Susceptibility Analysis Research Articles

LINC00470 promotes malignant progression of testicular germ cell tumors.

Testicular germ cell tumor (TGCT) is a common malignant tumor in adolescents. Now, many long non-coding RNAs (LncRNAs) have been found to have an important function in TGCT. LINC00470 is specifically and highly expressed in TGCT, however, there is still no definite information concerning its role and underlying mechanism in TGCT. The purpose of this research was to look into the involvement of LINC00470 in TGCT and its intrinsic mechanism. UCSC and GEPIA2 databases were used to analyze the expression of LINC00470, and the BEST website was used to perform GSEA enrichment analysis, immune infiltration analysis, and drug susceptibility analysis. SiRNA transfection was used to silence LINC00470 in TCAM-2 and NCCIT cells. Clone formation and Transwell assays were performed in TGCT cells to confirm the effects of LINC00470 on clone formation, migration, and invasion. Western Blot was performed to determine the expression of proteins related to the EMT and AKT signaling pathways. LINC00470 was specifically highly expressed in TGCT, and played a role in promoting tumor cell clone formation and cell metastasis by affecting the TGF-β and PI3K-AKT-mTOR signaling pathways to regulate the epithelial-mesenchymal transition (EMT) process; LINC00470 may also play a pro-tumor role by negatively regulating immune infiltration; in addition, the expression of LINC00470 was negatively correlated with the chemosensitivity of cisplatin in TGCT patients. LINC00470 may play a significant role in the etiology and metastasis of TGCT through EMT and AKT-mediated signaling pathways.

Design, characterization, and bioactivity evaluation of novel symmetrical N,N'-benzene-1,2-diylbis[1-(2-chloroquinolin-3-yl)methanimine] based metal complexes

This study presents the synthesis and characterization of two novel metal complexes derived from the symmetrical Schiff base N,N'-benzene-1,2-diylbis[1-(2-chloroquinolin-3-yl)methanimine] (OBCQ), coordinated with Nickel(II) (NiOBCQ) and Copper(II) (CuOBCQ). The structural elucidation of these complexes was achieved through a comprehensive suite of analytical techniques, including elemental analysis, UV–visible spectroscopy, mass spectrometry, infrared spectroscopy, magnetic susceptibility, conductivity measurements, and thermal analysis. The data confirm that both NiOBCQ and CuOBCQ adopt octahedral geometries, formulated as [Ni(OBCQ)(H₂O)₂(Cl)₂] and [Cu(OBCQ)(H₂O)₂(Cl)₂], respectively. Density Functional Theory (DFT) calculations were employed to validate the molecular structures and explore the quantum chemical parameters of OBCQ and its metal complexes. Additionally, in vitro assessments of anti-inflammatory and antioxidant activities revealed enhanced bioactivity for the metal complexes compared to the free OBCQ ligand. Molecular docking studies against key proteins (5IKT for Human Cyclooxygenase-2 and 5IJT for Human Peroxiredoxin 2) highlighted strong binding affinities and molecular interactions, suggesting that OBCQ and its metal complexes hold significant promise as novel therapeutic agents with multifaceted biological activities.

Imported Cutaneous Leishmaniasis from Peru Caused by Leishmania (Viannia) guyanensis in a Brazilian Patient: Case Report and In Vitro Drug Susceptibility Analysis

In South America, cutaneous leishmaniasis is caused by several species of the parasite of the genus Leishmania. Here, we describe an imported case of cutaneous leishmaniasis acquired in Peru by a Brazilian patient during her travel to Iquitos. Infection by Leishmania parasites was confirmed by histopathologic examination, and the patient was treated with pentavalent antimony (Pentostam), without clinical response. Molecular typing was performed by sequencing the ribosomal DNA internal transcribed spacer and heat-shock protein 70 gene, which identified the parasites as Leishmania guyanensis. The clinical isolate was similarly susceptible to amphotericin B, pentamidine, and miltefosine as the reference strain, while for pentavalent antimony, this clinical isolate was more susceptible than the reference strain, even though its susceptibility in vitro was still considered low. The patient was then treated with liposomal amphotericin B, with clinical improvement of the lesions.

Cluster spin glass behaviour of Co2+−Al3+ layered double hydroxides

Frequency-dependent magnetic behaviour of cobalt-aluminium layered double hydroxides (LDH) with the Co/Al ratio of 2 and 3, was studied between 2 and 300 K. It was found from analysis of the temperature-dependent ac magnetic susceptibility that these LDH exhibit a magnetic cluster spin glass behaviour regardless of their basal spacing value and the Co/Al ratio as evidenced by EA/kBT0 > 1 relation obtained using Vogel-Fulcher law. The obtained values of Mydosh parameters in the range of 0.017–0.052 suggest that some of these materials are not far from the canonical spin glasses, implying a rather small size of the magnetic clusters.

Impact of COVID-19 on the Prevalence and Drug Resistance of Bacteria Isolated From Bacterial Meningitis Cerebrospinal Fluid in Shandong Province: A Multicenter Retrospective Study.

Our objective was to evaluate the ramifications of the 2019 coronavirus disease (COVID-19) pandemic on the microbial profile and antimicrobial resistance patterns of bacteria isolated from cerebrospinal fluid (CSF) specimens of patients with bacterial meningitis. We conducted a retrospective analysis of laboratory results and clinical records about positive CSF cultures reported by the SPARSS network from 2017 to 2023. The study covered three distinct periods: January 2017 to December 2019 (before the COVID-19 pandemic), January 2020 to December 2022 (during the COVID-19 pandemic), and January 2023 to December 2023 (after the COVID-19 pandemic), with a total of 5793 CSF isolates collected. Notably, the proportion of male patients (61.3%) was higher than that of females. After COVID-19, we observed a notable shift in the seasonal peak of CSF pathogens, with a delay of approximately 3 months. Remarkable alterations were evident in both pediatric and adult CSF isolate profiles. In children, the predominant pathogens included coagulase-negative Staphylococcus (CoNS), Streptococcus pneumonia, and Escherichia coli. Notably. After COVID-19, there was a significant decrease in the proportion of CoNS (p = 0.0039) and a notable increase in E. coli (p = 0.0067). In adults, the top three pathogens were CoNS, Acinetobacter baumannii, and Klebsiella pneumoniae. After the pandemic, we observed a significant reduction in the prevalence of A. baumannii (p = 0.0059), while the proportions of K. pneumoniae, Pseudomonas aeruginosa, Enterobacter cloacae, and Enterococcus faecalis increased significantly (p < 0.05). Additionally, among multidrug-resistant bacteria, the detection rate of carbapenem-resistant E. coli escalated (p = 0.0375). Antimicrobial susceptibility analysis indicated a declining trend in resistance rates for CoNS and A. baumannii to certain antibiotics following the pandemic. Conversely, resistance to imipenem in A. baumannii increased. In conclusion, the COVID-19 pandemic has significantly influenced the composition, antimicrobial resistance patterns, and epidemiological dynamics of CSF-isolated bacteria in Shandong province. To effectively address these changes, ongoing and dynamic surveillance of pathogen trends and antimicrobial resistance rate is essential.

Synthesis, characterization, and biological potential of 2-thiophene carbaldehyde o-phenylenediamine Schiff base and its Cr(II), Mn(II), and Fe(II) Complexes

A Schiff base was produced through the chemical reaction of 2-thiophene carbaldehyde with o-phenylenediamine. The corresponding metal (II) chlorides were refluxed with the Schiff base to produce the complexes of Cr (II), Mn (II), and Fe (II). These complexes were then characterized by elemental analysis, FT-IR, atomic absorption spectroscopy, solubility, melting/decomposition temperature, and magnetic susceptibility. The vibrational peak at 1622 cm̄1 in the FT-IR spectral data of the Schiff base was ascribed to the vibration frequencies of azomethine u(C=N). But in the complexes, it was discovered that the azomethine band shifted between 1614 and 1659 cm̄1 , suggesting that they were involved in the complexes’ creation. The complexes’ measured absorption bands in the range of 713–769 cm1 were attributed to the M–N bond, indicating the occurrence of metal–nitrogen bonds. The complexes exhibit non-electrolyte properties attributed to their low molar conductance values ranging from 8.00 to 29 Ohm̄1 cm̄ ²mol̄¹. The determination of the melting point of the Schiff base yielded 120 °C, while the decomposition temperature fell within the range of 149–160 °C for the complexes, indicating their thermal stability. Analysis of magnetic susceptibility indicated an octahedral geometry for all the complexes, with values ranging from 2.24 to 3.12 BM. The elemental should analysis of both the Schiff base and its metal (II) complexes for C, H, and N indicated a close agreement between observed and calculated percentages, suggesting a consistent 1:2 metal-Schiff base ratio across all complexes. The qualitative analysis of the compounds confirmed the presence of chloride, which was quantified and determined to range from 4.62% to 7.90%. The prepared Schiff base and its metal (II) complexes underwent evaluation for their antibacterial efficacy against Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, and Pseudomonas aeruginosa, as well as their antifungal properties against Candida albicans and Aspergillus niger. The results of the experiments indicated that the metal complexes displayed notable antimicrobial effects.

Machine learning-based assessment of regional-scale variation of landslide susceptibility in central Vietnam.

Recurrent landslide events triggered by typhoons and tropical storms over Vietnam pose a longstanding threat to the nation's population and infrastructure. Changes in hydroclimatic conditions, especially the growing intensity and frequency of storms, have elevated landslide susceptibility in many parts of the country. This research examines the spatio-temporal variations in landslide susceptibility across central Vietnam over several years, using multi-temporal landslide inventories from Typhoon Ketsana (2009), Tropical Storm Podul (2013), and Typhoon Molave (2020). Additionally, the research explores the impact of individual landslide causative factors on the probabilistic occurrences of landslides. The post-event landslide susceptibility models of these three climate extreme events were developed using nine causative factors and a Random Forest machine learning algorithm. The results indicate a notable areal expansion of high to very high landslide susceptibility in the northern and eastern regions and a moderate reduction in the central and southern areas during the post-Molave period compared to the post-Ketsana period. These changes may be early indicators of increasing landslide susceptibility in response to changing hydro-climatic conditions. The research found that annual average rainfall and topographic elevation are the two most important variables influencing landslide prediction, showing a nonlinear relationship with landslide probability. The landslide susceptibility models achieved high Area Under the Receiver Operating Characteristic Curve (AUC) (>95%), accuracy (>89%), and sensitivity (>90%) scores, signifying the robustness of the models. Additionally, the uncertainty of the models was quantified and spatially mapped. This multi-temporal analysis of landslide susceptibility is crucial for understanding the regional susceptibility trends and identifying areas with increasing, decreasing, and consistently high susceptibility to landslides. These insights are invaluable for prioritizing mitigation and risk reduction strategies in landslide-prone regions and guiding appropriate land use planning.

Divalent transition metal complexes with mixed of β-enaminone and N,O-donor ligands: synthesis, characterization and biological assessment

This study extensively describes the synthesizing and characterizing of new β-enaminone complexes derived from dimedone and amines coordinated with transition metals Fe(II), Co(II), Ni(II), and Cu(II), also two ligand's metformin (Met) and 8-hydroxyquinoline (8-hq). These were determined via FT-IR, 1H-NMR, electron and mass spectroscopy, molar electrical conductivity, thermal analysis (TGA, DTA and DSC) and characterized by metal content determination (%), magnetic susceptibility and elemental analysis (C.H.N.) and SEM technique. The measurements indicate that the complexes have six coordination numbers, where the β-enaminone is coordinated as tetradentate ligand through the two nitrogen atoms and the two oxygen atoms beside metformin is coordinated through the two nitrogen atoms and 8-hydroxyquinoline is coordinated by oxygen and nitrogen atoms as bidentate ligands. The conductance suggests that all complexes have electrolytic behavior, being conductive in a ratio of (1:2). SEM results revealed the presence of nanostructures on sample surfaces. The biological activity of the prepared ligands and complexes are studied in different concentrations for four types of bacteria Staphylococcus aureus has (+G) and Escherichia coli, Pseudomonas aeruginosa, Klebsiella have (-G), well as, the influence of the fungus. The ligands have disparate effectiveness while complexes have high effectiveness inhibiting the bacteria and fungus. KEY WORDS: Mixed ligand systems, Dimedone, β-Enaminone ligands, Transition metals, Biological application Bull. Chem. Soc. Ethiop. 2025, 39(1), 65-78. DOI: https://dx.doi.org/10.4314/bcse.v39i1.5

Vulnerability assessment of elasmobranch species to fisheries in coastal Kenya: Implications for conservation and management policies

Ecological Risk Assessment (ERA) of species is useful for making informed management decisions based on relative vulnerability of species to fisheries. Understanding the vulnerability of species to fishing gears is important for targeted management measures especially for species known to have delicate life-history strategies such as the elasmobranchs. Productivity and Susceptibility Analysis (PSA), an ERA approach, was applied to 61 elasmobranch species (32 shark and 29 ray species) to assess their relative vulnerability (low, medium and high) to fishing by artisanal, prawn trawl and tuna longline fisheries in Kenya’s coastal waters. Overall, results showed 28 % of rays and 31 % of sharks were highly vulnerable to the fisheries, with the pelagic longline tuna fishery having the largest proportions of rays (50 %) and sharks (54 %) being highly vulnerable. Most of the species were in the medium vulnerability category. Among the artisanal gears, only gillnets had species that were highly vulnerable to the fishery, while relatively fewer species (n = 9) of both sharks and rays were highly vulnerable to the prawn trawlers compared to those in the medium vulnerability category (n = 25). Seventeen species classified as High Vulnerability Species Assemblage (HVSA), were assessed to be at high risk of overfishing by different gears, and are recommended for management as a complex. Of the HVSA group, two species; Pseudoginglymostoma brevicaudatum and Rhina ancylostoma are classified by the IUCN Red List of Threatened Species as Critically Endangered (CR), while another four; Rhinoptera jayakari, Mobula birostris, Stegostoma tigrinum and Carcharhinus plumbeus are Endangered (EN), with the rest being either Vulnerable (Gymnura poecilura, Pastinachus ater, Pateobatis jenkinsii, Taeniurops meyeni, Triaenodon obsesus, Carcharhinus falciformis, and Carcharhinus carcharias), Near Threatened (Maculabatis ambigua, Mustelus mosis, Prionace glauca) or classified as Data Deficient (Pliotrema warreni). Although majority of the species have been placed in the medium vulnerability category, some of them are those that are threatened with extinction globally, calling for a more precautionary management approach. A validation approach has been used to mitigate the problems of PSAs associated with data quality and uncertainty around estimated vulnerability indices. More robust application of PSA will require continuous updating of life-history attributes to improve on sensitivity. A precautionary Shark and Ray Management Plan (SRMP) that takes into account the outputs of the PSA is recommended for management and conservation of the elasmobranch stocks in Kenya’s marine waters.

Characterization, Antibiotic Susceptibility, and Clonal Analysis of Carbapenem-Resistant Klebsiella pneumoniae From Different Clinical Cases

Characterization, Antibiotic Susceptibility, and Clonal Analysis of Carbapenem-Resistant Klebsiella pneumoniae From Different Clinical Cases

Using Advanced InSAR Techniques and Machine Learning in Google Earth Engine (GEE) to Monitor Regional Black Soil Erosion—A Case Study of Yanshou County, Heilongjiang Province, Northeastern China

The black soil region experiences complex erosion due to natural processes and intense human activities, leading to soil degradation and adverse ecological and agricultural impacts. However, the complexities involved in quantifying regional erosion poses remarkable challenges in accurately assessing the current status of regional soil erosion for effective soil conservation. To solve this issue, we proposed a new method for monitoring soil erosion using Interferometric synthetic aperture radar (InSAR) technology and machine learning algorithms within the Google Earth Engine platform. The new method not only enables regional-scale monitoring, but also ensures high accuracy in measurement (millimeter-level). The erosion susceptibility of the study area (Yanshou County, Heilongjiang Province, Northeastern China) was also classified using random forest algorithms to refine the monitored and predicted soil erosion. The results indicate that the five-year (2016–2021) deformation in Yanshou County was −11.08 mm, with a significant mean cumulative deformation of −8.08 mm yr−1 occurring in 2017. The driving factor analysis shows that the region was subject to the compound effect of water and freeze–thaw erosion, closely related to crop phenological stages. The susceptibility analysis indicates that 73.3% of the region was susceptible to erosion, with a higher probability in river areas, at high altitudes, and on steep slopes. However, good vegetation cover can reduce the risk of soil erosion to some extent. This study offers a new perspective on monitoring regional soil erosion in the black soil region of China. The proposed method holds potential for future expansion to monitor soil erosion in a larger areas, thereby guiding the strategies development for protection of the agriculturally important black soil.

Structures and properties of the late pleistocene paleosols of the loess-soil section of Obi-Mazar (Tajikistan)

The loess-soil series of Central Asia cover the history of subaerial sedimentation of the last 2–2.5 mln years. Significant thicknesses, a large number of paleosols, and an impressive chronology place the loess-soil series of the Afghan-Tajik depression on a par with the famous sections of the Loess Plateau of China. The study of the most significant sections located within the Khovaling Loess Plateau makes it possible to develop a regional chronostratigraphic chart, to study the structure and conditions of formation of the main stratigraphic benchmarks–buried paleosols. The present study is devoted to the clarification of the structural features of loess and paleosols of the Late Pleistocene in one of the sections of the Khovaling–Obi-Mazar Plateau. Based on the results of stratigraphic dissection, description of the macro- and micromorphological structure, magnetic susceptibility analysis, study of the chemical and granulometric composition, a comprehensive description of the structure and properties was carried out and the most probable conditions for the formation of paleosols and loess were established. In the Late Pleistocene part of the section, two loess layers and a pedocomplex PC1 with three welded paleosols, consisting of a total of 7 horizons, are distinguished. The deposits are characterized by high silt content, carbon content, and the presence of signs of pedogenesis and biological activity in all layers of the studied section. Available data indicate the presence of a poorly developed MIS 3 paleosol in the upper loess layer. The developed pedocomplex PC1 of Obi-Mazar, according to its stratigraphic position, structural features, and magnetic susceptibility data, belongs to the MIS 5. According to preliminary data, its formation occurred in semi-humid and humid conditions under forest vegetation, which contributed to the biogenic segregation of Fe-Mn compounds, as well as intra- and interhorizon redistribution of carbonates due to diagenetic processes. Towards the end of the Last Interglacial, gradual aridization occurred, due to which the upper paleosol to be the least developed.

Evaluation of Potential Flood Areas in the Basin of Lake Ladik through AHP and GIS Integration, (Samsun, Türkiye)

Floods are a problem of many countries on a global scale. In Türkiye, especially in the summer months, large floods occur in the Black Sea Region coastal belt. The number and the destructive power of experienced floods are increasing day by day. It is not possible to prevent the occurrence of floods. But it is possible to take the necessary measures to prevent it from turning into a disaster. Recently, susceptibility analyses have been carried out for floods and similar natural disasters and the results help decision-makers. Within the scope of this study, flood susceptibility analysis was carried out by using multiple geographical factors together in the Basin of Lake Ladik of Samsun Province in the Black Sea Region. In the study, Analytical Hierarchy Process (AHP), Geographic Information Systems (GIS) and Remote Sensing (RS) techniques were used, which are multi-criteria decision-making methods. In this context, flood susceptibility analysis of the basin was carried out by using nine (9) different geographical factors (slope, aspect, lithology, soil, basin size, land use, landforms, precipitation, and drainage density). As a result of the study, for floods, there were identified four (4) different levels as low, medium, high, and very high; and 36.77% of the basin was found to be low, 30.03% was medium, 11.43% was high and 21.77% was found to be sensitive to possible floods at a very high level. The results of the study are also important for decision-makers to make flood risk planning.

Dual-modal detection of antimicrobial susceptibility in pathogenic bacteria based on the high-throughput microfluidic platform

For pathogenic bacterial infectious diseases such as sepsis, accurate and rapid antimicrobial susceptibility testing (AST) plays an important role in improving antimicrobial screening and clinical outcomes. Traditional culture-based AST assays have the limitations of time-consuming, labor-intensive, expensive, and consuming reagents. In this work, a simple, fast, high-throughput microfluidic platform integrated with isolation, identification, and detection functions was designed for antibiotic susceptibility analysis in pathogenic bacteria. For the above purpose, MnO2@ZIF-90 nanoprobes with dual functions of nanozyme and fluorescence were prepared for visual eye or RGB analysis through a smartphone APP. More importantly, the redox activity of bacterial membrane in active pathogenic bacteria could decompose the MnO2 of MnO2@ZIF-90 nanoprobes and reduce the enzyme-like activity, which weakens the colorimetric signal of Timebox. Meanwhile, the ATP released from active pathogenic bacteria further triggered the breakdown of the inner ZIF-90 layer, generating a fluorescence signal. Therefore, a dual detection combining colorimetric and fluorescence was used to perform more accurate and reliable antibiotic susceptibility analysis of pathogenic bacteria. With the proposed microfluidic platform, a low detection of 10 CFU mL−1 bacteria and fast AST results were achieved within 5 min. The clinical applicability of the platform was further demonstrated through the analysis of clinical samples. This work provides a low-cost, easy-to-operation, fast-response, and high-throughput platform for the AST assays in pathogenic bacterial infectious diseases such as sepsis.

Enhancing antimicrobial management: A 5–year retrospective analysis of urinary pathogen susceptibility at a tertiary care centre from January 2018 to December 2022

Objective: The study aims to collect data on prevalence and antibiotic susceptibility patterns of uropathogens in a hospital in India, and to analyze any changes that have occurred over the past 5 years. Methods: This retrospective study was conducted over 5 years at Lady Hardinge Medical College &amp; Associated Hospitals, New Delhi. Urine samples from patients who attended outpatient department or were admitted with diagnosis of urinary tract infection (UTI) were included in this study. Samples were cultured and tested to identify bacteria and determine antibiotic susceptibility using the Kirby-Bauer disc diffusion method. Results: A total of number of 151395 urine specimens were collected from January 2018 to December 2022. The prevalence of UTI was 7.5% (11372/151395) with the majority of patients being aged above 40 years (19.3%). The prevalence was higher in females (12.7%) as compared to males (3.2%). Escherichia (E.) coli was the predominant pathogen, accounting for 59.8% of cases, followed by Klebsiella spp. at 18.9%, and Enterococcus spp. at 8.3%. Gram-negative bacteria accounted for 89.5% of the isolates and exhibited good susceptibility to aminoglycosides and piperacillin-tazobactam, but showed resistance to fluoroquinolones. Methicillin-resistant Staphylococcus aureus (MRSA) was present in 35% of Staphylococcus (S.) aureus isolates with high susceptibility to glycopeptides and nitrofurantoin. Conclusions: The data suggest the need for careful selection of empirical therapy due to increasing resistance patterns. The stringent use of antimicrobial agents is pivotal to the control of antimicrobial resistance. Antibiotic susceptibility data contributes to tailoring the antibiotic stewardship programs to local needs.

Detecting shallow landslides – Susceptibility analysis on ÖBB lines

Detecting shallow landslides – Susceptibility analysis on ÖBB lines

Landslide risk assessment in mining areas using hybrid machine learning methods under fuzzy environment

Landslide risk assessment in coal mining economic cities faces challenges due to inadequate knowledge of indicator systems and modeling techniques, despite its crucial significance in geological disaster management. This study addresses this gap by proposing a novel framework encompassing data preparation, susceptibility analysis, consequence analysis, and final risk assessment. The primary objective is to reduce the complexity and inherent uncertainties associated with landslide risk assessment in these specific urban environments. First, two comprehensive databases for the indication system were established. One database focuses on landslide susceptibility, considering the region’s mining disturbances and disaster-prone environments. The other evaluates the effect of consequences while accounting for the pertinent risk variables. Second, a hybrid machine learning model called Geo-FR-SVM was developed by combining the GeoDetector, Frequency Ratio method, and Support Vector Machine model to improve landslide susceptibility mapping. Integrating the susceptibility map with the consequence map created using fuzzy set theory and fuzzy analytical hierarchy process methodologies resulted in the final landslide risk map. Our analysis revealed that elevation, distance to rivers and roads, groundwater level, and coal mining subsidence were the key factors influencing landslide occurrence in the Xishan mine area. The majority of the study area exhibits low landslide risk. However, higher consequence zones were primarily concentrated in highly populated residential regions and coal mine industrial zones in the east-central and western urban areas. Additionally, they are mainly distributed along the roads in the center region. With comparatively large percentages of landslide high-risk and extremely high-risk regions (4.596%, 3.855%, 3.625%, and 3.188%, respectively) at Tunlan Mine, Xiqu Mine, Zhenchengdi Mine, and Baijiazhuang Mine, these findings highlight the need for these mines to prioritize potential landslide identification and risk mitigation strategies. This framework offers broad applicability to other coal mining economic cities, serving as a valuable foundation for landslide risk management decision-making.

Integrated Magnetic and Geochemical Assessment of the Soil from the Steam Power Plant Area of South Kalimantan Province

Abstract The magnetic proxy approach has proven to be efficient in the assessment of pollution by potentially toxic elements when targeting soils or areas with a homogeneous background where anthropogenic magnetic signals can be easily distinguished. It’s crucial to conduct research on the impact of fly ash on the vicinity of the PLTU in this particular area, as it’s a previously unexplored area. The unique thing about this research is that this PLTU uses coal containing Fe, Pb, and Mg as fuel and has a fairly high susceptibility value for fly ash and bottom ash. This study is due to an analysis of the magnetic susceptibility and heavy metal content in the soil of the area around the Asam-Asam steam power plant (PLTU) of South Kalimantan Province, where geogenic input and fly ash can influence it. Heavy metals that have passed the threshold at all locations are Ti, Cr, Mn, Fe, Ni, Cu, V, and Al. Most of the correlation coefficients are strong and significant between magnetic susceptibility values and heavy metal concentrations at each location. The correspondence between magnetic susceptibility values and heavy metal content reflects the potential of magnetic proxy methods at polluted spots, provided that the lithological conditions are carefully considered.

Geospatial Intelligence for Landslide Susceptibility and Risk Analysis: Insights from NH31A and East Sikkim Himalaya Settlements

Slope instability is a serious concern in the Sikkim Himalayas. The town and numerous road segments along National Highway 31A were ravaged by multiple landslides that occurred in the nearby region. A bivariate statistical method known as frequency ratio (FR), information value (IV), and certainty factor (CF) analysis was employed in this work to examine landslide risk assessment (LRA) and landslide susceptibility zonation (LSZ) maps in the Rorachu watershed. This study represents the first comprehensive analysis of landslide risk in the populated areas of East Sikkim and along NH31A, offering a deeper understanding of the risks involved and contributing to the enhancement of local resilience against landslide hazards. A total of 153 different landslide locations were mapped using Google Earth and GIS software; 30% (46) of these locations were used to validate the models, and 70% of these (107) served as training data for the FR, IV, and CF models. The thirteen landslide causative factors (geology, soil, elevations, slope, curvature, drainage density (DD), road density (RD), rainfall, normalized difference vegetation index (NDVI), land use land cover (LULC), topographic position index (TPI), stream power index (SPI), and topographic wetness index (TWI)) were extracted from a spatial database for LSZ mapping. Landslides were most prevalent on slopes (35° to 50°), heights (2,500–4,100 m), and rainfall (2000–2,500 mm and 3,000–3,300 mm). The area under the curves (AUC) for the FR, IV, and CF models are 0.925 (92.50%), 0.846 (84.60%), and 0.868 (86.20%), respectively. The prediction rates are shown by the AUCs for the FR, IV, and CF models, which are 0.828 (82.8%), 0.750 (%), and 0.836 (83.60%), respectively. According to the landslide risk assessment (LRA), the FR (20.75%), IV (40.91%) and CF (18.78%) models showed high risk on Highway 31A, while the FR (9.05%), IV (38.59%) and CF (20.90%) models showed high risk in densely populated areas. These landslide risk and vulnerability maps can be used to develop land use planning strategies that can save lives and are useful for planners and mitigation measures. Special attention should be paid to urbanization, highway construction, and deforestation.

Hierarchical Genomic Analysis of Susceptibility to Schizophrenia in Sudanese multi-case families

Background Schizophrenia, with its diverse and complex presentation, is a prime candidate for genetic investigation. Its heritability in both familial and sporadic cases, clinical overlap with other psychiatric conditions, and individual variations in response to treatment contribute to its complexity. Numerous genes and associated biochemical pathways show significant differences at the population, familial, and individual levels. Additionally, schizophrenia may represent an evolutionary trade-off for human brain development, creativity, and intellectual performance. Material and Methods This case pseudo-control study analyzed the whole genomes/exomes of seven Sudanese families with multiple siblings affected by schizophrenia. We examined shared variants among family members, including both cases and controls, and unique variants shared between patients but not controls. These variants were filtered based on their impact on protein function, expression levels, allele frequencies, ACMG classification for rare variants, and disease associations. Networks were created to identify central genes and common biological pathways. Results and Discussion The examination of this complex disorder in Sudanese families revealed numerous variants, both common and rare, showing differences between families and between our population and those reported in the literature. This highlights the challenge of accounting for the known heritability of the disease. Our hierarchical approach demonstrates that schizophrenia’s etiology involves the cumulative effect of various interacting variants in an ascending order of influence. Common variants are shared among all samples, while rare variants are shared among two or three families, most of which are associated with schizophrenia. In conclusion The significance lies not merely in the number of detected variants but in understanding their interactive roles, step by step, to reveal the complete picture of the disease’s phenotype.