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PubMed1993

Spontaneous direct carotid-cavernous fistula in childhood.

We report the occurrence, surgical treatment and long-term follow-up of a spontaneous, direct carotid-cavernous fistula in a child. It is the third angiographically documented, spontaneously occurring fistula to be reported in this age group and the first to arise directly from the internal carotid artery based on our review of the literature. Although our patient required fistula closure, other reported fistulae were nonprogressive and did not require treatment. The communication between the internal carotid artery and the cavernous sinus was left sided while the contralateral eye was proptotic. The clinical features, selected hemodynamic characteristics, and treatment of carotid-cavernous fistulas are reviewed.

Arteriovenous Fistula↗

PubMed2026

Proteomic Immune Signatures of Severe HIV-Associated Tuberculosis in Sub-Saharan Africa: A Prospective, Multicenter Analysis From Uganda.

OBJECTIVES: Severe tuberculosis (TB) is a major cause of critical illness and death in people living with HIV (PLWH) worldwide. Despite this, the immunopathology of severe HIV-associated TB (HIV/TB) is poorly understood. We aimed to identify an immunopathologic signature of severe HIV/TB in sub-Saharan Africa. DESIGN AND SETTING: We analyzed proteomic data from two prospective observational cohorts of adults hospitalized with severe undifferentiated infection in Uganda: an urban discovery cohort (Entebbe, n = 241) and a rural validation cohort (Tororo, n = 253). PATIENTS: Adults (age ≥ 18 yr) hospitalized with severe febrile illness. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Across both cohorts, severe HIV/TB was common, affecting 18% of participants in the discovery cohort and 21% in the validation cohort. Overall mortality was significant (30-d mortality of 22% in the discovery cohort and 60-d mortality of 26% in the validation cohort). Participants were stratified into three HIV/TB phenotypes: HIV-negative without TB, PLWH without TB, and PLWH with microbiologically diagnosed TB. We applied ordinal random forest models in the discovery cohort as a supervised feature-selection approach to identify proteins associated with progressive HIV/TB phenotype. In both cohorts, PLWH with microbiologically diagnosed TB were at highest risk of critical illness and death (30-d mortality of 42% in the discovery cohort and 60-d mortality of 52% in the validation cohort). An eight-protein signature reliably distinguished this phenotype, reflecting mediators of macrophage/dendritic cell activation (lysosome-associated membrane glycoprotein 3), natural killer cell and T-cell stimulation and cytotoxicity (cluster of differentiation 70, class I-restricted T-cell-associated molecule), B-cell activation (immunoglobulin lambda constant 2), protease-mediated tissue injury (protease, serine 2 [trypsin-2]), dysregulated coagulation (serpin peptidase inhibitor, clade A [alpha-1 antitrypsin], member 5), extracellular matrix remodeling (epidermal growth factor-containing fibulin-like extracellular matrix protein 1), and growth hormone/insulin-like growth factor axis dysregulation (insulin-like growth factor binding protein 3). CONCLUSIONS: We identified an immunologic signature of severe HIV/TB defined by mediators of macrophage/dendritic cell and cytotoxic lymphocyte activation, extracellular matrix remodeling, and dysregulated coagulation. These findings offer new insight into HIV/TB pathobiology and highlight potential targets for host-directed therapies in this high-risk population.

Humans↗

PubMed2025

Estimating population structure using epigenome-wide methylation data.

INTRODUCTION: In epigenome-wide association analysis (EWAS), unaddressed population stratification often leads to inflation. We aimed to compute methylation population scores (MPSs) that predict genetic principal components (GPCs) using a feature selection and regression approach. METHODS: We used multi-ethnic methylation data (Illumina 450K/EPIC array) from unrelated MESA (n=929), CARDIA (n=1123), JHS (n=1365), ARIC (n=2338), and HCHS/SOL (n=1475) individuals, randomly assigning 85% of participants from each cohort to a training dataset and the remaining 15% to a test dataset. First, we estimated the associations of GPCs with each available CpG methylation site using linear regression within each cohort, adjusting for age, sex, smoking status, race/ethnic background (as a proxy for background information associated with lifestyle and other environmental exposures that may impact methylation), alcohol use status, body mass index, and cell type proportions. We meta-analyzed the associations across cohorts and selected CpG sites with association FDR-adjusted q-value <0.05. We next aggregated individuallevel data across the cohort-specific training datasets, and applied two-stage weighted least squares Lasso regression, with the GPCs as the outcomes and the selected CpG sites as penalized predictors, adjusting for the aforementioned covariates. The developed MPSs are the weighted sum of selected CpG sites from the Lasso. To evaluate the developed MPSs, we constructed them in the test dataset, and compared them with GPCs, and with MPSs constructed based on a previously-published paper. Comparison was based on correlation analysis and data visualization. We demonstrate the use of the MPSs in EWAS. RESULTS: In the test dataset, the MPSs were highly correlated with GPCs, with correlation decreasing, though not monotonically, for later components. Specifically, MPS1 and GPC1 had R2= 0.99, while MPS7 and GPC7 had R2=0.27 (the lowest observed correlation). In data visualization, MPSs had similar patterns as GPCs in differentiating self-reported White, Black, and Hispanic/Latino groups, while outperforming MPC constructed using alternative published methods. MPSs showed comparable performance to GPCs in reducing some of the inflation in EWAS. CONCLUSIONS: Methylation-based population scores provide a reliable estimate of population structure in the data and can complement GPCs when genetic data are absent. Unlike previous methods based on unsupervised methylation PCA, MPSs uses supervised learning with covariate adjustment to capture genetic structure across diverse populations. The weights for each GPCs derived in our study can be applied to generate MPSs in other studies.

Journal Article↗

PubMed2026

Knowledge-driven interpretable neural networks provide mechanistic insight.

Analyzing omics data in the context of pathway knowledge is critical for understanding the molecular mechanisms underlying pathological changes. However, current pathway analysis methods do not model the detailed mechanistic nature of biological interactions, limiting the understanding of pathway behavior to a relatively shallow level. To address this issue, we present a knowledge-driven machine learning framework that embeds features into pathway graphs and models reactions analytically, producing interpretable feature hierarchies and subnetworks in which functional associations are estimated to model biological interactions. The approach is agnostic to feature selection, enabling the use of full omics data sets without discarding weak signals. Applications to breast cancer microRNA-gene regulation data and COVID-19 metabolomic data highlight immune and metabolic pathways relevant to disease progression. This framework bridges predictive modeling with mechanistic interpretation and offers a foundation for integrative pathway analysis.

Humans↗

PubMed2026

Large-Scale Plasma Proteomics Identifies Early Molecular Deviations and Improves Risk Prediction for Heart Failure Among Individuals With Obesity.

AIMS: Heart failure (HF) is a major global public health challenge, with obesity being one of its key risk factors. Although several HF risk prediction models have been developed in the general population, few are specifically tailored to individuals with obesity. This underscores the urgent need for precise biomarkers to improve individual risk stratification and enable personalized prevention strategies. We aimed to develop and validate a plasma proteomics-based protein risk score (PRS) to predict incident HF among individuals with obesity. MATERIALS AND METHODS: We analysed 9831 participants with obesity (BMI ≥ 30 kg/m2) from the UK Biobank with baseline measurements of 2911 circulating proteins and up to 16 years of follow-up. Multivariable Cox regression identified proteins associated with incident HF after comprehensive covariate adjustment. A PRS was constructed using LASSO regression and evaluated in a held-out test set. Protein trajectories before HF onset were reconstructed using LOESS modelling. To enhance clinical feasibility, a minimal protein panel was identified using LightGBM with forward feature selection. RESULTS: A total of 727 participants developed HF during follow-up. Multivariable cox analyses identified 578 proteins significantly associated with HF. LASSO regression further selected 81 proteins to build the PRS, which showed a strong association with HF risk in both training (HR 3.57; 95% CI 3.19-4.00) and test cohorts (HR 2.45; 95% CI 2.20-2.74). Adding the PRS improved prediction beyond age and sex (ΔC = 0.091) and beyond the Pooled Cohort Equations to Prevent Heart Failure (PCP-HF) model (ΔC = 0.052), with consistent gains in NRI and IDI. Proteomic deviations were detectable up to 16 years before diagnosis. A four-protein panel (GDF15, NT-proBNP, TNFRSF10B, CTHRC1) achieved robust discrimination (AUC 0.789), outperforming NT-proBNP alone (AUC 0.695) and complementing the PCP-HF model (combined AUC 0.803). DISCUSSION: Large-scale plasma proteomics substantially improves HF risk prediction in individuals with obesity and reveals long-standing molecular alterations preceding clinical onset. A simplified four-protein panel maintains robust predictive accuracy and provides a practical approach for the early detection and targeted prevention of obesity-related HF.

Humans↗

PubMed2026

AI In Leukemia Diagnostics: Complementing the Pathologist's Role.

Artificial intelligence (AI) is reshaping every stage of leukemia diagnostics, from digital morphology and multiparameter flow cytometry to next-generation sequencing, multi-omics analysis, and emerging computational frontiers such as quantum-inspired feature selection. This review outlines how contemporary AI tools can automate labor-intensive quantitation, flag diagnostically salient patterns, and standardize interpretation, while the pathologist or hematologist retains authority over validation, context-specific integration, and clinical decision-making. We present an illustrative "human-in-the-loop" workflow that embeds AI modules within current laboratory information systems, emphasizing points where expert oversight mitigates algorithmic bias and resolves discordant findings. We further map the validator-integrator role across morphology, flow cytometry, and genomic/multi-omic interpretation and provide practical training competencies and use cases for AI-assisted hematopathology. Beyond technical deployment, the article addresses the educational transformation required for sustainable adoption. Drawing on international competency frameworks, including the Digital Health Competencies in Medical Education Framework and recently proposed AI-specific Entrustable Professional Activities, we map core skills that future hematopathologists must master: data-science literacy, critical appraisal of AI outputs, and ethical governance. We highlight evaluated training models such as the Pathology Informatics Essentials for Residents curriculum, Stanford Artificial Intelligence in Machine and Imaging workshops, and College of American Pathologists bootcamps and propose integration strategies adaptable across resource settings. By pairing rigorous validation with targeted education, AI can elevate rather than eclipse the diagnostic role of the leukemia specialist, enabling more timely, reproducible, and personalized patient care.

Humans↗

PubMed1994

Automated tracing and volume measurements of neurons from 3-D confocal fluorescence microscopy data.

Three-dimensional (3-D) image analysis algorithms and experimental results that demonstrate the feasibility of fully automated tracing of neurons from fluorescence confocal microscopy data are presented. The input to the automated analysis is a set of successive optical slices that have been acquired using a confocal scanning laser microscope. The output of the system is a labelled graph representation of the neuronal topology that is spatially aligned with the 3-D image data. A variety of topological and metric analyses can be carried out using this representation. For instance, precise measurements of volumes, lengths, diameters and tortuosities can be made over specific portions of the neuron that are specified in terms of the graph representation. The effectiveness of the method is demonstrated for a set of sample fields featuring selectively stained neurons. Additional work will be needed to refine the method for unsupervised use with complex data involving multiple intertwined neurons and extremely fine dendritic structures.

Algorithms↗

PubMed1981

Spectral analysis of Doppler velocity patterns in normals and patients with carotid artery stenosis.

A computerized pattern recognition program was utilized to assess the predictive ability of various parameters obtained from the spectra of ultrasonic pulsed Doppler signals from the carotid arteries. The most accurate features selected by linear regression analysis were the natural log (ln) of the ratio of the mean velocity in the internal carotid artery compared to that in the common carotid artery, and the ln of the maximum velocity, the ln of the maximum frequency, and the square of the fractional broadening term, all of which were measured at peak systole in the internal carotid artery. Using the combination of the velocity ratio and the fractional broadening term, the average difference in the estimated percentage stenosis, as compared to that obtained by arteriography, was 12.8%.

Arteriosclerosis↗

PubMed1993

Effective photodynamic action by rhodamine 123 leading to photosensitized killing of Chinese hamster ovary cells in tissue culture and a proposed mechanism.

The effectiveness of rhodamine 123 (R123) as a photosensitizer of cell killing is relatively low and correlates with its inefficient production of singlet oxygen. The known selective retention of R123 in the mitochondria of epithelially derived carcinoma cells, however, is a selective feature that could lead to a more useful therapeutic ratio if photosensitizing effectiveness could be increased. Chinese hamster ovary (CHO) cells in tissue culture were therefore exposed to R123 shortly before and during illumination under conditions controlled for oxygen concentration and temperature. Effective photosensitization of cell killing, as judged by colony formation, was produced by 95% but not by 19% O2 during illumination of cells at 5 degrees C or 37 degrees C, and this was additionally enhanced at the sublethal temperature of 42 degrees C. Two CHO cell lines were examined; one line, CHO-AA8, was proficient in the repair of DNA damage and the parent to the second line, CHO-EM9, that was deficient in the repair of DNA strand breaks. Cells of both lines incorporated R123 to a similar degree and were similarly photosensitized by the presence of high oxygen concentration. Furthermore, plasma membrane damage as judged by the exclusion of trypan blue was not observed immediately after illumination in the presence of R123, but was seen in the presence of meso-tetra-(4-sulfonatophenyl)-porphine (TPPS4). The extent of damage to the plasma membrane by TPPS4 was greater in the presence of 95% compared to 19% O2 during illumination.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗

PubMedDate not supplied

Improvement in specificity of ultrasonography for diagnosis of breast tumors by means of artificial intelligence.

A set of ultrasonograms of lesions from 200 patients between the ages of 14 and 93 years who underwent mammography followed by ultrasonographic examination and excisional biopsy has been studied with computer vision techniques to improve the ultrasonographic specificity of the diagnosis. Selected features representing the texture of the lesion were calculated and then classified by an artificial neural network. This network was biased toward correctly classifying all the malignant cases at the expense of some misclassification of the benign cases. The network diagnosed the malignant cases with 100% sensitivity and 40% specificity (compared with 0% specificity for the radiologists diagnosing the same set of cases in the breast imaging setting), and tests performed with a leave-one-out technique indicate that the network will generalize well to new cases. This suggests that methods based on neural network classification of texture features show promise for potentially decreasing the number of unnecessary biopsies by a significant amount in patients with sonographically identifiable lesions.

Adolescent↗

PubMed1994

Use of cephalexin-aztreonam-arabinose agar for selective isolation of Enterococcus faecium.

Cephalexin-aztreonam-arabinose agar (CAA), a new selective agar, was examined in comparison with nalidixic acid-colistin agar for the differentiation of Enterococcus faecium from other enterococci and the ability to isolate the organism from feces. Two hundred sixteen enterococcus isolates and a variety of gram-positive and gram-negative control strains were inoculated onto both media. All control strains of E. faecium were easily differentiated from Enterococcus faecalis and Enterococcus durans on the basis of arabinose fermentation on CAA. Differentiation of E. faecium from other enterococci or Streptococcus bovis was not possible on nalidixic acid-colistin agar. Increased isolation of E. faecium was demonstrated on CAA when both media were compared for the isolation of the organism from feces. CAA has been shown to possess excellent differential and selective features allowing the simple and effective isolation of E. faecium from heavily contaminated sites.

Agar↗

PubMed1990

Organizing principles for single joint movements. III. Speed-insensitive strategy as a default.

1. Human subjects made discrete elbow flexions in a horizontal plane over different distances, from a stationary initial position to a visually defined stationary target 9 degrees wide. We measured joint angle, acceleration, and electromyograms (EMGs) from two agonist and two antagonist muscles. 2. Subjects made movements over four different distances following one of four different instructions. The first instructed the subject simply to choose a comfortable speed. The other three explicitly emphasized either speed, accuracy, or maintenance of the "same" speed over different distances. These instructions produced a wide range of movement velocities. 3. The initial rises of the acceleration (and therefore of the inertial torque), as well as the initial slope of the agonist EMG, were all invariant over changes in the target distance for any single instruction but were all sensitive to the given instruction. 4. Our results demonstrate that the speed-insensitive strategy is a standard or default pattern for performing movements that may be carried out for different instructions over a wide range of speeds. A uniform intensity of excitation pulse is not a byproduct of moving at maximal speed. Submaximal intensities are associated with submaximal speeds and are a selected feature of the pattern of movement control.

Acceleration↗

PubMed1991

An autopsy study of the incidence of lacunes in relation to age, hypertension, and arteriosclerosis.

We investigated selected features of lacunes in 1,086 necropsy cases. Lacunes were found in brains from patients above the age of 40 years and were most common in brains from persons in their sixties but decreased in number in brains from older persons. The most common site of lacunes was the frontal lobe white matter, followed by the putamen, pons, parietal lobe white matter, thalamus, and caudate nucleus in descending order of frequency. By dividing the 1,086 cases into three groups according to blood pressure, we found more lacunes in the hypertensive and borderline hypertensive groups than in the normotensive group; the average number of lacunes per brain in each group was 3.61, 2.77, and 1.15, respectively. Diastolic hypertension was more closely related to the number of lacunes than was systolic hypertension. The extent of arteriolosclerosis of the medullary arteries in the frontal lobe white matter was measured and compared with the number of lacunes. There was a close correlation between lacunes and arterioloslerosis in all age groups.

Adult↗

PubMed1995

Alkaline phosphatase: placental and tissue-nonspecific isoenzymes hydrolyze phosphoethanolamine, inorganic pyrophosphate, and pyridoxal 5'-phosphate. Substrate accumulation in carriers of hypophosphatasia corrects during pregnancy.

Hypophosphatasia features selective deficiency of activity of the tissue-nonspecific (liver/bone/kidney) alkaline phosphatase (ALP) isoenzyme (TNSALP); placental and intestinal ALP isoenzyme (PALP and IALP, respectively) activity is not reduced. Three phosphocompounds (phosphoethanolamine [PEA], inorganic pyrophosphate [PPi], and pyridoxal 5'-phosphate [PLP]) accumulate endogenously and appear, therefore, to be natural substrates for TNSALP. Carriers for hypophosphatasia may have decreased serum ALP activity and elevated substrate levels. To test whether human PALP and TNSALP are physiologically active toward the same substrates, we studied PEA, PPi, and PLP levels during and after pregnancy in three women who are carriers for hypophosphatasia. Hypophosphatasemia corrected during the third trimester because of PALP in maternal blood. Blood or urine concentrations of PEA, PPi, and PLP diminished substantially during that time. After childbirth, maternal circulating levels of PALP decreased, and PEA, PPi, and PLP levels abruptly increased. In serum, unremarkable concentrations of IALP and low levels of TNSALP did not change during the study period. We conclude that PALP, like TNSALP, is physiologically active toward PEA, PPi, and PLP in humans. We speculate from molecular/crystallographic information, indicating significant similarity of structure of the substrate-binding site of ALPs throughout nature, that all ALP isoenzymes recognize these same three phosphocompound substrates.

Alkaline Phosphatase↗

PubMed1992

Psychiatry residency programs: trends in psychotherapy supervision.

The evolving dominance of psychobiologic over psychodynamic theoretical influences on education and practice presents new challenges for psychiatry. This article features selected data from the 1989 American Association of Directors of Psychiatric Residency Training annual survey (n = 215) that describe current teaching activities related to psychodynamic psychiatry, mainly psychotherapy. Results are based on a 50 percent return rate (107/215 questionnaires). Responses confirm the emergence of psychobiological (48%) over psychodynamic (40%) departmental orientations and report that the psychodynamic orientation has maintained strength as a secondary emphasis. Residents generally gain experience in a range of psychotherapy theories and modalities, including psychodynamic, cognitive, behavioral, individual, couples, family, and group therapies. Training in brief and short-term individual psychodynamic psychotherapy predominates, however. Use of video- and audiotaping in supervision is limited. Full-time faculty provide the bulk of psychotherapy instruction. This is carried out in both individual and group sessions, which are organized primarily around case reviews. Supervision-related problems include faculty availability, skill diversity, competence, theoretical flexibility, and attitudes, as well as program structure and standards.

Female↗

PubMed1983

Breast tissue classification using diagnostic ultrasound and pattern recognition techniques: I. Methods of pattern recognition.

This paper discusses the application of statistical pattern recognition techniques to problems in diagnostic ultrasound. Using our own system as an example, we describe the concepts and specific methods that we have applied to a problem involving the computer-aided classification of breast tissue in vivo. Topics include feature generation, feature selection and classification, as well as a method which estimates the probability of error on classifying future data. An accompanying paper applies these methods to the classification of backscattered RF signals from normal and diseased breast tissue.

Breast Diseases↗

PubMed1987

Quantitation of the immunocytochemical assay for estrogen receptor protein (ER-ICA) in human breast cancer by television imaging.

A Quantimet 720D Image Analysis System has been programmed for light microscopic evaluation of the nuclear estrogen receptor distribution in frozen sections of human breast cancer stained by the peroxidase-antiperoxidase method using monoclonal antibodies to estrogen receptor protein (ER). This method provides precise criteria for distinguishing ER-positive and -negative cells and a sensitive and reproducible means for densitometric quantification of the staining patterns. Although imaging sequence and graphic analysis are automated by computer programs, light pen interaction provides supervision of feature selection. Imaging of the immunocytochemical assay (ER-ICA) in 50 patients revealed marked heterogeneity of nuclear estrogen receptor concentration varying over a nearly 100 fold concentration range. Various ER concentration patterns were evident: (I) distributions with a single peak (CV = 5%) present at various concentration levels; (II) bimodal distributions, revealing co-existent ER-positive and ER-negative subpopulations; (III) multimodal distributions with a number of resolvable concentration peaks; and (IV) highly skewed distributions with or without discernible peaks, frequently extending over the entire concentration range. Statistical methods of de-convolution were applied to determine the frequency and ER concentration characteristics of component subpopulations in the mosaic cases and for resolving the proportion of ER-positive and -negative cells. An approach for evaluating nuclear ER content in conjunction with ER concentration patterns in individual patients revealed whether spread in the ER concentration distribution resulted from differences in nuclear ER content or from variability in nuclear volume distribution.

Antibodies, Monoclonal↗

PubMed2026

Machine learning-guided risk stratification in elderly AML based on genomic, immunophenotypic and therapeutic profiles.

BACKGROUND: Elderly patients with acute myeloid leukemia (AML) exhibit considerable biological and clinical heterogeneity, hindering precise prognosis. Existing prognostic systems inadequately capture the complexity of elderly AML due to their reliance on data from younger cohorts and omission of key factors like immunophenotypic markers and therapeutic profiles. This study aimed to develop and internally validate a machine learning-based prognostic model specifically tailored to elderly AML patients. METHODS: A total of 156 patients were analyzed using a two-stage modeling strategy. Clinical and genomic variables were modeled first, followed by independent analysis of immunophenotypic features. Feature selection was performed using multilayer perceptron (MLP) and random forest (RF), while multivariate Cox regression was used for final model construction. Internal validation was conducted using 1000 bootstrap iterations to assess model stability and performance. RESULTS: The model demonstrated strong predictive performance, with a concordance index (C-index) of 0.702. Time-dependent area under the curve (AUC) and calibration plots confirmed accurate prediction of 1-, 3-, and 5-year overall survival. Decision curve analysis indicated favorable net benefit across a range of threshold probabilities. Key independent prognostic factors identified included TP53 mutations, high CD13 expression, and IDH2 mutations. CONCLUSION: This model provides a robust and interpretable tool for individualized risk stratification in elderly AML. By integrating genomic, immunophenotypic, and therapeutic variables, it may help optimize treatment decisions and improve outcomes for this vulnerable population. Future efforts should focus on external validation and integration of dynamic biomarkers.

Humans↗