RNA synthetic biology, as a frontier interdisciplinary field, is driving the leap from fundamental research to precision medicine in life sciences through the engineered design of RNA components and the construction of genetic circuits. This paper aims to systematically outline the design principles, key technological breakthroughs, and biomedical applications of synthetic RNA genetic circuits. Building upon this foundation, it provides an in-depth analysis of current research bottlenecks and proposes future development directions. Commencing with a foundational role in the central dogma of RNA, this paper establishes a systematic classification framework for synthetic biology RNA components. At the cis-acting element level, it elaborates on how components such as riboswitches, RNA thermometers, and Toehold switches achieve precise gene expression regulation by responding to specific ligands, temperatures, or trigger RNAs through conformational changes. Concerning trans-acting elements, it delves into the molecular mechanisms of miRNA-mediated gene silencing, the high stability and “sponge-like adsorption” function conferred by the closed-loop structure of circRNA, the targeting role of siRNA within the RNAi pathway, and the targeting specificity of sgRNA within the CRISPR system. The paper emphasizes that rational design, sequence optimization, and chemical modifications can significantly enhance the performance and orthogonality of these natural elements. Secondly, the paper focuses on the design and optimization strategies for synthetic RNA regulatory modules. Taking miRNA-responsive circRNA switches as an example, it elucidates the principles of customized miRNA responsiveness. The engineering applications of circRNA are explored, introducing strategies for constructing functional RNA nanostructures via siRNA self-assembly. Building upon this, the paper emphasizes synthetic genetic circuits: from logical operations to resource allocation, enabling advanced cellular logic and functional regulation. For instance, by combining transcriptional cascade switches or utilizing the CRISPR-Cas13a system, an AND logic gate responsive to multiple miRNAs (such as miRNA-155 and miRNA-21) was constructed, significantly enhancing the specificity of disease diagnosis. Addressing the challenges of resource competition and expression noise faced by synthetic circuits within cells, this paper introduces computational models such as MIRELLA, with particular emphasis on the design of endogenous miRNA-based iFFLs. These advanced circuits, illustrated in this paper, have been successfully applied to real-time monitoring of cellular differentiation states and regulation of stem cell-directed differentiation. For cellular state detection and dynamic regulation, miRNA switches can be integrated with fluorescent systems to track differentiation statuses in real time via fluorescent signal changes. Synthetic genetic circuits, meanwhile, utilize endogenous miRNA logic integration alongside miSFITs technology to achieve state-specific protein regulation in human pluripotent stem cells, laying the groundwork for customized cellular control. This approach ingeniously harnesses intrinsic cellular regulatory mechanisms to buffer gene expression burdens, thereby enhancing circuit robustness. These advanced circuits, illustrated schematically herein, have been successfully applied to real-time monitoring of cellular differentiation states and regulation of stem cell-directed differentiation. At the therapeutic translation level, the paper systematically reviews application strategies for RNA technologies across multiple fields, including cancer, metabolic diseases, neurodegenerative diseases, cardiovascular diseases, regenerative medicine engineering, immunotherapy, and vaccine applications. For instance, in cancer treatment, specific killing of tumor cells is achieved by embedding targets for miRNAs specific to healthy cells within the genomes of oncolytic viruses (such as Zika virus). Within metabolic and degenerative diseases, LNP-delivered mRNA therapeutics and antisense oligonucleotide (ASO) technologies have demonstrated significant clinical progress. Finally, this paper highlights ongoing challenges in the field, including limited programmability of RNA elements, low in vivo delivery efficiency, and inadequate off-target risk assessment systems. It advocates for future integration of epigenomics and computational modelling to optimize element functionality, establishing an integrated “element-circuit-delivery” platform. Furthermore, leveraging single-cell sequencing and organoid technologies to develop a multidimensional safety assessment system is proposed to advance the deep integration and translation of RNA synthetic biology in personalized medicine. Consequently, RNA engineering has transcended single-dimensional regulation, evolving towards multi-layered, dynamic, and intelligent synthetic biological systems. Its deep integration with clinical needs will reshape disease diagnosis and treatment paradigms.

RNA synthetic biology, as a frontier interdisciplinary field, is driving the leap from fundamental research to precision medicine in life sciences through the engineered design of RNA components and the construction of genetic circuits. This paper aims to systematically outline the design principles, key technological breakthroughs, and biomedical applications of synthetic RNA genetic circuits. Building upon this foundation, it provides an in-depth analysis of current research bottlenecks and proposes future development directions. Commencing with a foundational role in the central dogma of RNA, this paper establishes a systematic classification framework for synthetic biology RNA components. At the cis-acting element level, it elaborates on how components such as riboswitches, RNA thermometers, and Toehold switches achieve precise gene expression regulation by responding to specific ligands, temperatures, or trigger RNAs through conformational changes. Concerning trans-acting elements, it delves into the molecular mechanisms of miRNA-mediated gene silencing, the high stability and “sponge-like adsorption” function conferred by the closed-loop structure of circRNA, the targeting role of siRNA within the RNAi pathway, and the targeting specificity of sgRNA within the CRISPR system. The paper emphasizes that rational design, sequence optimization, and chemical modifications can significantly enhance the performance and orthogonality of these natural elements. Secondly, the paper focuses on the design and optimization strategies for synthetic RNA regulatory modules. Taking miRNA-responsive circRNA switches as an example, it elucidates the principles of customized miRNA responsiveness. The engineering applications of circRNA are explored, introducing strategies for constructing functional RNA nanostructures via siRNA self-assembly. Building upon this, the paper emphasizes synthetic genetic circuits: from logical operations to resource allocation, enabling advanced cellular logic and functional regulation. For instance, by combining transcriptional cascade switches or utilizing the CRISPR-Cas13a system, an AND logic gate responsive to multiple miRNAs (such as miRNA-155 and miRNA-21) was constructed, significantly enhancing the specificity of disease diagnosis. Addressing the challenges of resource competition and expression noise faced by synthetic circuits within cells, this paper introduces computational models such as MIRELLA, with particular emphasis on the design of endogenous miRNA-based iFFLs. These advanced circuits, illustrated in this paper, have been successfully applied to real-time monitoring of cellular differentiation states and regulation of stem cell-directed differentiation. For cellular state detection and dynamic regulation, miRNA switches can be integrated with fluorescent systems to track differentiation statuses in real time via fluorescent signal changes. Synthetic genetic circuits, meanwhile, utilize endogenous miRNA logic integration alongside miSFITs technology to achieve state-specific protein regulation in human pluripotent stem cells, laying the groundwork for customized cellular control. This approach ingeniously harnesses intrinsic cellular regulatory mechanisms to buffer gene expression burdens, thereby enhancing circuit robustness. These advanced circuits, illustrated schematically herein, have been successfully applied to real-time monitoring of cellular differentiation states and regulation of stem cell-directed differentiation. At the therapeutic translation level, the paper systematically reviews application strategies for RNA technologies across multiple fields, including cancer, metabolic diseases, neurodegenerative diseases, cardiovascular diseases, regenerative medicine engineering, immunotherapy, and vaccine applications. For instance, in cancer treatment, specific killing of tumor cells is achieved by embedding targets for miRNAs specific to healthy cells within the genomes of oncolytic viruses (such as Zika virus). Within metabolic and degenerative diseases, LNP-delivered mRNA therapeutics and antisense oligonucleotide (ASO) technologies have demonstrated significant clinical progress. Finally, this paper highlights ongoing challenges in the field, including limited programmability of RNA elements, low in vivo delivery efficiency, and inadequate off-target risk assessment systems. It advocates for future integration of epigenomics and computational modelling to optimize element functionality, establishing an integrated “element-circuit-delivery” platform. Furthermore, leveraging single-cell sequencing and organoid technologies to develop a multidimensional safety assessment system is proposed to advance the deep integration and translation of RNA synthetic biology in personalized medicine. Consequently, RNA engineering has transcended single-dimensional regulation, evolving towards multi-layered, dynamic, and intelligent synthetic biological systems. Its deep integration with clinical needs will reshape disease diagnosis and treatment paradigms.

Objective: To investigate the status of condom use and its influencing factors among men who have sex with men (MSM), so as to provide a basis for improving condom utilization rates and AIDS prevention and control in this population. Methods: From May to October 2024, a snowball sampling method was employed to recruit MSM in Songjiang District, Shanghai Municipality. Self-administered questionnaires were used to collect data on demographic characteristics, AIDS-related knowledge, sexual behaviors, pre-exposure prophylaxis (PrEP) and post-exposure prophylaxis (PEP), and condom use in the past six months. Multivariable logistic regression model was used to analyze the influencing factors for consistent condom use. Results: A total of 921 MSM were surveyed, with a median age of 29.00 (interquartile range, 9.00) years. Among them, 697 (75.68%) were aware of AIDS-related knowledge, 826 (89.69%) expressed willingness to use PrEP, and 835 (90.66%) were willing to use PEP. Additionally, 787 (85.45%) MSM reported their age at first homosexual intercourse as ≥18 years, while 519 (56.35%) reported consistent condom use in the past six months. Multivariable logistic regression analysis revealed that MSM who were aware of AIDS-related knowledge (OR=0.582, 95% CI: 0.423-0.801), willing to use PrEP (OR =0.611, 95% CI: 0.385-0.969), and whose age at first homosexual intercourse was <18 years (OR=0.480, 95% CI: 0.330-0.700) were less likely to consistent use condoms. Conclusion The proportion of consistent condom use among the MSM remains relatively low, which is primarily associated with AIDS-related knowledge, willingness to use PrEP, and the age at first homosexual intercourse.

Objective To investigate the mechanism of Achyranthoside Ⅰ inhibits pyroptosis in chondrocytes through the nuclear factor-κB(NF-κB)/NOD receptor protein structure domain related proteins 3(NLRP3)/cystine containing aspartate specific proteins-1(caspase-1)signaling pathway.Methods Primary mouse chondrocytes were divided into blank group(phosphate buffered solution with the same volume),model group[10 ng·mL-1 interleukin-1β(IL-1 β)],control group(10 ng·mL-1 IL-1β+20 μmol·L-1 celecoxib)and experimental group(10 ng·mL-1 IL-1β+3 μg·mL-1 Achyranthoside Ⅰ).After 24 hours of intervention,the cell proliferation was measured by cell counting kit 8,the levels of superoxide dismutase(SOD),malondialdehyde(MDA),IL-1 and IL-6 were detected by enzyme-linked immunosorbent assay,the protein expression levels of NF-κB p65,NLRP3 and caspase-1 were detected by Western Blot.Results The apoptosis rates in experimental,control,model and blank groups were(13.34±0.61)％,(15.64±1.01)％,(21.81±1.10)％and 0;the SOD levels were(147.03±16.49),(130.09±7.33),(122.03±10.71)and(164.40±22.74)nU·mL-1;the MDA levels were(6.43±0.71),(7.63±1.01),(8.89±1.84)and(5.69±0.81)nmol·L-1;the IL-1 levels were(338.69±40.95),(361.78±32.15),(391.44±30.59)and(289.23±25.19)pg·mL-1;the IL-6 levels were(89.96±8.81),(101.10±11.59),(120.39±14.71)and(60.29±6.03)pg·mL-1;the relative expression levels of NF-κB p65 were 0.68±0.05,0.97±0.05,1.26±0.05 and 0.57±0.05;the relative expression levels of NLRP3 were 0.71±0.08,1.02±0.10,1.50±0.06 and 0.31±0.05;the relative expression levels of caspase-1 were 0.70±0.07,1.29±0.08,1.66±0.07 and 0.51±0.07,respectively.Compared with the model group,the differences of above indexes were statistically significant in the experimental group(all P＜0.05).Conclusion Achyranthoside Ⅰ can improve the oxidative stress status induced by IL-1 β in chondrocytes,reduce the expression of proteins related to the NF-κB signaling pathway,and thereby decrease the occurrence of caspase-1 dependent pyroptosis,providing a protective effect on chondrocytes.

Objective To investigate the mechanism of Achyranthoside Ⅰ inhibits pyroptosis in chondrocytes through the nuclear factor-κB(NF-κB)/NOD receptor protein structure domain related proteins 3(NLRP3)/cystine containing aspartate specific proteins-1(caspase-1)signaling pathway.Methods Primary mouse chondrocytes were divided into blank group(phosphate buffered solution with the same volume),model group[10 ng·mL-1 interleukin-1β(IL-1 β)],control group(10 ng·mL-1 IL-1β+20 μmol·L-1 celecoxib)and experimental group(10 ng·mL-1 IL-1β+3 μg·mL-1 Achyranthoside Ⅰ).After 24 hours of intervention,the cell proliferation was measured by cell counting kit 8,the levels of superoxide dismutase(SOD),malondialdehyde(MDA),IL-1 and IL-6 were detected by enzyme-linked immunosorbent assay,the protein expression levels of NF-κB p65,NLRP3 and caspase-1 were detected by Western Blot.Results The apoptosis rates in experimental,control,model and blank groups were(13.34±0.61)％,(15.64±1.01)％,(21.81±1.10)％and 0;the SOD levels were(147.03±16.49),(130.09±7.33),(122.03±10.71)and(164.40±22.74)nU·mL-1;the MDA levels were(6.43±0.71),(7.63±1.01),(8.89±1.84)and(5.69±0.81)nmol·L-1;the IL-1 levels were(338.69±40.95),(361.78±32.15),(391.44±30.59)and(289.23±25.19)pg·mL-1;the IL-6 levels were(89.96±8.81),(101.10±11.59),(120.39±14.71)and(60.29±6.03)pg·mL-1;the relative expression levels of NF-κB p65 were 0.68±0.05,0.97±0.05,1.26±0.05 and 0.57±0.05;the relative expression levels of NLRP3 were 0.71±0.08,1.02±0.10,1.50±0.06 and 0.31±0.05;the relative expression levels of caspase-1 were 0.70±0.07,1.29±0.08,1.66±0.07 and 0.51±0.07,respectively.Compared with the model group,the differences of above indexes were statistically significant in the experimental group(all P＜0.05).Conclusion Achyranthoside Ⅰ can improve the oxidative stress status induced by IL-1 β in chondrocytes,reduce the expression of proteins related to the NF-κB signaling pathway,and thereby decrease the occurrence of caspase-1 dependent pyroptosis,providing a protective effect on chondrocytes.

OBJECTIVES: To investigate the risk factors for the occurrence of cardiopulmonary dysfunction following ligation of hemodynamically significant patent ductus arteriosus (hsPDA) in preterm infants. METHODS: A retrospective collection of clinical data was conducted on preterm infants with a gestational age of <34 weeks who were admitted to the Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology from January 2018 to August 2024. These infants underwent hsPDA ligation after 1-2 courses of failed ibuprofen treatment. Based on the occurrence of blood pressure changes and oxygenation or ventilation failure postoperatively, the infants were divided into a cardiopulmonary dysfunction group (19 cases) and a non-cardiopulmonary dysfunction group (40 cases). Binary logistic regression analysis was performed to explore risk factors for postoperative cardiopulmonary dysfunction. RESULTS: Binary logistic regression analysis indicated that a faster average weight gain rate preoperatively and low levels of free triiodothyronine (FT₃) within one week before surgery were risk factors for cardiopulmonary dysfunction following hsPDA ligation (P<0.05). Receiver operating characteristic curve analysis showed that an average weight gain rate >11.45 g/(kg·d) and FT₃ levels <2.785 pmol/L within one week before surgery had predictive value for postoperative cardiopulmonary dysfunction (P<0.05). The combination of these two indicators provided the highest predictive value (P<0.05), with an area under the curve of 0.825, a sensitivity of 79%, and a specificity of 75%. CONCLUSIONS An average weight gain rate exceeding 11.45 g/(kg·d) and FT₃ levels below 2.785 pmol/L within one week before surgery are risk factors affecting cardiopulmonary function after hsPDA ligation. Preoperative assessment and intervention should be strengthened to reduce the risk of postoperative complications.
Humans ; Ductus Arteriosus, Patent/physiopathology* ; Risk Factors ; Female ; Infant, Newborn ; Male ; Retrospective Studies ; Infant, Premature ; Ligation/adverse effects* ; Hemodynamics ; Postoperative Complications/etiology* ; Logistic Models ; Lung Diseases/etiology*

The intelligent oxygen management system is a software designed with various algorithms to automatically titrate inhaled oxygen concentration according to specific patterns. This system can be integrated into various ventilator devices and used during assisted ventilation processes, aiming to maintain the patient's blood oxygen saturation within a target range. This paper employs a scoping review methodology, focusing on research related to intelligent oxygen management systems in neonatal intensive care units. It reviews the fundamental principles, application platforms, and clinical outcomes of these systems, providing a theoretical basis for clinical implementation.
Humans ; Intensive Care Units, Neonatal ; Infant, Newborn ; Oxygen/administration & dosage* ; Oxygen Inhalation Therapy/methods* ; Respiration, Artificial

Lithium(Li)salts are commonly used as psychotropic medications for the treatment of major depressive disorders.However,long-term use of Li salts poses a high risk of toxicity,necessitating continuous monitoring of Li concentration in patient blood to ensure medication safety,which is crucial for clinical treatment.Laser-induced breakdown spectroscopy(LIBS),as a rapid analytical technique,has been widely applied in the elemental analysis of complex matrices in various practical scenarios.In this study,LIBS technology combined with partial least squares(PLS)was employed for quantitative analysis of Li elements in blood matrix.A total of 45 clinical blood samples were utilized,and the quantitative models for plasma and whole blood matrices were separately investigated.The number of latent variables in the PLS algorithm was optimized using a five-fold cross-validation method.Results revealed that the PLS quantitative model constructed on the basis of plasma matrix achieved a predictive determination coefficient(R2)of 0.992,a predictive root mean square error(RMSEP)of 0.204 μg/mL,and a relative standard error(RSD)of 2.14%.In contrast,for the PLS quantitative model constructed on the basis of whole blood matrix,the R2 was 0.984,the RMSEP was 0.728 μg/mL,and the RSD was 3.45%Consequently,the LIBS model constructed on the basis of plasma calibration values demonstrated superior performance in quantitative analysis of Li element in whole blood,and LIBS technology provided a new possibility for rapid assessment of blood Li levels in clinical practice,with promising prospects for application.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Background/Aims: Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients. Methods: We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development. Results: Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients. Conclusions Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.