The association between emotional regulation dimensions and somatic symptom disorders: A systematic review and meta-analysis.

Clarifying the effect size of the association between somatic symptom disorders (SSDs) and defects in emotional regulation (ER) dimensions through a meta-analysis may improve ER-related treatment for SSD patients. SSDs exhibited a lower level of adaptive ER (overall Hedge's g = -0.618, 95 %CI [0.872, -0.365]; Hedge's g for ER dimensions of Awareness, Description, Clarity, Acceptance, Tolerance, Self-efficacy belief, and Cognitive Reappraisal ranged from -0.451 to -1.344). Maladaptive ER dimensions (catastrophizing and expressive inhibition) showed no significant associations with SSDs. Psychotherapy focusing on developing adaptive ER rather than reducing maladaptive ER may be a more promising approach for treating SSD patients.

[Differences in Soil Fertility and Bacterial Community Structure Between Carbon Inputs such as Biochar and Organic Fertilizer and Their Relationship].

The potato planting area of Guizhou Province ranks second in China. However, due to factors such as climatic conditions and unbalanced fertilization, soil organic matter in potato fields is consumed rapidly and has a large deficit, which affects soil biological function and soil fertility. Biochar and organic fertilizer are effective ways to supplement foreign aid organic matter to improve soil quality. However, the differences in soil fertility and microbial community structure and their relationships under the conditions of organic fertilizer or biochar combined with chemical fertilizer are not clear. In this study, three treatments of conventional fertilization （NPK）, increased application of biochar （NPKB）, and increased application of organic fertilizer （NPKO） were set up to investigate the characteristics of potato rhizosphere soil, bacterial community composition, and diversity； to analyze the effects of these factors on the soil integrated fertility index； and to explore the direct and indirect effects of IFI on soil fertility and bacterial community structure differences between treatments and their driving factors. The results showed that soil pH, available phosphorus （AP）, available potassium （AK）, total nitrogen （TN）, organic carbon （SOC）, and C/N ratio were significantly higher in the NPKB and NPKO treatments than in the NPK treatment （P<0.05）. Soil IFI was greatest for NPKO, followed by NPKB and least for the NPK treatment. A total of 8 214 ASVs were obtained from all the soil samples, belonging to 26 phyla, 75 classes, 165 orders, 176 families, and 251 genera （excluding unidentified fungi）. Proteobacteria, Actinobacteria, and Chloroflexi were the dominant phyla, accounting for 54.85% of all ASVs. Compared to that in the NPK and NPKB treatments, the NPKO treatment had the highest bacterial diversity and number of significantly different taxa, and soil AN, AP, AK, SOC, TN, and IFI were significant correlates of bacterial diversity index （P<0.05）. Additionally, pH, TN, and SOC were significant influencers of bacterial taxa differences （P<0.05）, with importance ranked as TN （70.59%） > SOC （49.42%） > pH （27.08%）. Structural equations suggested that pH-related soil properties and bacterial community diversity were the direct pathways influencing IFI, and soil pH-related soil characteristics could also indirectly affect IFI by affecting bacterial Shannon diversity. These results indicate that soil fertility and bacterial community structure were significantly different and correlated between the biochar and organic fertilizer addition treatments and that pH and bacterial community diversity were the key factors influencing IFI, with the NPKO treatment in particular having the best effect on improving IFI. Considering the effect of soil fertilization and the functional group of bacteria, NPKO is the recommended combination for the best synergistic effect of soil fertilization, that is, N 150 kg·hm-2+P2O5 135 kg·hm-2+K2O 135 kg·hm-2+organic fertilizer 6.6 t·hm-2.

Entropy drives the ligand recognition in G-protein-coupled receptor subtypes.

Achieving ligand subtype selectivity within highly homologous subtypes of G-protein-coupled receptor (GPCR) is critical yet challenging for GPCR drug discovery, primarily due to the unclear mechanism underlying ligand subtype selectivity, which hampers the rational design of subtype-selective ligands. Herein, we disclose an unusual molecular mechanism of entropy-driven ligand recognition in cannabinoid (CB) receptor subtypes, revealed through atomic-level molecular dynamics simulations, cryoelectron microscopy structure, and mutagenesis experiments. This mechanism is attributed to the distinct conformational dynamics of the receptor's orthosteric pocket, leading to variations in ligand binding entropy and consequently, differential binding affinities, which culminate in specific ligand recognition. We experimentally validated this mechanism and leveraged it to design ligands with enhanced or ablated subtype selectivity. One such ligand demonstrated favorable pharmacokinetic properties and significant efficacy in rodent inflammatory analgesic models. More importantly, it is precisely due to the high subtype selectivity obtained based on this mechanism that this ligand does not show addictive properties in animal models. Our findings elucidate the unconventional role of entropy in CB receptor subtype selectivity and suggest a strategy for rational design of ligands to achieve entropy-driven subtype selectivity for many pharmaceutically important GPCRs.

Knowledge, attitudes and practices of nurses regarding airway clearance in neurocritical illness patients: A cross-sectional study.

AIM: We aimed to assess the level of knowledge, attitudes and practices regarding airway clearance among nurses and explore the factors affecting the knowledge, attitudes and practices. DESIGN: A questionnaire-based cross-sectional study. BACKGROUND: Airway clearance is an important method of eliminating excess secretions. In neuroscience nursing, nurses are important executors of airway management, and their knowledge, attitudes and practices can influence the effectiveness of airway clearance. METHODS: This study was conducted from July to September 2023 in four hospitals in Jiangsu Province, China. A structured questionnaire about airway clearance was designed and used to collect the data. The nurses used this questionnaire to self-rate. The STROBE checklist for cross-sectional studies was followed. RESULTS: The age, work experience, highest educational attainment and technical title of the nurses can significantly influence their knowledge. The age, highest educational attainment and technical title of the nurses can significantly impact their attitudes. Practice scores were significantly influenced by age, work experience, technical title, whether the nurses had received any training on airway clearance techniques, and whether the department developed procedures for implementing the airway clearance technology. Nurses' attitudes were significantly associated with knowledge and practice, and there was no significant correlation between knowledge and practice. CONCLUSION: This study showed that age, work experience, highest educational attainment and training were related to knowledge, attitudes and practices. These findings suggest that nursing managers can conduct airway clearance training according to age group, working experience and education level of the nurses. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. IMPACT: The findings show that the level of knowledge, attitudes and practices related to airway clearance in neuroscience nursing among nurses were acceptable, which means that nurses can better perform airway management on patients. These findings serve as a significant reference for designing an airway clearance education for nurses and meet the needs of nurses in clinical nursing practice.

In vivo determination of the bioavailability of folic acid through the utilization of the PBPK model in conjunction with UPLC.

This paper employed a physiologically based pharmacokinetic model (PBPK) to investigate the transformations of folic acid and its metabolites in vivo. Additionally, an ultra-performance liquid chromatography (UPLC) method was developed to accurately measure the body's retention rate and conversion rate of folic acid, tetrahydrofolate, and 5-methyltetrahydrofolate. Furthermore, the bioavailability of folic acid in the body was assessed by combining this method with an evaluation technique for animal models. The study found that the gastric metabolism time was 2 h, while the small intestinal metabolism duration was 4 h. The maximum conversion rate was observed in plasma and liver after 6 h, and in the brain after 8 h. This serves as a framework for creating a model to assess the bioavailability of folic acid in living organisms, to enhance the safety and efficacy of folic acid intake.

Obesity-enriched gut microbe degrades myo-inositol and promotes lipid absorption.

Numerous studies have reported critical roles for the gut microbiota in obesity. However, the specific microbes that causally contribute to obesity and the underlying mechanisms remain undetermined. Here, we conducted shotgun metagenomic sequencing in a Chinese cohort of 631 obese subjects and 374 normal-weight controls and identified a Megamonas-dominated, enterotype-like cluster enriched in obese subjects. Among this cohort, the presence of Megamonas and polygenic risk exhibited an additive impact on obesity. Megamonas rupellensis possessed genes for myo-inositol degradation, as demonstrated in vitro and in vivo, and the addition of myo-inositol effectively inhibited fatty acid absorption in intestinal organoids. Furthermore, mice colonized with M. rupellensis or E. coli heterologously expressing the myo-inositol-degrading iolG gene exhibited enhanced intestinal lipid absorption, thereby leading to obesity. Altogether, our findings uncover roles for M. rupellensis as a myo-inositol degrader that enhances lipid absorption and obesity, suggesting potential strategies for future obesity management.

Long-term trends in lifestyle factors among respondents with dyslipidemia in the United States.

OBJECTIVES: To explore the long-term trends in unhealthy lifestyle factors and the risk sociodemographic subgroups among people with dyslipidemia. METHODS: Data extracted from the 1999 to 2018 National Health and Nutrition Examination Survey (NHANES). Lifestyle factors were smoking status, alcohol drinking, obesity, dietary quality, depression, physical activity, and sedentary behavior. A Joinpoint regression model was used to estimate trends in the log-transformed age-standardized prevalence. Multinomial logistic regression models adjusted for age, sex, and race/ethnicity were used to analyze subgroups by sociodemographic factors. RESULTS: Data for 33,680 respondents were extracted between 1999 and 2018. The prevalence of smoking and poor-quality diet decreased from 1999 to 2018 (P<0.001), while obesity significantly increased (P<0.001). The prevalence of depression marginally increased from 2005 to 2018 (P=0.074). We observed that non-Hispanic Black individuals, Hispanics, males, as well as those with lower family income-to-poverty ratios and education levels, unemployed individuals, or those lacking a spouse/live-in partner, were at elevated risk of unhealthy lifestyle factors when compared to the reference groups. CONCLUSIONS: Among NHANES respondents from 1999 to 2018 with dyslipidemia, significant reductions in the prevalence of current smoking and poor diet were observed, while the prevalence of obesity was markedly increased. There were sociodemographic differences in the management of lifestyle factors. Further initiatives to encourage people with dyslipidemia are required to reduce potential adverse outcomes.

Risk assessment and prediction of nosocomial infections based on surveillance data using machine learning methods.

BACKGROUND: Nosocomial infections with heavy disease burden are becoming a major threat to the health care system around the world. Through long-term, systematic, continuous data collection and analysis, Nosocomial infection surveillance (NIS) systems are constructed in each hospital; while these data are only used as real-time surveillance but fail to realize the prediction and early warning function. Study is to screen effective predictors from the routine NIS data, through integrating the multiple risk factors and Machine learning (ML) methods, and eventually realize the trend prediction and risk threshold of Incidence of Nosocomial infection (INI). METHODS: We selected two representative hospitals in southern and northern China, and collected NIS data from 2014 to 2021. Thirty-nine factors including hospital operation volume, nosocomial infection, antibacterial drug use and outdoor temperature data, etc. Five ML methods were used to fit the INI prediction model respectively, and to evaluate and compare their performance. RESULTS: Compared with other models, Random Forest showed the best performance (5-fold AUC = 0.983) in both hospitals, followed by Support Vector Machine. Among all the factors, 12 indicators were significantly different between high-risk and low-risk groups for INI (P < 0.05). After screening the effective predictors through importance analysis, prediction model of the time trend was successfully constructed (R2 = 0.473 and 0.780, BIC = -1.537 and -0.731). CONCLUSIONS: The number of surgeries, antibiotics use density, critical disease rate and unreasonable prescription rate and other key indicators could be fitted to be the threshold predictions of INI and quantitative early warning.

Phage display-derived alpaca nanobodies as potential therapeutics for Naja atra snake envenomation.

Naja atra, the Chinese cobra, is a major cause of snake envenomation in Asia, causing hundreds of thousands of clinical incidents annually. The current treatment, horse serum-derived antivenom, has unpredictable side effects and presents manufacturing challenges. This study focused on developing new-generation snake venom antidotes by using microbial phage display technology to derive nanobodies from an alpaca immunized with attenuated N. atra venom. Following confirmation of the immune response in the alpaca, we amplified VHH genes from isolated peripheral blood mononuclear cells and constructed a phage display VHH library of 1.0 × 107 transformants. After four rounds of biopanning, the enriched phages exhibited increased binding activity to N. atra venom. Four nanobody clones with high binding affinities were selected: aNAH1, aNAH6, aNAH7, and aNAH9. Specificity testing against venom from various snake species, including two Southeast Asian cobra species, revealed nanobodies specific to the genus Naja. An in vivo mouse venom neutralization assay demonstrated that all nanobodies prolonged mouse survival and aNAH6 protected 66.6% of the mice from the lethal dosage. These findings highlight the potential of phage display-derived nanobodies as valuable antidotes for N. atra venom, laying the groundwork for future applications in snakebite treatment.IMPORTANCEChinese cobra venom bites present a formidable medical challenge, and current serum treatments face unresolved issues. Our research applied microbial phage display technology to obtain a new, effective, and cost-efficient treatment approach. Despite interest among scientists in utilizing this technology to screen alpaca antibodies against toxins, the available literature is limited. This study makes a significant contribution by introducing neutralizing antibodies that are specifically tailored to Chinese cobra venom. We provide a comprehensive and unbiased account of the antibody construction process, accompanied by thorough testing of various nanobodies and an assessment of cross-reactivity with diverse snake venoms. These nanobodies represent a promising avenue for targeted antivenom development that bridges microbiology and biotechnology to address critical health needs.

AI-assisted discovery of high-temperature dielectrics for energy storage.

Electrostatic capacitors play a crucial role as energy storage devices in modern electrical systems. Energy density, the figure of merit for electrostatic capacitors, is primarily determined by the choice of dielectric material. Most industry-grade polymer dielectrics are flexible polyolefins or rigid aromatics, possessing high energy density or high thermal stability, but not both. Here, we employ artificial intelligence (AI), established polymer chemistry, and molecular engineering to discover a suite of dielectrics in the polynorbornene and polyimide families. Many of the discovered dielectrics exhibit high thermal stability and high energy density over a broad temperature range. One such dielectric displays an energy density of 8.3 J cc-1 at 200 °C, a value 11 × that of any commercially available polymer dielectric at this temperature. We also evaluate pathways to further enhance the polynorbornene and polyimide families, enabling these capacitors to perform well in demanding applications (e.g., aerospace) while being environmentally sustainable. These findings expand the potential applications of electrostatic capacitors within the 85-200 °C temperature range, at which there is presently no good commercial solution. More broadly, this research demonstrates the impact of AI on chemical structure generation and property prediction, highlighting the potential for materials design advancement beyond electrostatic capacitors.

Nonlinearly coupled electro-osmotic flow in variable charge soils.

Electro-osmosis has been valued as a promising technology to enhance the dewatering of waste sludge, stabilization and environmental remediation of soils with low permeability. However, the coefficient of electro-osmotic permeability (keo) is commonly taken as constant value which is particularly not the case in variable charge soil. As a result, the nonlinearity of the electro-osmotic flow (EOF) and the direction reverse could not be interpreted. Herein, the electro-chemical parameters were monitored in electro-osmotic experiment with natural variable charge soil. It was observed that the evolutions showed significant nonlinear behavior and were correlated. The comprehensive Zeta potential model proposed by the authors was applied to simulate the nonlinear keo induced by the variable pH and electrolyte concentration. The agreement between tested and simulated flow rate variation and excess pore water pressure distribution demonstrated the reliability of the theory. The error rate of the simulations through coupling nonlinear keo and voltage gradient Ex was reduced to 29.4% from 381.9% of calculations with constant parameters. The direction reverse of EOF was innovatively interpreted. Hence, the numerical model would act as a useful tool to connect these electro-chemical parameters and provide guidance to evaluate contributions of commonly used pH conditioning measurements.

Robust, scalable, and highly selective spirocyclic catalysts for industrial hydroformylation and isomerization-hydroformylation.

Hydroformylation (HF) or isomerization-hydroformylation (ISO-HF) represents the most direct and practical route for producing aldehydes on an industrial scale. To resolve the issues of low activity, low linear/branched (l/b) ratio, and low stability in HF and ISO-HF, we herein reported a class of spirocyclic diphosphites. Notably, the ligand termed O-SDPhite afforded excellent catalytic activity and regioselectivity for the HF of various olefins. Excellent l/b ratio and an unprecedented turnover number of up to 17,620,000 were achieved. O-SDPhite was also found to be effective in the regioselective ISO-HF of the industrially related cheap and abundant C4 Raffinates to n-valeraldehyde produced on a multimillion-ton scale. The reaction with O-SDPhite, superior to that of benchmark Biphephos, was continuously operated for 41 days and afforded an average 38.6 l/b ratio (31 days and 14.7 l/b ratio for Biphephos).

Electric fields reverse the differentiation of keratinocyte monolayer by down-regulating E-cadherin through PI3K/AKT/Snail pathway.

Re-epithelialization is an important step in skin wound healing, referring to the migration, proliferation, and differentiation of keratinocytes around the wound. During this process, the edges of the wound begin to form new epithelial cells, which migrate from the periphery of the wound towards the center, gradually covering the entire wound area. These newly formed epithelial cells proliferate and differentiate, ultimately forming a protective layer over the exposed dermal surface. Wound endogenous electric fields (EFs) are known as the dominant factor to facilitate the epidermal migration to wound center. However, the precise mechanisms by which EFs promote epidermal migration remains elusive. Here, we found that in a model of cultured keratinocyte monolayer in vitro, EFs application reversed the differentiation of cells, as indicated by the reduction of the early differentiation markers K1 and K10. Genetic manipulation confirmed that EFs reversed keratinocyte differentiation through down-regulating the E-cadherin-mediated adhesion. By RNA-sequencing analysis, we screened out Snail as the transcription suppressor of E-cadherin. Snail knockdown abolished the down-regulation of E-cadherin and the reversal of differentiation induced by EFs. KEGG analysis identified PI3K/AKT signaling for Snail induction under EFs. Inhibition of PI3K by LY294002 diminished the EFs-induced AKT activation and Snail augmentation, largely restoring the level of E-cadherin reduced by EFs. Finally, in model of full-thickness skin wounds in pigs, we found that weakening of the wound endogenous EFs by the direction-reversed exogenous EFs resulted in an up-regulation of E-cadherin and earlier differentiation in newly formed epidermis in vivo. Our research suggests that electric fields (EFs) decrease E-cadherin expression by suppressing the PI3K/AKT/Snail pathway, thereby reversing the differentiation of keratinocytes. This discovery provides us with new insights into the role of electric fields in wound healing. EFs intervene in intracellular signaling pathways, inhibiting the expression of E-cadherin, which results in a lower differentiation state of keratinocytes. In this state, keratinocytes exhibit increased migratory capacity, facilitating the migration of epidermal cells and wound reepithelialization.

Topological photonic crystal nanowire array laser with bulk states.

A topological photonic crystal InGaAsP/InP core-shell nanowire array laser with bulk states operating in the 1550 nm band is proposed and simulated. By optimizing the structure parameters, high Q factor of 1.2 × 105 and side-mode suppression ratio of 13.2 dB are obtained, which are 28.6 and 4.6 times that of a uniform nanowire array, respectively. The threshold and maximum output are 17% lower and 613% higher than that of the uniform nanowire array laser, respectively, due to the narrower nanowire slits and stronger optical confinement. In addition, a low beam divergence angle of 2° is obtained due to the topological protection. This work may pave the way for the development of high-output, low-threshold, low-beam-divergence nanolasers.

Urban landscape sustainability in karst mountainous cities: A landscape resilience perspective.

In the context of the rapid progress of global urbanization, the massive encroachment of social landscapes into ecological and productive landscapes has led to a series of environmental problems. Furthermore, analyzing the landscape resilience could effectively reveal the sustainable development ability of the urban landscape. This study establishes a social-ecological productive landscape resilience (SEPLR) evaluation system and reveals trade-offs and synergies between different landscape types and resilience. Finally, this study provides landscape management zonings based on the spatial and temporal dynamic characteristics of landscape resilience and subsystem resilience. The findings showed that: (1) The CUAG has significant landscape heterogeneity and change drastically, which is mainly manifested by the massive encroachment of social landscape into productive landscape. (2) The SEPLR of CUAG decreased slightly by 0.75 % over the decade, with significant changes of spatial distribution. (3) The comprehensive remediation areas and social development areas are the dominant management zones. The findings could be incorporated into the decision-making of land use trade-off development in CUAG to promote the coordinated development of social-ecological productive systems and improve the sustainability of urban landscape.

A multimodal physiological and psychological dataset for human with mental stress induced myocardial ischemia.

Accurate differentiation between angina with no obstructive coronary arteries (ANOCA) and mental stress-induced myocardial ischemia (MSIMI) is crucial for tailored treatment strategies, yet public data scarcity hampers understanding. Given the higher incidence of both conditions in women, this study prospectively enrolled 80 female ANOCA and 39 age-matched female controls, subjecting them to three types of mental stress tasks. ECGs were continuously monitored across Rest, Stress, and Recover stages of the mental stress tasks, with PET/CT imaging during the Stress stage to evaluate myocardial perfusion. With PET/CT serving as the gold standard for MSIMI diagnosis, 35 of the 80 ANOCA patients were diagnosed as MSIMI. Using ECG variables from different stages of mental stress tasks, we developed five machine learning models to diagnose MSIMI. The results showed that ECG data from different stages provide valuable information for MSIMI classification. Additionally, the dataset encompassed demographic details, physiological, and blood sample test results of the patients. We anticipate this new dataset will significantly push further progress in ANOCA and MSIMI research.

G-quadruplex-guided cisplatin triggers multiple pathways in targeted chemotherapy and immunotherapy.

G-quadruplexes (G4s) are atypical nucleic acid structures involved in basic human biological processes and are regulated by small molecules. To date, pyridostatin and its derivatives [e.g., PyPDS (4-(2-aminoethoxy)-N 2,N 6-bis(4-(2-(pyrrolidin-1-yl) ethoxy) quinolin-2-yl) pyridine-2,6-dicarboxamide)] are the most widely used G4-binding small molecules and considered to have the best G4 specificity, which provides a new option for the development of cisplatin-binding DNA. By combining PyPDS with cisplatin and its analogs, we synthesize three platinum complexes, named PyPDSplatins. We found that cisplatin with PyPDS (CP) exhibits stronger specificity for covalent binding to G4 domains even in the presence of large amounts of dsDNA compared with PyPDS either extracellularly or intracellularly. Multiomics analysis reveals that CP can effectively regulate G4 functions, directly damage G4 structures, activate multiple antitumor signaling pathways, including the typical cGAS-STING pathway and AIM2-ASC pathway, trigger a strong immune response and lead to potent antitumor effects. These findings reflect that cisplatin-conjugated specific G4 targeting groups have antitumor mechanisms different from those of classic cisplatin and provide new strategies for the antitumor immunity of metals.

Building RNA-Mediated Artificial Signaling Pathways between Endogenous Genes.

ConspectusSophisticated genetic networks play a pivotal role in orchestrating cellular responses through intricate signaling pathways across diverse environmental conditions. Beyond the inherent complexity of natural cellular signaling networks, the construction of artificial signaling pathways (ASPs) introduces a vast array of possibilities for reshaping cellular responses, enabling programmable control of living organisms. ASPs can be integrated with existing cellular networks and redirect output responses as desired, allowing seamless communication and coordination with other cellular processes, thereby achieving designable transduction within cells. Among diversified ASPs, establishing connections between originally independent endogenous genes is of particular significance in modifying the genetic networks, so that cells can be endowed with new capabilities to sense and deal with abnormal factors related to differentiated gene expression (i.e., solve the issues of the aberrant gene expression induced by either external or internal stimuli). In a typical scenario, the two genes X and Y in the cell are originally expressed independently. After the introduction of an ASP, changes in the expression of gene X may exert a designed impact on gene Y, subsequently inducing the cellular response related to gene Y. If X represents a disease signal and Y serves as a therapeutic module, the introduction of the ASP empowers cells with a new spontaneous defense system to handle potential risks, which holds great potential for both fundamental and translational studies.In this Account, we primarily review our endeavors in the construction of RNA-mediated ASPs between endogenous genes that can respond to differentiated RNA expression. In contrast to other molecules that may be restricted to specific pathways, synthetic RNA circuits can be easily utilized and expanded as a general platform for constructing ASPs with a high degree of programmability and tunability for diversified functionalities through predictable Watson-Crick base pairing. We first provide an overview of recent advancements in RNA-based genetic circuits, encompassing but not limited to utilization of RNA toehold switches, siRNA and CRISPR systems. Despite notable progress, most reported RNA circuits have to contain at least one exogenous RNA X as input or one engineered RNA Y as a target, which is not suitable for establishing endogenous gene connections. While exogenous RNAs can be engineered and controlled as desired, constructing a general and efficient platform for manipulation of naturally occurring RNAs poses a formidable challenge, especially for the mammalian system. With a focus on this goal, we are devoted to developing efficient strategies to manipulate cell responses by establishing RNA-mediated ASPs between endogenous genes, particularly in mammalian cells. Our step-by-step progress in engineering customized cell signaling circuits, from bacterial cells to mammalian cells, from gene expression regulation to phenotype control, and from small RNA to long mRNA of low abundance and more complex secondary structures, is systematically described. Finally, future perspectives and potential applications of these RNA-mediated ASPs between endogenous genes are also discussed.