Detection Of Rapid Changes Research Articles

Passive control and damage assessment with a pendulum tuned mass damper using mean square equations and second-order eigen-perturbation techniques

This paper proposes a novel framework for damage detection and retuning of a Pendulum Tuned Mass Damper (PTMD) addressing effects of stochasticity via mean-square equations and establishing rapid change detection. The framework was made possible via a Stochastic Differential Equation (SDE) formulation of the equations of motion considering a two degree of freedom base and structure system equipped with a PTMD. The system was assumed to be excited at the base with Gaussian white noise and the solutions were computed using a stochastic integration scheme. A Second Order Eigen-Perturbation (SOPS) estimate is used to carry out detection of sudden stiffness reduction in the base floor of the structure. Once damage is detected, mean square equations on monitored displacements were used to retune the PTMD by adapting the length of the pendulum. It was found that damage could be detected rapidly and successive retunings were able to minimize the mean square displacement of the damaged structure and stabilise it over time.

Design and Synthesis of an Azo Reductase Responsive Flavonol-Indomethacin Hybrid Used for the Diagnosis and Treatment of Colitis.

Human intestinal bacteria are the primary producers of azo reductase, and the content of azo reductase is closely associated with various intestinal diseases, including ulcerative colitis (UC). The rapid detection of changes in azo reductase levels is crucial for diagnosing and promptly intervening in UC. In this study, a therapeutic agent, FAI, specifically targeting UC, was designed and synthesized. This agent was developed by linking the anti-inflammatory drug indomethacin to flavonols with antioxidant activity via an azo bond (off-on). Breakage of the azo bond breaks results in the release of both fluorophores and drugs, achieving targeted tracing and integrated treatment effects. In vivo and in vitro fluorescence imaging experiments were used to demonstrate the potential of FAI in the diagnosis of UC, together with synergistic therapeutic effects through the release of both fluorophores and anti-inflammatory agents. Therefore, this diagnostic agent shows promise as a potential tool for diagnosing and treating UC.

Rapid safety assessment of reconstituted infant formula using electrical impedance analysis

A rapid method to assess freshness is crucial for the safe handling of reconstituted infant formula (RIF) and prevention of food-borne illnesses in infants. This study explored the use of electrical impedance measurement (EIM) at a constant frequency for real-time freshness evaluation of RIF. Initial electrical impedance of 89.16 ± 0.47 Ω decreased to 74.29 ± 0.23 Ω within 48 h at room temperature (20 °C) storage. Under temperature abuse conditions (30 °C), the electrical impedance rapidly dropped from 75.48 ± 0.52 Ω to 60.15 ± 4.76 Ω within 18 h, indicating more rapid spoilage. Notable changes in the electrical impedance were observed during temperature abuse. Empirical model analysis revealed a strong positive correlation between electrical impedance and conventional freshness parameters such as pH, protein, and microbial growth. This study demonstrates the potential of EIM for the rapid detection of freshness changes in RIF, offering valuable insights into the prevention of food-borne illnesses in infants.

A real-time oxygen uptake rate monitoring approach suitable for the antibody production process

Significant progress has been achieved in large-scale mammalian cell culture technology for biotherapeutics manufacturing over the past decades, necessitating the Process Analytical Technology (PAT) for the real-time measurement of critical quality attributes and the guidance for precise process control to ensure productivity, quality, and consistency. The Oxygen Uptake Rate (OUR) serves as a crucial indicator for characterizing the energy metabolism of mammalian cells, offering insights into cellular state and metabolism dynamics. However, current cellular OUR monitoring in antibody production depends mainly on costly gas analyzers or periodic manual sampling. Here, we introduce a novel method for in-line monitoring of cellular OUR in bioreactors based on the stationary liquid phase balance (SLPB) theory, which extends its applicability to diverse aeration and foam conditions without additional equipment or labor expenditures. We modeled the kLa of the aerated stirred bioreactor, assessed the influence of foam on liquid surfaces induced by gas sparging on oxygen transfer, and processed raw OUR data using a sliding filter. The established method was applied to monitoring the real-time OUR of Chinese Hamster Ovary (CHO) cell cultures for antibody production, demonstrating its excellent accuracy, sensitivity and readability. Aligned with the Quality by Design (QbD) concept, this real-time OUR estimation enables rapid detection of metabolic changes, revealing cellular physiology and facilitating precise feedback control in biotherapeutics manufacturing.

Role of artificial intelligence in medical radiology and imaging

Abstract Artificial intelligence (AI) is revolutionizing radiology, oncology, and other medicine and veterinary care areas. Adopting deep learning algorithms has significantly advanced image analysis and disease detection. This study explores how AI is reshaping the roles of radiologists and radiographers. It highlights its vital function in infection detection and control, as evidenced by its impact during the coronavirus disease 2019 (COVID-19) pandemic. In veterinary radiation oncology, AI supports complex contouring and treatment planning. However, while AI offers numerous advantages, its implementation must be cautiously approached. Radiologists face challenges, particularly the overwhelming volume of imaging data, which AI helps manage through artificial neural networks and machine learning (ML) algorithms—two significant innovations in this field. In veterinary radiation oncology, AI facilitates collaboration, standardization of data, and the creation of standard operating procedures. Early disease detection, enabled by AI, is essential for initiating treatments that can improve patient outcomes and prognosis. AI is crucial in analyzing large medical datasets, including imaging and clinical data, through advanced algorithms and ML techniques. In veterinary medicine, AI is key to addressing complex challenges in host–pathogen interactions, precision medicine, and predictive epidemiology. AI-powered solutions for continuous monitoring ensure that at-risk patients receive ongoing observation, enabling the rapid detection of changes in health markers. This approach is especially advantageous in managing chronic conditions, enabling proactive healthcare, and facilitating early intervention.

Comparative study of traditional and DNA-based methods for environmental impact assessment: A case study of marine aggregate extraction in the North Sea

Environmental impact assessments of marine aggregate extraction are traditionally conducted based on morphological characteristics of macrobenthos, which is time-consuming, labour-intensive and requires specific taxonomic expert knowledge. Bulk DNA metabarcoding is suggested as a promising alternative. This study compares the traditional morphological and the bulk DNA metabarcoding method to assess the impact of sand extraction activities on three sandbanks in the Belgian North Sea. Substantial differences in the detected species were observed between methods: Abundant and/or large macrobenthos species were detected by both methods, while small species or species with an exoskeleton were usually only detected by the morphological method. Taxa uniquely detected by bulk DNA metabarcoding could be explained by specimens identified at a higher taxonomic level by morphology, or by specimens with very low read numbers, probably representing species missed in the morphological sorting process, DNA traces on the specimens or false positives during PCR amplification efficiency. Despite the difference in detected species, comparable alpha and beta diversity patterns were observed by both methods, indicating that bulk DNA metabarcoding can effectively detect the overall ecological changes associated with sand extraction. We further demonstrate that bulk DNA metabarcoding reduces sample processing both in time (44 % faster) and cost (26 % cheaper) compared to the morphology-based identification. However, biomass quantification remains challenging for bulk DNA metabarcoding since of the ten most abundant genera, only two genera (Echinocardium and Ophelia) showed a significant positive correlation between biomass and read numbers. Additionally, bulk DNA metabarcoding does not provide information on life stages or size of the identified specimens. As such, our results underpin the complementary nature of both methods, wherein DNA-based analyses allow for rapid detection of community changes (as similar patterns in alpha and beta diversity and biotic index were observed), while morphology-based analyses provide additional information on e.g. secondary production (biomass) and size composition. We show how the strengths of both methods can be combined to assess the impact of sand extraction.

MicroRNA biogenesis is broadly disrupted by inhibition of the splicing factor SF3B1.

In animals, microRNA (miRNA) biogenesis begins with cotranscriptional cleavage of the primary (pri-)miRNA by the Microprocessor complex. Cotranscriptional splicing has been shown to influence Microprocessor cleavage when miRNAs are hosted in introns of protein-coding pri-miRNAs, but the impact of splicing on production of miRNAs hosted in long non-coding (lnc)RNAs is largely unknown. Here, we investigated the role of splicing in the biogenesis of miR-122, an lncRNA-hosted, highly expressed, medically important, liver-specific miRNA. We found that splicing inhibition by the SF3B1 inhibitor pladienolide B (PlaB) led to strong and rapid reduction in transcription of endogenous, but not plasmid-encoded, pri-miR-122, resulting in reduced production of mature miR-122. To allow detection of rapid changes in miRNA biogenesis despite the high stability of mature miRNAs, we used SLAMseq to globally quantify the effects of short-term splicing inhibition on miRNA synthesis. We observed an overall decrease in biogenesis of mature miRNAs following PlaB treatment. Surprisingly, miRNAs hosted in exons and introns were similarly affected. Together, this study provides new insights into the emerging role of splicing in transcription, demonstrating novel biological importance in promotion of miR-122 biogenesis from an lncRNA, and shows that SF3B1 is important for global miRNA biogenesis.

The detection of elemental content changes in electrode coating using laser-induced breakdown spectroscopy

The elemental content of battery electrode coating is prone to change due to the production technology and ambient factors. To ensure the consistent performance and safety of a lithium battery, the elemental content of the electrode coating needs to be kept strictly consistent. This study proposes an internal mixed matrix method that combines laser-induced breakdown spectroscopy and chemometric method to achieve rapid and accurate detection of elemental content changes in electrode coating. The stoichiometric ratios of analytical elements are calculated by using the spectra of laser-induced breakdown spectroscopy. The relationships between that stoichiometric ratios and the actual content of analytical elements are studied and show that they are linear. Thus, the content change of the analytical element can be determined by calculating the change of the stoichiometric ratio. The average relative errors for content changes of iron, lithium, and phosphorus are 6.43%, 2.96%, and 4.12%, respectively, and the lowest detection limits are 278.2 mg/kg, 20.5 mg/kg, and 105.4 mg/kg, respectively. Furthermore, the internal reference method is proposed to correct the effect of ambient gases and improve detection accuracy. The results are that when Fe I 372.751 nm and Fe I 373.485 nm are used as analytical lines, after correcting for the effect of ambient gases, the average relative errors of Fe content changes are reduced by 62% and 72%, respectively, and the lowest detection limits are increased by 67% and 71%, respectively.

Use of FreeStyle Libre for continuous glucose monitoring in adult horses.

To evaluate the feasibility of using the FreeStyle Libre (a continuous glucose monitoring system [CGMS]) for instantaneous continuous monitoring of interstitial glucose in adult horses and examine the applicability and accuracy of this system in horses submitted to combined glucose-insulin test (CGIT). Laboratory measurements and continuous glucose monitoring system (CGMS) readings were analyzed using a 2 × 2 factorial statistical model with repeated measures over time. This analysis assessed the effects of the test (factor 1), group (factor 2), and their interactions (test × group, test × time, and group × time). Pearson's correlation analysis was applied to blood glucose values. Mean comparisons were conducted using the t-test, and agreement between techniques was assessed via the Bland-Altman method, with a 95% confidence interval. Field study on private horse farms in association with a veterinary school. Ten healthy stallions were assigned to one of two groups based on their body condition scores (BCS). Group 1 (G1, n= 5) consisted of nonobese horses with a BCS of 5 or 6, while Group 2 (G2, n= 5) consisted of obese horses with a BCS of 7 or higher. A CGMS sensor was attached to the dorsolateral aspect of the proximal one third of each horse's neck. Laboratory blood glucose measurements and CGMS interstitial glucose readings were compared at different time points for up to 7days after sensor fixation. Obese horses were also submitted to CGIT on Day 4. A comparative analysis of glucose measurements obtained in G1 and G2 horses using the CGMS and enzymatic methods revealed significant group×time interactions (P<0.001) and time effects (P<0.001). No interactions were detected between group (P=0.45), test (P=0.62), group and test (P=0.28), or time and test (P=0.92). In G1 and G2, tests were significantly correlated (r=0.84 and P=0.00) at all time points (T0-T5). Agreement between the glucose values obtained using different methods was excellent despite a small time delay in CGMS detection of rapid changes in blood glucose. It was concluded that the CGMS can be used for indirect assessment of glycemic status (ie, based on interstitial glucose measurements) in nonobese and obese adult horses submitted to CGIT.

Effect of X-rays on Seedling Pigment, Biochemical Profile, and Molecular Variability in Astrophytum spp.

Cacti are important in agricultural economies and one of the most popular horticultural plant groups. The genus Astrophytum is one of the most valuable and desirable cacti for growers and collectors around the world. By selecting the appropriate breeding methods to induce variations in combination with modern biotechnology tools for rapid change detection, it is possible to meet the challenges of the modern world in creating new variability in plants. However, there exists a lack of research concerning the impact of ionizing radiation on cacti. The aim of the study was to assess the effects of X-rays at different doses (0 Gy—control, 15, 20, 25, and 50 Gy) on the dynamics of seed germination in vitro, changes in the color of seedlings, biochemical changes in the content of metabolites and changes at the molecular level in Astrophytum spp. ‘Purple’. A significant effect of X-rays on the induction of genetic variation was observed. Remarkably high polymorphism rates were observed, ranging from 59.09% for primer S12 to a full 100.0% for S3 and S8, as determined by the SCoT (Start-Codon-Targeted) marker. In addition, a large variation in the content of plant pigments (anthocyanins, carotenoids, chlorophyll a, and chlorophyll b) was noted. Additionally, discernible alterations in the color of the tested cactus seedlings, assessed by the RHSCC catalog, were attributed to the impact of ionizing radiation. These findings hold promise for the application of radiomutation breeding in acquiring new cactus cultivars.

Meso-aryltellurium-BODIPY-based fluorescence turn-on probe for selective, sensitive and fast glutathione sensing in HepG2 cells

Glutathione (GSH) as one most abundant thiol, acts as important roles in regulating cellular redox activities, and various diseases are closely related with its abnormal levels. Thus, monitoring intracellular GSH levels is essential for understanding cellular metabolism of many related diseases. In this work, we firstly reported a new fluorescence turn-on sensor, which was capable of selectively, sensitively and rapid sensing GSH over other thiols, especially cysteine and homocysteine in solutions and living cells. A meso-aryltellurium boron dipyrromethene (BODIPY) was firstly designed and synthesized, which showed silenced emission due to an efficient photoinduced electron transfer (PET) process from electron-rich Te to BODIPY, and then upon exposure to GSH, the meso-Te-C bond could be rapidly cleaved by the thiol group of GSH, thus resulting in an obvious fluorescence “turn-on” phenomenon through inhibition of the PET effect. This probe exhibited excellent selectivity and sensitivity towards GSH with a short response time of 2 min, showing a remarkable fluorescence enhancement observed at 541 nm with a large fluorescence quantum yield increase from nearly 0 to 0.73 upon excitation at 500 nm in PBS/CH3CN (9/1, v/v). The detection limit towards GSH was further calculated to be 1.7 nM by the linear fluorescence change at 541 nm in the GSH-concentration ranging from 0 to 4 μM. Furthermore, its sensing mechanism was validated by using mass spectrometry, confirming the rapid cleavage of the Te–C bond by GSH. Finally, cell imaging experiments demonstrated that this probe could successfully detect GSH in living cells, highlighting its potential for rapid and sensitive detection of intracellular GSH level changes. Therefore, a new meso-aryltellurium-BODIPY fluorescence turn-on sensor was firstly developed, which could selectively, sensitively and fast detect cellular GSH over other thiols based on the rapid cleavage of the meso Te–C bond.

Unsupervised land-use change detection using multi-temporal POI embedding

Rapid land-use change detection (LUCD) is pivotal for refined urban planning and management. In this paper, we investigate LUCD through learning embeddings of points of interest (POIs) from multiple temporalities. There are several prominent challenges: (1) the co-occurrence problem of multi-temporal POIs, (2) the heterogeneity of POI categorization, and (3) The lack of human-crafted labels. Therefore, multi-temporal POIs need to be aligned in the embedding space for effective LUCD. This study proposes a multi-temporal POI embedding (MT-POI2Vec) technique for LUCD in a fully unsupervised manner. In MT-POI2Vec, we first utilize random walks in POI networks to capture their single-period co-occurrence patterns; then, we leverage manifold learning to capture (1) single-period categorical semantics of POIs to enforce semantically similar POI embedding to be close and (2) cross-period categorical semantics to align multi-temporal POI embedding in a unified embedding space. We conducted experiments in Shenzhen, China, which demonstrates that the proposed method is effective. Compared with several baseline models, MT-POI2Vec can better align multi-temporal POIs and thus achieve higher performance in LUCD. In addition, our model can effectively identify areas with unchanged land use and land use changes in residential and industrial areas at a fine scale.

Two-photon fluorescence lifetime imaging microscopy of NADH metabolism in HIV-1 infected cells and tissues.

Rapid detection of microbial-induced cellular changes during the course of an infection is critical to understanding pathogenesis and immunological homeostasis. In the last two decades, fluorescence imaging has received significant attention for its ability to help characterize microbial induced cellular and tissue changes in in vitro and in vivo settings. However, most of these methods rely on the covalent conjugation of large exogenous probes and detection methods based on intensity-based imaging. Here, we report a quantitative, intrinsic, label-free, and minimally invasive method based on two-photon fluorescence lifetime (FLT) imaging microscopy (2p-FLIM) for imaging 1,4-dihydro-nicotinamide adenine dinucleotide (NADH) metabolism of virally infected cells and tissue sections. To better understand virally induced cellular and tissue changes in metabolism we have used 2p-FLIM to study differences in NADH intensity and fluorescence lifetimes in HIV-1 infected cells and tissues. Differences in NADH fluorescence lifetimes are associated with cellular changes in metabolism and changes in cellular metabolism are associated with HIV-1 infection. NADH is a critical co-enzyme and redox regulator and an essential biomarker in the metabolic processes. Label-free 2p-FLIM application and detection of NADH fluorescence using viral infection systems are in their infancy. In this study, the application of the 2p-FLIM assay and quantitative analyses of HIV-1 infected cells and tissue sections reveal increased fluorescence lifetime and higher enzyme-bound NADH fraction suggesting oxidative phosphorylation (OxPhos) compared to uninfected cells and tissues. 2p-FLIM measurements improve signal to background, fluorescence specificity, provide spatial and temporal resolution of intracellular structures, and thus, are suitable for quantitative studies of cellular functions and tissue morphology. Furthermore, 2p-FLIM allows distinguishing free and bound populations of NADH by their different fluorescence lifetimes within single infected cells. Accordingly, NADH fluorescence measurements of individual single cells should provide necessary insight into the heterogeneity of metabolic activity of infected cells. Implementing 2p-FLIM to viral infection systems measuring NADH fluorescence at the single or subcellular level within a tissue can provide visual evidence, localization, and information in a real-time diagnostic or therapeutic metabolic workflow.

Prenatal Detection of Rapid Progressive Changes in Massive Lymphangioma from Flank to the Lower Extremity.

Lymphangioma is a congenital anomaly in which abnormal lymphatic drainages localize to form a benign mass, but it has the tendency to grow in size and the potential to infiltrate surrounding structures, causing devastating effects and leading to severe morbidity. The most common site of lymphangioma is the neck region (cystic hygroma colli), whereas lymphangioma in the lower limbs is very rare, accounting for only 2% of cases. Accordingly, the prenatal diagnosis of lymphangioma of the lower limbs has been scarcely reported. This study describes two cases of lymphangioma of the lower limbs, focusing on unique sonographic features and the natural course of rapidly progressive changes, which is different from nuchal lymphangioma. Based on previous isolated case reports together with our two cases, lymphangioma of the lower limbs usually develops in the second trimester, tends to have rapidly progressive changes, and is unlikely to be associated with aneuploidy and structural anomalies. Diagnoses can be made by using sonographic findings pertaining to the subcutaneous complex and multi-septate anechoic cystic lesions in the lower limbs, the latter of which can infiltrate visceral structures. Prenatal detection can be helpful in laying the groundwork for providing counseling to the parents and the planning of management strategies, i.e., opting to terminate the pregnancy, revising delivery plans, and looking towards the postnatal management of the infant.

Biophysical, Biochemical, and Photochemical Analyses Using Reflectance Hyperspectroscopy and Chlorophyll a Fluorescence Kinetics in Variegated Leaves.

The adjustments that occur during photosynthesis are correlated with morphological, biochemical, and photochemical changes during leaf development. Therefore, monitoring leaves, especially when pigment accumulation occurs, is crucial for monitoring organelles, cells, tissue, and whole-plant levels. However, accurately measuring these changes can be challenging. Thus, this study tests three hypotheses, whereby reflectance hyperspectroscopy and chlorophyll a fluorescence kinetics analyses can improve our understanding of the photosynthetic process in Codiaeum variegatum (L.) A. Juss, a plant with variegated leaves and different pigments. The analyses include morphological and pigment profiling, hyperspectral data, chlorophyll a fluorescence curves, and multivariate analyses using 23 JIP test parameters and 34 different vegetation indexes. The results show that photochemical reflectance index (PRI) is a useful vegetation index (VI) for monitoring biochemical and photochemical changes in leaves, as it strongly correlates with chlorophyll and nonphotochemical dissipation (Kn) parameters in chloroplasts. In addition, some vegetation indexes, such as the pigment-specific simple ratio (PSSRc), anthocyanin reflectance index (ARI1), ratio analysis of reflectance spectra (RARS), and structurally insensitive pigment index (SIPI), are highly correlated with morphological parameters and pigment levels, while PRI, moisture stress index (MSI), normalized difference photosynthetic (PVR), fluorescence ratio (FR), and normalized difference vegetation index (NDVI) are associated with photochemical components of photosynthesis. Combined with the JIP test analysis, our results showed that decreased damage to energy transfer in the electron transport chain is correlated with the accumulation of carotenoids, anthocyanins, flavonoids, and phenolic compounds in the leaves. Phenomenological energy flux modelling shows the highest changes in the photosynthetic apparatus based on PRI and SIPI when analyzed with Pearson's correlation, the hyperspectral vegetation index (HVI) algorithm, and the partial least squares (PLS) to select the most responsive wavelengths. These findings are significant for monitoring nonuniform leaves, particularly when leaves display high variation in pigment profiling in variegated and colorful leaves. This is the first study on the rapid and precise detection of morphological, biochemical, and photochemical changes combined with vegetation indexes for different optical spectroscopy techniques.

Catalytic Modification of Porous Two-Dimensional Ni-MOFs on Portable Electrochemical Paper-Based Sensors for Glucose and Hydrogen Peroxide Detection.

Rapid and accurate detection of changes in glucose (Glu) and hydrogen peroxide (H2O2) concentrations is essential for the predictive diagnosis of diseases. Electrochemical biosensors exhibiting high sensitivity, reliable selectivity, and rapid response provide an advantageous and promising solution. A porous two-dimensional conductive metal-organic framework (cMOF), Ni-HHTP (HHTP = 2,3,6,7,10,11-hexahydroxytriphenylene), was prepared by using a one-pot method. Subsequently, it was employed to construct enzyme-free paper-based electrochemical sensors by applying mass-producing screen-printing and inkjet-printing techniques. These sensors effectively determined Glu and H2O2 concentrations, achieving low limits of detection of 1.30 μM and 2.13 μM, and high sensitivities of 5573.21 μA μM-1 cm-2 and 179.85 μA μM-1 cm-2, respectively. More importantly, the Ni-HHTP-based electrochemical sensors showed an ability to analyze real biological samples by successfully distinguishing human serum from artificial sweat samples. This work provides a new perspective for the use of cMOFs in the field of enzyme-free electrochemical sensing, highlighting their potential for future applications in the design and development of new multifunctional and high-performance flexible electronic sensors.

Rapid Detection of Changes in Image Textures of Carrots Caused by Freeze-Drying using Image Processing Techniques and Machine Learning Algorithms

The objective of this study was to evaluate the differences in texture parameters between freeze-dried and fresh carrot slices using image processing and artificial intelligence. Images of fresh and freeze-dried carrot slices were acquired using a digital camera. Texture parameters were extracted from slice images converted to individual color channels L, a, b, R, G, B, X, Y, and Z. A total of 1629 texture parameters, 181 for each of these color channels, were obtained. Models for the classification of freeze-dried and fresh carrot slices were created using various machine learning algorithms, based on attributes selected from a combined set of textures extracted from images in all color channels (L, a, b, R, G, B, X, Y, and Z). Using three different feature selection methods (Genetic Search, Ranker, and Best First), the 20 most effective texture parameters were determined for each method. The models with the highest classification accuracy obtained by applying various machine learning algorithms from Trees, Rules, Meta, Lazy, and Functions groups were determined. The classification successes obtained with the parameters selected from all three different feature selection algorithms were compared. Random Forest, Multi-class Classifier, Logistic and SMO machine learning algorithms achieved 100% accuracy in the classification performed with texture features obtained by each feature selection algorithm.

Identifying river changes by river pattern events: a case study of the Lower Yellow River, China

Accurate and timely detection of river change attaches importance to regional ecological security. Since river change is a complex and dynamic process, there are difficulties to describe it properly. Inspired by geographic events research, river pattern events are innovatively proposed to quantify river change process, combining multi-dimensional information thoroughly. First, inter- and intra- events are defined by comparing typologies changes of river patterns. Afterwards, a river pattern events model (RPEM), integrating "Event types-Spatial locations-River patterns-Morphological features-Hydrological attributes", was proposed to maximally characterize river change process. River pattern events were detected using the object increment difference (OID), and were interpreted as the semantic information in realistic rivers. Experimental results in the Lower Yellow River (LYR) demonstrated that the proposed method achieves good performance in assessing the morphological and hydrological change process. River pattern events are expected to support rapid detection and dynamic analysis of regional and global river change.

Biomacromolecular Profile in Human Primary Retinal Pigment Epithelial Cells—A Study of Oxidative Stress and Autophagy by Synchrotron-Based FTIR Microspectroscopy

Synchrotron radiation-based Fourier Transform Infrared (SR-FTIR) microspectroscopy is a non-destructive and chemically sensitive technique for the rapid detection of changes in the different components of the cell's biomacromolecular profile. Reactive oxygen species and oxidative stress may cause damage to the DNA, RNA, and proteins in the retinal pigment epithelium (RPE), which can further lead to age-related macular degeneration (AMD) and visual loss in the elderly. In this study, human primary RPEs (hRPEs) were used to study AMD pathogenesis by using an established in vitro cellular model of the disease. Autophagy-a mechanism of intracellular degradation, which is altered during AMD, was studied in the hRPEs by using the autophagy inducer rapamycin and treated with the autophagy inhibitor bafilomycin A1. In addition, oxidative stress was induced by the hydrogen peroxide (H2O2) treatment of hRPEs. By using SR-FTIR microspectroscopy and multivariate analyses, the changes in the phosphate groups of nucleic acids, Amide I and II of the proteins, the carbonyl groups, and the lipid status in the hRPEs showed a significantly different pattern under oxidative stress/autophagy induction and inhibition. This biomolecular fingerprint can be evaluated in future drug discovery studies affecting autophagy and oxidative stress in AMD.

Multiple fluorescence approaches to identify rapid changes in microbial indicators at karst springs

Karst springs are globally important for drinking water supply but are often also exceptionally vulnerable to contamination. Such springs usually exhibit strong variation in microbial water quality in sharp response to rainfall events, thus, posing a health hazard to consumers of water supplied from these sources. The rapid detection of such changes is extremely important as well as being able to establish a link to the sources of such pollution, so that appropriate measures can be taken both in terms of immediate protection of human health and the management of karst aquifers. In this study, a fluorescence-based multi-parameter approach was trialed in order to evaluate which methods can be used to monitor rainfall-induced rapid changes in microbial water quality at karst springs, as well as determine whether such changes can be linked to sources of human effluent contamination. The results from three monitoring periods at two karst springs revealed marked responses to rainfall events for all of the microbial parameters measured. Total cell count (TCC) measurements using flow cytometry (FCM) showed very strong positive correlations with the more conventionally monitored faecal indicator bacteria (FIB) and total coliforms (TC), indicating that such a fluorescence-based and cultivation-independent technique can be very useful to indicate rapid changes in microbial water quality at karst springs. Furthermore, very strong positive correlations were also found between tryptophan-like fluorescence (TLF) measurements and concentrations of all monitored microbial parameters, again demonstrating that such a fluorescence-based approach can also be useful for detecting rapid changes in concentrations of traditional faecal indicators. Interestingly, it was found that fluorescent whitening compounds (FWCs) signals do not necessarily follow temporal variations of microbial indicators. However, the frequency of detection of positive FWCs signals may still reveal useful information about the overall magnitude of human wastewater effluent impacts on karst aquifer systems.