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At least 19 recordsLinked to original sources

PubMedDate not supplied

[Aspects of auditory short-term memory according to a multimodal sequence paradigm].

Capacity and temporal characteristics of auditory short-term memory have been investigated through a simple multi-tonal sequence paradigm in five normally hearing subjects. They were required to judge whether the tonal sequence contained or not a tone probe following the sequence. Performance was evaluated relative to the sequence length (2, 4, 6 stimuli) and sequence-probe interval (1, 3, 6 s.). The subjects' performance has been proven to be mainly dependent on the number of the sequence components (90% of the explained variance), while sequence-probe interval represents a factor of minor weight. Furthermore, a strong recency effect has been shown for the last sequence component, extending to the preceding components in dependence of the sequence-probe interval. Contrasting to studies on the verbal short-term memory, a primary effect has been not demonstrated. As these results reflect the typical effects of auditory short-term memory, it is likely that memory tests based on simple tonal sequences may be suitable for clinical use.

Acoustic Stimulation↗

PubMed2004

On a multimode test sequencing problem.

Test sequencing is a binary identification problem wherein one needs to develop a minimal expected cost test procedure to determine which one of a finite number of possible failure states, if any, is present. In this paper, we consider a multimode test sequencing (MMTS) problem, in which tests are distributed among multiple modes and additional transition costs will be incurred if a test sequence involves mode changes. The multimode test sequencing problem can be solved optimally via dynamic programming or AND/OR graph search methods. However, for large systems, the associated computation with dynamic programming or AND/OR graph search methods is substantial due to the rapidly increasing number of OR nodes (denoting ambiguity states and current modes) and AND nodes (denoting next modes and tests) in the search graph. In order to overcome the computational explosion, we propose to apply three heuristic algorithms based on information gain: information gain heuristic (IG), mode capability evaluation (MC), and mode capability evaluation with limited exploration of depth and degree of mode Isolation (MCLEI). We also propose to apply rollout strategies, which are guaranteed to improve the performance of heuristics, as long as the heuristics are sequentially improving. We show computational results, which suggest that the information-heuristic based rollout policies are significantly better than traditional information gain heuristic. We also show that among the three information heuristics proposed, MCLEI achieves the best tradeoff between optimality and computational complexity.

Algorithms↗

PubMed1977

Temporal extrapolation of unimodal and multimodal stimulus sequences in retarded and nonretarded persons.

Retarded adolescents, CA-matched nonretarded adolescents, and MA-matched nonretarded children attempted to match the repetition rate of 10-second stimulus sequences presented under four modality switching conditions and at two pusle frequencies. Error magnitudes were least for the CA-matched subjects and under the faster pulse rate increased from the no-switching to maximum-switching condition in all groups. Error increases from the no-switching to maximum-switching condition were preponderantly underestimations. No differences between groups were obtained for a switching condition in which the modality-sequence pattern was aperiodic. A hypothesis of longer psycholoical refractory periods in retarded adolescents was rejected in favor of one explaining their inferior performance on sequential enumeration and tracking tasks in terms of inefficient organizational abilities.

Acoustic Stimulation↗

PubMed2026

Livestock Multi-Omics Integration: A Systematic Framework From Statistical Association to Causal Interpretation.

Livestock multi-omics integration is key to unraveling complex trait regulation, yet systematic, livestock-specific strategies remain scarce. This review traces the progression from single-omics accumulation to multi-dimensional integration, highlighting how large-scale genomic, epigenomic, and transcriptomic projects lay the foundation for functional dissection. We identify core impediments: extreme species diversity, marked data heterogeneity, limited sample sizes, and a pervasive reduction of multi-omics data to simplistic differential screens, resulting in low translational efficiency. We critically appraise four common pitfalls-overinterpreting correlation as causation, relegating proteomics to corroborating transcriptomics, incomplete microbiome-host integration lacking environmental context, and systematic neglect of metabolic fluxomics-and show how exposomics and fluxomics add necessary causal and dynamic dimensions. To address these, we propose a livestock-adapted three-tier analytical framework: (1) statistical association of cross-omics covariation patterns; (2) machine learning-driven feature mining and integrative modeling; and (3) causal interpretation encompassing Mendelian randomization, prior-knowledge-guided network inference, and physical causal evidence via fluxomics and metabolic control analysis. We further discuss how multimodal sequencing (single-cell, spatial, temporal) and generative AI can fundamentally mitigate heterogeneity and strengthen causal evidence. Finally, we outline future priorities in database standardization, livestock-specific benchmarking, and translational pipelines, charting a path from correlation-centric reporting to mechanistic causality and precision breeding.

Animals↗

PubMed1994

Sequential Therapy in the Treatment of Locally Advanced Noninflammatory Breast Cancer.

Optimal care of patients with locally advanced breast cancer requires the use and thoughtful integration of all effective modalities of treatment. A number of alternative combinations of surgery, chemotherapy, and radiation have been promoted, each with its own particular advantages and shortcomings. The advantages of sequenced, multimodality therapy of locally advanced, noninflammatory breast cancer include (1) the ability to convert nonresectable tumors to resectable ones, (2) early institution of systemic therapy, (3) in vivo evaluation of tumor response with the potential for optimization of therapy, and (4) relatively low morbidity rates with the ability to render most patients disease-free at their primary site. The results of this treatment strategy are discussed.

Journal Article↗

PubMed2025

Nonlinear transcriptional responses to gradual modulation of transcription factor dosage.

Genomic loci associated with common traits and diseases are typically non-coding and likely impact gene expression, sometimes coinciding with rare loss-of-function variants in the target gene. However, our understanding of how gradual changes in gene dosage affect molecular, cellular, and organismal traits is currently limited. To address this gap, we induced gradual changes in gene expression of four genes using CRISPR activation and inactivation. Downstream transcriptional consequences of dosage modulation of three master trans-regulators associated with blood cell traits (GFI1B, NFE2, and MYB) were examined using targeted single-cell multimodal sequencing. We showed that guide tiling around the TSS is the most effective way to modulate cis gene expression across a wide range of fold-changes, with further effects from chromatin accessibility and histone marks that differ between the inhibition and activation systems. Our single-cell data allowed us to precisely detect subtle to large gene expression changes in dozens of trans genes, revealing that many responses to dosage changes of these three TFs are nonlinear, including non-monotonic behaviours, even when constraining the fold-changes of the master regulators to a copy number gain or loss. We found that the dosage properties are linked to gene constraint and that some of these nonlinear responses are enriched for disease and GWAS genes. Overall, our study provides a straightforward and scalable method to precisely modulate gene expression and gain insights into its downstream consequences at high resolution.

Journal Article↗

PubMed2026

Integrating metagenomic next-generation sequencing into a multimodal diagnostic framework for spinal infection: enhancing etiological identification and clinical prediction.

BACKGROUND: Spinal infection (SI) remains diagnostically challenging because of heterogeneous etiologies, nonspecific clinical manifestations, and the limited sensitivity of conventional microbiological approaches, particularly following empirical antimicrobial exposure. Although metagenomic next-generation sequencing (mNGS) enables unbiased pathogen detection, its incremental clinical value beyond pathogen identification and its role within integrated diagnostic strategies remain incompletely established. METHODS: We retrospectively analyzed 208 consecutive patients with suspected SI between August 2022 and August 2025. Final diagnoses were established using a multidisciplinary-adjudicated composite reference standard incorporating clinical, radiological, microbiological, and histopathological evidence. The diagnostic performance of mNGS was compared with conventional culture and histopathology. Furthermore, multimodal predictive models integrating clinical variables and microbiological information were developed using L1-regularized logistic regression. RESULTS: In the comparative cohort, mNGS achieved a significantly higher diagnostic yield than culture (66.5% vs. 27.41%, P < 0.001). Among confirmed SI cases, mNGS demonstrated higher sensitivity than conventional culture (91.67% vs. 40.15%, P < 0.001). mNGS identified a substantially broader pathogen spectrum, ranging from fastidious organisms such as Mycobacterium tuberculosis and Brucella to rare pathogens including Talaromyces marneffei and Coxiella burnetii, and maintained robust sensitivity (98.2%) despite prior antibiotic exposure. While an integrated clinical model achieved an AUC of 0.916, mNGS as a standalone modality provided superior discriminative power (AUC = 0.889) compared to histopathology (AUC = 0.836), the Conventional Biomarker Model (AUC = 0.742), and culture (AUC = 0.693). CONCLUSIONS: mNGS is a high-yield diagnostic tool for spinal infection, particularly in culture-negative and antibiotic-pretreated scenarios. Integrating mNGS into a multimodal clinical framework facilitates etiological clarity and precision antimicrobial therapy.

Humans↗

PubMed2026

Large language models in bioinformatics: a comprehensive survey.

The emergence of foundation models with trillion-level parameters has redefined the landscape of artificial intelligence. Various fields are developing their own large-scale models, which can solve many problems within the field and improve work efficiency. Biological large-scale models are a cross-disciplinary research field that combines mathematics, computer science, and biology, aiming to simulate and understand the structure, function, and dynamic changes of biological systems through the establishment of complex computational models. This field covers multiple levels such as biological pathways, population dynamics, protein folding, etc., providing us with tools for deep exploration of the mysteries of life and applications in medicine, ecology, and other fields. This article reviews the background and research status of biological large-scale models, and discusses future directions. Large language models (LLMs) and other large-scale foundation models have rapidly advanced in recent years, enabling powerful representation learning and generation across text, sequences, and multimodal data. In bioinformatics and biomedicine, these models are increasingly used to analyze genomic sequences, infer protein properties and structures, support drug discovery, and integrate heterogeneous biomedical evidence. This survey reviews the basic principles of LLMs and summarizes representative applications in (i) gene and genome sequence analysis, (ii) protein structure and function prediction, and (iii) drug design, including virtual screening and personalized medicine. We also discuss emerging multi-model modeling approaches, as well as key challenges such as data quality and privacy, interpretability, generalization to new organisms and tasks, and responsible deployment in health-related settings. Finally, we outline future directions for developing reliable, scalable, and explainable bioinformatics foundation models.

bioinformatics↗

PubMed2005

Detection of vascular adhesion molecule-1 expression using a novel multimodal nanoparticle.

Endothelial vascular adhesion molecule-1 (VCAM-1) is a critical component of the leukocyte-endothelial adhesion cascade, and its strict temporal and spatial regulation make it an ideal target for imaging and therapy. The goal of this study was to develop novel VCAM-1-targeted imaging agents detectable by MRI and fluorescence imaging using phage display-derived peptide sequences and multimodal nanoparticles (NPs). We hypothesized that VCAM-1-mediated cell internalization of phage display-selected peptides could be harnessed as an amplification strategy to chaperone and trap imaging agents inside VCAM-1-expressing cells, thus improving target-to-background ratios. To accomplish our goal, iterative phage display was performed on murine endothelium under physiological flow conditions to identify a family of VCAM-1-mediated cell-internalizing peptides. One specific sequence, containing the VHSPNKK motif that has homology to the alpha-chain of very late antigen (a known ligand for VCAM-1), was shown to bind VCAM-1 and block leukocyte-endothelial interactions. Compared with VCAM-1 monoclonal antibody, the peptide showed 12-fold higher target-to-background ratios. A VHSPNKK-modified magnetofluorescent NP (VNP) showed high affinity for endothelial cells expressing VCAM-1 but surprisingly low affinity for macrophages. In contrast, a control NP without VCAM-1-targeting sequences showed no affinity for endothelial cells. In vivo, VNP successfully identified VCAM-1-expressing endothelial cells in a murine tumor necrosis factor-alpha-induced inflammatory model and colocalized with VCAM-1-expressing cells in atherosclerotic lesions present in cholesterol-fed apolipoprotein E apoE-/- mice. These results indicate that: (1) small peptide sequences can significantly alter targeting of NPs, (2) the used amplification strategy of internalization results in high target-to-background ratios, and (3) this technology is useful for in vivo imaging of endothelial markers.

Animals↗

PubMed1999

Multimodal efferent and recurrent neurons in the medial lobes of cockroach mushroom bodies.

Previous electrophysiological studies of cockroach mushroom bodies demonstrated the sensitivity of efferent neurons to multimodal stimuli. The present account describes the morphology and physiology of several types of efferent neurons with dendrites in the medial lobes. In general, efferent neurons respond to a variety of modalities in a context-specific manner, responding to specific combinations or specific sequences of multimodal stimuli. Efferent neurons that show endogenous activity have dendritic specializations that extend to laminae of Kenyon cell axons equipped with many synaptic vesicles, termed "dark" laminae. Efferent neurons that are active only during stimulation have dendritic specializations that branch mainly among Kenyon cell axons having few vesicles and forming the "pale" laminae. A new category of "recurrent" efferent neuron has been identified that provides feedback or feedforward connections between different parts of the mushroom body. Some of these neurons are immunopositive to antibodies raised against the inhibitory transmitter gamma-aminobutyric acid. Feedback pathways to the calyces arise from satellite neuropils adjacent to the medial lobes, which receive axon collaterals of efferent neurons. Efferent neurons are uniquely identifiable. Each morphological type occurs at the same location in the mushroom bodies of different individuals. Medial lobe efferent neurons terminate in the lateral protocerebrum among the endings of antennal lobe projection neurons. It is suggested that information about the sensory context of olfactory (or other) stimuli is relayed by efferent neurons to the lateral protocerebrum where it is integrated with information about odors relayed by antennal lobe projection neurons.

Animals↗

PubMed2003

Intra-deme molecular diversity in spatially expanding populations.

We report here a simulation study examining the effect of a recent spatial expansion on the pattern of molecular diversity within a deme. We first simulate a range expansion in a virtual world consisting in a two-dimensional array of demes exchanging a given proportion of migrants (m) with their neighbors. The recorded demographic and migration histories are then used under a coalescent approach to generate the genetic diversity in a sample of genes. We find that the shape of the gene genealogies and the overall pattern of diversity within demes depend not only on the age of the expansion but also on the level of gene flow between neighboring demes, as measured by the product Nm, where N is the size of a deme. For small Nm values (< approximately 20 migrants sent outwards per generation), a substantial proportion of coalescent events occur early in the genealogy, whereas with larger levels of gene flow, most coalescent events occur around the time of the onset of the spatial expansion. Gene genealogies are star shaped, and mismatch distributions are unimodal after a range expansion for large Nm values. In contrast, gene genealogies present a mixture of both very short and very long branch lengths, and mismatch distributions are multimodal for small Nm values. It follows that statistics used in tests of selective neutrality like Tajima's D statistic or Fu's F(S) statistic will show very significant negative values after a spatial expansion only in demes with high Nm values. In the context of human evolution, this difference could explain very simply the fact that analyses of samples of mitochondrial DNA sequences reveal multimodal mismatch distributions in hunter-gatherers and unimodal distributions in post-Neolithic populations. Indeed, the current simulations show that a recent increase in deme size (resulting in a larger Nm value) is sufficient to prevent recent coalescent events and thus lead to unimodal mismatch distributions, even if deme sizes (and therefore Nm values) were previously much smaller. The fact that molecular diversity within deme is so dependent on recent levels of gene flow suggests that it should be possible to estimate Nm values from samples drawn from a single deme.

Animals↗

PubMed1998

Clinical studies in non-small cell lung cancer: the CALGB experience.

Since 1984, the Cancer and Leukemia Group B (CALGB) has focused its clinical research in stage IV non-small cell lung cancer (NSCLC) on investigations of new agents and combinations. Currently, efforts are aimed at identifying non-cisplatin-based combinations with an increased therapeutic index. In stage III disease multimodality therapies have been pursued. Dillman et al. reported a study comparing standard radiotherapy versus induction chemotherapy followed by radiotherapy in patients with unresectable stage III NSCLC. The chemotherapy-treated patients were found to benefit with a 4-month increase in median survival time compared with patients receiving radiotherapy alone (13.8 vs. 9.7 months) and an increased 3-year survival rate of 23% versus 11%. This was the first randomized cooperative group study demonstrating a survival advantage resulting from the use of induction chemotherapy in locoregionally advanced NSCLC. In a subsequent study, the administration of additional "posterior" chemotherapy was not found to be feasible because of early disease progression and toxicity, while the administration of induction chemotherapy followed by concomitant chemoradiotherapy was feasible; therefore, the latter approach was studied further in a randomized phase III setting. This study compared a standard of two cycles of cisplatin and vinblastine followed by radiotherapy with an experimental arm of cisplatin and vinblastine followed by radiotherapy and concomitant carboplatin. Accrual to this study has been completed and results are expected in the near future. In resectable stage III disease, studies have focused on the optimal sequencing of multimodality therapy. A randomized study comparing standard regional therapy with radiotherapy and surgery versus a previously piloted approach combining chemotherapy, surgery, and radiotherapy was closed prematurely due to poor accrual. The next generation of studies in stage III NSCLC will focus on the integration of new chemotherapy agents into the treatment armamentarium for NSCLC. A randomized phase II study investigating paclitaxel, gemcitabine, and vinorelbine in combination with cisplatin in the induction setting and as concomitant chemoradiotherapy has recently been activated.

Antineoplastic Combined Chemotherapy Protocols↗

PubMedDate not supplied

Medical management of early-stage breast cancer.

With improved screening and education, a greater proportion of breast cancer is detected at an early stage. Although the prognosis for many of these patients is excellent following definitive local therapy alone, some subsets of node-negative patients have a 30% chance of eventually developing metastatic disease that will be incurable with current therapy. Thus, an increasing proportion of early-stage patients are being offered some form of adjuvant therapy, with the expectation of improved relapse-free survival, and possibly improved overall survival. Efforts have been made to base the selection of patients for adjuvant therapy on specific prognostic factors. Meanwhile, the scope and complexity of putative prognostic factors continues to widen, and now includes such items as the presence of occult microscopic metastases, DNA ploidy and proliferative fraction, cytogenetic abnormalities, oncogene expression, growth factor receptors, and expression of hormonally regulated proteins. In addition, there is now a considerable range of options with regard to the composition, dose intensity, and sequence of multimodality therapy. Data regarding the classification, significance, and interpretation of prognostic factors is reviewed together with the development, current status, and recommendations regarding adjuvant therapy for patients with early-stage breast cancer. For 1991, the National Cancer Institute (NCI) has estimated that 175,000 new cases of breast cancer will be diagnosed in American women. It is also estimated that 44,500 women will die of breast cancer. Unfortunately, the age-adjusted death rate from breast cancer has shown no overall change from 1930 through 1987. However, effective screening techniques continue to identify an increasing percentage of early-stage tumors, which should exceed 50% of all new tumors in 1991. Ultimately, our understanding of environmental and genetic risk factors may identify new ways to reduce the impact of this disease. In the interim, development and application of effective systemic adjuvant chemotherapy and hormonal therapy has become increasingly important. There is no question that a greater proportion of patients with less extensive disease are now being offered some form of adjuvant therapy. Meanwhile, selection of patients for adjuvant therapy, and choice among specific adjuvant regimens, has remained controversial. Analysis of multiple prognostic factors is performed not only in the context of cooperative investigational trials, but more often in the offices of individual physicians caring for individual patients. Tumor biopsies can now be routinely sent to specialized laboratories for performance of complex assays with potential prognostic information, although interpretation of these results with reference to a specific patient is often uncertain.(ABSTRACT TRUNCATED AT 400 WORDS)

Antineoplastic Agents↗

PubMed2000

Locoregional irradiation for inflammatory breast cancer: effectiveness of dose escalation in decreasing recurrence.

PURPOSE: To evaluate the effect of radiation dose escalation on locoregional control, overall survival, and long-term complication in patients with inflammatory breast cancer. PATIENTS AND METHODS: From September 1977 to December 1993, 115 patients with nonmetastatic inflammatory breast cancer were treated with curative intent at The University of Texas M. D. Anderson Cancer Center. The usual sequence of multimodal treatment consisted of induction FAC or FACVP chemotherapy, mastectomy (if the tumor was operable), further chemotherapy, and radiation therapy to the chest wall and draining lymphatics. Sixty-one patients treated from September 1977 to September 1985 received a maximal radiation dose of 60 Gy to the chest wall and 45-50 Gy to the regional lymph nodes, 22 treated once a day at 2 Gy per fraction, and 35 were treated b.i.d. (32 after mastectomy and all chemotherapy was completed, and 2 immediately after mastectomy; one patient had distant metastases discovered during b.i.d. irradiation, and treatment was stopped). Four additional patients received preoperative radiation with standard fractionation. Based on the analysis of the failure patterns of the patients, the dose was increased for the b.i.d. patients in the new series, with 51 Gy delivered to the chest wall and regional nodes, followed by a 15-Gy boost to the chest wall with electrons. From January 1986 to December 1993, 39 patients were treated b.i.d. to this higher dose after mastectomy and all the chemotherapy was completed; and 8 additional patients received preoperative irradiation with b.i.d. fractionation to 51 Gy. During this period, another 7 patients were treated using standard daily doses of 2 Gy per fraction to a total of 60 Gy, either because they had a complete response or minimal residual disease at mastectomy or because their work schedule did not permit the b.i.d. regimen. Comparison was made between the groups for locoregional control, disease-free and overall survival, and complication rates. RESULTS: The median follow-up time was 5.7 years (range, 1.8-17.6 years). For the entire patient group, the 5- and 10-year local control rates were 73.2% and 67.1%, respectively. The 5- and 10-year disease-free survival rates were 32.0% and 28.8%, respectively, and the overall survival rates for the entire group were 40.5% and 31.3%, respectively. To evaluate the effectiveness of dose escalation, a specific comparison of patients who received b.i.d. radiation after mastectomy and completion of adjuvant chemotherapy was performed. There were 32 patients treated b.i.d. to 60 Gy in the old series versus 39 patients treated b.i.d. to 66 Gy in the new series. There was an significant improvement in the rate of locoregional control for the b.i.d. patients for the old vs. new series, from 57.8% to 84.3% and from 57.8% to 77.0% (p = 0.028) at 5 and 10 years, respectively. Chemotherapy regimens did not change significantly during this time period.Long-term complications of radiation, such as arm edema more than 3 cm (7 patients), rib fracture (10 patients), severe chest wall fibrosis (4 patients), and symptomatic pneumonitis (5 patients), were comparable in the two groups, indicating that the dose escalation did not result in increased morbidity. Significant differences in the rates of locoregional control (p = 0.03) and overall survival (p = 0.03), and a trend of better disease-free survival (p = 0.06) were also observed that favored the recently treated patients receiving the higher doses of irradiation. CONCLUSION: Twice-daily postmastectomy radiation to a total of 66 Gy for patients with inflammatory breast cancer resulted in improved locoregional control, disease free survival, and overall survival, and was well tolerated.

Adult↗

PubMed2002

Global proteome analysis of a human gastric carcinoma.

An approach that combines analysis of global protein digests (GPDs) of various subcellular fractions with a novel chromatographic-based method to map protein expression profiles is described. The KATO III gastric carcinoma cell line was fractionated into membrane and cytosol fractions. Each subcellular fraction was digested with trypsin to yield complex mixtures of global protein tags (GPTs). These mixtures were fractionated by two dimensions of chromatography, and GPTs were sequenced by microcapillary liquid chromatography-tandem mass spectrometry (LC-MS/MS), using two further complementary dimensions of chromatography. Additionally, a novel method of protein expression profiling was used to map the KATO III human gastric carcinoma cell line. This method uses the cells' natural proteolytic processes to derive in vivo peptide tags that represent proteins of every functional class and from all subcellular compartments. In one example, expressed protein tags (EPTs) are naturally displayed on the surface of cells by multiligand receptors. Isolation and sequence identification of EPTs is an efficient approach for protein profiling that is complementary to GPT analysis. The EPT approach also provides a further unique subcellular fraction of the biological starting material. Isolation of the multiligand receptors was by immunoaffinity chromatography (IAC). In the current study, five individual peptide maps (two EPTs and three GPTs) of the KATO III cell line were fractionated by multimodal chromatography, and sequenced by on-line multimodal microcapillary LC-MS/MS. This analysis led to the identification of 4291 individual peptide sequences, which defined 1966 unique proteins expressed by this human carcinoma cell line.

Chromatography, Affinity↗

PubMed2025

The GSA Family in 2025: A Broadened Sharing Platform for Multi-omics and Multimodal Data.

The Genome Sequence Archive family (GSA family) provides a comprehensive suite of database resources for archiving, retrieving, and sharing multi-omics data for the global academic and industrial communities. It currently comprises four distinct database members: the Genome Sequence Archive (GSA, https://ngdc.cncb.ac.cn/gsa), the Genome Sequence Archive for Human (GSA-Human, https://ngdc.cncb.ac.cn/gsa-human), the Open Archive for Miscellaneous Data (OMIX, https://ngdc.cncb.ac.cn/omix), and the Open Biomedical Imaging Archive (OBIA, https://ngdc.cncb.ac.cn/obia). Compared to its 2021 version, the GSA family has expanded significantly by introducing a new repository, the OBIA, and by comprehensively upgrading the existing databases. Notable enhancements to the existing members include broadening the range of accepted data types, strengthening quality control systems, improving the data retrieval system, and refining data-sharing management mechanisms.

Humans↗

PubMed2007

"Sequence Agnosia" in Bálint's syndrome: defects in visuotemporal processing after bilateral parietal damage.

Bálint's syndrome is characterized by visuospatial dysfunction, with failure to attend to multiple objects in space and poor spatial localization manifested as impaired reaching and saccadic targeting. Less investigated in this disorder is perceptual processing along the dimension of time. We studied the performance of a patient with Bálint's syndrome on two oddity paradigms in which she had to indicate which of three objects was different in color, shape, or structure. Her initial difficulty with processing multiple objects present simultaneously in different locations recovered, but she had persistent difficulty processing objects seen sequentially at the same location. Further studies showed that this deficit was not due to impairments in sustained attention or in distributing attention over time, but to impaired processing of temporal sequences. The deficit was also present with auditory stimuli, indicating a multimodal failure of temporal sequencing. These findings show that bilateral parietal lesions affect not only the spatial but also the temporal organization of perception.

Agnosia↗

PubMed2026

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans↗