Identification Of Multiple Targets Research Articles

Enhancing autonomous vehicle navigation using SVM-based multi-target detection with photonic radar in complex traffic scenarios

Efficient transportation systems are essential for the development of smart cities. Autonomous vehicles and Intelligent Transportation Systems (ITS) are crucial components of such systems, contributing to safe, reliable, and sustainable transportation. They can reduce traffic congestion, improve traffic flow, and enhance road safety, thereby making urban transportation more efficient and environmentally friendly. We present an innovative combination of photonic radar technology and Support Vector Machine classification, aimed at improving multi-target detection in complex traffic scenarios. Central to our approach is the Frequency-Modulated Continuous-Wave photonic radar, augmented with spatial multiplexing, enabling the identification of multiple targets in various environmental conditions, including challenging weather. Notably, our system achieves an impressive range resolution of 7 cm, even under adverse weather conditions, utilizing an operating bandwidth of 4 GHz. This feature is particularly crucial for precise detection and classification in dynamic traffic environments. The radar system's low power requirement and compact design enhance its suitability for deployment in autonomous vehicles. Through comprehensive numerical simulations, our system demonstrated its capability to accurately detect targets at varying distances and movement states, achieving classification accuracies of 75% for stationary and 33% for moving targets. This research substantially contributes to ITS by offering a sophisticated solution for obstacle detection and classification, thereby improving the safety and efficiency of autonomous vehicles navigating through urban environments.

Immune checkpoint targeting antibodies hold promise for combinatorial cancer therapeutics.

Through improving the immune system's ability to recognize and combat tumor cells as well as its receptivity to changes in the tumor microenvironment, immunotherapy has emerged as a highly successful addition to the treatment of cancer. However, tumor heterogeneity poses a significant challenge in cancer therapy as it can undermine the anti-tumor immune response through the manipulation of the extracellular matrix. To address these challenges and improve targeted therapies and combination treatments, the food and drug administration has approved several immunomodulatory antibodies to suppress immunological checkpoints. Combinatorial therapies necessitate the identification of multiple targets that regulate the intricate communication between immune cells, cytokines, chemokines, and cellular responses within the tumor microenvironment. The purpose of this study is to provide a comprehensive overview of the ongoing clinical trials involving immunomodulatory antibodies in various cancer types. It explores the potential of these antibodies to modulate the immune system and enhance anti-tumor responses. Additionally, it discusses the perspectives and prospects of immunomodulatory therapeutics in cancer treatment. Although immunotherapy shows great promise in cancer treatment, it is not exempt from side effects that can arise due to hyperactivity of the immune system. Therefore, understanding the intricate balance between immune activation and regulation is crucial for minimizing these adverse effects and optimizing treatment outcomes. This study aims to contribute to the growing body of knowledge surrounding immunomodulatory antibodies and their potential as effective therapeutic options in cancer treatment, ultimately paving the way for improved patient outcomes and deepening our perception of the intricate interactivity between the immune system and tumors.

Structured Illumination Microscopy Improves Spot Detection Performance in Spatial Transcriptomics.

Spatial biology is a rapidly growing research field that focuses on the transcriptomic or proteomic profiling of single cells within tissues with preserved spatial information. Imaging-based spatial transcriptomics uses epifluorescence microscopy, which has shown remarkable results for the identification of multiple targets in situ. Nonetheless, the number of genes that can be reliably visualized is limited by the diffraction of light. Here, we investigate the effect of structured illumination (SIM), a super-resolution microscopy approach, on the performance of single-gene transcript detection in spatial transcriptomics experiments. We performed direct mRNA-targeted hybridization in situ sequencing for multiple genes in mouse coronal brain tissue sections. We evaluated spot detection performance in widefield and confocal images versus those with SIM in combination with 20×, 25× and 60× objectives. In general, SIM increases the detection efficiency of gene transcript spots compared to widefield and confocal modes. For each case, the specific fold increase in localizations is dependent on gene transcript density and the numerical aperture of the objective used, which has been shown to play an important role, especially for densely clustered spots. Taken together, our results suggest that SIM has the capacity to improve spot detection and overall data quality in spatial transcriptomics.

Unmixing Biological Fluorescence Image Data with Sparse and Low-Rank Poisson Regression.

Multispectral biological fluorescence microscopy has enabled the identification of multiple targets in complex samples. The accuracy in the unmixing result degrades (1) as the number of fluorophores used in any experiment increases and (2) as the signal-to-noise ratio in the recorded images decreases. Further, the availability of prior knowledge regarding the expected spatial distributions of fluorophores in images of labeled cells provides an opportunity to improve the accuracy of fluorophore identification and abundance. We propose a regularized sparse and low-rank Poisson unmixing approach (SL-PRU) to deconvolve spectral images labeled with highly overlapping fluorophores which are recorded in low signal-to-noise regimes. Firstly, SL-PRU implements multi-penalty terms when pursuing sparseness and spatial correlation of the resulting abundances in small neighborhoods simultaneously. Secondly, SL-PRU makes use of Poisson regression for unmixing instead of least squares regression to better estimate photon abundance. Thirdly, we propose a method to tune the SL-PRU parameters involved in the unmixing procedure in the absence of knowledge of the ground truth abundance information in a recorded image. By validating on simulated and real-world images, we show that our proposed method leads to improved accuracy in unmixing fluorophores with highly overlapping spectra. The source code used for this paper was written in MATLAB and is available with the test data at https://github.com/WANGRUOGU/SL-PRU. Supplementary data are available at Bioinformatics online.

Allopregnanolone: Regenerative therapeutic to restore neurological health

Chronic stress has been proposed as a driver of altered brain structure and function, including the pathogenesis of neurodegenerative diseases and a driver of disease progression. A key outcome of stress in the brain is structural remodeling of neural architecture, which may be a sign of successful adaptation, whereas persistence of these changes when stress ends indicate failed resilience. Neuroendocrine homeostasis and stress response are mainly dependent upon the functioning of the hypothalamic–pituitary–adrenal axis. Neurosteroids will fluctuate depending on whether the stress is acute or chronic. Advancements in neurosteroid research have led to the identification of multiple targets for drug development, but the most promising innovative target may be neurogenesis, given its potential impact in neurodegenerative disorders like Alzheimer's disease. Allopregnanolone is an endogenous pregnane neurosteroid and a reduced metabolite of progesterone, which acts as a potent allosteric modulator and direct activator of the GABA-chloride channel complex. Perhaps the most intriguing finding related to the potential therapeutic effects of allopregnanolone is its potential to promote neuroregeneration.

Multifactorial profiling of epigenetic landscapes at single-cell resolution using MulTI-Tag

Chromatin profiling at locus resolution uncovers gene regulatory features that define cell types and developmental trajectories, but it remains challenging to map and compare different chromatin-associated proteins in the same sample. Here we describe Multiple Target Identification by Tagmentation (MulTI-Tag), an antibody barcoding approach for profiling multiple chromatin features simultaneously in single cells. We optimized MulTI-Tag to retain high sensitivity and specificity, and we demonstrate detection of up to three histone modifications in the same cell: H3K27me3, H3K4me1/2 and H3K36me3. We apply MulTI-Tag to resolve distinct cell types and developmental trajectories; to distinguish unique, coordinated patterns of active and repressive element regulatory usage associated with differentiation outcomes; and to uncover associations between histone marks. Multifactorial epigenetic profiling holds promise for comprehensively characterizing cell-specific gene regulatory landscapes in development and disease.

Rapid immunohistological measurement of tyrosine hydroxylase in rat midbrain by near-infrared instrument-based detection

We present a robust, fresh-frozen approach to immunohistochemistry (IHC), without committing the tissue to IHC via fixation and cryopreservation while maintaining long-term storage, using LiCor-based infrared (IR) quantification for sensitive assessment of TH in immunoreacted midbrain sections for quantitative comparison across studies. In fresh-frozen tissue stored up to 1 year prior to IHC reaction, we found our method to be highly sensitive to rotenone treatment in 3-month-old Sprague-Dawley rats, and correlated with a significant decline in rotarod latency-to-fall measurement by approximately 2.5 fold. The measured midbrain region revealed a 31 % lower TH signal when compared to control (p < 0.01 by t test, n = 5). Bivariate analysis of integrated TH counts versus rotarod latency-to-fall indicates a positive slope and modest but significant correlation of R2 = 0.68 (p < 0.05, n = 10). These results indicate this rapid, instrument-based quantification method by IR detection successfully quantifies TH levels in rat brain tissue, while taking only 5 days from euthanasia to data output. This approach also allows for the identification of multiple targets by IHC with the simultaneous performance of downstream molecular analysis within the same animal tissue, allowing for the use of fewer animals per study.

Multiple Target Detection For OFDM Radar Based On Convolutional Neural Network

The objective of this paper is to propose a multiple target identification technique for orthogonal frequency division multiplexing (OFDM) radars. First, a 2-D (range &amp; Doppler) periodogram is obtained from the reflected signal through 2-D fast Fourier transform (FFT) of the received OFDM symbols. Usually, the peaks of the periodogram indicates the targets. Conventionally, peak search algorithms are used to find the multiple targets. In this paper, however, a convolutional neural network (CNN) classifier is proposed to identify the targets. The proposed technique does not need any additional information but the 2-D periodogram while the conventional method requires the noise variance as well as the periodogram. The performance is examined through computer simulation. According to the results, if the number of maximum identifiable targets are small, the proposed technique performs well. However, as the number increases, the detection accuracy decreases. In the simulation environments, the proposed method outperforms the conventional one. The proposed OFDM radar technique can be applied to 6G mobile communications to identify the moving targets around the transmitter without additional frequency resource for radar systems.

New Agents in Development for Sepsis: Any Reason for Hope?

Sepsis is a syndrome which is defined as a dysregulated host response to infection leading to organ failure. Since it remains one of the leading causes of mortality worldwide, numerous drug candidates have already been tested, and continue to be developed, as potential adjunct therapies. Despite convincing mechanisms of action and robust pre-clinical data, almost all drug candidates in the field of sepsis have failed to demonstrate clinical efficacy in the past two decades. Accordingly, the development of new sepsis drugs has markedly decreased in the past few years. Nevertheless, thanks to a better understanding of sepsis pathophysiology and pathways, new promising drug candidates are currently being developed. Instead of a unique sepsis profile as initially suspected, various phenotypes have been characterised. This has resulted in the identification of multiple targets for new drugs together with relevant biomarkers, and a better understanding of the most appropriate time to intervention. Within the entire sepsis drugs portfolio, those targeting the immune response are probably the most promising. Monoclonal antibodies targeting either cytokines or infectious agents are undoubtedly part of the potential successful therapeutic classes to come.

Seasonal phenotype-specific expression of microRNAs during metamorphosis in the European map butterfly Araschnia levana.

The European map butterfly (Araschnia levana) is a well-known example of seasonal polyphenism because the spring and summer imagoes exhibit distinct morphological phenotypes. The day length and temperature during larval and prepupal development determine whether spring or summer imagoes emerge after metamorphosis. Inspired by the fundamentally different transcriptomic profiles in prepupae developing from larvae exposed to long days or short days, we postulate that posttranscriptional epigenetic regulators such as microRNAs (miRNAs) may contribute to the epigenetic control of seasonal polyphenism in A. levana. To test this hypothesis, we used microarrays containing over 2,000 insect miRNAs to identify candidate regulators that are differentially expressed in last-instar larvae or pupae developing under long-day or short-day conditions. We used our transcriptomic database to identify potential 3'-untranslated regions of messenger RNAs to predict miRNA targets by considering both base pair complementarity and minimum free energy hybridization. This approach resulted in the identification of multiple targets of miRNAs that were differentially regulated in polyphenic morphs of A. levana including a candidate (miR-2856-3p) regulating the previously identified diapause bioclock protein gene. In conclusion, the expression profiling of miRNAs provided insights into their possible involvement in seasonal polyphenism of A. levana and offer an important resource for further studies.

Abstract 1187: Toward high-throughput, high-multiplex FFPE tumor tissue assays for translational research: 7-color, whole slide imaging

Abstract Background: Immuno-oncology research and predictive biomarkers discovery requires the ability to rapidly identify, quantify, and spatially map many cell sub-types of the tumor environment in FFPE tissue sections. Multiplexed immunofluorescence (IF) enables identification of multiple targets within separate spectral, or color, channels, which in turn enables more in-depth analysis of rare tissue material relative to traditional methods. Although many methods for multiplexed IF exist, they are often costly and require time-consuming assay development and long imaging times. The Ultivue® InSituPlex® technology enables rapid, optimized staining of multiple targets utilizing widely-used immunohistochemistry (IHC) staining and fluorescence imaging instrumentation. Here, we demonstrate the application of InSituPlex technology to image 6 targets and a nuclear counterstain in a 7-color single whole-slide scan, without linear unmixing-based image reconstruction. This technique expands the subtyping depth that can be achieved in a single imaging round and on a single section, and also increases sample-to-answer throughput with a streamlined, single-day workflow. Methods: InSituPlex technology was used to perform 6-plex immune profiling of different FFPE tumor sections. Slides were stained with a cocktail of primary antibodies using a Leica® Bond® RX autostainer and imaged on commercially available fluorescent slide scanners. Subsequent image analysis of the whole slide scans was carried out using Indica Labs HALO® software. Results: In this poster, we present an assay for pathology research that enables fast immuno-profiling in tumor tissues, using a streamlined staining workflow and 7-color imaging. Newly selected fluorophores were used with corresponding optical filter pairs, which increased the number of spectral channels available on commercially available slide scanners while limiting channel cross-talk. Analysis led to the identification of key immune cell phenotypes through marker colocalization without significant ambiguity between targets tagged with spectrally adjacent fluorescent labels. Conclusion: The newly-expanded fluorophore configuration of the InSituPlex technology enables high throughput identification of 6 targets and a nuclear counterstain on whole tumor sections, empowering translational and immuno-oncology research. Citation Format: Amanda J. Bares, Eloise M. Wheeler, Maël Manesse. Toward high-throughput, high-multiplex FFPE tumor tissue assays for translational research: 7-color, whole slide imaging [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1187.

Optimized ARROW-Based MMI Waveguides for High Fidelity Excitation Patterns for Optofluidic Multiplexing.

Multimode interference (MMI) waveguides can be used for multiplexing and de-multiplexing optical signals. High fidelity, wavelength dependent multi-spot patterns from MMI waveguides are useful for sensitive and simultaneous identification of multiple targets in multiplexed fluorescence optofluidic biosensors. Through experiments and simulation, this paper explores design parameters for an MMI rib anti-resonant reflecting optical waveguide (ARROW) in order to produce high fidelity spot patterns at the liquid core biomarker excitation region. Width and etch depth of the single excitation rib waveguide used to excite the MMI waveguide are especially critical because they determine the size of the input optical mode which is imaged at the MMI waveguide's output. To increase optical throughput into the MMI waveguide when light is coupled in from an optical fiber, tapers in the waveguide width can be used for better mode matching.

Fragile X syndrome

Fragile X syndrome (FXS) is the leading inherited form of intellectual disability and autism spectrum disorder, and patients can present with severe behavioural alterations, including hyperactivity, impulsivity and anxiety, in addition to poor language development and seizures. FXS is a trinucleotide repeat disorder, in which >200 repeats of the CGG motif in FMR1 leads to silencing of the gene and the consequent loss of its product, fragile X mental retardation 1 protein (FMRP). FMRP has a central role in gene expression and regulates the translation of potentially hundreds of mRNAs, many of which are involved in the development and maintenance of neuronal synaptic connections. Indeed, disturbances in neuroplasticity is a key finding in FXS animal models, and an imbalance in inhibitory and excitatory neuronal circuits is believed to underlie many of the clinical manifestations of this disorder. Our knowledge of the proteins that are regulated by FMRP is rapidly growing, and this has led to the identification of multiple targets for therapeutic intervention, some of which have already moved into clinical trials or clinical practice.

Preventive Effect and Safety of a Follicle Stimulating Hormone Inhibitory Formulation Containing a Mixture of Coicis Semen and Artemisia capillaris for Precocious Puberty: A Preliminary Experimental Study Using Female Rats.

Background Precocious puberty is a common endocrine disease in children. Inappropriate activation of hypothalamic–pituitary–gonadal axis leads to the development of secondary sexual characteristics at an earlier age than normal children and causes short stature in adulthood. Objectives The aim of this study is to evaluate the preventive effects of a herbal formulation containing a mixture of Coicis Semen and Artemisia capillaris (hEIF extract) on precocious puberty. Methods The preventive effect of hEIF extract on precocious puberty in rats was evaluated by measuring blood component after 3 weeks of treatment via oral administration. Network pharmacological analyses were performed to predict the bioactive components of hEIF extract. Results In vivo studies showed that hEIF extract significantly reduced follicle stimulating hormone (FSH) levels. After treatment with 200 mg/kg of hEIF extract, the FSH level was 5.33 ± 1.10 ng/mL, whereas the FSH level in the vehicle group was 46.73 ± 0.80 ng/mL. Moreover, the use of hEIF extract did not stimulate body growth and bone accretion in rats. The network pharmacological analysis led to the identification of multiple targets of hEIF extract related to lipolysis and the female sex hormone-related pathways. Conclusion hEIF extract can be used as an FSH inhibitor for the treatment of precocious puberty.

Bladder sensory physiology: neuroactive compounds and receptors, sensory transducers, and target-derived growth factors as targets to improve function.

Urinary bladder dysfunction presents a major problem in the clinical management of patients suffering from pathological conditions and neurological injuries or disorders. Currently, the etiology underlying altered visceral sensations from the urinary bladder that accompany the chronic pain syndrome, bladder pain syndrome (BPS)/interstitial cystitis (IC), is not known. Bladder irritation and inflammation are histopathological features that may underlie BPS/IC that can change the properties of lower urinary tract sensory pathways (e.g., peripheral and central sensitization, neurochemical plasticity) and contribute to exaggerated responses of peripheral bladder sensory pathways. Among the potential mediators of peripheral nociceptor sensitization and urinary bladder dysfunction are neuroactive compounds (e.g., purinergic and neuropeptide and receptor pathways), sensory transducers (e.g., transient receptor potential channels) and target-derived growth factors (e.g., nerve growth factor). We review studies related to the organization of the afferent limb of the micturition reflex and discuss neuroplasticity in an animal model of urinary bladder inflammation to increase the understanding of functional bladder disorders and to identify potential novel targets for development of therapeutic interventions. Given the heterogeneity of BPS/IC and the lack of consistent treatment benefits, it is unlikely that a single treatment directed at a single target in micturition reflex pathways will have a mass benefit. Thus, the identification of multiple targets is a prudent approach, and use of cocktail treatments directed at multiple targets should be considered.

All Oral HCV Therapies of the Future

Hepatitis C virus (HCV) therapy has revolved around pegylated interferon-alpha (PEG IFN) and ribavirin (RBV), with the recent addition of the direct-acting antivirals (DAA), telaprevir or boceprevir, to the regimen for genotype 1 patients. Further progress has been made with the identification of multiple targets, allowing for additional DAAs, including other protease inhibitors, NS5A inhibitors and NS5B polymerase inhibitors. Initial studies have shown these drugs to provide more effective therapy than the current standard of care when combined with PEG IFN and RBV. More recently, however, even without PEG IFN, combinations of DAAs have been shown to allow for shorter treatment duration, increased efficacy, and better safety profiles. These regimens have the potential to allow HCV to be eradicated with all oral therapy in the near future.

Visual search of experts in medical image reading: the effect of training, target prevalence, and expert knowledge.

The aims of this study are (a) To determine the effect of training on the multiple-target lesion search performance; and (b) To examine the effect of target prevalence on the performance of radiologists and novices. We conducted four sessions of 500 trials in a lesion search on a medical image task in which participants searched for three different target lesions. Participants were 10 radiologists and novices. In each session, the prevalence of the different target lesions varied from low (2%) to high (40%). The sensitivity of novices was higher in the later sessions than in the first session, whereas there were no differences among sessions in radiologists. The improvement on sensitivity of novices was largely due to attenuations of false alarm (FA) errors. In addition, miss rates of the three targets did not differ in data of novices, whereas radiologists produced a higher miss rate for the highest prevalence target lesion (non-serious lesion) than for the other two lesions (serious lesions). The conclusions are (a) The training for the multiple-target lesion search task can be effective to reduce FA errors; and (b) The prevalence effect on lesion search can be attenuated by the multiple-target identification and the knowledge about seriousness of lesions. This suggests that acquired knowledge about normal cases and serious lesions is an important aspect of a radiologists’ skill in searching for medical lesions and their high performance levels.

Addiction Therapeutics: Obstacles and Opportunities

Research over the past 2 decades has led to a fundamental understanding of the neurobiological bases of addiction (1). These insights have resulted in the identification of multiple targets (2), many already proven drugable, that could potentially revolutionize the treatment of substance use disorders (SUDs). Nonetheless, the goal of developing highly effective medications to treat SUDs remains largely unmet. Thus, there are no medications approved to treat either stimulant or cannabis use disorders, and the efficacy of available therapies for other SUDs (e.g., opiates, tobacco, alcohol) is far from ideal. The dearth of innovative medications to treat SUDs has been attributed to a low level of interest by the pharmaceutical and biotechnology sectors, a problem exacerbated by the retrenchment in psychiatry research and development (3). However, both the number of potential targets (2) and the molecules that have either failed in other psychiatric indications or are now parked for strategic reasons make SUDs an attractive rescue indication. In this commentary, we will briefly summarize some of the principal obstacles to developing medications for SUDs (reviewed in [4]), as well as some recent developments, including the report by Mariani et al. (5), that offer new therapeutic opportunities.

Inverse filtering of radar signals using compressed sensing with application to meteors

Compressed sensing, a method which relies on sparsity to reconstruct signals with relatively few measurements, provides a new approach to processing radar signals that is ideally suited to detailed imaging and identification of multiple targets. In this paper, we extend previously published theoretical work by investigating the practical problems associated with this approach. In deriving a discrete linear radar model that is suitable for compressed sensing, we discuss what the discrete model can tell us about continuously defined targets and show how sparsity in the latter translates to sparsity in the former. We provide details about how this problem can be solved when using large data sets. Through comparisons with matched filter processing, we validate our compressed sensing technique and demonstrate its application to meteors, where it has the potential to answer open questions about processes like fragmentation and flares. At the cost of computational complexity and an assumption of target sparsity, the benefits over pulse compression using a matched filter include no filtering sidelobes, noise removal, and higher possible range and Doppler frequency resolution.

Microwave Imaging: Identification of Multiple Targets Using an Enhancement Hybrid Method

Absract A new hybrid method for a complete identification of multiple scattering two-dimensional objects using microwaves is proposed in this study, where the scatterers are assumed to be separated with different homogenous dielectric mediums. The hybrid approach consists of initially retrieving the shape and the position of the scattering objects using a linear sampling method and then determining the electric permittivity and conductivity of the scatterers using an intelligent and deterministic method—the so-called adjoint sensitivity analysis. This approach is technically correct and well organized, which results in high computational speed, efficiency, and stability. In addition, the technique can be generalized for any scatterer structure. Numerical results are used to validate the feasibility of the approach proposed.