Clinical Use Research Articles

A Method for Studying the Size and Position of the Apical Bases of the Jaws Using Computed Tomography of the Jaws

The study of the apical bases has been relevant in orthodontics for many decades; its study was carried out both on jaw models and on lateral cephalograms. Dentistry today is impossible without three-dimensional studies, which allows you to study an object from any angle and visualize the smallest changes in the anatomical structures of the area under study. The use of cone beam computed tomography to study the apical bases of the jaws makes it possible to study the configuration, size, and position of both the bases themselves and the structures that form them. The parameters we proposed allow us to study the width, length and angle of inclination of the apical base on single CBCT sections. Clinical use of the proposed analysis will contribute to more complete and accurate orthodontic treatment planning.

The influence of MOGAD on diagnosis of multiple sclerosis using MRI.

Myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD) is an immune-mediated demyelinating disease that is challenging to differentiate from multiple sclerosis (MS), as the clinical phenotypes overlap, and people with MOGAD can fulfil the current MRI-based diagnostic criteria for MS. In addition, the MOG antibody assays that are an essential component of MOGAD diagnosis are not standardized. Accurate diagnosis of MOGAD is crucial because the treatments and long-term prognosis differ from those for MS. This Expert Recommendation summarizes the outcomes from a Magnetic Resonance Imaging in MS workshop held in Oxford, UK in May 2022, in which MS and MOGAD experts reflected on the pathology and clinical features of these disorders, the contributions of MRI to their diagnosis and the clinical use of the MOG antibody assay. We also critically reviewed the literature to assess the validity of distinctive imaging features in the current MS and MOGAD criteria. We conclude that dedicated orbital and spinal cord imaging (with axial slices) can inform MOGAD diagnosis and also illuminate differential diagnoses. We provide practical guidance to neurologists and neuroradiologists on how to navigate the current MOGAD and MS criteria. We suggest a strategy that includes useful imaging discriminators on standard clinical MRI and discuss imaging features detected by non-conventional MRI sequences that demonstrate promise in differentiating these two disorders.

Distinctive features and prognostic utility of neutrophil in severe patients with Klebsiella pneumoniae infection.

Neutrophil plays a pivotal role in the management of Klebsiella pneumoniae infection. Delineate the clinical characteristics and prognostic utility of neutrophil in severe patients with K. pneumoniae infection are crucial for clinical management and prognostic assessment. K. pneumoniae patients with different infection sites were enrolled from Medical Information Mart for Intensive Care IV and eICU Collaborative Research Database. Temporal variations of neutrophil counts within 30 days of clinical onset were examined using locally weighted scatterplot smoothing curves. Logistic regression analysis was performed to assess the relationship between neutrophil counts and hospital mortality. A total of 1,705 patients caused by K. pneumonia were included in the study. The non-survivor group exhibited a comparatively older age and a higher proportion of K. pneumoniae infections originating from respiratory and bloodstream sources compared to the survivor group (38.4% vs 21.1%, p<0.0001, and 15.1% vs 10.3%, p=0.021). Patients combined with multiple drug resistance strains, respiratory infection, liver disease, and above 60 years exhibited a specific dynamic process of neutrophil levels. Neutrophils counts peaked at admission and 1-2 weeks later. There was a 'U'-shaped relationship between neutrophil counts and hospital mortality. Neutrophils in K. pneumoniae infected patients have distinctive features and dynamic clinical trajectories. Close monitoring of severe patients infected with K. pneumoniae upon admission and during the first 1-2 weeks after admission is of utmost importance, particularly for patients with a neutrophil count exceeding 8.0×109/L.

Predictive models and biomarkers for survival in stage III breast cancer: a review of clinical applications and future directions

Stage III breast cancer, characterized by locally advanced tumors and potential regional lymph node involvement, presents a formidable challenge to both patients and healthcare professionals. Accurate prediction of survival outcomes is crucial for guiding treatment decisions and optimizing patient care. This publication explores the potential clinical utility of predictive tools, encompassing genetic markers, imaging techniques, and clinical parameters, to improve survival outcome predictions in stage III breast cancer. Multimodal approaches, integrating these tools, hold the promise of delivering more precise and personalized predictions. Despite the inherent challenges, such as data standardization and genetic heterogeneity, the future offers opportunities for refinement, driven by precision medicine, artificial intelligence, and global collaboration. The goal is to empower healthcare providers to make informed treatment decisions, ultimately leading to improved survival outcomes and a brighter horizon for individuals facing this challenging disease.

Mechanically Induced Motor Tremors Disrupt the Perception of Time.

Contemporary research has begun to show a strong relationship between movements and the perception of time. More specifically, concurrent movements serve to both bias and enhance time estimates. To explain these effects, we recently proposed a mechanism by which movements provide a secondary channel for estimating duration that is combined optimally with sensory estimates. However, a critical test of this framework is that by introducing "noise" into movements, sensory estimates of time should similarly become noisier. To accomplish this, we had human participants move a robotic arm while estimating intervals of time in either auditory or visual modalities (n = 24, ea.). Crucially, we introduced an artificial "tremor" in the arm while subjects were moving, that varied across three levels of amplitude (1-3 N) or frequency (4-12 Hz). The results of both experiments revealed that increasing the frequency of the tremor led to noisier estimates of duration. Further, the effect of noise varied with the base precision of the interval, such that a naturally less precise timing (i.e., visual) was more influenced by the tremor than a naturally more precise modality (i.e., auditory). To explain these findings, we fit the data with a recently developed drift-diffusion model of perceptual decision-making, in which the momentary, within-trial variance was allowed to vary across conditions. Here, we found that the model could recapitulate the observed findings, further supporting the theory that movements influence perception directly. Overall, our findings support the proposed framework, and demonstrate the utility of inducing motor noise via artificial tremors.

Efficacy and safety of Bacteroides fragilis BF839 for pediatric autism spectrum disorder: a randomized clinical trial.

The clinical utility of Bacteroides fragilis in treating autism spectrum disorder (ASD) remains unclear. Therefore, this randomized, double-blind, placebo-controlled study aimed to explore the therapeutic effects and safety of B. fragilis BF839 in the treatment of pediatric ASD. We examined 60 children aged 2-10 years diagnosed with ASD, and participants received either BF839 powder (10 g/bar with ≥106 CFU/bar of viable bacteria, two bars/day) or placebo for 16 weeks. The primary outcomes was Autism Behavior Checklist (ABC) score. The secondary outcomes were Childhood Autism Rating Scale (CARS), Social Responsiveness Scale (SRS), Normal Development of Social Skills from Infants to Junior High School Children (S-M), Gastrointestinal Symptom Rating Scale (GSRS) scores, and fecal microbiome composition. Assessments were performed on day 0 and at weeks 8 and 16. Compared with the placebo group, the BF839 group showed significant improvement in the ABC body and object use scores at week 16, which was more pronounced in children with ASD aged <4 years. Among children with a baseline CARS score ≥30, the BF839 group showed significant improvements at week 16 in the ABC total score, ABC body and object use score, CARS score, and GSRS score compared to the placebo group. Only two patients (6.67%) in the BF839 group experienced mild diarrhea. Compared with baseline and placebo group levels, the BF839 group showed a significant post-intervention increase in abundance of bifidobacteria and change in the metabolic function of neuroactive compounds encoded by intestinal microorganisms. BF839 significantly and safely improved abnormal behavior and gastrointestinal symptoms in children with ASD.

Dual-Locked Probe with Activatable Sonoafterglow Luminescence for Precise Imaging of MET-Induced Liver Injury.

Metformin (MET) is currently the first-line treatment for type 2 diabetes mellitus (T2DM). However, overdose and long-term use of MET may induce a serious liver injury. What's worse, diagnosis of MET-induced liver injury remains challenging in clinic. Although several probes have been reported for imaging MET-induced liver injury utilizing upregulated hepatic H2S as a biomarker, they are still at risk of nonspecific activation in complex physiological environments and rely on light excitation with limited imaging depth. Herein, we rationally designed and developed a dual-locked probe, DPA-H2S, for precise imaging of MET-induced liver injury by H2S-activated sonoafterglow luminescence. DPA-H2S is a small molecule consisting of a sonosensitizer protoporphyrin IX (PpIX) and an afterglow substrate that is dual-locked with a H2S-responsive 2,4-dinitrobenzene group and a 1O2-responsive electron-rich double bond. When employing DPA-H2S for imaging of MET-induced liver injury in vivo, since the PpIX moiety can produce 1O2 in situ at the liver site under focused ultrasound (US) irradiation, the two locks of DPA-H2S can be specifically activated by the highly upregulated H2S at the liver injury sites and the in situ generated 1O2, respectively. Thus, the sonoafterglow signal of DPA-H2S is significantly turned on, enabling precise imaging of the MET-induced liver injury. In vitro results showed that, through H2S-activated sonoafterglow luminescence, DPA-H2S was capable of imaging H2S with good sensitivity and high selectivity and realized deep tissue imaging (∼20 mm, signal-to-background ratio (SBR) = 3.4). Furthermore, we successfully applied DPA-H2S for precise in vivo imaging of MET-induced liver injury. We anticipate that our dual-locked probe, DPA-H2S, may serve as a promising tool in assisting the diagnosis of MET-induced liver injury in clinics and informing the clinical utilization of MET in the near future.

Opportunistic Assessment of Hip Fracture Risk Based on Chest CT.

Hip fracture (HF) has been described as the "last fracture of life" in the elderly, so the assessment of HF risk is extremely important. Currently, few studies have examined the relationship between imaging data from chest computed tomography (CT) and HF. This study demonstrated that pectoral muscle index (PMI) and vertebral body attenuation values could predict HF, aiming to opportunistically assess the risk of HF in patients without bone mineral density (BMD) based on chest CT for other diseases. In the retrospective study, 800 participants who had both BMD and chest CT were enrolled from January 2021 to January 2024. After exclusion, 472 patients were finally enrolled, divided into the healthy control (HC) group and the HF group. Clinical data were collected, and differences between the two groups were compared. A predictive model was constructed based on the PMI and CT value of the fourth thoracic vertebra (T4HU) by logistic regression analysis, and the predictive effect of the model was analyzed by using the receiver operating characteristic (ROC) curve. Finally, the clinical utility of the model was analyzed using decision curve analysis (DCA) and clinical impact curves. Both PMI and T4HU were lower in the HF group than in the HC group (p < 0.05); low PMI and low T4HU were risk factors for HF. The predictive model incorporating PMI and T4HU on the basis of age and BMI had excellent diagnostic efficacy with an area under the curve (AUC) of 0.865 (95% confidence interval [CI]: 0.830-0.894, p < 0.01), sensitivity and specificity of 0.820 and 0.754, respectively. The clinical utility of the model was validated using calibration curves and DCA. The AUC of the predictive model incorporating BMD based on age and BMI was 0.865 (95% CI: 0.831-0.895, p < 0.01), with sensitivity and specificity of 0.698 and 0.711, respectively. There was no significant difference in diagnostic efficacy between the two models (p = 0.967). PMI and T4HU are predictors of HF in patients. In the absence of dual-energy x-ray absorptiometry (DXA), the risk of HF can be assessed by measuring the PMI and T4HU on chest CT examination due to other diseases, and further treatment can be provided in time to reduce the incidence of HF.

Clinical Utility of Serum C-peptide Concentration for Hospitalized Patients with Hyperglycemia.

Serum C-peptide concentration is often utilized for diagnostic, prognostic, or therapeutic assessment in diabetes mellitus. However, there is limited clinical data regarding diagnostic and predictive value of C-peptide measured during hospitalizations for hyperglycemia. Adults admitted to Mayo Clinic inpatient facilities due to an acute hyperglycemic emergency between January 2017 and November 2022 were included in our study. Predictive capacity of C-peptide for discontinuation of therapeutic insulin was examined in the entire cohort and the subgroup of non-autoimmune non-pancreatitis diabetes (NANP-DM). We included 187 patients (63 women) in our study. During hospitalization, patients with type 1 diabetes antibodies displayed diminished serum C-peptide concentration (p=0.014), correlating inversely with subsequent HbA1c% [r= (-0.22), p=0.005]. Initial C-peptide concentrations did not differ between patients requiring insulin therapy during follow-up and those who did not (p=0.16). C-peptide concentrations showed limited predictive capacity for achieving glycemic control. Subgroup analyses in NANP-DM exhibited similar limited capacity for anticipating therapeutic insulin needs and achieving glycemic controls. C-peptide concentration did not exhibit a robust predictive capability for future need of insulin therapy and achieving glycemic control, limiting its utility in clinical practice within inpatient settings.

Approach and withdrawal from cognitively effortful activities: Development, validation, and transdiagnostic clinical utility of a cognitive motivation scale

BackgroundDeficits in cognition and motivation predict functioning in depressive and psychotic disorders. However, experimental tasks of cognitive motivation are inconsistently correlated with functioning, time-intensive, and not intuitive in clinical practice. We aimed to develop and validate a self-report instrument to assess motivation processes pertinent to engagement with cognitive activities in daily life. MethodFollowing item generation, scale dimensionality, reliability, and validity were evaluated iteratively over Studies 1–3 with online general adult participants (n1 = 205; n2 = 235; n3 = 181). The 20-item Cognitive Motivation scale was also validated in a Study 3 sub-sample reporting high levels of depressive symptoms (n = 74) and Study 4 early psychosis outpatients (n = 25). ResultsTwo-factor model of cognitive approach and cognitive withdrawal, each with good internal consistency, convergent validity, discriminant validity was supported. Cognitive withdrawal showed stronger associations with cognitive difficulties, depressive symptoms, and functional impairments than traditional motivation scale. Participants reporting high depression levels showed more severe difficulties with cognitive motivation than participants reporting low depression levels. In early psychosis outpatients, correlations with functioning and cognitive effort expenditure provided support for scale validity. LimitationsCross-sectional data collection restricted evaluation of repeated administration psychometric properties. Scale validation was mostly established in online community samples and a small patient sample during the COVID-19 pandemic, thereby limiting generalizability of clinical applications. ConclusionsCognitive Motivation scale is a promising tool for future intervention trials seeking to target motivational processes associated with functioning in the general population and potentially across patient groups with amotivation symptoms.

Foundation model-driven distributed learning for enhanced retinal age prediction.

The retinal age gap (RAG) is emerging as a potential biomarker for various diseases of the human body, yet its utility depends on machine learning models capable of accurately predicting biological retinal age from fundus images. However, training generalizable models is hindered by potential shortages of diverse training data. To overcome these obstacles, this work develops a novel and computationally efficient distributed learning framework for retinal age prediction. The proposed framework employs a memory-efficient 8-bit quantized version of RETFound, a cutting-edge foundation model for retinal image analysis, to extract features from fundus images. These features are then used to train an efficient linear regression head model for predicting retinal age. The framework explores federated learning (FL) as well as traveling model (TM) approaches for distributed training of the linear regression head. To evaluate this framework, we simulate a client network using fundus image data from the UK Biobank. Additionally, data from patients with type 1 diabetes from the UK Biobank and the Brazilian Multilabel Ophthalmological Dataset (BRSET) were utilized to explore the clinical utility of the developed methods. Our findings reveal that the developed distributed learning framework achieves retinal age prediction performance on par with centralized methods, with FL and TM providing similar performance (mean absolute error of 3.57 ± 0.18 years for centralized learning, 3.60 ± 0.16 years for TM, and 3.63 ± 0.19 years for FL). Notably, the TM was found to converge with fewer local updates than FL. Moreover, patients with type 1 diabetes exhibited significantly higher RAG values than healthy controls in all models, for both the UK Biobank and BRSET datasets (P < .001). The high computational and memory efficiency of the developed distributed learning framework makes it well suited for resource-constrained environments. The capacity of this framework to integrate data from underrepresented populations for training of retinal age prediction models could significantly enhance the accessibility of the RAG as an important disease biomarker.

The Current State of the Clinical Utility of Evidence-Based Practice for Ulcer Prevention in Long-Term Care Facilities

Background: Pressure ulcers (PUs) are localized skin injuries that mostly occur over bony prominences. PU prevalence in long-term care (LTC) facilities is currently extremely high despite the availability of evidence-based practice (EBP) guidelines at national and international levels. This narrative review aimed to investigate the current state of the clinical utility of EBP in the prevention of PUs in LTC facilities. Methods: A narrative review approach was used to synthesize studies that offer insights into the current state of clinical utility of EBP guidelines in LTC facilities. Studies were searched on PubMed, Web of Science, ScienceDirect, and Google Scholar. Findings: The findings revealed suboptimal implementation of EBP guidelines in LTC facilities in various countries. Nurses use clinically validated risk assessment tools less often to decide patients who are at risk of developing PUs for tailored interventions. Although scheduled positioning and the use of pressure relieving devices are commonly implemented, they are less documented in care plans. Nutritional assessments and interventions are the least often used. Nurses and other healthcare professionals often involve patients, family, and carers in planning and decision-making processes, but further improvements are still needed. Conclusion: There is a need to integrate into routine care clinically validated instruments for risk assessment for PU prevention in LTC facilities. Also, prioritizing nutritional assessments and interventions should be encouraged in LTC facilities, but there is a need to first understand barriers and facilitators.

Somatic Mosaicism in Brain Disorders.

Research efforts over the past decade have defined the genetic landscape of somatic variation in the brain. Neurons accumulate somatic mutations from development through aging with potentially profound functional consequences. Recent studies have revealed the contribution of somatic mosaicism to various brain disorders including focal epilepsy, neuropsychiatric disease, and neurodegeneration. One notable finding is that the effect of somatic mosaicism on clinical outcomes can vary depending on contextual factors, such as the developmental origin of a variant or the number and type of cells affected. In this review, we highlight current knowledge regarding the role of somatic mosaicism in brain disorders and how biological context can mediate phenotypes. First, we identify the origins of brain somatic variation throughout the lifespan of an individual. Second, we explore recent discoveries that suggest somatic mosaicism contributes to various brain disorders. Finally, we discuss neuropathological associations of brain mosaicism in different biological contexts and potential clinical utility.

Clinical-radiomics combination model for predicting the short-term efficacy of bipolar transurethral enucleation of the prostate in patients with benign prostatic hyperplasia

Abstract Background Bipolar transurethral enucleation of the prostate (B-TUEP) is a well-established surgical treatment for benign prostatic hyperplasia (BPH); however, its efficacy may vary depending on patient characteristics. Magnetic resonance imaging with radiomics analysis can offer comprehensive and quantitative information about prostate characteristics that may relate to surgical outcomes. This study aimed to explore the value of magnetic resonance imaging and radiomics analysis in predicting the short-term efficacy of B-TUEP for BPH. Materials and methods A total of 137 patients with BPH who underwent B-TUEP at 2 institutions were included. Radiological features were measured in the magnetic resonance images, and the radiomics score was developed from 1702 radiomics features extracted from the prostate and transitional zone regions of interest. Three prediction models were developed and validated based on clinical-radiological features, radiomic features, and their combinations. The models were evaluated using the area under the receiver operating characteristic curve, calibration curve, and decision curve analysis. Results The combination model exhibited the highest area under curve in both the training set (0.838) and the external validation set (0.802), indicating superior predictive performance and robustness. Furthermore, the combination model demonstrated good calibration (p &gt; 0.05) and optimal clinical utility. The combination model indicated that a higher maximum urine flow rate, lower transitional zone index, and higher radiomics score were associated with an increased risk of poor efficacy. Conclusions Magnetic resonance imaging with radiomic analysis can offer valuable insights for predicting the short-term efficacy of B-TUEP in patients with BPH. A combination model based on clinical and radiomics features can assist urologists in making more precise clinical decisions.

The Clinical Utility of Powdered and Flowable Matrices in Wound Repair and Tissue Regeneration.

Cellular and matrix-like products come in many forms. Among them, powdered and micronized formulations have become increasingly available and popular owing to their unique properties and advantages. Powders have increased tissue contact which many believe can enhance granulation tissue formation, they fill irregular and deep cavities, and they can be used in concert with sheet-like products and skin grafts for improved healing. Despite their advantages, powdered products do have certain limitations that hinder their use, including poor insurance coverage and a lack of CPT coding for adequate reimbursement in an outpatient setting, making their use primarily limited to the operating room. Also, most published data on powdered products consists of smaller case studies and case series, with few reports evaluating the efficacy and utility of powdered formulations compared to their sheet-like progenitors. In this manuscript, we organize available powdered matrix products by type of substrate: xenograft, allograft, placental-based, and synthetic, and review the data in support of various products in specific wound types. This review of the supporting literature provides the current body of evidence on the utility of powdered matrices in wounds.

Exposure-Response-Based Multiattribute Clinical Utility Score Framework to Facilitate Optimal Dose Selection for Oncology Drugs.

The advent of new therapeutic modalities highlighted deficiencies in the traditional maximum tolerated dose approach for oncology drug dose selection and prompted the Food and Drug Administration (FDA)'s Project Optimus initiative, which suggests that sponsors take a holistic approach, including efficacy, safety, and pharmacokinetic (PK) and pharmacodynamic data, in conjunction with integrated exposure-response (ER) analyses. However, this method comes with an inherent challenge of the collation of the multisource data. To address this issue, an ER-based clinical utility score (CUS) framework, combining benefit and risk into a single measurement, was developed. Model-predicted outcomes for each clinically relevant end point, informed by ER modeling, are converted to a CUS using a user-defined utility function. Thereafter, individual CUS is integrated into a single score with user-defined weighting for each end point. The user-defined weighting feature allows the user to incorporate expert knowledge/understanding into weighing the product's benefit versus risk profile. To validate the framework, data were leveraged from over 50 oncology programs from 2019 to 2023 on the basis of FDA new drug application/biologics license application review packages and/or related literature studies. Five representative cases were selected for in-depth evaluation. Results showed that the optimal benefit-risk ratio (highest CUS) was consistently observed at PK exposures synonymous with recommended doses. A recurring theme across cases was a greater emphasis on safety over efficacy in oncology drug dose determination. The ER-based CUS framework offers a strategic tool to navigate the complexities of dose selection in oncology programs. It serves as a pillar to the importance of integrative data analysis, aligning with the vision of Project Optimus, and demonstrates its potential in guiding dose optimization by balancing therapeutic benefits against risk.

NIR-Responsive Deployable and Self-Fitting 4D-Printed Bone Tissue Scaffold.

The treatment of irregular-shaped and critical-sized bone defects poses a clinical challenge. Deployable, self-fitting tissue scaffolds that can be implanted by minimally invasive procedures are a promising solution. Toward this, we fabricated NIR-responsive and programmable polylactide-co-trimethylene carbonate (PLMC) scaffolds nanoengineered with polydopamine nanoparticles (PDA) by extrusion-based three-dimensional (3D) printing. The 3D-printed scaffolds demonstrated excellent (>99%), fast (under 30 s), and tunable shape recovery under NIR irradiation. PLMC-PDA composites demonstrated significantly higher osteogenic potential in vitro as revealed by the significantly enhanced alkaline phosphatase (ALP) secretion and mineral deposition in contrast to neat PLMC. Intraoperative deployability and in vivo bone regeneration ability of PLMC-PDA composites were demonstrated, using self-fitting scaffolds in critical-sized cranial bone defects in rabbits. The 3D-printed scaffolds were deformed into compact shapes that could self-fit into the defect shape intraoperatively under low power intensity (0.76 W cm-2) NIR. At 6 and 12 weeks postsurgical implantation, near-complete bone regeneration was observed in PLMC-PDA composites, unlike neat PLMC through microcomputed tomography (micro-CT) analysis. The potential clinical utility of the 3D-printed composites to secure complex defects was confirmed through self-fitting of the scaffolds into irregular defects in ex vivo models of rabbit tibia, mandible, and tooth models. Taken together, the composite scaffolds fabricated here offer an innovative strategy for minimally invasive deployment to fit irregular and complex tissue defects for bone tissue regeneration.

Development and external validation of a risk prediction model for depression in patients with coronary heart disease

BackgroundDepression is an independent risk factor for adverse outcomes of coronary heart disease (CHD). This study aimed to develop a depression risk prediction model for CHD patients. MethodsThis study utilized data from the National Health and Nutrition Examination Survey (NHANES). In the training set, reference literature, logistic regression, LASSO regression, optimal subset algorithm, and machine learning random forest algorithm were employed to screen prediction variables, respectively. The optimal prediction model was selected based on the C-index, Net Reclassification Improvement (NRI), and Integrated Discrimination Improvement (IDI). A nomogram for the optimal prediction model was constructed. 3 external validations were performed. ResultsThe training set comprised 1375 participants, with a depressive symptoms prevalence of 15.2 %. The optimal prediction model was constructed using predictors obtained from optimal subsets algorithm (C-index = 0.774, sensitivity = 0.751, specificity = 0.685). The model includes age, gender, education, marriage, diabetes, tobacco use, antihypertensive drugs, high-density lipoprotein cholesterol (HDLC), and aspartate aminotransferase (AST). The model demonstrated consistent discrimination ability, accuracy, and clinical utility across the 3 external validations. LimitationsThe applicable population of the model is CHD patients. And the clinical benefits of interventions based on the prediction results are still unknown. ConclusionWe developed a depression risk prediction model for CHD patients, which was presented in the form of a nomogram for clinical application.

Potential for tumor aggressiveness and its association with vasculogenic mimicry marker in colorectal carcinomas in Indian population- A tertiary care hospital level study.

Vasculogenic mimicry (VM) is the ability of cancer stem cells of aggressive phenotype to mimic embryonic vascular network by forming channels lined by tumor cells, thereby, promoting tumor growth. These channels are periodic acid-schiff positive and CD34 negative and have been associated with tumor invasion, metastasis, and poor prognosis. It is a promising target for developing novel anticancer therapeutics and contributes to personalized medicine. Our study aims to look for an association of vasculogenic mimicry marker (VMM) with the aggressiveness of colorectal carcinomas (CRCs). All retrospective and prospective cases of colorectal adenocarcinomas received over period of five years, from 2017 to 2021 were included in this study and a case-control study was planned. The study population was divided into two comparison groups based on TNM staging (a) those with non-aggressive tumors (controls; TNM stage I and II) and (b) those with aggressive tumors (cases; TNM stage III and IV). A total of 36 controls and 27 cases were studied. Hematoxylin and eosin stain, PAS, and CD34 immunohistochemistry were conducted. PAS positivity with negative CD34 in the same case was designated as VMM positive. VMM status was correlated with tumor stage, grade, and other pathological markers of prognosis. The Chi-square test was used to find an association between the aggressiveness of CRCs and VM positivity. The P value < 0.05 was considered to be significant. It was found that VMM was significantly associated with the aggressiveness of CRCs. VMM is a promising marker for its clinical utility in day-to-day routine IHC studies and its positivity correlates with tumor aggressiveness.

Myrtleciclib, a CDK4/6/9 Inhibitor for the Treatment of Aggressive Cancers.

Selective Cyclin-Dependent Kinase 4/6 inhibitors (CDK4/6i) have revolutionized the treatment of breast cancer and have potential in other cancers, being manageable drugs yet with some bone marrow toxicity. Selective CDK9 inhibitors (CDK9i) never advanced into clinical use, partly due to side effects, including gastrointestinal toxicity, and a small window between activity and cytotoxicity, which results in a narrow therapeutic index (TI). To overcome the drawbacks of CDK4/6 and CDK9 inhibitors, we have developed myrtleciclib, a selective CDK4/6/9 inhibitor with few non-critical molecular off-targets. Myrtleciclib appears to bind to an allosteric site, unlike all other CDK4/6i and CDK9i acting by an ATP-competitive mechanism, which supports target specificity. Myrtleciclib's anti-proliferative effects are greater and its Therapeutic Index (TI) is broader than CDK9 and CDK4/6-only inhibitors. This can be explained by a moderate target inhibition, resulting in limited cytotoxicity. Moreover, we documented a synergy between CDK9 and CDK4/6 pathways inhibition, justifying increased drug efficacy, yet such synergy can only be achieved when the inhibition of both CDK9 and CDK4/6 is embedded within the same molecule and balanced within a certain ratio, as it is the case with myrtleciclib. Unlike CDK4/6i, myrtleciclib also induces cell death and apoptosis selectively on cancer cell lines, not on bystander cells. Synergy between myrtleciclib and other drugs with complementary Mechanism of Action (MoA) has also been documented. CDK4/6/9i might represent a new frontier in cancer treatment to overcome the limitations of CDK4/6i and CDK9i for the treatment of cancers, including aggressive cancers with high unmet needs.