Clinical Management Research Articles

Holodiastolic Flow Reversal in the Descending Aorta: A Marker of Concomitant Acute Myocarditis and Aortitis in Children-A Case Series.

This case series describes five pediatric patients with acute myocarditis presenting holodiastolic flow reversal in the descending aorta despite the absence of aortic run-off lesions. This Doppler finding highlights the role of aortitis or Concomitant Acute Myocarditis and Aortitis (CAMA). Cardiac magnetic resonance imaging (MRI) with late gadolinium enhancement (LGE) confirmed myocarditis in three cases. Key findings included poor response to exogenous catecholamines, elevated troponin I, hyponatremia, low vitamin D, and frequent biventricular involvement. Outcomes included one successful cardiac transplantation, one requiring levosimendan, and three fatalities. Low diastolic blood pressure and flow reversal in the descending aorta are critical clues for diagnosing CAMA. Clinical implications, pathophysiology, and management are discussed.

Streamlining data recording through optical character recognition: a prospective multi-center study in intensive care units

BackgroundThe manual entry of data into large patient databases requires significant resources and time. It is possible that a system that is enhanced with the technology of optical character recognition (OCR) can facilitate data entry, reduce data entry errors, and decrease the burden on healthcare personnel.MethodsThis was a prospective multi-center observational study across intensive care units (ICU) in 3 countries. Subjects were critically-ill and required invasive mechanical ventilation and extracorporeal life support. Clinical photos from various medical devices were uploaded using an OCR-enhanced case record form. The degree of data completeness, data accuracy, and time saved in entering data were compared with conventional manual data entry.ResultsThe OCR-based system was developed with 868 photos and validated with 469 photos. In independent validation by 8 untrained personnel involving 1018 data points, the overall data completeness was 98.5% (range 98.2–100%), while the overall data accuracy was 96.9% (range 95.3–100%). It significantly reduced data entry time compared to manual entry (mean reduction 43.9% [range 27.0–1.1%]). The average data entry time needed per patient were 3.4 (range 1.2–5.9) minutes with the OCR-based system, compared with 6.0 (range 2.2–8.1) minutes with manual data entry. Users reported high satisfaction with the tool, with an overall recommendation rate of 4.25 ± 1.04 (maximum of 5).ConclusionAn OCR-based data entry system can effectively and efficiently facilitate data entry into clinical databases, making it a promising tool for future clinical data management. Wider uptake of these systems should be encouraged to better understand their strengths and limitations in both clinical and research settings.

Clinical findings and management of intraocular foreign bodies (IOFB) in third-world country eye hospital

PurposeTo describe the demoFigurey and clinical characteristics of intraocular foreign body as open globe injury type at National Eye Center Cicendo Eye Hospital.MethodsThis descriptive-retrospective study is based on medical records of patients admitted to National Eye Center Cicendo Eye Hospital diagnosed with intraocular foreign bodies from January 2019 to June 2023.ResultsA total of twenty-one cases of ocular trauma specifically intraocular foreign bodies were recorded based on medical records. A total of 20 cases (95.2%) were male. The incidence of 15 cases (71.4%) of trauma in outdoor activities with the whole mechanism (100%) of penetrations. Most cases were referred cases (57.1%). 11 cases had surgery under 24 h prior to trauma (52.4%). The entry site of the foreign body was on the cornea (17 cases, 81%). Metallic foreign bodies account for 16 (76.2%); most locations are found on the retina (71.4%). More than three fourths of patients had single IOFB (76.2%). Visual acuity is mostly present between counting fingers- 0.1 Snellen. Patients showed to have had retinal breaks (61.9%).ConclusionThe majority of IOFB patients were working-age males. The nature of IOFBs is mostly metallic and retained in the posterior segment.

Comparing Comorbidity Indices to Predict Survival After Pediatric Hematopoietic Stem Cell Transplantation for Nonmalignant Disease.

Hematopoietic stem cell transplantation (HCT) is a potentially curative treatment for children with hematological or immunological disorders. However, treatment-related morbidity and mortality remain concerning. Various comorbidity indices are currently used to assess the risk of complications following pediatric HCT. We compared four comorbidity indices to determine which can most accurately estimate the risk of morbidity and mortality in pediatric nonmalignant HCT. We analyzed 308 pediatric allogeneic nonmalignant HCTs performed between January 2010 and December 2022. Four indices were evaluated: hematopoietic stem cell transplantation-specific comorbidity index (HCT-CI), youth nonmalignant hematopoietic stem cell transplantation comorbidity index (ynHCT-CI), simplified ynHCT-CI, and simplified comorbidity index (SCI). The primary outcome was overall survival (OS). The secondary outcome was graft-versus-host disease (GvHD)-free event-free survival (EFS), defined as acute GvHD Grade 3 or 4, extensive chronic GvHD, retransplantation, or death. The area under the receiver operator characteristic curve (AUC) was calculated per index and outcome at 100 days, 1 year, and 2 years post-HCT. For OS, AUC values ranged from 0.611 to 0.755. The simplified ynHCT-CI and ynHCT-CI generally had superior discriminative abilities for OS, although no significant difference was found. For EFS, AUC values were between 0.539 and 0.632. The ynHCT-CI performed best for EFS, with AUC values of the simplified ynHCT-CI marginally lower. The ynHCT-CI significantly outperformed the HCT-CI at 100 days post transplantation (p=0.045). The ynHCT-CI most accurately predicted outcomes after pediatric nonmalignant HCT. We propose the use of ynHCT-CI in future clinical management guidelines in this cohort.

Prioritisation of methods for assessing alcohol use in emergency room settings: findings from a qualitative study.

Limited alcohol-related injury data in hospital settings globally underscores the need for routine monitoring to inform policy formulation for injury prevention, especially in addressing violence and road traffic injuries. COVID-19, and the related alcohol sales bans in South Africa in 2020-2021 brought the impact of alcohol on trauma presenting to health facilities into sharp focus and highlighted the absence of practical, cost-effective and accurate alcohol diagnostic tools in emergency rooms. This qualitative study aims to identify valuable alcohol-related information for stakeholders to inform a validation study of alcohol diagnostics for injury-related trauma. We conducted five virtual Focus Group Discussions (FGDs) with four groups of stakeholders: clinicians (n=9), academics (n=4), hospital and other operational staff (n=6) and policymakers (n=4). FGDs were audio recorded and transcribed verbatim. Coding and thematic analyses were conducted using NVivo version 12. Results highlighted the belief that alcohol places a burden on the healthcare system and plays a significant role in injury causation and mortality. Currently, robust alcohol assessment in emergency rooms is lacking. Despite acknowledging that quantified blood alcohol levels would not change acute clinical management, there was consensus regarding the need-to-know patients' alcohol usage to inform long-term management and broader public health objectives. Findings support plans to validate the efficacy of selected alcohol diagnostic tools in public hospital settings and to further test their feasibility and utility at a national level.

Impact of Glucagon-like Peptide-1 Receptor Agonists on Mental Illness: Evidence from a Mendelian Randomization Study

Emerging evidence suggests that glucagon-like peptide-1 receptor (GLP1R) agonists may have potential benefits for mental illnesses. However, their exact effects remain unclear. This study investigated the causal relationship between glucagon-like peptide-1 receptor agonist (GLP1RA) and the risk of 10 common mental illnesses, including attention deficit and hyperactivity disorder, anorexia nervosa, anxiety disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, post-traumatic stress disorder, schizophrenia, cannabis use disorder, and alcohol use disorder. We selected GLP1RA as the exposure and conducted a Mendelian randomization (MR) analysis. The cis-eQTLs of the drug target gene GLP1R, provided by eQTLGen, were used to simulate the pharmacological effects of GLP1RA. Type 2 diabetes and BMI were included as positive controls. Using data from both the Psychiatric Genomic Consortium and FinnGen, we conducted separate MR analyses for the same disease across these two independent databases. Meta-analysis was used to pool the results. We found genetic evidence suggesting a causal relationship between GLP1RA and a reduced risk of schizophrenia [OR (95% CI) = 0.84 (0.71–0.98), I2 = 0.0%, common effects model]. Further mediation analysis indicated that this effect might be unrelated to improvements in glycemic control but rather mediated by BMI. However, the findings of this study provide insufficient evidence to support a causal relationship between GLP1RA and other mental illnesses. Sensitivity analyses did not reveal any potential bias due to horizontal pleiotropy or heterogeneity in the above results (p > 0.05). This study suggests that genetically proxied activation of glucagon-like peptide-1 receptor is associated with a lower risk of schizophrenia. GLP1R is implicated in schizophrenia pathogenesis, and its agonists may exert potential benefits through weight management. Our study provides useful information for understanding the neuropsychiatric effects of GLP1RA, which may contribute to refining future research designs and guiding clinical management. Moreover, our findings could have significant implications for overweight individuals at high risk of schizophrenia when selecting weight-loss medications. Future research should further investigate the potential mechanisms underlying the relationship between GLP1RA and schizophrenia.

Short- and Long-Term Mortality in Severely Injured Older Trauma Patients: A Retrospective Analysis

Background/Objectives: Older trauma patients experience increased in-hospital mortality due to the physiological challenges associated with aging and injury severity. However, limited data exist on long-term mortality rates beyond hospital discharge, particularly among severely injured elderly trauma patients. Understanding these outcomes is essential for improving clinical management and rehabilitation strategies. The objective of this study was to evaluate cumulative mortality rates (in-hospital, 28-day, 1-year, 2-year, and 3-year) in older trauma patients with an Injury Severity Score (ISS) ≥ 16. Independent risk factors for 1-year mortality were also identified. Methods: This retrospective cohort study included all trauma patients aged ≥ 65 years with ISS ≥ 16 admitted to the Emergency Department of our level 1 trauma center between January 2017 and December 2022. Demographic characteristics, injury patterns (Abbreviated Injury Scale (AIS) scores, ISS), and mortality rates were collected from electronic health records. Patients were stratified into two age groups: 65–80 years and >80 years. Mortality rates were compared with those in the corresponding age groups in the general Swiss population. Statistical analysis included Kaplan–Meier survival curves and logistic regression for identifying risk factors associated with 1-year mortality. Results: A total of 1189 older trauma patients with a mean ISS of 24.3 ± 7.9 were included. The most common injury was severe head trauma (AIS head ≥ 3: 70.6%), followed by chest trauma (AIS chest ≥ 3: 28.2%) and extremity injuries (AIS extremity ≥ 3: 17.4%). The overall in-hospital mortality rate was 10.3%. Mortality rates at 28 days, 1 year, 2 years, and 3 years were 15.8%, 26.5%, 31.5%, and 36.3%, respectively. Age-stratified analysis showed significantly higher mortality rates in patients aged > 80 years compared to the 65- to 80-year group at all post-discharge time points (28-day: 22.6% vs. 11.9%, p < 0.001; 1-year: 39.9% vs. 18.8%, p < 0.001; 2-year: 46.5% vs. 22.8%, p < 0.001; 3-year: 56.4% vs. 24.9%, p < 0.001). Compared to the general Swiss population, we observed significantly higher mortality rates at all measured time points in elderly trauma patients, particularly in those aged over 80 years, with 1-year mortality rates of 39.9% vs. 10% in the general population and 3-year mortality rates of 56.4% vs. 30% in the general population. Independent risk factors for 1-year mortality included advanced age and severe head injury (AIS head ≥ 3, p < 0.001). Conclusions: Severely injured elderly trauma patients face high long-term mortality risks, with 1-year mortality rates reaching 26.5% overall and nearly 40% in patients aged > 80 years. These findings highlight the need for research on tailored, holistic management strategies, including comprehensive in-hospital care, specialized neurorehabilitation, and post-discharge follow-up programs to improve survival and functional recovery in this vulnerable population.

Clinical and Genomic Characterization of Secondary Rectal Cancer After Radiotherapy for Prostate Cancer

Patients treated with radiotherapy (RT) for prostate cancer (PC) have increased risk of secondary rectal cancer (SRC) and more limited treatment options. To assess the tumor molecular profile, clinical characteristics, and oncologic outcomes of SRC after PC and compare them with those of primary rectal cancer (PRC). This case-control study included patients with SRC diagnosed 5 or more years after RT for PC and patients with PRC who were treated at Memorial Sloan Kettering Cancer Center in New York between February 1, 1994, and September 31, 2022. Clinical information and DNA sequencing data were analyzed. Oncologic outcomes were compared between patients with SRC and clinically matched patients with PRC using log-rank tests and Cox proportional hazards regression models. Numerical and categorical variables were compared using the Wilcoxon rank sum test and Fisher exact test, respectively. The analysis included 604 male patients with PRC (71.6%; median age, 55 [IQR, 46-66] years) and 64 male patients with SRC (median age, 78 [IQR, 72-82] years). Patients with SRC had more distal rectum (37 of 63 [58.7%] vs 131 of 581 [22.5%]; P < .001) and anterior rectal wall (20 of 57 [35.1%] vs 67 of 496 [13.5%]; P < .001) tumors, were less likely to receive neoadjuvant treatment (33 of 64 [51.6%] vs 570 of 604 [94.4%]), and had shorter 5-year overall survival (45.7% vs 64.9%; P = .01) and disease-free survival (40.3% vs 71.2%; P = .006) compared with clinically matched patients with PRC. Targeted DNA sequencing data from 31 SRC tumors identified lower mutational burden (median, 4.4 [IQR, 3.2-6.7] per megabase [Mb] vs 5.8 [IQR, 4.4-7.0] per Mb; P = .047), lower frequency of APC alterations (15 [48.4%] vs 432 [79.9%]; P < .001), and higher rates of SMAD4 inactivation (8 [25.8%] vs 54 [10.0%]; P = .01) compared with 541 PRC tumors. Whole-exome sequencing data from 17 SRC tumors identified a higher rate of frameshift deletions compared with 28 PRC tumors (median, 5.0 [IQR, 4.0-9.0] vs 2.5 [IQR, 1.0-4.2] variants; P < .001). In this case-control study, patients with SRC after RT for PC had worse survival and different molecular profiles than patients with PRC. These findings may help improve the clinical management of SRC.

Hereditary Haemorrhagic Cerebrovascular Disease: Implications for Clinical Management.

At present, treatment of hereditary haemorrhagic cerebrovascular disease remains in the symptomatic stage. It is more important to provide strategies for developing rational treatment methods, expanding our understanding with regard to the pathophysiology in the context of familial diseases. In this article, the combined data from the literature on diseases, including familial cerebral cavernous haemangiomas, hereditary cerebral haemorrhage with amyloidosis, familial intracranial aneurysms, cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, were reviewed to manage the haemorrhagic diseases discussed through genetic counselling and early prevention and treatment of these patients and their families, the genetics, pathogenesis, clinical manifestations and treatment. It is important to understand and treat hereditary haemorrhagic cerebrovascular disease through genetic treatment options.

Investigating Delayed Rupture of Flow Diverter-Treated Giant Aneurysm Using Simulated Fluid–Structure Interactions

Giant intracranial aneurysms are frequently treated shortly after discovery due to their increased risk of rupture and commonly symptomatic nature. Among available treatments, flow diverters are often the sole viable option, though they carry a rare but serious risk of delayed post-operative rupture. The underlying mechanisms of these ruptures remain unknown, due to the biomechanical complexity of giant aneurysms and challenges in replicating in vivo hemodynamic conditions within numerical simulation frameworks. This study presents a novel fluid–structure interaction simulation of a giant intracranial aneurysm treated with a flow diverter, based on high-resolution rotational angiography imaging. The resulting hemodynamics are compared to three established delayed-rupture hypotheses involving pressure rises, chaotic flow and autolysis. When considering wall compliance, the analysis reveals a consistent phase shift, dampening in pressure cycles, and an increased aneurysmal flow. These findings highlight the need for revisiting existing hypotheses and provide a foundation for advancing both computational modelling and clinical management strategies for giant intracranial aneurysms.

Comparison of the Point-Of-Care Coagulation Device Quantra With the TEG-5000 for Congenital Cardiac Surgery-A Pilot Study.

Congenital cardiac surgery with cardiopulmonary bypass (CPB) alters patients' hemostasis. Viscoelastic testing is a modern technology identifying coagulation abnormalities. A new device, the Quantra-QPlus System (HemoSonics LLC, Charlottesville, VA) has not yet been investigated during congenital cardiac surgery. This prospective observational pilot study investigated the correlation of Quantra and TEG-5000 in children undergoing cardiac surgery at Stanford Medicine Children's Health (SMCH). Patients (0-8 years) undergoing cardiac surgery with CPB were included after parental consent. Per standard of care at SMCH, a TEG-5000 and Clauss Fibrinogen were measured on CPB during rewarming (T1) as well as after administration of blood components and coagulation factors (T2). For the study purpose, Quantra measurements were performed simultaneously at T1 and T2. Quantra results were correlated with TEG-5000 results and Clauss Fibrinogen. In addition, the agreement for normal and abnormal results was calculated, and a post hoc simulated transfusion algorithm using TEG-5000 and Quantra thresholds was compared to patients' clinical management. From October 2022 to May 2023, 289 congenital cardiac surgeries were performed, 97 met inclusion criteria, 63 patients were consented, and 40 patients (12 females [30%] 28 males [70%]) included in the analysis. Median age and weight were 0.5 years and 6.33 kg, respectively. Correlation of Quantra/Clauss Fibrinogen was "moderate" and correlation of Quantra/TEG-5000 parameters ranged from "weak" to "very strong" Levels of agreement ranged from 15% to 97%. The post hoc simulated transfusion algorithm for TEG-5000 showed an agreement of 56% for FFP, 56% for Fibrinogen, and 95% for platelets and for Quantra, it was 40% for FFP, 87.5% for Fibrinogen, and 98% for platelets. Despite weaknesses in correlation and agreement both VET devices suggested appropriate coagulation management based on the simulated transfusion algorithms. Quantra and TEG-5000 are not interchangeable and none of them can be considered as "the gold standard". NTC 05295693.

A deep learning model based on chest CT to predict benign and malignant breast masses and axillary lymph node metastasis.

Differentiating early-stage breast cancer from benign breast masses is crucial for radiologists. Additionally, accurately assessing axillary lymph node metastasis (ALNM) plays a significant role in clinical management and prognosis for breast cancer patients. Chest computed tomography (CT) is a commonly used imaging modality in physical and preoperative evaluations. This study aims to develop a deep learning model based on chest CT imaging to improve the preliminary assessment of breast lesions, potentially reducing the need for costly follow-up procedures such as magnetic resonance imaging (MRI) or positron emission tomography-CT and alleviating the financial and emotional burden on patients. We retrospectively collected chest CT images from 482 patients with breast masses, classifying them as benign (n = 224) or malignant (n = 258) based on pathological findings. The malignant group was further categorized into ALNM-positive (n = 91) and ALNM-negative (n = 167) subgroups. Patients were randomly divided into training, validation, and test sets in an 8:1:1 ratio, with the test set excluded from model development. All patients underwent non-contrast chest CT before surgery. After preprocessing the images through cropping, scaling, and standardization, we applied ResNet-34, ResNet-50, and ResNet-101 architectures to differentiate between benign and malignant masses and to assess ALNM. Model performance was evaluated using sensitivity, specificity, accuracy, receiver operating characteristic (ROC) curves, and the area under the curve (AUC). The ResNet models effectively distinguished benign from malignant masses, with ResNet-101 achieving the highest performance (AUC: 0.964; 95% CI: 0.948-0.981). It also demonstrated excellent predictive capability for ALNM (AUC: 0.951; 95% CI: 0.926-0.975). In conclusion, these deep learning models show strong diagnostic potential for both breast mass classification and ALNM prediction, offering a valuable tool for improving clinical decision-making.

Convergence of Psoriatic Arthritis and Hyperuricemia: A Review of Emerging Data from This New Concept Called “Psout”

This review examines the concept of “psout”, an overlap syndrome of hyperuricemic psoriatic arthritis (HU-PsA) and co-existing gout and PsA. The manuscript explores its epidemiology, pathophysiology, clinical implications, and treatment strategies, focusing on emerging data since its first description in 2020. The psout concept is sustained by shared inflammatory and metabolic pathways between gout and PsA, contributing to a broad spectrum of phenotypes and moderate-to-severe clinical manifestations. Monosodium urate crystals and hyperuricemia are central to this overlap, influencing cytokine production, keratinocyte activation, and immune responses, being able to activate both innate and acquired immunity. Clinical management is complex due to diagnostic challenges and therapeutic considerations not yet implemented in international recommendations. Emerging data from clinical trials underscore the significance of hyperuricemia in worsening PsA outcomes while highlighting the potential of personalized treatments. Future research into shared pathophysiological mechanisms, the accurate description of the diversity of phenotypes, innovative imaging assessments, and therapeutic strategies could provide insights into the interplay of these two conditions and enhance patient outcomes.

Incidence, Management, and Outcomes of Intracranial Hemorrhage After Heart, Lung, and Liver Transplantation

BACKGROUND AND OBJECTIVES: Intracranial hemorrhage (ICH) after organ transplantation presents significant challenges in clinical management. We investigated the incidence, risk factors, and long-term outcomes of ICH after heart, liver, or lung transplantation. METHODS: We retrospectively reviewed patients who experienced ICH within 3 months post-transplantation between April 2017 and June 2023 at our institution. Data were curated from review of medical records and radiographic data. Functional status was assessed using the modified Rankin score (mRS) and Utility Weighted mRS (UWmRS) at 90 days and 1-year posthemorrhage. Statistical analyses included survival analysis, logistic and linear regressions. RESULTS: Among 2223 transplant recipients, 28 (1.3%) experienced ICH within 3 months post-transplant (mean age 56, 39% female patients). The primary hemorrhage types were intraparenchymal (43%), subdural (28.5%), and subarachnoid (28.5%). The transplant types were heart (54%), liver (39%), and lung (7%). The median preadmission mRS was 2. At 90 days post-ICH, the median mRS was 4, with an average UWmRS of 0.42; at 1 year, the median mRS was 5, and the UWmRS dropped to 0.11. Mortality was 39% at 90 days and 1-year post-ICH. Rehemorrhage occurred in 14% of patients. Higher ICH score was associated with significantly higher mRS scores at 90 days post-ICH indicating worse outcomes (adjusted estimate = 3.1, 95% CI 0.3-8.5—0.38, P = .031). CONCLUSION: ICH within 3 months of organ transplantation is associated with high morbidity and mortality. Early identification of high-risk patients and tailored management strategies are crucial for improving outcomes in this population.

Analyzing the landscape of coeliac crisis in adult and paediatric populations: A systematic review and meta-analysis.

Analyzing the landscape of coeliac crisis in adult and paediatric populations: A systematic review and meta-analysis.

A Stepwise decision tree model for differential diagnosis of Kimura’s disease in the head and neck

ObjectivesThis study aims to differentiate Kimura’s disease (KD) from Sjogren’s syndrome with mucosa-associated lymphoid tissue lymphoma (SS&MALT), neurofibromatosis (NF), and lymphoma in the head and neck by using a stepwise decision tree approach.Materials and methodsA retrospective analysis of 202 patients with pathologically confirmed KD, SS&MALT, NF, or lymphoma was conducted. Demographic and magnetic resonance imaging (MRI) data were collected, with qualitative features (e.g., skin thickening, lesion morphology, lymphadenopathy, MRI signal intensity) and quantitative variables (e.g., age, lesion size, apparent diffusion coefficients (ADCs), wash-in rate, time to peak (TTP), time-signal intensity curve (TIC) patterns) examined. A stepwise decision-tree model using the classification and regression trees (CART) algorithm was developed to aid in the differential diagnosis of KD in the head and neck. The model’s diagnostic accuracy and misclassification risk were assessed to evaluate its reliability and effectiveness.ResultsKey characteristics for KD included male predominance (91.7%), frequent lymphadenopathy (86.1%), and skin thickening (72.2%). Primary lesions of NF typically exhibited higher ADCs compared to those of KD, SS&MALT, and lymphoma. In lymphadenopathy, however, unique ADC patterns were observed: in KD, the ADCs of lymphadenopathy were lower than those of primary lesions, whereas in lymphoma, the ADCs of lymphadenopathy were comparable to those of primary lesions. Predictors for distinguishing KD included lesion’s location, ADCs, lymphadenopathy, and sizes (all p < 0.001). The decision-tree model achieved an impressive 99.0% accuracy in the differential diagnosis across the overall cohort, with a 10-fold cross-validated misclassification risk of 0.079 ± 0.024.ConclusionThe stepwise decision tree model, based on MRI features, showed high accuracy in differentiating KD from other head and neck diseases, offering a reliable diagnostic tool in clinical practice.Clinical relevanceKD is characterized by male predominance, skin thickening, and high incidence of lymphadenopathy. ADCs and TIC patterns are distinguishable in differentiating KD from SS&MALT, NF, and lymphoma in the head and neck. The decision tree model enhances the understanding of KD imaging features and facilitates accurate KD diagnosis, offering an easily accessible and convenient diagnostic tool for radiologists and physicians in daily practice and guiding tailored clinical management plans for affected patients.Clinical trial numberNot applicable.

Guidelines on the clinical management of neonatal hyperbilirubinemia (2025)

Guidelines on the clinical management of neonatal hyperbilirubinemia (2025)

Modulation of Fatty Acid Metabolism via Lactate-HCA1 Signaling: Potential Therapeutic Implications.

The lactate/HCA1 signaling pathway has emerged as a promising target for the clinical management of metabolic diseases, given its regulatory effects on triglyceride turnover and mobilization. However, the differential roles of this pathway in adipose tissue, skeletal muscle, and the liver raise important questions about whether its activation or inhibition would yield the most favorable outcomes. In adipose tissue, HCA1 activation suppresses lipolysis, while in skeletal muscle, recent evidence suggests that lactate may bypass HCA1 to directly enhance mitochondrial fatty acid oxidation. In the liver, HCA1 activation has been implicated in promoting lipid oxidation, offering potential therapeutic implications. This perspective also explores the potential of the lactate/HCA1 pathway to mediate systemic adaptations induced by exercise training, including enhanced mitochondrial capacity and metabolic flexibility. These insights underscore the pathway's relevance for both metabolic health and exercise physiology. However, the current understanding of the lactate/HCA1 pathway remains incomplete, with critical gaps in knowledge regarding its role in underrepresented populations and the molecular mechanisms underlying its tissue-specific effects. Addressing these limitations will be essential for refining the therapeutic and clinical applications of this pathway.

Development and validation of an immune signature-based risk model for prognostic assessment in melanoma

Melanoma is a highly invasive malignancy with poor prognoses in advanced stages. Developing a risk model that can accurately assess prognosis and guide personalized treatment is crucial for improving the clinical management of melanoma. This study aims to develop and validate an immune-based prognostic risk model for melanoma through comprehensive bioinformatics analysis. We collected transcriptomic data from multiple public databases and identified 9 immune features significantly associated with prognosis using single-sample Gene Set Enrichment Analysis (ssGSEA) and Cox regression. These features were utilized to construct the risk model, which was subsequently validated using relevant bulk transcriptomic datasets and single-cell transcriptomic datasets from the GEO database, encompassing diverse patient populations and sample types. The model effectively stratified patients into high-risk and low-risk groups with distinct survival outcomes. Further analysis revealed significant associations between the risk model and genomic heterogeneity indicators, such as tumor mutational burden (TMB), loss of heterozygosity (LOH), and immune checkpoint gene expression. The model robustness was confirmed using single-cell transcriptomic data, highlighting key genes with potential therapeutic relevance. Our findings provide a reliable prognostic tool and novel insights for personalized melanoma treatment, emphasizing the need for further clinical validation.

Over-integration of visual network in major depressive disorder and its association with gene expression profiles

Major depressive disorder (MDD) is a common psychiatric condition associated with aberrant functional connectivity in large-scale brain networks. However, it is unclear how the network dysfunction is characterized by imbalance or derangement of network modular interaction in MDD patients and whether this disruption is associated with gene expression profiles. We included 262 MDD patients and 297 healthy controls, embarking on a comprehensive analysis of intrinsic brain activity using resting-state functional magnetic resonance imaging (R-fMRI). We assessed brain network integration by calculating the Participation Coefficient (PC) and conducted an analysis of intra- and inter-modular connections to reveal the dysconnectivity patterns underlying abnormal PC manifestations. Besides, we explored the potential relationship between the above graph theory measures and clinical symptoms severity in MDD. Finally, we sought to uncover the association between aberrant graph theory measures and postmortem gene expression data sourced from the Allen Human Brain Atlas (AHBA). Relative to the controls, alterations in systemic functional connectivity were observed in MDD patients. Specifically, increased PC within the bilateral visual network (VIS) was found, accompanied by elevated functional connectivities (FCs) between VIS and both higher-order networks and Limbic network (Limbic), contrasted by diminished FCs within the VIS and between the VIS and the sensorimotor network (SMN). The clinical correlations indicated positive associations between inter-VIS FCs and depression symptom, whereas negative correlations were noted between intra-VIS FCs with depression symptom and cognitive disfunction. The transcriptional profiles explained 21–23.5% variance of the altered brain network system dysconnectivity pattern, with the most correlated genes enriched in trans-synaptic signaling and ion transport regulation. These results highlight the modular connectome dysfunctions characteristic of MDD and its linkage with gene expression profiles and clinical symptomatology, providing insight into the neurobiological underpinnings and holding potential implications for clinical management and therapeutic interventions in MDD.