Greater Sensitivity Research Articles

Fabrication of modified Sb2O3 nanospheres for the removal of hazardous malachite green organic pollutant and selective NO2 gas sensor

Sb2O3 and Ni modified Sb2O3 (Ni–Sb2O3) nanospheres were synthesized using low cost co-precipitation method and characterised using various instrumental methods such as X-ray Powder Diffraction (XRD), High Resolution Transmission Electron Microscopy (HR-TEM), Scanning Electron Microscopy (SEM), Energy dispersive X-ray spectroscopy (EDS), and Fourier-transform infrared (FT-IR) spectroscopy. The XRD pattern reveals cubic crystal lattice. The average size of Sb2O3 and Ni–Sb2O3 nanoparticles was calculated to be around 41 nm and 29 nm, respectively. The HR-TEM investigation of the Sb2O3 nanomaterial reveals homogeneous spherical balls with a fine dispersion. The random-shaped nanoparticles with porous surfaces and voids were revealed by SEM. EDS examination confirms the elemental composition of Sb (41.79 %) and O (58.21 %) in Sb2O3 and Sb (36.80 %), O (58.95 %), and Ni (4.25 %) in Ni–Sb2O3. Sb2O3 and Ni– Sb2O3 exhibit band gaps of 3.67 eV and 3.51 eV, respectively, according to UV–Vis analysis. The IR peaks 445.47, 642.18, and 745.18 in Sb2O3 and 438.72, 645.07, and 756.92 in Ni– Sb2O3 support the Sb–O bonding in the synthesized nanomaterials. The synthesized nanomaterials have been used for photocatalytic degradation of malachite green (MG) dye and sensing NO2, SO2, CO2, petroleum vapour and LPG gases. The MG dye was degraded 97.67 % in 120 min using Ni–Sb2O3 at optimized conditions (catalyst dose: 0.1 g/L to 0.3 g/L, pH: 7 and MG dye: 10 ppm). The gas sensing study showed that Ni–Sb2O3 sensor has greater sensitivity and selectivity for NO2 gas.

Efficient integration of analytical quality-by-design and tri-hued HPLC-DAD approach for synchronized assessment of gemigliptin and rosuvastatin in their fixed-dose pills: Application to stability study

Life-threatening atherosclerotic cardiovascular disorder is a well-recognized risk among diabetics, which is clinically ascribed to their unbalanced plasma lipoproteins. Gemigliptin-Rosuvastatin is a recently introduced polytherapy prescribed for the management of diabetic dyslipidemia. Currently, the main focus of several analysts is to design more ecologically friendly sustainable approaches for pharmaceutical analysis. In this context, an innovative tri-hued (green, blue, and white) stability-indicating HPLC-DAD approach was developed to concurrently quantify Gemigliptin and Rosuvastatin polypills. Consequently, a strategic integration between analytical quality-by-design and green/white analytical chemistry principles was specifically designed to optimize efficiency and practicality while minimizing ecological burden. Two experimental designs, namely two-level fractional factorial and Box-Behnken designs, were employed for screening and optimization procedures, respectively. Optimal separation was attained utilizing an Agilent HC-C18 column in conjunction with a mobile phase consisting of acetonitrile and 10 mM sodium dihydrogen phosphate buffer, pH 3 (60:40 v/v), eluted in an isocratic manner at a 1 mL/min flow rate. Both analytes exhibited good linearities within the concentration range of 0.5–100 μg/mL. Furthermore, stability studies were conducted on both drugs in response to variable stress degradation scenarios. Fortunately, the adopted approach was well-suited to resolve the studied drugs from their respective degradants, thereby verifying the method's stability-indicating power. Tri-hued evaluation for the implemented approach was performed via up-to-date metrics, specifically, the Analytical Eco-scale, AGREE, Blue Applicability Grade Index, and RGB 12. Ultimately, our adopted stability-indicating HPLC approach exhibited great sensitivity, specificity, applicability, and rapidity as well as being ecologically sound. It is worth noting that this is the first stability-indicating HPLC approach for simultaneous assessment of the studied drugs.

Daily Temperatures and Child Hospital Admissions in Aotearoa New Zealand: Case Time Series Analysis.

The influence of global climate change on temperature-related health outcomes among vulnerable populations, particularly young children, is underexplored. Using a case time series design, we analysed 647,000 hospital admissions of children aged under five years old in New Zealand, born between 2000 and 2019. We explored the relationship between daily maximum temperatures and hospital admissions across 2139 statistical areas. We used quasi-Poisson distributed lag non-linear models to account for the delayed effects of temperature over a 0-21-day window. We identified broad ICD code categories associated with heat before combining these for the main analyses. We conducted stratified analyses by ethnicity, sex, and residency, and tested for interactions with long-term temperature, socioeconomic position, and housing tenure. We found J-shaped temperature-response curves with increased risks of hospital admission above 24.1 °C, with greater sensitivity among Māori, Pacific, and Asian compared to European children. Spatial-temporal analysis from 2013-2019 showed rising attributable fractions (AFs) of admissions associated with increasing temperatures, especially in eastern coastal and densely populated areas. Interactive maps were created to allow policymakers to prioritise interventions. Findings emphasize the need for child-specific and location-specific climate change adaptation policies, particularly for socioeconomically disadvantaged groups.

Simulation and deposition of Tungsten oxide (WO3) films using DC sputtering towards UV photodetector for high responsivity

Tungsten trioxide (WO3) detects UV radiation with great sensitivity while disregarding visible light, and it also has excellent electron mobility, allowing for efficient charge transport and fast response times. This work aims to develop a highly sensitive UV photodetector using WO3 material by optimizing the deposition parameter partial oxygen pressure (PaO2) and annealing the samples at various temperatures to determine the best PaO2 and annealing temperature that results in an improvement in the UV photodetector's sensitivity. The material WO3 was coated on glass substrates using DC magnetron sputtering while altering the PaO2 as 6 × 10−2 Pa, 4 × 10−2 -2 Pa, and 2 × 10−2 Pa, and then each as-deposited sample from varied PaO2 was annealed at temperatures ranging from 100°C to 400°C. When the sample's responses were compared, it was observed that the sample deposited at PaO2 2 × 10−2 Pa and annealed at 400 °C exhibited good photodetection capabilities, as evidenced by several characterization techniques such as SEM, XRD, and IV characterization. The work was subsequently carried out by evaluating the sample deposited at PaO2 2 × 10−2 Pa and annealed at 700 °C, which produced a good result for UV photodetection with the device's responsivity of 1e+4 A/W.

Design of hydrogen sensor relying on Pd-MWCNT/WO3 sensing materials for selective and rapid hydrogen detection

In this investigation, hydrogen sensors were designed based on multi-walled carbon nanotubes (MWCNT) and Pd loaded on WO3 nanosheets by means of hydrothermal synthesis and impregnation reduction. First, WO3 with different morphologies were synthesized, including zero dimension (0D) nanoparticles, one dimension (1D) nanowires and two dimension (2D) nanosheets. After testing, the 2D-WO3 material was selected as the substrate material to form final Pd-MWCNT/WO3 composites. Outstandingly, Pd-MWCNT/WO3 sensor exhibited greatest sensitivity with high response value (371.13), fast response/recovery time (1/4 s) to 1000 ppm hydrogen at 175℃, excellent selectivity and reproducibility. Furthermore, the corresponding hydrogen sensing mechanism was proposed combining with DFT calculation of hydrogen adsorption energy. This was the first report on designing a novel ternary Pd-MWCNT/WO3 composites sensor applied to hydrogen detection and the first time to calculate the hydrogen adsorption energy of Pd-MWCNT/WO3.

Shedding Light on Cellular Secrets: A Review of Advanced Optical Biosensing Techniques for Detecting Extracellular Vesicles with a Special Focus on Cancer Diagnosis.

In the relentless pursuit of innovative diagnostic tools for cancer, this review illuminates the cutting-edge realm of extracellular vesicles (EVs) and their biomolecular cargo detection through advanced optical biosensing techniques with a primary emphasis on their significance in cancer diagnosis. From the sophisticated domain of nanomaterials to the precision of surface plasmon resonance, we herein examine the diverse universe of optical biosensors, emphasizing their specified applications in cancer diagnosis. Exploring and understanding the details of EVs, we present innovative applications of enhancing and blending signals, going beyond the limits to sharpen our ability to sense and distinguish with greater sensitivity and specificity. Our special focus on cancer diagnosis underscores the transformative potential of optical biosensors in early detection and personalized medicine. This review aims to help guide researchers, clinicians, and enthusiasts into the captivating domain where light meets cellular secrets, creating innovative opportunities in cancer diagnostics.

Preparation and application of multiple particle binding-liposomes for electrochemiluminescent signal amplification in bioassays.

In this study, multiple particle binding-liposomes (MPB-Lips), encapsulating the luminophore tris(2',2-bipyridyl)ruthenium (II) complex ([Ru(bpy)3]2+), were developed as an electrochemiluminescence (ECL) signal amplifier and were applied to detect the model analyte streptavidin (SA) using the indirect competitive ECL method. The MPB-Lips were prepared by mixing various ratios of two different liposomes-one containing a phospholipid with a primary amine group and a biotinyl group (BIO/NH2-Lip) and one containing a phospholipid with an N-hydroxysuccinimide group (NHS-Lip) to allow binding between particles via amide bonds. Quartz crystal microbalance analysis using SA-modified gold-coated quartz crystals showed that the frequency shift values of MPB-Lips gradually decreased in the order BIO/NH2-Lip:NHS-Lip = 1:0 < 1:1 < 1:3 < 1:5. This indicated that MPB-Lips were successfully formed. The indirect competitive ECL method using SA-modified gold electrodes showed that the 1:5-Lip system had greater sensitivity than the 1:0-Lip system-the limit of detection and quantification values for the systems were 1.84 and 6.30μgmL-1 for 1:0-Lip, and 1.20 and 1.74μgmL-1 for 1:5-Lip. Finally, the recovery of SA spiked in fetal bovine serum samples using the 1:5-Lip system showed good accuracy and precision with a recovery rate of 83-106% and relative standard deviation of 4-14%. Our study demonstrated that the MPB-Lips system was an effective and useful ECL amplifier and the ECL method using MPB-Lips could be applied to detect an analyte in a real sample.

Fluorescence Carbon Dots from Blood-Berries for Sensing Cr6+ Ions in Water and Application in White Light Emitting Diode.

Conventional techniques for identifying heavy metal ions in water are laborious and time-consuming. Therefore, it is necessary to create innovative sensing technologies that can detect with greater sensitivity and speed. Although there have been reports of optical-based assays utilising fluorescent nanomaterials, these assays usually rely on variations in signal strength. However, this approach has significant drawbacks when it comes to environmental monitoring. Fluorescence carbon dots (CDs) have been prepared by facile synthesis from Blood berries. A homemade heavy metal optical detector is constructed to accurately identify heavy metal ions, exclusively Cr6+ ions in a water medium. Their optical emission signature varies based on the specific chromium ions in solution, and the emission intensity also changes depending on its concentration. The quenching behaviour is attributed to the interaction between the metallic cations and the fluorescent surface states of the carbon dots. Another application is the encapsulation of CDs in PVDF polymer to form a flexible film and use it as a phosphor for LED conversion.

Microscopic characteristics of peri- and postmortem fracture surfaces

This study investigated if microscopic surface features captured with a scanning electron microscope (SEM) effectively discriminate fracture timing. We hypothesized that microscopic fracture characteristics, including delamination, osteon pullout, and microcracks, may vary as bone elasticity decreases, elucidating perimortem and postmortem events more reliably than macroscopic analyses. Thirty-seven unembalmed, defleshed human femoral shafts from males (n=18) and females (n=2) aged 33–81 years were fractured at experimentally simulated postmortem intervals (PMIs) ranging from 1 to 60 warm weather days (250–40,600 ADH). A gravity convection oven was used to approximate tissue decomposition at 37 C and 27 C, and the resulting heat-time unit (accumulated degree hours, or ADH) was used to examine fractures in elastic/wet versus brittle/dry bone. The bones were fractured with a drop test frame using a three-point bending setup, sensors were used to calculate fracture energy, and high-speed photography documented fracture events. The following data were collected to relate fracture appearance to the biomechanical properties of bone: PMI (postmortem interval) length in ADH, temperature, humidity, collagen percentage, water loss, bone mineral density, cortical bone thickness, fracture energy, age, sex, cause of death, and microscopic fracture feature scores. SEM micrographs were collected from the primary tension zones of each fracture surface, and three microscopic fracture characteristics were scored from a region of interest in the center of the tension zone: percentage of delaminated osteons, percent osteon pullout, and number of microcracks. Multiple linear regression showed that microscopic fracture surface features are strong predictors of ADH (adjusted R-squared=0.67 for the 0 – 40,000 ADH samples; adjusted R-squared=0.92 for the 0–16,000 ADH samples). Osteon pullout is the single best predictor of ADH. Additionally, water loss is the primary driver of bone elasticity changes in low ADH samples, while collagen fibers appear to remain intact until later in the postmortem interval (approximately 40,000 ADH in this study). The results of this study indicate microscopic fracture surface analysis detects the biomechanical effects of decreased elasticity more reliably and with greater sensitivity than macroscopic analysis.

Development and validation of a UPLC-MS/MS method for rapid and simultaneous quantification of BPI-460372 and its metabolites BPI-460444 and BPI-460456 in human plasma

In cancer development and progression, the Hippo signaling pathway functions. The transcriptional enhanced associate domain (TEAD) stands out as a pivotal transcription factor within this pathway, and the suppression of TEAD represents a promising approach for cancer treatment. The primary aim of the study was to establish an analytical method for the concurrent quantification of a novel TEAD target inhibitor, BPI-460372, and its principal metabolites, BPI-460444 and BPI-460456, in human plasma. The chromatographic separation utilized a XSelect™ HSS C18 column (2.1 × 100 mm, 2.5 µm), while quantification was conducted on a SCIEX API 4000 mass spectrometer. 22 plasma samples were tested via the developed method. The calibration curve for BPI-460372 exhibited linearity from 2 to 2000 ng/mL, while its metabolites BPI-460444 and BPI-460456 had linearity between 1 and 1000 ng/mL (r > 0.99). The precision (RSD) was ≤ 17.1 %, and the accuracy (RE) fell within the range of −17.7 % to 15.0 %, all meeting acceptance criteria. The matrix effect was from 101.0 % to 105.8 %. The extraction recovery of analytes fell within the range of 96.8 % to 104.1 % with an RSD of less than 7.4 %. The developed method was effectively utilized in an advanced solid tumor patient, and the concentration trends of the three analytes in plasma were found to be largely consistent. The established analytical method showed great sensitivity, simplicity, accuracy, and reliability for the rapid and simultaneous analysis of the TEAD target inhibitor BPI-460372, alongside its major metabolites BPI-460444 and BPI-460456 in human plasma. This analytical method provided essential support for future clinical investigations and pharmacokinetic analysis.

Association between movement speed and instability catch kinematics and the differences between individuals with and without chronic low back pain

Studies reported the existence of instability catch (IC) during trunk flexion in patients with chronic low back pain (CLBP). However, different movement speeds can cause different neuromuscular demands resulting in altered kinematic patterns. In addition, kinematic characterization corresponding to clinical observation of IC is still limited. Therefore, this study aimed to determine (1) the association between movement speed and kinematic parameters representing IC during trunk flexion and (2) the differences in kinematic parameters between individuals with and without CLBP. Fifteen no low back pain (NoLBP) and 15 CLBP individuals were recruited. Inertial measurement units (IMU) were attached to T3, L1, and S2 spinous processes. Participants performed active trunk flexion while IMU data were simultaneously collected. Total trunk, lumbar, and pelvic mean angular velocity (T_MV, L_MV, and P_MV), as well as number of zero-crossings, peak-to-peak, and area of sudden deceleration and acceleration (Num, P2P, and Area), were derived. Pearson’s correlation tests were used to determine the association between T_MV and L_MV, P_MV, Num, P2P, and Area. An ANCOVA was performed to determine the difference in kinematic parameters between groups using movement speed as a covariate. Significant associations (P < 0.05) were found between movement speed and other kinematic parameters, except for Area. Results showed that L_MV significantly differed from the P_MV (P = 0.002) in the CLBP group, while a significant between-group difference (P = 0.037) was found in the P_MV. Additionally, significant between-group differences (P < 0.05) in P2P and Area were observed. The associations between movement speed and kinematic parameters suggest that movement speed changes can alter kinematic patterns. Therefore, clinicians may challenge lumbopelvic neuromuscular control by modifying movement speed to elicit greater change in kinematic patterns. In addition, the NoLBP group used shared lumbar and pelvic contributions, while the CLBP group used less pelvic contribution. Finally, P2P and Area appeared to offer the greatest sensitivity to differentiate between the groups. Overall, these findings may enhance the understanding of the mechanism underlying IC in CLBP.

On the response of the CR-39 NTD to low doses of gamma rays using optical and photoluminescence spectroscopy

In this work, the response of the CR-39 nuclear track detector (NTD) exposed to different low doses of gamma rays was investigated using UV–Vis and photoluminescence spectroscopy. Five NTDs of CR-39 were irradiated with low gamma-ray doses ranging from 10 to 120 kGy using a60Co source. The dose of gamma rays correlates with red shift in the absorption spectra of a gamma-irradiated CR-39 detector. As the gamma dose increases, the indirect and direct energy band gaps, as well as Urbach energy, decrease gradually. However, the decrease in the indirect optical band gap is greater than the decrease in the direct band gap. The observed spectra of the CR-39 detector after being irradiated with different doses of γ-rays showed an acceptable variation in photoluminescence (PL) emission spectra generated by a well-defined excitation wavelength of 290 nm. Starting at 45 kGy dose, the integrated area of the photoluminescence peak increases and tends to saturate, whereas the photoluminescence peak height is linearly correlated with the gamma dose with high sensitivity, which is 53.1 ± 6.3 CPS. kGy−1. According to the current findings, photoluminescence (PL) spectroscopy has a greater sensitivity than UV–Vis spectroscopy for measuring the response of the CR-39 detector to gamma rays in the dose range of 10–120 kGy. The results reflected a potential possibility of using the CR-39 detector in dosimetric applications of low gamma ray doses through the high resolution achieved by photoluminescence (PL) and UV–Vis spectroscopy.

Improved method for detecting protein-protein interactions using proximity ligation assay.

Proximity ligation assay has been widely used to detect protein-protein interaction in cells and tissues. While with great sensitivity, its specificity was often neglected. Here, we report the existence of varying levels of false positives observed with this assay and provide suggestions to minimize false positives for more accurate detection of protein-protein interactions, especially for membrane proteins.

Performance of explainable artificial intelligence in guiding the management of patients with a pancreatic cyst

Background/objectivesPancreatic cyst management can be distilled into three separate pathways – discharge, monitoring or surgery– based on the risk of malignant transformation. This study compares the performance of artificial intelligence (AI) models to clinical care for this task. MethodsTwo explainable boosting machine (EBM) models were developed and evaluated using clinical features only, or clinical features and cyst fluid molecular markers (CFMM) using a publicly available dataset, consisting of 850 cases (median age 64; 65 % female) with independent training (429 cases) and holdout test cohorts (421 cases). There were 137 cysts with no malignant potential, 114 malignant cysts, and 599 IPMNs and MCNs. ResultsThe EBM and EBM with CFMM models had higher accuracy for identifying patients requiring monitoring (0.88 and 0.82) and surgery (0.66 and 0.82) respectively compared with current clinical care (0.62 and 0.58). For discharge, the EBM with CFMM model had a higher accuracy (0.91) than either the EBM model (0.84) or current clinical care (0.86). In the cohort of patients who underwent surgical resection, use of the EBM-CFMM model would have decreased the number of unnecessary surgeries by 59 % (n = 92), increased correct surgeries by 7.5 % (n = 11), identified patients who require monitoring by 122 % (n = 76), and increased the number of patients correctly classified for discharge by 138 % (n = 18) compared to clinical care. ConclusionsEBM models had greater sensitivity and specificity for identifying the correct management compared with either clinical management or previous AI models. The model predictions are demonstrated to be interpretable by clinicians.

A Comparative Study of Cystatin C and Creatinine as a Preliminary Marker of Nephropathy in Type 2 Diabetic Patients

Background: Type 2 diabetes disorder (T2DD) is one of the most common disorder in societies, and its causes are genetic and acquired. This disorder is characterized by an increase in the concentration of glucose in the blood. High concentrations of glucose in the blood for long periods lead to complications, the most important of which is diabetic nephropathy (DNP), which is characterized by the gradual loss of the kidney's filtration function.Material and methods: The present study was designed based on collecting twenty patients with newly DNP (as first group) and twenty healthy individuals (as second group). The levels of HbA1c, Creatinine and Cystatin C of all study individuals were measured using Chromatographic assay method, Kinetic colorimetric method and Immunoturbidimetric assay techniques respectively.Results: This study used the t-test statistical method to compare groups as well as sensitivity and specificity based on HbA1c, creatinine and Cystatin C biomarkers. The current study showed a higher the HbA1c percentage, creatinine level and Cystatin C level in the first group compared to the second group. On the other hand, the current study showed that Cystatin C has greater sensitivity and specificity than creatinine towards the DNP disease.Conclusion: The current study concluded by stating the importance of the role of Cystatin C as an early indicator of DNP disease, as the current study proved that Cystatin C has greater sensitivity and specificity than creatinine towards DNP disease

Muon g−2 , long-range muon spin force, and neutrino oscillations

Recent studies have proposed using a geocentric muon spin force to account for the (g−2)μ anomaly, with the long-range force mediator being a light axionlike particle. The mediator exhibits a CP-violating scalar coupling to nucleons and a normal derivative coupling to muons. Due to the weak symmetry, this axion inevitably couples to neutrinos, providing potential impact on neutrino oscillations. By utilizing neutrino data from BOREXINO, IceCube DeepCore, Super-Kamiokande, and SNO, we have identified that both atmospheric and solar neutrino data can impose stringent constraints on the long-range muon spin force model and the (g−2)μ parameter space. With optimized data analysis techniques and the potential from future experiments, such as JUNO, Hyper-Kamiokande, SNO+, and IceCube PINGU, there exists a promising opportunity to achieve even greater sensitivities. Indeed, neutrino oscillations offer a robust and distinctive cross-check for the model, offering stringent constraints on the (g−2)μ parameter space. Published by the American Physical Society 2024

Validation of the Danish Version of the Overall Depression Severity and Impairment Scale (ODSIS): A Reliable Instrument for Assessing Depression Symptoms and Functional Impairment.

In psychotherapy, having a reliable tracking tool is vital for effective treatment. We have validated the Danish version of the 'Overall Depression Severity and Impairment Scale' (ODSIS), which is used in the Unified Protocol for Emotional Disorders (UP) and other cognitive behavioural therapies. This five-item self-rating scale is expected to correspond closely to the gold-standard Beck Depression Inventory-II (BDI-II), but also to self-rating scales addressing daily functioning and well-being. Internal consistency is assessed using Cronbach's alpha and McDonald's omega. Criterion validity is explored through Pearson's correlation coefficient with BDI-II, the Work and Social Adjustment Scale (WSAS), the Five-Item World Health Organization Well-Being Index (WHO-5) and scatter plots, and an optimal cut-off score is determined using a receiver operating characteristic curve. The study included 340 respondents: 234 from a recent clinical trial, 56 psychiatric patients from inpatient/outpatient units and 50 healthy volunteers. ODSIS demonstrates strong internal consistency (Cronbach's alpha: 0.887-0.956, McDonald's omega: 0.888-0.957). Correlations with BDI-II, WSAS and WHO-5 highlight its strong criterion validity (BDI-II: 0.847, WSAS: 0.751, WHO-5: 0.771). The optimal cut-off score (> 7.5) for detecting depression shows great sensitivity (0.862) and specificity (0.731). The Danish version of ODSIS proves to be a reliable instrument for quantification of a combination of depression level and functional impairment from the symptoms. Its high correlation with established BDI-II makes it a brief and handy tool for repeated measurement in clinical and research settings.

The Importance of Proteomics in Saliva and Tears as Potential Non-invasive Methods for Identifying Biomarkers in the Prognosis and Diagnosis of Multiple Sclerosis Patients

: Over the past two decades, the advancement of analytical examinations like proteomics for investigating neuronal-related biomarkers has emerged as one of the most important and effective tools for clinical evaluation and prognosis. However, there remains an unmet need in this area. With advances in quantifying methods and detection in omics research, including proteomics and metabolomics, the close association of the salivary glands and tears with the nervous system has become increasingly evident. As noninvasive specimens, saliva and tears serve as attractive substitutes for neuronal biomarkers, containing numerous proteins and metabolites that represent various ailments in neurodegenerative illnesses like multiple sclerosis (MS). These noninvasive biomarkers might potentially correlate with susceptibility, severity, and pathogenesis of neurological disorders and could be utilized in early diagnosis and prognosis. Therefore, tear and salivary proteomics present novel insights into understanding disease progression and offer personalized treatment options with greater sensitivity. This approach helps highlight the most relevant experimental outcomes related to tear and salivary biomarkers for multiple sclerosis.

Ultrasensitive electrochemical sensor based on dimethylglyoxime/carbon paste electrode modified with a bimetallic nanocomposite for nickel detection in environmental water samples

To date, research in the monitoring of heavy metal pollution focuses on developing an advanced and selective sensor. In this study, an electrochemical sensor-based bimetallic nanocomposite modified dimethylglyoxime carbon paste electrode (DMG/CPE) was created to detect Ni2+ selectively. The bimetallic nanocomposite was prepared by depositing a thin layer of silver nanoparticles (AgNPs) on the surface of the magnetite (Fe3O4)/DMG/CPE electrode. The incorporation of Fe3O4 and AgNPs results in a synergistic effect, increasing electron transfer and expanding the electroactive surface area (from 2.78 mm2 to 3.81 mm2), hence leading to an increase in the peak current response (ΔIp = 26.15 ± 0.33 µA at modified CPE). The prepared AgNPs/Fe3O4/DMG/CPE electrode demonstrated excellent properties, allowing for a broad linear dynamic range lying between 2–10 nM; 10–100 nM; and 100–1000 nM and a limit of detection value of 0.6 nM (S/N = 3). Additionally, the developed sensor showed great sensitivity, selectivity, and reliability in the detection of Ni2+ in river water samples, making it promising for a sensitive and selective detection of Ni-contaminated water.

Biochemical Risk Factors of Atherosclerosis in Patients with Severe and Non-severe COVID-19

Background: COVID-19 may trigger the progression of atherosclerosis, potentially leading to its clinical manifestation. Among the serum biomarkers related to atherosclerotic disease, it seems helpful to evaluate biochemical factors such as CD147, ACE2, and ACE in patients with COVID-19. Methods: In this case-control study, serum samples from 90 patients were analyzed. The cohort included 30 patients hospitalized in the intensive care unit with COVID-19, 30 patients hospitalized in the ward with COVID-19, and 30 healthy individuals from Ayatollah Kashani Hospital (Tehran, Iran). These patients were admitted between December 10, 2022, and March 10, 2023. The concentrations of cholesterol, triglycerides, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and the activity levels of angiotensin-converting enzyme (ACE), angiotensin-converting enzyme 2 (ACE2), troponin, CPK, CPK-MB, and CD147 were determined and analyzed among the three groups. Results: There was no significant difference in age between the patients (55.40 ± 10.34 years) and the control group (58.34 ± 11.71 years). SARS-CoV2 viral RNA was detected in the pharyngeal swab samples of the COVID-19 patients. The levels of CD-147 (2528.43 ± 12.43 vs. 2176.7 ± 9.87 vs. 1346.3 ± 14.23), ACE (83 ± 3.05 vs. 97 ± 1.55 vs. 30.1 ± 2.32), troponin (0.972 ± 0.25 vs. 0.784 ± 0.21 vs. 0.021 ± 0.68), and cholesterol (199.73 ± 2.43 vs. 175.87 ± 5.21 vs. 144.97 ± 8.74) were significantly higher in severe cases compared to non-severe cases (P &lt; 0.05). ACE (AUC = 0.894) and CD147 (AUC = 0.821) had the highest sensitivity and specificity among the studied factors, respectively. Patients with normal levels of ACE and CPK-MB had a 0.16 times lower and 4.37 times greater chance of experiencing severe disease, respectively. Three strong correlations were found among the studied parameters: CD147 with ACE2 (r = 0.721) and cholesterol with triglyceride (r = 0.602) (P &lt; 0.05). Conclusions: Examining ACE and CD147 can help determine a person's susceptibility to atherosclerosis. These two factors have greater sensitivity and specificity and could be used as potential markers for monitoring disease progression.