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SH-U-454

✓ Approved

Bayer AG · 小分子 · 小分子

什么是 SH-U-454？

SH-U-454 是一种小分子，由Bayer AG研发。该药已获批，用于治疗相关适应症，给药途径：Injectable (Others)、Intravenous (IV)。

药物档案

公司Bayer AG
药物类别小分子, 影像药物
给药途径Injectable (Others), Intravenous (IV)
状态Approved
来源： ClinicalTrials.gov, Bayer AG

治疗适应症

SH-U-454 针对 1 个适应症，涉及 1 个治疗领域。

治疗领域疾病/病症分期
Cardiac disordersArteriosclerosis coronary artery✓ Approved

相关研究文献

PubMedGeneral physiology and biophysics2026-09-10

Bardoxolone methyl induces mitochondrial dysfunction, activation of the cytosolic stress response, and increased chaperone capacity in SH-SY5Y cells. Focus on mitochondrial protease LONP1.

Hudak Lubos L, Evinova Andrea A, Liskova Monika M, Guzikova Jaroslava J et al.

Our work aimed to study the impact of bardoxolone methyl, 2-cyano-3, 12-dioxooleana-1,9(11)-dien-28-oic acid methyl ester (CDDO-Me), on mitochondrial function and morphology in SH-SY5Y cells, molecular responses, with a focus on the expression of proteins of mitochondriaspecific unfolded protein response (mtUPR), the endoplasmic reticulum-specific UPR (UPRER), and the cytosolic stress response. Treatment of SH-SY5Y cells with CDDO-Me is associated with decreased relative cell survival associated with gasdermin E cleavage, compatible with pyroptotic cell death features. Treatment of SH-SY5Y cells with CDDO-Me results in decreased ROUTINE respiration, maximal respiration, succinate-driven maximal respiration, ATP-coupled respiration, and spare respiratory capacity. We have not observed significant changes in the expression of proteins that play important roles in both mtUPR (LONP1) and UPRER (HRD1 and SEL1L), whereas expression of cytosolic chaperone HSP70 was significantly increased in response to CDDO-Me. In addition, we have observed increased expression of mitochondrial chaperones HSP60 and GRP75 as well as ER chaperone GRP78. Finally, we have observed the formation of donut-like mitochondria induced by CDDO-Me. Our results, together with previously published data, indicate that mitochondrial dysfunction, activation of cytosolic stress response, and an increase in chaperone capacity elicited by CDDO-Me could be attributed to CDDO-Me's ability to inhibit LONP1 protease.

PMID 42717783
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PubMedJournal of food science2026-09-10

Influence of a Thermostable Fungal Xylanase Combined With Multi-Enzyme Complexes on the Structure, Physicochemical, and Functional Properties of Dietary Fiber From Hawthorn Pomace.

Sun Ying Y, Huo Chunyan C, Teng Chao C, Qiu Xueyu X et al.

Effects of xylanase (XynA) in combination with various fibrolytic enzymes on the extraction of soluble dietary fiber (SDF) from hawthorn pomace and on the modification of dietary fiber (DF) were investigated. A high-yield fungal strain (Thermomyces lanugiosus Q231) producing a thermostable xylanase (XynA) was screened, and the purified enzyme exhibited a specific activity of 29,470.70 U/mg. Biochemical characterization revealed that XynA exhibited excellent thermal and pH stability, with broad pH adaptability (6.0-8.5) and more than 60% residual activity below 70°C. Notably, at 65°C, the enzyme retained over 50% of its activity even after 500 min of incubation. The highest SDF yield (14.33%) was achieved using a multi-enzyme system containing 60 U/mL XynA, 60 U/mL cellulase, and 80 U/mL β-glucanase. Additionally, XynA and this enzyme system were employed to modify hawthorn pomace dietary fiber (HDF) to investigate the relationship between structural changes and functional properties. Structural analyses revealed that enzymatic treatment increased fiber crystallinity and generated a porous network. Furthermore, XynA-modified HDF exhibited significantly enhanced water-holding and oil-holding capacities, even surpassing the multi-enzyme treatment. This enzymatic modification with XynA and multi-enzymes markedly improved both the glucose adsorption capacity (GAC) and nitrite ion adsorption capacity (NIAC). These results demonstrate that XynA and the combined enzyme system can effectively increase SDF yield while improving the functional properties of HDF, highlighting their potential for developing high-value dietary fibers.

PMID 42719998
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PubMedSoft matter2026-09-10

U-Net++ based segmentation of textures across the CrB-CrE phase transition.

Osiecka-Drewniak Natalia N, Juszyńska-Gałązka Ewa E

Machine learning methods are currently widely employed for the classification and analysis of liquid crystal textures. In this work, we utilize the U-Net++ architecture to distinguish between textures corresponding to the crystalline B phase and the crystalline E phase. Both phases belong to the group of soft crystal phases and exhibit subtle morphological differences that make their identification challenging. For training purposes, texture datasets of both phases were combined into composite images, where regions of crystal B textures were embedded within crystal E backgrounds in the form of circular and rectangular patterns. This approach enabled the model to learn spatial features and phase boundaries more effectively. As a result of the analysis, we obtained pixel-wise probability maps and corresponding binary segmentation masks distinguishing the CrB and CrE phases. The proposed method demonstrates that deep learning may be useful for accurate and spatially resolved identification of liquid crystal phases. Moreover, this approach may provide a valuable tool for the quantitative determination of phase fractions, particularly within the very narrow temperature range of the CrB-CrE transition. Such quantitative analysis may be helpful in monitoring subtle texture changes occurring during phase transitions between soft crystal phases.

PMID 42719938
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PubMedFrontiers in neurology2026-09-10

Mortality patterns related to stroke and dementia among older adults in the U. S.: a CDC WONDER analysis from 1999 to 2024.

Saghir Maryam M, Saghir Eshal E, Khalid Maliha M, Umar Muhammad M et al.

Blood flow impairment due to stroke substantially causes neuronal loss, ultimately leading to cognitive decline. Dementia is a progressive neurocognitive disorder that represents a major public health challenge worldwide. We analyzed stroke and dementia related mortality trends among older adults using the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) database from 1999 to 2024. Age-Adjusted Mortality Rates (AAMRs) per 100,000 were calculated and categorized by demographics and region. Joinpoint regression was used to estimate Annual Percent Change (APC) and Average Annual Percent Change (AAPC). A total of 965,793 deaths due to stroke and dementia among older adults aged ≥65 years were recorded. Among the subgroups of dementia, unspecified dementia reported the greatest mortality. The AAMR observed a steep incline from 69.34 in 1999 to 99.25 in 2024. Older females observed higher overall AAMR than older males. Racially, Non-Hispanic Black population had the highest overall AAMR. Regionally, the highest overall AAMR was recorded by the Southern U. S. Despite COVID-19, the post pandemic era observed increasing mortality. Our cohort exhibited a rise in mortality rates among elderly with stroke and dementia, underscoring the need for preventive strategies, and targeted interventions in vulnerable populations and regions.

PMID 42719173
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PubMedEpidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil2026-09-10

Hepatitis A among people experiencing homelessness: a case series, Curitiba, Paraná State, Brazil, 2023-2024.

Silva Janilza Silveira JS, de Carvalho Renata Barbosa Vilaça Marques RBVM, de Oliveira Alcides Souto AS, Dos Santos Diego Spinoza DS et al.

To describe hepatitis A cases among people experiencing homelessness in Curitiba, Paraná State, Brazil, in 2023-2024. This case series included people experiencing homelessness who were reported with hepatitis A in the Notifiable Diseases Information System between November 1, 2023, and May 29, 2024, in Curitiba. This population was identified by reviewing electronic medical records and the registry database of the Consultório na Rua [Street Outreach Clinic] team. Sociodemographic, clinical, and laboratory variables were extracted. Of 281 reported cases, 18 (6.4%) occurred among individuals experiencing homelessness; 16 were male. The mean age was 31±7 years. Regarding substance use in this population, 17 individuals reported crack cocaine use and 14 reported alcohol use. Mean aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels were 1,290.94 (±1,144.82) U/L and 1,558.13 (±1,050.00) U/L, respectively. The mean total bilirubin level at clinical presentation was 5.29 (±3.59) mg/dL, and jaundice was present in 55.6% of cases. Two deaths were recorded among the 18 cases in individuals experiencing homelessness (mortality: 11.1%), compared with three deaths among the remaining 263 reported cases (mortality: 1.1%). Symptoms of acute liver failure were observed in hepatitis A cases among people experiencing homelessness, all of whom required hospitalization; deaths were also reported.

PMID 42718314
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PubMedNPJ digital medicine2026-09-10

PREDICT-GBM: A multicenter platform advancing personalized glioblastoma radiotherapy planning.

Zimmer Lucas L, Weidner Jonas J, Balcerak Michal M, Kofler Florian F et al.

Glioblastoma recurrence is largely driven by diffuse infiltration beyond radiologically visible margins, yet current radiotherapy guidelines rely on uniform margin expansions that ignore patient-specific biology and anatomy. While computational models promise to map this invisible growth and guide personalized planning, their clinical translation is hindered by a lack of standardized benchmarking and reproducible validation. To bridge this gap, we present PREDICT-GBM, an open-source platform integrating a curated, longitudinal, multi-center dataset of 243 patients with a standardized evaluation pipeline. We benchmark a novel U-Net-based recurrence prediction model against state-of-the-art biophysical and data-driven methods. Under iso-volumetric constraints, both biophysical and deep-learning approaches achieved modest but statistically significant gains in geometric coverage of future recurrence over guideline-based plans. On the combined cohort, our U-Net achieved the highest mean coverage of enhancing recurrence (79.37 ± 2.08%), surpassing guideline-based plans (paired Wilcoxon signed-rank test, Benjamini-Hochberg adjusted p = 2.9 × 10-5). The biophysical model GliODIL reached 78.91 ± 2.08% (p = 1.0 × 10-3), validating the platform's ability to compare diverse modeling paradigms. By providing a reproducible ecosystem for model training and validation, PREDICT-GBM addresses a major bottleneck toward personalized, computationally guided radiotherapy. The platform, models, and data are openly available at github.com/BrainLesion/PredictGBM .

PMID 42717239
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