Assessment Of Susceptibility Research Articles

Chemoproteogenomic stratification of the missense variant cysteinome

Cancer genomes are rife with genetic variants; one key outcome of this variation is widespread gain-of-cysteine mutations. These acquired cysteines can be both driver mutations and sites targeted by precision therapies. However, despite their ubiquity, nearly all acquired cysteines remain unidentified via chemoproteomics; identification is a critical step to enable functional analysis, including assessment of potential druggability and susceptibility to oxidation. Here, we pair cysteine chemoproteomics—a technique that enables proteome-wide pinpointing of functional, redox sensitive, and potentially druggable residues—with genomics to reveal the hidden landscape of cysteine genetic variation. Our chemoproteogenomics platform integrates chemoproteomic, whole exome, and RNA-seq data, with a customized two-stage false discovery rate (FDR) error controlled proteomic search, which is further enhanced with a user-friendly FragPipe interface. Chemoproteogenomics analysis reveals that cysteine acquisition is a ubiquitous feature of both healthy and cancer genomes that is further elevated in the context of decreased DNA repair. Reference cysteines proximal to missense variants are also found to be pervasive, supporting heretofore untapped opportunities for variant-specific chemical probe development campaigns. As chemoproteogenomics is further distinguished by sample-matched combinatorial variant databases and is compatible with redox proteomics and small molecule screening, we expect widespread utility in guiding proteoform-specific biology and therapeutic discovery.

Assessing the Efficacy of Chlorhexidine in Combating Most Important Causative Agents of Fungal Keratitis: An in Vitro Comparative Study With Seven Antifungal Agents

Purpose Fungal keratitis (FK) is a difficult condition to treat, particularly in underdeveloped nations. The study aimed to compare the in vitro activity of chlorhexidine (CHX) and seven antifungal agents against a collection of fungi recovered from FK patients. Methods Seventy-three fungi were collected from patients with FK included in study. The antifungal agents tested were fluconazole, voriconazole, posaconazole, miconazole, natamycin, amphotericin B, and caspofungin. The concentration range for CHX was 1–1024 μg/mL. Assessments of antifungal susceptibility were conducted using the EUCAST broth microdilution reference method. Results The findings demonstrated the beneficial in vitro inhibition of filamentous and yeast fungi by CHX. CHX demonstrated efficacy against Fusarium spp., Aspergillus spp., Candida spp., S. apiospermum and dematiceous fungi at concentrations of 4–64, 32–64, 4–32, 8, and 4–16 µg/mL respectively. The median MICs and MIC distributions of CHX showed no significant differences among the evaluated spp. (p > 0.05). The most effective antifungal drug was posaconazole, which was followed by voriconazole, caspofungin, and amphotericin B. Conclusion In situations where access to a range of antifungal medications and microbiological facilities is limited, CHX should be further investigated as a potential treatment for FK. It might be able to treat the condition as an inexpensive topical treatment.

Assessment of land degradation susceptibility within the Shaqlawa subregion of Northern Iraq-Kurdistan Region via synergistic application of remotely acquired datasets and advanced predictive models.

Land degradation (LD) is the decline in a land's functional capacity and productive potential, which includes various anthropogenic and natural drivers. This study focuses on three primary manifestations of LD including soil erosion, landslides, and rockfalls, which are the most prevalent in the Shaqlawa district. A set of 22 LD conditioning factors, encompassing curvature, lithology, aspect, river density, soil type, lineament density, river distance, elevation, road distance, length slope (LS), land use land cover (LULC), stream power index (SPI), valley depth, profile curvature, slope, solar radiation, road density, lineament distance, rainfall, topographic wetness index (TWI), plan curvature, and normalized difference vegetation index (NDVI), were integrated into the analysis. Variance inflation factors (VIF) and tolerance (TOL) values from linear regression indicate that most LD factors have acceptable levels of multicollinearity. The Information Gain Ratio (IGR) identified key variables TWI, NDVI, and lithology-as pivotal factors for predicting LD. Additionally, the study evaluated degradation factors using various machine learning (ML) algorithms, including random forest (RF), Naive Bayes, logistic regression, rotation forest, forest penalized attributes (FPA), and Fisher's Linear discriminant analysis (FLDA). This facilitated categorizing the study area into five susceptibility categories. The FLDA model categorized the highest area under very high degradation risk at 26.72%, emphasizing the varied insights each algorithm brought to characterizing the degradation risk. Additionally, the receiver operating characteristic curves (ROC) were employed for model validation, identifying RF as the most successful model in the training dataset with an area under the curve (AUC) of 0.882, while FLDA outperformed in the testing dataset with an AUC of 0.883. The identified LD-prone areas will help land-use planners and emergency management officials apply effective mitigation strategies for similar terrains.

Prevalence of extended-spectrum β-lactamase-producing Enterobacterales and carbapenemase-resistant Enterobacterales in British military cohorts

IntroductionTravel to resource-limited settings is a known risk for acquisition of extended-spectrum β-lactamase-producing Enterobacterales (ESBL-PE) and carbapenem-resistant Enterobacterales (CRE), which are both associated with increased morbidity and mortality. We investigated...

Curcumin Alleviates Airway Inflammation in Cough-Variant Asthmatic Rats by Modulating M1/M2 Macrophage Polarization.

With the increase of environmental pollution and atypical pathogen infections, the incidence of cough variant asthma (CVA) has been increasing annually, making it a pressing issue of the medical community. This study aims to observe the ameliorative effect of curcumin on a rat model of cough variant asthma. A rat model of cough variant asthma was induced by sensitization with ovalbumin combined with aluminum hydroxide (Al(OH)3), followed by repeated excitations. The drug was administered on the day of the initial nebulized attack, and gavage was administered for 14 d. Pathological changes in the lung tissues were observed, along with the assessment of cough susceptibility and airway resistance. The number of inflammatory cell eosinophils and leukocytes were determined in alveolar lavage fluid. Additionally, serum inflammatory factors and lung tissues Matrix Metalloproteinase-9 (MMP-9) protein were assessed. The level of M1/M2 macrophages was also detected. Following the administration of curcumin, there was reduced inflammatory infiltration, less disordered arrangement of the lung tissue, and decreased abnormal proliferation of lung tissues in cough variant asthma rats compared to the model group. Curcumin treatment led toa notable reduction in cough frequency, a significant decrease in pro-inflammatory factor concentration levels in serum and inflammatory cell counts in the alveolar lavage fluid, and a marked increase in anti-inflammatory factor levels (p < 0.05). Additionally, curcumin administration led to a significant increase in M2-type macrophage levels, while simultaneously decreasing the levels of M1-type macrophages (p < 0.05). The administration of curcumin effectively ameliorates ovalbumin-induced airway inflammation in cough-variant asthma rats. This effect is attributed to modulating macrophage polarization towards the anti-inflammatory M2 phenotype, thereby reducing airway inflammation, airway hyperresponsiveness, and lung tissue injury.

GIS-based statistical and limit equilibrium models in the assessment of slope stability and landslide susceptibility: the case study of the Aomar Miocene basin, Bouira, Algeria

GIS-based statistical and limit equilibrium models in the assessment of slope stability and landslide susceptibility: the case study of the Aomar Miocene basin, Bouira, Algeria

Genotoxicity of radiofrequency electromagnetic fields on mammalian cells in vitro: A systematic review with narrative synthesis

BackgroundOver the last decades, great concern has been raised about possible adverse effects to human health due to exposures to radiofrequency electromagnetic fields (RF-EMF, 100 kHz – 300 GHz) emitted by wireless communication technologies. In 2011 the International Agency for Research on Cancer classified RF-EMF as possibly carcinogenic to humans, highlighting that the evidence was weak and far from conclusive. Updated systematic reviews of the scientific literature on this topic are lacking, especially for mechanistic studies. ObjectivesTo perform a systematic review of the scientific literature on genotoxic effects induced by RF-EMF in in vitro experimental models. The overall aim is to assess the confidence and level of evidence of the induced effects in mammalian cell cultures. MethodsFull details regarding the eligibility criteria, information sources, and methods developed to assess risk of bias in the included study, are reported in our published protocol (Romeo et al. 2021). The databases NCBI PubMed, Web of Science, and EMF-Portal were used as information sources (last searched on 31st December 2022). In developing the systematic review, we followed the guidelines provided by the National Toxicology Program-Office of Health Assessment and Translation (NTP-OHAT), adapted to the evaluation of in vitro studies. A narrative synthesis of the body of evidence was performed by tabulating data classified according to meaningful groups (endpoints) and sub-groups (exposure parameters). This report, abstract included, conforms to the PRISMA 2020 (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines. ResultsOut of 7750 unique records identified, 159 articles were eligible for inclusion. From the extracted data, we identified 1111 experiments (defined as independent specific combinations of diverse biological and electromagnetic parameters). The large majority (80%) of experiments reviewed did not show statistically significant genotoxic effects of RF-EMF exposures, and most “positive” studies were rated as of moderate to low quality, with negative ratings in the key bias domains. A qualitative evidence appraisal was conducted at the endpoint level, and then integrated across endpoints. DiscussionTo the best of our knowledge, this is the first systematic review of the scientific literature on genotoxic effects in mammalian cell cultures in relation to RF-EMF exposure, which confirms and strengthens conclusions from previous syntheses of this specific topic thanks to the use of transparently reported methods, pre-defined inclusion criteria, and formal assessment of susceptibility to bias. Limitations of the evidence included were the frequent reporting of findings in graphical display only, and the large heterogeneity of experimental data, which precluded a meta-analysis. ConclusionsIn the assessment restricted to studies reporting a significant effect of the exposure on the outcome, we reached an overall assessment of “low” confidence in the level of evidence that RF-EMF induce genotoxic effects in mammalian cells However, 80% of experiments reviewed showed no effect of RF exposure on the large majority of endpoints, especially the irreversible ones, independently of the exposure features, level, and duration (moderate evidence of no effect). Therefore, we conclude that the analysis of the papers included in this review, although only qualitative, suggests that RF exposure does not increase the occurrence of genotoxic effects in vitro. Framework and fundingThis systematic review addresses one of the evidence streams considered in a larger systematic review of the scientific literature on the potential carcinogenicity of RF-EMF, performed by scientists from several Italian public research agencies. The project is supported by the Italian Workers’ Compensation Authority (INAIL) in the framework of the CRA with the Istituto Superiore di Sanità “BRiC 2018/06 – Scientific evidence on the carcinogenicity of electromagnetic fields”.

Susceptibility assessment of glacier-related debris flow on the southeastern Tibetan Plateau using different hybrid machine learning models

The southeastern Tibetan Plateau (SETP) is a construction area of several key infrastructure projects in China, such as the Sichuan-Tibet Railway and hydropower developments, which has historically faced the threat of glacier-related debris flows. However, a robust assessment of such debris flow susceptibility is a challenge due to the complex and variable climate, terrain and glacial environment. In this study, we used the hybrid models that combine statistical techniques (certainty factors, CF) with machine learning methods (logistic regression, LR; random forest, RF; extreme gradient boosting, XGBoost) to more accurately identify debris flow susceptible (DFS) areas. Topography, geology, and hydrological factors including glaciers and snow cover were used in these models to assess the DFS. Results show that 21 % to 42 % of the study area is very high susceptible to debris flows, particularly from Ranwu to Bomi and around Namcha Barwa. The hybrid models effectively enhance the accuracy of the DFS assessments. The CF-RF model showed the greatest improvement, with an 8.4 % increase in accuracy compared to the single model, the DFS spatial distribution of which aligns closely with field survey results. The glacial area ratio and annual snowmelt positively impact DFS accuracy, ranking 2nd and 9th in the factor importance, respectively. The results of this research could provide valuable assistance and guidance in mitigating glacier-related debris flow hazards.

Assessment of landslide susceptibility in the Himalayan state of Tripura, India, using a Multi-Model Approach

Landslides are the down slope mass movement of soil, rocks, and debris due to a natural or human activities resulting in widespread hazard events in India. The most affected areas comprise 15 percent of its landmass which includes Tripura and eleven Himalayan states and parts of the Western and Eastern Ghats in India. In Tripura, landslides cause road blockage and destruction of settlements, bringing economic and life losses in every year. Thus, this research is focused on identifying landslide susceptible zones and the significant causative factors behind landslides. Assessment of Landslide Susceptibility (LS) identifies fifteen major causative factors under five broad groups; topographic, geotechnical, hydrological, environmental, and anthropogenic. With application of Analytical Hierarchical Process (AHP), Frequency Ratio (FR), and Random Forest (RF)-based models were performed to extract landslide susceptible zonation map for Tripura. This study reveals that the successive hill ranges formed by young sedimentary lithologic formations associated with deforestation, heavy rainfall during monsoon, and anthropogenic activities (road constructions and jhumming) are the responsible geo-conditions for triggering landslides. In this study, while the AHP and FR model show only 1.95% and 11.46% confined along the hilltop of Jampui, Sakhan, and Longtarai, the RF model designated Tripura’s 30% land area as high and very high landslide susceptible zones (LSZ), predominantly over hills, foothills, and low laying undulating land (tillas). For the accuracy assessment, the ROC curve is used, which shows that RF model appears to be the maximum accurate (0.810) one, followed by FR (0.806) and AHP (0.744).

Assessment of Susceptibility of Potato (Solanum tuberosum L.) Cultivars to Root Lesion Nematode, Pratylenchus penetrans, and Disease Impact on Plant Growth and Tuber Weight

Assessment of Susceptibility of Potato (Solanum tuberosum L.) Cultivars to Root Lesion Nematode, Pratylenchus penetrans, and Disease Impact on Plant Growth and Tuber Weight

Susceptibility Screening of HIV-1 Viruses to Broadly Neutralizing Antibodies, Teropavimab and Zinlirvimab, in People with HIV-1 Suppressed by Antiretroviral Therapy

Background: HIV envelope (env) diversity may result in resistance to broadly neutralizing antibodies (bNAbs). Assessment of genotypic or phenotypic susceptibility to antiretroviral treatment is often performed in people with HIV-1 (PWH) and used for clinical trial screening for HIV-1 bNAb susceptibility. Optimal bNAb susceptibility screening methods are not yet clear. Methods: Phenotypic and genotypic analyses were conducted on 124 screening samples from a Phase 1b study of bNAbs teropavimab (3BNC117-LS) and zinlirvimab (10-1074-LS) administered with lenacapavir in virally suppressed PWH. Phenotypic analysis was conducted on integrated HIV-1 provirus and stimulated outgrowth virus, with susceptibility to bNAbs defined as 90% inhibitory concentration ≤2 μg/mL. The proviral DNA HIV env gene was genotyped using deep sequencing, and bNAb susceptibility predicted using published env amino acid signatures. Results: Proviral phenotypic results were reported for 109 of 124 samples; 75% (82/109) were susceptible to teropavimab, 65% (71/109) to zinlirvimab, and 50% (55/109) to both bNAbs. Phenotypic susceptibility of outgrowth viruses was available for 39 samples; 56% (22/39) were susceptible to teropavimab, and 64% (25/39) to zinlirvimab. Phenotypic susceptibilities correlated between these methods: teropavimab r = 0.82 (P&lt;0.0001); zinlirvimab r = 0.77 (P&lt;0.0001). Sixty-seven samples had genotypic and phenotypic data. Proviral genotypic signatures predicted proviral phenotypic susceptibility with high positive predictive value (68–86% teropavimab; 63–90% zinlirvimab). Conclusions: bNAb susceptibility was correlated among all three in-vitro assays used to determine teropavimab and zinlirvimab susceptibility in virally suppressed PWH. These findings may help refine PWH selection criteria for eligibility for future studies.

Assessment of groundwater susceptibility to contamination using GIS-based modified DRASTIC model in the Rib watershed, Upper Abay Basin, Ethiopia

ABSTRACT Groundwater is one of the most important sources of freshwater, contributing significantly for drinking and other domestic activities around the world. However, its quality is deteriorating over time due to overexploitation and anthropogenic activities. Rib watershed is located in the Tana basin (Ethiopia), is intensively cultivated and urbanizing area. Therefore, this study attempted to assess groundwater vulnerability to pollution using the GIS-based Modified DRASTIC Model. The modified DRASTIC model was selected due to it incorporates both hydrogeological parameters and anthropogenic factors for assessment. The necessary data were collected from the field, and downloaded from websites and laboratory experiments (No3 -). The results showed that more than 73.24% of the watershed is under medium to high vulnerability. Highly vulnerable areas of the watershed (22.48%) was confined to the Southern parts of the watershed (under built-up and cultivated areas). Based on single parameter sensitivity analysis, its vulnerability was highly influenced by aquifer media (24.1%), net recharge (21.75%), land use/land cover (15.1%), and depth of groundwater table (13.6%). The Modified drastic model was validated based on the observed data of nitrate concentration in groundwater. Based on the observed data of nitrate concentration, high-vulnerable areas were more contaminated than medium and low-vulnerable areas. The modified drastic index has a strong correlation with nitrate concentration with (r = 0.76) and (P < 0.043). Therefore, the result indicated that the area is vulnerable to contamination calling for appropriate groundwater management. Hence, this finding helps to plan and minimize future contamination of groundwater by considering its vulnerability before high-risk activities are allowed.

Assessment of the potential susceptibility of planktonic cells and bacterial biofilms by diosgenin

Bacterial biofilms are formed by a complex community of microorganisms, held together by a matrix that provides structural support and stability to microbial communities, making infections associated with biofilms more difficult to treat. In the face of growing research in the health area in search of antibiotics with action against biofilms, natural products present an effective alternative strategy. In this context, the aim of this study was to evaluate bacterial biofilm formation, assess the susceptibility of planktonic cells to diosgenin, and examine its efficacy on inhibiting and treating biofilms. The broth microdilution method was used to determine the Minimum Inhibitory Concentration (MIC). Six bacterial strains were tested: Staphylococcus aureus ATCC 25923, Pseudomonas aeruginosa ATCC 9027, Pseudomonas aeruginosa 24, Enterococcus faecalis INCQS 0017, Enterococcus faecalis INCQS 00018, and Enterococcus faecalis INCQS 654. The crystal violet method was employed to evaluate the potential of diosgenin in biofilm inhibition and eradication. Chlorhexidine gluconate served as a reference standard for the antibiofilm assays, along with the antibiotics norfloxacin, ampicillin, and gentamicin. MIC determination revealed that diosgenin exhibited intrinsic antimicrobial activity, with an MIC of 406 μg/mL against S. aureus ATCC 25923. The antibiofilm activity showed significant inhibition for E. faecalis 17 and moderate inhibition against E. faecalis 654 and S. aureus 25923. Furthermore, diosgenin effectively eradicated preformed biofilms of S. aureus 25923 and P. aeruginosa 9027, indicating its ability to interfere with biofilm biomass. These results suggest that diosgenin not only inhibits bacterial biofilm formation but also eradicates established biofilms, highlighting it as a promising candidate for the development of products aimed at combating bacterial biofilms.

Application of Microbiological Screening Tests in Assessment of Environmental Exposure to Antibiotics: Preliminary Studies.

Contact of aquatic microbiocenoses with antibiotics present in the environment can cause the former to develop resistance to antimicrobial drugs. Therefore, the search for methods to detect antibiotics and drug-resistant microorganisms in the environment is important. The presented paper proposes a simple procedure to assess environmental exposure to antibiotics and the presence of non-susceptible microorganisms. Medium solutions with selected antibiotics and a microbial growth indicator were applied to test plates, and were inoculated with water samples from various ecosystems. After incubation, the susceptibility of the microorganisms to antibiotics was determined and presented in chronic microbial toxic concentration (MTC) values. It was confirmed that the presented procedure enables the assessment of the antibiotic susceptibility and adaptation potential of unselected microorganisms from different aquatic ecosystems. However, the MTC values depend on the inoculum volume, the density and seasonal activity of the microorganisms, the method of inoculum preparation, and the incubation time of the test plate. The described procedure may be practically applied as a screening test to identify the presence of drug-resistant microorganisms. Additionally, it may also be suitable as a method to assess environmental exposure to antibiotics. However, prior standardisation is required before implementing this procedure in quantitative studies.

Synergistic assessment of multi-scenario urban waterlogging through data-driven decoupling analysis in high-density urban areas: A case study in Shenzhen, China

Extreme meteorological events and rapid urbanization have led to serious urban flooding problems. Characterizing spatial variations in flooding susceptibility and elucidating its driving factors are essential for preventing damages from urban pluvial flooding. However, conventional methods, limited by spatial heterogeneity and the intricate mechanisms of urban flooding, frequently demonstrated a deficiency in precision when assessing flooding susceptibility in dense urban areas. Therefore, this study proposed a novel framework for an integrated assessment of urban flood susceptibility, based on a comprehensive cascade modeling chain consisting of XGBoost, SHapley Additive exPlanations (SHAP), and Partial Dependence Plots (PDP) in combination with K-means. It aimed to recognize the specific influence of urban morphology and the spatial patterns of flooding risk agglomeration under different rainfall scenarios in high-density urban areas. The XGBoost model demonstrated enhanced accuracy and robustness relative to other three benchmark models: RF, SVR, and BPDNN. This superiority was effectively validated during both training and independent testing in Shenzhen. The results indicated that urban 3D morphology characteristics were the dominant factors for waterlogging magnitude, which occupied 46.02 % of relative contribution. Through PDP analysis, multi-staged trends highlighted critical thresholds and interactions between significant indicators like building congestion degree (BCD) and floor area ratio (FAR). Specifically, optimal intervals like BCD between 0 and 0.075 coupled with FAR values between 0.5 and 1 have the potential to substantially mitigate flooding risks. These findings emphasize the need for strategic building configuration within urban planning frameworks. In terms of the spatial-temporal assessment, a significant aggregation effect of high-risk areas that prone to prolonged duration or high-intensity rainfall scenarios emerged in the old urban districts. The approach in the present study provides quantitative insights into waterlogging adaptation strategies for sustainable urban planning and design.

An assessment of flood susceptibility using AHP and frequency ratio (FR) in the Lakhimpur district of Assam, India

An assessment of flood susceptibility using AHP and frequency ratio (FR) in the Lakhimpur district of Assam, India

An assessment of global land susceptibility to wind erosion based on deep-active learning modelling and interpretation techniques

Spatial accurate mapping of land susceptibility to wind erosion is necessary to mitigate its destructive consequences. In this research, for the first time, we developed a novel methodology based on deep learning (DL) and active learning (AL) models, their combination (e.g., recurrent neural network (RNN), RNN-AL, gated recurrent units (GRU), and GRU-AL) and three interpretation techniques (e.g., synergy matrix, SHapley Additive exPlanations (SHAP) decision plot, and accumulated local effects (ALE) plot) to map global land susceptibility to wind erosion. In this respect, 13 variables were explored as controlling factors to wind erosion, and eight of them (e.g., wind speed, topsoil carbon content, topsoil clay content, elevation, topsoil gravel fragment, precipitation, topsoil sand content and soil moisture) were selected as important factors via the Harris Hawk Optimization (HHO) feature selection algorithm. The four models were applied to map land susceptibility to wind erosion, and their performance was assessed by three measures consisting of area under of receiver operating characteristic (AUROC) curve, cumulative gain and Kolmogorov Smirnov (KS) statistic plots. The results revealed that GRU-AL model was considered as the most accurate, revealing that 38.5%, 12.6%, 10.3%, 12.5% and 26.1% of the global lands are grouped at very low, low, moderate, high and very high susceptibility classes to wind erosion hazard, respectively. Interpretation techniques were applied to interpret the contribution and impact of the eight input variables on the model’s output. Synergy plot revealed that the soil carbon content exhibited high synergy with DEM and soil moisture on the model’s predictions. ALE plot showed that soil carbon content and precipitation had negative feedback on the prediction of land susceptibility to wind erosion. Based on SHAP decision plot, soil moisture and DEM presented the highest contribution on the model’s output. Results highlighted new regions at high latitudes (southern Greenland coast, hotspots in Alaska and Siberia), which exhibited high and very high land susceptibility to wind erosion.

Geomorphological mapping for liquefaction likelihood: the Piniada Valley case study (central Greece)

Assessment of liquefaction susceptibility of sediments in alluvial plains is considered one of the first step for infrastructure planning, hazard mitigation, and land use management in seismically active regions. Subtle geomorphological features resulting from depositional processes could greatly contribute to estimating the liquefaction likelihood since they also dictate the type and distribution of sediments. Our case study is from the Piniada Valley (Greece), where widespread liquefaction phenomena were triggered by the 2021 Mw 6.3, Damasi earthquake. As we compiled a detailed geological map for the purposes of this investigation and correlated it to the spatial distribution of the earthquake-induced liquefaction phenomena, we observed that most of liquefaction surface evidence are related to point bars and abandoned river channels formed the last century. In particular, the areal liquefaction density was estimated at 60.7 and 67.1 manifestations per km2, for the point bars and abandoned channels, respectively. Following this outcome, we propose a refinement of the existing liquefaction susceptibility classifications by including point bar bodies as a distinct category, characterized by a very high susceptibility to liquefaction. In addition, we discuss the correlation between the observed liquefaction manifestations and the shallow lithofacies, sand or mud prone areas, within point bars. The outcome arisen by this research is that most of liquefaction phenomena (> 70%) occurred on the area covered by coarser materials deposited on the upstream part of high sinuosity meanders.

Multiple myeloma exosomal miRNAs suppress cGAS-STING antiviral immunity

DNA virus infection is a significant cause of morbidity and mortality in patients with multiple myeloma (MM). Monocyte dysfunction in MM patients plays a central role in infectious complications, but the precise molecular mechanism underlying the reduced resistance of monocytes to viruses in MM patients remains to be elucidated. Here, we found that MM cells were able to transfer microRNAs (miRNAs) to host monocytes/macrophages via MM cell-derived exosomes, resulting in the inhibition of innate antiviral immune responses. The screening of miRNAs enriched in exosomes derived from the bone marrow (BM) of MM patients revealed five miRNAs that negatively regulate the cGAS-STING antiviral immune response. Notably, silencing these miRNAs with antagomiRs in MM-bearing C57BL/KaLwRijHsd mice markedly reduced viral replication. These findings identify a novel mechanism whereby MM cells possess the capacity to inhibit the innate immune response of the host, thereby rendering patients susceptible to viral infection. Consequently, targeting the aberrant expression patterns of characteristic miRNAs in MM patients is a promising avenue for therapeutic intervention. Considering the miRNA score and relevant clinical factors, we formulated a practical and efficient model for the optimal assessment of susceptibility to DNA viral infection in patients with MM.

A comparison of phage susceptibility testing with two liquid high-throughput methods.

Phage therapy is a promising antibacterial strategy, especially given that drug-resistant bacterial infections are escalating worldwide. Because phages are not active against all strains of a given species, phages being considered for therapeutic use would ideally be tested against bacterial isolates from individual patients prior to administration. Standardized, clinically validated phage susceptibility testing (PST) methods are needed for assessing in vitro phage activity. This study compared two high-throughput liquid-based PST assays. The first, using the Biolog Omnilog™, assessed changes in microbial respiration leading to color changes based on a tetrazolium dye. The second, Agilent BioTek Cytation 7, assessed changes in optical density. Both used 96-well microtiter plate formats. A total of 55 diverse phages with activity against Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, Acinetobacter baumannii, or Enterococcus faecalis were studied against their respective susceptible bacterial hosts and non-susceptible controls, with susceptibility defined based on plaque assay. PST was performed by both assays in replicates, with results compared in terms of hold times (time through which bacterial growth is inhibited by phage compared to controls). Coefficients of variance and interclass correlation coefficients were used to assess inter- and intra-assay reproducibility. Based on a ≤50% coefficient of variance cutpoint, 87% of Biolog and 84% of Agilent assays were considered valid for susceptible bacteria, with 100% considered valid for non-susceptible bacteria by both systems. Using a 8 h hold time cutpoint, 100% of the results matched between the two assays. The interclass correlation coefficient showed 26% excellent agreement, 35% good agreement, and 17% moderate agreement between the two assays for susceptible isolates and 100% excellent agreement for non-susceptible isolates. Overall, the assays compared provided good/fair statistical reproducibility for the assessment of phage susceptibility.