Recent Research Research Articles

Emerging Neuroprotective Strategies: Unraveling the Potential of HDAC Inhibitors in Traumatic Brain Injury Management.

Traumatic brain injury (TBI) is a significant global health problem, leading to high rates of mortality and disability. It occurs when an external force damages the brain, causing immediate harm and triggering further pathological processes that exacerbate the condition. Despite its widespread impact, the underlying mechanisms of TBI remain poorly understood, and there are no specific pharmacological treatments available. This creates an urgent need for new, effective neuroprotective drugs and strategies tailored to the diverse needs of TBI patients. In the realm of gene expression regulation, chromatin acetylation plays a pivotal role. This process is controlled by two classes of enzymes: histone acetyltransferase (HAT) and histone deacetylase (HDAC). These enzymes modify lysine residues on histone proteins, thereby determining the acetylation status of chromatin. HDACs, in particular, are involved in the epigenetic regulation of gene expression in TBI. Recent research has highlighted the potential of HDAC inhibitors (HDACIs) as promising neuroprotective agents. These compounds have shown encouraging results in animal models of various neurodegenerative diseases. HDACIs offer multiple avenues for TBI management: they mitigate the neuroinflammatory response, alleviate oxidative stress, inhibit neuronal apoptosis, and promote neurogenesis and axonal regeneration. Additionally, they reduce glial activation, which is associated with TBI-induced neuroinflammation. This review aims to provide a comprehensive overview of the roles and mechanisms of HDACs in TBI and to evaluate the therapeutic potential of HDACIs. By summarizing current knowledge and emphasizing the neuroregenerative capabilities of HDACIs, this review seeks to advance TBI management and contribute to the development of targeted treatments.

Emerging Nanotechnology-based Therapeutics: A New Insight into Promising Drug Delivery System for Lung Cancer Therapy.

Lung cancer is a foremost global health issue due to its poor diagnosis. The advancement of novel drug delivery systems and medical devices will aid its therapy. In this review, the authors thoroughly introduce the ideas and methods for improving nanomedicine- based approaches for lung cancer therapy. This article provides mechanistic insight into various novel drug delivery systems (DDSs) including nanoparticles, solid lipid nanoparticles, liposomes, dendrimers, niosomes, and nanoemulsions for lung cancer therapy with recent research work. This review provides insights into various patents published for lung cancer therapy based on nanomedicine. This review also highlights the current status of approved and clinically tested nanoformulations for their treatment. For finding scholarly related data for the literature search, many search engines were employed including PubMed, Science Direct, Google, Scihub, Google Scholar, Research Gate, Web of Sciences, and several others. Various keywords and phrases were used for the search such as "nanoparticles", "solid lipid nanoparticles", "liposomes", "dendrimers", "niosomes", "nanoemulsions", "lung cancer", "nanomedicine", "nanomaterial", "nanotechnology", "in vivo" and "in vitro". The most innovative and cutting-edge nanotechnology-based approaches that are employed in pre-clinical and clinical studies to address problems associated with lung cancer therapies are also mentioned in future prospects. A variety of problems encountered with current lung cancer therapy techniques that frequently led to inadequate therapeutic success are also discussed in the end. The development of nanoformulations at the pilot scale still faces some difficulties, but their prospects for treating lung cancer appear to be promising in the future. Future developments and trends are anticipated as the evaluation comes to a close.

Gene Variant Analysis for the Detection of Hemophilia: A Literature Review

Background:: Proteins act as clotting factors to stop bleeding at the lesion site. This implies that people with hemophilia tend to bleed longer after an injury and are more prone to internal bleeding. Depending on the type of hemophilia, individuals with hemophilia will have lesser amounts of factor VIII or factor IX than people without it. Objective:: By analyzing the gene variant of hemophilia affected patient we can predict the severity of disease at earlier stage which helps to avoid further complications. Methods:: Predicting hemophilia can be achieved through potential technologies like machine learning. Using these technologies, one can detect and predict the severity of hemophilia, such as mild, moderate, or severe. Results:: y comparing the methods used in protein structure analysis, the advantages and limitations of methods used in protein structure analysis are discussed. Conclusion:: The best practices in predicting hemophilia are highlighted in this study and particularly aim at the basic understanding of applying the potential technologies in the prediction of hemophilia and its severity. This study represents recent research on hemophilia and the use of different machine learning techniques (MLT) in this area.

Two-Dimensional MXene-Based Functional Composites for Photocatalysts: Current Status and Perspectives

Abstract: MXenes, as novel two-dimensional (2D) transition metal carbides, nitrides or carbonitrides, have excellent metal conductivity, high carrier mobility, and surface-terminated groups regulated band structure. It can be thus used as a cocatalyst in photocatalytic systems to improve the photocatalytic properties. This review represented recent research progress on the controllable construction of MXene-based functional composites with zero-dimensional (0D), one-dimensional (1D), 2D, and three-dimensional (3D) semiconductor photocatalysts and their applications for photocatalysts. Extensive information related to 2D MXene-Based composites for photocatalysts and their associated patents were collected. The construction methods and photocatalytic enhancement mechanisms of 2D MXene-based composite photocatalysts were given. Due to their excellent physical and chemical properties, 2D MXene composites have been widely used in pollutant removal, hydrogen production, CO2 reduction, and nitrogen fixation. Through the construction of 2D MXene-based functional composite photocatalysts with novel structures and excellent performance, it provides a new perspective for the design and construction of high-efficiency photocatalysts. The future research directions of MXene-based composite photocatalysts was proposed.

Decoupling Between Brain Activity and Cerebrospinal Fluid Movement in Neurological Disorders.

Recent research has identified a link between the global mean signal of resting-state functional MRI (fMRI) and macro-scale cerebrospinal fluid movement, indicating the potential link between this resting-state dynamic and brain waste clearance. Consistent with this notion, the strength of this coupling has been associated with multiple neurodegenerative disease pathologies, especially the build-up of toxic proteins. This article aimed to review the latest advancements in this research area, emphasizing studies on spontaneous global brain activity that is tightly linked to the global mean resting-state fMRI signal, and aimed to discuss potential mechanisms through which this activity and associated physiological modulations might affect brain waste clearance. The available evidence supports the presence of a highly organized global brain activity that is linked to arousal and memory systems. This global brain dynamic, along with its associated physiological modulations, has the potential to influence brain waste clearance through multiple pathways through multiple pathways. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 3.

Short Fragmented Peptides from Pardachirus Marmoratus Exhibit Stronger Anticancer Activities in In Silico Residue Replacement and Analyses.

Cancer is a worldwide issue. It has been observed that conventional therapies face many problems, such as side effects and drug resistance. Recent research reportedly used marine-derived products to treat various diseases and explored their potential in treating cancers. This study aims to discover short-length anticancer peptides derived from pardaxin 6 through an in silico approach. Fragmented peptides ranging from 5 to 15 amino acids were derived from the pardaxin 6 parental peptide. These peptides were further replaced with one residue and, along with the original fragmented peptides, were predicted for their SVM scores and physicochemical properties. The top 5 derivative peptides were further examined for their toxicity, hemolytic probability, peptide structures, docking models, and energy scores using various web servers. The trend of in silico analysis outputs across 5 to 15 amino acid fragments was further analyzed. Results showed that when the amino acids were increased, SVM scores of the original fragmented peptides were also increased. Designed peptides had increased SVM scores, which was aligned with previous studies where the single residue replacement transformed the non-anticancer peptide into an anticancer agent. Moreover, in vitro studies validated that the designed peptides retained or enhanced anticancer effects against different cancer cell lines. Interestingly, a decreasing trend was observed in those fragmented derivative peptides. Single residue replacement in fragmented pardaxin 6 was found to produce stronger anticancer agents through in silico predictions. Through bioinformatics tools, fragmented peptides improved the efficiency of marine-derived drugs with higher efficacy and lower hemolytic effects in treating cancers.

The Astonishing Accomplishment of Biological Drug Delivery using Lipid Nanoparticles: An Ubiquitous Review.

Biotech drugs, including proteins, hormones, enzymes, DNA/RNA therapies, and cell-based treatments, are gaining popularity due to their effectiveness. However, effective delivery systems are needed to overcome administration challenges. Lipid nanoparticles (LNPs) have emerged as promising carriers for various therapies. LNPs are biocompatible, less likely to cause adverse reactions, and can stabilize delicate biological drugs, enhancing their stability and solubility. Scalable and cost-effective manufacturing processes make LNPs suitable for largescale production. Despite recent research efforts, challenges in stability, toxicity, and regulatory concerns have limited the commercial availability of LNP-based products. This review explores the applications, administration routes, challenges, and future directions of LNPs in delivering biopharmaceuticals.

Development and Outlook for Self-priming Pumps

Background: Self-priming pumps are a type of general mechanical equipment that is widely used in the petroleum, chemical, electric power, metallurgy, mining, shipbuilding, light industry, agriculture, civil defense, and other departments, and they play an important role in the global economy. The pump system is the most common piece of equipment that consumes the most electricity, and reducing the energy consumption of the pump will save a significant amount of energy. Objective: For the benefit of scholars and engineers, this paper summarizes the most recent research on self-priming pumps, analyzes their solutions to the problem of reducing energy consumption, and discusses their advantages and disadvantages. Methods: The typical self-priming pump patents are outlined below based on the many functions of the improved self-priming pump structure, including pump body protection, high efficiency, and energy savings, ease of movement, and improved seal. The current self-priming pump patents are used to examine the development trend for these pumps. Results: The fundamental issues with self-priming pumps are outlined and studied through comparisons of various types and functions, and a future course for their development is suggested. Conclusion: The development of self-priming pump technology benefits from the improvement of self-priming pump structure. A self-priming pump with a straightforward design, automation, high efficiency, and energy conservation has a promising future.

Topical Anti-ulcerogenic Effect of the Beta-adrenergic Blockers on Diabetic Foot Ulcers: Recent Advances and Future Prospectives.

Patients with diabetes suffer from major complications like Diabetic Retinopathy, Diabetic Coronary Artery Disease, and Diabetic Foot ulcers (DFUs). Diabetes complications are a group of ailments whose recovery time is especially delayed, irrespective of the underlying reason. The longer duration of wound healing enhances the probability of problems like sepsis and amputation. The delayed healing makes it more critical for research focus. By understanding the molecular pathogenesis of diabetic wounds, it is quite easy to target the molecules involved in the healing of wounds. Recent research on beta-adrenergic blocking drugs has revealed that these classes of drugs possess therapeutic potential in the healing of DFUs. However, because the order of events in defective healing is adequately defined, it is possible to recognize moieties that are currently in the market that are recognized to aim at one or several identified molecular processes. The aim of this study was to explore some molecules with different therapeutic categories that have demonstrated favorable effects in improving diabetic wound healing, also called the repurposing of drugs. Various databases like PubMed/Medline, Google Scholar and Web of Science (WoS) of all English language articles were searched, and relevant information was collected regarding the role of beta-adrenergic blockers in diabetic wounds or diabetic foot ulcers (DFUs) using the relevant keywords for the literature review. The potential beta-blocking agents and their mechanism of action in diabetic foot ulcers were studied, and it was found that these drugs have a profound effect on diabetic foot ulcer healing as per reported literatures. There is a need to move forward from preclinical studies to clinical studies to analyze clinical findings to determine the effectiveness and safety of some beta-antagonists in diabetic foot ulcer treatment.

Non-coding RNAs as Key Regulators of the Notch Signaling Pathway in Glioblastoma: Diagnostic, Prognostic, and Therapeutic Targets.

Glioblastoma multiforme (GBM) is a highly invasive brain malignancy originating from astrocytes, accounting for approximately 30% of central nervous system malignancies. Despite advancements in therapeutic strategies including surgery, chemotherapy, and radiopharmaceutical drugs, the prognosis for GBM patients remains dismal. The aggressive nature of GBM necessitates the identification of molecular targets and the exploration of effective treatments to inhibit its proliferation. The Notch signaling pathway, which plays a critical role in cellular homeostasis, becomes deregulated in GBM, leading to increased expression of pathway target genes such as MYC, Hes1, and Hey1, thereby promoting cellular proliferation and differentiation. Recent research has highlighted the regulatory role of non-coding RNAs (ncRNAs) in modulating Notch signaling by targeting critical mRNA expression at the post-transcriptional or transcriptional levels. Specifically, various types of ncRNAs, including long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), have been shown to control multiple target genes and significantly contribute to the carcinogenesis of GBM. Furthermore, these ncRNAs hold promise as prognostic and predictive markers for GBM. This review aims to summarize the latest studies investigating the regulatory effects of ncRNAs on the Notch signaling pathway in GBM.

Cross-Modal Clustering With Deep Correlated Information Bottleneck Method.

Cross-modal clustering (CMC) intends to improve the clustering accuracy (ACC) by exploiting the correlations across modalities. Although recent research has made impressive advances, it remains a challenge to sufficiently capture the correlations across modalities due to the high-dimensional nonlinear characteristics of individual modalities and the conflicts in heterogeneous modalities. In addition, the meaningless modality-private information in each modality might become dominant in the process of correlation mining, which also interferes with the clustering performance. To tackle these challenges, we devise a novel deep correlated information bottleneck (DCIB) method, which aims at exploring the correlation information between multiple modalities while eliminating the modality-private information in each modality in an end-to-end manner. Specifically, DCIB treats the CMC task as a two-stage data compression procedure, in which the modality-private information in each modality is eliminated under the guidance of the shared representation of multiple modalities. Meanwhile, the correlations between multiple modalities are preserved from the aspects of feature distributions and clustering assignments simultaneously. Finally, the objective of DCIB is formulated as an objective function based on a mutual information measurement, in which a variational optimization approach is proposed to ensure its convergence. Experimental results on four cross-modal datasets validate the superiority of the DCIB. Code is released at https://github.com/Xiaoqiang-Yan/DCIB.

Athafnafólk í opinberri stefnumótun á óvissutímum: Hvernig hugmyndin um notendastýrða persónulega aðstoð varð að veruleika á Íslandi

Þessi rannsókn leitast við að útskýra tímamótaákvörðun í þjónustu við fatlað fólk á Íslandi. Opinber stefnumótun hefur löngum einkennst af hægfara breytingum, sem gerast í smáum skrefum. Stundum bregður þó svo við að meiriháttar breytingar verða og stefnumál, sem verið hefur baráttumál hagsmunahópa um margra ára skeið, ná fram að ganga. Dagskrárkenningar leitast við að útskýra meiriháttar stefnubreytingar með því m.a. að beina athyglinni að því hvernig og hvers vegna tiltekin málefni koma til kasta stjórnvalda á hverju tíma. Bandaríski stjórnmálafræðingurinn, John W. Kingdon, setti fyrst fram kenningu sína um straumana þrjá og glugga tækifæranna fyrir rúmum 30 árum. Nýlegar rannsóknir evrópskra stjórnmálafræðinga halda því nú fram að nálgun Kingdons geti varpað ljósi á það hvernig það pólitíska kerfi sem stefnumótunin fer fram í virkar og hvernig hegðun og aðferðir þátttakenda í ferlinu hafa áhrif. Í þessari eigindlegu rannsókn er skoðað hvernig hugmyndin um notendastýrða persónulega aðstoð (NPA) varð að veruleika á Íslandi. Rannsóknin byggir á fyrirliggjandi gögnum og viðtölum við lykilfólk um þá framvindu mála sem leiddi til ákvörðunar um að innleiða NPA hér á landi. Rannsóknin lýsir því hvernig og undir hvaða kringumstæðum NPA komst á dagskrá stjórnvalda. Niðurstöðurnar sýna hvernig breytingar á verkaskiptingu milli ríkis og sveitarfélaga gáfu tækifæri fyrir nýja hugmyndafræði sem nýttist bæði notendum, viðskiptahagsmunum og pólitískum hagsmunum. Niðurstöðurnar benda til þess að þar hafi ekki aðeins verið réttur maður á réttum stað á réttum tíma, heldur varpa þær fræðilegu ljósi á það hvað einkennir athafnafólk í opinberri stefnumótun og hvernig og hvers vegna það skiptir máli á óvissutímum í stjórnmálum.

Nanotechnology-Based Approaches for Nose-to-Brain Drug Delivery in Neurodegenerative Diseases

: Drug delivery to the brain is a challenging task as many drugs do not cross the blood-brain barrier (BBB). As a result, designing strategies to target drugs to the brain requires significant effort. However, recent research has focused on the administration of drugs through the nose to the brain, a noninvasive way to bypass the BBB and deliver therapeutic molecules directly to the brain. Nose-to-brain drug delivery is a promising approach that allows for the direct transportation of therapeutic molecules to the brain while increasing drug concentration in the brain. This approach has gained considerable attention due to its non-invasive nature, which makes it feasible, reliable, and efficient. One promising approach for nose-to-brain drug delivery is the use of nanoparticles as a platform for drug and gene delivery. Nanoparticles offer several advantages, including the ability to protect therapeutic drugs from degradation and increase the efficacy of drug delivery due to their unique size, shape, and surface features. Nanoparticles can also be engineered to target specific cells or tissues, enabling more precise drug delivery to the brain. The use of nanoparticles for nose-to-brain drug delivery has been extensively studied, and recent developments have shown promising results. In addition, patents relating to medication targeting via the nasal route have been developed. These patents cover various aspects of drug delivery, including the use of different types of nanoparticles, methods for producing nanoparticles, and methods for delivering nanoparticles to the brain.

Cement-Based Composites Containing Carbon Nanofibers and Carbon Nanotubes

Abstract: In cement-based composites, carbon nanotubes (CNTs) and carbon nano fibres (CNFs) can act as crack bridging, delaying the development of nano fractures into microcracks. Recent research on the use of CNTs and CNFs in cement-based composites was reviewed in this paper. Earlier studies have demonstrated that cement-based composites reinforced with CNTs/CNFs have lower porosities and superior mechanical properties to plain cement-based composites. Using CNTs or CNFs in cement-based composites presents challenges due to their low matrix dispersion and weak interfacial contact. Some projected future investigations were indicated. Results: Earlier studies have demonstrated that cement-based composites reinforced with CNTs/CNFs have lower porosities and superior mechanical properties to plain cement-based composites. Using CNTs or CNFs in cement-based composites presents challenges due to their low matrix dispersion and weak interfacial contact . Recommendation: some projected future investigations were indicated.

QSAR Studies on Thienopyrimidines as Potential Antimicrobial Agents

Background: Recent research has revealed promising antibacterial action for thienopyrimidines. To comprehend the underlying molecular features underlying their antibacterial potency, a thorough quantitative structure-activity relationship (QSAR) investigation is required. Objective: In order to clarify the structural parameters for effective antibacterial activity, we conducted QSAR analyses on a variety of thienopyrimidines in this work. Methods: Through the analysis of physicochemical properties and molecular descriptors, we aimed to develop predictive models that can guide the design of novel thienopyrimidine derivatives with enhanced antimicrobial potential. Results: It was discovered through the descriptor importance analysis that specific physicochemical characteristics, including lipophilicity, electronic distribution, and steric effects, significantly influenced the antibacterial efficacy of these drugs. Conclusion: The identified molecular characteristics and descriptors can be used to guide the development of new thienopyrimidine derivatives with higher antibacterial activity.

Maternal prenatal social disadvantage and neonatal functional connectivity: Associations with psychopathology symptoms at age 12 months.

Recent research has reported effects of socioeconomic status on neurobehavioral development as early as infancy, including positive associations between income and brain structure, functional connectivity, and behavior later in childhood (Ramphal, Whalen, et al., 2020; Triplett et al., 2022). This study extends this literature by investigating the relation of maternal prenatal social disadvantage (PSD) to neonatal amygdala and hippocampus functional connectivity and whether socioeconomic-related alterations in functional connectivity subsequently predict behavior at age 12 months in a large, socioeconomically diverse sample (N = 261 mother-infant dyads). PSD was assessed across gestation; neonatal magnetic resonance imaging was completed within the first weeks of life; and infant internalizing and externalizing symptoms were evaluated using the Infant-Toddler Social and Emotional Assessment at age 12 months. The results showed that PSD was significantly related to neonatal right amygdala and left hippocampus functional connectivity with prefrontal and motor-related regions. Social disadvantage-related right amygdala and left hippocampus functional connectivity with these regions was subsequently related to infant externalizing and internalizing symptoms at age 12 months. Building off an emerging literature exploring prenatal impacts on neonatal functional connectivity, this study further emphasizes the important role of the maternal environment during gestation on infant brain function and its relationship with externalizing and internalizing behavior in the first years of life. The results suggest that the prenatal socioeconomic environment may be a promising target for interventions aimed at improving infant neurobehavioral outcomes. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Chinese EMR Named Entity Recognition Using Fused Label Relations Based on Machine Reading Comprehension Framework.

Chinese electronic medical record (EMR) presents significant challenges for named entity recognition (NER) due to their specialized nature, unique language features, and diverse expressions. Traditionally, NER is treated as a sequence labeling task, where each token is assigned a label. Recent research has reframed NER within the machine reading comprehension (MRC) framework, extracting entities in a question-answer format, achieving state-of-the-art performance. However, these MRC-based methods have a significant limitation: they extract entities of various types independently, ignoring their interrelations. To address this, we introduce the Fusion Label Relations with MRC (FLR-MRC) model, which enhances the MRC model by implicitly capturing dependencies among entity types. FLR-MRC models interrelations between labels using graph attention networks, integrating these with textual data to identify entities. On the benchmark CMeEE and CCKS2017-CNER datasets, FLR-MRC achieves F1-scores of 0.6652 and 0.9101, respectively, outperforming existing clinical NER methods.

Vapor-Liquid Equilibrium of System Comprising Green Solvents: A Holistic Review

Abstract: The design and operation of distillation columns is based on vapor-liquid equilibrium data, which is a necessity for the chemical industry. In recent years, chemical industry has embraced green chemistry and sustainable development. Furthermore, green solvents are more environmentfriendly and cleaner than conventional solvents and thus offer a good alternative. Very limited work has been reported in the literature that focuses on the generation of isobaric/isothermal vapor-liquid equilibrium (VLE) data of systems comprising green solvents. In this paper, reported VLE data are explored for three emerging green solvents, such as cyclopentyl methyl ether (CPME), γ- valerolactone (GVL), and 2-methyltetrahydrofuran (2-MeTHF). Emerging green solvents have favorable environmental, health, and safety characteristics, making them attractive alternatives for a wide range of applications. The study focuses on two critical separations; the extraction of formic acid from Power-to-X chemical processes and purification of acetic acid from chemical synthesis or fermentation processes. Both processes are integral parts of the chemical industry's sustainable development. To facilitate these separations, accurate VLE data for these green solvents with acetic acid/formic acid systems are essential. The paper reviews literature related to VLE data for systems involving these green solvents. It provides insights into the experimental conditions, equipment, analysis methods, thermodynamic models, and error-minimizing functions used in the previous studies. The researchers can refer to this information as a useful reference prior to the VLE experimentation and modeling of systems comprising these three green solvents. Moreover, the paper presents an overview of recent research on green solvents and their applications, illustrating their versatility and potential for various industrial processes. Research efforts are needed to generate VLE data for green solvent systems and support the chemical industry in transitions towards more sustainable practices.

Promising Influences of Moringa oleifera in Functional Foods against Metabolic Syndrome: A Comprehensive and Mechanistic Review.

Metabolic syndrome (MetS) is now considered a global issue with a growing financial and health impact. Numerous herbal alternatives have been examined and researched due to the ever-increasing demand for new medications to treat metabolic syndrome disorders. People have empirically employed Moringa oleifera (MO), a native plant to several Asian nations, for a variety of diseases. We sought to examine recent research on MO in MetS and its potential mechanism of action in the current review. Four databases, including PubMed, Scopus, Web of Sciences, and Google Scholar, were thoroughly searched, and the data were then compiled. In total, 146 papers covering nonclinical and clinical MO investigations in metabolic syndromerelated disorders are included in this study. Numerous research confirmed MO's positive impact on the control of blood glucose, blood pressure, hyperlipidemia, and obesity. Many molecular processes have been investigated, including increasing glucose transporter type 4 (GLUT4) expression, inhibition of β-Hydroxy-β-methylglutaryl-coenzyme A (HMG-CoA), α-glucosidase inhibiting, AMP-activated protein kinase (AMPK) activation, and other suggested mechanisms. The current review established much data favoring MO's potential advantages in metabolic syndrome. However, further research involving human studies is required in this area to determine whether Moringa can effectively treat metabolic syndrome.

Recent Research on the Identification, Assessment, and Response to Fraud Risks: Implications for Audit Practice and Topics for Future Research

SYNOPSIS The financial statement auditor’s identification of fraud risk factors, their assessment of fraud risk, and their fraud risk responses are key to the auditor’s consideration of fraud and fraud detection. Given that the last review of research related to the search for fraud during the audit occurred nearly a decade ago, we provide a summary of recent academic research to update and inform practitioners, researchers, standard setters, regulators, and other stakeholders in the financial reporting process. We categorize and summarize findings from recent academic studies that focus on the auditor’s identification, assessment, and responses to fraud risks. Implications for practice are presented for each of these areas, along with topics and questions for future research. JEL Classifications: M40; M41; M42; M48.