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insulin (Monotard MC / Novolin L / Human Monotard)

✓ Approved

Novo Nordisk A/S · INSR · 重组蛋白

什么是 insulin？

insulin 是一种重组蛋白，由Novo Nordisk A/S研发。该药已获批，用于治疗相关适应症，给药途径：Injectable (Others)、Intramuscular (IM) Injection、Subcutaneous Injection。

药物档案

商品名Monotard MC, Novolin L, Human Monotard
公司Novo Nordisk A/S
药物类别重组蛋白, 多肽类
分子靶点INSR
给药途径Injectable (Others), Intramuscular (IM) Injection, Subcutaneous Injection
状态Approved
来源： ClinicalTrials.gov, Novo Nordisk A/S

作用机制

分子靶点

insulin 作用于 1 个分子靶点：

INSRinsulin receptor (CD220, HHF5)
需要更深入的分析？Noah AI 可解释复杂机制并与同类药物比较。

治疗适应症

insulin 针对 2 个适应症，涉及 1 个治疗领域。

治疗领域疾病/病症分期
Metabolism and nutrition disordersType 1 diabetes mellitus✓ Approved
Metabolism and nutrition disordersType 2 diabetes mellitus✓ Approved

相关研究文献

PubMedNano-micro letters2026-10-26

Multi-Electron Transfer in Zinc-Based Batteries: Unraveling Redox Mechanisms Toward Next-Generation Self-Powered Technologies.

Zhou Chao C, Zhou Jiaju J, Guo Xiaojun X, Zhang Haoxiang H et al.

The rapid expansion of autonomous IoT networks and wearable electronics has intensified the demand for photo-rechargeable zinc-based batteries (PRZBBs). While realizing high overall energy conversion efficiency intrinsically relies on cathode materials capable of multi-electron transfer reactions, current literature largely treats the fundamental electrochemistry of aqueous zinc batteries and the macroscopic engineering of solar-integrated devices as isolated domains. This review bridges this critical gap, offering a unique positioning by establishing a unified analytical framework that directly links fundamental multi-electron redox mechanisms to the dynamic architectural requirements of PRZBBs. Moving beyond a conventional cataloging of material classes, we critically evaluate diverse cathode platforms, including transition metal oxides, Prussian blue analogues, organics, halogens, and sulfur. Our incremental contribution lies in decoupling how specific multi-step reaction kinetics, distinct voltage plateaus, and dominant charge carriers dictate solar cell coupling strategies, particularly concerning maximum power point matching and intermittent charging adaptability. Furthermore, we critically and systematically assess the practical bottlenecks of these chemistries, such as shuttle effects, kinetic limitations, and voltage hysteresis, that hinder scalable integration. Finally, we distill these insights into a prioritized, roadmap-oriented perspective, outlining the short- to long-term engineering and scientific milestones necessary to translate fundamental multi-electron zinc chemistry into next-generation, commercially viable self-powered technologies.

PMID 42928314
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PubMedDiseases (Basel, Switzerland)2026-10-26

Clinical Effectiveness, Safety, and Implementation of Artificial Intelligence-Assisted Insulin Management Systems in Type 1 and Type 2 Diabetes: A Systematic Review of Randomized Controlled Trials.

Rodrigues Victória Dogani VD, Catharin Virgínia Maria Cavallari Strozze VMCS, Audi Mauro M, Pereira Eliana de Souza Bastos Mazuqueli ESBM et al.

Artificial intelligence (AI) is increasingly being integrated into insulin management through decision-support systems, adaptive bolus calculators, conversational platforms, and automated insulin delivery (AID) technologies. However, the clinical effectiveness and safety of AI-assisted insulin management remain uncertain. To systematically evaluate evidence from randomized controlled trials (RCTs) investigating AI-assisted insulin management systems in individuals with type 1 or type 2 diabetes. A systematic literature review was conducted following PRISMA guidelines. PubMed/MEDLINE, Embase, and Cochrane CENTRAL were searched for RCTs evaluating AI-enabled insulin management interventions in insulin-treated individuals with diabetes. Eligible studies compared AI-based systems with standard care, clinician-guided insulin titration, conventional bolus calculators, or other AID algorithms. Outcomes included glycemic control, insulin titration, safety, and implementation-related measures. Owing to substantial heterogeneity, findings were synthesized narratively. We included seven RCTs published between 2020 and 2025. Interventions comprised clinical decision-support systems, adaptive bolus calculators, conversational AI platforms, neural-network-based artificial pancreas algorithms, and exercise-aware AID systems. AI-assisted interventions consistently demonstrated favorable safety profiles, with no increase in severe hypoglycemia, diabetic ketoacidosis, or serious adverse events. Some systems, particularly fully automated closed-loop platforms and conversational AI-guided insulin titration, showed improvements in time in range, glucose control, adherence, and insulin optimization. User acceptance and adherence emerged as important determinants of effectiveness. Current randomized evidence suggests that AI-assisted insulin management systems are safe, feasible, and capable of achieving glycemic outcomes comparable to conventional care. Although certain technologies demonstrate promising clinical benefits, the evidence base remains limited by small sample sizes, short follow-up durations, and heterogeneity across interventions. Larger, long-term randomized trials are needed to establish comparative effectiveness, optimize human-AI interaction, and support broader clinical implementation.

PMID 42930005
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PubMedBiosensors2026-10-26

Hybrid Multi-Biorecognition Laser-Scribed Graphene Platform for Electrochemical Detection of Insulin Resistance Biomarkers.

Rizalputri Lavita Nuraviana LN, Shetty Saptami Suresh SS, Martinez Mario Soto MS, Roux Eckaard Le EL et al.

Insulin resistance (IR) is a multifactorial metabolic condition that can precede type 2 diabetes, motivating integrated monitoring of complementary biomarkers associated with glucose-insulin homeostasis and adipose tissue dysfunction. Here, we present a hybrid multi-biorecognition laser-scribed graphene (LSG) electrochemical platform with four independently functionalized working electrodes for detecting glucose, insulin, adiponectin, and leptin. The platform combines glucose oxidase-mediated enzymatic sensing, a methylene-blue-labeled insulin aptamer, and antibody-based recognition for adiponectin and leptin. Each sensing channel showed concentration-dependent electrochemical responses in PBS and analyte-spiked 10% human serum. The glucose sensor retained comparable sensitivity in PBS and serum, while the insulin aptasensor and the adiponectin and leptin immunosensors remained responsive in the diluted biological matrix. A preliminary mixed-analyte study further showed that all four channels remained responsive in a common four-biomarker sample. Importantly, the four-analyte panel combines glucose and insulin, used in HOMA-IR, with adiponectin and leptin, which form the adiponectin-to-leptin ratio, demonstrating thcombines high surface area, good electrical conductivitye feasibility of integrating complementary biomarkers and distinct biosensing approaches side by side within a single multiplexed electrochemical platform, with potential for future application in early-stage insulin resistance assessment.

PMID 42930092
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PubMedJournal of medical case reports2026-10-26

High-dose regular insulin as a potential rescue therapy in severe aluminum phosphide poisoning: a case report.

Sedaghattalab Moslem M, Akbari Ghaidafeh G

Aluminum phosphide (rice tablet) can cause cardiocirculatory collapse and has negative cardiac inotropic effect. Positive inotropic effect of insulin on the cardiac myocytes is through calcium flux. Insulin increases the intramyocytes calcium concentration by increasing conductance of calcium through the L-type calcium channels and by increasing intramyocytes concentration of cyclic adenosine monophosphate. In addition to increasing the intramyocytes calcium level, insulin also enhances the responsiveness of the cardiac cells to calcium. High-dose insulin is a potential therapy for hypodynamic and hypotensive septic shock due to its positive inotropic qualities. In this paper, a critical aluminum phosphide poisoning patient (a 25-year-old Iranian young woman), presented with mixed severe metabolic acidosis and respiratory alkalosis, tachypnea, tachycardia, and hypotension. In contrast to our previous experiences that ingestion of aluminum phosphide tablets associated with multiple organ failure and severe shock in approximately all critical poisoning patients, early initiation of high-dose intravenous regular insulin for this patient prevented multiorgan dysfunction and death. Treatment with high-dose intravenous insulin associated with IV fluids, sodium bicarbonate, hydrocortisone, potassium, dextrose therapy and supportive care resolved completely signs and symptoms of patient after 3 days in ICU. High-dose intravenous regular insulin may be act as a rescue therapy for aluminum phosphide poisoning patients. While this single case suggests a potential benefit, further studies are required to confirm these findings.

PMID 42928247
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PubMedJournal of chemical information and modeling2026-10-26

SpectralMol: Spectral Graph Bisection Achieves Universal Molecular Fragment Decomposition for Drug-Like Molecule Generation.

Li Gang G, Lin Zhizhe Z, Zhou Teng T, Bai Weihua W et al.

Generating valid, diverse, and drug-like molecules remains a central challenge in computational drug discovery. A key bottleneck for fragment-based generative models is decomposition coverage: existing junction-tree methods fail on bridged bicyclic and spiro ring systems common in drug-like scaffolds. Our primary contribution is Fiedler-BFS (breadth-first search) molecular decomposition, a spectral bisection algorithm achieving 100% decomposition success on all 250,000 ZINC-250K molecules, including bridged and spiro systems where junction-tree methods fail. A decomposition ablation (5,000 molecules, 5 seeds) confirms that spectral structure drives the improvement: 91.4% vs 7.1% for random bisection. Compared to BRICS (break retrosynthetically interesting chemical substructures; a rule-based retrosynthesis method), Fiedler-BFS produces fewer fragments per molecule (2.31 vs 5.13), better suited for hierarchical generative modeling. As a secondary contribution, we instantiate the decomposition in a Tree-VAE (variational autoencoder) with classifier-free guidance over molecular properties, Inverse Multi-Quadratic MMD (maximum mean discrepancy) regularization, and gradient-based latent-space steering. Under a matched protocol in which the identical Tree-VAE is retrained while only the cut-bond set varies, Fiedler-BFS yields shorter, more learnable fragment trees than BRICS and junction-tree decomposition (validation reconstruction loss of 0.012 vs 0.048 vs 0.083). On ZINC-250K, the model achieves 100% chemical validity, 99.87% novelty, a mean QED (quantitative estimate of drug-likeness) of 0.603 (matching the ZINC-250K training mean), and an SA (synthetic accessibility score) of 2.70, confirming compatibility with a hierarchical generative pipeline for drug-like molecule generation. Property conditioning reaches only a 12.2% QED hit rate and, under robust metrics, does not outperform an unconditioned baseline; the v2 vocabulary naturally generates drug-like molecules with QED ≈ 0.60, so stronger property guidance remains an open challenge.

PMID 42929561
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PubMedOxford medical case reports2026-10-26

Probable Rabson-Mendenhall syndrome presenting with acanthosis nigricans: a case report.

Akhras Mira M, Hmaidan Mohammad M, Ghazal Rahaf R, Alebrahem Asad A et al.

Rabson-Mendenhall syndrome (RMS) is a rare autosomal recessive disorder caused by mutations in the insulin receptor gene (INSR), resulting in severe insulin resistance. We report the case of an 8-year-old boy who presented with progressive acanthosis nigricans of the neck, coarse facial features, generalized hypertrichosis, dental abnormalities, a fissured tongue, thickened nails, penile hypertrophy, and hepatomegaly. Laboratory results indicated hyperinsulinemia, severe insulin resistance and fasting hypoglycemia. Based on the clinical and laboratory findings, Rabson-Mendenhall syndrome was considered. Genetic confirmation was not performed because it was unavailable in our country. This case highlights the importance of recognizing acanthosis nigricans as a clinical marker of inherited metabolic syndromes, and the important role of dermatologists in its early recognition.

PMID 42928893
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