In-situ detoxification of schedule-I chemical warfare agents utilizing Zr(OH)4@W-ACF functional material for the development of next generation NBC protective gears.

Chemical warfare agents (CWAs) have become a pivotal concern for the global community and spurred a wide spectrum of research for the development of new generation protective materials. Herein, a highly effective self-detoxifying filter consisting of in-situ immobilized Zirconium hydroxide [Zr(OH)4] over woven activated carbon fabric [Zr(OH)4@W-ACF] is presented for the removal of CWAs. It was prepared to harness the synergistic effect of high surface area of W-ACF, leads to high dispersion of CWAs and high phosphilicity and reactivity of [Zr(OH)4]. The synthesized materials were characterized by ATR-FTIR, EDX, SEM, TEM, XPS, TGA, and BET surface area analyzer. The kinetics of  in-situ degradation of CWAs over Zr(OH)4@W-ACF were studied and found to be following the first-order reaction kinetics. The rate constant was found to be 0.244 min-1 and 2.31 × 10-2 min-1 for sarin and soman, respectively over Zr(OH)4@W-ACF. The potential practical applicability of this work was established by fabricating Zr(OH)4@W-ACF as reactive adsorbent layer for protective suit, and found to be meeting the specified criteria in terms of air permeability, tearing strength and nerve agent permeation as per TOP-08-2-501A:2013 and IS-17380:2020. The degradation products of CWAs were analyzed with NMR and GC-MS. The combined properties of dual functional textile with reactive material are expected to open up new exciting avenues in the field of CWAs protective clothing and thus find diverse application in defence and environmental sector.

MEGnet: Automatic ICA-based artifact removal for MEG using spatiotemporal convolutional neural networks.

Magnetoencephalography (MEG) is a functional neuroimaging tool that records the magnetic fields induced by neuronal activity; however, signal from non-neuronal sources can corrupt the data. Eye-blinks, saccades, and cardiac activity are three of the most common sources of non-neuronal artifacts. They can be measured by affixing eye proximal electrodes, as in electrooculography (EOG), and chest electrodes, as in electrocardiography (ECG), however this complicates imaging setup, decreases patient comfort, and can induce further artifacts from movement. This work proposes an EOG- and ECG-free approach to identify eye-blinks, saccades, and cardiac activity signals for automated artifact suppression. The contribution of this work is three-fold. First, using a data driven, multivariate decomposition approach based on Independent Component Analysis (ICA), a highly accurate artifact classifier is constructed as an amalgam of deep 1-D and 2-D Convolutional Neural Networks (CNNs) to automate the identification and removal of ubiquitous whole brain artifacts including eye-blink, saccade, and cardiac artifacts. The specific architecture of this network is optimized through an unbiased, computer-based hyperparameter random search. Second, visualization methods are applied to the learned abstraction to reveal what features the model uses and to bolster user confidence in the model's training and potential for generalization. Finally, the model is trained and tested on both resting-state and task MEG data from 217 subjects, and achieves a new state-of-the-art in artifact detection accuracy of 98.95% including 96.74% sensitivity and 99.34% specificity on the held out test-set. This work automates MEG processing for both clinical and research use, adapts to the acquired acquisition time, and can obviate the need for EOG or ECG electrodes for artifact detection.

Sampling and analyses of surfaces contaminated with chemical warfare agents by using a newly developed triple layered composite wipe.

A three-layered composite wipe was fabricated by laminating individual layers of non-woven polypropylene, activated carbon fabric (ACF) and aramid fabric for the sampling and investigation of chemical warfare agents (CWA)-contaminated urban porous and non-porous surfaces. The material of main ACF layer was characterized to ascertain its suitability to act as an efficient adsorbent for the surface wipe sampling. The performance of ACF-based composite wipe was determined by evaluating its extraction efficiency, wiping efficacy and adsorption capacity for the sampling of blister and nerve agent class of CWA-contaminated surfaces using gas chromatography-mass spectrometry (GC-MS). Parameters like amount of wipe required, solvent selection, amount of solvent, time of extraction etc. were optimized to achieve the maximum recovery of contaminating analytes required for the forensic investigations. Overall recoveries of contaminating analytes after sampling and extraction were found to be in the range of 45-85% for all types of surfaces. No breakthrough in wiping process was noticed up to contamination density (CD) 1.6 mg/cm2 for non-porous surface and 3.2 mg/cm2 for porous surfaces. ACF-based wipe was found capable to significantly reduce the vapour hazards from liquid sulphur mustard (HD) and sarin (GB). Contamination from surfaces could be preserved within the wipe up to 15 days for the extended forensic investigation purposes. Limit of detections (LOD) of contaminants was determined in the range of 0.8-6.8 ng/cm2 while limit of quantitation (LOQ) was achieved up to the range of 2.4-14.4 ng/cm2 for wipe sampling of different surfaces. Graphical abstract.

A review on test methods for insecticidal fabrics and the need for standardisation.

Insecticidal fabrics are effective personal protective measures against disease vectors and unlike bed nets, these fabrics can provide protection from day-biting mosquitoes and in outdoor environments. The rapid geographical expansion of day-biting mosquitoes and their role in disease transmission necessitate technological interventions, which can be effectively used during the daytime. There is a renewed interest in insecticidal fabrics mainly due to the recent outbreaks and geographical spread of dengue and chikungunya and with the emerging threat of Zika virus infection. Insecticidal fabrics are useful for protection from night-biting mosquitoes and also in situations were sleeping under a bed net is not possible. They are also effective against other biting arthropods like ticks, mites, tsetse flies, sand flies and body lice. Although long-lasting insecticidal fabrics factory-treated with permethrin are now commercially available for military and civilian use, there are no international guidelines for testing their efficacy. The different methods employed so far for testing bioefficacy, washing and quantification of permethrin are compiled in this review. The future prospects and challenges ahead for long-lasting insecticidal fabrics are discussed in the context of the increased threat from day-biting mosquitoes and the diseases transmitted by them. The review focuses on the need for standardisation of the test methods for ensuring adequate bioefficacy and safety to the user. The differences between long-lasting insecticidal nets and long-lasting insecticidal fabrics are elaborated, and the need for a separate registration and licencing procedure for long-lasting insecticidal fabrics is highlighted. A test procedure for insecticidal fabrics is described, which could be used until internationally accepted guidelines are available.

Superior Ophthalmic Vein Access for Embolization of an Indirect Carotid Cavernous Fistula.

Carotid cavernous fistulae (CCF) are defined as abnormal connections between the carotid circulation and cavernous sinus. CCFs can be categorized as being direct or indirect. Direct CCFs are usually associated with trauma, whereas indirect CCFs are associated with revascularization following cavernous sinus thrombosis. We present a case of a 53-year-old male who presented with tinnitus, proptosis, conjunctivitis, and blurry vision. The patient had a recent endovascular transvenous embolization that was only partially successful, with a residual carotid cavernous fistula draining to the left superior ophthalmic vein and multiple cortical veins. A physical examination of the patient showed elevated intraocular pressures bilaterally. The patient had a high-flow indirect carotid cavernous fistula with bilateral superior ophthalmic vein (SOV) and retrograde cortical vein drainage. The SOV was punctured with a micropuncture needle and was used to successfully gain access to the cavernous sinus. Multiple coils were placed in the posterior aspect of the sinus until there was complete occlusion of venous flow. Coils were packed up to the posterior aspect of the orbit near the junction of the cavernous sinus with the SOV, and the embolization was successful. Indirect CCFs have gradual onset and are usually low-flow. Low-flow CCFs might improve with medical management.Some CCFs may cause ocular manifestations and can be symptomatically managed with prism therapy or ocular patching for diplopia, lubrication for keratopathy, or topical agents for elevated intraocular pressures. However, patients presenting with persistent ocular morbidity may require surgical or endovascular intervention.

Mechanical Thrombectomy for Acute Ischemic Stroke After Cardiac Surgery.

Ischemic stroke is a rare yet devastating complication that may occur following cardiothoracic surgery. Fibrinolytic treatment is contraindicated due to elevated risk for hemorrhage. Mechanical thrombectomy entails a catheterized approach wherein the thrombus is physically removed from the vessel without the use of fibrinolytics, minimizing the possibility of intracranial hemorrhage. Here, we present two original cases of mechanical thrombectomy as treatment for patients experiencing emergent large vessel occlusion following cardiothoracic surgery. A literature review was conducted to determine current treatment guidelines, risk factors, and complications resulting from recanalization due to mechanical thrombectomy versus fibrinolytic therapy. One patient was admitted due to chronic, American College of Cardiology/American Heart Association stage D, New York Heart Association functional class IV heart failure and required complete, artificial hemodynamic support for two weeks and on the 19th day experienced neurologic decline secondary to a supraclinoid left internal carotid artery (ICA) occlusion. Mechanical thrombectomy resulted in distal reperfusion and neurologic improvement. The second patient presented with coronary artery disease and underwent triple coronary artery bypass grafting and endovein harvesting. On post-operative day 2, the patient experienced a left ICA occlusion extending to the cavernous ICA resulting in speech impairment and right-sided weakness. The patient was heparinized and underwent mechanical thrombectomy, resulting in immediate speech and muscle strength recovery. Medical advances allow mechanical thrombectomy to be performed in a timely and effective manner at specialized treatment centers. It offers endovascular treatment modalities to a unique patient population with postoperative stroke. In such patients, thrombectomy can safely provide reperfusion while reducing the risk of complications associated with conventional thrombolytics.

Quantifying the Impact of Type 2 Diabetes on Brain Perfusion Using Deep Neural Networks.

The effect of Type 2 Diabetes (T2D) on brain health is poorly understood. This study aims to quantify the association between T2D and perfusion in the brain. T2D is a very common metabolic disorder that can cause long term damage to the renal and cardiovascular systems. Previous research has discovered the shape, volume and white matter microstructures in the brain to be significantly impacted by T2D. We propose a fully-connected deep neural network to classify the regional Cerebral Blood Flow into low or high levels, given 16 clinical measures as predictors. The clinical measures include diabetes, renal, cardiovascular and demographics measures. Our model enables us to discover any nonlinear association which might exist between the input features and target. Moreover, our end-to-end architecture automatically learns the most relevant features and combines them without the need for applying a feature selection method. We achieved promising classification performance. Furthermore, in comparison with six (6) classical machine learning algorithms and six (6) alternative deep neural networks similarly tuned for the task, our proposed model outperformed all of them.

Automatic 1D Convolutional Neural Network-based Detection of Artifacts in MEG acquired without Electrooculography or Electrocardiography.

Magnetoencephalography (MEG) is a functional neuroimaging tool that records the magnetic fields induced by electrical neuronal activity; however, signal from non-neuronal sources can corrupt the data. Eye-Blinks (EB) and Cardiac Activity (CA) are two of the most common types of non-neuronal artifacts. They can be measured by affixing eye proximal electrodes, as in electrooculography (EOG) and chest electrodes, as in electrocardiography (EKG), however this complicates imaging setup, decreases patient comfort, and often induces further artifacts from facial twitching and postural muscle movement. We propose an EOG- and EKG-free approach to identify eye-blink, cardiac, or neuronal signals for automated artifact suppression. Our contributions are two-fold. First, we combine a data driven, multivariate decomposition approach based on Independent Component Analysis (ICA) and a highly accurate classifier constructed as a deep 1-D Convolutional Neural Network. Second, we visualize the features learned to reveal what features the model uses and to bolster user confidence in our model's training and potential for generalization. We train and test three variants of our method on resting state MEG data from 49 subjects. Our cardiac model achieves a 96% sensitivity and 99% specificity on the set-aside test-set. Our eye-blink model achieves a sensitivity of 85% and specificity of 97%. This work facilitates automated MEG processing for both, clinical and research use, and can obviate the need for EOG or EKG electrodes.

Using Convolutional Neural Networks to Automatically Detect Eye-Blink Artifacts in Magnetoencephalography Without Resorting to Electrooculography.

Magnetoencephelography (MEG) is a functional neuroimaging tool that records the magnetic fields induced by neuronal activity; however, signal from muscle activity often corrupts the data. Eye-blinks are one of the most common types of muscle artifact. They can be recorded by affixing eye proximal electrodes, as in electrooculography (EOG), however this complicates patient preparation and decreases comfort. Moreover, it can induce further muscular artifacts from facial twitching. We propose an EOG free, data driven approach. We begin with Independent Component Analysis (ICA), a well-known preprocessing approach that factors observed signal into statistically independent components. When applied to MEG, ICA can help separate neuronal components from non-neuronal ones, however, the components are randomly ordered. Thus, we develop a method to assign one of two labels, non-eye-blink or eye-blink, to each component. Our contributions are two-fold. First, we develop a 10-layer Convolutional Neural Network (CNN), which directly labels eye-blink artifacts. Second, we visualize the learned spatial features using attention mapping, to reveal what it has learned and bolster confidence in the method's ability to generalize to unseen data. We acquired 8-min, eyes open, resting state MEG from 44 subjects. We trained our method on the spatial maps from ICA of 14 subjects selected randomly with expertly labeled ground truth. We then tested on the remaining 30 subjects. Our approach achieves a test classification accuracy of 99.67%, sensitivity: 97.62%, specificity: 99.77%, and ROC AUC: 98.69%. We also show the learned spatial features correspond to those human experts typically use which corroborates our model's validity. This work (1) facilitates creation of fully automated processing pipelines in MEG that need to remove motion artifacts related to eye blinks, and (2) potentially obviates the use of additional EOG electrodes for the recording of eye-blinks in MEG studies.

Extraction and derivatization of chemical weapons convention relevant aminoalcohols on magnetic cation-exchange resins.

Analysis and identification of nitrogen containing aminoalcohols is an integral part of the verification analysis of chemical weapons convention (CWC). This study was aimed to develop extraction and derivatization of aminoalcohols of CWC relevance by using magnetic dispersive solid-phase extraction (MDSPE) in combination with on-resin derivatization (ORD). For this purpose, sulfonated magnetic cation-exchange resins (SMRs) were prepared using magnetite nanoparticles as core, styrene and divinylbenzene as polymer coat and sulfonic acid as acidic cation exchanger. SMRs were successfully employed as extractant for targeted basic analytes. Adsorbed analytes were derivatized with hexamethyldisilazane (HMDS) on the surface of extractant. Derivatized (silylated) compounds were analyzed by GC-MS in SIM and full scan mode. The linearity of the method ranged from 5 to 200ngmL(-1). The LOD and LOQ ranged from 2 to 6ngmL(-1) and 5 to 19ngmL(-1) respectively. The relative standard deviation for intra-day repeatability and inter-day intermediate precision ranged from 5.1% to 6.6% and 0.2% to 7.6% respectively. Recoveries of analytes from spiked water samples from different sources varied from 28.4% to 89.3%.

Liquid-liquid-solid microextraction and detection of nerve agent simulants by on-membrane Fourier transform infrared spectroscopy.

A coupling of novel liquid-liquid-solid microextraction (LLSME) technique based on porous hydrophobic membrane and Fourier-transform infrared spectroscopy has been presented for the detection, identification and quantification of markers and simulants of nerve agents. Two isomers O,O'-dihexyl methylphosphonate (DHMP) and O,O'-dipentyl isopropylphosphonate (DPIPP) were chosen as model analytes for the study. In the present technique, organic phase was immobilised within the pores of membrane after fixing it in an assembly, which was then immersed into aqueous sample of target analytes for extraction. The analytes were directly determined on the surface of membrane by FTIR spectroscopy without elution. On comparison with solid phase microextraction (SPME), LLSME was found to be much more efficient. The method was optimised and quantitative analyses were performed using calibration curves obtained via Beer's law and employing processing of spectra obtained, via a multivariate calibration technique partial least square (PLS). Relative standard deviations (RSDs) for intraday repeatability and interday reproducibility were found to be in the range of 0.20-0.50% and 0.20-0.60%, respectively. Limit of detection (LOD) was achieved up to 15 ng mL(-1). Applicability of the method was tested with an unknown real sample obtained in an international official proficiency test (OPT).

Determination of alkyl alkylphosphonic acids by liquid chromatography coupled with electrospray ionization tandem mass spectrometry using a dicationic reagent.

A new analytical method based on liquid chromatography/electrospray ionization tandem mass spectrometry (LC/ESI-MS/MS) is proposed and validated for the identification and quantification of alkyl alkylphosphonic acids (AAPAs) in aqueous matrices. Retrospective detection and identification of degradation products of chemical warfare agents is important as an indicator of possible use of chemical warfare agents or of environmental contamination. A commercially available solution of 1,9-nonanediyl-bis-(3-methylimidazolium)bisfluoride (NBMI) allowed detection of AAPAs by positive mode electrospray ionization mass spectrometry by forming an adduct with AAPAs. MS/MS experiments using an ion trap analyzer were carried out for unambiguous identification of AAPAs. Different parameters were optimized in order to obtain both an adequate chromatographic separation and a high sensitivity using experimental design methodology. Quantification was done with matrix-matched calibration standards of AAPAs. The method was validated in terms of linearity (r(2) >0.982), intra- and inter-day precisions (RSD below 15%), and robustness. The method is sensitive enough for the determination of AAPAs in aqueous matrices, with limits of detection in the 1-5 ng mL(-1) range and limits of quantification in the 5-20 ng mL(-1) range. Finally, the method was successfully applied to determine these AAPAs in aqueous samples provided by the Organization for the Prohibition of Chemical Weapons during 26(th) and 29(th) official proficiency tests. The added advantage of this method is identification of low mass range analyte at high mass range, which obviates the background noise at low mass range.

Dispersive solid-phase extraction for in-sorbent Fourier-transform infrared detection and identification of nerve agent simulants in analysis for verification of chemical weapon convention.

The combination of dispersive solid-phase extraction (DSPE) and Fourier-transform infrared (FTIR) spectroscopy is presented for detection and quantification of markers and simulants of nerve agents. Hydrophilic-lipophilic balance (HLB) sorbent was used for extraction and enrichment of organophosphonates from water. When the extraction efficiency of DSPE was compared with that of conventional solid-phase extraction (SPE), DSPE was more efficient. Extraction conditions such as extraction time, and type and quantity of sorbent material were optimized. In DSPE, extracted analytes are detected and quantified on the sorbent using FTIR as analytical technique. Absorbance in FTIR due to P-O-C stretching was used for detection and quantification. Infrared absorbance of different analytes were compared by determining their molar absorptivities (ε (max)). Quantitative analyses were performed employing modified Beer's law, and relative standard deviations (RSDs) for intraday repeatability and interday reproducibility were found to be in the range 0.30-0.90% and 0.10-0.80% respectively. The limit of detection (LOD) was 5-10 µg mL(-1). The applicability of the method was tested with an unknown sample prepared by mimicking the sample obtained in an international official proficiency test.

Enhanced detectability of fluorinated derivatives of N,N-dialkylamino alcohols and precursors of nitrogen mustards by gas chromatography coupled to Fourier transform infrared spectroscopy analysis for verification of chemical weapons convention.

N,N-Dialkylamino alcohols, N-methyldiethanolamine, N-ethyldiethanolamine and triethanolamine are the precursors of VX type nerve agents and three different nitrogen mustards respectively. Their detection and identification is of paramount importance for verification analysis of chemical weapons convention. GC-FTIR is used as complimentary technique to GC-MS analysis for identification of these analytes. One constraint of GC-FTIR, its low sensitivity, was overcome by converting the analytes to their fluorinated derivatives. Owing to high absorptivity in IR region, these derivatives facilitated their detection by GC-FTIR analysis. Derivatizing reagents having trimethylsilyl, trifluoroacyl and heptafluorobutyryl groups on imidazole moiety were screened. Derivatives formed there were analyzed by GC-FTIR quantitatively. Of these reagents studied, heptafluorobutyrylimidazole (HFBI) produced the greatest increase in sensitivity by GC-FTIR detection. 60-125 folds of sensitivity enhancement were observed for the analytes by HFBI derivatization. Absorbance due to various functional groups responsible for enhanced sensitivity were compared by determining their corresponding relative molar extinction coefficients ( [Formula: see text] ) considering uniform optical path length. The RSDs for intraday repeatability and interday reproducibility for various derivatives were 0.2-1.1% and 0.3-1.8%. Limit of detection (LOD) was achieved up to 10-15ng and applicability of the method was tested with unknown samples obtained in international proficiency tests.

Gas chromatography electron ionization mass spectrometric analysis of O-alkyl methylphosphinates for verification of Chemical Weapons Convention.

We describe the gas chromatography/mass spectrometric (GC/MS) analysis of O-alkyl methylphosphinates (AMPs), which are included in schedule 2B4 chemicals in the Chemical Weapons Convention (CWC). GC/MS analysis of variety of AMPs and their deuterated analogues revealed that their fragmentations were determined by alpha-cleavages, McLafferty +1 and hydrogen rearrangements. Based on the obtained electron ionization mass spectra of AMPs the fragmentation routes were rationalized, which were substantiated by the GC/MS analysis of deuterated analogues.

On-line high-performance liquid chromatography-ultraviolet-nuclear magnetic resonance method of the markers of nerve agents for verification of the Chemical Weapons Convention.

This paper details an on-flow liquid chromatography-ultraviolet-nuclear magnetic resonance (LC-UV-NMR) method for the retrospective detection and identification of alkyl alkylphosphonic acids (AAPAs) and alkylphosphonic acids (APAs), the markers of the toxic nerve agents for verification of the Chemical Weapons Convention (CWC). Initially, the LC-UV-NMR parameters were optimized for benzyl derivatives of the APAs and AAPAs. The optimized parameters include stationary phase C(18), mobile phase methanol:water 78:22 (v/v), UV detection at 268nm and (1)H NMR acquisition conditions. The protocol described herein allowed the detection of analytes through acquisition of high quality NMR spectra from the aqueous solution of the APAs and AAPAs with high concentrations of interfering background chemicals which have been removed by preceding sample preparation. The reported standard deviation for the quantification is related to the UV detector which showed relative standard deviations (RSDs) for quantification within +/-1.1%, while lower limit of detection upto 16mug (in mug absolute) for the NMR detector. Finally the developed LC-UV-NMR method was applied to identify the APAs and AAPAs in real water samples, consequent to solid phase extraction and derivatization. The method is fast (total experiment time approximately 2h), sensitive, rugged and efficient.