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UR

urea (Emolienta / urea, Vinas)

✓ Approved

Vinas · Small Molecule · Small Molecule

What is urea?

urea is a small molecule developed by Vinas. It is approved for therapeutic indications via topical.

Drug Profile

Brand NamesEmolienta, urea, Vinas
CompanyVinas
Drug ClassSmall Molecule
RouteTopical
StatusApproved
Sources: ClinicalTrials.gov, Vinas

Therapeutic Indications

urea is developed for 4 unique indications across 1 therapeutic area.

Therapeutic AreaConditionPhase
Skin and subcutaneous tissue disordersDermatitis allergic✓ Approved
Skin and subcutaneous tissue disordersDermatitis atopic✓ Approved
Skin and subcutaneous tissue disordersDermatitis contact✓ Approved
Skin and subcutaneous tissue disordersPsoriasis✓ Approved

Related Research Articles

PubMedJournal of hazardous materials2026-07-25

High-entropy-driven kinetic steering of urea electrooxidation enables coupled nitrite reduction for rapid urea-to-nitrogen conversion.

Yu Chunmu C, Li Xin X, Zhang Hao H, Fan Qingjuan Q et al.

The electrochemical urea oxidation reaction (UOR) is thermodynamically favorable toward N2 formation. However, achieving selective N2 production is kinetically challenged due to the underlying multistep mechanism involving bond cleavage and N-N bond formation. Herein, we report a high-entropy-driven kinetic steering strategy that accelerates the intrinsically favored "cyanate" pathway and couples it with selective NO2- reduction to achieve rapid urea-to-nitrogen conversion. A high-entropy oxide, CeMoCuFeCoOx (CMCFCO), steers UOR toward fast C-N cleavage and NO2- formation via entropy-induced site isolation. Coupled with a S-CuFe cathode in a flowing single-chamber membrane-free electrochemical cell (EC), the generated NO2- is selectively reduced to N2, preventing NO2- accumulation. Without iR compensation, CMCFCO delivers 300 mA cm-2 at 1.69 VRHE, and exhibits a pseudo-first-order rate constant of 0.068 min-1, 2.6-4.0 times higher than low-entropy oxides. S-CuFe reaches 1.48 A cm-2 at -1.3 VRHE. At 300 mA cm-2 in 1.5 M KOH + 0.33 M urea, 92.7% urea removal is achieved within 40 min with 93.8% Faradaic efficiency toward N2 products. In situ spectroscopy and DFT reveal that high-entropy-induced site isolation accelerates cyanate formation, while interfacial *N coupling on S-CuFe promotes selective N2 generation. This reaction-coupling framework reconciles kinetic accessibility with thermodynamic selectivity in UOR.

PMID 42497726
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PubMedGalen medical journal2026-07-25

Evaluation of Hemodialysis Efficacy for Serum and Salivary Clearance of Urea, Creatinine, and Uric Acid in Chronic Kidney Disease Patients : Short title: Evaluation of Hemodialysis Efficacy in CKD Patients.

Hosseini Azam A, Abbasi Farid F, Mirzaii-Dizgah Iraj I, Afshar Reza R

Chronic kidney disease (CKD) is a progressive and irreversible loss of kidney function that may progress to end-stage renal disease requiring hemodialysis. While hemodialysis is an established life-saving therapy, simple methods to assess its adequacy are needed. Saliva analysis is a non-invasive alternative to serum testing. This study evaluated changes in urea, creatinine, and uric acid levels in serum before and after hemodialysis and compared them with salivary levels to assess the adequacy of hemodialysis. A case-control study was conducted on 32 patients undergoing hemodialysis and 30 healthy controls. Blood and saliva samples were collected immediately before and after dialysis from patients and controls. Serum and salivary levels of markers were analyzed by biochemical methods. Serum and salivary levels of markers were compared between the patient group (before and after dialysis) and the control group by t-test and the diagnostic accuracy of salivary markers compared to serum markers was evaluated by the receiver-operating characteristic (ROC) curve and area under the curve (AUC). There were significant differences between the serum and salivary levels of urea, creatinine, and uric acid in patients before and after hemodialysis, and also with the control group (P0.05). There was a positive correlation between the serum and salivary levels of urea, creatinine and uric acid before hemodialysis, and creatinine after hemodialysis. The AUC for salivary urea and creatinine was 0.87 and 0.88, respectively, and the cut-off point for urea and creatinine was 55 mg/dL and 0.5 mg/dL, respectively. The ROC analysis for uric acid was not significant. This study showed that before hemodialysis, the changes in salivary urea, creatinine, and uric acid in CKD patients (in the fasting state) were similar to serum. Additionally, after hemodialysis, changes in salivary creatinine levels were similar to serum. Therefore, saliva analysis is suggested as a non-invasive alternative to serum analysis for assessment of the efficacy of hemodialysis.

PMID 42499362
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PubMedSmart molecules : open access2026-07-25

Porous two dimensional architectures for high efficiency electrocatalytic urea oxidation.

Zhu Kean K, Li Zebo Z, Chen Ruchuan R, Zhou Linai L et al.

Porous two-dimensional (2D) materials have emerged as promising electrocatalysts for the urea oxidation reaction (UOR) due to their high surface area, tunable electronic properties, and enhanced charge and mass transport. These structural advantages improve catalytic activity, selectivity, and reaction kinetics. However, challenges such as catalyst deactivation, structural instability, and limited mechanistic understanding still restrict their broader application. While previous studies have explored compositional tuning and catalytic performance, a systematic understanding of how porosity, defect engineering, and electronic structure modulation govern UOR efficiency and durability remains limited. This review comprehensively evaluates porous 2D materials for UOR, focusing on structure-activity relationships and fundamental catalytic mechanisms. Special attention is given to how pore architecture, surface defects, and electronic configurations regulate reaction pathways. Porous 2D materials are categorized into six major classes: oxides and their derivatives, hydroxides, sulfides, phosphides, carbides and nitrides, and other emerging materials. Unlike conventional reviews that primarily classify materials based on composition and performance, this work highlights the role of microstructural design in optimizing UOR electrocatalysis. By addressing existing knowledge gaps and identifying key structural parameters for catalyst optimization, this review provides a systematic framework for guiding the rational design of porous 2D materials in sustainable electrochemical energy conversion.

PMID 42500724
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PubMedGalen medical journal2026-07-25

Effect of Tamsulosin on Osteopontin Gene Expression in Preventing Ethylene Glycol-Induced Kidney Stone in Male Wistar Rats : Short title: Effect of Tamsulosin on Osteopontin Gene Expression.

Parvizrad Ramin R, Ghorbani Marghamlki Elahe E, Nikfar Somayeh S, Khalili Dermani Sara S

Tamsulosin, an α1-adrenergic receptor antagonist, has been proposed as a potential therapeutic agent against urolithiasis-induced renal damage. However, limited in vivo evidence exists regarding its renoprotective mechanisms. Forty male Wistar rats were randomly allocated into four groups (n=10/group): positive control, negative control (ethylene glycol-induced urolithiasis), prevention (tamsulosin administered simultaneously with ethylene glycol), and treatment (tamsulosin administered after model induction). Biochemical parameters including serum creatinine, urea, uric acid, calcium, and phosphorus were measured using rat-validated commercial kits (Pars Azmun, Iran). Normal ranges were defined based on published reference values. Gene expression was analyzed by qPCR using the 2^-ΔΔCt method. Study design and reporting followed the ARRIVE checklist. At day 30, the prevention group exhibited significantly lower serum creatinine (0.60 ± 0.08 mg/dL) compared to the negative control (0.98 ± 0.12 mg/dL, P0.01). Although urea levels were slightly higher in the prevention group (4.0 ± 0.7 mg/dL) versus the negative control (3.22 ± 0.6 mg/dL), the calculated BUN/creatinine ratio was significantly improved (46.7 vs. 33.0, P0.05). No significant changes were observed in serum calcium or phosphorus. Gene expression analysis showed upregulation of protective markers in the prevention group. In vivo findings on the beneficial effects of tamsulosin on the renal profile in ethylene glycol-induced urolithiasis illustrate its protective effects on the renal system through improvement of creatinine clearance and BUN/creatinine balance. This underscores its probable use as a protective therapeutic agent against renal injury of crystallization origin.

PMID 42499366
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PubMedFrontiers in immunology2026-07-25

Immune-inflammatory and metabolic signatures for osteoporosis risk stratification in primary Sjögren's syndrome: development and internal validation of an interpretable machine-learning model.

Dong Jingqi J, Zhang Jinle J, Wang Zelin Z, Liang Shufen S

Primary Sjögren's syndrome (pSS) is a systemic autoimmune disease. Osteoporosis (OP) is a common complication in patients with pSS (pSS-OP), which significantly affects their quality of life and prognosis. Currently, there is a lack of efficient and objective clinical tools for the early identification of pSS patients at high risk of osteoporosis, limiting the implementation of precise interventions. This study aims to integrate clinical indicators and immunological characteristics to develop and validate a machine learning model for predicting the risk of osteoporosis in patients with pSS, thereby facilitating early clinical identification and decision-making. Clinical data were collected from 384 patients with pSS. Lymphocyte subsets and serum cytokine levels of IL-2, IL-4, and IL-6 were measured in all participants. Missing data were handled using multiple imputation, followed by intergroup comparisons. Feature selection was performed using Lasso regression, random forest, and stepwise regression, and the intersection of these methods was used to identify the final predictors. Based on the selected features, nine machine learning models were constructed and compared, including decision tree, k-nearest neighbor, logistic regression, elastic net, random forest, support vector machine, multilayer perceptron, LightGBM, and XGBoost. Model performance was evaluated using ROC curves, calibration curves, decision curve, accuracy, F1 score, sensitivity, specificity, and other metrics. The SHAP method was applied to interpret the optimal model. Patients were divided into a pSS with OP and a pSS without OP group. Six core predictors were identified: Age, ESR, Urea, MON, Ca, and Fibrinogen. Among the nine models, the XGBoost model demonstrated the best performance. In the training set, the AUC was 0.890, and the F1 score was 0.90. In the test set, the AUC was 0.808, and the F1 score was 0.81. SHAP analysis revealed the following order of feature importance: Age, MON, ESR, Ca, Urea, and Fibrinogen. Among these, Ca contributed negatively to the model prediction, while the remaining features contributed positively. This study developed and internally validated an XGBoost machine learning model based on clinical and laboratory indicators for predicting osteoporosis risk in patients with pSS. The model demonstrated good discrimination and may assist early risk assessment.

PMID 42500666
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PubMedRSC advances2026-07-25

Carbon quantum dot modified clinochlore as a green support for the formation and stabilization of palladium nanoparticles in aqueous Suzuki-Miyaura coupling.

Gholinejad Mohammad M, Jafarpour Setare S, Sansano José M JM

A sustainable and efficient heterogeneous palladium catalyst was developed by supporting palladium nanoparticles on clinochlore as a naturally abundant clay mineral modified with carbon quantum dots (CQDs). The clinochlore-CQD support was synthesized via a straightforward hydrothermal method using citric acid and urea as the CQD precursors. The presence of CQDs provides an abundance of surface functional groups, facilitating the effective reduction and stabilization of Pd(0) from a PdCl2 precursor. Comprehensive characterization of the clinochlore-CQDs@Pd nanocomposite confirmed that the lamellar structure of the clinochlore remained intact and Pd nanoparticles homogeneously distributed without aggregation. The catalytic performance of the composite was evaluated in the Suzuki-Miyaura cross-coupling of aryl halides with arylboronic acids. The catalyst exhibited high activity toward a broad range of aryl iodides, bromides, and chlorides, delivering biaryl products in high to excellent yields under mild conditions in aqueous media. Furthermore, the key role of CQDs in enhancing palladium stabilization and catalytic efficiency was demonstrated. The catalyst was successfully recycled over several runs, with post-reaction characterization confirming its robust structural stability.

PMID 42500418
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