Biology subjects

Farooqi, H.

Publications and source records attributed to Farooqi, H..

5 recordsLinked to original sources

bioRxiv2025

Metric Validation for Detection of Delayed and Directed Coupling

BackgroundThe brain functions as a complex network of billions of interconnected neurons, coordinating processes from basic reflexes to high-level cognition. Dysfunction in these networks contribute to neurological and psychiatric disorders, including epilepsy, depression, and Parkinsons disease. Understanding these network alterations is essential for developing effective therapies. However, reconstructing network topology from human electrophysiology data is challenging due to sparse sampling, measurement noise, and variable time delays in interregional communication. Effective connectivity (EC) metrics have been developed to infer directed neural interactions, but their accuracy and robustness under real-world data constraints remain unclear. This study empirically evaluates common EC metrics to determine which most accurately reconstruct network topology in the presence of data limitations. MethodsWe generated Erd[o]s-Renyi networks and simulated time series using a time-delayed vector autoregressive (VAR) model. We systematically varied network size, data length, measurement noise, and network coverage. Variations of four commonly used EC metrics, cross-correlation, Granger causality, mutual information, and transfer entropy, were evaluated for reconstruction accuracy using cosine distance to compare estimated and true connectivity matrices. ResultsMultivariate transfer entropy demonstrated the highest accuracy across various conditions but required significantly longer computation times. For small networks (<30 nodes), mutual information and Granger causality rapidly and accurately reconstructed networks. For larger networks, partial cross-correlation performed well with good computational efficiency. Notably, zero-lag metrics perform no better than chance in nearly all conditions. ConclusionThe choice of an EC metric should consider specific data constraints.While multivariate transfer entropy is the most reliable across conditions, its long runtime limits its practical application. For large networks, partial cross-correlation offers a faster and reasonably accurate alternative. Granger causality and mutual information are effective for small networks. Critically, time-lagged metrics are essential for accurate network reconstructions, as failing to account for time delays leads to reconstructions no more accurate than random network models.

bioinformatics↗

bioRxiv2023

Inhibition of miR-214 expression by small molecules alleviates head and neck cancer metastasis by targeting ALCAM/TFAP2 signaling.

Predominantly, head and neck cancer (HNC) is considered a regional disease and develops in the nasal cavity, oral cavity, tongue, pharynx, and larynx. In the advanced stage, the HNC spread into distant organs. By the time head and neck cancer diagnosed, the estimated metastasis is occurred in 10-40% cases. The most important vital organs affected by distant metastasis are the lungs, bones, and liver. Despite several advancements in chemotherapies, no significant changes are observed as 5-year survival rate remains the same. Therefore, it is crucial to decipher molecular mechanisms contributing to the metastatic dissemination of head and neck cancer. Here, we tested a novel ALCAM/TFAP2 signaling by targeting multidisciplinary miR-214 expression in head and cancer cells. Our results revealed that HNC cell lines (CAL27, SCC-9, SCC-4, and SCC-25) exhibit higher expression of miR-214 compared with normal human bronchial epithelial (NHBE) cells. Higher expression of miR-214 drives the invasive potential of these cell lines. Down-regulation of miR-214 in CAL27 and SCC-9 cells either using an anti-miR-214 inhibitor (50nM) or a small molecule of green tea (EGCG) inhibited cell invasion. Treating CAL27 and SCC-9 cells with EGCG also reduces ALCAM expression, a key activated leukocyte cell adhesion molecule, potentially blocking mesenchymal phenotype. Dietary administration of EGCG significantly inhibits distant metastasis of SCC-9 cells into the lungs, liver, and kidneys. Our results also demonstrate that the reduction of miR-214 expression influences in vitro cell movement and extravasation, as evident by reduced CD31 expression, a neovascularization marker. Together, these studies suggest that identifying bioactive molecules that can inhibit distant metastasis regulated by the miRNAs may provide potent interventional approaches and a better understanding of the complex functions of miRNAs and their therapeutic targets for clinical application.

cancer biology↗

bioRxiv2023

Differentially deregulated microRNAs contribute to ultraviolet radiation-induced photocarcinogenesis through immunomodulation: An-analysis of microRNAs expression profiling.

MicroRNAs (miRNAs) are short non-coding RNA molecules (18-25 nucleotides) that regulate several fundamental biological processes. Emerging evidence has shown more than 1500 miRNAs functions in the cell cycle, proliferation, apoptosis, oxidative stress, immune response, DNA damage, and epigenetics alterations. miRNAs are bidirectionally in nature and act as a tumor suppressor and as an oncogene through crosstalk between tumor cells and immune cells. Although the roles of miRNAs in several cancers are well studied, little is known about ultraviolet B (UVB) radiation-induced skin cancer. Here, we performed a comprehensive screening of 1281 miRNAs in tumor tissues and compared their expression with normal skin. Our results demonstrate that the expression levels of 587 miRNAs were altered in tumor tissues compared to their expression in normal skin. The expression of 337 miRNAs was upregulated from 1.5-12 folds, while the expression of 250 miRNAs was downregulated up to 1.5-10 folds in tumors. Further, intraperitoneal injection of a mimic of down-regulated miR-15b (30nM) and an inhibitor of upregulated miR-133a (20nM) protect UVB-induced suppression of contact hypersensitivity (CHS) response. In conclusion, we identified a network of altered miRNAs in tumors that can serve as prognostic biomarkers and therapeutic targets to manage photocarcinogenesis effectively.

cancer biology↗

bioRxiv2022

Deep brain stimulation pulse sequences to optimally modulate frequency-specific neural activity

Precise neuromodulation systems are needed to identify the role of neural oscillatory dynamics in brain function, and to advance the development of electrical stimulation therapies tailored to each patients signature of brain dysfunction. Low-frequency, local field potentials (LFPs) are of increasing interest for the development of these systems because they reflect the synaptic inputs to a recorded neuronal population and can be chronically recorded in humans. Here, we identified stimulation pulse sequences to optimally minimize or maximize the 2-norm of frequency-specific LFP oscillations using a generalized mathematical model of spontaneous and stimulation-evoked LFP activity, and a subject-specific model of neural dynamics in the pallidum of a Parkinsons disease patient. We leveraged convex and mixed-integer optimization tools to identify the pulse patterns, and employed constraints on the pulse frequency and amplitude that are required to keep electrical stimulation within its safety envelope. Our analysis revealed that a combination of phase, amplitude, and frequency pulse modulation is needed to attain optimal suppression or amplification of the targeted oscillations. Phase modulation is sufficient to modulate oscillations with a constant amplitude envelope. To attain optimal modulation for oscillations with a time-varying envelope, a trade-off between frequency and amplitude pulse modulation is needed. The optimized pulse sequences identified here were invariant to changes in the dynamics of stimulation-evoked neural activity, including the damping and natural frequency or complexity (i.e., generalized vs. patient-specific model). Our results reveal the structure of pulse sequences that can be used in closed-loop brain stimulation devices to control neural activity in real-time. Significance StatementThis computational study reveals the structure of electrical pulse sequences that optimally modulate spontaneous, synaptic-related neural oscillations measured using local field potentials (LFPs). We considered constraints on the pulse amplitude and frequency, relevant to keep stimulation pulses within the safety envelope. Our mathematical analysis indicate that these optimized pulse sequences are invariant to changes in the studied neural dynamics, and a trade-off between amplitude and frequency pulse modulation is critical when the pulse amplitude is constrained. The pulse sequences identified here provide the rationale for the development of closed-loop neuromodulation systems that employ stimulation-evoked responses to control neural activity. These closed-loop systems will be key to characterize the role of neural activity in brain function and ultimately advance personalized neuromodulation devices.

bioengineering↗

bioRxiv2021

Controlling pallidal oscillations in real-time in Parkinson's disease using evoked interference deep brain stimulation (eiDBS): proof of concept in the human

Approaches to control basal ganglia neural activity in real-time are needed to clarify the causal role of 8-35 Hz ("beta band") oscillatory dynamics in the manifestation of Parkinsons disease (PD) motor signs. Here, we show that resonant beta oscillations evoked by electrical pulse with precise amplitude and timing can be used to predictably suppress or amplify spontaneous beta band activity in the internal segment of the globus pallidus (GPi) in the human. Using this approach, referred to as closed-loop evoked interference deep brain stimulation (eiDBS), we could suppress or amplify frequencyspecific (16-22 Hz) neural activity in a PD patient. Our results highlight the utility of eiDBS to characterize the role of oscillatory dynamics in PD and other brain conditions, and to develop personalized neuromodulation systems.

neuroscience↗