Polyaniline-based bovine serum albumin imprinted electrochemical sensor for ultra-trace-level detection in clinical and food safety applications.

Monitoring bovine serum albumin (BSA) at ultra-low levels is crucial for clinical and food safety applications, as it plays a significant role in identifying various health conditions and potential risks, necessitating fast, trace-level detection of BSA. This study proposes an approach to address these challenges by employing molecularly imprinted polymer (MIP) to develop an ultra-trace-level and cost-effective BSA sensing platform. The MIP electrochemical sensor was developed using polyaniline (PANI) combined with the protein crosslinker glutaraldehyde (GA) to optimize BSA surface imprinting in the MIP. As a result, the sensor achieves a sensitivity of 1.24 µA/log(pg/mL), with a picomolar detectable limit of 2.3 pg/mL (0.035 pM) and a wide detection range from 20 pg/mL to 200,000 pg/mL (0.303 pM to 3030 pM), making it suitable for clinical and food safety applications. Additionally, the study explores the interaction between an acidic surfactant protein eluent (acetic acid with sodium dodecyl sulfate, AcOH-SDS) and BSA vacant sites, enhancing recognition and re-binding. The PANI-based MIP sensor demonstrates initial feasibility and practicality in commercial milk and real human serum, opening avenues for early disease detection and ensuring food safety in BSA-related immune responses.

Green synthesized gold nanoparticles and CuO-based nonenzymatic sensor for saliva glucose monitoring.

Glucose, essential for brain and muscle functions, requires careful monitoring in diabetes and other chronic disease management. While blood glucose monitoring provides precise information about these diseases, it remains an invasive method. Saliva glucose monitoring could offer an alternative approach, but the glucose concentration in saliva is very low. In this work, we report a simple, low-cost, highly sensitive nonenzymatic electrochemical glucose sensor. We developed this sensor using green synthesized gold nanoparticles (AuNPs) and wet chemical synthesized copper oxide (CuO) nanoparticles on a screen-printed carbon electrode (Au/CuO/SPCE). The sensor's high sensitivity results from dual amplification strategies using AuNPs and CuO nanomaterials, each demonstrating catalytic activity towards glucose. This shows promising potential for saliva glucose monitoring. The AuNPs were synthesized using an Au precursor and orange peel extract (OPE), yielding stable colloidal AuNPs with a mean diameter of about 37 nm, thus eliminating the need for additional capping agents. Under optimal conditions, amperometric tests revealed that the sensor responded linearly to glucose concentrations ranging from 2 µM to 397 µM with a sensitivity of 236.70 µA mM-1 cm-2. Furthermore, the sensor demonstrated excellent reproducibility, stability and high selectivity for glucose in the presence of different biomolecules. We validated the sensor's efficacy by measuring glucose in human saliva, showing its potential for noninvasive glucose monitoring. This research advances the development of point-of-care devices, positioning the sensor as a promising tool for noninvasive glucose monitoring and improved diabetes management.

Morphometric features, seminal profile and diluters effect on post-thaw semen quality of Munshiganj cattle in Bangladesh.

The study investigates morphometric features, seminal profile and post-thaw semen quality of Munshiganj cattle. Morphometric features were measured using measuring tape from 20 Munshiganj cattle while coat color was measured by observing in naked eye. Fresh and post thaw semen quality parameters were analyzed using Computer Assisted semen analyzer (CASA). Coat color of Munshiganj male cattle were creamy white to dull pinkish and female were white to creamy. The mean body weight, body length, hearth girth, height at wither, head length, head width, ear length, ear width, fore leg length, hind leg length, tail length, tail doc circumference, horn length, horn diameter and mouth circumference were 362.80 kg, 137.31 cm, 160.66 cm, 135.21 cm, 50.97 cm, 20.58 cm, 19.75 cm, 9.88 cm, 73.02 cm, 74.84 cm, 106.10 cm, 20.75 cm, 13.60 cm, 16.12 cm and 43.00 cm, respectively. There was significant difference (p < 0.05) between male and female in terms of body weight (418.00 vs 307.60 kg), heart girth (173.74 vs 147.57 cm), head width (22.50 vs 18.67 cm), horn diameter (18.58 vs 13.66 cm) and mouth circumference (46.60 vs 39.40 cm). Average scrotal length was 16.76 cm while scrotal circumference was 32.70 cm. Age had significant effect (p < 0.05) on morphometric characteristics of Munshiganj male and female cattle. On the other hand, season had no significant effect on semen quality. Mean semen volume, sperm concentration, total motile, progressive, static, slow and live spermatozoa were 5.83 ± 0.88 ml, 1510.27 ± 844.07 million/ml, 91.9 ± 2.17 %, 63.80 ± 12.53 %, 8.10 ± 2.17 %, 0.10 ± 0.10 %, 91.38 ± 0.25 %, respectively. On the other hand, sperm head length and width, sperm tail length of Munshiganj cattle were 10.39 ± 0.16 µm, 4.26 ± 0.07 µm, 21.5 ± 0.52 µm, respectively. Individual breeding bull had a significant (p < 0.05) effect on post-thawed motile sperm percentage. Four different diluters (Triladyl, Steridyl, Tris-egg yolk-Citrate and Andromed) were used to compare the effects of diluter on post-thaw semen quality of Munshiganj cattle and found that diluter had no significant effect (p > 0.05) on post thaw semen quality except slow motility and proximal droplet percentages. Munshiganj cattle had a distinctive phenotypic feature with standard quality semen and had no effect of egg yolk free and egg yolk based diluters on post thaw semen quality.

Nonenzymatic Electrochemical Glutamate Sensor Using Copper Oxide Nanomaterials and Multiwall Carbon Nanotubes.

Glutamate is an important neurotransmitter due to its critical role in physiological and pathological processes. While enzymatic electrochemical sensors can selectively detect glutamate, enzymes cause instability of the sensors, thus necessitating the development of enzyme-free glutamate sensors. In this paper, we developed an ultrahigh sensitive nonenzymatic electrochemical glutamate sensor by synthesizing copper oxide (CuO) nanostructures and physically mixing them with multiwall carbon nanotubes (MWCNTs) onto a screen-printed carbon electrode. We comprehensively investigated the sensing mechanism of glutamate; the optimized sensor showed irreversible oxidation of glutamate involving one electron and one proton, and a linear response from 20 µM to 200 µM at pH 7. The limit of detection and sensitivity of the sensor were about 17.5 µM and 8500 µA·mM-1·cm-2, respectively. The enhanced sensing performance is attributed to the synergetic electrochemical activities of CuO nanostructures and MWCNTs. The sensor detected glutamate in whole blood and urine and had minimal interference with common interferents, suggesting its potential for healthcare applications.

Nitrogen fertilization impact on soil carbon pools and their stratification and lability in subtropical wheat-mungbean-rice agroecosystems.

Nitrogen (N) is the prime nutrient for crop production and carbon-based functions associated with soil quality. The objective of our study (2012 to 2019) was to evaluate the impact of variable rates of N fertilization on soil organic carbon (C) pools and their stocks, stratification, and lability in subtropical wheat (Triticum aestivum)-mungbean (Vigna radiata)-rice (Oryza sativa L) agroecosystems. The field experiment was conducted in a randomized complete block design (RCB) with N fertilization at 60, 80, 100, 120, and 140% of the recommended rates of wheat (100 kg/ha), mungbean (20 kg/ha), and rice (80 kg/ha), respectively. Composite soils were collected at 0-15 and 15-30 cm depths from each replicated plot and analyzed for microbial biomass (MBC), basal respiration (BR), total organic C (TOC), particulate organic C (POC), permanganate oxidizable C (POXC), carbon lability indices, and stratification. N fertilization (120 and 140%) significantly increased the POC at both depths; however, the effect was more pronounced in the surface layer. Moreover, N fertilization (at 120% and 140%) significantly increased the TOC and labile C pools when compared to the control (100%) and the lower rates (60 and 80%). N fertilization significantly increased MBC, C pool (CPI), lability (CLI), and management indices (CMI), indicating improved and efficient soil biological activities in such systems. The MBC and POC stocks were significantly higher with higher rates of N fertilization (120% and 140%) than the control. Likewise, higher rates of N fertilization significantly increased the stocks of labile C pools. Equally, the stratification values for POC, MBC, and POXC show evidence of improved soil quality because of optimum N fertilization (120-140%) to maintain and/or improve soil quality under rice-based systems in subtropical climates.

A dataset for internet of things based fish farm monitoring and notification system.

Water quality depends on many factors. Some of them are essential for maintaining the minimum sustainability of water. Because of the great dependence of fishes on the condition of the aquatic environment, the water quality can directly affect their activity. Therefore monitoring water quality is a very important issue to consider, especially in the fish farming industry. In this paper a digital fish farm monitoring system is introduced and a collection of experimental data of water quality monitoring was presented, which were directly collected from a fish pond. As the quality factor of water affects its aquatic life form sustainability, therefore the quality factors of the water were measured using digital sensors. Temperature, pH factor and Turbidity were selected as the basic quality factors to measure. The dataset contains data recorded from two different water levels to analyze the aquatic environment more efficiently. Each level has 9623 sets of data of the selected parameters. Collection was continued all day long for several days. Later collected sensor data were analyzed as short period time series to find its properties. Machine Learning regression method was used to predict near future conditions. Moreover data were processed to find any repetitive patterns in its properties. This dataset represents the exact condition of the environment of the fish pond. Therefore it can be used to develop a system to monitor fish farms digitally. Using these data in machine learning, predicting the future is possible for advance monitoring of a fish farm. The dataset is available in Mendeley Data[1].

Antibiotic resistance of Escherichia coli isolated from broilers sold at live bird markets in Chattogram, Bangladesh.

OBJECTIVE: The present study was carried out to appraise the antibiotic resistance and to detect some of the target resistant genes in Escherichia coli (E. coli) isolated from apparently healthy broilers. MATERIALS AND METHODS: Cloacal swab samples (n = 60) were collected from apparently healthy broilers (n = 60) sold at two different live bird markets (LBMs) of Chattogram, Bangladesh. Isolation and identification of the Escherichia coli was done by the following standard bacteriological techniques followed by biochemical tests. The antibiotic susceptibility of E. coli isolates was determined by the disk diffusion method. The antibiotic resistant genes were detected by polymerase chain reaction (PCR) using specific primers. RESULTS: The overall prevalence of E. coli in broilers was 61.67% (n = 37/60) (95% CI = 49-72.93). The antibiogram study showed that the isolates were 100% resistant to ampicillin and tetracycline followed by sulfomethoxazole-trimethoprim (94.59%, n = 35/37) and nalidixic acid (91.89%, n = 34/37). To the contrary, 56.76% (n = 21/37) isolates were sensitive to both ceftriaxone and gentamicin followed by colistin (48.65%, n = 18/37). All of E. coli isolates were multidrug resistant (MDR) and carried bla TEM, tetA, and Sul2 genes. CONCLUSION: The presence of MDR genes in E. coli isolates in broilers could pose a serious public health threat.