Collaborative Enhancement of Consistency and Accuracy in US Diagnosis of Thyroid Nodules Using Large Language Models.

Background Large language models (LLMs) hold substantial promise for medical imaging interpretation. However, there is a lack of studies on their feasibility in handling reasoning questions associated with medical diagnosis. Purpose To investigate the viability of leveraging three publicly available LLMs to enhance consistency and diagnostic accuracy in medical imaging based on standardized reporting, with pathology as the reference standard. Materials and Methods US images of thyroid nodules with pathologic results were retrospectively collected from a tertiary referral hospital between July 2022 and December 2022 and used to evaluate malignancy diagnoses generated by three LLMs-OpenAI's ChatGPT 3.5, ChatGPT 4.0, and Google's Bard. Inter- and intra-LLM agreement of diagnosis were evaluated. Then, diagnostic performance, including accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC), was evaluated and compared for the LLMs and three interactive approaches: human reader combined with LLMs, image-to-text model combined with LLMs, and an end-to-end convolutional neural network model. Results A total of 1161 US images of thyroid nodules (498 benign, 663 malignant) from 725 patients (mean age, 42.2 years ± 14.1 [SD]; 516 women) were evaluated. ChatGPT 4.0 and Bard displayed substantial to almost perfect intra-LLM agreement (κ range, 0.65-0.86 [95% CI: 0.64, 0.86]), while ChatGPT 3.5 showed fair to substantial agreement (κ range, 0.36-0.68 [95% CI: 0.36, 0.68]). ChatGPT 4.0 had an accuracy of 78%-86% (95% CI: 76%, 88%) and sensitivity of 86%-95% (95% CI: 83%, 96%), compared with 74%-86% (95% CI: 71%, 88%) and 74%-91% (95% CI: 71%, 93%), respectively, for Bard. Moreover, with ChatGPT 4.0, the image-to-text-LLM strategy exhibited an AUC (0.83 [95% CI: 0.80, 0.85]) and accuracy (84% [95% CI: 82%, 86%]) comparable to those of the human-LLM interaction strategy with two senior readers and one junior reader and exceeding those of the human-LLM interaction strategy with one junior reader. Conclusion LLMs, particularly integrated with image-to-text approaches, show potential in enhancing diagnostic medical imaging. ChatGPT 4.0 was optimal for consistency and diagnostic accuracy when compared with Bard and ChatGPT 3.5. © RSNA, 2024 Supplemental material is available for this article.

US-based Sequential Algorithm Integrating an AI Model for Advanced Liver Fibrosis Screening.

Background Noninvasive tests can be used to screen patients with chronic liver disease for advanced liver fibrosis; however, the use of single tests may not be adequate. Purpose To construct sequential clinical algorithms that include a US deep learning (DL) model and compare their ability to predict advanced liver fibrosis with that of other noninvasive tests. Materials and Methods This retrospective study included adult patients with a history of chronic liver disease or unexplained abnormal liver function test results who underwent B-mode US of the liver between January 2014 and September 2022 at three health care facilities. A US-based DL network (FIB-Net) was trained on US images to predict whether the shear-wave elastography (SWE) value was 8.7 kPa or higher, indicative of advanced fibrosis. In the internal and external test sets, a two-step algorithm (Two-step#1) using the Fibrosis-4 Index (FIB-4) followed by FIB-Net and a three-step algorithm (Three-step#1) using FIB-4 followed by FIB-Net and SWE were used to simulate screening scenarios where liver stiffness measurements were not or were available, respectively. Measures of diagnostic accuracy were calculated using liver biopsy as the reference standard and compared between FIB-4, SWE, FIB-Net, and European Association for the Study of the Liver guidelines (ie, FIB-4 followed by SWE), along with sequential algorithms. Results The training, validation, and test data sets included 3067 (median age, 42 years [IQR, 33-53 years]; 2083 male), 1599 (median age, 41 years [IQR, 33-51 years]; 1124 male), and 1228 (median age, 44 years [IQR, 33-55 years]; 741 male) patients, respectively. FIB-Net obtained a noninferior specificity with a margin of 5% (P < .001) compared with SWE (80% vs 82%). The Two-step#1 algorithm showed higher specificity and positive predictive value (PPV) than FIB-4 (specificity, 79% vs 57%; PPV, 44% vs 32%) while reducing unnecessary referrals by 42%. The Three-step#1 algorithm had higher specificity and PPV compared with European Association for the Study of the Liver guidelines (specificity, 94% vs 88%; PPV, 73% vs 64%) while reducing unnecessary referrals by 35%. Conclusion A sequential algorithm combining FIB-4 and a US DL model showed higher diagnostic accuracy and improved referral management for all-cause advanced liver fibrosis compared with FIB-4 or the DL model alone. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Ghosh in this issue.

The AP2/ERF transcription factor TOE4b regulates photoperiodic flowering and grain yield per plant in soybean.

Photoperiod-mediated flowering determines the phenological adaptability of crops including soybean (Glycine max). A genome-wide association study (GWAS) identified a new flowering time locus, Time of flowering 13 (Tof13), which defined a gene encoding an AP2/ERF transcription factor. This new transcription factor, which we named TOE4b, is localized in the nucleus. TOE4b has been selected for soybean latitude adaptability. The existing natural variant TOE4bH4 was rare in wild soybean accessions but occurred more frequently in landraces and cultivars. Notably, TOE4bH4 improved high-latitude adaptation of soybean to some extent. The gene-edited TOE4b knockout mutant exhibited earlier flowering, conversely, TOE4b overexpression delayed flowering time. TOE4b is directly bound to the promoters and gene bodies of the key flowering integration factor genes FT2a and FT5a to inhibit their transcription. Importantly, TOE4b overexpression lines in field trials not only showed late flowering but also altered plant architecture, including shorter internode length, more internodes, more branches and pod number per plant, and finally boosted grain yield per plant by 60% in Guangzhou and 87% in Shijiazhuang. Our findings therefore identified TOE4b as a pleiotropic gene to increase yield potential per plant in soybean, and these results provide a promising option for breeding a soybean variety with an idealized plant architecture that promotes high yields.

Natural variation of FKF1 controls flowering and adaptation during soybean domestication and improvement.

Soybean (Glycine max) is a major source of protein and edible oil world-wide and is cultivated in a wide range of latitudes. However, it is extremely sensitive to photoperiod, which influences flowering time, maturity, and yield, and severely limits soybean latitude adaptation. In this study, a genome-wide association study (GWAS) identified a novel locus in accessions harboring the E1 allele, called Time of flowering 8 (Tof8), which promotes flowering and enhances adaptation to high latitude in cultivated soybean. Gene functional analyses showed that Tof8 is an ortholog of Arabidopsis FKF1. We identified two FKF1 homologs in the soybean genome. Both FKF1 homologs are genetically dependent on E1 by binding to E1 promoter to activate E1 transcription, thus repressing FLOWERING LOCUS T 2a (FT2a) and FT5a transcription, which modulate flowering and maturity through the E1 pathway. We also demonstrate that the natural allele FKF1bH3 facilitated adaptation of soybean to high-latitude environments and was selected during domestication and improvement, leading to its rapid expansion in cultivated soybean. These findings provide novel insights into the roles of FKF1 in controlling flowering time and maturity in soybean and offer new means to fine-tune adaptation to high latitudes and increase grain yield.

GIGANTEA orthologs, E2 members, redundantly determine photoperiodic flowering and yield in soybean.

Soybean (Glycine max L.) is a typical photoperiod-sensitive crop, such that photoperiod determines its flowering time, maturity, grain yield, and phenological adaptability. During evolution, the soybean genome has undergone two duplication events, resulting in about 75% of all genes being represented by multiple copies, which is associated with rampant gene redundancy. Among duplicated genes, the important soybean maturity gene E2 has two homologs, E2-Like a (E2La) and E2-Like b (E2Lb), which encode orthologs of Arabidopsis GIGANTEA (GI). Although E2 was cloned a decade ago, we still know very little about its contribution to flowering time and even less about the function of its homologs. Here, we generated single and double mutants in E2, E2La, and E2Lb by genome editing and determined that E2 plays major roles in the regulation of flowering time and yield, with the two E2 homologs depending on E2 function. At high latitude regions, e2 single mutants showed earlier flowering and high grain yield. Remarkably, in terms of genetic relationship, genes from the legume-specific transcription factor family E1 were epistatic to E2. We established that E2 and E2-like proteins form homodimers or heterodimers to regulate the transcription of E1 family genes, with the homodimer exerting a greater function than the heterodimers. In addition, we established that the H3 haplotype of E2 is the ancestral allele and is mainly restricted to low latitude regions, from which the loss-of-function alleles of the H1 and H2 haplotypes were derived. Furthermore, we demonstrated that the function of the H3 allele is stronger than that of the H1 haplotype in the regulation of flowering time, which has not been shown before. Our findings provide excellent allelic combinations for classical breeding and targeted gene disruption or editing.

Expansion Dynamics of a Shell-Shaped Bose-Einstein Condensate.

We report the creation of a shell BEC in the presence of Earth's gravity with immiscible dual-species BECs of sodium and rubidium atoms. After minimizing the displacement between the centers of mass of the two BECs with a magic-wavelength optical dipole trap, the interspecies repulsive interaction ensures the formation of a closed shell of sodium atoms with its center filled by rubidium atoms. Releasing the double BEC together from the trap, we observe explosion of the filled shell accompanied by energy transfer from the inner BEC to the shell BEC. With the inner BEC removed, we obtain a hollow shell BEC that shows self-interference as a manifestation of implosion. Our results pave an alternative way for investigating many of the intriguing physics offered by shell BECs.

Performance and comparison of artificial intelligence and human experts in the detection and classification of colonic polyps.

OBJECTIVE: The main aim of this study was to analyze the performance of different artificial intelligence (AI) models in endoscopic colonic polyp detection and classification and compare them with doctors with different experience. METHODS: We searched the studies on Colonoscopy, Colonic Polyps, Artificial Intelligence, Machine Learning, and Deep Learning published before May 2020 in PubMed, EMBASE, Cochrane, and the citation index of the conference proceedings. The quality of studies was assessed using the QUADAS-2 table of diagnostic test quality evaluation criteria. The random-effects model was calculated using Meta-DISC 1.4 and RevMan 5.3. RESULTS: A total of 16 studies were included for meta-analysis. Only one study (1/16) presented externally validated results. The area under the curve (AUC) of AI group, expert group and non-expert group for detection and classification of colonic polyps were 0.940, 0.918, and 0.871, respectively. AI group had slightly lower pooled specificity than the expert group (79% vs. 86%, P < 0.05), but the pooled sensitivity was higher than the expert group (88% vs. 80%, P < 0.05). While the non-experts had less pooled specificity in polyp recognition than the experts (81% vs. 86%, P < 0.05), and higher pooled sensitivity than the experts (85% vs. 80%, P < 0.05). CONCLUSION: The performance of AI in polyp detection and classification is similar to that of human experts, with high sensitivity and moderate specificity. Different tasks may have an impact on the performance of deep learning models and human experts, especially in terms of sensitivity and specificity.

[Neuropsychological development of human immunodeficiency virus-exposed uninfected infants/young children]. / äººç±»å ç–«ç¼ºé™·ç— æ¯’æš´éœ²æœªæ„ŸæŸ“å©´å¹¼å„¿çš„ç¥žç»å¿ƒç†å‘è‚²çŠ¶å†µ.

OBJECTIVES: To investigate the level of neuropsychological development in human immunodeficiency virus (HIV)-exposed uninfected (HEU) infants/young children and the influence of maternal HIV infection on the neuropsychological development of HEU infants/young children. METHODS: A total of 141 HEU infants/young children, aged 0-18 months and born to HIV-infected mothers, who were managed in four maternal and child health care hospitals in Yunnan Province of China from June 2019 to December 2020 and met the inclusion criteria were enrolled as the HEU group. A total of 141 HIV-unexposed uninfected (HUU) infants/young children who were born to healthy mothers and managed in the same hospitals, matched at a ratio of 1:1 based on sex, age, method of birth, birth weight, and gestational age, were enrolled as controls. Griffiths Development Scales-Chinese Edition was used to assess the development in the five domains of locomotion, personal-social, hearing and language, eye-hand co-ordination, and performance (visual perception and space integration ability). A questionnaire survey was performed to collect relevant information. The multivariate logistic regression analysis was used to assess the influence of maternal HIV infection on the neuropsychological development of HEU infants/young children. RESULTS: Compared with the HUU group, the HEU group had significantly higher detection rates of retardation in the domains of hearing and language and performance (P<0.05). The multivariate logistic regression analysis showed that maternal HIV infection increased the risk of retardation in the domains of hearing and language (OR=2.661, 95%CI: 1.171-6.047, P<0.05) and performance (OR=2.321, 95%CI: 1.156-4.658, P<0.05). CONCLUSIONS: Maternal HIV infection can negatively affect the development of hearing and language and performance in HEU infants/young children, and further studies are needed to clarify related mechanisms.

Extracellular vesicles released by transforming growth factor-beta 1-preconditional mesenchymal stem cells promote recovery in mice with spinal cord injury.

Spinal cord injury (SCI) causes neuroinflammation, neuronal death, and severe axonal connections. Alleviating neuroinflammation, protecting residual cells and promoting neuronal regeneration via endogenous neural stem cells (eNSCs) represent potential strategies for SCI treatment. Extracellular vesicles (EVs) released by mesenchymal stem cells have emerged as pathological mediators and alternatives to cell-based therapies following SCI. In the present study, EVs isolated from untreated (control, C-EVs) and TGF-ß1-treated (T-EVs) mesenchymal stem cells were injected into SCI mice to compare the therapeutic effects and explore the underlying mechanisms. Our study demonstrated for the first time that the application of T-EVs markedly enhanced the proliferation and antiapoptotic ability of NSCs in vitro. The infusion of T-EVs into SCI mice increased the shift from the M1 to M2 polarization of reactive microglia, alleviated neuroinflammation, and enhanced the neuroprotection of residual cells during the acute phase. Moreover, T-EVs increased the number of eNSCs around the epicenter. Consequently, T-EVs further promoted neurite outgrowth, increased axonal regrowth and remyelination, and facilitated locomotor recovery in the chronic stage. Furthermore, the use of T-EVs in Rictor-/- SCI mice (conditional knockout of Rictor in NSCs) showed that T-EVs failed to increase the activation of eNSCs and improve neurogenesis sufficiently, which suggested that T-EVs might induce the activation of eNSCs by targeting the mTORC2/Rictor pathway. Taken together, our findings indicate the prominent role of T-EVs in the treatment of SCI, and the therapeutic efficacy of T-EVs for SCI treatment might be optimized by enhancing the activation of eNSCs via the mTORC2/Rictor signaling pathway.

A critical suppression feedback loop determines soybean photoperiod sensitivity.

Photoperiod sensitivity is crucial for soybean flowering, adaptation, and yield. In soybean, photoperiod sensitivity centers around the evening complex (EC) that regulates the transcriptional level of the core transcription factor E1, thereby regulating flowering. However, little is known about the regulation of the activity of EC. Our study identifies how E2/GIGANTEA (GI) and its homologs modulate photoperiod sensitivity through interactions with the EC. During long days, E2 interacts with the blue-light receptor flavin-binding, kelch repeat, F box 1 (FKF1), leading to the degradation of J/ELF3, an EC component. EC also suppresses E2 expression by binding to its promoter. This interplay forms a photoperiod regulatory loop, maintaining sensitivity to photoperiod. Disruption of this loop leads to losing sensitivity, affecting soybean's adaptability and yield. Understanding this loop's dynamics is vital for molecular breeding to reduce soybean's photoperiod sensitivity and develop cultivars with better adaptability and higher yields, potentially leading to the creation of photoperiod-insensitive varieties for broader agricultural applications.

Novel biomimetic mesoporous silica nanoparticle system possessing targetability and immune synergy facilitates effective solid tumor immuno-chemotherapy.

New strategies that enhance both the targetability of chemotherapy drugs and the synergistic effects of chemotherapy and immunotherapy are urgently needed for efficacious solid tumor therapy. In this study, a novel biomimetic nanoparticle system possessing the properties of tumor targeting and immune synergy was designed to meet these requirements. Mesoporous silica nanoparticles loaded with the chemotherapeutic drug doxorubicin (DOX) were coated with cell membranes modified by glycosylphosphatidylinositol (GPI)-anchored anti-HER2 single chain variable fragment (scFv) and the GPI-anchored co-stimulatory molecule CD80 (to promote solid tumor-targeted chemotherapy and cooperated immunotherapy, respectively). The impact of the nanotherapeutic system on both tumor-targeted chemotherapy and cellular immune response was investigated through in vitro and in vivo experiments. The results show that the novel biomimetic therapeutic system effectively promoted antitumor efficiency in vitro and in vivo. In addition, this therapeutic system further enhanced antitumor capacity by increasing CD8+ T cell activation and cytokine production and reducing myeloid-derived suppressor cell (MDSC) levels in tumors.

Value of Multimodal Data From Clinical and Sonographic Parameters in Predicting Recurrence of Hepatocellular Carcinoma After Curative Treatment.

OBJECTIVE: The objective of the work described here was to assess the value of the combination of pre-operative multimodal data-including clinical data, contrast-enhanced ultrasound (CEUS) information and liver stiffness measurement (LSM) based on 2-D shear wave elastography (SWE)-in predicting early (within 1 y) and late (after 1 y) recurrence of hepatocellular carcinoma (HCC) after curative treatment. METHODS: We retrospectively included 101 patients with HCC who met the Milan criteria and received curative treatment. The multimodel data from clinical parameters, LSM by 2-D SWE and CEUS enhancement patterns were collected. The association between different variables in HCC recurrence was accessed using a Cox proportional hazard model. On the basis of the independent factors of early recurrence, models with different source variables were established (Clinical Model, CEUS-Clinical Model, SWE-Clinical Model, CEUS-SWE-Clinical Model). The goodness-of-fit of models was evaluated and the performance trends of different models were calculated by time-dependent area under the curve (AUC). RESULTS: Two-dimensional SWE, CEUS enhancement patterns and clinical parameters (spleen length, multiple tumors, α-fetoprotein, albumin and prothrombin time) were independently associated with early recurrence (all p values <0.05). Multiple tumors and a decrease in albumin independently contributed to the late recurrence. The model fit of CEUS-SWE-Clinical Model was superior to other models in predicting early recurrence (all p values <0.05). The AUCs of the CEUS-Clinical Model were higher from 2 mo to 7 mo, while the SWE-Clinical Model had higher AUCs from 9 mo to 12 mo. CONCLUSION: CEUS enhancement patterns and 2-D SWE were independent predictors of HCC early recurrence as the two factors contributed to the predictive performance at different times. The multimodal model, which included diverse data in predicting early HCC recurrence, had the best goodness-of-fit.

Can monodisperse microbubble-based three-dimensional contrast-enhanced ultrasound reduce quantitative heterogeneity? An in vitro study.

BACKGROUND: Heterogeneity within the tumor may cause large heterogeneity in quantitative perfusion parameters. Three-dimensional contrast-enhanced ultrasound (3D-CEUS) can show the spatial relationship of vascular structure after post-acquisition reconstruction and monodisperse bubbles can resonate the ultrasound pulse, resulting in the increase in sensitivity of CEUS imaging. OBJECTIVES: To evaluate whether the combination of 3D-CEUS and monodisperse microbubbles could reduce the heterogeneity of quantitative CEUS. MATERIAL AND METHODS: Three in vitro perfusion models with perfusion volume ratio of 1:2:4 were set up. Both quantitative 2D-CEUS and 3D-CEUS were used to acquire peak intensity (PI) with 2 kinds of ultrasound agents. One was a new kind of monodisperse bubbles produced in this study, named Octafluoropropane-loaded cerasomal microbubbles (OC-MBs), the other was SonoVue®. The coefficient of variation (CV) was calculated to evaluate the cross-sectional variability. Pearson's correlation analysis was used to assess the correlation between weighted PIs (average of PIs of 3 different planes) and perfusion ratios. RESULTS: The average CVs of quantitative 3D-CEUS was slightly lower than that of 2D-CEUS (0.41 ±0.17 compared to 0.55 ±0.26, p = 0.3592). As for quantitative 3D-CEUS, the PI of the OC-MBs has shown better stability than that of SonoVue®, but without a significant difference (average CVs: 0.32 ±0.19 compared to 0.50 ±0.10, p = 0.0711). In the 2D-CEUS condition, the average CVs of OC-MBs group and SonoVue® group were 0.68 ±0.15 and 0.41 ±0.17 (p = 0.2747). As for 3D-CEUS condition, using OC-MBs group and SonoVue®, the r-values of the weighted PI and perfusion ratio were 0.8685 and 0.5643, respectively, while that of 2D-CEUS condition were 0.7760 and 0.3513, respectively. CONCLUSIONS: Our in vitro experiments showed that OC-MBs have the potential in acquiring more stable quantitative CEUS value, as compared to the SonoVue® in 3D-CEUS condition. The combination of 3D-CEUS and OC-MBs can reflect perfusion volume more precisely and may be a potential way to reduce quantitative heterogeneity.

Silencing long intergenic non-protein coding RNA 00987 inhibits proliferation, migration, and invasion of osteosarcoma cells by sponging miR-376a-5p to regulate FNBP1 expression.

High expression of long intergenic non-protein coding RNA 987 (LINC00987) is strongly associated with low overall survival of osteosarcoma; however, its role in osteosarcoma remains unclear. This study explored the biological function and underlying mechanism of LINC00987 in osteosarcoma. In this study, LINC00987 expression in osteosarcoma cells was analyzed using Cancer Cell Line Encyclopedia and qRT-PCR. The proliferation and migration and invasion in osteosarcoma cells were evaluated using Cell Counting Kit-8 and Transwell assays, respectively. Bioinformatic analysis was used to predict the LINC00987-bound miRNAs and miR-376a-5p-bound mRNAs. Dual-luciferase reporter assays were used to assess the interaction between miR-376a-5p, LINC00987, and forming-binding protein 1 (FNBP1). FNBP1 expression was measured by western blotting. LINC00987 was found to be upregulated in osteosarcoma cells. LINC00987 silencing suppressed proliferation, migration, and invasion of osteosarcoma cells. Additionally, miR-376a-5p expression was downregulated in osteosarcoma cells. miR-376a-5p knockdown reversed the effect of LINC00987 silencing on the biological function of osteosarcoma cell. miR-376a-5p was found to target LINC00987 and FNBP1. FNBP1protein level was increased in osteosarcoma cells; however, it was inhibited by silencing LINC00987 and enhanced by silencing miR-376a-5p. In conclusions, this study suggests LINC00987 silencing inhibits osteosarcoma cell proliferation, migration, and invasion by sponging miR-376a-5p to regulate FNBP1 expression. LINC00987 as a potential therapeutic target for osteosarcoma.

Post-exercise Effects and Long-Term Training Adaptations of Hormone Sensitive Lipase Lipolysis Induced by High-Intensity Interval Training in Adipose Tissue of Mice.

Although studies have proven that high-intensity interval training (HIIT) shows a comparable effect to moderate-intensity continuous training (MICT) on reducing body fat, especially visceral fat, the mechanism is still unclear. Since MICT consumes more fat during exercise, the mechanism of HIIT weight loss may be related to post-exercise effects, long-term adaptive changes, and hormone sensitive lipase (HSL). The objective of this study was to compare the post-effects of acute exercise, long-term adaptive changes on HSL activity, and catecholamine-induced lipolysis between HIIT and MICT. Following a 14-week high-fat diet (HFD), obese female C57Bl/6 mice were divided into acute exercise groups (one time training, sacrificed at rest and 0, 1, and 12 h after exercise, n = 49), -L groups (12-week long-term training, 12-h fasting, n = 21), and -C groups (12-week training, primary adipocytes were isolated and stimulated by catecholamine in vitro, n = 18). MICT or HIIT treadmill protocols (running distance matched) were carried out during training. Comparison of acute exercise effects by two-way ANOVA showed no time × group interaction effect, however, a significant increase in HSL-Ser563 (at 0 and 1 h) and Ser660 phosphorylation (at 0, 1, and 12 h) in inguinal (subcutaneous) fat was only observed in HIIT mice (p < 0.05 vs. rest), but not in MICT mice. The periuterine (visceral) fat HSL expression and phosphorylation of HIIT mice was similar to or lower than MICT mice. After long-term training, 12-h fasting significantly increased periuterine fat Ser563 phosphorylation in HIIT mice (p < 0.05), but there was no change in MICT mice. Under stimulation of catecholamine in vitro, isolated primary adipocytes from periuterine fat of long-term HIIT mice showed a higher Ser563 increase than that found in MICT mice (p < 0.05). The quantity of triglyceride (TG) lipid bonds (representing lipolysis level) was significantly lower after HIIT than MICT (p < 0.05). The results indicate that (1) acute HIIT can induce an increase of HSL phosphorylation in subcutaneous fat lasting at least 12 h, implying longer post-exercise lipolysis than MICT and (2) long-time HIIT has a better effect on improving catecholamine resistance of visceral adipocytes caused by a HFD, which allows fat to be mobilized more easily when stimulated.