BackgroundExcellent image quality is crucial for workup of hepatocellular carcinoma (HCC) in patients with liver cirrhosis because a signature tumor signal allows for non-invasive diagnosis without histologic proof. Photon-counting detector computed tomography (PCD-CT) can enhance abdominal image quality, especially in combination with a novel iterative reconstruction algorithm, quantum iterative reconstruction (QIR).The purpose of this study was to analyze the impact of different QIR levels on PCD-CT imaging of HCC in both phantom and patient scans.MethodsVirtual monoenergetic images at 50 keV were reconstructed using filtered back projection and all available QIR levels (QIR 1–4). Objective image quality properties were investigated in phantom experiments. The study also included 44 patients with triple-phase liver PCD-CT scans of viable HCC lesions. Quantitative image analysis involved assessing the noise, contrast, and contrast-to-noise ratio of the lesions. Qualitative image analysis was performed by three raters evaluating noise, artifacts, lesion conspicuity, and overall image quality using a 5-point Likert scale.ResultsNoise power spectra in the phantom experiments showed increasing noise suppression with higher QIR levels without affecting the modulation transfer function. This pattern was confirmed in the in vivo scans, in which the lowest noise levels were found in QIR-4 reconstructions, with around a 50% reduction in median noise level compared with the filtered back projection images. As contrast does not change with QIR, QIR-4 also yielded the highest contrast-to-noise ratios. With increasing QIR levels, rater scores were significantly better for all qualitative image criteria (all p < .05).ConclusionsWithout compromising image sharpness, the best image quality of iodine contrast optimized low-keV virtual monoenergetic images can be achieved using the highest QIR level to suppress noise. Using these settings as standard reconstruction for HCC in PCD-CT imaging might improve diagnostic accuracy and confidence.

BackgroundAs the characteristic functional component in ginger, gingerols possess several health-promoting properties. Long non-coding RNAs (lncRNAs) act as crucial regulators of diverse biological processes. However, lncRNAs in ginger are not yet identified so far, and their potential roles in gingerol biosynthesis are still unknown. In this study, metabolomic and transcriptomic analyses were performed in three main ginger cultivars (leshanhuangjiang, tonglingbaijiang, and yujiang 1 hao) in China to understand the potential roles of the specific lncRNAs in gingerol accumulation.ResultsA total of 744 metabolites were monitored by metabolomics analysis, which were divided into eleven categories. Among them, the largest group phenolic acid category contained 143 metabolites, including 21 gingerol derivatives. Of which, three gingerol analogs, [8]-shogaol, [10]-gingerol, and [12]-shogaol, accumulated significantly. Moreover, 16,346 lncRNAs, including 2,513, 1,225, and 2,884 differentially expressed (DE) lncRNA genes (DELs), were identified in all three comparisons by transcriptomic analysis. Gene ontology enrichment (GO) analysis showed that the DELs mainly enriched in the secondary metabolite biosynthetic process, response to plant hormones, and phenol-containing compound metabolic process. Correlation analysis revealed that the expression levels of 11 DE gingerol biosynthesis enzyme genes (GBEGs) and 190 transcription factor genes (TF genes), such as MYB1, ERF100, WRKY40, etc. were strongly correlation coefficient with the contents of the three gingerol analogs. Furthermore, 7 and 111 upstream cis-acting lncRNAs, 1,200 and 2,225 upstream trans-acting lncRNAs corresponding to the GBEGs and TF genes were identified, respectively. Interestingly, 1,184 DELs might function as common upstream regulators to these GBEGs and TFs genes, such as LNC_008452, LNC_006109, LNC_004340, etc. Furthermore, protein–protein interaction networks (PPI) analysis indicated that three TF proteins, MYB4, MYB43, and WRKY70 might interact with four GBEG proteins (PAL1, PAL2, PAL3, and 4CL-4).ConclusionBased on these findings, we for the first time worldwide proposed a putative regulatory cascade of lncRNAs, TFs genes, and GBEGs involved in controlling of gingerol biosynthesis. These results not only provide novel insights into the lncRNAs involved in gingerol metabolism, but also lay a foundation for future in-depth studies of the related molecular mechanism.

The emergence of scalar Higgs-type amplitude modes in systems where symmetry is spontaneously broken has been a highly successful, paradigmatic description of phase transitions, with implications ranging from high-energy particle physics to low-energy condensed matter systems. Here, we uncover two successive high temperature phase transitions in the pyrochlore magnet Nd2Ru2O7 at TN = 147 K and T* = 97 K, that lead to giant phonon instabilities and culminate in the emergence of a highly coherent excitation. This coherent excitation, distinct from other phonons and from conventional magnetic modes, stabilizes at a low energy of 3 meV. We assign it to a collective Higgs-type amplitude mode, that involves bond energy modulations of the Ru4 tetrahedra. Its striking two-fold symmetry, incompatible with the underlying crystal structure, highlights the possibility of multiple entangled broken symmetries.

BackgroundClear cell renal cell carcinoma (ccRCC) is the dominant subtype of kidney cancer. Dysregulation of long-chain acyl-CoA synthetase 1 (ACSL1) is strongly implicated in undesirable results in varieties of cancers. Nevertheless, the dysregulation and associated multi-omics characteristics of ACSL1 in ccRCC remain elusive.MethodsWe probed the mRNA and protein profiles of ACSL1 in RCC using data from the Cancer Genome Atlas, Gene Expression Omnibus, the Human Protein Atlas (HPA), and Clinical Proteomic Tumor Analysis Consortium (CPTAC) and verified them in our patient cohort and RCC cell lines. Correlations between ACSL1 expression and clinicopathological features, epigenetic modification and immune microenvironment characteristics were analyzed to reveal the multi-omics profile associated with ACSL1.ResultsACSL1 was down-regulated in ccRCC tissues compared to adjacent normal tissues. Lower expression of ACSL1 was linked to unfavorable pathological parameters and prognosis. The dysregulation of ACSL1 was greatly ascribed to CpG island-associated methylation modification. The ACSL1 high-expression subgroup had enriched fatty acid metabolism-related pathways and high expression of ferroptosis-related genes. In contrast, the ACSL1 low-expression subgroup exhibited higher immune and microenvironment scores, elevated expression of immune checkpoints PDCD1, CTLA4, LAG3, and TIGIT, and higher TIDE scores. Using data from the GDSC database, we corroborated that down-regulation of ACSL1 was associated with higher sensitivity towards Erlotinib, Pazopanib, and PI3K-Akt-mTOR-targeted therapeutic strategies.ConclusionTaken together, our findings point to ACSL1 as a biomarker for prognostic prediction of ccRCC, identifying the tumor microenvironment (TME) phenotype, and even contributing to treatment decision-making in ccRCC patients.

BackgroundTo explore the impact of preoperative 3D printing on the fixation of posterior rib fractures utilizing a memory alloy embracing device of rib under thoracoscopy.MethodsThe enrolled patients were divided into the 3D printing (11 patients) and the non-3D printing (18 patients) groups, based on whether a 3D model of ribs was prepared prior to surgery. Analysis was conducted comparing the average fixation time per fracture, postoperative fixation loss, and poor reduction of fractured end between the two groups.ResultsThe average fixation time of each fracture was 27.2 ± 7.7 min in the 3D printing group and 29.3 ± 8.2 min in the non-3D printing group, with no statistically significant difference observed between the two groups (P > 0.05). The incidence of poor fracture fixation in the 3D printing group was statistically lower than that in the non-3D printing group (12.9% vs. 44.7%, P < 0.05). Further stratified analysis revealed that the off-plate rate in the 3D printing group and the non-3D group was (3.2% vs. 12.8%, P > 0.05), and the dislocation rate of the fractured end was (9.7% vs. 31.9%, P < 0.05).ConclusionsThe application of 3D printing technology to prepare the rib model before surgery is proves beneficial in reducing the occurrence of poor fixation of fractures and achieving precise and individualized treatment.

Breast cancer can metastasize to various organs, including the lungs. The immune microenvironment of the organs to be metastasized plays a crucial role in the metastasis of breast cancer. Infection with pathogens such as viruses and bacteria can alter the immune status of the lung. However, the effect of chronic inflammation caused by bacteria on the formation of a premetastatic niche within the lung is unclear, and the contribution of specific immune mediators to tumor metastasis also remains largely undetermined. Here, we used a mouse model revealing that chronic pulmonary bacterial infection augmented breast cancer lung metastasis by recruiting a distinct subtype of tumor-infiltrating MHCIIhi neutrophils into the lung, which exhibit cancer-promoting properties. Functionally, MHCIIhi neutrophils enhanced the lung metastasis of breast cancer in a cell-intrinsic manner. Furthermore, we identified CCL2 from lung tissues as an important environmental signal to recruit and maintain MHCIIhi neutrophils. Our findings clearly link bacterial-immune crosstalk to breast cancer lung metastasis and define MHCIIhi neutrophils as the principal mediator between chronic infection and tumor metastasis.