Biology subjects

Azimi, A.

Publications and source records attributed to Azimi, A..

12 recordsLinked to original sources

bioRxiv2026

Distinct nigral and brainstem pathology markers map onto separable subthalamic electrophysiological signatures in Parkinson's disease

Subthalamic local field potentials (LFPs) are increasingly used as physiomarkers of the symptomatic state in Parkinsons disease, but their relationship to the underlying neurodegenerative pathology remains unclear. Here, we combined OFF-medication subthalamic LFP recordings with quantitative MRI markers of nigral and brainstem pathology in 33 people with Parkinsons disease. Distinct pathological markers mapped onto dissociable electrophysiological components. Substantia nigra pars compacta susceptibility was associated with increased occupancy, duration and rate of low-{beta} bursts, whereas nigral free water was associated with greater low-frequency aperiodic offset and a steeper slope. Pedunculopontine nucleus free-water- corrected axial diffusivity was selectively associated with high-frequency aperiodic activity, and this relationship strengthened with increasing nigral susceptibility, consistent with dopaminergic-state- dependent influences of extranigral pathology on subthalamic physiology. Only low-frequency aperiodic offset was also associated with contralateral bradykinesia. These findings indicate that the subthalamic LFP is not a unitary readout of dopamine loss or motor state, but an integrated physiological signal in which pathology across interconnected systems is expressed through separable oscillatory and aperiodic components. Chronically implanted devices may therefore provide physiological readouts of underlying disease biology alongside control signals for adaptive therapy.

neuroscience↗

bioRxiv2025

Attcatvgg-Net: an Explainable Multioutput Deep Learning Framework for Cataract Stage Classification and Visual Acuity Regression using Multicolor Fundus Images

PurposeThe purpose of this study is to develop and evaluate an attention-guided deep learning model using the multicolor imaging module of Spectralis Optical Coherence Tomography (OCT) imaging for automated cataract severity classification and Visual Acuity (VA) prediction. MethodsWe analyzed 314 multicolor fundus images from 169 patients. Images were preprocessed using an enhanced Retinex algorithm and segmented into three concentric macular zones: Zone 1 (fovea, central 1.5 mm diameter), Zone 2 (parafovea, 1.5-2.5 mm ring), and Zone 3 (perifovea, >2.5 mm radius). A multi-output convolutional neural network (AttCatVgg-Net), based on VGG-16 and enhanced with a Convolutional Block Attention Module (CBAM), was trained to simultaneously perform three-class cataract classification (normal to mild, moderate, severe) and visual acuity (VA) regression. Model performance was assessed using accuracy, AUC, F1-score, and regression metrics. Statistical analyses included the Wilcoxon signed-rank test and the Spearman correlation test. ResultsFor cataract grading, the integrated model using all wavelengths and zones achieved 92.5% accuracy, 94.7% area under the ROC curve (AUC), and a 92.1% F1-score. The green channel alone achieved 90.1% accuracy and 0.93 AUC, while the red channel yielded lower performance (76.3% accuracy, 0.83 AUC). Among anatomical zones, Zone 1 (fovea) and Zone 3 achieved 84.3% and 84.71% accuracy and 0.88 and 0.89 AUC, respectively, whereas Zone 2 underperformed (60.41% accuracy, 0.71 AUC). For visual acuity prediction, the full model achieved a mean absolute error (MAE) of 0.1181 and a coefficient of determination (R-squared) of 0.7759. The green channel demonstrated the strongest correlation with actual VA (correlation coefficient = 0.823, p < 0.001), followed by green-red (0.817) and blue (0.809). The green channel also achieved the lowest Mean Squared Error (MSE = 0.0369) and Root Mean Square Error (RMSE = 0.1920), outperforming other channels. ConclusionsAttention-guided deep learning applied to Spectralis OCT multicolor imaging enables accurate, objective classification of cataract severity and estimation of cataract-related visual acuity loss.

bioengineering↗

bioRxiv2025

A canonical gated neural circuit model for flexible perceptual decisions

Flexible perceptual decision-making requires rapid, context-dependent adjustments, yet the neural circuit mechanisms underlying its parsimonious representations remain unclear. Here, we propose a minimal mean-field neural circuit model that integrates sensory evidence and selects actions via distributed neuronal encoding, guided by data from a task that dissociates perceptual choice from motor response - abstract perceptual decision-making. The models nonlinear gating of action selective (AS) neurons replicates parietal cortical activity observed during task performance. Critically, recurrent excitation within the evidence integration (EI) population supports sensory evidence accumulation, working memory for sequential sampling, and reward rate optimisation. Moreover, the dynamics of EI and AS neuronal activities in the same model respectively mirror parietal neuronal activities related to sensory evidence encoding and ramping-to-threshold firing in a separate reaction-time task, while suggesting that decision readout engages both neuronal populations. The model also predicts decision interference in a novel two-stage decision version of the task, accounting for choice accuracy decrements observed in other experiments while predicting slower decisions. Together, these findings propose a minimal mean-field circuit-level mechanism unifying perceptual, memory-based, and abstract decision-making.

neuroscience↗

bioRxiv2025

Palbociclib CDK4/6- and Crizotinib MET/ALK/ROS1-inhibitors Synergize to Enhance Senescence and Immune Recognition in Melanoma Cells Independently of BRAF/NRAS Status

"Pro-senescence therapy", which triggers both permanent cell cycle arrest and an immune response, has been proposed as a strategy for cancer treatment, but is still controversial. To assess this strategy in melanoma, we performed a high throughput microscopy-based senescence screen utilizing a panel of melanoma cell lines with different driver mutations and a collection of clinical and experimental drugs. We found that vemurafenib and trametinib, which inhibit BRAFV600E and MEK1/2, respectively, induced senescence in some but not all BRAF-mutant cell lines. In contrast, palbociclib, BKM-120 and crizotinib, which inhibit CDK4/6, PI3K, and MET/ALK/ROS1, respectively, triggered senescence in most cell lines, irrespective of BRAF/NRAS mutation status, and overcame intrinsic and acquired vemurafenib resistance. The combination of palbociclib and crizotinib synergized to further enhance the senescence response in all cell lines irrespective of BRAF/NRAS mutation status, increased the expression of SASP factors, such as IL-1 and {beta}, and HLA class I and other markers for recognition by NK and T cells. Further, this combination caused a significant increase in CD8+ T cells and pro-inflammatory macrophages in the tumor microenvironment and a marked reduction of mouse melanoma tumor growth that was dependent on CD8+ T cells, suggesting increased immune surveillance. Our findings suggest that pro-senescence therapy based on concomitant inhibition of both CDK4/6 and MET/ALK/ROS1 could be developed further as an alternative treatment strategy for melanoma. Significance: Pro-senescence therapy based on combined targeting of CDK4/6 with palbociclib and MET/ALK/ROS1 with crizotinib inhibits melanoma tumor growth through anti-tumor immune response activation, providing an alternative treatment strategy for melanoma.

cancer biology↗

bioRxiv2025

Neural oscillation as a selective modulatory mechanism on decision confidence, speed and accuracy

Neural oscillations have been associated with decision-making processes, but their underlying network mechanisms remain unclear. This study investigates how neural oscillations influence decision network models of competing cortical columns with varying intrinsic and emergent timescales. Our findings reveal that decision networks with faster excitatory than inhibitory synapses are more susceptible to oscillatory modulations. Higher in-phase oscillation amplitude reduces decision confidence without affecting accuracy, while decision speed increases. In contrast, anti-phase modulation increases decision accuracy, confidence and speed. Increasing oscillation frequency reverses these effects. Changing oscillatory phase difference gradually modulates decision behaviour, with decision confidence affected nonlinearly. Moreover, neural resonance can further enhance modulatory susceptibility for network with faster excitatory than inhibitory synapses. These effects decouple decision accuracy, speed and confidence, challenging standard speed-accuracy trade-off. These phenomena can be explained by excitatory neural populations contributing more to in-phase modulation, while inhibitory neural populations to anti-phase modulation. State-space trajectories momentum swinging with respect to network steady states and decision uncertainty manifold further provide insights into the neural circuit mechanisms. Our work provides mechanistic insights into how neurobiological diversity shapes decision-making processes in the presence of ubiquitous neural oscillations. Significance StatementNeural oscillations shape how the brain balances decision speed, accuracy, and confidence. Here, we show that tuning oscillatory amplitude, frequency, or phase can selectively alter these decision measures. In some cases, these modulations even break the usual trade-off between speed and accuracy, revealing a more flexible decision-making mechanism than previously assumed. Our findings highlight how synaptic time scales and rhythmic brain activity can give rise to distinct patterns of decision performance. This insight may guide new strategies for improving decisional processes in both healthy populations and clinical conditions.

neuroscience↗

bioRxiv2025

Limitations of Dynamic Causal Modelling for Multistable Cortical Circuits

Dynamic causal modelling (DCM) is widely used to infer effective connectivity from neuroimaging data. However, its applicability to neural systems with complex, multistable dynamics remains uncertain--particularly when using the standard estimation approach based on variational Bayesian inference under the Laplace approximation. To investigate this limitation, we constructed biologically grounded cortical columnar neural mass models exhibiting three distinct multistable regimes: bistable fixed points associated with decision-making, coexisting oscillatory states through period-doubling bifurcations, and deterministic chaotic dynamics. These models were used to simulate local field potentials, which served as inputs to DCM. Bayesian model selection successfully identified the correct model architecture in all cases. However, Bayesian model averaging of the winning models failed to accurately estimate extrinsic connectivity parameters, leading to substantial discrepancies between the dynamics of the reconstructed and ground-truth systems. These results suggest that even when model selection is accurate, parameter estimation can break down under complex dynamics. Compared to previous applications of DCM to simpler neural systems, our study highlights significant limitations in its ability to capture the structure of multistable and globally nonlinear dynamics. We conclude that caution is warranted when applying variational Laplace-based DCM procedures to experimental paradigms involving bifurcations, chaotic trajectories, or other forms of dynamical complexity.

neuroscience↗

bioRxiv2021

Biocide's susceptibility and frequency of biocide resistance genes and the effect of exposure to sub-inhibitory concentrations of sodium hypochlorite on antibiotic susceptibility of Stenotrophomonas maltophilia

The overuse of biocides in healthcare-facilities poses risk for emergence and spread of antibiotic resistance among nosocomial pathogens. Hospital-acquired infections due to S. maltophiliahave been increased. The objective of this study was to evaluate the susceptibility of S. maltophilia clinical isolates to commonly used biocides in hospitals, as well asthe frequency of biocides resistance genes among them. This study also intended to assess the effect of exposureof S. maltophilia isolates to sub-inhibitory concentrations of sodium hypochlorite upon the antimicrobial susceptibility patterns.This study included 97 S.maltophiliaisolates.Biofilm formation was determined by microtiter plate assay. The susceptibility tests of five biocides were studied against all S. maltophilia isolates by microbroth dilution method. Susceptibility of isolates to antibiotics by disk diffusion method were compared before and after exposure to sub-inhibitory concentrations of sodium hypochlorite. Presence of qacE, qacE{Delta}1, SugE genes was screened by PCR. Based on minimum inhibitory and bactericidal concentrations of biocidessodium hypochlorite 5% and ethyl alcohol 70% were the strongest and weakest against S. maltophilia isolates, respectively. The frequency of sugE gene resistance genes was found 90.7% in our clinical S. maltophilia isolates. None of the isolates carried qacE and qacE{Delta}1 gene. Exposure to sub-inhibitory concentration of sodium hypochlorite showed significantly change the susceptibility of isolates towards ceftazidime (P = .019), ticarcillin/clavulanate (P = .009), and chloramphenicol (P = .028).This study demonstrated that exposure to sub-inhibitory concentrations of sodium hypochlorite leads to reduced antibiotic susceptibility and development of multidrug-resistant S.maltophilia strains.

microbiology↗

bioRxiv2021

Enhancement of hippocampal-thalamocortical temporal coordination during slow-frequency long-duration anterior thalamic spindles

Temporal nesting of cortical slow oscillations (SO), thalamic spindles and hippocampal ripples indicates the succession of regional neuronal interactions required for memory consolidation. However how the thalamic activity during spindles organizes hippocampal dynamics remains largely undetermined. We analyzed simultaneous recordings of anterodorsal thalamus and CA1 in mice to determine the contribution of thalamic spindles in cross-regional synchronization. Our results indicated that temporal hippocampo-thalamocortical coupling were more enhanced during slower and longer thalamic spindles. Additionally, spindles occurring closer to SO trough were more strongly coupled to ripples. We found that the temporal association between CA1 spiking/ripples and thalamic spindles was stronger following spatial exploration compared to baseline sleep. We further developed a hippocampal-thalamocortical model to explain the mechanism underlying the duration and frequency-dependent coupling of thalamic spindles to hippocampal activity. Our findings shed light on our understanding of the functional role of thalamic activity during spindles on multi-regional information transfer.

neuroscience↗

bioRxiv2021

Electrolysis of Bacterial Biofilm

Biofilms are a significant global health problem and are of most important clinical impediments of the century. Biofilms play a crucial role in antimicrobial resistance and chronic infections by acting as reservoir for microorganisms. Therefore greater understanding of biofilm and novel methods to eliminate them are needed. We considered electrolysis as a contrivance to decompose and disperse the Pseudomonas aeruginosa biofilm in microtiter dishes. We showed electrolysis effectively eliminated the Pseudomonas aeruginosa biofilm with the potential to change our approach in tackling biofilms.

microbiology↗

bioRxiv2020

PTENP1-AS contributes to BRAF inhibitor resistance and is associated with adverse clinical outcome in stage III melanoma

Approximately 50% of human cutaneous melanomas carry activating mutations in the serine/threonine protein kinase BRAF. BRAF inhibitors (BRAFi) selectively target the oncogenic BRAFV600E/K and are effective in approximately 80% of patients carrying the mutation. However, resistance to BRAFi is common and emerges within a median time of 6-7 months of treatment and is prolonged to 11 months when combined with MEK inhibitors. Better characterization of the underlying molecular processes is therefore needed to further improve treatments. Inactivation of the tumor suppressor gene PTEN has been suggested to occur during melanomagenesis and drug resistance development. We recently demonstrated that transcription of PTEN is negatively regulated by an antisense RNA from the PTEN pseudogene (PTENP1-AS) and here set out to investigate the impact of this molecular pathway on the resistance to BRAFi and clinical outcome. We used a panel of BRAFi resistant A375 sublines, and observed increased levels of PTENP1-AS associated with reduced expression of PTEN. Furthermore, this loss of PTEN expression was correlated to increased recruitment of Enhancer of zeste homolog 2 (EZH2) and formation of the transcriptional repression mark H3K27me3 at the PTEN promoter in the resistant cells. We demonstrated that targeting of PTENP1-AS was able to re-activate the expression of PTEN and sensitize resistant melanoma cells to BRAFi. Finally, we showed that PTENP1-AS is a promising prognostic marker for clinical outcome in melanoma patients as high expression of PTENP1-AS in regional lymph node metastases from stage III melanoma patients correlated with poor survival.

cancer biology↗

bioRxiv2020

A comprehensive proteomic SWATH-MS workflow for profiling blood extracellular vesicles: a new avenue for glioma tumour surveillance

There is a real need for biomarkers that can indicate glioma disease burden and inform clinical management, particularly in the recurrent glioblastoma (GBM; grade IV glioma) setting where treatment-associated brain changes can confound current and expensive tumour surveillance methods. In this regard, extracellular vesicles (EVs; 30-1000 nm membranous particles) hold major promise as robust tumour biomarkers. GBM-EVs encapsulate molecules that reflect the identity and molecular state of their cell-of-origin and cross the blood-brain-barrier into the periphery where they are readily accessible. Despite the suitability of circulating-EVs for GBM biomarker discovery, sample complexity has hindered comprehensive quantitative proteomic studies. Here, sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) was used in conjunction with a targeted data extraction strategy to comprehensively profile circulating-EVs isolated from plasma. Plasma-EVs sourced from pre-operative glioma II-IV patients (n=41) and controls (n=11) were sequenced by SWATH-MS, and the identities and absolute quantities of the proteins were extracted by aligning the SWATH-MS data against a custom glioma spectral library comprised of 8662 high confidence protein species. Overall, 4054 plasma-EV proteins were quantified across the cohorts, and putative circulating-EV biomarker proteins identified (adjusted p-value<0.05) included previously reported GBM-EV proteins identified in vitro and in neurosurgical aspirates. Principle component analyses showed that plasma-EV protein profiles clustered according to glioma subtype and WHO-grade, and plasma-EV proteins reflected the extent of glioma aggression. Using SWATH-MS, we describe the most comprehensive proteomic plasma-EV profiles for glioma and highlight the promise of this approach as an accurate and sensitive tumour monitoring method. Objective blood-based measurements of glioma tumour activity will support the implementation of next-generation, patient-centred therapies and are ideal surrogate endpoints for recurrent progression that would allow clinical trial protocols to be more dynamic and adapt to the individual patient and their cancer.

pathology↗

bioRxiv2018

Chemogenetic inhibition of ventral tegmental area dopamine neurons or their inputs to the nucleus accumbens disrupts cue-triggered reward seeking but not reward taking

Reward-paired cues stimulate reward-seeking behavior through a combination of motivational and cognitive processes. We used pathway-specific chemogenetic inhibition of dopamine neurons to determine their role in the cue-elicited reward seeking, and applied a novel analytic approach to assay cue-induced changes in reward expectancy. Inhibiting ventral tegmental area dopamine neurons abolished cue-induced reward seeking but not reward retrieval, indicating that this pathway modulates response vigor but not reward expectancy. Locally inhibiting dopamine inputs to nucleus accumbens also disrupted cue-elicited reward seeking but not retrieval. Interestingly, the suppression produced by this treatment was greater in rats that responded to cues with exploratory reward seeking, without attempting to retrieve reward, than in rats exhibiting complete bouts of seeking with retrieval, indicating that individuals differ in their reliance on a dopamine-mediated motivational process. These findings shed new light on the behavioral and neural mechanisms of adaptive and compulsive forms of cue-motivated behavior.

neuroscience↗