Tool For Identification Research Articles

Organization and Structures for Detection and Monitoring of CKD Across World Countries and Regions: Observational Data From a Global Survey

Rationale & ObjectiveEstablished therapeutic interventions effectively mitigate the risk and progression of chronic kidney disease (CKD). Countries and regions have a compelling need for organizational structures that enable early identification of people with CKD who can benefit from these proven interventions. We aimed to report the current global status of CKD detection programs. Study DesignA multinational cross-sectional survey. Setting & ParticipantsStakeholders, including nephrologist leaders, policymakers, and patient advocates from 167 countries, participating in the International Society of Nephrology (ISN) survey from June to September 2022. OutcomesStructures for the detection and monitoring of CKD, including CKD surveillance systems in the form of registries, community-based detection programs, case-finding practices, and availability of measurement tools for risk identification. Analytical ApproachDescriptive statistics. ResultsOf all participating countries, 19% (n=31) reported CKD registries and 25% (n=40) reported implementing CKD detection programs as part of their national policies. There were variations in CKD detection program, with 50% (n=20) using a reactive approach (managing cases as identified) and 50% (n=20) actively pursuing case-finding in at-risk populations. Routine case-finding for CKD in high-risk populations was widespread, particularly for diabetes (n=152; 91%) and hypertension (n=148; 89%). Access to diagnostic tools, estimated glomerular filtration rate (eGFR) and urine albumin-creatinine ratio (UACR), was limited, especially in low-income (LICs) and lower-middle-income (LMICs) countries, at primary (eGFR: LICs 22%, LMICs 39%, UACR: LICs 28%, LMICs 39%) and secondary/tertiary healthcare levels (eGFR: LICs 39%, LMICs 73%, UACR: LICs 44%, LMICs 70%), potentially hindering CKD detection. LimitationsA lack of detailed data prevented an in-depth analysis. ConclusionThis comprehensive survey highlights a global heterogeneity in the organization and structures (surveillance systems, detection programs and tools) for early identification of CKD. Ongoing efforts should be geared toward bridging such disparities to optimally prevent the onset and progression of CKD and its complications.

Big data analysis for Covid-19 in hospital information systems.

The COVID-19 pandemic has triggered a global public health crisis, affecting hundreds of countries. With the increasing number of infected cases, developing automated COVID-19 identification tools based on CT images can effectively assist clinical diagnosis and reduce the tedious workload of image interpretation. To expand the dataset for machine learning methods, it is necessary to aggregate cases from different medical systems to learn robust and generalizable models. This paper proposes a novel deep learning joint framework that can effectively handle heterogeneous datasets with distribution discrepancies for accurate COVID-19 identification. We address the cross-site domain shift by redesigning the COVID-Net's network architecture and learning strategy, and independent feature normalization in latent space to improve prediction accuracy and learning efficiency. Additionally, we propose using a contrastive training objective to enhance the domain invariance of semantic embeddings and boost classification performance on each dataset. We develop and evaluate our method with two large-scale public COVID-19 diagnosis datasets containing CT images. Extensive experiments show that our method consistently improves the performance both datasets, outperforming the original COVID-Net trained on each dataset by 13.27% and 15.15% in AUC respectively, also exceeding existing state-of-the-art multi-site learning methods.

The development of multiplex PCR assays for the rapid identification of multiple Saccostrea species, and their practical applications in restoration and aquaculture

BackgroundThe ecology and biology of oysters (Ostreidae) across the tropics is poorly understood. Morphological plasticity and shared characteristics among oysters have resulted in the misidentification of species, creating challenges for understanding basic species-specific biological information that is required for restoration and aquaculture. Genetic barcoding has proven essential for accurate species identification and understanding species geographic ranges. To reduce the costs of molecular species identification we developed multiplex assays using the cytochrome c oxidase subunit I (COI or cox1) barcoding gene for the rapid identification of five species of oysters within the genus Saccostrea that are commonly found in Queensland, Australia: Saccostrea glomerata, Saccostrea lineage B, Saccostrea lineage F, Saccostrea lineage G, and Saccostrea spathulata (lineage J).ResultsMultiplex assays were successful in species-specific amplification of targeted species. The practical application of these primers was tested on wild spat collected from a pilot restoration project in Moreton Bay, Queensland, with identified species (S. glomerata, lineage B and lineage G) validated by Sanger sequencing. DNA sampling by extraction of oyster pallial fluid was also tested on adult oysters collected from the Noosa estuary in Queensland to assess whether oysters were able to be identified non-destructively. DNA concentrations as low as 1 ng/ μL still amplified in most cases, allowing for identification, and mortality at 6 weeks post pallial fluid collection was low (3 out of 104 sampled oysters).ConclusionThese multiplex assays will be essential tools for species identification in future studies, and we successfully demonstrate their practical application in both restoration and aquaculture contexts in Queensland. The multiplex assays developed in this study outline easily replicable methods for the development of additional species-specific primer sets for the rapid identification of other species of Saccostrea found across the Indo-Pacific, which will be instrumental in unravelling the taxonomic ambiguities within this genus in tropical regions.

Machine-Learning and Physics-Based Tool for Anomaly Identification in Propulsion Systems

Launch anomalies occur frequently during the early phase of a program, with many of the anomalies attributed to propulsion systems. Approaches for identifying and mitigating potential propulsion failures can aid development programs and accelerate the resolution of root cause investigations. In reusable systems, anomaly detection methods can be employed to detect latent system health issues that could become problematic as the system ages. Modern launch support relies on human judgement for redline limit generation and visual family data comparison for many operational aspects, which makes it challenging to identify failure modes and to diagnose an anomaly. Additionally, family data comparison is unavailable for the first few launches of a new vehicle. Automated tools to quickly identify system failures of new and reusable systems can bridge these gaps. Physics-based modeling and machine learning (PBMML) offers methods that can improve the reliability of new or reusable launch vehicles by identifying propulsion anomalies or issues before they jeopardize future space missions. PBMML can then be used to inform corrective actions. This paper describes an anomaly data generation module which automates the process of simulating anomalous scenarios in launch vehicle and fluid networks, while a long-term short-term memory network is used to provide real-time anomaly classification on a simplified stage test case.

Emotion expression salience and racially biased weapon identification: A diffusion modeling approach.

Racial stereotypes are commonly activated by informational cues that are detectable in people's faces. Here, we used a sequential priming task to examine whether and how the salience of emotion (angry/scowling vs. happy/smiling expressions) or apparent race (Black vs. White) information in male face primes shapes racially biased weapon identification (gun vs. tool) decisions. In two experiments (Ntotal = 546) using two different manipulations of facial information salience, racial bias in weapon identification was weaker when the salience of emotion expression versus race was heightened. Using diffusion decision modeling, we tested competing accounts of the cognitive mechanism by which the salience of facial information moderates this behavioral effect. Consistent support emerged for an initial bias account, whereby the decision process began closer to the "gun" response upon seeing faces of Black versus White men, and this racially biased shift in the starting position was weaker when emotion versus race information was salient. We discuss these results vis-à-vis prior empirical and theoretical work on how facial information salience moderates racial bias in decision-making.

BUSINESS RISK CONTROL TECHNIQUES AND ENTREPRENEURIAL SUCCESS: EVIDENCE FROM SELECTED TERTIARY INSTITUTIONS’ STUDENTS IN EKITI STATE NIGERIA

Risk control techniques are key instrument for enhancing the entrepreneurial successes required in tertiary students in the face of herculean economic hardship. This study examined the nexus between risk control techniques and business performance among selected tertiary institutions’ students in Ekiti State. The study adopted a cross-sectional survey design cum double sampling techniques comprising purposive and convenience. The study further employed a structured questionnaire to gather data from a sample size of two hundred and sixty-seven (267) participants. Descriptive statistic, Friedman’s rank test and simple regression techniques were adopted in the data analysis. The study showcased the rank-order analysis of risk control techniques and entrepreneurial successes criteria. Further results also revealed the positive relationship between risk control techniques and entrepreneurial successes of selected tertiary institutions’ students in Ekiti State, Nigeria. The study recommended that educational stakeholders in tertiary institutions ensure that their students are equipped with the necessary understanding of risk management techniques, which can assist them in their respective commercial endeavours. Furthermore, tertiary institutions should incorporate into their entrepreneurship curriculum a variety of risk identification tools that will effectively stimulate the entrepreneurial intention and behaviour of students. Tertiary universities should establish enterprises that can function as incubators for their students to gain practical experience in business development.

Early Detection and Intervention for Children with High Risk of Cerebral Palsy: A Survey of Physical Therapists and Occupational Therapists in Brazil

Aims The purpose of this study was to assess the current clinical practice of physiotherapists and occupational therapists on early detection and early intervention for children with cerebral palsy (CP) in Brazil. Methods This was a cross-sectional study. A purpose-developed electronic survey was disseminated across the country to physiotherapists and occupational therapists working with young children with or at risk of CP. Results A total of 205 anonymous respondents were included. Most participants (64.4%) agree that the diagnosis of CP can be made before 6 months of age. General Movements Assessment (26.8%) and Hammersmith Infant Neurological Examination (37.1%) were used infrequently. Infants at risk for CP receive therapy twice a week or more by 58.5% of therapists, 93.2% identified parents’ goals as the most important factor in customizing the early intervention program. The most frequent intervention strategies for this age group were active stimulation of the child (n = 182), family training (n = 161), strategies to optimize the environment (n = 143), and neurodevelopmental treatment/Bobath (n = 99). Conclusions Currently, pediatric physiotherapists and occupational therapists in Brazil do not fully incorporate best practice tools for early identification of children with CP, nor sufficient best evidence-based interventions.

Deep learning for automatic facial detection and recognition in Japanese macaques: illuminating social networks.

Individual identification plays a pivotal role in ecology and ethology, notably as a tool for complex social structures understanding. However, traditional identification methods often involve invasive physical tags and can prove both disruptive for animals and time-intensive for researchers. In recent years, the integration of deep learning in research has offered new methodological perspectives through the automatisation of complex tasks. Harnessing object detection and recognition technologies is increasingly used by researchers to achieve identification on video footage. This study represents a preliminary exploration into the development of a non-invasive tool for face detection and individual identification of Japanese macaques (Macaca fuscata) through deep learning. The ultimate goal of this research is, using identification done on the dataset, to automatically generate a social network representation of the studied population. The current main results are promising: (i) the creation of a Japanese macaques' face detector (Faster-RCNN model), reaching an accuracy of 82.2% and (ii) the creation of an individual recogniser for the Kōjima Island macaque population (YOLOv8n model), reaching an accuracy of 83%. We also created a Kōjima population social network by traditional methods, based on co-occurrences on videos. Thus, we provide a benchmark against which the automatically generated network will be assessed for reliability. These preliminary results are a testament to the potential of this approach to provide the scientific community with a tool for tracking individuals and social network studies in Japanese macaques.

Enzymatic Synthesis and Structural Modeling of Bio-Based Oligoesters as an Approach for the Fast Screening of Marine Biodegradation and Ecotoxicity.

Given the widespread use of esters and polyesters in products like cosmetics, fishing nets, lubricants and adhesives, whose specific application(s) may cause their dispersion in open environments, there is a critical need for stringent eco-design criteria based on biodegradability and ecotoxicity evidence. Our approach integrates experimental and computational methods based on short oligomers, offering a screening tool for the rapid identification of sustainable monomers and oligomers, with a special focus on bio-based alternates. We provide insights into the relationships between the chemical structure and properties of bio-based oligomers in terms of biodegradability in marine environments and toxicity in benchmark organisms. The experimental results reveal that the considered aromatic monomers (terephthalic acid and 2,5-furandicarboxylic acid) accumulate under the tested conditions (OECD 306), although some slight biodegradation is observable when the inoculum derives from sites affected by industrial and urban pollution, which suggests that ecosystems adapt to non-natural chemical pollutants. While clean seas are more susceptible to toxic chemical buildup, biotic catalytic activities offer promise for plastic pollution mitigation. Without prejudice to the fact that biodegradability inherently signifies a desirable trait in plastic products, nor that it automatically grants them a sustainable "license", this study is intended to facilitate the rational design of new polymers and materials on the basis of specific uses and applications.

European Stroke Organisation (ESO) Guidelines on the diagnosis and management of patent foramen ovale (PFO) after stroke.

Patent foramen ovale (PFO) is frequently identified in young patients with cryptogenic ischaemic stroke. Potential stroke mechanisms include paradoxical embolism from a venous clot which traverses the PFO, in situ clot formation within the PFO, and atrial arrhythmias due to electrical signalling disruption. The purpose of this guideline is to provide recommendations for diagnosing, treating, and long-term managing patients with ischaemic stroke and PFO. Conversely, Transient Ischaemic Attack (TIA) was not considered an index event in this context because only one RCT involved TIA patients. However, this subgroup analysis showed no significant differences between TIA and stroke outcomes. The working group identified questions and outcomes, graded evidence, and developed recommendations following the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach and the European Stroke Organisation (ESO) standard operating procedure for guideline development. This document underwent peer-review by independent experts and members of the ESO Guideline Board and Executive Committee. The working group acknowledges the current evidentiary gap in delineating an unequivocal diagnostic algorithm for the detection of PFO. Although transoesophageal echocardiography is conventionally held as the most accurate diagnostic tool for PFO identification, its status as the 'gold standard' remains unsubstantiated by rigorously validated evidence. We found high-quality evidence to recommend PFO closure plus antiplatelet therapy in selected patients aged 18-60 years in whom no other evident cause of stroke is found but a PFO (i.e. PFO-associated stroke). The PASCAL classification system can be used to select such candidates for PFO closure. Patients with both a large right-to-left shunt and an atrial septal aneurysm benefit most from PFO closure. There is insufficient evidence to make an evidence-based recommendation on PFO closure in patients older than 60 and younger than 18 years. We found low quality evidence to suggest against PFO closure in patients with unlikely PFO-related stroke according to the PASCAL classification, except in specific scenarios (Expert Consensus). We suggest against long-term anticoagulation in patients with PFO-associated stroke unless anticoagulation is indicated for other medical reasons. Regarding the long-term AF monitoring after PFO closure, the working group concluded that there remains significant uncertainty regarding the risks and benefits associated with the use of long-term cardiac monitoring, such as implantable loop recorders. This document provides additional guidance, in the form of evidence-based recommendations or expert consensus statements, on diagnostic methods for PFO detection, and medical management after PFO closure.

A High-Homology Region Provides the Possibility of Detecting β-Barrel Pore-Forming Toxins from Various Bacterial Species.

The pathogenicity of many bacteria, including Bacillus cereus and Staphylococcus aureus, depends on pore-forming toxins (PFTs), which cause the lysis of host cells by forming pores in the membranes of eukaryotic cells. Bioinformatic analysis revealed a region homologous to the Lys171-Gly250 sequence in hemolysin II (HlyII) from B. cereus in over 600 PFTs, which we designated as a "homologous peptide". Three β-barrel PFTs were used for a detailed comparative analysis. Two of them-HlyII and cytotoxin K2 (CytK2)-are synthesized in Bacillus cereus sensu lato; the third, S. aureus α-toxin (Hla), is the most investigated representative of the family. Protein modeling showed certain amino acids of the homologous peptide to be located on the surface of the monomeric forms of these β-barrel PFTs. We obtained monoclonal antibodies against both a cloned homologous peptide and a 14-membered synthetic peptide, DSFNTFYGNQLFMK, as part of the homologous peptide. The HlyII, CytK2, and Hla regions recognized by the obtained antibodies, as well as an antibody capable of suppressing the hemolytic activity of CytK2, were identified in the course of this work. Antibodies capable of recognizing PFTs of various origins can be useful tools for both identification and suppression of the cytolytic activity of PFTs.

Transfer learning enables identification of multiple types of RNA modifications using nanopore direct RNA sequencing

Nanopore direct RNA sequencing (DRS) has emerged as a powerful tool for RNA modification identification. However, concurrently detecting multiple types of modifications in a single DRS sample remains a challenge. Here, we develop TandemMod, a transferable deep learning framework capable of detecting multiple types of RNA modifications in single DRS data. To train high-performance TandemMod models, we generate in vitro epitranscriptome datasets from cDNA libraries, containing thousands of transcripts labeled with various types of RNA modifications. We validate the performance of TandemMod on both in vitro transcripts and in vivo human cell lines, confirming its high accuracy for profiling m6A and m5C modification sites. Furthermore, we perform transfer learning for identifying other modifications such as m7G, Ψ, and inosine, significantly reducing training data size and running time without compromising performance. Finally, we apply TandemMod to identify 3 types of RNA modifications in rice grown in different environments, demonstrating its applicability across species and conditions. In summary, we provide a resource with ground-truth labels that can serve as benchmark datasets for nanopore-based modification identification methods, and TandemMod for identifying diverse RNA modifications using a single DRS sample.

Multiplexing the Identification of Microorganisms via Tandem Mass Tag Labeling Augmented by Interference Removal through a Novel Modification of the Expectation Maximization Algorithm.

Having fast, accurate, and broad spectrum methods for the identification of microorganisms is of paramount importance to public health, research, and safety. Bottom-up mass spectrometer-based proteomics has emerged as an effective tool for the accurate identification of microorganisms from microbial isolates. However, one major hurdle that limits the deployment of this tool for routine clinical diagnosis, and other areas of research such as culturomics, is the instrument time required for the mass spectrometer to analyze a single sample, which can take ∼1 h per sample, when using mass spectrometers that are presently used in most institutes. To address this issue, in this study, we employed, for the first time, tandem mass tags (TMTs) in multiplex identifications of microorganisms from multiple TMT-labeled samples in one MS/MS experiment. A difficulty encountered when using TMT labeling is the presence of interference in the measured intensities of TMT reporter ions. To correct for interference, we employed in the proposed method a modified version of the expectation maximization (EM) algorithm that redistributes the signal from ion interference back to the correct TMT-labeled samples. We have evaluated the sensitivity and specificity of the proposed method using 94 MS/MS experiments (covering a broad range of protein concentration ratios across TMT-labeled channels and experimental parameters), containing a total of 1931 true positive TMT-labeled channels and 317 true negative TMT-labeled channels. The results of the evaluation show that the proposed method has an identification sensitivity of 93-97% and a specificity of 100% at the species level. Furthermore, as a proof of concept, using an in-house-generated data set composed of some of the most common urinary tract pathogens, we demonstrated that by using the proposed method the mass spectrometer time required per sample, using a 1 h LC-MS/MS run, can be reduced to 10 and 6 min when samples are labeled with TMT-6 and TMT-10, respectively. The proposed method can also be used along with Orbitrap mass spectrometers that have faster MS/MS acquisition rates, like the recently released Orbitrap Astral mass spectrometer, to further reduce the mass spectrometer time required per sample.

Tunable and narrowband shortwave infrared light sensing enabled by dual-Fano resonance enhanced sum-frequency generation

Tunable and narrowband light detection provides a means of selectively detecting optical signals at a specific wavelength, enabling a precise tool for object identification, machine vision, spectroscopy, and so on. Simultaneous tunable and narrowband response in shortwave infrared (SWIR) detectors is critical yet still challenging. This work utilizes dual-Fano resonance enhanced sum-frequency generation in a two-layer structure comprising a silicon metasurface and a two-dimensional (2D) nonlinear GaSe layer to realize tunable and narrowband light detection in the SWIR range. The silicon metasurface affords a high-quality-factor dual-Fano resonance in the SWIR regime, which enhances the near-field optical density of the two resonant wavelengths (pump and signal) when passing through the 2D nonlinear layer, leading to drastically enhanced sum-frequency generation. The sum-frequency light at a visible wavelength that contains the information of the SWIR signal light, can then be detected by a low-noise visible detector. The tunability and selectivity in the response spectrum stem from the geometry-dependent dual-Fano resonance in the silicon metasurface, covering the 1200–1550 nm range. The upconversion detector exhibits a sub-nanometer narrowband detection with a full width at half maximum of down to ∼0.1 nm, owing to the high quality factor of the Fano resonances. This SWIR narrowband detection is one of the best performances reported so far, much narrower than commercial filter products. The peak value of the specific detectivity of 1.5 × 1012 Jones at 1256.3 nm is achieved, comparable to broadband commercial InGaAs detectors. The detector designs in this work open up the opportunity of upconversion sensors for delicate spectroscopic applications.

Mannheimia indoligenes sp. nov., proposed for clade V organisms of Mannheimia.

A set of 25 strains belonging to clade V of Mannheimia mainly isolated from cattle was investigated and is proposed to represent Mannheimia indoligenes sp. nov. The species can be separated from the other validly published species of the genus by pheno- and genotype. Only indole separates M. indoligenes and Mannheimia varigena while two to seven characters separate M. indoligenes from other species of Mannheimia. Thirteen strains belonging to biogroups 6, 7, 8C, 9, 10, 12 and UG5 formed a monophyletic group based on 16S rRNA gene sequence comparisons with 98-100 % similarity. Eight of these strains were further included in the whole genome comparison. Digital DNA-DNA hybridization showed that the similarities between the suggested type strain M14.4T and the other strains of M. indoligenes were 62.9 % or higher. The average nucleotide identity was 95.5 % or higher between M14.4T and the other strains of the species. The rpoB gene sequence similarity was 95-100 % within M. indoligenes. MALDI-TOF allowed a clear separation from other Mannheimia species further supporting classification as a novel species and making it the diagnostic identification tool of choice for M. indoligenes. The type strain is M14.4T (=CCUG 77347T=DSM 116804T) isolated from a cattle tongue in Scotland.

Thermally resistant nuclease in Serratia marcescens hinders PCR reactions and degrades PCR products.

Polymerase chain reaction (PCR) is an important tool for exogenous gene acquisition and recombinants identification. There exist two problems when using Serratia marcescens as a template for PCR amplification: amplified PCR products are rapidly degraded, and the results of PCR amplification are unstable. The aim of the present work was to elucidate the reasons for this. By mixing PCR products amplified from Escherichia coli DH5α with S. marcescens supernatant or pellet, we found that the DNA-degrading substance in S. marcescens is thermally resistant and present both intracellularly and extracellularly. We then determined that it is protein, and most likely S. marcescens nuclease, that degrades PCR products since the addition of SDS and EDTA can effectively inhibit or block the degradation of PCR products. By knocking out the S. marcescens nuclease encoding gene, nucA, we confirmed that the nuclease is responsible for the degradation of PCR products and the instability of PCR amplification. This work is the first to show that the S. marcescens nuclease is temporarily and partially inhibited by high temperatures during PCR and recovers rapidly at room temperature after PCR.

A DNA barcode reference library of Croatian mosquitoes (Diptera: Culicidae): implications for identification and delimitation of species, with notes on the distribution of potential vector species

BackgroundMosquitoes pose a risk to human health worldwide, and correct species identification and detection of cryptic species are the most important keys for surveillance and control of mosquito vectors. In addition to traditional identification based on morphology, DNA barcoding has recently been widely used as a complementary tool for reliable identification of mosquito species. The main objective of this study was to create a reference DNA barcode library for the Croatian mosquito fauna, which should contribute to more accurate and faster identification of species, including cryptic species, and recognition of relevant vector species.MethodsSampling was carried out in three biogeographical regions of Croatia over six years (2017–2022). The mosquitoes were morphologically identified; molecular identification was based on the standard barcoding region of the mitochondrial COI gene and the nuclear ITS2 region, the latter to identify species within the Anopheles maculipennis complex. The BIN-RESL algorithm assigned the COI sequences to the corresponding BINs (Barcode Index Number clusters) in BOLD, i.e. to putative MOTUs (Molecular Operational Taxonomic Units). The bPTP and ASAP species delimitation methods were applied to the genus datasets in order to verify/confirm the assignment of specimens to specific MOTUs.ResultsA total of 405 mosquito specimens belonging to six genera and 30 morphospecies were collected and processed. Species delimitation methods assigned the samples to 31 (BIN-RESL), 30 (bPTP) and 28 (ASAP) MOTUs, with most delimited MOTUs matching the morphological identification. Some species of the genera Culex, Aedes and Anopheles were assigned to the same MOTUs, especially species that are difficult to distinguish morphologically and/or represent species complexes. In total, COI barcode sequences for 34 mosquito species and ITS2 sequences for three species of the genus Anopheles were added to the mosquito sequence database for Croatia, including one individual from the Intrudens Group, which represents a new record for the Croatian mosquito fauna.ConclusionWe present the results of the first comprehensive study combining morphological and molecular identification of most mosquito species present in Croatia, including several invasive and vector species. With the exception of some closely related species, this study confirmed that DNA barcoding based on COI provides a reliable basis for the identification of mosquito species in Croatia.Graphical

Missing persons and infrastructures of search and identification

People go missing all over the world, but the reasons for disappearances are enormously diverse. Some people are intentionally disappeared by the state: totalitarian and military governments as well as various paramilitary and criminal organizations have used enforced disappearances as a tactic to control the population and create submissive citizens or subjects though fear and insecurity. Both civilians and soldiers disappear invariably in the chaotic circumstances of war and armed conflict. Some people disappear in natural catastrophes or fatal accidents; some disappear of their own free will. Whatever the reason for disappearance, it disturbs the everyday flow of life in families and communities, and in many places, it creates anomalies for modern state bureaucracies. Unaccounted-for absences give rise to search practices, but the circumstances of search are radically different in different places and different contexts of disappearance. One way to approach these differences is to analyse the infrastructures of search in each site. I am especially interested in the entanglement of the local with the global, and of the spatial reach of search infrastructures . Moreover, I consider the significance of the material affordances of some infrastructural forms, especially of the DNA as the key tool for identification. I make some observations on how the entanglements of local and transnational investment and the material affordances of the techniques allow some of the disappeared to be found and identified, while others stay more ‘disappearable’ (Laakkonen 2022).

Biomarkers of mussel exposure to Vibrionaceae: A review

For more than a century, bacterial infections caused by Vibrio spp. have affected various species of mussels around the world, with limited insights into the responses implemented by mussels against these infections. A combination of chemical analyses and carefully selected biological endpoints from haemolymph and tissues can be used to identify the welfare status of mussels and potentially protect aquatic ecosystems from catastrophic health threats. Recent developments in biomarker identification tools, such as omics and bioinformatics, have been successfully applied to evaluate the effect of environmental pollutants and other chemicals on mussels. However, the application of biomarkers to assess mussel health is limited. This review describes the available scientific literature on biomarker research for Vibrio-mussel interactions, and those aspects related to mussel health and disease assessment, grouped as biomarkers of exposure, effects, and susceptibility. From the review, it is clear that when integrated biomarkers are used, they can provide a deeper understanding of the relative health and potential susceptibility of mussels for better management practices. Furthermore, health biomarker data can be used to build resilience in mussels against climate change conditions, strengthen biosecurity management programs, improve farming and processing efficiency, and add value in terms of market-desirable traits. These data hold promise for advancing sustainability efforts within the aquaculture industry.Graphical abstract

Hematological ratios in patients with acute decompensation and acute-on-chronic liver failure: prognostic factors.

Acute-on-chronic liver failure (ACLF) is the most severe form of acutely decompensated cirrhosis and is characterized by the presence of intense systemic inflammation. Leucocyte quantification can serve as an indirect indicator of systemic inflammation. In our study, we investigated the predictive value of hematological ratios (neutrophils to lymphocytes, monocyte to lymphocytes, platelets to lymphocytes, lymphocytes to C-reactive protein, and neutrophils to lymphocytes and platelets) in acute decompensation (AD) and ACLF patients and their relation to disease severity and early mortality. We included 60 patients with ACLF and AD, and 30 cirrhotic controls. Clinical data were collected, and survival was followed for 1 and 6 months. Blood samples were analyzed at admission for differential leucocytes and assessed for liver and renal function tests. The leukocyte ratios were calculated and compared, and their correlation with liver function indicators and prognosis was assessed. All ratios were significantly higher in AD and ACLF patients compared to control (except for lymphocyte to C-reactive protein ratio which was significantly lower), and were positively correlated with Child-Pugh score, model for end-stage liver disease (MELD)-Na, and ACLF severity scores. Multivariate regression revealed that neutrophil to lymphocyte ratio, monocyte to lymphocyte ratio, and MELD-Na were independent prognostic factors of 1-month and 6-month mortality. A unique prognostic nomogram incorporating MELD-Na, neutrophil to lymphocyte ratio, and monocyte to lymphocyte ratio could be proposed for predicting prognosis in AD and ACLF patients. Cheap, easy, and noninvasive hematological ratios are introduced as a tool for early identification and risk stratification of AD and ACLF patients.