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Background: Fatty acid oxidation (FAO) is considered to play a vital part in tumor metabolic reprogramming. But the comprehensive description of FAO dysregulation in tumors has not been unknown. Methods: We obtained FAO genes, RNA-seq data and clinical information from the Msigdb, TCGA and GTEx databases. We assessed their prognosis value using univariate cox analysis, survival analysis and Kaplan-Meier curve. We determined the function of FAO genes using gene set variation analysis. The correlation analysis was calculated by corrplot R package. Immunotherapy response was assessed through TIDE scores. The protein expression levels of FAO genes were validated using immunohistochemistry (IHC). Results: The FAO scores were highest in COAD but lowest in PCPG. FAO scores were significantly associated with the prognosis of some cancers in OS, DSS, DFI and PFI. Besides, gene set variation analysis identified that FAO scores were related to immune-related pathways, and immune infiltration analysis showed FAO scores were positively related to cancer-associated fibroblasts and various immune-related genes. TIDE scores were significantly decreased in ACC, CHOL, ESCA, GBM, LAML, SARC, SKCM and THCA compared with normal samples, while it was significantly increased in BLCA, LUAD, LUSC, PCPG, PRAD and STAD. Besides, most FAO genes were downregulated in pan-cancer compared with normal samples. Moreover, we found copy number variation (CNV) of FAO genes played a positive role in their mRNA expression, while methylation was negative. We determined FAO genes were closely related to some drugs in pan-cancer. Conclusions: FAO score is a novel and promising factor for predicting outcomes.

Objective: We report a low-grade endometrial stromal sarcoma (ESS) with a novel CDKN1A-JAZF1 fusion gene arising from abdominal wall endometrioma. Case report: A 40-year-old woman presented with a 5.5-cm abdominal wall mass juxtaposed to the postoperative scar of two cesarean sections. Histologically, the tumor exhibited obvious tongue-like protrusions into the surrounding tissue, showed spindle cells with multinodular growth pattern that occasionally rotate around small arteries. Immunohistochemically, the tumor cells were positive for CD10, estrogen receptor (ER), progesterone receptor (PR), negatively stained for smooth muscle actin (SMA), CD117, CyclinD1. In addition, a previously undescribed gene fusion between CDNK1A 5′ end of exon 1(NM_000389.5) and JAZF1 3′ end of exon 5 (NM_175,061,3) was reported in this case. Conclusion: This report of ESS suggesting that rapidly growing abdominal wall masses without menstruation-related should be promptly evaluated and treated aggressively. In addition, we have expanded the molecular landscape of low-grade ESS.

The confluence of 3-D integration and network-on-chip (NoC) provides an effective solution to the scalability problem of on-chip interconnects. In 3-D integration, through-silicon via (TSV) is considered to be the most promising bonding technology. However, TSVs are also precious link resources because they consume significant chip area and possibly lead to routing congestion in the physical design stage. In addition, TSVs suffer from serious yield losses that shrink the effective TSV density. Thus, it is necessary to implement a TSV-economical 3-D NoC architecture in cost-effective design. For symmetric 3-D mesh NoCs, we observe that the TSVs bandwidth utilization is low and they rarely become the contention spots in networks as planar links. Based on this observation, we propose the TSV sharing (TS) scheme to save TSVs in 3-D NoC by enabling neighboring routers to share the vertical channels in a time division multiplexing way. We also investigate different TS implementation alternatives and show how TS improves TSV-effectiveness (TE) in multicore processors through a design space exploration. In experiments, we comprehensively evaluate TSs influence on all layers of system. It is shown that the proposed method significantly promotes TE with negligible performance overhead. [ABSTRACT FROM PUBLISHER]

In the complex realm of nuclear engineering, understanding the kinetics behavior of neutrons in reactors is a task of considerable importance for safety. The effective delayed neutron fraction (βeff), neutron prompt generation time (Λ) and other neutron kinetics parameters are pivotal for dynamics analysis in nuclear reactor. Because of the limited realistic conditions, these parameters have traditionally been challenging to measure experimentally, compelling researchers to rely on numerical computations for their determination, especially for pebble-bed high-temperature gas-cooled reactors (HTGRs). Yet conventional numerical techniques necessitate direct core condition data and often presuppose simplistic treatments of delayed neutron energies, resulting in computational inefficiencies and imprecise outcomes. A central difficulty lies with the process involving VSOP and CITATION codes, used in HTGR calculations of neutron kinetics parameters, which requires the formulation of input cards based on VSOP output for any core state—This procedure can confound researchers. Furthermore, the limited data library (ENDF/B-Ⅵ.8) available to VSOP restricts the accuracy attainable through these methods. In this paper, in an effort to refine this process, a multi-group cross section library, XPZLIB, containing delayed neutron data was generated. This library leverages the comprehensive nuclear data from the ENDF/B-Ⅷ.0 library, processed using the enhanced NJOY2016 code equipped with a developed XPZR module and an automatic processing system, PyNjoy2022. The HTGR physics lattice code XPZ was then used to homogenize the delayed neutron data, ensuring that the necessary energy-related information was retained in preparation for subsequent calculations of energy-dependent neutron kinetic parameters. A unique homogenization technique was also developed to handle the delayed neutron precursor decay constants (λ), which unlike other parameters, are time-dependent. These calculations of kinetics parameters for HTGRs are conducted via the importance function weighting method facilitated by the core physical analysis code PANGU. This method utilizes the adjoint neutron flux as the weighting function, which is determined from the adjoint neutron transport equation. The approach produced a collection of single-speed neutron kinetic parameters as well as a 6-group energy-dependent effective delayed neutron fraction. The accuracy and validity of this methodology were confirmed by benchmarking the results against Monte Carlo solutions using iterated fission probability method. The findings not only confirm that comprehensive numerical calculations are feasible for determining neutron kinetics parameters in HTGR environments but also provide a robust foundation for subsequent dynamics analyses. By contrasting the new method with pre-existing pre-fitting methods, the superiority of this advanced technique became evident, signifying a significant stride forward in the field of reactor dynamics and safety analysis.