Conserved intronic secondary structures with concealed branch sites regulate alternative splicing of poison exons.

Alternative splicing (AS) generates multiple RNA isoforms and increases the complexities of transcriptomes and proteomes. However, it remains unclear how RNA structures contribute to AS regulation. Here, we systematically search transcriptomes for secondary structures with concealed branch sites (BSs) in the alternatively spliced introns and predict thousands of them from six organisms, of which many are evolutionarily conserved. Intriguingly, a highly conserved stem-loop structure with concealed BSs is found in animal SF3B3 genes and colocalizes with a downstream poison exon (PE). Destabilization of this structure allows increased usage of the BSs and results in enhanced PE inclusion in human and Drosophila cells, leading to decreased expression of SF3B3. This structure is experimentally validated using an in-cell SHAPE-MaP assay. Through RNA interference screens of 28 RNA-binding proteins, we find that this stem-loop structure is sensitive to U2 factors. Furthermore, we find that SF3B3 also facilitates DNA repair and protects genome stability by enhancing interaction between ERCC6/CSB and arrested RNA polymerase II. Importantly, both Drosophila and human cells with the secondary structure mutated by genome editing exhibit altered DNA repair in vivo. This study provides a novel and common mechanism for AS regulation of PEs and reveals a physiological function of SF3B3 in DNA repair.

DMGL-MDA: A dual-modal graph learning method for microbe-drug association prediction.

The interaction between human microbes and drugs can significantly impact human physiological functions. It is crucial to identify potential microbe-drug associations (MDAs) before drug administration. However, conventional biological experiments to predict MDAs are plagued by drawbacks such as time-consuming, high costs, and potential risks. On the contrary, computational approaches can speed up the screening of MDAs at a low cost. Most computational models usually use a drug similarity matrix as the initial feature representation of drugs and stack the graph neural network layers to extract the features of network nodes. However, different calculation methods result in distinct similarity matrices, and message passing in graph neural networks (GNNs) induces phenomena of over-smoothing and over-squashing, thereby impacting the performance of the model. To address these issues, we proposed a novel graph representation learning model, dual-modal graph learning for microbe-drug association prediction (DMGL-MDA). It comprises a dual-modal embedding module, a bipartite graph network embedding module, and a predictor module. To assess the performance of DMGL-MDA, we compared it against state-of-the-art methods using two benchmark datasets. Through cross-validation, we illustrated the superiority of DMGL-MDA. Furthermore, we conducted ablation experiments and case studies to validate the effective performance of the model.

Deep learning predicts DNA methylation regulatory variants in the human brain and elucidates the genetics of psychiatric disorders.

There is growing evidence for the role of DNA methylation (DNAm) quantitative trait loci (mQTLs) in the genetics of complex traits, including psychiatric disorders. However, due to extensive linkage disequilibrium (LD) of the genome, it is challenging to identify causal genetic variations that drive DNAm levels by population-based genetic association studies. This limits the utility of mQTLs for fine-mapping risk loci underlying psychiatric disorders identified by genome-wide association studies (GWAS). Here we present INTERACT, a deep learning model that integrates convolutional neural networks with transformer, to predict effects of genetic variations on DNAm levels at CpG sites in the human brain. We show that INTERACT-derived DNAm regulatory variants are not confounded by LD, are concentrated in regulatory genomic regions in the human brain, and are convergent with mQTL evidence from genetic association analysis. We further demonstrate that predicted DNAm regulatory variants are enriched for heritability of brain-related traits and improve polygenic risk prediction for schizophrenia across diverse ancestry samples. Finally, we applied predicted DNAm regulatory variants for fine-mapping schizophrenia GWAS risk loci to identify potential novel risk genes. Our study shows the power of a deep learning approach to identify functional regulatory variants that may elucidate the genetic basis of complex traits.

Correction: Virus-mimicking nanosystems: from design to biomedical applications.

Correction for 'Virus-mimicking nanosystems: from design to biomedical applications' by Hao-Yang Liu et al., Chem. Soc. Rev., 2023, 52, 8481-8499, https://doi.org/10.1039/D3CS00138E.

One-Step Dual-Color Labeling of Viral Envelope and Intraviral Genome with Quantum Dots Harnessing Virus Infection.

Labeling the genome and envelope of a virus with multicolor quantum dots (QDs) simultaneously enables real-time monitoring of viral uncoating and genome release, contributing to our understanding of virus infection mechanisms. However, current labeling techniques require genetic modification, which alters the virus's composition and infectivity. To address this, we utilized the CRISPR/Cas13 system and a bioorthogonal metabolic method to label the Japanese encephalitis virus (JEV) genome and envelopes with different-colored QDs in situ. This technique allows one-step two-color labeling of the viral envelope and intraviral genome with QDs harnessing virus infection. In combination with single-virus tracking, we visualized JEV uncoating and genome release in real time near the endoplasmic reticulum of live cells. This labeling strategy allows for real-time visualization of uncoating and genome release at the single-virus level, and it is expected to advance the study of other viral infection mechanisms.

The Role and Clinical Relevance of Glycolysis-Associated Genes on Immune Infiltration in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) poses a significant challenge with dismal survival rates, necessitating a deeper understanding of its molecular mechanisms and the development of improved therapies. Metabolic reprogramming, particularly heightened glycolysis, plays a crucial role in HCC progression. Glycolysis-associated genes (GAGs) emerge as key players in HCC pathogenesis, influencing the tumor microenvironment and immune responses. This study aims to investigate the intricate interplay between GAGs and the immune landscape within HCC, offering valuable insights into potential prognostic markers and therapeutic targets to enhance treatment strategies and patient outcomes. Through the exploration of GAGs, we have identified two distinct molecular glycolytic subtypes in HCC patients, each exhibiting significant differences in both the immune microenvironment and prognosis. A risk model comprising five key GAGs was formulated and subsequently evaluated for their predictive accuracy. Our findings underscore the diverse tumor microenvironment and immune responses associated with the varying glycolytic subtypes observed in HCC. The identified key GAGs hold promise as prognostic indicators for evaluating HCC risk levels, predicting patient outcomes, and guiding clinical treatment decisions, particularly in the context of anticipating responses to immunotherapy drugs.

Origin of Polarization in Bismuth Sodium Titanate-Based Ceramics.

The classical view of the structural changes that occur at the ferroelectric transition in perovskite-structured systems, such as BaTiO3, is that polarization occurs due to the off-center displacement of the B-site cations. Here, we show that in the bismuth sodium titanate (BNT)-based composition 0.2(Ba0.4Sr0.6TiO3)-0.8(Bi0.5Na0.5TiO3), this model does not accurately describe the structural situation. Such BNT-based systems are of interest as lead-free alternatives to currently used materials in a variety of piezo-/ferroelectric applications. A combination of high-resolution powder neutron diffraction, impedance spectroscopy, and ab initio calculations reveals that Ti4+ contributes less than a third in magnitude to the overall polarization and that the displacements of the O2- ions and the A-site cations, particularly Bi3+, are very significant. The detailed examination of the ferroelectric transition in this system offers insights applicable to the understanding of such transitions in other ferroelectric perovskites, particularly those containing lone pair elements.

Electrochemiluminescence-Based Single-Particle Tracking of the Biomolecules Moving along Intercellular Membrane Nanotubes between Live Cells.

Electrochemiluminescence (ECL) imaging, a rapidly evolving technology, has attracted significant attention in the field of cellular imaging. However, its primary limitation lies in its inability to analyze the motion behaviors of individual particles in live cellular environments. In this study, we leveraged the exceptional ECL properties of quantum dots (QDs) and the excellent electrochemical properties of carbon dots (CDs) to develop a high-brightness ECL nanoprobe (CDs-QDs) for real-time ECL imaging between living cells. This nanoprobe has excellent signal-to-noise ratio imaging capabilities for the single-particle tracking (SPT) of biomolecules. Our finding elucidated the enhanced ECL mechanism of CDs-QDs in the presence of reactive oxygen species through photoluminescence, electrochemistry, and ECL techniques. We further tracked the movement of single particles on membrane nanotubes between live cells and confirmed that the ECL-based SPT technique using CD-QD nanoparticles is an effective approach for monitoring the transport behaviors of biomolecules on membrane nanotubes between live cells. This opens a promising avenue for the advancement of ECL-based single-particle detection and the dynamic quantitative imaging of biomolecules.

Childhood urbanicity is associated with emotional episodic memory-related striatal function and common variation in NTRK2.

BACKGROUND: Childhoods in urban or rural environments may differentially affect the risk of neuropsychiatric disorders, possibly through memory processing and neural response to emotional stimuli. Genetic factors may not only influence individuals' choices of residence but also modulate how the living environment affects responses to episodic memory. METHODS: We investigated the effects of childhood urbanicity on episodic memory in 410 adults (discovery sample) and 72 adults (replication sample) with comparable socioeconomic statuses in Beijing, China, distinguishing between those with rural backgrounds (resided in rural areas before age 12 and relocated to urban areas at or after age 12) and urban backgrounds (resided in cities before age 12). We examined the effect of childhood urbanicity on brain function across encoding and retrieval sessions using an fMRI episodic memory paradigm involving the processing of neutral or aversive pictures. Moreover, genetic association analyses were conducted to understand the potential genetic underpinnings that might contribute to memory processing and neural mechanisms influenced by early-life urban or rural environments. RESULTS: Episodic memory retrieval accuracy for more difficult neutral stimuli was similar between those with urban and rural childhoods, whereas aversive stimuli elicited higher retrieval accuracy in the urban group (P = 0.023). For aversive stimuli, subjects with urban childhood had relatively decreased engagement of the striatum at encoding and decreased engagement of the hippocampus at retrieval. This more efficient striatal encoding of aversive stimuli in those with urban childhoods was associated with common variation in neurotrophic tyrosine kinase receptor type 2 (NTRK2) (right striatum: P = 1.58×10-6). These findings were confirmed in the replication sample. CONCLUSIONS: We suggest that this differential striatal processing of aversive stimuli observed in individuals with urban or rural childhoods may represent mechanisms by which childhood urbanicity may affect brain circuits, heightening behavioral responses to negative stressors associated with urban environments. NTRK2-associated neural processes in the striatum may play a role in these processes.

SnSe2 Quantum Dots and Chlorhexidine Acetate Suppress Synergistically Non-radiative Recombination Loss for High Efficiency and Stability Perovskite Solar Cells.

Non-radiative recombination losses limit the property of perovskite solar cells (PSCs). Here, a synergistic strategy of SnSe2QDs doping into SnO2 and chlorhexidine acetate (CA) coating on the surface of perovskite is proposed. The introduction of 2D SnSe2QDs reduces the oxygen vacancy defects and increases the carrier mobility of SnO2. The optimized SnO2 as a buried interface obviously improves the crystallization quality of perovskite. The CA containing abundant active sites of ─NH2/─NH─, ─C═N, CO, ─Cl groups passivate the defects on the surface and grain boundary of perovskite. The alkyl chain of CA also improves the hydrophobicity of perovskite. Moreover, the synergism of SnSe2QDs and CA releases the residual stress and regulates the energy level arrangement at the top and bottom interface of perovskite. Benefiting from these advantages, the bulk and interface non-radiative recombination loss is greatly suppressed and thereby increases the carrier transport and extraction in devices. As a result, the best power conversion efficiency (PCE) of 23.41% for rigid PSCs and the best PCE of 21.84% for flexible PSCs are reached. The rigid PSC maintains 89% of initial efficiency after storing nitrogen for 3100 h. The flexible PSCs retain 87% of the initial PCE after 5000 bending cycles at a bending radius of 5 mm.

Oridonin-induced ferroptosis and apoptosis: a dual approach to suppress the growth of osteosarcoma cells.

BACKGROUND: Osteosarcoma (OS) is one of the most common aggressive bone malignancy tumors in adolescents. With the application of new chemotherapy regimens, finding new and effective anti-OS drugs to coordinate program implementation is urgent for the patients of OS. Oridonin had been proved to mediate anti-tumor effect on OS cells, but its mechanism has not been fully elucidated. METHODS: The effects of oridonin on the viability, clonal formation and migration of 143B and U2OS cells were detected by CCK-8, colony formation assays and wound-healing test. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was used to explore the mechanism of oridonin on OS. Western blot (WB), real-time quantitative PCR (qRT-PCR) were used to detect the expression levels of apoptosis and ferroptosis-relative proteins and genes. Annexin V-FITC apoptosis detection kit and flow cytometry examination were used to detect the level of apoptosis. Iron assay kit was used to evaluate the relative Fe2+ content. The levels of mitochondrial membrane potential and lipid peroxidation production was determined by mitochondrial membrane potential detection kit and ROS assay kit. RESULTS: Oridonin could effectively inhibit the survival, clonal formation and metastasis of OS cells. The KEGG results indicated that oridonin is associated with the malignant phenotypic signaling pathways of proliferation, migration, and drug resistance in OS. Oridonin was capable of inhibiting expressions of BAX, cl-caspase3, SLC7A11, GPX4 and FTH1 proteins and mRNA, while promoting the expressions of Bcl-2 and ACSL4 in 143B and U2OS cells. Additionally, we found that oridonin could promote the accumulation of reactive oxygen species (ROS) and Fe2+ in OS cells, as well as reduce mitochondrial membrane potential, and these effects could be significantly reversed by the ferroptosis inhibitor ferrostatin-1 (Fer-1). CONCLUSION: Oridonin can trigger apoptosis and ferroptosis collaboratively in OS cells, making it a promising and effective agent for OS therapy.

Divergent projections of the prelimbic cortex mediate autism- and anxiety-like behaviors.

The comorbidity of autism spectrum disorder and anxiety is common, but the underlying circuitry is poorly understood. Here, Tmem74-/- mice showed autism- and anxiety-like behaviors along with increased excitability of pyramidal neurons (PNs) in the prelimbic cortex (PL), which were reversed by Tmem74 re-expression and chemogenetic inhibition in PNs of the PL. To determine the underlying circuitry, we performed conditional deletion of Tmem74 in the PNs of PL of mice, and we found that alterations in the PL projections to fast-spiking interneurons (FSIs) in the dorsal striatum (dSTR) (PLPNs-dSTRFSIs) mediated the hyperexcitability of FSIs and autism-like behaviors and that alterations in the PL projections to the PNs of the basolateral amygdaloid nucleus (BLA) (PLPNs-BLAPNs) mediated the hyperexcitability of PNs and anxiety-like behaviors. However, the two populations of PNs in the PL had different spatial locations, optogenetic manipulations revealed that alterations in the activity in the PL-dSTR or PL-BLA circuits led to autism- or anxiety-like behaviors, respectively. Collectively, these findings highlight that the hyperactivity of the two populations of PNs in the PL mediates autism and anxiety comorbidity through the PL-dSTR and PL-BLA circuits, which may lead to the development of new therapeutics for the autism and anxiety comorbidity.

Redox Relay-Induced C-S Radical Cross-Coupling Strategy: Application in Nontraditional Site-Selective Thiocyanation of Quinoxalinones.

Oxidative cross-coupling is a powerful strategy to form C-heteroatom bonds. However, oxidative cross-coupling for constructing C-S bond is still a challenge due to sulfur overoxidation and poisoning transition-metal catalysts. Now, electrochemical redox relay using sulfur radicals formed in situ from inorganic sulfur source offers a solution to this problem. Herein, electrochemical redox relay-induced C-S radical cross-coupling of quinoxalinones and ammonium thiocyanate with bromine anion as mediator is presented. The electrochemical redox relay comprised initially the formation of sulfur radical via indirect electrochemical oxidation, simultaneous electrochemical reduction of the imine bond, electro-oxidation-triggered radical coupling involving dearomatization-rearomatization, and the reformation of the imine bond through anodic oxidation. Applying this strategy, various quinoxalinones bearing multifarious electron-deficient/-rich substituents at different positions were well compatible with moderate to excellent yields and good steric hindrance compatibility under constant current conditions in an undivided cell without transition-metal catalysts and additional redox reagents. Synthetic applications of this methodology were demonstrated through gram-scale preparation and follow-up transformation. Notably, such a unique strategy may offer new opportunities for the development of new quinoxalinone-core leads.

Gas-phase F-atom migration reaction of deprotonated N-fluoroarenesulfonamides.

RATIONALE: Recently N-Fluoroarenesulfonamides (ArSO2 NHF) were found to be promising precursors for the preparation of N-fluorobenzenesulfonimide derivatives without applying F2 . However, very few studies have discussed the mass spectrometric behaviors of ArSO2 NHF with N-F structure. METHODS: In this article, we applied high-resolution electrospray ionization tandem mass spectrometry (HR-ESI-MS/MS) to study the effect on the mass spectrometric behaviors of ArSO2 NHF after the introduction of the F-atom to the N-atom of ArSO2 NH2 . RESULTS: High-resolution electrospray ionization mass spectrometry (HR-ESI-MS) experiments showed that ArSO2 NHF produced only good signals in negative ion mode, and the dominating product ion SO2 F- at m/z 83 was observed in all HR-ESI-MS/MS of ArSO2 NF- with different substituents in the Ar group. The formation of the product ion SO2 F- was proof of the gas-phase F-atom migration rearrangement from the N-atom to the S-atom in ESI-MS/MS of ArSO2 NF- . CONCLUSION: To fully explain the gas-phase reaction mechanism from ArSO2 NF- to SO2 F- , we studied the HR-ESI-MS/MS of deprotonated ArSO2 NHF and also performed theoretical calculations. Both results confirmed that ArSO2 NF- first underwent Smiles rearrangement to yield intermediate I (INT1) ArNFSO2 - , and then the F-atom of ArNFSO2 - migrated from the N-atom to the S-atom to form intermediate II (INT2) ArN- SO2 F, which finally dissociated to SO2 F- at m/z 83 with loss of a neutral nitrene (ArN). All these results showed that the formation of the product ion SO2 F- from ArSO2 NF- was a common and intrinsic gas-phase reactivity of ArSO2 NF- .

Modified physiologic criteria for the field triage scheme: Efficacy of major trauma recognition in different age groups in Asia.

BACKGROUND: Major trauma is a leading cause of unexpected death globally, with increasing age-adjusted death rates for unintentional injuries. Field triage schemes (FTSs) assist emergency medical technicians in identifying appropriate medical care facilities for patients. While full FTSs may improve sensitivity, step-by-step field triage is time-consuming. A simplified FTS (sFTS) that uses only physiological and anatomical criteria may offer a more rapid decision-making process. However, evidence for this approach is limited, and its performance in identifying all age groups requiring trauma center resources in Asia remains unclear. METHODS: We conducted a multinational retrospective cohort study involving adult trauma patients admitted to emergency departments in the included countries from 2016 to 2020. Prehospital and hospital data were reviewed from the Pan-Asia Trauma Outcomes Study database. Patients aged ≥18 years transported by emergency medical services were included. Patients lacking data regarding age, sex, physiological criteria, or injury severity scores were excluded. We examined the performance of sFTS in all age groups and fine-tuned physiological criteria to improve sFTS performance in identifying high-risk trauma patients in different age groups. RESULTS: The sensitivity and specificity of the physiological and anatomical criteria for identifying major trauma (injury severity score ≥ 16) were 80.6% and 58.8%, respectively. The modified sFTS showed increased sensitivity and decreased specificity, with more pronounced changes in the young age group. Adding the shock index further increased sensitivity in both age groups. CONCLUSIONS: sFTS using only physiological and anatomical criteria is suboptimal for Asian adult patients with trauma of all age groups. Adjusting the physiological criteria and adding a shock index as a triage tool can improve the sensitivity of severely injured patients, particularly in young age groups. A swift field triage process can maintain acceptable sensitivity and specificity in severely injured patients.

Air pollution interacts with genetic risk to influence cortical networks implicated in depression.

Air pollution is a reversible cause of significant global mortality and morbidity. Epidemiological evidence suggests associations between air pollution exposure and impaired cognition and increased risk for major depressive disorders. However, the neural bases of these associations have been unclear. Here, in healthy human subjects exposed to relatively high air pollution and controlling for socioeconomic, genomic, and other confounders, we examine across multiple levels of brain network function the extent to which particulate matter (PM2.5) exposure influences putative genetic risk mechanisms associated with depression. Increased ambient PM2.5 exposure was associated with poorer reasoning and problem solving and higher-trait anxiety/depression. Working memory and stress-related information transfer (effective connectivity) across cortical and subcortical brain networks were influenced by PM2.5 exposure to differing extents depending on the polygenic risk for depression in gene-by-environment interactions. Effective connectivity patterns from individuals with higher polygenic risk for depression and higher exposures with PM2.5, but not from those with lower genetic risk or lower exposures, correlated spatially with the coexpression of depression-associated genes across corresponding brain regions in the Allen Brain Atlas. These converging data suggest that PM2.5 exposure affects brain network functions implicated in the genetic mechanisms of depression.

Quantum teleportation of physical qubits into logical code spaces.

Quantum error correction is an essential tool for reliably performing tasks for processing quantum information on a large scale. However, integration into quantum circuits to achieve these tasks is problematic when one realizes that nontransverse operations, which are essential for universal quantum computation, lead to the spread of errors. Quantum gate teleportation has been proposed as an elegant solution for this. Here, one replaces these fragile, nontransverse inline gates with the generation of specific, highly entangled offline resource states that can be teleported into the circuit to implement the nontransverse gate. As the first important step, we create a maximally entangled state between a physical and an error-correctable logical qubit and use it as a teleportation resource. We then demonstrate the teleportation of quantum information encoded on the physical qubit into the error-corrected logical qubit with fidelities up to 0.786. Our scheme can be designed to be fully fault tolerant so that it can be used in future large-scale quantum technologies.

An assessment of the antihyperlipidemic ingredients of Qi Ge Decoction based on metabolomics combined with serum pharmacochemistry.

This study aims to explore the pharmacological substance basis of Qi Ge Decoction (QG) in antihyperlipidemia through a combination of metabolomics and serum pharmacochemistry. We used ultra-performance liquid chromatography quadrupole-time-of-flight/MS (UPLC Q-TOF/MS) to analyze and identify the chemical constituents of QG in vitro and in blood chemical components. The metabolomics technology was used to analyze serum biomarkers of QG in preventing and treating hyperlipidemia. We constructed a mathematical model of the relationship between constituents absorbed into the blood and endogenous biomarkers and explored the potential therapeutic application of QG for the prevention and treatment of hyperlipidemia. Compared with the model group, the levels of total cholesterol and triglyceride in the QG group were significantly decreased (P < 0.01). A total of 12 chemical components absorbed into the blood were identified, and 48 biomarkers of the hyperlipidemia model were obtained from serum metabolomic analysis, of which 15 metabolites were backregulated after QG intervention. Puerarin, hesperetin, puerarin xyloside, calycosin, and monohydroxy-tetramethoxyflavone had a high correlation with the biomarkers regulated by QG. This study elucidated the material basis of QG in the intervention of hyperlipidemia, thereby facilitating future research aimed at further revealing the pharmacodynamic material basis of QG's antihyperlipidemic effects.

UPLC-Q-TOF/MS analysis of chemical components of single decoction and combined decoction of Qige decoction reveals the differences between various preparation processes.

The aim of this work was to explore the differences between various pharmaceutical processes in combined solutions of a single decoction (QGHBY) and a combined decoction (QGHJY) of Qi-Ge decoction from the perspective of chemical composition changes, so as to further guide the clinical application of drugs. A combined solution of a single decoction and a combined decoction of Astragali Radix, Puerariae Lobatae Radix and Citri Reticulatae Chachiensis Pericarpium was prepared with the same technological parameters. The chemical components of the two were detected and identified based on UPLC-Q-TOF/MS, and the different components were determined by principal component analysis. Eighty-eight compounds were identified in the pharmaceutical solution of Qi-Ge decoction. Principal component analysis revealed 11 different components of QGHBY and QGHJY with the conditions of Variable Importance in Projection (VIP) ≥ 1, fold change ≥ 2 and p < 0.05, among which hesperidin, hesperitin, isosinensetin, sinensetin and 5-demethylnobiletin were the components of Citri Reticulatae Chachiensis Pericarpium. The levels of these 11 different components in QGHJY were higher than those of QGHBY. The combined decoction is beneficial for the dissolution of flavonoids and other chemical components, and there is a significant difference in the content of chemical components between modern herbal concentrate granules and traditional decoctions.

Development of a prediction model for emergency medical service witnessed traumatic out-of-hospital cardiac arrest: A multicenter cohort study.

BACKGROUND/PURPOSE: To develop a prediction model for emergency medical technicians (EMTs) to identify trauma patients at high risk of deterioration to emergency medical service (EMS)-witnessed traumatic cardiac arrest (TCA) on the scene or en route. METHODS: We developed a prediction model using the classical cross-validation method from the Pan-Asia Trauma Outcomes Study (PATOS) database from 1 January 2015 to 31 December 2020. Eligible patients aged ≥18 years were transported to the hospital by the EMS. The primary outcome (EMS-witnessed TCA) was defined based on changes in vital signs measured on the scene or en route. We included variables that were immediately measurable as potential predictors when EMTs arrived. An integer point value system was built using multivariable logistic regression. The area under the receiver operating characteristic (AUROC) curve and Hosmer-Lemeshow (HL) test were used to examine discrimination and calibration in the derivation and validation cohorts. RESULTS: In total, 74,844 patients were eligible for database review. The model comprised five prehospital predictors: age <40 years, systolic blood pressure <100 mmHg, respiration rate >20/minute, pulse oximetry <94%, and levels of consciousness to pain or unresponsiveness. The AUROC in the derivation and validation cohorts was 0.767 and 0.782, respectively. The HL test revealed good calibration of the model (p = 0.906). CONCLUSION: We established a prediction model using variables from the PATOS database and measured them immediately after EMS personnel arrived to predict EMS-witnessed TCA. The model allows prehospital medical personnel to focus on high-risk patients and promptly administer optimal treatment.