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At least 19 recordsLinked to original sources
PubMed2025

Integration of single cell multiomics data by deep transfer hypergraph neural network.

Multi-omics characterization of individual cells offers remarkable potential for analyzing the dynamics and relationships of gene regulatory states across millions of cells. How to integrate multimodal data is an open problem, existing integration methods struggle with accuracy and modality-specific biological variation retention. In this paper, we present scHyper (scalable, interpretable machine learning for single cell integration), a low-code and data-efficient deep transfer model designed for integrating paired and unpaired single-cell multimodal data. We benchmark scHyper against datasets from different multimodal data. ScHyper learns a low-dimensional representation and aligns the covariance matrices of the measured modalities, achieving high accuracy even with large scale atlas-level datasets with low memory and computational time across different cell lines, shedding light on regulatory relationships between different types of omics. Altogether, we show that scHyper is a versatile and robust tool for cell-type label transfer and integration from multimodal single-cell datasets.

Single-Cell Analysis↗
PubMed1986

Segmental cable modelling of electrotonic transfer properties of deep superior colliculus neurons in the cat.

A segmental cable model of tecto-reticulo-spinal neurons of cat superior colliculus was constructed, based on detailed anatomical measurements from three neurons. The calculated membrane resistance for which the model best fitted the measured input resistance was 2,300-3,000 omega cm2. Electrotonic length of dendrites fell under 0.59-1.20 and 0.52-1.05 length constants, while the mean electrotonic length for the three cells averaged 0.91, 0.79, 0.81 and 0.80, 0.70, 0.71 (for sealed-end and open-end cable termination, respectively). Dendrite-to-soma conductance ratios averaged 16.0, 10.7, 7.5 and 21.3, 14.1, 11.4 for the two different end conditions, respectively. Synaptic efficacy was estimated by the transfer of steady-state voltage or current reaching the soma from distal dendritic locations. While voltage transfer was less than 1%, almost 60% of injected current (or charge) reached the soma. Analysis of voltage transients recorded experimentally in TRSNs demonstrated considerable difference between parameters derived from either equivalent-cylinder model or segmental cable model. The obvious deviations of TRSNs both in anatomical and electrotonic respect from the assumptions of the equivalent-cylinder model indicate that the detailed cable model will give a more appropriate description of these neurons. The significance of the estimated electrotonic parameters for the particular burst generation mechanism of TRSNs is discussed.

Animals↗
PubMed2025

Hepatocyte proteome destabilization and novel targets for PFASs unveiled through combined thermal proteome profiling and deep transfer learning.

Identifying protein targets for per- and polyfluoroalkyl substances (PFASs) is essential to understand their toxicity and health risks. However, knowledge about their interacting proteins is limited since reliable identification methods are lacking. We developed an integrated approach combining thermal proteome profiling (TPP) and deep transfer learning (DTL) modeling to efficiently identify cellular targets of PFAS. TPP measured PFAS binding proteins and the affinities by nanospray liquid chromatography tandem mass spectrometry, while DTL models were constructed to predict PFAS-protein affinities using neural network algorithms. TPP results revealed that PFASs uniquely destabilized the proteome of HepG2 cells, unlike the stabilizing effects by other xenobiotics. Key protein targets for three representative PFASs (PFOA, GenX and Novec 649) were identified, which exhibited weak binding affinities (median EC50 ≈ 30 μM). The number of protein targets increased with molecular weights among the three PFASs. The DTL model achieved a higher Pearson correlation coefficient of 0.89, and reduced mean squared errors by 54 % over previous models for drug-protein interactions. Notably, TPP and DTL jointly pinpointed ribosomal proteins as novel targets of GenX, potentially linking it to cell apoptosis through disrupted protein synthesis. Biolayer interferometry validated GenX binding to RPL4 protein, driven by electrostatic interactions and halogen bonds. This integrated approach effectively uncovers novel PFASs targets, advancing insights into their adverse health effects.

Humans↗
PubMed1976

Crystal structure of a complex between lumiflavin and 2,6-diamino-9-ethylpurine: a flavin adenine dinucleotide model exhibiting charge-transfer interactions.

The x-ray structure of the deep red crystalline complex lumiflavin-2,6-diamino-9-ethylpurine has been determined. The flavin and adenine derivatives form hydrogen-bonded base pairs of the Watson-Crick type. The molecules in the crystal also associate via extensively overlapped flavin/adenine and flavin/flavin stacking interactions in which there are several contacts that are closer than van der Waals distances. This, together with the red color of the crystals, is indicative of the formation of a charge-transfer complex.

Adenine↗
PubMed2026

EvoSNR-Prom: Predicting promoters at single-nucleotide resolution with label-aware transfer learning of the pretrained EVO model.

The precise identification of promoters is crucial for understanding gene regulation. Deep learning methods have achieved considerable success in promoter prediction, yet most operate at the sequence level with coarse-grained labels. This means they label an entire DNA segment as either a "promoter" or "non-promoter," which results in a lack of the nucleotide-level resolution in prediction. In this study, we propose EvoSNR-Prom, a model designed for promoter prediction at single-nucleotide resolution. EvoSNR-Prom is built on the Evo foundation model and formulates promoter identification as a token-level sequence labeling problem, analogous to named entity recognition in natural language processing. To address the limited contextual information available in single-nucleotide tokenization, we introduce a lexicon-enhanced embedding strategy that incorporates biologically meaningful DNA lexicons, enriching contextual representations and improving the model's ability to capture complex sequence motifs. Furthermore, to enhance predictive performance on small size datasets, we integrate a label-aware transfer learning framework to leverage knowledge from well-annotated source species to a target organism. The results across various prokaryotic datasets show that EvoSNR-Prom achieves excellent performance. This work provides a valuable computational framework for the high-precision analysis of gene regulatory elements, contributing to the advancement of promoter prediction at single-nucleotide resolution.

Promoter Regions, Genetic↗
PubMed1989

Crystallization of yeast iso-2-cytochrome c using a novel hair seeding technique.

A hair seeding technique has been developed to obtain diffraction quality crystals of yeast (Saccharomyces cerevisiae) iso-2-cytochrome c, a model for studies of protein folding and biological electron transfer reactions. Deep red crystals of this protein were obtained from 88 to 92% saturated solutions of ammonium sulfate containing 20 mg protein/ml, 0.1 M-sodium phoshate, 0.3 M-sodium chloride, 0.04 M-dithiothreitol and adjusted to phosphate, 0.3 M-sodium chloride, 0.04 M-dithiothreitol and adjusted to pH 6.0. Rapid crystal growth was observed, but only along the path of the seeding hair stroke. The space group is P4(3)2(1)2 (or P4(1)2(1)2) with a = b = 36.4 A, c = 137.8 A (1 A = 0.1 nm) and Z = 8. Crystals are stable in the X-ray beam for more than 10 days and diffract to at least 2.5 A resolution. The same hair seeding methodology has proven useful in obtaining crystals of specifically designed mutant iso-2 proteins and in other protein systems where consistent crystal growth had previously proven difficult to attain.

Crystallization↗
PubMed1978

Electronic properties of sulfhydryl- and imidazole-containing peptide-cobalt(II) complexes: their relationship to cobalt(II)-substituted "blue" copper proteins.

The electronic properties of 2:1 sulfhydryl- and imidazole-containing peptide-Co(II) complexes have been investigated and compared with those of Co(II)-substituted "blue" copper proteins. The Co(II) complexes of N-mercaptoacetyl-L-histidine and 3-mercaptopropionyl-L-histidine gave the ligand field parameters of deltat = 4110 and B = 756 cm(-1), and of deltat = 4120 and B = 724 cm(-1), respectively. These values correspond well to those (deltat = 4900 and B = 730 cm(-1)) of Co(II)-substituted "blue" copper proteins. The energy differences between S leads to M(II) charge transfer bands of Co(II)-Cu(II) couples were about 14,000 cm(-1) in both the proteins and the model complexes. The spectral results suggest that "blue" copper site has a pseudotetrahedral geometry and a deep absorption near 600 nm atributes to S leads to Cu(II) charge transfer.

Cobalt↗
PubMed1988

Miniature implantable laser Doppler probe monitoring of free tissue transfer.

A 2.5-mm fiber-optic laser Doppler flowmetry probe has been applied in an experimental dog model as well as in 5 clinical cases to provide continuous readout of deep tissue perfusion. The rectus abdominis muscle in the dog was used for the experimental verification of the probe, which has a linear correlation with flow rate and a rapid response (6 seconds) to arterial occlusion and venous occlusion (20 seconds). Four of the 5 free tissue transfers survived with the laser Doppler instrument correctly identifying the lack of flow, both intraoperatively and postoperatively, in the failed flap. This probe greatly extends the versatility of laser Doppler flow measurement in the clinical setting and may be nearly an ideal probe for monitoring free tissue transfer, particularly muscle.

Animals↗
PubMed2026

Predictive design of tissue-specific mammalian enhancers that function in the mouse embryo.

Enhancers control tissue-specific gene expression across animals1. Although deep learning2,3 has enabled enhancer prediction and design in mammalian cell lines and non-mammalian model organisms4-10 (reviewed in a previous publication11), it remains unclear whether such approaches can operate within the regulatory complexity of mammalian genomes and tissues in vivo. Here we present a general strategy for designing tissue-specific enhancers that function reliably in mice. We use deep learning to train compact convolutional neural networks on curated chromatin accessibility data and fine-tune them by transfer learning on validated human and mouse enhancers. Guided by these models, we design 15 synthetic enhancers for the heart, limb and central nervous system in mouse embryos, all of which are active in their intended target tissue. These results demonstrate that mammalian enhancer function can be reliably inferred from DNA sequence alone, enabling the predictive de novo design of tissue-specific synthetic enhancers from modest training sets. This work establishes a generalizable framework for programmable control of mammalian gene expression in vivo, opening new avenues in functional genomics, synthetic biology and gene therapy.

Animals↗
PubMed1979

Space-filling models of kinase clefts and conformation changes.

Space-filling models of yeast hexokinase, adenylate kinase, and phosphoglycerate kinase drawn by computer clearly portray the bilobal character of these phosphoryl transfer enzymes, and the deep cleft which is formed between the lobes. A dramatic conformational change occurs in hexokinase as glucose binds to the bottom of the cleft, which causes the two lobes of hexokinase to come together. A substrate-induced closing of the active site cleft is postulated to occur in other kinases as well. This change may provide a mechanism by which some of these enzymes reduce their inherent adenosine triphosphatase activity and could be a general requirement of the kinase reaction.

Adenylate Kinase↗
PubMed1985

Influence of hypothermia and circulatory arrest on cerebral temperature distributions.

A finite element model of the bioheat transfer equation has been developed to simulate the temperature distribution in the head of a subhuman primate. Simulations were made of the induction of deep hypothermia and of subsequent hypothermic circulatory arrest (HCA). Simulations of the circulatory arrest phase were performed with different values of surface heat transfer coefficient and tissue metabolic heat generation. Numerical results were compared with experimental data for the same procedure. The simulations indicate the brain cools rapidly to a near isothermal condition in response to an infusion of cold arterial blood. However, extracerebral structures cool much more slowly. The bulk of heat gain by the brain during HCA is due to heat transfer from these warmer extra-cerebral tissues. These results suggest extended cooling by cardiopulmonary bypass (CPB) combined with surface cooling pads should reduce or even prevent the rise of brain temperatures during HCA.

Animals↗
PubMed2025

DeepWheat: predicting the effects of genomic variants on gene expression and regulatory activities across tissues and varieties in wheat using deep learning.

Spatiotemporal gene expression shapes key agronomic traits, yet tissue-specific prediction remains challenging in complex crops. We present DeepWheat, a broadly applicable deep learning framework comprising DeepEXP and DeepEPI, for accurate, tissue-specific gene expression prediction. DeepEXP integrates sequence and epigenomic features to predict gene expression (PCC 0.82-0.88), while DeepEPI predicts epigenomic maps from DNA sequence to support model transfer across varieties. Validations in five wheat cultivars confirm robustness and accuracy. DeepWheat also identifies regulatory variants with strong expression effects, enabling targeted cis-regulatory elements editing and offering a powerful tool for crop functional genomics and breeding.

Triticum↗
PubMed1990

The influence of model parameter values on the prediction of skin surface temperature: I. Resting and surface insulation.

A model is presented of heat transfer and temperature distributions in the skin and superficial tissues. It is based on a finite difference numerical solution of the one-dimensional multilayer coupled bioheat equation. In this paper, the model is used to investigate the influence of the values of parameters chosen to represent the physiological and heat transfer processes on the temperature of the skin under resting conditions and after insulation of the skin surface. Equilibrium resting temperatures were strongly influenced by deep body temperature especially at lower heat transfer coefficients on the skin surface, but slightly affected by the values chosen for skin blood flow and metabolic heat generation; both the heat transfer coefficients and environmental temperature strongly influenced the surface temperature. After surface insulation the temperature elevation was strongly influenced by the thermal conductivities of tissues, skin blood flow and deep boundary temperature; metabolic heat generation was only significantly at unphysiologically high values.

Humans↗
PubMed1991

The influence of model parameter values on the prediction of skin surface temperature: II. Contact problems.

A model of heat transfer and temperature distribution in the skin and superficial tissues which is based on a finite difference numerical solution of the one-dimensional multilayer coupled bioheat equation is presented. The model is used to investigate the influence of the values chosen to represent the physiological and thermal properties of the tissues on the skin surface temperature after contact with an external medium. It was found that the skin blood flow and dermal conductivity were the main cutaneous parameters which influence the contact response, but in terms of normalized temperature the response was little influenced by cutaneous metabolic heat generation and deep dermal temperature. For contact with a good conductor, the transient behaviour was sensitive to the heat transfer coefficient on the outer surface and the thickness of the contact material, but insensitive to the conductivity of the material.

Humans↗
PubMed1987

Mathematical circulation model for the blood-flow-heat-loss relationship in the rat tail.

A mathematical model for the heat-loss-blood-flow relationship is developed for the rat tail. When supplied with experimental values of heat loss and blood flow, the model allows one to compute the distribution of flow in deep and cutaneous vessels as a function of body core and tail temperature and to determine the savings in heat loss that result from alterations in the pattern of circulation and from counter-current heat transfer. Blood flow in the cutaneous and deep lying veins of the tail is controlled by both central and local temperatures and increases fairly linearly with deep body temperature. However, the distribution of blood flow in the tail is controlled only by local tail temperature and is independent of deep body temperature. The change in venous distribution of flow has a great impact on the conservation of heat and can reduce the heat loss from the circulating blood by more than 50% when venous return is directed to deep lying veins. On the other hand, counter-current heat transfer is of only minor importance in the control of heat loss from the tail, resulting at most in a 10% saving of heat loss, and that only at the smallest rate of blood flow.

Animals↗
PubMed1985

Penetration of a cardiotoxin into cardiolipin model membranes and its implications on lipid organization.

The interaction of cardiotoxin II of Naja mossambica mossambica with cardiolipin model membranes was investigated by binding, fluorescence, resonance energy transfer, fluorescence quenching, 31P NMR, freeze-fracture, and small-angle X-ray experiments. An initially electrostatic binding appeared to be accompanied by a deep penetration, most likely into the acyl chain region of the phospholipids, indicating a hydrophobic contribution to the strong interaction (KD congruent to 5 X 10(-8) M). This binding results in a fusion of unilamellar vesicles as indicated by a fluorescence-based fusion assay, freeze-fracture, and X-ray diffraction. In these fused structures freeze-fracture electron microscopy reveals the appearance of particles, which is accompanied by the induction of an isotropic component in 31P NMR. The well-defined particles are interpreted as inverted micelles, and the localization of the cardiotoxin molecule in these structures is discussed.

Animals↗
PubMedDate not supplied

Differences between two feline epilepsy models in sleep and waking state disorders, state dependency of seizures and seizure susceptibility: amygdala kindling interferes with systemic penicillin epilepsy.

The objective of the study was to determine whether contemporary feline models of petit mal (systemic penicillin epilepsy) or temporal lobe epilepsy (amygdala kindling) resemble human seizure disorders with respect to disturbances of sleep and waking states, the state dependency of seizures, and transference of seizure susceptibility. These variables were examined in 6-h polygraphic recordings before and during exposure to both seizure models in 24 cats; 12 cats had intramuscular (i.m.) injections of 300,000 or 400,000 IU/kg of penicillin prior to kindling, and 12 were kindled before penicillin challenge. Results were as follows. First, penicillin increased light slow wave sleep (SWS) and drowsiness, during which spike-wave (SW) activity was maximal. Generalized tonic-clonic convulsions (GTCs) occurred predominantly in drowsiness after awakening from SWS. Second, kindling produced more deep SWS than did penicillin; susceptibility to kindled GTCs peaked during deep SWS, especially in transition to rapid eye movement sleep (REM). Third, penicillin did not influence subsequent sleep disorders or seizure susceptibility during kindling; kindling interfered with penicillin-induced GTCs, SW activity, and sleep disorders. Collectively, the findings suggest distinct state disorders and state-dependent seizure profiles in the two models. These differences parallel human analogues and may have contributed to the transference results. Kindling is a chronic model with persistent sleep and seizure abnormalities that differ from and may have discouraged penicillin epilepsy. Penicillin is an acute model with transient state and seizure disorders, a fact that may account for the absence of penicillin transference to kindling.

Amygdala↗
PubMed2026

Blood mitochondrial heteroplasmic variants and cognitive performance in late midlife: REGARDS study.

BACKGROUND: Studies linking mitochondrial DNA (mtDNA) variants to cognition yielded inconsistent findings, and the underlying mechanisms remain unclear. We investigated whether mtDNA heteroplasmic variants were associated with cognitive outcomes, including the Montreal Cognitive Assessment (MoCA), in 197 late midlife adults from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort with complete data. METHODS: MtDNA was sequenced from blood using targeted deep sequencing. Adjusted linear and mixed-effects models examined the associations by functional regions, genes, total variant burden, nonsynonymous variants, and control regions. RESULTS: Heteroplasmic variants in the control region (β = -0.44, 95% CI: -0.83, -0.05, p = 0.027) and transfer RNA (tRNA) genes (β = -1.34, 95% CI: -2.58, -0.11, p = 0.034) were associated with MoCA baseline scores. Individual variants in cytochrome c oxidase subunit 1 (CO1) (β = -1.51, 95% CI: -2.54, -0.47, p = 0.005), NADH dehydrogenase subunit 1 (ND1) (β = -2.63, 95% CI: -4.56, -0.70, p = 0.008), and Displacement Loop (D-LOOP2) (β = -2.25, 95% CI: -4.20, -0.30, p = 0.025) was associated with reduced baseline MoCA scores. The ND6 (β = −1.23, 95% CI: −2.09, − 0.37, p = 0.006), ND4 (β = −1.11, 95% CI: −2.02, − 0.20, p = 0.018), ATP Synthase Membrane Subunit 8 (ATP8; β = −1.38, 95% CI: −2.63, − 0.13, p = 0.031), and D-LOOP1 (β = −0.61, 95% CI: −1.20, − 0.01, p = 0.045) genes suggested a potential association with executive function. Longitudinal Animal Fluency Test (AFT) scores were inversely associated with heteroplasmic variants in coding regions (β = -0.10, 95% CI: -0.19, -0.006, p = 0.049), the total number of variants (β = -0.06, 95% CI: -0.11, -0.003, p = 0.037) and total nonsynonymous variants (β = -0.11, 95% CI: -0.21, -0.01, p = 0.040). Variants in the control region were associated with the greatest decline in verbal fluency (β = −0.20, 95% CI: −0.39 to − 0.002, p = 0.049). No associations were observed between mitochondrial variants and verbal memory performance or the MoCA composite scores. CONCLUSIONS: Our study indicates that mitochondrial variants measured in blood may provide insight into cognitive function during midlife. However, additional studies are needed to validate these associations and to address potential power limitations in our study.

Humans↗