Low Potential CO2 Reduction by Inert Fe(II)-Macrobicyclic Complex: A New Concept of Cavity Assisted CO2 Activation.

The advantage of a pre-organized π-cavity of Fe(II) complex of a newly developed macrobicycle cryptand is explored for CO2 reduction by overcoming the problem of high overpotential associated with the inert nature of the cryptate. Thus, a bipyridine-centered tritopic macrobicycle having a molecular π-cavity capable of forming Fe(II) complex as well as potential for CO2 encapsulation is synthesized. The inert Fe(II)-cryptate shows much lower potential in cyclic voltammetry than the Fe(II)-tris-dimethylbipyridine (Fe-MBP) core. Interestingly, this cryptate shows electrochemical CO2 reduction at a considerably lower potential than the Fe-MBP inert core. Therefore, this study represents that a well-structured π-cavity may generate a new series of molecular catalysts for the CO2 reduction reaction (CO2 RR), even with the inert metal complexes.

Evaluation of the Efficacy and Safety of Intravenous Immunoglobulin (IVIG) in Moderate-to-Severe Hospitalized COVID-19 Patients: A Randomized, Open-Label Parallel-Group Study.

Purpose: Since February 2020, the world has been overwhelmed by the SARS-CoV-2 outbreak, and several patients suffered interstitial pneumonia and respiratory failure requiring mechanical ventilation, threatening the capability of healthcare systems to handle this amount of critical cases. Intravenous immunoglobulins (IVIG) possess potential immunomodulatory properties beneficial for COVID-19 patients, yet evidence supporting IVIG as adjunctive therapy remains sparse. This study evaluated the outcomes of adjunctive IVIG with the standard of care (SoC) in moderate-to-severe COVID-19 patients. Methods: This randomized study included 59 moderate-to-severe COVID-19 patients with known comorbidities. One arm (n = 33) received high-dose IVIG (400 mg/kg/day) within 48 hours for five days alongside SoC, while the other arm (n = 26) received SoC, comprising steroids, enoxaparin, and remdesivir. The primary endpoint was clinical improvement, as measured by the National Early Warning Score 2 (NEWS2) and discharged/death proportions. Secondary outcomes included IVIG safety, hospitalization duration, changes in oxygen saturation, inflammatory markers, IgG titer, CTSS (CT severity score), and radiological findings. Results: There was an improvement in the NEWS2 at the end of treatment in the IVIG arm (5.67 vs. 5.96). A significant absolute effect improvement (Day 1 vs. Day 9) was seen in serum LDH, D-dimer, hs-CRP, IL-6, CTSS, procalcitonin, respiratory rate, and chest radiographic findings. SARS-CoV-2 IgG titer increased significantly in the IVIG arm. There was a statistically significant reduction in mortality in the IVIG group (5 vs. 10). Conclusion: IVIG was a safe and effective adjunctive therapy to SoC treatment in moderate-to-severe COVID-19 patients needing ventilatory support. Furthermore, studies are required to validate our findings. This trial is registered with CTRI/2021/05/033622.

Micromolar Affinity and Higher: Synthetic Host-Guest Complexes with High Stabilities.

The design of high-affinity synthetic host-guest complexes is of paramount importance because they are key elements in constructing unprecedented supramolecular assemblies, functional materials, molecular probes, artificial signal transduction events, and interfaces with the biological world. The present review article collects recent achievements in the design of 1 : 1 host-guest complexes with outstanding stabilities, i.e., exceeding 106  M-1 . The relationships between the measured thermodynamic constants and the structural parameters of the interacting species are analyzed. The design features of high-affinity hosts are discussed in light of their binding properties. Different solvents and different types of noncovalent interactions are considered for the stabilization of the complexes. Finally, some hints are provided for the design of future synthetic receptors displaying high affinity and selectivity.

One-Pot Dual C-C Coupling Reaction via Site Selective Cascade Formation by PdII -Cryptate of an Amino-Ether Heteroditopic Macrobicycle.

Selectivity of aryl iodo over ethynyl iodo toward the Suzuki cross coupling reaction is explored by utilizing a palladium complex of amino-ether heteroditopic macrobicycle. Subsequently, unreacted ethynyl iodide undergoes homocoupling reaction in the same catalytic atmosphere, thereby representing a cascade dual C-C coupling reaction. Furthermore, this approach is extended for novel one-pot synthesis of unsymmetrical 1,3-diynes.

Heteroditopic Macrobicyclic Molecular Vessels for Single Step Aerial Oxidative Transformation of Primary Alcohol Appended Cross Azobenzenes.

A series of oxy-ether tris-amino heteroditopic macrobicycles (L1-L4) with various cavity dimensions have been synthesized and explored for their Cu(II) catalyzed selective single step aerial oxidative cross-coupling of primary alcohol based anilines with several aromatic amines toward the formation of primary alcohol appended cross azobenzenes (POCABs). The beauty of this transformation is that the easily oxidizable benzyl/primary alcohol group remains unhampered during the course of this oxidation due to the protective oxy-ether pocket of this series of macrobicyclic vessels. Various dimensionalities of the molecular vessels have shown specific size complementary selection for substrates toward efficient syntheses of regioselective POCAB products. To establish the requirement of the three-dimensional cavity based additives, a particular catalytic reaction has been examined in the presence of macrobicycles (L2 and L3) versus macrocycles (MC1 and MC2) and tripodal acyclic (AC1 and AC2) analogous components, respectively. Subsequently, L1-L4 have been extensively utilized toward the syntheses of as many as 44 POCABs and are characterized by different spectroscopic techniques and single crystal X-ray diffraction studies.

A heteroditopic macrocycle as organocatalytic nanoreactor for pyrroloacridinone synthesis in water.

A heteroditopic macrocycle is reported as an efficient organocatalytic nanoreactor for the synthesis of diversely functionalized pyrroloacridinones in aqueous medium. A library of compounds was synthesized in a one-step pathway utilizing 10 mol % of the nanoreactor following a sustainable methodology in water with high yields.

Polyamide-Polyamine Cryptand as Dicarboxylate Receptor: Dianion Binding Studies in the Solid State, in Solution, and in the Gas Phase.

Polyamide-polyamine hybrid macrobicycle L is explored with respect to its ability to bind α,ω-dicarboxylate anions. Potentiometric studies of protonated L with the series of dianions from succinate (suc2-) through glutarate (glu2-), α-ketoglutarate (kglu2-), adipate (adi2-), pimelate (pim2-), suberate (sub2-), to azelate (aze2-) have shown adipate preference with association constant value of K = 4900 M-1 in a H2O/DMSO (50:50 v/v) binary solvent mixture. The binding constant increases from glu2- to adi2- and then continuously decreases with the length of the anion chain. Further, potentiometric studies suggest that hydrogen bonding between the guest anions and the amide/ammonium protons of the receptor also contributes to the stability of the associations along with electrostatic interactions. Negative-mode electrospray ionization of aqueous solutions of host-guest complexes shows clear evidence for the selective formation of 1:1 complexes. Single-crystal X-ray structures of complexes of the receptor with glutaric acid, α-ketoglutaric acid, adipic acid, pimelic acid, suberic acid, and azelaic acid assist to understand the observed binding preferences. The solid-state structures reveal a size/shape complementarity between the host and the dicarboxylate anions, which is nicely reflected in the solution state binding studies.

Mercury air, urine monitoring and health effects on occupationally exposed dental healthcare workers in Delhi, India.

BACKGROUND: Mercury (Hg) is a toxic heavy metal with multiple uses in various medical devices. Hg is used in dentistry as a restorative material. Such use creates significant exposure to dental practitioners. Hence, it is important to assess the risk created by Hg use in healthcare. OBJECTIVE: To quantify airborne Hg vapour exposure and Hg levels in dental healthcare workers, and determine the association of various symptoms and diseases to Hg exposure. METHODS: Air monitoring of Hg vapours were conducted in dental clinics and amalgam rooms. Urine samples were collected from occupationally exposed dental healthcare workers and urine Hg levels were measured. A cross-sectional health survey was conducted in 23 healthcare units of Delhi to determine an association between Hg exposure and various health effects. RESULTS: Hg vapour concentration ranged from 0.96µg/m3 to 15µg/m3, the highest concentration was recorded in the amalgam room (15µg/m3). Urine Hg levels in healthcare workers (0.51±0.17µg/L) were higher than the control (0.29±0.05µg/L). A cross-sectional health survey revealed a significant prevalence of confusion, forgetfulness, muscle spasm, and tremors by the respondents. CONCLUSION: Hg concentration in dental clinics may hover above the prescribed safe levels posing a definitive health risk to healthcare workers. Urinary Hg measurements did not reveal an excess of body burden except in one case. Since Hg bio accumulates, it is probable as these workers grow older, they may end up with a higher body burden of Hg that may lead to a variety of adverse health outcomes.

Schrödinger spectrum based continuous cuff-less blood pressure estimation using clinically relevant features from PPG signal and its second derivative.

The presented study estimates cuff-less blood pressure (BP) from photoplethysmography (PPG) signals using multiple machine-learning (ML) models and the semi-classical signal analysis (SCSA) technique. The study proposes a novel signal reconstruction algorithm, which optimizes the semi-classical constant of the SCSA approach and eliminates the trade-off between complexity and accuracy during signal reconstruction. It predicts BP values using regression algorithms by processing reconstructed PPG signals' spectral features, extracting clinically relevant PPG and its second derivative's (SDPPG) morphological features. The developed method was assessed using a virtual in-silico dataset with more than 4000 subjects and the Multi-Parameter Intelligent Monitoring in Intensive Care Units (MIMIC-II) dataset. Results showed that the method attained a mean absolute error (MAE) of 5.37 and 2.96 mmHg for systolic and diastolic BP, respectively, using the CatBoost algorithm. This approach met the Association for the Advancement of Medical Instrumentation's standard and achieved Grade A for all BP categories in the British Hypertension Society protocol. The proposed framework performs well even when applied to a combined clinically relevant database originating from MIMIC-III and the Queensland dataset. The proposed method's performance is further evaluated in a non-clinical setting with noisy and deformed PPG signals to validate the efficacy of the SCSA method. The noise stress tests further showed that the algorithm maintained its key feature detection, signal reconstruction capability, and estimation accuracy up to a 10 dB SNR ratio. The proposed cuff-less BP estimation technique has the potential to perform well in mobile healthcare devices due to its straightforward implementation approach.

Boosting Algorithms based Cuff-less Blood Pressure Estimation from Clinically Relevant ECG and PPG Morphological Features.

Blood Pressure (BP) is often coined as a critical physiological marker for cardiovascular health. Multiple studies have explored either Photoplethysmogram (PPG) or ECG-PPG derived features for continuous BP estimation using machine learning (ML); deep learning (DL) techniques. Majority of those derived features often lack a stringent biological explanation and are not significantly correlated with BP. In this paper, we identified several clinically relevant (bio-inspired) ECG and PPG features; and exploited them to estimate Systolic (SBP), and Diastolic Blood Pressure (DBP) values using CatBoost, and AdaBoost algorithms. The estimation performance was then compared against popular ML algorithms. SBP and DBP achieved a Pearson's correlation coefficient of 0.90 and 0.83 between estimated and target BP values. The estimated mean absolute error (MAE) values are 3.81 and 2.22 mmHg with a Standard Deviation of 6.24 and 3.51 mmHg, respectively, for SBP and DBP using CatBoost. The results surpassed the Advancement of Medical Instrumentation (AAMI) standards. For the British Hypertension Society (BHS) protocol, the results achieved for all the BP categories resided in Grade A. Further investigation reveals that bio-inspired features along with tuned ML models can produce comparable results w.r.t parameter-intensive DL networks. ln(HR × mNPV), HR, BMI index, ageing index, and PPG-K point were identified as the top five key features for estimating BP. The group-based analysis further concludes that a trade-off lies between the number of features and MAE. Increasing the no. of features beyond a certain threshold saturates the reduction in MAE.

Pneumothorax in lung metastasis of advanced soft tissue sarcoma patients treated with oral pazopanib.

AIM: Data on occurrence of pneumothorax after the use of oral pazopanib in advanced soft tissue sarcoma (STS) with lung metastases are scarce in literature. We aimed to evaluate those in our patients. METHODS: This was a single center retrospective study of incidence of pneumothorax in patients with lung metastases in advanced STS treated with oral pazopanib between July, 2016 and December, 2020. Patients were treated with pazopanib usually from 2nd line onwards with a dose ranging from 400 mg to 800 mg once daily. RESULTS: Total of 34 patients with lung metastasis in a setting of advanced STS were treated with oral pazopanib during the study period. The setting of pazopanib use was 2nd line in four and 1st line in one of them. The starting dose was 600 mg once daily in three patients, 400 mg OD in one patient, and 800 mg OD in one patient. Five patients developed pneumothorax with duration on pazopanib of 6, 7, 24, 6, and 2.5 months, respectively. Three patients had symptoms and required chest tube drainage. None of them were smokers or had any other underlying lung disease. The disease response of those patients was stable disease in four and partial response in one during treatment with pazopanib. One patient had a rechallenge with further pazopanib course without any recurrence of pneumothorax. CONCLUSIONS: Pneumothorax is a rare pulmonary complication after pazopanib use in patients with lung metastasis. Clinicians should be aware of this rare complication as literature is scarce. Rechallenge with pazopanib is feasible after pneumothorax.

Systemic inflammatory response syndrome criteria (SIRS) and sepsis 3 criteria for assessing outcomes in sepsis: A prospective observational study.

Background: Sepsis is a major cause of death in hospitalised patients worldwide. Most studies for assessing outcomes in sepsis are from the western literature. Sparse data from Indian settings are available comparing the systemic inflammatory response syndrome (SIRS), Sequential Organ Failure Assessment (SOFA) and quick SOFA (qSOFA) (sepsis 3 criteria) for assessing outcomes in sepsis. In this study, we aimed to compare the SIRS criteria and sepsis 3 criteria to assess disease outcome at day 28 (recovery/mortality) in a North Indian tertiary care teaching hospital. Methods: A prospective observational study was performed in the Department of Medicine from 2019 to early 2020. Patients admitted to the medical emergency with clinical suspicion of sepsis were included. Systemic inflammatory response syndrome, qSOFA and SOFA scores were calculated at the time of presentation to the hospital. Patients were followed through the course of their hospital stay. Results: Out of 149 patients, 139 were included in the analysis. Patients who died had significantly higher mean SOFA, qSOFA scores and mean change in SOFA score than patients who survived (P value <0.01). There was no statistical difference between recovery and deaths at similar SIRS scores. A 40.30% fatality rate was recorded. Systemic inflammatory response syndrome had low Area Under Curve (AUC) (0.47) with low sensitivity (76.8) and specificity (21.7). SOFA had the maximum AUC (0.68) compared to qSOFA (0.63) and SIRS (0.47). SOFA also had the maximum sensitivity (98.1) while the qSOFA score had the maximum specificity (84.3). Conclusion: SOFA and qSOFA scores had superior predictive ability as compared to the SIRS score in assessing mortality in sepsis patients.

Split Frequency and Load-Shift Keying Based Bi-directional Data Transfer Technique in Wireless Implantable Medical Devices.

The 'power frequency splitting' phenomenon is widely observed over critical coupling conditions in the wireless power transfer system. Frequency splitting occurs in the voltage gain and power delivered to the load (PDL) curve but not in the end-to-end power transfer efficiency curve. This brief has considered the mutual inductance model to analyze the relationship between characteristic frequencies and circuit parameters in the wireless series-parallel system. Here authors have proposed a novel co-simulation platform using ANSYS MAXWELL and SIMPLORER for dynamic modeling of frequency-dependent resistance in a flexible polymer coil setup. The wireless power and bidirectional data transmission protocol were developed over a single link using Frequency shift keying (FSK) based forward data transfer (downlink) and Load shift keying (LSK) based backward data transfer (uplink) technique. The split frequency-based FSK modulation scheme helps in continuous wireless power transmission without disrupting the carrier amplitude for large power delivery, high data rate, and high-power transfer efficiency. The trade-off between link gain, bandwidth, and efficiency limits the application of the 'frequency splitting based data transfer technique' after a certain distance. A detection (tertiary) coil co-planar with the transmitter coil receives and decodes backscattered data from the receiver side using LSK. The three-coil architecture does not affect the split point locations of the two-coil system and slightly reduces link gain.

Signal Quality Assessment of Photoplethysmogram Signals using Quantum Pattern Recognition Technique and lightweight CNN Module.

Photoplethysmography (PPG) signal comprises physiological information related to cardiorespiratory health. High-quality PPG signals are necessary to extract cardiores-piratory information accurately. Motion artifacts can easily corrupt PPG signals due to human locomotion, leading to noise enriched, poor quality signals. Several rule-based and Machine-Learning (ML) - based approaches for PPG signal quality estimation are available, but those algorithms' efficacy is questionable. So, the authors propose a lightweight CNN architecture for signal quality assessment by employing a novel Quantum Pattern Recognition (QPR) technique. The proposed algorithm is validated on manually annotated data obtained from the University of Queensland database. A total of 28366, 5s signal segments are preprocessed and transformed into image files of 20 x 500 pixels for input to the 2D CNN architecture. The developed model classifies the PPG signal as 'good' and 'bad' with an accuracy of 98.3% with 99.3% sensitivity, 94.5% specificity and 98.9% F1-score. The experimental analysis concludes that slim module based architecture and novel Spatio-temporal pattern recognition technique improve the system's performance. The proposed approach is suitable for a resource-constrained wearable implementation.

Sewer gas poisoning causing transient and focal ST-segment elevation in the ECG: Case report.

In India, a large number of sanitary care workers are involved in manual scavenging. This exposes them to sewer gas mainly consisting of hydrogen sulphide. Sewer gas toxicity primarily causes neurological injury, followed by cardiac and respiratory involvement. A few cases of diffuse ST-segment elevation in the electrocardiogram (ECG) following hydrogen sulphide poisoning are known in the literature. Here, we report a case of acute sewer gas poisoning in a 45-year-old man with transient and focal ST-segment elevation in the anteroseptal leads of the ECG mimicking acute anterior wall myocardial infarction.

Heavy Metal Accumulation in Fruits and Vegetables and Human Health Risk Assessment: Findings From Maharashtra, India.

background: Vegetables are consumed enormously by humans all over the world. Consumption of contaminated fruits and vegetables is the most likely route of heavy metal exposure. Hence, it is important to quantify heavy metal concentration in frequently consumed fruits and vegetables. materials and methods: The main aim of our study is to investigate heavy metal (Pb, Cd, As, and Hg) contamination in 24 different kinds of vegetables and fruits grown in the industrialized city of Solapur, Maharashtra, India. Potential health risks due to the consumption of fruits and vegetables were assessed. Heavy metal concentration and quality of native soil were also determined. Vegetable and fruit samples were analyzed using Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) Agilent 7500. results: The mean concentrations of selected heavy metals in fruits and vegetables analyzed were: Lead (0.17 ± 0.38 mg/kg) > Mercury (0.06 ± 0.09 mg/kg) > Cadmium (0.02 ± 0.007 mg/kg) > Arsenic (0.002 ± 0.003 mg/kg). Among them, garlic showed the highest heavy metal accumulation followed by potato. conclusion: Overall, vegetables showed higher metal accumulations than fruits. Some vegetables showed alarming levels of human health risk indices such as the Metal Pollution Index (MPI), Health Risk Index (HRI) and Hazard Index (HI), suggesting that reducing the intake amount of these vegetables may lower the adverse health effects.

Human Health Risk Assessment due to Heavy Metals in Ground and Surface Water and Association of Diseases With Drinking Water Sources: A Study From Maharashtra, India.

Background: Contamination of freshwater sources can be caused by both anthropogenic and natural processes. According to Central Pollution Control Board, Maharashtra along with 2 other states, contribute 80% of hazardous waste generated in India, including heavy metal pollution. Hence, it is important to quantify heavy metal concentrations in drinking water sources in such areas. Materials and methods: Water samples were analyzed for toxic elements (F, As, Cd, Hg, Pb, Ni, Cu, Zn, Mn, and Cr) using Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) Agilent 7500. Health risks due to ingestion and dermal contact was assessed. A total of 557 people were randomly selected, with consumers from all 4 types of water sources that is surface water, hand pump, wells, and municipal water. Spot urine samples were collected from 47 people after considering inclusion and exclusion criteria. Urine was collected for estimating mercury and arsenic levels in the study participants. Results: Arsenic contributes the most health risk from ingestion from water. Among surface water users, 14 people (32%) reported frequent loose stool (P-value < .05) (OR 2.5), and 11 people (23%) reported frequent abdominal pain (OR 1.9). Hand pump and well water users reported frequent abdominal pain (27%) (OR 1.4) and gastric discomfort (31%) (P-value < .05) (OR 3) respectively. The mean value of urinary Hg and As were 4.91 ± 0.280 and 42.04 ± 2.635 µg/L respectively. Conclusion: Frequent loose stool, gastric discomfort, and frequent abdominal pain were associated with the various sources of drinking water. Urine Hg levels were found higher than the NHANES (USA) Survey. It is recommended that frequent monitoring of drinking water should be enforced around the industrial hub, so that appropriate actions can be taken if present in excess.

Adaptable Class-D Power Amplifier based Power Modulation and Data Transfer Technique for Biomedical Systems.

Class-D half and full-bridge power amplifiers (PA) finds their usefulness in wireless power transfer (WPT) blocks for a biomedical implant. This brief presents a 13.56-MHz wireless power transfer system using an adaptive PA structure and digital control scheme for providing sufficient power during downlink data transfer. This scheme prevents efficiency degradation due to amplitude modulation. Simultaneously changing PA structure and operating frequency gives a higher degree of freedom for power modulation. The transmitter and receiver sides were designed in the 0.18-µm CMOS process using 1.8 V and 5 V devices.

Introduction of Boosting Algorithms in Continuous Non-Invasive Cuff-less Blood Pressure Estimation using Pulse Arrival Time.

Blood Pressure (BP) is a critical biomarker for cardiorespiratory health. Conventional non-invasive BP measurement devices are mostly built on the principle of auscultation, oscillometry, or tonometry. The strong correlation between the Pulse Arrival Time (PAT) and BP has enabled unconstrained cuff-less BP monitoring. In this paper, we exploited that relationship for estimating Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), and Mean Arterial pressure (MAP) values. The proposed model involves extraction of PAT values by denoising the signals using advanced filtering techniques and finally employing machine learning algorithms to estimate cuff-less BP. The results are validated against Advancement of Medical Instrumentation (AAMI) standards and British Hypertension Society (BHS) protocols. The proposed method meets the AAMI standards in the context of estimating DBP and MAP values. The model's accuracy achieved Grade A for both MAP and DBP values using the CatBoost algorithm, whereas it achieved grade A for MAP and Grade B for DBP using the XGBoost algorithm based on the BHS standards.

Development on Linearizing Front End and Amplification Structure for Commercial GMR Sensor-based Cardiorespiratory Monitoring system.

Magnetoplethysmogram (MPG) is typically acquired by placing a giant magnetoresistance sensor (GMR)-magnet system in a blood vessel's (e.g., radial artery) vicinity. This brief analyzed multiple linearizing front ends for the GMR-magnet system. GMR based analog front end's (AFE) gain requirement is derived through COMSOL and MATLAB-based simulation considering the raw signal data. After that, we designed a fully differential difference amplifier (FDDA) in 0.18 µm, 1.8 V process using the SPICE environment for amplification of MPG signals. An automatic calibration method is used for compensating the GMR sensor's offset and lowering it to a few µV level during constant current excitation. This proposed GMR-magnet system is a stepping stone towards noninvasive arterial pulse waveform (APW) detection using the MPG principle, with or without direct skin contact. The DDA achieves open and closed-loop gain of 102 dB and 32 dB, phase margin of 62◦, an IRN of 1.8µV, and a unity-gain frequency of 32kHz, resulting in a closed-loop bandwidth of 800 Hz while dissipating 1.2 µA from a 1.8-V supply.