Patient Samples Research Articles

Performance Evaluation of 2 FDA-Approved Fentanyl Immunoassays against LC-MS/MS Reference.

Fentanyl, a synthetic opioid, has caused many recent overdose deaths. Diagnosis of fentanyl abuse is not served by traditional opiate assays due to differences in chemical structure between synthetics and natural opioids. To our knowledge, this is the first study that uses liquid chromatography-tandem mass spectrometry (LC-MS/MS) as the reference method to evaluate and compare the ARK Fentanyl II Assay (ARK II) and the Fentanyl II Enzyme Immunoassay by Roche (FEN2). The ARK II is designed to detect fentanyl in urine samples, whereas the FEN2 is designed to detect norfentanyl, which is the major metabolite. Two hundred patient urine samples including 100 positive and 100 negative samples according to an in-house LC-MS/MS assay were selected for the study. These samples were tested using the ARK II and the FEN2 to determine their performances relative to LC-MS/MS results. The FEN2 showed a positive and negative predictive value of 100% and 97% and a concordance with LC-MS/MS of 98.5% (kappa 0.97). The ARK II showed a positive and negative predictive value of 100% and 95% and a concordance with LC-MS/MS of 97.5% (kappa 0.95). Additionally, the FEN2 accurately identified 9 positive samples with a range of fentanyl concentrations from 0 to 18 ng/mL for which norfentanyl levels were less than the cutoff of 5 ng/mL, indicating potentially greater sensitivity than otherwise stated. The FEN2 and the ARK II were evaluated to be similar in terms of positive and negative predictive value during the analysis of 200 patient samples, as well as equally concordant with the LC-MS/MS reference, despite differences in design.

The adjunctive use of antimicrobial photodynamic therapy, light-emitting-diode photobiomodulation and ozone therapy in regenerative treatment of stage III/IV grade C periodontitis: a randomized controlled clinical trial

ObjectivesTo assess the short-term efficacy of multiple sessions of antimicrobial photodynamic therapy (aPDT), light-emitting-diode (LED) photobiomodulation, and topical ozone therapy applications following surgical regenerative treatments on clinical parameters, patient-centered outcomes, and mRNA expression levels of VEGF, IL-6, RunX2, Nell-1, and osterix in gingival crevicular fluid samples in patients with stage III/IV, grade C periodontitis.Materials and methodsForty-eight systemically healthy patients were assigned into four groups to receive adjunctive modalities with regenerative periodontal surgical treatment. A 970 ± 15 nm diode laser plus indocyanine-green for aPDT group, a 626 nm LED for photobiomodulation group, and topical gaseous ozone were applied at 0, 1, 3, and 7 postoperative days and compared to control group. The clinical periodontal parameters, early wound healing index (EHI), and postoperative patients’ morbidity were evaluated. The mRNA levels of biomarkers were assessed by real-time polymerase chain reaction.ResultsNo significant difference in the clinical parameters except gingival recession (GR) was identified among the groups. For group-by-time interactions, plaque index (PI) and probing pocket depths (PD) showed significant differences (p = 0.034; p = 0.022). In sites with initial PD > 7 mm, significant differences were observed between control and photobiomodulation groups in PD (p = 0.011), between control and aPDT, and control and photobiomodulation groups in CAL at 6-month follow-up (p = 0.007; p = 0.022). The relative osterix mRNA levels showed a statistically significant difference among the treatment groups (p = 0.014).ConclusionsThe additional applications of aPDT and LED after regenerative treatment of stage III/IV grade C periodontitis exhibited a more pronounced beneficial effect on clinical outcomes in deep periodontal pockets.

Older Adults with Cancer and Common Comorbidities-Challenges and Opportunities in Improving Their Cancer Treatment Outcomes.

The older American population is rapidly increasing, and millions of older adults will be cancer survivors with comorbidities. This population faces specific challenges regarding treatment and has unique clinical needs. Recognizing this need, the National Cancer Institute (NCI), in collaboration with the National Institute on Aging (NIA), hosted a webinar series, entitled "Cancer, Aging, and Comorbidities." This commentary provides a reflection of five thematic areas covered by the webinar series, which was focused on improving cancer treatment for older adults with cancer and comorbidities: i) the impact of comorbidities on treatment tolerability and patient outcomes; ii) the impact of comorbidities on cancer clinical trial design; iii) the development of wearable devices in measuring comorbidities in cancer treatment; iv) the effects of nutrition and the microbiome on cancer therapy and; v) the role of senescence and senotherapy in age-related diseases. While advances have been made in these areas, many gaps and challenges exist and are discussed in this commentary. To improve cancer survivorship in older populations with comorbidities, aging and comorbidities must be jointly considered and incorporated across the spectrum of cancer research. This includes more basic research of the mechanisms linking comorbidities and cancer development and treatment response, building critical resources and infrastructure (eg, preclinical models and patient samples), conducting clinical trials focused on the older population, integrating geriatric assessment into cancer treatment, and incorporating novel technologies, such as wearable devices into clinical trials and cancer care.

Identification of HOXC Gene Family as Prognostic and Immune-Related Biomarkers in Breast Cancer Through mRNA Transcriptional Profile and Experimental Validation.

Breast cancer (BC) is the most common malignancy in women worldwide, and more effective biomarkers are urgently needed for the prevention and treatment of BC. Our study aimed to investigate the role of the HOXC gene family (HOXCs) and its relationship with the immune response in BC. The differential expression of HOXCs and its clinical prognostic significance in BC were explored using bioinformatics analysis, and the cBioPortal database was used to evaluate the genetic mutation profile of the HOXCs in BC. The results indicated that the expression levels of HOXC4, 10, 11, 12, and 13 were significantly increased in BC tissues compared with the normal tissues, and expressions of these genes were closely associated with BC stage, among them, high expression levels of HOXC10 and HOXC13 predicted poor outcome in BC patients. In addition, to elucidate the essential role of HOXCs in the tumor microenvironment and immunotherapeutic response of BC, the impact of HOXCs on the regulation of immune infiltration in BC was comprehensively assessed. The result showed thatHOXC10 and HOXC13 expressions were significantly positively linked with the infiltration levels of CD8+T cell and M1 macrophage, while they werenegatively related to Mast and Natural killer cells, suggesting the important influence of HOXCs on regulating tumor immunity in BC patients. Lastly, the RT-qPCR assay was employed to validate HOXCs expression in samples of BC patients. In conclusion, HOXCs may be a promising prognostic indicator and couldregulate the immune infiltration in BC patients, thus being apromising targeted immunotherapy for BC.

Genomic Evolution and Surveillance of Respiratory Syncytial Virus during the 2023-2024 Season.

Respiratory syncytial virus (RSV) is a significant cause of morbidity, particularly in infants. This study describes RSV genomic diversity and disease outcomes during the 2023-2024 season in the Johns Hopkins Hospital System (JHHS). Between August and December 2023, 406 patient samples were sequenced, showing that RSV-B GB5.0.5a was the dominant genotype detected. RSV-A genotype GA2.3.5 was detected less frequently. Metadata analysis of patient data revealed that, although RSV-B was more commonly detected, patients with RSV-A infections were more frequently hospitalized. Analysis of both the G- and F-genes revealed multiple amino acid substitutions in both RSV-A and RSV-B, with some positions within the F-protein that could be associated with evasion of antibody responses. Phylogenetic analysis revealed the genetic diversity of circulating GB5.0.5a and GA2.3.5 genotypes. This study serves as an important baseline for genomic surveillance of RSV within the JHHS and will assist in characterizing the impact of the newly approved RSV vaccines on RSV genomic evolution and the emergence of escape mutations.

Comparative Analysis of Mitochondria Surrounding the Intercalated Discs in Heart Diseases-An Ultrastructural Pilot Study.

Mitochondria play a crucial role in adapting to fluctuating energy demands, particularly in various heart diseases. This study investigates mitochondrial morphology near intercalated discs in left ventricular (LV) heart tissues, comparing samples from patients with sinus rhythm (SR), atrial fibrillation (AF), dilated cardiomyopathy (DCM), and ischemic cardiomyopathy (ICM). Transmission electron microscopy was used to analyze mitochondria within 0-3.5 μm and 3.5-7 μm of intercalated discs in 9 SR, 10 AF, 9 DCM, and 8 ICM patient samples. Parameters included mean size in µm2 and elongation, count, percental mitochondrial area in the measuring frame, and a conglomeration score. AF patients exhibited higher counts of small mitochondria in the LV myocardium, resembling SR. DCM and ICM groups had fewer, larger, and often hydropic mitochondria. Accumulation rates and percental mitochondrial area were similar across groups. Significant positive correlations existed between other defects/size and hydropic mitochondria and between count/area and conglomeration score, while negative correlations between count and size/other defects and between hydropic mitochondria and count could be seen as well. Mitochondrial parameters in the LV myocardium of AF patients were similar to those of SR patients, while DCM and ICM displayed distinct changes, including a decrease in number, an increase in size, and compromised mitochondrial morphology. Further research is needed to fully elucidate the pathophysiological role of mitochondrial morphology in different heart diseases, providing deeper insights into potential therapeutic targets and interventions.

Clinical Metagenomic Next-Generation Sequencing for Diagnosis of Central Nervous System Infections: Advances and Challenges.

Central nervous system (CNS) infections carry a substantial burden of morbidity and mortality worldwide, and accurate and timely diagnosis is required to optimize management. Metagenomic next-generation sequencing (mNGS) has proven to be a valuable tool in detecting pathogens in patients with suspected CNS infection. By sequencing microbial nucleic acids present in a patient's cerebrospinal fluid, brain tissue, or samples collected outside of the CNS, such as plasma, mNGS can detect a wide range of pathogens, including rare, unexpected, and/or fastidious organisms. Furthermore, its target-agnostic approach allows for the identification of both known and novel pathogens. This is particularly useful in cases where conventional diagnostic methods fail to provide an answer. In addition, mNGS can detect multiple microorganisms simultaneously, which is crucial in cases of mixed infections without a clear predominant pathogen. Overall, clinical mNGS testing can help expedite the diagnostic process for CNS infections, guide appropriate management decisions, and ultimately improve clinical outcomes. However, there are key challenges surrounding its use that need to be considered to fully leverage its clinical impact. For example, only a few specialized laboratories offer clinical mNGS due to the complexity of both the laboratory methods and analysis pipelines. Clinicians interpreting mNGS results must be aware of both false negatives-as mNGS is a direct detection modality and requires a sufficient amount of microbial nucleic acid to be present in the sample tested-and false positives-as mNGS detects environmental microbes and their nucleic acids, despite best practices to minimize contamination. Additionally, current costs and turnaround times limit broader implementation of clinical mNGS. Finally, there is uncertainty regarding the best practices for clinical utilization of mNGS, and further work is needed to define the optimal patient population(s), syndrome(s), and time of testing to implement clinical mNGS.

Use of Impedance Cardiography to Guide Blood Pressure Lowering Medication Selection: Systematic Review of Randomized Controlled Trials.

Blood pressure (BP) control can be difficult to attain due to multiple factors, including choosing and titrating antihypertensive medications. Measurement of hemodynamic parameters using impedance cardiography (ICG) at the point of care may allow better alignment of medication with the mechanism(s) underlying an individual's hypertension. We conducted a systematic review of randomized controlled trials of ICG compared to usual care for attainment of BP control. We searched Medline inclusive of year 1946 to January 31, 2024 using a combination of MeSH terms and key words. English-language articles were eligible for inclusion if they described results of a randomized controlled trial designed to compare ICG-guided BP medication selection to usual care (i.e., clinician judgment/guidelines-based alone) among a sample of hypertensive patients. Of 1952 titles screened, six trials met inclusion criteria. The first was published in 2002 from a specialty clinic in the United States, and the most recent in 2021 from a specialty clinic in China. One trial was conducted in a primary care setting. Sample sizes ranged from 102 to 164. Participants randomized to ICG-guided antihypertensive medication had reduced BP in the short-term to a greater extent than those randomized to usual care, with odds ratios for BP control (<140/90 mmHg) at three months ranging from 1.87 to 2.92. This effect was seen in both specialty clinics and in a primary care setting. Incorporation of ICG in the clinical setting may facilitate medication selection that leads to a greater proportion of patients obtaining BP control in the short-term.

Determination of warfarin in volumetric absorptive microsampling by liquid chromatography-tandem mass spectrometry

ObjectiveThis study aims to develop and validate bioanalytical method for quantifying warfarin in VAMS samples using liquid chromatography tandem mass spectrometry (LC-MS/MS), directly implementing the method to patients receiving warfarin therapy. MethodsThe UPLC-MS/MS method was developed and optimized, with quercetin as the internal standard. Sample preparation was carried out using protein precipitation with methanol-acetonitrile (1:3 v/v). ResultsChromatographic separation was achieved using Acquity® UPLC BEH C18 column with 0.1 % formic acid-acetonitrile-methanol (30:69:1 v/v) as mobile phase, in isocratic elution. Multiple Reaction Monitoring (MRM) detection was done using m/z values of 307.10 → 161.06 for warfarin and 301.03 → 150.98 for quercetin as internal standard, using Electrospray Ionization (ESI) negative ion source. The clinical application of the bioanalytical method was carried out on 25 patients receiving warfarin therapy at Universitas Indonesia Hospital and warfarin levels were well within the calibration range from 6.05 to 431.39 ng/mL. ConclusionA novel method has been developed to analyze warfarin in VAMS samples. This method has been fully validated according to guideline from FDA 2022 and is linear in the range of 5–500 ng/mL and the value of r ≥ 0.9977, and successfully applied for the analysis of warfarin in VAMS samples of clinical patients.

Adherence to the Gluten-Free Diet Role as a Mediating and Moderating of the Relationship between Food Insecurity and Health-Related Quality of Life in Adults with Celiac Disease: Cross-Sectional Study.

This cross-sectional study aimed to estimate the relationship between food insecurity (FI) and health-related quality of life (HRQoL) in patients with celiac disease (CD) and assess whether this relationship is mediated or moderated by adherence to the gluten-free diet (GFD). The results of 1162 samples of patients diagnosed with CD showed that 8.3% of individuals who have a combined score of less than 13 exhibited excellent or very good adherence to the GFD. Furthermore, moderate and fair to poor adherence to the GFD was demonstrated, respectively and 71.9% of the patients had poor HRQoL levels. A significant and moderate positive correlation between FI and GFD adherence (r = 0.489) was found, indicating that 24% of the variance in FI is shared with GFD adherence. The patients' gender, marital status, and monthly income made statistically significant contributions to the prediction (p < 0.05). Females had significantly lower HRQoL scores than males (B = -4.619, 95% CL: -6.08, -3.16) after holding all other variables constant. In conclusion, FI is mediated by GFD adherence to HRQoL. Moreover, a significant total effect relation was found between HRQoL and both FI and GFD adherence, suggesting that lowering symptoms and complications associated with CD may reduce the impact of FI on HRQoL.

Intelligent tongue diagnosis model for gastrointestinal diseases based on tongue images

BackgroundCurrently, the diagnosis of gastrointestinal diseases relies heavily on electronic endoscopy, which is not suitable for all individuals and insufficient for dynamic patient monitoring. Therefore, there is an urgent need for a convenient and noninvasive examination method to enhance the diagnosis and monitoring of gastrointestinal diseases. MethodsSince the tongue is a significant reflection of the digestive system and closely associated with gastrointestinal diseases, our study aims to develop a diagnostic framework based on tongue features. We have collected a dataset of 2,167 tongue coating images from 949 consecutive patients, including 905 images from healthy individuals and 1,262 images from patients with various gastrointestinal conditions. Notably, each patient sample may represent distinct gastrointestinal diseases. This study introduces a novel approach to information fusion detection, integrating hand-crafted and auto-encoded features, alongside disease detection employing Squeeze and Excitation (SE) and Slot attention mechanisms. These two branches respectively analyze image feature and spatial position information when utilizing tongue images for diagnosing gastrointestinal diseases. The amalgamation of predictions from both aspects yields the final detection outcome. ResultsFor both healthy and diseased cohorts, the optimal classification metrics were achieved: AUC = 0.886, ACC = 0.849, and TPR = 0.965, indicating satisfactory performance. Notably, our framework demonstrated promising results in detecting five common gastrointestinal diseases: Helicobacter pylori infection, bile reflux, reflux esophagitis, gastric erosion, and duodenal erosion. Ablation experiments underscored the efficacy of mixed features in multi-color space, showcasing an increase in AUC and ACC by 13.48 % and 12.05 % respectively. Furthermore, the attention mechanism, by focusing on the middle region of tongue images, contributed to a 6.12 % increase in AUC and a 6.35 % increase in ACC. ConclusionsIn this study, we successfully develop and validate a diagnosis framework for gastrointestinal diseases based on tongue image features. By utilizing tongue images, we achieve intelligent diagnosis of gastrointestinal diseases, establishing tongue diagnosis as a convenient, cost-effective, and noninvasive method for diagnosing and screening gastrointestinal diseases.

Glioblastoma phenotypic and genetic heterogeneity, comparison of MRI and PET/CT parameters with tumor molecular genetic characteristics

Glioblastoma (GB) is an extremely heterogeneous tumor, which is caused by genomic instability, high growth rate, and neovascularization. Molecular and genetic characteristics of GB play a major role in the prognosis of the disease, which is reflected in the new WHO classification of CNS tumors from 2021. Purpose of this research is comparison MRI parameters (ADC CBF), metabolic activity on 11C-MET PET/СT with glioblastoma genetic profile. 40 patients (age 55±12 years, sex M/F = 31/9) with newly diagnosed GB were examined by MRI with assessment of diffusion parameters (ADCmin) and ASL perfusion (CBFmax) and 11С-МЕТ PET/CT with the calculation of tumor to normal index (METmax). Since these VOI (1cm3) did not always coincide, it was decided to measure all parameters in each VOI on all image maps (PMOD automatic contour transfer). A total of 9 measurements were obtained for each patient: METmax, METcbf, METadc; ADCmin, ADCmet, ADCcbf; CBFmax, CBFmet, CBFadc. Comparative and correlation analysis was carried out both in the total GB group and separately in the groups MGMT+/and EGFR+/and different Ki67 levels (cut-off 20%). In results 45% of patients had CBFmax, ADCmin and METmax mismatch. Significant correlations were found in the METmax VOI between METmaxADCmet (Rs = -0.37) and METcbfADCcbf (Rs = -0.05). CBFmax and CBFmet correlated with Ki67 (Rs = 0.38 and Rs = 0.48, respectively) and increased in Ki67 20% GB group. GB genetic subgroup analysis showed: MGMT+ had significantly higher ADCmin1.01 (10-3 mm2/sec), Se = 78%, Sp = 74%, AUC = 0.77, it means that cells were more tightly packed. In METmax VOI, METmax was negatively correlated with ADCmet (Rs = -0.72) and CBFmet was positively correlated with Ki-67 (Rs = 0.89); EGFR+ tumors had significantly higher METmax 3.29 (Se = 88%, Sp = 70%, AUC = 0.82), that was negatively correlated with ADCmet (Rs = -0.85). In case when Ki67 20% GB demonstrated significantly higher CBFmax 108.177ml/100/min (Se = 70%, Sp = 94%, AUC 0.75) and a strong negative correlation between METmax and ADCmet, (Rs = -0,65) in METmax VOI. Our study shown that CBFmax, ADCmin and METmax localization coincide in 45% of cases, which proves the presence of variety in the structure and functional activity of different areas of GB. The correlation of MGMT methylation and ADC (ADCmin 1.01 (10-3 mm2/sec), Se = 78%, Sp = 74%, AUC = 0.77) confirms the recent studies results of this tumor subtype lower needs of the new membranes construction, that’s due to the inhibition of the mechanism of the DNA repair system. EGFR amplification presence in our patient sample was associated with a significant higher MET metabolism (МЕTmax 3.29, Se = 88%, Sp = 70%, AUC = 0.82) and correlated with height level of Ki67 (Rs = -0.85), confirming the fact of GB cells amino acids increased consumption for membrane synthesis. The obtained correlations MET with ADC and the absence of those with CBF, confirms the dependence glioma methionine metabolism of the new cell membranes building, rather than on neovascularization. Revealed mismatch of MRI and PET/CT parameters confirmed GB structure heterogeneity phenomenon, as well as their significant differences in various genetic status GB subgroups.

Nano fuzzy alarming system for blood transfusion requirement detection in cancer using deep learning

Periodic blood transfusion is a need in cancer patients in which the disease process as well as the chemotherapy can disrupt the natural production of blood cells. However, there are concerns about blood transfusion side effects, the cost, and the availability of donated blood. Therefore, predicting the timely requirement for blood transfusion considering patient variability is a need, and here for the first-time deal with this issue in blood cancer using in vivo data. First, a data set of 98 samples of blood cancer patients including 61 features of demographic, clinical, and laboratory data are collected. After performing multivariate analysis and the approval of an expert, effective parameters are derived. Then using a deep recurrent neural network, a system is presented to predict a need for packed red blood cell transfusion. Here, we use a Long Short-Term Memory (LSTM) neural network for modeling and the cross-validation technique with 5 layers for validation of the model along with comparing the result with networking and non-networking machine learning algorithms including bidirectional LSTM, AdaBoost, bagging decision tree based, bagging KNeighbors, and Multi-Layer Perceptron (MLP). Results show the LSTM outperforms the other methods. Then, using the swarm of fuzzy bioinspired nanomachines and the most effective parameters of Hgb, PaO2, and pH, we propose a feasibility study on nano fuzzy alarming system (NFABT) for blood transfusion requirements. Alarming decisions using the Internet of Things (IoT) gateway are delivered to the physician for performing medical actions. Also, NFABT is considered a real-time non-invasive AI-based hemoglobin monitoring and alarming method. Results show the merits of the proposed method.

Nano fuzzy alarming system for blood transfusion requirement detection in cancer using deep learning

Periodic blood transfusion is a need in cancer patients in which the disease process as well as the chemotherapy can disrupt the natural production of blood cells. However, there are concerns about blood transfusion side effects, the cost, and the availability of donated blood. Therefore, predicting the timely requirement for blood transfusion considering patient variability is a need, and here for the first-time deal with this issue in blood cancer using in vivo data. First, a data set of 98 samples of blood cancer patients including 61 features of demographic, clinical, and laboratory data are collected. After performing multivariate analysis and the approval of an expert, effective parameters are derived. Then using a deep recurrent neural network, a system is presented to predict a need for packed red blood cell transfusion. Here, we use a Long Short-Term Memory (LSTM) neural network for modeling and the cross-validation technique with 5 layers for validation of the model along with comparing the result with networking and non-networking machine learning algorithms including bidirectional LSTM, AdaBoost, bagging decision tree based, bagging KNeighbors, and Multi-Layer Perceptron (MLP). Results show the LSTM outperforms the other methods. Then, using the swarm of fuzzy bioinspired nanomachines and the most effective parameters of Hgb, PaO2, and pH, we propose a feasibility study on nano fuzzy alarming system (NFABT) for blood transfusion requirements. Alarming decisions using the Internet of Things (IoT) gateway are delivered to the physician for performing medical actions. Also, NFABT is considered a real-time non-invasive AI-based hemoglobin monitoring and alarming method. Results show the merits of the proposed method.

Trauma patients have reduced ex vivo flow-dependent platelet hemostatic capacity in a microfluidic model of vessel injury.

Trauma is the leading cause of death in individuals up to 45 years of age. Alterations in platelet function are a critical component of trauma-induced coagulopathy (TIC), yet these changes and the potential resulting dysfunction is incompletely understood. The lack of clinical assays available to explore platelet function in this patient population has hindered detailed understanding of the role of platelets in TIC. The objective of this study was to assess trauma patient ex vivo flow-dependent platelet hemostatic capacity in a microfluidic model. We hypothesized that trauma patients would have flow-regime dependent alterations in platelet function. Blood was collected from trauma patients with level I activations (N = 34) within 60 min of hospital arrival, as well as healthy volunteer controls (N = 10). Samples were perfused through a microfluidic model of injury at venous and arterial shear rates, and a subset of experiments were performed after incubation with fluorescent anti-CD41 to quantify platelets. Complete blood counts were performed as well as plasma-based assays to quantify coagulation times, fibrinogen, and von Willebrand factor (VWF). Exploratory correlation analyses were employed to identify relationships with microfluidic hemostatic parameters. Trauma patients had increased microfluidic bleeding times compared to healthy controls. While trauma patient samples were able to deposit a substantial amount of clot in the model injury site, the platelet contribution to microfluidic hemostasis was attenuated. Trauma patients had largely normal hematology and plasma-based coagulation times, yet had elevated D-Dimer and VWF. Venous microfluidic bleeding time negatively correlated with VWF, D-Dimer, and mean platelet volume (MPV), while arterial microfluidic bleeding time positively correlated with oxygenation. Arterial clot growth rate negatively correlated with red cell count, and positively with mean corpuscular volume (MCV). We observed changes in clot composition in trauma patient samples reflected by significantly diminished platelet contribution, which resulted in reduced hemostatic function in a microfluidic model of vessel injury. We observed a reduction in platelet clot contribution under both venous and arterial flow ex vivo in trauma patient samples. While our population was heterogenous and had relatively mild injury severity, microfluidic hemostatic parameters correlated with different patient-specific data depending on the flow setting, indicating potentially differential mechanistic pathways contributing to platelet hemostatic capacity in the context of TIC. These data were generated with the goal of identifying key features of platelet dysfunction in bleeding trauma patients under conditions of flow and to determine if these features correlate with clinically available metrics, thus providing preliminary surrogate markers of physiological platelet dysfunction to be further studied across larger cohorts. Future studies will continue to explore those relationships and further define mechanisms of TIC and their relationship with patient outcomes.

Immune-checkpoint inhibitor-mediated myocarditis: CTLA4, PD1 and LAG3 in the heart.

Immune-checkpoint inhibitors (ICIs) have revolutionized oncology, with nearly 50% of all patients with cancer eligible for treatment with ICIs. However, patients on ICI therapy are at risk for immune-related toxicities that can affect any organ. Inflammation of the heart muscle, known as myocarditis, resulting from ICI targeting cytotoxic Tlymphocyte-associated antigen 4 (CTLA4), programmed cell death protein 1 (PD1) and PD1 ligand 1 (PDL1) is an infrequent but potentially fatal complication. ICI-mediated myocarditis (ICI-myocarditis) is a growing clinical entity given the widespread use of ICIs, its increased clinical recognition and growing use of combination ICI treatment, a well-documented risk factor for ICI-myocarditis. In this Review, we approach ICI-myocarditis from a basic and mechanistic perspective, synthesizing the recent data from both preclinical models and patient samples. We posit that mechanistic understanding of the fundamental biology of immune-checkpoint molecules may yield new insights into disease processes, which will enable improvement in diagnostic and therapeutic approaches. The syndrome of ICI-myocarditis is novel, and our understanding of immune checkpoints in the heart is in its nascency. Yet, investigations into the pathophysiology will inform better patient risk stratification, improved diagnostics and precision-based therapies for patients.

Immune-checkpoint inhibitor-mediated myocarditis: CTLA4, PD1 and LAG3 in the heart.

Immune-checkpoint inhibitors (ICIs) have revolutionized oncology, with nearly 50% of all patients with cancer eligible for treatment with ICIs. However, patients on ICI therapy are at risk for immune-related toxicities that can affect any organ. Inflammation of the heart muscle, known as myocarditis, resulting from ICI targeting cytotoxic Tlymphocyte-associated antigen 4 (CTLA4), programmed cell death protein 1 (PD1) and PD1 ligand 1 (PDL1) is an infrequent but potentially fatal complication. ICI-mediated myocarditis (ICI-myocarditis) is a growing clinical entity given the widespread use of ICIs, its increased clinical recognition and growing use of combination ICI treatment, a well-documented risk factor for ICI-myocarditis. In this Review, we approach ICI-myocarditis from a basic and mechanistic perspective, synthesizing the recent data from both preclinical models and patient samples. We posit that mechanistic understanding of the fundamental biology of immune-checkpoint molecules may yield new insights into disease processes, which will enable improvement in diagnostic and therapeutic approaches. The syndrome of ICI-myocarditis is novel, and our understanding of immune checkpoints in the heart is in its nascency. Yet, investigations into the pathophysiology will inform better patient risk stratification, improved diagnostics and precision-based therapies for patients.

Identifying Health Literacy Strengths and Needs Among Jordanian Acute Myocardial Infarction Patients.

Acute myocardial infarction is a significant health issue, particularly in Jordan where ischemic heart disease is the leading cause of death. Effective management of acute myocardial infarction is essential to mitigate its consequences. Although health literacy is crucial for the successful management of acute myocardial infarction, research about the strengths and needs of health literacy among acute myocardial infarction patients is still limited. This study was conducted to identify the health literacy strengths and needs of Jordanian acute myocardial infarction patients using cluster analysis. A cross-sectional design was used to conduct this study in a sample of acute myocardial infarction patients in Jordan (N = 114). A demographics questionnaire and the Health Literacy Questionnaire were used to collect the data. Data analysis was performed using hierarchical cluster analysis using Ward's method. Seven distinct clusters of acute myocardial infarction patients were identified, each characterized by unique health literacy profiles and sociodemographic characteristics. Cluster 7 had the highest health literacy scores across all nine Health Literacy Questionnaire scales. Sociodemographic factors such as age, education level, and gender influenced health literacy levels, with female, younger, more educated patients exhibiting higher health literacy. Through identifying the specific strengths and needs, this research provides a foundation for developing targeted health literacy interventions for acute myocardial infarction patients. Improving health literacy among acute myocardial infarction patients can enhance their ability to manage their health and potentially reduce the complications associated with acute myocardial infarction.

Understanding Internalized Stigma’s Role in Sex-Specific Suicidal Ideation among Individuals with Bipolar Disorder

Background: The experience of stigma can exert a profound impact on the mental health and well-being of individuals with bipolar disorder (BD). Our study explores which factors of internalized stigma are associated with suicidal ideation and how they differ between the two sexes in a clinical sample of BD patients. Methods: The study follows a cross-sectional study design, employing the Clinical Global Impression for Bipolar Patients (CGI-BP) to evaluate the overall severity of illness and the alteration in patients affected by bipolar disorder, the Internalized Stigma of Mental Illness (ISMI) assessing self-stigma among individuals experiencing mental disorders, and the Columbia Suicide Severity Rating Scale (C-SSRS) identifying and assessing individuals vulnerable to suicide. Descriptive analyses, analysis of variance (ANOVA), and logistic regression analysis were conducted, and 344 BD subjects were recruited. Results: Our ANOVA results revealed a significant association between sex and suicide across ISMI sub-items (p = 0.000). Logistic regression analysis comprised three phases: Discrimination was consistently significant across all phases (p &lt; 0.001), while Alienation and Stereotype emerged as additional predictors of suicide in later phases of the analysis (p &lt; 0.001). Conclusions: Our study contributes to the growing body of literature on internalized stigma, sex, and suicidality among individuals with bipolar disorder. Early intervention programs and prevention strategies are needed.

Understanding Internalized Stigma's Role in Sex-Specific Suicidal Ideation among Individuals with Bipolar Disorder.

Background: The experience of stigma can exert a profound impact on the mental health and well-being of individuals with bipolar disorder (BD). Our study explores which factors of internalized stigma are associated with suicidal ideation and how they differ between the two sexes in a clinical sample of BD patients. Methods: The study follows a cross-sectional study design, employing the Clinical Global Impression for Bipolar Patients (CGI-BP) to evaluate the overall severity of illness and the alteration in patients affected by bipolar disorder, the Internalized Stigma of Mental Illness (ISMI) assessing self-stigma among individuals experiencing mental disorders, and the Columbia Suicide Severity Rating Scale (C-SSRS) identifying and assessing individuals vulnerable to suicide. Descriptive analyses, analysis of variance (ANOVA), and logistic regression analysis were conducted, and 344 BD subjects were recruited. Results: Our ANOVA results revealed a significant association between sex and suicide across ISMI sub-items (p = 0.000). Logistic regression analysis comprised three phases: Discrimination was consistently significant across all phases (p < 0.001), while Alienation and Stereotype emerged as additional predictors of suicide in later phases of the analysis (p < 0.001). Conclusions: Our study contributes to the growing body of literature on internalized stigma, sex, and suicidality among individuals with bipolar disorder. Early intervention programs and prevention strategies are needed.