Biology subjects

Mahmud, A.

Publications and source records attributed to Mahmud, A..

10 recordsLinked to original sources

bioRxiv2026

Direct electrochemical cortisol detection via transition-resolved interrogation at a defect-engineered graphene interface

Continuous tracking of cortisol is central to understanding human stress physiology, yet direct electrochemical detection without biological receptors remains challenging despite its promise for stable and dynamic sensing. Electrochemical reduction of cortisol typically occurs at highly negative potentials, where parasitic interfacial currents, hydrogen evolution, and substantial capacitive background overlap with the cortisol reduction signal, preventing accurate quantification. We overcome this barrier through an integrated material-measurement strategy combining a defect-engineered graphene interface with a transition-resolved interrogation (TRI) measurement strategy. First, we engineered polybenzimidazole-derived laser-induced graphene containing nitrogen-rich defects while suppressing oxygen-derived functionalities which reduced parasitic background currents within the same cathodic potential regime. Next, we designed TRI to leverage differences in the time-dependent evolution of overlapping cathodic processes to isolate a localized cortisol-associated electrochemical reduction transition. Derivative-domain projection coupled with background estimation enables its reliable quantification. This integrated sensing architecture enables sensitive, selective, and dynamic cortisol detection in both artificial and biological interstitial fluids at low nanomolar concentrations. The response remains reproducible across physiologically relevant variations in pH, ionic strength, temperature, and repeated cycling. Together, these capabilities provide a basis for continuous electrochemical cortisol monitoring for future study of stress physiology.

bioengineering↗

bioRxiv2026

ProteoformTracker: an interactive tool for planning proteoform detectability in top-down and middle-down proteomics

Characterizing proteome complexity in disease contexts is essential for understanding molecular mechanisms and advancing therapeutic development. Mass spectrometry (MS)-based top-down and middle-down proteomics (TDP/MDP) can resolve intact proteoforms - protein molecules carrying a unique combination of isoform sequence and post-translational modifications (PTMs); however, their technical complexity and modest throughput present challenges for experimental planning and limit their broader application. Here, we present ProteoformTracker, an online web tool that prospectively models MS signal and evaluates the feasibility of using TDP/MDP to distinguish a target proteoform from related isoforms and the background proteome. ProteoformTracker takes as input a gene's annotated isoforms, a novel long-read/assembled transcript, or an rMATS alternative-splicing event, with or without user-specified PTMs, and predicts each proteoform's MS1 charge-state envelope and exact isotope pattern, scores per-bond MS2 fragmentation propensity, and searches the full reference human proteome for confounding proteins that could share the target's intact mass or a charge-state m/z peak. ProteoformTracker also supports middle-down workflows via simulated partial protease digestion. Results are rendered as interactive, zoomable MS1 and MS2 visualizations with live resolvability and fragment-ion statistics, letting users incorporate outside evidence into which confounders they compare against. We envision ProteoformTracker as a useful tool for users to plan TDP/MDP experiments targeting specific proteoforms. ProteoformTracker is implemented in R (Shiny) with a Python backend for exact mass and isotope-pattern calculation and is freely available at http://www.proteoformtracker.org together with the documentation and a walkthrough.

bioinformatics↗

bioRxiv2025

Sensitive Hormone and Neurotransmitter Detection with Carbon Flower Electrodes

Carbon-based electrochemical sensors have attracted substantial attention for continuous health monitoring due to their high surface area, wide potential window, capability for repeated measurements, and compatibility with soft wearable electronics. However, they face challenges when detecting target biomarker concentrations in the low nanomolar range (sensitivity) and differentiating them in a mixture (selectivity), limiting their applicability in real scenarios. Herein, we present sensitive and selective carbon flower sensors, fabricated via a facile and patternable spray-coating process on soft, stretchable substrates. The carbon flowers--obtained through the synthesis of polyacrylonitrile and subsequent heat treatments--exhibit unique hierarchical morphologies, high surface area, and excellent conductivity, ideal for mass transport and electrochemical detection. We demonstrate the detection of estradiol, serotonin, melatonin, dopamine, uric acid, and ascorbic acid with detection limits as low as sub-nanomolar. The carbon flower sensors exhibit good repeatability across 100 cycles and over several weeks, robustness to pH and salt variations, and excellent performance in complex bio-fluids such as artificial saliva. In mixtures containing up to four analytes, they differentiate individual molecules, demonstrating the selectivity of the carbon flowers. This combination of sensitivity, selectivity, and mechanical compatibility makes carbon flower sensors well-suited for biomolecular sensing in soft, skin-conformable wearable electronic patches.

bioengineering↗

bioRxiv2025

High-precision Biomedical Text Corpora for Multi-Entity Recognition: A CoDiet study

We present here five biomedical, multi-entity corpora that can be used as benchmarks for named-entity recognition (NER), targeted to literature on metabolic syndrome. The CoDiet-Gold corpus contains annotations for 500 full-text publications and 348,406 annotations. It is divided into CoDiet-Gold-public (450 documents) and CoDiet-Gold-private (50 documents). Each document was independently annotated by two human experts, with disagreements fully adjudicated by a third expert. The CoDiet-Electrum corpus (2,998,273 annotations) contains 4,423 publications that were annotated using case-insensitive matching of the surface forms with punctuation ignored, found in CoDiet-Gold-public. Finally, for the same 4,423 documents, two fully machine annotated corpora CoDiet-Bronze (2,938,738 annotations) and CoDiet-Silver (2,298,988 annotations), were created by utilising existing NER algorithms to annotate these. These corpora contain categories (organisms, disease, genes, proteins, metabolites) that add depth to existing corpora, as well as new categories that do not appear in other corpora (food, dietary methods, sample types, computational methods, study methodology, population characteristics, data types, and microbiome).

bioinformatics↗

bioRxiv2020

BANCOVID, the first D614G variant mRNA-based vaccine candidate against SARS-CoV-2 elicits neutralizing antibody and balanced cellular immune response

Effective vaccine against SARS-CoV-2 is the utmost importance in the current world. More than 1 million deaths are accounted for relevant pandemic disease COVID-19. Recent data showed that D614G genotype of the virus is highly infectious and responsible for almost all infection for 2nd wave. Despite of multiple vaccine development initiatives, there are currently no report that has addressed this critical variant D614G as vaccine candidate. Here we report the development of an mRNA-LNP vaccine considering the D614G variant and characterization of the vaccine in preclinical trial. The surface plasmon resonance (SPR) data with spike protein as probe and competitive neutralization with RBD and S2 domain revealed that immunization generated specific antibody pools against the whole extracellular domain (RBD and S2) of the spike protein. The anti-sera and purified IgGs from immunized mice on day 7 and 14 neutralized SARS-CoV-2 pseudovirus in ACE2-expressing HEK293 cells in a dose dependent manner. Importantly, immunization protected mice lungs from pseudovirus entry and cytopathy. The immunologic responses have been implicated by a balanced and stable population of CD4+ cells with a Th1 bias. The IgG2a to IgG1 and (IgG2a+IgG2b) to (IgG1+IgG3) ratios were found 1{+/-}0.2 and 1.24{+/-}0.1, respectively. These values are comparatively higher than relevant values for other published SARS-CoV-2 vaccine in development,1, 2 and suggesting higher viral clearance capacity for our vaccine. The data suggested great promise for immediate translation of the technology to the clinic.

immunology↗

bioRxiv2020

Reagentless Biomolecular Analysis Using a Nanoscale Molecular Pendulum

The ability to sense biological inputs using self-contained devices unreliant on external reagents or reporters would open countless opportunities to collect information about our health and environment. Currently, a very limited set of molecular inputs can be detected using this type of sensor format. The development of versatile reagentless sensors that could track molecular analytes in biological fluids remains an unmet need. Here, we describe a new universal sensing mechanism that is compatible with the analysis of proteins that are important physiological markers of stress, allergy, cardiovascular health, inflammation and cancer. The sensing mechanism we developed is based on the measurement of field-induced directional diffusion of a nanoscale molecular pendulum tethered to an electrode surface and the sensitivity of electron-transfer reaction kinetics to molecular size. Using time-resolved electrochemical measurements of diffusional motion, the presence of an analyte bound to a sensor complex can be continuously tracked in real time. We show that this sensing approach is compatible with making measurements in blood, saliva, urine, tears and sweat and that the sensors can collect data in situ in living animals. The sensor platform described enables a broad range of applications in personalized health monitoring.

bioengineering↗

bioRxiv2020

Proteome Exploration of Legionella pneumophila for Identifying Novel Therapuetics: A Hierarchical Subtractive Genomics and Reverse Vaccinology Approach

Legionella pneumophila, the causative agent of a serious type of pneumonia (lung infection) called Legionnaires disease. It is emerging as an antibacterial resistant strain day by day. Hence, the identification of novel drug targets and vaccine candidates is essential to fight against this pathogen. Herein attempts were taken through subtractive genomics approach on complete proteome of L. pneumophila to address the challenges of multidrug resistance. A total 2930 proteins from L. pneumophila proteome were investigated through diverse subtractive proteomics approaches, e.g., identification of human non-homologous and pathogen-specific essential proteins, druggability and anti-target analysis, prediction of subcellular localization, human microbiome non-homology screening, protein-protein interactions studies in order to find out effective drug and vaccine targets. Only 3 were identified that fulfilled all these criteria and proposed as novel drug targets against L. pneumophila. Furthermore, outer membrane protein TolB was identified as potential vaccine target with better antigenicity score and allowed for further in silico analysis to design a unique multiepitope subunit vaccine against it. Antigenicity and transmembrane topology screening, allergenicity and toxicity assessment, population coverage analysis, and molecular docking approach were adopted to generate the most potent epitopes. The final vaccine was constructed by the combination of highly immunogenic epitopes along with suitable adjuvant and linkers. The designed vaccine construct showed higher binding interaction with different MHC molecules and human immune TLR2 receptors with minimum deformability at molecular level. The translational potency and microbial expression of the vaccine protein was also analyzed using pET28a(+) vector. The present study aids in the development of novel therapeutics and vaccine candidates for efficient treatment of the infections caused by Legionella pneumophila. However, further wet lab-based investigations and in vivo trials are highly recommended to experimentally validate our prediction.

bioinformatics↗

bioRxiv2019

Subtractive Genomic Analysis for Identification of Novel Drug Targets and Vaccine Candidates against Bartonella bacilliformis subsp. Ver097

Bartonella bacilliformis is the causative agent of Carrions disease, one of the truly neglected tropical diseases found in Peru, Colombia and Ecuador. Recent evidence predicts that Bartonella bacilliformis subsp. ver097 can emerge as an antibacterial resistant strain and hence identification of novel drug targets is a crying need. Subtractive genome analysis of B. bacilliformis subsp. ver097 was successfully done in order to address the challenges. Various computational tools and online based servers were used to screen out human homologous proteins of pathogen and proteins involved in common metabolic pathways of host and pathogen. Only 7 proteins involved in pathogen specific pathways were further analyzed to identify membrane proteins. Flagellar biosynthesis protein FlhA and ABC transporter permease were found to be novel as targets according to DrugBank database. To avoid side effects in human while administering drugs, human anti-targets analysis was performed to confirm non-homology of selected novel drug targets. Both predicted proteins also showed probability of antigenicity prediction through VaxiJen, however, Flagellar biosynthesis protein FlhA showed broad spectrum conservancy with Bartonella strains. Therefore, Flagellar biosynthesis protein FlhAcould facilitate the development of novel drugs and therapeutic compounds along with vaccines for efficient treatment of infections caused by Bartonella bacilliformis subsp. ver097.

bioinformatics↗

bioRxiv2018

The geography of malaria elimination in Bangladesh: combining data layers to estimate the spatial spread of parasites

Malaria control programs face difficult resource allocation decisions. Of particular concern for countries aiming for malaria elimination, the regular movement of individuals to and from endemic areas undermines local interventions by reintroducing infections and sustaining local transmission. Quantifying this movement of malaria parasites around a country has become a priority for national control programs, but remains methodologically challenging, particularly in areas with highly mobile populations. Here, we combined multiple data sources to measure the geographical spread of malaria parasites, including epidemiological surveillance data, travel surveys, parasite genetic data, and anonymized mobile phone data. We collected parasite genetic barcodes and travel surveys from 2,090 patients residing in 176 unions in southeast Bangladesh. We developed a genetic mixing index to quantify the likelihood of samples being local or imported. We then inferred the direction and intensity of parasite flow between locations using an epidemiological model, and estimated the proportion of imported cases assuming mobility patterns parameterized using the travel survey and mobile phone calling data. Our results show that each data source provided related but different information about the patterns of geographic spread of parasites. We identify a consistent north/south separation of the Chittagong Hill Tracts region in Bangladesh, and found that in addition to imported infections from forested regions, frequent mixing also occurs in low transmission but highly populated areas in the southwest. Thus, unlike risk maps generated from incidence alone, our maps provide evidence that elimination programs must address ongoing movement of parasites around the lower transmission areas in the southwest.

epidemiology↗

bioRxiv2018

On the role of different age groups during pertussis epidemics in California, 2010 and 2014

BackgroundThere is limited information on the roles of different age groups in propagating pertussis outbreaks, and the temporal changes in those roles since the introduction of acellular pertussis vaccines.\n\nMethodsThe relative roles of different age groups in propagating the 2010 and the 2014 pertussis epidemics in California were evaluated using the RR statistic that measures the change in the groups proportion among all detected cases before-vs.-after the epidemic peak.\n\nResultsFor the 2010-11 epidemic, evidence for a predominant transmission age group was weak, with the largest RR estimates being 1.26(95%CI (1.08,1.46)) (aged 11-13y); 1.19(1.01,1.4) (aged 9-10y); 1.17(0.86,1.59) (aged 14-15y); 1.12(0.86,1.46) (aged 16-19y); and 1.1(0.89,1.36) (aged 7-8y). The 2014 epidemic showed a strong signal of the role of older adolescents, with the highest RR estimate being in those aged 14-15y (RR=1.83(1.61,2.07)), followed by adolescents aged 16-19y (RR=1.41(1.24,1.61)) and 11-13y (RR=1.26(1.12,1.41)), with lower RR estimates in other age groups.\n\nConclusionsAs the time following introduction of acellular pertussis vaccines in California progressed, older adolescents played an increasing role in transmission during the major pertussis outbreaks. Booster pertussis vaccination for older adolescents with vaccines effective against pertussis transmission should be considered with the aim of mitigating future pertussis epidemics in the community.

epidemiology↗