Variation In Specificity Research Articles

Parasitic plants show striking convergence in host preference across angiosperm lineages.

The host specificity of a parasite underpins its ecology, distribution, invasive potential and adaptability, yet for most parasitic plants host ranges are poorly understood. We examine host-parasite relationships across lineages to infer how host specificity may have influenced the evolution of parasitism in plants. Host preference data for all plant holoparasite species were manually collected from literature and herbarium specimens, then analysed to investigate and visualise host diversity and specificity. We reveal a disproportionality in host preference across host lineages: the Asteraceae contains 10% of angiosperm diversity but is infected by 31% of parasite species; meanwhile Monocots comprise 23% but are infected by just 3.2%. Furthermore, we observe striking convergence in host preference: Asteraceae, Euphorbiaceae and Fabaceae are infected by six, five and four independent parasite lineages, respectively. We also demonstrate considerable variation in the degree of host specificity among closely related parasite species; a result that does not reflect the expectation of holoparasites - especially endoparasites - as host specialists. The marked pattern of convergence in preference across disparate lineages points to a common pathway in the evolution of parasitism of eudicots in preference to monocots, which may have in turn have been driven by a divergence in host root and vascular architecture. The unexpected variation in host specificity among closely related species suggests that even apparent generalists may comprise cryptic host-specific taxa. This highlights the value of host preference as an additional consideration in parasitic plant taxonomy. Together, our data point to a complex interplay between ecological and physiological factors driving the evolution of host-parasite interactions. Moreover, they emphasize how little is known about the ecology of most holoparasitic plants, a group of organisms that are especially vulnerable at a time of unprecedented biodiversity loss and extinction.

Identification of a robust bacterial pyranose oxidase which displays an unusual pH dependence

Pyranose oxidases are valuable biocatalysts, yet only a handful of bacterial pyranose oxidases are known. These bacterial enzymes exhibit noteworthy distinctions from their extensively characterized fungal counterparts, encompassing variations in substrate specificity and structural attributes. Herein a bacterial pyranose oxidase from Oscillatoria princeps (OPOx) was biochemically characterized in detail. In contrast to the fungal pyranose oxidases, OPOx could be well expressed in Escherichia coli as soluble, fully flavinylated and active oxidase. It was found to be highly thermostable (melting temperature >90 ⁰C) and showed activity on glucose, exhibiting an exceptionally low KM value (48 μM). Elucidation of its crystal structure revealed similarities with fungal pyranose oxidases, such as being a tetramer with a large central void leading to a narrow substrate access tunnel. In the active site, the FAD cofactor is covalently bound to a histidine. OPOx displays a relatively narrow pH optimum for activity with a sharp decline at relatively basic pH values which is accompanied with a drastic change in its flavin absorbance spectrum. The pH-dependent switch in flavin absorbance features and oxidase activity was shown to be fully reversible. It is hypothesized that a glutamic acid helps to stabilize the protonated form of the histidine that is tethered to the FAD. OPOx presents itself as a valuable biocatalyst as it is highly robust, well-expressed in E. coli, shows low KM values for monosaccharides and has a peculiar pH dependent “on-off switch”.

Evaluation of Diagnostic Performance of Three Commercial Interferon-Gamma Release Assays for Mycobacterium tuberculosis

Interferon-gamma release assays (IGRAs) have gained attention for the diagnosis of latent tuberculosis infection (LTBI) due to their higher specificity compared to the tuberculin skin test (TST). However, the IGRA’s performance varies across different populations. This study evaluated the diagnostic performance of three IGRAs (TBF-FIA, TBF-ELISA, and QFT-Plus) in Ghana, comparing them among individuals exposed and unexposed to MTB infection. Conducted in TB clinics across three regions, this prospective and cross-sectional study included healthy individuals with no known TB exposure (unexposed group) and patients with confirmed active TB (exposed group). Blood samples were tested using all three assays as per the manufacturers’ guidelines. The TBF-ELISA showed 3.4% higher sensitivity but 4.6% lower specificity compared to QFT-Plus. The TBF-FIA had sensitivity of 78.5–87.3% and specificity of 82.9–90.0%. These findings indicate that while the three IGRAs offer similar diagnostic accuracy, the variations in specificity and limited data on assays like TBF-FIA require further investigation.

Host Tropism and Structural Biology of ABC Toxin Complexes.

ABC toxin complexes are a class of protein toxin translocases comprised of a multimeric assembly of protein subunits. Each subunit displays a unique composition, contributing to the formation of a syringe-like nano-machine with natural cargo carrying, targeting, and translocation capabilities. Many of these toxins are insecticidal, drawing increasing interest in agriculture for use as biological pesticides. The A subunit (TcA) is the largest subunit of the complex and contains domains associated with membrane permeation and targeting. The B and C subunits, TcB and TcC, respectively, package into a cocoon-like structure that contains a toxic peptide and are coupled to TcA to form a continuous channel upon final assembly. In this review, we outline the current understanding and gaps in the knowledge pertaining to ABC toxins, highlighting seven published structures of TcAs and how these structures have led to a better understanding of the mechanism of host tropism and toxin translocation. We also highlight similarities and differences between homologues that contribute to variations in host specificity and conformational change. Lastly, we review the biotechnological potential of ABC toxins as both pesticides and cargo-carrying shuttles that enable the transport of peptides into cells.

Biochemical and Hematological Derangement in Plasmodium falciparum Infected Patients Attending Health Facilities in Northern Taraba State, Nigeria

Plasmodium falciparum predominates as the leading cause of malaria-related mortality, particularly in sub-Saharan Africa, posing a significant global health threat. This study aims to assess the hematological and biochemical alterations attributed to P. falciparum infection among patients seeking care in health facilities across Northern Local Government Areas of Taraba State, encompassing Jalingo, Lau, and Zing. A prospective cross-sectional study method was adopted and enrolled 1,500 participants who underwent testing for P. falciparum using Giemsa-stained blood film examination, Rapid Diagnostic Test (RDT), and Polymerase Chain Reaction (PCR). Hematological parameters, including Packed Cell Volume (PCV), white blood cell counts, and erythrocyte sedimentation rate (ESR), as well as biochemical markers such as albumin, bilirubin, and electrolyte levels, were assessed. Results shows that, out of 1,500 individuals, 304 were infected with P. falciparum, representing a prevalence of 20.3%. Significant differences were observed in hematological and biochemical parameters between infected and non-infected participants, including lower PCV and platelet counts, elevated neutrophil counts, and altered liver enzyme levels among parasitized individuals. The study also compared the diagnostic performance of RDT and microscopy, revealing variations in sensitivity and specificity. This study underscores the clinical utility of hematological and biochemical parameters in malaria management, particularly in resource-limited settings like Nigeria. The findings highlight the importance of comprehensive diagnostic approaches and suggest integrating these adjunct tools into malaria treatment protocols to enhance patient care and outcomes. Keywords: Malaria, Derangement, Haematological, Biochemical, Plasmodium falciparum

Diagnostic performance of AI-based models versus physicians among patients with hepatocellular carcinoma: a systematic review and meta-analysis.

Hepatocellular carcinoma (HCC) is a common primary liver cancer that requires early diagnosis due to its poor prognosis. Recent advances in artificial intelligence (AI) have facilitated hepatocellular carcinoma detection using multiple AI models; however, their performance is still uncertain. This meta-analysis aimed to compare the diagnostic performance of different AI models with that of clinicians in the detection of hepatocellular carcinoma. We searched the PubMed, Scopus, Cochrane Library, and Web of Science databases for eligible studies. The R package was used to synthesize the results. The outcomes of various studies were aggregated using fixed-effect and random-effects models. Statistical heterogeneity was evaluated using I-squared (I2) and chi-square statistics. We included seven studies in our meta-analysis;. Both physicians and AI-based models scored an average sensitivity of 93%. Great variation in sensitivity, accuracy, and specificity was observed depending on the model and diagnostic technique used. The region-based convolutional neural network (RCNN) model showed high sensitivity (96%). Physicians had the highest specificity in diagnosing hepatocellular carcinoma(100%); furthermore, models-based convolutional neural networks achieved high sensitivity. Models based on AI-assisted Contrast-enhanced ultrasound (CEUS) showed poor accuracy (69.9%) compared to physicians and other models. The leave-one-out sensitivity revealed high heterogeneity among studies, which represented true differences among the studies. Models based on Faster R-CNN excel in image classification and data extraction, while both CNN-based models and models combining contrast-enhanced ultrasound (CEUS) with artificial intelligence (AI) had good sensitivity. Although AI models outperform physicians in diagnosing HCC, they should be utilized as supportive tools to help make more accurate and timely decisions.

Computer-aided detection of tuberculosis from chest radiographs in a tuberculosis prevalence survey in South Africa: external validation and modelled impacts of commercially available artificial intelligence software

Computer-aided detection (CAD) can help identify people with active tuberculosis left undetected. However, few studies have compared the performance of commercially available CAD products for screening in high tuberculosis and high HIV settings, and there is poor understanding of threshold selection across products in different populations. We aimed to compare CAD products' performance, with further analyses on subgroup performance and threshold selection. We evaluated 12 CAD products on a case-control sample of participants from a South African tuberculosis prevalence survey. Only those with microbiological test results were eligible. The primary outcome was comparing products' accuracy using the area under the receiver operating characteristic curve (AUC) against microbiological evidence. Threshold analyses were performed based on pre-defined criteria and across all thresholds. We conducted subgroup analyses including age, gender, HIV status, previous tuberculosis history, symptoms presence, and current smoking status. Of the 774 people included, 516 were bacteriologically negative and 258 were bacteriologically positive. Diverse accuracy was noted: Lunit and Nexus had AUCs near 0·9, followed by qXR, JF CXR-2, InferRead, Xvision, and ChestEye (AUCs 0·8-0·9). XrayAME, RADIFY, and TiSepX-TB had AUC under 0·8. Thresholds varied notably across these products and different versions of the same products. Certain products (Lunit, Nexus, JF CXR-2, and qXR) maintained high sensitivity (>90%) across a wide threshold range while reducing the number of individuals requiring confirmatory diagnostic testing. All products generally performed worst in older individuals, people with previous tuberculosis, and people with HIV. Variations in thresholds, sensitivity, and specificity existed across groups and settings. Several previously unevaluated products performed similarly to those evaluated by WHO. Thresholds differed across products and demographic subgroups. The rapid emergence of products and versions necessitates a global strategy to validate new versions and software to support CAD product and threshold selections. Government of Canada.

Natural variation in infection specificity of Caenorhabditis briggsae isolates by two RNA viruses.

Antagonistic relationships such as host-virus interactions potentially lead to rapid evolution and specificity in interactions. The Orsay virus is so far the only horizontal virus naturally infecting the nematode C. elegans. In contrast, several related RNA viruses infect its congener C. briggsae, including Santeuil (SANTV) and Le Blanc (LEBV) viruses. Here we focus on the host's intraspecific variation in sensitivity to these two intestinal viruses. Many temperate-origin C. briggsae strains, including JU1264 and JU1498, are sensitive to both, while many tropical strains, such as AF16, are resistant to both. Interestingly, some C. briggsae strains exhibit a specific resistance, such as the HK104 strain, specifically resistant to LEBV. The viral sensitivity pattern matches the strains' geographic and genomic relationships. The heavily infected strains mount a seemingly normal small RNA response that is insufficient to suppress viral infection, while the resistant strains show no small RNA response, suggesting an early block in viral entry or replication. We use a genetic approach from the host side to map genomic regions participating in viral resistance polymorphisms. Using Advanced Intercrossed Recombinant Inbred Lines (RILs) between virus-resistant AF16 and SANTV-sensitive HK104, we detect Quantitative Trait Loci (QTLs) on chromosomes IV and III. Building RILs between virus-sensitive JU1498 and LEBV-resistant HK104 followed by bulk segregant analysis, we identify a chromosome II QTL. In both cases, further introgressions of the regions confirmed the QTLs. This diversity provides an avenue for studying virus entry, replication, and exit mechanisms, as well as host-virus specificity and the host response to a specific virus infection.

In vitro screening model for compound interactions with human and dairy animal BCRP orthologs

AbstractOrthologs of breast cancer resistance protein (BCRP/ABCG2), an ATP‐binding cassette (ABC) efflux transmembrane transporter, are present in several species. The list of compounds known to interact with BCRP is growing, and many questions remain concerning species‐specific variations in substrate specificity and affinity and the potency of inhibitors. As the most abundant efflux transporter known to be present in the blood–milk barrier, BCRP can increase the elimination of certain xenobiotics to milk, posing a risk for suckling offspring and dairy product consumers. Here we developed a model that can be employed to investigate species‐specific differences between BCRP substrates and inhibitors. Membrane vesicles were isolated from transiently transduced human embryonic kidney (HEK) 293 cells, overexpressing BCRP, with human, bovine, caprine, and ovine cDNA sequences. To confirm BCRP transport activity in the transduced cells, D‐luciferin efflux was measured and to confirm transport activity in the membrane vesicles, [3H] estrone‐3‐sulfate ([3H]E1S) influx was measured. We also determined the Michaelis–Menten constant (Km) and Vmax of [3H]E1S for each species. We have developed an in vitro transport model to study differences in compound interactions with BCRP orthologs from milk‐producing animal species and humans. BCRP transport activity was demonstrated in the species‐specific transduced cells by a reduced accumulation of D‐luciferin compared with the control cells, indicating BCRP‐mediated efflux of D‐luciferin. Functionality of the membrane vesicle model was demonstrated by confirming ATP‐dependent transport and by quantifying the kinetic parameters, Km and Vmax for the model substrate [3H]E1S. The values were not significantly different between species for the model substrates tested. This model can be insightful for appropriate inter‐species extrapolations and risk assessments of xenobiotics in lactating woman and dairy animals.

Comparison of SensPERT® Leishmania rapid test with two other immunochromatographic tests for the diagnosis of canine visceral leishmaniasis in Brazil.

In urban environments, dogs serve as the primary reservoir for visceral leishmaniasis (VL). Rapidly diagnosing canine VL through tests enables early treatment and a favorable prognosis. This study aimed to assess the diagnostic performance of the SensPERT® Leishmania test kit (Dechra®), Alere® Leishmaniasis Ac test kit, and the rapid test dual path platform (TR-DPP®) Bio-Manguinhos in detecting VL. 30 serum samples from reactive VL dogs and 30 serum samples from healthy dogs were employed for assessing the sensitivity and specificity variation between SensPERT® Leishmania test kit, Alere® Leishmaniasis Ac test kit, and rapid test dual platform - TR-DPP®. The SensPERT® Leishmania test outperformed Alere® and TR-DPP® in terms of sensitivity, specificity, positive and negative predictive values and demonstrated near-perfect concordance with Alere® and substantial concurrence with TR-DPP®. The SensPERT® Leishmania rapid test proved to be a promising test in the detection of VL in dogs.

Urgent Need to Understand and Prevent Gonococcal Infection: From the Laboratory to Real-World Context.

Neisseria gonorrhoeae is widespread globally. Primary prevention is unsuccessful and antimicrobial resistance threatens optimal management. There is no specific vaccine and natural infection studies show that N gonorrhoeae can avoid and suppress immune responses. In addition to extensive variation in expression and specificity of many gonococcal surface antigens, it induces a robust inflammatory response through the Th17 pathway with a large influx of neutrophils and inflammatory cytokines but evades macrophages. The Th1- and Th2-mediated response is suppressed, resulting in low, short-lived antibody titers. Real-world evidence suggests that gonorrhea cases are reduced among recipients of Neisseria meningitidis group B vaccines containing outer membrane vesicles (OMVs). Although the first randomized trial of an OMV-containing MenB vaccine against N gonorrhoeae infection did not show statistically significant vaccine efficacy, ongoing trials might shed further light. Several candidate vaccine antigens for a gonococcal-specific vaccine are being evaluated preclinically but only one has reached clinical trials.

Genome-wide identification of the LEA gene family in Panax ginseng: Evidence for the role of PgLEA2-50 in plant abiotic stress response

Ginseng frequently encounters environmental stress during its growth and development. Late Embryogenesis Abundant (LEA) proteins play a crucial role in combating adversity stress, particularly against abiotic challenges In this study, 107 LEA genes from ginseng, spanning eight subfamilies, were identified, demonstrating significant evolutionary conservation, with the LEA2 subfamily being most prominent. Gene duplication events, primarily segmental duplications, have played a major role in the expansion of the LEA gene family, which has undergone strong purifying selection. PgLEAs were unevenly distributed across 22 chromosomes, with each subfamily featuring unique structural domains and conserved motifs. PgLEAs were expressed in various tissues, exhibiting distinct variations in abundance and tissue specificity. Numerous regulatory cis-elements, related to abiotic stress and hormones, were identified in the promoter region. Additionally, PgLEAs were regulated by a diverse array of abiotic stress-related transcription factors. A total of 35 PgLEAs were differentially expressed following treatments with ABA, GA, and IAA. Twenty-three PgLEAs showed significant but varied responses to drought, extreme temperatures, and salinity stress. The transformation of tobacco with the key gene PgLEA2-50 enhanced osmoregulation and antioxidant levels in transgenic lines, improving their resistance to abiotic stress. This study offers insights into functional gene analysis, focusing on LEA proteins, and establishes a foundational framework for research on ginseng's resilience to abiotic stress.

Dyrk1a is required for craniofacial development in Xenopus laevis.

Loss of function variations in the dual specificity tyrosine-phosphorylation-regulated kinase 1 A (DYRK1A) gene are associated with craniofacial malformations in humans. Here we characterized the effects of deficient DYRK1A in craniofacial development using a developmental model, Xenopus laevis. Dyrk1a mRNA and protein were expressed throughout the developing head and both were enriched in the branchial arches which contribute to the face and jaw. Consistently, reduced Dyrk1a function, using dyrk1a morpholinos and pharmacological inhibitors, resulted in orofacial malformations including hypotelorism, altered mouth shape, slanted eyes, and narrower face accompanied by smaller jaw cartilage and muscle. Inhibition of Dyrk1a function resulted in misexpression of key craniofacial regulators including transcription factors and members of the retinoic acid signaling pathway. Two such regulators, sox9 and pax3 are required for neural crest development and their decreased expression corresponds with smaller neural crest domains within the branchial arches. Finally, we determined that the smaller size of the faces, jaw elements and neural crest domains in embryos deficient in Dyrk1a could be explained by increased cell death and decreased proliferation. This study is the first to provide insight into why craniofacial birth defects might arise in humans with variants of DYRK1A.

Advances and Challenges in SARS-CoV-2 Detection: A Review of Molecular and Serological Technologies.

The urgent need for accurate COVID-19 diagnostics has led to the development of various SARS-CoV-2 detection technologies. Real-time reverse transcriptase polymerase chain reaction (RT-qPCR) remains a reliable viral gene detection technique, while other molecular methods, including nucleic acid amplification techniques (NAATs) and isothermal amplification techniques, provide diverse and effective approaches. Serological assays, detecting antibodies in response to viral infection, are crucial for disease surveillance. Saliva-based immunoassays show promise for surveillance purposes. The efficiency of SARS-CoV-2 antibody detection varies, with IgM indicating recent exposure and IgG offering prolonged detectability. Various rapid tests, including lateral-flow immunoassays, present opportunities for quick diagnosis, but their clinical significance requires validation through further studies. Challenges include variations in specificity and sensitivity among testing platforms and evolving assay sensitivities over time. SARS-CoV-2 antigens, particularly the N and S proteins, play a crucial role in diagnostic methods. Innovative approaches, such as nanozyme-based assays and specific nucleotide aptamers, offer enhanced sensitivity and flexibility. In conclusion, ongoing advancements in SARS-CoV-2 detection methods contribute to the global effort in combating the COVID-19 pandemic.

Life-stage specificity and temporal variations in transcriptomes and DNA methylomes of the reef coral Pocillopora damicornis in response to thermal acclimation

Understanding the acclimation capacity of reef corals across generations to thermal stress and its underlying molecular underpinnings could provide insights into their resilience and adaptive responses to future climate change. Here, we acclimated adult brooding coral Pocillopora damicornis to high temperature (32 °C vs. 29 °C) for three weeks and analyzed the changes in phenotypes, transcriptomes and DNA methylomes of adult corals and their brooded larvae. Results showed that although adult corals did not show noticeable bleaching after thermal exposure, they released fewer but larger larvae. Interestingly, larval cohorts from two consecutive lunar days exhibited contrasting physiological resistance to thermal stress, as evidenced by the divergent responses of area-normalized symbiont densities and photochemical efficiency to thermal stress. RNA-seq and whole-genome bisulfite sequencing revealed that adult and larval corals mounted distinct transcriptional and DNA methylation changes in response to thermal stress. Remarkably, larval transcriptomes and DNA methylomes also varied greatly among lunar days and thermal treatments, aligning well with their physiological metrics. Overall, our study shows that changes in transcriptomes and DNA methylomes in response to thermal acclimation can be highly life stage-specific. More importantly, thermally-acclimated adult corals could produce larval offspring with temporally contrasting photochemical performance and thermal resilience, and such variations in larval phenotypes are associated with differential transcriptomes and DNA methylomes, and are likely to increase the likelihood of reproductive success and plasticity of larval propagules under thermal stress.

Automated Midline Shift Detection and Quantification in Traumatic Brain Injury: A Comprehensive Review

AbstractTraumatic brain injury (TBI) often results in midline shift (MLS) that is a critical indicator of the severity and prognosis of head injuries. Automated analysis of MLS from head computed tomography (CT) scans using artificial intelligence (AI) techniques has gained much attention in the past decade and has shown promise in improving diagnostic efficiency and accuracy. This review aims to summarize the current state of research on AI-based approaches for MLS analysis in TBI cases, identify the methodologies employed, evaluate the performance of the algorithms, and draw conclusions regarding their potential clinical applicability. A comprehensive literature search was conducted, identifying 15 distinctive publications. The identified articles were analyzed for their focus on MLS detection and quantification using AI techniques, including their choice of AI algorithms, dataset characteristics, and methodology. The reviewed articles covered various aspects related to MLS detection and quantification, employing deep neural networks trained on two-dimensional or three-dimensional CT imaging datasets. The dataset sizes ranged from 11 patients' CT scans to 25,000 CT images. The performance of the AI algorithms exhibited variations in accuracy, sensitivity, and specificity, with sensitivity ranging from 70 to 100%, and specificity ranging from 73 to 97.4%. AI-based approaches utilizing deep neural networks have demonstrated potential in the automated detection and quantification of MLS in TBI cases. However, different researchers have used different techniques; hence, critical comparison is difficult. Further research and standardization of evaluation protocols are needed to establish the reliability and generalizability of these AI algorithms for MLS detection and quantification in clinical practice. The findings highlight the importance of AI techniques in improving MLS diagnosis and guiding clinical decision-making in TBI management.

Rapid Arterial Occlusion Evaluation (RACE) Tool in Detecting Large Cerebral Vessel Occlusions; a Systematic Review and Meta-Analysis.

Large vessel occlusion (LVO) strokes are linked to higher mortality rates and a greater risk of long-term disability. This study aimed to evaluate the diagnostic performance of the Rapid Arterial Occlusion Evaluation (RACE) tool in detecting LVO through a systematic review and meta-analysis. A comprehensive search was conducted across online databases including PubMed, Embase, Scopus, and Web of Science, up to June 25th, 2023. Additionally, a manual search on Google and Google Scholar was performed to identify studies that assessed the diagnostic accuracy of the RACE scale in detecting LVO among patients with stroke symptoms. Data extracted from 43 studies were analyzed. The optimal cut-off points were determined to be 3 and 4, with a sensitivity of 0.86 (95% confidence interval (CI): 0.78, 0.91) and specificity of 0.57 (95% CI: 0.49, 0.67) for cut-off ≥3, and a sensitivity of 0.78 (95% CI: 0.70, 0.84) and specificity of 0.68 (95% CI: 0.59, 0.75) for cut-off ≥4. Subgroup meta-regression analysis revealed significant variations in sensitivity and specificity. RACE scale's sensitivity was significantly higher in LVO detection in suspected stroke cases, in pre-hospital settings, prospective design studies, and when considering both anterior and posterior occlusions for LVO definition. RACE scale's specificity was significantly higher when evaluating confirmed stroke cases, in-hospital settings, and considering only anterior occlusions for LVO definition and retrospective design studies. Notably, RACE exhibited higher sensitivity and specificity when utilized by neurologists and physicians compared to other emergency staff. Despite these variations, our study found comparable diagnostic accuracy across different conditions. A high level of evidence indicates that the RACE scale lacks promising diagnostic value for detection of LVOs. A sensitivity range of 0.69 to 0.86 is insufficient for a screening tool intended to aid in the diagnosis of strokes, considering the substantial morbidity and mortality associated with this condition.

Artificial Intelligence in Laboratory Technologies for Early Detection and Prognostication of Sepsis: A Systematic Review

Background: Sepsis: a complex clinical syndrome--represents life-threatening organ dysfunction instigated by an infection's dysregulated host response. Early detection and accurate prognostication of sepsis are crucial; they pave the way for timely intervention, ultimately enhancing patient outcomes. The rise in interest towards Artificial Intelligence (AI) applications within laboratory technologies is directly related to its potential for improving early detection and prognosis forecasting in sepsis cases; this interest comes as AI continues its advancement. Methods: We conducted a systematic review of studies utilizing AI algorithms in laboratory settings for early sepsis detection and prognostication: our methods entailed searching relevant databases for research published until October 2023. Our inclusion criteria spanned original articles; these applied machine learning (ML) and deep learning (DL) techniques to laboratory data--with the aim being sepsis prediction. We assessed the quality of the studies, extracted and synthesized data on AI model performance metrics - including: area under receiver operating characteristic curve (AUROC), sensitivity, specificity, and accuracy. Results: The review encompassed eight studies meeting the inclusion criteria; AI models showcased exceptional predictive capabilities--evidenced by a range of AUROC values from 0.799 to 0.9213, signifying noticeably acceptable performance. However, there was wide variation in sensitivity and specificity among these analyses: an indicator of heterogeneity in model performance. Superior prognostic accuracy and potential for real-time monitoring of patients' early sepsis signs emerged in several models: notably, within the first 12 hours of patient admission - their highest predictive period. The models frequently outperformed traditional scoring systems. Conclusion: Laboratory technology's AI applications significantly promise sepsis' early detection and prognostication. Reviewed studies suggest AI models may surpass traditional methods, offering potential integration into clinical workflows for rapid sepsis identification aid. Nevertheless, we also acknowledged both the variability in model performance and necessity of additional validation across diverse clinical settings. Future research: it must concentrate on two key aspects--the refinement of AI algorithms to enhance sensitivity and precision; furthermore, it should delve into evaluating the clinical impact of tools for sepsis prediction that are assisted by AI.

Diversity and host specificity of Borrelia burgdorferi's outer surface protein C (ospC) alleles in synanthropic mammals, with a notable ospC allele U absence from mixed infections.

Interactions among pathogen genotypes that vary in host specificity may affect overall transmission dynamics in multi-host systems. Borrelia burgdorferi, a bacterium that causes Lyme disease, is typically transmitted among wildlife by Ixodes ticks. Despite the existence of many alleles of B. burgdorferi's sensu stricto outer surface protein C (ospC) gene, most human infections are caused by a small number of ospC alleles ["human infectious alleles" (HIAs)], suggesting variation in host specificity associated with ospC. To characterize the wildlife host association of B. burgdorferi's ospC alleles, we used metagenomics to sequence ospC alleles from 68 infected individuals belonging to eight mammalian species trapped at three sites in suburban New Brunswick, New Jersey (USA). We found that multiple allele ("mixed") infections were common. HIAs were most common in mice (Peromyscus spp.) and only one HIA was detected at a site where mice were rarely captured. ospC allele U was exclusively found in chipmunks (Tamias striatus), and although a significant number of different alleles were observed in chipmunks, including HIAs, allele U never co-occurred with other alleles in mixed infections. Our results suggest that allele U may be excluding other alleles, thereby reducing the capacity of chipmunks to act as reservoirs for HIAs.

Fluorescence and Near-Infrared Light for Detection of Secondary Caries: A Systematic Review.

Early detection of secondary caries near dental restorations is essential to prevent further complications. This systematic review seeks to evaluate the sensitivity of fluorescence and near-infrared (NIR) imaging techniques for detecting secondary caries and to provide insight into their clinical utility. A comprehensive search strategy was used to select studies from seven databases, emphasizing diagnostic accuracy studies of secondary caries detection using fluorescence and NIR imaging techniques. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) instrument assessed bias risk and practicality. Two evaluators performed data extraction, screening, and quality assessment independently. From 3110 initial recordings, nine studies were selected for full-text analysis. Wide variations in sensitivity (SE) and specificity (SP) values were reported across the studies. These studies exhibited variable SE and SP values, and the findings highlighted the importance of method selection based on clinical context. This systematic review underlines the potential for fluorescence and NIR imaging to detect secondary caries. However, results from different studies vary, indicating the need to consider additional variables such as restoration materials. Although these technologies exhibit potential for detecting caries, our research underscores the complex procedure of identifying secondary caries lesions. It is a continuous necessity for progress in dental diagnostics to promptly identify secondary caries lesions, particularly those in proximity to tooth-colored ones.