Biomedical subjects

Hao Shi

Publications and source records attributed to Hao Shi.

5 recordsLinked to original sources

PubMed2026

Natural deep eutectic solvent in situ formation-based extraction method coupled to high-performance anion-exchange chromatography with pulsed amperometric detection for multiclass carbohydrates in hot pot bases.

A novel method was developed for the simultaneous extraction of fourteen multiclass carbohydrates from high-fat foods via the in situ formation of deep eutectic adducts from analytes and acetate ions. Different natural deep eutectic solvents (NADESs) composed of fructose and organic acids were tested as extraction solvents. A model NADES formulated with sodium acetate and fructose was characterized using Fourier transform infrared (FTIR) spectroscopy and hydrogen nuclear magnetic resonance (1H-NMR) spectroscopy. The critical extraction parameters were systematically optimized using multi-response surface methodology (MRSM) with a central composite design (CCD). The extract was analyzed using high-performance anion-exchange chromatography coupled with pulsed amperometric detection (HPAEC-PAD) using a sodium hydroxide-sodium acetate eluent, which did not require organic solvents. This approach exhibited good linearity over the concentration range of 0.02-10 mg L-1, with correlation coefficients (r) ranging from 0.9994 to 0.9999. The limits of detection and quantification were in the ranges of 0.06-0.42 mg kg-1 and 0.19-1.3 mg kg-1, respectively, which were significantly lower than those of liquid chromatography (LC). The protocol was successfully applied to the determination of fourteen carbohydrates in forty-five hotpot seasoning samples. The recoveries ranged from 86.3% to 104.1%, with relative standard deviations (RSDs) of 0.9-7.1%. By integrating multiple techniques, this strategy simplifies operations, shortens extraction time, and achieves baseline separation of three carbohydrate classes that exhibit poor resolution using a conventional LC method. This study describes an efficient procedure for the simultaneous determination of multiple trace-level carbohydrates in complex samples using HPAEC-PAD.

Journal Article↗

PubMed2026

Targeting Regnase-1 in B7-H3-CAR T cells reprograms the tumor microenvironment and enhances antitumor efficacy for osteosarcoma.

The microenvironment in solid tumors represents an immunosuppressive therapeutic barrier to CAR T cell therapy, and it is currently unknown whether it can be reshaped by the deletion of negative regulators in CAR T cells. To address this knowledge gap, we evaluated the intrinsic and extrinsic effects of deleting the negative regulator Regnase-1 (Reg-1) in B7-H3-CAR T cells for the immunotherapy of osteosarcoma. Reg-1 knockout (KO) improved the antitumor activity of human and murine B7-H3-CAR T cells in vivo. In immune-competent models, Reg-1 KO also endowed murine B7-H3-CAR T cells with the ability to create a proinflammatory landscape characterized by an influx of interferon gamma (IFN-γ)-producing endogenous T cells and natural killer (NK) cells and a reduction of inhibitory myeloid cells, including M2-like macrophages. Thus, deleting Reg-1 has cell- and non-cell-autonomous benefits, nominating Reg-1 KO B7-H3-CAR T cells as a promising cell product for early-phase clinical testing in patients with solid tumors.

Animals↗

PubMed2026

Spatially resolved multi-omics analysis of indigenous Bacillus-fortified high-temperature Daqu.

Layer-dependent patterns associated with indigenous Bacillus fortification on high-temperature Daqu remain unclear. Here, six indigenous functional Bacillus strains were combined to fortify Daqu at three inoculation levels (QH4, QH5, QH6), with non-fortified as the control (CK). Upper, middle, and lower shelf-layer samples were profiled by physicochemical measurements, volatilomics, organic acid analysis, untargeted metabolomics, 16S/ITS amplicon sequencing, and metagenomics. PERMANOVA showed significant effects of treatment, spatial layer, and their interaction on physicochemical, volatile, bacterial, and fungal profiles (P = 0.001). Among the three inoculation levels, QH5 showed the most balanced performance: QH5_M exhibited the highest observed mean peak temperature (63.3 °C; +4.5 °C relative to CK_M), and its group-mean temperature remained ≥ 60 °C for seven consecutive days. Multi-omics analyses indicated coordinated, non-linear, and layer-dependent differences associated with indigenous Bacillus fortification, with QH5_M showing the most pronounced combined thermal, pyrazine, substrate, microbial, and predicted functional profile. These findings indicate that moderate indigenous Bacillus fortification was associated with distinct layer-dependent thermal and flavor profiles and coordinated microbial, metabolic, and predicted functional differences.

Bacillus↗

PubMed2025

KAT6A and KAT7 Histone Acetyltransferase Complexes Are Molecular Dependencies and Therapeutic Targets in NUP98-Rearranged Acute Myeloid Leukemia.

UNLABELLED: NUP98 fusion oncoproteins (FO) are a hallmark of childhood acute myeloid leukemia. NUP98 FOs drive leukemogenesis through phase-separated condensate formation and maintenance of an active chromatin landscape at stem cell-associated genes in cooperation with epigenetic regulators. In this study, we show that MYST family histone acetyltransferase (HAT) complex proteins, including KAT6A/MOZ, KAT7/HBO1, and the common KAT6A/7 complex subunit BRPF1, associate with NUP98 FOs on chromatin and within condensates. MYST HATs are molecular dependencies in NUP98-rearranged (NUP98-r) leukemia, and genetic inactivation or pharmacologic inhibition of KAT6A and KAT7 impairs NUP98-r cell fitness. KAT6A/7 inhibition decreased global H3K23ac levels, displaced NUP98::HOXA9 from chromatin at the Meis1 locus, and led to myeloid cell differentiation. Additionally, KAT6A/7 inhibition decreased leukemic burden in multiple NUP98-r leukemia xenograft mouse models, synergized with menin inhibitor treatment, and was efficacious in menin inhibitor-resistant cells. In summary, we show that MYST family HATs are therapeutically actionable dependencies in NUP98-r acute myeloid leukemia. SIGNIFICANCE: KAT6A and KAT7 associate with NUP98 FOs to drive leukemogenesis. Inhibition of their HAT activity is an effective therapeutic strategy in NUP98-r leukemias, including those resistant to menin inhibition. Moreover, combined KAT6A/7 and menin inhibition is synergistic, supporting clinical translation to improve outcomes for NUP98 FO-driven leukemias.

Humans↗

PubMed2025

Development and validation of a deep learning model based on cascade mask regional convolutional neural network to noninvasively and accurately identify human round spermatids.

INTRODUCTION: The difficulty of identifying human round spermatids (hRSs) has impeded applications of the human round spermatid injection (ROSI) technique. RSs can be accurately screened through flow cytometric analysis utilizing the Hoechst fluorescence profile reflecting DNA, but this method is not suitable for isolating hRSs due to the toxicity associated with Hoechst staining. OBJECTIVE: To evaluate the capacity of a deep learning model grounded in a cascade mask region-based convolutional neural network (R-CNN) for the noninvasive and accurate identification of hRSs. METHODS: In this study, we presented the development and validation of a deep learning model for identifying hRSs through the analysis of 3457 optical light microscope images of sorted hRSs obtained via flow cytometric analysis. The model's accuracy and specificity were evaluated by calculating the mean average precision (mAP). Furthermore, a double-blind experiment was conducted to access the reliability of the proposed model in accurately identifying hRSs. It detected the expression of protamine (PRM1) and/or peanut lectin (PNA), which are established markers for RSs. RESULTS: Our deep learning-based model demonstrated a high precision, achieving a mAP of over 0.80 for isolating hRSs in test datasets. The expression of PRM1 and/or PNA was observed in all cells noninvasively selected by our AI model during an independent double-blind test. This phenomenon confirmed the accuracy and effectiveness of the proposed model. The model's capability for noninvasive and accurate isolation of hRSs among spermatogenic cells highlighted its robustness and generalizability for clinical applications. CONCLUSION: The deep learning AI model based on a cascade R-CNN has the ability to accurately identify hRSs among spermatogenic cells. The application of this noninvasive method, which requires no additional procedures in clinical practice, is able to facilitate the widespread implementation of ROSI technique. Therefore, it can provide patients with spermatogenic arrest the opportunity to become biological fathers.

Humans↗