Biology subjects

Tamang, S.

Publications and source records attributed to Tamang, S..

4 recordsLinked to original sources

bioRxiv2025

Acid-Sensing Ion Channel 1a Deficiency Drives Endocrine Hypertension in Male Mice

BackgroundAcid-sensing ion channel 1a (ASIC1a) is an H+-gated cation channel that responds to extracellular acidosis in both normal and pathological states, including ischemia, inflammation, and metabolic disturbances. While ASIC1a regulates vascular reactivity, its role in blood pressure regulation remains unclear, particularly concerning sex, aging, and disease. This study aims to investigate whether ASIC1a: 1) contributes to cardiovascular function in a sex-dependent manner; 2) plays a dynamic role in cardiovascular homeostasis with aging; and 3) modulates the development of angiotensin II-induced systemic hypertension. MethodsRadiotelemeters were implanted in 6- and 18-month-old male and female wild-type (Asic1a+/+) and ASIC1a knockout (Asic1a-/-) mice to monitor mean arterial blood pressure and heart rate under baseline conditions and in response to angiotensin II. Blood gases, electrolytes, hormones, and end-organ injury were also assessed. ResultsAged male Asic1a-/- mice develop hypertension driven by aldosterone excess and sympathetic overactivity, which is accompanied by cardiac hypertrophy, aortic fibrosis, and glomerular hypertrophy. Female Asic1a-/- mice remain unaffected. In male Asic1a-/- mice, hyperaldosteronism occurs independent of the renin-angiotensin system and mitigates angiotensin II-induced hypertension. Furthermore, 6-month-old male Asic1a-/- mice exhibit elevated corticosterone, hypokalemia, reduced urine osmolality, increased pulse pressure, and cardiomyocyte hypertrophy that precedes hypertension. ConclusionsThese findings establish ASIC1a as a novel, sex-specific regulator of cardiovascular function, linking early corticosterone excess in male mice to hyperaldosteronism and implicating ASIC1a deficiency as a potential driver of endocrine-related hypertension. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/645371v2_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@145dcf0org.highwire.dtl.DTLVardef@1ac468eorg.highwire.dtl.DTLVardef@14c4ad5org.highwire.dtl.DTLVardef@1c4fd2e_HPS_FORMAT_FIGEXP M_FIG C_FIG

physiology↗

bioRxiv2022

A machine learning liver-on-a-chip system for safer drug formulation

Drug metabolism leads to biotransformations of pharmaceutical substances that alter drug efficacy, toxicity, as well as drug interactions. Modeling these processes ex vivo stands to greatly accelerate our capacity to develop safe and efficacious drugs and formulations. Recognizing the liver as the primary site of drug metabolism, here we report a novel whole-tissue ex vivo liver screening platform that enabled modeling of hepatic metabolism and tracking of hepatotoxic drug metabolites. We applied the system for the characterization of acetaminophen (APAP) metabolism and identified interactions that can mitigate the generation of toxic metabolites ex vivo. Combining our experimental platform with state-of-the-art machine learning, we validated two novel functional excipients that can prevent APAP hepatotoxicity in vivo in mice. To assess translational potential, we prototyped a novel solid dosage form with controlled release of both APAP and our functional excipients. Our this platform provides innovative potential access to actionable data on drug metabolism to support the development of new therapeutic approaches.

bioengineering↗

bioRxiv2020

Temporally-specific sequences of neural activity across interconnected corticolimbic structures during reward anticipation

Functional neuroimaging studies indicate that interconnected parts of the subcallosal anterior cingulate cortex (ACC), striatum, and amygdala play a fundamental role in affect in health and disease. Yet, while the patterns of neural activity engaged in striatum and amygdala during affective processing are well established, especially during reward anticipation, little is known about subcallosal ACC. Here we recorded neural activity in non-human primate subcallosal ACC and compared this to interconnected parts of basolateral amygdala and rostromedial striatum while macaque monkeys performed reward-based tasks. Applying multiple analysis approaches, we found that neurons in subcallosal ACC and rostromedial striatum preferentially signal anticipated reward using short bursts of activity that form temporally specific patterns. By contrast, basolateral amygdala uses a mixture of both temporally specific and more sustained patterns of activity to signal anticipated reward. Thus, dynamic patterns of neural activity across populations of neurons are engaged in affect, especially in subcallosal ACC. HIGHLIGHTSO_LISustained changes in neural activity signal anticipated reward in basolateral amygdala C_LIO_LITemporally specific patterns signal anticipated reward in all areas recorded C_LIO_LINeurons exhibit more punctate encoding when tasks become more complex C_LIO_LITemporally specific patterns of neural activity signal different anticipated rewards in BLA C_LI

neuroscience↗

bioRxiv2017

Amygdala Input Differentially Influences Prefrontal Local Field Potential And Single Neuron Encoding Of Reward-Based Decisions

Reward-guided behaviors require functional interaction between amygdala, orbital (OFC), and medial (MFC) divisions of prefrontal cortex, but the neural mechanisms underlying these interactions are unclear. Here, we used a decoding approach to analyze local field potentials (LFPs) recorded from OFC and MFC of monkeys engaged in a stimulus-choice task, before and after excitotoxic amygdala lesions. Whereas OFC LFP responses were strongly modulated by the amount of reward associated with each stimulus, MFC responses best represented which stimulus subjects decided to choose. This was counter to what we observed in the level of single neurons where their activity was closely associated with the value of the stimuli presented on each trial. After lesions of the amygdala, stimulus-reward value and choice encoding were reduced in OFC and MFC, respectively. However, while the lesion-induced decrease in OFC LFP encoding of stimulus-reward value mirrored changes in single neuron activity, reduced choice encoding in MFC LFPs was distinct from changes in single neuron activity. Thus, LFPs and single neurons represent different information required for decision-making in OFC and MFC. At the circuit-level, amygdala input to these two areas play a distinct role in stimulus-reward encoding in OFC and choice encoding in MFC.

neuroscience↗