A silicon diode-based optoelectronic interface for bidirectional neural modulation.

The development of advanced neural modulation techniques is crucial to neuroscience research and neuroengineering applications. Recently, optical-based, nongenetic modulation approaches have been actively investigated to remotely interrogate the nervous system with high precision. Here, we show that a thin-film, silicon (Si)-based diode device is capable to bidirectionally regulate in vitro and in vivo neural activities upon adjusted illumination. When exposed to high-power and short-pulsed light, the Si diode generates photothermal effects, evoking neuron depolarization and enhancing intracellular calcium dynamics. Conversely, low-power and long-pulsed light on the Si diode hyperpolarizes neurons and reduces calcium activities. Furthermore, the Si diode film mounted on the brain of living mice can activate or suppress cortical activities under varied irradiation conditions. The presented material and device strategies reveal an innovated optoelectronic interface for precise neural modulations.

Deciphering the interaction between PKM2 and the built-in thermodynamic properties of the glycolytic pathway in cancer cells.

Most cancer cells exhibit high glycolysis rates under conditions of abundant oxygen. Maintaining a stable glycolytic rate is critical for cancer cell growth as it ensures sufficient conversion of glucose carbons to energy, biosynthesis, and redox balance. Here we deciphered the interaction between PKM2 and the thermodynamic properties of the glycolytic pathway. Knocking down or knocking out PKM2 induced a thermodynamic equilibration in the glycolytic pathway, characterized by the reciprocal changes of the Gibbs free energy (ΔG) of the reactions catalyzed by PFK1 and PK, leading to a less exergonic PFK1-catalyzed reaction and a more exergonic PK-catalyzed reaction. The changes in the ΔGs of the two reactions cause the accumulation of intermediates, including the substrate PEP (the substrate of PK), in the segment between PFK1 and PK. The increased concentration of PEP in turn increased PK activity in the glycolytic pathway. Thus, the interaction between PKM2 and the thermodynamic properties of the glycolytic pathway maintains the reciprocal relationship between PK concentration and its substrate PEP concentration, by which, PK activity in the glycolytic pathway can be stabilized and effectively counteracts the effect of PKM2 KD or KO on glycolytic rate. In line with our previous reports, this study further validates the roles of the thermodynamics of the glycolytic pathway in stabilizing glycolysis in cancer cells. Deciphering the interaction between glycolytic enzymes and the thermodynamics of the glycolytic pathway will promote a better understanding of the flux control of glycolysis in cancer cells.

Induction of lung progenitor cell-like organoids by porcine pluripotent stem cells.

Organoids are in vitro 3D models that are generated using stem cells to study organ development and regeneration. Despite the extensive research on lung organoids, there is limited information on pig lung cell generation or development. Here, we identified five epithelial cell types along with their characteristic markers using scRNA-seq. Additionally, we found that NKX2.1 and FOXA2 acted as the crucial core transcription factors in porcine lung development. The presence of SOX9/SOX2 double-positive cells was identified as a key marker for lung progenitor cells. The Monocle algorithm was used to create a pseudo-temporal differentiation trajectory of epithelial cells, leading to the identification of signaling pathways related to porcine lung development. Moreover, we established the differentiation method from porcine pluripotent stem cells (pPSCs) to SOX17+ FOXA2+ definitive endoderm (DE) and NKX2.1+ FOXA2+ CDX2- anterior foregut endoderm (AFE). The AFE is further differentiated into lung organoids while closely monitoring the differentiation process. We showed that NKX2.1 overexpression facilitated the induction of lung organoids and supported subsequent lung differentiation and maturation. This model offers valuable insights into studying the interaction patterns between cells and the signaling pathways during the development of the porcine lung.

Deficiency of geranylgeranyl biphosphate synthase in kidney tubules causes cystic kidney disease.

Polycystic kidney disease (PKD) is a common hereditary kidney disease. Although PKD occurrence is associated with certain gene mutations, its onset regulatory mechanisms are still not well understood. Here, we first report that the key enzyme geranylgeranyl diphosphate synthase (GGPPS) is specifically expressed in renal tubular epithelial cells of mouse kidneys. We aimed to explore the role of GGPPS in PKD. In this study, we established a Ggppsfl/fl:Cdh16cre mouse model and compared its phenotype with that of wild-type mice. A Ggpps-downregulation HK2 cell model was also used to further determine the role of GGPPS. We found that GGPPS was specifically expressed in renal tubular epithelial cells of mouse kidneys. Its expression also increased with age. Low GGPPS expression was observed in human ADPKD tissues. In the Ggppsfl/fl:Cdh16cre mouse model, Ggpps deletion in renal tubular epithelial cells induced the occurrence and development of renal tubule cystic dilation and caused the death of mice after birth due to abnormal renal function. Enhanced proliferation of cyst-lining epithelial cells was also observed after the knockout of Ggpps. These processes were related to the increased rate of Rheb on membrane/cytoplasm and hyperactivation of mTORC1 signaling. In conclusion, the deficiency of GGPPS in kidney tubules induced the formation of renal cysts. It may play a critical role in PKD pathophysiology. A novel therapeutic strategy could be designed according to this work.

Human striatal organoids derived from pluripotent stem cells recapitulate striatal development and compartments.

The striatum links neuronal circuits in the human brain, and its malfunction causes neuronal disorders such as Huntington's disease (HD). A human striatum model that recapitulates fetal striatal development is vital to decoding the pathogenesis of striatum-related neurological disorders and developing therapeutic strategies. Here, we developed a method to construct human striatal organoids (hStrOs) from human pluripotent stem cells (hPSCs), including hStrOs-derived assembloids. Our hStrOs partially replicated the fetal striatum and formed striosome and matrix-like compartments in vitro. Single-cell RNA sequencing revealed distinct striatal lineages in hStrOs, diverging from dorsal forebrain fate. Using hStrOs-derived assembloids, we replicated the striatal targeting projections from different brain parts. Furthermore, hStrOs can serve as hosts for striatal neuronal allografts to test allograft neuronal survival and functional integration. Our hStrOs are suitable for studying striatal development and related disorders, characterizing the neural circuitry between different brain regions, and testing therapeutic strategies.

Uncovering neural substrates across Alzheimer's disease stages using contrastive variational autoencoder.

Alzheimer's disease is the most common major neurocognitive disorder. Although currently, no cure exists, understanding the neurobiological substrate underlying Alzheimer's disease progression will facilitate early diagnosis and treatment, slow disease progression, and improve prognosis. In this study, we aimed to understand the morphological changes underlying Alzheimer's disease progression using structural magnetic resonance imaging data from cognitively normal individuals, individuals with mild cognitive impairment, and Alzheimer's disease via a contrastive variational autoencoder model. We used contrastive variational autoencoder to generate synthetic data to boost the downstream classification performance. Due to the ability to parse out the nonclinical factors such as age and gender, contrastive variational autoencoder facilitated a purer comparison between different Alzheimer's disease stages to identify the pathological changes specific to Alzheimer's disease progression. We showed that brain morphological changes across Alzheimer's disease stages were significantly associated with individuals' neurofilament light chain concentration, a potential biomarker for Alzheimer's disease, highlighting the biological plausibility of our results.

G-quadruplexes as pivotal components of cis-regulatory elements in the human genome.

BACKGROUND: Cis-regulatory elements (CREs) are crucial for regulating gene expression, and G-quadruplexes (G4s), as prototypal non-canonical DNA structures, may play a role in this regulation. However, the relationship between G4s and CREs, especially with non-promoter-like functional elements, requires further systematic investigation. We aimed to investigate the associations between G4s and human cCREs (candidate CREs) inferred from the Encyclopedia of DNA Elements (ENCODE) data. RESULTS: We found that G4s are prominently enriched in most types of cCREs, especially those with promoter-like signatures (PLS). The co-occurrence of CTCF signals with H3K4me3 or H3K27ac signals strengthens the association between cCREs and G4s. Genetic variants in G4s, particularly within their G-runs, exhibit higher regulatory potential and deleterious effects compared to cCREs. The G-runs within G4s near transcriptional start sites (TSSs) are more evolutionarily constrained compared to G-runs in cCREs, while those far from the TSS are relatively less conserved. The presence of G4s is often linked to a more favorable local chromatin environment for the activation and execution of regulatory function of cCREs, potentially attributable to the formation of G4 secondary structures. Finally, we discovered that G4-associated cCREs exhibit widespread activation in a variety of cancers. CONCLUSIONS: Our study suggests that G4s are integral components of human cis-regulatory elements, extending beyond their potential role in promoters. The G4 primary sequences are associated with the localization of CREs, while the G4 structures are linked to the activation of these elements. Therefore, we propose defining G4s as pivotal regulatory elements in the human genome.

Functionalized 2D membranes for separations at the 1-nm scale.

The ongoing evolution of two-dimensional (2D) material-based membranes has prompted the realization of mass separations at the 1-nm scale due to their well-defined selective nano- and subnanochannels. Strategic membrane functionalization is further found to be key to augmenting channel accuracy and efficiency in distinguishing ions, gases and molecules within this range and is thus trending as a research focus in energy-, resource-, environment- and pharmaceutical-related applications. In this review, we present the fundamentals underpinning functionalized 2D membranes in various separations, elucidating the critical "method-interaction-property" relationship. Starting with an introduction to various functionalization strategies, we focus our discussion on functionalization-induced channel-species interactions and reveal how they shape the transport- and operation-related features of the membrane in different scenarios. We also highlight the limitations and challenges of current functionalized 2D membranes and outline the necessary breakthroughs needed to apply them as reliable and high-performance separation units across industries in the future.

Real-Time Simulation of the Reaction Kinetics of Supported Metal Nanoparticles.

A common issue with supported metal catalysts is the sintering of metal nanoparticles, resulting in catalyst deactivation. In this study, we propose a theoretical framework for realizing a real-time simulation of the reactivity of supported metal nanoparticles during the sintering process, combining density functional theory calculations, microkinetic modeling, Wulff-Kaichew construction, and sintering kinetic simulations. To validate our approach, we demonstrate its feasibility on α-Al2O3(0001)-supported Ag nanoparticles, where the simulated sintering behavior and ethylene epoxidation reaction rate as a function of time show qualitative agreement with experimental observation. Our proposed theoretical approach can be employed to screen out the promising microstructure feature of α-Al2O3 for stable supported Ag NPs, including the surface orientation and promoter species modified on it. The outlined approach of this work may be applied to a range of different thermocatalytic reactions other than ethylene epoxidation and provide guidance for the development of supported metal catalysts with long-term stability.

DNA-Mediated Magnetic-Dimer Assembly for Fault-Free Ultra-High-Field Magnetic Resonance Imaging of Tumors.

Ultra-high-field (UHF) magnetic resonance imaging (MRI) stands as a pivotal cornerstone in biomedical imaging, yet the challenge of false imaging persists, constraining its full potential. Despite the development of dual-mode contrast agents improving conventional MRI, their effectiveness in UHF remains suboptimal due to the high magnetic moment, resulting in diminished T1 relaxivity and excessively enhanced T2 relaxivity. Herein, we report a DNA-mediated magnetic-dimer assembly (DMA) of iron oxide nanoparticles that harnesses UHF-tailored nanomagnetism for fault-free UHF-MRI. DMA exhibits a dually enhanced longitudinal relaxivity of 4.42 mM-1·s-1 and transverse relaxivity of 26.23 mM-1·s-1 at 9 T, demonstrating a typical T1-T2 dual-mode UHF-MRI contrast agent. Importantly, DMA leverages T1-T2 dual-modality image fusion to achieve artifact-free breast cancer visualization, effectively filtering interference from hundred-micrometer-level false-positive signals with unprecedented precision. The UHF-tailored T1-T2 dual-mode DMA contrast agents hold promise for elevating the accuracy of MR imaging in disease diagnosis.

The Ycx1 protein encoded by the yeast YDL206W gene plays a role in calcium and calcineurin signaling.

Calcium is ubiquitously present in all living cells and plays important regulatory roles in a wide variety of biological processes. In yeast, many effects of calcium are mediated via the action of calcineurin, a calcium/calmodulin-dependent protein phosphatase. Proper signaling of calcium and calcineurin is important in yeast, and the calcineurin pathway has emerged as a valuable target for developing novel antifungal drugs. Here, we report a role of YDL206W in calcium and calcineurin signaling in yeast. YDL206W is an uncharacterized gene in yeast, encoding a protein with two sodium/calcium exchange domains. Disrupting the YDL206W gene leads to a diminished level of calcium-induced activation of calcineurin and a reduced accumulation of cytosolic calcium. Consistent with a role of calcineurin in regulating pheromone and cell wall integrity signaling, the ydl206wΔ mutants display an enhanced growth arrest induced by pheromone treatment and poor growth at elevated temperature. Subcellular localization studies indicate that YDL206W is localized in endoplasmic reticulum and Golgi. Together, our results reveal YDL206W as a new regulator for calcineurin signaling in yeast and suggest a role of the endoplasmic reticulum and Golgi in regulating cytosolic calcium in yeast.

StMLP1, as a Kunitz trypsin inhibitor, enhances potato resistance and specifically expresses in vascular bundles during Ralstonia solanacearum infection.

Miraculin-like proteins (MLPs), members of the Kunitz trypsin inhibitor (KTI) family that are present in various plants, have been discovered to have a role in defending plants against pathogens. In this study, we identified a gene StMLP1 in potato that belongs to the KTI family. We found that the expression of StMLP1 gradually increases during Ralstonia solanacearum (R. solanacearum) infection. We characterized the promoter of StMLP1 as an inducible promoter that can be triggered by R. solanacearum and as a tissue-specific promoter with specificity for vascular bundle expression. Our findings demonstrate that StMLP1 exhibits trypsin inhibitor activity, and that its signal peptide is essential for proper localization and function. Overexpression of StMLP1 in potato can enhance the resistance to R. solanacearum. Inhibiting the expression of StMLP1 during infection accelerated the infection by R. solanacearum to a certain extent. In addition, the RNA-seq results of the overexpression-StMLP1 lines indicated that StMLP1 was involved in potato immunity. All these findings in our study reveal that StMLP1 functions as a positive regulator that is induced and specifically expressed in vascular bundles in response to R. solanacearum infection.

Mapping morphological cortical networks with joint probability distributions from multiple morphological features.

Morphological features sourced from structural magnetic resonance imaging can be used to infer human brain connectivity. Although integrating different morphological features may theoretically be beneficial for obtaining more precise morphological connectivity networks (MCNs), the empirical evidence to support this supposition is scarce. Moreover, the incorporation of different morphological features remains an open question. In this study, we proposed a method to construct cortical MCNs based on multiple morphological features. Specifically, we adopted a multi-dimensional kernel density estimation algorithm to fit regional joint probability distributions (PDs) from different combinations of four morphological features, and estimated inter-regional similarity in the joint PDs via Jensen-Shannon divergence. We evaluated the method by comparing the resultant MCNs with those built based on different single morphological features in terms of topological organization, test-retest reliability, biological plausibility, and behavioral and cognitive relevance. We found that, compared to MCNs built based on different single morphological features, MCNs derived from multiple morphological features displayed less segregated, but more integrated network architecture and different hubs, had higher test-retest reliability, encompassed larger proportions of inter-hemispheric edges and edges between brain regions within the same cytoarchitectonic class, and explained more inter-individual variance in behavior and cognition. These findings were largely reproducible when different brain atlases were used for cortical parcellation. Further analysis of macaque MCNs revealed weak, but significant correlations with axonal connectivity from tract-tracing, independent of the number of morphological features. Altogether, this paper proposes a new method for integrating different morphological features, which will be beneficial for constructing MCNs.

Alkali Metal Cations Induce Structural Evolution on Au(111) During Cathodic Polarization.

The activity of the electrocatalytic CO2 reduction reaction (CO2RR) is substantially affected by alkali metal cations (AM+) in electrolytes, yet the underlying mechanism is still controversial. Here, we employed electrochemical scanning tunneling microscopy and in situ observed Au(111) surface roughening in AM+ electrolytes during cathodic polarization. The roughened surface is highly active for catalyzing the CO2RR due to the formation of surface low-coordinated Au atoms. The critical potential for surface roughening follows the order Cs+ > Rb+ > K+ > Na+ > Li+, and the surface proportion of roughened area decreases in the order of Cs+ > Rb+ > K+ > Na+ > Li+. Electrochemical CO2RR measurements demonstrate that the catalytic activity strongly correlates with the surface roughness. Furthermore, we found that AM+ is critical for surface roughening to occur. The results unveil the unrecognized effect of AM+ on the surface structural evolution and elucidate that the AM+-induced formation of surface high-activity sites contributes to the enhanced CO2RR in large AM+ electrolytes.

Silver Surface-Assisted Dehydrobrominative Cross-Coupling between Identical Aryl Bromides.

Cross-coupling reactions represent an indispensable tool in chemical synthesis. An intriguing challenge in this field is to achieve selective cross-coupling between two precursors with similar reactivity or, to the limit, the identical molecules. Here we report an unexpected dehydrobrominative cross-coupling between 1,3,5-tris(2-bromophenyl)benzene molecules on silver surfaces. Using scanning tunneling microscopy, we examine the reaction process at the single-molecular level, quantify the selectivity of the dehydrobrominative cross-coupling, and reveal the modulation of selectivity by substrate lattice-related catalytic activity or molecular assembly effect. Theoretical calculations indicate that the dehydrobrominative cross-coupling proceeds via regioselective C-H bond activation of debrominated TBPB and subsequent highly selective C-C coupling of the radical-based intermediates. The reaction kinetics plays an important role in the selectivity for the cross-coupling. This work not only expands the toolbox for chemical synthesis but also provides important mechanistic insights into the selectivity of coupling reactions on the surface.

Comparative analysis of sleep parameters and structures derived from wearable flexible electrode sleep patches and polysomnography in young adults.

Polysomnography (PSG) is the gold standard for clinical sleep monitoring, but its cost, discomfort, and limited suitability for continuous use present challenges. The flexible electrode sleep patch (FESP) emerges as an economically viable and patient-friendly solution, offering lightweight, simple operation, and self-applicable. Nevertheless, its utilization in young individuals remains uncertain. The objective of this study was to compare sleep data obtained by FESP and PSG in healthy young individuals and analyze agreement for sleep parameters and structure classification. Overnight monitoring with FESP and PSG recordings in 48 participants (mean age: 23 yr) was done. Correlation analysis, Bland-Altman plots, and Cohen's kappa coefficient assessed consistency. Sensitivity, specificity, and predictive values compared classification against PSG. FESP showed strong correlation and consistency with PSG for sleep monitoring. Bland-Altman plots indicated small errors and high consistency. Kappa values (0.70-0.84) suggested substantial agreement for sleep stage classification. Pearson correlation coefficient values for sleep stages (0.75-0.88) and sleep parameters (0.80-0.96) confirm that FESP has a strong application. Intraclass correlation coefficient yielded values between 0.65 and 0.97. In addition, FESP demonstrated an impressive accuracy range of 84.12-93.47% for sleep stage classification. The FESP also features a wearable self-test program with an error rate of no more than 8% for both deep sleep and wake. In young adults, FESP demonstrated reliable monitoring capabilities comparable to PSG. With its low cost and user-friendly design, FESP is a potential alternative for portable sleep assessment in clinical and research applications. Further studies involving larger populations are needed to validate its diagnostic potential.NEW & NOTEWORTHY By comparison with PSG, this study confirmed the reliability of an efficient, objective, low-cost, and noninvasive portable automatic sleep-monitoring device FESP, which provides effective information for long-term family sleep disorder diagnosis and sleep quality monitoring.

Integrating machine learning and artificial intelligence in life-course epidemiology: pathways to innovative public health solutions.

The integration of machine learning (ML) and artificial intelligence (AI) techniques in life-course epidemiology offers remarkable opportunities to advance our understanding of the complex interplay between biological, social, and environmental factors that shape health trajectories across the lifespan. This perspective summarizes the current applications, discusses future potential and challenges, and provides recommendations for harnessing ML and AI technologies to develop innovative public health solutions. ML and AI have been increasingly applied in epidemiological studies, demonstrating their ability to handle large, complex datasets, identify intricate patterns and associations, integrate multiple and multimodal data types, improve predictive accuracy, and enhance causal inference methods. In life-course epidemiology, these techniques can help identify sensitive periods and critical windows for intervention, model complex interactions between risk factors, predict individual and population-level disease risk trajectories, and strengthen causal inference in observational studies. By leveraging the five principles of life-course research proposed by Elder and Shanahan-lifespan development, agency, time and place, timing, and linked lives-we discuss a framework for applying ML and AI to uncover novel insights and inform targeted interventions. However, the successful integration of these technologies faces challenges related to data quality, model interpretability, bias, privacy, and equity. To fully realize the potential of ML and AI in life-course epidemiology, fostering interdisciplinary collaborations, developing standardized guidelines, advocating for their integration in public health decision-making, prioritizing fairness, and investing in training and capacity building are essential. By responsibly harnessing the power of ML and AI, we can take significant steps towards creating healthier and more equitable futures across the life course.

Supramolecular Polyurethane "Ligaments" Enabling Room-Temperature Self-Healing Flexible Perovskite Solar Cells and Mini-Modules.

Flexible perovskite solar cells (F-PSCs) have emerged as promising alternatives to conventional silicon solar cells for applications in portable and wearable electronics. However, the mechanical stability of inherently brittle perovskite, due to residual lattice stress and ductile fracture formation, poses significant challenges to the long-term photovoltaic performance and device lifetime. In this paper, to address this issue, a dynamic "ligament" composed of supramolecular poly(dimethylsiloxane) polyurethane (DSSP-PPU) is introduced into the grain boundaries of the PSCs, facilitating the release of residual stress and softening of the grain boundaries. Remarkably, this dynamic "ligament" exhibits excellent self-healing properties and enables the healing of cracks in perovskite films at room temperature. The obtained PSCs have achieved power conversion efficiencies of 23.73% and 22.24% for rigid substrates and flexible substrates, respectively, also 17.32% for flexible mini-modules. Notably, the F-PSCs retain nearly 80% of their initial efficiency even after subjecting the F-PSCs to 8000 bending cycles (r = 2 mm), which can further recover to almost 90% of the initial efficiency through the self-healing process. This remarkable improvement in device stability and longevity holds great promise for extending the overall lifetime of F-PSCs.

A Self-Assembled 3D/0D Quasi-Core-Shell Structure as Internal Encapsulation Layer for Stable and Efficient FAPbI3 Perovskite Solar Cells and Modules.

FAPbI3 perovskites have garnered considerable interest owing to their outstanding thermal stability, along with near-theoretical bandgap and efficiency. However, their inherent phase instability presents a substantial challenge to the long-term stability of devices. Herein, this issue through a dual-strategy of self-assembly 3D/0D quasi-core-shell structure is tackled as an internal encapsulation layer, and in situ introduction of excess PbI2 for surface and grain boundary defects passivating, therefore preventing moisture intrusion into FAPbI3 perovskite films. By utilizing this method alone, not only enhances the stability of the FAPbI3 film but also effectively passivates defects and minimizes non-radiative recombination, ultimately yielding a champion device efficiency of 23.23%. Furthermore, the devices own better moisture resistance, exhibiting a T80 lifetime exceeding 3500 h at 40% relative humidity (RH). Meanwhile, a 19.51% PCE of mini-module (5 × 5 cm2) is demonstrated. This research offers valuable insights and directions for the advancement of stable and highly efficient FAPbI3 perovskite solar cells.

Temporal changes in plasma metabolic signatures to predict immune response of antiretroviral therapy among people living with HIV.

Antiretroviral therapy (ART) is an effective treatment for people living with HIV (PLHIVs), requiring an extended period to achieve immune reconstitution. Metabolic alterations induced by ART are crucial for predicting long-term therapeutic responses, yet comprehensive investigation through large-scale clinical studies is still lacking. Here, we collected plasma samples from 108 PLHIVs to the untargeted plasma metabolomics study, based on the longitudinal metabolomics design. Cross-sectional analyzes were performed at pre- and post-ART to explore the metabolic transformation induced by the therapy. Subsequently, delta values between pre- and post-ART measurements were calculated to quantify metabolic alterations. Then, the optimal set of metabolic traits and clinical signatures were further identified and applied to construct random forest model for predicting the future therapeutic responses to ART. We found distinct ART-induced metabolic transformation among PLHIVs. After confounder-adjustments, five metabolites exhibited significant associations with future immune response: tetracosatetraenoic acid (24:4n-6) (pre-ART) (odds ratio [OR]: 0.978, 95% confidence interval [CI]: 0.955~0.997), 1-(3,4-dihydroxyphenyl)-5-hydroxy-3-decanone (pre-ART) (OR: 1.298, 95% CI: 1.061~1.727), beta-PC-M6 (change) (OR: 0.967, 95% CI: 0.938~0.993), d-Galactaro-1,4-lactone (change) (OR: 1.032, 95% CI: 1.007~1.063), Annuionone C (change) (OR: 1.100, 95% CI: 1.030~1.190). The addition of plasma metabolites to clinical markers accurately predicted immune response to ART with an area under curve of 0.91. Notably, most disrupted metabolites were significantly correlated with blood lipids, suggesting that metabolic transformation might contribute to dyslipidemia among PLHIVs. This study highlights the distinct metabolic transformation post-ART among PLHIVs and reveals the potential role of metabolic transformation as key determinants of ART efficacy.