Diagnostic Refinement Research Articles

Artificial Intelligence for Cervical Spine Fracture Detection: A Systematic Review of Diagnostic Performance and Clinical Potential.

Systematic review. Artificial intelligence (AI) and deep learning (DL) models have recently emerged as tools to improve fracture detection, mainly through imaging modalities such as computed tomography (CT) and radiographs. This systematic review evaluates the diagnostic performance of AI and DL models in detecting cervical spine fractures and assesses their potential role in clinical practice. A systematic search of PubMed/Medline, Embase, Scopus, and Web of Science was conducted for studies published between January 2000 and July 2024. Studies that evaluated AI models for cervical spine fracture detection were included. Diagnostic performance metrics were extracted and included sensitivity, specificity, accuracy, and area under the curve. The PROBAST tool assessed bias, and PRISMA criteria were used for study selection and reporting. Eleven studies published between 2021 and 2024 were included in the review. AI models demonstrated variable performance, with sensitivity ranging from 54.9% to 100% and specificity from 72% to 98.6%. Models applied to CT imaging generally outperformed those applied to radiographs, with convolutional neural networks (CNN) and advanced architectures such as MobileNetV2 and Vision Transformer (ViT) achieving the highest accuracy. However, most studies lacked external validation, raising concerns about the generalizability of their findings. AI and DL models show significant potential in improving fracture detection, particularly in CT imaging. While these models offer high diagnostic accuracy, further validation and refinement are necessary before they can be widely integrated into clinical practice. AI should complement, rather than replace, human expertise in diagnostic workflows.

Angiotensin II Type-1 Receptor Antibody in Solid Organ Transplantation - Is It Time to Test?

Angiotensin II type-1 receptor antibody (AT1R-Ab) has been mooted as a potential effector of both acute and chronic antibody mediated rejection (AMR). A growing body of literature on the topic is now coming under scrutiny in the context of the evolving Banff AMR diagnostic classification system and refinement of recommendations for histocompatibility testing by the Sensitization in Transplantation Assessment of Risk (STAR) workgroup. This mini-review discusses the latest understanding of pathophysiological mechanisms, clinical evidence for the pathogenicity of AT1R-Ab, and methods of laboratory testing.

Promise and Peril of a Genotype-First Approach to Mendelian Cardiovascular Disease.

Precision medicine, which among other aspects includes an individual's genomic data in diagnosis and management, has become the standard-of-care for Mendelian cardiovascular disease (CVD). However, early identification and management of asymptomatic patients with potentially lethal and manageable Mendelian CVD through screening, which is the promise of precision health, remains an unsolved challenge. The reduced costs of genomic sequencing have enabled the creation of biobanks containing in-depth genetic and health information, which have facilitated the understanding of genetic variation, penetrance, and expressivity, moving us closer to the genotype-first screening of asymptomatic individuals for Mendelian CVD. This approach could transform health care by diagnostic refinement and facilitating prevention or therapeutic interventions. Yet, potential benefits must be weighed against the potential risks, which include evolving variant pathogenicity assertion or identification of variants with low disease penetrance; costly, stressful, and inappropriate diagnostic evaluations; negative psychological impact; disqualification for employment or of competitive sports; and denial of insurance. Furthermore, the natural history of Mendelian CVD is often unpredictable, making identification of those who will benefit from preventive measures a priority. Currently, there is insufficient evidence that population-based genetic screening for Mendelian CVD can reduce adverse outcomes at a reasonable cost to an extent that outweighs the harms of true-positive and false-positive results. Besides technical, clinical, and financial burdens, ethical and legal aspects pose unprecedented challenges. This review highlights key developments in the field of genotype-first approaches to Mendelian CVD and summarizes challenges with potential solutions that can pave the way for implementing this approach for clinical care.

Dimensional Affective Sensitivity to Hormones across the Menstrual Cycle (DASH-MC): A transdiagnostic framework for ovarian steroid influences on psychopathology.

Fluctuations in progesterone (P4) and estradiol (E2) across the menstrual cycle can exert direct effects on biological systems implicated in neuropsychiatric disorders and represent a key biological source of variability in affective, cognitive, and behavioral disorders. Although these cyclical symptoms may be most readily identified when they occur exclusively in relation to the menstrual cycle, as in DSM-5 premenstrual dysphoric disorder, symptom changes of similar magnitude occur in a larger proportion of people with ongoing psychiatric disorders. Studies investigating cyclical regulation of brain and behavior often produce inconsistent results, which may be attributed to a lack of focus on specific hormonal events and individual differences in related sensitivities. We propose a transdiagnostic Dimensional Affective Sensitivity to Hormones across the Menstrual Cycle (DASH-MC) framework, postulating that atypical neural responses to several key hormonal events provoke specific temporal patterns of affective and behavioral change across the menstrual cycle. We review prospective and experimental evidence providing initial support for these dimensions, which include (1) luteal-onset negative affect caused by a sensitivity to E2 or P4 surges (mediated by neuroactive metabolites such as allopregnanolone), typified by irritability and hyperarousal; (2) perimenstrual-onset negative affect caused by a sensitivity to low or falling E2, typified by low mood and cognitive dysfunction; and (3) preovulatory-onset positive affect dysregulation caused by a sensitivity to E2 surges, typified by harmful substance use and other risky reward-seeking. This multidimensional, transdiagnostic framework for hormone sensitivity can inform more precise research on ovarian steroid regulation of psychopathology, including further mechanistic research, diagnostic refinement, and precision psychiatry treatment development. Additionally, given the high rates of hormone sensitivity across affective disorders, the DASH-MC may guide broader insights into the complex neurobiological vulnerabilities driving female-biased affective risk, as well as potential triggers and mechanisms of affective state change in psychiatric disorders.

Advancing Breast Cancer Diagnosis: The Impact of Elastography Integration Into Breast Imaging Reporting and Data System (BIRADS) Categorization.

This study evaluates the impact of integrating elastography into the Breast Imaging Reporting and Data System (BIRADS) categorization on breast cancer diagnostics in an African population. It explores the association and agreement between traditional BIRADS and those modified by elastography, as well as between quantitative and qualitative elastography methods. A total of 200 participants who underwent breast imaging as part of their diagnostic evaluation for breast lesions were included in the study. Participant characteristics, including age distribution and indicators for breast cancer diagnoses, were analyzed. Brightness mode (B-mode) findings without elastography were assessed using the BIRADS classification. Elastography was integrated into the BIRADS categorization to evaluate its impact on breast cancer diagnostics.The association and agreement between BIRADS with and without elastography were analyzed. Participants predominantly aged 40-49 showed significant staging differences with the integration of elastography. Traditional B-mode staging identified 29 (49%) of participants in BIRADS stage IV and 14 (23%) in stage V, whereas elastography adjusted these figures significantly, enhancing diagnostic refinement. There was a fair agreement between BIRADS with and without elastography (kappa = 0.322), while a substantial agreement was found between quantitative and qualitative elastography (kappa = 0.674). The results of the study provide evidence that the integration of elastography into BIRADS categorization can significantly improve the accuracy of breast cancer diagnosis in African women. Elastography enhanced lesion characterization, supporting more personalized and precise clinical management. Continued research is needed to fully integrate elastography into routine diagnostic workflows and understand its broader clinical implications in Africa.

Psychometric evaluation and validation of the Brain Fag Syndrome Scale among students at Bayero University Kano

Background: This study delved into the Psychometric Evaluation and Validation of the Brain Fag Syndrome Scale (BFSS) among students at Bayero University Kano. Documented extensively among African students, particularly in academic settings, Brain Fag Syndrome (BFS) is rooted in recurrent mental exhaustion impacting students emotionally and physically. As the concept of BFS as an exhaustion syndrome emerged, a thorough examination of its psychometric properties became essential. Methods: Employing a cross-sectional survey design, 625 3rd-year undergraduate students from Bayero University Kano were randomly selected, representing 89.3% of the intended sample size. Socio-demographic characteristics were explored, scale reliability was measured using Cronbach's alpha, and Exploratory Factor Analysis (EFA) was conducted to unveil the BFSS latent structure. The Brain Fag Syndrome and Fatigue Assessment Questionnaire development stemmed from identified components related to Fatigue and Exhaustion. Results: Analysis with SPSS v26 included all 625 participants with complete data. BFSS exhibited moderate to good reliability (Cronbach's alpha ≈ 0.738). EFA identified a distinct "Fatigue and Exhaustion Factor," strongly linked to fatigue and concentration challenges. A scree plot aided in retaining optimal factors, highlighting the dominance of the identified factor. Conclusion: This study significantly contributes to the validation of the Brain Fag Syndrome Scale (BFSS) and the derivation of a prototype questionnaire for fatigue and exhaustion syndrome. The identified factors align with the evolving understanding of BFS as an exhaustion syndrome, informing diagnostic criteria refinement and enriching the discourse on students' psychological well-being within a cultural context.

Decoding the tumor microenvironment and molecular mechanism: unraveling cervical cancer subpopulations and prognostic signatures through scRNA-Seq and bulk RNA-seq analyses.

Cervical carcinoma (CC) represents a prevalent gynecological neoplasm, with a discernible rise in prevalence among younger cohorts observed in recent years. Nonetheless, the intrinsic cellular heterogeneity of CC remains inadequately investigated. We utilized single-cell RNA sequencing (scRNA-seq) transcriptomic analysis to scrutinize the tumor epithelial cells derived from four specimens of cervical carcinoma (CC) patients. This method enabled the identification of pivotal subpopulations of tumor epithelial cells and elucidation of their contributions to CC progression. Subsequently, we assessed the influence of associated molecules in bulk RNA sequencing (Bulk RNA-seq) cohorts and performed cellular experiments for validation purposes. Through our analysis, we have discerned C3 PLP2+ Tumor Epithelial Progenitor Cells as a noteworthy subpopulation in cervical carcinoma (CC), exerting a pivotal influence on the differentiation and progression of CC. We have established an independent prognostic indicator-the PLP2+ Tumor EPCs score. By stratifying patients into high and low score groups based on the median score, we have observed that the high-score group exhibits diminished survival rates compared to the low-score group. The correlations observed between these groups and immune infiltration, enriched pathways, single-nucleotide polymorphisms (SNPs), drug sensitivity, among other factors, further underscore their impact on CC prognosis. Cellular experiments have validated the significant impact of ATF6 on the proliferation and migration of CC cell lines. This study enriches our comprehension of the determinants shaping the progression of CC, elevates cognizance of the tumor microenvironment in CC, and offers valuable insights for prospective CC therapies. These discoveries contribute to the refinement of CC diagnostics and the formulation of optimal therapeutic approaches.

Clinicopathological and molecular landscape of 5-year IDH-wild-type glioblastoma survivors: A multicentric retrospective study

Five-year glioblastoma (GBM) survivors (LTS) are the minority of the isocitrate dehydrogenase (IDH)-wild-type GBM patients, and their molecular fingerprint is still largely unexplored. This multicenter retrospective study analyzed a large LTS-GBM cohort from nine Italian institutions and molecularly characterized a subgroup of patients by mutation, DNA methylation (DNAm) and copy number variation (CNV) profiling, comparing it to standard survival GBM. Mutation scan allowed the identification of pathogenic variants in most cases, showing a similar mutational spectrum in both groups, and highlighted TP53 as the most commonly mutated gene in the LTS group. We confirmed DNAm as a valuable tool for GBM classification with a diagnostic refinement by using brain tumor classifier v12.5. LTS were more heterogeneous with more cases classified as diffuse pediatric high-grade glioma subtypes and having peculiar CNVs. We observed a global higher methylation in CpG islands and in gene promoters of LTS with methylation levels of distinct gene promoters correlating with prognosis.

Complexities of Coexisting Cardiac Amyloidosis and Coronary Artery Disease: A Contemporary Review of Diagnostic and Treatment Approaches.

Cardiac amyloidosis (CA) represents an emerging challenge in cardiovascular medicine, with notable clinical overlaps and diagnostic complexities when coexisting with coronary artery disease (CAD). This integrative review navigates the intricate terrain of CA and CAD, elucidating epidemiology, clinical presentations, and diagnostic considerations. Examining both immunoglobulin light chain amyloidosis (AL) and transthyretin amyloidosis, we underscore their shared demographic associations, diagnostic intricacies, and potential diagnostic confounders with CAD. Notably, we emphasize the impact of CA on epicardial coronary arteries and the consequential implications for coronary microcirculation. Further exploration reveals the connection between CA and acute myocardial infarction, emphasizing early recognition as pivotal. In terms of differential diagnosis, we underscore the significance of clinical symptoms, electrocardiography, echocardiography, cardiac magnetic resonance, and bone scintigraphy. Additionally, we scrutinize the intricate realm of treatment, encompassing medication selection, antithrombotic strategies, and revascularization modalities. Our review addresses the distinctive challenges posed by CA patients' limited tolerance for conventional therapies. This comprehensive synthesis serves as an invaluable resource for clinicians confronting the intricate intersection of CA and CAD. By offering insights into diagnostic refinement and innovative therapeutic avenues, we aim to enhance patient outcomes and quality of life within this complex clinical landscape.

HEMATOLOGY PROFILES AND DISEASE SEVERITY OF PEDIATRIC DENGUE VIRUS INFECTION AT A TERTIARY HOSPITAL IN SURABAYA, INDONESIA

Highlights Dengue virus infections exhibit a spectrum of clinical manifestations, ranging from asymptomatic cases to severe disease, with the potential for fatalities if not managed effectively. Hematology factors significantly contribute to the severity of dengue virus infection. Abstract Background: The escalating incidence of dengue cases in Surabaya, Indonesia, underscores the imperative to comprehend the hematology profiles and disease severity in pediatric patients affected by dengue virus infections (DVI). As the prevalence of DVI continues to surge, understanding the nuanced clinical manifestations becomes paramount for effective management and mitigation of the disease burden. Objective: This study aimed to characterize the hematology profiles and the disease severity of dengue virus infections (DVI) among pediatric patients hospitalized at Dr. Soetomo General Academic Hospital, Surabaya, Indonesia throughout 2019. Material and Method: A retrospective descriptive cross-sectional study was conducted using secondary data from medical records. Pediatric patients aged six months to 18 years were enrolled. A total sampling method comprised 67 patients meeting the inclusion criteria. Result: Severe thrombocytopenia was most commonly observed in dengue hemorrhagic fever (DHF) III cases (36.4%), while leukopenia was predominant in DF cases (42.2%). High hematocrit levels were more prevalent in DHF III cases (27.3%), and high hemoglobin levels were most frequently identified in DHF II and DHF III cases (33% in each case). Significant differences in DVI severity were observed in platelets and hemoglobin levels (p=0.0002 and p=0.0066, respectively) but not in leukocyte and hematocrit levels. Conclusion: Mild thrombocytopenia was prevalent in Dengue Fever (DF), while severe thrombocytopenia was most prevalent in Dengue Hemorrhagic Fever (DHF) grade III. Leukopenia was prominent in DF patients, and platelets and hemoglobin levels varied across severity of DVI. These findings provide insights for improved clinical management and diagnostic criteria refinement.

P-Type Processes and Predictability: The Winter Precipitation Type Research Multiscale Experiment (WINTRE-MIX)

Abstract During near-0°C surface conditions, diverse precipitation types (p-types) are possible, including rain, drizzle, freezing rain, freezing drizzle, ice pellets, wet snow, snow, and snow pellets. Near-0°C precipitation affects wide swaths of the United States and Canada, impacting aviation, road transportation, power generation and distribution, winter recreation, ecology, and hydrology. Fundamental challenges remain in observing, diagnosing, simulating, and forecasting near-0°C p-types, particularly during transitions and within complex terrain. Motivated by these challenges, the field phase of the Winter Precipitation Type Research Multiscale Experiment (WINTRE-MIX) was conducted from 1 February to 15 March 2022 to better understand how multiscale processes influence the variability and predictability of p-type and amount under near-0°C surface conditions. WINTRE-MIX took place near the U.S.–Canadian border, in northern New York and southern Quebec, a region with plentiful near-0°C precipitation influenced by terrain. During WINTRE-MIX, existing advanced mesonets in New York and Quebec were complemented by deployment of 1) surface instruments, 2) the National Research Council Convair-580 research aircraft with W- and X-band Doppler radars and in situ cloud and aerosol instrumentation, 3) two X-band dual-polarization Doppler radars and a C-band dual-polarization Doppler radar from the University of Illinois, and 4) teams collecting manual hydrometeor observations and radiosonde measurements. Eleven intensive observing periods (IOPs) were coordinated. Analysis of these WINTRE-MIX IOPs is illuminating how synoptic dynamics, mesoscale dynamics, and microscale processes combine to determine p-type and its predictability under near-0°C conditions. WINTRE-MIX research will contribute to improving nowcasts and forecasts of near-0°C precipitation through evaluation and refinement of observational diagnostics and numerical forecast models.

Characterization of Switch/Sucrose Nonfermenting Complex Proteins and Nestin Expression in a Cohort of Pediatric Central Nervous System Tumors.

Tumors of the central nervous system (CNS) in pediatric patients have undergone significant diagnostic refinement through the use of immunohistochemistry (IHC) and molecular techniques. The utility of these novel IHC antibodies has been demonstrated with the inactivation of the switch/sucrose nonfermenting (SWI/SNF) chromatin-remodeling complex in the diagnosis of atypical teratoid/rhabdoid tumors, predominantly through the loss of integrase interactor 1 (INI1; SMARCB1 ). Alternatively, these tumors may have inactivation of brahma-related gene 1 (BRG1; SMARCA4 ) in a subset of cases. The role of other SWI/SNF component proteins and their expression in pediatric brain tumors is not well established. Nestin, an intermediate filament, has been shown to be present in some pediatric CNS tumors, but of uncertain diagnostic and prognostic significance. We sought to explore the immunohistochemical expression profile for common SWI/SNF subunits and nestin in a pediatric CNS tumor cohort. Using a 118-sample tissue microarray, we performed IHC for INI1, BRG1, brahma (BRM), ARID1A, ARID1B, polybromo 1, and nestin. In 19 cases, INI1 was lost and BRG1 was lost in 2 cases. Interestingly, 6 cases originally diagnosed as primitive neuroectodermal tumors showed isolated loss of BRM. Other SWI/SNF proteins did not provide further diagnostic resolution. Nestin was positive in 76.2% of INI1/BRG1-deficient tumors, compared with 29.1% in INI1/BRG1-intact tumors yielding a sensitivity of 76.2%, specificity of 68.0%, and a P value of <0.001, but nestin positivity did not correlate specifically with poor outcomes. In conclusion, we confirm the utility of BRG1 IHC in the workup of pediatric CNS tumors, which may facilitate a difficult diagnosis when conventional markers are inconclusive, or as a first-line marker in cases where intraoperative smears are suggestive of atypical teratoid/rhabdoid tumor. Although nestin expression was associated with SWI/SNF inactivation, it did not yield statistically significant diagnostic or prognostic information in our study. Interestingly, we identified 6 tumors with isolated BRM IHC loss, the significance of which is uncertain but warrants further investigation.

Molecular Heterogeneity in BRAF-Mutant Gliomas: Diagnostic, Prognostic, and Therapeutic Implications

Over the last few decades, deciphering the alteration of molecular pathways in brain tumors has led to impressive changes in diagnostic refinement. Among the molecular abnormalities triggering and/or driving gliomas, alterations in the MAPK pathway reign supreme in the pediatric population, as it is encountered in almost all low-grade pediatric gliomas. Activating abnormalities in the MAPK pathway are also present in both pediatric and adult high-grade gliomas. Across those alterations, BRAF p.V600E mutations seem to define homogeneous groups of tumors in terms of prognosis. The recent development of small molecules inhibiting this pathway retains the attention of neurooncologists on BRAF-altered tumors, as conventional therapies showed no significant effect, nor prolonged efficiency on the high-grade or low-grade unresectable forms. Nevertheless, tumoral heterogeneity and especially molecular alteration(s) associated with MAPK-pathway abnormalities are not fully understood with respect to how they might lead to the specific dismal prognosis of those gliomas and/or affect their response to targeted therapies. This review is an attempt to provide comprehensive information regarding molecular alterations related to the aggressiveness modulation in BRAF-mutated gliomas and the current knowledge on how to use those targeted therapies in such situations.

Retrospective in silico mutation profiling of SARS-CoV-2 structural proteins circulating in Uganda by July 2021: Towards refinement of COVID-19 disease vaccines, diagnostics, and therapeutics.

The SARS-CoV-2 virus, the agent of COVID-19, caused unprecedented loss of lives and economic decline worldwide. Although the introduction of public health measures, vaccines, diagnostics, and therapeutics disrupted the spread of the SARS-CoV-2, the emergence of variants poses substantial threat. This study traced SARS-CoV-2 variants circulating in Uganda by July 2021 to inform the necessity for refinement of the intervention medical products. A comprehensive in silico analysis of the SARS-CoV-2 genomes detected in clinical samples collected from COVID-19 patients in Uganda revealed occurrence of structural protein variants with potential of escaping detection, resisting antibody therapy, or increased infectivity. The genome sequence dataset was retrieved from the GISAID database and the open reading frame encoding the spike, envelope, membrane, or nucleocapsid proteins was translated. The obtained protein sequences were aligned and inspected for existence of variants. The variant positions on each of the four alignment sets were mapped on predicted epitopes as well as the 3D structures. Additionally, sequences within each of the sets were clustered by family. A phylogenetic tree was constructed to assess relationship between the encountered spike protein sequences and Wuhan-Hu-1 wild-type, or the Alpha, Beta, Delta and Gamma variants of concern. Strikingly, the frequency of each of the spike protein point mutations F157L/Del, D614G and P681H/R was over 50%. The furin and the transmembrane serine protease 2 cleavage sites were unaffected by mutation. Whereas the Delta dominated the spike sequences (16.5%, 91/550), Gamma was not detected. The envelope protein was the most conserved with 96.3% (525/545) sequences being wild-type followed by membrane at 68.4% (397/580). Although the nucleocapsid protein sequences varied, the variant residue positions were less concentrated at the RNA binding domains. The dominant nucleocapsid sequence variant was S202N (34.5%, 205/595). These findings offer baseline information required for refining the existing COVID-19 vaccines, diagnostics, and therapeutics.

EPCO-02. GENOME-WIDE DNA METHYLATION PROFILING AND GENETIC CHARACTERIZATION OF LONG-TERM SURVIVAL IDH WILD-TYPE GLIOBLASTOMA PATIENTS

Abstract Glioblastoma multiforme (GBM) has a dismal outcome of approximately 12 months. Less than 5% of patients (long-term survivors-LTS) survives more than 5-years, including IDH-mutant gliomas. Nevertheless, the molecular fingerprint of LTS remains largely uncharted. DNA methylation (DNAm) is an epigenetic modification, altered in cancer and used to classify brain tumors. In this multicentric study sponsored by Alleanza Contro il Cancro (ACC) network, we aimed to molecularly characterize LTS vs standard survival GBM (CTR) by DNAm/Copy Number Variation (CNV) and mutation profiling. We analyzed 51 IDHwt GBM samples (27LTS/24CTR) by Illumina EPIC beadChip and AmpliSeq Comprehensive Cancer Panel. We ran methylation data through the brain tumor classifiers v11b4 and v12.5, performed multidimensional scaling analysis and investigated differentially methylated regions (DMR) correlating them with survival. According to v11b4, cases were classified as: 43 GBM IDHwt (22LTS/21CTR), 27 with a calibrated score &amp;gt;0.84 (16LTS); Plexus Tumor with low scores (2LTS/3CTR); 3 LTS samples did not match. A diagnostic refinement was observed by the v12.5, with 48 cases classifying as GBM IDHwt (25LTS/23CTR) and 35 (19LTS) with optimal score. The LTS group was more heterogeneous, with 4 cases matching in the pedHGG subtypes, including 2 cases in young adults, one with high tumor mutational burden and MSH6 mutation. No specific DNAm genomic profile was observed for LTS patients but we identified 18 significant DMRs, 4 associated with survival probability. At CNV analysis, most cases showed classical alterations (Chr7 gain with or w/o EGFR amplification, 9p21 loss, Chr10 loss) while pedHGG were associated with PDGFRA amplification, 1q gain, 13q loss. NGS identified at least 1 pathogenic variant in 40 cases (22CTR/18LTS) and showed a higher prevalence of mutation negative cases among LTS. No significant difference between the 2 groups was observed in terms of prevalence of mutated genes or number of VUS per sample.

Acute myelogenous leukemia – current recommendations and approaches in molecular-genetic assessment

Acute myelogenous leukemia is a multi-step hematological malignancy, affecting function, growth, proliferation and cell cycle of myeloid precursors. Overall assessment of patients with the disease requires among everything else, a comprehensive investigation of the genetic basis through various methods such as cytogenetic and molecular-genetic ones. This clarification provides diagnostic refinement and carries prognostic and predictive value in respect of essential therapeutic choices.With this review of the literature, we focus on summarizing the latest recommendations and preferred genetic methods, as well as on emphasizing on their general benefits and limitations. Since none of these methods is actually totipotent, we also aim to shed light over the often-difficult choice of appropriate genetic analyses.

Modification Indices for Diagnostic Classification Models

Diagnostic classification models (DCMs) are psychometric models for evaluating a student’s mastery of the essential skills in a content domain based upon their responses to a set of test items. Currently, diagnostic model and/or Q-matrix misspecification is a known problem with limited avenues for remediation. To address this problem, this paper defines a one-sided score statistic that is a computationally efficient method for detecting under-specification at the item level of both the Q-matrix and the model parameters of the particular DCM chosen in an analysis. This method is analogous to the modification indices widely used in structural equation modeling. The results of a simulation study show the Type I error rate of modification indices for DCMs are acceptably close to the nominal significance level when the appropriate mixture reference distribution is used. The simulation results indicate that modification indices are very powerful in the detection of an under-specified Q-matrix and have ample power to detect the omission of model parameters in large samples or when the items are highly discriminating. An application of modification indices for DCMs to an analysis of response data from a large-scale administration of a diagnostic test demonstrates how they can be useful in diagnostic model refinement.

Multiscale evaluation of CMIP5 models using wavelet-based descriptive and diagnostic techniques

Time–frequency localization of model-data discrepancies may provide useful information for climate models inter-comparison, and especially for the goals of climate model refinement and improvement. CMIP5 models of the long-term historical (1850–2005) run experiment are compared using wavelet-based multiscale descriptive and diagnostic techniques with interesting results. Wavelet coherence maps can visualize the ability of alternative CMPI5 models to capture the observed climate variability at different time scales, while the performance of each CMIP5 model is assessed using goodness of fit relative measures on a scale-by-scale basis. Finally, the plots of wavelet decompositions of CMIP5 models and observed temperature series at different scales can detect and locate model/data disagreements across frequencies and over time, thus providing useful information to researchers for model diagnostic refinement and improvement.

Allosteric perspective on the mutability and druggability of the SARS-CoV-2 Spike protein

Recent developments in the SARS-CoV-2 pandemic point to its inevitable transformation into an endemic disease, urging both refinement of diagnostics for emerging variants of concern (VOCs) and design of variant-specific drugs in addition to vaccine adjustments. Exploring the structure and dynamics of the SARS-CoV-2 Spike protein, we argue that the high-mutability characteristic of RNA viruses coupled with the remarkable flexibility and dynamics of viral proteins result in a substantial involvement of allosteric mechanisms. While allosteric effects of mutations should be considered in predictions and diagnostics of new VOCs, allosteric drugs advantageously avoid escape mutations via non-competitive inhibition originating from alternative distal locations. The exhaustive allosteric signaling and probing maps presented herein provide a comprehensive picture of allostery in the spike protein, making it possible to locate potential mutations that could work as new VOC “drivers” and to determine binding patches that may be targeted by newly developed allosteric drugs.

Preclinical and clinical evidence on the approach-avoidance conflict evaluation as an integrative tool for psychopathology.

The approach-avoidance conflict (AAC), i.e. the competing tendencies to undertake goal-directed actions or to withdraw from everyday life challenges, stands at the basis of humans' existence defining behavioural and personality domains. Gray's Reinforcement Sensitivity Theory posits that a stable bias toward approach or avoidance represents a psychopathological trait associated with excessive sensitivity to reward or punishment. Optogenetic studies in rodents and imaging studies in humans associated with cross-species AAC paradigms granted new emphasis to the hippocampus as a hub of behavioural inhibition. For instance, recent functional neuroimaging studies show that functional brain activity in the human hippocampus correlates with threat perception and seems to underlie passive avoidance. Therefore, our commentary aims to (i) discuss the inhibitory role of the hippocampus in approach-related behaviours and (ii) promote the integration of functional neuroimaging with cross-species AAC paradigms as a means of diagnostic, therapeutic, follow up and prognosis refinement in psychiatric populations.