Dissecting the high-resolution genetic architecture of complex phenotypes by accurately estimating gene-based conditional heritability.

Despite extensive research on global heritability estimation for complex traits, few methods accurately dissect local heritability. A precise local heritability estimate is crucial for high-resolution mapping in genetics. Here, we report the effective heritability estimator (EHE) that can use p values from genome-wide association studies (GWASs) for local heritability estimation by directly converting marginal heritability estimates of SNPs to a non-redundant heritability estimate of a gene or a small genomic region. EHE provides higher accuracy and precision for local heritability estimation among seven compared methods. Importantly, EHE can be applied to estimate the conditional heritability of nearby genes, where redundant heritability among the genes can also be removed further. The conditional estimation can be guided by tissue-specific expression profiles (or other functional scores) to prioritize and quantify more functionally important genes of complex phenotypes. Applying EHE to 42 complex phenotypes from the UK Biobank, we revealed the existence of two types of distinct genetic architectures for various complex phenotypes and found that highly pleiotropic genes are not enriched for more heritability compared to other candidate susceptibility genes. EHE provides an accurate and robust way to dissect the genetic architecture of complex phenotypes.

Deciphering the role of Enterococcus faecium cytidine deaminase in gemcitabine resistance of gallbladder cancer.

Gemcitabine-based chemotherapy is a cornerstone of standard care for gallbladder cancer (GBC) treatment. Still, drug resistance remains a significant challenge, influenced by factors such as tumor-associated microbiota impacting drug concentrations within tumors. Enterococcus faecium, a member of tumor-associated microbiota, was notably enriched in the GBC patient cluster. In this study, we investigated the biochemical characteristics, catalytic activity, and kinetics of the cytidine deaminase of E. faecium (EfCDA). EfCDA showed the ability to convert gemcitabine to its metabolite 2',2'-difluorodeoxyuridine. Both EfCDA and E. faecium can induce gemcitabine resistance in GBC cells. Moreover, we determined the crystal structure of EfCDA, in its apo form and in complex with 2', 2'-difluorodeoxyuridine at high resolution. Mutation of key residues abolished the catalytic activity of EfCDA and reduced the gemcitabine resistance in GBC cells. Our findings provide structural insights into the molecular basis for recognizing gemcitabine metabolite by a bacteria CDA protein and may provide potential strategies to combat cancer drug resistance and improve the efficacy of gemcitabine-based chemotherapy in GBC treatment.

Powerful and robust inference of complex phenotypes' causal genes with dependent expression quantitative loci by a median-based Mendelian randomization.

Isolating the causal genes from numerous genetic association signals in genome-wide association studies (GWASs) of complex phenotypes remains an open and challenging question. In the present study, we proposed a statistical approach, the effective-median-based Mendelian randomization (MR) framework, for inferring the causal genes of complex phenotypes with the GWAS summary statistics (named EMIC). The effective-median method solved the high false-positive issue in the existing MR methods due to either correlation among instrumental variables or noises in approximated linkage disequilibrium (LD). EMIC can further perform a pleiotropy fine-mapping analysis to remove possible false-positive estimates. With the usage of multiple cis-expression quantitative trait loci (eQTLs), EMIC was also more powerful than the alternative methods for the causal gene inference in the simulated datasets. Furthermore, EMIC rediscovered many known causal genes of complex phenotypes (schizophrenia, bipolar disorder, and total cholesterol) and reported many new and promising candidate causal genes. In sum, this study provided an efficient solution to discriminate the candidate causal genes from vast amounts of GWAS signals with eQTLs. EMIC has been implemented in our integrative software platform KGGSEE.

Running exercise alleviates hippocampal neuroinflammation and shifts the balance of microglial M1/M2 polarization through adiponectin/AdipoR1 pathway activation in mice exposed to chronic unpredictable stress.

Running exercise has been shown to alleviate depressive symptoms. However, the mechanism underlying the antidepressant effects of running exercise is not fully understood. The imbalance of M1/M2 microglia phenotype/polarization and concomitant dysregulation of neuroinflammation play crucial roles in the pathogenesis of depression. Running exercise increases circulating levels of adiponectin which is known to cross the blood‒brain barrier and suppress inflammatory responses. AdipoR1 is an adiponectin receptor that is involved in regulating microglial phenotypes and activation states. However, whether running exercise regulates hippocampal microglial phenotypes and neuroinflammation through adiponectin/AdipoR1 to exert its antidepressant effects remains unclear. In the current study, 4 weeks of running exercise significantly alleviated the depressive-like behaviors of chronic unpredictable stress (CUS)-exposed mice. Moreover, running exercise decreased the microglial numbers and altered microglial morphology in three subregions of the hippocampus to restore the M1/M2 balance; these effects were accompanied by regulation of pro-/anti-inflammatory cytokine production and secretion in CUS-exposed mice. These effects may involve elevation of peripheral tissue (adipose tissue and muscle) and plasma adiponectin levels, and hippocampal AdipoR1 levels as well as activation of the AMPK-NF-κB/STAT3 signaling pathway by running exercise. When an adeno-associated virus was used to knock down hippocampal AdipoR1, mice showed depressive-like behaviors and alterations in microglia and inflammatory factor expression in the hippocampus that were similar to those observed in CUS-exposed mice. Together, these results suggest that running exercise maintains the M1/M2 balance and inhibits neuroinflammation in the hippocampus of CUS-exposed mice. These effects might occur via adiponectin/AdipoR1-mediated activation of the AMPK-NF-κB/STAT3 signaling pathway.

Feedback-related brain activity in individual decision: evidence from a gambling EEG study.

In this study, based on scalp electroencephalogram (EEG), we conducted cortical source localization and functional network analyses to investigate the underlying mechanism explaining the decision processes when individuals anticipate maximizing gambling benefits, particularly in situations where the decision outcomes are inconsistent with the profit goals. The findings shed light on the feedback monitoring process, wherein incongruity between outcomes and gambling goals triggers a more pronounced medial frontal negativity and activates the frontal lobe. Moreover, long-range theta connectivity is implicated in processing surprise and uncertainty caused by inconsistent feedback conditions, while middle-range delta coupling reflects a more intricate evaluation of feedback outcomes, which subsequently modifies individual decision-making for optimizing future rewards. Collectively, these findings deepen our comprehension of decision-making under circumstances where the profit goals are compromised by decision outcomes and provide electrophysiological evidence supporting adaptive adjustments in individual decision strategies to achieve maximum benefit.

Evaluating the depression state during perinatal period by non-invasive scalp EEG.

Perinatal depression, with a prevalence of 10 to 20% in United States, is usually missed as multiple symptoms of perinatal depression are common in pregnant women. Worse, the diagnosis of perinatal depression still largely relies on questionnaires, leaving the objective biomarker being unveiled yet. This study suggested a safe and non-invasive technique to diagnose perinatal depression and further explore its underlying mechanism. Considering the non-invasiveness and clinical convenience of electroencephalogram for mothers-to-be and fetuses, we collected the resting-state electroencephalogram of pregnant women at the 38th week of gestation. Subsequently, the difference in network topology between perinatal depression patients and healthy mothers-to-be was explored, with related spatial patterns being adopted to achieve the classification of pregnant women with perinatal depression from those healthy ones. We found that the perinatal depression patients had decreased brain network connectivity, which indexed impaired efficiency of information processing. By adopting the spatial patterns, the perinatal depression could be accurately recognized with an accuracy of 87.88%; meanwhile, the depression severity at the individual level was effectively predicted, as well. These findings consistently illustrated that the resting-state electroencephalogram network could be a reliable tool for investigating the depression state across pregnant women, and will further facilitate the clinical diagnosis of perinatal depression.

Integrative ATAC-seq and RNA-seq analysis of myogenic differentiation of ovine skeletal muscle satellite cell.

Skeletal muscle satellite cells (SMSCs) play an important role in regulating muscle growth and regeneration. Chromatin accessibility allows physical interactions that synergistically regulate gene expression through enhancers, promoters, insulators, and chromatin binding factors. However, the chromatin accessibility altas and its regulatory role in ovine myoblast differentiation is still unclear. Therefore, ATAC-seq and RNA-seq analysis were performed on ovine SMSCs at the proliferation stage (SCG) and differentiation stage (SCD). 17,460 DARs (differential accessibility regions) and 3732 DEGs (differentially expressed genes) were identified. Based on joint analysis of ATAC-seq and RNA-seq, we revealed that PI3K-Akt, TGF-ß and other signaling pathways regulated SMSCs differentiation. We identified two novel candidate genes, FZD5 and MAP2K6, which may affect the proliferation and differentiation of SMSCs. Our data identify potential cis regulatory elements of ovine SMSCs. This study can provide a reference for exploring the mechanisms of the differentiation and regeneration of SMSCs in the future.

Cryo-EM structure of amyloid fibril formed by α-synuclein hereditary A53E mutation reveals a distinct protofilament interface.

Synucleinopathies like Parkinson's disease (PD), dementia with Lewy bodies (DLB), and multiple systems atrophy (MSA), have the same pathologic feature of misfolded α-synuclein protein (α-syn) accumulation in the brain. PD patients who carry α-syn hereditary mutations tend to have earlier onset and more severe clinical symptoms than sporadic PD patients. Therefore, revealing the effect of hereditary mutations to the α-syn fibril structure can help us understand these synucleinopathies' structural basis. Here, we present a 3.38 Å cryo-electron microscopy structure of α-synuclein fibrils containing the hereditary A53E mutation. The A53E fibril is symmetrically composed of two protofilaments, similar to other fibril structures of WT and mutant α-synuclein. The new structure is distinct from all other synuclein fibrils, not only at the interface between proto-filaments, but also between residues packed within the same proto-filament. A53E has the smallest interface with the least buried surface area among all α-syn fibrils, consisting of only two contacting residues. Within the same protofilament, A53E reveals distinct residue re-arrangement and structural variation at a cavity near its fibril core. Moreover, the A53E fibrils exhibit slower fibril formation and lower stability compared to WT and other mutants like A53T and H50Q, while also demonstrate strong cellular seeding in α-synuclein biosensor cells and primary neurons. In summary, our study aims to highlight structural differences - both within and between the protofilaments of A53E fibrils - and interpret fibril formation and cellular seeding of α-synuclein pathology in disease, which could further our understanding of the structure-activity relationship of α-synuclein mutants.

Near Infrared-II Excited Triplet Fusion Upconversion with Anti-Stokes Shift Approaching the Theoretical Limit.

The anti-Stokes shift represents the capacity of photon upconversion to convert low-energy photons to high-energy photons. Although triplet exciton-mediated photon upconversion presents outstanding performance in solar energy harvesting, photoredox catalysis, stereoscopic 3D printing, and disease therapeutics, the interfacial multistep triplet exciton transfer leads to exciton energy loss to suppress the anti-Stokes shift. Here, we report near infrared-II (NIR-II) excitable triplet exciton-mediated photon upconversion using a hybrid photosensitizer consisting of lead sulfide quantum dots (PbS QDs) and new surface ligands of thiophene-substituted diketopyrrolopyrrole (Th-DPP). Under 1064 nm excitation, this photon upconversion revealed a record-corrected upconversion efficiency of 0.37% (normalized to 100%), with the anti-Stokes shift (1.07 eV) approaching the theoretical limit (1.17 eV). The observation of this unexpected result is due to our discovery of the presence of a weak interaction between the sulfur atom on Th-DPP and Pb2+ on the PbS QDs surface, facilitating electronic coupling between PbS QDs and Th-DPP, such that the realization of triplet exciton transfer efficiency is close to 100% even when the energy gap is as small as 0.04 eV. With this premise, this photon upconversion as a photocatalyst enables the production of standing organic gel via photopolymerization under 1064 nm illumination, displaying NIR-II photon-driven photoredox catalysis. This research not only establishes the foundation for enhancing the performance of NIR-II excitable photonic upconversion but also promotes its development in photonics and photoredox catalysis.

Incidence trends of primary liver cancer in different geographical regions of China from 1978 to 2012 and projections to 2032: An age-period-cohort analysis.

China accounted for 45.3% of new cases of primary liver cancer (PLC) worldwide in 2020. While variations in PLC incidence between different regions of China and decreasing incidence in overall China have been reported, incidence patterns have not been thoroughly explored by region. We examined the nearly status and temporal trends of PLC incidence in different geographical regions in China and project future trends. The age-standardized incidence rate (ASR) was estimated for 1978 to 2012 by different geographical regions and gender in China. Age-period-cohort model was adopted to evaluate age and birth cohort effects on the temporal trend of five registries of China (Hong Kong, Shanghai, Jiashan, Harbin and Zhongshan), Bayesian age-period-cohort model was adopted to project future trends for 2013 to 2032. PLC incidence in China exhibits marked geographical disparity, with the highest incidence in Southwest China, and gender differences being particularly pronounced in South China. While other registries exhibited decreasing trend, Zhongshan exhibited an increasing trend, with the cohort effect showing a marked upward trend for females born in 1916 to 1949 and males born in 1916 to 1962. During 2013 to 2032, the ASR appears to increase by 86.9% for men and 40.0% for women in Zhongshan, while the remaining registries will decline by around 50%. Since the high incidence of hepatitis B virus infection in early birth cohort, recent rise of nonviral risk factors and the severe aging of the Chinese population, it may be critical to tailor future prevention and control strategies for PLC to the distribution of risk factors in different geographical regions.

Inertial Multi-Force Deformability Cytometry for High-Throughput, High-Accuracy, and High-Applicability Tumor Cell Mechanotyping.

Previous on-chip technologies for characterizing the cellular mechanical properties often suffer from a low throughput and limited sensitivity. Herein, an inertial multi-force deformability cytometry (IMFDC) is developed for high-throughput, high-accuracy, and high-applicability tumor cell mechanotyping. Three different deformations, including shear deformations and stretch deformations under different forces, are integrated with the IMFDC. The 3D inertial focusing of cells enables the cells to deform by an identical fluid flow, and 10 parameters, such as cell area, perimeter, deformability, roundness, and rectangle deformability, are obtained in three deformations. The IMFDC is able to evaluate the deformability of different cells that are sensitive to different forces on a single chip, demonstrating the high applicability of the IMFDC in analyzing different cell lines. In identifying cell types, the three deformations exhibit different mechanical responses to cells with different sizes and deformability. A discrimination accuracy of ≈93% for both MDA-MB-231 and MCF-10A cells and a throughput of ≈500 cells s-1 can be achieved using the multiple-parameters-based machine learning model. Finally, the mechanical properties of metastatic tumor cells in pleural and peritoneal effusions are characterized, enabling the practical application of the IMFDC in clinical cancer diagnosis.

Broadband Room-Temperature Photodetection via InBiTe3 Nanosheet.

Broadband room-temperature photodetection has become a pressing need as application requirements for communication, imaging, spectroscopy, and sensing have evolved. Topological insulators (TIs) have narrow bandgap structures with a wide absorption spectral response range, which should meet the requirements of broadband detection. However, owing to their high carrier concentration and low carrier mobility resulting in poor noise equivalent power (NEP), they are generally considered unsuitable for photodetection. Here, InBiTe3 alloy nanosheet formed by doping In2Te3 into Bi2Te3(≈ 1:1) is utilized, effectively improving carrier mobility by over ten times while maintaining a narrow bandgap structure, to fabricate a broadband photodetector covering a wide response range from visible to millimeter wave (MMW). Under the synergistic multi-mechanism of the photoelectric effect in the visible-infrared region and the electromagnetic-induced potential well (EIW) effect in Terahertz band, the performance of NEP = 75 pW Hz-1/2 and response time τ ≈100 µs in visible to infrared band and the performance of NEP = 6.7 × 10-3 pW Hz-1/2, τ ≈8 µs in Terahertz region are achieved. The results demonstrate the promising prospects of topological insulator alloy (like InBiTe3) nanosheet in optoelectronic detection applications and provide a direction for the research into high-performance broadband photoelectric detectors via TIs.

Plant litter loss exacerbates drought influences on grasslands.

Plant litter is known to affect soil, community, and ecosystem properties. However, we know little about the capacity of litter to modulate grassland responses to climate change. Using a 7-yr litter removal experiment in a semiarid grassland, here we examined how litter removal interacts with a 2-yr drought to affect soil environments, plant community composition, and ecosystem function. Litter loss exacerbates the negative impacts of drought on grasslands. Litter removal increased soil temperature but reduced soil moisture and nitrogen mineralization, which substantially increased the negative impacts of drought on primary productivity and the abundance of perennial rhizomatous graminoids. Moreover, complete litter removal shifted plant community composition from grass-dominated to forb-dominated and reduced species and functional group asynchrony, resulting in lower ecosystem temporal stability. Our results suggest that ecological processes that lead to reduction in litter, such as burning, grazing, and haying, may render ecosystems more vulnerable and impair the capacity of grasslands to withstand drought events.

Phylogenomics and biogeographical diversification of Collabieae (Orchidaceae) and its implication in the reconstruction of the dynamic history of Asian evergreen broadleaved forests.

The tribe Collabieae (Epidendroideae, Orchidaceae) comprises approximately 500 species. Generic delimitation within Collabieae are confusing and phylogenetic interrelationships within the Collabieae have not been well resolved. Plastid genomes and nuclear internal transcribed spacer (ITS) sequences were used to estimate the phylogenetic relationships, ancestral ranges, and diversification rates of Collabieae. The results showed that Collabieae was subdivided into nine clades with high support. We proposed to combine Ancistrochilus and Pachystoma into Spathoglottis, merge Collabium and Chrysoglossum into Diglyphosa, and separate Pilophyllum and Hancockia as distinctive genera. The diversification of the nine clades of Collabieae might be associated with the uplift of the Himalayas during the Late Oligocene/Early Miocene. The enhanced East Asian summer monsoon in the Late Miocene may have promoted the rapid diversification of Collabieae at a sustained high diversification rate. The increased size of terrestrial pseudobulbs may be one of the drivers of Collabieae diversification. Our results suggest that the establishment and development of evergreen broadleaved forests facilitated the diversification of Collabieae.

Total net-rate of 27.88 Tb/s full C-band transmission over 4,550†km using 150†km span length and high-gain EDFA amplification.

We experimentally demonstrate a total net-rate of 27.88 Tb/s for C-band wavelength-division multiplexing (WDM) transmission over an ultralong span-length of 150 km. It is the largest net capacity × span-length product of 4182 Tb/s·km for C-band, single-core, standard single-mode optical fiber transmission over a length of more than 3,000 km. A total of 99 channels, spaced at 50 GHz intervals, are employed for transmitting 32 GBaud probabilistically constellation-shaped (PCS) 64QAM signals with an information entropy of 5.5. High gain amplifiers can achieve wavelength-division multiplexing (WDM) transmission with a bandwidth of 6.25 THz, at a noise figure below 4.3 dB, without the assistance of distributed Raman amplification.

Multi-channel broadband optical chaos generation assisted by phase modulation and CFBG feedback.

In this paper, we propose a novel and simple multi-channel broadband optical chaos generation scheme based on phase modulation and chirped fiber Bragg grating (CFBG). Firstly, phase modulation is introduced to generate more new frequency components to broaden the spectrum of the phase chaos. Meanwhile, the accumulated dispersion from CFBG distorts the intensity chaos, converts phase chaos to intensity chaos, and weakens the laser relaxation oscillation. This process would lead to energy redistribution in the power spectrum, effectively increasing the chaotic bandwidth. Then, the wavelength detuning between CFBG and the semiconductor laser is introduced to enhance the chaotic bandwidth further. The experiment results show that the 10 dB bandwidths of the five channels are up to 31.0 GHz, 34.3 GHz, 36.3 GHz, 40 GHz, and 40 GHz, respectively. Note that the maximum bandwidth of the PD in our experiment is limited to 40 GHz. In addition, the multi-channel chaotic signals obtained from the experiment system are used to generate multi-channel physical random numbers. After the post-processing operations, the total rate of five parallel high-speed physical random number generation channels is 4.64 Tbit/s (160 GSa/s × 5bit × 1 channel + 160 GSa/s × 6bit × 4 channels). As far as we know, this is the highest record of using external cavity feedback semiconductor lasers to generate random numbers, which has great potential to meet the security requirements of next-generation Tbit/s optical communication systems.

Fast fiber nonlinearity compensation method for PDM coherent optical transmission systems based on the Fourier neural operator.

Fiber nonlinearity compensation (NLC) is likely to become an indispensable component of coherent optical transmission systems for extending the transmission reach and increasing capacity per fiber. In this work, we introduce what we believe to be a novel fast black-box neural network model based on the Fourier neural operator (FNO) to compensate for the chromatic dispersion (CD) and nonlinearity simultaneously. The feasibility of the proposed approach is demonstrated in uniformly distributed as well as probabilistically-shaped 32GBaud 16/32/64-ary quadrature amplitude modulation (16/32/64QAM) polarization-division-multiplexed (PDM) coherent optical communication systems. The experimental results demonstrate that about 0.31 dB Q-factor improvement is achieved compared to traditional digital back-propagation (DBP) with 5 steps per span for PDM-16QAM signals after 1600 km standard single-mode fiber (SSMF) transmission at the optimal launched power of 4 dBm. While, the time consumption is reduced from 6.04 seconds to 1.69 seconds using a central processing unit (CPU), and from 1.54 seconds to only 0.03 seconds using a graphic processing unit (GPU), respectively. This scheme also reveals noticeable generalization ability in terms of launched power and modulation format.

High-reliability infrared broadband thin-film polarizing beam splitter with ZnSe compensation layers.

Thin-film polarizing beam splitters (PBSs) fulfill a pivotal role in laser beam splitting, modulation, shaping and isolation. In this study, a high-reliability infrared broadband thin-film PBS was developed. To correct for tensile stress in Ge/YbF3 multilayer coatings, ZnSe compensation layers were incorporated in the multilayer design. The effects of different symmetrical periods on the spectral properties of the infrared PBS were systematically discussed. The infrared PBS operated at 45° and in the long-wave infrared (LWIR) band. Using the percent of optical extrema monitoring (POEM) strategy combined with the high-temperature optical constants (HTOC) of Ge film, the infrared PBS was precisely fabricated on ZnSe substrates. Subsequently, the spectral performance and film reliability of the infrared PBS were carefully characterized. Specifically, the transmittance of p-polarization surpassed 96%, while the extinction ratio exceeded 100:1 within the 10.6 ± 0.15 µm band. The infrared PBS demonstrated commendable environmental reliability, in addition to exhibiting excellent spectral characteristics.

End-to-end learning strategy based on a frequency domain feature decoupling network emulator with joint probabilistic shaping and equalization for a 300-Gbit/s OAM mode division multiplexing transmission.

Mode coupling and device nonlinear impairment appear to be a long-standing challenge in the orbital angular momentum (OAM) mode division multiplexing (MDM) of intensity modulation direct detection (IM/DD) transmission systems. In this paper, we propose an end-to-end (E2E) learning strategy based on a frequency domain feature decoupling network (FDFDnet) emulator with joint probabilistic shaping (PS) and equalization for an OAM-MDM IM/DD transmission with three modes. Our FDFDnet emulator can accurately build a complex nonlinear model of an OAM-MDM system by separating the signal into features from different frequency domains. Furthermore, a FDFDnet-based E2E strategy for joint PS and equalization is presented with the aim of compensating the signal impairment for the OAM-MDM IM/DD system. An experiment is carried out on a 300 Gbit/s carrierless amplitude phase-32 (CAP-32) signal with three OAM modes over a 10 km ring-core fiber transmission, and the results show that the proposed FDFDnet emulator outperforms the traditional CGAN emulator, with improvements in the modelling accuracy of 30.8%, 26.3% and 31% for the three OAM modes. Moreover, the receiver sensitivity of the proposed E2E learning strategy is higher than for the CGAN emulator by 3, 2.5, 2.2 dBm and the real channel by 5.5, 5.1, and 5.3 dBm for the three OAM modes, respectively. Our experimental results demonstrate that the proposed FDFDnet emulator-based E2E learning strategy is a promising contender for achieving ultra-high-capacity interconnectivity between data centers.

Effects of the stress hyperglycemia ratio on long-term mortality in patients with triple-vessel disease and acute coronary syndrome.

AIMS: Risk assessment for triple-vessel disease (TVD) remain challenging. Stress hyperglycemia represents the regulation of glucose metabolism in response to stress, and stress hyperglycemia ratio (SHR) is recently found to reflect true acute hyperglycemic status. This study aimed to evaluate the prognostic value of SHR and its role in risk stratification in TVD patients with acute coronary syndrome (ACS). METHODS: A total of 3812 TVD patients with ACS with available baseline SHR measurement were enrolled from two independent centers. The endpoint was cardiovascular mortality. Cox regression was used to evaluate the association between SHR and cardiovascular mortality. The SYNTAX (Synergy Between Percutaneous Coronary Intervention With Taxus and Cardiac Surgery) II (SSII) was used as the reference model in the model improvement analysis. RESULTS: During a median follow-up of 5.1 years, 219 (5.8%) TVD patients with ACS suffered cardiovascular mortality. TVD patients with ACS with high SHR had an increased risk of cardiovascular mortality after robust adjustment for confounding (high vs. median SHR: adjusted hazard ratio 1.809, 95% confidence interval 1.160-2.822, P = 0.009), which was fitted as a J-shaped pattern. The prognostic value of the SHR was found exclusively among patients with diabetes instead of those without diabetes. Moreover, addition of SHR improved the reclassification abilities of the SSII model for predicting cardiovascular mortality in TVD patients with ACS. CONCLUSIONS: The high level of SHR is associated with the long-term risk of cardiovascular mortality in TVD patients with ACS, and is confirmed to have incremental prediction value beyond standard SSII. Assessment of SHR may help to improve the risk stratification strategy in TVD patients who are under acute stress.