Immune checkpoint inhibitors-induced diabetes mellitus (review).

Immune checkpoint inhibitors (ICIs) have become extensively utilized in the early-stage treatment of various cancers, offering additional therapeutic possibilities for patients with advanced cancer. However, certain patient populations are susceptible to experiencing toxic adverse effects from ICIs, such as thyrotoxicosis, rashes, among others. Specifically, ICIDM, induced by immune checkpoint inhibitors, exhibits characteristics similar to insulin-dependent diabetes mellitus (Type 1 Diabetes Mellitus, T1DM). ICIDM is characterized by a rapid onset and may coincide with severe ketoacidosis. Despite a favorable response to insulin therapy, patients typically require lifelong insulin dependence. After discussing the autoimmune adverse effects and the specifics of ICIs-induced diabetes mellitus (ICIDM), it is important to note that certain patient populations are particularly susceptible to experiencing toxic adverse effects from ICIs. Specifically, ICIDM, which is triggered by immune checkpoint inhibitors, mirrors the characteristics of insulin-dependent diabetes mellitus (Type 1 Diabetes Mellitus, T1DM). This article conducts an in-depth analysis of the literature to explore the pathogenesis, disease progression, and treatment strategies applicable to diabetes induced by immune checkpoint inhibitors (ICIDM).

Application of 5T glutamate chemical exchange saturation transfer imaging in brain tumors: preliminary results.

PURPOSE: Glutamate chemical exchange saturation transfer (GluCEST) is a non-invasive CEST imaging technique for detecting glutamate levels in tissues. We aimed to investigate the reproducibility of the 5T GluCEST technique in healthy volunteers and preliminarily explore its potential clinical application in patients with brain tumors. METHODS: Ten volunteers (4 males, mean age 29 years) underwent three 5T GluCEST imaging scans. The reproducibility of the three imaging GluCEST measurements was assessed using one-way repeated measures analysis of variance (ANOVA), generalized estimating equations, and linear mixed models. Twenty-eight patients with brain tumors (10 males, mean age 54 years) underwent a single GluCEST scan preoperatively, and t-tests were used to compare the differences in GluCEST values between different brain tumors. In addition, the diagnostic accuracy of GluCEST values in differentiating brain tumors was assessed using the receiver work characteristics (ROC) curve. RESULTS: The coefficients of variation of GluCEST values in healthy volunteers were less than 5% for intra-day, inter-day, and within-subjects and less than 10% for between-subjects. High-grade gliomas (HGG) had higher GluCEST values compared to low-grade gliomas (LGG) (P < 0.001). In addition, cerebellopontine angle (CPA) meningiomas had higher GluCEST values than acoustic neuromas (P < 0.001). The area under the curve (AUC) of the GluCEST value for differentiating CPA meningioma from acoustic neuroma was 0.93. CONCLUSION: 5T GluCEST images are highly reproducible in healthy brains. In addition, the 5T GluCEST technique has potential clinical applications in differentiating LGG from HGG and CPA meningiomas from acoustic neuromas.

LCGNet: Local Sequential Feature Coupling Global Representation Learning for Functional Connectivity Network Analysis with fMRI.

Analysis of functional connectivity networks (FCNs) derived from resting-state functional magnetic resonance imaging (rs-fMRI) has greatly advanced our understanding of brain diseases, including Alzheimer's disease (AD) and attention deficit hyperactivity disorder (ADHD). Advanced machine learning techniques, such as convolutional neural networks (CNNs), have been used to learn high-level feature representations of FCNs for automated brain disease classification. Even though convolution operations in CNNs are good at extracting local properties of FCNs, they generally cannot well capture global temporal representations of FCNs. Recently, the transformer technique has demonstrated remarkable performance in various tasks, which is attributed to its effective self-attention mechanism in capturing the global temporal feature representations. However, it cannot effectively model the local network characteristics of FCNs. To this end, in this paper, we propose a novel network structure for Local sequential feature Coupling Global representation learning (LCGNet) to take advantage of convolutional operations and self-attention mechanisms for enhanced FCN representation learning. Specifically, we first build a dynamic FCN for each subject using an overlapped sliding window approach. We then construct three sequential components (i.e., edge-to-vertex layer, vertex-to-network layer, and network-to-temporality layer) with a dual backbone branch of CNN and transformer to extract and couple from local to global topological information of brain networks. Experimental results on two real datasets (i.e., ADNI and ADHD-200) with rs-fMRI data show the superiority of our LCGNet.

Karyotype analysis of Quasipaaspinosa David, 1875 (Anura, Dicroglossidae) with conventional cytogenetic techniques.

The current study analyzed the chromosomal karyotype of Quasipaaspinosa David, 1875 from Hunan Province, China. The karyotype, C-banding, BrdU-banding pattern were characterized using direct preparation of bone-marrow cells and hemocyte cultures. The findings indicated that Q.spinosa was a diploid species (2n = 26) that lacked heteromorphic chromosomes and secondary constrictions. C-banding analysis revealed an abundance of positive signals in the centromere regions, while the BrdU-banding pattern showed three phases in both male and female, occurring consistently and in chronological sequence during S-phase. Notably, there was no asynchronous replication in the late phase. This study enhanced our understanding of the karyotypic structure of Q.spinosa by conventional cytogenetic techniques, thus providing essential scientific insights into the cytogenetics of Q.spinosa.

Adsorption performance and mechanism of pectin modified with ß-cyclodextrin for Zn2+ and Cu2.

Removing heavy metals from aqueous solutions has drawn more and more attentions these years because of their serious global health challenge to human society. To develop an adsorbent with green, stable and high-efficiency for adsorption of heavy metals, pectin ß-cyclodextrin composite was successfully prepared and used for Zn2+ and Cu2+ adsorption for the first time. Various variables that influence the adsorption performance were explored, and the optimal adsorption conditions were determined. According to the pseudo-second-order kinetic model, the adsorption process of Zn2+ and Cu2+ by the adsorbent was mainly chemical adsorption. The adsorbent adsorption process was an exothermic and non-spontaneous process. According to the Langmuir isotherm model, the maximum adsorption capacity was 12.51 ± 0.33 and 24.98 ± 0.23 mg/g for Zn2+ and Cu2+, respectively. The FTIR, EDX and XPS results revealed that the main mechanisms of removing pollutants by adsorbent were ion exchange and coordination. In addition, electrostatic attraction and chelation were present in the adsorption process. After five adsorption desorption cycles, the pectin ß-cyclodextrin composite adsorbent still exhibited adsorption and regeneration capabilities. This study provides a low-cost, effective and simple method for preparation of modified pectin, which has excellent application potential in the removal of heavy metal ions from wastewater.

A simple method improving acoustic mode identification capability based on genetic algorithms.

This letter develops a simple approach of duct mode identification and reconstruction based on genetic algorithms, which can extend the azimuthal mode order range compared to the conventional method based on the (spatial) discrete Fourier transform. The underlying principle is reconstructing the dominant mode from the modal identification forward model through optimization by exploiting the sparsity of the mode amplitude vector. The performance is experimentally demonstrated for detections of one and two azimuthal modes under noisy conditions with nondominant modes. Overall, the proposed genetic-algorithm-based framework for solving acoustic inverse problems is beneficial to duct acoustic testing, particularly design evaluations of fan blades and acoustic liners for aeroengines.

Assessment of the influence of levees along Yangtze River on Oncomelania hupensis, the intermediate host of Schistosoma japonicum.

BACKGROUND: Oncomelania hupensis is the exclusive intermediate host of Schistosoma japonicum in China. Snail control is an essential component of schistosomiasis elimination programme. With 70 years of continuous efforts, the range of O. hupensis had reduced significantly, but slowed down in last decades. A large number of levees against flooding were constructed along Yangtze River and its affiliated lakes in the middle and lower reaches, which influenced the hydrology and ecology in the alluvial plains. The purpose of this study was to assess the impact of levees on the distribution of O. hupensis in the middle and lower reaches of the Yangtze River. METHODS: The snail habitats were digitalised by hand-held GPS system. The years for discovery and elimination of snail habitats were extracted from historical records. The accumulated snail-infested range for each habitat was calculated on the basis of annual reports. The current distribution of O. hupensis was determined by systematic and environmental sampling. The geographical distribution of levees was obtained from satellite imagery. To assess the impact of levees, the data pertaining to O. hupensis were divided into two parts: inside and outside the Yangtze River. Joinpoint regression was utilised to divide the study time span and further characterise the regression in each period. The 5-year-period moving averages of eliminated area infested by snails were calculated for the habitats inside and outside Yangtze River. The moving routes of corresponding geographical median centres were simulated in ArcGIS. Hotspot analysis was used to determine the areas with statistical significance clustering of O. hupensis density. RESULTS: Three periods were identified according to Joinpoint regression both inside and outside Yangtze River. The area infested by O. hupensis increased in the first two periods. It decreased rapidly outside Yangtze River year over year after 1970, while that inside the Yangtze River did not change significantly. Furthermore, the latter was significantly higher than the former. It was observed that the present density of O. hupensis inside Yangtze River was lower than outside the Yangtze River. The median centre for eliminated ranges inside Yangtze River wavered between the east (lower reach) and the west (middle reach). In contrast, the median centre for eliminated ranges continuously moved from the east to the west. CONCLUSIONS: Our findings indicated that the levees had a considerable negative impact on the distribution of O. hupensis outside Yangtze River. Some hotspots observed in the irrigation areas need a sluice system at the inlet of branch for snail control. The major distribution of O. hupensis located in Hubei might be caused by severe waterlogging. The intensive surveillance should be implemented there. The biggest two freshwater lakes, the major endemic regions historically, were identified as cold spots. The long-term impact of Three Gorges Dam on the distribution of O. hupensis in the lakes should be monitored and evaluated.

Efficient Vibration Measurement and Modal Shape Visualization Based on Dynamic Deviations of Structural Edge Profiles.

As a non-contact method, vision-based measurement for vibration extraction and modal parameter identification has attracted much attention. In most cases, artificial textures are crucial elements for visual tracking, and this feature limits the application of vision-based vibration measurement on textureless targets. As a computation technique for visualizing subtle variations in videos, the video magnification technique can analyze modal responses and visualize modal shapes, but the efficiency is low, and the processing results contain clipping artifacts. This paper proposes a novel method for the application of a modal test. In contrast to the deviation magnification that exaggerates subtle geometric deviations from only a single image, the proposed method extracts vibration signals with sub-pixel accuracy on edge positions by changing the perspective of deviations from space to timeline. Then, modal shapes are visualized by decoupling all spatial vibrations following the vibration theory of continuous linear systems. Without relying on artificial textures and motion magnification, the proposed method achieves high operating efficiency and avoids clipping artifacts. Finally, the effectiveness and practical value of the proposed method are validated by two laboratory experiments on a cantilever beam and an arch dam model.

Microwave ablation on ex vivo porcine pancreas: The influence of ablation parameters on ablation results and fat liquefaction.

The pancreas is adjacent to critical organs; excessive microwave ablation (MWA) can result in serious complications. The purpose of this paper is to provide the reference data of pancreas MWA for clinicians, analyze the ablation outcomes under different ablation parameters, and determine the critical temperature of pancreatic surface fat liquefaction outflow. Combinations of two power levels (30 W and 55 W), three antenna diameters (1.3 mm, 1.6 mm, and 1.9 mm), and three ablation times (1 min, 1.5 min, and 2 min) were applied to an ex vivo pig pancreas. Temperature measurements were taken at four thermocouple points. The center point is located 5 mm horizontally from the antenna slot, with a temperature measurement point located 5 mm above, below, and to the right of the center point. Main effect analysis and variance analysis were used to quantify the influences of each factor on the ablation outcomes. At 30 W, the antenna diameter contributing the most at 48.5%. At 30 W-1.3 mm-1 min, the spherical index (1.41) is closest to 1. At 55 W, the coagulation zone size was almost only affected by the ablation time, with a contribution rate of 28.7%, the temperature at point C exceeds point B. On the surface of the ex vivo porcine pancreas, the fat outflow temperature was 54ã. Ablation combinations with low power, short duration, and small antenna diameter results in a more nearly spherical coagulation zone. When performing MWA on the pancreas, it is advisable to avoid areas with higher fat content, while keeping the pancreatic surface temperature below 54°C.

Insight on photocatalytic synchronous oxidation and reduction for pollutant removal: Chemical energy conversion between macromolecular organic pollutants and heavy metal.

Collaborative treatment of pollutants is a promising approach for wastewater treatment. In this work, a covalent organic framework material (COFs) with an imine structure was synthesised by the Schiff base reaction, and photochemical tests showed good photochemical effects. It was used to explore the photocatalytic treatment of co-existing pollutants (heavy metal ions and antibiotics) and the performance of treating co-existing wastewater was investigated. The degradation performance of levofloxacin (LVX) and Cr(VI) was improved in the coexisting pollutants system, with the LVX degradation being 4.2 times more effective than that of the LVX solitary system. Moreover, this phenomenon was also observed in LVX/Ag(I), LVX/Fe(III), sulfadiazine/Cr(VI), norfloxacin/Cr(VI) and tetracycline/Cr(VI) systems. The analysis of active species suggesting that the synergistic promotion of photocatalytic oxidation-reduction systems was not only promoting from the improvement of simple charge separation, but it was also found that high-valent metal species can act directly in the oxidative decomposition of antibiotics. The interaction of pollutants and intermediates were rationally exploited and confirmed by control experiments and theoretical calculation. This conclusion helps us to re-examine the underlying mechanisms of photocatalytic synchronous oxidation and reduction reactions, simultaneously beneficial for the development of mixed pollutant control processes.

Elucidating the causal nexus and immune mediation between frailty and chronic kidney disease: integrative multi-omics analysis.

BACKGROUND: Empirical research has consistently documented the concurrent manifestation of frailty and chronic kidney disease (CKD). However, the existence of a reverse causal association or the influence of confounding variables on these correlations remains ambiguous. METHODS: Our analysis of 7,078 participants from National Health and Nutrition Examination Survey(NHANES) (1999-2018) applied weighted logistic regression and Mendelian Randomization (MR) to investigate the correlation between the frailty index (FI) and renal function. The multivariate MR analysis was specifically adjusted for type 2 diabetes and hypertension. Further analysis explored 3282 plasma proteins to link FI to CKD. A two-step network MR highlighted immune cells' mediating roles in the FI-CKD relationship. RESULT: Genetically inferred FI and various renal function markers are significantly correlated, as supported by NHANES analyses. Multivariate MR analysis revealed a direct causal association between the FI and CKD. Additionally, our investigation into plasma proteins identified Tmprss11D and MICB correlated with FI and CKD, respectively. A two-step network MR to reveal 15 immune cell types, notably Central Memory CD4+ T cells and Lymphocytes, as crucial mediators between FI and CKD. CONCLUSION: Our work establishes a causal connection between frailty and CKD, mediated by specific immune cell profiles. These findings highlight the importance of immune mechanisms in the frailty-CKD interplay and suggest that targeting shared risk factors and immune pathways could improve management strategies for these conditions. Our research contributes to a more nuanced understanding of frailty and CKD, offering new avenues for intervention and patient care in an aging population.

Fungal Saprotrophic Promotion and Plant Pathogenic Suppression under Ditch-Buried Straw Return with Appropriate Burial Amount and Depth.

Fungi as heterotrophs are key participants in the decomposition of organic materials and the transformation of nutrients in agroecosystems. Ditch-buried straw return as a novel conservation management strategy can improve soil fertility and alter hydrothermal processes. However, how ditch-buried straw return strategies affect the soil fungal community is still unclear. Herein, a 7-year field trial was conducted to test the influences of burial depth (0, 10, 20, 30, and 40 cm) and the amount of ditch-buried straw (half, full, double) on the diversity, composition, and predicted functions of a soil fungal community, as well as the activities of carbon-degraded enzymes. Under the full amount of straw burial, the abundance of phylum Ascomycota was 7.5% higher as compared to other burial amount treatments. This further increased the activity of cellobiohydrolase by 32%, as revealed by the positive correlation between Ascomycota and cellobiohydrolase. With deeper straw burial, however, the abundance of Ascomycota and ß-D-glucopyranoside activity decreased. Moreover, genus Alternaria and Fusarium increased while Mortierella decreased with straw burial amount and depth. FUNgild prediction showed that plant fungal pathogens were 1- to 2-fold higher, whilst arbuscular mycorrhizal fungi were 64% lower under straw buried with double the amount and at a depth of 40 cm. Collectively, these findings suggest that ditch-buried straw return with a full amount and buried at a depth less than 30 cm could improve soil nutrient cycles and health and may be beneficial to subsequent crop production.

Three-layer heterogeneous network based on the integration of CircRNA information for MiRNA-disease association prediction.

Increasing research has shown that the abnormal expression of microRNA (miRNA) is associated with many complex diseases. However, biological experiments have many limitations in identifying the potential disease-miRNA associations. Therefore, we developed a computational model of Three-Layer Heterogeneous Network based on the Integration of CircRNA information for MiRNA-Disease Association prediction (TLHNICMDA). In the model, a disease-miRNA-circRNA heterogeneous network is built by known disease-miRNA associations, known miRNA-circRNA interactions, disease similarity, miRNA similarity, and circRNA similarity. Then, the potential disease-miRNA associations are identified by an update algorithm based on the global network. Finally, based on global and local leave-one-out cross validation (LOOCV), the values of AUCs in TLHNICMDA are 0.8795 and 0.7774. Moreover, the mean and standard deviation of AUC in 5-fold cross-validations is 0.8777+/-0.0010. Especially, the two types of case studies illustrated the usefulness of TLHNICMDA in predicting disease-miRNA interactions.

Clinical therapeutic effect of self-prescribed Sanhanchushi Tongbi on lumbar disc herniation.

BACKGROUND: Lumbar disc herniation (LDH) commonly occurs during spinal surgery; LDH is on the increase in younger patients and is classified as "paralysis" and "back pain." Sanhanchushi Tongbi (SPST) is a customized prescription. It disperses cold, relieves pain, removes cold from the meridians and viscera, and treats neuropathic pain. However, few studies have investigated its mechanism of pain relief. AIM: To observe the clinical therapeutic effects on LDH treated with self-prescribed SPST. METHODS: A total of 211 patients with LDH syndrome were divided into two groups: 107 patients in the control group were treated with conventional massage combined with traction, and 104 patients in the observation group were treated with a combination of the control regimen and self-prescribed oral SPST. The patients were treated for 4 wk. Indices of traditional Chinese medicine (TCM) syndrome score and serum inflammatory factor levels were measured. RESULTS: After therapy, the TCM syndrome score in the observation group was significantly lower than that in the control group (P < 0.05). The main symptoms, clinical signs, daily activities, and Japanese Orthopedic Association scores in the observation group were significantly higher than those in the control group after therapy (P < 0.05). The levels of tumor necrosis factor-α, interleukin-6, and C-reactive protein were lower in the observation group than in the control group (P < 0.05). In the observation group, superoxide dismutase levels were significantly higher, whereas malondialdehyde levels were significantly lower, compared with the control group (P < 0.05). The overall efficacy rate in the observation group was 96.15%, which was substantially higher than that in the control group (88.79%; P < 0.05). CONCLUSION: Self-prescribed SPST can reduce the levels of inflammatory and pain-causing factors as well as lumbar pain in patients with LDH.

The pathogenesis mechanism and potential clinical value of lncRNA in gliomas.

Glioma is the most common malignant tumor in the central nervous system, and its unique pathogenesis often leads to poor treatment outcomes and prognosis. In 2021, the World Health Organization (WHO) divided gliomas into five categories based on their histological characteristics and molecular changes. Non-coding RNA is a type of RNA that does not encode proteins but can exert biological functions at the RNA level, and long non-coding RNA (lncRNA) is a type of non-coding RNA with a length exceeding 200 nt. It is controlled by various transcription factors and plays an indispensable role in the regulatory processes in various cells. Numerous studies have confirmed that the dysregulation of lncRNA is critical in the pathogenesis, progression, and malignancy of gliomas. Therefore, this article reviews the proliferation, apoptosis, invasion, migration, angiogenesis, immune regulation, glycolysis, stemness, and drug resistance changes caused by the dysregulation of lncRNA in gliomas, and summarizes their potential clinical significance in gliomas.

Exploring the ecological security evaluation of water resources in the Yangtze River Basin under the background of ecological sustainable development.

The Yangtze River (hereafter referred to as the YZR), the largest river in China, is of paramount importance for ensuring water resource security. The Yangtze River Basin (hereafter referred to as the YRB) is one of the most densely populated areas in China, and complex human activities have a significant impact on the ecological security of water resources. Therefore, this paper employs theories related to ecological population evolution and the Driving Force-Pressure-State-Impact-Response (DPSIR) model to construct an indicator system for the ecological security of water resources in the YRB. The report evaluates the ecological security status of water resources in each province of the YRB from 2010 to 2019, clarifies the development trend of its water resource ecological security, and proposes corresponding strategies for regional ecological security and coordinated economic development. According to the results of the ecological population evolution competition model, the overall indicator of the ecological security of water resources in the YRB continues to improve, with the safety level increasing annually. Maintaining sound management of water resources in the YRB is crucial for sustainable socioeconomic development. To further promote the ecological security of water resources in the YRB and the coordinated development of the regional economy, this paper proposes policy suggestions such as promoting the continuous advancement of sustainable development projects, actively adjusting industrial structure, continuously enhancing public environmental awareness, and actively participating in international ecological construction and seeking cooperation among multiple departments.

Nitrogen input modulates the effects of coastal acidification on nitrification and associated N2O emission.

Acidification of coastal waters, synergistically driven by increasing atmospheric carbon dioxide (CO2) and intensive land-derived nutrient inputs, exerts significant stresses on the biogeochemical cycles of coastal ecosystem. However, the combined effects of anthropogenic nitrogen (N) inputs and aquatic acidification on nitrification, a critical process of N cycling, remains unclear in estuarine and coastal ecosystems. Here, we showed that increased loading of ammonium (NH4+) in estuarine and coastal waters alleviated the inhibitory effect of acidification on nitrification rates but intensified the production of the potent greenhouse gas nitrous oxide (N2O), thus accelerating global climate change. Metatranscriptomes and natural N2O isotopic signatures further suggested that the enhanced emission of N2O may mainly source from hydroxylamine (NH2OH) oxidation rather than from nitrite (NO2-) reduction pathway of nitrifying microbes. This study elucidates how anthropogenic N inputs regulate the effects of coastal acidification on nitrification and associated N2O emissions, thereby enhancing our ability to predict the feedbacks of estuarine and coastal ecosystems to climate change and human perturbations.

Quantifying social roles in multi-animal videos using subject-aware deep-learning.

Analyzing social behaviors is critical for many fields, including neuroscience, psychology, and ecology. While computational tools have been developed to analyze videos containing animals engaging in limited social interactions under specific experimental conditions, automated identification of the social roles of freely moving individuals in a multi-animal group remains unresolved. Here we describe a deep-learning-based system - named LabGym2 - for identifying and quantifying social roles in multi-animal groups. This system uses a subject-aware approach: it evaluates the behavioral state of every individual in a group of two or more animals while factoring in its social and environmental surroundings. We demonstrate the performance of subject-aware deep-learning in different species and assays, from partner preference in freely-moving insects to primate social interactions in the field. Our subject-aware deep learning approach provides a controllable, interpretable, and efficient framework to enable new experimental paradigms and systematic evaluation of interactive behavior in individuals identified within a group.

Optimizing Prediction of In-Hospital Mortality in Elderly Patients With Acute Myocardial Infarction: A Nomogram Approach Using the Age-Adjusted Charlson Comorbidity Index Score.

BACKGROUND: To study the age-adjusted Charlson comorbidity index (ACCI) scale, which is a comprehensive quantification of multimorbidity coexistence, for the assessment of the risk of acute myocardial infarction death in elderly people. METHODS AND RESULTS: A total of 502 older patients with acute myocardial infarction were studied at Qilu Hospital from September 2017 to March 2022. They were categorized on the basis of ACCI into low (≤5), intermediate (6, 7), and high (≥8) risk groups. Hospitalization duration was observed, with death as the end point. least absolute shrinkage and selection operator regression was used to screen variables, 10-fold cross-validation was performed to validate the screened variables, a Cox regression nomogram predicting the risk of patient death was prepared, hazard ratio with 95% CI was calculated, a nomogram calibration curve was constructed, and a receiver operating characteristic curve, decision curve analysis, and a clinical impact curve were established. From 62 potential factors in a least absolute shrinkage and selection operator regression, 12 were selected via 10-fold cross-validation. Retain variables with significant statistical differences in the Cox regression. A nomogram of the risk of death from acute infarction was constructed, and risk factors included ventricular tachycardia/fibrillation, atrial fibrillation, nicorandil, angiotensin-converting enzyme inhibitors/angiotensin-converting enzyme inhibitors, ß blockers, and ACCI score, carbon dioxide combining power, and blood calcium concentration. CONCLUSIONS: The ACCI score effectively assesses multimorbidity in the older patients. As ACCI rises, the death risk from acute myocardial infarction grows. The study's nomogram is valid and clinically applicable.