Graphitic carbon nitride derived probes for the recognition of heavy metal pollutants of environmental concern in water bodies.

Graphitic carbon nitride (g-CN) has a number of valuable features that have been recognized during the studies related to its photocatalytic activity enhancement derived by visible light. Because of these characteristics, g-CN can be used as a detecting signal transducer with different transmission modalities. The latest up-to-date detection capabilities of modified g-CN nanoarchitectures are covered in this study. The structural features and synthetic methodologies have been discussed in a number of reports. Herein, employment of the g-CN as a promising probing modality for the recognition of different toxic heavy metals is the promising feature of the present study.

Organic Covalent Interaction-based Frameworks as Emerging Catalysts for Environment and Energy Applications: Current Scenario and Opportunities.

The term "covalent organic framework" (COF) refers to a class of porous organic polymeric materials made from organic building blocks that have been covalently bonded. The preplanned and predetermined bonding of the monomer linkers allow them to demonstrate directional flexibility in two- or three-dimensional spaces. COFs are modern materials, and the discovery of new synthesis and linking techniques has made it possible to prepare them with a variety of favorable features and use them in a range of applications. Additionally, they can be post-synthetically altered or transformed into other materials of particular interest to produce compounds with enhanced chemical and physical properties. Because of its tunability in different chemical and physical states, post-synthetic modifications, high stability, functionality, high porosity and ordered geometry, COFs are regarded as one of the most promising materials for catalysis and environmental applications. This study highlights the basic advancements in establishing the stable COFs structures and various post-synthetic modification approaches. Further, the photocatalytic applications, such as organic transformations, degradation of emerging pollutants and removal of heavy metals, production of hydrogen and Conversion of carbon dioxide (CO2 ) to useful products have also been presented. Finally, the future research directions and probable outcomes have also been summarized, by focusing their promises for specialists in a variety of research fields.

Recent Advances in the Catalytic Asymmetric Friedel-Crafts Reactions of Indoles.

Functionalized chiral indole derivatives are privileged and versatile organic frameworks encountered in numerous pharmaceutically active agents and biologically active natural products. The catalytic asymmetric Friedel-Crafts reaction of indoles, catalyzed by chiral metal complexes or chiral organocatalysts, is one of the most powerful and atom-economical approaches to access optically active indole derivatives. Consequently, a wide range of electrophilic partners including α,ß-unsaturated ketones, esters, amides, imines, ß,γ-unsaturated α-keto- and α-ketiminoesters, ketimines, nitroalkenes, and many others have been successfully employed to achieve a plethora of functionalized chiral indole moieties. In particular, strategies for C-H functionalization in the phenyl of indoles require incorporation of a directing or blocking group in the phenyl or azole ring of indole. The discovery of chiral catalysts which can control enantiodiscrimination has gained a great deal of attention in recent years. This review will provide an updated account on the application of the asymmetric Friedel-Crafts reaction of indoles in the synthesis of diverse chiral indole derivatives, covering the timeframe from 2011 to today.

Graphitic carbon nitride nanosheets as promising candidates for the detection of hazardous contaminants of environmental and biological concern in aqueous matrices.

Monitoring of pollutant and toxic substances is essential for cleaner environment and healthy life. Sensing of various environmental contaminants and biomolecules such as heavy metals, pharmaceutics, toxic gases, volatile organic compounds, food toxins, and pathogens is of high importance to guaranty the good health and sustainable environment to community. In recent years, graphitic carbon nitride (g-CN) has drawn a significant amount of interest as a sensor due to its large surface area and unique electrochemical properties, low bandgap energy, high thermal and chemical stability, facile synthesis, nontoxicity, and electron rich property. Furthermore, the binary and ternary nanocomposites of graphitic carbon nitride further enhance their performance as a sensor making it a cost effective, fast, and reliable gadget for the purpose, and opens a wide area of research. Numerous reviews addressing a variety of applications including photocatalytic energy conversion, photoelectrochemical detection, and hydrogen evolution of graphitic carbon nitride have been documented to date. But a lesser attention has been devoted to the mechanistic approaches towards sensing of variety of pollutants concerned with environmental and biological aspects. Herein, we present the sensing features of graphitic carbon nitride towards the detection of various analytes including toxic heavy metals, pharmaceuticals, phenolic compounds, nitroaromatic compounds, volatile organic molecules, toxic gases, and foodborne pathogens. This review will undoubtedly provide future insights for researchers working in the field of sensors, allowing them to investigate the intriguing graphitic carbon nitride material as a sensing platform that is comparable to several other nanomaterials documented in the literature. Therefore, we hope that this study could reveal some intriguing sensing properties of graphitic carbon nitride, which may help researchers better understand how it interacts with contaminants of environmental and biological concern. Graphitic carbon nitride Nanosheets as Promising Analytical Tool for Environmental and Biological Monitoring of Hazardous Substances.

Advances in Metal-Organic Framework (MOFs) based biosensors for diagnosis: An update.

Metal-organic frameworks (MOFs) have significant advantages over other candidate classes of chemo-sensory materials owing to their extraordinary structural tunability and characteristics. MOF-based biosensing is a simple, and convenient method for identifying various species. Biomarkers are molecular or cellular processes that link environmental exposure to a health outcome. Biomarkers are important in understanding the links between environmental chemical exposure and the development of chronic diseases, as well as in identifying disease-prone subgroups. Until now, several species, including nanoparticles (NPs) and their nanocomposites, small molecules, and unique complex systems, have been used for the chemical sensing of biomarkers. Following the overview of the field, we discussed the various fabrication methods for MOFs development in this review. We provide a thorough overview of the previous five years of progress to broaden the scope of analytes for future research. Several enzymatic and non-enzymatic sensors are offered, together with a mandatory measuring method that includes detection range and dynamic range. In addition, we reviewed the comparison of enzymatic and non-enzymatic biosensors, inventive edges, and the difficulties that need to be solved. This work might open up new possibilities for material production, sensor development, medical diagnostics, and other sensing fields.

Covalent Organic Frameworks-Based Membranes as Promising Modalities from Preparation to Separation Applications: An Overview.

Covalent organic frameworks (COFs) are a promising class of porous crystalline materials made up of covalently connected and periodically protracted network topologies through organic linkers. The tailorability of organic linker and intrinsic structures endow COFs with a tunable porosity and structure, low density, facilely-tailored functionality, and large surface area, attracting increasing amount of interests in variety of research areas of membrane separations. COF-based membranes have spawned a slew of new research projects, ranging from fabrication methodologies to separation applications. Herein, we tried to emphasis the major developments in the synthetic approaches of COFs based membranes for a variety of separation applications such as, separation of gaseous mixtures, water treatment as well as separation of isomeric and chiral organic compounds. The proposed methods for fabricating COF-based continuous membranes and columns for real world applications are also thoroughly explored. Finally, a viewpoint on the future directions and remaining challenges for COF research in the area of separation is provided.

Photocatalytic Water-Splitting by Organic Conjugated Polymers: Opportunities and Challenges.

The future challenges associated with the shortage of fossil fuels and their current environmental impacts intrigued the researchers to look for alternative ways of generating green energy. Solar-driven water splitting into oxygen and hydrogen is one of those advanced strategies. Researchers have studied various semiconductor materials to achieve potential results. However, it encountered multiple challenges such as high cost, low photostability and efficiency, and required multistep modifications. The conjugated polymers (CPs) have emerged as promising alternatives for conventional inorganic semiconductors. The CPs offer low cost, sufficient light absorption efficiency, excellent photo and chemical stability, and molecular optoelectronic tunable characteristics. Furthermore, organic CPs also present higher flexibility to tune the basic framework of the backbone of the polymers, amendments in the sidechain to incorporate desired functionalities, and much-needed porosity to serve better for photocatalytic applications. This review article summarizes the recent advancements made in visible-light-driven water splitting covering the aspects of synthetic strategies and experimental parameters employed for water splitting reactions with special emphasis on conjugated polymers such as linear CPs, planarized CPs, graphitic carbon nitride (g-C3 N4 ), conjugated microporous polymers (CMPs), covalent organic frameworks (COFs), and conjugated polymer-based nanocomposites (CPNCs). The current challenges and future prospects have also been described briefly.

Synthesis, α-amylase and α-glucosidase inhibition and molecular docking studies of indazole derivatives.

Herein, we report the synthesis and inhibitory potential of indazole (Methyl 1H-indazole-4-carboxylate) derivatives (1-13) against α-amylase and α-glucosidase enzymes. The described derivatives demonstrated good inhibitory potential with IC50 values, ranging between 15.04 ± 0.05 to 76.70 ± 0.06 µM ± SEM for α-amylase and 16.99 ± 0.19 to 77.97 ± 0.19 µM ± SEM for α-glucosidase, respectively. In particular, compounds (8-10 and 12) displayed significant inhibitory activities against both the screened enzymes, with their inhibitory potential comparable to the standard acarbose (12.98 ± 0.03 and 12.79 ± 0.17 µM ± SEM, respectively). Additionally, the influence of different substituents on enzyme inhibition activities was assessed to study the structure activity relationships. Molecular docking simulations were performed to rationalize the binding of derivatives/compounds with enzymes. All the synthesized derivatives (1-13) were characterized with the aid of spectroscopic instruments such as 1H-NMR, 13C-NMR, HR-MS, elemental analysis and FTIR.Communicated by Ramaswamy H. Sarma.

Automatic emotion recognition in healthcare data using supervised machine learning.

Human feelings are fundamental to perceive the conduct and state of mind of an individual. A healthy emotional state is one significant highlight to improve personal satisfaction. On the other hand, bad emotional health can prompt social or psychological well-being issues. Recognizing or detecting feelings in online health care data gives important and helpful information regarding the emotional state of patients. To recognize or detection of patient's emotion against a specific disease using text from online sources is a challenging task. In this paper, we propose a method for the automatic detection of patient's emotions in healthcare data using supervised machine learning approaches. For this purpose, we created a new dataset named EmoHD, comprising of 4,202 text samples against eight disease classes and six emotion classes, gathered from different online resources. We used six different supervised machine learning models based on different feature engineering techniques. We also performed a detailed comparison of the chosen six machine learning algorithms using different feature vectors on our dataset. We achieved the highest 87% accuracy using MultiLayer Perceptron as compared to other state of the art models. Moreover, we use the emotional guidance scale to show that there is a link between negative emotion and psychological health issues. Our proposed work will be helpful to automatically detect a patient's emotion during disease and to avoid extreme acts like suicide, mental disorders, or psychological health issues. The implementation details are made publicly available at the given link: https://bit.ly/2NQeGET.

Synthesis of a novel polysuccinimide based resin for the ultrahigh removal of anionic azo dyes from aqueous solution.

A novel hyper-cross-linked polyamide resin (PSI-PA) has been synthesized for the ultrahigh removal of Congo red (CR) and Eriochrom Black T (EBT) from aqueous solution. The mesoporous resin, having a specific surface area (98.80 m2 g-1), showed maximum adsorption capacity (Qmax) of 522.18 mg g-1 for CR (pH 9.0) and 460.34 mg g-1 for EBT (pH 6) at room temperature. The adsorption of these dyes was rapid and the equilibrium was attained within 4 h. The kinetic data was well-fitted by pseudo-second-order rate equation. Analysis of the surface chemical composition of loaded PSI-PA by XPS revealed the appearance of a new peak at around 166.0 eV (S 2p), confirming the adsorption of the sulfur-based dyes onto the resin. Examination of experimental data of dyes adsorption by a variety of non-linear adsorption isotherms and kinetic models suggested that the Langmuir model exhibited the best fit with high correlation coefficients for both CR (R2 = 0.9966) and EBT (R2 = 0.9934). PSI-PA has been extensively characterized by FT-IR, solid state 13C (CP-MAS) NMR, EDS, TGA and BET analysis. Moreover, PSI-PA exhibited 82% removal efficiency for dyes in simulated effluents, manifesting its promise and utility for treating industrial effluent.

Frequency of metabolic syndrome in patients with type-2 diabetes.

BACKGROUND: Diabetes, Hypertension, Obesity and Ischaemic Heart Disease have become a problem of public health magnitude with substantial economic burden both in the developed as well as the developing countries. Obesity is quite frequent in Type 2 diabetics and also plays a central role in causing Metabolic Syndrome (MetS). Metabolic Syndrome significantly increases the incidence of cardiovascular complications. This study was done to determine the frequency of MetS in our Type 2 diabetic patients as most of the components of MetS can be modified and identifying/managing these at an early stage might be of considerable help in reducing cardiovascular complications. METHODS: This cross-sectional study was done in Medical 'B' and Medical 'A' wards of Ayub Teaching Hospital, Abbottabad from Nov, 08 to April, 09. Type 2 Diabetic patients aged above 40 years who gave informed consent were included in the study. Data was collected through a structured proforma. Frequency of Metabolic Syndrome was estimated according to the IDF consensus worldwide definition of the MetS. RESULTS: Of the 100 patients enrolled in this study 56 were females and 44 were males with a mean age of 59.9 years. Out of these 100 participants seventy six (76%) were diagnosed to have metabolic syndrome. Of the 56 females, forty eight (85.71%) were having metabolic syndrome while twenty eight (63.63%) of the 44 male participants were having the syndrome. The difference was statistically significant (p < 0.05). CONCLUSION: Frequency of MetS was found to be significantly high in this study with female preponderance. All the components, except Hypertension were more frequent in females. Diabetic patients with metabolic syndrome need more aggressive approach in management so as to decrease the incidence of cardiovascular complications.