Managing Dry Eye Disease with Novel Medications: Mechanism, Study Validity, Safety, Efficacy, and Practical Application.

Dry eye disease (DED) is a common condition that affects mainly older individuals and women. It is characterized by reduced tear production and increased tear evaporation. Symptoms include burning, irritation, tearing, and blurry vision. This paper reviews key trials of various new DED treatments, including their mechanism of action, study outcomes, safety, and efficacy. The paper also includes a critical assessment of the trial's validity and potential pharmacy applications of these new treatments. The literature search was conducted through PubMed, the Cochrane Central Register of Controlled Trials, and Google Scholar. The keywords "Dry Eye Disease", "lifitegrast", "cyclosporine", "loteprednol etabonate", "varenicline nasal spray", and "perfluorohexyloctane" were used to identify these medications' landmark trials. The articles deemed these medications safe and efficacious, with minimal side effects. Our randomized controlled trial validity comparison found the trials robust with predominantly low bias. Cyclosporine and loteprednol are effective when artificial tears fail, while perfluorohexyloctane reduces tear film evaporation and is preservative-free. Varenicline offers drug delivery via the nasal route and is appropriate for contact lens users. In conclusion, these FDA-approved novel medications exhibit safety and efficacy in managing DED. Further research is needed on long-term outcomes, efficacy, and side-effect comparisons, and combination therapy benefits.

Assessing Ability for ChatGPT to Answer Total Knee Arthroplasty-Related Questions.

BACKGROUND: Artificial intelligence in the field of orthopaedics has been a topic of increasing interest and opportunity in recent years. Its applications are widespread both for physicians and patients, including use in clinical decision-making, in the operating room, and in research. In this study, we aimed to assess the quality of ChatGPT answers when asked questions related to total knee arthroplasty. METHODS: ChatGPT prompts were created by turning 15 of the American Academy of Orthopaedic Surgeons Clinical Practice Guidelines into questions. An online survey was created, which included screenshots of each prompt and answers to the 15 questions. Surgeons were asked to grade ChatGPT answers from 1 to 5 based on their characteristics: (1) relevance, (2) accuracy, (3) clarity, (4) completeness, (5) evidence-based, and (6) consistency. There were 11 Adult Joint Reconstruction fellowship-trained surgeons who completed the survey. Questions were subclassified based on the subject of the prompt: (1) risk factors, (2) implant/intraoperative, and (3) pain/functional outcomes. The average and standard deviation for all answers, as well as for each subgroup, were calculated. Inter-rater reliability (IRR) was also calculated. RESULTS: All answer characteristics were graded as being above average (ie, a score > 3). Relevance demonstrated the highest scores (4.43 ± 0.77) by surgeons surveyed, and consistency demonstrated the lowest scores (3.54 ± 1.10). ChatGPT prompts in the Risk Factors group demonstrated the best responses, while those in the Pain/Functional Outcome group demonstrated the lowest. The overall IRR was found to be 0.33 (poor reliability), with the highest IRR for relevance (0.43) and the lowest for evidence-based (0.28). CONCLUSIONS: ChatGPT can answer questions regarding well-established clinical guidelines in total knee arthroplasty with above-average accuracy but demonstrates variable reliability. This investigation is the first step in understanding large language model artificial intelligence like ChatGPT and how well they perform in the field of arthroplasty.

Validation of an artificial intelligence-based method to automate Cobb angle measurement on spinal radiographs of children with adolescent idiopathic scoliosis.

BACKGROUND: Accurately measuring the Cobb angle on radiographs is crucial for diagnosis and treatment decisions for adolescent idiopathic scoliosis (AIS). However, manual Cobb angle measurement is time-consuming and subject to measurement variation, especially for inexperienced clinicians. AIM: This study aimed to validate a novel artificial-intelligence-based (AI) algorithm that automatically measures the Cobb angle on radiographs. DESIGN: This is a retrospective cross-sectional study. SETTING: The population of patients attended the Stollery Children's Hospital in Alberta, Canada. POPULATION: Children who: 1) were diagnosed with AIS, 2) were aged between 10 and 18 years old, 3) had no prior surgery, and 4) had a radiograph out of brace, were enrolled. METHODS: A total of 330 spinal radiographs were used. Among those, 130 were used for AI model development and 200 were used for measurement validation. Automatic Cobb angle measurements were validated by comparing them with manual ones measured by a rater with 20+ years of experience. Analysis was performed using the standard error of measurement (SEM), inter-method intraclass correlation coefficient (ICC2,1), and percentage of measurements within clinical acceptance (≤5°). Subgroup analysis was conducted by severity, region, and X-ray system to identify any systematic biases. RESULTS: The AI method detected 346 of 352 manually measured curves (mean±standard deviation: 24.7±9.5°), achieving 91% (316/346) of measurements within clinical acceptance. Excellent reliability was obtained with 0.92 ICC and 0.79° SEM. Comparable performance was found throughout all subgroups, and no systematic biases in performance affecting any subgroup were discovered. The algorithm measured each radiograph approximately 18s on average which is slightly faster than the estimated measurement time of an experienced rater. Radiographs taken by the EOS X-ray system were measured more quickly on average than those taken by a conventional digital X-ray system (10s vs. 26s). CONCLUSIONS: An AI-based algorithm was developed to measure the Cobb angle automatically on radiographs and yielded reliable measurements quickly. The algorithm provides detailed images on how the angles were measured, providing interpretability that can give clinicians confidence in the measurements. CLINICAL REHABILITATION IMPACT: Employing the algorithm in practice could streamline clinical workflow and optimize measurement accuracy and speed in order to inform AIS treatment decisions.

Examining General Vaccine Acceptance and COVID-19 Vaccine Intention: Comparison across Pharmacies in California and Ohio.

Given the complexities surrounding vaccine acceptance of COVID-19 and other vaccines, it is important to determine the underlying health beliefs of patients in order to bridge gaps and promote vaccine confidence. With pharmacies as key hubs for vaccinations and vaccine conversations, examining patient perspectives through the lens of community pharmacy may provide a targeted insight into their patient populations. The primary objectives of this study were to measure COVID-19 vaccine intention and compare vaccine acceptance at pharmacies and clinics between California and Ohio. The secondary objectives included subgroup comparisons of vaccine intention and vaccine acceptance based on demographic characteristics. A previously validated survey instrument (5C survey tool) was administered at pharmacy sites in California and Ohio to examine respondents' vaccine acceptance (confidence, complacency, constrains, calculation, and collective responsibility). Additional items were added to capture flu and COVID-19 vaccine intention. Reliability and confirmatory factor analysis were completed for the 13-item 5C. Comparisons were made between sites and within different demographic groups. Good reliability (Cronbach's alpha = 0.768) was found, with nearly all items loading on their hypothesized domains. Respondents from Ohio had significantly higher complacency and constraints domain scores. Highest acceptance was revealed in females, individuals with a Master's degree or higher, and individuals with the intention to receive a flu vaccine. The adapted 5C is a reasonable tool to measure vaccine intention in English-speaking populations in the US. Certain demographic groups may have lower vaccine acceptance; pharmacists could consider implementing a tool, such as the 5C tool, to identify low acceptance. Given that the 5C tool gathers information on different domains of vaccine acceptance, healthcare professionals could utilize these results to improve trust and vaccine confidence in their patient populations; focused conversations concerning any of the respective domains could best address individual concerns and barriers about vaccinations, notably the COVID-19 and flu vaccines.

Fast Tracking-Vaccine Safety, Efficacy, and Lessons Learned: A Narrative Review.

(1) Background: The COVID-19 pandemic has led to the fast-tracked development of vaccines under emergency use authorization. In light of the growing concerns about fast-tracked vaccines, this article reviews the safety, efficacy, and lessons learned of previously fast-tracked vaccines. (2) Methods: An article search regarding the safety and efficacy of fast-tracked vaccines was done in PubMed, Embase, Web of Science, and ScienceDirect. Of the 104 results, 24 articles were included. Five articles about BiovaxID, THERATOPE®, Sipuleucel-T, and AIDSVAX were also reviewed. (3) Results: The overall efficacy was shown to be 77-100%, with seroprotection against the viruses ranging from 87 to 100%. The antibody responses for optimal protection against the viruses fall within 85-97%. Generally, the fast-tracked vaccines were well-tolerated and had few significant adverse events, except for the H1N1 pandemic vaccine and its association with narcolepsy. To have accurate, precise, and timely fast-tracked vaccines, communication, sharing resources/data, and improving the current structures/outbreak operations are crucial. (4) Conclusions: This review found the FDA's fast-tracking process for vaccines to have rigorous standards similar to the normal process. The previous fast-tracked vaccines were safe and efficacious. The lessons drawn from previous studies highlighted the significance of planning and utilizing global resources during significant outbreaks.

COVID-19 behavioral questionnaire (CoBQ): Comparing the pandemic's impact on health behavior in three US states.

Background: The COVID-19 pandemic impacted daily routines for a majority of the population, with implications for their health behaviors. Racial and ethnic minorities have been disproportionately impacted by COVID-19. The novel COVID-19 Behavioral Questionnaire (CoBQ) was developed in Fall 2020 to provide a means to measure the impact of the COVID-19 pandemic on the United States population. The study utilized behavioral domains to determine which demographic groups reported that they were made the most vulnerable during Fall-Winter 2020-2021 of the pandemic. Objectives: The study aimed to further validate and test the CoBQ in varied US regions and compare the scores obtained from three states, California, Ohio, and Illinois. Methods: A prospective, multi-site survey-based study was designed to further validate and test the 17-item CoBQ in varied populations. Respondents included patients on routine visits at each pharmacy or clinical site who agreed to complete the survey online via Qualtrics. Data analyses included descriptive statistics, psychometric testing, and comparison of groups using Analysis of Variance. Results: Completed surveys (n = 507) between October 2021 and March 2021 were analyzed. Respondents were mostly female, white, and had some college education. The CoBQ showed improved reliability compared with previous testing and strong construct validity through factor analysis. Overall scores were similar between three states. The most impacted groups included those who reported within the 18-49 age group, a yearly household income <$50 000, or education up to high school. Conclusions: The CoBQ is the first validated tool to measure the negative impact of the COVID-19 pandemic on health behaviors. Results could serve as a baseline to address the most vulnerable patient groups and support identified behavioral needs during a similar pandemic situation.

The association among cancer patients' collaboration with their healthcare providers, self-management and well-being during radiotherapy: An observational, cross-sectional survey.

OBJECTIVES: Patients adapt to cancer through self-management, which requires collaboration between patients and their healthcare providers. We aimed to describe patterns of patient-provider collaboration during radiotherapy and examine associations among patient-provider collaboration, self-management and well-being. METHODS: An observational, cross-sectional study was conducted at a cancer centre in the province of Ontario, Canada. Cancer patients (N = 130) completed a one-time questionnaire during their radiotherapy. The questionnaire assessed three variables: collaboration with healthcare providers, self-management and well-being. Patterns of collaboration were analysed using descriptive statistics. Associations among study variables were assessed through structural equation modelling (SEM). Separate models were tested for patient-nurse and patient-oncologist collaboration. RESULTS: Participants reported greater collaboration with oncologists than with nurses or radiation therapists. Most participants reported no collaboration with other providers within healthcare teams (e.g. social workers, dietitians). SEM revealed different patterns for the patient-nurse and patient-oncologist collaboration models, where collaboration predicted one self-management aspect, and both physical and mental well-being. CONCLUSION: During radiotherapy, patients collaborated mainly with doctors, nurses and radiation therapists. Collaborative relationships between patients and providers may enhance patient outcomes by fostering their self-management skills. Initiatives to strengthen patient-provider relationships and support self-management should be developed and applied to interprofessional-cancer-care teams. IMPACT: This is the first known study to empirically support the links among patient-provider collaboration, self-management and patient outcomes. The study results can enhance practice, research and education.

Biodiversity and thermal ecological function: The influence of freshwater algal diversity on local thermal environments.

The influence of temperature on diversity and ecosystem functioning is well studied; the converse however, that is, how biodiversity influences temperature, much less so. We manipulated freshwater algal species diversity in microbial microcosms to uncover how diversity influenced primary production, which is well documented in biodiversity research. We then also explored how visible-spectrum absorbance and the local thermal environment responded to biodiversity change. Variations in the local thermal environment, that is, in the temperature of the immediate surroundings of a community, are known to matter not only for the rate of ecosystem processes, but also for persistence of species assemblages and the very relationship between biodiversity and ecosystem functioning. In our microcosm experiment, we found a significant positive association between algal species richness and primary production, a negative association between primary production and visible-spectrum absorbance, and a positive association between visible-spectrum absorbance and the response of the local thermal environment (i.e., change in thermal infrared emittance over a unit time). These findings support an indirect effect of algal diversity on the local thermal environment pointing to a hitherto unrecognized biodiversity effect in which diversity has a predictable influence on local thermal environments.

Degrés de collaboration perçus entre les patients atteints de cancer et leurs prestataires de soins pendant la radiothérapie.

Cette étude décrit les tendances en matière de relations collaboratives entre les patients et les professionnels de la santé pendant la radiothérapie. Pour ce faire, 130 patients atteints de cancer et traités par radiothérapie dans un centre de cancérologie de l'Ontario ont répondu à un sondage ponctuel. Les principales variables de l'étude portaient sur la collaboration entre les patients et les prestataires de soins de santé et le bien-être des participants. L'étude a révélé que les patients collaboreraient mieux avec les infirmières, les radio-oncologues et les radiothérapeutes qu'avec les nutritionnistes, les travailleurs sociaux et le personnel d'accompagnement spirituel [F(5, 760) = 430,42, p<001]. Les participants qui vivaient davantage de détresse vis-à-vis leurs symptômes collaboraient toutefois mieux les travailleurs sociaux (p < .05) et les nutritionnistes (p < .05), par rapport à ceux qui vivaient moins de détresse. Nous avons émis l'hypothèse selon laquelle les participants dont les symptômes étaient moins contraignants ne ressentaient pas le besoin de rencontrer ces professionnels. Nous discutons actuellement des futures orientations concernant l'intégration de mesures centrées sur le patient (avec l'éducation axée sur l'autogestion, par exemple) dans les modèles interprofessionnels de soins du cancer.

Perceived levels of collaboration between cancer patients and their providers during radiation therapy.

This study described the patterns within collaborative relationships between patients and health care professionals during radiation therapy (RT). A one-time survey was administered to cancer patients (N=130) receiving RT at one Ontario cancer centre. The key study variables were collaboration between patients and health care providers and participants' well-being. Participants reported higher levels of collaboration with nurses, radiation oncologists, and radiation therapists than with dietitians, social workers and spiritual support personnel [F(5, 760) = 430.42, p < .001]. Participants with more symptom distress collaborated more with some health care professionals than those with less distress, but this was only true for collaboration with social workers (p < .05) and dietitians (p < .05). We postulated that participants did not require services from dietitians and social workers when symptom burden was low. Future directions regarding integration of patient-centred measures (e.g., self-management education) into interprofessional models for cancer care are discussed.

Design and synthesis of orally bioavailable aminopyrrolidinone histone deacetylase 6 inhibitors.

Histone deacetylase 6 (HDAC6) removes the acetyl group from lysine residues in a number of non-histone substrates and plays important roles in microtubule dynamics and chaperone activities. There is growing interest in identifying HDAC6-selective inhibitors as chemical biology tools and ultimately as new therapeutic agents. Herein we report the design, synthesis, and phenotypic screening of a novel class of 3-aminopyrrolidinone-based hydroxamic acids as HDAC6 inhibitors. In particular, the α-methyl-substituted enantiomer 33 (3-S) showed significant in-cell tubulin acetylation (Tub-Ac) with an EC50 of 0.30 µM but limited impact on p21 levels at various concentrations. In enzyme inhibition assays, 33 demonstrated high selectivity for HDAC6 with an IC50 of 0.017 µM and selectivity indexes of 10 against HDAC8 and over 4000 against HDAC1-3 isoforms. Moreover, 33 has suitable drug metabolism and pharmacokinetics properties compared with other hydroxamic acid-based HDAC inhibitors, warranting further biological studies and development as a selective HDAC6 inhibitor.

Structure-Based Design and Synthesis of Potent Cyclic Peptides Inhibiting the YAP-TEAD Protein-Protein Interaction.

The YAP-TEAD protein-protein interaction (PPI) mediates the oncogenic function of YAP, and inhibitors of this PPI have potential usage in treatment of YAP-involved cancers. Here we report the design and synthesis of potent cyclic peptide inhibitors of the YAP-TEAD interaction. A truncation study of YAP interface 3 peptide identified YAP(84-100) as a weak peptide inhibitor (IC50 = 37 µM), and an alanine scan revealed a beneficial mutation, D94A. Subsequent replacement of a native cation-π interaction with an optimized disulfide bridge for conformational constraint and synergistic effect between macrocyclization and modification at positions 91 and 93 greatly boosted inhibitory activity. Peptide 17 was identified with an IC50 of 25 nM, and the binding affinity (K d = 15 nM) of this 17mer peptide to TEAD1 proved to be stronger than YAP(50-171) (K d = 40 nM).

Identification of a novel aminotetralin class of HDAC6 and HDAC8 selective inhibitors.

Herein we report the identification of a novel class of HDAC6 and HDAC8 selective inhibitors through a unique chemistry and phenotypic screening strategy. Tetrahydroisoquinoline 12 was identified as a potent HDAC6 and HDAC8 dual inhibitor from a focused library through cellular tubulin acetylation and p21 induction screening assays. Scaffold hopping from 12 led to the discovery of an aminotetralin class of HDAC inhibitors. In particular, the 3-R stereoisomer 32 showed highly potent inhibition against HDAC6 and HDAC8 with IC50 values of 50 and 80 nM, respectively. Treatment of neuroblastoma BE(2)C cells with 32 resulted in elevated levels of acetylated tubulin, TrkA, and neurite outgrowth with only marginal effects on p21 induction and histone H3 acetylation. Consistent with its weak enzymatic inhibition of HDAC1, 32 showed significantly less cytotoxicity than SAHA and moderately inhibited the growth of myeloma NCI-H929 and OPM-2 cells.

Potential drug interventions for diabetic retinopathy.

Diabetic retinopathy (DR) is of great interest to the drug discovery community owing to the rising worldwide prevalence of diabetes and its associated complications. The complex molecular mechanism associated with DR development and the poor translatability of available animal models to late-stage DR are considered to be major hurdles for drug discovery. Here we will provide an overview of the mechanistic rationale as well as clinical efficacy of drug candidates, and highlight emerging and potential targets for therapeutic intervention at different stages of DR.

Pharmacokinetic optimization of class-selective histone deacetylase inhibitors and identification of associated candidate predictive biomarkers of hepatocellular carcinoma tumor response.

Herein, we describe the pharmacokinetic optimization of a series of class-selective histone deacetylase (HDAC) inhibitors and the subsequent identification of candidate predictive biomarkers of hepatocellular carcinoma (HCC) tumor response for our clinical lead using patient-derived HCC tumor xenograft models. Through a combination of conformational constraint and scaffold hopping, we lowered the in vivo clearance (CL) and significantly improved the bioavailability (F) and exposure (AUC) of our HDAC inhibitors while maintaining selectivity toward the class I HDAC family with particular potency against HDAC1, resulting in clinical lead 5 (HDAC1 IC50 = 60 nM, mouse CL = 39 mL/min/kg, mouse F = 100%, mouse AUC after single oral dose at 10 mg/kg = 6316 h·ng/mL). We then evaluated 5 in a biomarker discovery pilot study using patient-derived tumor xenograft models, wherein two out of the three models responded to treatment. By comparing tumor response status to compound tumor exposure, induction of acetylated histone H3, candidate gene expression changes, and promoter DNA methylation status from all three models at various time points, we identified preliminary candidate response prediction biomarkers that warrant further validation in a larger cohort of patient-derived tumor models and through confirmatory functional studies.

Application of p21 and klf2 reporter gene assays to identify selective histone deacetylase inhibitors for cancer therapy.

Novel 2-aminoanilide histone deacetylase (HDAC) inhibitors were designed to increase their contact with surface residues surrounding the HDAC active site compared to the contacts made by existing clinical 2-aminoanilides such as SNDX-275, MGCD0103, and Chidamide. Their HDAC selectivity was assessed using p21 and klf2 reporter gene assays in HeLa and A204 cells, respectively, which provide a cell-based readout for the inhibition of HDACs associated either with the p21 or klf2 promoter. A subset of the designed compounds selectively induced p21 over klf2 relative to the clinical reference compound SNDX-275. A representative lead compound from this subset had antiproliferative effects in cancer cells associated with induction of acetylated histone H4, endogenous p21, cell cycle arrest, and apoptosis. The p21- versus klf2-selective compounds described herein may provide a chemical starting point for developing clinically-differentiated HDAC inhibitors for cancer therapy.

Cerebral grey, white matter and csf in never-medicated, first-episode schizophrenia.

We report the first voxel-based morphometric (VBM) study to examine cerebral grey and white matter and cerebrospinal fluid (CSF) using computational morphometry in never-medicated, first-episode psychosis (FEP). Region-of-interest (ROI) analysis was also performed blind to group membership. 26 never-medicated individuals with FEP (23 with DSM-IV schizophrenia) and 38 healthy controls had MRI brain scans. Groups were balanced for age, sex, handedness, ethnicity, paternal socio-economic status, and height. Healthy controls were recruited from the local community by advertisement. Grey matter, white matter, and CSF: global brain volume ratios were significantly smaller in patients. Patients had significantly less grey matter volume in L and R caudate nuclei, cingulate gyri, parahippocampal gyri, superior temporal gyri, cerebellum and R thalamus, prefrontal cortex. They also had significantly less white matter volume in the R anterior limb of the internal capsule fronto-occipital fasciculus and L and R fornices, and significantly greater CSF volume especially in the R lateral ventricle. Excluding the 3 subjects with brief psychotic disorder did not alter our results. Our data suggest that fronto-temporal and subcortical-limbic circuits are morphologically abnormal in never-medicated, schizophrenia. ROI analysis comparing the schizophrenia group (n=23) with the healthy controls (n=38) confirmed caudate volumes were significantly smaller bilaterally by 11%, and lateral ventricular volume was significantly larger on the right by 26% in the patients. Caudate nuclei and lateral ventricular volume measurements were uncorrelated (Pearson correlation coefficient 0.30, p=0.10), ruling out the possibility of segmentation artefact. Ratio of lateral ventricle to caudate volume was bilaterally significantly increased (p<0.005, 2-tailed), which could represent an early biomarker in first-episode, never-medicated schizophrenia.

Mapping chemical space using molecular descriptors and chemical genetics: deacetylase inhibitors.

An objective of chemical genetics is to understand the relationships between the structures of small molecules and their phenotypic effects in intact living systems. We present here the results of a global analysis of a molecular descriptor space constructed using structural descriptors of an aryl 1,3-dioxane-based diversity-oriented synthesis-derived library containing structural biasing elements directed at inhibiting protein deacetylases. Using principal component analysis and three-dimensional visualization, we generated metric space maps with morphological features contributed by different diversity elements within the library. Filtering these maps using phenotypic descriptors derived from measurements of small-molecule activities in an array of cell-based assays revealed different densities of biological activity within specific subspaces. These results provide evidence that certain structural features may be important for conferring potency and selectivity on deacetylase inhibitors with respect to tubulin and histone acetylation. Moreover, these results highlight an example of the importance of using functional measures to assess molecular diversity. Similar analyses of other chemical spaces and activity classes promise to facilitate the development of chemical genetics.

Modular synthesis and preliminary biological evaluation of stereochemically diverse 1,3-dioxanes.

Modular synthesis and substrate stereocontrol were combined to furnish 18,000 diverse 1,3-dioxanes whose distribution in chemical space rivals that of a reference set of over 2,000 bioactive small molecules. Library quality was assessed at key synthetic stages, culminating in a detailed postsynthesis analysis of purity, yield, and structural characterizability, and the resynthesis of library subsets that did not meet quality standards. The importance of this analysis-resynthesis process is highlighted by the discovery of new biological probes through organismal and protein binding assays, and by determination of the building block and stereochemical basis for their bioactivity. This evaluation of a portion of the 1,3-dioxane library suggests that many additional probes for chemical genetics will be identified as the entire library becomes biologically annotated.

Multidimensional chemical genetic analysis of diversity-oriented synthesis-derived deacetylase inhibitors using cell-based assays.

Systematic chemical genetics aims to explore the space representing interactions between small molecules and biological systems. Beyond measuring binding interactions and enzyme inhibition, measuring changes in the activity of proteins in intact signaling networks is necessary. Toward this end, we are partitioning chemical space into regions with different biological activities using a panel of cell-based assays and small molecule "chemical genetic modifiers." Herein, we report on the use of this methodology for the discovery of 617 small molecule inhibitors of histone deacetylases from a multidimensional screen of an encoded, diversity-oriented synthesis library. Following decoding of chemical tags and resynthesis, we demonstrate the selectivity of one inhibitory molecule (tubacin) toward alpha-tubulin deacetylation and another (histacin) toward histone deacetylation. These small molecules will facilitate dissecting the role of acetylation in a variety of cell biological processes.