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Influence of lighting on sleep behaviour, circadian rhythm and spontaneous blink rate in stabled riding school horses (Equus caballus)

Modern horse husbandry involves significant time spent indoors, often in suboptimal lighting conditions and with frequent night-time disturbances by humans for management purposes. The aim of this study was to investigate the influence of a customised light-emitting diode (LED) lighting system and a standard fluorescent lighting fixture on equine sleep behaviours, circadian rhythmicity and spontaneous blink rates in horses. Ten riding school horses experienced two stable lighting conditions for four weeks each in a cross-over study running from January to March, 2023. The treatment lighting consisted of an LED system that provided timed, blue-enriched white polychromatic light by day and dim red light at night, and control lighting was a fluorescent tube that was turned on and off manually morning and evening. During week 4 of each experimental period, spontaneous blink rate was recorded twice for 30 min, behaviour of horses in their stables was recorded continuously for 72 h, and hair samples for circadian clock gene analysis were collected at 4-h intervals for 52 h. No differences were detected for total sleep, lateral or sternal recumbency, wakefulness, standing, standing sleep, or spontaneous blink rate (P > 0.05), between lighting conditions. The lighting period (Day versus Night) influenced total sleep (P < 0.01), total recumbency (P < 0.01), wakefulness (P < 0.01), and standing sleep (P < 0.05) in both conditions. For the treatment condition only, higher wakefulness was recorded during Day (P < 0.05). An overall effect of time for clock genes PER2 and DBP was detected (P < 0.01), but there was no effect of treatment, or time by treatment interaction. Cosinor analysis detected significant 24-h rhythmicity for PER2 and DBP (P < 0.01) in both lighting conditions. Results imply that dim red light at night does not negatively impact normal sleep patterns or circadian rhythmicity, and provide evidence supporting further research to better understand the role of blue-enriched LED light at promoting increased wakefulness during daytime in stabled horses.

Illegal drugs sensor: Performance evaluation and identification based on terahertz photonic crystal fiber

Excessive hormone release, the possibility of sleep disturbances, and a brief and quick improvement in the functioning of many organs, the physiological system, the nerves, etc. are all consequences of the abuse of incentive medications. Illegal narcotics have terrible long-term impacts on human health, including the possibility of death, in addition to their immediate effects. These consequences highlight the need for more obviousness and accuracy in the detection of illicit drugs, as well as for their detection to be done gently, effectively, and consistently. This work introduces an illicit drug sensor based on PCF, with an eye toward these as the primary targets. Three illegal drugs – ketamine, amphetamine, and cocaine – have been simulated for the sensor. Two types of circular air holes in cladding of varying sizes have been developed for a single core PCF. The cladding has three-layer chain and wind turbine-shaped air holes, and a circular air hole in the core region that will be used to field test drug samples, all included to achieve low confinement losses and high sensitivity. A maximum Relative Sensitivity (RS) of 99.92%, 99.12% and 98.83% at ketamine, amphetamine, and cocaine respectively is revealed by the recently established PCF analysis, which was presented out right away. Furthermore, we looked at the Confinement Loss (CL) associated with these illicit drugs, which was around 1.275 × 10−7 dB/m, 2.653 × 10−9 dB/m, and 4.106 × 10−10 dB/m, besides Effective Material Loss (EML) of 0.0042 cm-1, 0.0044 cm-1 and 0.0045 cm-1. Refractive index changes in PCF are usually the cause of action for PCF-based biosensors. These modifications have an impact on how light travels within the fiber. Drug molecules interact with light as a result of changes in the optical properties of the core that occur during light propagation through it.

Evaluating the potential of underwater television to contribute to marine litter assessments alongside bottom trawling

Marine litter presents a global threat to marine ecosystems, human health, and safety. Therefore, it is important to increase our knowledge about spatiotemporal trends of litter in the environment. Bottom trawl surveys provide a practical method for monitoring seafloor litter on the continental shelf, but can have severe negative impacts on the environment. Here we evaluate the potential of an ongoing underwater television survey (UWTV) to also collect litter density data, and develop model-based indices of litter densities integrating coastal and offshore trawl survey data using geostatistical models. Based on our case study along the Swedish west coast, we find that UWTV in its current format may be limited as an alternative to trawling in areas with relatively low densities. There are also clear spatial trends in litter, with the highest densities in near-shores areas currently only included in the national monitoring program. Our results illustrate the potential of combining data, but also the importance of careful sampling designing for marine litter monitoring.

Priorities for consent-based and well-supported climate relocations

Mode of birth and maternal depression/severe anxiety: Findings from Millennium Cohort Study

Introduction Limited evidence exists on the association between mode of birth and long-term depression and/or severe anxiety in mothers. We aimed to examine the association between mode of birth and depression and/or severe anxiety by 14 years postpartum. Methods We used data from the Millennium Cohort Study. Data on mode of birth were collected when mothers were 9 months postpartum, and categorized as spontaneous vaginal birth (VB), assisted VB, induced VB, emergency cesarean section (CS), planned CS, and CS after induction. Depression/severe anxiety were collected as one variable and self reported by mothers at 9 months, 3, 5, 7, 11, and 14 years postpartum based on a doctor diagnosis. The primary outcome measure was a diagnosis of depression/severe anxiety up to 14 years postpartum. We used multivariable logistic regression models to estimate crude and adjusted odds ratios (OR) for the association between mode of birth and depression/severe anxiety by 14 years postpartum. Results There were 10,507 singleton mothers included in our analyses. Fully adjusted odds ratio (aOR)for the association between mode of birth and depression/severe anxiety by 14 years postpartum was induced VB, (aOR, 1.13 [95% CI], 1.01–2.28), assisted VB (aOR, 1.03 [95% CI], 0.89–1.19), Emergency CS, (aOR, 1.08 [95% CI], 0.92–1.27), planned CS (aOR, 1.09 [95% CI], 0.93–1.27), and CS after induction (aOR, 1.08 [95% CI], 0.91–1.28). Fully adjusted models did not report any significant association between mode of birth and depression/severe anxiety at other postpartum time points. Conclusions The present findings provide support for association between induction of labor and the risk of long-term depression/severe anxiety by 14 years postpartum. The findings provide no evidence to support association between other modes of birth and maternal depression/anxiety.

The microbiota vault initiative: safeguarding Earth’s microbial heritage for future generations

Effectiveness of interactive dashboards as audit and feedback tools in primary care: A systematic review

Interactive audit and feedback dashboards, which summarize performance using quality indicators, are increasingly used to enhance care processes and outcomes, but their effectiveness in primary care remains underexplored. This systematic review aimed to evaluate the impact of these dashboards in primary care settings by analyzing studies that compared their use to usual care or similar interventions without dashboards. A comprehensive search across MEDLINE (via Ovid), Embase, Cochrane Library, Scopus, and Web of Science through November 2024 was conducted. Risk of bias was assessed using Cochrane tools, and evidence quality was evaluated with GRADE. Relevant data, including features of the interactive dashboards, were extracted, and findings were synthesized narratively and visualized with forest plots. Six studies met the inclusion criteria, comprising five randomized controlled trials and one non-randomized trial, all with low or moderate risk of bias. Four studies incorporating dashboards into multifaceted interventions showed improvements in at least one primary outcome, while two studies using standalone dashboards reported mixed results. Significant heterogeneity in dashboard design, study settings, targeted health conditions, and quality indicators limits the generalizability of these findings. Nonetheless, the results highlight the potential of interactive dashboards to improve quality indicators performance in primary care, particularly as part of broader intervention strategies. Standardized evaluation frameworks and rigorous, consistent reporting are needed in future research to better isolate the effects of interactive dashboards and enhance the robustness and applicability of the evidence in varied primary care contexts. Registration Prospero (CRD42024506727).

Hepatitis B virus promotes liver cancer by modulating the immune response to environmental carcinogens

Abstract Hepatitis B virus (HBV) infection is associated with hepatitis and hepatocellular carcinoma (HCC). Considering that most HBV-infected individuals remain asymptomatic, the mechanism linking HBV to hepatitis and HCC remains uncertain. Herein, we demonstrate that HBV alone does not cause liver inflammation or cancer. Instead, HBV alters the chronic inflammation induced by chemical carcinogens to promote liver carcinogenesis. Long-term HBV genome expression in mouse liver increases liver inflammation and cancer propensity caused by a carcinogen, diethylnitrosamine (DEN). HBV plus DEN-activated interleukin-33 (IL-33)/regulatory T cell axis is required for liver carcinogenesis. Pitavastatin, an IL-33 inhibitor, suppresses HBV plus DEN-induced liver cancer. IL-33 is markedly elevated in HBV+ hepatitis patients, and pitavastatin use significantly correlates with reduced risk of hepatitis and its associated HCC in patients. Collectively, our findings reveal that environmental carcinogens are the link between HBV and HCC risk, creating a window of opportunity for cancer prevention in HBV carriers.

Pain, fatigue, and associated gene expressions over chemotherapy in patients with colorectal cancer

Context Patients with colorectal cancer undergoing chemotherapy often experience significant pain and fatigue. Limitations in understanding the complex phenotypes and biological mechanisms of these symptoms hinder effective interventions. Objectives This study aimed to identify the pain and fatigue patterns during one chemotherapy cycle and associated gene expression profiles. Method In a prospective longitudinal study, 34 patients with colorectal cancer from a major cancer center in the Northeastern US were recruited. Self-reported outcome measures of pain and fatigue and blood samples were collected at baseline, post-chemotherapy, and at the end of the chemotherapy cycle. RNA sequencing followed by differential expression analysis identified changes in gene expression. Linear mixed models examined associations between symptoms and possible biomarkers over time. Results The sample had a mean age of 58.4 years old, with 97% being white and non-Hispanic. Among participants, 44.1% had stage III cancer, and 26.5% were undergoing initial chemotherapy. Abdominal pain was the most frequently reported symptom. Fatigue levels significantly worsened post-chemotherapy (P = 0.011) and after recovery (P = 0.018). Critical pathways involved inflammatory response and myeloid cell development (FDR < 5%). Mixed-effect linear regression analysis revealed statistically significant associations between the upregulation of LILRA6 and higher pain interference (β = −6.621, p = 0.010) and fatigue (β = −6.621, p = 0.010), as well as between the downregulation of CACNG6 (β = −1.043, p = 0.047) and PRSS33 upregulation (β = 1.384, p = 0.038) and increased pain interference. Given the small sample size, these findings should be interpreted with caution. Conclusion These findings suggest inflammation and specific biomarkers may drive pain and fatigue during chemotherapy. Further preclinical models or clinical cohorts are needed to validate these results and explore potential implications for targeted interventions to reduce symptom burden in patients with colorectal cancer.

Role of stem-like cells in chemotherapy resistance and relapse in pediatric T-cell acute lymphoblastic leukemia

Abstract T-ALL relapses are characterized by chemotherapy resistance, cellular diversity and dismal outcome. To gain a deeper understanding of the mechanisms underlying relapses, we conduct single-cell RNA sequencing on 13 matched pediatric T-ALL patient-derived samples at diagnosis and relapse, along with samples derived from 5 non-relapsing patients collected at diagnosis. This comprehensive longitudinal single-cell study in T-ALL reveals significant transcriptomic diversity. Notably, 11 out of 18 samples exhibit a subpopulation of T-ALL cells with stem-like features characterized by a common set of active regulons, expression patterns and splice isoforms. This subpopulation, accounting for a small proportion of leukemia cells at diagnosis, expands substantially at relapse, indicating resistance to therapy. Strikingly, increased stemness at diagnosis is associated with higher risk of treatment induction failure. Chemotherapy resistance is validated through in-vitro and in-vivo drug testing. Thus, we report the discovery of treatment-resistant stem-like cells in T-ALL, underscoring the potential for devising future therapeutic strategies targeting stemness-related pathways.

Harmonic oscillator based particle swarm optimization

Numerical optimization techniques are widely applied across various fields of science and technology, ranging from determining the minimal energy of systems in physics and chemistry to identifying optimal routes in logistics or strategies for high-speed trading. Here, we present a novel method that integrates particle swarm optimization (PSO), a highly effective and widely used algorithm inspired by the collective behavior of bird flocks searching for food, with the physical principle of conserving energy and damping in harmonic oscillators. This physics-based approach allows smoother convergence throughout the optimization process and wider tunability options. We evaluated our method on a standard set of test functions and demonstrated that, in most cases, it outperforms its natural competitors, including the original PSO, as well as commonly used optimization methods such as COBYLA and Differential Evolution.

The impact of fiscal pressure on education expenditure: Evidence from China

Adjusting the tax distribution relationship among governments at all levels in the reform of the fiscal and taxation system will inevitably trigger changes in local government fiscal revenue. Will the fiscal pressures accompanying such changes have a significant impact on the expenditure decisions of local governments? Drawing on the 2002 Income Tax Sharing Reform in China as a quasi-natural experiment, we apply an intensity difference-in-difference methodology to evaluate how fiscal pressure influence county-level education provision. The empirical evidence indicates that counties most exposed to the reform experienced a marked reduction in the proportion of fiscal expenditure devoted to education, with the impact exhibiting a lagged and persistent pattern. The heterogeneity analysis reveals that fiscal pressure has a more pronounced negative impact on education expenditure in counties with developed economies, lower pre-reform education expenditure ratios, and outflow of transfer payments, while special transfer payments can better alleviate this negative effect. In addition, we also found that county governments will give priority to cutting education expenditure after suffering a fiscal shock, and intergovernmental competition further amplifies the adverse effect of fiscal pressure on county education expenditure.The analysis and conclusions of this article help to explain the reasons for insufficient education expenditure at the county level across China, thereby providing effective suggestions for the local government’s fiscal expenditure decision-making choices under fiscal pressure, and also providing important inspiration for advancing modern fiscal and tax system reforms.

Level of satisfaction to clinical learning environment and its associated factors among nursing students of public universities in Central Ethiopia

Background Students’ satisfaction with clinical learning environment is a vital to evaluate teaching-learning process. However, there is a scarcity of information regarding the nursing students’ satisfaction with clinical learning environment and associated factors in Ethiopia. The purpose of this study was aimed to assess level of satisfaction to clinical learning environment and its associated factors among nursing students of public universities in Central Ethiopia, 2022. Méthodes An institution based cross-sectional study was conducted among 245 undergraduate nursing students found in Universities of central Ethiopia from September 1–30, 2022. A simple random sampling technique was applied to recruit study participants. Data were collected via pretested self-administered questionnaire. The data were entered into Epi data version 3.1 and exported to SPSS version 25 for analysis. Descriptive statistics like frequency, percentage, median and IQR were computed. Binary and multivariable logistic regression analysis was done. For measuring the strength of the association between the outcome and independent variables, adjusted odds ratios (AOR) along with 95% confidence interval (CI) was used. Finally, statistical significance was declared at p-value <0.05. Results In this study, nearly half of nursing students, 49% [95% CI (42.6–55.4)] were satisfied with clinical learning environment. Students who did met their clinical learning outcome [AOR = 2.742 (95%CI: 1.407–5.343)], Students those who met 3 times per week with clinical preceptors [AOR: 2.829 (95% CI: 1.428–5.602)] and students who perceived inadequate supporting staffs [(AOR: 0.136 (95%CI: (0.073–0.254)] were associated factors. Conclusion Meeting clinical learning outcome, students’ perception of staff supports and having a frequent contact of supervisor were an association with satisfaction statistically.

Innovation and valuation of Chinese born-global firms

With the advancement of corporate globalization, an increasing number of small and medium-sized enterprises (SMEs) have leveraged globalized resources to achieve accelerated growth mode that significantly depart from the traditional gradual development trajectories of large enterprises. Notably, the emergence and evolution of born-global (BG) firms have attracted substantial scholarly attention in international business research. This paper studies the innovation and valuation of Chinese born-global (BG) firms, based on dynamic capabilities theory and resource-based view, explores the determinant factors of becoming BG firms, and explores an empirical analysis of changes in the value of BG firms. This paper utilizes the OLS model and panel model, as well as Heckman two-stage, propensity score matching (PSM), and heterogeneity analyzes. We conducted some empirical tests on financial data from 2007 to 2021. The empirical results show that the implementation of the BG mode by enterprises contributes to the growth of corporate value and innovation plays a positive moderating role in this relationship. In addition, the determinant factors for a company to adopt the BG mode are total assets, ownership, and the rate of the largest shareholder. Heterogeneity analysis indicates greater impact on private, foreign, and eastern regional firms. The Heckman two-stage selection model effectively addressed the identification requirements for exclusion restriction variables, while the PSM methodology demonstrated improved covariate balance distributions across matched groups. This dual approach collectively mitigated endogeneity concerns and enhanced the robustness of estimation outcomes. Finally, this study provides business managers with a valuation model for enterprise internationalization, which helps small and medium-sized enterprises choose BG mode to start the internationalization process in their initial stage. Furthermore, this study has significantly enriched the existing literature concerning innovation, corporate value, and equity characteristics of BG firms, while establishing novel theoretical perspectives and methodological avenues for subsequent research investigations.

Real-time human-robot interaction and service provision using hybrid intelligent computing framework

Human-robot interaction has gained significant attention in various domains, including healthcare, customer service, and industrial automation. High computational cost, inefficient service matching, and elevated failure rates in dynamic service contexts are some primary disadvantages of existing query-processing systems. This research introduces a Hybrid Intelligent Computing Model (HICM) to improve robots’ ability to process inquiries autonomously. The goal is to make robots better at responding to human questions in real time with efficient, personalized, and context-specific solutions. Using self-organized computing approaches, robotic agents can reliably provide end-users with services suited to their demands. Due to their autonomous nature, robots must be able to calculate quickly and accurately to provide timely services. To meet these needs, the proposed HICM incorporates a sophisticated decision-support system to handle human questions and find the appropriate services. Within this decision-making framework, the model evaluates the characteristics and relevance of questions about accessible services by combining annealing and Tabu Search approaches. To avoid addressing queries incompatibly, the Tabu Search technique approaches query resolution as a non-convergent optimization issue. Comparing HICM’s performance to other models reveals significant improvements over CDS, DGTA, and CCS. In particular, HICM reduced calculation time by 8.67%, service time by 15.09%, and failure rates by 7.87%. In terms of important metrics, HICM fared better than the competing models. Its success factor was 11.8% higher, its matching ratio was 14.88% higher, and its failure rates were 6.22% lower. These findings demonstrate the model’s efficiency and reliability in terms of robotic query processing and real-time service delivery.

One-year survival after critical care as a decision basis for advance care directives in general medicine: Real word data analysis of 149,144 patients

Providing counsel on advance care directives is challenging for general practitioners. Counselling is done on unknown future circumstances of possible critical illness and critical care in intensive care units. Following the principles of evidence-based medicine, the physician’s task is to communicate evidence and elucidate the patient’s position on it. However, suitable evidence of chances of survival in case of critical illness is lacking. Aim of this study was to generate long-term survival rates of patients receiving critical care as evidence for general practitioners who provide counselling for patients on advance care directives. We conducted a retrospective cohort study analysing one-year survival rates of critical care using German health insurance claims data from an anonymised nationwide health claims data pool of over five million German patients. All patients over 18 years of age receiving critical care for the first time were included.Main outcome of our study were one-year survival probabilities depending on age and on acute life prolonging procedures. Procedures analysed were non-invasive and invasive mechanical ventilation (nMV, iMV), renal replacement therapy (RRT), their combinations (nMV + RRT, iMV + RRT), and cardiopulmonary resuscitation (CPR). A total of 149,144 datasets was analysed. One-year survival probability of all patients was 77.5%. Survival rates ranged from 94.5% in patients under 50 without any further acute life prolonging procedures to 16.4% in those older than 80 who received iMV + RRT. The application of at least one procedure was associated with an increased risk of death (HR 3.06, 95% CI 2.99 to 3.12) as was CPR (HR 4.22, 95% CI 4.07 to 4.37). Differences between pre- and COVID periods were modest. To enable patient’s decision-making in creating advance care directives, our results provide easily applicable external evidence for general practitioners counselling on advance care directives by providing probabilities of survival in critical care.

Climate is stronger than you think: Exploring functional planting and TRIAD zoning for increased forest resilience to extreme disturbances

In the face of global changes, forest management must now consider adapting forests to novel and uncertain conditions alongside objectives of conservation and production. In this perspective, we modified the TRIAD zoning approach to add a resilience component through functionally diverse plantations following harvesting in the extensive areas. We then assessed the capacity of this new “TRIAD+” zoning approach for improving the resilience of the mature forest biomass to climate change and three potential extreme pulse disturbances: a large fire, a severe drought, and an insect outbreak. We used the forest landscape simulation model LANDIS-II on a management unit in Mauricie (Quebec, Canada) to simulate and compare the TRIAD+ scenario with a classic TRIAD zoning scenario, and two business-as-usual harvesting scenarios with and without functional enrichment planting. We also simulated three different climate change scenarios (Baseline, RCP 4.5 and RCP 8.5) in which these management and extreme disturbance scenarios took place. We monitored the changes in three variables: the mature wood biomass across the landscape, the mature biomass of each functional group, and the functional diversity of stands in the landscape. Resilience was measured according to three indicators: resistance, net change and recovery time of mature biomass. TRIAD+ management resulted in a good compromise, harvesting the same amount of wood as other scenarios while increasing the surface of protected forests by around 240% compared to BAU scenarios, and improving the mean functional diversity of stands by around 15% compared to the classic TRIAD and BAU without plantations. Following the pulse disturbance events, TRIAD+ also increased the resilience of the mature biomass across the landscape. However, this increase was limited, depended on the resilience indicator and the event considered, and was negligible in terms of tree biomass recovered in the long term. It’s uncertain whether these results stemmed from the relative lack of small-scale interactions in LANDIS-II through which the effect of functional diversity on stand resilience should occur, or if this effect is small to begin with. Overall, our study reveals that an adaptation component can be included in current or future management strategies, but that increasing functional diversity via plantations will likely be insufficient to significantly boost forest resilience. Future research should therefore explore other (combined) means of increasing forest resilience, and improve the representation of small-scale interactions in landscape-scale models.

ChunkUIE: Chunked instruction-based unified information extraction

Large language models (LLMs) have demonstrated remarkable performance across various linguistic tasks. However, existing LLMs perform inadequately in information extraction tasks for both Chinese and English. Numerous studies attempt to enhance model performance by increasing the scale of training data. However, discrepancies in the number and type of schemas used during training and evaluation can harm model effectiveness. To tackle this challenge, we propose ChunkUIE, a unified information extraction model that supports Chinese and English. We design a chunked instruction construction strategy that randomly and reproducibly divides all schemas into chunks containing an identical number of schemas. This approach ensures that the union of schemas across all chunks encompasses all schemas. By limiting the number of schemas in each instruction, this strategy effectively addresses the performance degradation caused by inconsistencies in schema counts between training and evaluation. Additionally, we construct some challenging negative schemas using a predefined hard schema dictionary, which mitigates the model’s semantic confusion regarding similar schemas. Experimental results demonstrate that ChunkUIE enhances zero-shot performance in information extraction.

In vitro assessment of berberine-loaded carboxymethyl chitosan hydrogel: A promising antimicrobial candidate for S. aureus-induced bovine mastitis treatment

Bovine mastitis poses significant challenges to the global dairy industry, leading to substantial economic losses and public health concerns. Staphylococcus aureus, a prevalent causative agent of bovine mastitis, depends on effective adhesion and biofilm formation to establish infections. Berberine (BER), a naturally occurring phytochemical, demonstrates broad-spectrum antibacterial activity but suffers from poor bioavailability. This study developed a composite berberine-carboxymethyl chitosan/sodium alginate hydrogel to address these limitations. The hydrogel was characterized using scanning electron microscopy, Fourier-transform infrared spectroscopy, and X-ray diffraction. In vitro assessments revealed that the BER hydrogel eradicated S. aureus biofilms (42% eradication at 156.26 μg/mL), inhibited bacterial adhesion, and reduced inflammatory cytokines (IL-6 and TNF-α) in S. aureus-infected MAC-T cells, with compliant biosafety biocompatibility (hemolysis rate <5%) and sustained drug release (100% over 6 h), though pH-dependent release kinetics necessitate microenvironment-specific formulation refinement. In conclusion, the BER hydrogel represents a potential therapeutic candidate for S. aureus-induced bovine mastitis.

3Mont: A multi-omics integrative tool for breast cancer subtype stratification

Breast Cancer (BRCA) is a heterogeneous disease, and it is one of the most prevalent cancer types among women. Developing effective treatment strategies that address diverse types of BRCA is crucial. Notably, among different BRCA molecular sub-types, Hormone Receptor negative (HR-) BRCA cases, especially Basal-like BRCA sub-types, lack estrogen and progesterone hormone receptors and they exhibit a higher tumor growth rate compared to HR+ cases. Improving survival time and predicting prognosis for distinct molecular profiles is substantial. In this study, we propose a novel approach called 3-Multi-Omics Network and Integration Tool (3Mont), which integrates various -omics data by applying a grouping function, detecting pro-groups, and assigning scores to each pro-group using Feature importance scoring (FIS) component. Following that, machine learning (ML) models are constructed based on the prominent pro-groups, which enable the extraction of promising biomarkers for distinguishing BRCA sub-types. Our tool allows users to analyze the collective behavior of features in each pro-group (biological groups) utilizing ML algorithms. In addition, by constructing the pro-groups and equalizing the feature numbers in each pro-group using the FIS component, this process achieves a significant 20% speedup over the 3Mint tool. Contrary to conventional methods, 3Mont generates networks that illustrate the interplay of the prominent biomarkers of different -omics data. Accordingly, exploring the concerted actions of features in pro-groups facilitates understanding the dynamics of the biomarkers within the generated networks and developing effective strategies for better cancer sub-type stratification. The 3Mont tool, along with all supporting materials, can be found at https://github.com/malikyousef/3Mont.git.