Search Results (15,598)

Radio Frequency Identification (RFID) is an emerging technology in Industry 4.0 for low-cost logistics, yet direction and orientation estimation typically requires multiple antennas, and robustness under industrial multipath fading, operator variability, and signal fragmentation has not been evaluated. To address this gap, this study proposes a single-antenna RFID system that evaluated thirteen architectures spanning unsupervised methods (clustering algorithms) and supervised methods (classical machine learning, deep learning, and hybrid architectures) on Received Signal Strength Indicator (RSSI) and phase time-series reconstructed through a pipeline of Savitzky–Golay smoothing, phase unwrapping, and cubic spline resampling to $N=50--300$ samples, preserving signal morphology across variable-length RFID passes. The system further incorporates a physics-informed augmentation strategy that encodes multipath fading, distance variation, and fragmentation into synthetic training samples for cross-domain generalization without hardware modification. In controlled laboratory experiments, both direction and orientation tasks achieved $>99.5\%$ accuracy, while direction tracking was additionally validated on an industrial shop floor under varying distances, Non-Line-of-Sight (NLoS) occlusions, and signal fragmentation. Zero-shot transfer caused accuracy to degrade to near-chance levels for several configurations, confirming a pronounced domain gap. Domain adaptation with XGBoost recovered direction accuracy to $>97\%$ under severe fragmentation under NLoS conditions, with an inference latency of ≈150 $\mathsf{\mu }$s. Under domain-adapted shop floor conditions, direction accuracy exceeded the 75–92% reported in prior single-antenna laboratory studies, suggesting that physics-informed domain adaptation is a promising approach for single-antenna RFID tracking in Industrial Internet of Things (IIoT) logistics environments. Full article

Prevention of crossing collisions between cyclists and vehicles at nonsignalized intersections on community roads where walls and hedges limit visibility is required in Japan. Because available observation information in real-time is limited on community roads, the use of statistical information that represents the typical movement characteristics of cyclists is effective to compensate for the lack of observation information. From such a background, in our previous study, we proposed a method to construct “location-dependent statistical information” (LDSI) and a method to utilize it as “virtual observation” (VO) and “virtual control input” (VCI) in stochastic position estimation. Here, although LDSI was constructed for multiple clusters of cyclists, the classification method of the cyclists observed in real-time was not considered. In the real world, the limitation of the observation information causes classification uncertainty. Thus, in this study, we propose a position estimation method that utilizes soft classification results and considers classification uncertainty by integrating VO and VCI derived from LDSI of each cluster. To evaluate the proposed method in this study, we conduct a simulation and an experiment in the real world. Through the comparison with conventional methods, we confirm that our proposed method in this study improves the performance of the position estimation. The proposed method will contribute to a cooperative safety system. Full article

Cryptorchidism is one of the most frequently diagnosed developmental disorders of the male canine reproductive system, defined as the failure of one or both testes to descend into the scrotum. Physiologically, testicular descent is typically completed by six to eight weeks of age, although some authors extend this period to sixteen weeks. Failure of testicular descent beyond this timeframe is considered pathological. The condition has multiple causes and affects between 1% and 10% of the canine population. Genetics is the most significant factor, indicating the hereditary basis of cryptorchidism. In addition, increasing attention has been directed toward the potential impact of environmental and epigenetic factors on the incidence of cryptorchidism, suggesting that the condition may result from complex interactions between genetic predisposition and external influences. The effect of hormones (such as INSL3 and testosterone), mechanical factors (including narrowing of the inguinal canal, abnormalities of the gubernaculum, and shortening of the spermatic cord), and environmental factors (for example, exposure to external estrogens and maternal stress during pregnancy) all contribute to the development of this disorder. Recent results have emphasized the role of the orexin system, particularly the OX2R receptor, in regulating endocrine and reproductive functions in cryptorchid testes. Computed tomography is increasingly utilized in complex cases due to its high precision in localizing retained testes. Clinically, cryptorchidism may present unilaterally or bilaterally. Unilateral cryptorchidism may preserve partial fertility, whereas bilateral cryptorchidism results in complete infertility. Undescended testes may be located in the abdominal cavity or inguinal canal. Major complications include an increased risk of testicular cancer (Sertoli cell tumors and seminomas) and endocrine disorders leading to feminization. Diagnosis is based on clinical examination and imaging modalities such as ultrasound. Orchiectomy, involving the removal of both the retained and normally descended testicles, is thought to be the gold standard for treatment. This method helps avoid complications and the transmission of the defect to offspring. According to Fédération Cynologique Internationale (FCI) standards, affected individuals should not be used for breeding or shows. Early detection, surgical intervention, and consistent exclusion from breeding programs are the primary strategies for reducing the incidence of this disorder in the canine population. Full article

In close-range monocular visual measurement and cooperative target pose estimation, conventional planar targets are constrained by viewpoint changes and are prone to perspective distortion. Although spherical targets provide omnidirectional observability, their PnP-based pose estimation may still suffer from large errors under limited fields of view and sparse feature observations. To address this issue, this paper proposes an integrated visual measurement framework covering both high-precision spherical target construction and robust pose estimation. First, a composite marker layout based on adaptively scaled latitude–longitude topology is designed. To suppress cumulative distortion caused by long-sequence multi-view rigid registration, a center-to-pole point-cloud stitching strategy is developed, and multiple observations are fused using geometric-consistency weighting to accurately reconstruct the feature-point coordinate system of the target. Second, a joint optimization method is proposed by combining feature-point reprojection error with a contour center consistency constraint. Specifically, the theoretical contour center is predicted from the analytical projection model of the sphere and constrained to agree with the observed contour center fitted from the image. In addition, an SQPnP-based sequential reinitialization mechanism is introduced to improve robustness under sparse-point observations. Simulation results demonstrate that the proposed method achieves higher accuracy and robustness under continuous pose changes, sparse feature points, and different noise levels, compared with EPnP, EPnP+LM, LM, and SQPnP, while real-image experiments further demonstrate its practical feasibility. Full article

Antibody–drug conjugates (ADCs) are a promising therapeutic modality for treating cancer. TM4SF1 is an integral membrane protein that internalizes from the cell surface along microtubules to the nucleus and is highly expressed on the surface of both tumor endothelium and tumor cells. We previously reported that in human tumor xenografts in mice, an ADC directed to mouse TM4SF1 (2A7A-LP2) effectively regressed tumors through an anti-vascular mechanism, and an ADC directed to human TM4SF1 (v1.10-LP2) effectively regressed tumors through an anti-tumor cell mechanism. In this study, we investigated the actions of the mouse TM4SF1-directed ADC on VEGF-A-provoked angiogenic vessels. We employed an adenovirus expressing mouse VEGF-A¹⁶⁴ (Ad-VEGF-A) to induce surrogate tumor blood vessels in the ears of nude mice. We showed that an immune effector function-ablated ADC, 3m2A7A-LP2, was better tolerated than its parent 2A7A-LP2. Homing of 3m2A7A to Ad-VEGF-A-induced new blood vessels became evident within six hours after intraperitoneal injection. A single dose of 3m2A7A-LP2 at 3 mg/kg disrupted evolving Ad-VEGF-A-provoked blood vessels within forty-eight hours, and three doses of 3m2A7A-LP2 at 48 h intervals caused striking local ear necrosis; in each case, there was no apparent harm to vessels in the corresponding control virus-injected ears and the surrounding tissues of the same mice. Our studies demonstrate that an ADC-directed against mouse TM4SF1 specifically targeted the newly formed blood vessels induced by Ad-VEGF-A at multiple stages of their development. Thus, TM4SF1-directed ADCs, through their ability to target angiogenic vessels, represent an alternative anti-angiogenic approach for treating solid tumors. Full article

Background/Objectives: While ¹⁷⁷Lu-DOTATATE has demonstrated clinical efficacy in peptide receptor radionuclide therapy (PRRT) for neuroendocrine tumors (NETs), current dosing regimens do not account for potential sex-based pharmacokinetic differences. Our study systematically characterizes sex-dependent pharmacokinetic variations of ¹⁷⁷Lu-DOTATATE in preclinical models to provide the first preclinical evidence base informing future sex-stratified clinical investigations. Methods: Sex-stratified pharmacokinetic and biodistribution studies were conducted in male and female SD rats following intravenous administration of ¹⁷⁷Lu-DOTATATE at multiple dose levels: 2.86, 5.71, and 11.43 mCi/kg. Metabolic stability and renal excretion patterns were characterized. Safety assessments included acute toxicity, vascular irritation, hemolysis, and allergenicity testing. Therapeutic efficacy was evaluated exclusively in female AR42J xenograft-bearing CB-17 SCID mice. Results: Significant sex-dependent pharmacokinetic differences were observed at high (11.43 mCi/kg) and low (2.86 mCi/kg) dose levels, with females exhibiting 30–40% higher AUC and C_max values compared to males (p < 0.05). Both sexes demonstrated preferential accumulation in SSTR-expressing tissues, particularly the pancreas (females: 10.87 ± 2.51% ID/g; males: 9.10 ± 0.76% ID/g) and adrenal glands, with rapid clearance from non-target organs. Radio-HPLC analysis confirmed high metabolic stability with no detectable radiolabeled metabolites, and over 90% of radioactivity was recovered through renal excretion. Safety assessments demonstrated excellent tolerability across dose levels. In female xenograft models, treatment achieved tumor growth inhibition of 92.35–96.44% and 100% survival rate versus 10% in controls, though mid/high doses caused weight loss. Conclusions: Our study provides systematic preclinical evidence of sex-dependent pharmacokinetic differences in ¹⁷⁷Lu-DOTATATE, with females demonstrating significantly higher systemic exposure than males at specific dose levels. These findings establish the systematic preclinical evidence base for sex-dependent pharmacokinetic differences in ¹⁷⁷Lu-DOTATATE, providing a scientific rationale for incorporating sex as a stratification variable in future dosimetry-guided clinical studies. Full article

Feline panleukopenia virus (FPLV) is the primary causative agent of a highly contagious and often fatal disease affecting domestic cats and other felids. The increasing isolation of species-specific FPLV variants from multiple host species has garnered considerable attention, highlighting the need to investigate their genetic diversity. In this study, three FPLV isolates were obtained and phylogenetically classified into two distinct FPLV-China groups within separate clusters. Compared to the prototype FPLV (M38246.1), these isolates exhibited seven amino acid substitutions in the NS1 (n = 6) and VP2 (n = 1) proteins. Further analysis of 157 NS1 sequences and 947 VP2 sequences retrieved from the NCBI database revealed 113 and 479 synonymous substitutions and 71 and 279 non-synonymous substitutions, respectively. Notably, the majority of these substitutions occurred as single events (57% in NS1, 40/71; 55% in VP2, 153/279) or were present in no more than five FPLV sequences (23% in NS1, 16/71; 32% in VP2, 89/279). However, three non-synonymous substitutions in the NS1 protein (Ile443Val, His595Gln, and Val596Leu) were detected in more than half of the 157 sequences analyzed. In the VP2 protein, six non-synonymous substitutions (Ala91Ser, Thr101Ile, Val232Ile, Lys93Asn, Asp323Asn, and Val562Leu) were each found in 20 to 40 FPLV sequences. Furthermore, ten sites in the NS protein and 224 sites in the VP2 protein exhibited both synonymous and non-synonymous substitutions simultaneously. Additionally, 75 sites in VP2 harbored multiple non-synonymous substitutions. These findings provide valuable insights for future research on the genetic determinants and vaccine development of FPLV. Full article

Food security is increasingly threatened by climate change and population growth. Sweet potato has become a crucial crop for ensuring food security due to its adaptability to marginal lands and high yield potential. However, its sustainable production is severely limited by diverse biotic stresses (including fungi, viruses, nematodes, insect pests and bacteria), which cause substantial yield losses. Despite its considerable importance, the key bottlenecks in this field remain unresolved, including the incomplete elucidation of core resistance mechanisms, unclear molecular regulatory networks underlying defense responses, insufficient understanding of crosstalk among multiple stresses, and limited integration of emerging technologies into practical resistance breeding. This review synthesizes the latest advances over the past two years. We dissect sweet potato’s defense mechanisms from multiple dimensions and provide novel insights into biotic stress resistance gene regulatory networks. Given that sweet potato production faces the combined effects of multiple pests and biotic-abiotic stresses, we elaborate on the complex stress interactions in sweet potato. In addition, we propose biotic stress management strategies and a ten-year cultivar improvement roadmap that leverages the potential of emerging technologies, including artificial intelligence (AI), gene editing, novel omics approaches and synthetic biology. Taken together, with continuous intensification of global biotic stress challenges, systematic multi-dimensional strategies are imperative to alleviate biotic stress-associated yield and quality impairment in sweet potato. On this basis, this review provides a valuable theoretical and practical reference for resistance breeding and the sustainable production of sweet potato. Full article

Pathological events in a wide range of diseases, from severe infections to sterile inflammatory disorders. PMR serves as the terminal step that releases large quantities of damage-associated molecular patterns (DAMPs)—intracellular molecules that act as danger signals once outside the cell. These DAMPs can trigger strong inflammatory responses, and in many cases, may precipitate a cytokine storm, a hyperactive immune reaction that often amplifies tissue injury beyond the initial insult. For decades, scientists generally believed that PMR resulted from membrane pore-forming cell death, such as pyroptosis or necroptosis, which causes osmotic imbalance and passive membrane swelling. However, in recent years, it was discovered that Nerve Injury-Induced Protein 1 (NINJ1) mediates PMR through active oligomerization. This review first uses pathogen infection as a classical model to explore how multiple cell death pathways converge on plasma membrane rupture (PMR). Subsequently, we elaborate on the structure and function of NINJ1 as a core executor of PMR. Finally, we broaden our perspective from infection to other non-infectious but equally PMR-driven major diseases, and systematically evaluate the commonalities and prospects of NINJ1-targeted therapeutic strategies across different pathological scenarios. It is hoped that this will provide new insights for future researchers in this field. Full article

Histone deacetylase (HDAC) inhibitors are approved for cancer treatment and are being investigated for a wide range of other diseases. Despite their therapeutic promise, clinical studies have reported cardiac side effects, particularly electrocardiogram (EKG) abnormalities, with QT interval prolongation being one of the most consistently reported findings. The mechanisms underlying these cardiac effects remain unclear. In this study, we investigated the role of HDAC3 in cardiac electrophysiology. We found that postnatal depletion of cardiac HDAC3 in mice caused QT interval prolongation, recapitulating the EKG abnormalities reported with HDAC inhibitor use. Adult-onset inducible depletion of cardiac HDAC3 induced additional EKG abnormalities, including T-wave flattening, inversion, and biphasic T waves, which are also observed clinically. Loss of HDAC3 deacetylase activity, without affecting HDAC3 protein levels, was sufficient to induce QT prolongation. Disruption of HDAC3 function altered the expression of ion channel genes, including the downregulation of potassium channel genes such as Kcnh2, Kcne1, and Kcnip2. Moreover, a single dose of HDAC inhibitors, romidepsin or mocetinostat, caused reversible QT prolongation in mice. Consistent with these findings, HDAC inhibitor treatment altered the expression of potassium channel genes, with a predominant downregulation of multiple Kcn family members, including Kcnq1, Kcnh2, and Kcnip2. These findings establish HDAC3 enzymatic activity as a key regulator of cardiac repolarization and provide mechanistic insight into HDAC inhibitor-associated cardiotoxicity. Full article

Background/Objectives: Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a major global health challenge, exacerbated by the emergence of multidrug-resistant strains and limited efficacy of existing therapies. Given the involvement of multiple essential mycobacterial proteins, multitarget drug discovery represents a rational therapeutic strategy. Methods: In this study, an integrated in silico pipeline combining machine learning–based quantitative structure–activity relationship modeling, graph neural network–driven drug–target affinity prediction, molecular docking, molecular dynamics (MD) simulations, and pharmacokinetic–toxicity profiling was employed to identify potential antitubercular leads from natural products. Results: A curated library of over 0.69 million compounds from the COCONUT database was systematically screened against seven essential M. tuberculosis protein targets. Machine learning and heterogeneous graph neural network models effectively captured complex ligand–protein interaction patterns, enabling high-confidence multitarget prioritization. Structure-based docking and MM-GBSA analyses revealed favorable binding affinities, further supported by 100 ns Molecular Dynamics simulations demonstrating stable binding and conformational integrity. In silico ADMET and toxicity predictions identified pharmacokinetically balanced candidates, while density functional theory calculations corroborated favorable electronic properties. Conclusion: Notably, a myricetin-based flavonoid glycoside exhibited consistent multitarget binding and dynamic stability across all targets. Overall, this study underscores the potential of integrated artificial intelligence and structure-based approaches in accelerating natural product-based antitubercular drug discovery and supports further experimental validation of prioritized leads. Full article

Cystic echinococcosis (CE) is a zoonotic disease caused by the larval stage of the Echinococcus granulosus sensu lato (s.l.) complex. The disease is globally distributed, with particularly high prevalence in Central Asian countries, including Kazakhstan. Despite its significant impact on public health and livestock production, data on CE in sheep in Kazakhstan remain limited. This study investigated the prevalence and genetic diversity of Echinococcus granulosus sensu stricto (s.s.) in sheep across Kazakhstan, addressing an important zoonotic disease affecting both livestock and human health. Over the course of one year, a total of 31,389 sheep were examined, and cystic echinococcosis cysts were collected from the livers and lungs of 550 infected sheep across 14 regions of Kazakhstan. Molecular analyses targeting mitochondrial genes (nad1, cox1) were performed to determine genetic diversity. The results revealed a higher occurrence of CE in the southern regions of the country. Among the genotyped isolates (57), genotype G1 was dominant, accounting for 84.2% (48) of the samples, whereas genotype G3 (9) was detected at a lower frequency in three regions. A total of 11 distinct haplotypes were identified, indicating considerable genetic diversity among the isolates. Haplotype network analysis suggested gene flow among populations and revealed the widespread presence of the most common haplotype (EgKZ-2) across multiple regions. These findings highlight the need for continuous monitoring and targeted control strategies for cystic echinococcosis, emphasizing the importance of understanding parasite genetic diversity for public health interventions and livestock management in endemic areas. Overall, this study contributes to the understanding of the genetic diversity and transmission dynamics of E. granulosus s.s. in Central Asia. Full article

Cover-collapse sinkholes are one of the most hazardous geohazards, causing severe damage to civil infrastructure, roadway networks, and substantial economic disruptions. In the United States alone, the economic loss caused by cover-collapse sinkholes exceed USD 300 million annually. Despite extensive research on the causes and formation mechanisms of cover-collapse sinkholes, reliable prediction of the collapse range remains a significant challenge because the development of cover-collapse sinkholes occurs underground and is generally undetectable at the ground surface until collapse occurs. This study presents a comprehensive review of 162 peer-reviewed journal articles, technical reports, and case studies to systematically identify the key factors governing the collapse range of cover-collapse sinkholes. This paper covers several influencing factors for collapse range of cover-collapse sinkholes, including soil properties, geometric characteristics of cavities and soil cover, hydraulic conditions, and the presence of buried structures. Among these factors, soil cohesion, friction angles, void ratio, soil cover thickness, and cavity geometry are identified as the key influencing factors for the collapse range of cover-collapse sinkholes. In addition, existing prediction methods were also summarized, which are predominantly empirical and have limited capability to capture the influence of multiple factors on the collapse range. Based on the literature review, this study finally identifies current research gaps and suggests future directions for developing more accurate and integrated models to predict collapse range of cover-collapse sinkholes. Full article

Cardiovascular diseases remain the leading cause of mortality in developed countries. Among these conditions, acute myocardial infarction (AMI) is associated with particularly high rates of cardiac morbidity and mortality. Cardiac development in mammals is primarily dependent on cardiomyocyte (CM) proliferation during embryonic and early postnatal stages. However, following birth, the proliferative capacity of CMs declines markedly, with only limited cellular renewal occurring during adult life in response to pathological injury. Consequently, the irreversible loss of functional cardiomyocytes and the subsequent formation of fibrotic scar tissue frequently lead to persistent cardiac dysfunction and progressive impairment of cardiac physiology. Cardiomyocyte self-renewal is a tightly regulated process involving multiple molecular pathways. Among factors implicated in this regulation, microRNAs (miRNAs) have emerged as key modulators coordinating both cardiac development and tissue repair mechanisms. In this context, extracellular vesicles (EVs) have attracted considerable interest as potential modulators of these regenerative processes. In particular, mesenchymal stromal cells (MSCs) represent a promising therapeutic platform due to their immunomodulatory and anti-fibrotic properties demonstrated across multiple in vitro and in vivo models. Furthermore, the therapeutic potential of MSC-derived EVs can be enhanced through bioengineering approaches aimed at improving targeted molecular delivery. In this review, we summarize recent advances in the development and application of EV-based therapeutic strategies, with particular emphasis on their potential use as advanced therapy medicinal products (ATMPs) for cardiovascular regeneration and repair. Full article

In urban environments with signal blockage and multipath effects, GNSS observation errors often exhibit temporal correlation. The Gaussian white noise assumption adopted in conventional tightly coupled Kalman filtering is prone to model mismatch under such conditions, which may lead to an underestimation of state uncertainty and consequently cause the protection level (PL) to fail to reliably bound the true positioning error. To address this issue, this paper proposes a tightly coupled GNSS/INS integrity monitoring method based on state augmentation and frequency-domain constrained parameter tuning. The method introduces first-order Gauss-Markov processes (GMP) to model major time-correlated error sources, including residual ephemeris and clock errors, residual tropospheric delay, and code multipath, by augmenting them into the filter state for joint estimation. The model parameters are further conservatively tuned based on power spectral density (PSD) envelope constraints to obtain more consistent covariance estimates. Based on this, the covariance output from the augmented filter is incorporated into the multiple hypothesis solution separation (MHSS) framework, enabling the protection level computation to better match the actual error statistics. Experimental results using vehicular field test data show that the proposed method effectively improves estimation consistency and significantly reduces the risk of PL underestimation in degraded environments. Furthermore, it achieves reliable bounding of horizontal positioning errors without noticeable degradation in positioning accuracy, while maintaining good system availability. These results demonstrate the effectiveness of covariance construction based on physical error modeling and PSD envelope constraints for integrity monitoring in complex environments. Full article