Multidimensional Screening Research Articles

Psychometric Properties of the German Version of the Benzodiazepine Dependence Self-Report Questionnaire

AbstractTo facilitate measurement and screening of benzodiazepine/Z-drug dependence, the Dutch “Benzodiazepine Dependence Self-Report Questionnaire” was translated into German (Bendep-SRQ-GV) and psychometrically evaluated. A cross-sectional online study with 343 benzodiazepine/Z-drug users was conducted. Structural validity and reliability were assessed using confirmatory factor analysis, while convergent validity was evaluated through correlation and receiver operating characteristic analyses with the “Severity of Dependence Scale” (SDS). Furthermore, the use of simple sum subscale and total scale scores was reviewed. A model with four first-order factors and one second-order factor fitted the data best. The questionnaire showed good to excellent reliability. The scores correlated satisfactorily with the model-based factor scores and the SDS, indicating good convergent validity and supporting the use of simple sum scores. The study provided strong evidence for the validity and reliability of the Bendep-SRQ-GV as a measure of benzodiazepine/Z-drug dependence, which represents a significant step towards developing a multidimensional screening tool.

The CAREPAL-8: a short screening tool for multidimensional family caregiver burden in palliative care

BackgroundFamily caregivers of terminally ill and dying people do not only experience varying levels but also different dimensions of caregiver-related strain and burden. The aim of the study was to develop a short multidimensional screening tool for the detection of burden in family caregivers in palliative care.MethodsFamily caregivers of cancer patients newly admitted to specialist inpatient palliative care (N = 232) completed questionnaires on psychological burden, quality of life, social support and need fulfillment. A latent class mixture model was used to identify discrete classes of family caregivers related to their multidimensional caregiver burden. Multinomial logistic regression analyses were performed to identify the most predictive items from a set of established questionnaires.ResultsFour latent classes of family caregivers were identified: Currently stable caregivers (37%), Caregivers with unmet needs (20%), Psychologically burdened caregivers (30%), and High-risk caregivers (13%). Each of these classes describes a different risk profile of multidimensional family caregiver burden, although family caregivers exhibit high levels of distress across all classes. From a set of 48 items, we identified eight items that predicted the class membership best. These items represent the items of the novel multidimensional screening tool: The 8-item Screening Tool for Family Caregiver Burden in Palliative Care (CAREPAL-8). Except for social support, the items maintained fidelity to the conceptualization of multidimensional caregiver burden used in this study. A preliminary classification system was developed, which has yet to be validated.ConclusionsThis study represents the first step in the establishment of a practical, self-administered screening tool that might help healthcare providers to tailor caregiver care according to their burden in daily practice. Brevity of the 8-item tool might facilitate its use in routine clinical care.

A general solution to the quasi linear screening problem

We provide an algorithm for solving multidimensional screening problems which are intractable analytically. The algorithm is a primal–dual algorithm which alternates between optimizing the primal problem of the surplus extracted by the principal and the dual problem of the optimal assignment to deliver to the agents for a given surplus. We illustrate the algorithm by solving (i) the generic monopolist price discrimination problem and (ii) an optimal tax problem covering income and savings taxes when citizens differ in multiple dimensions.

Correlation between the optimal screening for prediction of referral and outcome yellow flag tool and patient-reported legacy outcome measures in patients undergoing shoulder surgery

BackgroundThe Optimal Screening for Prediction of Referral and Outcome Yellow Flag (OSPRO-YF) Tool is a 10-item multidimensional screening tool utilized to evaluate pain-related psychological traits in individuals with musculoskeletal pain conditions. The validity of postoperatively collected OSPRO-YF is unclear. This study sought to assess validity of the OSPRO-YF by comparing it to PRO scores in both pre- and postoperative settings. HypothesisThe authors hypothesized that OSPRO-YF overall score would correlate with shoulder and global function PROs at pre- and postoperative timepoints. MethodsA review of 101 patients undergoing shoulder surgery by one sports medicine orthopedic surgeon at a large academic institution was conducted. 90 and 54 patients had complete pre- and postoperative PRO responses. OSPRO-YF, American Shoulder and Elbow Surgeons Evaluation Form (ASES), and Patient-Reported Outcomes Measurement Information System Computer Adaptive Test (PROMIS-CAT) were routinely administered before and after surgery at the senior author’s clinic visits. Concurrent validity of OSPRO-YF at either timepoint was assessed by comparing scores with PROs cross-sectionally using Pearson correlations and multiple comparison corrections. ResultsPreoperatively, higher OSPRO-YF total score was associated with greater concurrent PROMIS-CAT Pain Interference (r=0.43; p<0.01) and Depression (r=0.36; p=0.05) and lower ASES (r=-0.34; p<0.01). Higher postoperative OSPRO-YF was also associated with greater concurrent PROMIS-CAT Pain Interference (r=0.43; p<0.01) and Depression (r=0.36; p<0.01) and lower ASES (r=-0.34; p=0.01). ASES had strong correlation with SANE and Pain scores at both pre- and postoperative timepoints. SANE was not significantly associated with OSPRO-YF total score or number of YFs at either timepoints. ConclusionThe study findings support the clinical validity of the 10-item OSPRO-YF tool when administered before or after shoulder surgery. For patients exhibiting suboptimal recovery or those identified as high risk at initial screening, assessment of pain-related psychological distress postoperatively may be particularly beneficial in guiding rehabilitation.

Rapid discovery of natural skin-lightening ingredients based on an integrated screening strategy based on molecular docking and zebrafish model.

Natural herbs have been widely considered a reservoir for skin-lightening ingredients, but discovery of the effective ingredients from herbs remains a large challenge. This research aimed to rapidly identify compounds with skin-lightening activity in Chinese herbs. The structure information of herbal compounds was collected and selected from the open-source data. High throughput virtual screening (HTVS) and Extra precision (XP) docking modes were used to screen for compounds that could bind to the mushroom tyrosinase involved in melanin synthesis. Furthermore, molecular dynamics (MD) simulations were introduced to assess the binding stability of those compounds with the key target protein. The candidate compounds found by this kind of multidimensional molecular screening were finally tested for their ability to inhibit pigmentation and potential toxicity using an invivo zebrafish animal model. A Natural Compounds Database was established with 5616 natural compounds. Fourteen compounds with favorable binding capability were screened by the XP docking mode with mushroom tyrosinase and five compounds among them were found to have superior dynamic binding performance through MD simulations. Then the Zebrafish animal experiments revealed that two components, sennoside B (SB) and sennoside C (SC), could significantly inhibit melanogenesis rather than the other three compounds. Meanwhile, there were no obvious side effects observed in SB and SC about the morphology, heart rate, or body length of zebrafish. A strategy for rapid screening of compounds with whitening activity has been established, and two potent skin-lightening compounds, SB and SC, have been identified from a vast library of herbal compounds. This study revealed that SB and SC have potential for topical use in skin lightening for the first time. The findings of this study would provide an important theoretical basis for the application of these two compounds in the cosmetic field in the future.

Multidimensional combinatorial screening for high-level production of erythritol in Yarrowia lipolytica

Yarrowia lipolytica was successfully engineered to synthesize erythritol from crude glycerol, a cheap by-product of biodiesel production, but the yield remained low. Here, a biosensor-guided adaptive evolution screening platform was constructed to obtain mutant strains which could efficiently utilize crude glycerol to produce erythritol. Erythrose reductase D46A (M1) was identified as a key mutant through whole-genome sequencing of the strain G12, which exhibited higher catalytic activity (1.6-fold of the wild-type). M1 was further modified to obtain a combinatorial mutant with 4.1-fold enhancement of catalytic activity. Finally, the metabolic network was reconfigured to redirect carbon fluxes toward erythritol synthesis. The erythritol titer of the engineered strain G31 reached 220.5 g/L with a productivity of 1.8 g/L/h in a 5-L bioreactor. The study provides valuable guidance for biosensor-based ultra-high-throughput screening strategies in Y. lipolytica, as well as presenting a new paradigm for the sustainable valorization of crude glycerol.

Adaptation of the comprehensive rheumatologic assessment of frailty (CRAF) as a multidimensional frailty screening tool in patients with rheumatoid arthritis in Vietnam

BackgroundIn recent times, there has been acknowledgment of the prevalence of frailty and pre-frailty among individuals with rheumatoid arthritis (RA). Comprehensive Rheumatologic Assessment of Frailty (CRAF) stands out as a dependable tool grounded in synthesis and clinical judgment. Despite this, a validated Vietnamese rendition of the CRAF is currently unavailable. This study seeks to assess the reliability and validity of the CRAF in a patient with RA in Vietnam.MethodsA cross-sectional investigation was carried out with 402 patients diagnosed with rheumatoid arthritis, encompassing both inpatients and outpatients at the Centre for Rheumatology at Bach Mai Hospital in Hanoi, Vietnam. CRAF was employed to gauge the extent of frailty. To establish convergent validity, the scores from the CRAF were correlated with those from the Fried phenotype. Discriminant validity was ascertained through the utilization of receiver operating characteristic (ROC) curve analysis. Additionally, a multivariate logistic regression model was applied to evaluate the individual determinants’ relative impact on the CRAF.ResultsIn testing for convergent validity, a significant correlation was found between CRAF and Fried phenotype (p < 0.001). The discriminatory power of CRAF was higher than those of the Fried phenotype (difference between areas under the ROC curves = 0.947 (95% CI: 0.927–0.967). Variables associated with frailty at the multivariate analysis were comorbitidy, medication intake, BMI, DAS28-CRP, and age (all at p < 0.01).ConclusionCRAF exhibited strong validity and accurate discrimination. Incorporating frailty assessment into regular rheumatological practices could signify a significant advancement in the care of rheumatoid arthritis.

Droplet array with microfluidic concentration gradient (DA-MCG) for 2-dimensional reaction condition screening

Droplet microfluidic technology can use each microdroplet as a microreactor, which has the advantages of low reagent dosage, less cross contamination, and fast reaction time. Combining concentration gradient generation with droplet formation and capture to form a two-dimensional reaction condition screening platform (including reactant concentration and reaction time) is expected to broaden the application range of microfluidic screening. In this work, a microfluidic chip that can dynamically generate and capture microdroplets and form static microdroplet array was designed and fabricated. An optimized Christmas tree structure by adjusting the horizontal channel length ratio was used to generate a chemical concentration gradient while obtaining a uniform outlet flow rate, forming a droplet array with different concentrations. The performance of droplet array with microfluidic concentration gradient (DA-MCG) was verified using sodium fluorescein as a model reagent. The chromogenic reaction of NaOH and phenolphthalein, and luminol chemiluminescence reaction were used to verify the two-dimensional screening ability of DA-MCG. The results indicated that the DA-MCG has the potential to be applied in the field of multi-dimensional drug screening.

Dynamic microphysiological system chip platform for high-throughput, customizable, and multi-dimensional drug screening

Spheroids and organoids have attracted significant attention as innovative models for disease modeling and drug screening. By employing diverse types of spheroids or organoids, it is feasible to establish microphysiological systems that enhance the precision of disease modeling and offer more dependable and comprehensive drug screening. High-throughput microphysiological systems that support optional, parallel testing of multiple drugs have promising applications in personalized medical treatment and drug research. However, establishing such a system is highly challenging and requires a multidisciplinary approach. This study introduces a dynamic Microphysiological System Chip Platform (MSCP) with multiple functional microstructures that encompass the mentioned advantages. We developed a high-throughput lung cancer spheroids model and an intestine-liver-heart-lung cancer microphysiological system for conducting parallel testing on four anti-lung cancer drugs, demonstrating the feasibility of the MSCP. This microphysiological system combines microscale and macroscale biomimetics to enable a comprehensive assessment of drug efficacy and side effects. Moreover, the microphysiological system enables evaluation of the real pharmacological effect of drug molecules reaching the target lesion after absorption by normal organs through fluid-based physiological communication. The MSCP could serves as a valuable platform for microphysiological system research, making significant contributions to disease modeling, drug development, and personalized medical treatment.

Chemical screening by time-resolved X-ray scattering to discover allosteric probes

Drug discovery relies on efficient identification of small-molecule leads and their interactions with macromolecular targets. However, understanding how chemotypes impact mechanistically important conformational states often remains secondary among high-throughput discovery methods. Here, we present a conformational discovery pipeline integrating time-resolved, high-throughput small-angle X-ray scattering (TR-HT-SAXS) and classic fragment screening applied to allosteric states of the mitochondrial import oxidoreductase apoptosis-inducing factor (AIF). By monitoring oxidized and X-ray-reduced AIF states, TR-HT-SAXS leverages structure and kinetics to generate a multidimensional screening dataset that identifies fragment chemotypes allosterically stimulating AIF dimerization. Fragment-induced dimerization rates, quantified with time-resolved SAXS similarity analysis (kVR), capture structure–activity relationships (SAR) across the top-ranked 4-aminoquinoline chemotype. Crystallized AIF–aminoquinoline complexes validate TR-SAXS-guided SAR, supporting this conformational chemotype for optimization. AIF–aminoquinoline structures and mutational analysis reveal active site F482 as an underappreciated allosteric stabilizer of AIF dimerization. This conformational discovery pipeline illustrates TR-HT-SAXS as an effective technology for targeting chemical leads to important macromolecular states.

Multidimensional screening of pancreatic cancer spheroids reveals vulnerabilities in mitotic and cell-matrix adhesion signaling that associate with metastatic progression and decreased patient survival

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy, with a median survival of less than 12 months and a 5-year survival of less than 10 %. Here, we have established an image-based screening pipeline for quantifying single PDAC spheroid dynamics in genetically and phenotypically diverse PDAC cell models. Wild-type KRas PDAC cells formed tight/compact spheroids – compaction of these structures was completely blocked by cytoplasmic dynein and focal adhesion kinase (FAK) inhibitors. In contrast, PDAC cells containing mutant KRas formed loosely aggregated spheroids that grew significantly slower following inhibition of polo-like kinase 1 (PLK1) or focal adhesion kinase (FAK). Independent of genetic background, multicellular PDAC-mesenchymal stromal cell (MSC) spheroids self-organized into structures with an MSC-dominant core. The inclusion of MSCs into wild-type KRas PDAC spheroids modestly affected their compaction; however, MSCs significantly increased the compaction and growth of mutant KRas PDAC spheroids. Notably, exogenous collagen 1 potentiated PANC1 spheroid compaction while ITGA1 knockdown in PANC1 cells blocked MSC-induced PANC1 spheroid compaction. In agreement with a role for collagen-based integrin adhesion complexes in stromal cell-induced PDAC phenotypes, we also discovered that MSC-induced PANC1 spheroid growth was completely blocked by the ITGB1 immunoneutralizing antibody mAb13. Finally, multiplexed single-cell immunohistochemical analysis of a 25 patient PDAC tissue microarray revealed a relationship between decreased variance in Spearman r correlation for ITGA1 and PLK1 expression within the tumor cell compartment of PDAC in patients with advanced disease stage, and elevated expression of both ITGA1 and PLK1 in PDAC was found to be associated with decreased patient survival. Taken together, this work uncovers new therapeutic vulnerabilities in PDAC that are relevant to the progression of this stromal cell-rich malignancy and which may reveal strategies for improving patient outcomes.

Multidimensional Criteria for Virtual Screening of PqsR Inhibitors Based on Pharmacophore, Docking, and Molecular Dynamics.

Pseudomonas aeruginosa is a clinically challenging pathogen due to its high resistance to antibiotics. Quorum sensing inhibitors (QSIs) have been proposed as a promising strategy to overcome this resistance by interfering with the bacterial communication system. Among the potential targets of QSIs, PqsR is a key regulator of quorum sensing in Pseudomonas aeruginosa. However, the current research on PqsR inhibitors is limited by the lack of diversity in the chemical structures and the screening methods. Therefore, this study aims to develop a multidimensional screening model for PqsR inhibitors based on both ligand- and receptor-based approaches. First, a pharmacophore model was constructed from a training set of PqsR inhibitors to identify the essential features and spatial arrangement for the activity. Then, molecular docking and dynamics simulations were performed to explore the core interactions between PqsR inhibitors and their receptor. The results indicate that an effective PqsR inhibitor should possess two aromatic rings, one hydrogen bond acceptor, and two hydrophobic groups and should form strong interactions with the following four amino acid residues: TYR_258, ILE_236, LEU_208, and GLN_194. Moreover, the docking score and the binding free energy should be lower than -8 kcal/mol and -40 kcal/mol, respectively. Finally, the validity of the multidimensional screening model was confirmed by a test set of PqsR inhibitors, which showed a higher accuracy than the existing screening methods based on single characteristics. This multidimensional screening model would be a useful tool for the discovery and optimization of PqsR inhibitors in the future.

Development and validation of the screening tool for age-related hearing loss in the community based on the information platform

IntroductionCurrently, age-related hearing loss has become prevalent, awareness and screening rates remain dismally low. Duing to several barriers, as time, personnel training and equipment costs, available hearing screening tools do not adequately meet the need for large-scale hearing detection in community-dwelling older adults. Therefore, an accurate, convenient, and inexpensive hearing screening tool is needed to detect hearing loss, intervene early and reduce the negative consequences and burden of untreated hearing loss on individuals, families and society.ObjectivesThe study harnessed "medical big data" and "intelligent medical management" to develop a multi-dimensional screening tool of age-related hearing loss based on WeChat platform.MethodsThe assessment of risk factors was carried out by cross-sectional survey, logistic regression model and receiver operating characteristic (ROC) curve analysis. Combining risk factor assessment, Hearing handicap inventory for the elderly screening version and analog audiometry, the screening software was been developed by JavaScript language and been evaluated and verified.ResultsA total of 401 older adults were included in the cross-sectional study. Logistic regression model (univariate, multivariate) and reference to literature mention rate of risk factors, 18 variables (male, overweight/obesity, living alone, widowed/divorced, history of noise, family history of deafness, non-light diet, no exercising habit, smoking, drinking, headset wearer habit, hypertension, diabetes, hyperlipidemia, cardiovascular and cerebrovascular diseases, hyperuricemia, hypothyroidism, history of ototoxic drug use) were defined as risk factors. The area under the ROC curve (AUC) of the cumulative score of risk factors for early prediction of age-related hearing loss was 0.777 [95% CI (0.721, 0.833)]. The cumulative score threshold of risk factors was defined as 4, to classify the older adults into low-risk (< 4) and high-risk (≥ 4) hearing loss groups. The sensitivity, specificity, positive predictive value, and negative predictive value of the screen tool were 100%, 65.5%, 71.8%, and 100.0%, respectively. The Kappa index was 0.6.ConclusionsThe screening software enabled the closed loop management of real-time data transmission, early warning, management, whole process supervision of the hearing loss and improve self-health belief in it. The software has huge prospects for application as a screening approach for age-related hearing loss.

Pathways of depressive symptoms to self-harm and suicide warning signs during COVID-19 pandemic: The role of anxiety and related distress, dysfunction and somatization

BackgroundEarly in the COVID-19 pandemic, concern about widespread waves of depression and suicide emerged worldwide. Clarity on the relationship between mental health symptoms and warning signs of current self-harm or suicide thoughts and behaviors (ShSTB) in Mexican adults could be useful for designing effective public health policies and preventive strategies during health emergencies. ObjectiveThe present study uses a path model to explore the relationship between depressive symptoms, anxiety, and related distress, dysfunction, and somatization with ShSTB warning signs in Mexican adults during the COVID-19 pandemic. The study also describes the relative risks of these mental health variables for men and women, and for those who were seeking psychological care versus those who were not. MethodThe study was conducted with 18,449 Mexicans (M = 33 years, SD = 11.00, range = 18–59), including 12,188 women (66.10 %) and 2706 (14.67 %) who were seeking psychological care. A web-based application included two multidimensional screening scales to evaluate depression, anxiety and somatic symptoms and related distress/dysfunction, as well as past and current ShSTB. Based on the participants' sex, the entire sample was randomly divided into two sub-samples to compare and replicate the Confirmatory Factor Analysis (CFA) results, getting evidence of the multidimensionality of the scales. With the two sub-samples, we also tested the nested models from a structural equation model (SEM) to suggest a relationship between mental health and self-harm/suicide variables. FindingsOur findings suggest that 31 % of participants were at risk for depression, 42.30 % for anxiety, 38.30 % for Marked Distress, Dysfunction and Somatization (MDDS), 33.30 % for at least one ShSTB, and 4.20 % for Previous Self Harm Thoughts and Behaviors (PShTB) during the COVID-19 pandemic. A greater percentage of women and participants seeking psychological care showed high levels of mental health symptoms, PShTB, MDDS, and ShSTB. The path model suggested a direct influence of PShTB and MDDS on ShSTB. Depression symptoms lead to ShSTB in three possible ways: through PShTB, PShTB affecting MDDS, and generalized anxiety affecting MDDS. Discussion and outlookThe pandemic was accompanied by a high prevalence of depression-anxiety, marked distress, dysfunction and somatization and self-harm/suicide thoughts and behaviors. The findings of this study suggest evidence over the well-known association between depression and anxiety, and between depression, previous self-harm thoughts and behaviors, and self-harm/suicide. The evidence suggests to distinguish when participants were suffering from MDDS and anxious depression from those only suffering from depression. The methodological conditions of the study suggest a comprehensive model of ShSTB prevention. Findings also suggest the need to care for Mexicans with depressive symptoms and PShTB as well as those suffering from anxious depression with MDDS to prevent suicide, by implementing effective public health policies and preventive strategies to reduce the mental health gap during health emergencies. LimitationsThis research was a cross-sectional study, suggesting that future analyses should focus on the evaluation of its consistency with confirmed diagnoses of mental health disorders, self-harm/suicide risks, and the effect of remote psychological help to address these problems.

Precise redesign for improving enzyme robustness based on coevolutionary analysis and multidimensional virtual screening.

Natural enzymes are able to function effectively under optimal physiological conditions, but the intrinsic performance often fails to meet the demands of industrial production. Existing strategies are based mainly on the evaluation and subsequent combination of single-point mutations; however, this approach often suffers from a limited number of designable residues and from low accuracy. Here, we propose a strategy (Co-MdVS) based on coevolutionary analysis and multidimensional virtual screening for precise design to improve enzyme robustness, employing nattokinase as a model. Using this strategy, we efficiently screened 8 dual mutants with enhanced thermostability from a virtual mutation library containing 7980 mutants. After further iterative combination, the optimal mutant M6 exhibited a 31-fold increase in half-life at 55 °C, significantly enhanced acid resistance, and improved catalytic efficiency with different substrates. Molecular dynamics simulations indicated that the reduced flexibility of thermal and acid-sensitive regions resulted in a significantly increased robustness of M6. Furthermore, the potential of multidimensional virtual screening in enhancing design precision has been validated on l-rhamnose isomerase and PETase. Therefore, the Co-MdVS strategy introduced in this research may offer a viable approach for developing enzymes with enhanced robustness.

(Invited) Accelerating Electrocatalysts’ Activity and Stability Assessments

The standard approach to new electrocatalysts development and testing is prohibitively slow. Moreover, it fails to meet the complexity of real devices. As a rule, it consists of routinely repeated steps, including synthesis, physicochemical characterization, and electrochemical measurements. The latter is typically based on the application of rotating disk electrodes (RDE) as conductive solid support to carry electrocatalysts and bulk electrochemical cells with liquid electrolytes as the reaction media.The current work will contain two main parts presenting our recent approaches to tackling the abovementioned limitations of the classical electrochemical test systems. As a representative example, oxygen evolution reaction (OER) electrocatalysis in electrolytes of different pH is taken. It will be shown that bearing in mind the intrinsic limitations of the aqueous mode systems (AMSs), significant acceleration of electrocatalysts’ activity and stability measurements can be achieved by using coupled techniques based on different scanning flow cells.1, 2 This approach is ideal for quick multidimensional parameter space screening. However, further tests in real systems are necessary after identifying promising candidates. It will be shown that also this step can be accelerated using model gas diffusion electrode (GDE)-based setups.3, 4 Moreover, qualitatively different information, e.g. electrocatalyst dissolution assessment, can be achieved using GDE setups coupled to external analytics like inductively coupled plasma mass spectrometry (on-line ICP-MS). While it will be shown that using two approaches, facile screening and real-device level proof tests, are feasible, limitations and challenges will also be discussed, together with further directions to develop these techniques.

Risk for anxiety and depression among men with prostate cancer.

280 Background: Men with prostate cancer (PC) commonly experience symptoms of anxiety, depression, and suicidality; yet, identifying men in need of mental health support can be difficult, particularly as gender role socialization may deter men from seeking care. We aimed to identify sociodemographic, clinical, and social factors associated with risk for clinically significant anxiety and depression among men with PC. Methods: 118 men with PC completed the Cancer Experience Registry, provided sociodemographic and clinical information, degree of symptom and side effect (SSE) burden in the prior month (16 items), completed the CancerSupportSource Risk for Anxiety and Risk for Depression 2-item subscales , and PROMIS Emotional Support and Instrumental Support 4-item subscales. Bivariate analysis was used to identify significant variables associated with risk for anxiety or depression to be included in subsequent models. Multivariable logistic regression was used to determine which factors significantly predicted risk (1=At risk; 0=Not) for 1) anxiety and 2) depression Independent variables included sociodemographic (age, race/ethnicity, employment, income, marital status), and clinical factors (time since diagnosis, staging, treatment status, history of recurrence, radical prostatectomy, chemotherapy, hormone or radiation therapy, total SSE burden), and social support (caregiver (Y/N), emotional and instrumental support). Results: The sample was 84% Non-Hispanic (NH) White, 9% NH Black. Mean age was 66 years ( SD=9.8). 42% NED, 23% localized, 26% metastatic disease. 53% were retired, 35% employed, and 10% unemployed due to disability (UDTD). 31% were at risk for clinical levels of anxiety; 25% were at risk for clinical levels of depression. In multivariable logistic regression analysis: significant predictors of risk for anxiety ( p&lt;.001) included age (OR =0.88, p&lt;.01), not having a caregiver (OR =5.02, p=.02), and emotional support (OR =0.81, p=.04). Risk for depression ( p&lt;.001) was significantly predicted by instrumental support (OR=0.67, p=.01) and higher among those with active, localized disease compared to NED (OR =10.84, p=.02), and among those UDTD compared to employed (OR =11.09, p=.03). Significant correlates of risk for anxiety and depression in bivariate but not multivariate analysis: marital status, time since diagnosis, and total SSE burden. Conclusions: Younger age, UDTD, localized cancer status, social support, and not having a caregiver were significant predictors of risk for clinical levels of anxiety or depression. Routine risk assessment for anxiety and depression, coupled with multidimensional distress screening can help triage patients to tailored care. Further, those with greater social support and those with a caregiver had lower odds of being at risk for anxiety or depression, emphasizing the need for connecting men with cancer to emotional and instrumental supportive services in their community.

Screening the NCI diversity set V for anti-MRSA activity: cefoxitin synergy and LC-MS/MS confirmation of folate/thymidine biosynthesis inhibition.

New antibacterial agents and agent combinations are urgently needed to combat antimicrobial resistance. A multidimensional chemical library screening strategy was used to identify compounds in the National Cancer Institute (NCI) diversity set V library (1,593 compounds) with anti-methicillin-resistant Staphylococcus aureus (MRSA) activity. In this effort, library compounds were screened for anti-MRSA activity in both their original [un-metabolized (UM)] and human liver microsome-metabolized [post-metabolized (PM)] forms and in the absence and presence of sub-minimum inhibitory concentration (MIC) levels of cefoxitin. This strategy allows for the identification of intrinsically active agents, agents with active metabolites, and agents that can act synergistically with cefoxitin. Sixteen UM compounds with MICs ≤ 12.5 µM were identified. No agents with substantially enhanced activity after microsomal metabolism were found. Several agents showed significant apparent synergy with cefoxitin, and checkerboard assays were used to confirm synergy for four of these (celastrol, porfiromycin, 4-quinazolinediamine, and teniposide). A follow-up comparative screen in the absence and presence of 4-µM thymidine was used to identify three agents as likely folate/thymidine biosynthesis inhibitors. A liquid chromatography-mass spectrometry (LC-MS/MS) assay for deoxythymidine triphosphate (dTTP) was used to confirm these three as suppressing dTTP biosynthesis in MRSA. Bactericidal vs bacteriostatic activity was also evaluated. This study further demonstrates the utility of comparative library screening to identify novel bioactive agents with interesting synergies and biological activities. The identification of several folate/thymidine biosynthesis inhibitors from this small screen indicates that this pathway is a viable target for new drug discovery efforts. IMPORTANCE New antibacterial agents are urgently needed to counter increasingly resistant bacteria. One approach to this problem is library screening for new antibacterial agents. Library screening efforts can be improved by increasing the information content of the screening effort. In this study, we screened the National Cancer Institute diversity set V against methicillin-resistant Staphylococcus aureus (MRSA) with several enhancements. One of these is to screen the library before and after microsomal metabolism as means to identify potential active metabolites. A second enhancement is to screen the library in the absence and presence of sub-minimum inhibitory concentration levels of another antibiotic, such as cefoxitin in this study. This identified four agents with synergistic activity with cefoxitin out of 16 agents with good MRSA activity alone. Finally, active agents from this effort were counter-screened in the presence of thymidine, which quickly identified three folate/thymidine biosynthesis inhibitors, and also screened for bactericidal vs bacteriostatic activity.

Solving multidimensional screening problems using a generalized single crossing property

Solving multidimensional screening problems using a generalized single crossing property

Survival Bias, Non-Lineal Behavioral and Cortico-Limbic Neuropathological Signatures in 3xTg-AD Mice for Alzheimer's Disease from Premorbid to Advanced Stages and Compared to Normal Aging.

Pre-clinical research in aging is hampered by the scarcity of studies modeling its heterogeneity and complexity forged by pathophysiological conditions throughout the life cycle and under the sex perspective. In the case of Alzheimer's disease, the leading cause of dementia in older adults, we recently described in female wildtype and APP23 mice a survival bias and non-linear chronology of behavioral signatures from middle age to long life. Here, we present a comprehensive and multidimensional (physical, cognitive, and neuropsychiatric-like symptoms) screening and underlying neuropathological signatures in male and female 3xTg-AD mice at 2, 4, 6, 12, and 16 months of age and compared to their non-transgenic counterparts with gold-standard C57BL/6J background. Most variables studied detected age-related differences, whereas the genotype factor was specific to horizontal and vertical activities, thigmotaxis, coping with stress strategies, working memory, and frailty index. A sex effect was predominantly observed in classical emotional variables and physical status. Sixteen-month-old mice exhibited non-linear age- and genotype-dependent behavioral signatures, with higher heterogeneity in females, and worsened in naturalistically isolated males, suggesting distinct compensatory mechanisms and survival bias. The underlying temporal and spatial progression of Aβ and tau pathologies pointed to a relevant cortico-limbic substrate roadmap: premorbid intracellular Aβ immunoreactivity and pSer202/pThr205 tau phosphorylation in the amygdala and ventral hippocampus, and the entorhinal cortex and ventral hippocampus as the areas most affected by Aβ plaques. Therefore, depicting phenotypic signatures and neuropathological correlates can be critical to unveiling preventive/therapeutic research and intervention windows and studying adaptative behaviors and maladaptive responses relevant to psychopathology.