Temperature-dependent RNA editing in octopus extensively recodes the neural proteome.

In poikilotherms, temperature changes challenge the integration of physiological function. Within the complex nervous systems of the behaviorally sophisticated coleoid cephalopods, these problems are substantial. RNA editing by adenosine deamination is a well-positioned mechanism for environmental acclimation. We report that the neural proteome of Octopus bimaculoides undergoes massive reconfigurations via RNA editing following a temperature challenge. Over 13,000 codons are affected, and many alter proteins that are vital for neural processes. For two highly temperature-sensitive examples, recoding tunes protein function. For synaptotagmin, a key component of Ca2+-dependent neurotransmitter release, crystal structures and supporting experiments show that editing alters Ca2+ binding. For kinesin-1, a motor protein driving axonal transport, editing regulates transport velocity down microtubules. Seasonal sampling of wild-caught specimens indicates that temperature-dependent editing occurs in the field as well. These data show that A-to-I editing tunes neurophysiological function in response to temperature in octopus and most likely other coleoids.

Single-cell and spatial atlases of spinal cord injury in the Tabulae Paralytica.

Here, we introduce the Tabulae Paralytica-a compilation of four atlases of spinal cord injury (SCI) comprising a single-nucleus transcriptome atlas of half a million cells, a multiome atlas pairing transcriptomic and epigenomic measurements within the same nuclei, and two spatial transcriptomic atlases of the injured spinal cord spanning four spatial and temporal dimensions. We integrated these atlases into a common framework to dissect the molecular logic that governs the responses to injury within the spinal cord1. The Tabulae Paralytica uncovered new biological principles that dictate the consequences of SCI, including conserved and divergent neuronal responses to injury; the priming of specific neuronal subpopulations to upregulate circuit-reorganizing programs after injury; an inverse relationship between neuronal stress responses and the activation of circuit reorganization programs; the necessity of re-establishing a tripartite neuroprotective barrier between immune-privileged and extra-neural environments after SCI and a failure to form this barrier in old mice. We leveraged the Tabulae Paralytica to develop a rejuvenative gene therapy that re-established this tripartite barrier, and restored the natural recovery of walking after paralysis in old mice. The Tabulae Paralytica provides a window into the pathobiology of SCI, while establishing a framework for integrating multimodal, genome-scale measurements in four dimensions to study biology and medicine.

Structural basis of ligand recognition and self-activation of orphan GPR52.

GPR52 is a class-A orphan G-protein-coupled receptor that is highly expressed in the brain and represents a promising therapeutic target for the treatment of Huntington's disease and several psychiatric disorders1,2. Pathological malfunction of GPR52 signalling occurs primarily through the heterotrimeric Gs protein2, but it is unclear how GPR52 and Gs couple for signal transduction and whether a native ligand or other activating input is required. Here we present the high-resolution structures of human GPR52 in three states: a ligand-free state, a Gs-coupled self-activation state and a potential allosteric ligand-bound state. Together, our structures reveal that extracellular loop 2 occupies the orthosteric binding pocket and operates as a built-in agonist, conferring an intrinsically high level of basal activity to GPR523. A fully active state is achieved when Gs is coupled to GPR52 in the absence of an external agonist. The receptor also features a side pocket for ligand binding. These insights into the structure and function of GPR52 could improve our understanding of other self-activated GPCRs, enable the identification of endogenous and tool ligands, and guide drug discovery efforts that target GPR52.

A functional logic for neurotransmitter corelease in the cholinergic forebrain pathway.

The cholinergic system of the basal forebrain plays an integral part in behaviors ranging from attention to learning, partly by altering the impact of noise in neural populations. The circuit computations underlying cholinergic actions are confounded by recent findings that forebrain cholinergic neurons corelease both acetylcholine (ACh) and GABA. We have identified that corelease of ACh and GABA by cholinergic inputs to the claustrum, a structure implicated in the control of attention, has opposing effects on the electrical activity of claustrum neurons that project to cortical vs. subcortical targets. These actions differentially alter neuronal gain and dynamic range in the two types of neurons. In model networks, the differential effects of ACh and GABA toggle network efficiency and the impact of noise on population dynamics between two different projection subcircuits. Such cholinergic switching between subcircuits provides a potential logic for neurotransmitter corelease in implementing behaviorally relevant computations.

Unveiling the underestimated direct emissions of nitrous acid (HONO).

Gaseous nitrous acid (HONO) is a critical source of hydroxyl radicals (OH) in the troposphere. While both direct and secondary sources contribute to atmospheric HONO, direct emissions have traditionally been considered minor contributors. In this study, we developed δ15N and δ18O isotopic fingerprints to identify six direct HONO emission sources and conducted a 1-y case study on the isotopic composition of atmospheric HONO at rural and urban sites. Interestingly, we identified that livestock farming is a previously overlooked direct source of HONO and determined its HONO to ammonia (NH3) emission ratio. Additionally, our results revealed that spatial and temporal variations in atmospheric HONO isotopic composition can be partially attributed to direct emissions. Through a detailed HONO budget analysis incorporating agricultural sources, we found that direct HONO emissions accounted for 39~45% of HONO production in rural areas across different seasons. The findings were further confirmed by chemistry transport model simulations, highlighting the significance of direct HONO emissions and their impact on air quality in the North China Plain. These findings provide compelling evidence that direct HONO emissions play a more substantial role in contributing to atmospheric HONO than previously believed. Moreover, the δ15N and δ18O isotopic fingerprints developed in this study may serve as a valuable tool for further research on the atmospheric chemistry of reactive nitrogen gases.

Solving independent set problems with photonic quantum circuits.

An independent set (IS) is a set of vertices in a graph such that no edge connects any two vertices. In adiabatic quantum computation [E. Farhi, et al., Science 292, 472-475 (2001); A. Das, B. K. Chakrabarti, Rev. Mod. Phys. 80, 1061-1081 (2008)], a given graph G(V, E) can be naturally mapped onto a many-body Hamiltonian [Formula: see text], with edges [Formula: see text] being the two-body interactions between adjacent vertices [Formula: see text]. Thus, solving the IS problem is equivalent to finding all the computational basis ground states of [Formula: see text]. Very recently, non-Abelian adiabatic mixing (NAAM) has been proposed to address this task, exploiting an emergent non-Abelian gauge symmetry of [Formula: see text] [B. Wu, H. Yu, F. Wilczek, Phys. Rev. A 101, 012318 (2020)]. Here, we solve a representative IS problem [Formula: see text] by simulating the NAAM digitally using a linear optical quantum network, consisting of three C-Phase gates, four deterministic two-qubit gate arrays (DGA), and ten single rotation gates. The maximum IS has been successfully identified with sufficient Trotterization steps and a carefully chosen evolution path. Remarkably, we find IS with a total probability of 0.875(16), among which the nontrivial ones have a considerable weight of about 31.4%. Our experiment demonstrates the potential advantage of NAAM for solving IS-equivalent problems.

Dynamic transcriptome landscape of maize pericarp development.

As a maternal tissue, the pericarp supports and protects for other components of seed, such as embryo and endosperm. Despite the importance of maize pericarp in seed, the genome-wide transcriptome pattern throughout maize pericarp development has not been well characterized. Here, we developed RNA-seq transcriptome atlas of B73 maize pericarp development based on 21 samples from 5 days before fertilization (DBP5) to 32 days after fertilization (DAP32). A total of 25 346 genes were detected in programming pericarp development, including 1887 transcription factors (TFs). Together with pericarp morphological changes, the global clustering of gene expression revealed four developmental stages: undeveloped, thickening, expansion and strengthening. Coexpression analysis provided further insights on key regulators in functional transition of four developmental stages. Combined with non-seed, embryo, endosperm, and nucellus transcriptome data, we identified 598 pericarp-specific genes, including 75 TFs, which could elucidate key mechanisms and regulatory networks of pericarp development. Cell wall related genes were identified that reflected their crucial role in the maize pericarp structure building. In addition, key maternal proteases or TFs related with programmed cell death (PCD) were proposed, suggesting PCD in the maize pericarp was mediated by vacuolar processing enzymes (VPE), and jasmonic acid (JA) and ethylene-related pathways. The dynamic transcriptome atlas provides a valuable resource for unraveling the genetic control of maize pericarp development.

SPTLC3 Is Essential for Complex I Activity and Contributes to Ischemic Cardiomyopathy.

BACKGROUND: Dysregulated metabolism of bioactive sphingolipids, including ceramides and sphingosine-1-phosphate, has been implicated in cardiovascular disease, although the specific species, disease contexts, and cellular roles are not completely understood. Sphingolipids are produced by the serine palmitoyltransferase enzyme, canonically composed of 2 subunits, SPTLC1 (serine palmitoyltransferase long chain base subunit 1) and SPTLC2 (serine palmitoyltransferase long chain base subunit 2). Noncanonical sphingolipids are produced by a more recently described subunit, SPTLC3 (serine palmitoyltransferase long chain base subunit 3). METHODS: The noncanonical (d16) and canonical (d18) sphingolipidome profiles in cardiac tissues of patients with end-stage ischemic cardiomyopathy and in mice with ischemic cardiomyopathy were analyzed by targeted lipidomics. Regulation of SPTLC3 by HIF1α under ischemic conditions was determined with chromatin immunoprecipitation. Transcriptomics, lipidomics, metabolomics, echocardiography, mitochondrial electron transport chain, mitochondrial membrane fluidity, and mitochondrial membrane potential were assessed in the cSPTLC3KO transgenic mice we generated. Furthermore, morphological and functional studies were performed on cSPTLC3KO mice subjected to permanent nonreperfused myocardial infarction. RESULTS: Herein, we report that SPTLC3 is induced in both human and mouse models of ischemic cardiomyopathy and leads to production of atypical sphingolipids bearing 16-carbon sphingoid bases, resulting in broad changes in cell sphingolipid composition. This induction is in part attributable to transcriptional regulation by HIF1α under ischemic conditions. Furthermore, cardiomyocyte-specific depletion of SPTLC3 in mice attenuates oxidative stress, fibrosis, and hypertrophy in chronic ischemia, and mice demonstrate improved cardiac function and increased survival along with increased ketone and glucose substrate metabolism utilization. Depletion of SPTLC3 mechanistically alters the membrane environment and subunit composition of mitochondrial complex I of the electron transport chain, decreasing its activity. CONCLUSIONS: Our findings suggest a novel essential role for SPTLC3 in electron transport chain function and a contribution to ischemic injury by regulating complex I activity.

Kif9 is an active kinesin motor required for ciliary beating and proximodistal patterning of motile axonemes.

Most motile cilia have a stereotyped structure of nine microtubule outer doublets and a single central pair of microtubules. The central pair of microtubules are surrounded by a set of proteins, termed the central pair apparatus. A specific kinesin, Klp1 projects from the central pair and contributes to ciliary motility in Chlamydomonas. The vertebrate ortholog, Kif9, is required for beating in mouse sperm flagella, but the mechanism of Kif9/Klp1 function remains poorly defined. Here, using Xenopus epidermal multiciliated cells, we show that Kif9 is necessary for ciliary motility and the proper distal localization of not only central pair proteins, but also radial spokes and dynein arms. In addition, single-molecule assays in vitro reveal that Xenopus Kif9 is a long-range processive motor, although it does not mediate long-range movement in ciliary axonemes in vivo. Together, our data suggest that Kif9 is integral for ciliary beating and is necessary for proper axonemal distal end integrity.

MpbPPI: a multi-task pre-training-based equivariant approach for the prediction of the effect of amino acid mutations on protein-protein interactions.

The accurate prediction of the effect of amino acid mutations for protein-protein interactions (PPI $\Delta \Delta G$) is a crucial task in protein engineering, as it provides insight into the relevant biological processes underpinning protein binding and provides a basis for further drug discovery. In this study, we propose MpbPPI, a novel multi-task pre-training-based geometric equivariance-preserving framework to predict PPI  $\Delta \Delta G$. Pre-training on a strictly screened pre-training dataset is employed to address the scarcity of protein-protein complex structures annotated with PPI $\Delta \Delta G$ values. MpbPPI employs a multi-task pre-training technique, forcing the framework to learn comprehensive backbone and side chain geometric regulations of protein-protein complexes at different scales. After pre-training, MpbPPI can generate high-quality representations capturing the effective geometric characteristics of labeled protein-protein complexes for downstream $\Delta \Delta G$ predictions. MpbPPI serves as a scalable framework supporting different sources of mutant-type (MT) protein-protein complexes for flexible application. Experimental results on four benchmark datasets demonstrate that MpbPPI is a state-of-the-art framework for PPI $\Delta \Delta G$ predictions. The data and source code are available at https://github.com/arantir123/MpbPPI.

Improving therapeutic synergy score predictions with adverse effects using multi-task heterogeneous network learning.

Drug combinations could trigger pharmacological therapeutic effects (TEs) and adverse effects (AEs). Many computational methods have been developed to predict TEs, e.g. the therapeutic synergy scores of anti-cancer drug combinations, or AEs from drug-drug interactions. However, most of the methods treated the AEs and TEs predictions as two separate tasks, ignoring the potential mechanistic commonalities shared between them. Based on previous clinical observations, we hypothesized that by learning the shared mechanistic commonalities between AEs and TEs, we could learn the underlying MoAs (mechanisms of actions) and ultimately improve the accuracy of TE predictions. To test our hypothesis, we formulated the TE prediction problem as a multi-task heterogeneous network learning problem that performed TE and AE learning tasks simultaneously. To solve this problem, we proposed Muthene (multi-task heterogeneous network embedding) and evaluated it on our collected drug-drug interaction dataset with both TEs and AEs indications. Our experimental results showed that, by including the AE prediction as an auxiliary task, Muthene generated more accurate TE predictions than standard single-task learning methods, which supports our hypothesis. Using a drug pair Vincristine-Dasatinib as a case study, we demonstrated that our method not only provides a novel way of TE predictions but also helps us gain a deeper understanding of the MoAs of drug combinations.

Enhanced Storage Capacity via Anion Substitution for Advanced Delayed X-ray Detection.

X-ray radiation information storage, characterized by its ability to detect radiation with delayed readings, shows great promise in enabling reliable and readily accessible X-ray imaging and dosimetry in situations where conventional detectors may not be feasible. However, the lack of specific strategies to enhance the memory capability dramatically hampers its further development. Here, we present an effective anion substitution strategy to enhance the storage capability of NaLuF4:Tb3+ nanocrystals attributed to the increased concentration of trapping centers under X-ray irradiation. The stored radiation information can be read out as optical brightness via thermal, 980 nm laser, or mechanical stimulation, avoiding real-time measurement under ionizing radiation. Moreover, the radiation information can be maintained for more than 13 days, and the imaging resolution reaches 14.3 lp mm-1. These results demonstrate that anion substitution methods can effectively achieve high storage capability and broaden the application scope of X-ray information storage.

Spectrum-Dependent Image Convolutional Processing via a Two-Dimensional Polarization-Sensitive Photodetector.

Currently, the improvement in the processing capacity of traditional processors considerably lags behind the demands of real-time image processing caused by the advancement of photodetectors and the widespread deployment of high-definition image sensors. Therefore, achieving real-time image processing at the sensor level has become a prominent research domain in the field of photodetector technology. This goal underscores the need for photodetectors with enhanced multifunctional integration capabilities than can perform real-time computations using optical or electrical signals. In this study, we employ an innovative p-type semiconductor GaTe0.5Se0.5 to construct a polarization-sensitive wide-spectral photodetector. Leveraging the wide-spectral photoresponse, we realize three-band imaging within a wavelength range of 390-810 nm. Furthermore, real-time image convolutional processing is enabled by configuring appropriate convolution kernels based on the polarization-sensitive photocurrents. The innovative design of the polarization-sensitive wide-spectral GaTe0.5Se0.5-based photodetector represents a notable contribution to the domain of real-time image perception and processing.

Temperature-Dependent Color-Tunable Afterglow in Zirconium-Doped CsCdCl3 Perovskite for Advanced Anti-Counterfeiting and Thermal Distribution Detection.

Persistent luminescence (PersL) materials exhibit thermal-favored optical behavior, enabling their unique applications in security night vision signage, in vivo bioimaging, and optical anti-counterfeiting. Therefore, developing efficient and color-tunable PersL materials is significantly crucial in promoting advanced practical use. In this study, hexagonal Zr4+ -doped CsCdCl3 perovskite is synthesized via a hydrothermal reaction with a tunable photoluminescent (PL) behavior through heterovalent substitution. Moreover, the incorporation of Zr4+ ions result in an extra blue emission band, originating from the enhanced excitonic recombination in D3d octahedrons. Furthermore, the afterglow performances of the samples are dramatically improved, along with the noticeable temperature-dependent PersL as well as the thermo-luminescence with tunable color output. Detailed analysis reveals that the unique temperature-dependent PersL and thermo-luminescence color change are attributed to the presence of multiple luminous centers and abundant traps. Overall, this work facilitates the development of optical intelligence platforms and novel thermal distribution probes with the as-developed halides perovskite for its superior explored PersL characteristic.

Topological charge identification of superimposed orbital angular momentum beams under turbulence using an attention mechanism.

Due to the unique features, orbital angular momentum (OAM) beams have been widely explored for different applications. Accurate determination of the topological charge (TC) of these beams is crucial for their optimal utilization. In this paper, we propose a method that combines adaptive image processing techniques with a simple, parameter-free attention module (SimAM) based convolutional neural network to accurately identify the TC of high-order superimposed OAM beams. Experimental results demonstrate that under the combined influence of non-extreme light intensity and turbulence, it can achieve >95% identification accuracy of TCs ranging from ±1 to ±40. Moreover, even under partial-pattern-missing conditions, our method maintains an accuracy rate of over 80%. Compared with traditional attention mechanisms, SimAM does not require additional network design, significantly reducing the computational costs. Our approach showcases remarkable efficiency, robustness, and cost-effectiveness, making it adaptable to challenging factors such as non-uniform lighting and partially occluded light paths. This research provides a new direction for recognizing OAM modes with valuable implications for the future of communication systems.

Chemical Sensors Based on Covalent Organic Frameworks.

Covalent organic frameworks (COFs) are a type of crystalline porous polymer composed of light elements through strong covalent bonds. COFs have attracted considerable attention due to their unique designable structures and excellent material properties. Currently, COFs have shown outstanding potential in various fields, including gas storage, pollutant removal, catalysis, adsorption, optoelectronics, and their research in the sensing field is also increasingly flourishing. In this review, we focus on COF-based sensors. Firstly, we elucidate the fundamental principles of COF-based sensors. Then, we present the primary application areas of COF-based sensors and their recent advancements, encompassing gas, ions, organic compounds, and biomolecules sensing. Finally, we discuss the future trends and challenges faced by COF-based sensors, outlining their promising prospects in the field of sensing.

Effect of exposures to multiple metals on blood pressure and hypertension in the elderly: a community-based study.

A chronic disease, hypertension (HTN) is prevalent among the elderly. Exploring the factors that influence HTN and blood pressure (BP) changes is of great public health significance. However, mixed exposure to multiple serum metals has had less research on the effects on BP and HTN for the elderly. From April to August 2019, 2372 people participated in the community physical examination program for the elderly in Tongling City, Anhui Province. We measured BP and serum levels of 10 metals and collected basic demographic information. We analyzed the relationship between metal levels and changes in BP and HTN by the least absolute shrinkage and selection operator regression, Bayesian kernel machine regression model, and generalized linear model. In multiple models, lead (Pb) and cadmium (Cd) were still significantly associated with HTN occurrence after adjusting for potential confounders (Pb: ORquartile 4 VS quartile 1 = 1.20, 95% CI 1.01-1.43; Cd: ORquartile 4 VS quartile 1 = 1.37, 95% CI 1.16-1.62). In the male subgroup, results were similar to those of the general population. In the female group, Cd was positively correlated with HTN and systolic blood pressure, while Pb was not. According to this study, Pb and Cd were correlated with BP and HTN positively, and there was a certain joint effect. To some extent, our findings provide clues for the prevention of hypertension in the elderly.

Cystathionine γ-lyase-derived H2S negatively regulates thymic egress via allosteric inhibition of sphingosine-1-phosphate lyase.

Thymic egress is a crucial process for thymocyte maturation, strictly regulated by sphingosine-1-phosphate lyase (S1PL). Recently, cystathionine γ-lyase (CSE), one of the enzymes producing hydrogen sulfide (H2S), has emerged as a vital immune process regulator. However, the molecular connection between CSE, H2S and thymic egress remains largely unexplored. In this study, we investigated the regulatory function of CSE in the thymic egress of immune cells. We showed that genetic knockout of CSE or pharmacological inhibition by CSE enzyme inhibitor NSC4056 or D,L-propargylglycine (PAG) significantly enhanced the migration of mature lymphocytes and monocytes from the thymus to the peripheral blood, and this redistribution effect could be reversed by treatment with NaHS, an exogenous donor of H2S. In addition, the CSE-generated H2S significantly increased the levels of S1P in the peripheral blood, thymus and spleen of mice, suppressed the production of proinflammatory cytokines and rescued pathogen-induced sepsis in cells and in vivo. Notably, H2S or polysulfide inhibited S1PL activity in cells and an in vitro purified enzyme assay. We found that this inhibition relied on a newly identified C203XC205 redox motif adjacent to the enzyme's active site, shedding light on the biochemical mechanism of S1PL regulation. In conclusion, this study uncovers a new function and mechanism for CSE-derived H2S in thymic egress and provides a potential drug target for treating S1P-related immune diseases.

Association between physical activity, peak expiratory flow, and cognitive function in aging: a cross-sectional analysis.

BACKGROUND: The aging global population is experiencing escalating challenges related to cognitive deficits and dementia. This study explored the interplay between pulmonary function, physical activity, and cognitive function in older U.S. adults to identify modifiable risk factors for cognitive decline. METHODS: Utilizing NHANES 2011-2012 data, we conducted a cross-sectional analysis of 729 participants aged ≥ 60 years. Cognitive function, peak expiratory flow (PEF), and physical activity were assessed. Weighted logistic regression and mediation analyses were employed to examine associations. RESULTS: The sample size was 729 (weighted mean [SD] age, 67.1 [5.3] years; 53.6% female participants). Preliminary correlation analysis indicated a positive correlation between the global cognitive score and physical activity (ß = 0.16; p < 0.001), recreational activity (ß = 0.22; p < 0.001), and PEF in percent predicted (PEF%) (ß = 0.18; p < 0.001). Compared to those with a PEF% >100%, the PEF% (80-100%) group (OR, 2.66; 95% CI, 1.34-5.29; p = 0.005) and PEF% <80% group (OR, 3.36; 95% CI, 1.67-6.76; p = 0.001) were significantly associated with higher cognitive deficits risk. Recreational activity meeting guidelines was linked to a lower risk of cognitive deficits (OR, 0.24; 95% CI, 0.10-0.57; p = 0.001). Mediation analysis demonstrated that PEF mediates the relationship between physical activity and cognitive function. CONCLUSION: This study revealed significant associations between lower PEF, diminished physical activity, and increased cognitive deficits in elderly individuals. The results supported the hypothesis that pulmonary function may mediate the connection between activity and cognitive health, emphasizing the importance of respiratory health in cognitive aging. Recognizing these associations is crucial for clinical care and public health policy aiming to mitigate cognitive decline in aging populations. While these findings are intriguing, validation through longitudinal design studies is deemed necessary.

Impact of resistance exercise on patients with chronic kidney disease.

BACKGROUND: Chronic kidney disease (CKD) has become an increasingly important public health disease with a high incidence rate and mortality. Although several studies have explored the effectiveness of resistance exercise in improving the prognosis of CKD patients, the number of studies is still limited and the results are still controversial. OBJECTIVES: We conducted this meta-analysis of randomized controlled trials (RCT) studies to evaluate the effectiveness of resistance exercise on CKD patients. METHODS: The PubMed, Embase, and Cochrane Library databases were searched from the inception date to October 2023. The meta-analysis was conducted to evaluate 12 main indicators, including glomerular filtration rate (GFR)(ml/(min•1.73m2)), C-reactive protein (CRP) (mg/L), serum creatinine (mg/dL), hemoglobin (g/dL), Glycosylated Hemoglobin, Type A1C (HBA1c) (%), high Density Lipoprotein (HDL) (mg/dL), low Density Lipoprotein (LDL) (mg/dL), 6-min walk(m), body mass index (BMI) (kg/m2), fat-free mass (kg), fat mass (kg), grip strength (kgf). RESULTS: Sixteen RCT studies were included in this meta-analysis from 875 records. GFR exhibited no significant change in CKD patients treated with resistance exercise (WMD 1.82; 95%CI -0.59 to 4.23; P = 0.139). However, 6-min walk (WMD 89.93; 95%CI 50.12 to 129.74; P = 0.000), fat-free mass (WMD 6.53; 95%CI 1.14 to 11.93; P = 0.018) and grip strength (WMD 3.97; 95%CI 1.89 to 6.05; P = 0.000) were significantly improved with resistance exercise. The level of CRP (WMD - 2.46; 95%CI -4.21 to -0.72; P = 0.006) and HBA1c (WMD - 0.46; 95%CI -0.63 to -0.29; P = 0.000) dropped significantly after resistance exercise treatment. CONCLUSIONS: Resistance exercise can improve physical function, metabolic condition, inflammatory response and cardiopulmonary function in CKD patients, specifically reflected in the increase of indicators fat-free mass, grip strength, 6-min walk, as well as the decrease of indicators HBA1c and CRP.