Development and validation of an ICP-MS method and its application in assessing heavy metals in whole blood samples among occupationally exposed lead smelting plant workers.

Occupational exposure to heavy metals affects various organ systems and poses a significant health risk to workers. Consequently, its precise estimation is of clinical concern and warrants the need for an analytical method with reliable precision and accuracy. The current study aimed to develop an analytical method using inductively coupled plasma‒mass spectrometry (ICP-MS) to detect trace to elevated levels of potentially toxic elements in human blood. The sample preparation was optimized using a two-step ramp temperature microwave acid digestion program. The toxic elements were quantified using ICP-MS operating in kinetic energy discrimination (KED) mode, adjusting the data acquisition parameters and instrumental settings. The analytical method was validated using standard performance parameters. Each validation parameter was aligned with the acceptable criteria outlined in standard guidelines. The method achieved optimal linearity (r2 > 0.99), recovery (85.60-112.00%), and precision (1.35-7.03%), was capable of detecting the lowest concentrations of 0.32, 0.28, 0.28, and 0.19 µg/L, and was capable of quantifying trace levels of 1.01, 0.88, 0.90, and 0.62 µg/L for arsenic (As), cadmium (Cd), mercury (Hg), and lead (Pb), respectively. Post-validation, the method was applied to estimate heavy metals in blood samples from 250 Pb-smelting plant workers, revealing potential health implications of occupational exposure. The cohort analysis revealed that demographic and employment factors were associated with elevated blood Pb levels, leading to symptoms and health risks. Clinical analysis revealed that 33.6% of the participants experienced hypertension. These findings highlight the significant health risks associated with elevated blood Pb levels. The weak but significant correlation with systolic blood pressure underscores the need for improved monitoring and workplace safety. This emphasizes the importance of continuous monitoring, targeted interventions, and enhanced occupational hygiene to protect workers' well-being.

QD-based fluorescent nanosensors: Production methods, optoelectronic properties, and recent food applications.

Food quality and safety are crucial public health concerns with global significance. In recent years, a series of fluorescence detection technologies have been widely used in the detection/monitoring of food quality and safety. Due to the advantages of wide detection range, high sensitivity, convenient and fast detection, and strong specificity, quantum dot (QD)-based fluorescent nanosensors have emerged as preferred candidates for food quality and safety analysis. In this comprehensive review, several common types of QD production methods are introduced, including colloidal synthesis, self-assembly, plasma synthesis, viral assembly, electrochemical assembly, and heavy-metal-free synthesis. The optoelectronic properties of QDs are described in detail at the electronic level, and the effect of food matrices on QDs was summarized. Recent advancements in the field of QD-based fluorescent nanosensors for trace level detection and monitoring of volatile components, heavy metal ions, food additives, pesticide residues, veterinary-drug residues, other chemical components, mycotoxins, foodborne pathogens, humidity, and temperature are also thoroughly summarized. Moreover, we discuss the limitations of the QD-based fluorescent nanosensors and present the challenges and future prospects for developing QD-based fluorescent nanosensors. As shown by numerous publications in the field, QD sensors have the advantages of strong anti-interference ability, convenient and quick operation, good linear response, and wide detection range. However, the reported assays are laboratory-focused and have not been industrialized and commercialized. Promising research needs to examine the potential applications of bionanotechnology in QD-based fluorescent nanosensors, and focus on the development of smart packaging films, labeled test strips, and portable kits-based sensors.

Development and validation of Graphite Furnace Atomic Absorption Spectrometry method and its application for clinical evaluation of blood lead levels among occupationally exposed lead smelting plant workers.

The growing interest in estimating the blood lead levels, for early detection of lead exposure, warranted a need for a validated analytical method for trace levels estimation of lead. The present study aimed to develop an analytical method for detecting trace amounts to elevated levels of lead in human blood using the Graphite Furnace Atomic Absorption Spectrometry technique and its application in evaluating blood lead levels among occupationally exposed individuals. The method validation was performed with standard test parameters including linearity, recovery, precision, method detection limit, and limit of quantification. The validation results for each performance parameter were in agreement with acceptable criteria as per standard guidelines. The correlation was observed as optimum linear (R2 = 0.998) between absorbance and lead concentration range from 0 to 10 µg/dL. The recoveries for spiked samples ranged between 95 and 105%. The calculated value for the method detection limit was 0.16 µg/dL and the limit of quantification was 0.51 µg/dL. The precision for all spiked concentrations was below 10% of the relative standard deviation. Evaluation of lead exposure among occupationally exposed individuals revealed the study population had found average blood lead level (42.80 ± 12.47 µg/dL), which was above the upper acceptable limit suggested by Occupational Safety and Health Administration, USA. The majority of system-specific symptoms were observed among study groups having mean blood lead levels above 40 µg/dL. However, sociodemographic status and employment factors were found possible determinants of the prevalence of high blood lead levels.

Plasmonic Ag decorated AlOOH for highly sensitive SERS detection of affinity OH groups molecules enriched in hotspots.

Significant breakthroughs have been made in the development of surface-enhanced Raman scattering (SERS) substrates constructed by depositing plasmonic Ag onto nanostructured platforms. AlOOH is widely fabricated using hydrothermal, microwave, and microemulsion methods. Among these, the high catalytic activity of AlOOH prepared by the microemulsion method is derived from its high specific surface area, more active surface OH groups, and multi-active adsorption sites. And nanomaterials with such excellent properties have not yet been fabricated on a SERS-based platform to improve the Raman-enhanced properties of Ag achieving high-sensitivity detection of probe molecules especially with affinity for OH groups. The precious metal Ag has long been known to serve as traps to capture electrons and holes generated by plasmon resonance, reducing electron-hole recombination and exhibiting high activity in photocatalytic processes. In this work, to demonstrate the SERS substrate activity of the AlOOH@Ag complex, it has been successfully applied to identify congo red (CR) molecules with high sensitivity, methyl blue (MB) and methyl orange (MO), enabling trace-level detection with enhanced performance much stronger than Ag substrate.

Manipulating "Hot Spots" from Nanometer to Angstrom: Toward Understanding Integrated Contributions of Molecule Number and Gap Size for Ultrasensitive Surface-Enhanced Raman Scattering Detection.

Narrower gaps between metal nanoparticles (so-called "hot spots") in surface-enhanced Raman scattering (SERS) substrates contribute to stronger electromagnetic (EM) enhancement; however, the accompanying steric effect hinders analyte molecules entering hot spots to access the benefit. To comprehensively understand integrated contributions of the gap size and molecule number accommodated in hot spots and then optimize design of SERS substrates, the thermal shrinking method was employed to manipulate hot spots and the "hottest zone" was defined to evaluate the integrated contributions to SERS intensity of the two factors. In the conventional shrink-adsorption mode, the contributions of the molecule number and gap size are competitive when the gap width is comparable with the target molecule size, which leads to oscillating behavior of SERS intensity versus gap size, and it is analyte molecule size dependent. This result suggests that engineering hot spots should be target molecule directed to achieve ultrasensitive detection. In the proposed adsorption-shrink mode, the contributions of the molecule number and gap size are synergistic, which makes the detection ability of the adsorption-shrink mode attains a single-molecule (SM) level. Excellent performance of the adsorption-shrink SERS strategy benefits detection of trace level pollutants in complex environments. Detection ranges for contaminants with different metal affinity, such as thiram, malachite green (MG), and formaldehyde, are as low as parts per billion, even down to parts per trillion.