Drug Database
ZO

zolpidem tartrate (Stilnox CR / FK199B / Stilnoxium)

✓ Approved

Astellas Pharma · GABRA1 · Small Molecule

What is zolpidem tartrate?

zolpidem tartrate is a small molecule developed by Astellas Pharma. It is approved for therapeutic indications via oral (po).

Drug Profile

Brand NamesStilnox CR, FK199B, Stilnoxium
CompanyAstellas Pharma
Drug ClassSmall Molecule
Molecular TargetGABRA1
RouteOral (PO)
StatusApproved
Sources: ClinicalTrials.gov, Astellas Pharma

Mechanism of Action

Molecular Targets

zolpidem tartrate acts on 1 molecular target:

GABRA1gamma-aminobutyric acid type A receptor alpha1 subunit (DEE19, ECA4)
Want deeper analysis?Noah AI can explain complex mechanisms and compare to similar drugs.

Therapeutic Indications

zolpidem tartrate is developed for 1 unique indication across 1 therapeutic area.

Therapeutic AreaConditionPhase
Psychiatric disordersInsomnia✓ Approved

Related Research Articles

PubMedSmall (Weinheim an der Bergstrasse, Germany)2026-07-17

Performance Enhancement of All-Inorganic CsPbI3 Perovskite Solar Cells through Functional Additive and Buried Interface Engineering.

Cai Hengzhuo H, Lin Junfeng J, Lyu Wanyang W, Yi Lingyi L et al.

All-inorganic CsPbI3 perovskite solar cells (IPSCs) are regarded as promising candidates due to their ideal bandgap and excellent thermal stability. However, their practical application is hindered by phase instability and severe interfacial defects, which lead to performance degradation and poor durability. Here, this work proposes a low-temperature synergistic regulation strategy that combines oxamide additive with potassium tartrate interfacial modification to simultaneously optimize interface and adjust bulk crystallization process of CsPbI3 film. The incorporation of oxamide effectively suppresses iodide vacancy defects, promotes uniform crystal growth and reduces non-radiative recombination, while the buried-interface modification by potassium tartrate regulates the energy-level alignment, passivates interfacial traps and promotes carrier extraction. Benefiting from this dual regulation, the modified CsPbI3-based IPSCs achieve a power conversion efficiency of 18.89% and exhibit significantly improved environmental stability. This work provides a simple, effective and scalable approach to address the intrinsic phase instability and interfacial defect problems in CsPbI3-based IPSCs.

PMID 42464936
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PubMedNpj mental health research2026-07-17

Mendelian randomization of risk factors for premenstrual disorders.

Yang Yihui Y, Tang Bowen B, Hysaj Elgeta E, Xiang Nanyan N et al.

The causal role of established risk factors for premenstrual disorders (PMDs) remains unclear. We used Mendelian randomization (MR) to assess causality for eight known-risk factors identified through a literature review. Summary statistics for these risk factors were from genome-wide association studies (GWAS) with sample size ranging from 129,017 to 1.2 million, and for PMDs from a GWAS of 72,297 participants. Findings were validated using one-sample MR in LifeGene cohort (n = 5674-5937). In two-sample MR, genetic liability to smoking initiation (OR = 1.25 (1.10-1.43)), earlier menarche (OR = 0.94 (0.89-0.98) per year), and higher BMI (OR = 1.19 (1.05-1.34) per kg/m2) were associated with PMD risk. No causal association was indicated for anemia, childhood abuse, childhood asthma, diabetes, and endometriosis. In one-sample MR, point estimates for BMI (OR = 1.10 (0.88-1.38) per kg/m²) and earlier menarche (OR = 0.98 (0.83-1.15) per year) were directionally consistent with the two-sample MR findings, but the confidence intervals included null effects. However, a null association was observed for smoking (OR = 0.94 (0.77-1.16)). The two-sample MR supports causal role of earlier menarche, higher BMI, and smoking in risk of PMDs. The lack of replication in one-sample MR highlights the need for triangulating evidence from future well-powered and methodologically comparable studies to strengthen these findings.

PMID 42463960
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PubMedInternational journal of colorectal disease2026-07-17

Evaluating the usefulness of 18F-FDG PET/MR in rectal cancer staging: a prospective comparison with histopathological findings.

Maksim Rafał R, Hempel Dominika D, Mojsak Małgorzata M, Śliwowska-Burzyńska Justyna J et al.

Accurate preoperative staging of rectal cancer (RC) is essential for treatment planning. MRI is the standard for local assessment but has limitations in evaluating nodal involvement and tumor deposits. Hybrid PET/MR combines morphological and metabolic imaging and may improve staging accuracy. This study assessed PET/MR performance in RC and regional lymph nodes staging compared with histopathology. Sixteen patients with biopsy-proven rectal cancer underwent PET/MR with ^18F-FDG. Tumor size, T stage, nodal status, and tumor deposits were evaluated using multiparametric MR sequences (T1, T2, diffusion-weighted, contrast-enhanced) combined with PET. Imaging findings were compared to histopathological results. Diagnostic performance metrics, including accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were calculated with corresponding 95% confidence intervals. PET/MR accurately staged the primary tumor in 81.25% of cases (95% CI: 57.0-93.4), with sensitivity of 100%, specificity of 50.0%, PPV of 76.9%, and NPV of 100% for advanced T-stage assessment. Three cT3 tumors were downstaged to pT2; no tumors were upstaged. For nodal staging based on ESGAR criteria, diagnostic accuracy was 75.0% (95% CI: 50.5-89.8), with sensitivity of 57.1%, specificity of 88.9%, PPV of 80.0%, and NPV of 72.7%. Tumor deposits were not detected on imaging but were present in four specimens. Incidental findings included a biopsy-confirmed breast adenocarcinoma and one benign thyroid lesion. 18F-FDG PET/MR shows potential for accurate assessment of the primary tumor and reliable exclusion of advanced T-stage disease. However, its performance in nodal staging and tumor deposit detection remains limited. Given the small sample size and potential confounding from preoperative radiotherapy, these findings should be considered hypothesis-generating and require validation in larger prospective cohorts.

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PubMedInternational journal of endocrinology2026-07-17

Causal Associations of Heparin-Binding Growth and Differentiation Factors With Thyroid Cancer: A Two-Sample Mendelian Randomization Study.

Zhang Xiwei X, Yang Dongqiang D, Liu Yan Y, Wu Yanzhao Y et al.

Heparin-binding growth and differentiation factors (GDFs) play roles in various cellular processes and are potential contributors to thyroid cancer. Although population-based studies have documented associations between heparin-binding GDFs and thyroid cancer, their causal relationships remain unclear. A two-sample Mendelian randomization (MR) analysis was conducted using published genome-wide association studies (GWASs) data. The primary method for estimating causal effects was the inverse-variance weighted (IVW) approach, supplemented by multiple sensitivity analyses including weighted median, MR-Egger, and MR-PRESSO. Heterogeneity and outlier effects were systematically evaluated. Additionally, key MR findings were validated at the transcriptomic level using differential expression analysis of data from the Cancer Genome Atlas (TCGA). The IVW method revealed significant causal relationships between midkine levels (OR = 1.2099, 95% CI: 1.013-1.445, p = 0.0355) and IGF2 (OR = 0.7496, 95% CI: 0.6056-0.9279, p = 0.0081) with thyroid cancer and between heparin-binding EGF-like growth factor and malignant thyroid neoplasms (OR = 0.8821, 95% CI: 0.7873-0.9882, p = 0.0304). Heterogeneity was identified in the association between FGF1 and malignant thyroid neoplasms (Q = 20.725, p = 0.036). Neither MR-Egger analysis nor the MR-PRESSO global test found evidence of horizontal pleiotropy in the association between heparin-binding GDFs and thyroid cancer. The robustness of these findings was supported by sensitivity analyses, and transcriptomic analysis of TCGA data further revealed that midkine (MDK was significantly upregulated in thyroid tumor tissues. Genetically predicted midkine levels and IGF2 were associated with thyroid cancer, and heparin-binding EGF-like growth factor was associated with malignant thyroid neoplasms. Future studies are needed to validate these findings.

PMID 42466099
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PubMedFrontiers in medicine2026-07-17

Exploring potential associations between blood metabolites and cirrhosis risk: a Mendelian randomization and LC-MS/MS analysis.

Lv Duoduo D, Han Ning N, Tang Hong H

The development of cirrhosis is closely intertwined with metabolic processes. No previous studies have reported a clear causal relationship between cirrhosis and metabolic processes. Thus, this study aimed to explore the potential associations between blood metabolites and cirrhosis using Mendelian randomization (MR) combined with targeted metabolomics analysis. A two-sample MR analysis was conducted using genome-wide association study data to evaluate the associations of circulating metabolites with cirrhosis. Statistical evaluations employed inverse variance-weighted models, MR-Egger regression, and sensitivity tests addressing pleiotropy and heterogeneity. In addition, blood samples were collected from 10 patients with liver cirrhosis and 10 healthy controls. Blood amino acid concentrations were measured using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to provide preliminary clinical evidence supporting the MR-derived candidate metabolites. The MR analysis found that increases in 11 metabolites/metabolic ratios were associated with elevated risks of liver cirrhosis, whereas increases in the remaining 3 metabolites were related to the prevention of the occurrence of liver cirrhosis. Among these candidates, genetically predicted higher glutamine degradant levels were associated with a lower risk of cirrhosis (OR = 0.877, 95% CI: 0.784-0.981, p = 0.022). Pathway analysis further suggested that arginine biosynthesis, proline metabolism, and nitrogen metabolism may be involved in metabolic alterations related to cirrhosis. The LC-MS/MS analysis showed lower glutamate and glutathione levels in patients with cirrhosis than in controls, providing preliminary support for altered glutamine-related metabolism in cirrhosis. This study provides suggestive MR evidence linking specific circulating metabolites to cirrhosis risk. In particular, glutamine-related metabolic alterations may be associated with susceptibility to cirrhosis. These findings provide exploratory insights into metabolite-related pathways that may contribute to cirrhosis development.

PMID 42465103
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PubMedmedRxiv : the preprint server for health sciences2026-07-17

Recalibrating Mendelian randomization under winner's curse, sample structure and polygenicity.

Yang Yihe Y, Lin Zhaotong Z, Xue Haoran H, Zhu Xiaofeng X

Recently, Hu et al. (2024) conducted a benchmarking study showing that most existing Mendelian randomization (MR) methods exhibit substantial bias and inflated type-I error rates in real data. They attributed these failures to two largely neglected sources of bias: winner's curse and polygenicity-induced bias. Although a few methods have been developed to address one or both of these issues, existing approaches either do not fully account for both biases or are restricted to the univariable setting. In this paper, we propose a multivariable Rao-Blackwellization that corrects winner's curse while accounting for polygenicity and sample structure in a unified framework. Unlike univariable Rao-Blackwellization, where instrument selection yields a truncated normal statistic amenable to a Mills-ratio correction, multivariable Rao-Blackwellization conditions on a noncentral χ 2 statistic, for which no analogous correction is available. We derive closed-form conditional moments under this instrument selection model and use them to construct bias-corrected summary statistics that can be integrated into a wide range of existing MR methods. Simulations and real data analyses show that, when combined with methods such as MR-cML and MR-BEE, the proposed correction substantially improves type-I error control and yields more robust inference.

PMID 42465877
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