Unique stick-slip crack dynamics of double-network hydrogels under pure-shear loading.

In this work, we have found that a prenotched double-network (DN) hydrogel, when subjected to tensile loading in a pure-shear geometry, exhibits intriguing stick-slip crack dynamics. These dynamics synchronize with the oscillation of the damage (yielding) zone at the crack tip. Through manipulation of the loading rate and the predamage level of the brittle network in DN gels, we have clarified that this phenomenon stems from the significant amount of energy dissipation required to form the damage zone at the crack tip, as well as a kinetic contrast between the rapid crack extension through the yielding zone (slip process) and the slow formation of a new yielding zone controlled by the external loading rate (stick process).

Study of tree shrew biology and models: A booming and prosperous field for biomedical research.

The tree shrew ( Tupaia belangeri) has long been proposed as a suitable alternative to non-human primates (NHPs) in biomedical and laboratory research due to its close evolutionary relationship with primates. In recent years, significant advances have facilitated tree shrew studies, including the determination of the tree shrew genome, genetic manipulation using spermatogonial stem cells, viral vector-mediated gene delivery, and mapping of the tree shrew brain atlas. However, the limited availability of tree shrews globally remains a substantial challenge in the field. Additionally, determining the key questions best answered using tree shrews constitutes another difficulty. Tree shrew models have historically been used to study hepatitis B virus (HBV) and hepatitis C virus (HCV) infection, myopia, and psychosocial stress-induced depression, with more recent studies focusing on developing animal models for infectious and neurodegenerative diseases. Despite these efforts, the impact of tree shrew models has not yet matched that of rodent or NHP models in biomedical research. This review summarizes the prominent advancements in tree shrew research and reflects on the key biological questions addressed using this model. We emphasize that intensive dedication and robust international collaboration are essential for achieving breakthroughs in tree shrew studies. The use of tree shrews as a unique resource is expected to gain considerable attention with the application of advanced techniques and the development of viable animal models, meeting the increasing demands of life science and biomedical research.

Machine learning prediction model for gray-level co-occurrence matrix features of synchronous liver metastasis in colorectal cancer.

BACKGROUND: Synchronous liver metastasis (SLM) is a significant contributor to morbidity in colorectal cancer (CRC). There are no effective predictive device integration algorithms to predict adverse SLM events during the diagnosis of CRC. AIM: To explore the risk factors for SLM in CRC and construct a visual prediction model based on gray-level co-occurrence matrix (GLCM) features collected from magnetic resonance imaging (MRI). METHODS: Our study retrospectively enrolled 392 patients with CRC from Yichang Central People's Hospital from January 2015 to May 2023. Patients were randomly divided into a training and validation group (3:7). The clinical parameters and GLCM features extracted from MRI were included as candidate variables. The prediction model was constructed using a generalized linear regression model, random forest model (RFM), and artificial neural network model. Receiver operating characteristic curves and decision curves were used to evaluate the prediction model. RESULTS: Among the 392 patients, 48 had SLM (12.24%). We obtained fourteen GLCM imaging data for variable screening of SLM prediction models. Inverse difference, mean sum, sum entropy, sum variance, sum of squares, energy, and difference variance were listed as candidate variables, and the prediction efficiency (area under the curve) of the subsequent RFM in the training set and internal validation set was 0.917 [95% confidence interval (95%CI): 0.866-0.968] and 0.09 (95%CI: 0.858-0.960), respectively. CONCLUSION: A predictive model combining GLCM image features with machine learning can predict SLM in CRC. This model can assist clinicians in making timely and personalized clinical decisions.

On the shoulder of ADC: The development of 124I-IMMU-132, an iodine-124-labelled Trop-2-targeting molecular probe for micro-PET imaging.

BACKGROUND: Trop-2 is closely related to the development and progression of a variety of tumours and poor prognosis. This study aimed to construct an iodine-124 (124I)-labelled antibody-drug conjugate (ADC) positron emission tomography (PET) probe which could noninvasively image Trop-2 in vivo, providing an important method for the diagnosis of tumours with high Trop-2 expression in clinical practice and monitoring their treatment. METHODS: In this study, a novel Trop-2-targeting molecular probe, 124I-IMMU-132, was constructed to better reveal the expression of Trop-2. The targeting and binding abilities of the probe to Trop-2-positive tumours were investigated in Capan-1/MDA-MB-468/Mcf-7 cells and their animal models. RESULTS: The constructed 124I-IMMU-132 probe maintained both reliable radiochemical characteristics and binding affinity (Kd = 2.200 nmol/L). The uptake of the probe by Trop-2-positive Capan-1/MDA-MB-468 cells increased in a time-dependent manner. The probe bound specifically to Capan-1/MDA-MB-468 tumours in vivo. The SUVmax Tumour/muscle ratio gradually increased with time, from 4.30 ± 0.55-10.78 ± 1.80 (p < 0.01) in the Capan-1 model and from 8.84 ± 0.95-32.20 ± 2.9 (p < 0.001) in the MDA-MB-468 model. The biodistribution and pharmacokinetics of 124I-IMMU-132 in a mouse model were consistent with the imaging results, and the dosimetry estimation in humans was acceptable. CONCLUSIONS: 124I-IMMU-132 PET is a promising imaging technique for delineating Trop-2-positive tumours. It has great potential in early diagnosis and targeted selection of patients that could benefit from its application.

Furin Egress from the TGN is Regulated by Membrane-Associated RING-CH Finger (MARCHF) Proteins and Ubiquitin-Specific Protease 32 (USP32) via Nondegradable K33-Polyubiquitination.

Furin primarily localizes to the trans-Golgi network (TGN), where it cleaves and activates a broad range of immature proproteins that play critical roles in cellular homeostasis, disease progression, and infection. Furin is retrieved from endosomes to the TGN after being phosphorylated, but it is still unclear how furin exits the TGN to initiate the post-Golgi trafficking and how its activity is regulated in the TGN. Here three membrane-associated RING-CH finger (MARCHF) proteins (2, 8, 9) are identified as furin E3 ubiquitin ligases, which catalyze furin K33-polyubiquitination. Polyubiquitination prevents furin from maturation by blocking its ectodomain cleavage inside cells but promotes its egress from the TGN and shedding. Further ubiquitin-specific protease 32 (USP32) is identified as the furin deubiquitinase in the TGN that counteracts the MARCHF inhibitory activity on furin. Thus, the furin post-Golgi trafficking is regulated by an interplay between polyubiquitination and phosphorylation. Polyubiquitination is required for furin anterograde transport but inhibits its proprotein convertase activity, and phosphorylation is required for furin retrograde transport to produce fully active furin inside cells.

Discriminative feature analysis of dairy products based on machine learning algorithms and Raman spectroscopy.

Discriminant analysis of similar food samples is an important aspect of achieving food quality control. The effective combination of Raman spectroscopy and machine learning algorithms has become an extremely attractive approach to develop intelligent discrimination techniques. Feature spectral analysis can help researchers gain a deeper understanding of the data patterns in food quality discrimination. Herein, this work takes the discrimination of three brands of dairy products as an example to investigate the Raman spectral feature based on the support vector machines (SVM), extreme learning machines (ELM) and convolutional neural network (CNN) algorithms. The results show that there are certain differences in the optimal spectral feature interval corresponding to different machine learning algorithms. Selecting the appropriate spectral feature interval can maintain high recognition accuracy and improve the computational efficiency of the algorithm. For example, the SVM algorithm has a recognition accuracy of 100% in the 890-980 cm-1, 1410-1500 cm-1 fusion spectral range, which takes about 200 s. The ELM algorithm also has a recognition accuracy of 100% in the 890-980 cm-1, 1410-1500 cm-1 fusion spectral range, which takes less than 0.3 s. The CNN algorithm has a recognition accuracy of 100% in the 890-980 cm-1, 1050-1180 cm-1, 1410-1500 cm-1 fusion spectral range, which takes about 80 s. In addition, by analyzing the distribution of spectral feature intervals based on Euclidean distance, the distribution of experimental samples based on feature spectra is visually displayed. Through the spectral feature analysis process of similar samples, a set of analysis strategies is provided to deeply reveal the data foundation of classification algorithms, which can provide reference for the analysis of relevant discriminative research patterns.

PCSK9 Inhibitor Added to High-Intensity Statin Therapy to Prevent Cardiovascular Events in Patients with Acute Coronary Syndrome after Percutaneous Coronary Intervention: A Randomized, Double- Blind, Placebo-Controlled, Multicenter SHAWN Study.

BACKGROUND: It is currently uncertain whether the combination of a proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitor and high-intensity statin treatment can effectively reduce cardiovascular events in patients with acute coronary syndrome (ACS) who have undergone percutaneous coronary intervention (PCI) for culprit lesions. METHODS: This study protocol describes a double-blind, randomized, placebo-controlled, multicenter study aiming to investigate the efficacy and safety of combining a PCSK9 inhibitor with high-intensity statin therapy in patients with ACS following PCI. A total of 1212 patients with ACS and multiple lesions will be enrolled and randomly assigned to receive either PCSK9 inhibitor plus high-intensity statin therapy or high-intensity statin monotherapy. The randomization process will be stratified by sites, diabetes, initial presentation and use of stable (≥4 weeks) statin treatment at presentation. PCSK 9 inhibitor or its placebo is injected within 4 hours after PCI for the culprit lesion. The primary endpoint is the composite of cardiovascular death, myocardial infarction, stroke, re-hospitalization due to ACS or heart failure, or any ischemia-driven coronary revascularization at one-year follow-up between two groups. Safety endpoints mean PCSK 9 inhibitor and statin intolerance. CONCLUSION: The SHAWN study has been specifically designed to evaluate the effectiveness and safety of adding a PCSK9 inhibitor to high-intensity statin therapy in patients who have experienced ACS following PCI. The primary objective of this study is to generate new evidence regarding the potential benefits of combining a PCSK9 inhibitor with high-intensity statin treatment in reducing cardiovascular events among these patients.

Immunobiology of COVID-19: Mechanistic and therapeutic insights from animal models.

The distribution of the immune system throughout the body complicates in vitro assessments of coronavirus disease 2019 (COVID-19) immunobiology, often resulting in a lack of reproducibility when extrapolated to the whole organism. Consequently, developing animal models is imperative for a comprehensive understanding of the pathology and immunology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. This review summarizes current progress related to COVID-19 animal models, including non-human primates (NHPs), mice, and hamsters, with a focus on their roles in exploring the mechanisms of immunopathology, immune protection, and long-term effects of SARS-CoV-2 infection, as well as their application in immunoprevention and immunotherapy of SARS-CoV-2 infection. Differences among these animal models and their specific applications are also highlighted, as no single model can fully encapsulate all aspects of COVID-19. To effectively address the challenges posed by COVID-19, it is essential to select appropriate animal models that can accurately replicate both fatal and non-fatal infections with varying courses and severities. Optimizing animal model libraries and associated research tools is key to resolving the global COVID-19 pandemic, serving as a robust resource for future emerging infectious diseases.

Cooperative Rh/Achiral Phosphoric Acid-Enabled [3+3] Cycloannulation of Carbonyl Ylides with Quinone Monoimines: Synthesis of Benzofused Dioxabicyclo[3.2.1]octane Scaffolds.

A cooperative Rh/achiral phosphoric acid-enabled [3+3] cycloaddition of in situ-generated carbonyl ylides with quinone monoimines has been developed. With the ability to build up the molecular complexity rapidly and efficiently, this method furnishes highly functionalized oxa-bridged benzofused dioxabicyclo[3.2.1]octane scaffolds bearing two quaternary centers in good to excellent yields under mild conditions. Moreover, the utility of the current method was demonstrated by gram-scale synthesis and elaboration of the products into various functionalized oxa-bridged heterocycles.

Chemoproteomic strategy identifies PfUCHL3 as the target of halofuginone.

The human malaria parasite Plasmodium falciparum (P. falciparum) continues to pose a significant public health challenge, leading to millions of fatalities globally. Halofuginone (HF) has shown a significant anti-P. falciparum effect, suggesting its potential as a therapeutic agent for malaria treatment. In this study, we synthesized a photoaffinity labeling probe of HF to identify its direct target in P. falciparum. Our results reveal that ubiquitin carboxyl-terminal hydrolase 3 (PfUCHL3) acts as a crucial target protein of HF, which modulates parasite growth in the intraerythrocytic cycle. In particular, we discovered that HF potentially forms hydrogen bonds with the Leu10, Glu11, and Arg217 sites of PfUCHL3, thereby inducing an allosteric effect by promoting the embedding of the helix 6' region on the protein surface. Furthermore, HF disrupts the expression of multiple functional proteins mediated by PfUCHL3, specifically those that play crucial roles in amino acid biosynthesis and metabolism in P. falciparum. Taken together, this study highlights PfUCHL3 as a previously undisclosed druggable target of HF, which contributes to the development of novel anti-malarial agents in the future.

Hybrid supercapacitors using metal-organic framework derived nickel-sulfur compounds.

HYPOTHESIS: Metal-organic frameworks (MOFs) are highly suitable precursors for supercapacitor electrode materials owing to their high porosity and stable backbone structures that offer several advantages for redox reactions and rapid ion transport. EXPERIMENTS: In this study, a carbon-coated Ni9S8 composite (Ni9S8@C-5) was prepared via sulfuration at 500 ℃ using a spherical Ni-MOF as the sacrificial template. FINDING: The stable carbon skeleton derived from Ni-MOF and positive structure-activity relationship due to the multinuclear Ni9S8 components resulted in a specific capacity of 278.06 mAh·g-1 at 1 A·g-1. Additionally, the hybrid supercapacitor (HSC) constructed using Ni9S8@C-5 as the positive electrode and the laboratory-prepared coal pitch-based activated carbon (CTP-AC) as the negative electrode achieved an energy density of 69.32 Wh·kg-1 at a power density of 800.06 W·kg-1, and capacity retention of 83.06 % after 5000 cycles of charging and discharging at 5 A·g-1. The Ni-MOF sacrificial template method proposed in this study effectively addresses the challenges associated with structural collapse and agglomeration of Ni9S8 during electrochemical reactions, thus improving its electrochemical performance. Hence, a simple preparation method is demonstrated, with broad application prospects in supercapacitor electrodes.

Investigation of Levan-Derived Nanoparticles of Dolutegravir: A Promising Approach for the Delivery of Anti-HIV Drug as Milk Admixture.

Nanoparticles composed of Levan and Dolutegravir (DTG) have been successfully synthesized using a spray drying procedure specifically designed for milk/food admixture applications. Levan, obtained from the microorganism Bacillus subtilis, was thoroughly characterized using MALDI-TOF and solid-state NMR technique to confirm its properties. In the present study, this isolated Levan was utilized as a carrier for drug delivery applications. The optimized spray-dried nanoparticles exhibited a smooth surface morphology with particle sizes ranging from 195 to 329 nm. In the in-vitro drug release experiments conducted in water media, the spray-dried nanoparticles showed 100 % release, whereas the unprocessed drug exhibited only 50 % release at the end of 24 h. Notably, the drug release in milk was comparable to that in plain media, indicating the compatibility. The improved dissolution rate observed for the nanoparticles could be attributed to the solid-state conversion (confirmed by XRD analysis) of DTG from its crystalline to amorphous state. The stability of the drug was verified using Fourier Transform Infra-Red Spectroscopy and Thermogravimetry-Differential Scanning Calorimetry analysis. To evaluate the in-vitro cellular toxicity, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay was conducted, which revealed the CC50 value of 88.88 ± 5.10 µg/mL for unprocessed DTG and 101.08 ± 37.37 µg/mL for DTG nanoparticles. These results indicated that the toxicity of the nanoparticles was comparable to the unprocessed drug. Furthermore, the anti-HIV activity of the nanoparticles in human cell lines was found to be similar to that of the pure drug, emphasizing the therapeutic efficacy of DTG in combating HIV.

Application of deep learning in isolated tooth identification.

BACKGROUND: Teeth identification has a pivotal role in the dental curriculum and provides one of the important foundations of clinical practice. Accurately identifying teeth is a vital aspect of dental education and clinical practice, but can be challenging due to the anatomical similarities between categories. In this study, we aim to explore the possibility of using a deep learning model to classify isolated tooth by a set of photographs. METHODS: A collection of 5,100 photographs from 850 isolated human tooth specimens were assembled to serve as the dataset for this study. Each tooth was carefully labeled during the data collection phase through direct observation. We developed a deep learning model that incorporates the state-of-the-art feature extractor and attention mechanism to classify each tooth based on a set of 6 photographs captured from multiple angles. To increase the validity of model evaluation, a voting-based strategy was applied to refine the test set to generate a more reliable label, and the model was evaluated under different types of classification granularities. RESULTS: This deep learning model achieved top-3 accuracies of over 90% in all classification types, with an average AUC of 0.95. The Cohen's Kappa demonstrated good agreement between model prediction and the test set. CONCLUSIONS: This deep learning model can achieve performance comparable to that of human experts and has the potential to become a valuable tool for dental education and various applications in accurately identifying isolated tooth.

Investigation of 3D vessel reconstruction under Doppler imaging with phantoms: Towards reconstruction of the Circle of Willis.

BACKGROUND: Stroke is the second leading cause of death across the globe. Early screening and risk detection could provide early intervention and possibly prevent its incidence. Imaging modalities, including 1D-Transcranial Doppler Ultrasound (1D-TCD) or Transcranial Color-code sonography (TCCS), could only provide low spatial resolution or 2D image information, respectively. Notably, 3D imaging modalities including CT have high radiation exposure, whereas MRI is expensive and cannot be adopted in patients with implanted devices. This study proposes an alternative imaging solution for reconstructing 3D Doppler ultrasound geared towards providing a screening tool for the 3D vessel structure of the brain. METHODS: The system comprises an ultrasound phased array attached to a servo motor, which can rotate 180˚ at a speed of 2˚/s. We extracted the color Doppler ROI from the image before reconstructing it into a 3D view using a customized pixel-based algorithm. Different vascular diameters, flow velocity, and depth were tested using a vascular phantom with a pumped flow to confirm the system for imaging blood flow. These variables were set to mimic the vessel diameter, flow speed, and depth of the Circle of Willis (CoW) during a transcranial screening. RESULTS AND CONCLUSIONS: The lower values of absolute error and ratio were found in the larger vascular channels, and vessel diameter overrepresentation was observed. Under different flow velocities, such diameter overrepresentation in the reconstructed flow did not change much; however, it did change with different depths. Meanwhile, the setting of the velocity scale and the color gain affected the dimension of reconstructed objectives. Moreover, we presented a 3D image of CoW from a subject to demonstrate its potential. The findings of this work can provide a good reference for further studies on the reconstruction of the CoW or other blood vessels using Doppler imaging.

Pan-cancer analysis for the prognostic and immunological role of CD47: interact with TNFRSF9 inducing CD8 + T cell exhaustion.

PURPOSE: The research endeavors to explore the implications of CD47 in cancer immunotherapy effectiveness. Specifically, there is a gap in comprehending the influence of CD47 on the tumor immune microenvironment, particularly in relation to CD8 + T cells. Our study aims to elucidate the prognostic and immunological relevance of CD47 to enhance insights into its prospective utilities in immunotherapeutic interventions. METHODS: Differential gene expression analysis, prognosis assessment, immunological infiltration evaluation, pathway enrichment analysis, and correlation investigation were performed utilizing a combination of R packages, computational algorithms, diverse datasets, and patient cohorts. Validation of the concept was achieved through the utilization of single-cell sequencing technology. RESULTS: CD47 demonstrated ubiquitous expression across various cancer types and was notably associated with unfavorable prognostic outcomes in pan-cancer assessments. Immunological investigations unveiled a robust correlation between CD47 expression and T-cell infiltration rather than T-cell exclusion across multiple cancer types. Specifically, the CD47-high group exhibited a poorer prognosis for the cytotoxic CD8 + T cell Top group compared to the CD47-low group, suggesting a potential impairment of CD8 + T cell functionality by CD47. The exploration of mechanism identified enrichment of CD47-associated differentially expressed genes in the CD8 + T cell exhausted pathway in multiple cancer contexts. Further analyses focusing on the CD8 TCR Downstream Pathway and gene correlation patterns underscored the significant involvement of TNFRSF9 in mediating these effects. CONCLUSION: A robust association exists between CD47 and the exhaustion of CD8 + T cells, potentially enabling immune evasion by cancer cells and thereby contributing to adverse prognostic outcomes. Consequently, genes such as CD47 and those linked to T-cell exhaustion, notably TNFRSF9, present as promising dual antigenic targets, providing critical insights into the field of immunotherapy.

Different mechanisms underlie similar species-area relationships in two tropical archipelagoes.

Despite much research in the field of island biogeography, mechanisms regulating insular diversity remain elusive. Here, we aim to explore mechanisms underlying plant species-area relationships in two tropical archipelagoes in the South China Sea. We found positive plant species-area relationships for both coral and continental archipelagoes. However, our results showed that different mechanisms contributed to similar plant species-area relationships between the two archipelagoes. For coral islands, soil nutrients and spatial distance among communities played major roles in shaping plant community structure and species diversity. By contrast, the direct effect of island area, and to a lesser extent, soil nutrients determined plant species richness on continental islands. Intriguingly, increasing soil nutrients availability (N, P, K) had opposite effects on plant diversity between the two archipelagoes. In summary, the habitat quality effect and dispersal limitation are important for regulating plant diversity on coral islands, whereas the passive sampling effect, and to a lesser extent, the habitat quality effect are important for regulating plant diversity on continental islands. More generally, our findings indicate that island plant species-area relationships are outcomes of the interplay of both niche and neutral processes, but the driving mechanisms behind these relationships depends on the type of islands.

Fate of florfenicol and linezolid resistance genes and their bacterial hosts during two waste treatment models in swine feedlots.

Florfenicol resistance genes (FRGs) are widely present in livestock farms. The aim of this study was to evaluate the removal efficiencies of FRGs as well as the relationships between FRGs, mobile genetic elements (MGEs) and bacterial communities during the natural drying (ND) and anaerobic digestion (AD) processes of manure treatment in swine farms by combining bacterial isolation, quantitative PCR and metagenomic approaches. Solid manure showed a higher abundance of FRGs than fresh manure and was the main contamination source of fexA and fexB in ND farms, whilst biogas slurry displayed a lower abundance of FRGs than the wastewater in AD farms. Moreover, fresh manure and wastewater showed a high abundance of optrA, and wastewater was the main contamination source of cfr in both ND and AD farms. Both optrA/fexA-positive enterococci and cfr/fexA-positive staphylococci were mainly isolated along the farms' treatment processes. The cfr-positive staphylococci were highly prevalent in wastewater (57.14 % - 100 %) and may be associated with nasal-derived cfr-positive porcine staphylococci. An increased abundance of Enterococcus, Jeotgalibaca and Vagococcus in the bacterial community structures may account for the high optrA abundance in wastewater and Jeotgalibaca may be another potential host of optrA. Furthermore, the abundance of FRG-related MGEs increased by 22.63 % after the ND process and decreased by 66.96 % in AD farms. A significant correlation was observed between cfr and ISEnfa4, whereas no significance was found between optrA and IS1216E, although IS1216E is the predominant insertion sequence involved in the transfer of optrA. In conclusion, manure and wastewater represented independent pollution sources of FRGs in swine farms. Associated MGEs might play a key role in the transfer and persistence of FRGs. The AD process was more efficient in the removal of FRGs than the ND method, nevertheless a longer storage of slurry may be required for a complete removal.

Treatment outcomes amongst older people with HIV infection receiving antiretroviral therapy.

OBJECTIVES: There is conflicting data regarding the response of older people with HIV (PWH) to antiretroviral therapy (ART). The objective of this study was to evaluate the long-term immunological and virological responses, changes in regimen, and adverse drug reactions (ADRs) in older participants (50+ years) compared with younger (18-34 years) and middle-aged (35-49 years) PWH. METHODS: A retrospective review of medical records was conducted on 1622 participants who received ART in Yunnan Province, China, from 2010 to 2019. The study compared CD4+ T-cell counts, CD4+/CD8+ ratio, and relative numbers between different groups using the Kruskal-Wallis test. Cox proportional hazards regression models were used to identify variables associated with the occurrence of immune reconstitution insufficiency. The rates of immune reconstitution, incidence of ADRs, and rates of treatment change were analyzed using the chi-squared test or Fisher's exact test. RESULTS: Over 95% achieved viral load 200 copies/ml or less, with no age-related difference. However, older participants exhibited significantly lower CD4+ T-cell counts and CD4+/CD8+ recovery post-ART (P < 0.001), with only 32.21% achieving immune reconstitution (compared with young: 52.16%, middle-aged: 39.29%, P < 0.001) at the end of follow-up. Middle-aged and elderly participants changed ART regimens more because of ADRs, especially bone marrow suppression and renal dysfunction. CONCLUSION: Although the virological response was consistent across age groups, older individuals showed poorer immune responses and higher susceptibility to side effects. This underscores the need for tailored interventions and comprehensive management for older patients with HIV.