Systematic assessment of long-read RNA-seq methods for transcript identification and quantification.

The Long-read RNA-Seq Genome Annotation Assessment Project Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. Using different protocols and sequencing platforms, the consortium generated over 427 million long-read sequences from complementary DNA and direct RNA datasets, encompassing human, mouse and manatee species. Developers utilized these data to address challenges in transcript isoform detection, quantification and de novo transcript detection. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. Incorporating additional orthogonal data and replicate samples is advised when aiming to detect rare and novel transcripts or using reference-free approaches. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

Flexiplex: a versatile demultiplexer and search tool for omics data.

MOTIVATION: The process of analyzing high throughput sequencing data often requires the identification and extraction of specific target sequences. This could include tasks, such as identifying cellular barcodes and UMIs in single-cell data, and specific genetic variants for genotyping. However, existing tools, which perform these functions are often task-specific, such as only demultiplexing barcodes for a dedicated type of experiment, or are not tolerant to noise in the sequencing data. RESULTS: To overcome these limitations, we developed Flexiplex, a versatile and fast sequence searching and demultiplexing tool for omics data, which is based on the Levenshtein distance and thus allows imperfect matches. We demonstrate Flexiplex's application on three use cases, identifying cell-line-specific sequences in Illumina short-read single-cell data, and discovering and demultiplexing cellular barcodes from noisy long-read single-cell RNA-seq data. We show that Flexiplex achieves an excellent balance of accuracy and computational efficiency compared to leading task-specific tools. AVAILABILITY AND IMPLEMENTATION: Flexiplex is available at https://davidsongroup.github.io/flexiplex/.

Effect of particle size on liver MRI R 2 * relaxometry: Monte Carlo simulation and phantom studies.

PURPOSE: To investigate the effect of particle size on liver R 2 * $$ {\mathrm{R}}_2^{\ast } $$ by Monte Carlo simulation and phantom studies at both 1.5 T and 3.0 T. METHODS: Two kinds of particles (i.e., iron sphere and fat droplet) with varying sizes were considered separately in simulation and phantom studies. MRI signals were synthesized and analyzed for predicting R 2 * $$ {\mathrm{R}}_2^{\ast } $$ , based on simulations by incorporating virtual liver model, particle distribution, magnetic field generation, and proton movement into phase accrual. In the phantom study, iron-water and fat-water phantoms were constructed, and each phantom contained 15 separate vials with combinations of five particle concentrations and three particle sizes. R 2 * $$ {\mathrm{R}}_2^{\ast } $$ measurements in the phantom were made at both 1.5 T and 3.0 T. Finally, differences in R 2 * $$ {\mathrm{R}}_2^{\ast } $$ predictions or measurements were evaluated across varying particle sizes. RESULTS: In the simulation study, strong linear and positively correlated relationships were observed between R 2 * $$ {\mathrm{R}}_2^{\ast } $$ predictions and particle concentrations across varying particle sizes and magnetic field strengths ( r ≥ 0.988 $$ r\ge 0.988 $$ ). The relationships were affected by iron sphere size ( p < 0.001 $$ p<0.001 $$ ), where smaller iron sphere size yielded higher predicted R 2 * $$ {\mathrm{R}}_2^{\ast } $$ , whereas fat droplet size had no effect on R 2 * $$ {\mathrm{R}}_2^{\ast } $$ predictions ( p ≥ 0.617 $$ p\ge 0.617 $$ ) for constant total fat concentration. Similarly, the phantom study showed that R 2 * $$ {\mathrm{R}}_2^{\ast } $$ measurements were relatively sensitive to iron sphere size ( p ≤ 0.004 $$ p\le 0.004 $$ ) unlike fat droplet size ( p ≥ 0.223 $$ p\ge 0.223 $$ ). CONCLUSION: Liver R 2 * $$ {\mathrm{R}}_2^{\ast } $$ is affected by iron sphere size, but is relatively unaffected by fat droplet size. These findings may lead to an improved understanding of the underlying mechanisms of R 2 * $$ {\mathrm{R}}_2^{\ast } $$ relaxometry in vivo, and enable improved quantitative MRI phantom design.

Inhibition of inflammation and apoptosis through the cyclic GMP-AMP synthase-stimulator of interferon genes pathway by stress granules after ALKBH5 demethylase activation during diabetic myocardial ischaemia-reperfusion injury.

AIM: Post-transcriptional modifications and their specific mechanisms are the focus of research on the regulation of myocardial damage. Stress granules (SGs) can inhibit the inflammatory response by inhibiting the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway. This study investigated whether alkylation repair homologue protein 5 (ALKBH5) could affect myocardial inflammation and apoptosis during diabetic myocardial ischaemia-reperfusion injury (IRI) through the cGAS-STING pathway via SGs. METHODS: A diabetes ischaemia-reperfusion rat model and a high glucose hypoxia/reoxygenation cell model were established. Adeno-associated virus (AAV) and lentivirus (LV) were used to overexpress ALKBH5, while the SG agonist arsenite (Ars) and the SG inhibitor anisomycin were used as interventions. Then, the levels of apoptosis and related indicators in the cell and rat models were measured. RESULTS: In the in vivo experiment, compared with the normal sham group, the degree of myocardial tissue damage, creatine kinase-MB and cardiac troponin I in serum, and myocardial apoptosis, the infarcted area of myocardium, and the level of B-cell lymphoma 2 associated X protein, cGAS-STING pathway and inflammatory factors in the diabetes ischaemia-reperfusion group were significantly increased. However, the expression of SGs and the levels of ALKBH5, rat sarcoma-GTPase-activating protein-binding protein 1, T-cell intracellular antigen-1 and Bcl2 were significantly decreased. After AAV-ALKBH5 intervention, the degree of myocardial tissue damage, degree of myocardial apoptosis, and extent of myocardial infarction in myocardial tissue were significantly decreased. In the in vitro experiment, compared with those in the normal control group, the levels of lactate dehydrogenase, inflammation and apoptosis were significantly greater, and cell viability and the levels of ALKBH5 and SGs were decreased in the high glucose and hypoxia/reoxygenation groups. In the high glucose hypoxia/reoxygenation cell model, the degree of cell damage, inflammation, and apoptosis was greater than those in the high glucose and hypoxia/reoxygenation models, and the levels of ALKBH5 and SGs were further decreased. LV-ALKBH5 and Ars alleviated the degree of cell damage and inhibited inflammation and cell apoptosis. The inhibition of SGs could partly reverse the protective effect of LV-ALKBH5. The cGAS agonist G140 antagonized the inhibitory effects of the SG agonist Ars on cardiomyocyte apoptosis, inflammation and the cGAS-STING pathway. CONCLUSION: Both ALKBH5 and SGs inhibited myocardial inflammation and apoptosis during diabetic myocardial ischaemia-reperfusion. Mechanistically, ALKBH5 might inhibit the apoptosis of cardiomyocytes by promoting the expression of SGs through the cGAS-STING pathway.

Induced transparency by interference or polarization.

Polarization of optical fields is a crucial degree of freedom in the all-optical analogue of electromagnetically induced transparency (EIT). However, the physical origins of EIT and polarization-induced phenomena have not been well distinguished, which can lead to confusion in associated applications such as slow light and optical/quantum storage. Here we study the polarization effects in various optical EIT systems. We find that a polarization mismatch between whispering gallery modes in two indirectly coupled resonators can induce a narrow transparency window in the transmission spectrum resembling the EIT lineshape. However, such polarization-induced transparency (PIT) is distinct from EIT: It originates from strong polarization rotation effects and shows a unidirectional feature. The coexistence of PIT and EIT provides additional routes for the manipulation of light flow in optical resonator systems.

Split-half reliability estimates of an online card sorting task in a community sample of young and elderly adults.

Executive function is vital for normal social, cognitive, and motor functions. Executive function decline due to aging increases the risk of disability and falls in older adults, which has become an urgent public health issue. Fast and convenient neuropsychological tools are thus needed to identify high-risk groups as early as possible to conduct a timely intervention. Card sorting tasks, such as Wisconsin Card Sorting Task (WCST) and its variants, are popular tools for measuring executive function. This study investigated the reliability of an open-source, self-administered, online, short-version card sorting task with a sample of young (n = 107, 65 females, age: M = 30.1 years, SD = 5.5 years) and elderly Chinese (n = 113, 53 females, age: M = 64.0 years, SD = 6.7 years). We developed an automated scoring and visualization procedure following the recent recommendations on scoring perseverative responses to make the results comparable to the standardized WCST. Reliability estimates of commonly used measures were calculated using the split-half method. All task indices' reliabilities were reasonably good in both old and young groups except for "failure-to-maintain-set." Elderly Chinese adults showed compromised task performance on all measures compared with the young Chinese adults at the group level. The R script of automated scoring and estimation of reliability is publicly available.

The reciprocal interactions between microglia and T cells in Parkinson's disease: a double-edged sword.

In Parkinson's disease (PD), neurotoxic microglia, Th1 cells, and Th17 cells are overactivated. Overactivation of these immune cells exacerbates the disease process and leads to the pathological development of pro-inflammatory cytokines, chemokines, and contact-killing compounds, causing the loss of dopaminergic neurons. So far, we have mainly focused on the role of the specific class of immune cells in PD while neglecting the impact of interactions among immune cells on the disease. Therefore, this review demonstrates the reciprocal interplays between microglia and T cells and the associated subpopulations through cytokine and chemokine production that impair and/or protect the pathological process of PD. Furthermore, potential targets and models of PD neuroinflammation are highlighted to provide the new ideas/directions for future research.

Friction properties of black phosphorus: a first-principles study.

Based on the first-principle, the friction anisotropy, structural super-lubricity and oxidation induced ultra-low friction of black phosphorus at atomic scale under different loads have been studied. The results show that the interface friction of black phosphorus is anisotropic, that is, the friction along the armchair direction is greater than that along the zigzag direction. Moreover, the friction between the black phosphorus interfaces shows a structural superlubricity property, and the incommensurate interface friction is approximately one thousandth of the commensurate interface friction, which is mainly due to the less electronic charge and the smaller amplitude of electronic charge change between the incommensurate interfaces during the friction process. In addition, the oxidation of black phosphorus is beneficial for lubrication between interfaces.

[Electrocardiogram signal classification based on fusion method of residual network and self-attention mechanism].

In the diagnosis of cardiovascular diseases, the analysis of electrocardiogram (ECG) signals has always played a crucial role. At present, how to effectively identify abnormal heart beats by algorithms is still a difficult task in the field of ECG signal analysis. Based on this, a classification model that automatically identifies abnormal heartbeats based on deep residual network (ResNet) and self-attention mechanism was proposed. Firstly, this paper designed an 18-layer convolutional neural network (CNN) based on the residual structure, which helped model fully extract the local features. Then, the bi-directional gated recurrent unit (BiGRU) was used to explore the temporal correlation for further obtaining the temporal features. Finally, the self-attention mechanism was built to weight important information and enhance model's ability to extract important features, which helped model achieve higher classification accuracy. In addition, in order to mitigate the interference on classification performance due to data imbalance, the study utilized multiple approaches for data augmentation. The experimental data in this study came from the arrhythmia database constructed by MIT and Beth Israel Hospital (MIT-BIH), and the final results showed that the proposed model achieved an overall accuracy of 98.33% on the original dataset and 99.12% on the optimized dataset, which demonstrated that the proposed model can achieve good performance in ECG signal classification, and possessed potential value for application to portable ECG detection devices.

Pressure enhanced negative thermal expansion in 2H CuScO2 from first-principles calculations.

Finding materials with negative thermal expansion (NTE) property is challenging. Tuning NTE is of fundamental and technological importance. Pressure enhanced negative thermal expansion behavior in 2H CuScO2 is found and expounded using density functional theory (DFT) and quasi-harmonious approximation (QHA). The frequencies of low energy modes and Grüneisen parameters decrease under pressure, but the bulk modulus increases with pressure. The transverse vibration of Cu atoms becomes stronger under pressure and the materials undergo thermal softening. These factors including thermal softening, pressure induced decrease of Grüneisen parameters and pressure induced strengthening of transverse vibration of Cu atoms all contribute to the enhanced negative thermal expansion property in 2H CuScO2 in view of the thermodynamic relationship , Grüneisen's theory of thermal expansion and the mechanism of NTE, respectively.

Relaxivity-iron calibration in hepatic iron overload: Reproducibility and extension of a Monte Carlo model.

The aim of this study was to reproduce relaxivity-iron calibration in hepatic iron overload using a Monte Carlo model, and further extend the model with multiple spin echo (MSE) imaging. As previously reported, relationships between relaxation rates ( R2* and single spin echo R2 ) and liver iron concentration (LIC) can be characterized by a Monte Carlo model incorporating realistic liver structure, iron distribution, and proton mobility. In this study, relaxivity-iron calibration curves at 1.5 and 3.0 T were simulated using the Monte Carlo model. Furthermore, the model was extended with MSE imaging, and iron calibrations were evaluated using two different fitting models: mononexponential with a constant offset and nonmonoexponential. Results consistent with previous empirical calibrations and Monte Carlo predictions were accurately reproduced for relaxivity-iron calibration. The predicted R2* and single spin echo R2 increased by a factor of 2.00 and 1.51, respectively, at 1.5 versus 3.0 T. MSE signals and their corresponding R2 depended strongly on LIC, interecho time, and field strength. Preliminary results showed that a nonmonoexponential model accurately characterizes the simulated MSE signals, and that strong correlations were found between predicted relaxation parameters and LIC. In conclusion, relaxivity-iron calibration is reproducible using the proposed Monte Carlo model. Furthermore, this model can be readily extended to other important applications, including predicting signal behavior for MSE imaging.

Primate-specific miRNA-637 inhibited tumorigenesis in human pancreatic ductal adenocarcinoma cells by suppressing Akt1 expression.

As a primate-specific microRNA, miR-637 has been discovered for nearly 10 years. Our previous study demonstrated that miR-637 acted as a suppressor in hepatocellular carcinoma. However, its biomedical significance in pancreatic cancer remains obscure. In the present study, miR-637 was found to be significantly downregulated in pancreatic ductal adenocarcinoma (PDAC) cell lines and most of the PDAC specimens. Furthermore, the enforced overexpression of miR-637 dramatically inhibited cell proliferation and induced apoptosis of PDAC cells. Akt1, as a serine/threonine-protein kinase, has been identified as an oncogene in multiple cancers including pancreatic cancer. Our data confirmed that Akt1 was a novel target for miR-637, and its knockdown also induced cell growth inhibition and apoptosis in PDAC cells. In conclusion, our data indicated that miR-637 acted as a tumor-suppressor in PDAC, and the suppressive effect was mediated, at least partially, by suppressing Akt1 expression.

Utilization willingness of institutional care between disabled and non-disabled seniors: evidence from Jiangsu, China.

BACKGROUND: Due to rapidly growing number of old adults and diminishing supportive functions of family in China, the issue of willingness to use institutional care is of high priority, especially for disabled seniors. The objective of this study is to compare the willingness of institutional care and its determinants between disabled and non-disabled seniors in China. METHODS: 2493 seniors (60+) were randomly selected from a cross-sectional study conducted in three urban districts and three rural counties in Jiangsu Province. Binary logistic regression model was employed to examine differences towards the preference for institutional care between two subgroups, and to identify factors associated with willingness of institutional care between disabled and non-disabled seniors. RESULTS: Of 2493 respondents, 402 (16.1%) were disabled seniors. Overall, 14.2% of the participants had willingness for institutional care in Jiangsu, China. The willingness for institutional care among non-disabled seniors (OR = 0.513; 95%CI 0.387-9.680) was significantly lower than that among disabled ones. The preference for institutional care of both disabled and non-disabled seniors was associated with household income. The willingness of institutional care was also related to age, education and living arrangement among disabled seniors. Meanwhile, non-disabled seniors who had non-communicable diseases were found to be more likely to choose elder care in institution. CONCLUSIONS: Our findings indicated that the willingness for institutional care among disabled seniors was significantly higher than that among non-disabled ones. Household income was determinant of utilization willingness for institutionalization both in disabled and non-disable seniors. Different policies should be made or modified for disabled and non-disabled seniors separately.

Improving mass-univariate analysis of neuroimaging data by modelling important unknown covariates: Application to Epigenome-Wide Association Studies.

Statistical inference on neuroimaging data is often conducted using a mass-univariate model, equivalent to fitting a linear model at every voxel with a known set of covariates. Due to the large number of linear models, it is challenging to check if the selection of covariates is appropriate and to modify this selection adequately. The use of standard diagnostics, such as residual plotting, is clearly not practical for neuroimaging data. However, the selection of covariates is crucial for linear regression to ensure valid statistical inference. In particular, the mean model of regression needs to be reasonably well specified. Unfortunately, this issue is often overlooked in the field of neuroimaging. This study aims to adopt the existing Confounder Adjusted Testing and Estimation (CATE) approach and to extend it for use with neuroimaging data. We propose a modification of CATE that can yield valid statistical inferences using Principal Component Analysis (PCA) estimators instead of Maximum Likelihood (ML) estimators. We then propose a non-parametric hypothesis testing procedure that can improve upon parametric testing. Monte Carlo simulations show that the modification of CATE allows for more accurate modelling of neuroimaging data and can in turn yield a better control of False Positive Rate (FPR) and Family-Wise Error Rate (FWER). We demonstrate its application to an Epigenome-Wide Association Study (EWAS) on neonatal brain imaging and umbilical cord DNA methylation data obtained as part of a longitudinal cohort study. Software for this CATE study is freely available at http://www.bioeng.nus.edu.sg/cfa/Imaging_Genetics2.html.

Improved liver R2* mapping by pixel-wise curve fitting with adaptive neighborhood regularization.

PURPOSE: To improve liver R2* mapping by incorporating adaptive neighborhood regularization into pixel-wise curve fitting. METHODS: Magnetic resonance imaging R2* mapping remains challenging because of the serial images with low signal-to-noise ratio. In this study, we proposed to exploit the neighboring pixels as regularization terms and adaptively determine the regularization parameters according to the interpixel signal similarity. The proposed algorithm, called the pixel-wise curve fitting with adaptive neighborhood regularization (PCANR), was compared with the conventional nonlinear least squares (NLS) and nonlocal means filter-based NLS algorithms on simulated, phantom, and in vivo data. RESULTS: Visually, the PCANR algorithm generates R2* maps with significantly reduced noise and well-preserved tiny structures. Quantitatively, the PCANR algorithm produces R2* maps with lower root mean square errors at varying R2* values and signal-to-noise-ratio levels compared with the NLS and nonlocal means filter-based NLS algorithms. For the high R2* values under low signal-to-noise-ratio levels, the PCANR algorithm outperforms the NLS and nonlocal means filter-based NLS algorithms in the accuracy and precision, in terms of mean and standard deviation of R2* measurements in selected region of interests, respectively. CONCLUSIONS: The PCANR algorithm can reduce the effect of noise on liver R2* mapping, and the improved measurement precision will benefit the assessment of hepatic iron in clinical practice. Magn Reson Med 80:792-801, 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Clinical Research on the Comprehensive Curative Effect of Acupuncture and Traditional Chinese Medicine for Pelvic Inflammatory Sequelae.

BACKGROUND This randomized, controlled trial was designed to assess whether acupuncture plus an oral administration of Chinese herbal medicine provides greater relief of symptoms than oral administration of Chinese herbal medicine alone for treatment of pelvic inflammatory sequelae. MATERIAL AND METHODS Sixty-two patients ages 22 to 45 years with pelvic inflammatory sequelae were randomly assigned into one of 2 groups: an herbal group (n=30) and an herbal with acupuncture group (n=32). Both groups were treated for 3 courses of 3 months each. RESULTS Significant improvement of clinical symptoms and signs of pelvic inflammatory sequelae occurred in both treatment groups. The total effective rate for the herbal group was 83.33%, and for the herbal with acupuncture group it was 100% ([i]P[/i]=0.354 for difference between groups). During treatment, 5 patients had adverse reactions of nausea, loss of appetite, and diarrhea. After adjustment of the herb prescription, all adverse reactions disappeared. CONCLUSIONS Our results highlight the benefit of oral administration of Chinese herbal medicine along with acupuncture; this had a greater clinical curative effect rate than oral administration of Chinese herbal medicine alone when treating pelvic inflammatory sequelae.

The effects of cognitive intervention on cognitive impairments after intensive care unit admission.

Patients who survive critical illness commonly suffer cognitive impairments. We aimed to study the effects of cognitive intervention to treat the long-term impairments observed among different populations of intensive care unit (ICU) survivors. The results showed that the intervention significantly suppressed the deterioration of cognitive function in these patients. Medical and neurological ICU survivors were more susceptible than post-anaesthesia ICU patients to severe cognitive damage. In the former, the deterioration of impairments can be slowed by cognitive intervention. In comparison, intervention exerted significantly positive effects on the recovery of the cognitive functions of post-anaesthesia care unit patients. Furthermore, young populations were more likely than older populations to recover from acute cognitive impairments, and the impairment observed among the older population seemed to be multi-factorial and irreversible.

Rapid look-up table method for noise-corrected curve fitting in the R2* mapping of iron loaded liver.

PURPOSE: Fitting the measured decay signal to the first moment in the presence of noncentral chi noise (M(1) NCM) can correctly address the effect of noise on the effective transverse relaxation rate (R2*) relaxometry of iron loaded liver. However, this method requires intensive computation, which restricts its application to R2* mapping. This work aims to develop a rapid implementation of the M(1) NCM method for R2* mapping. METHODS: The computation of the confluent hypergeometric function in the M(1) NCM model was approximated using cubic spline interpolation with breakpoints and coefficients precalculated and stored in a look-up table (M(1) NCM-LUT). The performance of the proposed M(1) NCM-LUT method was evaluated through simulation and based on in vivo liver R2* relaxometry data. RESULTS: In both simulation and in vivo studies, the maximum absolute difference between R2* maps generated by the M(1) NCM and M(1) NCM-LUT methods was nearly 10(-3) s(-1) or less, and the M(1) NCM-LUT method obtained a R2* map in approximately 1 s and achieved an acceleration of approximately five orders of magnitude. CONCLUSION: The proposed M(1) NCM-LUT method can significantly increase the speed of the liver R2* mapping using the M(1) NCM model. This development is important in promoting application of this R2* mapping technique for tissue iron quantification.

Laparoscopy-Assisted D2 Radical Gastrectomy for Advanced Gastric Cancer.

BACKGROUND/AIMS: The aim of this study was to investigate the efficacy and advantages of laparoscopy-assisted gastrectomy (LAG) with D2 lymphadenectomy versus conventional open D2 gastrectomy (ODG) in advanced gastric cancer (AGC) patients. METHODOLOGY: From June 2009 to June 2014, 233 patients who were treated by conventional radical ODG and 188 cases who underwent radical LAG for AGC at our department were enrolled in this study. Clinical data recorded in hospital database was retrospectively reviewed and analyzed. RESULTS: There were no significant differences in age, gender or preoperative laboratory tests distribution between the LAG group and the ODG group. Two (1%) of the patients who underwent LAG required conversion to ODG. The advantages of minimally invasive surgery including earlier recovery of bowel movements and shorter postoperative hospitalization time were observed in LAG group. The number of harvested lymph nodes was 24.3 ± 3.3 in the LAG group and 25.0 ± 2.8 in ODG (p = 0.110). CONCLUSIONS: Although prospective randomized trials with long follow-up period are needed to identify the feasibility, we have shown the safety and advantages of LAG with D2 lymphadenectomy for treating AGC patients in this study.

Clinical value and mechanistic analysis of HIIT on modulating risk and symptoms of depression: A systematic review.

Background: The exact causal mechanisms of depression remain unclear due to the complexity of the triggers, which has led to limitations in treating depression using modern drugs. High-intensity interval training (HIIT) is as effective as medication in treating depression without toxic side effects. Typically, HIIT requires less time commitment (i.e., shorter exercise duration) and exhibits pronounced benefits on depressive symptoms than other forms of physical exercise. This review summarizes the risk reduction and clinical effects of HIIT for depression and discusses the underlying mechanisms, providing a theoretical basis for utilizing HIIT in treating depression. Methods: A database search was conducted in PubMed, Embase, Web of Science, and Scopus from inception up to October 2022. The methodological quality of the included literature was evaluated by the physiotherapy evidence database (PEDro) scale criteria. The review focused on evaluating the changes in depression risk or symptoms of HIIT interventions in healthy individuals, patients with depression, and patients with other disorders co-morbid with depression. Consequently, the mechanisms associated with depression related HIIT were summarized. Results: A total of 586 participants (52 % female; mean age: 43.58±8.93 years) from 22 studies were included. Implementing HIIT using different exercise types alleviates depressive symptoms in individuals with depression and in individuals with depression who have exhibited comorbidities and reduced depression scale scores in subjects immediately after acute exercise. In addition, the long-interval HIIT and short-interval HIIT in the treatment of patients with cardiovascular or psychiatric disorders may reduce depressive symptoms via complex exercise-related changes on several levels, including by effecting the following measures: releasing monoamines, reducing neuronal death, inducing neurogenesis, modulating the functional homeostasis of the HPA axis, and enhancing the level of inflammation in the body. Conclusion: HIIT is a relatively safe and effective antidepressant, which may involve multiple neurobiological mechanisms (release of monoamines, reducing neuronal death, inducing neurogenesis, modulating the functional homeostasis of the HPA axis, and enhancing the level of inflammation in the body), thereby reducing the risk or symptoms of depression in participants.