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The SARS-CoV-2 Delta variant has spread rapidly worldwide. To provide data on its virological profile, we here report the first local transmission of Delta in mainland China. All 167 infections could be traced back to the first index case. Daily sequential PCR testing of quarantined individuals indicated that the viral loads of Delta infections, when they first become PCR-positive, were on average ~1000 times greater compared to lineage A/B infections during the first epidemic wave in China in early 2020, suggesting potentially faster viral replication and greater infectiousness of Delta during early infection. The estimated transmission bottleneck size of the Delta variant was generally narrow, with 1-3 virions in 29 donor-recipient transmission pairs. However, the transmission of minor iSNVs resulted in at least 3 of the 34 substitutions that were identified in the outbreak, highlighting the contribution of intra-host variants to population-level viral diversity during rapid spread. The SARS-CoV-2 Delta variant has spread rapidly worldwide. Here, the authors characterise a single chain of transmission of Delta in China, and find evidence that it is more infectious and replicates faster during early infection compared to early pandemic lineages.

The problem of extracting bearing weak fault features under variable-speed conditions with strong background noise interference remains challenging due to the limitations of existing feature extraction methods. These methods, especially those that rely on manual parameter tuning and rigid regularization, often struggle with noise suppression and robustness optimization, resulting in inaccurate extraction of weak fault features. To overcome this drawback, this study proposes a novel weak fault feature extraction method based on tensor decomposition model for bearings. First, the time–frequency tensor is constructed based on the short-time Fourier transform. Then, two types of fault properties in tensor are explored and an improved tensor decomposition model is proposed to realize the accurate extraction of weak fault features under variable-speed conditions. In addition, the decomposed feature tensor is conducted by a multichannel global energy-weighted fusion strategy, which significantly improves the robustness in extracting multichannel weak fault features. The effectiveness and superiority of the proposed method are systematically investigated through both simulated and experimental case studies. The results demonstrate that the method effectively eliminates background noise interference in measurements while augmenting the resolution of fault features.

Multichannel signals contain an abundance of fault characteristic information on equipment and show greater potential for weak fault characteristics extraction and early fault detection. However, how to effectively utilize the advantages of multichannel signals with their information richness while eliminating interference components caused by strong background noise and information redundancy to achieve accurate extraction of fault characteristics is still challenging for mechanical fault diagnosis based on multichannel signals. To address this issue, an effective weak fault detection framework for multichannel signals is proposed in this paper. Firstly, the advantages of a tensor on characterizing fault information were displayed, and the low-rank property of multichannel fault signals in a tensor domain is revealed through tensor singular value decomposition. Secondly, to tackle weak fault characteristics extraction from multichannel signals under strong background noise, an adaptive threshold function is introduced, and an adaptive low-rank tensor estimation model is constructed. Thirdly, to further improve the accurate estimation of weak fault characteristics from multichannel signals, a new sparsity metric-oriented parameter optimization strategy is provided for the adaptive low-rank tensor estimation model. Finally, an effective multichannel weak fault detection framework is formed for rolling bearings. Multichannel data from the repeatable simulation, the publicly available XJTU-SY whole lifetime datasets and an accelerated fatigue test of rolling bearings are used to validate the effectiveness and practicality of the proposed method. Excellent results are obtained in multichannel weak fault detection with strong background noise, especially for early fault detection.

Background Syntaxin4 (STX4) gene encodes the protein STX4, a member of soluble N-ethylmaleimide-sensitive factor attachment protein receptors protein, playing a vital role in cell invadopodium formation and invasion, which is associated with the malignant progression of various human cancers. However, the expression and prognostic significance of STX4 in kidney renal clear cell carcinoma (KIRC) remain to be investigated. Methods In this study, we collected the mRNA expression of STX4 in 535 KIRC patients from The Cancer Genome Atlasthrough the University of California Santa Cruz Xena database platform. Then we explored the expression of STX4 in KIRC, and the relationship with clinicopathological characteristics and prognostic value. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes function enrichment analyses were used to explore the potential mechanism of STX4 in KIRC. qRT-PCR analysis was performed toverify the above results with real world tissue specimens. Results The results indicated that STX4 was up-expressed in KIRC, and were associated with higher histological grade, advanced stage, and poorer prognosis. Moreover, elevated STX4 expression is an independent risk factor for KIRC. qRT-PCR analysis showed that STX4 was significantly elevated in 10 paired of KIRC samples compared to normal samples. Functional enrichment analysis indicated that endo/exocytosis, autophagy, mTOR signaling pathway, and NOD-like receptor signaling pathway were enriched. Conclusions In summary, STX4 is constantly up-expressed in KIRC tissues, associated with a poor prognosis. We suggest that it can be an effective biomarker for the prognosis of KIRC and may be a novel therapeutic target in KIRC.

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cancer, marked by high molecular heterogeneity and limited responsiveness to targeted or immune therapies. Ribosome biogenesis (Ribosis), a central regulator of cell growth and metabolism, has emerged as a driver of tumor aggressiveness. However, its role in ccRCC pathogenesis and prognosis remains poorly defined. We integrated bulk RNA sequencing, single-cell RNA sequencing, and spatial transcriptomics sequencing data to dissect the biological functions and clinical relevance of Ribosis-related genes in ccRCC. Through pseudotime trajectory analysis and metabolic flux inference, we examined malignant progression and metabolic reprogramming. A prognostic model based on a Ribosis-related signature (RBRS) was built using 118 machine learning algorithm combinations and validated in internal and external cohorts. A web-based calculator was also developed. We further analyzed immune infiltration, genomic alterations, tumor microenvironment features, and drug sensitivity. Expression of five core Ribosis-related genes (RPL38, RPS2, RPS14, RPS19, RPS28) was validated by qRT-PCR. We identified a Ribosis-high malignant subpopulation with enhanced stemness, poor prognosis, and elevated oxidative phosphorylation. These cells showed increased metabolic activity, especially in the pyruvate-lactate axis, potentially facilitating immune evasion. The RBRS model outperformed 32 published signatures (C-index = 0.68). High-risk patients exhibited an \"immune-activated yet immunosuppressed\" microenvironment, with increased CD8 T-cell infiltration and elevated regulatory T cells, myeloid-derived suppressor cells, and immune checkpoint expression (e.g., PDCD1, CTLA-4). Despite active antigen presentation and immune cell recruitment, terminal tumor-killing capacity was impaired. High-risk tumors also showed higher mutation burden, frequent copy number loss of tumor suppressor genes, and resistance to common targeted therapies. The five RBRS genes were significantly upregulated in tumor tissues, consistent with bulk RNA-seq data. We reveal Ribosis as a key driver of ccRCC progression. The RBRS model demonstrates robust prognostic value and translational utility, linking Ribosis to metabolism, immune dysfunction, and therapy resistance, offering new insights for risk stratification and precision treatment in ccRCC.

Background Cartilage defects are common sports injuries without significant treatment. Articular cartilage with inferior regenerative potential resulted in the poor formation of hyaline cartilage in defects. Acellular matrix scaffolds provide a microenvironment and biochemical properties similar to those of native tissues and are widely used for tissue regeneration. Therefore, we aimed to design a novel acellular cartilage matrix scaffold (ACS) for cartilage regeneration and hyaline-like cartilage formation. Methods Four types of cartilage injury models, including full-thickness cartilage defects (6.5 and 8.5 mm in diameter and 2.5 mm in depth) and osteochondral defects (6.5 and 8.5 mm in diameter and 5 mm in depth), were constructed in the trochlear groove of the right femurs of pigs (n = 32, female, 25–40 kg). The pigs were divided into 8 groups (4 in each group) based on post-surgery treatment differences. was assessed by macroscopic appearance, magnetic resonance imaging (MRI), micro–computed tomography (micro-CT), and histologic and immunohistochemistry tests. Results At 6 months, the ACS-implanted group exhibited better defect filling and a greater number of chondrocyte-like cells in the defect area than the blank groups. MRI and micro-CT imaging evaluations revealed that ACS implantation was an effective treatment for cartilage regeneration. The immunohistochemistry results suggested that more hyaline-like cartilage was generated in the defects of the ACS-implanted group. Conclusions ACS implantation promoted cartilage repair in full-thickness cartilage defects and osteochondral defects with increased hyaline-like cartilage formation at the 6-month follow-up.

Osteoarthritis (OA) is the most common degenerative joint disease worldwide, with the main pathological manifestation of articular cartilage degeneration. It have been investigated that pharmacological activation of transient receptor potential vanilloid 1 (TRPV1) significantly alleviated cartilage degeneration by abolishing chondrocyte ferroptosis. In this work, in view of the thermal activated feature of TRPV1, Citrate‐stabilized gold nanorods (Cit‐AuNRs) is conjugated to TRPV1 monoclonal antibody (Cit‐AuNRs@Anti‐TRPV1) as a photothermal switch for TRPV1 activation in chondrocytes under near infrared (NIR) irradiation. The conjugation of TRPV1 monoclonal antibody barely affect the morphology and physicochemical properties of Cit‐AuNRs. Under NIR irradiation, Cit‐AuNRs@Anti‐TRPV1 exhibited good biocompatibility and flexible photothermal responsiveness. Intra‐articular injection of Cit‐AuNRs@Anti‐TRPV1 followed by NIR irradiation significantly activated TRPV1 and attenuated cartilage degradation by suppressing chondrocytes ferroptosis. The osteophyte formation and subchondral bone sclerosis are remarkably alleviated by NIR‐inspired Cit‐AuNRs@Anti‐TRPV1. Furthermore, the activation of TRPV1 by Cit‐AuNRs@Anti‐TRPV1 evidently improved physical activities and alleviated pain of destabilization of the medial meniscus (DMM)‐induced OA mice. The study reveals Cit‐AuNRs@Anti‐TRPV1 under NIR irradiation protects chondrocytes from ferroptosis and attenuates OA progression, providing a potential therapeutic strategy for the treatment of OA. Li et al develop a Cit‐AuNRs@Anti‐TRPV1 switch for photothermal activation of TRPV1 signaling for the treatment of osteoarthritis. Cit‐AuNRs@Anti‐TRPV1 has good photothermal responsiveness, and it can rapidly warm up under near‐infrared (NIR) irradiation. By controlling the NIR power and action time, it can realize effective, controllable and targeted activation of TRPV1, thereby suppressing the ferroptosis of chondrocytes to attenuate OA.

Kidney renal clear cell carcinoma (KIRC) remains a significant challenge worldwide because of its poor prognosis and high mortality rate, and accurate prognostic gene signatures are urgently required for individual therapy. This study aimed to construct and validate a seven-gene signature for predicting overall survival (OS) in patients with KIRC. The mRNA expression profile and clinical data of patients with KIRC were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC). Prognosis-associated genes were identified, and a prognostic gene signature was constructed. Then, the prognostic efficiency of the gene signature was assessed. The results obtained using data from the TCGA were validated using those from the ICGC and other online databases. Gene set enrichment analyses (GSEA) were performed to explore potential molecular mechanisms. A seven-gene signature (PODXL, SLC16A12, ZIC2, ATP2B3, KRT75, C20orf141, and CHGA) was constructed, and it was found to be effective in classifying KIRC patients into high- and low-risk groups, with significantly different survival based on the TCGA and ICGC validation data set. Cox regression analysis revealed that the seven-gene signature had an independent prognostic value. Then, we established a nomogram, including the seven-gene signature, which had a significant clinical net benefit. Interestingly, the seven-gene signature had a good performance in distinguishing KIRC from normal tissues. GSEA revealed that several oncological signatures and GO terms were enriched. This study developed a novel seven-gene signature and nomogram for predicting the OS of patients with KIRC, which may be helpful for clinicians in establishing individualized treatments.

ABSTRACT Background Bladder intracavitary hyperthermic perfusion chemotherapy (HIPEC) is a promising treatment for non‐muscular invasive bladder cancer (NMIBC). However, the molecular mechanisms underlying the response to HIPEC remain poorly understood. This study aimed to elucidate the transcriptomic profiles associated with the response to HIPEC in NMIBC patients. Methods RNA sequencing was performed on bladder tumor samples from NMIBC patients who underwent HIPEC treatment. Differentially expressed genes (DEGs) between responders and non‐responders to HIPEC were identified. Gene ontology and pathway analysis were conducted to explore the biological functions and pathways enriched in the DEGs. Additionally, the expression of specific immune‐related genes was evaluated for their association with HIPEC response. The diagnostic efficiency of selected genes in predicting relapse before and after HIPEC treatment was assessed in a validation cohort. Results We assessed the expression status of differentially expressed genes (DEGs) between responders and non‐responders to HIPEC. Gene ontology and pathway analysis revealed that DEGs were enriched in immune‐related pathways, including cytokine‐cytokine receptor interaction, chemokine signaling pathway, and antigen processing and presentation. Furthermore, the expression of several immune‐related genes, including ZMAP4, UPP2, and GALR1, was significantly associated with the response to HIPEC. Therefore, the immune system's reaction plays a crucial role in the response to HIPEC in patients with NMIBC. At last, a considerable diagnostic efficiency that tissue TMEFF2, KRT222, and GTSF1 in predicting relapse in NMIBC patients after HIPEC treatment, and ZMAP4, UPP2, and GALR1 in predicting relapse in NMIBC patients before HIPEC treatment in the validation cohort. Conclusion Transcriptomic profiling revealed that immune‐related pathways and genes play a crucial role in the response to HIPEC in NMIBC patients. These findings suggest that transcriptomic profiling could provide a valuable tool for predicting treatment outcomes and identifying therapeutic targets for NMIBC.

Renal cell carcinoma (RCC) is the second most common human urinary tumor. Eupatilin is the main active ingredient of the traditional Chinese medicine Artemisia asiatica. The effect of Eupatilin on RCC and the underlying mechanism remain unknown. Here, we investigated the anticancer effects and mechanisms of Eupatilin in RCC in vivo and in vitro, laying an experimental foundation for the clinical application of Eupatilin in the treatment of RCC. The results showed that Eupatilin significantly inhibited 786-O cell viability and migration and promoted apoptosis. Eupatilin inhibited the expression of miR-21 in 786-O cells, and overexpression of miR-21 suppressed the effect of Eupatilin on viability, apoptosis, and migration in 786-O cells. Eupatilin inhibited the growth of renal tumors in nude mice by downregulating miR-21. YAP1, which was identified as a target of miR-21, showed significantly lower expression in RCC tissues than in healthy tissues. miR-21 significantly inhibited YAP1 protein expression in 786-O cells and tumor tissues isolated from nude mice, and YAP1 attenuated the effect of miR-21 on the viability, apoptosis, and migration of 786-O cells. In conclusion, Eupatilin inhibited the expression of miR-21, which mediated the proapoptotic and antimigratory effects of Eupatilin by suppressing YAP1 in renal cancer cells. These results suggested that Eupatilin could be a potent agent for the treatment of RCC.