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In-stream habitat enhancement is widely used to improve ecological conditions in rivers, often prioritizing key fish life stages such as spawning and juvenile development. However, no standard approaches exist to predict their effects on fish recruitment and populations. Here, we use a spatially-explicit population dynamics model that integrates functional habitat dynamics to assess the impact of two rehabilitation measures in a hydropower-impacted section of the Inn River (SE Germany) on the recruitment potential of four rheophilic and lithophilic fish species - grayling, nase, barbel, and chub. Rehabilitation measures implemented included the construction of a bypass channel and an island side-channel system to improve both longitudinal connectivity and habitat conditions. In addition, we analyzed two alternatives, which would enhance functional availability of nursery habitats from actual 33.2% to 66.8% and 95.3%, respectively. The results suggest that the improved habitat conditions will yield on average additional 14.9 individuals/ha (5.6 kg/ha) of the target species. However, the limited accessibility of usable nursery habitat constitutes a significant recruitment bottleneck for all species. In the alternative scenarios, the increase of functional connectivity will result in average densities of 17.9 and 25.8 individuals/ha, respectively. However, potential further improvements are species-specific, because of distinct population responses to spawning-to-nursery habitat ratios, with density changes varying between -11.7% for grayling and +172.6% for chub. This study not only demonstrates the applicability of the modeling approach for assessing and planning rehabilitation measures but also emphasizes the importance of considering habitat ratios and their functional connectivity to optimize recruitment potential.

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PURPOSE: To develop an automated deep learning model for MRI-based segmentation and detection of intracranial arterial calcification. METHODS: A novel deep learning model under the variational autoencoder framework was developed. A theoretically grounded dissimilarity loss was proposed to refine network features extracted from MRI and restrict their complexity, enabling the model to learn more generalizable MR features that enhance segmentation accuracy and robustness for detecting calcification on MRI. RESULTS: The proposed method was compared with nine baseline methods on a dataset of 113 subjects and showed superior performance (for segmentation, Dice similarity coefficient: 0.620, area under precision-recall curve [PR-AUC]: 0.660, 95% Hausdorff Distance: 0.848 mm, Average Symmetric Surface Distance: 0.692 mm; for slice-wise detection, F1 score: 0.823, recall: 0.764, precision: 0.892, PR-AUC: 0.853). For clinical needs, statistical tests confirmed agreement between the true calcification volumes and predicted values using the proposed approach. Various MR sequences, namely T1, time-of-flight, and SNAP, were assessed as inputs to the model, and SNAP provided unique and essential information pertaining to calcification structures. CONCLUSION: The proposed deep learning model with a dissimilarity loss to reduce feature complexity effectively improves MRI-based identification of intracranial arterial calcification. It could help establish a more comprehensive and powerful pipeline for vascular image analysis on MRI.

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Demographic history and mutational load are of paramount importance for the adaptation of the endangered species. However, the effects of population evolutionary history and genetic load on the adaptive potential in endangered conifers remain unclear. Here, using population transcriptome sequencing, whole chloroplast genomes and mitochondrial DNA markers, combined with niche analysis, we determined the demographic history and mutational load for three threatened whitebark pines having different endangered statuses, Pinus bungeana, P. gerardiana and P. squamata. Demographic inference indicated that severe bottlenecks occurred in all three pines at different times, coinciding with periods of major climate and geological changes; in contrast, while P. bungeana experienced a recent population expansion, P. gerardiana and P. squamata maintained small population sizes after bottlenecking. Abundant homozygous-derived variants accumulated in the three pines, particularly in P. squamata, while the species with most heterozygous variants was P. gerardiana. Abundant moderately and few highly deleterious variants accumulated in the pine species that have experienced the most severe demographic bottlenecks (P. gerardiana and P. squamata), most likely because of purging effects. Finally, niche modeling showed that the distribution of P. bungeana might experience a significant expansion in the future, and the species' identified genetic clusters are also supported by differences in the ecological niche. The integration of genomic, demographic and niche data has allowed us to prove that the three threatened pines have contrasting patterns of demographic history and mutational load, which may have important implications in their adaptive potential and thus are also key for informing conservation planning.

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Understanding the dynamics of population recovery in threatened species requires robust longitudinal monitoring datasets. However, evidence-based decision-making is often impeded by variable data collection approaches, necessitating critical evaluation of restricted available baselines. The Hainan gibbon, the world's rarest primate, had possibly declined to only seven or eight individuals in 1978 at Bawangling National Nature Reserve but has experienced subsequent population growth. Past population estimates lack detailed reporting of survey effort, and multiple conflicting estimates are available, hindering assessment of gibbon recovery. We investigated all reported estimates of Bawangling gibbon population size from 1978 to 2022, to evaluate the biological signal of population trends and the extent to which noise associated with varying survey effort, reporting and estimation may mask or misrepresent any underlying signal. This longitudinal dataset demonstrates that the Bawangling population experienced a series of bottlenecks and recoveries, with three successive periods of growth interspersed by population crashes (1978-1989, 1989-2000 and 2000-2022). The rate of gibbon population recovery was progressively slower over time in each successive period of growth, and this potential decline in recovery rate following serial bottlenecks suggests that additional management strategies may be required alongside "nature-based solutions" for this species. However, population viability analysis suggests the 1978 founder population is unlikely to have been as low as seven individuals, raising concerns for interpreting reported historical population counts and understanding the dynamics of the species' recovery. We caution against overinterpreting potential signals within "messy" conservation datasets, and we emphasise the crucial importance of standardised replicable survey methods and transparent reporting of data and effort in all future surveys of Hainan gibbons and other highly threatened species.

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Barley is one of the founder crops of the Neolithic transition in West Asia. While recent advances in genomics have provided a rather detailed picture of barley domestication, there are contradictory views on how the domestication process affected genetic diversity. We set out to revisit this question by integrating public DNA sequencing data from ancient barley and wide collections of extant wild and domesticated accessions. Using two previously overlooked approaches - analyses of chloroplast genomes and genome-wide proportions of private variants - we found that the barley cultivated six millennia ago was genetically unique and more diverse when compared to extant landraces and cultivars. Moreover, the chloroplast genomes revealed a link between the ancient barley, an obscure wild genotype from north-eastern Libya, and a distinct population of barley cultivated in Ethiopia/Eritrea. Based on these results, we hypothesize past existence of a wider North African population that included both wild and cultivated types and suffered from genetic erosion in the past six millennia, likely due to a rapid desertification that ended the Holocene African humid period. Besides providing clues about the origin of Ethiopian landraces, the hypothesis explains the post-domestication loss of diversity observed in barley. Analyses of additional samples will be necessary to resolve the history of African barley and its contribution to the extant cultivated gene pool.

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Although it is well known that humans substantially altered the Malagasy ecosystems, the timing of the human arrival as well as the extension of their environmental impact is yet not well understood. This research aims to study the influence of early human impact and climate change on rainforests and wildlife in northern Madagascar during the past millennia. Results obtained from the lake sediment in a montane environment showed significant changes in vegetation within the lake catchment associated with a major drought that started approximately 1100 years ago. Human impact, revealed by fires, began at roughly the same time and occurred outside the lake catchment. Although this does not dismiss the impacts that humans had at a regional scale, this result demonstrates that the late Holocene natural drought also significantly impacted the ecosystems independently of anthropogenic activities. At a regional scale, a review of species demographic history revealed a substantial number of population bottlenecks during the last millennia, probably resulting from this combination of human-related impact and natural climate changes. This research highlights the importance of a multi-site and multi-proxy comparison for deciphering the nature and succession of environmental changes.

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Background: Discoveries of new species often depend on one or a few specimens, leading to delays as researchers wait for additional context, sometimes for decades. There is currently little professional incentive for a single expert to publish a stand-alone species description. Additionally, while many journals accept taxonomic descriptions, even specialist journals expect insights beyond the descriptive work itself. The combination of these factors exacerbates the issue that only a small fraction of marine species are known and new discoveries are described at a slow pace, while they face increasing threats from accelerating global change. To tackle this challenge, this first compilation of Ocean Species Discoveries (OSD) presents a new collaborative framework to accelerate the description and naming of marine invertebrate taxa that can be extended across all phyla. Through a mode of publication that can be speedy, taxonomy-focused and generate higher citation rates, OSD aims to create an attractive home for single species descriptions. This Senckenberg Ocean Species Alliance (SOSA) approach emphasises thorough, but compact species descriptions and diagnoses, with supporting illustrations and with molecular data when available. Even basic species descriptions carry key data for distributions and ecological interactions (e.g., host-parasite relationships) besides universally valid species names; these are essential for downstream uses, such as conservation assessments and communicating biodiversity to the broader public. New information: This paper presents thirteen marine invertebrate taxa, comprising one new genus, eleven new species and one re-description and reinstatement, covering wide taxonomic, geographic, bathymetric and ecological ranges. The taxa addressed herein span three phyla (Mollusca, Arthropoda, Echinodermata), five classes, eight orders and twelve families. Apart from the new genus, an updated generic diagnosis is provided for four other genera. The newly-described species of the phylum Mollusca are Placiphorellamethanophila Voncina, sp. nov. (Polyplacophora, Mopaliidae), Lepetodrilusmarianae Chen, Watanabe & Tsuda, sp. nov. (Gastropoda, Lepetodrilidae), Shinkailepasgigas Chen, Watanabe & Tsuda, sp. nov. (Gastropoda, Phenacolepadidae) and Lyonsiellaillaesa Machado & Sigwart, sp. nov. (Bivalvia, Lyonsiellidae). The new taxa of the phylum Arthropoda are all members of the subphylum Crustacea: Lepechinellanaces Lörz & Engel, sp. nov. (Amphipoda, Lepechinellidae), Cuniculomaeragrata Tandberg & Jazdzewska, gen. et sp. nov. (Amphipoda, Maeridae), Pseudionellapumulaensis Williams & Landschoff, sp. nov. (Isopoda, Bopyridae), Mastigoniscusminimus Wenz, Knauber & Riehl, sp. nov. (Isopoda, Haploniscidae), Macrostylispapandreas Jonannsen, Riehl & Brandt, sp. nov. (Isopoda, Macrostylidae), Austroniscusindobathyasellus Kaiser, Kniesz & Kihara, sp. nov. (Isopoda, Nannoniscidae) and Apseudopsisdaria Esquete & Tato, sp. nov. (Tanaidacea, Apseudidae). In the phylum Echinodermata, the reinstated species is Psychropotesbuglossa E. Perrier, 1886 (Holothuroidea, Psychropotidae).The study areas span the North and Central Atlantic Ocean, the Indian Ocean and the North, East and West Pacific Ocean and depths from 5.2 m to 7081 m. Specimens of eleven free-living and one parasite species were collected from habitats ranging from an estuary to deep-sea trenches. The species were illustrated with photographs, line drawings, micro-computed tomography, confocal laser scanning microscopy and scanning electron microscopy images. Molecular data are included for nine species and four species include a molecular diagnosis in addition to their morphological diagnosis.The five new geographic and bathymetric distribution records comprise Lepechinellanaces Lörz & Engel, sp. nov., Cuniculomaeragrata Tandberg & Jazdzewska, sp. nov., Pseudionellapumulaensis Williams & Landschoff, sp. nov., Austroniscusindobathyasellus Kaiser, Kniesz & Kihara, sp. nov. and Psychropotesbuglossa E. Perrier, 1886, with the novelty spanning from the species to the family level. The new parasite record is Pseudionellapumulaensis Williams & Landschoff, sp. nov., found in association with the hermit crab Pagurusfraserorum Landschoff & Komai, 2018.

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The significance of the ethical review process in human-based research undertakings cannot be overemphasized as it is necessary to uphold ethical standards and protect participants. However, the review process per se can act as a bottleneck, potentially hindering research progress and leading to academic dishonesty. The present work explores the benefits and challenges of ethical review, emphasizing issues like intellectual theft, forced authorship, and the stifling of independent researchers. Proposed solutions include leveraging previously approved designs, empowering experienced professors for clearance, establishing panels of researchers, creating voluntary ethical approval offices, utilizing private consultancy offices, and establishing a transnational ethical clearance authority. In conclusion, this work stresses the importance of finding mechanisms to streamline the ethical review process while maintaining ethical standards to foster integrity in research and combat academic dishonesty.

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The island of Nias/Indonesia shows an extremely reduced genetic diversity indicating a strong founder effect. As a consequence, the prevalence of some disease genes should significantly differ among populations depending on the gene pool passed on to the founder population and their successive expansion as it has already been documented for several monogenic diseases. Results of the current study based on routine laboratory blood examination give rise to the notion that this might also hold true for polygenic disorders. We observed very high prevalence of hyperglycemia (non-fasting glucose above 200 mg/dL in 14 % Nias population compared to 1.5 % in the population of the neighboring island of Sumatra) accompanied by hypertriglyceridemia, high non-HDL-cholesterol, and low HDL-cholesterol levels. These findings suggest that the Nias population may be disproportionally affected by prediabetes and type 2 diabetes mellitus. By contrast, laboratory parameters potentially indicative of other polygenic disorders such as total plasma cholesterol, electrolytes, creatinine, urea, and uric acid were comparable between the inhabitants of Nias and Sumatra islands. To our knowledge this is the first study suggesting that the extremely strong genetic bottleneck seen in the Nias population translates into the widespread metabolic disease with potentially deleterious influence on public health.

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It is well known that highly inbred dogs are more prone to diseases than less inbred or outbred dogs. This is because inbreeding increases the load of recessive deleterious variants. Using the genomes of 392 dogs belonging to 83 breeds, we investigated the association between the abundance of homozygous deleterious variants and dog health. We used the number of non-routine veterinary care events for each breed to assess the level of morbidity. Our results revealed a highly significant positive relationship between the number of homozygous deleterious variants located within the runs of homozygosity (RoH) tracts of the breeds and the level of morbidity. The dog breeds with low morbidity had a mean of 87 deleterious SNVs within the RoH, but those with very high morbidity had 187 SNVs. A highly significant correlation was also observed for the loss-of-function (LoF) SNVs within RoH tracts. The dog breeds that required more veterinary care had 2.3 times more homozygous LoF SNVs than those that required less veterinary care (112 vs. 50). The results of this study could be useful for understanding the disease burden on breed dogs and as a guide for dog breeding programs.

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The Seychelles magpie-robin's (SMR) five island populations exhibit some of the lowest recorded levels of genetic diversity among endangered birds, and high levels of inbreeding. These populations collapsed during the 20th century, and the species was listed as Critically Endangered in the IUCN Red List in 1994. An assisted translocation-for-recovery program initiated in the 1990s increased the number of mature individuals, resulting in its downlisting to Endangered in 2005. Here, we explore the temporal genomic erosion of the SMR based on a dataset of 201 re-sequenced whole genomes that span the past ~150 years. Our sample set includes individuals that predate the bottleneck by up to 100 years, as well as individuals from contemporary populations established during the species recovery program. Despite the SMR's recent demographic recovery, our data reveal a marked increase in both the genetic load and realized load in the extant populations when compared to the historical samples. Conservation management may have reduced the intensity of selection by increasing juvenile survival and relaxing intraspecific competition between individuals, resulting in the accumulation of loss-of-function mutations (i.e. severely deleterious variants) in the rapidly recovering population. In addition, we found a 3-fold decrease in genetic diversity between temporal samples. While the low genetic diversity in modern populations may limit the species' adaptability to future environmental changes, future conservation efforts (including IUCN assessments) may also need to assess the threats posed by their high genetic load. Our computer simulations highlight the value of translocations for genetic rescue and show how this could halt genomic erosion in threatened species such as the SMR.

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Recently, Graph Neural Networks (GNNs) have gained widespread application in automatic brain network classification tasks, owing to their ability to directly capture crucial information in non-Euclidean structures. However, two primary challenges persist in this domain. First, within the realm of clinical neuro-medicine, signals from cerebral regions are inevitably contaminated with noise stemming from physiological or external factors. The construction of brain networks heavily relies on set thresholds and feature information within brain regions, making it susceptible to the incorporation of such noises into the brain topology. Additionally, the static nature of the artificially constructed brain network's adjacent structure restricts real-time changes in brain topology. Second, mainstream GNN-based approaches tend to focus solely on capturing information interactions of nearest neighbor nodes, overlooking high-order topology features. In response to these challenges, we propose an adaptive unsupervised Spatial-Temporal Dynamic Hypergraph Information Bottleneck (ST-DHIB) framework for dynamically optimizing brain networks. Specifically, adopting an information theory perspective, Graph Information Bottleneck (GIB) is employed for purifying graph structure, and dynamically updating the processed input brain signals. From a graph theory standpoint, we utilize the designed Hypergraph Neural Network (HGNN) and Bi-LSTM to capture higher-order spatial-temporal context associations among brain channels. Comprehensive patient-specific and cross-patient experiments have been conducted on two available datasets. The results demonstrate the advancement and generalization of the proposed framework.

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Accurate histopathological subtype prediction is clinically significant for cancer diagnosis and tumor microenvironment analysis. However, achieving accurate histopathological subtype prediction is a challenging task due to (1) instance-level discrimination of histopathological images, (2) low inter-class and large intra-class variances among histopathological images in their shape and chromatin texture, and (3) heterogeneous feature distribution over different images. In this paper, we formulate subtype prediction as fine-grained representation learning and propose a novel multi-instance selective transformer (MIST) framework, effectively achieving accurate histopathological subtype prediction. The proposed MIST designs an effective selective self-attention mechanism with multi-instance learning (MIL) and vision transformer (ViT) to adaptive identify informative instances for fine-grained representation. Innovatively, the MIST entrusts each instance with different contributions to the bag representation based on its interactions with instances and bags. Specifically, a SiT module with selective multi-head self-attention (S-MSA) is well-designed to identify the representative instances by modeling the instance-to-instance interactions. On the contrary, a MIFD module with the information bottleneck is proposed to learn the discriminative fine-grained representation for histopathological images by modeling instance-to-bag interactions with the selected instances. Substantial experiments on five clinical benchmarks demonstrate that the MIST achieves accurate histopathological subtype prediction and obtains state-of-the-art performance with an accuracy of 0.936. The MIST shows great potential to handle fine-grained medical image analysis, such as histopathological subtype prediction in clinical applications.

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The partial information decomposition (PID) aims to quantify the amount of redundant information that a set of sources provides about a target. Here, we show that this goal can be formulated as a type of information bottleneck (IB) problem, termed the "redundancy bottleneck" (RB). The RB formalizes a tradeoff between prediction and compression: it extracts information from the sources that best predict the target, without revealing which source provided the information. It can be understood as a generalization of "Blackwell redundancy", which we previously proposed as a principled measure of PID redundancy. The "RB curve" quantifies the prediction-compression tradeoff at multiple scales. This curve can also be quantified for individual sources, allowing subsets of redundant sources to be identified without combinatorial optimization. We provide an efficient iterative algorithm for computing the RB curve.

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A central challenge in hypothesis testing (HT) lies in determining the optimal balance between Type I (false positive) and Type II (non-detection or false negative) error probabilities. Analyzing these errors' exponential rate of convergence, known as error exponents, provides crucial insights into system performance. Error exponents offer a lens through which we can understand how operational restrictions, such as resource constraints and impairments in communications, affect the accuracy of distributed inference in networked systems. This survey presents a comprehensive review of key results in HT, from the foundational Stein's Lemma to recent advancements in distributed HT, all unified through the framework of error exponents. We explore asymptotic and non-asymptotic results, highlighting their implications for designing robust and efficient networked systems, such as event detection through lossy wireless sensor monitoring networks, collective perception-based object detection in vehicular environments, and clock synchronization in distributed environments, among others. We show that understanding the role of error exponents provides a valuable tool for optimizing decision-making and improving the reliability of networked systems.

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The exceptional semiconducting properties of two-dimensional (2D) transition metal dichalcogenides (TMDs) have made them highly promising for the development of future electronic and optoelectronic devices. Extensive studies of TMDs are partly associated with their ability to generate 2D-confined hot carriers above the conduction band edges, enabling potential applications that rely on such transient excited states. In this work, room-temperature spatiotemporal hot carrier dynamics in monolayer MoS2 is studied by transient absorption microscopy (TAM), featuring an initial ultrafast expansion followed by a rapid negative diffusion, and ultimately a slow long-term expansion of the band edge C-excitons. We provide direct experimental evidence to identify the abnormal negative diffusion process as a spatial contraction of the hot carriers resulting from spatial variation in the hot phonon bottleneck effect due to the Gaussian intensity distribution of the pump laser beam.

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Achieving commercially significant yields of recombinant proteins in Bacillus subtilis requires the optimization of its protein production pathway, including transcription, translation, folding, and secretion. Therefore, in this study, our aim was to maximize the secretion of a reporter α-amylase by overcoming potential bottlenecks within the secretion process one by one, using a clustered regularly interspaced short palindromic repeat-Cas9 (CRISPR-Cas9) system. The strength of single and tandem promoters was evaluated by measuring the relative α-amylase activity of AmyQ integrated into the B. subtilis chromosome. Once a suitable promoter was selected, the expression levels of amyQ were upregulated through the iterative integration of up to six gene copies, thus boosting the α-amylase activity 20.9-fold in comparison with the strain harboring a single amyQ gene copy. Next, α-amylase secretion was further improved to a 26.4-fold increase through the overexpression of the extracellular chaperone PrsA and the signal peptide peptidase SppA. When the final expression strain was cultivated in a 3 L fermentor for 90 h, the AmyQ production was enhanced 57.9-fold. The proposed strategy allows for the development of robust marker-free plasmid-less super-secreting B. subtilis strains with industrial relevance.

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There are two primary measures of the amount of genetic variation in a population at a locus: heterozygosity and the number of alleles. Effective population size (N e) provides both an expectation of the amount of heterozygosity in a population at drift-mutation equilibrium and the rate of loss of heterozygosity because of genetic drift. In contrast, the number of alleles in a population at drift-mutation equilibrium is a function of both N e and census size (N C). In addition, populations with the same N e can lose allelic variation at very different rates. Allelic variation is generally much more sensitive to bottlenecks than heterozygosity. Expressions used to adjust for the effects of violations of the ideal population on N e do not provide good predictions of the loss of allelic variation. These effects are much greater for loci with many alleles, which are often important for adaptation. We show that there is a linear relationship between the reduction of N C and the corresponding reduction of the expected number of alleles at drift-mutation equilibrium. This makes it possible to predict the expected effect of a bottleneck on allelic variation. Heterozygosity provides good estimates of the rate of adaptive change in the short-term, but allelic variation provides important information about long-term adaptive change. The guideline of long-term N e being greater than 500 is often used as a primary genetic metric for evaluating conservation status. We recommend that this guideline be expanded to take into account allelic variation as well as heterozygosity.

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Biological invasion consists of spatially and temporally varying stages, accompanied by ecological and evolutionary changes. Understanding the genomics underlying invasion dynamics provides critical insights into the geographic sources and genetic diversity, contributing to successful invasions across space and time. Here, we used genomic data and model-based approaches to characterize the invasion dynamics of Hypochaeris radicata L., a noxious weed in Korea. Genetic diversity and assignment patterns were investigated using 3563 SNPs of 283 individuals sampled from 22 populations. We employed a coalescent-based simulation method to estimate demographic changes for each population and inferred colonization history using both phylogenetic and population genetic model-based approaches. Our data suggest that H. radicata has been repeatedly been introduced to Korea from multiple genetic sources within the last 50 years, experiencing weak population bottlenecks followed by subsequent population expansions. These findings highlight the potential for further range expansion, particularly in the presence of human-mediated dispersal. Our study represents the first population-level genomic research documenting the invasion dynamics of the successful worldwide invader, H. radicata, outside of Europe.