Chak Sangma

Single-nucleotide polymorphisms (SNPs) in RNA viruses such as Zika virus (ZIKV) can alter viral pathogenicity and are therefore critical molecular markers for surveillance. Here, we report an electrochemical hydrogel biosensor that discriminates a clinically relevant ZIKV SNP through a sequence-dependent bioconjugation mechanism between peptide nucleic acids (PNAs) and silver nanoparticles (AgNPs). A single guanine-to-thymine substitution in the PNA probe produces distinct AgNP coordination modes, resulting in markedly different nanoparticle aggregation states, colorimetric signatures, and silver oxidation profiles. Transmission electron microscopy reveals that guanine-containing PNAs induce AgNP clustering through strong nucleobase–silver coordination, whereas thymine-containing PNAs preserve dispersed nanoparticles. These coordination patterns persist upon hybridization with complementary or mismatched ZIKV RNA, establishing PNA–AgNP bioconjugation as the primary determinant of the sensing response. Integration of this mechanism into an AgNP-hydrogel matrix enables the sensitive and selective electrochemical detection of short synthetic targets (15 bp) with an LOD of 0.004 nM, LOQ of 0.015 nM, and 7.4% RSD, alongside full-length 10.8 kbp viral RNA. This work demonstrates how nucleobase-specific PNA–nanoparticle interactions can be harnessed to achieve robust SNP discrimination in RNA viruses.

As cannabis legalization expands globally, detecting Δ⁹-tetrahydrocannabinol (Δ⁹-THC) in air has become crucial for public health monitoring. This research addresses a significant gap by developing the first electrochemical sensor for gas-phase Δ⁹-THC detection, effectively overcoming electrode fouling challenges commonly found in liquid-phase sensing. Our innovative approach employs a manganese dioxide-modified screen-printed graphene electrode (MnO₂/SPGE) with a poly(acrylic acid) membrane immobilized with Fast Blue B salt. This configuration creates a selective sensing interface that facilitates both accumulation and specific interaction with Δ⁹-THC molecules. The proposed sensor demonstrated excellent analytical performance with a linear detection range of 25–250 ppb (R² = 0.9905), a limit of detection of 4.5 ppb, and sensitivity of 0.06 μA/ppb. Interference studies revealed exceptional selectivity, with minimal signal variations (±5%) despite high concentration ratios of potential interferents commonly found in postcannabis smoking environments. The proposed sensor’s practical applicability was validated through comparative analysis with HPLC and GC–MS, successfully detecting Δ⁹-THC in cannabis tobacco smoke while showing no response to non- Δ⁹-THC-containing cigarette samples. This low-cost, disposable sensor offers significant advantages in simplicity, portability, and accessibility compared to conventional gas chromatography–mass spectrometry techniques, making it suitable for field applications in air quality monitoring related to cannabis investigations.

Nanoparticle-incorporated hydrogels are promising for functional material design, but effective dispersion of nanoparticles within the polymer matrix remains a critical challenge. This study presents a prepolymerization self-assembly strategy to optimize the distribution of silver nanoparticles (AgNPs) for sensing applications using phloroglucinol (PHL) as both a reducing agent and a self-assembly template. By inducing assembly between PHL and silver ions prior to polymerization, we achieved a uniform distribution of AgNPs throughout the hydrogel matrix. Characterization results confirmed the formation of a porous nanocomposite structure with superior stability. Crucially, electrochemical evaluations revealed that the hydrogel exhibits high specificity toward 2,4,6-trinitrotoluene (TNT). This selectivity is attributed to molecular recognition sites generated by the PHL-directed self-assembly. These findings offer a scalable approach to designing high-performance hydrogel sensors for the selective detection of explosives.

Nitroreductase (NTR) is an enzyme that specifically reduces nitroaromatic activity. Some nitroaromatic explosives are exploited by terrorists. Among these highly explosive materials, 2,4,6-trinitrotoluene (TNT) is often used, which makes detection of TNT an important research topic in the fight against terrorism. TNT vapor detection by gas sensor is an approach that has been under active investigation for several years. Despite this effort, presently there is limited practical success, in part, due to the ultra-low volatility nature of TNT. In this work, we propose an application of the NTR reaction in a hydrogel gas sensor to detect TNT vapor. Firstly, NTR activity in the hydrogel was confirmed by adding TNT and 2,4-dinitrotoluene (DNT) solutions to the NTR-hydrogel sensor conducting cyclic voltammetry (CV) experiments. Then, further CV experiments were carried out with gas phase samples. The CV graphs of NTR-hydrogels detecting vapors containing the explosive substrates and negative controls were compared. Results showed that the signal from the nitroaromatics increased with exposure time where the TNT signal was the highest of all tested compounds. The gas sensor was sensitive enough to detect TNT gas presented in an ambient air at room temperature.

Nosocomial infection is one of the most important problems that occurs in hospitals, as it directly affects susceptible patients or patients with immune deficiency. Klebsiella pneumoniae (K. pneumoniae) is the most common cause of nosocomial infections in hospitals. K. pneumoniae can cause various diseases such as pneumonia, urinary tract infections, septicemias, and soft tissue infections, and it has also become highly resistant to antibiotics. The principal routes for the transmission of K. pneumoniae are via the gastrointestinal tract and the hands of hospital personnel via healthcare workers, patients, hospital equipment, and interventional procedures. These bacteria can spread rapidly in the hospital environment and tend to cause nosocomial outbreaks. In this research, we developed a MIP-based electrochemical biosensor to detect K. pneumoniae. Quantitative detection was performed using an electrochemical technique to measure the changes in electrical signals in different concentrations of K. pneumoniae ranging from 10 to 10⁵ CFU/mL. Our MIP-based K. pneumoniae sensor was found to achieve a high linear response, with an R² value of 0.9919. A sensitivity test was also performed on bacteria with a similar structure to that of K. pneumoniae. The sensitivity results show that the MIP-based K. pneumoniae biosensor with a gold electrode was the most sensitive, with a 7.51 (% relative current/log concentration) when compared with the MIP sensor applied with Pseudomonas aeruginosa and Enterococcus faecalis, where the sensitivity was 2.634 and 2.226, respectively. Our sensor was also able to achieve a limit of detection (LOD) of 0.012 CFU/mL and limit of quantitation (LOQ) of 1.61 CFU/mL.

Nitroreductase (NTR) is an enzyme with a specific activity to nitroaromatic reduction. Some nitroaromatic explosives are exploited by terrorists. Among these materials, 2,4,6- trinitrotoluene (TNT) is a major high explosive which makes detection of TNT an important research topic. TNT vapor detection by gas sensor is an approach under investigated for many years. Even though, there is a limited success at present, in part, due to the ultra-low volatility nature of TNT. In this work, we propose an application of the NTR reaction in a hydrogel gas sensor to detect TNT vapor. Firstly, NTR activity in the hydrogel was confirmed by adding TNT and 2,4-dinitrotoluene (DNT) solutions to an NTR-hydrogel sensor following by cyclic voltammetry (CV) experiments. Then, the other CV experiments were carried out with gas phase samples. The CV graphs of NTR-hydrogels detecting vapors containing the explosive substrates and negative controls were compared. Results showed that the signal from the nitroaromatics increased with exposure time where the TNT signal was the highest of all tested compounds. The gas sensor was sensitive enough to detect TNT gas presented in an ambient air at room temperature.

In Thailand, most of the bomb devices produced by terrorists use trinitrotoluene (TNT) as the main explosive material. Detecting TNT and preventing detonation could save many civilians. Due to its low vapor pressure, TNT requires an extremely high sensitivity method for detection. In this paper, we propose an application of polyacrylamide gel as an electrochemical gas sensor for explosive material detection. Cyclic voltammetry signals were collected from samples including TNT, pentaerythritol tetranitrate (PETN) and non-explosive vapors. It was found that a timederivative calculation of the signal was unique to each chemical, rather than the signal itself, demonstrating utility for the detection of explosive material. This approach for making a gel-based sensor and data analysis looks promising and requires further validation.

Zika virus (ZIKV) is a flavivirus that was first identified in 1947. Initially, the virus was of little concern for health authorities given there were very few casualties among those suffering an infection. As such, only limited studies were performed on ZIKV. Recently, the viral infection has been linked to microcephaly in infants, which has prompted a dramatic increase in scientific interest in ZIKV research, including methods to allow for rapid virus identification. In this work we report the development of a new type of ZIKV electrochemical biosensor based on surface imprinted polymers and graphene oxide composites. The biosensor was used to detect ZIKV by measuring changes in the electrical signal with changing virus concentrations in buffer and serum using standard electrochemical techniques. The detection limit of our method is similar to the detection limit of the real-time quantitative reverse transcription PCR method.