arXiv subjects

Dipankar Biswas

Publications and source records attributed to Dipankar Biswas.

4 recordsLinked to original sources

arXiv2026

Alteration of the Brains Microbiome and Neuroinflammation Associated with Ventricular Catheters

Background and Objectives: Proximal catheter obstruction is the leading cause of ventriculoperitoneal shunt failure, yet the biological triggers of peri-catheter inflammation and tissue ingrowth remain poorly defined. Evidence of bacterial ribosomal RNA in human brain tissue suggests that low-biomass microbial exposure may influence the inflammatory microenvironment surrounding implants. This study examined if microbial signal is detectable in unaltered brain tissue and if catheter implantation produces microbial shifts relevant to shunt dysfunction. Methods: Twenty-nine female mice were assigned to unaltered control (UC), trauma control (TC), plain silicone catheter (PSC), or antibiotic-impregnated catheter (AIC) groups. Brain and cecum tissues were harvested at postoperative days 7 and 28 for 16S rRNA sequencing. Microbial composition and predicted functional pathways were analyzed. A separate cohort underwent longitudinal MRI to assess edema, glial scar formation, and macrophage-associated susceptibility signal. Results: Low-level microbial signal was detected in unaltered brain tissue. Catheter implantation induced material-dependent shifts in brain-associated microbial composition. PSC was associated with enrichment of pro-inflammatory taxa, whereas AIC favored immune-regulatory taxa. Predicted short-chain fatty acid biosynthesis was highest in AIC and lowest in PSC, while predicted lipopolysaccharide biosynthesis trended higher in PSC. MRI showed similar edema resolution but higher macrophage-associated susceptibility signal in PSC animals. Conclusion: Intracranial catheter implantation produces material-dependent shifts in low-biomass brain-associated microbial signal that parallel differential neuroimmune activation. These findings suggest catheter material may shape a biologically relevant peri-catheter niche with implications for chronic gliosis and proximal shunt obstruction.

q-bio.GN↗

arXiv2026

A Framework for Feature Discovery in Intracranial Pressure Monitoring Data Using Neural Network Attention

We present a novel framework for analyzing intracranial pressure monitoring data by applying interpretability principles. Intracranial pressure monitoring data was collected from 60 patients at Johns Hopkins. The data was segmented into individual cardiac cycles. A convolutional neural network was trained to classify each cardiac cycle into one of seven body positions. Neural network attention was extracted and was used to identify regions of interest in the waveform. Further directions for exploration are identified. This framework provides an extensible method to further understand the physiological and clinical underpinnings of the intracranial pressure waveform, which could lead to better diagnostic capabilities for intracranial pressure monitoring.

q-bio.QM↗

arXiv2025

Scaling Laws and Universal Features of Tethered Polymer Distributions in Confined Geometries

We develop a unified scaling framework for the end-position distributions of tethered polymers confined in finite cylindrical geometries. Two observables are analysed: the longitudinal distribution P(x), along the confinement axis, and the transverse distribution P(y), perpendicular to the confinement axis. Using exact Fourier-sine and image-method representations with adaptive numerical schemes, we construct and test six scaling strategies for P(x) and five for P(y), encompassing geometric similarity, tether-position sweeps, confinement-strength crossovers, persistence-length effects, boundary-layer scaling near absorbing walls, and tether-centered coil scaling. Quantitative collapse diagnostics such as RMS residuals on common support, modal-energy fractions, and survival probabilities are combined with limiting-regime analysis and direct numerical evaluation to distinguish genuine universality from visually misleading overlap. From these tests we obtain a kappa-based confinement diagram and a two-parameter (kappa, a/L) regime map that link classical theories such as Flory/de Gennes blobs, Odijk deflection segments, and wormlike-chain behaviour within a single spectral picture. Gaussian, multimode, and eigenmode-dominated regimes are identified by explicit thresholds in modal composition and collapse error, providing operational criteria for when Gaussian or single-mode descriptions are valid and when full multimode structure is required. The resulting framework provides a compact, reproducible toolkit for analysing confined-polymer statistics, with applications to simulations and experiments on DNA, chromatin, and other biopolymers where confinement, stiffness, and tethering jointly control spatial organization.

cond-mat.soft↗

arXiv2020

Charge trap layer enabled positive tunable V$_{fb}$ in $β$-Ga$_{2}$O$_{3}$ gate stacks for enhancement mode transistors

$β$-Ga$_{2}$O$_{3}$ based enhancement mode transistor designs are critical for the realization of low loss, high efficiency next generation power devices with rudimentary driving circuits. A novel approach towards attaining a high positive flat band voltage (V$_{fb}$) of 10.6 V in $β$-Ga$_{2}$O$_{3}$ metal-oxide-semiconductor capacitors (MOSCAPs), with the ability to fine tune it between 3.5 V to 10.6 V, using a polycrystalline AlN charge trap layer has been demonstrated. This can enable enhancement mode operation over a wide doping range. Excellent V$_{fb}$ retention of ${\sim}$97% for 10$^{4}$ s at 55 $^{\circ}$C was exhibited by the gate stacks after charge trapping, hence reducing the requirement of frequent charge injection cycles. In addition, low gate leakage current density (J$_{g}$) for high negative gate voltages (V$_{g}$${\sim}$-60 V) indicates the potential of this gate stack to enable superior breakdown characteristics in enhancement mode transistors.

physics.app-ph↗