Machine learning enabled design features of antimicrobial peptides selectively targeting peri-implant disease progression.

Peri-implantitis is a complex infectious disease that manifests as progressive loss of alveolar bone around the dental implants and hyper-inflammation associated with microbial dysbiosis. Using antibiotics in treating peri-implantitis is controversial because of antibiotic resistance threats, the non-selective suppression of pathogens and commensals within the microbial community, and potentially serious systemic sequelae. Therefore, conventional treatment for peri-implantitis comprises mechanical debridement by nonsurgical or surgical approaches with adjunct local microbicidal agents. Consequently, current treatment options may not prevent relapses, as the pathogens either remain unaffected or quickly re-emerge after treatment. Successful mitigation of disease progression in peri-implantitis requires a specific mode of treatment capable of targeting keystone pathogens and restoring bacterial community balance toward commensal species. Antimicrobial peptides (AMPs) hold promise as alternative therapeutics through their bacterial specificity and targeted inhibitory activity. However, peptide sequence space exhibits complex relationships such as sparse vector encoding of sequences, including combinatorial and discrete functions describing peptide antimicrobial activity. In this paper, we generated a transparent Machine Learning (ML) model that identifies sequence-function relationships based on rough set theory using simple summaries of the hydropathic features of AMPs. Comparing the hydropathic features of peptides according to their differential activity for different classes of bacteria empowered predictability of antimicrobial targeting. Enriching the sequence diversity by a genetic algorithm, we generated numerous candidate AMPs designed for selectively targeting pathogens and predicted their activity using classifying rough sets. Empirical growth inhibition data is iteratively fed back into our ML training to generate new peptides, resulting in increasingly more rigorous rules for which peptides match targeted inhibition levels for specific bacterial strains. The subsequent top scoring candidates were empirically tested for their inhibition against keystone and accessory peri-implantitis pathogens as well as an oral commensal bacterium. A novel peptide, VL-13, was confirmed to be selectively active against a keystone pathogen. Considering the continually increasing number of oral implants placed each year and the complexity of the disease progression, prevalence of peri-implant diseases continues to rise. Our approach offers transparent ML-enabled paths towards developing antimicrobial peptide-based therapies targeting the changes in the microbial communities that can beneficially impact disease progression.

Attorney demands for protected psychological test information: Is access necessary for cross examination or does it lead to misinformation? An interorganizational* position paper.

Objective: Some attorneys claim that to adequately cross examine neuropsychological experts, they require direct access to protected test information, rather than having test data analyzed by retained neuropsychological experts. The objective of this paper is to critically examine whether direct access to protected test materials by attorneys is indeed necessary, appropriate, and useful to the trier-of-fact. Method: Examples are provided of the types of nonscientific misinformation that occur when attorneys, who lack adequate training in testing, attempt to independently interpret neurocognitive/psychological test data. Results: Release of protected test information to attorneys introduces inaccurate information to the trier of fact, and jeopardizes future use of tests because non-psychologists are not ethically bound to protect test content. Conclusion: The public policy underlying the right of attorneys to seek possibly relevant documents should not outweigh the damage to tests and resultant misinformation that arise when protected test information is released directly to attorneys. The solution recommended by neuropsychological/psychological organizations and test publishers is to have protected psychological test information exchanged directly and only between clinical psychologist/neuropsychologist experts.

Designing Collagen-Binding Peptide with Enhanced Properties Using Hydropathic Free Energy Predictions.

Collagen is fundamental to a vast diversity of health functions and potential therapeutics. Short peptides targeting collagen are attractive for designing modular systems for site-specific delivery of bioactive agents. Characterization of peptide-protein binding involves a larger number of potential interactions that require screening methods to target physiological conditions. We build a hydropathy-based free energy estimation tool which allows quick evaluation of peptides binding to collagen. Previous studies showed that pH plays a significant role in collagen structure and stability. Our design tool enables probing peptides for their collagen-binding property across multiple pH conditions. We explored binding features of currently known collagen-binding peptides, collagen type I alpha chain 2 sense peptide (TKKTLRT) and decorin LRR-10 (LRELHLNNN). Based on these analyzes, we engineered a collagen-binding peptide with enhanced properties across a large pH range in contrast to LRR-10 pH dependence. To validate our predictions, we used a quantum-dots-based binding assay to compare the coverage of the peptides on type I collagen. The predicted peptide resulted in improved collagen binding. Hydropathy of the peptide-protein pair is a promising approach to finding compatible pairings with minimal use of computational resources, and our method allows for quick evaluation of peptides for binding to other proteins. Overall, the free-energy-based tool provides an alternative computational screening approach that impacts protein interaction search methods.

Engineered Peptides Enable Biomimetic Route for Collagen Intrafibrillar Mineralization.

Overcoming the short lifespan of current dental adhesives remains a significant clinical need. Adhesives rely on formation of the hybrid layer to adhere to dentin and penetrate within collagen fibrils. However, the ability of adhesives to achieve complete enclosure of demineralized collagen fibrils is recognized as currently unattainable. We developed a peptide-based approach enabling collagen intrafibrillar mineralization and tested our hypothesis on a type-I collagen-based platform. Peptide design incorporated collagen-binding and remineralization-mediating properties using the domain structure conservation approach. The structural changes from representative members of different peptide clusters were generated for each functional domain. Common signatures associated with secondary structure features and the related changes in the functional domain were investigated by attenuated total reflectance Fourier-transform infrared (ATR-FTIR) and circular dichroism (CD) spectroscopy, respectively. Assembly and remineralization properties of the peptides on the collagen platforms were studied using atomic force microscopy (AFM). Mechanical properties of the collagen fibrils remineralized by the peptide assemblies was studied using PeakForce-Quantitative Nanomechanics (PF-QNM)-AFM. The engineered peptide was demonstrated to offer a promising route for collagen intrafibrillar remineralization. This approach offers a collagen platform to develop multifunctional strategies that combine different bioactive peptides, polymerizable peptide monomers, and adhesive formulations as steps towards improving the long-term prospects of composite resins.

Forensic neuropsychology: History and current status.

Objective:This review provides a summary of historical details and current practice activities related to Forensic Neuropsychology (FN). Under the auspices of the American Board of Clinical Neuropsychology (ABCN), the Forensic Neuropsychology Special Interest Group (FNSIG) views the FN as a subspecialty, which has developed over time as the straightforward result of more than 20 years of numerous publications, extensive continuing education, focused research and growth of forensic practice within neuropsychology. In this article, the FNSIG core work group documents and integrates information that is the basis of efforts to consolidate practice knowledge and facilitate attainment of forensic practice competencies by clinical neuropsychologists. Method:Overview of continuing education topics at professional conferences, search results that identify relevant books and peer-reviewed publications, as well as pertinent findings across years of large-scale national survey results. Results:Relevant evidence has shown for decades that FN is prominent within Clinical Neuropsychology as practiced in the United States and Canada. A majority of U.S. neuropsychologists have received FN training and provide forensic evaluation services. FN practice time per week is considerable for many practitioners, and across survey epochs has been shown to be increasing. Conclusion:The present review leads to the conclusion that in the interest of promoting the acquisition of competence, FN practice should remain a focal point of training and continuing education. Alternate routes to attain competence are discussed, as are ongoing professional activities that undoubtedly will ensure continued growth of, and interest in, the subspecialty of FN.

Are there differences in performance validity test scores between African American and White American neuropsychology clinic patients?

OBJECTIVE: The purpose of the present study was to compare performance on a wide range of PVTs in a neuropsychology clinic sample of African Americans and White Americans to determine if there are differences in mean scores or cut-off failure rates between the two groups, and to identify factors that may account for false positive PVT results in African American patients. METHOD: African American and White American non-compensation-seeking neuropsychology clinic patients were compared on a wide range of standalone and embedded PVTs: Dot Counting Test, b Test, Warrington Recognition Memory Test, Rey 15-item plus recognition, Rey Word Recognition Test, Digit Span (ACSS, RDS, 3-digit time, 4-digit time), WAIS-III Picture Completion (Most discrepant index), WAIS-III Digit Symbol/Coding (recognition equation), Rey Auditory Verbal Learning Test, Rey Complex figure, WMS-III Logical Memory, Comalli Stroop Test, Trails A, and Wisconsin Card Sorting Test. RESULTS: When groups were equated for age and education, African Americans obtained mean performances significantly worse than White Americans on only four of 25 PVT scores across the 14 different measures (Stroop Word Reading and Color Naming, Trails A, Digit Span 3-digit time); however, FSIQ was also significantly higher in White American patients. When subjects with borderline IQ (FSIQ = 70 to 79) were excluded (resulting in 74 White Americans and 25 African Americans), groups no longer differed in IQ and only continued to differ on a single PVT cutoff (Trails A). Further, specificity rates in African Americans were comparable to those of White Americans with the exception of the b Test, the Dot Counting Test, and Stroop B. CONCLUSIONS: PVT performance generally does not differ as a function of Black versus White race once the impact of intellectual level is controlled, and most PVT cutoffs appear appropriate for use in African Americans of low average IQ or higher.

Peptide-Enabled Nanocomposites Offer Biomimetic Reconstruction of Silver Diamine Fluoride-Treated Dental Tissues.

Caries is the most ubiquitous infectious disease of mankind, and early childhood caries (ECC) is the most prevalent chronic disease in children worldwide, with the resulting destruction of the teeth recognized as a global health crisis. Recent the United States Food and Drug Administration (FDA) approval for the use of silver diamine fluoride (SDF) in dentistry offers a safe, accessible, and inexpensive approach to arrest caries progression in children with ECC. However, discoloration, i.e., black staining, of demineralized or cavitated surfaces treated with SDF has limited its widespread use. Targeting SDF-treated tooth surfaces, we developed a biohybrid calcium phosphate nanocomposite interface building upon the self-assembly of synthetic biomimetic peptides. Here, an engineered bifunctional peptide composed of a silver binding peptide (AgBP) is covalently joined to an amelogenin derived peptide (ADP). The AgBP provides anchoring to the SDF-treated tooth tissue, while the ADP promotes rapid formation of a calcium phosphate isomorph nanocomposite mimicking the biomineralization function of the amelogenin protein. Our results demonstrate that the bifunctional peptide was effective in remineralizing the biomineral destroyed by caries on the SDF-treated tooth tissues. The proposed engineered peptide approach offers a biomimetic path for remineralization of the SDF-treated tissues producing a calcium phosphate nanocomposite interface competent to be restored using commonly available adhesive dental composites.

Official position of the American Academy of Clinical Neuropsychology on test security.

To provide education regarding the critical importance of test security for neuropsychological and psychological tests, and to establish recommendations for best practices for maintaining test security in forensic, clinical, teaching, and research settings. Previous test security guidelines were not adequately specified. METHOD: Neuropsychologists practicing in a broad range of settings collaborated to develop detailed and specific guidance regarding test security to best ensure continued viability of neuropsychological and psychological tests. Implications of failing to maintain test security for both the practice of neuropsychology and for society at large were identified. Types of test data that can be safely disclosed to nonpsychologists are described.Specific procedures can be followed that will minimize risk of invalidating future use of neuropsychological and psychological measures.Clinical neuropsychologists must commit to protecting sensitive neuropsychological and psychological test information from exposure to nonpsychologists, and now have specific recommendations that will guide that endeavor.

Cross-validation of RAVLT performance validity indicators and the RAVLT/RO discriminant function in a large known groups sample.

OBJECTIVE: To cross-validate RAVLT performance validity cut-offs and the RAVLT/RO discriminant function in a large neuropsychological sample. METHOD: RAVLT scores and the RAVLT/RO discriminant function were compared in credible (n = 100) and noncredible (n = 353) neuropsychology referrals. RESULTS: Noncredible patients scored lower than credible patients on RAVLT scores and the RAVLT/RO discriminant function. With cut-offs set to ≥90% specificity, highest sensitivities were observed for the discriminant function (cut-off ≤.064; 55.8%), recognition total (cut-off ≤9; 53.1%), the recognition combination score (≤10; 47.7%), and total learning across trials (cut-off ≤31; 45.3%). Individuals with histories of learning difficulties were over-represented in the 10% of credible patients exceeding cut-offs. When these individuals were removed, cut-offs could be tightened while still maintaining at least 90% specificity, and thereby increasing sensitivity (e.g., recognition total cut-off ≤10, 65% sensitivity; RAVLT/RO discriminant function cut-off ≤.176, 58% sensitivity). When three of the most sensitive, non-overlapping scores were considered in combination, 17% of credible patients failed ≥1 of the three cut-offs, while 3% failed two, and only 1% failed all three. In contrast, in the noncredible sample, more than two-thirds failed one or more of the three cut-offs, nearly half failed ≥2, and nearly a quarter failed all three. CONCLUSIONS: RAVLT PVT cut-offs and the RAVLT/RO discriminant function achieve approximately 50% sensitivity, and approach 65% sensitivity when cut-offs specific to samples without histories of learning problems are employed, confirming that RAVLT cut-offs and the RAVLT/RO discriminant function continue to be valuable techniques in the identification of performance invalidity.

Reconfigurable Dual Peptide Tethered Polymer System Offers a Synergistic Solution for Next Generation Dental Adhesives.

Resin-based composite materials have been widely used in restorative dental materials due to their aesthetic, mechanical, and physical properties. However, they still encounter clinical shortcomings mainly due to recurrent decay that develops at the composite-tooth interface. The low-viscosity adhesive that bonds the composite to the tooth is intended to seal this interface, but the adhesive seal is inherently defective and readily damaged by acids, enzymes, and oral fluids. Bacteria infiltrate the resulting gaps at the composite-tooth interface and bacterial by-products demineralize the tooth and erode the adhesive. These activities lead to wider and deeper gaps that provide an ideal environment for bacteria to proliferate. This complex degradation process mediated by several biological and environmental factors damages the tooth, destroys the adhesive seal, and ultimately, leads to failure of the composite restoration. This paper describes a co-tethered dual peptide-polymer system to address composite-tooth interface vulnerability. The adhesive system incorporates an antimicrobial peptide to inhibit bacterial attack and a hydroxyapatite-binding peptide to promote remineralization of damaged tooth structure. A designer spacer sequence was incorporated into each peptide sequence to not only provide a conjugation site for methacrylate (MA) monomer but also to retain active peptide conformations and enhance the display of the peptides in the material. The resulting MA-antimicrobial peptides and MA-remineralization peptides were copolymerized into dental adhesives formulations. The results on the adhesive system composed of co-tethered peptides demonstrated both strong metabolic inhibition of S. mutans and localized calcium phosphate remineralization. Overall, the result offers a reconfigurable and tunable peptide-polymer hybrid system as next-generation adhesives to address composite-tooth interface vulnerability.

Combining genetic algorithm with machine learning strategies for designing potent antimicrobial peptides.

BACKGROUND: Current methods in machine learning provide approaches for solving challenging, multiple constraint design problems. While deep learning and related neural networking methods have state-of-the-art performance, their vulnerability in decision making processes leading to irrational outcomes is a major concern for their implementation. With the rising antibiotic resistance, antimicrobial peptides (AMPs) have increasingly gained attention as novel therapeutic agents. This challenging design problem requires peptides which meet the multiple constraints of limiting drug-resistance in bacteria, preventing secondary infections from imbalanced microbial flora, and avoiding immune system suppression. AMPs offer a promising, bioinspired design space to targeting antimicrobial activity, but their versatility also requires the curated selection from a combinatorial sequence space. This space is too large for brute-force methods or currently known rational design approaches outside of machine learning. While there has been progress in using the design space to more effectively target AMP activity, a widely applicable approach has been elusive. The lack of transparency in machine learning has limited the advancement of scientific knowledge of how AMPs are related among each other, and the lack of general applicability for fully rational approaches has limited a broader understanding of the design space. METHODS: Here we combined an evolutionary method with rough set theory, a transparent machine learning approach, for designing antimicrobial peptides (AMPs). Our method achieves the customization of AMPs using supervised learning boundaries. Our system employs in vitro bacterial assays to measure fitness, codon-representation of peptides to gain flexibility of sequence selection in DNA-space with a genetic algorithm and machine learning to further accelerate the process. RESULTS: We use supervised machine learning and a genetic algorithm to find a peptide active against S. epidermidis, a common bacterial strain for implant infections, with an improved aggregation propensity average for an improved ease of synthesis. CONCLUSIONS: Our results demonstrate that AMP design can be customized to maintain activity and simplify production. To our knowledge, this is the first time when codon-based genetic algorithms combined with rough set theory methods is used for computational search on peptide sequences.

American Academy of Clinical Neuropsychology (AACN) 2021 consensus statement on validity assessment: Update of the 2009 AACN consensus conference statement on neuropsychological assessment of effort, response bias, and malingering.

Objective: Citation and download data pertaining to the 2009 AACN consensus statement on validity assessment indicated that the topic maintained high interest in subsequent years, during which key terminology evolved and relevant empirical research proliferated. With a general goal of providing current guidance to the clinical neuropsychology community regarding this important topic, the specific update goals were to: identify current key definitions of terms relevant to validity assessment; learn what experts believe should be reaffirmed from the original consensus paper, as well as new consensus points; and incorporate the latest recommendations regarding the use of validity testing, as well as current application of the term 'malingering.' Methods: In the spring of 2019, four of the original 2009 work group chairs and additional experts for each work group were impaneled. A total of 20 individuals shared ideas and writing drafts until reaching consensus on January 21, 2021. Results: Consensus was reached regarding affirmation of prior salient points that continue to garner clinical and scientific support, as well as creation of new points. The resulting consensus statement addresses definitions and differential diagnosis, performance and symptom validity assessment, and research design and statistical issues. Conclusions/Importance: In order to provide bases for diagnoses and interpretations, the current consensus is that all clinical and forensic evaluations must proactively address the degree to which results of neuropsychological and psychological testing are valid. There is a strong and continually-growing evidence-based literature on which practitioners can confidently base their judgments regarding the selection and interpretation of validity measures.

Bioinspired multifunctional adhesive system for next generation bio-additively designed dental restorations.

Resin-based composite has overtaken dental amalgam as the most popular material for the repair of lost or damaged tooth structure. In spite of the popularity, the average composite lifetime is about half that of amalgam restorations. The leading cause of composite-restoration failure is decay at the margin where the adhesive is applied. The adhesive is intended to seal the composite/tooth interface, but the adhesive seal to dentin is fragile and readily degraded by acids, enzymes and other oral fluids. The inherent weakness of this material system is attributable to several factors including the lack of antimicrobial properties, remineralization capabilities and durable mechanical performance - elements that are central to the integrity of the adhesive/dentin (a/d) interfacial seal. Our approach to this problem offers a transition from a hybrid to a biohybrid structure. Discrete peptides are tethered to polymers to provide multi-bio-functional adhesive formulations that simultaneously achieve antimicrobial and remineralization properties. The bio-additive materials design combines several functional properties with the goal of providing an adhesive that will serve as a durable barrier to recurrent decay at the composite/tooth interface. This article provides an overview of our multi-faceted approach which uses peptides tethered to polymers and new polymer chemistries to achieve the next generation adhesive system - an adhesive that provides antimicrobial properties, repair of defective dentin and enhanced mechanical performance.

Evidence for co-translational misincorporation of non-canonical amino acid hydroxyproline in recombinant antibodies produced in Chinese Hamster Ovary (CHO) cell lines.

With the advent of highly sensitive technologies such as tandem mass spectrometry and next-generation sequencing, recombinant antibodies are now routinely analyzed for the presence of low-level sequence variants including amino acid misincorporations. During mAb cell culture process development, we found that proline was replaced with the non-canonical amino acid, hydroxyproline, in the protein sequence. We investigated the relationship between proline content in the cell culture media and proline sequence variants and found that the proline concentration was inversely correlated with the amount of sequence variants detected in the protein sequence. Hydroxyproline incorporation has been previously reported in recombinant proteins produced in mammalian expression systems as a post-translational modification. Given the dependency on proline levels, the mechanism was then investigated. To address the possibility of co-translational misincorporation of hydroxyproline, we used tandem mass spectrometry to measure incorporation of stable-isotope labelled hydroxyproline added to the feed of a production bioreactor. We discovered co-translational misincorporation of labelled hydroxyproline in the recombinant antibody. These findings are significant, since they underscore the need to track non-canonical amino acid incorporation as a co-translational event in CHO cells. Understanding the mechanism of hydroxyproline incorporation is crucial in developing an appropriate control strategy during biologics production.

Antimicrobial Peptide-Polymer Conjugates for Dentistry.

Bacterial adhesion and growth at the composite/adhesive/tooth interface remain the primary cause of dental composite restoration failure. Early colonizers, including Streptococcus mutans, play a critical role in the formation of dental caries by creating an environment that reduces the adhesive's integrity. Subsequently, other bacterial species, biofilm formation, and lactic acid from S. mutans demineralize the adjoining tooth. Because of their broad spectrum of antibacterial activity and low risk for antibiotic resistance, antimicrobial peptides (AMPs) have received significant attention to prevent bacterial biofilms. Harnessing the potential of AMPs is still very limited in dentistry-a few studies have explored peptide-enabled antimicrobial adhesive copolymer systems using mainly nonspecific adsorption. In the current investigation, to avoid limitations from nonspecific adsorption and to prevent potential peptide leakage out of the resin, we conjugated an AMP with a commonly used monomer for dental adhesive formulation. To tailor the flexibility between the peptide and the resin material, we designed two different spacer domains. The spacer-integrated antimicrobial peptides were conjugated to methacrylate (MA), and the resulting MA-AMP monomers were next copolymerized into dental adhesives as AMP-polymer conjugates. The resulting bioactivity of the polymethacrylate-based AMP conjugated matrix activity was investigated. The antimicrobial peptide conjugated to the resin matrix demonstrated significant antimicrobial activity against S. mutans. Secondary structure analyses of conjugated peptides were applied to understand the activity differential. When mechanical properties of the adhesive system were investigated with respect to AMP and cross-linking concentration, resulting AMP-polymer conjugates maintained higher compressive moduli compared to hydrogel analogues including polyHEMA. Overall, our result provides a robust approach to develop a fine-tuned bioenabled peptide adhesive system with improved mechanical properties and antimicrobial activity. The results of this study represent a critical step toward the development of peptide-conjugated dentin adhesives for treatment of secondary caries and the enhanced durability of dental composite restorations.

Malingering Detection of Cognitive Impairment With the b Test Is Boosted Using Machine Learning.

Objective: Here we report an investigation on the accuracy of the b Test, a measure to identify malingering of cognitive symptoms, in detecting malingerers of mild cognitive impairment. Method: Three groups of participants, patients with Mild Neurocognitive Disorder (n = 21), healthy elders (controls, n = 21), and healthy elders instructed to simulate mild cognitive disorder (malingerers, n = 21) were administered two background neuropsychological tests (MMSE, FAB) as well as the b Test. Results: Malingerers performed significantly worse on all error scores as compared to patients and controls, and performed poorly than controls, but comparably to patients, on the time score. Patients performed significantly worse than controls on all scores, but both groups showed the same pattern of more omission than commission errors. By contrast, malingerers exhibited the opposite pattern with more commission errors than omission errors. Machine learning models achieve an overall accuracy higher than 90% in distinguishing patients from malingerers on the basis of b Test results alone. Conclusions: Our findings suggest that b Test error scores accurately distinguish patients with Mild Neurocognitive Disorder from malingerers and may complement other validated procedures such as the Medical Symptom Validity Test.

Threats to adhesive/dentin interfacial integrity and next generation bio-enabled multifunctional adhesives.

Nearly 100 million of the 170 million composite and amalgam restorations placed annually in the United States are replacements for failed restorations. The primary reason both composite and amalgam restorations fail is recurrent decay, for which composite restorations experience a 2.0-3.5-fold increase compared to amalgam. Recurrent decay is a pernicious problem-the standard treatment is replacement of defective composites with larger restorations that will also fail, initiating a cycle of ever-larger restorations that can lead to root canals, and eventually, to tooth loss. Unlike amalgam, composite lacks the inherent capability to seal discrepancies at the restorative material/tooth interface. The low-viscosity adhesive that bonds the composite to the tooth is intended to seal the interface, but the adhesive degrades, which can breach the composite/tooth margin. Bacteria and bacterial by-products such as acids and enzymes infiltrate the marginal gaps and the composite's inability to increase the interfacial pH facilitates cariogenic and aciduric bacterial outgrowth. Together, these characteristics encourage recurrent decay, pulpal damage, and composite failure. This review article examines key biological and physicochemical interactions involved in the failure of composite restorations and discusses innovative strategies to mitigate the negative effects of pathogens at the adhesive/dentin interface. © 2019 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater 107B:2466-2475, 2019.

Wait, There's a Baby in this Bath Water! Update on Quantitative and Qualitative Cut-Offs for Rey 15-Item Recall and Recognition.

OBJECTIVE: Evaluate the effectiveness of Rey 15-item plus recognition data in a large neuropsychological sample. METHOD: Rey 15-item plus recognition scores were compared in credible (n = 138) and noncredible (n = 353) neuropsychology referrals. RESULTS: Noncredible patients scored significantly worse than credible patients on all Rey 15-item plus recognition scores. When cut-offs were selected to maintain at least 89.9% specificity, cut-offs could be made more stringent, with the highest sensitivity found for recognition correct (cut-off ≤11; 62.6% sensitivity) and the combination score (recall + recognition - false positives; cut-off ≤22; 60.6% sensitivity), followed by recall correct (cut-off ≤11; 49.3% sensitivity), and recognition false positive errors (≥3; 17.9% sensitivity). A cut-off of ≥4 applied to a summed qualitative error score for the recall trial resulted in 19.4% sensitivity. Approximately 10% of credible subjects failed either recall correct or recognition correct, whereas two-thirds of noncredible patients (67.7%) showed this pattern. Thirteen percent of credible patients failed either recall correct, recognition correct, or the recall qualitative error score, whereas nearly 70% of noncredible patients failed at least one of the three. Some individual qualitative recognition errors had low false positive rates (<2%) indicating that their presence was virtually pathognomonic for noncredible performance. Older age (>50) and IQ < 80 were associated with increased false positive rates in credible patients. CONCLUSIONS: Data on a larger sample than that available in the 2002 validation study show that Rey 15-item plus recognition cut-offs can be made more stringent, and thereby detect up to 70% of noncredible test takers, but the test should be used cautiously in older individuals and in individuals with lowered IQ.

Peptide Mediated Antimicrobial Dental Adhesive System.

The most common cause for dental composite failures is secondary caries due to invasive bacterial colonization of the adhesive/dentin (a/d) interface. Innate material weakness often lead to an insufficient seal between the adhesive and dentin. Consequently, bacterial by-products invade the porous a/d interface leading to material degradation and dental caries. Current approaches to achieve antibacterial properties in these materials continue to raise concerns regarding hypersensitivity and antibiotic resistance. Herein, we have developed a multi-faceted, bio-functionalized approach to overcome the vulnerability of such interfaces. An antimicrobial adhesive formulation was designed using a combination of antimicrobial peptide and a ε-polylysine resin system. Effector molecules boasting innate immunity are brought together with a biopolymer offering a two-fold biomimetic design approach. The selection of ε-polylysine was inspired due to its non-toxic nature and common use as food preservative. Biomolecular characterization and functional activity of our engineered dental adhesive formulation were assessed and the combinatorial formulation demonstrated significant antimicrobial activity against Streptococcus mutans. Our antimicrobial peptide-hydrophilic adhesive hybrid system design offers advanced, biofunctional properties at the critical a/d interface.

Self-assembling antimicrobial peptides on nanotubular titanium surfaces coated with calcium phosphate for local therapy.

Bacterial infection is a serious medical problem leading to implant failure. The current antibiotic based therapies rise concerns due to bacterial resistance. The family of antimicrobial peptides (AMP) is one of the promising candidates as local therapy agents due to their broad-spectrum activity. Despite AMPs receive increasing attention to treat infection, their effective delivery to the implantation site has been limited. Here, we developed an engineered dual functional peptide which delivers AMP as a biomolecular therapeutic agent onto calcium phosphate (Ca-P) deposited nanotubular titanium surfaces. Dual functionality of the peptide was achieved by combining a hydroxyapatite binding peptide-1 (HABP1) with an AMP using a flexible linker. HABP functionality of the peptide provided a self-coating property onto the nano-topographies that are designed to improve osteointegration capability, while AMP offered an antimicrobial protection onto the implant surface. We successfully deposited calcium phosphate minerals on nanotubular titanium oxide surface using pulse electrochemical deposition (PECD) and characterized the minerals by XRD, FT-IR, FE-SEM. Antimicrobial activity of the engineered peptide was tested against S. mutans (gram- positive) and E. coli (gram-negative) both in solution and on the Ca-P coated nanotubular titanium surface. In solution activity of AMP and dual functional peptide have the same Minimum Inhibitory Concentration (MIC) (32 mg/mL). The peptide also resulted in the reduction of the number of bacteria both for E.coli and S. mutans compare to control groups on the surface. Antimicrobial features of dual functional peptides are strongly correlated with their structures suggesting tunability in design through linkers regions. The dual-function peptide offers single-step solution for implant surface functionalization that could be applicable to any implant surface having different topographies.