The spindle checkpoint proteins BUB1 and BUBR1: (SLiM)ming down to the basics.

Benzimidazole 1 (BUB1) and budding uninhibited by benzimidazole 1-related 1 (BUBR1) are multidomain paralogs with key roles in chromosome alignment during mitosis and the spindle assembly checkpoint (SAC), an evolutionarily conserved signaling pathway that monitors errors in chromosome segregation during cell division in eukaryotes. Although BUB1 and BUBR1 share a similar domain organization and short linear interaction motifs (SLiMs), they control distinct aspects of chromosome congression and the SAC. Here we discuss the roles of BUB1 and BUBR1 SLiMs in mitosis and complement this with additional insights gleamed from studying their evolution. We show that BUB1 and BUBR1 SLiMs form highly specific interactions that are carefully orchestrated in space and time and contend that they define BUB1 and BUBR1 as organizing hubs that drive SAC signaling and ensure genome stability.

Extracellular lactate as an alternative energy source for retinal bipolar cells.

Retinal bipolar and amacrine cells receive visual information from photoreceptors and participate in the first steps of image processing in the retina. Several studies have suggested the operation of aerobic glycolysis and a lactate shuttle system in the retina due to the high production of this metabolite under aerobic conditions. However, whether bipolar cells form part of this metabolic circuit remains unclear. Here, we show that the monocarboxylate transporter 2 is expressed and functional in inner retinal neurons. Additionally, we used genetically encoded FRET nanosensors to demonstrate the ability of inner retinal neurons to consume extracellular lactate as an alternative to glucose. In rod bipolar cells, lactate consumption allowed cells to maintain the homeostasis of ions and electrical responses. We also found that lactate synthesis and transporter inhibition caused functional alterations and an increased rate of cell death. Overall, our data shed light on a notable but still poorly understood aspect of retinal metabolism.

Loss-of-function G6PD variant moderated high fat diet-induced obesity, adipocyte hypertrophy, and fatty liver in male rats.

Obesity is a major risk factor for liver and cardiovascular diseases. However, obesity-driven mechanisms that contribute to the pathogenesis of multiple organ diseases are still obscure and treatment is inadequate. We hypothesized that increased glucose-6-phosphate dehydrogenase (G6PD), the key rate-limiting enzyme in the pentose shunt, is critical in evoking metabolic reprogramming in multiple organs and is a significant contributor to the pathogenesis of liver and cardiovascular diseases. G6PD is induced by carbohydrate-rich diet and insulin. Long-term (8 months) high-fat diet (HFD) feeding increased body weight and elicited metabolic reprogramming in visceral fat, liver, and aorta, of the wild-type rats. In addition, HFD increased inflammatory chemokines in visceral fat. Interestingly, CRISPR-edited loss-of-function Mediterranean G6PD variant (G6PDS188F) rats, which mimic human polymorphism, moderated HFD-induced weight gain and metabolic reprogramming in visceral fat, liver, and aorta. The G6PDS188F variant prevented HFD-induced CCL7 and adipocyte hypertrophy. Furthermore, the G6PDS188F variant increased Magel2 - a gene encoding circadian clock-related protein that suppresses obesity associated with Prader-Willi syndrome - and reduced HFD-induced non-alcoholic fatty liver. Additionally, the G6PDS188F variant reduced aging-induced aortic stiffening. Our findings suggest G6PD is a regulator of HFD-induced obesity, adipocyte hypertrophy, and fatty liver.

Radiation necrosis after radiation therapy treatment of brain metastases: A computational approach.

Metastasis is the process through which cancer cells break away from a primary tumor, travel through the blood or lymph system, and form new tumors in distant tissues. One of the preferred sites for metastatic dissemination is the brain, affecting more than 20% of all cancer patients. This figure is increasing steadily due to improvements in treatments of primary tumors. Stereotactic radiosurgery (SRS) is one of the main treatment options for patients with a small or moderate number of brain metastases (BMs). A frequent adverse event of SRS is radiation necrosis (RN), an inflammatory condition caused by late normal tissue cell death. A major diagnostic problem is that RNs are difficult to distinguish from BM recurrences, due to their similarities on standard magnetic resonance images (MRIs). However, this distinction is key to choosing the best therapeutic approach since RNs resolve often without further interventions, while relapsing BMs may require open brain surgery. Recent research has shown that RNs have a faster growth dynamics than recurrent BMs, providing a way to differentiate the two entities, but no mechanistic explanation has been provided for those observations. In this study, computational frameworks were developed based on mathematical models of increasing complexity, providing mechanistic explanations for the differential growth dynamics of BMs relapse versus RN events and explaining the observed clinical phenomenology. Simulated tumor relapses were found to have growth exponents substantially smaller than the group in which there was inflammation due to damage induced by SRS to normal brain tissue adjacent to the BMs, thus leading to RN. ROC curves with the synthetic data had an optimal threshold that maximized the sensitivity and specificity values for a growth exponent ß* = 1.05, very close to that observed in patient datasets.

Reproducible Reporting of the Collection and Evaluation of Annotations for Artificial Intelligence Models.

This work puts forth and demonstrates the utility of a reporting framework for collecting and evaluating annotations of medical images used for training and testing artificial intelligence (AI) models in assisting detection and diagnosis. AI has unique reporting requirements, as shown by the AI extensions to the Consolidated Standards of Reporting Trials (CONSORT) and Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) checklists and the proposed AI extensions to the Standards for Reporting Diagnostic Accuracy (STARD) and Transparent Reporting of a Multivariable Prediction model for Individual Prognosis or Diagnosis (TRIPOD) checklists. AI for detection and/or diagnostic image analysis requires complete, reproducible, and transparent reporting of the annotations and metadata used in training and testing data sets. In an earlier work by other researchers, an annotation workflow and quality checklist for computational pathology annotations were proposed. In this manuscript, we operationalize this workflow into an evaluable quality checklist that applies to any reader-interpreted medical images, and we demonstrate its use for an annotation effort in digital pathology. We refer to this quality framework as the Collection and Evaluation of Annotations for Reproducible Reporting of Artificial Intelligence (CLEARR-AI).

Training pathologists to assess stromal tumour-infiltrating lymphocytes in breast cancer synergises efforts in clinical care and scientific research.

A growing body of research supports stromal tumour-infiltrating lymphocyte (TIL) density in breast cancer to be a robust prognostic and predicive biomarker. The gold standard for stromal TIL density quantitation in breast cancer is pathologist visual assessment using haematoxylin and eosin-stained slides. Artificial intelligence/machine-learning algorithms are in development to automate the stromal TIL scoring process, and must be validated against a reference standard such as pathologist visual assessment. Visual TIL assessment may suffer from significant interobserver variability. To improve interobserver agreement, regulatory science experts at the US Food and Drug Administration partnered with academic pathologists internationally to create a freely available online continuing medical education (CME) course to train pathologists in assessing breast cancer stromal TILs using an interactive format with expert commentary. Here we describe and provide a user guide to this CME course, whose content was designed to improve pathologist accuracy in scoring breast cancer TILs. We also suggest subsequent steps to translate knowledge into clinical practice with proficiency testing.

Overcoming chemotherapy resistance in low-grade gliomas: A computational approach.

Low-grade gliomas are primary brain tumors that arise from glial cells and are usually treated with temozolomide (TMZ) as a chemotherapeutic option. They are often incurable, but patients have a prolonged survival. One of the shortcomings of the treatment is that patients eventually develop drug resistance. Recent findings show that persisters, cells that enter a dormancy state to resist treatment, play an important role in the development of resistance to TMZ. In this study we constructed a mathematical model of low-grade glioma response to TMZ incorporating a persister population. The model was able to describe the volumetric longitudinal dynamics, observed in routine FLAIR 3D sequences, of low-grade glioma patients acquiring TMZ resistance. We used the model to explore different TMZ administration protocols, first on virtual clones of real patients and afterwards on virtual patients preserving the relationships between parameters of real patients. In silico clinical trials showed that resistance development was deferred by protocols in which individual doses are administered after rest periods, rather than the 28-days cycle standard protocol. This led to median survival gains in virtual patients of more than 15 months when using resting periods between two and three weeks and agreed with recent experimental observations in animal models. Additionally, we tested adaptive variations of these new protocols, what showed a potential reduction in toxicity, but no survival gain. Our computational results highlight the need of further clinical trials that could obtain better results from treatment with TMZ in low grade gliomas.

The shape of cancer relapse: Topological data analysis predicts recurrence in paediatric acute lymphoblastic leukaemia.

Although children and adolescents with acute lymphoblastic leukaemia (ALL) have high survival rates, approximately 15-20% of patients relapse. Risk of relapse is routinely estimated at diagnosis by biological factors, including flow cytometry data. This high-dimensional data is typically manually assessed by projecting it onto a subset of biomarkers. Cell density and "empty spaces" in 2D projections of the data, i.e. regions devoid of cells, are then used for qualitative assessment. Here, we use topological data analysis (TDA), which quantifies shapes, including empty spaces, in data, to analyse pre-treatment ALL datasets with known patient outcomes. We combine these fully unsupervised analyses with Machine Learning (ML) to identify significant shape characteristics and demonstrate that they accurately predict risk of relapse, particularly for patients previously classified as 'low risk'. We independently confirm the predictive power of CD10, CD20, CD38, and CD45 as biomarkers for ALL diagnosis. Based on our analyses, we propose three increasingly detailed prognostic pipelines for analysing flow cytometry data from ALL patients depending on technical and technological availability: 1. Visual inspection of specific biological features in biparametric projections of the data; 2. Computation of quantitative topological descriptors of such projections; 3. A combined analysis, using TDA and ML, in the four-parameter space defined by CD10, CD20, CD38 and CD45. Our analyses readily extend to other haematological malignancies.

Initial interactions with the FDA on developing a validation dataset as a medical device development tool.

Quantifying tumor-infiltrating lymphocytes (TILs) in breast cancer tumors is a challenging task for pathologists. With the advent of whole slide imaging that digitizes glass slides, it is possible to apply computational models to quantify TILs for pathologists. Development of computational models requires significant time, expertise, consensus, and investment. To reduce this burden, we are preparing a dataset for developers to validate their models and a proposal to the Medical Device Development Tool (MDDT) program in the Center for Devices and Radiological Health of the U.S. Food and Drug Administration (FDA). If the FDA qualifies the dataset for its submitted context of use, model developers can use it in a regulatory submission within the qualified context of use without additional documentation. Our dataset aims at reducing the regulatory burden placed on developers of models that estimate the density of TILs and will allow head-to-head comparison of multiple computational models on the same data. In this paper, we discuss the MDDT preparation and submission process, including the feedback we received from our initial interactions with the FDA and propose how a qualified MDDT validation dataset could be a mechanism for open, fair, and consistent measures of computational model performance. Our experiences will help the community understand what the FDA considers relevant and appropriate (from the perspective of the submitter), at the early stages of the MDDT submission process, for validating stromal TIL density estimation models and other potential computational models. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Intrahepatic Cholangiolitis in Cystic Fibrosis (ICCF): An Under-Appreciated Cause of Persistent Cholestasis in Infancy.

Liver histology in infants with cystic fibrosis (CF) and persistent cholestasis is seldom reported in detail. We extend previous observation of a distinctive intrahepatic cholangiopathy (ICCF) to 3 additional infants homozygous for CFTR pathological variants and a fourth infant with a heterozygous CFTR variant, summarizing our experience in 10 infants with CFTR variants and persistent cholestasis. Cholangiograms demonstrate abnormal extrahepatic ducts in 2 infants with CF, 1 with uniform dilatation interpreted as a choledochal cyst and the other with narrow patent ducts. Liver histology in 3 CF homozygotes had prominent ductular reaction with a focally destructive cholangiolitis (inflammation of small bile ducts). The CFTR heterozygote had generalized portal edema with ductular reaction and paucity but no cholangitis. Cholestasis slowly subsided in all infants. ICCF is characterized by severe ductular reaction, prominent cholangiocyte injury, and multifocal necrotizing cholangiolitis. Local aggregates of portal ceroid might suggest previous bile leakage from damaged ducts. ICCF in liver biopsies from infants with cystic fibrosis and persistent cholestasis is unrelated to the specific CFTR genotype. Liver biopsy findings and intraoperative cholangiogram help rule out biliary atresia. ICCF is an early manifestation of CF, a likely prototype for pathogenesis of cystic fibrosis liver disease later in life.

Cortical and subcortical microstructure integrity changes after repetitive transcranial magnetic stimulation therapy in cocaine use disorder and relates to clinical outcomes.

Cocaine use disorder (CUD) is a worldwide public health condition that is suggested to induce pathological changes in macrostructure and microstructure. Repetitive transcranial magnetic stimulation (rTMS) has gained attention as a potential treatment for CUD symptoms. Here, we sought to elucidate whether rTMS induces changes in white matter (WM) microstructure in frontostriatal circuits after 2 weeks of therapy in patients with CUD and to test whether baseline WM microstructure of the same circuits affects clinical improvement. This study consisted of a 2-week, parallel-group, double-blind, randomized controlled clinical trial (acute phase) (sham [n = 23] and active [n = 27]), in which patients received two daily sessions of rTMS on the left dorsolateral prefrontal cortex (lDLPFC) as an add-on treatment. T1-weighted and high angular resolution diffusion-weighted imaging (DWI-HARDI) at baseline and 2 weeks after served to evaluate WM microstructure. After active rTMS, results showed a significant increase in neurite density compared with sham rTMS in WM tracts connecting lDLPFC with left and right ventromedial prefrontal cortex (vmPFC). Similarly, rTMS showed a reduction in orientation dispersion in WM tracts connecting lDLPFC with the left caudate nucleus, left thalamus, and left vmPFC. Results also showed a greater reduction in craving Visual Analogue Scale (VAS) after rTMS when baseline intra-cellular volume fraction (ICVF) was low in WM tracts connecting left caudate nucleus with substantia nigra and left pallidum, as well as left thalamus with substantia nigra and left pallidum. Our results evidence rTMS-induced WM microstructural changes in fronto-striato-thalamic circuits and support its efficacy as a therapeutic tool in treating CUD. Further, individual clinical improvement may rely on the patient's individual structural connectivity integrity.

Evolutionary dynamics at the tumor edge reveal metabolic imaging biomarkers.

Human cancers are biologically and morphologically heterogeneous. A variety of clonal populations emerge within these neoplasms and their interaction leads to complex spatiotemporal dynamics during tumor growth. We studied the reshaping of metabolic activity in human cancers by means of continuous and discrete mathematical models and matched the results to positron emission tomography (PET) imaging data. Our models revealed that the location of increasingly active proliferative cellular spots progressively drifted from the center of the tumor to the periphery, as a result of the competition between gradually more aggressive phenotypes. This computational finding led to the development of a metric, normalized distance from 18F-fluorodeoxyglucose (18F-FDG) hotspot to centroid (NHOC), based on the separation from the location of the activity (proliferation) hotspot to the tumor centroid. The NHOC metric can be computed for patients using 18F-FDG PET-computed tomography (PET/CT) images where the voxel of maximum uptake (standardized uptake value [SUV]max) is taken as the activity hotspot. Two datasets of 18F-FDG PET/CT images were collected, one from 61 breast cancer patients and another from 161 non-small-cell lung cancer patients. In both cohorts, survival analyses were carried out for the NHOC and for other classical PET/CT-based biomarkers, finding that the former had a high prognostic value, outperforming the latter. In summary, our work offers additional insights into the evolutionary mechanisms behind tumor progression, provides a different PET/CT-based biomarker, and reveals that an activity hotspot closer to the tumor periphery is associated to a worst patient outcome.

Unveiling the ChatGPT phenomenon: Evaluating the consistency and accuracy of endodontic question answers.

AIM: Chatbot Generative Pre-trained Transformer (ChatGPT) is a generative artificial intelligence (AI) software based on large language models (LLMs), designed to simulate human conversations and generate novel content based on the training data it has been exposed to. The aim of this study was to evaluate the consistency and accuracy of ChatGPT-generated answers to clinical questions in endodontics, compared to answers provided by human experts. METHODOLOGY: Ninety-one dichotomous (yes/no) questions were designed and categorized into three levels of difficulty. Twenty questions were randomly selected from each difficulty level. Sixty answers were generated by ChatGPT for each question. Two endodontic experts independently answered the 60 questions. Statistical analysis was performed using the SPSS program to calculate the consistency and accuracy of the answers generated by ChatGPT compared to the experts. Confidence intervals (95%) and standard deviations were used to estimate variability. RESULTS: The answers generated by ChatGPT showed high consistency (85.44%). No significant differences in consistency were found based on question difficulty. In terms of answer accuracy, ChatGPT achieved an average accuracy of 57.33%. However, significant differences in accuracy were observed based on question difficulty, with lower accuracy for easier questions. CONCLUSIONS: Currently, ChatGPT is not capable of replacing dentists in clinical decision-making. As ChatGPT's performance improves through deep learning, it is expected to become more useful and effective in the field of endodontics. However, careful attention and ongoing evaluation are needed to ensure its accuracy, reliability and safety in endodontics.

Opioid Overdoses and Take-Home Naloxone Interventions: Ethnographic Evidence for Individual-Level Barriers to Treatment of Opioid Use Disorders in Rural Appalachia.

Introduction: Research indicates that take-home naloxone (THN) is saving lives across rural Appalachia, but whether it also results in treatment for opioid use disorders (OUDs) remains unclear. This study involves a detailed qualitative analysis of interviews with 16 individuals who had overdosed on opioids 61 times to understand why a THN intervention does not routinely lead to OUD treatment. Methods: This study builds upon a one-year (2018) qualitative study on community responses to opioid overdose fatalities in four adjacent rural counties in Western Pennsylvania. Using a semi-structured interview guide, 16 individuals who had experienced one or more overdoses were interviewed. Using NVivo, the transcribed audio-recorded interviews were coded, and a thematic analysis of the coded text was conducted. Findings: Findings reveal that of the 29 overdoses that included a THN intervention, only eight resulted in treatment. The analysis derives five individual-level barriers to treatment: (1) opioid dependence, (2) denial/readiness, (3) opioid withdrawal fears, (4) incarceration concerns, and (5) stigma and shame. These barriers impeded treatment, even though all the interviewees knew of treatment programs, how to access them, and in some cases had undergone treatment previously. Discussion and Conclusion: findings indicate that there is evidence that the five barriers make entering treatment after a THN intervention challenging and seemingly insurmountable at times. Recommendations based on the findings include increasing efforts to reduce stigma of OUDs in the community, including self-stigma resulting from misusing opioids, increasing informational efforts about Good Samaritan Laws, and increasing familiarity with medication-assisted treatments for OUDS.

(F)utility of preoperative pulmonary function testing in pectus excavatum to assess severity.

PURPOSE: The utility of pulmonary function testing (PFT) in pectus excavatum (PE) has been subject to debate. Although some evidence shows improvement from preoperative to postoperative values, the clinical significance is uncertain. A high failure-to-completion rate for operative PFT (48%) was identified in our large institutional cohort. With such a high non-completion rate, we questioned the overall utility of PFT in the preoperative assessment of PE and sought to evaluate if other measures of PE severity or cardiopulmonary function could explain this finding. METHODS: Demographics, clinical findings, and results from cardiac MRI, PFT (spirometry and plethysmography), and cardiopulmonary exercise tests (CPET) were reviewed in 270 patients with PE evaluated preoperatively between 2015 and 2018. Regression modeling was used to measure associations between PFT completion and cardiopulmonary function. RESULTS: There were no differences in demographics, symptoms, connective tissue disorders, or multiple indices of pectus severity and cardiac deformation in PFT completers versus non-completers. While regression analysis revealed higher RVEF, LVEF, and LVEF-Z scores, lower RV-ESV/BSA, LV-ESV/BSA, and LV-ESV/BSA-Z scores, and abnormal breathing reserve in PFT completers vs. non-completers, these findings were not consistent across continuous and binary analyses. CONCLUSIONS: We found that PFT completers were not significantly different from non-completers in most structural and functional measures of pectus deformity and cardiopulmonary function. Inability to complete PFT is not an indicator of pectus severity.

ChatGPT performance in prosthodontics: Assessment of accuracy and repeatability in answer generation.

STATEMENT OF PROBLEM: The artificial intelligence (AI) software program ChatGPT is based on large language models (LLMs) and is widely accessible. However, in prosthodontics, little is known about its performance in generating answers. PURPOSE: The purpose of this study was to determine the performance of ChatGPT in generating answers about removable dental prostheses (RDPs) and tooth-supported fixed dental prostheses (FDPs). MATERIAL AND METHODS: Thirty short questions were designed about RDPs and tooth-supported FDP, and 30 answers were generated for each of the questions using ChatGPT-4 in October 2023. The 900 generated answers were independently graded by experts using a 3-point Likert scale. The relative frequency and absolute percentage of answers were described. Accuracy was assessed using the Wald binomial method, while repeatability was evaluated using percentage agreement, Brennan and Prediger coefficient, Conger generalized Cohen kappa, Fleiss kappa, Gwet AC, and Krippendorff alpha methods. Confidence intervals were set at 95%. Statistical analysis was performed using the STATA software program. RESULTS: The performance of ChatGPT in generating answers related to RDP and tooth-supported FDP was limited. The answers showed a reliability of 25.6%, with a confidence range between 22.9% and 28.6%. The repeatability ranged from substantial to moderate. CONCLUSIONS: The results show that currently ChatGPT has limited ability to generate answers related to RDPs and tooth-supported FDPs. Therefore, ChatGPT cannot replace a dentist, and, if professionals were to use it, they should be aware of its limitations.

Uncovering a novel mechanism: Butyrate induces estrogen receptor alpha activation independent of estrogen stimulation in MCF-7 breast cancer cells.

Butyrate is a promising candidate for an antitumoral drug, as it promotes cancer cell apoptosis and reduces hormone receptor activity, while promoting differentiation and proliferation in normal cells. However, the effects of low-dose butyrate on breast cancer cell cultures are unclear. We explored the impact of sub-therapeutic doses of butyrate on estrogen receptor alpha (ERα) transcriptional activity in MCF-7 cells, using RT-qPCR, Western blot, wound-healing assays, and chromatin immunoprecipitation. Our results showed that sub-therapeutic doses of sodium butyrate (0.1 - 0.2 mM) increased the transcription of ESR1, TFF1, and CSTD genes, but did not affect ERα protein levels. Moreover, we observed an increase in cell migration in wound-healing assays. ChIP assays revealed that treatment with 0.1 mM of sodium butyrate resulted in estrogen-independent recruitment of ERα at the pS2 promoter and loss of NCoR. Appropriate therapeutic dosage of butyrate is essential to avoid potential adverse effects on patients' health, especially in the case of estrogen receptor-positive breast tumors. Sub-therapeutic doses of butyrate may induce undesirable cell processes, such as migration due to low-dose butyrate-mediated ERα activation. These findings shed light on the complex effects of butyrate in breast cancer and provide insights for research in the development of antitumoral drugs.

Simultaneous Optimization and Integration of Multiple Process Heat Cascade and Site Utility Selection for the Design of a New Generation of Sugarcane Biorefinery.

Biorefinery plays a crucial role in the decarbonization of the current economic model, but its high investments and costs make its products less competitive. Identifying the best technological route to maximize operational synergies is crucial for its viability. This study presents a new superstructure model based on mixed integer linear programming to identify an ideal biorefinery configuration. The proposed formulation considers the selection and process scale adjustment, utility selection, and heat integration by heat cascade integration from different processes. The formulation is tested by a study where the impact of new technologies on energy efficiency and the total annualized cost of a sugarcane biorefinery is evaluated. As a result, the energy efficiency of biorefinery increased from 50.25% to 74.5% with methanol production through bagasse gasification, mainly due to its high heat availability that can be transferred to the distillery, which made it possible to shift the bagasse flow from the cogeneration to gasification process. Additionally, the production of DME yields outcomes comparable to methanol production. However, CO2 hydrogenation negatively impacts profitability and energy efficiency due to the significant consumption and electricity cost. Nonetheless, it is advantageous for surface power density as it increases biofuel production without expanding the biomass area.

A Hybrid Cryptosystem Incorporating a New Algorithm for Improved Entropy.

Today, safeguarding sensitive content through encryption is crucial. This work presents a hybrid cryptosystem for images that employs both asymmetric and symmetric encryption. The asymmetric component involves applying the Diffie-Hellman protocol and the ElGamal cryptosystem to securely transmit two constants. These constants are necessary for the symmetrical aspect to generate dynamic permutations, substitution boxes, and round keys. Following an encryption process with fourteen rounds, the encrypted images are processed by an algorithm proposed to enhance entropy, a critical metric for assessing encryption quality. It increases the frequencies of the basic colors to achieve a histogram closely resembling a uniform distribution, but it increases the image size by approximately 8%. This improves the entropy values achieved by the hybrid cryptosystem, bringing them remarkably close to the ideal value of 8.0. In specific instances, the entropy values were elevated from 7.99926 to 8.0. The proposed method exhibits resilience against various attacks, including differential, linear, brute force, and algebraic attacks, as evaluated through the entropy, correlation, goodness of fit, Discrete Fourier Transform (DFT), Number of Pixels Change Rate (NPCR), Unified Average Changing Intensity (UACI), Avalanche Criteria (AC), contrast, energy, and homogeneity. Further, encrypted images are subjected to noise attacks ranging from 20% to 50% noise, including additive, multiplicative, occlusion noise, as well as the newly introduced χ2 noise. The noise damage is quantified using the proposed Similarity Parameter (SP), and a 3 × 3 median filter is employed to enhance the visual quality.

Terbinafine-Resistant Dermatophytes and the Presence of Trichophyton indotineae in North America.

Dermatophytes are common causes of skin, hair, and nail infections in humans. The most common species causing infections in humans are Trichophyton rubrum, Trichophyton mentagrophytes, and Trichophyton interdigitale. Outbreaks of recalcitrant dermatophytosis have been reported in parts of South Asia, including those caused by a hypervirulent and resistant species, Trichophyton indotineae. We evaluated the antifungal susceptibility profiles of dermatophytes received by our laboratory from institutions across North America between 2021 and 2022 and performed species identification for isolates deemed to demonstrate in vitro resistance. Susceptibility testing was performed by CLSI broth microdilution methods, and species identification was performed by DNA sequence analysis. During this 2-year period, 271 dermatophyte isolates were included, the majority of which demonstrated low MIC values for terbinafine (geometric mean [GM] and modal MIC, 0.031 µg/mL and 0.008 µg/mL, respectively) and the azoles itraconazole, posaconazole, and voriconazole (0.035 to 0.049 µg/mL and ≤0.03 µg/mL). However, 18.6% of the isolates tested were resistant to terbinafine (MIC ≥ 0.5 µg/mL), including 21 T. rubrum and 21 T. indotineae isolates. These isolates were received from several different states in the United States and two provinces in Canada. In contrast, resistance to itraconazole was relatively rare. We also searched our laboratory database for earlier isolates that were resistant to terbinafine and identified 3 additional T. indotineae isolates, the earliest of which was from 2017. These results demonstrate that terbinafine resistance in dermatophytes was relatively common over this 2-year period and that T. indotineae is present in multiple areas in North America. Continued surveillance is warranted.