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Advances in non‐germ cell tumours of the testis: focus on new molecular developments in sex cord‐stromal tumours
No full textTesticular sex cord-stromal tumours (TSCSTs) represent ~4%-8% of all testicular neoplasms. Most show a Leydig or Sertoli cell phenotype and exhibit benign clinical behaviour. However, a subset of ~10% is malignant and clinically problematic, as TGCTs do not respond to systemic therapy. Classification of TSCSTs has relied on morphology, with several entities being defined based on their resemblance to more common ovarian counterparts (e.g. granulosa cell tumours). In recent years, multiple clinicopathologic and molecular studies have improved our understanding of the mechanisms that underlie pathogenesis and progression in TSCSTs, providing data that can be useful to refine classification and prognostication. In this review, we summarise the major recent advances in TSCSTs, focusing on molecular alterations and biomarkers relevant for diagnosis, classification and prognosis
Core-Periphery Principle Guided State Space Model for Functional Connectome Classification
No full textUnderstanding the organization of human brain networks has become a central focus in neuroscience, particularly in the study of functional connectivity, which plays a crucial role in diagnosing neurological disorders. Advances in functional magnetic resonance imaging and machine learning techniques have significantly improved brain network analysis. However, traditional machine learning approaches struggle to capture the complex relationships between brain regions, while deep learning methods, particularly Transformer-based models, face computational challenges due to their quadratic complexity in long-sequence modeling. To address these limitations, we propose a Core-Periphery State-Space Model (CP-SSM), an innovative framework for functional connectome classification. Specifically, we introduce Mamba, a selective state-space model with linear complexity, to effectively capture long-range dependencies in functional brain networks. Furthermore, inspired by the core-periphery (CP) organization, a fundamental characteristic of brain networks that enhances efficient information transmission, we design CP-MoE, a CP-guided Mixture-of-Experts that improves the representation learning of brain connectivity patterns. We evaluate CP-SSM on two benchmark fMRI datasets: ABIDE and ADNI. Experimental results demonstrate that CP-SSM surpasses Transformer-based models in classification performance while significantly reducing computational complexity. These findings highlight the effectiveness and efficiency of CP-SSM in modeling brain functional connectivity, offering a promising direction for neuroimaging-based neurological disease diagnosis. Our code is available at https://github.com/m1nhengChen/cpssm
Child Behavioral Scores Correlate With Prenatal Tobacco and Marijuana Exposure, Sociodemographic Variables and Interactions of Default Mode and Dorsal Attention Networks
No full textIntroduction: Prenatal substance exposure is an increasing problem that has been linked to multiple neurodevelopmental impairments and alterations to brain functional connectivity.
Methods: Behavioral scores and functional network correlation data were obtained from the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study. First, behavioral scores based on the child behavioral checklist were tested for associations with prenatal exposure to several substances along with demographic data. Then differences in resting-state functional networks were assessed based on prenatal substance exposure. Third, we assessed the impact of resting-state functional networks on behavioral scores. A linear regression was used for all these analyses, and a false discovery rate < 0.05 was considered significant.
Results: Based on the selection criteria, 6674 subjects were included in the analysis. Prenatal tobacco exposure (PTE), prenatal marijuana exposure, household income, and food insecurity were associated with worse behavioral scores. Additionally, PTE was significantly associated with increased connectivity between the default mode network (DMN) and dorsal attention network (DAN) and decreased intra-network connectivity within the DAN. Finally, there were five CBCL scales that were associated with differences in network connectivity.
Conclusion: Taken together, these results suggest PTE to be associated with multiple functional networks, including those associated with several CBCL scales
Craniofacial Keloid Management Using Post-Excisional Adjuvant Brachytherapy: A Case Report
No full textIntroduction: Keloids are fibroproliferative scars that that can range from mildly abnormal wound healing to significant and excessive outgrowth of skin beyond the area of the wound. They may be associated with microtrauma, and surgery is a well-recognized risk factor in patients with predisposition keloid scars formation. Treatment options can range from minimally invasive medical therapy to surgical excision of the keloid. Methods: In this paper, we present an interesting case of craniofacial keloid likely secondary to microtrauma, treated with surgical excision, split thickness skin graft, and adjuvant brachytherapy. Given that keloid secondary to surgical wounds tend to most commonly occur at the skin edges, brachytherapy was applied at the wound margins in addition to the wound bed to reduce the risk of keloids recurrence. Results: Post-operative results at 2 years demonstrated no recurrence in the treated area, thus decreasing the overall keloid burden in the patient. In addition, patient reported high overall satisfaction with the outcomes. Conclusion: This paper demonstrated that brachytherapy can be an effective adjunct treatment following excision of keloid scars, with no evidence of long-term recurrence
A Novel Multimodal Deep Image Analysis Model for Predicting Extraction/Non‐Extraction Decision
No full textObjective: This study aimed to develop a deep learning model classifier capable of predicting the extraction/non-extraction binary decision using lateral cephalometric radiographs (LCRs) and intraoral scans (IOS) to serve as an additional decision-support tool for orthodontists.
Materials and methods: The dataset was composed of LCRs and IOS from 617 patients (mean age: 18.2, 63.5% female) treated at the Indiana University School of Dentistry. Subjects were categorised into two groups: extraction (192) and non-extraction (425). Two sets of features were extracted from IOS: traditional arch measurements and novel tooth spatial features. For LCRs, features were derived using CephNet-based landmark detection (Land), a convolutional autoencoder (AE), and the dimensionality was reduced using Principal Component Analysis (PCA). Models were evaluated using accuracy, sensitivity, specificity, positive predictive value (PPV or precision), negative predictive value (NPV), positive likelihood ratio (LR+), negative likelihood ratio (LR-), and F1 score.
Results: IOS + Land model achieved the highest overall accuracy (77%) and F1 score (0.62), with strong specificity (83%) and PPV (62%). In contrast, the Land model yielded the highest sensitivity (82%), but at the cost of lower specificity (57%). McNemar's test revealed that the AE model was significantly less accurate than IOS + AE (p = 0.048), IOS + Land (p = 0.006), and IOS + AE + Land (p = 0.005).
Conclusion: Deep learning models can predict the extraction/non-extraction decision using IOS and LCRs with high accuracy and diagnostic performance. Multimodal approaches, particularly those integrating IOS with cephalometric landmarks, demonstrate superior accuracy, sensitivity, and specificity compared to single-modality models
Psychological Comorbidity in Patients Presenting to the Emergency Department With Low‐Risk Chest Pain and Anxiety
No full textObjective: Low-risk chest pain (LRCP) is one of the most common conditions presenting in the emergency department (ED) and is strongly associated with anxiety. The purpose of this study is to determine the prevalence of other psychological comorbidities and clinical factors associated with severe anxiety in LRCP.
Methods: Baseline data is analyzed from the PACER trial comparing the effectiveness of two telehealth interventions for LRCP patients with anxiety. Key eligibility criteria are a HEART score < 7 and either a GAD-7 anxiety score ≥ 8 or a positive PHQ screener for panic disorder. Psychological comorbidity measures included the Patient Health Questionnaire 8-item (PHQ-8) depression scale, the PHQ-14 somatization scale, the Primary Care Posttraumatic Stress Disorder Screen, the Sheehan Disability Scale, and the General Self-Efficacy Scale. Multivariable modeling is used to determine factors associated with severe anxiety.
Results: The 375 patients had a mean age of 39.9; 70.9% were women; 62.9% were White, 32.6% Black, and 4.5% other race. The majority (75%) screened positive for panic disorder, and 42% of participants had severe anxiety (GAD-7 ≥ 15). Non-anxiety psychological comorbidity was very high; the proportion of patients exceeding scale cut points was 58% for depression, 57% for PTSD, 52% for somatization, 59% for high disability, and 31% for low self-efficacy; each was significantly associated with severe anxiety on univariable analysis. Four patient characteristics were independently associated with severe anxiety in multivariable models: odds ratios (95% CI) were 2.7 (1.5-4.9) for depression, 2.3 (1.4-3.9) for low self-efficacy, 2.1 (1.2-3.6) for low education (high school or less), and 1.8 (1.0 to 3.3) for female sex.
Conclusions: LRCP is accompanied not only by anxiety but also by other potentially treatable psychological comorbidities Severe anxiety is more common in individuals with depression, low self-efficacy, lower education, and possibly women
Acute care confidence of PT students: determining the optimal number and type of simulation sessions
No full textP-632. Evaluation of the BIOFIRE® SPOTFIRE® Respiratory/Sore Throat (R/ST) Panel Mini for Use With Anterior Nasal Swab Specimens in the Near-Patient Testing Setting
No full textBackground:
The BIOFIRE® SPOTFIRE® Respiratory/Sore Throat (R/ST) Panel Mini provides results for five viral pathogens commonly responsible for upper respiratory tract infection (Respiratory menu) or one bacterial and four viral pathogens commonly responsible for pharyngitis (Sore Throat menu). For the Respiratory menu, the test is currently indicated for use with nasopharyngeal swab (NPS) specimens in viral transport media. NPS specimens may cause discomfort, which can lead to inconsistent sample quality or refusal to provide a specimen, especially in children. Anterior nasal swab (ANS) specimens are a common specimen type for many diagnostic tests and are more convenient and comfortable to collect. The purpose of this study was to assess the performance of the BIOFIRE SPOTFIRE R/ST Panel Mini when testing ANS specimens in viral transport media.
Methods:
ANS specimens were collected from consented/assented subjects with signs and symptoms of upper respiratory tract infection in near-patient testing settings. Enrollment was conducted between March 2024 and February 2025 at five study sites in the US. Each ANS specimen was tested at the study sites using the BIOFIRE SPOTFIRE R/ST Panel Mini by non-laboratory healthcare professionals. Performance of the BIOFIRE SPOTFIRE R/ST Panel Mini when using ANS specimens was determined by a comparison to FDA-cleared molecular tests.
Results:
A total of 805 ANS specimens were collected and tested with the BIOFIRE SPOTFIRE R/ST Panel Mini. When testing ANS specimens, the BIOFIRE SPOTFIRE R/ST Panel Mini demonstrated an overall positive percent agreement (PPA) of 95.4% and a negative percent agreement (NPA) of 99.1% in comparison to the reference methods.
Conclusion:
The BIOFIRE SPOTFIRE R/ST Panel Mini is a sensitive, specific, and robust test for the rapid detection of five common viral pathogens responsible for upper respiratory tract infection when using ANS specimens in a near-patient testing setting. The convenience, comfort, and patient acceptance of ANS specimens is expected to aid in the effective diagnosis and management of upper respiratory tract infections in near-patient testing settings.
The BIOFIRE SPOTFIRE R/ST Panel Mini is not cleared or approved for use with ANS specimens in viral transport media
Altered natural killer cell function in children with severe malaria
No full textMemory-like natural killer (NK) cells with enhanced antibody-dependent cellular cytotoxicity (ADCC) have correlated with protection from uncomplicated malaria in prior studies. However, the role of NK cells in severe malaria (SM) has not been characterized. In Ugandan sites with moderate and low malaria transmission, we evaluated NK cell (CD56bright, CD56dim, CD56neg) phenotype and ADCC function by flow cytometry in children <5 years of age with SM (n = 21) and control community children (CC, n = 19). Children with SM had similar total NK cell counts to CC. Children with SM had a higher proportion of LILRB1+ NK cells than CC. The level of malaria transmission in an area was related to NK cell function. In the low malaria transmission area only, children with SM had a higher proportion than CC of NK cells that degranulated, whereas children with SM from both low and moderate malaria transmission areas had lower IFN-γ production than CC. We next evaluated functional Boolean gating for degranulation and IFN-γ production (CD107a+/IFN-γ-, CD107a-/IFN-γ+, and CD107a+/IFN-γ+) in relation to memory-like and checkpoint/exhaustion NK cell markers in low and moderate malaria transmission SM and CC groups. We found there was a significant increase in degranulating only NK cells (CD107a+, IFN-γ-) in children with SM compared to CC solely in the low malaria transmission area. However, there was a significant decrease in NK cells that produced IFN-γ but did not degranulate (CD107a-, IFN-γ+) in children with SM compared to CC in both low and moderate transmission areas. Our data reveal compound functional differences in NK cells among children with SM living in areas of low versus moderate malaria transmission; however, a consistent finding is reduced NK cell IFN-γ production in SM, regardless of transmission intensity
Indiana Emergency Medical Services Workforce January 11 - April 14, 2025 Student Data Report
No full textThis report summarizes findings from the Indiana EMS Student Pulse Check survey for January 11 through April 14, 2025, reflecting responses from 104 EMS trainees. Over half of respondents were enrolled in EMT programs, and most reported no prior ambulance experience. Students identified average training costs of approximately 24 following program completion. Respondents most often became aware of EMS careers through personal connections and expressed employment preferences primarily for fire departments and hospital-based ambulance services. Key factors influencing job selection included cost of living, commute time, and community safety. Health insurance, paid time off, and retirement plans were the most valued employment benefits, while peer support, shift coverage practices, and fatigue management plans were notable non-benefit considerations. Most students completed their training outside their home zip code, indicating frequent travel to access EMS education programs