Synergistic Potential Research Articles

Low‐cost 0D and 2D carbon material co‐decorated titanium dioxide ternary heterojunction for rapid and efficient bacteria killing under visible light

AbstractRecently, the issue of bacterial resistance has gotten worse because of the overuse of antibiotics. The newborn superbacteria, such as vancomycin‐resistant bacteria, were hard to kill, inspiring researchers to find new ways to kill the bacteria efficiently. TiO2 was used as an efficient photocatalyst for water splitting and pollutant degradation. However, the weak efficiency limited the application to solve the drug‐resistance problem. Consequently, the incorporation of low‐cost 0D carbon quantum dots (CQDs) and 2D graphene oxide (GO) was pursued to amplify the visible light absorption capabilities of TiO2 and thereby elevate its photocatalytic activity. After forming the heterogeneous interface of CQDs and TiO2, CQDs converted part of visible light into wavelength less than 400 nm using the up‐conversion property. The modification of CQDs enabled electrons to be easily transferred from the conduction band of CQDs to the conduction band of TiO2. Meanwhile, GO can act as an electron acceptor, reduce the recombination efficiency of holes and electrons, and transfer the photogenerated electrons in the redox reaction in the heterogeneous interface. Because of the excellent absorption of GO, TiO2/CQDs/GO reached 57.8°C after 20 min irradiation under 1.5 times sunlight, which provided a prerequisite for photodynamic antibacterial therapy/photothermal antibacterial therapy synergistic antibacterial potential. TiO2/CQDs/GO possessed an antibacterial efficiency as high as 99.3% toward Staphylococcus aureus which has a bright future in disinfection in vivo and medical devices as well as water sterilization.

Enhancing therapy with nano-based delivery systems: exploring the bioactive properties and effects of apigenin.

Apigenin, a potent natural flavonoid, has emerged as a key therapeutic agent due to its multifaceted medicinal properties in combating various diseases. However, apigenin's clinical utility is greatly limited by its poor water solubility, low bioavailability and stability issues. To address these challenges, this review paper explores the innovative field of nanotechnology-based delivery systems, which have shown significant promise in improving the delivery and effectiveness of apigenin. This paper also explores the synergistic potential of co-delivering apigenin with conventional therapeutic agents. Despite the advantageous properties of these nanoformulations, critical challenges such as scalable production, regulatory approvals and comprehensive long-term safety assessments remain key hurdles in their clinical adoption which must be addressed for commercialization of apigenin-based formulations.

Exploring the impact of acetylsalicylic acid and conditioned medium obtained from mesenchymal cells, individually and in combination, on cognitive function, histological changes, and oxidant-antioxidant balance in male rats with hippocampal injury.

The hippocampus is susceptible to damage, leading to negative impacts on cognition. Conditioned medium (CM) obtained from adipose tissue-derived mesenchymal stem cells (MSCs) and acetylsalicylic acid (ASA) have shown neuroprotective effects independently. This study explored the synergistic potential of ASA and CM from adipose-derived MSCs against hippocampal injury. Adult male Wistar rats received bilateral hippocampal ethidium bromide (EB) injections to induce hippocampal damage. Rats were treated with ASA and/or CM derived from adipose tissue MSCs every 48h for 16 days. Behavioral tests (open field test, Morris water maze, novel object recognition, and passive avoidance), oxidative stress, Western blot analysis of brain-derived neurotrophic factor (BDNF) and cerebral dopamine neurotrophic factor (CDNF) expression, and hippocampal histological investigation were conducted. Administration of EB caused impairments in spatial, recognition, and passive avoidance memory, as well as heightened oxidative stress, reduced BDNF/CDNF expression, and pyramidal cell loss in the hippocampal CA1 region. Administration of ASA, CM, or a combination of both mitigated these hippocampal damages and cognitive deficits, elevated BDNF and CDNF levels, and alleviated the CA1 necrosis caused by EB. Moreover, co-administering ASA and CM resulted in greater improvements in spatial memory compared to administering ASA alone, suggesting possible synergistic interactions. The ability of ASA, CM obtained from adipose tissue-derived MSCs, and their combination therapy to alleviate hippocampal injuries highlights their promising therapeutic potential as a neuroprotection strategy against brain damage. Our findings provide preliminary evidence of the potential synergistic effects of ASA and CM, which warrants further investigations.

Co-amorphous systems of sulfasalazine with matrine-type alkaloids: Enhanced solubility behaviors and synergistic therapeutic potential

Sulfasalazine (SULF), a sulfonamide antibiotic, has been utilized in the treatment of rheumatoid arthritis (RA) and inflammatory bowel disease (IBD) since its discovery. However, its poor water solubility causes the high daily doses (1–––3 g) for patients, which may lead to the intolerable toxic and side effects for their lifelong treatment for RA and IBD. In this work, two water-soluble natural anti-inflammatory alkaloids, matrine (MAR) and sophoridine (SPD), were employed to construct the co-amorphous systems of SULF for addressing its solubility issue. These newly obtained co-amorphous forms of SULF were comprehensively characterized by powder X-ray diffraction (PXRD), temperature-modulated differential scanning calorimetry (mDSC), Fourier-transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS). We also investigated their dissolution behavior, including powder dissolution, in vitro release, and intrinsic dissolution rate. Both co-amorphous systems exhibited superior dissolution performance compared to crystalline SULF. The underlying mechanism responsible for the enhanced dissolution behaviors in co-amorphous systems were also elucidated. These mechanisms include the inhibition of nucleation, complexation, increased hydrophilicity, and robust intermolecular interactions in aqueous solutions. Importantly, these co-amorphous systems demonstrated satisfactory physical stability under various storage conditions. Network pharmacological analysis was utilized to investigate the potential therapeutic targets of both co-amorphous systems against RA, revealing similar yet distinct multi-target synergistic therapeutic mechanisms in the treatment of this condition. Our study suggests these drug-drug co-amorphous systems hold promise for optimizing SULF dosage in the future and providing a potential drug combination strategy.

The LAMB3-EGFR signaling pathway mediates synergistic Anti-Cancer effects of berberine and emodin in Pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy, primarily due to the intrinsic development of chemoresistance. The most apparent histopathological feature associated with chemoresistance is the alterations in extracellular matrix (ECM) proteins. Natural dietary botanicals such as berberine (BBR) and emodin (EMO) have been shown to possess chemo-preventive potential by regulating ECM in various cancers. Herein, we further investigated the potential synergistic effects of BBR and EMO in enhancing anticancer efficacy by targeting ECM proteins in pancreatic cancer. Genomewide transcriptomic profiling identified that LAMB3 was significantly upregulated in PDAC tissue and highly associated with poor overall survival (OS, hazard ratio [HR], 2.99, 95 % confidence interval [CI], 1.46–6.15; p = 0.003) and progress-free survival (PFS, HR, 2.59; 95 % CI, 1.30–5.18; p = 0.007) in PDAC. A systematic series of functional experiments in BxPC-3 and MIA-PaCa-2 cells revealed that the combination of BBR and EMO exhibited synergistic anti-tumor potential, as demonstrated by cell proliferation, clonogenicity, migration, and invasion assays (p < 0.05–0.001). The combination also altered the expression of key proteins involved in apoptosis, EMT, and EGFR/ERK1,2/AKT signaling. These findings were further supported by patient-derived organoids (PDOs), where the combined treatment resulted in fewer and smaller organoids compared to each compound individually (p < 0.05–0.001). Our results suggest that BBR combined with EMO exerts synergistic anti-cancer effects by modulating the EGFR-signaling pathway through interference with LAMB3 in PDAC.

The Synergistic Potential of Hydrogel Microneedles and Nanomaterials: Breaking Barriers in Transdermal Therapy.

The stratum corneum, which acts as a strong barrier against external agents, presents a significant challenge to transdermal drug delivery. In this regard, microneedle (MN) patches, designed as modern systems for drug delivery via permeation through the skin with the ability to pass through the stratum corneum, are known to be convenient, painless, and effective. In fact, MN have shown significant breakthroughs in transdermal drug delivery, and among the various types, hydrogel MN (HMNs) have demonstrated desirable inherent properties. Despite advancements, issues such as limited loading capacity, uncontrolled drug release rates, and non-uniform therapeutic approaches persist. Conversely, nanomaterials (NMs) have shown significant promise in medical applications, however, their efficacy and applicability are constrained by challenges including poor stability, low bioavailability, limited payload capacity, and rapid clearance by the immune system. Incorporation of NMs within HMNs offers new prospects to address the challenges associated with HMNs and NMs. This combination can provide a promising field of research for improved and effective delivery of therapeutic agents and mitigate certain adverse effects, addressing current clinical concerns. The current review highlights the use of NMs in HMNs for various therapeutic and diagnostic applications.

Customized Heteronuclear Dual Single-Atom and Cluster Assemblies via D-Band Orchestration for Oxygen Reduction Reaction.

Advanced oxygen reduction reaction (ORR) catalysts, integrating with well-dispersed single atom (SA) and atomic cluster (AC) sites, showcase potential in bolstering catalytic activity. However, the precise structural modulation and in-depth investigation of their catalytic mechanisms pose ongoing challenges. Herein, a proactive cluster lockdown strategy is introduced, relying on the confinement of trinuclear clusters with metal atom exchange in the covalent organic polymers, enabling the targeted synthesis of a series of multicomponent ensembles featuring FeCo (Fe or Co) dual-single-atom (DSA) and atomic cluster (AC) configurations (FeCo-DSA/AC) via thermal pyrolysis. The designed FeCo-DSA/AC surpasses Fe- and Co-derived counterparts by 18 mV and 49 mV in ORR half-wave potential, whilst exhibiting exemplary performance in Zn-air batteries. Comprehensive analysis and theoretical simulation elucidate the enhanced activity stems from adeptly orchestrating dz 2-dxz and O 2p orbital hybridization proximate to the Fermi level, fine-tuning the antibonding states to expedite OH* desorption and OOH* formation, thereby augmenting catalytic activity. This work elucidates the synergistic potentiation of active sites in hybrid electrocatalysts, pioneering innovative targeted design strategies for single-atom-cluster electrocatalysts.

Novel Strategy for Human Deep Vein Thrombosis Diagnosis Based on Metabolomics and Stacking Machine Learning.

Deep vein thrombosis (DVT) is a serious health issue that often leads to considerable morbidity and mortality. Diagnosis of DVT in a clinical setting, however, presents considerable challenges. The fusion of metabolomics techniques and machine learning methods has led to high diagnostic and prognostic accuracy for various pathological conditions. This study explored the synergistic potential of dual-platform metabolomics (specifically, gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS)) to expand the detection of metabolites and improve the precision of DVT diagnosis. Sixty-one differential metabolites were identified in serum from DVT patients: 22 from GC-MS and 39 from LC-MS. Among these, five key metabolites were highlighted by SHapley Additive exPlanations (SHAP)-guided feature engineering and then used to develop a stacking diagnostic model. Additionally, a user-friendly interface application system was developed to streamline and automate the application of the diagnostic model, enhancing its practicality and accessibility for clinical use. This work showed that the integration of dual-platform metabolomics with a stacking machine learning model enables faster and more accurate diagnosis of DVT in clinical environments.

Pectin functionalized with Cu/Fe nanoparticles for enhanced degradation of methylene blue from wastewater

IntroductionIn the present study, citrus pectin-stabilized copper/iron bimetallic nanoparticle (NP) catalyst has been used for the degradation of methylene blue (MB) dye in wastewater produced from the food industry.MethodsThe P@Cu/Fe composites were synthesized by co-precipitation and the sol–gel methods.Results and discussionThe characterization of the composites was carried out using UV, FTIR, SEM, and XRD techniques, revealing that P1@Cu/FeNPs synthesized through co-precipitation had a particle size of 150–35 nm with an irregular spherical and hexagonal shape. P2@Cu/FeNPs, synthesized using the gel combustion method using triethylamine as fuel, proved to be a better nanocatalyst with spherical particles having a uniform structure and size distribution of 105–23 nm. The mean zeta potential value of P1@Cu/FeNPs was found to be between 0 and 5mv, showing the composite to be less stable and 13 mv for more stable P2@Cu/FeNPs. The degradation of MB by P1@Cu/FeNPs was recorded up to 23.57% after 35 min and the nanocomposite synthesized by the sol–gel method exhibited 97.28% degradation in 30 min. The P2@Cu/FeNPs performed the best degradation due to their synergistic impact. In essence, this research represents a step toward the synthesis of bimetallic NPs using a biomaterial (citrus pectin) with improved synergistic photocatalytic potential that can induce different features in nanomaterials. Pectin-functionalized NPs using different metals should be synthesized and tested for different catalytic applications.

Synergistic and antagonistic drug interactions are prevalent but not conserved across acute myeloid leukemia cell lines.

Acute myeloid leukemia (AML) is the most prevalent type of leukemia in adults. Its heterogeneity, both between patients and within the same patient, is often a factor contributing to poor treatment outcomes. Despite advancements in AML biology and medicine in general, the standard AML treatment, the combination of cytarabine and daunorubicin, has remained the same for decades. Combination drug therapies are proven effective in achieving targeted efficacy while minimizing drug dosage and unintended side effects, a common problem for older AML patients. However, a systematic survey of the synergistic potential of drug-drug interactions in the context of AML pathology is lacking. Here, we examine the interactions between 15 commonly used cancer drugs across distinct AML cell lines and demonstrate that synergistic and antagonistic drug-drug interactions are widespread but not conserved across these cell lines. Notably, enasidenib and venetoclax, recently approved anticancer agents, exhibited the highest counts of synergistic interactions and the fewest antagonistic ones. In contrast, 6-Thioguanine, a purine analog, was involved in the highest number of antagonistic interactions. The interactions we report here cannot be attributed solely to the inherent natures of these three drugs, as each drug we examined was involved in several synergistic or antagonistic interactions in the cell lines we tested. Importantly, these drug-drug interactions are not conserved across cell lines, suggesting that the success of combination therapies might vary significantly depending on AML genotypes. For instance, we found that a single mutation in the TF1 cell line could dramatically alter drug-drug interactions, even turning synergistic interactions into antagonistic ones. Our findings provide a preclinical survey of drug-drug interactions, revealing the complexity of the problem.

Combined endodontic and regenerative periodontal therapy for managing questionable mandibular anterior teeth with radicular cysts

Abstract Endodontic microsurgery (EMS) presents a great treatment option for unresolved periradicular pathologies, typically involving the removal of the apical root portion and adjacent inflamed tissues. This case report describes the management of persistent periapical lesions in the lower anterior teeth of a 32-year-old male. Root canal treatment was completed 4 years before presentation. The patient presented to the clinic with tooth mobility and mild discomfort and large radiographical periapical radiolucency. The case was diagnosed with previously treated with asymptomatic apical periodontitis. EMS was performed in conjunction with periodontal-guided tissue regeneration that includes bone graft and resorbable membrane and the teeth showed favorable resolution of the symptoms. Histopathological analysis showed the presence of a radicular cyst. After 3 years of follow-up, cone-beam computed tomography and periapical radiographs demonstrated substantial lesion regression and favorable outcome. This case report offering promising insights into the synergistic potential of combined endodontic and regenerative periodontal therapy in cases with unresolved periapical lesion with extensive bone destruction.

Synergistic potential of essential oil combinations against Microsporum, Trichophyton, and Epidermophyton.

Dermatophyte infections globally account for 20 to 25% of fungal infections. Dermatophytes have begun exhibiting antifungal drug resistance, making it challenging to treat this particular infection. Essential oils could be used as alternative solutions as they have been used for a long period to treat different infections. The research has demonstrated the antifungal efficacy of cinnamon, clove, lemongrass, tea tree, thyme, and garlic essential oils, and the impact of their combinations was assayed against Microsporum canis, Trichophyton tonsurans, T. violaceum, T. verrucosum, and Epidermophyton floccosum. Polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP) was used to identify the most prevalent M. canis. The accession number of M. canis was obtained as ON007275. All tested essential oils exhibited antidermatophytic action except garlic. A synergistic effect was attained by cinnamon + clove, cinnamon + lemongrass, clove + lemongrass, clove + tea tree, and thyme + tea tree combinations. Concerning antifungal activity, M. canis was the most susceptible dermatophytic species, except in the case of thyme T. violaceum, which was the most susceptible dermatophytic species. The maximum inhibition was recorded in the cases of cinnamon and cinnamon + lemongrass combination against M. canis. The least minimum inhibitory concentrations were attained by cinnamon and clove against M. canis, cinnamon + clove against M. canis and T. violaceum, and cinnamon + lemongrass against M. canis, T. violaceum, T. verrucosum, and E. floccosum. The least minimum fungicidal concentration showed by cinnamon against M. canis, cinnamon + clove against M. canis and T. violaceum, cinnamon + lemongrass against M. canis, T. violaceum, T. verrucosum, and E. floccosum, and clove + lemongrass against M. canis.

Synergistic degradation of p-nitrophenol using peroxymonosulfate activated with a bimetallic Mn3O4–Cu2O catalyst: Investigation of strong interactions between metal oxides

The use of efficient, eco-friendly catalysts is essential for activating peroxymonosulfate (PMS) to degrade organic contaminants in aqueous media. In this study, we developed a novel approach to fabricating bimetallic MnCu catalysts (Mn:Cu molar ratios: 10:1, 5:1, 3:1, and 2:1) comprising tetragonal Mn3O4 and cubic Cu2O. MnCu-5:1 exhibited superior catalytic activity for the degradation of p-nitrophenol (PNP) using PMS because of the synergistic interplay between Mn and Cu. Experimental and density functional theory (DFT) calculation data revealed that the mixed valence states and strong interactions between Mn and Cu in the MnCu-5:1 system increased the electron transfer efficiency and promoted electron transfer to PMS. The results of quenching experiments elucidated a primary radical mechanism and minor nonradical pathway for the PNP degradation over the MnCu-5:1/PMS system. DFT calculations confirmed a relatively high adsorption energy of the Mn3O4–Cu2O (MnCu) composite, indicating enhanced catalytic performance. The superior reactivity of the composite was verified by analyzing its density of states and electrostatic difference potential. Our findings offer fresh perspectives for harnessing the synergistic potential of less toxic mixed metal oxides for controlling catalytic properties and help achieve a better understanding of the activation mechanism for contaminant degradation over MnCu catalysts.

Stereolithographic 3D Printing of Intrinsically Flame‐Retardant Shape‐Memory Polymers

AbstractThis study presents a novel approach to fabricate 3D‐printed phosphorous‐based acrylate monomers using stereolithographic 3D printing technology, aiming to create demonstrators with exceptional shape‐memory characteristics and robust flame retardant properties. The synthesized materials combine the advantages of 3D printing precision with the intrinsic flame retardancy of phosphorous‐based monomers, offering a versatile solution for applications requiring both shape memory functionality and fire resistance. The limiting oxygen index (LOI) value of the intrinsically flame‐retardant shape‐memory polymer (IFR‐SMP) can reach 34%, and the vertical combustion rating after UL 94 can obtain V‐0. The mechanism of the IFR‐SMP flame retardant mainly includes terminating a free‐radical chain reaction and gas phase dilution, which indicates that the gas‐phase mechanism plays an important role in the flame retardancy. This work advances the frontiers of 3D printing technology by demonstrating the synergistic potential of shape memory and flame retardancy within a single material system, providing a pathway toward the development of innovative and resilient materials for the future.

Synergistic Anti-Dermatophytic Potential of Nanoparticles and Essential Oils Combinations

AbstractConventional antifungal therapies becoming less effective in treating dermatophytic infections. For this reason, researchers are looking for alternative treatments. The current research has tested the antifungal efficacy of eight novel synthesized metallic nanoparticle compounds: Ag0.49Cr2.51O4, Ag0.99Fe1.01O3, CoLa0.019Fe1.981O4, Co0.99Fe1.99O4, Ag0.99Cr1.01O2, Ca0.99Fe1.99O4, CoBi0.019Fe1.981O4, and Cu0.99Fe1.99O4 were synthesized by a flash auto-combustion reaction to evaluate synergistic potential of the Np’s exhibited antifungal activity in combination with Cinnamon, clove, lemongrass, tea tree and thyme essential oils extracted by soxhlet method against Microsporum canis, Trichophyton tonsurans, T. violaceum, T. verrucosum, and Epidermophyton floccosum. Four nanoparticle compounds exhibited antifungal activity which were: Ag0.49Cr2.51O4, Ag0.99Fe1.01O3, CoLa0.019Fe1.981O4, and Co0.99Fe1.99O4 against all tested dermatophytes. Maximum inhibition was recorded in the cases of Ag0.99Fe1.01O3, Ag0.99Fe1.01O3 + cinnamon against M.canis. Least minimum inhibitory concentrations were attained by Cinnamon against M. canis, Ag0.99Fe1.01O3 against M.canis, T. tonsurans, and T.violaceum, Ag0.99Fe1.01O3+Cinnamon against M. canis, T. violaceum and, T. verrucosum, Ag0.99Fe1.01O3 + Clove, and Ag0.99Fe1.01O3 + Lemongrass against M. canis. The study showed promising results regarding the synergistic antifungal efficacy of nanoparticle compounds combined with essential oils in the cases of Ag0.99Fe1.01O3 with cinnamon, Ag0.99Fe1.01O3 with clove and Ag0.99Fe1.01O3 with lemon grass against all tested dermatophytes.

Exploring Synergistic GHG Emissions Mitigation Potential and Costs of Room Air Conditioners.

This study explores the potential of synergistically reducing direct (refrigerant) and indirect (electricity) greenhouse gas (GHG) emissions in the global room air conditioning (RAC) sector, based on 80% of global RAC manufactured in China. Three scenarios are evaluated: Business-as-usual (BAU) based on maintaining refrigerant and energy efficiency levels from 2021 China RAC sales shares, Kigali Amendment compliant with 10% energy efficiency improvement by 2025 (KAE), and accelerated refrigerant transition and energy efficiency improvement (ATE). Each scenario considers the costs of refrigerant and efficiency measures for export market groups based on Kigali Amendment classifications. BAU predicts around 1 Gt CO2-eq average annual global RAC emissions (2022-2060). Cumulative emission reductions in China's RAC manufacturing under KAE and ATE are 12.2 and 17.2 Gt CO2-eq A5II and A5I (except China), presenting cost-effective abatement measures, with average costs of -$51.4 and -$68.8/t CO2-eq in KAE and ATE. Cumulative average abatement costs are around $18 and $4/t CO2-eq globally. KAE and ATE scenarios would avoid surface temperature rises of 0.023 (±0.002) °C and 0.027 (±0.003) °C, respectively, versus BAU. Collaboration between China and importing countries is urged to enhance energy efficiency in RACs traded, ensuring sustainable mitigation aligned with the Kigali Amendment.

DGAT1 and DGAT2 Inhibitors for Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) Management: Benefits for Their Single or Combined Application.

Inhibiting diacylglycerol acetyltransferase (DGAT1, DGAT2) enzymes (iDGAT1, iDGAT2), involved in triglyceride (TG) synthesis, improves hepatic steatosis in metabolic dysfunction-associated steatotic liver disease (MASLD) patients. However, their potential synergism in disease onset (SLD) and progression (metabolic dysfunction-associated steatohepatitis, fibrosis) has been poorly explored. We investigated iDGAT1 and iDGAT2 efficacy, alone or combined (iDGAT1/2) on fat accumulation and hepatocellular injury in hepatocytes (HepG2) and on fibrogenic processes in hepatic stellate cells (LX2). We further tested whether the addition of MitoQ antioxidant to iDGAT1/2 would enhance their effects. SLD and MASH conditions were reproduced in vitro by supplementing Dulbecco's Modified Eagle's Medium (DMEM) with palmitic/oleic acids (PAOA) alone (SLD-medium), or plus Lipopolisaccaride (LPS), fructose, and glucose (MASH-medium). In SLD-medium, iDGAT1 and iDGAT2 individually, and even more in combination, reduced TG synthesis in HepG2 cells. Markers of hepatocellular damage were slightly decreased after single iDGAT exposure. Conversely, iDGAT1/2 counteracted ER/oxidative stress and inflammation and enhanced mitochondrial Tricarboxylic acid cycle (TCA) and respiration. In HepG2 cells under a MASH-like condition, only iDGAT1/2 effectively ameliorated TG content and oxidative and inflammatory mediators, further improving bioenergetic balance. LX2 cells, challenged with SLD/MASH media, showed less proliferation and slower migration rates in response to iDGAT1/2 drugs. MitoQ combined with iDGAT1/2 improved cell viability and dampened free fatty acid release by stimulating β-oxidation. Dual DGAT inhibition combined with antioxidants open new perspectives for MASLD management.

Beyond the Conventional Structural MRI: Clinical Application of Deep Learning Image Reconstruction and Synthetic MRI of the Brain.

Recent technological advancements have revolutionized routine brain magnetic resonance imaging (MRI) sequences, offering enhanced diagnostic capabilities in intracranial disease evaluation. This review explores 2 pivotal breakthrough areas: deep learning reconstruction (DLR) and quantitative MRI techniques beyond conventional structural imaging. DLR using deep neural networks facilitates accelerated imaging with improved signal-to-noise ratio and spatial resolution, enhancing image quality with short scan times. DLR focuses on supervised learning applied to clinical implementation and applications. Quantitative MRI techniques, exemplified by 2D multidynamic multiecho, 3D quantification using interleaved Look-Locker acquisition sequences with T2 preparation pulses, and magnetic resonance fingerprinting, enable precise calculation of brain-tissue parameters and further advance diagnostic accuracy and efficiency. Potential DLR instabilities and quantification and bias limitations will be discussed. This review underscores the synergistic potential of DLR and quantitative MRI, offering prospects for improved brain imaging beyond conventional methods.

The clinical and imaging data fusion model for single-period cerebral CTA collateral circulation assessment.

The Chinese population ranks among the highest globally in terms of stroke prevalence. In the clinical diagnostic process, radiologists utilize computed tomography angiography (CTA) images for diagnosis, enabling a precise assessment of collateral circulation in the brains of stroke patients. Recent studies frequently combine imaging and machine learning methods to develop computer-aided diagnostic algorithms. However, in studies concerning collateral circulation assessment, the extracted imaging features are primarily composed of manually designed statistical features, which exhibit significant limitations in their representational capacity. Accurately assessing collateral circulation using image features in brain CTA images still presents challenges. To tackle this issue, considering the scarcity of publicly accessible medical datasets, we combined clinical data with imaging data to establish a dataset named RadiomicsClinicCTA. Moreover, we devised two collateral circulation assessment models to exploit the synergistic potential of patients' clinical information and imaging data for a more accurate assessment of collateral circulation: data-level fusion and feature-level fusion. To remove redundant features from the dataset, we employed Levene's test and T-test methods for feature pre-screening. Subsequently, we performed feature dimensionality reduction using the LASSO and random forest algorithms and trained classification models with various machine learning algorithms on the data-level fusion dataset after feature engineering. Experimental results on the RadiomicsClinicCTA dataset demonstrate that the optimized data-level fusion model achieves an accuracy and AUC value exceeding 86% . Subsequently, we trained and assessed the performance of the feature-level fusion classification model. The results indicate the feature-level fusion classification model outperforms the optimized data-level fusion model. Comparative experiments show that the fused dataset better differentiates between good and bad side branch features relative to the pure radiomics dataset. Our study underscores the efficacy of integrating clinical and imaging data through fusion models, significantly enhancing the accuracy of collateral circulation assessment in stroke patients.

The effect of technological overlap on acquisition premiums: moderating roles of target firm's technology clockspeed and industry munificence

PurposeDrawing on the literature on technological acquisition and the knowledge-based view , this study examines how technological overlap between acquiring and target firms influences acquisition premiums. We further explore how the resulting synergies are contingent on the dynamic characteristics of the target firm, specifically its technology clockspeed and industry munificence. Technology clockspeed indicates the pace of technological evolution, reflecting internal dynamic resources, while industry munificence represents the abundance of external resources. These boundary conditions illustrate the dynamics of synergies, explaining their moderation effects on acquisition premiums.Design/methodology/approachWe analyze a sample of 369 technological acquisitions by publicly traded U.S. firms between 1990 and 2011. To test our hypotheses, we used the ordinary least squares regression model with robust standard errors clustered by acquiring firms. In the robustness checks, we applied the generalized estimating equations to account for non-independent observations in our sample and verified that the results were robust to an alternative two-way clustering approach.FindingsWe suggest that a low level of technological overlap between an acquiring firm and its target firm leads the acquiring firm to offer a high acquisition premium because of the expected synergistic potential that evolves from combining two distant technological bases. We further find that this effect is contingent on the target firm's technology clockspeed and industry munificence. Specifically, the negative effect is amplified when target firms exhibit a rapid pace of technological evolution, whereas it is weakened when target firms operate in highly munificent industries characterized by robust growth and abundant resource flows.Research limitations/implicationsThis study has several limitations, but it offers opportunities for future research. First, our sample is limited to domestic acquisitions between U.S. publicly traded firms, which may restrict generalizability. Cross-border acquisitions could reveal different dynamics, as technology leakage and national security concerns might make technological overlap a more sensitive factor. Additionally, private firms were not included, and their distinct strategic considerations could provide further insights. Future research could explore post-acquisition data to validate these synergies and expand the scope to include international contexts and private firms for a comprehensive analysis.Practical implicationsOur findings highlight important implications for managers in technology sector acquisitions. This study underscores the need for a thorough evaluation of target firms to avoid misjudging synergies. Low technological overlap can heighten expectations for value creation, making it crucial for executives to accurately assess potential synergies to prevent overestimation. Managers should consider both internal resources and external industry conditions when evaluating synergies. Ultimately, these insights help managers offer informed prices that reflect true strategic synergies, adopting effective valuation practices to mitigate risks of financial overpayments and poor post-merger performance.Social implicationsThe social implications of our findings emphasize the broader impact of acquisition decisions on innovation and competition within the technology sector. By ensuring accurate valuation and avoiding overpayment, companies can allocate resources more efficiently, fostering sustainable growth and innovation. This diligent approach can reduce the risk of corporate failures.Originality/valueThis study makes two key theoretical contributions. First, it identifies technological overlap as a critical determinant of acquisition premiums in technological acquisitions, addressing gaps in the literature that focused on CEO characteristics and managerial attention. Second, it expands the theoretical framework by highlighting the dynamic nature of synergies, influenced by the target firm's technology clockspeed and industry munificence. By integrating both acquiring and target firm characteristics, this study provides a relational perspective on value creation, explaining why firms pay high premiums and offering a more comprehensive understanding of the strategic motivations in technological acquisitions.