The mitochondrial genome of Bottapotamon fukienense (Brachiura: Potamidae) is fragmented into two chromosomes.

BACKGROUND: China is the hotspot of global freshwater crab diversity, but their wild populations are facing severe pressures associated with anthropogenic factors, necessitating the need to map their taxonomic and genetic diversity and design conservation policies. RESULTS: Herein, we sequenced the mitochondrial genome of a Chinese freshwater crab species Bottapotamon fukienense, and found that it is fragmented into two chromosomes. We confirmed that fragmentation was not limited to a single specimen or population. Chromosome 1 comprised 15,111 base pairs (bp) and there were 26 genes and one pseudogene (pseudo-nad1) encoded on it. Chromosome 2 comprised 8,173 bp and there were 12 genes and two pseudogenes (pseudo-trnL2 and pseudo-rrnL) encoded on it. Combined, they comprise the largest mitogenome (23,284 bp) among the Potamidae. Bottapotamon was the only genus in the Potamidae dataset exhibiting rearrangements of protein-coding genes. Bottapotamon fukienense exhibited average rates of sequence evolution in the dataset and did not differ in selection pressures from the remaining Potamidae. CONCLUSIONS: This is the first experimentally confirmed fragmentation of a mitogenome in crustaceans. While the mitogenome of B. fukienense exhibited multiple signs of elevated mitogenomic architecture evolution rates, including the exceptionally large size, duplicated genes, pseudogenisation, rearrangements of protein-coding genes, and fragmentation, there is no evidence that this is matched by elevated sequence evolutionary rates or changes in selection pressures.

Age-related differences in the loss and recovery of serial sarcomere number following disuse atrophy in rats.

BACKGROUND: Older adults exhibit a slower recovery of muscle mass following disuse atrophy than young adults. At a smaller scale, muscle fibre cross-sectional area (i.e., sarcomeres in parallel) exhibits this same pattern. Less is known, however, about age-related differences in the recovery of muscle fibre length, driven by increases in serial sarcomere number (SSN), following disuse. The purpose of this study was to investigate age-related differences in SSN adaptations and muscle mechanical function during and following muscle immobilization. We hypothesized that older adult rats would experience a similar magnitude of SSN loss during immobilization, however, take longer to recover SSN than young following cast removal, which would limit the recovery of muscle mechanical function. METHODS: We casted the plantar flexors of young (8 months) and old (32 months) male rats in a shortened position for 2 weeks, and assessed recovery during 4 weeks of voluntary ambulation. Following sacrifice, legs were fixed in formalin for measurement of soleus SSN and physiological cross-sectional area (PCSA) with the un-casted soleus acting as a control. Ultrasonographic measurements of pennation angle (PA) and muscle thickness (MT) were conducted weekly. In-vivo active and passive torque-angle relationships were constructed pre-cast, post-cast, and following 4 weeks of recovery. RESULTS: From pre- to post-cast, young and older adult rats experienced similar decreases in SSN (-20%, P < 0.001), muscle wet weight (-25%, P < 0.001), MT (-30%), PA (-15%, P < 0.001), and maximum isometric torque (-40%, P < 0.001), but there was a greater increase in passive torque in older (+ 180%, P < 0.001) compared to young adult rats (+ 68%, P = 0.006). Following cast removal, young exhibited quicker recovery of SSN and MT than old, but SSN recovered sooner than PA and MT in both young and old. PCSA nearly recovered and active torque fully recovered in young adult rats, whereas in older adult rats these remained unrecovered at ∼ 75%. CONCLUSIONS: This study showed that older adult rats retain a better ability to recover longitudinal compared to parallel muscle morphology following cast removal, making SSN a highly adaptable target for improving muscle function in elderly populations early on during rehabilitation.

Enhanced root system architecture in oilseed rape transformed with Rhizobium rhizogenes.

Transformation of plants using wild strains of agrobacteria is termed natural transformation and is not covered by GMO legislation in e.g. European Union and Japan. In the current study, offspring lines (A11 and B3) of Rhizobium rhizogenes naturally transformed oilseed rape (Brassica napus) were randomly selected to characterize the morphological traits, and the implications of such morphological changes on plant drought resilience. It was found that the introduction of Ri-genes altered the biomass partitioning to above- and under-ground parts of oilseed rape plants. Compared to the wild type (WT), the A11 and B3 lines possessed 1.2-4.0 folds lower leaf and stem dry weight, leaf area and plant height, but had 1.3-5.8 folds greater root dry weight, root length and root surface area, resulting in a significantly enhanced root: shoot dry mass ratio and root surface area: leaf area ratio. In addition, the introduction of Ri-genes conferred reduced stomatal pore aperture and increased stomatal density in the B3 line, and increased leaf thickness in A11 line, which could benefit plant drought resilience. Finally, the modulations in morphological traits as a consequence of transformation with Ri-genes are discussed concerning resilience in water-limited conditions. These findings reveal the potential of natural transformation with R. rhizogenes for drought-targeted breeding in crops.

Sleep maintains excitatory synapse diversity in the cortex and hippocampus.

Insufficient sleep is a global problem with serious consequences for cognition and mental health.1 Synapses play a central role in many aspects of cognition, including the crucial function of memory consolidation during sleep.2 Interference with the normal expression or function of synapse proteins is a cause of cognitive, mood, and other behavioral problems in over 130 brain disorders.3 Sleep deprivation (SD) has also been reported to alter synapse protein composition and synapse number, although with conflicting results.4,5,6,7 In our study, we conducted synaptome mapping of excitatory synapses in 125 regions of the mouse brain and found that sleep deprivation selectively reduces synapse diversity in the cortex and in the CA1 region of the hippocampus. Sleep deprivation targeted specific types and subtypes of excitatory synapses while maintaining total synapse density (synapse number/area). Synapse subtypes with longer protein lifetimes exhibited resilience to sleep deprivation, similar to observations in aging and genetic perturbations. Moreover, the altered synaptome architecture affected the responses to neural oscillations, suggesting that sleep plays a vital role in preserving cognitive function by maintaining the brain's synaptome architecture.

How can we measure resource quality when resources differ in many ways? Deconstructing shelter quality in a social fish.

Resource quality is an important concept in ecology and evolution that attempts to capture the fitness benefits a resource affords to an organism. Yet "quality" is a multivariate concept, potentially affected by many variables pertaining to the resource, its surroundings, and the resource chooser. Researchers often use a small number of proxy variables to simplify their estimation of resource quality, but without vetting their proxies against a wider set of potential quality estimators this approach risks overlooking potentially important characteristics that can explain patterns of resource use in their study systems. Here we used Neolamprologus multifasciatus, a group-living cichlid fish that utilizes empty snail shells as shelter resources, to examine how shells were used by, and partitioned among, group members in relation to a range of attributes, including shell size, intactness, texture, spatial position, and usage by heterospecifics. This approach generated a comprehensive picture of what characteristics contribute to the attractiveness and quality of each shell resource, confirming the importance of two previously proposed shell characteristics, size and intactness, but highlighting the influences of other unexplored variables, including shell spatial position and usage by heterospecifics. We also present a generally applicable "resource attractiveness index" as a means to estimate resource quality based on resource choice data. This index incorporates information from any number of resource characteristics and is of particular use when researchers wish to quantify resource value, but many characteristics jointly contribute to the value and attractiveness of the resource.

RobMedNAS: searching robust neural network architectures for medical image synthesis.

Investigating U-Net model robustness in medical image synthesis against adversarial perturbations, this study introduces RobMedNAS, a neural architecture search strategy for identifying resilient U-Net configurations. Through retrospective analysis of synthesized CT from MRI data, employing Dice coefficient and mean absolute error metrics across critical anatomical areas, the study evaluates traditional U-Net models and RobMedNAS-optimized models under adversarial attacks. Findings demonstrate RobMedNAS's efficacy in enhancing U-Net resilience without compromising on accuracy, proposing a novel pathway for robust medical image processing. .

Hospital design for inpatient psychiatry: A realistic umbrella review.

The evaluation of the effects of architecture and design in psychiatric hospitals primarily focuses on final outcomes, such as disease progression, and is made from the perspective of evidence-based medicine. Meanwhile, the evidence-informed, realist approach addresses how the intervention works. Understanding the underlying action mechanisms of the intervention is needed to facilitate its scaling-up and adaptation in new environments. This umbrella review reports in which ways architecture and design have an effect on patients' and staff experience in inpatient psychiatric hospital. The search was constructed around three key concepts (psychiatric hospital, design, and staff and patient outcomes) and was conducted across three reference databases (Embase, Medline, and PsychINFO). Academic and gray literature was analyzed. Information on design and architectural features in psychiatric hospitals, their effects on patients and staff experience, and the acting mechanisms enabling these effects were extracted. From 951 original references, 14 full texts were included in the analysis. Design and architectural features (e.g., aesthetic appeal of places, home-like environment) in psychiatric hospitals address patients' stress, boost social interaction, foster patients' autonomy and feelings of control, ensure respect for patient's privacy and dignity, and prevent under-and overstimulation. Using theory-driven evaluation may facilitate future hospital renovation and the evaluation of its effect.

Optimized nitrogen management improves grain yield of rice by regulating panicle architecture in South China.

Optimized nitrogen (N) management (OPT), with reduced total N input and more N applied during panicle development, has been proved to increase grain yield of rice through panicle enlargement. However, the changes in panicle architecture and source of variation are not well understood. A hybrid rice variety named Tianyou 3618 was subjected to OPT and farmer's fertilizer practice (FFP) in early cropping seasons of 2016 and 2017. With 16.7 % less N input, OPT increased panicle size by 8.6 % and 27.4 %, and grain yield by 13.8 % and 12.3 % for 2016 and 2017, respectively. OPT had greater dry matter accumulation and N uptake from panicle initiation to heading, which bolstered panicle enlargement. The number of surviving florets per branch was quite constant under different N treatments for all primary, secondary, and tertiary branches, implying that panicle size was mainly determined by the number of branches rather than the number of florets per branch. Little change was observed between OPT and FFP in differentiation, degeneration and survival of primary branches and their florets. Surviving secondary and tertiary branches and their florets were significantly more under OPT than those under FFP. The increase in surviving secondary branches under OPT resulted from both enhanced differentiation and reduced degeneration. While the increase in surviving tertiary branches under OPT was merely from enhanced differentiation though their degeneration was also dramatically increased. Among the increased differentiated florets under OPT, 32.4%-36.3 % and 61.6%-67.7 % came from secondary and tertiary branches, respectively. Among the increased surviving florets under OPT, 62.2%-65.2 % and 32.5%-37.8 % came from secondary and tertiary branches, respectively. Both secondary branches and tertiary branches were principal contributors to the increase in panicle size of OPT. To our knowledge, this is the first report on the detailed changes in panicle architecture and their involvement in panicle enlargement and yield gain under OPT.

[Genetic architecture of anterior abdominal wall hernias]. / Geneticheskaya arkhitektura gryzh perednei bryushnoi stenki.

OBJECTIVE: To analyze genome-wide studies devoted to polymorphisms of factors of anterior abdominal wall hernias, to study the association of the most common polymorphism In Russian population. MATERIAL AND METHODS: Searching for literature data was carried out in the RSCI and PubMed databases. We enrolled national and foreign reports. The study on Russian population included 577 people. RESULTS: We found 5 genome-wide studies performed by foreign authors. We identified the loci responsible for genetic predisposition to inguinal hernias: WT1, EFEMP1, EBF2 and ADAMTS6. The Japanese scientists revealed an important role of loci TGFB2, RNA5SP214/VGLL2, LOC646588, HMCN2, ATP5F1CP1/CDKN3. In other studies, loci 1q41 (ZC3H11B), 2p16.1 (EFEMP1), 6p22.1 (MHC region), 7q33 (CALD1) and 11p13 (WT1) determined different hernias. The EFEMP1 gene polymorphism was among genes most associated with anterior abdominal wall hernias in all studies. Analysis of this polymorphism In Russian population revealed significant association with anterior abdominal wall hernias. CONCLUSION: The obtained data on target correction of DNA chains can significantly reduce the incidence of anterior abdominal wall hernias. In turn, this will significantly reduce the cost of surgical treatment and risk of complications with recurrences of hernias. Moreover, identifying the most associated polymorphisms may be valuable to determine the most appropriate surgical treatment.

Comprehensive genomic profiling of infiltrative follicular variant of papillary thyroid carcinoma.

BACKGROUND: Infiltrative follicular variant of papillary thyroid carcinoma (IFVPTC) exhibits nuclear characteristics typical of papillary thyroid carcinoma (PTC) but demonstrates a follicular growth pattern. The diagnosis of IFVPTC presenting with atypical nuclear features of PTC poses challenges for both preoperative cytopathology and postoperative histopathology. In such cases, molecular markers are needed to serve as diagnostic aids. Given the limited knowledge of IFVPTC's genomic features, this study aimed to characterize its genetic alterations and identify clinically relevant molecular markers. METHODS: Whole-exome sequencing of 50 IFVPTC tumor-normal pairs identified single-nucleotide variants, somatic copy number alterations (sCNAs), and subclonal architecture. Key mutations were verified via polymerase chain reaction and Sanger sequencing, whereas valuable biomarkers were validated via immunohistochemistry (IHC). RESULTS: This study found that endogenous processes rather than exogenous mutagens dominated the shaping of the genome of IFVPTC during tumorigenesis. BRAF V600E was the only common trunk mutation and significantly mutated gene in IFVPTC. Subcloning analysis found that most IFVPTC samples harbored two or more coexisting clones. sCNA analysis revealed that human leukocyte antigen C (HLA-C) and HLA-A were significantly amplified. Subsequent IHC investigations indicated that HLA-C shows promise in averting the misclassification of challenging-to-interpret IFVPTC and invasive encapsulated follicular variant of PTC (I-EFVPTC) as noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP). Although there were several similarities between classic PTC and IFVPTC, they differed significantly in their sCNA patterns. CONCLUSIONS: This study provides valuable insights into IFVPTC's genetic alterations and highlights the potential of HLA-C IHC to distinguish challenging-to-interpret IFVPTC and I-EFVPTC from NIFTP, which will enhance the understanding of its molecular features for improved diagnosis and management.

UC-Hybrid: Uncertainty-based contrastive learning on hybrid network for medical image segmentation.

Medical image segmentation has made remarkable progress with advances in deep learning technology, depending on the quality and quantity of labeled data. Although various deep learning model structures and training methods have been proposed and high performance has been published, limitations such as inter-class accuracy bias exist in actual clinical applications, especially due to the significant lack of small object performance in multi-organ segmentation tasks. In this paper, we propose an uncertainty-based contrastive learning technique, namely UncerNCE, with an optimal hybrid architecture for high classification and segmentation performance of small organs. Our backbone architecture adopts a hybrid network that employs both convolutional and transformer layers, which have demonstrated remarkable performance in recent years. The key proposal of this study addresses the multi-class accuracy bias and resolves a common tradeoff in existing studies between segmenting regions of small objects and reducing overall noise (i.e., false positives). Uncertainty based contrastive learning based on the proposed hybrid network performs spotlight learning on selected regions based on uncertainty and achieved accurate segmentation for all classes while suppressing noise. Comparison with state-of-the-art techniques demonstrates the superiority of our results on BTCV and 1K data.

RNA-Independent Regulatory Functions of lncRNA in Complex Disease.

During the metagenomics era, high-throughput sequencing efforts both in mice and humans indicate that non-coding RNAs (ncRNAs) constitute a significant fraction of the transcribed genome. During the past decades, the regulatory role of these non-coding transcripts along with their interactions with other molecules have been extensively characterized. However, the study of long non-coding RNAs (lncRNAs), an ncRNA regulatory class with transcript lengths that exceed 200 nucleotides, revealed that certain non-coding transcripts are transcriptional "by-products", while their loci exert their downstream regulatory functions through RNA-independent mechanisms. Such mechanisms include, but are not limited to, chromatin interactions and complex promoter-enhancer competition schemes that involve the underlying ncRNA locus with or without its nascent transcription, mediating significant or even exclusive roles in the regulation of downstream target genes in mammals. Interestingly, such RNA-independent mechanisms often drive pathological manifestations, including oncogenesis. In this review, we summarize selective examples of lncRNAs that regulate target genes independently of their produced transcripts.

Analysis of Runs of Homozygosity in Aberdeen Angus Cattle.

A large number of cattle breeds have marked phenotypic differences. They are valuable models for studying genome evolution. ROH analysis can facilitate the discovery of genomic regions that may explain phenotypic differences between breeds affecting traits of economic importance. This paper investigates genome-wide ROH of 189 Aberdeen Angus bulls using the Illumina Bovine GGP HD Beadchip150K to structurally and functionally annotate genes located within or in close ROH of the Aberdeen Angus cattle genome. The method of sequential SNP detection was used to determine the ROH. Based on this parameter, two ROH classes were allocated. The total length of all ROH islands was 11,493 Mb. As a result of studying the genomic architecture of the experimental population of Aberdeen Angus bulls, nine ROH islands and 255 SNPs were identified. Thirteen of these overlapped with regions bearing 'selection imprints' previously identified in other breeds of cattle, and five of these regions were identified in other Aberdeen Angus populations. The total length of the ROH islands was 11,493 Mb. The size of individual islands ranged from 0.038 to 1.812 Mb. Structural annotation showed the presence of 87 genes within the identified ROH islets.

The Influence of Logging-Related Soil Disturbance on Pioneer Tree Regeneration in Mixed Temperate Forests.

The recovery of soil properties and the proper growth of natural tree regeneration are key elements for maintaining forest productivity after selective logging operations. This study was conducted on the soil properties and natural growth of two pioneer seedling species of alder and maple which were on skid trails in the mixed beech forests of northern Iran. To examine the long-term effects, we randomly selected six skid trails, with two replicates established for each of three time periods since last use (10, 20, and 30 years ago). Random plots 4 m × 10 m in size, three plots on each skid trail and six plots on areas without soil compaction (control), were selected. Measurements included the physical and chemical properties of the soil and the growth, and the architectural and qualitative characteristics of the seedlings. The results showed that all the soil properties of the 10- and 20-year-old skid trails were significantly different from the control area (except for the soil moisture in the 20-year-old skid trail). The 30-year-old skid trail showed values of other soil properties which were not significantly different from the control area, except for the amounts of organic matter and soil nitrogen, which was less than the control. The skid trails had a negative effect on all of the growth, qualitative, and architectural indices of seedlings. The characteristics of seedlings were related to soil characteristics and had the highest correlation with the soil penetration resistance (R-value from -0.41 to -0.63 for stem growth, p < 0.05; -0.57 to -0.90 for root growth, p < 0.01; and -0.76 to -0.86 for biomass, p < 0.01). The correlation coefficient between soil penetration resistance and the Dickson quality index of alder and maple seedlings was, respectively, -0.74 and -0.72, p < 0.01. The negative effect of soil compaction on root growth (-27.69% for alder seedlings and -28.08% for maple seedlings) was greater than on stem growth (-24.11% for alder seedlings and -16.27% for maple seedlings). The amount of growth, qualitative, and architectural indices of alder seedlings were higher than that of maple seedlings. Although alder is a better choice as compared to maple seedling in the initial year, the results of our study show that it is recommended to plant both alder and maple on skid trails after logging operations.

Nanoporous Carbon Materials as Solid Contacts for Microneedle Ion-Selective Sensors.

Continuous sensing of biomarkers, such as potassium ions or pH, in wearable patches requires miniaturization of ion-selective sensor electrodes. Such miniaturization can be achieved by using nanostructured carbon materials as solid contacts in microneedle-based ion-selective and reference electrodes. Here we compare three carbon materials as solid contacts: colloid-imprinted mesoporous (CIM) carbon microparticles with ∼24-28 nm mesopores, mesoporous carbon nanospheres with 3-9 nm mesopores, and Super P carbon black nanoparticles without internal porosity but with textural mesoporosity in particle aggregates. We compare the effects of carbon architecture and composition on specific capacitance of the material, on the ability to incorporate ion-selective membrane components in the pores, and on sensor performance. Functioning K+ and H+ ion-selective electrodes and reference electrodes were obtained with gold-coated stainless-steel microneedles using all three types of carbon. The sensors gave near-Nernstian responses in clinically relevant concentration ranges, were free of potentially detrimental water layers, and showed no response to O2. They all exhibited sufficiently low long-term potential drift values to permit calibration-free, continuous operation for close to 1 day. In spite of the different specific capacitances and pore architecture of the three types of carbon, no significant difference in potential stability for K+ ion sensing was observed between electrodes that used each material. In the observed drift values, factors other than the carbon solid contact are likely to play a role, too. However, for pH sensing, electrodes with CIM as a carbon solid contact, which had the highest specific capacitance and best access to the pores, exhibited better long-term stability than electrodes with the other carbon materials.

3D Leaf-Like Copper-Zinc Alloy Enables Dendrite-Free Zinc Anode for Ultra-Long Life Aqueous Zinc Batteries.

Metallic zinc exhibits immense potential as an anode material for aqueous rechargeable zinc batteries due to its high theoretical capacity, low redox potential, and inherent safety. However, practical applications are hindered by dendrite formation and poor cycling stability. Herein, a facile substitution reaction method is presented to fabricate a 3D leaf-like Cu@Zn composite anode. This unique architecture, featuring a 3D network of leaf-like Cu on a Zn foil surface, significantly reduces nucleation overpotential and facilitates uniform Zn plating/stripping, effectively suppressing dendrite growth. Notably, an alloy layer of CuZn5 forms in situ on the 3D Cu layer during cycling. DFT calculations reveal that this CuZn5 alloy possesses a lower Zn binding energy compared to both Cu and Zn metal, further promoting Zn plating/stripping and enhancing electrochemical kinetics. Consequently, the symmetric Cu@Zn electrode exhibits remarkable cycling stability, surpassing 1300 h at 0.5 mA cm-2 with negligible dendrite formation. Furthermore, full cells comprising Cu@Zn||VO2 exhibit superior capacity and rate performance compared to bare Zn anodes. This work provides a promising strategy for constructing highly stable and efficient Zn anodes for next-generation aqueous zinc batteries.

MonARCh: an actor based architecture for dynamic linked data monitoring.

Monitoring the data sources for possible changes is an important consumption requirement for applications running in interaction with the Web of Data. In this article, MonARCh which is an architecture for monitoring the result changes of registered SPARQL queries in the Linked Data environment, is proposed. MonARCh can be comprehended as a publish/subscribe system in the general sense. However, it differs in how communication with the data sources is realized. Data sources in the Linked Data environment do not publish the changes in the data. MonARCh provides the necessary communication infrastructure between the data sources and the consumers for the notification of changes. Users subscribe SPARQL queries to the system which are then converted to federated queries. MonARCh periodically checks for updates by re-executing SERVICE clauses and notifying users in case of any result change. In addition, to provide scalability, MonARCh takes the advantage of concurrent computation of the actor model. The parallel join algorithm utilized speeds up query execution and result generation processes. The design science methodology is used during the design, implementation and evaluation of the architecture. When compared to the literature MonARCh meets all the sufficient requirements from the linked data monitoring and state of the art perspectives while having many outstanding features from both points of view. The evaluation results show that even while working under the limited two-node cluster setting MonARCh could reach from 300 to 25,000 query monitoring capacity according to the diverse query selectivities executed within our test bench.

Intercalating Architecture for the Design of Charge Density Wave in Metallic MA2Z4 Materials.

We present a novel approach to induce charge density waves (CDWs) in metallic MA2Z4 materials, resembling the behavior observed in transition metal dichalcogenides (TMDCs). This method leverages the intercalating architecture to maintain the same crystal field and Fermi surface topologies. Our investigation reveals that CDW instability in these materials arises from electron-phonon coupling (EPC) between the d band and longitudinal acoustic (LA) phonons, mirroring TMDC's behavior. By combining α-MA2Z4 with 1H-MX2 materials in a predictive CDW phase diagram using critical EPC constants, we demonstrate the feasibility of extending CDW across material families with comparable crystal fields and reveal the crucial role in CDW instability of the competition between ionic charge transfer and electron correlation. We further uncover a strain-induced Mott transition in ß2-NbGe2N4 monolayer featuring star-of-David patterns. This work highlights the potential of intercalating architecture to engineer CDW materials, expanding our understanding of CDW instability and correlation physics.

Phenotypic and transcriptomics characterization uncovers genes underlying tuber yield traits and gene expression marker development in potato under aeroponics.

MAIN CONCLUSION: Transcriptome analysis in potato varieties revealed genes associated with tuber yield-related traits and developed gene expression markers. This study aimed to identify genes involved in high tuber yield and its component traits in test potato varieties (Kufri Frysona, Kufri Khyati, and Kufri Mohan) compared to control (Kufri Sutlej). The aeroponic evaluation showed significant differences in yield-related traits in the varieties. Total RNA sequencing was performed using tuber and leaf tissues on the Illumina platform. The high-quality reads (QV > 25) mapping with the reference potato genomes revealed statistically significant (P < 0.05) differentially expressed genes (DEGs) into two categories: up-regulated (> 2 Log2 fold change) and down-regulated (< -2 Log2 fold change). DEGs were characterized by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Collectively, we identified genes participating in sugar metabolism, stress response, transcription factors, phytohormones, kinase proteins, and other genes greatly affecting tuber yield and its related traits. A few selected genes were UDP-glucose glucosyltransferase, glutathion S-transferase, GDSL esterase/lipase, transcription factors (MYB, WRKY, bHLH63, and BURP), phytohormones (auxin-induced protein X10A, and GA20 oxidase), kinase proteins (Kunitz-type tuber invertase inhibitor, BRASSINOSTEROID INSENSITIVE 1-associated receptor kinase 1) and laccase. Based on the selected 17 peptide sequences representing 13 genes, a phylogeny tree and motifs were analyzed. Real time-quantitative polymerase chain reaction (RT-qPCR) analysis was used to validate the RNA-seq results. RT-qPCR based gene expression markers were developed for the genes such as 101 kDa heat shock protein, catechol oxidase B chloroplastic, cysteine protease inhibitor 1, Kunitz-type tuber invertase inhibitor, and laccase to identify high yielding potato genotypes. Thus, our study paved the path for potential genes associated with tuber yield traits in potato under aeroponics.

Auto-Spikformer: Spikformer architecture search.

Introduction: The integration of self-attention mechanisms into Spiking Neural Networks (SNNs) has garnered considerable interest in the realm of advanced deep learning, primarily due to their biological properties. Recent advancements in SNN architecture, such as Spikformer, have demonstrated promising outcomes. However, we observe that Spikformer may exhibit excessive energy consumption, potentially attributable to redundant channels and blocks. Methods: To mitigate this issue, we propose a one-shot Spiking Transformer Architecture Search method, namely Auto-Spikformer. Auto-Spikformer extends the search space to include both transformer architecture and SNN inner parameters. We train and search the supernet based on weight entanglement, evolutionary search, and the proposed Discrete Spiking Parameters Search (DSPS) methods. Benefiting from these methods, the performance of subnets with weights inherited from the supernet without even retraining is comparable to the original Spikformer. Moreover, we propose a new fitness function aiming to find a Pareto optimal combination balancing energy consumption and accuracy. Results and discussion: Our experimental results demonstrate the effectiveness of Auto-Spikformer, which outperforms the original Spikformer and most CNN or ViT models with even fewer parameters and lower energy consumption.