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Jing Hu

Publications and source records attributed to Jing Hu.

5 recordsLinked to original sources
PubMed2026

Hydrogen-rich water combined with traditional Chinese medicine compound in the treatment of kidney stones: a randomized controlled prospective clinical trial.

JOURNAL/mgres/04.03/01612956-202701000-00009/figure1/v/2026-09-13T085902Z/r/image-tiff The formation and development of kidney stones are related to abnormal urine metabolism, oxidative stress and inflammation. Hydrogen-rich water has clear efficacy in antioxidant and improving inflammatory status, while Ye-Shi-Shi-Lin-Formula is a clinically effective traditional Chinese medicine compound preparation for treating kidney stones. This randomized controlled prospective clinical trial from July 2025 to March 2026 at the Seventh People's Hospital Affiliated to Shanghai University of Traditional Chinese Medicine examined the effect of hydrogen-rich water and Ye-Shi-Shi-Lin-Formula on kidney stones. The included 100 patients with kidney stones were randomly divided into blank, hydrogen-rich water, hydrogen-rich water and Chinese medicine, and Chinese medicines groups. The patients received drinking hydrogen-rich water and/or Ye-Shi-Shi-Lin-Formula daily for 12 weeks. All subjects received basic treatment following the guidelines. Imaging examination, urine metabolism testing, renal function, inflammation and oxidative stress index, blood routine and liver function are used to detect the efficacy and safety of hydrogen-rich water and Ye-Shi-Shi-Lin-Formula. Results showed that the total effective rate of kidney stone treatment in blank group, Chinese medicines group, hydrogen-rich water and Chinese medicine group and hydrogen-rich water group was 28%, 76%, 80% and 32%. The Ye-Shi-Shi-Lin-Formula can partially alleviate the oxidative stress, uric acid metabolism and urinary magnesium levels of patients with kidney stone and improve the function of renal tubules. The hydrogen-rich water therapy showed only efficacy in improving glutathione reductase but the combination of hydrogen-rich water and Ye-Shi-Shi-Lin-Formula has shown superior efficacy in improving oxidative stress and related metabolic factors of blood uric acid and urine stones, as well as in renal tubular function. The results indicate that the addition of hydrogen-rich water can improve urinary metabolism and oxidative stress status in the treatment of kidney stones with Ye-Shi-Shi-Lin-Formula. The study was registered at the International Traditional Medicine Clinical Trial Registry (Registration No. ITMCTR2025001446).

Humans↗
PubMed2025

soFusion: facilitating tissue structure identification via spatial multi-omics data fusion.

The rapid advancement of spatial multi-omics technologies has opened new avenues for dissecting tissue architecture with unprecedented resolution. However, inherent disparities across omics modalities, such as differences in biological hierarchy and resolution, pose significant challenges for integrative analysis. To address this, we present soFusion, a method for representation learning on spatial multi-omics data that enables automated identification of tissue compartmentalization. soFusion employs a graph convolutional network (GCN) to extract latent embeddings from spatial omics profiles. To simultaneously capture both cross-modality relationships and modality-specific features, we introduce a novel strategy for intra- and inter-omics feature learning. Moreover, modality-specific decoders are designed to preserve the unique information embedded in each omics type. We evaluated soFusion on multiple datasets including gene expression, protein expression, and epigenetic features. Across all benchmarks, soFusion consistently outperformed existing methods in delineating anatomical structures and identifying spatial domains with improved continuity and reduced noise. Collectively, soFusion offers an effective solution for spatial multi-omics integration, substantially enhancing the robustness of spatial domain identification.

Humans↗
PubMed2025

TRIM63 Overexpression in FISH-Negative MiTF Family Altered Renal Cell Carcinoma (MiTF RCC).

TFE3 and TFEB break-apart fluorescent in situ hybridization (FISH) assays are the "gold standard" for diagnostic confirmation of microphthalmia-associated transcription factor (MiTF) family-altered renal cell carcinoma (MiTF RCC), which includes TFE3-rearranged RCC and TFEB-altered RCC. However, FISH assays, for multiple reasons, may lead to equivocal or false-negative results, especially in cryptic fusions resulting from intrachromosomal inversions involving 5' partner genes, such as non-POU domain-containing octamer-binding protein (NONO); GRIPI-associated protein 1 (GRIPAP1); RNA-binding motif protein, X chromosome (RBMX); and RNA-binding motif protein 10 (RBM10). When FISH results are negative in cases with strong morphological suspicion of the listed tumor entities, pathologists may recommend targeted RT-PCR or panel-based RNA fusion sequencing for diagnostic confirmation. Our recent RNA in situ hybridization (RNA ISH)-based study demonstrated RNA expression of the tripartite motif containing 63 (TRIM63) to be highly enriched in TFE3-rearranged RCC and TFEB-altered RCC, including 2 FISH false-negative RCC cases harboring RBM10::TFE3 fusion. Based on these observations, we hypothesized that TRIM63 positivity could aid in diagnosing cases that are negative by conventional FISH assay but remain morphologically suspicious, representing an unmet clinical need in this area. We collected 20 RCC cases with morphological suspicion (with equivocal/indeterminate immunohistochemistry panel) of MiTF RCC, which were TRIM63 positive, negative/equivocal for TFE3/TFEB gene rearrangement by FISH, and underwent next-generation sequencing (NGS). On NGS correlation, 14 of 20 (70%) FISH-negative TRIM63-positive tumors harbored an MiTF gene rearrangement. In the remaining 6 cases, we were unable to fully ascertain the MiTF rearrangement status due to the inherent limitation of the NGS panel utilized. The cases with MiTF gene rearrangement include TFE3 rearrangement in 60% (12/20) and TFEB low-level copy gains (with an additional missense mutation in 1 case) in 10% (2/20) of samples. RBM10:TFE3 fusion was seen in 67% (8/12) of TFE3-rearranged RCC in this cohort. TRIM63 RNA ISH assay could aid in identifying cases that harbor TFE3 or TFEB rearrangement associated with false-negative or equivocal TFE3/TFEB FISH results, especially those involving gene fusions with a paracentric Xp11 inversion. Overall, employment of TRIM63 RNA ISH coupled with TFE3/TFEB FISH assays and follow-up genomic interrogation enhanced diagnostic accuracy for patients with MiTF RCC.

Carcinoma, Renal Cell↗
PubMed2025

MitoTracer facilitates the identification of informative mitochondrial mutations for precise lineage reconstruction.

Mitochondrial (MT) mutations serve as natural genetic markers for inferring clonal relationships using single cell sequencing data. However, the fundamental challenge of MT mutation-based lineage tracing is automated identification of informative MT mutations. Here, we introduced an open-source computational algorithm called "MitoTracer", which accurately identified clonally informative MT mutations and inferred evolutionary lineage from scRNA-seq or scATAC-seq samples. We benchmarked MitoTracer using the ground-truth experimental lineage sequencing data and demonstrated its superior performance over the existing methods measured by high sensitivity and specificity. MitoTracer is compatible with multiple single cell sequencing platforms. Its application to a cancer evolution dataset revealed the genes related to primary BRAF-inhibitor resistance from scRNA-seq data of BRAF-mutated cancer cells. Overall, our work provided a valuable tool for capturing real informative MT mutations and tracing the lineages among cells.

Humans↗
PubMed2023

MitoTracer facilitates the identification of informative mitochondrial mutations for precise lineage reconstruction.

Mitochondrial (MT) mutations serve as natural genetic markers for inferring clonal relationships using single cell sequencing data. However, the fundamental challenge of MT mutation-based lineage tracing is automated identification of informative MT mutations. Here, we introduced an open-source computational algorithm called "MitoTracer", which accurately identified clonally informative MT mutations and inferred evolutionary lineage from scRNA-seq or scATAC-seq samples. We benchmarked MitoTracer using the ground-truth experimental lineage sequencing data and demonstrated its superior performance over the existing methods measured by high sensitivity and specificity. MitoTracer is compatible with multiple single cell sequencing platforms. Its application to a cancer evolution dataset revealed the genes related to primary BRAF-inhibitor resistance from scRNA-seq data of BRAF-mutated cancer cells. Overall, our work provided a valuable tool for capturing real informative MT mutations and tracing the lineages among cells.

Journal Article↗