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Toona sinensis (Chinese toon) is a valuable forest resource widely used in gastronomy, phytotherapy, and timber production. MYC transcriptional factors are critical to a variety of biological functions. However, the MYC family remains unsystematically characterized in T. sinensis. A total of 18 TsMYC genes were identified in the T. sinensis genome and grouped into six distinct subfamilies according to phylogenetic analysis in this study. This classification was further supported by analyses of gene structure and conserved motifs. Evolutionary analysis revealed that the TsMYC gene family achieved expansion via whole-genome duplication (WGD) and segmental duplication, with these genes experiencing intense purifying selection throughout the evolutionary process. Additionally, 42 cis-acting elements were detected in the promoter regions of TsMYC genes, and the protein–protein interaction (PPI) network demonstrated that MYC2 serves as a central component in the jasmonic acid (JA) signaling pathway. Expression profiling showed that all TsMYC genes except TsMYC17 were highly expressed in leaves. TsMYC genes displayed distinct expression patterns under salt stress and various phytohormone treatments, with TsMYC17 being the only gene consistently upregulated under all conditions. Subcellular localization assays confirmed that TsMYC17 is localized in the nucleus. These findings suggest that TsMYC17 may play a key role in mediating responses to multiple hormonal signals and abiotic stresses. This research lays a foundation for future investigations into the molecular characteristics and biological roles of the TsMYC17 gene.

The multifocal metalens with an adjustable intensity has great potential in many applications such as the multi-imaging system, but it is less studied. In this paper, by combining the electro-optic material barium titanate (BTO) with the Pancharatnam-Berry phase, an electrically modulated bifocal metalens in a visible light band is innovatively proposed. Due to the electro-optic effect, we can control the refractive index of the BTO nanofins to vary between 2.4 and 3.07 by applying different voltages (0–60 V). Thus, the method of modulating the intensity ratio of the two focal points is applying an electric field. It is different from using phase change materials or changing the ellipticity of incident light, the strategies proposed in previous studies. Moreover, when the applied voltage is 0 V or 60 V, the bifocal metalens becomes a single focal metalens with different focal lengths, and the full width at half maximum of each focal point is close to the diffraction limit. It has great potential in applications of optical storage, communication and imaging systems.

Although conventional traveling-wave fault location devices can detect fault points, their positioning accuracy degrades under complex operating conditions due to sag effects, dynamic line parameter variations, and environmental interference, failing to meet the requirements of high-reliability power grids. Concurrently, existing dynamic capacity expansion devices primarily focus on real-time monitoring of conductor temperature, current-carrying capacity, and environmental param but lack precise fault location functionality. To address these challenges, this paper proposes an integrated dynamic capacity expansion and traveling-wave positioning device capable of monitoring conductor temperature, ambient temperature, power-frequency current, and traveling-wave current. For the first time, a temperature-sag-line length coupling correction model is introduced. By real-time monitoring ambient and conductor temperature variations, the dynamic influence of environmental temperature on conductor sag effects is quantified to correct the actual transmission line length, thereby optimizing the double-ended traveling-wave fault location model. Case study results demonstrate that the positioning accuracy for the same fault point is improved to within 200 m, providing theoretical foundations and technological breakthroughs for intelligent operation-maintenance and rapid fault resolution in transmission lines.

Hippocampal ripple-replay events are typically identified using a two-step process that at each time point uses past and future data to determine whether an event is occurring. This prevents researchers from identifying these events in real time for closed-loop experiments. It also prevents the identification of periods of nonlocal representation that are not accompanied by large changes in the spectral content of the local field potentials (LFPs). In this work, we present a new state-space model framework that is able to detect concurrent changes in the rhythmic structure of LFPs with nonlocal activity in place cells to identify ripple-replay events in a causal manner. The model combines latent factors related to neural oscillations, represented space, and switches between coding properties to explain simultaneously the spiking activity from multiple units and the rhythmic content of LFPs recorded from multiple sources. The model is temporally causal, meaning that estimates of the switching state can be made at each instant using only past information from the spike and LFP signals, or can be combined with future data to refine those estimates. We applied this model framework to simulated and real hippocampal data to demonstrate its performance in identifying ripple-replay events.

Idiopathic pulmonary fibrosis (IPF) is a long-lasting, continuously advancing, and irrevocable interstitial lung disorder with an obscure origin and inadequately comprehended pathological mechanisms. Despite the intricate and uncharted causes and pathways of IPF, the scholarly consensus upholds that the transformation of fibroblasts into myofibroblasts—instigated by injury to the alveolar epithelial cells—and the disproportionate accumulation of extracellular matrix (ECM) components, such as collagen, are integral to IPF’s progression. The introduction of two novel anti-fibrotic medications, pirfenidone and nintedanib, have exhibited efficacy in decelerating the ongoing degradation of lung function, lessening hospitalization risk, and postponing exacerbations among IPF patients. Nonetheless, these pharmacological interventions do not present a definitive solution to IPF, positioning lung transplantation as the solitary potential curative measure in contemporary medical practice. A host of innovative therapeutic strategies are presently under rigorous scrutiny. This comprehensive review encapsulates the recent advancements in IPF research, spanning from diagnosis and etiology to pathological mechanisms, and introduces a discussion on nascent therapeutic methodologies currently in the pipeline.

In this study, we conducted a meta-analysis to estimate the relationship between the consumption of dairy products and the risk of prostate cancer. We searched PubMed, Embase and Cochrane databases for relevant articles and identified a total of thirty-three cohort studies between 1989 and 2020. The qualities of included studies were assessed using Newcastle–Ottawa scale. Pooled adjusted relative risks (RR) with 95 % CI were calculated. We performed subgroup analyses stratified by dairy type, prostate cancer type, follow-up years, treatment era, collection times, adjustment for confounders and geographic location. In the subgroup analysis stratified by prostate cancer type, the pooled RR were 0·98 (95 % CI 0·94, 1·03) in the advanced group, 1·10 (95 % CI 0·98, 1·24) in the non-advanced group and 0·92 (95 % CI 0·84, 1·00) in the fatal group. In the dose–response analysis, a positive association for the risk of prostate cancer was observed for total dairy products 400 g/d (RR: 1·02; 95 % CI 1·00, 1·03), total milk 200 g/d (RR: 1·02; 95 % CI 1·01, 1·03), cheese 40 g/d (RR: 1·01; 95 % CI 1·00, 1·03) and butter 50 g/d (RR: 1·03; 95 % CI 1·01, 1·05). A decreased risk was observed for the intake of whole milk 100 g/d (RR: 0·97; 95 % CI 0·96, 0·99). Our meta-analysis suggests that high intakes of dairy products may be associated with an increased risk of prostate cancer; however, since many of the studies were affected by prostate-specific antigen (PSA) screening bias, additional studies with an adjustment of PSA screening are needed.

G protein-coupled receptor 75 (GPR75), a novel member of the rhodopsin-like G protein-coupled receptor (GPCR) family, has been identified across various tissues and organs, where it contributes to biological regulation and disease progression. Recent studies suggest potential interactions between GPR75 and ligands such as 20-hydroxyeicosatetraenoic acid (20-HETE) and C-C motif chemokine ligand 5 (CCL5/RANTES); however, its definitive endogenous ligand remains unidentified, and GPR75 is currently classified as an orphan receptor by International Union of Basic and Clinical Pharmacology (IUPHAR). Research on GPR75 deorphanization has underscored its critical roles in disease models, particularly in metabolic health, glucose regulation, and stability of the nervous and cardiovascular systems. However, the signaling pathways of GPR75 across different pathological conditions require further investigation. Importantly, ongoing studies are targeting GPR75 for drug development, exploring small molecule inhibitors, antibodies, and gene silencing techniques, positioning GPR75 as a promising GPCR target for treating related diseases. This review summarizes the recent advancements in GPR75 deorphanization research, examines its functions across tissues and systems, and highlights its links to metabolic, cardiovascular, and neurological disorders, thereby providing a resource for researchers to better understand the biological functions of this receptor.

Accumulating evidence demonstrates that lncRNAs are involved in the regulation of the immune microenvironment and early tumor development. Immunogenic cell death occurs mainly through the release or increase of tumor-associated antigen and tumor-specific antigen, exposing “danger signals” to stimulate the body’s immune response. Given the recent development of immunotherapy in lung adenocarcinoma, we explored the role of tumor immunogenic cell death-related lncRNAs in lung adenocarcinoma for prognosis and immunotherapy benefit, which has never been uncovered yet. Based on the lung adenocarcinoma cohorts from the TCGA database and GEO database, the study developed the immunogenic cell death index signature by several machine learning algorithms and then validated the signature for prognosis and immunotherapy benefit of lung adenocarcinoma patients, which had a more stable performance compared with published signatures in predicting the prognosis, and demonstrated predictive value for benefiting from immunotherapy in multiple cohorts of multiple cancers, and also guided the utilization of chemotherapy drugs.

Tumor-associated macrophages (TAMs) are a specific subset of macrophages that reside inside the tumor microenvironment. The dynamic interplay between TAMs and tumor cells plays a crucial role in the treatment response and prognosis of lung adenocarcinoma (LUAD). The study aimed to examine the association between TAMs and LUAD to advance the development of targeted strategies and immunotherapeutic approaches for treating this type of lung cancer. The study employed single-cell mRNA sequencing data to characterize the immune cell composition of LUAD and delineate distinct subpopulations of TAMs. The “BayesPrism” and “Seurat” R packages were employed to examine the association between these subgroups and immunotherapy and clinical features to identify novel immunotherapy biomarkers. Furthermore, a predictive signature was generated to forecast patient prognosis by examining the gene expression profile of immunotherapy-associated TAMs subsets and using 104 machine-learning techniques. A comprehensive investigation has shown the existence of a hitherto unidentified subgroup of TAMs known as RGS1 + TAMs, which has been found to have a strong correlation with the efficacy of immunotherapy and the occurrence of tumor metastasis in LUAD patients. CD83 was identified CD83 as a distinct biomarker for the expression of RGS1 + TAMs, showcasing its potential utility as an indicator for immunotherapeutic interventions. Furthermore, the prognostic capacity of the RTMscore signature, encompassing three specific mRNA (NR4A2, MMP14, and NPC2), demonstrated enhanced robustness when contrasted against the comprehensive collection of 104 features outlined in the published study. CD83 has potential as an immunotherapeutic biomarker. Meanwhile, The RTMscore signature established in the present study might be beneficial for survival prognostication.

Gastric cancer (GC) is a prevalent form of cancer worldwide and has a high death rate, with less than 40% of patients surviving for 5 years. GC demonstrates a vital characteristic of evading regulatory cell death (RCD). However, the extent to which RCD patterns are clinically significant in GC has not been well investigated. The study created a regulatory cell death index (RCDI) signature by employing 101 machine-learning algorithms. These algorithms were based on the expression files of 1292 GC patients from 6 multicenter cohorts. RCDI is a reliable and robust determinant of the likelihood of surviving in general. Furthermore, the precision of RCDI surpasses that of the 20 signatures that have been previously disclosed. The presence of RCDI signature is closely linked to immunological characteristics, such as the infiltration of immune cells, the presence of immunotherapy markers, and the activation of immune-related functions. This suggests that there is a higher level of immune activity in cases with RCDI signature. Collectively, the use of RCDI has the potential to be a strong and encouraging method for enhancing the clinical results of individual individuals with GC.