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Towards intracellular engineering of living organisms, the development of new biocompatible polymerization system applicable for an intrinsically non-natural macromolecules synthesis for modulating living organism function/behavior is a key step. Herein, we find that the tyrosine residues in the cofactor-free proteins can be employed to mediate controlled radical polymerization under 405 nm light. A proton-coupled electron transfer (PCET) mechanism between the excited-state TyrOH* residue in proteins and the monomer or the chain transfer agent is confirmed. By using Tyr-containing proteins, a wide range of well-defined polymers are successfully generated. Especially, the developed photopolymerization system shows good biocompatibility, which can achieve in-situ extracellular polymerization from the surface of yeast cells for agglutination/anti-agglutination functional manipulation or intracellular polymerization inside yeast cells, respectively. Besides providing a universal aqueous photopolymerization system, this study should contribute a new way to generate various non-natural polymers in vitro or in vivo to engineer living organism functions and behaviours. Developing a biocompatible polymerization system applicable for the synthesis of intrinsically non-natural polymers is a key step towards intracellular engineering of living organism. Here the authors report tyrosine residues-mediated radical photopolymerizations for intracellular synthesis of non-natural macromolecules

Distant metastasis (DM) is the main cause of treatment failure in locally advanced rectal cancer. Adjuvant chemotherapy is usually used for distant control. However, not all patients can benefit from adjuvant chemotherapy, and particularly, some patients may even get worse outcomes after the treatment. We develop and validate an MRI-based radiomic signature (RS) for prediction of DM within a multicenter dataset. The RS is proved to be an independent prognostic factor as it not only demonstrates good accuracy for discriminating patients into high and low risk of DM in all the four cohorts, but also outperforms clinical models. Within the stratified analysis, good chemotherapy efficacy is observed for patients with pN2 disease and low RS, whereas poor chemotherapy efficacy is detected in patients with pT1–2 or pN0 disease and high RS. The RS may help individualized treatment planning to select patients who may benefit from adjuvant chemotherapy for distant control. Distant metastasis (DM) is the main cause of treatment failure in locally advanced rectal cancer. Here, the authors developed and validated a radiomic signature (RS) for prediction of DM within a multicenter dataset, and suggest that it may help with stratification of patients who might benefit from adjuvant chemotherapy for DM.

The dynamic study of coacervates in vitro contributes our understanding of phase separation mechanisms in cells due to complex intracellular physiology. However, current researches mainly involve the use of exogenous auxiliary agents to form multi-compartmental coacervates with short-term stability. Herein, we report the endogenous self-organizing of multi-component coacervates (HA/PDDA/BSA/DMAEMA) induced by a dynamic stimulation process of protein-mediated photopolymerization. As polymerization proceeds, the cycled structural evolution and maturation from coacervate droplets into multi-compartmental coacervates, coacervate vesicles and coacervate droplets are revealed, which are driven by electrostatic interaction and osmotic pressure difference supported by dynamic and thermodynamic control. Specially, by regulating the light stimulation time, a type of multi-compartmental coacervates can be widely obtained with high structural stability over 300 days. Being a promising artificial cell model, it shows the special characteristic of compartmentalized encapsulation of substrates, efficiently improving enzymatic interfacial catalytic efficiency of organelle-like communication. Our study holds great potential for advancing the understanding of the structural evolution mechanism of membraneless organelles and provides an instructive technique for constructing multi-compartmental coacervates with long-term stability. Coacervate dynamics are studied to aid in understanding of phase separation cells, but obtaining sufficient stability can be challenging. Here, the authors report the development of multi-component coacervates that self-organise by protein mediated photopolymerisation, and are stable for over 300 days.

Background Recent studies indicate important roles for long noncoding RNAs (lncRNAs) in the regulation of gene expression by acting as competing endogenous RNAs (ceRNAs). However, the specific role of lncRNAs in skeletal muscle atrophy is still unclear. Our study aimed to identify the function of lncRNAs that control skeletal muscle myogenesis and atrophy. Methods RNA sequencing was performed to identify the skeletal muscle transcriptome (lncRNA and messenger RNA) between hypertrophic broilers and leaner broilers. To study the ‘sponge’ function of lncRNA, we constructed a lncRNA‐microRNA (miRNA)‐gene interaction network by integrated our previous submitted skeletal muscle miRNA sequencing data. The primary myoblast cells and animal model were used to assess the biological function of the lncIRS1 in vitro or in vivo. Results We constructed a myogenesis‐associated lncRNA‐miRNA‐gene network and identified a novel ceRNA lncRNA named lncIRS1 that is specifically enriched in skeletal muscle. LncIRS1 could regulate myoblast proliferation and differentiation in vitro, and muscle mass and mean muscle fibre in vivo. LncIRS1 increases gradually during myogenic differentiation. Mechanistically, lncIRS1 acts as a ceRNA for miR‐15a, miR‐15b‐5p, and miR‐15c‐5p to regulate IRS1 expression, which is the downstream of the IGF1 receptor. Overexpression of lncIRS1 not only increased the protein abundance of IRS1 but also promoted phosphorylation level of AKT (p‐AKT) a central component of insulin‐like growth factor‐1 pathway. Furthermore, lncIRS1 regulates the expression of atrophy‐related genes and can rescue muscle atrophy. Conclusions The newly identified lncIRS1 acts as a sponge for miR‐15 family to regulate IRS1 expression, resulting in promoting skeletal muscle myogenesis and controlling atrophy.

Hepatocellular carcinoma (HCC) is a highly heterogeneous malignant tumor characterized by a high recurrence rate and poor prognosis. In recent years, the study of miRNAs as potential prognostic markers and therapeutic targets, as well as their regulation of the glucose metabolism pathway in HCC, has attracted widespread attention. This study aims to construct a risk model for predicting the prognosis of HCC by analyzing differentially expressed glycolysis-related miRNAs and further explore their relationship with the immune microenvironment and drug sensitivity. In this study, the original mRNA and miRNA expression data of HCC were downloaded from the TCGA and GEO databases, respectively, with a total of 374 TCGA samples and 97 GSE30297 samples collected. A prognostic risk score model for HCC was constructed using LASSO regression analysis, and survival differences between different risk groups were analyzed using Kaplan-Meier curves. Metascape and GSEA analyses were performed for functional enrichment to explore the potential molecular mechanisms of the model miRNAs. Additionally, the CIBERSORT algorithm was used to analyze the immune microenvironment, and the “pRRophetic” package was employed to predict the sensitivity of HCC patients to commonly used chemotherapy drugs. Real-time quantitative PCR (RT-qPCR) was used to detect the expression levels of these glycolysis-metabolism-related miRNAs with prognostic value in tumor tissues and adjacent normal tissues of HCC patients. Through differential expression analysis, a total of 4,421 differentially expressed mRNAs and 106 differentially expressed miRNAs were screened, and 59 glycolysis-metabolism-related differential miRNAs were identified. Cox univariate regression and LASSO regression analysis were used to select 10 prognosis-related miRNAs, and a risk score model based on these miRNAs was constructed. The validation results of the model in both the training and test sets showed that the overall survival (OS) of the high-risk group was significantly lower than that of the low-risk group ( P  < 0.05). The nomogram model further validated the independent predictive value of the risk score for the prognosis of HCC patients. Immune microenvironment analysis revealed that the content of immune cells, such as M0 macrophages and regulatory T cells (Tregs), was higher in the high-risk group, while the content of immune cells, such as resting NK cells, was lower. Drug sensitivity analysis showed that the risk score was significantly correlated with the sensitivity to various chemotherapeutic drugs (e.g., Methotrexate, Paclitaxel). The results of RT-qPCR showed that the expression levels of hsa-mir-454 and hsa-mir-149 were up-regulated in HCC, and the expression level of hsa-mir-621 was down-regulated in HCC. However, the expression level of hsa-mir-653 was not significant in HCC, and the difference was not statistically significant. In patients with recurrent and primary HCC, the results showed significant expression differences between hsa-mir-454 and hsa-mir-621. Specifically, hsa-mir-454 was upregulated in recurrent tumor samples, while hsa-mir-621 was downregulated. Notably, hsa-mir-149 and hsa-mir-653 showed no statistically significant differences between the two groups. This study established a reliable prognostic risk scoring model for HCC by screening differentially expressed glycolysis-related miRNAs, which effectively distinguishes between high-risk and low-risk patients and predicts patient survival. Additionally, the model is closely associated with the immune microenvironment and drug sensitivity, offering strong support for personalized treatment and clinical decision-making in HCC.

Background Current prognostic prediction models of colorectal cancer (CRC) include only the preoperative measurement of tumor markers, with their available repeated postoperative measurements underutilized. CRC prognostic prediction models were constructed in this study to clarify whether and to what extent the inclusion of perioperative longitudinal measurements of CEA, CA19-9, and CA125 can improve the model performance, and perform a dynamic prediction. Methods The training and validating cohort included 1453 and 444 CRC patients who underwent curative resection, with preoperative measurement and two or more measurements within 12 months after surgery, respectively. Prediction models to predict CRC overall survival were constructed with demographic and clinicopathological variables, by incorporating preoperative CEA, CA19-9, and CA125, as well as their perioperative longitudinal measurements. Results In internal validation, the model with preoperative CEA, CA19-9, and CA125 outperformed the model including CEA only, with the better area under the receiver operating characteristic curves (AUCs: 0.774 vs 0.716), brier scores (BSs: 0.057 vs 0.058), and net reclassification improvement (NRI = 33.5%, 95% CI: 12.3 ~ 54.8%) at 36 months after surgery. Furthermore, the prediction models, by incorporating longitudinal measurements of CEA, CA19-9, and CA125 within 12 months after surgery, had improved prediction accuracy, with higher AUC (0.849) and lower BS (0.049). Compared with preoperative models, the model incorporating longitudinal measurements of the three markers had significant NRI (40.8%, 95% CI: 19.6 to 62.1%) at 36 months after surgery. External validation showed similar results to internal validation. The proposed longitudinal prediction model can provide a personalized dynamic prediction for a new patient, with estimated survival probability updated when a new measurement is collected during 12 months after surgery. Conclusions Prediction models including longitudinal measurements of CEA, CA19-9, and CA125 have improved accuracy in predicting the prognosis of CRC patients. We recommend repeated measurements of CEA, CA19-9, and CA125 in the surveillance of CRC prognosis.

Background The biological phenotype of tumours evolves during neoadjuvant chemotherapy (NAC). Accurate prediction of pathological complete response (pCR) to NAC in the early-stage or posttreatment can optimize treatment strategies or improve the breast-conserving rate. This study aimed to develop and validate an autosegmentation-based serial ultrasonography assessment system (SUAS) that incorporated serial ultrasonographic features throughout the NAC of breast cancer to predict pCR. Methods A total of 801 patients with biopsy-proven breast cancer were retrospectively enrolled from three institutions and were split into a training cohort (242 patients), an internal validation cohort (197 patients), and two external test cohorts (212 and 150 patients). Three imaging signatures were constructed from the serial ultrasonographic features before (pretreatment signature), during the first–second cycle of (early-stage treatment signature), and after (posttreatment signature) NAC based on autosegmentation by U-net. The SUAS was constructed by subsequently integrating the pre, early-stage, and posttreatment signatures, and the incremental performance was analysed. Results The SUAS yielded a favourable performance in predicting pCR, with areas under the receiver operating characteristic curve (AUCs) of 0.927 [95% confidence interval (CI) 0.891–0.963] and 0.914 (95% CI 0.853–0.976), compared with those of the clinicopathological prediction model [0.734 (95% CI 0.665–0.804) and 0.610 (95% CI 0.504–0.716)], and radiologist interpretation [0.632 (95% CI 0.570–0.693) and 0.724 (95% CI 0.644–0.804)] in the external test cohorts. Furthermore, similar results were also observed in the early-stage treatment of NAC [AUC 0.874 (0.793–0.955)–0.897 (0.851–0.943) in the external test cohorts]. Conclusions We demonstrate that autosegmentation-based SAUS integrating serial ultrasonographic features throughout NAC can predict pCR with favourable performance, which can facilitate individualized treatment strategies.

Summary The proliferation, apoptosis, and differentiation of myoblasts are essential processes in skeletal muscle development. During this developmental process, microRNAs (miRNAs) play crucial roles. In our previous RNA-seq study (accession number GSE62971), we found that miR-16-5p was differentially expressed between fast and slow growth in chicken. In this study, we report that miR-16-5p could inhibit myoblast proliferation, promote myoblast apoptosis, and repress myoblast differentiation by directly binding to the 3′ UTR of SESN1 , which is also differentially expressed. Overexpression of SESN1 significantly promoted the proliferation, inhibited apoptosis, and induced differentiation of myoblasts. Conversely, its loss of function hampered myoblast proliferation, facilitated myoblast apoptosis, and inhibited myoblast differentiation. Interestingly, we found SESN1 could regulate p53 by a feedback mechanism, thereby participating in the regulation of p53 signaling pathway, which suggests that this feedback is indispensable for myoblast proliferation and apoptosis. Altogether, these data demonstrated that miR-16-5p directly targets SESN1 to regulate the p53 signaling pathway, and therefore affecting myoblast proliferation and apoptosis. Additionally, SESN1 targets myogenic genes to control myoblast differentiation.

Macromolecule bactericides present challenges such as low biocompatibility and not being biodegradable, so broad-spectrum bactericides without accumulated bacteria resistance are now in urgent demand all over the world. Lysozyme, a kind of wide-spread natural enzyme easily extracted from nature, has become attractive for agriculture and medicine use. However, Gram-negative bacterial strains are highly resistant to natural lysozymes, which limits their practical application. In this study, rather than directly modifying antibacterial-active substance with lysozyme, we show an effective way to improve antibacterial performance by altering the hydrophobic functional groups of natural lysozymes and synthesize a type of hydrophobic modified lysozyme (HML). Compared with other modification methods, the antibacterial performance has been increased by over 50%. We investigated its antibacterial mechanism against Gram-negative bacteria and showed that HML could be used to treat pathogenic bacteria without obvious accumulated resistance appearance, which is a great advantage over commercial antibiotics. Overall, it is anticipated that HML could be potentially applied to food safety, infection therapy, and enzyme-medicine applications.