An individual-level weighted artificial neural network method to improve the systematic bias in BrainAGE analysis.

BrainAGE is a commonly used machine learning technique to measure the accelerated/delayed development pattern of human brain structure/function with neuropsychiatric disorders. However, recent studies have shown a systematic bias ("regression toward mean" effect) in the BrainAGE method, which indicates that the prediction error is not uniformly distributed across Chronological Ages: for the older individuals, the Brain Ages would be under-estimated but would be over-estimated for the younger individuals. In the present study, we propose an individual-level weighted artificial neural network method and apply it to simulation datasets (containing 5000 simulated subjects) and a real dataset (containing 135 subjects). Results show that compared with traditional machine learning methods, the individual-level weighted strategy can significantly reduce the "regression toward mean" effect, while the prediction performance can achieve the comparable level with traditional machine learning methods. Further analysis indicates that the sigmoid active function for artificial neural network shows better performance than the relu active function. The present study provides a novel strategy to reduce the "regression toward mean" effect of BrainAGE analysis, which is helpful to improve accuracy in exploring the atypical brain structure/function development pattern of neuropsychiatric disorders.

Emissions of fine particulate nitrated phenols from various on-road vehicles in China.

Nitrated phenols are receiving increasing attention due to their adverse impacts on the environment and human health. Previous measurements have revealed the non-ignorable contribution of vehicle exhaust to atmospheric nitrated phenols in urban areas. However, there is a lack of comprehensive understanding of the emission characteristics and the total emission of nitrated phenols from current on-road traffic. This study investigated the emissions from eight passenger vehicles, eight trucks, and two taxis, with fuel types including diesel, gasoline, and compressed natural gas. Exhaust emissions were collected and measured using a mobile measurement system on two testing routes. Twelve nitrated phenols in the collected fine particulate matter were detected using ultrahigh performance liquid chromatography-mass spectrometry. Overall, the emission profiles of fine particulate nitrated phenols varied with vehicle load and fuel type. The 4-nitrophenol and its methyl derivatives were dominant nitrated phenol species emitted by the vehicles with proportions of 38.4%-68.0%, which is significantly different from the proportions of nitrated phenols emitted from biomass burning and coal combustion. The emission factors also exhibited large variations across vehicle type, fuel type, and emission standards, with relatively low values for gasoline vehicles and taxis fueled by compressed natural gas and high values for diesel vehicles. Based on the emission factors of nitrated phenols from different vehicles, the estimated total emission of nitrated phenols from on-road vehicles in China was 58.9 Mg (-86%-85% within 95% confidence interval), with diesel trucks contributing the most substantial fractions. This work highlights the very high level of emissions of nitrated phenols from diesel vehicles and provides an essential basis for atmospheric modeling and effective pollution control.

Altered pharmacodynamics and pharmacokinetics of cisatracurium in patients with severe mitral valve regurgitation during anaesthetic induction period.

AIM: The aim of the current study was to characterize the pharmacokinetics (PK) and pharmacodynamics (PD) of cisatracurium in patients with severe mitral valve regurgitation (MR) during the anaesthetic induction period. METHODS: Thirty patients in the clinical trial were divided into two groups: the MR group (n = 15) and the control group (n = 15). Arterial blood samples were obtained before (time 0) and at 1, 2, 4, 6, 8, 10, 15 and 20 min after intravenous injection of 0.15 mg kg-1 cisatracurium. The degree of neuromuscular block was measured by train of four (TOF) testing. The concentration of cisatracurium in the plasma was determined by high-performance liquid chromatography. A conventional two-compartment model and integrated PK/PD model were applied to PK and PD data analysis, respectively. RESULTS: The results of PK model fitting demonstrated that severe MR reduced the distribution rate of cisatracurium from the central to peripheral compartment, resulting in a higher concentration of the drug in the plasma. The time to the maximal neuromuscular blocking effect of cisatracurium was delayed in the MR group (2.08 min in the control group vs. 4.12 min in the MR group). The PK/PD model indicated that the distribution rate of cisatracurium from the blood to the effect compartment was decreased in the MR group. CONCLUSIONS: The present study suggested that the PK and PD of cisatracurium were significantly altered in patients with severe MR. The study has the potential to improve the safety of anaesthetic induction in patients with severe MR through accurate prediction of the PD responses of cisatracurium using the established PK/PD model.

Altered Cisatracurium Pharmacokinetics and Pharmacodynamics in Patients with Congenital Heart Defects.

The neuromuscular blocking agent cisatracurium is frequently used adjunctively in anesthesia to facilitate endotracheal intubation and to provide muscle relaxation during surgery. We aimed to determine the pharmacokinetics (PK)/pharmacodynamics (PD) of cisatracurium in patients with congenital heart defects (CHDs), such as ventricular septal defects and atrial septal defects, and to assess the effects of CHDs on the PK/PD profiles of cisatracurium. A modified two-compartment model with drug clearance from both compartments was best fitted to the PK data to determine the PK parameters. The model suggested that septal defects significantly lowered the rate of cisatracurium distribution from the central to peripheral compartment. The intercompartment rate constants k12 and k21 were significantly reduced (35%-60%, P < 0.05) in patients with ventricular septal defects and in patients with atrial septal defects compared with control patients. Consistently, septal defects caused a marked increase (160%-175%, P < 0.001) in the distribution half-life. Furthermore, significantly delayed pharmacodynamic responses to cisatracurium were observed in patients with septal defects. The onset time (i.e., the time to maximal neuromuscular block) was prolonged from 2.2 minutes to 5.0 minutes. PK/PD modeling suggested that reduced concentrations of cisatracurium in the effect compartment due to poorer distribution were the main cause of lagged pharmacodynamic responses. In conclusion, cisatracurium PK/PD were significantly altered in patients with septal defects. Our study should be of use in clinical practice for the administration of cisatracurium to patients with CHDs.

Norwegian scabies presenting as erythroderma: A case report.

BACKGROUND: Norwegian scabies (NS) is a serious parasitic skin condition. Although NS is one of the causes of erythroderma, it is frequently overlooked. Therefore, it is essential to raise awareness regarding NS presenting as erythroderma. CASE SUMMARY: We present a case of NS that persisted for more than 3 years. After following nonstandard treatment, the patient's rash worsened and gradually progressed into erythroderma. Finally, NS was diagnosed by skin microscopy and pathology. CONCLUSION: When patients with pruritic dermatosis have high-risk factors such as prolonged bed rest and immunodeficiency, clinicians need to enhance their awareness of NS and ensure prompt diagnosis and treatment.

Current Development of Data Resources and Bioinformatics Tools for Anticoronavirus Peptide.

BACKGROUND: Since December 2019, the emergence of severe acute respiratory syndrome coronavirus 2, which gave rise to coronavirus disease 2019 (COVID-19), has considerably impacted global health. The identification of effective anticoronavirus peptides (ACVPs) and the establishment of robust data storage methods are critical in the fight against COVID-19. Traditional wet-lab peptide discovery approaches are timeconsuming and labor-intensive. With advancements in computer technology and bioinformatics, machine learning has gained prominence in the extraction of functional peptides from extensive datasets. METHODS: In this study, we comprehensively review data resources and predictors related to ACVPs published over the past two decades. In addition, we analyze the influence of various factors on model performance. RESULTS: We have reviewed nine ACVP-containing databases, which integrate detailed information on protein fragments effective against coronaviruses, providing crucial references for the development of antiviral drugs and vaccines. Additionally, we have assessed 15 peptide predictors for antiviral or specifically anticoronavirus activity. These predictors employ computational models to swiftly screen potential antiviral candidates, offering an efficient pathway for drug development. CONCLUSION: Our study provides conclusive results and insights into the performance of different computational methods, and sheds light on the future trajectory of bioinformatics tools for ACVPs. This work offers a representative overview of contributions to the field, with an emphasis on the crucial role of ACVPs in combating COVID-19.

Viral metagenomic analysis reveals diverse viruses and a novel bocaparvovirus in the enteric virome of snow leopard (Panthera uncia).

The enteric virome, comprising a complex community of viruses inhabiting the gastrointestinal tract, plays a significant role in health and disease dynamics. In this study, the fecal sample of a wild snow leopard was subjected to viral metagenomic analysis using a double barcode Illumina MiSeq platform. The resulting reads were de novo assembled into contigs with SOAPdenovo2 version r240. Additional bioinformatic analysis of the assembled genome and genome annotation was done using the Geneious prime software (version 2022.0.2). Following viral metagenomic analysis and bioinformatic analysis, a total of 7 viral families and a novel specie of bocaparvovirus tentatively named Panthera uncia bocaparvovirus (PuBOV) with GenBank accession number OQ627713 were identified. The complete genome of PuBOV was predicted to contain 3 open reading frames (ORFs), contains 5433 nucleotides and has a G + C content of 47.40 %. BLASTx analysis and pairwise sequence comparison indicated the novel virus genome was a new species in the genus Bocaparvovirus based on the species demarcation criteria of the International Committee on the Taxonomy of Viruses. This study provides valuable insights into the diversity and composition of the enteric virome in wild endangered snow leopards. The identification and characterization of viruses in wildlife is crucial for developing effective strategies to manage and mitigate potential zoonotic and other viral disease threats to human and animal health.

MicroRNA-101 inhibited postinfarct cardiac fibrosis and improved left ventricular compliance via the FBJ osteosarcoma oncogene/transforming growth factor-ß1 pathway.

BACKGROUND: Cardiac interstitial fibrosis is a major cause of the deteriorated performance of the heart in patients with chronic myocardial infarction. MicroRNAs (miRs) have recently been proven to be a novel class of regulators of cardiovascular diseases, including those associated with cardiac fibrosis. This study aimed to explore the role of miR-101 in cardiac fibrosis and the underlying mechanisms. METHODS AND RESULTS: Four weeks after coronary artery ligation of rats, the expression of miR-101a and miR-101b (miR-101a/b) in the peri-infarct area was decreased. Treatment of cultured rat neonatal cardiac fibroblasts with angiotensin II also suppressed the expression of miR-101a/b. Forced expression of miR-101a/b suppressed the proliferation and collagen production in rat neonatal cardiac fibroblasts, as revealed by cell counting, MTT assay, and quantitative reverse transcription-polymerase chain reaction. The effect was abrogated by cotransfection with AMO-101a/b, the antisense inhibitors of miR-101a/b. c-Fos was found to be a target of miR-101a because overexpression of miR-101a decreased the protein and mRNA levels of c-Fos and its downstream protein transforming growth factor-ß1. Silencing c-Fos by siRNA mimicked the antifibrotic action of miR-101a, whereas forced expression of c-Fos protein canceled the effect of miR-101a in cultured cardiac fibroblasts. Strikingly, echocardiography and hemodynamic measurements indicated remarkable improvement of the cardiac performance 4 weeks after adenovirus-mediated overexpression of miR-101a in rats with chronic myocardial infarction. Furthermore, the interstitial fibrosis was alleviated and the expression of c-Fos and transforming growth factor-ß1 was inhibited. CONCLUSION: Overexpression of miR-101a can mitigate interstitial fibrosis and the deterioration of cardiac performance in postinfarct rats, indicating the therapeutic potential of miR-101a for cardiac disease associated with fibrosis.

Viral metagenomics of the gut virome of diarrheal children with Rotavirus A infection.

Diarrhea is a leading cause of morbidity and mortality in children worldwide and represents a major dysbiosis event. Rotavirus has been recognized as a global leading pathogen of diarrhea. This study is aimed at investigating differences in the gut virome between diarrheal children and healthy controls. In 2018, 76 diarrheal fecal samples and 27 healthy fecal samples in Shanghai and 40 diarrheal fecal samples and 19 healthy fecal samples in Taizhou were collected to investigate the composition of the gut virome. Viral metagenomic analyses revealed that the alpha diversity of the diarrheal virome was not significantly different from that of the healthy virome, and the beta diversity had a significant difference between diarrheal and healthy children. The diarrheal virome was mainly dominated by the families Adenoviridae, Astroviridae, Caliciviridae, and Picornaviridae. Meanwhile, the healthy virome also contains phages, including Microviridae and Caudovirales. The high prevalence of diverse enteric viruses in all samples and the little abundance of Microviridae and Caudovirales in diarrheal groups were identified. The study introduced a general overview of the gut virome in diarrheal children, revealed the compositional differences in the gut viral community compared to healthy controls, and provided a reference for efficient treatments and prevention of virus-infectious diarrhea in children.

Diagnostic efficacy of serum presepsin for postoperative infectious complications: a meta-analysis.

Background: Postoperative infectious complications (PICs) are major concerns. Early and accurate diagnosis is critical for timely treatment and improved outcomes. Presepsin is an emerging biomarker for bacterial infections. However, its diagnostic efficacy for PICs across surgical specialties remains unclear. Methods: In this study, a systematic search on MEDLINE, Embase, Google Scholar, and Cochrane Library was performed on September 30, 2023, to identify studies that evaluated presepsin for diagnosing PICs. PIC is defined as the development of surgical site infection or remote infection. Pooled sensitivity, specificity, and hierarchical summary receiver operating characteristic (HSROC) curves were calculated. The primary outcome was the assessment of the efficacy of presepsin for PIC diagnosis, and the secondary outcome was the investigation of the reliability of procalcitonin or C-reactive protein (CRP) in the diagnosis of PICs. Results: This meta-analysis included eight studies (n = 984) and revealed that the pooled sensitivity and specificity of presepsin for PIC diagnosis were 76% (95% confidence interval [CI] 68%-82%) and 83% (95% CI 75%-89%), respectively. The HSROC curve yielded an area under the curve (AUC) of 0.77 (95% CI 0.73-0.81). Analysis of six studies on procalcitonin showed a combined sensitivity of 78% and specificity of 77%, with an AUC of 0.83 derived from the HSROC. Meanwhile, data from five studies on CRP indicated pooled sensitivity of 84% and specificity of 79%, with the HSROC curve yielding an AUC of 0.89. Conclusion: Presepsin exhibits moderate diagnostic accuracy for PIC across surgical disciplines. Based on the HSROC-derived AUC, CRP has the highest diagnostic efficacy for PICs, followed by procalcitonin and presepsin. Nonetheless, presepsin demonstrated greater specificity than the other biomarkers. Further study is warranted to validate the utility of and optimize the cutoff values for presepsin. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42023468358.

A database of anti-coronavirus peptides.

Since 2019, the novel coronavirus (SARS-COV-2) disease (COVID-19) has caused a worldwide epidemic. Anti-coronavirus peptides (ACovPs), a type of antimicrobial peptides (AMPs), have demonstrated excellent inhibitory effects on coronaviruses. However, state-of-the-art AMP databases contain only a small number of ACovPs. Additionally, the fields of these databases are not uniform, and the units or evaluation standards of the same field are inconsistent. Most of these databases have not included the target domains of ACovPs and description of in vitro and in vivo assays to measure the inhibitory effects of ACovPs. Here, we present a database focused on ACovPs (ACovPepDB), which contains comprehensive and precise ACovPs information of 518 entries with 214 unique ACovPs manually collected from public databases and published peer-reviewed articles. We believe that ACovPepDB is of great significance for facilitating the development of new peptides and improving treatment for coronavirus infection. The database will become a portal for ACovPs and guide and help researchers perform further studies. The ACovPepDB is available at http://i.uestc.edu.cn/ACovPepDB/ .

BBPpredict: A Web Service for Identifying Blood-Brain Barrier Penetrating Peptides.

Blood-brain barrier (BBB) is a major barrier to drug delivery into the brain in the treatment of central nervous system (CNS) diseases. Blood-brain barrier penetrating peptides (BBPs), a class of peptides that can cross BBB through various mechanisms without damaging BBB, are effective drug candidates for CNS diseases. However, identification of BBPs by experimental methods is time-consuming and laborious. To discover more BBPs as drugs for CNS disease, it is urgent to develop computational methods that can quickly and accurately identify BBPs and non-BBPs. In the present study, we created a training dataset that consists of 326 BBPs derived from previous databases and published manuscripts and 326 non-BBPs collected from UniProt, to construct a BBP predictor based on sequence information. We also constructed an independent testing dataset with 99 BBPs and 99 non-BBPs. Multiple machine learning methods were compared based on the training dataset via a nested cross-validation. The final BBP predictor was constructed based on the training dataset and the results showed that random forest (RF) method outperformed other classification algorithms on the training and independent testing dataset. Compared with previous BBP prediction tools, the RF-based predictor, named BBPpredict, performs considerably better than state-of-the-art BBP predictors. BBPpredict is expected to contribute to the discovery of novel BBPs, or at least can be a useful complement to the existing methods in this area. BBPpredict is freely available at http://i.uestc.edu.cn/BBPpredict/cgi-bin/BBPpredict.pl.

PDL1Binder: Identifying programmed cell death ligand 1 binding peptides by incorporating next-generation phage display data and different peptide descriptors.

Monoclonal antibody drugs targeting the PD-1/PD-L1 pathway have showed efficacy in the treatment of cancer patients, however, they have many intrinsic limitations and inevitable drawbacks. Peptide inhibitors as alternatives might compensate for the drawbacks of current PD-1/PD-L1 interaction blockers. Identifying PD-L1 binding peptides by random peptide library screening is a time-consuming and labor-intensive process. Machine learning-based computational models enable rapid discovery of peptide candidates targeting the PD-1/PD-L1 pathway. In this study, we first employed next-generation phage display (NGPD) biopanning to isolate PD-L1 binding peptides. Different peptide descriptors and feature selection methods as well as diverse machine learning methods were then incorporated to implement predictive models of PD-L1 binding. Finally, we proposed PDL1Binder, an ensemble computational model for efficiently obtaining PD-L1 binding peptides. Our results suggest that predictive models of PD-L1 binding can be learned from deep sequencing data and provide a new path to discover PD-L1 binding peptides. A web server was implemented for PDL1Binder, which is freely available at http://i.uestc.edu.cn/pdl1binder/cgi-bin/PDL1Binder.pl.

Substantial emissions of nitrated aromatic compounds in the particle and gas phases in the waste gases from eight industries.

Nitrated aromatic compounds, the ubiquitous nitrogen-containing organic pollutants, impact the environment and organisms adversely. As industrial raw materials and intermediates, nitrated aromatic compounds and their aromatic precursors are widely employed in the industrial production activities. Nevertheless, their emission from industrial waste gases has so far not been studied extensively. In this study, the concentrations of 12 nitrated aromatic compounds in the particle and gas phases downwind of 16 factories encompassing eight industries (i.e., pharmaceutical, weaving and dyeing, herbicide, explosive, painting, phenolic resin, paper pulp and polystyrene foam industries), were determined by ultra-high-performance liquid chromatography-mass spectrometry. Their concentrations in the particle and gas phases from different factories ranged from 114.7 ± 63.5 to 296.6 ± 62.5 ng m-3 and 148.7 ± 7.4 to 309.8 ± 26.2 ng m-3, respectively, thus, exhibiting significantly high concentrations as compared to the background sites. Among the 12 detected species, 4-nitrophenol, 5-nitrosalicylic acid, 3-nitrosalicylic acid and 4-methyl-2,6-dinitrophenol were observed to be the predominant species, with total fractions up to 47.9-72.3% and 63.1-70.3% in the particle and gas phases, respectively. Their emission profiles with respect to the industrial activities exhibited large discrepancies as compared to the combustion sources, thus, indicating different formation mechanisms. The emission ratios of particulate nitrated aromatic compounds owing to the industrial activities were estimated between 0.5 ± 0.2 and 4.3 ± 1.5 ng µg-1, which were higher than or comparable to those from various combustion sources. The findings from this study confirm the industrial emission to be an important source of nitrated aromatic compounds in the atmosphere. The substantial emissions of nitrated aromatic compounds from various industries reported in this study provide the fundamental basis for further emission estimation and pollution control.

Size distributions of nitrated phenols in winter at a coastal site in north China and the impacts from primary sources and secondary formation.

Nitrated phenols in particulate matters are among the major components of brown carbon, harm plant growth and human health. To understand the size distributions of nitrated phenols in the polluted coastal region and the factors influencing these distributions, size-resolved particulate matters were collected from a rural site in the coastal city of Qingdao, China, in January 2019, and analyzed for the presence of 11 nitrated phenols. The average concentrations of total nitrated phenols in fine- and coarse-mode particles were 123.6 and 37.2 ng m-3, respectively. 4-Nitrophenol was found to be the dominant nitrated phenol, followed by 3-methyl-6-nitrocatechol, 3-methyl-4-nitrophenol, and 4-nitrocatechol. On average, maximum concentrations of nitrated phenols were in condensation-mode particles, whereas a minor concentration peak of nitro-salicylic acids was present in droplet-mode particles. In addition, a minor concentration peak of 4-methyl-2,6-dinitrophenol was noticed in coarse-mode particles. Comparisons of the size distributions under different situations confirmed that both primary emissions and secondary formation had significant effects on the abundances and particle-sizes of nitrated phenols. Coal combustion in residential villages and firework burning during a festival led to a sharp increase of nitrated phenols in condensation-mode particles, whereas dust promoted their heterogeneous formation in coarse-mode particles, and high humidity in the coastal area facilitated their aqueous formation in droplet-mode particles.

Nitrated phenols and the phenolic precursors in the atmosphere in urban Jinan, China.

Nitrated phenols are a major class of brown carbon in the atmosphere and have adverse effects on human and plants health. They are emitted from combustion sources or produced by oxidation of phenolic precursors. In this study, fine particulates, total suspended particulates, and gas-phase samples were collected in urban Jinan in winter, spring, and summer, and UHPLC-MS analysis was used to determine 8 phenolic compounds and 12 nitrated phenols in these samples. The seasonal average concentrations of total phenolic compounds and total nitrated phenols were in the ranges of 2.6-18.7 ng m-3 and 13.5-105.4 ng m-3, respectively. The concentrations of phenolic compounds and nitrated phenols were highest in winter, followed (in decreasing order) by spring, and summer. Phenol and salicylic acid were the most abundant phenolic species in both gaseous and particulate samples. 4-Nitrophenol was the most abundant nitrated phenols in particulate matters, followed by 4-nitrocatechol and 5-nitrosalicylic acid, while 4-nitrophenol and 2,4-dinitrophenol were the dominant species in the gas phase. The distributions of phenolic compounds and nitrated phenols in fine and coarse particles and in gas and particle phases were largely dependent on the aerosol size distribution, the ambient temperature, and the compound volatility. More of them were distributed in fine particles and gas-phase in summer than in spring. It was found that phenol, catechol, methyl-catechols, 4-nitrophenol, and methyl-nitrophenols mainly derived from coal combustion, while biomass burning was the main source of cresols, 2,6-dimethyl-4-nitrophenol, 4-nitrocatechol, and methyl-nitrocatechols. In addition, secondary formation contributed the largest fraction of nitrosalicylic acids and vehicle exhaust was the major source of cresols, 2,6-dimethyl-4-nitrophenol, and 4-methyl-2,6-dinitrophenol. Further correlation analysis revealed positive correlations between nitrated phenols and corresponding phenolic precursors, indicating the important roles that phenolic precursors played in the secondary formation and abundance of nitrated phenols in the atmosphere.

[Protective effects of perfluorocarbon combined with ligustrazine against lung ischemia-reperfusion injury in rats].

OBJECTIVE: To investigate the effects of perfluorocarbon and ligustrazine in protecting the lungs against ischemia-reperfusion injury in rats. METHDS: Forty SD rats with ischemia-reperfusion lung injury were randomized equally into control, ligustrazine, perfluorocarbon, and perfluorocarbon plus ligustrazine groups and received the corresponding treatment via the tail vein 5 min before reperfusion. The lung tissues were harvested and the levels of malondialdehyde (MDA), myeloperoxidase (MPO), superoxide dismutase (SOD) and tumor necrosis factor-α (TNF-α) were detected 3 h after reperfusion. The pathological changes and pathological scores of the lung tissues were analyzed. RESULTS: MDA and MPO levels were significantly lower and SOD activities significantly higher in the lung tissues in the 3 treatment groups than in the control group (P<0.05). The rats in the combined treatment group showed a significantly lower MPO level and a significantly higher SOD activity than those treated with ligustrazine or perfluorocarbon alone (P<0.05). No significant difference was found in TNF-α levels in the lung tissues among the 4 groups (P>0.05). The lung tissues in the control group showed obvious edema and exudation, and the tissues in ligustrazine and perfluorocarbon groups showed no edema but with a few red blood cells and exudation; no edema was found in the combined treatment group with only a small amount of exudation. The pathological scores differed significantly among the 4 groups. CONCLUSION: Perfluorocarbon and ligustrazine, especially in combined use, can promote endogenous oxygen free radical scavenging, decrease peripheral blood proinflammatory cytokines, and inhibit neutrophils filtration in the lungs of rats with ischemia/reperfusion lung injury.

miR-1 exacerbates cardiac ischemia-reperfusion injury in mouse models.

Recent studies have revealed the critical role of microRNAs (miRNAs) in regulating cardiac injury. Among them, the cardiac enriched microRNA-1(miR-1) has been extensively investigated and proven to be detrimental to cardiac myocytes. However, solid in vivo evidence for the role of miR-1 in cardiac injury is still missing and the potential therapeutic advantages of systemic knockdown of miR-1 expression remained unexplored. In this study, miR-1 transgenic (miR-1 Tg) mice and locked nucleic acid modified oligonucleotide against miR-1 (LNA-antimiR-1) were used to explore the effects of miR-1 on cardiac ischemia/reperfusion injury (30 min ischemia followed by 24 h reperfusion). The cardiac miR-1 level was significantly increased in miR-1 Tg mice, and suppressed in LNA-antimiR-1 treated mice. When subjected to ischemia/reperfusion injury, miR-1 overexpression exacerbated cardiac injury, manifested by increased LDH, CK levels, caspase-3 expression, apoptosis and cardiac infarct area. On the contrary, LNA-antimiR-1 treatment significantly attenuated cardiac ischemia/reperfusion injury. The expression of PKCε and HSP60 was significantly repressed by miR-1 and enhanced by miR-1 knockdown, which may be a molecular mechanism for the role miR-1 in cardiac injury. Moreover, luciferase assay confirmed the direct regulation of miR-1 on protein kinase C epsilon (PKCε) and heat shock protein 60 (HSP60). In summary, this study demonstrated that miR-1 is a causal factor for cardiac injury and systemic LNA-antimiR-1 therapy is effective in ameliorating the problem.