Comparative Study of Planar Octahedron Molecular Structure via Eccentric Invariants.

A branch of graph theory that makes use of a molecular graph is called chemical graph theory. Chemical graph theory is used to depict a chemical molecule. A graph is connected if there is an edge between every pair of vertices. A topological index is a numerical value related to the chemical structure that claims to show a relationship between chemical structure and various physicochemical attributes, chemical reactivity, or, you could say, biological activity. In this article, we examined the topological properties of a planar octahedron network of m dimensions and computed the total eccentricity, average eccentricity, Zagreb eccentricity, geometric arithmetic eccentricity, and atom bond connectivity eccentricity indices, which are used to determine the distance between the vertices of a planar octahedron network.

A critical analysis of wastewater use in agriculture and associated health risks in Pakistan.

Freshwater shortage and its contamination with various types of pollutants are becoming the most alarming issues worldwide due to impacts on socioeconomic values. Considering an increasing freshwater scarcity, it is imperative for the growers, particularly in semiarid and arid areas, to use wastewater for crop production. Wastewaters generally contain numerous essential inorganic and organic nutrients which are considered necessary for plant metabolism. Besides, this practice provokes various hygienic, ecological and health concerns due to the occurrence of toxic substances such as heavy metals. Pakistan nowadays faces a severe freshwater scarcity. Consequently, untreated wastewater is used routinely in the agriculture sector. In this review, we have highlighted the negative and positive affectivity of wastewater on the chemical characteristics of the soil. This review critically delineates toxic metal accumulation in soil and their possible soil-plant-human transfer. We have also estimated and deliberated possible health hazards linked with the utilization of untreated city waste effluents for the cultivation of food/vegetable crops. Moreover, we carried out a multivariate analysis of data (144 studies of wastewater crop irrigation in Pakistan) to trace out common trends in published data. We have also compared the limit values of toxic metals in irrigation water, soil and plants. Furthermore, some viable solutions and future viewpoints are anticipated taking into account the on-ground situation in Pakistan-such as planning and sanitary matters, remedial/management technologies, awareness among local habitants (especially farmers) and the role of the government, NGOs and pertinent stakeholders. The data are supported by 13 tables and 7 figures.

On Topological Properties for Benzenoid Planar Octahedron Networks.

Chemical descriptors are numeric numbers that capture the whole graph structure and comprise a basic chemical structure. As a topological descriptor, it correlates with certain physical aspects in addition to its chemical representation of underlying chemical substances. In the modelling and design of any chemical network, the graph is important. A number of chemical indices have been developed in theoretical chemistry, including the Wiener index, the Randic index, and many others. In this paper, we look at the benzenoid networks and calculate the exact topological indices based on the degrees of the end vertices.

Effect of co-application of wastewater and freshwater on the physiological properties and trace element content in Raphanus sativus: soil contamination and human health.

Nowadays, the use of wastewater for crop irrigation is increasing at global scale mainly due to freshwater scarcity and economic benefits. However, the presence of different types of pollutants including the trace elements (TEs) poses a serious threat to environmental and human health. This pot study evaluated the effect of alone and mixed irrigation water [wastewater (WW) with canal water (CW) and tube-well water (TW)] on TEs build-up in the soil, their soil-plant transfer and allied health hazards in District Vehari. The WW samples were mainly contaminated with Cd (0.03 mg/L), Cr (1.45 mg/L), Cu (0.35 mg/L) and Ni (0.40 mg/L). The CW contained high levels of Cr and Fe, while TW was contaminated with Pb and Cr. In soil, the concentrations of Cd, Fe and Mn exceeded their respective limit values for all the treatments. Among all the treatments, TEs concentration was found highest in WW-3 irrigated soil. Application of all the treatments resulted in TEs (Cu, 60.1 mg/kg; Cd, 8.2 mg/kg; Ni, 39.9 mg/kg; Fe, 4411 mg/kg; Zn, 111.3 mg/kg and Pb, 44.5 mg/kg) accumulation mainly in the edible parts of Raphanus sativus. Compared to other treatments, TW and TW + CW irrigated plants accumulated higher levels of TEs. Results showed linear trends among TEs accumulation and alterations in physiological attributes of R. sativus. High TEs accumulation in TW irrigated treatments (TW + WW-1 and TW + CW) caused maximum H2O2 production, lipid peroxidation and decline in plant pigments. Risk assessment parameters showed both carcinogenic and non-carcinogenic risks for all the irrigation treatments due to high TEs contents in edible tissues. It is concluded that alone or combined application of WW, TW and CW is not fit for vegetable irrigation, in the studied area, due to high TEs contents.

Assessment of arsenic exposure by drinking well water and associated carcinogenic risk in peri-urban areas of Vehari, Pakistan.

Arsenic (As) is a highly toxic and carcinogenic element. It has received considerable consideration worldwide in recent years due to its highest toxicity to human, and currently, high concentrations observed in the groundwater. Some recent media and research reports also highlighted possible As contamination of groundwater systems in Pakistan. However, there is a scarcity of data about As contents in groundwater in different areas/regions of the country. Consequently, the current study estimated the As concentration in the groundwater used for drinking purpose in 15 peri-urban sites of district Vehari, Pakistan. In total, 127 groundwater samples were collected and examined for As contents in addition to physicochemical characteristics such as temperature, electrical conductivity, pH, total soluble salts, chloride, carbonates, bicarbonates, sodium, potassium, lithium, calcium and barium. Results indicated that the groundwater samples were not fully fit for drinking purposes with several parameters, especially the alarming levels of As (mean As: 46.9 µg/L). It was found that 83% groundwater samples of peri-urban sites in district Vehari have As concentration greater than WHO lower permissible limit (10 µg/L). The risk assessment parameters (mean hazard quotient: 3.9 and mean cancer risk: 0.0018) also showed possible carcinogenic and non-carcinogenic risks associated with ingestion of As-contaminated groundwater at peri-urban sites. Based on the findings, it is anticipated that special monitoring and management of groundwater is necessary in the studied area in order to curtail the health risks associated with the use of As-contaminated drinking water. Moreover, appropriate remediation and removal of As from groundwater is also imperative for the study area before being used for drinking purpose to avoid As exposure and related risks to the local community.

Quantification and risk assessment of heavy metal build-up in soil-plant system after irrigation with untreated city wastewater in Vehari, Pakistan.

In peri-urban areas of district Vehari, farmers are using untreated city wastewater for crop irrigation owing to the scarcity of good-quality irrigation water. This practice may pose severe environmental and health issues to local inhabitants attributed to the high levels of potentially toxic metals in wastewater. The present study evaluated the potential impacts of wastewater irrigation on metals (Cd, Cr, Cu, Fe, Ni, Mn, Pb and Zn) build-up in the soil-plant continuum and associated health risks. In this study, wastewater (n = 17), soil (n = 108) and plant (n = 65) samples were collected from 15 peri-urban sites of three tehsils of district Vehari. Results showed that the mean concentration (mg/L) of Cd (0.02), Mn (0.25) and Fe (1.57) in wastewater samples was higher than their respective threshold values. Similarly, Cd, Mn and Fe concentration in soil was beyond the permissible limits of agricultural soil receiving wastewater irrigation. However, plants showed high accumulation of Pb, Cr and Fe than their respective limits depending on the vegetable/crop species. The health risk parameters showed that Pb and Cd are the major toxic chemical substances to human health, and the daily intake of crop plants can pose a potential health threat due to wastewater-irrigated crop consumption. Results highlighted the necessity of wastewater pretreatment to avoid the soil and vegetable contamination by wastewater irrigation and to reduce the associated health risks.

Study for Some Eccentricity-based Topological Indices of Second Type of Dominating David-derived Network.

BACKGROUND: Dominating David-derived networks are widely studied due to their fractal nature, with applications in topology, chemistry, and computer sciences. The use of molecular structure descriptors is a standard procedure that is used to correlate the biological activity of molecules with their chemical structures, which can be useful in the field of pharmacology. OBJECTIVE: This article's goal is to develop analytically closed computing formulas for eccentricity-based descriptors of the second type of dominating David-derived derived network. Thermodynamic characteristics, physicochemical properties, and chemical and biological activities of chemical graphs are just a few of the many properties that may be determined using these computation formulas. METHODS: Vertex sets were initially divided according to their degrees, eccentricities, and cardinalities of occurrence. The eccentricity-based indices are then computed using some combinatorics and these partitions. RESULTS: Total eccentricity, average eccentricity, and the Zagreb index are distance-based topological indices utilized in this study for the second type of dominating David-derived network, denoted as D_2 (m). CONCLUSION: These calculations will assist the readers in estimating the fractal and difficult-to-handle thermodynamic and physicochemical aspects of chemical structure. Apart from configuration and impact resistance, the D_2 (m) design has been used for fundamental reasons in a variety of technical and scientific advancements.

Glycomic and Glycoproteomic Techniques in Neurodegenerative Disorders and Neurotrauma: Towards Personalized Markers.

The proteome represents all the proteins expressed by a genome, a cell, a tissue, or an organism at any given time under defined physiological or pathological circumstances. Proteomic analysis has provided unparalleled opportunities for the discovery of expression patterns of proteins in a biological system, yielding precise and inclusive data about the system. Advances in the proteomics field opened the door to wider knowledge of the mechanisms underlying various post-translational modifications (PTMs) of proteins, including glycosylation. As of yet, the role of most of these PTMs remains unidentified. In this state-of-the-art review, we present a synopsis of glycosylation processes and the pathophysiological conditions that might ensue secondary to glycosylation shortcomings. The dynamics of protein glycosylation, a crucial mechanism that allows gene and pathway regulation, is described. We also explain how-at a biomolecular level-mutations in glycosylation-related genes may lead to neuropsychiatric manifestations and neurodegenerative disorders. We then analyze the shortcomings of glycoproteomic studies, putting into perspective their downfalls and the different advanced enrichment techniques that emanated to overcome some of these challenges. Furthermore, we summarize studies tackling the association between glycosylation and neuropsychiatric disorders and explore glycoproteomic changes in neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Huntington disease, multiple sclerosis, and amyotrophic lateral sclerosis. We finally conclude with the role of glycomics in the area of traumatic brain injury (TBI) and provide perspectives on the clinical application of glycoproteomics as potential diagnostic tools and their application in personalized medicine.

Molecular and Biochemical Characterization, Antimicrobial Activity, Stress Tolerance, and Plant Growth-Promoting Effect of Endophytic Bacteria Isolated from Wheat Varieties.

Endophytic bacteria have been utilized as an alternative source to chemical fertilizers and pesticides to enhance plant productivity and defense mechanisms against biotic and abiotic stress. Five endophytic bacterial strains were isolated from the seeds of three different Pakistani wheat varieties (Ghaneemat-e-IBGE, Atta-Habib, and Siren). The isolated strains AH-1, S-5, S-7, GI-1, and GI-6 showed phylogenetic similarity with Bacillus altitudinis, B. aryabhattai, B. wiedmannii, Pseudomonas aeruginosa, and Burkholderia gladioli, respectively. All strains showed catalase activity (except AH-1) and Indole-3-acetic acid production, with the highest concentration (16.77 µg·mL-1) found for GI-6, followed by S-5 (11.5 µg·mL-1), nitrogen assimilation (except S-7), phosphorus solubilization (except S-7 and AH-1), and ability to produce siderophores, with maximum productions for GI-6 (31 ± 3.5 psu) and GI-1 (30 ± 2.9 psu). All five analyzed strains possessed antimicrobial activity, which was particularly strong in GI-6 and S-5 against Klebsiella pneumonia, Escherichia coli, and Bacillus subtilis. Increasing salinity stress with NaCl negatively affected the bacterial growth of all isolates. However, strains GI-6 and S-5 showed salt tolerance after three days of incubation. A drought tolerance test resulted in a negative impact of poly ethylene glycol on bacterial growth, which was, however, less pronounced in GI-6 strain. The GI-6 strain revealed growth-promoting effects on inoculated wheat plants.

Current Status of Pyrethroids Resistance in Aedes aegypti (Culicidae: Diptera) in Lahore District, Pakistan: A Novel Mechanistic Insight.

Aedes aegypti (Linnaeus, 1762) is a major vector responsible for dengue transmission. Insecticides are being used as the most effective tool to control vector populations in Lahore, Pakistan. Control of Ae. aegypti is threatened by the development of resistance against insecticides. The current status of insecticide resistance was evaluated against pyrethroids (deltamethrin, cypermethrin, and lambda-cyhalothrin) in different populations of Lahore (Model Town, Mishri Shah, Sadar Cantt, Walton, and Valencia). The susceptibility of the larval and adult populations was tested following the standard WHO guidelines. Moderate to high levels of resistance were found against pyrethroids in the larval (RR50: 3.6-27.2 and RR90: 5-90) and adult populations (percentage mortality < 98%). Biochemical assays revealed a statistically significant increase in the enzyme level in all field populations compared to the laboratory strain. The value of esterase was one-fold higher, monooxygenase was 3.9- to 4.7-fold higher, and glutathione S-transferases was 1.9- to 2.6-fold higher in field populations compared to the laboratory strain. These results depict the presence of resistance against deltamethrin, cypermethrin, and lambda-cyhalothrin in field populations of Lahore mediated by metabolic enzymes i.e. esterases, monooxygenases, and glutathione S-transferase.

Alcohol drinking and brain morphometry in apparently healthy community-dwelling Japanese men.

The clinical implications of alcohol consumption have been extensively examined; however, its effects on brain structures in apparently healthy community-dwellers remain unclear. Therefore, we investigated the relationship between alcohol consumption and brain gray matter volume (GMV) in community-dwelling Japanese men using voxel-based morphometry (VBM). We recruited cognitively intact Japanese men, aged 40-79 years, from a population-based cohort in Shiga, Japan. Brain magnetic resonance imaging was performed, on average, 2 years after demographic and medical information was obtained in 2010-2014. A multivariable linear regression analysis of 639 men was conducted to elucidate the relationship between the amount of alcohol consumed and GMV. VBM statistics were analyzed by threshold-free cluster enhancement with a family-wise error rate of <0.05. The results obtained demonstrated that the amount of alcohol consumed was associated with lower GMV. The VBM analysis showed lower GMV within the parahippocampal, entorhinal, cingulate, insular, temporal, and frontal cortices and cerebellum in very heavy drinkers (≥42 ethanol g/day) than in non-drinkers. Furthermore, alcohol consumption was associated with a higher white matter lesion volume. These results suggest subclinical structural changes similar to alcohol-related neurological diseases.

Machine Learning for Diagnosis of AD and Prediction of MCI Progression From Brain MRI Using Brain Anatomical Analysis Using Diffeomorphic Deformation.

Background: With the growing momentum for the adoption of machine learning (ML) in medical field, it is likely that reliance on ML for imaging will become routine over the next few years. We have developed a software named BAAD, which uses ML algorithms for the diagnosis of Alzheimer's disease (AD) and prediction of mild cognitive impairment (MCI) progression. Methods: We constructed an algorithm by combining a support vector machine (SVM) to classify and a voxel-based morphometry (VBM) to reduce concerned variables. We grouped progressive MCI and AD as an AD spectrum and trained SVM according to this classification. We randomly selected half from the total 1,314 subjects of AD neuroimaging Initiative (ADNI) from North America for SVM training, and the remaining half were used for validation to fine-tune the model hyperparameters. We created two types of SVMs, one based solely on the brain structure (SVMst), and the other based on both the brain structure and Mini-Mental State Examination score (SVMcog). We compared the model performance with two expert neuroradiologists, and further evaluated it in test datasets involving 519, 592, 69, and 128 subjects from the Australian Imaging, Biomarker & Lifestyle Flagship Study of Aging (AIBL), Japanese ADNI, the Minimal Interval Resonance Imaging in AD (MIDIAD) and the Open Access Series of Imaging Studies (OASIS), respectively. Results: BAAD's SVMs outperformed radiologists for AD diagnosis in a structural magnetic resonance imaging review. The accuracy of the two radiologists was 57.5 and 70.0%, respectively, whereas, that of the SVMst was 90.5%. The diagnostic accuracy of the SVMst and SVMcog in the test datasets ranged from 88.0 to 97.1% and 92.5 to 100%, respectively. The prediction accuracy for MCI progression was 83.0% in SVMst and 85.0% in SVMcog. In the AD spectrum classified by SVMst, 87.1% of the subjects were Aß positive according to an AV-45 positron emission tomography. Similarly, among MCI patients classified for the AD spectrum, 89.5% of the subjects progressed to AD. Conclusion: Our ML has shown high performance in AD diagnosis and prediction of MCI progression. It outperformed expert radiologists, and is expected to provide support in clinical practice.

Soils of the Southern Syria - A big database for the future land management planning.

As non-renewable natural resources, restoring Syrian soil quality is a vital issue for sustainable future planning after conflict ends. The data provided in this research exhibit features and physiochemical properties for soils from the southern part of Syria until the Jordanian border, which can provide decision-makers with sufficient information for rehabilitation stage after conflict in a regional scale. The data were collected from 107 representative soil profiles covering diverse agroecosystems throughout the area (i.e. Dara and Alswieda governorates). The most important data findings of this research included the first detection of Palygorskite {(Mg,Al)2Si4O10(OH)•4(H2O)} in Syrian soils, which is considered a strong evidence for the direct effects of the climate change on agroecosystem. Vertisols, Inceptisols, Entisols, Mollisols, and Aridisols were the most widespread soil types in the area. Overall, the database involves the field morphological characteristics, physicochemical, and mineralogical analyses.

Heavy metal contamination and exposure risk assessment via drinking groundwater in Vehari, Pakistan.

The presence of toxic substances in aquifers, particularly potentially toxic heavy metals, is an important environmental and social concern worldwide. These heavy metals are capable to exert many injurious health effects in human beings by intake of drinking metal-contaminated water. However, very little attention is paid towards quantitative and qualitative analysis of groundwater used for drinking purpose in several less-developed countries. Therefore, this study was intended to estimate, for the first time, the heavy metal levels in groundwater/drinking water in District Vehari, Pakistan. A total of 129 groundwater samples were obtained and subjected to analyze heavy metal concentrations (lead, copper, cadmium, nickel, manganese, chromium, iron, and zinc). Moreover, pH, electrical conductivity, temperature, total dissolved solids, and anion (carbonates, chloride, and bicarbonates) and cation (calcium, potassium, sodium, lithium, and barium) contents of groundwater were also determined. It was noticed that the values of several groundwater physicochemical characteristics such as cation contents, alkalinity, chloride concentration, and especially the concentrations of heavy metals such as Pb (93%), Cd (68%), and Fe (100%) were higher than their limit values given by WHO. Principal component analysis separately grouped heavy metals and physicochemical characteristics of groundwater. The risk assessment indices predicted potential carcinogenic risks due to the consumption of metal-rich groundwater, predominantly with Cd (0.0007-0.03). The mean hazard quotient (HQ) values for all the metals were < 1, while Pb showed HQ > 1 envisaging non-carcinogenic risk with the consumption of studied groundwater. The findings of the study emphasized on the need of appropriate approaches to remediate groundwater before being used for drinking purpose.

The genus Parasola in Pakistan with the description of two new species.

Parasola is a genus of small, veil-less coprinoid mushrooms in the family Psathyrellaceae (Agaricales). The genus is not well documented in Asia, specifically in Pakistan. In this study we describe two new species Parasola glabra and P. pseudolactea from Pakistan, based on morphological and molecular data. Phylogeny based on three DNA regions: nuc rDNA region encompassing the internal transcribed spacers 1 and 2 along with the 5.8S rDNA (ITS), nuc 28S rDNA D1-D2 domains (28S) and translation elongation factor 1α gene (TEF1α) show that the new taxa are clustered in a clade formed by the members of section Parasola of genus Parasola. Parasola glabra with grayish pileus, slightly depressed pileal disc, lamellae separated from the stipe by pseudocollarium, basidiospores 14.5-16.5 × 9.5-11.5 × 8.0-10.5 µm, in front view broadly ovoid to oblong, some with rhomboidal outline, in side view ellipsoid, with eccentric germ-pore of 1.5 µm diameter. Parasola pseudolactea with yellowish brown to dull brown pileus, disc indistinctly umbonate, lamellae free, pseudocollarium absent, basidiospores 13.5-14.5 × 10.5-12.0 × 9.5-10.5 µm, in face view rounded triangular to heart shaped, rarely ovoid to subglobose, in side view ellipsoid to oblong, with eccentric germ-pore of 1.5 µm diam. In addition to these new species, P. auricoma and P. lilatincta were also studied. Morphological descriptions for the new species and comparison with known Parasola species are provided. Our observations highlight the diversity of Parasola in northern Pakistan and further document the need for additional systematic focus on the region's fungi.

A Review of Environmental Contamination and Health Risk Assessment of Wastewater Use for Crop Irrigation with a Focus on Low and High-Income Countries.

Population densities and freshwater resources are not evenly distributed worldwide. This has forced farmers to use wastewater for the irrigation of food crops. This practice presents both positive and negative effects with respect to agricultural use, as well as in the context of environmental contamination and toxicology. Although wastewater is an important source of essential nutrients for plants, many environmental, sanitary, and health risks are also associated with the use of wastewater for crop irrigation due to the presence of toxic contaminants and microbes. This review highlights the harmful and beneficial impacts of wastewater irrigation on the physical, biological, and chemical properties of soil (pH, cations and anions, organic matter, microbial activity). We delineate the potentially toxic element (PTEs) build up in the soil and, as such, their transfer into plants and humans. The possible human health risks associated with the use of untreated wastewater for crop irrigation are also predicted and discussed. We compare the current condition of wastewater reuse in agriculture and the associated environmental and health issues between developing and developed countries. In addition, some integrated sustainable solutions and future perspectives are also proposed, keeping in view the regional and global context, as well as the grounded reality of wastewater use for crop production, sanitary and planning issues, remedial techniques, awareness among civil society, and the role of the government and the relevant stakeholders.

Margin based ontology sparse vector learning algorithm and applied in biology science.

In biology field, the ontology application relates to a large amount of genetic information and chemical information of molecular structure, which makes knowledge of ontology concepts convey much information. Therefore, in mathematical notation, the dimension of vector which corresponds to the ontology concept is often very large, and thus improves the higher requirements of ontology algorithm. Under this background, we consider the designing of ontology sparse vector algorithm and application in biology. In this paper, using knowledge of marginal likelihood and marginal distribution, the optimized strategy of marginal based ontology sparse vector learning algorithm is presented. Finally, the new algorithm is applied to gene ontology and plant ontology to verify its efficiency.