Shared decision making with breast cancer patients - does it work? Results of the cluster-randomized, multicenter DBCG RT SDM trial.

BACKGROUND AND PURPOSE: Shared decision making (SDM) is a patient engaging process advocated especially for preference-sensitive decisions, such as adjuvant treatment after breast cancer. An increasing call for patient engagement in decision making highlights the need for a systematic SDM approach. The objective of this trial was to investigate whether the Decision Helper (DH), an in-consultation patient decision aid, increases patient engagement in decisions regarding adjuvant whole breast irradiation. MATERIAL AND METHODS: Oncologists at four radiotherapy units were randomized to practice SDM using the DH versus usual practice. Patient candidates for adjuvant whole breast irradiation after breast conserving surgery for node-negative breast cancer were eligible. The primary endpoint was patient-reported engagement in the decision process assessed with the Shared Decision Making Questionnaire (SDM-Q-9) (range 0-100, 4 points difference considered clinical relevant). Other endpoints included oncologist-reported patient engagement, decisional conflict, fear of cancer recurrence, and decision regret after 6 months. RESULTS: Of the 674 included patients, 635 (94.2%) completed the SDM-Q-9. Patients in the intervention group reported higher level of engagement (median 80; IQR 68.9 to 94.4) than the control group (71.1; IQR 55.6 to 82.2; p < 0.0001). Oncologist-reported patient engagement was higher in the invention group (93.3; IQR 82.2 to 100) compared to control group (73.3; IQR 60.0 to 84.4) (p < 0.0001). CONCLUSION: Patient engagement in medical decision making was significantly improved with the use of an in-consultation patient decision aid compared to standard. The DH on adjuvant whole breast irradiation is now recommended as standard of care in the Danish guideline.

Patient readiness for shared decision making about treatment: Conceptualisation and development of the ReadySDM.

INTRODUCTION: Shared decision making (SDM) requires an active role of both clinicians and patients. We aimed to conceptualise patient readiness for SDM about treatment, and to develop a patient questionnaire to assess readiness. METHODS: We used the results of a scoping review and a qualitative study to inform the patient readiness construct. We conducted five additional rounds of data collection to finalise the construct definition and develop the Patient Readiness for SDM Questionnaire (ReadySDM ) in an oncological setting: (1) longitudinal interviews with patients with cancer during and after a treatment decision-making process; (2) a pilot study among experts, clinicians, and patients for feedback on the concept and items; (3) a field test among (former) patients with cancer to test item format and content validity, and to reduce the number of items; (4) cognitive interviews with people with low literacy to test the comprehensibility of the questionnaire; and (5) a field test among (former) patients who faced a cancer treatment decision in the last year, to test the content validity of the final version of the questionnaire. RESULTS: A total of 251 people participated in the various rounds of data collection. We identified eight elements of patient readiness for SDM about treatment: (1) understanding of and attitude towards SDM; (2) information skills; (3) skills in communicating and claiming space; (4) self-awareness; (5) consideration skills; (6) self-efficacy; (7) emotional distress; and (8) experienced time. We developed the 20-item ReadySDM to retrospectively measure these elements in an oncological setting. CONCLUSION: We conducted a thorough procedure to conceptualise patient readiness and to develop the ReadySDM . The questionnaire aims to provide novel insights into ways to enhance SDM in daily practice. PATIENT OR PUBLIC CONTRIBUTION: Multiple people with lived experience were involved in various phases of the study. They were asked for input on the study design, the conceptualisation of readiness, and the development of the questionnaire.

New 4-(N-cinnamoylbutyl)aminoacridines as potential multi-stage antiplasmodial leads.

A novel family of 4-aminoacridine derivatives was obtained by linking this heteroaromatic core to different trans-cinnamic acids. The 4-(N-cinnamoylbutyl)aminoacridines obtained exhibited in vitro activity in the low- or sub-micromolar range against (i) hepatic stages of Plasmodium berghei, (ii) erythrocytic forms of Plasmodium falciparum, and (iii) early and mature gametocytes of Plasmodium falciparum. The most active compound, having a meta-fluorocinnamoyl group linked to the acridine core, was 20- and 120-fold more potent, respectively, against the hepatic and gametocyte stages of Plasmodium infection than the reference drug, primaquine. Moreover, no cytotoxicity towards mammalian and red blood cells at the concentrations tested was observed for any of the compounds under investigation. These novel conjugates represent promising leads for the development of new multi-target antiplasmodials.

Neural correlates of transitive inference: An SDM meta-analysis on 32 fMRI studies.

Transitive inference (TI) is a critical capacity involving the integration of relevant information into prior knowledge structure for drawing novel inferences on unobserved relationships. To date, the neural correlates of TI remain unclear due to the small sample size and heterogeneity of various experimental tasks from individual studies. Here, the meta-analysis on 32 fMRI studies was performed to detect brain activation patterns of TI and its three paradigms (spatial inference, hierarchical inference, and associative inference). We found the hippocampus, prefrontal cortex (PFC), putamen, posterior parietal cortex (PPC), retrosplenial cortex (RSC), supplementary motor area (SMA), precentral gyrus (PreCG), and median cingulate cortex (MCC) were engaged in TI. Specifically, the RSC was implicated in the associative inference, whereas PPC, SMA, PreCG, and MCC were implicated in the hierarchical inference. In addition, the hierarchical inference and associative inference both evoked activation in the hippocampus, medial PFC, and PCC. Although the meta-analysis on spatial inference did not generate a reliable result due to insufficient amount of investigations, the present work still offers a new insight for better understanding the neural basis underlying TI.

Evidence-based Shared-Decision-Making Assistant (SDM-assistant) for choosing antipsychotics: protocol of a cluster-randomized trial in hospitalized patients with schizophrenia.

BACKGROUND: Choosing an antipsychotic medication is an important medical decision in the treatment of schizophrenia. This decision requires risk-benefit assessments of antipsychotics, and thus, shared-decision making between physician and patients is strongly encouraged. Although the efficacy and side-effect profiles of antipsychotics are well-established, there is no clear framework for the communication of the evidence between physicians and patients. For this reason, we developed an evidence-based shared-decision making assistant (SDM-assistant) that presents high-quality evidence from network meta-analysis on the efficacy and side-effect profile of antipsychotics and can be used as a basis for shared-decision making between physicians and patients when selecting antipsychotic medications. METHODS: The planned matched-pair cluster-randomised trial will be conducted in acute psychiatric wards (n = 14 wards planned) and will include adult inpatients with schizophrenia or schizophrenia-like disorders (N = 252 participants planned). On the intervention wards, patients and their treating physicians will use the SDM-assistant, whenever a decision on choosing an antipsychotic is warranted. On the control wards, antipsychotics will be chosen according to treatment-as-usual. The primary outcome will be patients' perceived involvement in the decision-making during the inpatient stay as measured with the SDM-Q-9. We will also assess therapeutic alliance, symptom severity, side-effects, treatment satisfaction, adherence, quality of life, functioning and rehospitalizations as secondary outcomes. Outcomes could be analysed at discharge and at follow-up after three months from discharge. The analysis will be conducted per-protocol using mixed-effects linear regression models for continuous outcomes and logistic regression models using generalised estimating equations for dichotomous outcomes. Barriers and facilitators in the implementation of the intervention will also be examined using a qualitative content analysis. DISCUSSION: This is the first trial to examine a decision assistant specifically designed to facilitate shared-decision making for choosing antipsychotic medications, i.e., SDM-assistant, in acutely ill inpatients with schizophrenia. If the intervention can be successfully implemented, SDM-assistant could advance evidence-based medicine in schizophrenia by putting medical evidence on antipsychotics into the context of patient preferences and values. This could subsequently lead to a higher involvement of the patients in decision-making and better therapy decisions. TRIAL REGISTRATION: German Clinical Trials Register (ID: DRKS00027316 , registration date 26.01.2022).

Evaluation Method for Quality Risks of Safety in Prefabricated Building Construction Using SEM-SDM Approach.

The construction of prefabricated buildings is an effective and efficient approach to improving construction processes and productivity. However, there are practical problems in this approach, such as listing, safety risk levels, and quality control. This study aims to develop a systematic approach for determining the key factors affecting prefabricated building projects' quality and safety risk and assessing this risk. Based on the literature review, a structured questionnaire was distributed to 408 China-based construction organizations. Considering the factors of safety risk evaluation systems for construction, the safety risk model of prefabricated buildings is established and combined with structural equation modeling (SEM) and a system dynamic model (SDM). A detailed case study was conducted to verify the empirical findings. The results show that pre-construction, during-construction, and after-construction significantly influence the quality risk (from high to low). The final comprehensive score is 92.71, indicating that the construction safety of the residential building is generally controllable and the quality is guaranteed. Furthermore, the investment risk of such projects can be assessed using SEM and SDM. This study contributes to the literature by considering quality-risk-influencing factors in this field. Furthermore, the findings provide an understanding of implementation and quality risk control for prefabricated building projects and provide valuable information to departments in charge of improving the safety risk performance of such projects.

Tunable gold nanorod/NAO conjugates for selective drug delivery in mitochondria-targeted cancer therapy.

Nonyl acridine orange (NAO) is a lipophilic and positively charged molecule widely used as a mitochondrial fluorescent probe. NAO is cytotoxic at micromolar concentration and might be potentially used as a mitochondria-targeted drug for cancer therapy. However, the use of NAO under in vivo conditions would be compromised by the unspecific interactions with off-target cells and negatively charged proteins present in the bloodstream. To tackle this limitation, we have synthesized NAO analogues carrying an imidazole group for their specific binding to nitrilotriacetic (NTA) functionalized gold nanorods (AuNRs). We demonstrate that AuNRs provide 104 binding sites and a controlled delivery under acidic conditions. Upon incubation with mouse embryonic fibroblasts, the endosomal acidic environment releases the NAO analogues from AuNRs, as visualized through the staining of the mitochondrial network. The addition of the monoclonal antibody Cetuximab to the conjugates enhanced their uptake within lung cancer cells and the conjugates were cytotoxic at subnanomolar concentrations (c50 ≈ 0.06 nM). Moreover, the specific interactions of Cetuximab with the epidermal growth factor receptor (EGFR) provided a specific targeting of EGFR-expressing lung cancer cells. After intravenous administration in patient-derived xenografts (PDX) mouse models, the conjugates reduced the progression of EGFR-positive tumors. Overall, the NAO-AuNRs provide a promising strategy to realize membrane mitochondria-targeted conjugates for lung cancer therapy.

The NAO Variability Prediction and Forecasting with Multiple Time Scales Driven by ENSO Using Machine Learning Approaches.

Machine learning methods have now become an optional technique in Earth science research, and such data-driven solutions have also made tremendous progress in weather forecasting and climate prediction in recent years. Since climate data are typically time series, the neural network layers, which can identify the intrinsic connections between the points of the sequence and features in two-dimensional data, perform particularly well for climate prediction. The North Atlantic Oscillation (NAO) is a prominent atmospherical mode in the northern hemisphere, with the frequency change characteristic of sea level pressure (SLP) in the North Atlantic sector. One of the reasons why NAO prediction is still challenging is that NAO is also proven to be influenced by other climate circulations, the most significant of which is the interaction between El Niño-Southern Oscillation (ENSO) and NAO. Therefore, sea surface temperature (SST) in the Pacific Ocean used to characterize ENSO is also one of the factors that contribute to the evolution of NAO and can be used as an input factor to predict the NAO. In this paper, the seasonal lag correlation between ENSO and NAO is explored and analyzed. The interaction has been considered in both short-term forecasting and midterm prediction of the NAO variability. The monthly NAO index (NAOI) fluctuation is predicted using the Niño indices based on the RF-Var model, and the accuracy achieves 68% when the lead time is about three months. In addition, integrating multiple physical variables directly related to the NAO and Pacific SST, the short-term NAO forecasting is conducted using a multi-channel neural network named AccNet with trajectory gated recursive unit (TrajGRU) layer. AccNet has the ability to identify the mechanism of the high-frequency variation in several days, and the NAO variability is indicated by SLP. The loss function of AccNet is set to anomaly correlation coefficient (ACC), which is the indicator that verifies spatial correlation in geoscience. Forecasting extreme events of NAO between 2010 and 2021, AccNet presents higher flexibility compared against other structures that can capture spatial-temporal features.

Ready for SDM- evaluation of an interprofessional training module in shared decision making - A cluster randomized trial.

OBJECTIVE: Ready for SDM was developed in Norway as a comprehensive modularized curriculum for health care providers (HCP). The current study evaluated the efficacy of one of the modules, a 2-hour interprofessional SDM training designed to enhance SDM competencies. METHODS: A cluster randomized controlled trial was conducted with eight District Psychiatric Centres randomized to wait-list control (CG) or intervention group (IG). Participants and trainers were not blinded to their allocation. The IG received a 2-hour didactic and interactive training, using video examples. The primary outcome was the agreement between the participants' and an expert assessment of patient involvement in a video recorded consultation. The SDM-knowledge score was a secondary outcome. RESULTS: Compared to the CG (n = 65), the IG (n = 69) judged involvement behavior in a communication example more accurately (mean difference of weighted T, adjusted for age and gender:=-0.098, p = 0.028) and demonstrated better knowledge (mean difference=-0.58; p = 0.014). A sensitivity analysis entering a random effect for cluster turned out not significant. CONCLUSION: The interprofessional group training can improve HCPs' SDM-competencies. PRACTICE IMPLICATIONS: Addressing interprofessional teams using SDM communication training could supplement existing SDM training approaches. More research is needed to evaluate the training module's effects as a component of large-scale implementation of SDM.

Comparison of the CollaboRATE and SDM-Q-9 questionnaires to appreciate the patient-reported level of shared decision-making.

OBJECTIVE: To compare CollaboRATE and SDM-Q-9 questionnaires when appreciating patient-perceived level of shared decision-making (SDM) in doctor-patient consultations. METHODS: Data were harvested from five separate studies on SDM, conducted in three university and one large community hospital in the Netherlands, using Dutch versions of both questionnaires. CollaboRATE and SDM-Q-9 scores were expressed as percentages. Correlation was assessed using Spearman's Rho coefficient. Bland&Altman analysis was used to assess the degree of agreement. Top scores were calculated to assess possible ceiling effects. RESULTS: The five studies included 442 patients. Median CollaboRATE scores (88.9%, IQR 81.5-100%) were significantly higher (p < 0.001) than SDM-Q-9 scores (80.0%, IQR 64.4-100%). Correlation was moderate (Rho=0.53, p < 0.001). A systematic, 12.5-point higher score was found across the range of scores when using CollaboRATE. Top scores for CollaboRATE and SDM-Q-9 were present in 37.5% and 17% of questionnaires, respectively. CONCLUSIONS: Overall, CollaboRATE and SDM-Q-9 questionnaires showed a high level of patient-perceived SDM. However, CollaboRATE only moderately correlated with SDM-Q-9 and had a stronger ceiling effect. PRACTICE IMPLICATIONS: When choosing a SDM-measurement tool, its benefits and limitations should be weighed. These metrics should be combined with objective scores of SDM, as these may differ from the patients' subjective interpretation.

A common neural substrate for number comparison, hand reaching and grasping: A SDM-PSI meta-analysis of neuroimaging studies.

The reliance of number processing on sensorimotor mechanisms involved in hand action has been extensively documented by behavioural studies. Nonetheless, where and how the computations of number and hand action interact in the brain has received limited attention. In this study we investigated the brain networks underlying symbolic number comparison and the hand action of reaching and grasping, capitalizing on functional imaging studies meta-analyzed with the seed-based d mapping with permutation of subject images meta-analytic method (SDM-PSI). The main objective was to test whether and to what extent symbolic number processing recruits the same sensorimotor network involved in the hand action of reaching and grasping. We included 42 studies (756 participants) adopting symbolic number comparison tasks and 58 studies (867 participants) investigating hand reaching and hand grasping. The conjunction analysis of brain networks common to number processing, reaching, and grasping revealed spatial convergence over frontoparietal areas. Specifically, four clusters were identified, in and around the left and right intraparietal sulci, in the left precentral gyrus, and in the supplementary motor area. The degree of overlap was extensive, since the reach/grasp network mostly included the number areas. A qualitative analysis of functional characterization capitalizing on the Neurosynth database depicted a strong multifunctionality of the regions of overlap between numbers and hand action: these brain areas were also associated to a variety of functions within the domains of memory and imagery, visuospatial attention, and language. Overall, these results characterize the neuroanatomical substrate of the interaction between reaching, grasping, and symbolic number comparison.

A metabolically stable PET tracer for imaging synaptic vesicle protein 2A: synthesis and preclinical characterization of [18F]SDM-16.

PURPOSE: To quantify the synaptic vesicle glycoprotein 2A (SV2A) changes in the whole central nervous system (CNS) under pathophysiological conditions, a high affinity SV2A PET radiotracer with improved in vivo stability is desirable to minimize the potential confounding effect of radiometabolites. The aim of this study was to develop such a PET tracer based on the molecular scaffold of UCB-A, and evaluate its pharmacokinetics, in vivo stability, specific binding, and nonspecific binding signals in nonhuman primate brains, in comparison with [11C]UCB-A, [11C]UCB-J, and [18F]SynVesT-1. METHODS: The racemic SDM-16 (4-(3,5-difluorophenyl)-1-((2-methyl-1H-imidazol-1-yl)methyl)pyrrolidin-2-one) and its two enantiomers were synthesized and assayed for in vitro binding affinities to human SV2A. We synthesized the enantiopure [18F]SDM-16 using the corresponding enantiopure arylstannane precursor. Nonhuman primate brain PET scans were performed on FOCUS 220 scanners. Arterial blood was drawn for the measurement of plasma free fraction (fP), radiometabolite analysis, and construction of the plasma input function. Regional time-activity curves (TACs) were fitted with the one-tissue compartment (1TC) model to obtain the volume of distribution (VT). Nondisplaceable binding potential (BPND) was calculated using either the nondisplaceable volume of distribution (VND) or the centrum semiovale (CS) as the reference region. RESULTS: SDM-16 was synthesized in 3 steps with 44% overall yield and has the highest affinity (Ki = 0.9 nM) to human SV2A among all reported SV2A ligands. [18F]SDM-16 was prepared in about 20% decay-corrected radiochemical yield within 90 min, with greater than 99% radiochemical and enantiomeric purity. This radiotracer displayed high specific binding in monkey brains and was metabolically more stable than the other SV2A PET tracers. The fP of [18F]SDM-16 was 69%, which was higher than those of [11C]UCB-J (46%), [18F]SynVesT-1 (43%), [18F]SynVesT-2 (41%), and [18F]UCB-H (43%). The TACs were well described with the 1TC. The averaged test-retest variability (TRV) was 7 ± 3%, and averaged absolute TRV (aTRV) was 14 ± 7% for the analyzed brain regions. CONCLUSION: We have successfully synthesized a novel SV2A PET tracer [18F]SDM-16, which has the highest SV2A binding affinity and metabolical stability among published SV2A PET tracers. The [18F]SDM-16 brain PET images showed superb contrast between gray matter and white matter. Moreover, [18F]SDM-16 showed high specific and reversible binding in the NHP brains, allowing for the reliable and sensitive quantification of SV2A, and has potential applications in the visualization and quantification of SV2A beyond the brain.

Using the Social Robot NAO for Emotional Support to Children at a Pediatric Emergency Department: Randomized Clinical Trial.

BACKGROUND: Social robots (SRs) have been used for improving anxiety in children in stressful clinical situations, such as during painful procedures. However, no studies have yet been performed to assess their effect in children while waiting for emergency room consultations. OBJECTIVE: This study aims to assess the impact of SRs on managing stress in children waiting for an emergency room procedure through the assessment of salivary cortisol levels. METHODS: This was an open randomized clinical trial in children attending a pediatric emergency department. Children accessing the emergency room were randomized to 1 of 3 groups: (1) playing with a NAO SR, (2) playing with a study nurse, or (3) waiting with parents. The salivary cortisol levels of all children were measured through a swab. Salivary cortisol levels before and after the intervention were compared in the 3 groups. We calculated the effect size of our interventions through the Cohen d-based effect size correlation (r). RESULTS: A total of 109 children aged 3-10 years were enrolled in the study, and 94 (86.2%) had complete data for the analyses. Salivary cortisol levels significantly decreased more in the group exposed to robot interaction than in the other two groups (r=0.75). Cortisol levels decreased more in girls (r=0.92) than in boys (r=0.57). CONCLUSIONS: SRs are efficacious in decreasing stress in children accessing the emergency room and may be considered a tool for improving emotional perceptions of children and their families in such a critical setting. TRIAL REGISTRATION: ClinicalTrials.gov NCT04627909; https://clinicaltrials.gov/ct2/show/study/NCT04627909.

The Multifocal Approach to Sharing in Shared Decision Making: A Critical Appraisal of the MAPPIN'SDM.

OBJECTIVE: Shared decision making integrates health care provider expertise with patient values and preferences. The MAPPIN'SDM is a recently developed measurement instrument that incorporates physician, patient, and observer perspectives during medical consultations. This review sought to critically appraise the development, sensibility, reliability, and validity of the MAPPIN'SDM and to determine in which settings it has been used. METHODS: This critical appraisal was performed through a targeted review of the literature. Articles outlining the development or measurement property assessment of the MAPPIN'SDM or that used the instrument for predictor or outcome purposes were identified. RESULTS: Thirteen studies were included. The MAPPIN'SDM was developed by both adapting and building on previous shared decision making measurement instruments, as well as through creation of novel items. Content validity, face validity, and item quality of the MAPPIN'SDM are adequate. Internal consistency ranged from 0.91 to 0.94 and agreement statistics from 0.41 to 0.92. The MAPPIN'SDM has been evaluated in several populations and settings, ranging from chronic disease to acute oncological settings. Limitations include high reading levels required for self-administered patient questionnaires and the small number of studies that have employed the instrument to date. CONCLUSION: The MAPPIN'SDM generally shows adequate development, sensibility, reliability, and validity in preliminary testing and holds promise for shared decision making research integrating multiple perspectives. Further research is needed to develop its use in other patient populations and to assess patient understanding of complex item wording.

Methodology for preparing a cosmetic sample for the development of Microorganism Detection System (SDM) software and artificial intelligence learning to recognize specific microbial species.

INTRODUCTION AND OBJECTIVE: The article presents the methodology of preparing a cosmetic sample for analysi, and the creation of a dataset for teaching artificial intelligence to recognize specific species of microorganisms in cosmetic samples in terms of compliance with the ISO standard document, to develop of the Microorganism Detection System (SDM). MATERIAL AND METHODS: Methodology of preparation a cosmetic sample for testing covers the steps from taking a cosmetic sample to obtaining separated living microorganisms through staining to photos, which in the final stage are used for analysis of the purity of cosmetics by SDM, as well as for learning and testing of the deep convolutional neural network (CNN) for detecting and classifying cells of specific species of bacteria, fungi and yeast in cosmetics, according to the document of standard PN-EN ISO 17516-2014:11. RESULTS: A new techique was devised for preparing a cosmetic sample for the development of Microorganism Detection System (SDM) software, and artificial intelligence learning to recognize specific microbial species. Based on metod demonstrated, the Intelligent algorithms of SDM proved to be effective in counting and recognizing specific microorganisms (average accuracy for Candida albicans - 97%, Escherichia coli - 76%, Pseudomonas aeruginosa - 70%, Staphylococcus aureus - 85%), which are the most important species for the assessment of the purity of cosmetics. In addition, the reproducibility of the developed method was verified, and the results obtained were comparable to the breeding methods currently used, based on specific standards. CONCLUSIONS: The experiments confirmed the high sensitivity and specificity of the SDM method, its repeatability and, above all, the comparability of the results with clasic methods of European standards.

The Microorganism Detection System (SDM) for microbiological control of cosmetic products.

The Microorganism Detection System (SDM) is a new solution using artificial intelligence, unique on the international scale, to correctly identify and count microorganisms, with particular emphasis on specificlisted microorganisms (Document of Standard PN-EN ISO 17516-2014:11) - Candida albicans, Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus. SDM enables the use of algorithms for microscopic image interpretation in the microbiological assessment of the cosmetics in accordance with the standard, providing an answer to whether the tested product complies with the standard. Apart from the software part of SDM, an integral part of the system is an innovative methodology for preparing a cosmetic sample for testing. The experiments confirm the high sensitivity and specificity of the SDM method, its repeatability and, above all, the comparability of the results with the methods of European standards.

The Effect of Conjugation with Octaarginine, a Cell-Penetrating Peptide on Antifungal Activity of Imidazoacridinone Derivative.

Acridine cell-penetrating peptide conjugates are an extremely important family of compounds in antitumor chemotherapy. These conjugates are not so widely analysed in antimicrobial therapy, although bioactive peptides could be used as nanocarriers to smuggle antimicrobial compounds. An octaarginine conjugate of an imidazoacridinone derivative (Compound 1-R8) synthetized by us exhibited high antifungal activity against reference and fluconazole-resistant clinical strains (MICs ≤ 4 µg mL-1). Our results clearly demonstrate the qualitative difference in accumulation of the mother compound and Compound 1-R8 conjugate into fungal cells. Only the latter was transported and accumulated effectively. Microscopic and flow cytometry analysis provide some evidence that the killing activity of Compound 1-R8 may be associated with a change in the permeability of the fungal cell membrane. The conjugate exhibited low cytotoxicity against human embryonic kidney (HEK-293) and human liver (HEPG2) cancer cell lines. Nevertheless, the selectivity index value of the conjugate for human pathogenic strains remained favourable and no hemolytic activity was observed. The inhibitory effect of the analysed compound on yeast topoisomerase II activity suggested its molecular target. In summary, conjugation with R8 effectively increased imidazoacridinone derivative ability to enter the fungal cell and achieve a concentration inside the cell that resulted in a high antifungal effect.

Electrochemical DNA Sensor Based on Acridine Yellow Adsorbed on Glassy Carbon Electrode.

Electrochemical DNA sensors offer unique opportunities for the sensitive detection of specific DNA interactions. In this work, a voltametric DNA sensor is proposed on the base of glassy carbon electrode modified with carbon black, adsorbed acridine yellow and DNA for highly sensitive determination of doxorubicin antitumor drug. The signal recorded by cyclic voltammetry was attributed to irreversible oxidation of the dye. Its value was altered by aggregation of the hydrophobic dye molecules on the carbon black particles. DNA molecules promote disaggregation of the dye and increased the signal. This effect was partially suppressed by doxorubicin compensate for the charge of DNA in the intercalation. Sensitivity of the signal toward DNA and doxorubicin was additionally increased by treatment of the layer with dimethylformamide. In optimal conditions, the linear range of doxorubicin concentrations determined was 0.1 pM-1.0 nM, and the detection limit was 0.07 pM. No influence of sulfonamide medicines and plasma electrolytes on the doxorubicin determination was shown. The DNA sensor was tested on two medications (doxorubicin-TEVA and doxorubicin-LANS) and showed recoveries of 102-105%. The DNA sensor developed can find applications in the determination of drug residues in blood and for the pharmacokinetics studies.