A novel fast robust optimization algorithm for intensity-modulated proton therapy with minimum monitor unit constraint.

BACKGROUND: Intensity-modulated proton therapy (IMPT) optimizes spot intensities and position, providing better conformability. However, the successful application of IMPT is dependent upon addressing the challenges posed by range and setup uncertainties. In order to address the uncertainties in IMPT, robust optimization is essential. PURPOSE: This study aims to develop a novel fast algorithm for robust optimization of IMPT with minimum monitor unit (MU) constraint. METHODS AND MATERIALS: The study formulates a robust optimization problem and proposes a novel, fast algorithm based on the alternating direction method of multipliers (ADMM) framework. This algorithm enables distributed computation and parallel processing. Ten clinical cases were used as test scenarios to evaluate the performance of the proposed approach. The robust optimization method (RBO-NEW) was compared with plans that only consider nominal optimization using CTV (NMO-CTV) without handling uncertainties and PTV (NMO-PTV) to handle the uncertainties, as well as with conventional robust-optimized plans (RBO-CONV). Dosimetric metrics, including D95, homogeneity index, and Dmean, were used to evaluate the dose distribution quality. The area under the root-mean-square dose (RMSD)-volume histogram curves (AUC) and dose-volume histogram (DVH) bands were used to evaluate the robustness of the treatment plan. Optimization time cost was also assessed to measure computational efficiency. RESULTS: The results demonstrated that the RBO plans exhibited better plan quality and robustness than the NMO plans, with RBO-NEW showing superior computational efficiency and plan quality compared to RBO-CONV. Specifically, statistical analysis results indicated that RBO-NEW was able to reduce the computational time from 389.70 ± 207.40 $389.70\pm 207.40$ to 228.60 ± 123.67 $228.60\pm 123.67$ s ( p < 0.01 $p<0.01$ ) and reduce the mean organ-at-risk (OAR) dose from 9.38 ± 12.80 $9.38\pm 12.80$ % of the prescription dose to 9.07 ± 12.39 $9.07\pm 12.39$ % of the prescription dose ( p < 0.05 $p<0.05$ ) compared to RBO-CONV. CONCLUSION: This study introduces a novel fast robust optimization algorithm for IMPT treatment planning with minimum MU constraint. Such an algorithm is not only able to enhance the plan's robustness and computational efficiency without compromising OAR sparing but also able to improve treatment plan quality and reliability.

Characterization of the malignant cells and microenvironment of infantile fibrosarcoma via single-cell RNA sequencing.

Background: Infantile fibrosarcoma (IFS) is the most prevalent soft tissue sarcoma in children under 1 year old and is known for its rapid growth. The tumor lacks specific immunohistochemical tumor marker and a general view of tumor microenvironment (TME). Its primary therapeutic intervention places patients at a risk of disability or mutilation. This study aimed to elucidate the universal transcriptional characteristics of IFS and explore novel targets for diagnosis and therapy using single-cell RNA sequencing (scRNA-seq). Methods: Fresh tissue samples of IFS for scRNA-seq were collected from four patients before other treatments were administered. We conducted cell clustering, inferring copy number variation from scRNA-seq (InferCNV) analysis, gene differential expression analysis, cell function evaluation, Pearson correlation analysis, and cell-cell and ligand-receptor interaction analysis to investigate the distinct ecosystem of IFS. Results: According to the single-cell resolution data, we depicted the cell atlas of IFS, which comprised 14 cell populations. Through comparison with normal cells, the malignant cells were distinguished, and potential novel markers (POSTN, IGFBP2 and CTHRC1) were identified. We also found four various functional malignant cell subtypes, three of which exhibited cancer stem cells (CSCs) phenotypes, and investigated the interplay between these subtypes and nonmalignant cells in the TME of IFS. Endothelial cells and macrophages were found to dominate the cell-cell communication landscape within the microenvironment, promoting tumorigenesis via multiple receptor-ligand interactions. Conclusions: This study provides a comprehensive characterization of the tumor transcriptome and TME of IFS at the cellular level, offering valuable insights for clinically significant advancements in the immunohistochemical diagnosis and treatment of IFS.

Optimizing linear energy transfer distribution in intensity-modulated proton therapy using the alternating direction method of multipliers.

Purpose: This study develop a novel linear energy transfer (LET) optimization method for intensity-modulated proton therapy (IMPT) with minimum monitor unit (MMU) constraint using the alternating direction method of multipliers (ADMM). Material and methods: The novel LET optimization method (ADMM-LET) was proposed with (1) the dose objective and the LET objective as the optimization objective and (2) the non-convex MMU threshold as a constraint condition. ADMM was used to solve the optimization problem. In the ADMM-LET framework, the optimization process entails iteratively solving the dose sub-problem and the LET sub-problem, simultaneously ensuring compliance with the MMU constraint. Three representative cases, including brain, liver, and prostate cancer, were utilized to evaluate the performance of the proposed method. The dose and LET distributions from ADMM-LET were compared to those obtained using the published iterative convex relaxation (ICR-LET) method. Results: The results demonstrate the superiority of ADMM-LET over ICR-LET in terms of LET distribution while achieving a comparable dose distribution. More specifically, for the brain case, the maximum LET (unit: keV/µm) at the optic nerve decreased from 5.45 (ICR-LET) to 1.97 (ADMM-LET). For the liver case, the mean LET (unit: keV/µm) at the clinical target volume increased from 4.98 (ICR-LET) to 5.50 (ADMM-LET). For the prostate case, the mean LET (unit: keV/µm) at the rectum decreased from 2.65 (ICR-LET) to 2.14 (ADMM-LET). Conclusion: This study establishes ADMM-LET as a new approach for LET optimization with the MMU constraint in IMPT, offering potential improvements in treatment outcomes and biological effects.

Single-cell landscape of undifferentiated pleomorphic sarcoma.

Undifferentiated pleomorphic sarcoma (UPS) is a highly aggressive malignant soft tissue tumor with a poor prognosis; however, the identity and heterogeneity of tumor populations remain elusive. Here, eight major cell clusters were identified through the RNA sequencing of 79,569 individual cells of UPS. UPS originates from mesenchymal stem cells (MSCs) and features undifferentiated subclusters. UPS subclusters were predicted to exist in two bulk RNA datasets, and had a prognostic value in The Cancer Genome Atlas (TCGA) dataset. The functional heterogeneity of malignant UPS cells and the immune microenvironment were characterized. Additionally, the fused cells were innovatively detected by expressing both monocyte/macrophage markers and other subcluster-associated genes. Based on the ligand-receptor interaction analysis, cellular interactions with epidermal growth factor receptor (EGFR) and vascular endothelial growth factor receptor (VEGFR) were abundant. Furthermore, 73% of patients with UPS (48/66) showed positive EGFR expression, which was associated with a poor prognosis. EGFR blockade with cetuximab inhibited tumor growth in a patient-derived xenograft model. Our transcriptomic studies delineate the landscape of UPS intratumor heterogeneity and serve as a foundational resource for further discovery and therapeutic exploration.

The potential mechanism of Aidi injection against neuroblastoma-an investigation based on network pharmacology analysis.

Background: Aidi injection, a classic traditional Chinese medicine (TCM) formula, has been used on a broader scale in treating a variety of cancers. In this study, we aimed to explore the potential anti-tumor effects of Aidi injection in the treatment of neuroblastoma (NB) using network pharmacology (NP). Methods: To elucidate the anti-NB mechanism of Aidi injection, an NP-based approach and molecular docking validation were employed. The compounds and target genes were collected from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database and Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine (BATMAN-TCM) database. The protein-protein interaction network was constructed using the STRING database. clusterProfiler (R package) was utilized to annotate the bioinformatics of hub target genes. The gene survival analysis was performed on R2, a web-based genomic analysis application. iGEMDOCK was used for molecular docking validation, and GROMACS was utilized to validate molecular docking results. Furthermore, we investigated the anticancer effects of gomisin B and ginsenoside Rh2 on human NB cells using a cell viability assay. The Western blot assay was used to validate the protein levels of target genes in gomisin B- and ginsenoside Rh2-treated NB cells. Results: A total of 2 critical compounds with 16 hub target genes were identified for treating NB. All 16 hub genes could potentially influence the survival of NB patients. The top three genes (EGFR, ESR1, and MAPK1) were considered the central hub genes from the drug-compound-hub target gene-pathway network. The endocrine resistance and estrogen signaling pathways were identified as the therapeutic pathways using the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Gomisin B and ginsenoside Rh2 showed a good binding ability to the target protein in molecular docking. The results of cell experiments showed the anti-NB effect of gomisin B and ginsenoside Rh2. In addition, the administration of gomisin B over-regulated the expression of ESR1 protein in MYCN-amplified NB cells. Conclusion: In the present study, we investigated the potential pharmacological mechanisms of Aidi against NB and revealed the anti-NB effect of gomisin B, providing clinical evidence of Aidi in treating NB and establishing baselines for further research.

Feasibility study of multiple-energy Bragg peak proton FLASH on a superconducting gantry with large momentum acceptance.

BACKGROUND: While the Bragg peak proton beam (BP) is capable of superior target conformity and organs-at-risk sparing than the transmission proton beam (TB), its efficacy in FLASH-RT is hindered by both a slow energy switching process and the beam current. A universal range shifter (URS) can pull back the high-energy proton beam while preserving the beam current. Meanwhile, a superconducting gantry with large momentum acceptance (LMA-SC gantry) enables fast energy switching. PURPOSE: This study explores the feasibility of multiple-energy BP FLASH-RT on the LMA-SC gantry. METHOD AND MATERIALS: A simultaneous dose and spot map optimization algorithm was developed for BP FLASH-RT treatment planning to improve the dose delivery efficiency. The URS was designed to be 0-27 cm thick, with 1 cm per step. BP plans using the URS were optimized using single-field optimization (SFO) and multiple-field optimization (MFO) for ten prostate cancer patients and ten lung cancer patients. The plan delivery parameters, dose, and dose rate metrics of BP plans were compared to those of TB plans using the parameters of the LMA-SC gantry. RESULTS: Compared to TB plans, BP plans significantly reduced MUs by 42.7% (P < 0.001) with SFO and 33.3% (P < 0.001) with MFO for prostate cases. For lung cases, the reduction in MUs was 56.8% (P < 0.001) with SFO and 36.4% (P < 0.001) with MFO. BP plans also outperformed TB plans by reducing mean normal tissue doses. BP-SFO plans achieved a reduction of 56.7% (P < 0.001) for prostate cases and 57.7% (P < 0.001) for lung cases, while BP-MFO plans achieved a reduction of 54.2% (P < 0.001) for the prostate case and 40.0% (P < 0.001) for lung cases. For both TB and BP plans, normal tissues in prostate and lung cases received 100.0% FLASH dose rate coverage (>40 Gy/s). CONCLUSIONS: By utilizing the URS and the LMA-SC gantry, it is possible to perform multiple-energy BP FLASH-RT, resulting in better normal tissue sparing, as compared to TB plans.

Establishment of Biliary Atresia Prognostic Classification System via Survival-Based Forward Clustering - A New Biliary Atresia Classification.

OBJECTIVES: To develop a machine learning algorithm with prognosis data to identify different clinical phenotypes of biliary atresia (BA) and provide instructions for choosing treatment schemes. METHODS: Six hundred thirty-nine cases of type III BA were retrospectively collected from the Children's Hospital of Fudan University from Jan 1st, 2017 to Dec 1st, 2019 as a training dataset, and a survival-based forward clustering method, which can also be used to predict the subtype of a new patient was developed to identify BA subtypes. RESULTS: A total of 2 clusters were identified (cluster 1 = 324 and cluster 2 = 315), where cluster 2 had a lower 2 y native liver survival post-Kasai rate. The infant patients in cluster 2 have higher weight, liver, and spleen volume, wider portal vein width, and older operative age; worse coagulation and liver function results; higher grade of liver fibrosis and detection rate of hepatic portal fibrous mass, and higher recent infection detection rate of herpes simplex virus type I. With the proposed prognostic classification system, the authors predicted the subtypes of the 187 cases of type III BA in a testing dataset collected from the whole year of 2020. The p-value computed from the log-rank testing for the Kaplan-Meier survival curves of the predicted two testing groups was 0.0113. CONCLUSIONS: This classification system would be a convenient tool to choose appropriate treatment and accelerate the choice-making between clinicians and infant patients.

Deciphering pathological behavior of pediatric medullary thyroid cancer from single-cell perspective.

Background: Pediatric medullary thyroid cancer (MTC) is one of the rare pediatric endocrine neoplasms. Derived from C cells of thyroid glands, MTC is more aggressive and more prompt to metastasis than other types of pediatric thyroid cancer. The mechanism remains unclear. Methods: We performed single-cell transcriptome sequencing on the samples of the primary tumor and metastases lymph nodes from one patient diagnosed with MTC, and it is the first single-cell transcriptome sequencing data of pediatric MTC. In addition, whole exome sequencing was performed and peripheral blood was regarded as a normal reference. All cells that passed quality control were merged and analyzed in R to discover the association between tumor cells and their microenvironment as well as tumor pathogenesis. Results: We first described the landscape of the single-cell atlas of MTC and studied the interaction between the tumor cell and its microenvironment. C cells, identified as tumor cells, and T cells, as the dominant participant in the tumor microenvironment, were particularly discussed in their development and interactions. In addition, the WES signature of tumor cells and their microenvironment were also described. Actively immune interactions were found, indicating B cells, T cells and myeloid cells were all actively participating in immune reaction in MTC. T cells, as the major components of the tumor microenvironment, proliferated in MTC and could be divided into clusters that expressed proliferation, immune effectiveness, and naive markers separately.

MiT family translocation renal cell carcinoma with retroperitoneal metastasis in childhood: a case report.

RCC accounts for only 0.1%-0.3% of all kidney tumors and 2%-6% of malignant kidney tumors in children. Accounting for approximately one-third of the total number of cases in children and adolescents with RCC, Xp11.2 tRCC is the most common subtype of the MiT family translocation renal cell carcinoma, which is a group of rare childhood and adult tumors, characterized by recurrent gene rearrangements of TFE3. Here we report a rare case of a 6-year-old male patient with MiT family translocation renal cell carcinoma (MiTF tRCC) where the patient developed retroperitoneal metastasis. The patient underwent partial nephrectomy (PN), radical nephrectomy (RN), abdominal lymph node resection, and intestinal adhesion lysis. Microscopically, we detected focal and nest clump-shaped clusters of tumor cells whose cytoplasm was bright and clear. Immunohistochemistry (IHC) showed tumor cells diffusely expressed TFE3, and fluorescence in situ hybridization (FISH) demonstrated disruption of the TFE3 locus, confirming the diagnosis of Xp11.2 tRCC, the most common subtype of MiTF tRCC. Eventually, the patient obtained a good therapeutic result. This case can provide a good reference and guidance for pediatric urologists and oncologists to recognize and diagnose rare renal cell carcinoma in children.

A Novel Ultrahigh-Dose-Rate Proton Therapy Technology: Spot-Scanning Proton Arc Therapy + FLASH (SPLASH).

PURPOSE: To take full advantage of FLASH dose rate (40 Gy/s) and high-dose conformity, we introduce a novel optimization and delivery technique, the spot-scanning proton arc therapy (SPArc) + FLASH (SPLASH). METHODS AND MATERIALS: SPLASH framework was implemented in an open-source proton planning platform (MatRad, Department of Medical Physics in Radiation Oncology, German Cancer Research Center). It optimizes with the clinical dose-volume constraint based on dose distribution and the dose-average dose rate by minimizing the monitor unit constraint on spot weight and accelerator beam current sequentially, enabling the first dynamic arc therapy with voxel-based FLASH dose rate. This new optimization framework minimizes the overall cost function value combined with plan quality and voxel-based dose-rate constraints. Three representative cases (brain, liver, and prostate cancer) were used for testing purposes. Dose-volume histogram, dose-rate-volume histogram, and dose-rate map were compared among intensity modulated proton radiation therapy (IMPT), SPArc, and SPLASH. RESULTS: SPLASH/SPArc could offer superior plan quality over IMPT in terms of dose conformity. The dose-rate-volume histogram results indicated SPLASH could significantly improve V40 Gy/s in the target and region of interest for all tested cases compared with SPArc and IMPT. The optimal beam current per spot is simultaneously generated, which is within the existing proton machine specifications in the research version (<200 nA). CONCLUSIONS: SPLASH offers the first voxel-based ultradose-rate and high-dose conformity treatment using proton beam therapy. Such a technique has the potential to fit the needs of a broad range of disease sites and simplify clinical workflow without applying a patient-specific ridge filter, which has never before been demonstrated.

An energy minimization strategy based on an improved nonlinear conjugate gradient method for accelerating the charged polymer dynamics simulation.

Using a hybrid simulation method that combines a non-linear conjugate gradient (NCG) method for solving large-scale unconstrained optimization problems with a Brownian dynamics (BD) model for polymer chains, we investigate the pre-equilibrium simulation of charged polymers in different dielectric systems from an energy minimization perspective. We propose an improved NCG coefficient (ßLPRPk) that satisfies a sufficient descent condition with a greater parameter under a strong Wolfe line search and converges globally for nonconvex minimization. Furthermore, preliminary numerical results show that the ßLPRPk coefficient is more efficient than many existing NCG coefficients for a large number of practical test problems from our model. We further compare the performance of the improved NCG method with that of other mainstream numerical methods in energy minimization, and the simulation results suggest that the NCG method is more competitive in terms of cost-effectiveness. Importantly, we apply the geometrically optimized configuration obtained by performing the NCG method to the pre-equilibrium simulation, and the numerical results show that it increases the computational efficiency of a pure solvent and biomolecule-solution systems at most by about 32 and 70 times, respectively, with the relative energy errors being controlled below 1 × 10-2 and 4.5 × 10-3, respectively. More importantly, the final pre-equilibrium configuration of the BD simulation that performs energy minimization and the traditional BD simulation matched closely.

BACH1-induced ferroptosis drives lymphatic metastasis by repressing the biosynthesis of monounsaturated fatty acids.

Esophageal squamous cell carcinoma (ESCC) is one of the fatal malignancies worldwide. It has an increased propensity to metastasize via lymphogenous routes in an early stage. The prognosis of patients with lymph node metastases (LNM) is often worse than that of patients without metastases. Although several factors have been found to influence metastasis, the mechanisms of preference for specific metastatic routes remain poorly understood. Herein, we provide evidence that the intrinsic hypersensitivity of tumor cells to ferroptosis may proactively drive lymphatic metastasis. Serum autoantibodies associated with LNM of early ESCC were screened using a whole-proteome protein array containing 19 394 human recombinant proteins, and an anti-BACH1 autoantibody was first identified. Pan-cancer analysis of ferroptosis-related genes with preferential lymphatic metastasis and preferential hematogenous metastasis based on The Cancer Genome Atlas data was performed. Only BACH1 showed significant overexpression in tumors with preferential lymphatic metastasis, whereas it was downregulated in most tumors with preferential nonlymphatic metastasis. In addition, it was found that the serum levels of autoantibodies against BACH1 were elevated in early-stage patients with LNM. Interestingly, BACH1 overexpression and ferroptosis induction promoted LNM but inhibited hematogenous metastasis in mouse models. Transcriptomic and lipidomic analyses found that BACH1 repressed SCD1-mediated biosynthesis of monounsaturated fatty acids, especially oleic acid (OA). OA significantly attenuated the ferroptotic phenotypes and reversed the metastatic properties of BACH1-overexpressing cells. OA addition significantly rescued the ferroptotic phenotypes and reversed the metastatic properties of BACH1-overexpressing cells. Importantly, the concentration gradient of OA between primary lesions and the lymph resulted in the chemoattraction of tumor cells to promote invasion, thus facilitating lymphatic metastasis. BACH1-induced ferroptosis drives lymphatic metastasis via the BACH1-SCD1-OA axis. More importantly, this study confirms that ferroptosis is a double-edged sword in tumorigenesis and tumor progression. The clinical application of ferroptosis-associated agents requires a great caution.

Progress of oncolytic virotherapy for neuroblastoma.

As a neuroendocrine tumor derived from the neural crest, neuroblastoma (NB) is the most common extracranial solid tumor in children. The prognosis in patients with low- and intermediate-risk NB is favorable while that in high-risk patients is often detrimental. However, the management of the considerably large proportion of high-risk patients remains challenging in clinical practice. Among various new approaches, oncolytic virus (OV) therapy offers great advantages in tumor treatment, especially for high-risk NB. Genetic modified OVs can target NB specifically without affecting normal tissue and avoid the widespread drug resistance issue in anticancer monotherapy. Meanwhile, its safety profile provides great potential in combination therapy with chemo-, radio-, and immunotherapy. The therapeutic efficacy of OV for NB is impressive from bench to bedside. The effectiveness and safety of OVs have been demonstrated and reported in studies on children with NB. Furthermore, clinical trials on some OVs (Celyvir, Pexa-Vec (JX-594) and Seneca Valley Virus (NTX-010)) have reported great results. This review summarizes the latest evidence in the therapeutic application of OVs in NB, including those generated in cell lines, animal models and clinical trials.

Single-cell and spatial transcriptomics reveal the fibrosis-related immune landscape of biliary atresia.

BACKGROUND: Biliary atresia (BA) is a devastating inflammatory and fibrosing cholangiopathy of neonates with unknown aetiology. We aim to investigate the relationship between these two main characteristics. METHODS: Single-cell RNA sequencing and spatial transcriptomics were performed on liver samples from a cohort of 14 objects (BA: n = 6; control: n = 8). We conducted data integration and cell-type annotation based on gene expression profiling. Furthermore, we identified fibrosis-related immune cells according to their spatial locations, GO and KEGG analysis. Finally, SPOTlight and CIBERSORTx were used to deconvolute ST data and microarray data of the GSE46960 cohorts, respectively. RESULTS: Immune subpopulations inhabiting the 'fibrotic niche' (areas of scarring), comprising 'intermediate' CD14++ CD16+ monocytes, scar-associated macrophages, natural killer T cells, transitional B cells and FCN3+ neutrophils were identified. GO and KEGG analyses showed that pathways including 'positive regulation of smooth muscle cell/fibroblast proliferation' and 'positive regulation of/response to VEGFR/VEGF/EGFR/FGF' were enriched in these cell types. Interactions analysis showed that communication among 'FGF_FGFR', 'RPS19-C5AR1', 'CD74_COPA/MIF/APP' and 'TNFRSF1A/B_GRN' was extensive. Finally, the results of deconvolution for ST data and microarray data validated that the proportions of certain identified fibrosis-related cell types we identified were increased in BA. DISCUSSION: Fibrosis is an important feature of BA, in which the immune system plays an important role. Our work reveals the subpopulations of immune cells enriched in the fibrotic niche of BA liver, as well as key related pathways and molecules; some are highlighted for the first time in liver fibrosis. These newly identified interactions might partly explain why the rate of liver fibrosis occurs much faster in BA than in other liver diseases. CONCLUSION: Our study revealed the molecular, cellular and spatial immune microenvironment of the fibrotic niche of BA.

The Cellular and Molecular Landscape of Synchronous Pediatric Sialoblastoma and Hepatoblastoma.

Sialoblastoma (SBL) is an infrequent embryonal malignant tumor originating from the salivary gland, resembling primitive salivary gland anlage, whereas hepatoblastoma (HB) is the most common pediatric liver malignancy. The simultaneous occurrence of both tumors is extremely rare. Here we reported a case of a 6-month-old infant diagnosed with synchronous SBL and HB. The patient received neoadjuvant chemotherapy followed by surgical resection. Fresh tissues of both tumors were collected before and after chemotherapy, which were further profiled by whole exome sequencing (WES) and single-cell RNA sequencing (scRNA-seq). WES analysis revealed potential somatic driver mutation PIK3CA p.Glu454Lys for SBL and canonical mutation CTNNB1 p.Ser45Pro for HB. No shared somatic variants or common copy number alterations were found between SBL and HB primary tumor samples. Though scRNA-seq, single-cell atlases were constructed for both tumors. SBL may recapitulate a pre-acinar stage in the development of salivary gland, including basaloid, duct-like, myoepithelial-like, and cycling phenotypes. In the meantime, HB was composed of tumor cells resembling different stages of the liver, including hepatocyte-like, hepatic progenitor-like, and hepatoblast-like cells. After chemotherapy, both tumors were induced into a more mature phenotype. In terms of transcriptional signatures, SBL and HB showed enhanced expression of epithelial markers KRT8, KRT18, and essential embryo development genes SDC1, MDK, indicating the disruption of normal embryo epithelium development. Finally, heterozygous deleterious germline mutation BLM and FANCI were identified which could predispose the patient to higher cancer risk. It partially explained the reason for the co-occurrence of SBL and HB. Taken together, we provided valuable resources for deciphering cellular heterogeneity and adaptive change of tumor cells after chemotherapy for synchronous SBL and HB, providing insights into the mechanisms leading to synchronous pediatric tumors.

Gamma-glutamyl transpeptidase has different efficacy on biliary atresia diagnosis in different hospital patient groups: an application of machine learning approach.

OBJECTIVES: Gamma-glutamyl transpeptidase (GGT) is the most widely used biomarker in the early diagnosis of biliary atresia (BA), but its diagnostic efficacy is questionable in different sub-populations. We aim to identify subgroups that are defined by specific variables with cut-offs and can significantly affect the diagnostic efficacy of GGT for detecting BA. METHODS: Clinical data from 1273 infants with neonatal obstructive jaundice (NOJ) diagnosed between January 2012 and December 2017 at the Children's Hospital of Fudan University were enrolled, reviewed, and analyzed. Random forest-based Virtual Twins method was used to identify potential subgroups. RESULTS: Hemoglobin (HGB) and fasting gallbladder filling were selected as defining variables. The diagnostic efficacy of GGT was significantly better (AUC = 0.855) for patients with hemoglobin (HGB) ≤ 105 g/L and a gallbladder that was not or poorly filled. Diagnostic efficacy was worst in the subgroup defined by HGB > 105 g/L (AUC = 0.722). The inclusion of interaction terms between GGT and the subgroups in a logistic regression model significantly improved (p = 0.002) prediction performance. CONCLUSIONS: This study provides evidence that the diagnostic efficacy of GGT can differ significantly across different subgroups. Therefore, a GGT diagnostic result should be interpreted cautiously when patients belong to subgroups with low diagnostic efficacy. The development of a prediction model and/or clinical diagnostic pathway for early detection of BA should also account for the heterogeneous diagnostic efficacy of GGT.

Single-cell transcriptional profiling reveals heterogeneity and developmental trajectories of Ewing sarcoma.

PURPOSE: Ewing sarcoma (EwS) is an aggressive malignant neoplasm composed of small round cells. The heterogeneity and developmental trajectories of EwS are uncertain. METHODS: Single-cell RNA sequencing was performed on 4 EwS tumor tissue samples, and 3 transcriptional atlases were generated. K-nearest neighbor algorithm was used to predict the origin of tumor cells at single-cell resolution. Monocle2 package was used to perform pseudotime trajectory analysis in tumor cells. Differentially expressed genes were compared against those in all other clusters via the FindMarkers function, and then they were subjected to GO analysis using clusterProfiler package. RESULTS: Combined with the results of k-nearest neighbor algorithm and pseudotime trajectory analysis in tumor cells, we thought meningeal EwS originated from neural crest cells during epithelial to mesenchymal transition and simulated the process of neural crest cell lineage differentiation. But for perirenal EwS and spinal EwS, we hypothesized that after the neural crest cell lineage mutated into them, the tumor cells did not maintain the differentiation trajectory of neural crest cell lineage, and the development trajectory of tumor cells became chaotic. GO analysis results showed that interferon signaling pathway-related biological processes play an essential role in the tumorigenesis and tumor progression process of EwS, and among these biological processes genes, JAK1 gene up-regulated most significantly and highly expressed in all tumor cells. Ruxolitinib was used to explore the function of JAK1. Targeting JAK1 can promote apoptosis of EwS tumor cells, inhibit the migration and invasion of EwS tumor cells, and inhibit cell proliferation by inducing cell cycle S phase arrest. CONCLUSION: EwS was derived from neural crest cell lineage with variable developmental timing of oncogenic conversion, and the JAK1 might be a candidate for therapeutic targets of EwS.

A Dynamic Thermal-Mechanical Coupling Numerical Model to Solve the Deformation and Thermal Diffusion of Plates.

Elastic materials include metal plates, rubber, foam, airbags and so on, which have a good buffer effect, toughness and strong recovery ability. In this paper, the deformation and thermal diffusion of 2D and 3D thin plates are studied. Two models are established for the deformation of 2D thin plates. The bending deformation equation of rectangular and circular plates is derived, and the semi-analytical solution of the deflection function w(x,y) is found through the Fourier series approximation in the polar coordinate. The consistencies of the numerical solution and the theoretical solution are verified by numerical method. Then, we find that the factors affecting the deformation are related to the Young's modulus, load, plate length and deformation factor α of the material. In a separate temperature physics field, we establish a heat conduction model of 2D graphene film. Three numerical schemes of the transient heat conduction equation of FDM-FEM are given. In contrast, this paper uses the implicit Euler method to discrete the time term. Furthermore, we compared the difference between the adiabatic condition and the convection condition by the graphical method and the curve trend. The results show that the temperature near the adiabatic boundary is higher. Finally, we proposed a 3D dynamic thermal-mechanical coupling model (3D-DTMCM) that has been established. A laser heating monocrystalline silicon sheet with periodic motion formula is given. The temperature radiation of the laser heat source has Gaussian distribution characteristics. Our proposed model can dynamically determine Young's modulus with a variable temperature. The numerical results show that the higher the temperature is, the higher the strain energy density of the plate is. In addition, the deformation amplitude of the plates in the coupling field is larger than that in the single mechanical field. Finally, we also discussed the stress field distribution of mixed cracks under high temperature and high load. Our research provides theoretical support for the deformation of different plates, and also reflects the value of the coupled model in practical applications.

Diagnostic Value and Effectiveness of an Artificial Neural Network in Biliary Atresia.

Objectives: Biliary atresia (BA) is a devastating pediatric liver disease. Early diagnosis is important for timely intervention and better prognosis. Using clinical parameters for non-invasive and efficient BA diagnosis, we aimed to establish an artificial neural network (ANN). Methods: A total of 2,384 obstructive jaundice patients from 2012 to 2017 and their 137 clinical parameters were screened for eligibility. A standard binary classification feed-forward ANN was employed. The network was trained and validated for accuracy. Gamma-glutamyl transpeptidase (GGT) level was used as an independent predictor and a comparison to assess the network effectiveness. Results: We included 46 parameters and 1,452 patients for ANN modeling. Total bilirubin, direct bilirubin, and GGT were the most significant indicators. The network consisted of an input layer, 3 hidden layers with 12 neurons each, and an output layer. The network showed good predictive property with a high area under curve (AUC) (0.967, sensitivity 97.2% and specificity 91.0%). Five-fold cross validation showed the mean accuracy for training data of 93.2% and for validation data of 88.6%. Conclusions: The high accuracy and efficiency demonstrated by the ANN model is promising in the noninvasive diagnosis of BA and could be considered as in a low-cost and independent expert diagnosis system.

Neuraxial adjuvants for prevention of perioperative shivering during cesarean section: A network meta-analysis following the PRISMA guidelines.

BACKGROUND: Perioperative shivering is clinically common during cesarean sections under neuraxial anesthesia, and several neuraxial adjuvants are reported to have preventive effects on it. However, the results of current studies are controversial and the effects of these neuraxial adjuvants remain unclear. AIM: To evaluate the effects of neuraxial adjuvants on perioperative shivering during cesarean sections, thus providing an optimal choice for clinical application. METHODS: A systematic review and network meta-analysis were conducted following the PRISMA (Preferred Reported Items for Systematic Review and Meta-analysis) guidelines. Analyses were performed using Review Manager 5.3 and Stata 14.0. We searched PubMed, EMBASE, Web of Science, and Cochrane Central databases for eligible clinical trials assessing the effects of neuraxial adjuvants on perioperative shivering and other adverse events during cesarean sections. Perioperative shivering was defined as the primary endpoint, and nausea, vomiting, pruritus, hypotension, and bradycardia were the secondary outcomes. RESULTS: Twenty-six studies using 9 neuraxial adjuvants for obstetric anesthesia during caesarean sections were included. The results showed that, compared with placebo, pethidine, fentanyl, dexmedetomidine, and sufentanil significantly reduced the incidence of perioperative shivering. Among the four neuraxial adjuvants, pethidine was the most effective one for shivering prevention (OR = 0.15, 95%CI: 0.07-0.35, surface under the cumulative ranking curve 83.9), but with a high incidence of nausea (OR = 3.15, 95%CI: 1.04-9.57) and vomiting (OR = 3.71, 95%CI: 1.81-7.58). The efficacy of fentanyl for shivering prevention was slightly inferior to pethidine (OR = 0.20, 95%CI: 0.09-0.43), however, it significantly decreased the incidence of nausea (OR = 0.34, 95%CI: 0.15-0.79) and vomiting (OR = 0.25, 95%CI: 0.11-0.56). In addition, compared with sufentanil, fentanyl showed no impact on haemodynamic stability and the incidence of pruritus. CONCLUSION: Pethidine, fentanyl, dexmedetomidine, and sufentanil appear to be effective for preventing perioperative shivering in puerperae undergoing cesarean sections. Considering the risk-benefit profiles of the included neuraxial adjuvants, fentanyl is probably the optimal choice.