allele change weakened the enhancer activity in an allele-specific manner to decrease CEBPB expression via long-range promoter-enhancer interactions, mediated by the transcription factor, REST, and thus decreased CRC risk. In summary, our study provides a genetic resource and a generalizable strategy for CRC etiology investigation, and highlights the biological implications of CEBPB in CRC tumorigenesis, shedding new light on the etiology of CRC.

Deep-learning-driven dose prediction and verification for stereotactic radiosurgical treatment of isolated brain metastases.

Purpose: While deep learning has shown promise for automated radiotherapy planning, its application to the specific scenario of stereotactic radiosurgery (SRS) for brain metastases using fixed-field intensity modulated radiation therapy (IMRT) on a linear accelerator remains limited. This work aimed to develop and verify a deep learning-guided automated planning protocol tailored for this scenario. Methods: We collected 70 SRS plans for solitary brain metastases, of which 36 cases were for training and 34 for testing. Test cases were derived from two distinct clinical institutions. The envisioned automated planning process comprised (1): clinical dose prediction facilitated by deep-learning algorithms (2); transformation of the forecasted dose into executable plans via voxel-centric dose emulation (3); validation of the envisaged plan employing a precise dosimeter in conjunction with a linear accelerator. Dose prediction paradigms were established by engineering and refining two three-dimensional UNet architectures (UNet and AttUNet). Input parameters encompassed computed tomography scans from clinical plans and demarcations of the focal point alongside organs at potential risk (OARs); the ensuing output manifested as a 3D dose matrix tailored for each case under scrutiny. Results: Dose estimations rendered by both models mirrored the manual plans and adhered to clinical stipulations. As projected by the dual models, the apex and average doses for OARs did not deviate appreciably from those delineated in the manual plan (P-value≥0.05). AttUNet showed promising results compared to the foundational UNet. Predicted doses showcased a pronounced dose gradient, with peak concentrations localized within the target vicinity. The executable plans conformed to clinical dosimetric benchmarks and aligned with their associated verification assessments (100% gamma approval rate at 3 mm/3%). Conclusion: This study demonstrates an automated planning technique for fixed-field IMRT-based SRS for brain metastases. The envisaged plans met clinical requirements, were reproducible across centers, and achievable in deliveries. This represents progress toward automated paradigms for this specific scenario.

Single-cell and bulk RNA sequencing analysis of B cell marker genes in TNBC TME landscape and immunotherapy.

Objective: This study amied to investigate the prognostic characteristics of triple negative breast cancer (TNBC) patients by analyzing B cell marker genes based on single-cell and bulk RNA sequencing. Methods: Utilizing single-cell sequencing data from TNBC patients, we examined tumor-associated B cell marker genes. Transcriptomic data from The Cancer Genome Atlas (TCGA) database were used as the foundation for predictive modeling. Independent validation set was conducted using the GSE58812 dataset. Immune cell infiltration into the tumor was assessed through various, including XCELL, TIMER, QUANTISEQ, CIBERSORT, CIBERSORT-ABS, and ssGSEA. The TIDE score was utilized to predict immunotherapy outcomes. Additional investigations were conducted on the immune checkpoint blockade gene, tumor mutational load, and the GSEA enrichment analysis. Results: Our analysis encompassed 22,106 cells and 20,556 genes in cancerous tissue samples from four TNBC patients, resulting in the identification of 116 B cell marker genes. A B cell marker gene score (BCMG score) involving nine B cell marker genes (ZBP1, SEL1L3, CCND2, TNFRSF13C, HSPA6, PLPP5, CXCR4, GZMB, and CCDC50) was developed using TCGA transcriptomic data, revealing statistically significant differences in survival analysis (P<0.05). Functional analysis demonstrated that marker genes were predominantly associated with immune-related pathways. Notably, substantial differences between the higher and lower- BCMG score groups were observed in terms of immune cell infiltration, immune cell activity, tumor mutational burden, TIDE score, and the expression of immune checkpoint blockade genes. Conclusion: This study has established a robust model based on B-cell marker genes in TNBC, which holds significant potential for predicting prognosis and response to immunotherapy in TNBC patients.

Genome-wide association analysis of left ventricular imaging-derived phenotypes identifies 72 risk loci and yields genetic insights into hypertrophic cardiomyopathy.

Left ventricular regional wall thickness (LVRWT) is an independent predictor of morbidity and mortality in cardiovascular diseases (CVDs). To identify specific genetic influences on individual LVRWT, we established a novel deep learning algorithm to calculate 12 LVRWTs accurately in 42,194 individuals from the UK Biobank with cardiac magnetic resonance (CMR) imaging. Genome-wide association studies of CMR-derived 12 LVRWTs identified 72 significant genetic loci associated with at least one LVRWT phenotype (P < 5 × 10-8), which were revealed to actively participate in heart development and contraction pathways. Significant causal relationships were observed between the LVRWT traits and hypertrophic cardiomyopathy (HCM) using genetic correlation and Mendelian randomization analyses (P < 0.01). The polygenic risk score of inferoseptal LVRWT at end systole exhibited a notable association with incident HCM, facilitating the identification of high-risk individuals. The findings yield insights into the genetic determinants of LVRWT phenotypes and shed light on the biological basis for HCM etiology.

Customized Trajectory Optimization and Compliant Tracking Control for Passive Upper Limb Rehabilitation.

Passive rehabilitation training in the early poststroke period can promote the reshaping of the nervous system. The trajectory should integrate the physicians' experience and the patient's characteristics. And the training should have high accuracy on the premise of safety. Therefore, trajectory customization, optimization, and tracking control algorithms are conducted based on a new upper limb rehabilitation robot. First, joint friction and initial load were identified and compensated. The admittance algorithm was used to realize the trajectory customization. Second, the improved butterfly optimization algorithm (BOA) was used to optimize the nonuniform rational B-spline fitting curve (NURBS). Then, a variable gain control strategy is designed, which enables the robot to track the trajectory well with small human-robot interaction (HRI) forces and to comply with a large HRI force to ensure safety. Regarding the return motion, an error subdivision method is designed to slow the return movement. The results showed that the customization force is less than 6 N. The trajectory tracking error is within 12 mm without a large HRI force. The control gain starts to decrease in 0.5 s periods while there is a large HRI force, thereby improving safety. With the decrease in HRI force, the real position can return to the desired trajectory slowly, which makes the patient feel comfortable.

New treatment insights into pancreatic acinar cell carcinoma: case report and literature review.

Pancreatic acinar cell carcinoma (PACC) is a rare pancreatic malignancy with unique clinical, molecular, and morphologic features. The long-term survival of patients with PACC is substantially better than that of patients with ductal adenocarcinoma of the pancreas. Surgical resection is considered the first choice for treatment; however, there is no standard treatment option for patients with inoperable disease. The patient with metastatic PACC reported herein survived for more than 5 years with various treatments including chemotherapy, radiotherapy, antiangiogenic therapy and combined immunotherapy.

Dosimetric impact of hollow intraoral stents for head and neck cancer radiotherapy: A phantom study.

PURPOSE: To investigate the dosimetric impact of the calculation boundaries and dose calculation algorithms of radiotherapy in head and neck cancer patients with an opened oral cavity connected to the exterior by a hollow intraoral positioning stent. METHODS AND MATERIALS: A homemade silicone phantom with an opened oral cavity was placed in a CIRS head phantom to model head and neck cancer patients with a hollow intraoral positioning stent. 3D-CRT plans were designed on CT images of the phantom in Monaco and Pinnacle3 treatment planning systems (TPSs) with the same beam parameters. The default boundary and manually extrapolated boundary were both adopted in these two TPSs to explore the dosimetric impact on treatment plans. The nanoDot™ optically stimulated luminescence dosimeters (OSLDs) were chosen to measure the planned dose surrounding the oral cavity of the head phantom after calibration. RESULT: The doses in the air cavity and two measuring points at the joint area were dramatically changed from 0.0, 92.4 and 148.8 cGy to 177.8, 244.2 and 244.1 cGy in Monaco after adopting the extrapolated boundary. While the calculated doses at the same place were changed from 61.2, 143.7 and 198.3 cGy to 175.4, 234.7 and 233.2 cGy in Pinnacle3 with a similar calculation boundary. For the Monaco TPS, the relative errors compared to the OSLD measured doses were 2.94 ± 1.93%, 0.53 ± 8.64%, 2.65 ± 1.87% and 3.93 ± 1.69% at 4 measuring positions. In contrast, the relative errors 4.03 ± 1.93%, 4.85 ± 8.64%, 7.61 ± 1.87% and 5.61 ± 1.69% were observed in Pinnacle3 . CONCLUSION: The boundary setting of an opened oral cavity in TPSs has a significant dosimetric impact on head and neck cancer radiotherapy. An extrapolated boundary should be manually set up to include the whole oral cavity in the dose calculation domain to avoid major dose deviations.

Bre1/RNF20 promotes Rad51-mediated strand exchange and antagonizes the Srs2/FBH1 helicases.

Central to homologous recombination (HR) is the assembly of Rad51 recombinase on single-strand DNA (ssDNA), forming the Rad51-ssDNA filament. How the Rad51 filament is efficiently established and sustained remains partially understood. Here, we find that the yeast ubiquitin ligase Bre1 and its human homolog RNF20, a tumor suppressor, function as recombination mediators, promoting Rad51 filament formation and subsequent reactions via multiple mechanisms independent of their ligase activities. We show that Bre1/RNF20 interacts with Rad51, directs Rad51 to ssDNA, and facilitates Rad51-ssDNA filament assembly and strand exchange in vitro. In parallel, Bre1/RNF20 interacts with the Srs2 or FBH1 helicase to counteract their disrupting effect on the Rad51 filament. We demonstrate that the above functions of Bre1/RNF20 contribute to HR repair in cells in a manner additive to the mediator protein Rad52 in yeast or BRCA2 in human. Thus, Bre1/RNF20 provides an additional layer of mechanism to directly control Rad51 filament dynamics.

Effect of radiotherapy interruption on nasopharyngeal cancer.

Nasopharyngeal carcinoma (NPC) is a malignant tumor originating from the epithelial cells of the nasopharynx with a unique geographic distribution, and is particularly prevalent in East and Southeast Asia. Due to its anatomical location, the surgery is difficult to access and the high sensitivity of nasopharyngeal cancer to radiotherapy (RT) makes it the main treatment modality. Radical radiotherapy is the first-line treatment for early-stage nasopharyngeal carcinoma and the cornerstone of multidisciplinary treatment for patients with locally advanced nasopharyngeal carcinoma. Nevertheless, radiotherapy interruption is inevitable as a consequence of unavoidable factors such as public holidays, machine malfunction, patient compliance, and adverse response to treatment, which in turn leads to a reduction in bioactivity and causes sublethal loss of tumor cells to repair. Unirradiated tumor cells are more likely to repopulate at or near their original fastest growth rate during this interval. If no measures are taken after the radiotherapy interruption, such as increasing the dose of radiotherapy and systemic therapy, the tumor is most likely to go uncontrolled and then progress. This review describes the effects of radiotherapy interruption on nasopharyngeal carcinoma, the mechanism of the effect, and explores the measures that can be taken in response to such interruption.

Co-profiling reveals distinct patterns of genomic chromatin accessibility and gene expression in pulmonary hypertension caused by chronic hypoxia.

INTRODUCTION: Aberrant gene expression is a key mechanism underlying pulmonary hypertension (PH) development. The alterations of genomic chromatin accessibility and their relationship with the aberrant gene expressions in PH are poorly understood. We used bulk Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) and RNA sequencing (RNA-seq) in pulmonary artery smooth muscle cells (PASMCs) of chronic hypoxia-exposed rats mimicking group 3 human PH. METHODS: Adult Sprague Dawley rats were commercially obtained from Hunan SJA (Hunan SJA Laboratory Animal Co., Changsha, China) and randomizedly allocated into four groups exposing to nomobaric hypoxia or normoxia for 1 or 28 days respectively. After the assessment of pulmonary hemodynamics, smooth muscle cells were isolated from intralobular arteries and simultaneously subjected to bulk Assay of ATAC-seq and RNA-seq. RESULTS: Hypoxic exposure for continuous 28-days, but not for 1-day, induced established PH phenotypes in rats. ATAC-seq revealed a major distribution of differential accessibility regions (DARs) annotated to the genome in out-of-promoter regions, following 1-day or 28-days hypoxia. 1188 DAR-associated genes and 378 differentially expressed genes (DEGs) were identified in rats after exposure to 1-day hypoxia, while 238 DAR-associated genes and 452 DEGs for 28-days hypoxia. Most of the DAR-associated genes or DEGs in 1-day did not overlap with that of 28-days hypoxia. A Pearson correlation analysis indicated no significant correlation between ATAC-seq and RNA-seq. CONCLUSIONS: The alterations in genomic chromatin accessibility and genes expression of PASMCs in the initial stage of hypoxia are distinct from the established stage of hypoxia-induced PH. The genomic differential accessibility regions may not be the main mechanisms directly underlying the differentially expressed genes observed either in the initial or established stages of PH. Thus the time-course alterations of gene expression and their possible indirect link with genomic chromatin accessibility warrant more attention in mechanistic study of pulmonary hypertension.

Biophysical cues to improve the immunomodulatory capacity of mesenchymal stem cells: The progress and mechanisms.

Mesenchymal stem cells (MSCs) can maintain immune homeostasis and many preclinical trials with MSCs have been carried out around the world. In vitro culture of MSCs has been found to result in the decline of immunomodulatory capacity, migration and proliferation. To address these problems, simulating the extracellular environment for preconditioning of MSCs is a promising and inexpensive method. Biophysical cues in the external environment that MSCs are exposed to have been shown to affect MSC migration, residency, differentiation, secretion, etc. We review the main ways in which MSCs exert their immunomodulatory ability, and summarize recent advances in mechanical preconditioning of MSCs to enhance immunomodulatory capacity and related mechanical signal sensing and transduction mechanisms.

Redox-associated messenger RNAs identify novel prognostic values and influence the tumor immune microenvironment of lung adenocarcinoma.

Background: An imbalance of redox homeostasis participates in tumorigenesis, proliferation, and metastasis, which results from the production of reactive oxygen species (ROS). However, the biological mechanism and prognostic significance of redox-associated messenger RNAs (ramRNAs) in lung adenocarcinoma (LUAD) still remain unclear. Methods: Transcriptional profiles and clinicopathological information were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) of LUAD patients. A total of 31 overlapped ramRNAs were determined, and patients were separated into three subtypes by unsupervised consensus clustering. Biological functions and tumor immune-infiltrating levels were analyzed, and then, differentially expressed genes (DEGs) were identified. The TCGA cohort was divided into a training set and an internal validation set at a ratio of 6:4. Least absolute shrinkage and selection operator regression were used to compute the risk score and determine the risk cutoff in the training set. Both TCGA and GEO cohort were distinguished into a high-risk or low-risk group at the median cutoff, and then, relationships of mutation characteristics, tumor stemness, immune differences, and drug sensitivity were investigated. Results: Five optimal signatures (ANLN, HLA-DQA1, RHOV, TLR2, and TYMS) were selected. Patients in the high-risk group had poorer prognosis, higher tumor mutational burden, overexpression of PD-L1, and lower immune dysfunction and exclusion score compared with the low-risk group. Cisplatin, docetaxel, and gemcitabine had significantly lower IC50 in the high-risk group. Conclusion: This study constructed a novel predictive signature of LUAD based on redox-associated genes. Risk score based on ramRNAs served as a promising biomarker for prognosis, TME, and anti-cancer therapies of LUAD.

Inguinal nodal clinical target volume delineation based on analysis of anatomical locations of normal and metastatic lymph nodes in pelvic malignant tumors.

PURPOSE: To optimize inguinal nodal clinical target volume (CTV) delineation based on analysis of the anatomical locations and embryonic development of normal and metastatic inguinal lymph nodes (ILNs) in patients with pelvic malignant tumors, including cervical, vaginal, vulvar, and anal tumors. MATERIALS AND METHODS: One hundred and eighty-one patients with pelvic malignancies and 415 involved ILNs treated with intensity-modulated radiation therapy were selected. First, the inguinal nodal CTV was divided into three fields as follows: I, horizontal superficial inguinal field; II, vertical superficial inguinal field; and III, deep inguinal field. Initial CTV delineation of each field was based on analysis of the anatomical locations and embryonic development of normal ILNs. Subsequently, the positions of metastatic ILNs relative to the proper anatomical landmarks or vessels were determined to optimally delineate the final ILN CTV contours. Eighty percent of the data acquired (n = 145) were used as test data for optimization and analysis, the remaining 20% (n = 36) were used for delineation validation. RESULTS: In total, 252 positive ILNs in 103 cervical cancer patients, 94 positive ILNs in 41 vulvar cancer patients, 8 positive ILNs in 3 vaginal cancer patients, and 61 positive ILNs in 34 anal cancer patients were enrolled. Detailed target volume contouring guidelines for the three divisions were determined on images. All positive ILNs from the remaining 20% patients were located in the CTV boundaries delineated based on analysis of 80% of the data acquired. Importantly, the final inguinal nodal CTV field determined using our method was substantially smaller than defined by existing atlases, and the femoral vessels were excluded in the delineation. CONCLUSIONS: This study provided anatomical, embryonic, surgical, and statistical evidence to facilitate ILN CTV delineation in radiotherapy planning for patients with pelvic malignancies.

Radiotherapy Improves Survival of Patients With Lymphovascular Invasion in pT1b Esophageal Squamous Cell Cancer After Endoscopic Submucosal Dissection.

INTRODUCTION: Adjuvant radiotherapy is recommended for pT1b esophageal squamous cell cancer (ESCC) after endoscopic submucosal dissection (ESD). However, it is unclear whether additional radiotherapy can improve patient survival. This study aimed to evaluate the efficacy of adjuvant radiotherapy after ESD for pT1b ESCC. METHODS: This was a multicenter, cross-sectional study involving 11 hospitals in China. Between January 2010 and December 2019, patients with T1bN0M0 ESCC treated with or without adjuvant radiotherapy after ESD were included. Survival between groups was compared. RESULTS: Overall, 774 patients were screened, and 161 patients were included. Forty-seven patients (29.2%) received adjuvant radiotherapy after ESD (RT group) and 114 (70.8%) underwent ESD alone (non-RT group). There were no significant differences in overall survival (OS) and disease-free survival (DFS) between the RT and non-RT groups. Lymphovascular invasion (LVI) was the only prognostic factor. In the LVI+ group, adjuvant radiotherapy significantly improved survival (5-year OS: 91.7% vs 59.5%, P = 0.050; 5-year DFS: 92.9% vs 42.6%, P = 0.010). In the LVI- group, adjuvant radiotherapy did not improve survival (5-year OS: 83.5% vs 93.9%, P = 0.148; 5-year DFS: 84.2% vs 84.7%, P = 0.907). The standardized mortality ratios were 1.52 (95% confidence interval 0.04-8.45) in the LVI+ group with radiotherapy and 0.55 (95% confidence interval 0.15-1.42) in the LVI- group without radiotherapy. DISCUSSION: Adjuvant radiotherapy could improve survival in pT1b ESCC with LVI+ other than LVI- after ESD. Selective adjuvant radiotherapy based on LVI status achieved survival rates similar to those of the general population.

Design, synthesis and pharmacological evaluation of ß-carboline derivatives as potential antitumor agent via targeting autophagy.

A series of novel ß-carboline derivatives was designed, synthesized and evaluated as potential anticancer agents. Among them, compound 6g showed the most potent antiproliferative activity against the 786-0, HT-29 and 22RV1 cell lines with IC50 values of 2.71, 2.02, and 3.86 µM, respectively. The antitumor efficiency of compound 6gin vivo was also evaluated, and the results revealed that compound 6g significantly suppressed tumor development and reduced tumor weight in a mouse colorectal cancer homograft model. Further investigation on mechanisms of action demonstrated that compound 6g inhibited HCT116 cell growth by stimulating the ATG5/ATG7-dependent autophagic pathway. These molecules might be served as candidates for further development of colorectal cancer therapy agent.

Establishment and validation of a prognostic nomogram for extrahepatic cholangiocarcinoma.

Simple summary: Accurately estimate the prognosis of patients with ECCA is important. However, the TNM system has some limitations, such as low accuracy, exclusion of other factors (e.g., age and sex), and poor performance in predicting individual survival risk. In contrast, a nomogram-based clinical model related to a comprehensive analysis of all risk factors is intuitive and straightforward, facilitating the probabilistic analysis of tumor-related risk factors. Simultaneously, a nomogram can also effectively drive personalized medicine and facilitate clinicians for prognosis prediction. Therefore, we construct a novel practical nomogram and risk stratification system to predict CSS in patients with ECCA. Background: Accurately estimate the prognosis of patients with extrahepatic cholangiocarcinoma (ECCA) was important, but the existing staging system has limitations. The present study aimed to construct a novel practical nomogram and risk stratification system to predict cancer-specific survival (CSS) in ECCA patients. Methods: 3415 patients diagnosed with ECCA between 2010 and 2015 were selected from the SEER database and randomized into a training cohort and a validation cohort at 7:3. The nomogram was identified and calibrated using the C-index, receiver operating characteristic curve (ROC), and calibration plots. Decision curve analysis (DCA), net reclassification index (NRI), integrated discrimination improvement (IDI) and the risk stratification were used to compare the nomogram with the AJCC staging system. Results: Nine variables were selected to establish the nomogram. The C-index (training cohort:0.785; validation cohort:0.776) and time-dependent AUC (>0.7) showed satisfactory discrimination. The calibration plots also revealed that the nomogram was consistent with the actual observations. The NRI (training cohort: 1-, 2-, and 3-year CSS:0.27, 0.27,0.52; validation cohort:1-,2-,3-year CSS:0.48,0.13,0.34), IDI (training cohort: 1-, 2-, 3-year CSS:0.22,0.18,0.16; validation cohort: 1-,2-,3-year CSS:0.18,0.16,0.17), and DCA indicated that the established nomogram significantly outperformed the AJCC staging system (P<0.05) and had better recognition compared to the AJCC staging system. Conclusions: We developed a practical prognostic nomogram to help clinicians assess the prognosis of patients with ECCA.

Introduce a rotational robust optimization framework for spot-scanning proton arc (SPArc) therapy.

Objective. Proton dosimetric uncertainties resulting from the patient's daily setup errors in rotational directions exist even with advanced image-guided radiotherapy techniques. Thus, we developed a new rotational robust optimization SPArc algorithm (SPArcrot) to mitigate the dosimetric impact of the rotational setup error in Raystation ver. 6.02 (RaySearch Laboratory AB, Stockholm, Sweden).Approach.The initial planning CT was rotated ±5° simulating the worst-case setup error in the roll direction. The SPArcrotuses a multi-CT robust optimization framework by taking into account of such rotational setup errors. Five cases representing different disease sites were evaluated. Both SPArcoriginaland SPArcrotplans were generated using the same translational robust optimized parameters. To quantitatively investigate the mitigation effect from the rotational setup errors, all plans were recalculated using a series of pseudo-CT with rotational setup error (±1°/±2°/±3°/±5°). Dosimetric metrics such as D98% of CTV, and 3D gamma analysis were used to assess the dose distribution changes in the target and OARs.Main results.The magnitudes of dosimetric changes in the targets due to rotational setup error were significantly reduced by the SPArcrotcompared to SPArc in all cases. The uncertainties of the max dose to the OARs, such as brainstem, spinal cord and esophagus were significantly reduced using SPArcrot. The uncertainties of the mean dose to the OARs such as liver and oral cavity, parotid were comparable between the two planning techniques. The gamma passing rate (3%/3 mm) was significantly improved for CTV of all tumor sites through SPArcrot.Significance.Rotational setup error is one of the major issues which could lead to significant dose perturbations. SPArcrotplanning approach can consider such rotational error from patient setup or gantry rotation error by effectively mitigating the dose uncertainties to the target and in the adjunct series OARs.