Test Of Model Research Articles

A comprehensive comparison of goodness-of-fit tests for logistic regression models

A comprehensive comparison of goodness-of-fit tests for logistic regression models

Pasteurella multocida infection induces blood–brain barrier disruption by decreasing tight junctions and adherens junctions between neighbored brain microvascular endothelial cells

Meningitis induced by Pasteurella multocida has been substantially described in clinical practice in both human and veterinary medicine, but the underlying mechanisms have not been previously reported. In this study, we investigated the influence of P. multocida infection on the permeability of the blood–brain barrier (BBB) using different models. Our in vivo tests in a mouse model and in vitro tests using human brain microvascular endothelial cell (hBMEC) model showed that P. multocida infection increased murine BBB permeability in mice and hBMEC monolayer permeability. Furthermore, we observed that P. multocida infection resulted in decreased expression of tight junctions (ZO1, claudin-5, occludin) and adherens junctions (E-cadherin) between neighboring hBMECs. Subsequent experiments revealed that P. multocida infection promoted the activation of hypoxia inducible factor-1α (HIF-1α)/vascular endothelial growth factor A (VEGFA) signaling and NF-κB signaling, and suppressed the HIF-1α/VEGFA significantly remitted the decrease in ZO1/E-cadherin induced by P. multocida infection (P < 0.001). NF-κB signaling was found to contribute to the production of chemokines such as TNF-1α, IL-β, and IL-6. Additionally, transmission electron microscopy revealed that paracellular migration might be the strategy employed by P. multocida to cross the BBB. This study provides the first evidence of the migration strategy used by P. multocida to traverse the mammalian BBB. The data presented herein will contribute to a better understanding of the pathogenesis of the zoonotic pathogen P. multocida.

Validating instructional practice scale for university instructors in Ethiopia

Background Measurement is essential for methods of instruction to be successful. Having an instrument that is reliable and validated in the given setting is vital. The primary goal of this research project is to validate the instructional practice scale (IPS) for university instructors in the Ethiopian context. Methods By implementing a cross-sectional descriptive survey research design, 1,254 participants across four public universities – Arbaminch, Dilla, Wachamo, and Jinka representing the first, second, third, and fourth generations, respectively were randomly selected and participated. The data was split in half and underwent an exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Results The three components of the EFA were alternately filled with seventeen items that satisfied certain standards, had a loading value of &gt; .5, and a Cronbach alpha of ≥ .874. The factors identified in the EFA have been confirmed to be the thirteen items with loading, Cronbach alpha, Raykov’s rho coefficient (rho_A), composite reliability (CR) value of &gt;.7, and Average Variance Explained (AVE) value of &gt; .5. Tests of measurement and structural models showed a good fit. The Fornell-Larcker criterion, which is employed in discriminant validity analysis, demonstrates that the square root of the AVE for each construct is higher than the correlation it exhibits with other constructs. The correlations’ heterotrait–monotrait (HTMT) ratio is getting close to zero, and there isn’t one in the confidence interval at the.05 significance level. Both guaranteed strong discriminant validity. Conclusion For university instructors, the 13 items generally have powerful psychometric properties. The three subsections of the instruction practice scale—planning (4 indicators), delivering (4 indicators), and assessment (5 indicators) — are meant to measure the instructional practice effectively. Implications of the findings were further discussed.

Deep learning-based scoring method of the three-chamber social behaviour test in a mouse model of alcohol intoxication. A comparative analysis of DeepLabCut, commercial automatic tracking and manual scoring

BackgroundAlcohol consumption and withdrawal alter social behaviour in humans in a sex-dependent manner. The three-chamber test is a widely used paradigm to assess rodents' social behaviour, including sociability and social novelty. Automatic tracking systems are commonly used to score time spent with conspecifics, despite failing to score direct interaction time with conspecifics rather than time in the nearby zone. Thereby, the automatically scored results are usually inaccurate and need manual corrections. New methodNew advances in artificial intelligence (AI) have been used recently to analyze complex behaviours. DeepLabCat is a pose-estimation toolkit that allows the tracking of animal body parts. Thus, we used DeepLabCut, to introduce a scoring model of the three-chamber test to investigate alcohol withdrawal effects on social behaviour in mice considering sex and withdrawal periods. We have compared the results of two automatic pose estimation methods: automatic tracking (AnyMaze) and DeepLabCut considering the manual scoring method, the current gold standard. ResultsWe have found that the automatic tracking method (AnyMaze) has failed to detect the significance of social deficits in female mice during acute withdrawal. However, tracking the animal's nose using DeepLabCut showed a significant social deficit in agreement with manual scoring. Interestingly, this social deficit was shown only in females during acute and recovered by the protracted withdrawal. DLC and manually scored results showed a higher Spearman correlation coefficient and a lower bias in the Bland-Altman analysis. Conclusionour approach helps improve the accuracy of scoring the three-chamber test while outperforming commercial automatic tracking systems.

Isolation of Anti-Prion Compounds from Curcuma phaeocaulis Valeton Extract.

Prion diseases, known as a group of fatal neurodegenerative disorders caused by prions, remain incurable despite extensive research efforts. In a recent study, crude extract from Curcuma phaeocaulis Valeton (Cp) showed promising anti-prion efficacy in in vitro and in vivo models, prompting further investigation into their active compounds. We endeavored to identify the chemical constituents of the Cp extract and discover potential anti-prion agents. With the use of centrifugal partition chromatography (CPC), major constituents were isolated from the n-hexane (HX) fraction of the extract in a single step. Spectroscopic analysis confirmed the presence of curcumenone, curcumenol, and furanodienone. Subsequent efficacy testing in a cell culture model of prion disease identified curcumenol and furanodienone as active compounds. This study underscores the potential of natural products in the search for effective treatments against prion diseases.

Large animal model species in pluripotent stem cell therapy research and development for retinal diseases: a systematic review.

Retinal cell therapy modalities, in the category of advanced therapy medicinal products (ATMPs), are being developed to target several retinal diseases. Testing in large animal models (LAMs) is a crucial step in translating retinal ATMPs into clinical practice. However, challenges including budgetary and infrastructure constraints can hinder LAM research design and execution. Here, to facilitate the comparison of the various LAMs in pluripotent retinal cell therapy research, we aimed to systematically evaluate the species distribution, reported scientific utility, and methodology of a range of LAMs. A systematic search using the words retina, stem cell, transplantation, large animal, pig, rabbit, dog, and nonhuman primate was conducted in the PubMed, Embase, Science Direct and GoogleScholar databases in February 2023. We included 22 studies involving pluripotent stem cells (induced pluripotent stem cells or human embryonic stem cells) in LAMs, including non-human primates (NHP), pigs, dogs, and rabbits. Nearly half of the studies utilized wild-type animal models. In other studies, retinal degeneration features were simulated via laser, chemical, or genetic insult. Transplants were delivered subretinally, either as cell suspensions or pre-formed monolayers (with or without biodegradable scaffolding). The transplanted cells dose per eye varied widely (40,000 - 4,000,000 per dose). Cells were delivered via vitrectomy surgery in 15 studies and by an "ab externo" approach in one study. Structural outcomes were assessed using confocal scanning laser ophthalmoscopy imaging. Functional outcomes included multifocal electroretinogram and, in one case, a measure of visual acuity. Generally, cell suspension transplants exhibited low intraretinal incorporation, while monolayer transplants incorporated more efficiently. Immune responses posed challenges for allogeneic transplants, suggesting that autologous iPSC-derived transplants may be required to decrease the likelihood of rejection. The use of appropriate LAMs helps to advance the development of retinal ATMPs. The anatomical similarity of LAM and human eyes allows the implementation of clinically-relevant surgical techniques. While the FDA Modernization Act 2.0 has provided a framework to consider alternative methods including tissue-on-a-chip and human cell culture models for pharmacologic studies, LAM testing remains useful for cell and tissue replacement studies to inform the development of clinical trial protocols.

Wind-induced vibration response of supertall sightseeing tower evaluation during construction through wind tunnel test of aeroelastic models

Four construction phases of an ultra-high sightseeing tower with a cable-barrel composite structure and their wind-induced vibration response were studied. The first-order natural vibration characteristic of the structure in four different construction phases was calculated through finite element models, and associated aeroelastic models were also designed. Meanwhile, rough strips are applied uniformly on the surface of the model to compensate the Reynolds number of the wind tunnel test. The performance of this method was investigated utilizing the pressure test of rigid segment models. The wind-induced vibration response under four construction conditions, and the effects of wind direction angle, wind speed and structural damping ratio were investigated through the wind tunnel test of aeroelastic models. The results show that sticking rough strips on the surface can effectively improve the Reynolds number of wind tunnel tests. As the wind speed during construction increases, the structural wind-induced vibration response intensifies. A large vortex-induced resonance occurs in the construction phase of a cable-barrel composite structure with the Strouhal number around 0.12 under turbulent conditions in this study. Furthermore, the crosswind-induced vibration response of the structure at a wind deflection angle of 0° is greater than 45° and 90°. Specifically, the mean value of downwind displacement and the maximum value of standard deviation (STD) of downwind and crosswind displacements on the prototype tower top at 0° during construction phases are 1.21 m, 0.35 m, and 0.25 m respectively. Thus, the risk of large wind-induced vibration should be fully considered during construction. Implementing corresponding damping measures to improve the damping ratio of the structure proves effective in restraining its vibration.

Sexual behaviors and HIV-related knowledge among GBMSM: evidence from 2011 to 2021 in Hangzhou, China.

Considering that many new HIV infections are transmitted by homosexual behaviors, gay, bisexual, and other men who have sex with men (GBMSM) are more likely to be infected with HIV than other groups due to the higher risk associated with unprotected anal intercourse. It is important to explore the changes in sexual behaviors and HIV-related knowledge among GBMSM in the last 10 years, which could provide evidence for improving public health interventions to reduce HIV infections. The study sought to explore the changes of 3 sexual behaviors and HIV knowledge among men who have sex with men from 2011 to 2021. Data were collected from national HIV sentinel surveillance among GBMSM in Hangzhou conducted between 2011 and 2021. Univariate and multivariate logistic regression were used to analyze the associated factors of sexual behaviors. The variation trend of variables was evaluated based on the linear trend test in the regression model. A total of 5111 GBMSM with an average age of 32.00years were incorporated in the analysis. From 2011 to 2021, the HIV-related knowledge score of GBMSM ranged from 6 to 7.5, and it increased significantly (P trend < .001). The rate of homosexual sex in the past 6months remained at a high level (75.06%-82.75%). Homosexual behavior was associated with a higher HIV-related knowledge score (P = .004). Heterosexual sex was associated with an increase in the old age, married persons, and domicile outside the province (P < .05). Commercial sex was associated with an increase in drug users (P <.001). In the past 10 years, HIV-related knowledge of GBMSM increased and the rate of unprotected sex was at a high level among GBMSM, especially in heterosexual behaviors. Moreover, the likelihood of having homosexual behaviors is raised with the increasing HIV-related knowledge. Conducting precise behavioral interventions for GBMSM are crucial for preventing HIV infection.

In vitro three-dimensional volumetric printing of vitreous body models using decellularized extracellular matrix bioink

Hyalocytes, which are considered to originate from the monocyte/macrophage lineage, play active roles in vitreous collagen and hyaluronic acid synthesis. Obtaining a hyalocyte-compatible bioink during the 3D bioprinting of eye models is challenging. In this study, we investigated the suitability of a cartilage-decellularized extracellular matrix (dECM)-based bioink for printing a vitreous body model. Given that achieving a 3D structure and environment identical to those of the vitreous body necessitates good printability and biocompatibility, we examined the mechanical and biological properties of the developed dECM-based bioink. Furthermore, we proposed a 3D bioprinting strategy for volumetric vitreous body fabrication that supports cell viability, transparency, and self-sustainability. The construction of a 3D structure composed of bioink microfibers resulted in improved transparency and hyalocyte-like macrophage activity in volumetric vitreous mimetics, mimicking real vitreous bodies. The results indicate that our 3D structure could serve as a platform for drug testing in disease models and demonstrate that the proposed printing technology, utilizing a dECM-based bioink and volumetric vitreous body, has the potential to facilitate the development of advanced eye models for future studies on floater formation and visual disorders.

Estimation and inference in low frequency factor model regressions with overlapping observations

A low frequency factor model regression uses changes or returns computed at a lower frequency than data available. Using overlapping observations to estimate low frequency factor model regressions results in more efficient estimates of OLS coefficients and standard errors, relative to using independent observations or high frequency estimates. I derive the relevant inference and propose a new method to correct for the induced autocorrelation. I present a series of simulations and empirical examples to support the theoretical results. In tests of asset pricing models, using overlapping observations results in lower pricing errors, compared to existing alternatives.

Hybrid Quantum or Purely Classical? Assessing the Utility of Quantum Feature Embeddings

Background As graph datasets—including social networks, supply chains, and bioinformatics data—grow in size and complexity, researchers are driven to search for solutions enhancing model efficiency and speed. One avenue that may provide a solution is Quantum Graph Learning (QGL), a subfield of Quantum Machine Learning (QML) that applies machine learning inspired or powered by quantum computing to graph learning tasks. Methods We reevaluate Quantum Feature Embeddings (QFE), a QGL methodology published by Xu et al. earlier this year. QFE uses Variational Quantum Circuits to preprocess node features and then sends them to a classical Graph Neural Network (GNN), with the goal of increasing performance and/or decreasing total model size. Xu et al. evaluated this methodology by comparing its performance with the performance of variously-sized classical models on the benchmark datasets PROTEINS and ENZYMES, and they report success. Our core methodology and learning task remain unchanged. However, we have made several changes to the experimental design that enhance the rigor of the study: 1) we include the testing of models with no embedder; 2) we conduct a thorough hyperparameter search using a state-of-the-art optimization algorithm; and 3) we conduct stratified five-fold cross-validation, which mitigates the bias produced by our small datasets and provides multiple test statistics from which we can calculate a confidence interval. Results We produce classical models that perform comparably to QFE and significantly outperform the small classical models used in Xu et al.’s comparison. Notably, many of our classical models achieve this using fewer parameters than the QFE models we trained. Xu et al. do not report their total model sizes. Conclusion Our study sheds doubt on the efficacy of QFE by demonstrating that small, well-tuned classical models can perform just as well as QFE, highlighting the importance of hyperparameter tuning and rigorous experimental design.

Unified specification tests in partially linear quantile regression models

We propose specification tests for parametric quantile regression models versus semiparametric alternatives over a continuum of quantile levels. The test statistics are constructed as continuous functionals of a quantile-marked residual process. We show that using an orthogonal projection on the tangent space of nuisance parameters at each quantile index delivers unified asymptotic properties for tests based on different estimators. Consistency of the tests and asymptotic power under a sequence of local alternatives converging to the null at a parametric rate are also discussed. We propose a simple multiplier bootstrap procedure to carry out the tests, whose nominal levels are well approximated in our simulation study for modest sample sizes.

Designing an explainable bio-inspired model for suspended sediment load estimation: eXtreme Gradient Boosting coupled with Marine Predators Algorithm

This study aimed to develop an accurate and reliable model for predicting suspended sediment load (SL) in river systems, which is crucial for water resource management and environmental protection. While Xtreme Gradient Boosting (XGB), a powerful ensemble machine learning (ML) model, has been employed in previous studies, the novelty of this research lies in the introduction of a hybrid approach that synergistically combines XGB with the bio-inspired Marine Predators Algorithm (XGB-MPA) to estimate SL in the Yeşilirmak River (Turkey). To this end, streamflow (Q) and sediment concentration (SC) values as well as their lag times (1 to 3 month lag times) were fed as input variables – under 9 scenarios – into ML models. A time series of datasets from March 1973 to December 2011 and January 2012 to March 2023 were used for training and testing of ML models, respectively. The superiority of the proposed model (XGB-MPA) compared to two other hybrid models, including XGB-PSO (Particle Swarm Optimization) and XGB-GWO (Grey Wolf Optimization) was also investigated. According to the results, the simultaneous application of Q and SC lag time values as inputs has led to the best SL estimates by XGB-MPA, with XGB-MPA9 (RMSE = 103.7 ton/day; NSE = 0.96) exhibiting the lowest error rates. In addition, XGB-MPA has performed better than XGB in all scenarios, with the lowest and highest reduction in RMSE being 19.3% (scenario 5) and 97.4% (scenario 1), respectively. When comparing the performance of hybrid models, the proposed XGB-MPA model has performed best with MAE, RMSE and NSE of 40.94, 103.7 and 0.96, respectively, in comparison with 816.02, 1063.74 and −2.94 for XGB-PSO and 693.16, 981.68 and −2.37 for XGB-GWO. Further research can include the use of time series of efficient variables extracted from satellite images (e.g. land cover, river morphology, etc.) as model inputs. Highlights Improvement of SL estimation by coupling MPA with XGB model Using delayed combinations of streamflow and sediment concentration as model inputs Superiority of MPA compare to PSO and GWO in SL estimation Greater variations in SHAP caused by sediment concentration compared to streamflow Further studies required on the effects of hydrological and topographical features

In Vivo Testing of a Second-Generation Prototype Accessory for Single Transapical Left Ventricular Assist Device Implantation.

A new accessory was developed to allow implantation of left ventricular assist devices (LVADs) without requiring an anastomosis to the ascending aorta. The accessory combines the LVAD inflow and outflow into a dual-lumen device. Initial prototypes encountered reduced pump performance in vitro, but a second-generation prototype successfully addressed this issue. This feasibility study aimed to demonstrate the anatomic fit, safe implantation, and hemodynamic effectiveness of the LVAD with the accessory. The accessory was implanted in ten female pigs (104 ± 13 kg). Following sternotomy and apical coring under cardiopulmonary bypass, a balloon catheter was retrogradely inserted and exteriorized through the coring site, where it was inflated within the distal third of the outflow graft. It was utilized to pull the accessory's outflow across the aortic valve. After LVAD attachment, the catheter was removed. Echocardiography revealed no relevant valve regurgitation post-implantation. During ramp testing, pump flow increased from 3.7 ± 1.2 to 5.4 ± 1.2 L/min. Necropsy confirmed correct accessory placement in nine animals. No valve lesions or device thrombosis were observed. The accessory enabled LVAD implantation without compromising pump performance. Future work includes design refinements for implantation without cardiopulmonary bypass and long-term testing in a chronic heart failure model.

Stemness and hybrid epithelial-mesenchymal profiles guide peritoneal dissemination of malignant mesothelioma and pseudomyxoma peritonei.

Intrabdominal dissemination of malignant mesothelioma (MM) and pseudomyxoma peritonei (PMP) is poorly characterized with respect to the stemness window which malignant cells activate during their reshaping on the epithelial-mesenchymal (E/M) axis. To gain insights into stemness properties and their prognostic significance in these rarer forms of peritoneal metastases (PM), primary tumor cultures from 55 patients selected for cytoreductive surgery with hyperthermic intraperitoneal chemotherapy were analyzed for cancer stem cells (CSC) by aldehyde dehydrogenase 1 (ALDH1) and spheroid formation assays, and for expression of a set of plasticity-related genes to measure E/M transition (EMT) score. Intratumor heterogeneity was also analyzed. Samples from PM of colorectal cancer were included for comparison. Molecular data were confirmed using principal component and cluster analyses. Associations with survival were evaluated using Kaplan-Meier and Cox regression models. The activity of acetylsalicylic acid (ASA), a stemness modifier, was tested in five cultures. Significantly increased amounts of ALDH1bright-cells identified high-grade PMP, and discriminated solid masses from ascitic/mucin-embedded tumor cells in both forms of PM. Epithelial/early hybrid EMT scores and an early hybrid expression pattern correlated with pluripotency factors were significantly associated with early peritoneal progression (p = .0343 and p = .0339, respectively, log-rank test) in multivariable models. ASA impaired spheroid formation and increased cisplatin sensitivity in all five cultures. These data suggest that CSC subpopulations and hybrid E/M states may guide peritoneal spread of MM and PMP. Stemness could be exploited as targetable vulnerability to increase chemosensitivity and improve patient outcomes. Additional research is needed to confirm these preliminary data.

Precision spectroscopy on 9Be overcomes limitations from nuclear structure

Many powerful tests of the standard model of particle physics and searches for new physics with precision atomic spectroscopy are hindered by our lack of knowledge of nuclear properties. Ideally, these properties may be derived from precise measurements of the most sensitive and theoretically best-understood observables, often found in hydrogen-like systems. Although these measurements are abundant for the electric properties of nuclei, they are scarce for the magnetic properties, and precise experimental results are limited to the lightest of nuclei1–4. Here we focus on 9Be, which offers the unique possibility to use comparisons between different charge states available for high-precision spectroscopy in Penning traps to test theoretical calculations typically obscured by nuclear structure. In particular, we perform high-precision spectroscopy of the 1s hyperfine and Zeeman structure in hydrogen-like 9Be3+. We determine the effective Zemach radius with an uncertainty of 500 ppm, and the bare nuclear magnetic moment with an uncertainty of 0.6 parts per billion— uncertainties unmatched beyond hydrogen. Moreover, we compare our measurements with the measurements conducted on the three-electron charge state 9Be+ (ref. 5), which enables testing the calculation of multi-electron diamagnetic shielding effects of the nuclear magnetic moment at the parts per billion level. Furthermore, we test the quantum electrodynamics methods used for the calculation of the hyperfine splitting. Our results serve as a crucial benchmark for transferring high-precision results of nuclear magnetic properties across different electronic configurations.

Determining the CP property of [formula omitted] coupling via a novel jet substructure observable

Determining the CP property of the Higgs boson is important for a precision test of the Standard Model as well as for the search for new physics. We propose a novel jet substructure observable based on the azimuthal anisotropy in a linearly polarized gluon jet that is produced in association with a Higgs boson at hadron colliders, and demonstrate that it provides a new CP-odd observable for determining the CP property of the Higgs-top interaction. We introduce a factorization formalism to define a polarized gluon jet function with the insertion of an infrared-safe azimuthal observable to capture the linear polarization.

The impact of economic growth targets on the level of green development-A perspective on officials’ promotion incentives and environmental regulations

Currently, China is at a critical stage of accelerating the green transformation of its economic development model, with considerable attention being paid to achieving this transformation while maintaining moderate economic growth. This study uses 271 prefecture-level cities in China from 2006 to 2020 to examine the impact of local government economic growth target constraints on the level of green economic development and to elucidate the underlying mechanisms. The results show that economic growth targets significantly inhibit the level of urban green development, with this effect being more pronounced in the economically developed eastern regions of China. Hard constraints on economic growth targets have a greater inhibitory effect on green development than soft constraints. The greater the promotion pressure on local officials, the stronger the inhibitory effect of economic growth target constraints on green development. The test of the mediation effect model reveals that economic growth targets can inhibit green development by affecting the degree of regional marketization, leading to mismatches in the capital and labor markets. Moreover, environmental regulations can mitigate the inhibitory effect of economic growth targets on green development levels. The conclusions of this study provide useful insights for local governments to optimize economic development target constraint mechanisms and accelerate high-quality green economic development.

Demulsification of water in crude oil emulsions via phosphonium-based ionic liquids: Statistical modeling and optimization

In the present study, the performance of two ionic liquids namely Tetrabutylphosphonium bromide (TBPB) and Tetraoctylphosphonium bromide (TOPB) as the demulsifying compounds are investigated in the demulsification operation of water in light and medium crude oil emulsions for the first time. The response surface methodology (RSM) is employed to evaluate the impact of temperature, pH, water content, demulsifier concentration, and settling time on the demulsification efficiencies of studied demulsifiers. In order to design the requisite experiments and optimize the effective factors on the water removal efficiency, the central composite design (CCD) is applied. To determine the optimal conditions of input parameters, four exact models are created by utilizing the responses of 184 experiments to predict the demulsification efficiencies of two demulsifiers for two types of crude oils based on statistical tests of different models using the analysis of variance (ANOVA). High R2 coefficient values imply that the developed models could reproduce the experimental results of the studied demulsifiers appropriately. At the optimal conditions, the water in light and medium crude oil emulsions are completely broken in the samples containing TOPB. Moreover, TBPB agent presents high and acceptable demulsification efficiencies for both types of crude oils at the optimal values of process parameters i.e. 98.078% and 96.025% for light and medium crude oil emulsions, respectively. The superior demulsification performance of TOPB with respect to TBPB can be ascribed to the longer alkyl chain length of TOPB.

HAIR TONIC OF BROCCOLI (BRASSICA OLERACEA VAR. ITALICA) EXTRACT: FORMULATION, PHYSICAL CHARACTERISTIC, STABILITY AND HAIR GROWTH ACTIVITY TEST

Objective: Hair loss is a common scalp concern for both men and women. Broccoli (Brassica oleracea var. Italica) is a vegetable plant in the cabbage family or brassicaceae that has antioxidant activity and levels of flavonoids that can encourage hair growth. Hair tonic is one of cosmetic products that contain ingredients to nourish hair. The purpose of this study was to investigate the physical stability and activity of hair development in hair tonic preparations using broccoli stalks extracted at different concentrations of 30%, 35%, and 40%, followed by an examination of the hair growth activity test in an animal model. Methods: This study hair tonic was prepared with Broccoli (Brassica oleracea var. Italica), the sample used the broccoli stalks, which was taken by purposive sampling. Evaluation of the preparation includes physical characteristic observation, pH examination, homogeneity of the preparation, irritation test, and stability test of the preparation using a cycling test, and check the activity test of hair growth in rats’ skin. Results: The results showed that the hair tonic preparation containing broccoli stalks extracts was stable at a temperature (4 °C±40 °C) where the odor, color, shape, homogeneity, and pH remained constant. In statistical testing using ANOVA analysis, each group of the hair tonic formula of broccoli stalks extract showed hair growth activity in male white rats. The hair tonic formulation containing 40% broccoli stalks extract had better hair growth activity compared to the 30% and 35% formula groups. The hair tonic prepared from broccoli extract is confirmed safe for use after successfully passing the skin irritation test. Conclusion: The hair tonic of broccoli extracts had met the standard of physical characteristics during storage time and it has a good activity test on hair growth in male white rats. This study provides a novel formulation in hair growth.