Target Region Research Articles

Can eDNA Present in Aquatic Environments of Rural Areas Help Identify Species Diversity in the Order Anura?

Paddy fields are classified as wetland environments, and they comprise freshwater ecosystems. They are ecologically important habitats and breeding grounds for many aquatic insects, amphibians, and reptiles. However, paddy field ecosystems are constantly threatened by climate change and the indiscriminate use of pesticides. The metabarcode analysis of eDNA (environmental DNA) method is highly effective at accumulating information on many organisms that inhabit paddy field ecosystems. It can indirectly identify the existence of taxa that are no longer found in the target ecosystem due to behavioral characteristics, such as those exhibited by amphibians. In the metabarcoding results of this study, genes of five species of frogs were found, but it was impossible to confirm all of the frogs’ taxa, morphological pictures, and croak sounds. On the other hand, some frog taxa were only found in the metabarcoding analysis. The eDNA of the frogs found only in the metabarcoding analysis is estimated to have been introduced from nearby areas inhabited by frogs rather than the target region. Due to the powerful analytical resolution of eDNA metabarcoding, this eDNA-based paddy field search is expected to help investigate the biodiversity in agricultural ecosystems.

Canine Multiple System Degeneration Associated with Sequence Variants in SERAC1

Canine multiple system degeneration (CMSD) is an early onset, progressive movement disorder affecting Kerry Blue Terriers and Chinese Crested dogs. The associated pathologic lesions include degeneration of the cerebellum, caudate nucleus, and substantia nigra. CMSD is inherited as an autosomal recessive trait in both dog breeds. Previous linkage mapping localized the CMSD locus to a 15 MB region on canine chromosome 1 (CFA1). Next-generation sequencing was used to generate whole-genome sequences from the DNA of an affected dog from each breed. The resulting sequence reads were aligned to the NCBI canine reference genome (build 3.1). Among the homozygous sequence variants within the CFA1 target region, a nonsense variant in exon 15 of SERAC1 was identified in the affected Kerry Blue Terrier, while in the Chinese Crested dog, a 4 bp deletion in the SERAC1 exon 4 acceptor splice site was found. RT-PCR showed that this deletion resulted in exon 4 skipping. Genotyping of large cohorts of Kerry Blue Terriers and Chinese Crested dogs for the respective breed-specific SERAC1 variants showed complete concordance between genotype and disease phenotype. Genotype–phenotype concordance was also observed in offspring generated by cross breeding between SERAC1-heterozygous Kerry Blue Terrier and Chinese Crested dogs, with only the compound heterozygotes exhibiting the disease phenotype, further confirming the recessive inheritance of CMSD. Variants in human SERAC1 are associated with disorders with a range of ages of disease onset and patterns of clinical signs, but that are all characterized by movement abnormalities similar to those of the dogs with CMSD. Canine CMSD could serve as a valuable model to elucidate the mechanisms underlying SERAC1-deficiency disorders and to evaluate potential therapeutic interventions.

Automated planning of curved needle channels in 3D printed patient-tailored applicators for cervical cancer brachytherapy.

Purpose&#xD;Patient-tailored intracavitary/interstitial (IC/IS) brachytherapy (BT) applicators may increase dose conformity in cervical cancer patients. Current configuration planning methods in these custom applicators rely on manual specification or a small set of (straight) needles. This work introduces and validates a two-stage approach for establishing channel configurations in the 3D printed patient-tailored ARCHITECT applicator. &#xD;&#xD;Methods&#xD;For each patient, the patient-tailored applicator shape was based on the first BT application with a commercial applicator and integrated connectors to a commercial (Geneva) intrauterine tube and two lunar ring channels. First, a large candidate set was generated of channels that steer the needle to desired poses in the target region and are contained in the applicator. The channels' centrelines were represented by Bézier curves. Channels running between straight target segments and entry points were optimised and refined to ensure (dynamic) feasibility. Second, channel configurations were selected using geometric coverage optimisation. This workflow was applied to establish patient-tailored geometries for twenty-two patients previously treated using the Venezia applicator. Treatment plans were automatically generated using the in-house developed algorithm BiCycle. Plans for the clinically used configuration, TPclin, and patient-tailored configuration, TParch, were compared.&#xD;&#xD;Results&#xD;Channel configurations could be generated in clinically feasible time (median: 2651s, range 1826-3812s). All TParchand TPclinplans were acceptable, but planning aims were more frequently attained with patient-tailored configurations (115/132 versus 100/132 instances). Median CTVIRD98and bladderD2cm3doses significantly improved (p< 0.001 andp< 0.01 respectively) in TParchplans in comparison with TPclinplans, and in approximately half of the patients dosimetric indices improved. &#xD;&#xD;Conclusion&#xD;Automated patient-tailored BT channel configuration planning for 3D printed applicators is clinically feasible. A treatment planning study showed that all plans met planning limits for the patient-tailored configurations, and in selected cases improved the plan quality in comparison with commercial applicator configurations.&#xD.

Binding profiles for 961 Drosophila and C. elegans transcription factors reveal tissue-specific regulatory relationships.

A catalog of transcription factor (TF) binding sites in the genome is critical for deciphering regulatory relationships. Here we present the culmination of the efforts of the Model Organism ENCyclopedia Of DNA Elements (modENCODE) and the model organism Encyclopedia of Regulatory Networks (modERN) consortia to systematically assay TF binding events in vivo in two major model organisms, Drosophila melanogaster (fly) and Caenorhabditis elegans (worm). These datasets comprise 605 TFs identifying 3.6M sites in the fly and 356 TFs identifying 0.9 M sites in the worm and represent the majority of the regulatory space in each genome. We demonstrate that TFs associate with chromatin in clusters termed "metapeaks", that larger metapeaks have characteristics of high occupancy target (HOT) regions, and that the importance of consensus sequence motifs bound by TFs depends on metapeak size and complexity. Combining ChIP-seq data with single cell RNA-seq data in a machine learning model identifies TFs with a prominent role in promoting target gene expression in specific cell types, even differentiating between parent-daughter cells during embryogenesis. These data are a rich resource for the community that should fuel and guide future investigations into TF function. To facilitate data accessibility and utility, all strains expressing GFP-tagged TFs are available at the stock centers for each organism. The chromatin immunoprecipitation sequencing data are available through the ENCODE Data Coordinating Center, GEO, and through a direct interface that provides rapid access to processed data sets and summary analyses, as well as widgets to probe the cell type-specific TF-target relationships.

Advanced Object Tracking through Conditional Online Updates and Noise Suppression

Object tracking under complex environmental conditions, such as background clutter, occlusion, and rapid motion, presents significant challenges. This paper addresses these issues by proposing a tracking algorithm integrating background suppression, target region enhancement, and an adaptive online template update mechanism to improve tracking accuracy. The proposed method uses the initial bounding box of the target object as a reference template and selectively updates specific regions online to suppress noise and retain critical features. We evaluated the proposed method using the OTB dataset to validate it. The baseline model without the proposed method showed a success rate of 0.417 and a precision of 0.586, while the algorithm with the proposed method achieved improved values of 0.524 and 0.728, respectively. Qualitative evaluations further confirmed the robustness of the proposed method, demonstrating high performance in scenarios with occlusion and complex backgrounds. Rather than updating all regions indiscriminately, the proposed method selectively updates the template using representative values from the target object's information. This selective update mechanism ensures the incorporation of the most relevant and accurate features, enabling the algorithm to adapt to changes in the target's appearance while minimizing noise integration. Emphasizing the feature regions and suppressing noise are also critical for maintaining a clear and precise representation of the target object, reducing the likelihood of confusion by irrelevant background information. Future research will focus on developing balanced update strategies that integrate new information while maintaining stable and reliable target characteristics.

Improving cross-regional model transfer performance in crop classification by crop time series correction

ABSTRACT Cross-Regional Model Transfer (CRMT) provides a solution to crop classification challenges in target regions with limited labeled samples. However, when the source region (source domain) and the target region (target domain) are spatially distant, a shift in crop Satellite Image Time Series (SITS) occurs, resulting in suboptimal performance of SITS-based classification models in the target domain. To address this issue, we propose a novel domain adaptation method, named SITS Correction. This method mitigates the SITS shift by introducing correction factors to improve the classification performance of CRMT. The correction factors consist of source domain correction units and target domain correction units, which are from variables associated with the SITS shift. In cases where labeled samples are available in the target domain, the SITS have calculated Barycenter (i.e. SitsB) as the correction units, which then combine the source domain and the target domain’s SitsB to form a SITS-based correction factor. When no labeled samples are available, the correction units are substituted by Barycenter of the temperature variables time series (i.e. temperature indicator) influencing crop growth, and the correction factors are composed of temperature indicators from both the source and target domains. We validate SITS Correction through transfer experiments conducted in four regions, encompassing various years, crops, and classification methods. Experimental results demonstrate a significant improvement in crop classification performance with SITS Correction in both scenarios – target domain with labeled samples (accuracy increased by 39.1%) and target domain without labeled samples (accuracy increased by 14.8%). This research provides a practical option for crop classification in target regions with either limited or no labeled samples.

Efficient path planning for autonomous vehicles based on RRT* with variable probability strategy and artificial potential field approach.

With the rapid development of autonomous driving technology, path planning has gained significant attention as it holds great potential for improving safety. The Rapidly-exploring Random Tree star(RRT*) algorithm has attracted much attention because of its good adaptability and expansibility. However, how solving problems in the RRT* algorithm such as slow convergence time, significant search range randomness, and unpredictability is a challenge. Therefore, an RRT* enhancement algorithm combining variable probability goal-bias strategy and artificial potential field(APF) method(Improved A-RRT*) is proposed in this paper. Firstly, the variable probability goal-bias strategy is introduced in the sampling process to make random tree expand towards the target direction and improve the directional searchability of the random tree. Secondly, the potential field function in APF is improved to prevent falling into local optimum problems during path generation. Thirdly, improved APF is combined with RRT*, the target generates a gravitational field on random tree, and the obstacle generates a repulsive force on it, leading random tree to grow toward the target region. Finally, the proposed algorithm is compared with RRT* algorithm and its derivative algorithm. The experimental results demonstrate that the proposed algorithm has obvious optimizations in convergence speed and path quality.

Nanomagnetic Guidance Shapes the Structure-Function Relationship of Developing Cortical Networks.

In this study, we implement large-scale nanomagnetic guidance on cortical neurons to guide dissociated neuronal networks during development. Cortical networks cultured over microelectrode arrays were exposed to functionalized magnetic nanoparticles, followed by magnetic field exposure to guide neurites over 14 days in vitro. Immunofluorescence of the axonal protein Tau revealed a greater number of neurites that were longer and aligned with the nanomagnetic force relative to nonguided networks. This was further confirmed through brightfield imaging on the microelectrode arrays during development. Spontaneous electrophysiological recordings revealed that the guided networks exhibited increased firing rates and frequency in force-aligned connectivity identified through Granger Causality. Applying this methodology across networks with nonuniform force directions increased local activity in target regions, identified as regions in the direction of the nanomagnetic force. Altogether, these results demonstrate that nanomagnetic forces guide the structure and function of dissociated cortical neuron networks at the millimeter scale.

Engineering Budesonide Microparticles for Enhancing Pulmonary Targeting: Validation through In Vivo Investigations

AbstractThe study aimed to develop and evaluate budesonide inhalation micro‐suspension to target inflammation in the lower trachea and bronchi. Initially, the slurry phase is prepared by dispersing the drug (0.25 and 0.5 mg ml−1) in the Water for Injection with polysorbate 80. The slurry is mixed with the aqueous phase comprising other excipients. The mixture is further subjected to the treatment with homogenizer. The prepared formulations are subjected to various physio‐chemical analysis like description, density, pH, osmolality, viscosity, shelf life, impurities, assay, particle size, etc. Andersen cascade impactor is used to estimate the aerodynamic performance. In vivo analysis is initiated with the induction of Asthma in Sprague Dawley rats by ovalbumin challenge intranasally and the treatment is given with the aid of a nebulizer. Lastly, the biochemical estimations are carried out in blood and bronchoalveolar lavage fluid (BALF). The lungs are also subjected to morphological and histological evaluations. The physio‐chemical and analytical examination indicated a stable formulation that is compliant with the standard guidelines. The D90 value of the test formulation is ≤4.5 µm. Cascade impactor evaluation estimated almost, 2–10% higher amount of budesonide reaching the target region as compared to the marketed product. Test formulation attenuated the manifestation of ovalbumin‐induced asthma through suppression of inflammatory cell count in blood and BALF, and modulation of Lactate dehydrogenase and Alkaline Phosphatase levels which is further confirmed by histopathological analysis. The formulated budesonide micro‐suspension demonstrated stability, safety, and efficient delivery to the target site.

Effects of fMRI neurofeedback of right inferior frontal cortex on inhibitory brain activation in children with ADHD.

We aimed to replicate previous effects of functional magnetic resonance imaging neurofeedback (fMRI-NF) in right inferior frontal cortex (rIFC) on IFC activation during a Stop Task in a larger group of boys with attention-deficit/hyperactivity disorder (ADHD). The present double-blind, randomized controlled trial tested the effects of 15 runs of active versus sham fMRI-NF of rIFC on performance and activation associated with successful and failed inhibition versus Go trials during a tracking Stop task in 88 boys with ADHD (44 active; 44 sham), controlling for age and medication status. No significant group-by-time interaction effects were observed for performance or brain activation during the successful stop trials, and post hoc analysis showed very low numbers of active fMRI-NF learners. Nevertheless, during error monitoring, there was a significant group-by-time interaction effect on post-error reaction time slowing and in left IFC activation, which were both increased after active compared to sham fMRI-NF. The findings are in line with our previous observation of left IFC upregulation after fMRI-NF of rIFC relative to active fMRI-NF of parahippocampal gyrus. This highlights the potentially wider regional effects that fMRI-NF of a particular self-control target region has on other self-regulatory regions in ADHD. This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

The DLPFC is centrally involved in resolving Stroop conflicts, suppressing distracting sensory input within the auditory and visual system.

Cognitive control is a prerequisite for successful, goal-oriented behavior. The dorsolateral prefrontal cortex (DLPFC) is assumed to be a key player in applying cognitive control; however, the neural mechanisms by which this process is accomplished are still unclear. To further address this question, an audiovisual Stroop task was used, comprising simultaneously presented pictures and spoken names of actors and politicians. Depending on the task block, participants had to indicate whether they saw the face or heard the name of a politician or an actor (visual vs. auditory blocks). In congruent trials, both stimuli (visual and auditory) belonged to the same response category (actor or politician); in incongruent trials, they belonged to different categories. During this task, activity in sensory target regions was measured via functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG), respectively. Specifically, fNIRS was used to monitor activity levels within the auditory cortex, while the EEG-based event-related potential of the N170 was considered as a marker of FFA (fusiform face area) involvement. Additionally, we assessed the effects of inhibitory theta-burst stimulation-a specific protocol based on repetitive transcranial magnetic stimulation (rTMS)-over the right DLPFC. Non-invasive brain stimulation is one of the few means to draw causal conclusions in human neuroscience. In this case, rTMS was used to temporarily inhibit the right DLPFC as a presumed key player in solving Stroop conflicts in one of two measurement sessions; then, effects were examined on behavioral measures as well as neurophysiological signals reflecting task-related activity in the frontal lobes and sensory cortices. The results indicate a central role of the DLPFC in the implementation of cognitive control in terms of a suppression of distracting sensory input in both the auditory cortex and visual system (FFA) in high-conflict situations. Behavioral data confirm a reduced Stroop effect following previous incongruent trials ("Gratton effect") that was only accomplished with an intact DLPFC (i.e., following placebo stimulation). Because non-invasive brain stimulation is uniquely suited to causally test neuroscientific hypotheses in humans, these data give important insights into some of the mechanisms by which the DLPFC establishes conflict resolution across different sensory modalities.

Camellia oleifera trunks detection and identification based on improved YOLOv7

SummaryCamellia oleifera typically thrives in unstructured environments, making the identification of its trunks crucial for advancing agricultural robots towards modernization and sustainability. Traditional target detection algorithms, however, fall short in accurately identifying Camellia oleifera trunks, especially in scenarios characterized by small targets and poor lighting. This article introduces an enhanced trunk detection algorithm for Camellia oleifera based on an improved YOLOv7 model. This model incorporates dynamic snake convolution instead of standard convolutions to bolster its feature extraction capabilities. It integrates more contextual information, thus enhancing the model's generalization ability across various scenes. Additionally, coordinate attention is introduced to refine the model's spatial feature representation, amplifying the network's focus on essential target region features, which in turn boosts detection accuracy and robustness. This feature selectively strengthens response levels across different channels, prioritizing key attributes for classification and localization. Moreover, the original coordinate loss function of YOLOv7 is replaced with EIoU loss, further enhancing the model's robustness and convergence speed. Experimental results demonstrate a recall rate of 96%, a mean average precision (mAP) of 87.9%, an F1 score of 0.87, and a detection speed of 18 milliseconds per frame. When compared with other models like Faster‐RCNN, YOLOv3, ScaledYOLOv4, YOLOv5, and the original YOLOv7, our improved model shows mAP increases of 8.1%, 7.0%, 7.5%, and 6.6% respectively. Occupying only 70.8 MB, our model requires 9.8 MB less memory than the original YOLOv7. This model not only achieves high accuracy and detection efficiency but is also easily deployable on mobile devices, providing a robust foundation for future intelligent harvesting technologies.

Quantifying free tropospheric moisture sources over the western tropical Atlantic with numerical water tracers and isotopes

AbstractTropical free‐tropospheric humidity plays a crucial role for the Earth's radiative balance and climate sensitivity. In addition to atmospheric humidity, stable water isotopes can provide important information about the hydrological cycle. We use the isotope‐ and water tagging‐enabled version of the COSMOiso model to determine isotopic fingerprints of diagnosed moisture pathways over the western tropical Atlantic (WTA). A convection‐permitting, high‐resolution (5 km) nudged simulation is performed for January–February 2020. During this period, the target region is characterized by alternating large‐scale circulation regimes with different humidity and isotope signatures. Moist conditions in the middle troposphere (300–650 hPa) are associated with moisture transport from the south, east, southeast, as well as evaporation from the North Atlantic, while dry conditions correspond to extratropical transport from the north and west. To predict the contribution of different moisture sources, we used a statistical model based on the local specific humidity and temperature as predictors and obtained an R‐squared (R2) of 0.52. Adding water isotopes improved the prediction (R2 = 0.73), showing that isotopes provide unique information on moisture sources and transport patterns beyond conventional local observations.

Research on Radar Target Detection Based on the Electromagnetic Scattering Imaging Algorithm and the YOLO Network

In this paper, the radar imaging technology based on the time-domain (TD) electromagnetic scattering algorithm is used to generate image datasets quickly and apply them to target detection research. Considering that radar images are different from optical images, this paper proposes an improved strategy for the traditional You Only Look Once (YOLO)v3 network to improve target detection accuracy on radar images. The speckle noise in radar images can cover the real information of a target image and increase the difficulty of target detection. The attention mechanisms are added to the traditional YOLOv3 network to strengthen the weight of the target region. By comparing the target detection accuracy under different attention mechanisms, an attention module with higher detection accuracy is obtained. The validity of the proposed detection network is verified on a simulation dataset, a measured real dataset, and a mixed dataset. This paper is about an interdisciplinary study of computational electromagnetics, remote sensing, and artificial intelligence. Experiments verify that the proposed composite network has better detection performance.

Genome-wide association study revealed some new candidate genes associated with flowering and maturity time of soybean in Central and West Siberian regions of Russia.

The duration of flowering and maturity is an important agricultural trait determining the suitability of a variety for cultivation in the target region. In the present study, we used genome-wide association analysis (GWAS) to search for loci associated with soybean flowering and maturity in the Central and West Siberian regions of Russia. A field experiment was conducted in 2021/2022 at two locations (Orel and Novosibirsk). A germplasm collection of 180 accessions was genotyped using SoySNP50K Illumina Infinium Bead-Chip. From the initial collection, we selected 129 unrelated accessions and conducted GWAS on this dataset using two multi-locus models: FarmCPU and BLINK. As a result, we identified 13 loci previously reported to be associated with duration of soybean development, and 17 new loci. 33 candidate genes were detected in these loci using analysis of co-expression, gene ontology, and literature data, with the best candidates being Glyma.03G177500, Glyma.13G177400, and Glyma.06G213100. These candidate genes code the Arabidopis orthologs TOE1 (TARGET OF EAT 1), SPL3 (SQUAMOSA PROMOTER BINDING PROTEIN LIKE 3), the DELLA protein, respectively. In these three genes, we found haplotypes which may be associated with the length of soybean flowering and maturity, providing soybean adaptation to a northern latitudes.

A systematic approach for scoping potential key biodiversity areas

AbstractThe new key biodiversity areas (KBA) standard is an important method for identifying regions of the planet‐hosting unique biodiversity. KBAs are identified through the implementation of threshold‐based criteria that can be applied to any target species and region. Current methods to rapidly assess the existence of potential KBAs in different areas of the planet still present important challenges, although they are needed to accelerate the KBA identification process for large numbers of species globally. We developed a methodology to scan geographical regions and detect potential KBAs under multiple criteria. We tested the methodology on 59 species of reptiles and amphibians in Italy through the application of selected KBA criteria. Potential KBAs were identified for multiple species under most criteria, covering 1.4%–12% of the study area, depending on analytical settings. Cell size used to identify KBAs played an important role in shaping the distribution of potential KBAs, also affecting the overlap between areas triggered by different criteria. New potential KBAs identified in this study are only partially coincident with current KBAs in Italy (previously identified for birds) and within the national protected areas.

Three-dimensional radiation dosimetry of carbon ion beams using surfactant hydrogels: Fundamental investigation.

In carbon ion radiotherapy, accurate measurement of the three-dimensional (3D) absorbed dose distribution is critical for effectively targeting tumors. Although micellar gel dosimeters exhibit considerable potential for measuring 3D absorbed dose distributions, few studies have focused on radiotherapy using carbon ion beams. This study investigated the applicability of the surfactant hydrogel dosimeter (SHD), a micellar gel dosimeter, to measuring a 3D dose absorbed through carbon ion beam irradiation. A cubic target region of 34mm per side was established at a depth of 46mm below the upper surface of an SHD specimen. Scanning irradiation was performed using a pencil beam of carbon ions at the Ion-beam Radiation Oncology Center in Kanagawa ("i-ROCK"), Japan, under irradiation conditions set by the treatment planning system ("Monaco for Carbon", Ver. 5.20, Elekta AB, Sweden) to create a spread-out Bragg peak within the target. The physical dose was set to 10Gy at the isocenter, situated at the center of the target. The SHD responsiveness was measured twice using optical computed tomography (CT) ("Vista 15", Modus Medical Devices, Canada) for three irradiated specimens, and six types of measured optical attenuation coefficient (OAC) were obtained. To assess whether the OAC represented the absorbed dose expected in the treatment plan, we compared the relative distribution of the OAC and that of the absorbed dose. Relative fraction (RF) was used to measure the difference between the relative value of the OAC and that of the absorbed dose. Moreover, the distribution of OH radical (•OH) concentration obtained by Monte Carlo simulation ("PHITS" ver. 3.24 JAEA, Japan) and that of the OAC were compared. In the direction of beam travel, the relative distribution of the OAC was lower than that of the absorbed dose. This discrepancy could be attributed to a decrease in the concentration of •OH produced by irradiation owing to the recombination reaction, which does not accurately reflect the absorbed dose. By contrast, the distributions in the plane perpendicular to the beam travel were consistent. The RF increased from±3% to±13% along the beam travel direction. The small RF in the plane perpendicular to the beam travel could be attributed to the constant distribution of linear energy transfer, regardless of the irradiation position, and the generation of radicals proportionally to the absorbed dose. The increase in RF along the beam travel direction was ascribed to ring artifacts in the irradiated region. The measurement of the absorbed dose distribution in the beam travel direction should be improved. The observed discrepancy is attributed to the reduced reactivity of the SHD due to a high liner energy transfer near the Bragg peak. However, the absorbed dose distribution can be effectively evaluated in the plane perpendicular to the direction of beam travel.

Gradient descent optimization of acoustic holograms for transcranial focused ultrasound

Acoustic holographic lenses, also known as acoustic holograms, can change the phase of a transmitted wavefront in order to shape and construct complex ultrasound pressure fields, often for focusing the acoustic energy on a target region. These lenses have been proposed for transcranial focused ultrasound (tFUS) to create diffraction-limited focal zones that target specific brain regions while compensating for skull aberration. Holograms are currently designed using time-reversal approaches in full-wave time-domain numerical simulations. Such simulations need time-consuming computations, which severely limits the adoption of iterative optimization strategies. In the time-reversal method, the number and distribution of virtual sources can significantly influence the final sound field. Because of the computational constraints, predicting these effects and determining the optimal arrangement is challenging. This study introduces an efficient method for designing acoustic holograms using a volumetric holographic technique to generate focused fields inside the skull. The proposed method combines a modified mixed-domain method for ultrasonic propagation with a gradient descent iterative optimization algorithm. The findings are further validated in underwater experiments with a realistic 3D-printed skull phantom. This approach enables substantially faster holographic computation than previously reported techniques. The iterative process uses explicitly defined loss functions to bias the ultrasound field’s optimization parameters to specific desired characteristics, such as axial resolution, transversal resolution, coverage, and focal region uniformity, while eliminating the uncertainty associated with virtual sources in time-reversal techniques. The proposed techniques enable more rapid hologram computation and more flexibility in tailoring ultrasound fields for specific therapeutic requirements.

Enhancing Variant Calling in Whole-Exome Sequencing Data Using Population-Matched Reference Genomes.

Whole-exome sequencing (WES) data are frequently used for cancer diagnosis and genome-wide association studies (GWAS), based on high-coverage read mapping, informative variant calling, and high-quality reference genomes. The center position of the currently used genome assembly, GRCh38, is now challenged by two newly published telomere-to-telomere (T2T) genomes, T2T-CHM13 and T2T-YAO, and it becomes urgent to have a comparative study to test population specificity using the three reference genomes based on real case WES data. Here we report our analysis along this line for 19 tumor samples collected from Chinese patients. The primary comparison of the exon regions among the three references reveals that the sequences in up to ∼ 1% target regions in T2T-YAO are widely diversified from GRCh38 and may lead to off-target in sequence capture. However, T2T-YAO still outperforms GRCh38 genomes by obtaining 7.41% more mapped reads. Due to more reliable read-mapping and closer phylogenetic relationship with the samples than GRCh38, T2T-YAO reduces half of variant calls of clinical significance which are mostly benign, while maintaining sensitivity in identifying pathogenic variants. T2T-YAO also outperforms T2T-CHM13 in reducing calls of Chinese-specific variants. Our findings highlight the critical need for employing population-specific reference genomes in genomic analysis to ensure accurate variant analysis and the significant benefits of tailoring these approaches to the unique genetic backgrounds of each ethnic group.

Occurrence of human infection with Salmonella Typhi in sub-Saharan Africa

Typhoid fever, caused by Salmonella enterica serovar Typhi, results in over 1.2 million cases and 29 thousand deaths annually from sub-Saharan Africa. Combating this disease requires various intervention approaches, such as typhoid conjugate vaccines and improving water, sanitation, and hygiene. Enhancing the effectiveness of these strategies necessitates a deeper understanding of the variation of the typhoid fever across the target region. Although the magnitude and variation of typhoid fever at the country level have been studied globally, sub-national variation remains underexplored. To address this gap, we collected data from 229 published reports on typhoid fever occurrences in sub-Saharan Africa between January 2000 and December 2020. The dataset includes information on the year and geographical location of observation, diagnostic tests used, and the type of studies in which typhoid fever was reported. By analyzing this dataset, we can gain insights into the sub-national heterogeneity of typhoid fever’s burden in the region. This knowledge will be instrumental in designing more effective intervention strategies to combat the disease.