Search Results (63)

Rice (Oryza sativa L.) production in the Philippines remains highly vulnerable to recurrent outbreaks of the Rice Black Bug (RBB; Scotinophara coarctata F.) and White Stemborer (WSB; Scirpophaga innotata W.), two of the most destructive pests in Southeast Asian rice ecosystems. Classical economic threshold levels (ETLs) are difficult to estimate in smallholder settings due to the lack of cost–loss data, often leading to either delayed or excessive pesticide application. To address this, the present study developed an adaptive outbreak-forecasting framework that integrates the Number–Size (N–S) fractal model with machine learning (ML) classifiers to define and predict pest regime transitions. Seven years (2018–2024) of light-trap surveillance data from the Philippine Rice Research Institute–Midsayap Experimental Station were combined with daily climate variables from the NASA POWER database, including air temperature, humidity, precipitation, wind, soil moisture, and lunar phase. The N–S fractal model identified natural breakpoints in the log–log cumulative frequency of pest counts, yielding early-warning and severe-outbreak thresholds of 134 and 250 individuals for WSB and 575 and 11,383 individuals for RBB, respectively. Eight ML algorithms such as Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, Balanced Bagging, LightGBM, XGBoost, and CatBoost were trained on variance-inflation-filtered climatic and temporal predictors. Among these, CatBoost achieved the highest predictive performance for WSB at the 94.3rd percentile (accuracy = 0.932, F1 = 0.545, ROC–AUC = 0.957), while Logistic Regression performed best for RBB at the 75.1st percentile (F1 = 0.520, ROC–AUC = 0.716). SHAP (SHapley Additive exPlanations) analysis revealed that outbreak probability increases under warm nighttime temperatures, high surface soil moisture, moderate humidity, and calm wind conditions, with lunar phase exerting additional modulation of nocturnal pest activity. The integrated fractal–ML approach thus provides a statistically defensible and ecologically interpretable basis for adaptive pest surveillance. It offers an early-warning system that supports data-driven integrated pest management (IPM), reduces unnecessary pesticide use, and strengthens climate resilience in Philippine rice ecosystems. Full article

Rifampicin-resistant tuberculosis (RR-TB) remains a major threat to global TB control, primarily driven by mutations in the rpoB gene of Mycobacterium tuberculosis (Mtb). Most resistance-conferring mutations occur within the 81-base pair RIF resistance determining region (RRDR), particularly at codons S450L, H445Y/D, and D435V, which are strongly associated with high level resistance. However, increasing evidence of low-frequency and disputed variants both within and beyond the RRDR reveals a broader genetic spectrum that contributes to diagnostic uncertainty and variable phenotypic outcomes. This review summarizes current knowledge of high frequency, low frequency, and disputed rpoB mutations and their implications for molecular detection of RIF resistance. Structural analyses show that specific amino acid substitutions alter key hydrogen bonds or create steric hindrance in the RIF-binding pocket, leading to diverse resistance levels. Despite the success of molecular platforms such as Xpert MTB/RIF and line probe assays, their hotspot-based detection limits sensitivity to noncanonical variants. Lowering the minimum inhibitory concentration (MIC) breakpoint and integrating sequencing-based approaches, such as targeted and whole-genome sequencing, can enhance detection accuracy. A combined genomic and phenotypic framework will be essential to close existing diagnostic gaps and advance precision guided management of RIF-resistant and multidrug-resistant tuberculosis. Full article

Against the backdrop of electricity market liberalization and deregulation, accurate electricity price forecasting is critical for optimizing power dispatch and promoting the low-carbon transition of energy structures. However, electricity prices exhibit inherent complexities such as seasonality, high volatility, and non-stationarity, which undermine the efficacy of traditional forecasting methodologies. To address these challenges, this study proposes a four-stage Decomposition-Reconstruction-Optimization-Integration (DROI) framework, coupled with an econometric breakpoint test, to evaluate forecasting performance across distinct time segments of Spanish electricity price data. The framework employs CEEMDAN for signal decomposition, decomposing complex price sequences into intrinsic mode functions to retain essential features while mitigating noise, followed by frequency-based data reconstruction; integrates the Improved Sparrow Search Algorithm (ISSA) to optimize initial model parameters, minimizing errors induced by subjective factors; and leverages Convolutional Neural Networks (CNN) for frequency-domain feature extraction, enhanced by an attention mechanism to weight channels and prioritize critical attributes, paired with Long Short-Term Memory (LSTMs) for temporal sequence forecasting. Experimental results validate the method’s robustness in both interval forecasting (IPCP = 100% and IPNAW is the smallest, Experiment 1.3) and point forecasting tasks (MAPE = 1.3758%, Experiment 1.1), outperforming naive approaches in processing stationary sequence clusters and demonstrating substantial economic utility to inform sustainable power system management. Full article

This study proposes a hybrid analytical framework for detecting chondromalacia using vibroacoustic (VAG) signals from patients with knee osteoarthritis (OA) and healthy controls (HCs). The methodology combines nonlinear signal decomposition, feature extraction, and deep learning classification. Raw VAG signals, recorded with a custom multi-sensor system during open (OKC) and closed (CKC) kinetic chain knee flexion–extension, underwent preprocessing (denoising, segmentation, normalization). Ensemble Empirical Mode Decomposition (EEMD) was used to isolate Intrinsic Mode Functions (IMFs), and Detrended Fluctuation Analysis (DFA) computed local (α₁) and global (α₂) scaling exponents as well as breakpoint location. Frequency–energy features of IMFs were statistically assessed and selected via Neighborhood Component Analysis (NCA) for support vector machine (SVM) classification. Additionally, reconstructed α₁/α₂-based signals and raw signals were converted into continuous wavelet transform (CWT) scalograms, classified with convolutional neural networks (CNNs) at two resolutions. The SVM approach achieved the best performance in CKC conditions (accuracy 0.87, AUC 0.91). CNN classification on CWT scalograms also demonstrated robust OA/HC discrimination with acceptable computational times at higher resolutions. Results suggest that combining multiscale decomposition, nonlinear fluctuation analysis, and deep learning enables accurate, non-invasive detection of cartilage degeneration, with potential for early knee pathology diagnosis. Full article

We aimed to explore SARS-CoV-2 evolution during in vitro neutralisation using next generation sequencing, and to determine whether sera from individuals immunised with two doses of the Pfizer-BioNTech vaccine (BNT162b2) were as effective at neutralising the variant of concern (VOC) Delta (B.1.617.2) compared to the earlier lineages Beta (B.1.351) and wild-type (A.2.2) virus. Using a live-virus SARS-CoV-2 neutralisation assay in Vero E6 cells, we determined neutralising antibody titres (nAbT) against three SARS-CoV-2 strains (wild type, Beta, and Delta) in 14 participants (vaccine-naïve (n = 2) and post-second dose of BNT162b2 vaccination (n = 12)), median age 45 years [IQR 29–65]; the median time after the second dose was 21 days [IQR 19–28]. The determination of nAbT was based on cytopathic effect (CPE) and in-house quantitative reverse transcriptase real-time quantitative polymerase chain reaction (RT-qPCR) to confirm SARS-CoV-2 replication. A total of 110 representative samples including inoculum, neutralisation breakpoints at 72 h, and negative and positive controls underwent genome sequencing. By integrating live-virus neutralisation assays with deep sequencing, we characterised both functional antibody responses and accompanying viral genetic changes. There was a reduction in nAbT observed against the Delta and Beta VOC compared with wild type, 4.4-fold (p ≤ 0.0006) and 2.3-fold (p = 0.0140), respectively. Neutralising antibodies were not detected in one vaccinated immunosuppressed participant and the vaccine-naïve participants (n = 2). The highest nAbT against the SARS-CoV-2 variants investigated was obtained from a participant who was vaccinated following SARS-CoV-2 infection 12 months prior. Limited consensus level mutations occurred in the various SARS-CoV-2 lineage genomes during in vitro neutralisation; however, consistent minority allele frequency variants (MFV) were detected in the SARS-CoV-2 polypeptide, spike (S), and membrane protein. Findings from countries with high COVID-19 incidence may not be applicable to low-incidence settings such as Australia; as seen in our cohort, nAbT may be significantly higher in vaccine recipients previously infected with SARS-CoV-2. Monitoring viral evolution is critical to evaluate the impact of novel SARS-CoV-2 variants on vaccine effectiveness, as mutational profiles in the sub-consensus genome could indicate increases in transmissibility and virulence or suggest the development of antiviral resistance. Full article

Understanding structural regime shifts in crypto asset markets is vital for early detection of systemic risk. This study applies the Generalized Sup Augmented Dickey–Fuller (GSADF) test to daily high-frequency price data of five major crypto assets—BTC, ETH, SOL, AAVE, and BCH—from 2023 to 2025. The results reveal asset-specific structural breaks: BTC and BCH aligned with macroeconomic shocks, while DeFi tokens (e.g., AAVE, SOL) exhibited fragmented, project-driven shifts. The S&P 500 index, in contrast, showed no persistent regime shifts, indicating greater structural stability. To examine inter-asset linkages, we construct co-occurrence matrices based on GSADF breakpoints. These reveal strong co-explosivity between BTC and other assets, and unexpectedly weak synchronization between ETH and AAVE, underscoring the sectoral idiosyncrasies of DeFi tokens. While the GSADF test remains central to our analysis, we also employ a Markov Switching Model (MSM) as a secondary tool to capture short-term volatility clustering. Together, these methods provide a layered view of long- and short-term market dynamics. This study highlights crypto markets’ structural heterogeneity and proposes scalable computational frameworks for real-time monitoring of explosive behavior. Full article

Flooding frequency in the lower Yellow River (YR) exhibited an abrupt increase post-934 CE, causing catastrophic societal disruptions. However, the quantitative relationship between this abrupt increase and the intensification of human activity in the midstream Loess Plateau (LP)’s Primary Sediment Source Area (PSSA) remains uncertain. This study systematically evaluates the threshold effects of human activities on YR flooding through multi-proxy historical records, GIS-based spatial analysis, and nonparametric statistical tests. The results show that from 934 to 1102 CE, the population density in the PSSA surged from 1.3 to 19.8 persons/km² (a 14.2-fold increase, p = 0.005). A 2400-year-scale comparison using 934 CE as the breakpoint revealed that the mean population density in this region increased from 5.2 to 51 persons/km² (a 9.8-fold increase). This dramatic population surge drove a 1.4-fold increase in the cultivation rate (from 8.6% to 20.5%), leading to a 5.4-fold rise in sediment yield (1.6 × 10⁸ → 1.02 × 10⁹ t/yr, p = 0.035), a 10-fold acceleration in downstream sedimentation rate (0.3 → 3.3 cm/yr, p = 0.001), and ultimately a 5.5-fold escalation in flooding frequency (from 1.6 to 10.4 events per 20 years, p < 0.0001). The study identifies 19.8 persons/km² as the ecological pressure threshold. It proposes converting population density to ecological pressure equivalents adjusted for soil–water conservation coverage (e.g., terracing/afforestation). When the equivalent ecological pressure exceeds 19.8 persons/km², pre-defined sediment control measures (e.g., tillage restrictions/afforestation mandates) should be enforced in the PSSA. Full article

Background/Objectives: Antimicrobial resistance of the E. coli O25 ST131 clonal lineage poses a significant therapeutic challenge worldwide, often involving resistance to fluoroquinolones and extended-spectrum beta-lactamase (ESBL) production. This retrospective study compared the dissemination of multidrug-resistant E. coli O25 ST131 isolated from the urine of outpatients at the largest Croatian clinical microbiology department across six years over two study periods. Methods: The E. coli O25 ST131 clonal lineage was detected via a rapid PCR method using pabB and trpA primers after positive agglutination with E. coli serogroup O25 antisera. ESBL phenotypes and antibiotic susceptibility were investigated according to EUCAST guidelines and breakpoint tables. Results: In the first period, there were a total of 45 isolates of E. coli O25 ST131, among which 30 were isolates with proven ESBL production. In the second period, a total of 114 isolates of E. coli O25 ST131 were detected, among which 75 (65.8%) were ESBL-positive (p > 0.05). In ESBL-negative strains, the multidrug-resistant (MDR) phenotype was characterized by simultaneous resistance to ampicillin, co-trimoxazole, and fluoroquinolones (with an equal proportion of 3/15 isolates in the first period and 7/39 isolates in the second period, p > 0.05). There was no statistically significant difference in the frequency of MDR detection across the two study periods (36/45 and 98/114, p > 0.05). This is the first detection of E. coli O25 ST131 in the outpatient population in Zagreb. Conclusions: There was no statistically significant difference in the frequency of detecting the E. coli O25 ST 131 clone across the two study periods. The high frequency of MDR phenotype among ESBL-negative isolates of E. coli O25 ST131 and an equally high proportion of MDR strains among ESBL producers in this clonal lineage, with the total detection of MDR isolates ≥ 80% in both study periods, are the reasons why this bacterial clone poses a public health threat and why further investigation into its metabolic and virulence characteristics is needed in order to estimate its spreading potential among the outpatient population in Zagreb. Full article

Background: It is widely accepted that the 3D chromatin organization in human cell nuclei is not random and recent investigations point towards an interactive relation of epigenetic functioning and chromatin (re-)organization. Although chromatin organization seems to be the result of self-organization of the entirety of all molecules available in the cell nucleus, a general question remains open as to what extent chromatin organization might additionally be predetermined by the DNA sequence and, if so, if there are characteristic differences that distinguish typical regions involved in dysfunction-related aberrations from normal ones, since typical DNA breakpoint regions involved in disease-related chromosome aberrations are not randomly distributed along the DNA sequence. Methods: Highly conserved k-mer patterns in intronic and intergenic regions have been reported in eukaryotic genomes. In this article, we search and analyze regions deviating from average spectra (ReDFAS) of k-mer word frequencies in the human genome. This includes all assembled regions, e.g., telomeric, centromeric, genic as well as intergenic regions. Results: A positive correlation between k-mer spectra and 3D contact frequencies, obtained exemplarily from given Hi-C datasets, has been found indicating a relation of ReDFAS to chromatin organization and interactions. We also searched and found correlations of known functional annotations, e.g., genes correlating with ReDFAS. Selected regions known to contain typical breakpoints on chromosomes 9 and 5 that are involved in cancer-related chromosomal aberrations appear to be enriched in ReDFAS. Since transposable elements like ALUs are often assigned as major players in 3D genome organization, we also studied their impact on our examples but could not find a correlation between ALU regions and breakpoints comparable to ReDFAS. Conclusions: Our findings might show that ReDFAS are associated with instable regions of the genome and regions with many chromatin contacts which is in line with current research indicating that chromatin loop anchor points lead to genomic instability. Full article

Flashiness refers to the rapidity and frequency of fluctuations in river flow. It can provide insights into flooding, by capturing dramatic increases in river flow, as well as contaminant transport, relating to concentrations of diffuse pollution. Despite a very well gauged river system, there is limited research in Great Britain targeting this component of river flow. This study addresses that gap in knowledge, with a detailed spatio-temporal analysis of river flashiness in Great Britain. Using 513 gauging stations, with historical records of at least 30 years, the average Richards–Baker flashiness index ($\overline{RBI}$) was calculated for 1990–2020, showing an overall west- (0.6–0.8) to east-coast (0.1–0.2) gradient, being higher in the west (with the exception of some gauges in the south-east). Employing random forest models, the main predictor for flashiness was found to be soil composition, with some additional region-specific predictors. These include flood attenuation by reservoirs and catchment areas, affecting flashiness in the north and west of Great Britain. Additionally, using a subset of 208 gauging stations with data recorded from 1970 to 2020, a temporal analysis examined significant breakpoints and/or trends in yearly flashiness, using the Pettitt test and Mann–Kendall trend test, respectively. Increases in flashiness were found mainly in the north-east and south-west of Great Britain, with implications in flooding and river health. On a seasonal scale, and using a monthly $\overline{RBI}$, the timing of flashy events was found to oscillate between autumn and spring over the 50 years, gravitating around winter. Full article

CDKL5 deficiency disorder (CDD) is an X-linked dominant epileptic encephalopathy, characterized by early-onset and drug-resistant seizures, psychomotor delay, and slight facial features. Genomic variants inactivating CDKL5 or impairing its protein product kinase activity have been reported, making next-generation sequencing (NGS) and chromosomal microarray analysis (CMA) the standard diagnostic tests. We report a suspicious case of CDD in a female child who tested negative upon NGS and CMA and harbored an X chromosome de novo pericentric inversion. The use of recently developed genomic techniques (optical genome mapping and whole-genome sequencing) allowed us to finely characterize the breakpoints, with one of them interrupting CDKL5 at intron 1. This is the fifth case of CDD reported in the scientific literature harboring a structural rearrangement on the X chromosome, providing evidence for the hypothesis that this type of anomaly can represent a recurrent pathogenic mechanism, whose frequency is likely underestimated, with it being overlooked by standard techniques. The identification of the molecular etiology of the disorder is extremely important in evaluating the pathological outcome and to better investigate the mechanisms associated with drug resistance, paving the way for the development of specific therapies. Karyotype and genomic techniques should be considered in all cases presenting with CDD without molecular confirmation. Full article

A ~3-kb deletion-type DNA copy number variation (CNV, esv3587290) located at intron 7 of the VANGL1 gene (1p13.1, MIM*610132) has been proposed as a genetic factor in lupus nephritis (LN) development in adult systemic lupus erythematosus (SLE) patients across European-descent populations, but its replication in other ethnicities has been inconsistent and its association with LN in childhood-onset SLE (cSLE) remains unknown. Here, we performed an exploratory association study in a sample of 66 unrelated cSLE Mexican patients (11 males, 55 females; ages 7.8 to 18.6 years). Two stratified groups were compared: cSLE patients with (N = 39) or without (N = 27) LN, as diagnosed by renal biopsy (N = 17), proteinuria (N = 33), urinary protein–creatinine ratio > 0.2 (N = 34), and erythrocyturia and/or granular casts in urinary sediment (N = 16). For esv3587290 CNV genotyping, we performed an end-point PCR assay with breakpoint confirmation using Sanger sequencing. We also determined the allelic frequencies of the esv3587290 CNV in 181 deidentified ethnically matched individuals (reference group). The obtained genotypes were tested for Hardy–Weinberg equilibrium using the χ² test. Associations between LN and esv3587290 CNV were tested by calculating the odds ratio (OR) and using Pearson’s χ² tests, with a 95% confidence interval and p ≤ 0.05. The esv3587290 CNV allele (OR 0.108, 95% CI 0.034–0.33, p = 0.0003) and the heterozygous genotype (OR 0.04, 95% CI 0.119–0.9811, p = 0.002) showed a significant protective effect against LN development. Finally, we characterized the precise breakpoint of the esv3587290 CNV to be NG_016548.1(NM_138959.3):c.1314+1339_1315-897del in our population. This report supports the notion that a broad genetic heterogeneity underlies the susceptibility for developing LN. Full article

Chromosomal translocations can result in phenotypic effects of varying severity, depending on the position of the breakpoints and the rearrangement of genes within the interphase nucleus of the translocated chromosome regions. Balanced translocations are often asymptomatic phenotypically and are typically detected due to a decrease in fertility resulting from issues during meiosis. Robertsonian translocations are among the most common chromosomal abnormalities, often asymptomatic, and can persist in the population as a normal polymorphism. We serendipitously discovered a Robertsonian translocation between chromosome 21 and chromosome 22, which is inherited across three generations without any phenotypic effect, notably only in females. In situ hybridization with alpha-satellite DNAs revealed the presence of both centromeric sequences in the translocated chromosome. The reciprocal translocation resulted in a partial deletion of the short arm of both chromosomes 21, and 22, with the ribosomal RNA genes remaining present in the middle part of the new metacentric chromosome. The rearrangement did not cause alterations to the long arm. The spread of an asymptomatic heterozygous chromosomal polymorphism in a population can lead to mating between heterozygous individuals, potentially resulting in offspring with a homozygous chromosomal configuration for the anomaly they carry. This new karyotype may not produce phenotypic effects in the individual who presents it. The frequency of karyotypes with chromosomal rearrangements in asymptomatic heterozygous form in human populations is likely underestimated, and molecular karyotype by array Comparative Genomic Hybridization (array-CGH) analysis does not allow for the identification of this type of chromosomal anomaly, making classical cytogenetic analysis the preferred method for obtaining clear results on a karyotype carrying a balanced rearrangement. Full article

The most common form of hereditary spastic paraplegia (HSP), SPG4 is caused by single nucleotide variants and microrearrangements in the SPAST gene. The high percentage of multi-exonic deletions or duplications observed in SPG4 patients is predisposed by the presence of a high frequency of Alu sequences in the gene sequence. In the present study, we analyzed DNA and RNA samples collected from patients with different microrearrangements in SPAST to map gene breakpoints and evaluate the mutation mechanism. The study group consisted of 69 individuals, including 50 SPG4 patients and 19 healthy relatives from 18 families. Affected family members from 17 families carried varying ranges of microrearrangements in the SPAST gene, while one individual had a single nucleotide variant in the 5′UTR of SPAST. To detect the breakpoints of the SPAST gene, long-range PCR followed by sequencing was performed. The breakpoint sequence was detected for five different intragenic SPAST deletions and one duplication, revealing Alu-mediated microhomology at breakpoint junctions resulting from non-allelic homologous recombination in these patients. Furthermore, SPAST gene expression analysis was performed using patient RNA samples extracted from whole blood. Quantitative real-time PCR tests performed in 14 patients suggest no expression of transcripts with microrearrangements in 5 of them. The obtained data indicate that nonsense-mediated decay degradation is not the only mechanism of hereditary spastic paraplegia in patients with SPAST microrearrangements. Full article

Confronting the challenge of biofilm resistance and widespread antimicrobial resistance (AMR), this study emphasizes the need for innovative monitoring methods and explores the potential of bacteriophages against bacterial biofilms. Traditional methods, like optical density (OD) measurements and confocal microscopy, crucial in studying biofilm–virus interactions, often lack real-time monitoring and early detection capabilities, especially for biofilm formation and low bacterial concentrations. Addressing these gaps, we developed a new real-time, label-free radiofrequency sensor for monitoring bacteria and biofilm growth. The sensor, an open-ended coaxial probe, offers enhanced monitoring of bacterial development stages. Tested on a biological model of bacteria and bacteriophages, our results indicate the limitations of traditional OD measurements, influenced by factors like sedimented cell fragments and biofilm formation on well walls. While confocal microscopy provides detailed 3D biofilm architecture, its real-time monitoring application is limited. Our novel approach using radio frequency measurements (300 MHz) overcomes these shortcomings. It facilitates a finer analysis of the dynamic interaction between bacterial populations and phages, detecting real-time subtle changes. This method reveals distinct phases and breakpoints in biofilm formation and virion interaction not captured by conventional techniques. This study underscores the sensor’s potential in detecting irregular viral activity and assessing the efficacy of anti-biofilm treatments, contributing significantly to the understanding of biofilm dynamics. This research is vital in developing effective monitoring tools, guiding therapeutic strategies, and combating AMR. Full article