Synergistic effects of starch and carrageenan from Kappaphycus alvarezii in composite film formation: Physicochemical and degradable properties.

Rising concerns around plastic pollution from single-use plastic (SUPs), especially food packaging, have driven interest in sustainable alternatives. As such, algae biomass has gained attention for bioplastic production due to algae's rapid growth and abundant polysaccharides. This research focuses on extracting carrageenan from Kappaphycus alvarezii, extensively cultivated in Sabah, Malaysia, and utilizing it in combination with starch and glycerol to develop algae-based films. The physicochemical properties and degradation rate of these films were evaluated, revealing that the addition of carrageenan enhanced overall thermal stability meanwhile increasing water solubility, water content but reducing the degradation rate and swelling degree. This is primarily due to the crystalline structures of carrageenan, which provide a more rigid arrangement compared to the network of starch polymers. However, the incorporation of starch into the blends has enhanced the elongation and surface morphology, resulting in more balanced properties. Overall, these carrageenan films displayed impressive thermal, mechanical, and biodegradability characteristics, establishing their viability as substitutes for conventional plastics.

AI-Driven Innovations in Alzheimer's Disease: Integrating Early Diagnosis, Personalized Treatment, and Prognostic Modelling.

Alzheimer's disease (AD) presents a significant challenge in neurodegenerative research and clinical practice due to its complex etiology and progressive nature. The integration of artificial intelligence (AI) into the diagnosis, treatment, and prognostic modelling of AD holds promising potential to transform the landscape of dementia care. This review explores recent advancements in AI applications across various stages of AD management. In early diagnosis, AI-enhanced neuroimaging techniques, including MRI, PET, and CT scans, enable precise detection of AD biomarkers. Machine learning models analyze these images to identify patterns indicative of early cognitive decline. Additionally, AI algorithms are employed to detect genetic and proteomic biomarkers, facilitating early intervention. Cognitive and behavioral assessments have also benefited from AI, with tools that enhance the accuracy of neuropsychological tests and analyze speech and language patterns for early signs of dementia. Personalized treatment strategies have been revolutionized by AI-driven approaches. In drug discovery, virtual screening and drug repurposing, guided by predictive modelling, accelerate the identification of effective treatments. AI also aids in tailoring therapeutic interventions by predicting individual responses to treatments and monitoring patient progress, allowing for dynamic adjustment of care plans. Prognostic modelling, another critical area, utilizes AI to predict disease progression through longitudinal data analysis and risk prediction models. The integration of multi-modal data, combining clinical, genetic, and imaging information, enhances the accuracy of these predictions. Deep learning techniques are particularly effective in fusing diverse data types to uncover new insights into disease mechanisms and progression. Despite these advancements, challenges remain, including ethical considerations, data privacy, and the need for seamless integration of AI tools into clinical workflows. This review underscores the transformative potential of AI in AD management while highlighting areas for future research and development. By leveraging AI, the healthcare community can improve early diagnosis, personalize treatments, and predict disease outcomes more accurately, ultimately enhancing the quality of life for individuals with AD.

Phytochemical, biological, and nutritional properties of the prickly pear, Opuntia dillenii: A review.

Opuntia (Cactaceae) species are native to arid and semi-arid regions of Mexico and the southern United States and grow in various climatic zones. Opuntia dillenii is a cactus fruit with many beneficial properties, and it is used as a medicinal plant in various countries. This review paper provides updated information on the phytochemical and pharmacological aspects of O. dillenii. The fruit contains valuable compounds such as flavonoids, phenolics, ascorbic acid, betanin, and essential elements, which have been isolated and identified. The fruit also exhibits diverse pharmacological activities, such as antioxidant, anti-inflammatory, anti-tumor, neuroprotective, hepatoprotective, hypotensive, anti-diabetic, antifungal, and anticancer effects. Moreover, molecular docking and ADMET predictions were performed to evaluate the antibacterial potential of the fruit against Escherichia coli protein. This paper suggests that O. dillenii has significant potential as a complementary therapy for various pathological conditions.

Insights into medicinal attributes of imidazo[1,2-a]pyridine derivatives as anticancer agents.

Cancer ranks among the most life-threatening diseases worldwide and is continuously affecting all age groups. Consequently, many research studies are being carried out to develop new cancer treatments, but many of them experience resistance and cause severe toxicity to the patients. Therefore, there is a continuous need to design novel anticancer agents that are target-based, have a higher potency, and have minimal toxicity. The imidazo[1,2-a]pyridine (IP) pharmacophore has been found to be a prominent moiety in the field of medicinal chemistry due to its vast biological properties. Also, it holds immense potential for combating cancer with minimal side effects, depending on the substitution patterns of the core structure. IPs exhibit significant capability in regulating various cellular pathways, offering possibilities for targeted anticancer effects. The present review summarizes the anticancer profile of numerous IP derivatives synthesized and developed by various researchers from 2016 till now, as inhibitors of phosphoinositide-3-kinase/mammalian target of rapamycin (PI3K/mTOR), protein kinase B/mammalian target of rapamycin (Akt/mTOR), aldehyde dehydrogenase (ALDH), and tubulin polymerization. This review provides a comprehensive analysis of the anticancer activity afforded by the discussed IP compounds, emphasizing the structure-activity-relationships (SARs). The aim is also to underscore the potential therapeutic future of the IP moiety as a potent partial structure for upcoming cancer drug development and to aid researchers in the field of rational drug design.

A Case of Acute Migraine Without Aura Treated With a New FDA-Approved Medication Ubrogepant.

Ubrogepant is the first medication that blocks calcitonin gene-related peptide (CGRP), a protein released during a migraine attack, from binding to its receptors. Ubrogepant has shown positive safety, efficacy, and tolerability results for the treatment of acute migraine in phase 3 randomized trials. At this time, there are very few case reports on ubrogepant. Herein, we describe a complex patient with treatment-resistant migraine who showed substantial improvement in migraine severity, duration, and overall disability after using ubrogepant. A 46-year-old woman with a 25-year history of migraine presented with an improvement in headache severity, duration, and disability after using a new FDA-approved medication, ubrogepant, for less than five months. Before commencing ubrogepant,her headache duration hours ranged from 36 to 60 hours, headache severity was rated 7.5/10, and mean headache days ranged from 10 to 12 days. After taking ubrogepant, her headache duration was less than 12 hours, headache severity was 3/10, and mean headache days was five. Previously, she had been prescribed a combination of first-line medications with little improvement in headache severity. Her Migraine Disability Assessment (MIDAS) score showed moderate disability resulting in missed work and lower quality of life. To date, there have been no case reports showing the efficacy of the new FDA-approved medication, ubrogepant, showing a greater than 50% decrease in headache duration.

Leveraging AI for the diagnosis and treatment of autism spectrum disorder: Current trends and future prospects.

The integration of artificial intelligence (AI) into the diagnosis and treatment of autism spectrum disorder (ASD) represents a promising frontier in healthcare. This review explores the current landscape and future prospects of AI technologies in ASD diagnostics and interventions. AI enables early detection and personalized assessment of ASD through the analysis of diverse data sources such as behavioural patterns, neuroimaging, genetics, and electronic health records. Machine learning algorithms exhibit high accuracy in distinguishing ASD from neurotypical development and other developmental disorders, facilitating timely interventions. Furthermore, AI-driven therapeutic interventions, including augmentative communication systems, virtual reality-based training, and robot-assisted therapies, show potential in improving social interactions and communication skills in individuals with ASD. Despite challenges such as data privacy and interpretability, the future of AI in ASD holds promise for refining diagnostic accuracy, deploying telehealth platforms, and tailoring treatment plans. By harnessing AI, clinicians can enhance ASD care delivery, empower patients, and advance our understanding of this complex condition.

Integrating the quintuple helix approach into atmospheric microplastics management policies for planetary health preservation.

Microplastic pollution (MP) has become a major global environmental issue, negatively impacting terrestrial and aquatic ecosystems as well as human health. Tackling this complex problem necessitates a multidisciplinary approach and collaboration among diverse stakeholders. Within this context, the Quintuple Helix framework, which highlights the involvement of academia, government, industry, civil society, and the environment, provides a comprehensive and inclusive perspective for formulating effective policies to manage atmospheric microplastics. This paper discusses each helix's roles, challenges, and opportunities and proposes strategies for collaboration and knowledge exchange among them. Furthermore, the paper highlights the importance of interdisciplinary research, innovative technologies, public awareness campaigns, regulatory frameworks, and corporate responsibility in achieving sustainable and resilient microplastic management policies. The Quintuple Helix approach can mitigate MP, safeguard ecosystems, and preserve planetary health by fostering collaboration and coordination among diverse stakeholders.

Adsorption parameters optimization of spent coffee ground biochar for methylene blue removal using response surface methodology.

This study investigates the potential of spent coffee ground biochar (SCGB) as a sustainable and cost-effective adsorbent for the removal of methylene blue (MB), a hazardous dye commonly used in the textile and printing industries. A response surface methodology (RSM) approach with central composite design (CCD) was employed to systematically investigate the effects of key process parameters, including adsorbent dosage, solution pH, contact time and temperature, on MB removal efficiency. The analysis revealed that adsorbent dosage and temperature as critical factors influencing MB removal, with a linear model providing a strong correlation. Optimal conditions for MB removal were determined to be 0.99 g of SCGB, 30 min of contact time, 30 °C temperature, and a solution pH of 7. Under these conditions, MB removal reached 99.99%, with a desirability of 1.000. The experimental results closely matched the predicted values, differing by only 0.02%, thus validating the accuracy of the model. Kinetic studies indicated a rapid adsorption process, well-described by both pseudo-first and pseudo-second order models. Isotherm analysis confirmed the applicability of the Freundlich model, suggesting favorable adsorption with increasing MB concentration. The high adsorption capacity of SCGB is attributed to its carbonaceous and porous structure, highlighting its potential as an effective adsorbent for dye removal in wastewater treatment applications.

Bio fabricated palladium nano particles using phytochemicals from aqueous cranberry fruit extract for anti-bacterial, cytotoxic activities and photocatalytic degradation of anionic dyes.

The low cost and ecological compatibility of green technology makes it superior to chemical approaches in the generation of metal nanoparticles. The current study shows the use of cranberry fruit extract in the environmentally friendly green production of palladium nanoparticles. It is well known that the fruit extract from cranberries has a rich phytochemical composition that makes it a useful bio reducing agent for the formation of PdNPs. Several spectroscopic techniques, including ultraviolet-visible spectroscopy (UV-vis), X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and energy-dispersive X-ray spectroscopy (EDX), were used to characterize the palladium nanoparticles (PdNPs). The diffractogram of the XRD analysis shows significant reflections at 39.98° (111), 46.49° (200), and 67.95° (220), which indicate the face-centered cubic (FCC) structure of PdNPs and demonstrate the crystallinity of the produced nanoparticles from the green method. The SEM and TEM structural and morphological analyses reveal that the synthesized nanoparticles have a spherical shape with size ranging between 2 nm to 50 nm. In addition, the synthesized PdNPs demonstrated possible antibacterial activity on both Gram-positive and Gram-negative bacteria as well as a cytotoxic effect on the MCF-7 breast cancer cell line. The degradation of Indigo Carmine (IC) and Sunset Yellow (SY) dyes can be effectively catalyzed by biogenic PdNPs, according to the results.

A comprehensive review on the enantiomeric separation of chiral drugs using metal-organic frameworks.

Chiral drugs play an important role in modern medicine, but obtaining pure enantiomers from racemic mixtures can pose challenges. When a drug is chiral, only one enantiomer (eutomer) typically exhibits the desired pharmacological activity, while the other (distomer) may be biologically inactive or even toxic. Racemic drug formulations introduce additional health risks, as the body must still process the inactive or detrimental enantiomer. Some distomers have also been linked to teratogenic effects and unwanted side effects. Therefore, developing efficient and scalable methods for separating chiral drugs into their pure enantiomers is critically important for improving patient safety and outcomes. Metal-organic frameworks (MOFs) show promise as novel materials for chiral separation due to their highly tunable structures and interactions. This review summarizes recent advancements in using MOFs for chromatographic and spectroscopic resolution of drug enantiomers. Both the opportunities and limitations of MOF-based separation techniques are discussed. A thorough understanding of these methods could aid the continued development of pure enantiomer formulations and help reduce health risks posed by racemic drug mixtures.

Integrating knowledge graphs into machine learning models for survival prediction and biomarker discovery in patients with non-small-cell lung cancer.

Accurate survival prediction for Non-Small Cell Lung Cancer (NSCLC) patients remains a significant challenge for the scientific and clinical community despite decades of advanced analytics. Addressing this challenge not only helps inform the critical aspects of clinical study design and biomarker discovery but also ensures that the 'right patient' receives the 'right treatment'. However, survival prediction is a highly complex task, given the large number of 'omics; and clinical features, as well as the high degree of freedom that drive patient survival. Prior knowledge could play a critical role in uncovering the complexity of a disease and understanding the driving factors affecting a patient's survival. We introduce a methodology for incorporating prior knowledge into machine learning-based models for prediction of patient survival through Knowledge Graphs, demonstrating the advantage of such an approach for NSCLC patients. Using data from patients treated with immuno-oncologic therapies in the POPLAR (NCT01903993) and OAK (NCT02008227) clinical trials, we found that the use of knowledge graphs yielded significantly improved hazard ratios, including in the POPLAR cohort, for models based on biomarker tumor mutation burden compared with those based on knowledge graphs. Use of a model-defined mutational 10-gene signature led to significant overall survival differentiation for both trials. We provide parameterized code for incorporating knowledge graphs into survival analyses for use by the wider scientific community.

Folate-conjugated carbon nanotubes as a promising therapeutic approach for targeted cancer therapy.

Conventional systemic cancer therapy often causes numerous adverse events. However, discovering overexpressed folate receptors in solid tumours has paved the way for targeted chemotherapy. Folic acid (FA), a ligand for these receptors, is frequently combined with chemotherapeutic drugs to improve their effectiveness. Carbon nanotubes have emerged as a versatile and promising method for delivering these folate-conjugated nano-systems, ensuring targeted delivery of therapeutic agents to cancerous cells. When FA-conjugated nanotubes dissociate, they release the drug-loaded nanotubes inside the malignant cells, reducing off-target effects. These nanotubes can also be used for combination therapies, producing synergistic effects. This review aims to comprehensively gather and critically evaluate the latest methods for delivering therapeutics using FA-conjugated nanovehicles. Additionally, it seeks to enhance our comprehension of the pertinent chemistry and biochemical pathways involved in this approach.

Gallic acid loaded self-nano emulsifying hydrogel-based drug delivery system against onychomycosis.

Aim: To developed and investigate gallic acid (GA) loaded self-nanoemulsifying drug delivery systems (SNEDDS) for treating onychomycosis via transungual route. Materials & methods: The SNEDDS were prepared by direct dispersion technique and were evaluated for characteristics parameters using Fourier transform infrared, differential scanning calorimetry, confocal microscopy, transmission electron microscopy and zeta sizer. Furthermore, the safety of prepared formulation was evaluated via Hen's egg test-chorioallantoic membrane study and stability was confirmed using different parameters. Also, its effectiveness was evaluated against fungal strain Trichophyton mentagrophytes. Results: The SNEDDS displayed a particle size of 199.8 ± 4.21 nm and a zeta potential; of -22.75 ± 2.09 mV. Drug release study illustrated a sustained release pattern with a release of 70.34 ± 0.20% over a period of 24 h. The penetration across the nail plate was found to be 1.59 ± 0.002 µg/mg and 0.97 ± 0.001 µg/mg for GA loaded SNEDDS and GA solution respectively. An irritation score of 0.52 ± 0.005 and 3.84 ± 0.001 was reported for GA loaded SNEDDS hydrogel and GA solution, indicating a decrease in the drug's irritation potential from slightly irritating to non irritating due to its entrapment within the SNEDDS. Conclusion: GA loaded SNEDDS has potential to address limitations of conventional treatments, enhancing the drug's efficacy and reducing the likelihood of resistance in the treatment of Onychomycosis.

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A state-of-the-art review of metal oxide nanoflowers for wastewater treatment: Dye removal.

Dye wastewater consists of high solids concentrations, heavy metals, minor contaminants, dissolved chemical oxygen demand, and microorganisms. Nanoflowers are nanoparticles that resemble flowers when viewed at a microscopic level. Inorganic metal oxide nanoflowers have been discovered to be a potential source for overcoming this situation. Their flower-like features give them a higher surface area to volume ratio and porosity structure, which can absorb a significant amount of dye. The metal oxide nanoflower synthesized from different synthesis methods is used to compare which one is cost-effective and capable of generating a large scale of nanoflower. This review has demonstrated outstanding dye removal efficiency by applying inorganic nanoflowers to dye removal. Since both adsorption and photocatalytic reactions enhance the dye degradation process, complete dye degradation could be achieved. Meanwhile, the inorganic metal oxide nanoflowers' exemplary reusability characteristics with negligible performance drop further prove that this approach is highly sustainable and may help to save costs. This review has proven the momentum of obtaining high dye removal efficiency in wastewater treatment to conclude that the metal oxide nanoflower study is worth researching.

Advances in artificial intelligence for drug delivery and development: A comprehensive review.

Artificial intelligence (AI) has emerged as a powerful tool to revolutionize the healthcare sector, including drug delivery and development. This review explores the current and future applications of AI in the pharmaceutical industry, focusing on drug delivery and development. It covers various aspects such as smart drug delivery networks, sensors, drug repurposing, statistical modeling, and simulation of biotechnological and biological systems. The integration of AI with nanotechnologies and nanomedicines is also examined. AI offers significant advancements in drug discovery by efficiently identifying compounds, validating drug targets, streamlining drug structures, and prioritizing response templates. Techniques like data mining, multitask learning, and high-throughput screening contribute to better drug discovery and development innovations. The review discusses AI applications in drug formulation and delivery, clinical trials, drug safety, and pharmacovigilance. It addresses regulatory considerations and challenges associated with AI in pharmaceuticals, including privacy, data security, and interpretability of AI models. The review concludes with future perspectives, highlighting emerging trends, addressing limitations and biases in AI models, and emphasizing the importance of collaboration and knowledge sharing. It provides a comprehensive overview of AI's potential to transform the pharmaceutical industry and improve patient care while identifying further research and development areas.

Development of Lipid Polymer Hybrid Nanoparticles of Abietic Acid: Optimization, In-Vitro and Preclinical Evaluation.

The objective of the current research was to develop abietic acid (AA)-loaded hybrid polymeric nanoparticles (HNPs) for anti-inflammatory and antioxidant activity after oral administration. AAHNPs were developed by microinjection technique and optimized by 3-factor 3-level Box-Behnken design. The AAHNPs were evaluated for morphology, FTIR, X-ray diffraction, in-vitro release, ex-vivo permeation, in-vitro antioxidant, and in-vivo anti-inflammatory activity. The optimized AAHNPs (AAHNPsopt) displayed 384.5 ± 6.36nm of PS, 0.376 of PDI, 23.0 mV of ZP, and 80.01 ± 1.89% of EE. FTIR and X-ray diffraction study results revealed that AA was encapsulated into a HNPs matrix. The AAHNPsopt showed significant (P < 0.05) high and sustained release of AA (86.72 ± 4.92%) than pure AA (29.87 ± 3.11%) in 24h. AAHNPsopt showed an initial fast release of AA (20.12 ± 3.07% in 2h), which succeeded in reaching the therapeutic concentration. The AAHNPsopt showed 2.49-fold higher ex-vivo gut permeation flux than pure AA due to the presence of lipid and surfactant. The AAHNPsopt exhibited significantly (P < 0.05, P < 0.01, P < 0.001) higher antioxidant activity as compared to pure AA at each concentration. AAHNPsopt formulation displayed a significantly (P < 0.05) higher anti-inflammatory effect (21.51 ± 2.23% swelling) as compared to pure AA (46.51 ± 1.74% swelling). From the in-vitro and in-vivo finding, it was concluded that HNPs might be a suitable carrier for the improvement of the therapeutic efficacy of the drug.

Investigating mechanistic insights of curcumin in blocking the Interleukin-8 signaling pathway associated with Breast Cancer: An in-silico approach.

Interleukin-8 (IL-8) is a chemokine, a type of signaling molecule that has a role in immunological responses and inflammation. In recent years, IL-8 is additionally related to cancer growth and recurrence. Breast cancer growth, progression, and metastatic development are all linked to IL-8. Breast cancer cells are known to develop faster when IL-8 stimulates their proliferation and survival. It can also cause angiogenesis, or the creation of new blood vessels, which is necessary for tumor nutrition and growth. IL-8 and curcumin have been subjects of interest in drug design, particularly in the context of inflammation-related disorders and cancer. This study aims to give an overview of the role of IL-8. Inhibitor-based treatment approaches were being used to target IL-8 with curcumin. Molecular docking method was employed to find a potential interaction to supress competitive inhibition of IL-8 with curcumin. PASS analysis and ADMET characteristics were also being carried out. In the end, IL-8 complexed with curcumin is chosen for MD simulations. Overall, our results showed that during the simulation, the complex stayed comparatively stable. It is also possible to investigate curcumin further as a possible treatment option. The combined results imply that IL-8 and their genetic alterations can be studied in precision cancer therapeutic treatments, utilizing target-driven therapy and early diagnosis.

Environmental implications and nanotechnological advances in octocrylene-enriched sunscreen formulations: A comprehensive review.

Ultraviolet (UV) radiation is a major contributor to skin aging, cancer, and other detrimental health effects. Sunscreens containing FDA-approved UV filters, like avobenzone, offer protection but suffer from photodegradation and potential phototoxicity. Encapsulation, antioxidants, and photostabilizers are strategies employed to combat these drawbacks. Octocrylene, an organic UV filter, utilizes nanotechnology to enhance sun protection factor (SPF). This review examines recent literature on octocrylene-enriched sunscreens, exploring the interplay between environmental impact, nanotechnological advancements, and clinical trial insights. A critical focus is placed on the environmental consequences of sunscreen use, particularly the potential hazards UV filters pose to marine ecosystems. Research in the Mediterranean Sea suggests bacterial sensitivity to these filters, raising concerns about their integration into the food chain. This review aims to guide researchers in developing effective strategies for photostabilization of UV filters. By combining encapsulation, photostabilizers, and antioxidants, researchers can potentially reduce phototoxic effects and contribute to developing more environmentally friendly sunscreens.

Investigating the adsorption potential of char derived from waste latex for methylene blue removal.

This study presents the adsorption of methylene blue (MB) dye using latex char derived from pyrolysis of latex gloves. The adsorption process was investigated systematically using Response Surface Methodology (RSM) with a Central Composite Design (CCD). The effects of four key variables, namely pH, time, temperature, and adsorbent dosage, were studied using a factorial design enriched with center points and axial points. Experimental data were analyzed using a second-order polynomial regression model to construct a response surface model, which elucidated the relationship between the variables and MB removal efficiency. The study found that the char obtained at 800 °C exhibited the highest adsorption capacity due to its increased carbonization, expanded surface area, and diverse pore structure. Analysis of Variance (ANOVA) confirmed the significance of the quadratic model, with remarkable agreement between predicted and experimental outcomes. Diagnostic plots validated the model's reliability, while 3D contour graphs illustrated the combined effects of variables on MB removal efficiency. Optimization using DoE software identified optimal conditions resulting in a 99% removal efficiency, which closely matched experimental results. Additionally, adsorption isotherms revealed that the Freundlich model best described the adsorption behavior, indicating heterogeneous surface adsorption with multilayer adsorption. This comprehensive study provides valuable insights into the adsorption process of MB dye using latex char, with implications for wastewater treatment and environmental remediation.

Evaluation of the effect of precursor ratios on the electrochemical performances of binder-free NiMn-phosphate electrodes for supercapattery.

Binary metal phosphate electrodes have been widely studied for energy storage applications due to the synergistic effects of two different transition elements that able to provide better conductivity and stability. Herein, the battery-type binder-free nickel-manganese phosphate (NiMn-phosphate) electrodes were fabricated with different Ni:Mn precursor ratios via microwave-assisted hydrothermal technique for 5 min at 90 °C. Overall, NiMn3P electrode (Ni:Mn = 1:3) showed an outstanding electrochemical performance, displaying the highest specific (areal) capacity at 3 A/g of 1262.4 C/g (0.44 C/cm2), and the smallest charge transfer resistance of 108.8 Ω. The enhanced performance of NiMn3P electrode can be ascribed to the fully grown amorphous nature and small-sized flake and flower structures of NiMn3P electrode material on the nickel foam (NF) surface. This configuration offered a higher number of active sites and a larger exposed area, facilitating efficient electrochemical reactions with the electrolyte. Consequently, the NiMn3P//AC electrode combination was chosen to further investigate its performance in supercapattery. The NiMn3P//AC supercapattery exhibited remarkable energy density of 105.4 Wh/kg and excellent cyclic stability with 84.7% retention after 3000 cycles. These findings underscored the superior electrochemical performance of the battery-type binder-free NiMn3P electrode, and highlight its potential for enhancing the overall performance of supercapattery.