Search Results (10)

Background/Objectives: Education on antibiotic use has the potential to positively shape the practices and perspectives of future professionals. Assessing awareness levels of antibiotic resistance among university students is, therefore, critical, as they represent a vital demographic capable of influencing public health outcomes, especially in low- and middle-income countries. Methods: This cross-sectional study employed the World Health Organization’s Antibiotic Resistance: Multi-Country Public Awareness Survey, which examines demographics, antibiotic use, knowledge, perspectives, and sources of information. A total of 922 surveys were collected from students across various disciplines at two universities in Greater Guayaquil. Results: Most participants reported obtaining antibiotics through healthcare professionals, adhering to proper usage instructions, and purchasing them primarily from pharmacies. However, only 56% of the responses were correct, with many students incorrectly associating antibiotic use with conditions where they are typically ineffective. Despite these gaps, the students expressed positive attitudes toward proposed measures to address antibiotic resistance. While the participants demonstrated familiarity with terms related to antibiotic resistance and identified doctors and educators as their main sources of information, educational campaigns were not widely recognized as important. Conclusions: These findings evidence knowledge gaps among an essential group, suggesting the need for targeted health programs, preventive strategies, and educational initiatives to combat misinformation regarding antimicrobial resistance. Full article

To investigate the changes in the composition and structure of the dissolved organic matter (DOM) of the lysate solutions of different types of soil after green manure tilling treatment, we set up two types of soil materials (fluvo-aquic soil; coastal saline soil) and three green manure tilling treatments (T1: CK—without green manure, T2: tilling Dongmu70 rye, and T3: tilling rapeseed green manure); then, the soil leachate was obtained with a soil column simulation test and its DOM spectral properties were determined. The rapeseed green manure leachate demonstrated a significantly higher humic macromolecule content and aromaticity compared to Dongmu70 rye leachate. Fluorescence Index (FI) values (1.5–2.2) suggest a mixed origin of dissolved organic matter (DOM) from both terrestrial and microbial-derived sources. All Humification Index (HIX) values remained below 1, indicating low humification levels and limited stabilization of DOM within the leachate system, and Biological Index (BIX) values exceeding 1 across all soil layers highlight the predominance of a recent biological metabolism in shaping DOM autochthonous origins. The SUVA₂₆₀ values in Dongmu70 rye–moist soils and rapeseed green manure–coastal saline soil exhibited reductions of 0.020–2.573 L·(mg·m)⁻¹ relative to pre-drenching levels. After tilling rapeseed green manure, the SUVA₂₅₄ value of coastal saline soil at the 60–90 cm layer decreased by 1.941 L·(mg·m)⁻¹. This study shows that differences in green manure and soil type affect DOM sources and composition, reducing DOM leaching, with coastal saline soil + rapeseed green manure and fluvo-aquic soil + Dongmu70 rye being the advantageous combinations. The study results provide theoretical guidance for applying green manure coupled with freshwater leaching technology in the context of saline and alkaline land with multiple soil types. Full article

Storm events have a notable impact on natural organic matter (NOM) and trihalomethanes (THMs). Water samples were collected and analyzed from Ulutan Dam (UD), in the Zonguldak region, Turkey. During four storm events, the data indicated the presence of hysteresis patterns in three of the four storms, with elevated concentrations of organic constituents observed during the falling limb of the hydrographs. It was observed that a higher specific THM (sp.THM) concentration (201.83 µg/L) was reached with an average specific UV absorbance (SUVA) value of 6.66 L/mg·m in the fourth storm. This means that the primary sources of THM precursors are the aromatic compounds present in NOM. A significant correlation between UV absorbance (UV₂₅₄) and dissolved organic carbon (DOC) (R = 0.99–0.92) for all storms was observed. Chlorine demand also yielded a strong correlation (R = 0.81–0.99) with UV₂₅₄ and DOC. Therefore, the present study indicates that UV₂₅₄ can be an effective parameter for monitoring applicable chlorine dosage in drinking water treatment management as faced with storm events. On the other hand, the results of the study also provide valuable insight into the direct and indirect link between short-term precipitation events and their impact on the structural and THM precursors in surface water sources. Full article

In order to effectively improve the dim and small target detection ability of photoelectric detection system to solve the high false rate issue under complex clouds scene in background modeling, a novelty Hessian matrix and F-norm collaborative filtering is proposed in this paper. Considering the influence of edge noise, we propose an improved Hessian matrix background modeling (IHMM) algorithm, where a local saliency function for adaptive representation of the local gradient difference between the target and background region is constructed to suppress the background and preserve the target. Because the target energy is still weak after the background modeling, a new local multi-scale gradient maximum (LMGM) energy-enhancement model is constructed to enhance the target signal, and with the help of LMGM, the target’s energy significant growth and the target’s recognition are clearer. Thus, based on the above preprocessing, using the motion correlation of the target between frames, this paper proposes an innovative collaborative filtering model combining F-norm and Pasteur coefficient (FNPC) to obtain the real target in sequence images. In this paper, we selected six scenes of the target size of 2 × 2 to 3 × 3 and with complex clouds and ground edge contour to finish experimental verification. By comparing with 10 algorithms, the background modeling indicators SSIM, SNR, and IC of the IHMM model are greater than 0.9999, 47.4750 dB, and 12.1008 dB, respectively. In addition, the target energy-enhancement effect of LMGM model reaches 17.9850 dB in six scenes, and when the false alarm rate is 0.01%, the detection rate of the FNPC model reaches 100% in all scenes. It shows that the algorithm proposed in this paper has excellent performance in dim and small target detection. Full article

Cells respond to genome damage by inducing restorative programs, typified by the SOS response of Escherichia coli. Streptococcus pneumoniae (the pneumococcus), with no equivalent to the SOS system, induces the genetic program of competence in response to many types of stress, including genotoxic drugs. The pneumococcal competence regulon is controlled by the origin-proximal, auto-inducible comCDE operon. It was previously proposed that replication stress induces competence through continued initiation of replication in cells with arrested forks, thereby increasing the relative comCDE gene dosage and expression and accelerating the onset of competence. We have further investigated competence induction by genome stress. We find that absence of RecA recombinase stimulates competence induction, in contrast to SOS response, and that double-strand break repair (RexB) and gap repair (RecO, RecR) initiation effectors confer a similar effect, implying that recombinational repair removes competence induction signals. Failure of replication forks provoked by titrating PolC polymerase with the base analogue HPUra, over-supplying DnaA initiator, or under-supplying DnaE polymerase or DnaC helicase stimulated competence induction. This induction was not correlated with concurrent changes in origin-proximal gene dosage. Our results point to arrested and unrepaired replication forks, rather than increased comCDE dosage, as a basic trigger of pneumococcal competence. Full article

Despite its wide applications, the spatiotemporal fusion of coarse- and fine-resolution satellite images is limited primarily to the availability of clear-sky fine-resolution images, which are commonly scarce due to unfavorable weather, and such a limitation might cause errors in spatiotemporal fusion. Thus, the effective use of limited fine-resolution images, while critical, remains challenging. To address this issue, in this paper we propose a new phenological similarity strategy (PSS) to select the optimal combination of image pairs for a prediction date. The PSS considers the temporal proximity and phenological similarity between the base and prediction images and computes a weight for identifying the optimal combination of image pairs. Using the PSS, we further evaluate the influence of input data on the fusion accuracy by varying the number and temporal distribution of input images. The results show that the PSS (mean R = 0.827 and 0.760) outperforms the nearest date (mean R = 0.786 and 0.742) and highest correlation (mean R = 0.821 and 0.727) strategies in both the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) and the linear mixing growth model (LMGM), respectively, for fusing Landsat 8 OLI and MODIS NDVI datasets. Furthermore, base images adequately covering different growth stages yield better predictability than simply increasing the number of base images. Full article

The normalized difference vegetation index (NDVI) is a powerful tool for understanding past vegetation, monitoring the current state, and predicting its future. Due to technological and budget limitations, the existing global NDVI time-series data cannot simultaneously meet the needs of high spatial and temporal resolution. This study proposes a high spatiotemporal resolution NDVI fusion model based on histogram clustering (NDVI_FMHC), which uses a new spatiotemporal fusion framework to predict phenological and shape changes. Meanwhile, this model also uses four strategies to reduce error, including the construction of an overdetermined linear mixed model, multiscale prediction, residual distribution, and Gaussian filtering. Five groups of real MODIS_NDVI and Landsat_NDVI datasets were used to verify the predictive performance of the NDVI_FMHC. The results indicate that NDVI_FMHC has higher accuracy and robustness in forest areas (r = 0.9488 and ADD = 0.0229) and cultivated land areas (r = 0.9493 and ADD = 0.0605), while the prediction effect is relatively weak in areas subject to shape changes, such as flooded areas (r = 0.8450 and ADD = 0.0968), urban areas (r = 0.8855 and ADD = 0.0756), and fire areas (r = 0.8417 and ADD = 0.0749). Compared with ESTARFM, NDVI_LMGM, and FSDAF, NDVI_FMHC has the highest prediction accuracy, the best spatial detail retention, and the strongest ability to capture shape changes. Therefore, the NDVI_FMHC can obtain NDVI time-series data with high spatiotemporal resolution, which can be used to realize long-term land surface dynamic process research in a complex environment. Full article

Multidrug resistance (MDR) often results from the acquisition of mobile genetic elements (MGEs) that encode MDR gene(s), such as conjugative plasmids. The spread of MDR plasmids is founded on their ability of horizontal transference, as well as their faithful inheritance in progeny cells. Here, we investigated the genetic factors involved in the prevalence of the IncI conjugative plasmid pESBL, which was isolated from the Escherichia coli O104:H4 outbreak strain in Germany in 2011. Using transposon-insertion sequencing, we identified the pESBL partitioning locus (par). Genetic, biochemical and microscopic approaches allowed pESBL to be characterized as a new member of the Type Ib partitioning system. Inactivation of par caused mis-segregation of pESBL followed by post-segregational killing (PSK), resulting in a great fitness disadvantage but apparent plasmid stability in the population of viable cells. We constructed a variety of pESBL derivatives with different combinations of mutations in par, conjugational transfer (oriT) and pnd toxin-antitoxin (TA) genes. Only the triple mutant exhibited plasmid-free cells in viable cell populations. Time-lapse tracking of plasmid dynamics in microfluidics indicated that inactivation of pnd improved the survival of plasmid-free cells and allowed oriT-dependent re-acquisition of the plasmid. Altogether, the three factors—active partitioning, toxin-antitoxin and conjugational transfer—are all involved in the prevalence of pESBL in the E. coli population. Full article

Due to technical limitations, it is impossible to have high resolution in both spatial and temporal dimensions for current NDVI datasets. Therefore, several methods are developed to produce high resolution (spatial and temporal) NDVI time-series datasets, which face some limitations including high computation loads and unreasonable assumptions. In this study, an unmixing-based method, NDVI Linear Mixing Growth Model (NDVI-LMGM), is proposed to achieve the goal of accurately and efficiently blending MODIS NDVI time-series data and multi-temporal Landsat TM/ETM+ images. This method firstly unmixes the NDVI temporal changes in MODIS time-series to different land cover types and then uses unmixed NDVI temporal changes to predict Landsat-like NDVI dataset. The test over a forest site shows high accuracy (average difference: −0.0070; average absolute difference: 0.0228; and average absolute relative difference: 4.02%) and computation efficiency of NDVI-LMGM (31 seconds using a personal computer). Experiments over more complex landscape and long-term time-series demonstrated that NDVI-LMGM performs well in each stage of vegetation growing season and is robust in regions with contrasting spatial and spatial variations. Comparisons between NDVI-LMGM and current methods (i.e., Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), Enhanced STARFM (ESTARFM) and Weighted Linear Model (WLM)) show that NDVI-LMGM is more accurate and efficient than current methods. The proposed method will benefit land surface process research, which requires a dense NDVI time-series dataset with high spatial resolution. Full article

The hallmark of Mycobacterium tuberculosis is its ability to persist for a long-term in host granulomas, in a non-replicating and drug-tolerant state, and later awaken to cause disease. To date, the cellular factors and the molecular mechanisms that mediate entry into the persistence phase are poorly understood. Remarkably, M. tuberculosis possesses a very high number of toxin-antitoxin (TA) systems in its chromosome, 79 in total, regrouping both well-known (68) and novel (11) families, with some of them being strongly induced in drug-tolerant persisters. In agreement with the capacity of stress-responsive TA systems to generate persisters in other bacteria, it has been proposed that activation of TA systems in M. tuberculosis could contribute to its pathogenesis. Herein, we review the current knowledge on the multiple TA families present in this bacterium, their mechanism, and their potential role in physiology and virulence. Full article