Risk factors for hemorrhagic cystitis in children undergoing hematopoietic stem cell transplantation: a systematic review and meta-analysis.

BACKGROUND: The risk factors for hemorrhagic cystitis (HC) in children undergoing hematopoietic stem cell transplantation (HSCT) are unclear. Therefore, we conducted this systematic review and meta-analysis to investigate the risk factors for HC in children undergoing HSCT. METHODS: We performed this meta-analysis by retrieving studies from PubMed, EMBASE, and the Cochrane Library up to October 10, 2023, and analyzing those that met the inclusion criteria. I2 statistics were used to evaluate heterogeneity. RESULTS: Twelve studies, including 2,764 patients, were analyzed. Male sex (odds ratio [OR] = 1.52; 95% confidence interval [CI], 1.16-2.00; p = 0.003, I2 = 0%), allogeneic donor (OR = 5.28; 95% CI, 2.60-10.74; p < 0.00001, I2 = 0%), human leukocyte antigen (HLA) mismatched donor (OR = 1.86; 95% CI, 1.00-3.44; p = 0.05, I2 = 31%), unrelated donor (OR = 1.58; 95% CI, 1.10-2.28; p = 0.01, I2 = 1%), myeloablative conditioning (MAC) (OR = 3.17; 95% CI, 1.26-7.97; p = 0.01, I2 = 0%), busulfan (OR = 2.18; 95% CI, 1.33-3.58; p = 0.002, I2 = 0%) or anti-thymoglobulin (OR = 1.65; 95% CI, 1.07-2.54; p = 0.02, I2 = 16%) use, and cytomegalovirus (CMV) reactivation (OR = 2.64; 95% CI, 1.44-4.82; p = 0.002, I2 = 0%) were risk factors for HC in children undergoing HSCT. CONCLUSIONS: Male sex, allogeneic donor, HLA-mismatched, unrelated donor, MAC, use of busulfan or anti-thymoglobulin, and CMV reactivation are risk factors for HC in children undergoing HSCT.

Artificial intelligence-driven prognostic system for conception prediction and management in intrauterine adhesions following hysteroscopic adhesiolysis: a diagnostic study using hysteroscopic images.

Introduction: Intrauterine adhesions (IUAs) caused by endometrial injury, commonly occurring in developing countries, can lead to subfertility. This study aimed to develop and evaluate a DeepSurv architecture-based artificial intelligence (AI) system for predicting fertility outcomes after hysteroscopic adhesiolysis. Methods: This diagnostic study included 555 intrauterine adhesions (IUAs) treated with hysteroscopic adhesiolysis with 4,922 second-look hysteroscopic images from a prospective clinical database (IUADB, NCT05381376) with a minimum of 2 years of follow-up. These patients were randomly divided into training, validation, and test groups for model development, tuning, and external validation. Four transfer learning models were built using the DeepSurv architecture and a code-free AI application for pregnancy prediction was also developed. The primary outcome was the model's ability to predict pregnancy within a year after adhesiolysis. Secondary outcomes were model performance which evaluated using time-dependent area under the curves (AUCs) and C-index, and ART benefits evaluated by hazard ratio (HR) among different risk groups. Results: External validation revealed that using the DeepSurv architecture, InceptionV3+ DeepSurv, InceptionResNetV2+ DeepSurv, and ResNet50+ DeepSurv achieved AUCs of 0.94, 0.95, and 0.93, respectively, for one-year pregnancy prediction, outperforming other models and clinical score systems. A code-free AI application was developed to identify candidates for ART. Patients with lower natural conception probability indicated by the application had a higher ART benefit hazard ratio (HR) of 3.13 (95% CI: 1.22-8.02, p = 0.017). Conclusion: InceptionV3+ DeepSurv, InceptionResNetV2+ DeepSurv, and ResNet50+ DeepSurv show potential in predicting the fertility outcomes of IUAs after hysteroscopic adhesiolysis. The code-free AI application based on the DeepSurv architecture facilitates personalized therapy following hysteroscopic adhesiolysis.

Exploiting biochemical data to improve osteosarcoma diagnosis with deep learning.

Early and accurate diagnosis of osteosarcomas (OS) is of great clinical significance, and machine learning (ML) based methods are increasingly adopted. However, current ML-based methods for osteosarcoma diagnosis consider only X-ray images, usually fail to generalize to new cases, and lack explainability. In this paper, we seek to explore the capability of deep learning models in diagnosing primary OS, with higher accuracy, explainability, and generality. Concretely, we analyze the added value of integrating the biochemical data, i.e., alkaline phosphatase (ALP) and lactate dehydrogenase (LDH), and design a model that incorporates the numerical features of ALP and LDH and the visual features of X-ray imaging through a late fusion approach in the feature space. We evaluate this model on real-world clinic data with 848 patients aged from 4 to 81. The experimental results reveal the effectiveness of incorporating ALP and LDH simultaneously in a late fusion approach, with the accuracy of the considered 2608 cases increased to 97.17%, compared to 94.35% in the baseline. Grad-CAM visualizations consistent with orthopedic specialists further justified the model's explainability.

Microglial P2Y6 calcium signaling promotes phagocytosis and shapes neuroimmune responses in epileptogenesis.

Microglial calcium signaling is rare in a baseline state but strongly engaged during early epilepsy development. The mechanism(s) governing microglial calcium signaling are not known. By developing an in vivo uridine diphosphate (UDP) fluorescent sensor, GRABUDP1.0, we discovered that UDP release is a conserved response to seizures and excitotoxicity across brain regions. UDP can signal through the microglial-enriched P2Y6 receptor to increase calcium activity during epileptogenesis. P2Y6 calcium activity is associated with lysosome biogenesis and enhanced production of NF-κB-related cytokines. In the hippocampus, knockout of the P2Y6 receptor prevents microglia from fully engulfing neurons. Attenuating microglial calcium signaling through calcium extruder ("CalEx") expression recapitulates multiple features of P2Y6 knockout, including reduced lysosome biogenesis and phagocytic interactions. Ultimately, P2Y6 knockout mice retain more CA3 neurons and better cognitive task performance during epileptogenesis. Our results demonstrate that P2Y6 signaling impacts multiple aspects of myeloid cell immune function during epileptogenesis.

Genetically Encoded Sensors for the In Vivo Detection of Neurochemical Dynamics.

The ability to measure dynamic changes in neurochemicals with high spatiotemporal resolution is essential for understanding the diverse range of functions mediated by the brain. We review recent advances in genetically encoded sensors for detecting neurochemicals and discuss their in vivo applications. For example, notable progress has been made with respect to sensors for second messengers such as cyclic adenosine monophosphate, enabling in vivo real-time monitoring of these messengers at single-cell and even subcellular resolution. Moreover, the emergence of highly sensitive sensors for neurotransmitters and neuromodulators has greatly accelerated the study of these signaling molecules in a wide variety of behavioral models using an array of powerful imaging techniques. Finally, we discuss the future direction of neurochemical sensors, including their ability to measure neurochemical concentrations and the potential for multiplex imaging.

Thermal conductivity of wrinkled graphene ring with defects.

Graphene rings have great prospects in the fields of biological modulators, electrochemical biosensors, and resonators, but are prone to wrinkling which can affect their physical properties. This work establishes a theoretical model predicting the torsional wrinkling behavior of defective monolayer graphene rings, which provides direct understanding and reliable accuracy of the wrinkle levels. Then the thermal conductivity of wrinkled graphene rings is studied considering different wrinkle levels, defect concentrations and radii. It is found that with increased radius, defect concentration and torsional angle, the ratio of wrinkle amplitude to wavelength increases gradually. Vacancy defects and radii have more significant influences on the thermal conductivity than torsional wrinkles. The main influence mechanism of wrinkles and defects on thermal conductivity is revealed by phonon density of state. This work provides theoretical guidance for thermal manipulation based on the wrinkle-tuning approach.

Phosphocreatine promotes epigenetic reprogramming to facilitate glioblastoma growth through stabilizing BRD2.

Glioblastoma (GBM) exhibits profound metabolic plasticity for survival and therapeutic resistance, while the underlying mechanisms remain unclear. Here, we show that GBM stem cells (GSCs) reprogram the epigenetic landscape by producing substantial amounts of phosphocreatine (PCr). This production is attributed to the elevated transcription of brain-type creatine kinase (CKB), mediated by Zinc finger E-box binding homeobox 1 (ZEB1). PCr inhibits the poly-ubiquitination of the chromatin regulator bromodomain containing protein 2 (BRD2) by outcompeting the E3 ubiquitin ligase SPOP for BRD2 binding. Pharmacological disruption of PCr biosynthesis by cyclocreatine leads to BRD2 degradation and a decrease in its targets' transcription, which inhibits chromosome segregation and cell proliferation. Notably, cyclocreatine treatment significantly impedes tumor growth and sensitizes tumors to a BRD2 inhibitor in mouse GBM models without detectable side effects. These findings highlight that high production of PCr is a druggable metabolic feature of GBM and a promising therapeutic target for GBM treatment.

The causal relationship between sleep disturbances and the risk of frailty: a two-sample Mendelian randomization study.

OBJECTIVE: Adequate sleep is closely related to people's health. However, with increasing age, the quality of sleep worsens. At the same time, among elderly individuals, frailty is also a disturbing factor, which makes elderly individuals more vulnerable to negative factors. To explore the relationship between the two, we conducted this study. METHODS: In this paper, independent genetic variations related to insomnia, sleep duration and daytime sleepiness were selected as IVs, and related genetic tools were used to search published genome-wide association studies for a two-sample Mendelian randomization (TSMR) analysis. The inverse-variance weighted (IVW) method was used as the main Mendelian randomization analysis method. Cochran's Q test was used to test heterogeneity, MR‒Egger was used to test horizontal pleiotropy, and the MR-PRESSO test was used to remove outliers. RESULTS: According to our research, insomnia (OR = 1.10, 95% CI 1.03-1.17, P = 2.59e-97), long sleep duration (OR = 0.66, 95% CI 0.37-1.17, P = 0.02), short sleep duration (OR = 1.30, 95% CI 1.22-1.38, P = 2.23e-17) and daytime sleepiness (OR = 1.49, 95% CI 1.25-1.77, P = 0.96e-4) had a bidirectional causal relationship with frailty. CONCLUSIONS: Our research showed that there is a causal relationship between sleep disturbances and frailty. This result was obtained by a TSMR analysis, which involves the use of genetic variation as an IV to determine causal relationships between exposure and outcome. Future TSMR studies should include a larger sample for analysis.

Explainable Federated Medical Image Analysis through Causal Learning and Blockchain.

Federated learning (FL) enables collaborative training of machine learning models across distributed medical data sources without compromising privacy. However, applying FL to medical image analysis presents challenges like high communication overhead and data heterogeneity. This paper proposes novel FL techniques using explainable artificial intelligence (XAI) for efficient, accurate, and trustworthy analysis. A heterogeneity-aware causal learning approach selectively sparsifies model weights based on their causal contributions, significantly reducing communication requirements while retaining performance and improving interpretability. Furthermore, blockchain provides decentralized quality assessment of client datasets. The assessment scores adjust aggregation weights so higher-quality data has more influence during training, improving model generalization. Comprehensive experiments show our XAI-integrated FL framework enhances efficiency, accuracy and interpretability. The causal learning method decreases communication overhead while maintaining segmentation accuracy. The blockchain-based data valuation mitigates issues from low-quality local datasets. Our framework provides essential model explanations and trust mechanisms, making FL viable for clinical adoption in medical image analysis.

IFITM3 mediates inflammation induced myocardial injury through JAK2/STAT3 signaling pathway.

Myocarditis is an inflammation of the heart muscle often associated with viral infections and can lead to dilated cardiomyopathy. Interferon-induced transmembrane protein 3 (IFITM3) is a small endosomal membrane protein with anti-viral activity against multiple viruses and is also implicated in non-infectious diseases such as cancer and Alzheimer's Disease. Since the IFITM3 proteins are expressed both in T cells and in cardiomyocytes, it is reasonable to hypothesize that these molecules could affect myocarditis either through their effect on the autoimmune response or through direct modulation of cardiomyocyte damage. The aim of this study was to investigate the role of IFITM3 in experimental autoimmune myocarditis (EAM)-mediated myocardial injury. Immunization of rats with cardiac myosin results in substantial cardiac inflammation and is associated with increased expression of IFITM3 after 21 days. In vivo IFITM3 shRNA knockdown using the lentivirus transfection method reduced cardiac injury while restoring IFITM3 expression reversed the protective effect of IFITM3 RNA interference. To determine the direct impact of IFITM3, the rat ventricular cell line, H9c2, was treated with palmitic acid which causes apoptosis in these cells. Suppressing IFITM3 expression protects H9c2 cells while overexpressing IFITM3 enhances cell injury. JAK inhibitors reduced IFITM3-mediated myocardial cell injury. In conclusion, IFITM3 may mediate myocardial injury in EAM rats and palmitic acid-induced damage to H9c2 cells through the JAK2/STAT3 pathway.

Dynamical interplay between superconductivity and pseudogap in cuprates as revealed by terahertz third-harmonic generation spectroscopy.

We report on nonlinear terahertz third-harmonic generation (THG) measurements on YBa2Cu3O6+x thin films. Different from conventional superconductors, the THG signal starts to appear in the normal state, which is consistent with the crossover temperature T* of pseudogap over broad doping levels. Upon lowering the temperature, the THG signal shows an anomaly just below Tc in the optimally doped sample. Notably, we observe a beat pattern directly in the measured real-time waveform of the THG signal. We elaborate that the Higgs mode, which develops below Tc, couples to the mode already developed below T*, resulting in an energy level splitting. However, this coupling effect is not evident in underdoped samples. We explore different potential explanations for the observed phenomena. Our research offers valuable insight into the interplay between superconductivity and pseudogap.

Influence of a private-public risk pool and an opt-out framing on earthquake protection demand for Canadian homeowners in Quebec and British Columbia.

This article describes the design and analysis of web-based choice experiments that examine how the demand for earthquake protection in Quebec and British Columbia (BC), Canada, is influenced by the default option and the structure of the insurance plan. Homeowners in both provinces were given the opportunity to purchase protection against earthquake losses when presented with one of the following options: the current private insurance plan and proposed public-private Risk Pools with different levels of the public layer. The default frame was changed so the homeowner could either opt-in by purchasing this coverage or opt-out of being given this protection and receiving a premium discount. Assigning participants to the public-private Risk Pools rather than the current private insurance plan increases the likelihood of purchasing earthquake insurance protection by an odds ratio of 2.7 or greater in BC and Quebec. Furthermore, opt-out enrollment design substantially increases take-up of earthquake protection relative to opt-in enrollment. The policy implications of these findings are discussed.

Unveiling the Intrinsic Photophysics in Quasi-Two-Dimensional Perovskites.

The two-dimensional (2D) perovskites have drawn intensive attention due to their unique stability and outstanding optoelectronic properties. However, the debate surrounding the spatial phase distribution and band alignment among different 2D phases in the quasi-2D perovskite has created complexities in understanding the carrier dynamics, hindering material and device development. In this study, we employed highly sensitive transient absorption spectroscopy to investigate the carrier dynamics of (BA)2(MA)n-1PbnI3n+1 quasi-2D Ruddlesden-Popper perovskite thin films, nominally prepared as n = 4. We observed the carrier-density-dependent electron and hole transfer dynamics between the 2D and three-dimensional (3D) phases. Under a low carrier density within the linear response range, we successfully resolved three ultrafast processes of both electron and hole transfers, spanning from hundreds of femtoseconds to several picoseconds, tens to hundreds of picoseconds, and hundreds of picoseconds to several nanoseconds, which can be attributed to lateral-epitaxial, partial-epitaxial, and disordered-interface heterostructures between 2D and 3D phases. By considering the interplay among the phase structure, band alignment, and carrier dynamics, we have proposed material synthesis strategies aimed at enhancing the carrier transport. Our results not only provide deep insights into an accurate intrinsic photophysics of quasi-2D perovskites but also inspire advancements in the practical application of these materials.

Noncollinear Optical Parametric Amplification of Broadband Infrared Sum Frequency Generation Vibrational Spectroscopy.

Sum-frequency generation (SFG) vibrational spectroscopy is an invaluable tool in surface science, known for its specificity to surfaces and interfaces. Despite its wide application, it is often hampered by weak signal detection. Here, we present an innovative enhancement technique of postsample amplification, using a picosecond noncollinear optical parametric amplifier (NOPA). We conducted a systematical investigation into the impact of different intensities of pump and SFG seed light, as the input signal in NOPA, and demonstrated this method on the octadecanethiol (ODT) molecules on gold films. The amplified SFG by NOPA reproduced the SFG vibrational spectra, enhanced by about 4 orders of magnitude but with broader spectral resolution due to the short pulse width of the pump light in NOPA. This study makes it possible to realize highly sensitive SFG measurements, marking a significant advancement in spectroscopic analysis techniques.

Ultralong afterglow of heavy-atom-free carbon dots with a phosphorescence lifetime of up to 3.7 s for encryption and fingerprinting description.

Metal-free room-temperature phosphorescent (RTP) materials with changeable colors have attracted great attention in anti-counterfeiting information encryption. Most ultralong-lifetime RTP (URTP) luminophores are traditionally obtained through heavy atom effects via enhancing the spin-orbit coupling efficiency. Here, we report the self-assembly of URTP carbon dots (CDs) using diphenylaminourea as the precursor through a thermal-evaporation assisted covalent-binding approach in the presence of boric acid (BA). The BA-functionalized diphenylaminourea-derived CDs (denoted as D-CDs1.5/BA composites) show a rigid network structure with B-C linkages connected to the surface of the CDs, which can effectively suppress the free vibration of CDs to promote intersystem crossover, finally resulting in an excellent URTP afterglow performance. They feature a low singlet-triplet energy gap and reduced nonradiative attenuation properties. As a result, the D-CDs1.5/BA composites exhibit a bifunctional fluorescence/phosphorescence performance with a high phosphorescence quantum efficiency (12.67%) and an ultra-long green afterglow phosphorescence lifetime of up to 3.66 s. A high-level information encryption and fingerprinting description based on the URTP D-CDs1.5/BA composites were then investigated. This work contributes to the feasible design and preparation of novel URTP CD materials with both ultra-long afterglow and a high phosphorescence efficiency, making them promising candidates for advanced anti-counterfeiting applications.

Gut lymph purification alleviates acute lung injury induced by intestinal ischemia-reperfusion in rats by removing danger-associated molecular patterns from gut lymph.

Background: The potential effect of removing danger-associated molecular patterns (DAMPs) from gut lymph on reducing acute lung injury (ALI) induced by gut ischemia-reperfusion injury (GIRI) is uncertain. This study aimed to investigate whether gut lymph purification (GLP) could improve GIRI-induced acute lung injury in rats by clearing danger-associated molecular patterns. Materials and methods: Rats were divided into four groups: Sham, GIRI, GIRI + gut lymph drainage (GLD), and GIRI + GLP. After successful modeling, lung tissue samples were collected from rats for hematoxylin-eosin (HE) staining and detection of apoptotic indexes. We detected the DAMPs levels in blood and lymph samples. We observed the microstructure of AEC Ⅱ and measured the expression levels of apoptosis indexes. Results: The GIRI group showed destruction of alveolar structure, thickened alveolar walls, and inflammatory cell infiltration. This was accompanied by significantly increased levels of high mobility group protein-1 (HMGB-1) and Interleukin-6 (IL-6), while reduced levels of heat shock protein 70 (HSP 70) and Interleukin-10 (IL-10) in both lymph and serum. In contrast, the lung tissue damage in the GIRI + GLP group was significantly improved compared to the GIRI group. This was evidenced by a reduction in the expression levels of HMGB-1 and IL-6 in both lymph and serum and an increase in HSP 70 and IL-10 levels. Additionally, organelle structure of AEC II was significantly improved in the GIRI + GLP group compared to the GIRI group. Conclusions: GLP inhibits inflammation and cell apoptosis in GIRI-induced ALI by blocking the link between DAMPs and mononuclear phagocytes, reducing the severity of ALI.

Loureirin A Promotes Cell Differentiation and Suppresses Migration and Invasion of Melanoma Cells via WNT and AKT/mTOR Signaling Pathways.

Resina Draconis is a traditional Chinese medicine, with the in-depth research, its medicinal value in anti-tumor has been revealed. Loureirin A is extracted from Resina Draconis, however, research on the anti-tumor efficacy of Loureirin A is rare. Herein, we investigated the function of Loureirin A in melanoma. Our research demonstrated that Loureirin A inhibited the proliferation of and caused G0/G1 cell cycle arrest in melanoma cells in a concentration-dependent manner. Further study showed that the melanin content and tyrosinase activity was enhanced after Loureirin A treatment, demonstrated that Loureirin A promoted melanoma cell differentiation, which was accompanied with the reduce of WNT signaling pathway. Meanwhile, we found that Loureirin A suppressed the migration and invasion of melanoma cells through the protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling pathway. Taken together, this study demonstrated for the first time the anti-tumor effects of Loureirin A in melanoma cells, which provided a novel therapeutic strategy against melanoma.

Changes in frailty and depressive symptoms among middle-aged and older Chinese people: a nationwide cohort study.

BACKGROUND AND AIMS: The older people bears a severe burden of disease due to frailty and depressive symptoms, however, the results of association between the two in the older Chinese people have been conflicting. Therefore, this study aimed to investigate the developmental trajectories and interactions of frailty and depressive symptoms in the Chinese middle-aged and older adults. METHODS: The study used four waves of data from 2011, 2013, 2015 and 2018 in the China Health and Retirement Longitudinal Study (CHARLS) database, focused on middle-aged and older people ≥ 45 years of age, and analyzed using latent growth models and cross-lagged models. RESULTS: The parallel latent growth model showed that the initial level of depressive symptoms had a significant positive predictive effect on the initial level of frailty. The rate of change in depressive symptoms significantly positively predicted the rate of change in frailty. The initial level of frailty had a significant positive predictive effect on the initial level of depressive symptoms, but a significant negative predictive effect on the rate of change in depressive symptoms. The rate of change in frailty had a significant positive predictive effect on the rate of change in depressive symptoms. The results of the cross-lagged analysis indicated a bidirectional causal association between frailty and depressive symptoms in the total sample population. Results for the total sample population grouped by age and gender were consistent with the total sample. CONCLUSIONS: This study recommends advancing the age of concern for frailty and depressive symptoms to middle-aged adults. Both men and women need early screening and intervention for frailty and depressive symptoms to promote healthy aging.

Ivabradine Alleviates Experimental Autoimmune Myocarditis-Mediated Myocardial Injury.

Ivabradine (IVA) reduces heart rate by inhibiting hyperpolarization-activated cyclic nucleotide-gated channels (HCNs), which play a role in the promotion of pacemaker activity in cardiac sinoatrial node cells. HCNs are highly expressed in neural and myocardial tissues and are involved in the modulation of inflammatory neuropathic pain. However, whether IVA exerts any effect on myocardial inflammation in the pathogenesis of heart failure is unclear. We employed single-cell RNA sequencing (scRNA-seq) in porcine cardiac myosin-induced experimental autoimmune myocarditis rat model to determine the effects and mechanisms of IVA. Lewis rats (n = 32) were randomly divided into the normal, control, high-dose-IVA, and low-dose-IVA groups. Heart rate and blood pressure were measured on days 0 and 21, respectively. Echocardiography was performed on day 22, and inflammation of the myocardium was evaluated via histopathological examination. Western blot was employed to detect the expression of HCN1-4, MinK-related protein 1 (MiRP1), matrix metalloproteinase 2 (MMP-2), MMP-9, and transforming growth factor-ß (TGF-ß). Furthermore, enzyme-linked immunosorbent assay was performed to measure serum IL-1, IL-6, and TNF-α. The relative mRNA levels of collagen I, collagen III, and α-smooth muscle actin (α-SMA) were determined via qRT-PCR. We found that IVA reduced the total number of cells infiltrated into the myocardium, particularly in the subset of fibroblasts, endocardia, and monocytes. IVA administration ameliorated cardiac inflammation and reduced collagen production. Results of the echocardiography indicated that left ventricular internal diameter at end-systole LVIDs increased whereas left ventricular ejection fraction and left ventricular fractional shortening decreased in the control group. IVA improved cardiac performance. The expression of HCN4 and MiRP1 protein and the level of serum IL-1, IL-6, and TNF-α were decreased by IVA treatment. In conclusion, HCNs and the helper proteins were increased in the profile of myocardial inflammation. HCNs may be involved in the regulation of myocardial inflammation by inhibiting immune cell infiltration. Our findings can contribute to the development of IVA-based combination therapies for the future treatment of cardiac inflammation and heart failure.

Non-Equilibrium Assembly of Atomically-Precise Copper Nanoclusters.

Accurate structure control in dissipative assemblies is vital for precise biological functions. However, the accuracy and functionality of current artificial dissipative assembly are far from this objective. Herein, we introduce a novel approach by harnessing complex chemical reaction networks (CRN) rooted in coordination chemistry to create well-defined dissipative assemblies. We designed atomically-precise Cu nanocluster (CuNCs), specifically Cu11 (µ9 -Cl)(µ3 -Cl)3 L6 Cl clusters (L = 4-methyl-piperazine-1-carbodithioate). Cu(I)-ligand ratio change and dynamic Cu(I)-Cu(I) metallophilic/coordination interactions enable the reorganization of CuNCs into metastable CuL2 , finally converting into the equilibrium [CuL·Y]Cl complexes (Y = MeCN or H2 O) via Cu(I) oxidation/reorganization and ligand exchange process. Upon adding fuels (ascorbic acid, AA), the system goes further dissipative cycles. We observed that the encapsulated/bridging halide ions exert a subtle influence on the optical properties of CuNCs and topological changes of polymeric networks when integrating CuNCs as crosslink sites. CuNCs duration and switch period could be controlled by varying the ions, AA concentration, O2 pressure and pH. The unique Cu(I)-Cu(I) metallophilic and coordination interactions provide a versatile toolbox for designing delicate life-like materials, paving the way for tailored dissipative assemblies with precise structures and functionalities. Furthermore, these CuNCs can be employed as modular units within polymers for materials mechanics or functionalization studies, expanding their potential applications. This article is protected by copyright. All rights reserved.