Drug-induced Kidney Disease: Revisited.

Drug-induced kidney disease (DIKD) is a frequent cause of acute and chronic kidney disease (CKD) that leads to high morbidity, hospitalization, and increased healthcare costs. There is a need to constantly update our knowledge in this field, given the ever-burgeoning list of newer treatments that are emerging, especially in the field of cancer immunotherapy. Generalizing the complex pathways causing DIKD from different agents, the common mechanisms include direct toxicity, immune-mediated injury, and drug-induced alterations in renal blood flow. Proper management of this condition involves risk minimization, early detection of renal damage, and timely discontinuation of potential agents to avoid irreversible renal damage.

Silver and Copper Nanoparticle-Loaded Self-Assembled Pseudo-Peptide Thiourea-Based Organic-Inorganic Hybrid Gel with Antibacterial and Superhydrophobic Properties for Antifouling Surfaces.

The escalating threat of antimicrobial resistance has become a global health crisis. Therefore, there is a rising momentum in developing biomaterials with self-sanitizing capabilities and inherent antibacterial properties. Despite their promising antimicrobial properties, metal nanoparticles (MNPs) have several disadvantages, including increased toxicity as the particle size decreases, leading to oxidative stress and DNA damage that need consideration. One solution is surface functionalization with biocompatible organic ligands, which can improve nanoparticle dispersibility, reduce aggregation, and enable targeted delivery to microbial cells. The existing research predominantly concentrates on the advancement of peptide-based hydrogels for coating materials to prevent bacterial infection, with limited exploration of developing surface coatings using organogels. Herein, we have synthesized organogel-based coatings doped with MNPs that can offer superior hydrophobicity, oleophobicity, and high stability that are not easily achievable with hydrogels. The self-assembled gels displayed distinct morphologies, as revealed by scanning electron microscopy and atomic force microscopy. The cross-linked matrix helps in the controlled and sustained release of MNPs at the site of bacterial infection. The synthesized self-assembled gel@MNPs exhibited excellent antibacterial properties against harmful bacteria such as Escherichia coli and Staphylococcus aureus and reduced bacterial viability up to 95% within 4 h. Cytotoxicity testing against metazoan cells demonstrated that the gels doped with MNPs were nontoxic (IC50 > 100 µM) to mammalian cells. Furthermore, in this study, we coated the organogel@MNPs on cotton fabric and tested it against Gram +ve and Gram -ve bacteria. Additionally, the developed cotton fabric exhibited superhydrophobic properties and developed a barrier that limits the interaction between bacteria and the surface, making it difficult for bacteria to adhere and colonize, which holds potential as a valuable resource for self-cleaning coatings.

Geometric Transformation of Modified Multiwalled Carbon Nanotubes-Based Heterometallic Nanostructured Material: A Model for the Electrochemical Discrimination of Insecticides.

Multifunctional carbon-based materials exhibit a large number of unprecedented active sites via an electron transfer process and act as a desired platform for exploring high-performance electroactive material. Herein, we exemplify the holistic design of a heterometallic nanostructured material (MWCNTs@KR-6/Mn/Sn/Pb) formed by the integration of metals (Mn2+, Sn2+, and Pb2+) and a dipodal ligand (KR-6) at the surface of multiwalled carbon nanotubes (MWCNTs). First, MWCNTs@KR-6 was readily synthesized via a noncovalent approach, which was further sequentially doped by Mn2+, Sn2+, and Pb2+ to give MWCNTs@KR-6/Mn/Sn/Pb. The designed material showed excellent electrochemical activity for the discrimination of insecticides belonging to structurally different classes. In contrast to that of the individual building components, both the stability and electrochemical activity of heterometallic nanostructured material were remarkably enhanced, resulting in a magnificent electrochemical performance of the developed material. Hence, the current work reports a comprehensive synthetic approach for MWCNTs@KR-6/Mn/Sn/Pb synthesis by synergizing unique properties of the heterometallic complex with MWCNTs. This work also offers a new insight into the design of multifunctional carbon-based materials for discrimination of different analytes on the basis of their redox potential.

Synthesis and characterization of a novel copper carboxylate complex and a copper complex-coated polyether sulfone membrane for efficient degradation of methylene blue dye under UV irradiation: the single crystal X-ray structure of the copper carboxylate complex.

Synthesis of a novel binuclear Cu(II) carboxylate complex under ambient laboratory conditions is presented. The complex exhibits a paddle wheel structure in which the axial positions are occupied by two copper atoms instead of two water molecules. The synthesized complex was characterized by single-crystal X-ray crystallography, FT-IR, X-ray diffraction, and UV-visible spectroscopy techniques. The thermal stability of the metal complex was studied by the thermogravimetric analysis study. The synthesized metal complex was employed for the synthesis of metal complex-coated polyether sulfone (PES) membranes which were characterized before and after filtration using the FESEM technique. The photocatalytic efficiency of the metal complex was studied for the degradation of methylene blue dye under UV irradiation in the presence of H2O2 and was compared with the photodegradation efficiency of the metal complex-coated polyether sulfone (PES) membrane.

An Encyclopedic Compendium on Chemosensing Supramolecular Metal-Organic Gels.

Chemosensing, an interdisciplinary scientific domain, plays a pivotal role ranging from environmental monitoring to healthcare diagnostics and (inter)national security. Metal-organic gels (MOGs) are recognized for their stability, selectivity, and responsiveness, making them valuable for chemosensing applications. Researchers have explored the development of MOGs based on different metal ions and ligands, allowing for tailored properties and sensitivities, and have even demonstrated their applications as portable sensors such as paper-based test strips for practical use. Herein, several studies related to MOGs development and their applications in the chemosensing field via UV-visible or luminance along with electrochemical approach are presented. These papers explored MOGs as versatile materials with their use in sensing bio or environmental analytes. This review provides a foundational understanding of key concepts, methodologies, and recent advancements in this field, fostering the scientific community.

Prophylactic dexamethasone for rebound pain after peripheral nerve block in adult surgical patients: systematic review, meta-analysis, and trial sequential analysis of randomised controlled trials.

BACKGROUND: Rebound pain occurs after the resolution of peripheral nerve block and hampers patient recovery in the postoperative period. We sought to synthesise available data from randomised controlled trials (RCTs) evaluating the efficacy of prophylactic dexamethasone for rebound pain in adult patients undergoing surgery with a peripheral nerve block. METHODS: In this systematic review and meta-analysis, RCTs reporting rebound pain and use of dexamethasone in the context of a peripheral nerve block were searched in various databases and updated in May 2023. The primary outcome was the incidence of rebound pain; secondary outcomes included the severity and time to onset of rebound pain, patient satisfaction with pain control, sleep disturbance because of pain, and adverse effects of dexamethasone. Subgroup analysis was conducted based on the effect of route of administration (intravenous or perineural) on the incidence of rebound pain. Trial sequential analysis was performed to rule out the possibility of a false positive result. RESULTS: Seven RCTs comprising 574 patients were included in this review. The dexamethasone group was associated with a reduction in the incidence of rebound pain with an odds ratio of 0.16 (95% confidence interval 0.10-0.27, P=0.00, I2=0%) compared with the control group. Trial sequential analysis confirmed the adequate information size for the beneficial effect of dexamethasone. Subgroup analysis showed that both intravenous and perineural administration were associated with a significant reduction in the incidence of rebound pain. CONCLUSIONS: Current evidence suggests that both intravenous and perineural dexamethasone reduce the incidence of rebound pain after a peripheral nerve block provided for postoperative analgesia. SYSTEMATIC REVIEW PROTOCOL: PROSPERO CRD42023424031.

Core-Labeled Reverse Micelle-Based Supramolecular Solvents for Assisted Quick and Sensitive Determination of Amitriptyline in Wastewater.

In recent years, the issue of pharmaceutical contaminants in water bodies has emerged as a significant environmental concern owing to the potential negative impacts on both aquatic ecosystems and human health. Consequently, the development of efficient and eco-friendly methods for their determination and removal is of paramount importance. In this context, the development of a surfactant ensemble sensor has been explored for hard-to-sense amphiphilic drug, i.e., amitriptyline. Herein, a pyrene-based amphiphile chemoreceptor was synthesized and characterized through various spectroscopic techniques such as 1H, 13C NMR, single-crystal XRD, FTIR, and ES-mass spectrometry. Then, dodecanoic acid (DA) and a pyrene-based receptor in a THF/water solvent system were used to generate reverse micelle-based self-aggregates of SUPRAS (SUPRAmolecular Solvent). The structural aspects, such as morphology and size, along with the stability of the SUPRAS aggregates were unfolded through spectroscopic and microscopic insights. The present investigation describes a synergistic approach that combines the unique properties of premicellar concentration of supramolecular solvent with the promising potential of pyrene-based receptor for enhanced amitriptyline extraction with simultaneous determination from water (LOD = 12 nM). To evaluate the effectiveness of the developed aggregates in real-world scenarios, experiments were conducted to determine the sensing efficiency among various pharmaceutical pollutants commonly found in water sources. The results reveal that the synergistic nanoensemble exhibits remarkable sensing ability, toward the amitriptyline (AMT) drug outperforming conventional methods.

Solvent directed morphogenesis of a peptidic-benzimidazolium dipodal receptor: ratiometric detection and catalytic degradation of ochratoxin A.

Ochratoxin A (OTA) is the most abundant and harmful toxin found in agriculture and processed food. The environment and human health are both harmed by this mycotoxin. As a result, in various scenarios, selective detection and biodegradation of ochratoxin A are essential. The current study reveals the morphogenesis of a peptidic-benzimidazolium dipodal receptor (SS4) and its application as a catalytic and sensing unit for the detection and degradation of OTA in an aqueous medium. Initially, a facile and scalable method was executed to synthesize SS4, and solvent-directed morphogenesis were examined under SEM analysis. Consequently, molecular recognition properties of self-assembled architectures were explored using UV-visible absorption, fluorescence spectroscopy, and atomic force microscopy (AFM). The designed probe showed a ratiometric response for OTA and served as a catalytic unit for the degradation of OTA at a short interval of 25 min. The biodegradation pathway for OTA was accomplished using LC-MS analysis. Furthermore, the reliability of the developed method was checked by determining the spiked concentrations of the OTA in cereals and wine samples. The results obtained are in good agreement with the % recovery and RSD values. The present work provides a robust, selective, and sensitive method of detection and degradation for OTA.

A Deep Learning Algorithm to Identify Anatomical Landmarks on Computed Tomography of the Temporal Bone.

BACKGROUND: Petrous temporal bone cone-beam computed tomography scans help aid diagnosis and accurate identification of key operative landmarks in temporal bone and mastoid surgery. Our primary objective was to determine the accuracy of using a deep learning convolutional neural network algorithm to augment identification of structures on petrous temporal bone cone-beam computed tomography. Our secondary objective was to compare the accuracy of convolutional neural network structure identification when trained by a senior versus junior clinician. METHODS: A total of 129 petrous temporal bone cone-beam computed tomography scans were obtained from an Australian public tertiary hospital. Key intraoperative landmarks were labeled in 68 scans using bounding boxes on axial and coronal slices at the level of the malleoincudal joint by an otolaryngology registrar and board-certified otolaryngologist. Automated structure identification was performed on axial and coronal slices of the remaining 61 scans using a convolutional neural network (Microsoft Custom Vision) trained using the labeled dataset. Convolutional neural network structure identification accuracy was manually verified by an otolaryngologist, and accuracy when trained by the registrar and otolaryngologist labeled datasets respectively was compared. RESULTS: The convolutional neural network was able to perform automated structure identification in petrous temporal bone cone-beam computed tomography scans with a high degree of accuracy in both axial (0.958) and coronal (0.924) slices (P < .001). Convolutional neural network accuracy was proportionate to the seniority of the training clinician in structures with features more difficult to distinguish on single slices such as the cochlea, vestibule, and carotid canal. CONCLUSION: Convolutional neural networks can perform automated structure identification in petrous temporal bone cone-beam computed tomography scans with a high degree of accuracy, with the performance being proportionate to the seniority of the training clinician. Training of the convolutional neural network by the most senior clinician is desirable to maximize the accuracy of the results.

Portable Sensor Array for On-Site Detection and Discrimination of Pesticides and Herbicides Using Multivariate Analysis.

Modern agricultural practice relies heavily on pesticides and herbicides to increase crop productivity, and consequently, their residues have a negative impact on the environment and public health. Thus, keeping these issues in account, herein we developed an azodye-based chromogenic sensor array for the detection and discrimination of pesticides and herbicides in food and soil samples, utilizing machine learning approaches such as hierarchical clustering analysis, principal component analysis, linear discriminant analysis (LDA), and partial least square regression (PLSR). The azodye-based sensor array was developed in combination with various metal ions owing to their different photophysical properties, which led to distinct patterns toward various pesticides and herbicides. The obtained distinct patterns were recognized and processed through automated multivariate analysis, which enables the selective and sensitive identification and discrimination of various target analytes. Further, the qualitative and quantitative determination of target analytes were performed using LDA and PLSR; the results obtained show a linear correlation with varied concentrations of target analytes with R2 values from 0.89 to 0.96, the limit of detection from 5.3 to 11.8 ppm with a linear working range from 1 to 30 µM toward analytes under investigation. Further, the developed sensor array was successfully utilized for the discrimination of a binary mixture of pesticide (chlorpyrifos) and herbicide (glyphosate).

Efficacy of Different Approaches of Quadratus Lumborum Block for Postoperative Analgesia After Cesarean Delivery: A Bayesian Network Meta-analysis of Randomized Controlled Trials.

OBJECTIVES: Various approaches to quadratus lumborum block (QLB) have been found to be an effective analgesic modality after cesarean delivery (CD). However, the evidence for the superiority of any individual approach still needs to be demonstrated. Therefore, we conducted this network meta-analysis to compare and rank the different injection sites for QLB for pain-related outcomes after CD. MATERIALS AND METHODS: PubMed, EMBASE, SCOPUS, and the Cochrane Central Registers of Controlled Trials (CENTRAL) were searched for randomized controlled trials (RCTs) evaluating the role of any approach of QLB with placebo/no block for post-CD pain. The primary outcome was parenteral consumption of morphine milligram equivalents in 24 postoperative hours. The secondary end points were early pain scores (4 to 6 h), late pain scores (24 h), adverse effects, and block-related complications. We used the surface under cumulative ranking probabilities to order approaches. The analysis was performed using Bayesian statistics (random-effects model). RESULTS: Thirteen trials enrolling 890 patients were included. The surface under cumulative ranking probability for parenteral morphine equivalent consumption in 24 hours was the highest (87%) for the lateral approach, followed by the posterior and anterior approaches. The probability of reducing pain scores at all intervals was highest with the anterior approach. The anterior approach also ranked high for postoperative nausea and vomiting reduction, the only consistent reported side effect. DISCUSSION: The anterior approach QLB had a superior probability for most patient-centric outcomes for patients undergoing CD. The findings should be confirmed through large RCTs.

An artificial intelligence algorithm for the classification of sphenoid sinus pneumatisation on sinus computed tomography scans.

BACKGROUND: Classifying sphenoid pneumatisation is an important but often overlooked task in reporting sinus CT scans. Artificial intelligence (AI) and one of its key methods, convolutional neural networks (CNNs), can create algorithms that can learn from data without being programmed with explicit rules and have shown utility in radiological image classification. OBJECTIVE: To determine if a trained CNN can accurately classify sphenoid sinus pneumatisation on CT sinus imaging. METHODS: Sagittal slices through the natural ostium of the sphenoid sinus were extracted from retrospectively collected bone-window CT scans of the paranasal sinuses for consecutive patients over 6 years. Two blinded Otolaryngology residents reviewed each image and classified the sphenoid sinus pneumatisation as either conchal, presellar or sellar. An AI algorithm was developed using the Microsoft Azure Custom Vision deep learning platform to classify the pattern of pneumatisation. RESULTS: Seven hundred eighty images from 400 patients were used to train the algorithm, which was then tested on a further 118 images from 62 patients. The algorithm achieved an accuracy of 93.2% (95% confidence interval [CI] 87.1-97.0), 87.3% (95% CI 79.9-92.7) and 85.6% (95% CI 78.0-91.4) in correctly identifying conchal, presellar and sellar sphenoid pneumatisation, respectively. The overall weighted accuracy of the CNN was 85.9%. CONCLUSION: The CNN described demonstrated a moderately accurate classification of sphenoid pneumatisation subtypes on CT scans. The use of CNN-based assistive tools may enable surgeons to achieve safer operative planning through routine automated reporting allowing greater resources to be directed towards the identification of pathology.

Local and systemic inflammatory response to the intrauterine infusion of enzymes during estrus in water buffaloes with subclinical endometritis.

Our objective was to determine the effects of intrauterine infusion of proteolytic enzymes in buffaloes with subclinical endometritis (SCE) at estrus on the resolution of endometrial inflammation and reproductive performance. Buffaloes at spontaneous estrus (E1) were screened for SCE by endometrial cytology to identify SCE (≥5% PMN, n = 22) and non-SCE (<5% PMNs, n = 14) animals. All buffaloes underwent uterine ultrasonographic examination, low volume uterine lavage (cytokines and acute phase proteins) and blood sampling (cytokines and acute-phase proteins) at E1. On the same day (E1), SCE buffaloes were randomly selected either for intrauterine infusion of proteolytic enzymes (ENY, n = 11) or saline (PC, n = 11). Buffaloes without SCE were kept as untreated control (NC; n = 14). All buffaloes were re-examined and re-sampled during subsequent estrus (E2), inseminated during the following estrus (E3), and assessed for fertility related outcomes. Proteolytic infusion resulted a reduction in uterine PMN (P < 0.01) in SCE buffaloes. The concentrations of interleukin (IL)-1ß and tumor necrosis factor (TNF)-α in uterus, and TNF-α and IL-10 in serum were higher (P < 0.01) at E1 in buffaloes with SCE (PC and ENY) compared to NC. After treatment, uterine IL-1ß and TNF-α (P = 0.02), and serum TNF-α and IL-10 were lower within the animals of ENY group (P < 0.01). Before treatment, buffaloes with SCE had higher concentrations (P < 0.01) of serum and uterine amyloid-A and haptoglobin, which decreased (P < 0.01) after treatment in the ENY group. None of the fertility outcomes differ between the treatment groups. In conclusion, intrauterine infusion of proteolytic enzymes reduced endometrial inflammation; however, did not improve reproductive outcomes.

Pharmacological agents for prevention of pruritus in women undergoing Caesarean delivery with neuraxial morphine: a systematic review and Bayesian network meta-analysis.

BACKGROUND: Neuraxial opioids provide effective analgesia for Caesarean delivery, however, pruritus can be a troubling side-effect. Effective agents to prevent pruritus are needed. Our objective was to perform an updated systematic review and network meta-analysis to provide clinicians with a comparison of relative efficacy of available interventions to reduce the incidence of pruritus, induced by either intrathecal or epidural single-shot morphine, in women undergoing Caesarean delivery. METHODS: Databases systematically searched (up to January 2022) included PubMed MEDLINE, Web of Science, EBSCO CINAHL, Embase, LILACS, and two Cochrane databases. We included randomised, controlled trials involving adult female patients undergoing Caesarean delivery. We pooled trials comparing interventions used for preventing pruritus after Caesarean delivery and performed a Bayesian model network meta-analysis. RESULTS: The final primary network included data from comparisons of 14 distinct interventions (including placebo) used to reduce the incidence of pruritus in 6185 participants. We judged five interventions to be 'definitely superior' to placebo: propofol, opioid agonist-antagonists (neuraxial), opioid antagonists, opioid agonist-antagonists (systemic), and serotonin antagonists. For the network evaluating the incidence of severe pruritus (warranting additional therapeutic treatment of pruritus), data were available for 14 interventions (including placebo) in 4489 patients. For this outcome, we judged three interventions to be 'definitely superior' to placebo: dopamine antagonists (neuraxial) and systemic and neuraxial opioid agonist-antagonists. CONCLUSION: Our analysis found several interventions to be effective in reducing the incidence of pruritus. Although sub-hypnotic doses of propofol appear to have an antipruritic effect, replication of this finding and further investigation of optimal dosing are warranted. SYSTEMATIC REVIEW PROTOCOL: PROSPERO (CRD42022367058).

A Computer Vision Algorithm to Classify Pneumatization of the Mastoid Process on Temporal Bone Computed Tomography Scans.

BACKGROUND: Pneumatization of the mastoid process is variable and of significance to the operative surgeon. Surgical approaches to the temporal bone require an understanding of pneumatization and its implications for surgical access. This study aims to determine the feasibility of using deep learning convolutional neural network algorithms to classify pneumatization of the mastoid process. METHODS: De-identified petrous temporal bone images were acquired from a tertiary hospital radiology picture archiving and communication system. A binary classification mode in the pretrained convolutional neural network was used to investigate the utility of convolutional neural networks in temporal bone imaging. False positive and negative images were reanalyzed by the investigators and qualitatively assessed to consider reasons for inaccuracy. RESULTS: The overall accuracy of the model was 0.954. At a probability threshold of 65%, the sensitivity of the model was 0.860 (95% CI 0.783-0.934) and the specificity was 0.989 (95% CI 0.960-0.999). The positive predictive value was 0.973 (95% CI 0.904-0.993) and the negative predictive value was 0.935 (95% CI 0.901-0.965). The false positive rate was 0.006. The F1 number was 0.926 demonstrating a high accuracy for the model. CONCLUSION: The temporal bone is a complex anatomical region of interest to otolaryngologists. Surgical planning requires high-resolution computed tomography scans, the interpretation of which can be augmented with machine learning. This initial study demonstrates the feasibility of utilizing machine learning algorithms to discriminate anatomical variation with a high degree of accuracy. It is hoped this will lead to further investigation regarding more complex anatomical structures in the temporal bone.

Analgaesic efficacy of single-injection serratus anterior plane block for breast surgery: A systematic review, meta-analysis and trial sequential analysis of randomised controlled trials.

There is conflicting evidence regarding the analgaesic efficacy of single-shot serratus anterior plane block (SAP) for breast surgery. This meta-analysis aimed to evaluate the analgaesic efficacy of SAP compared with non-block care (NBC) and other regional blocks, i.e. paravertebral block (PVB) and modified pectoral nerve block (PECS block) for breast surgery. PubMed, Embase, Scopus, the Cochrane Central Register of Controlled Trials and ClinicalTrials.gov were searched. We included randomized controlled trials reporting the use of the SAP block in adult breast surgery. The primary outcome was postoperative oral morphine equivalent (OME) consumption for up to 24 hours. Random-effects models were used to pool results and mean difference (MD), and odds ratio (OR) was calculated for continuous and dichotomous outcomes, respectively. GRADE guidelines were used to evaluate the strength of evidence, and trial sequential analysis (TSA) was performed to provide certainty to the conclusion. Twenty-four trials enrolling 1789 patients were included. Moderate strength evidence suggested that SAP provided a significant reduction in 24-hour OME compared with NBC [MD - 24.9 mg (95% CI - 41.54, -8.25; P < 0.001, I2 = 99.68%)]. TSA ruled out the possibility of false-positive results. Subgroup analysis for the SAP demonstrated that the superficial plane approach was more effective in reducing opioid consumption than the deep approach. The odds of developing PONV were significantly lower in SAP compared to NBC. Compared with PVB and PECS, SAP block was not statistically different for 24-hour OME and time to first rescue analgaesia. Single-shot SAP reduced opioid consumption, prolonged analgaesia duration, lowered pain scores, and decreased the incidence of PONV compared to NBC. There was no statistically significant difference in the studied endpoints between SAP, PVB, and PECS blocks.

Measuring the Impact of Augmented Reality in Flipped Learning Mode on Critical Thinking, Learning Motivation, and Knowledge of Engineering Students.

Digital electronics is a fundamental subject for engineering students, and it enables the students to learn design-based approaches and solve complex engineering problems. Students learn about minimization techniques for reducing the hardware components and size of the circuit by solving complex Boolean equations. The Karnaugh map (K-map) is one such technique utilized in digital electronics to solve complex Boolean equations and design AND-OR-INVERT (AOI) logical diagrams. The K-map technique involves several steps to solve the Boolean expression, and students often find it difficult to follow the K-map process. In this study, an AR-based learning system was developed using Unity 3D and Vuforia SDK that aimed to teach the students about the step-wise operation of the K-map technique. An experimental study was conducted with 128 undergraduate engineering students to determine the impact of the AR learning system on the critical thinking skills, learning motivation, and knowledge gain of students. The students were divided into two groups: experimental group (N = 64) and control group (N = 64). The AR learning system was implemented in flipped learning mode and utilized to provide in-class activities during the learning. The experimental group students utilized the AR learning system for in-class activities whereas control group students performed in-class activities using the traditional approach. The experimental outcomes indicate that the use of AR technology has a significant positive impact on the critical thinking skills, learning motivation, and knowledge gain of students. The study also found that critical thinking skills and learning motivation have a significant positive correlation with the knowledge gain of students in the experimental group.

Fabrication of FRET based nano sensor from biomass-derived fluorescent carbon quantum dots and naphthalimide for ratiometric detection of nitric oxide: To examine nitrite levels in meat samples.

Nitric oxide (NO) is a ubiquitous, gaseous, free radical signaling molecule which plays a key role in physiological and pathological processes. Literature reports revealed that the conventional methods such as colorimetry, electron paramagnetic resonance (EPR), electrochemical etc. to detect NO are costly, time consuming and lack resolution, particularly in aqueous or biological system. Thus, in this context, herein we have developed covalently linked biomass derived carbon quantum dots (CQDs) and naphthalimide based nano sensor system for FRET based ratiometric detection of nitric oxide (NO) in pure aqueous media. The CQDs derived from orange peels were characterized using UV-visible absorption, fluorescence spectroscopy, PXRD, TEM, FT-IR and zeta potential studies. Further, the obtained CQDs were functionalized with amine functionality, and subsequently linked with naphthalimide derivative (5) using terephthaldehyde through covalent bond formation. The conjugation of naphthalimide (5) and functionalized CQDs was studied using DLS, zeta potential, FT-IR and time resolved fluorescence spectroscopy. The excitation of developed nano sensor system at λex 360 nm results in fluorescence emission at λem 530 nm which establishes the FRET pair between the CQDs and naphthalimide unit. However, in the presence of NO, the observed FRET pair abolishes due to the cleavage of NO susceptible imine bond. The developed sensor demonstrates high selectivity towards NO with limit of detection (LOD) and limit of quantification (LOQ) of 15 nM and 50 nM respectively. Further, the developed sensor system was also utilized for indirect detection of nitrite (NO2-) in food samples for food safety and monitoring.

Correlation of Nasal Mucosal Temperature and Nasal Patency-A Computational Fluid Dynamics Study.

OBJECTIVES: Recent evidence suggests that detection of nasal mucosal temperature, rather than direct airflow detection, is the primary determinant of subjective nasal patency. This study examines the role of nasal mucosal temperature in the perception of nasal patency using in vivo and computational fluid dynamics (CFD) measurements. METHODS: Healthy adult participants completed Nasal Obstruction Symptom Evaluation (NOSE) and Visual Analogue Scale (VAS) questionnaires. A temperature probe measured nasal mucosal temperature at the vestibule, inferior turbinate, middle turbinate, and nasopharynx bilaterally. Participants underwent a CT scan, used to create a 3D nasal anatomy model to perform CFD analysis of nasal mucosal and inspired air temperature and heat flux along with mucosal surface area where heat flux >50 W/m2 (SAHF50). RESULTS: Eleven participants with a median age of 27 (IQR 24; 48) were recruited. Probe-measured temperature values correlated strongly with CFD-derived values (r = 0.87, p < 0.05). Correlations were seen anteriorly in the vestibule and inferior turbinate regions between nasal mucosal temperature and unilateral VAS (r = 0.42-0.46; p < 0.05), between SAHF50 and unilateral VAS (r = -0.31 to -0.36; p < 0.05) and between nasal mucosal temperature and SAHF50 (r = -0.37 to -0.41; p < 0.05). Subjects with high patency (VAS ≤10) had increased heat flux anteriorly compared with lower patency subjects (VAS >10; p < 0.05). CONCLUSION: Lower nasal mucosal temperature and higher heat flux within the anterior nasal cavity correlates with a perception of improved unilateral nasal patency in healthy individuals. LEVEL OF EVIDENCE: 4 Laryngoscope, 133:1328-1335, 2023.

Modelling the effects of post-FESS middle turbinate synechiae on sinonasal physiology: A computational fluid dynamics study.

OBJECTIVE(S): Chronic rhinosinusitis (CRS) is common and often requires surgical intervention. Surgical failure may lead to persistent symptoms and recalcitrant disease, often secondary to synechiae between the middle turbinate (MT) and lateral nasal wall. Synechiae prevention techniques have been extensively investigated, however evidence for the effect of synechiae on sinonasal physiology is lacking. We aimed to model the effects of MT synechiae on a post-functional endoscopic sinus surgery (FESS) sinonasal cavity using computational fluid dynamics (CFD). METHODS: DICOM data from a CT-sinus of a healthy 25-year-old female was segmented to create a three-dimensional model. Virtual surgery was performed to simulate a "full-house" FESS procedure. Multiple models were created, each with a single unilateral virtual MT synechia of varying extent. CFD analysis was performed on each model and compared with a post-FESS control model without synechiae. Airflow velocity, humidity and mucosal surface and air temperature values were calculated. RESULTS: All synechiae models demonstrated aberrant downstream sinonasal airflow. There was reduced ventilation of the ipsilateral frontal, ethmoid and sphenoid sinuses, with a concentrated central "jet" in the middle meatus region. Effects were proportionate to the size of synechiae. The impact on bulk inspired airflow was negligible. CONCLUSION: Post-FESS synechiae between the MT and lateral nasal wall significantly disrupt local downstream sinus ventilation and nasal airflow. These findings may explain the persistent symptoms seen in post-FESS CRS patients with MT synechiae, reinforcing the importance of prevention and adhesiolysis. Larger cohort studies with multiple models of actual post-FESS patients with synechiae are required to validate these findings.