Variable Sensitivity Research Articles

Variable bioenergetic sensitivity of neurons and astrocytes to insulin and extracellular glucose

Energy flow within cellular elements of the brain is a well-orchestrated, tightly regulated process, however, details underlying these functions at the single-cell level are still poorly understood. Studying hypometabolism in aging and neurodegenerative diseases may benefit from experimentation on unicellular bioenergetics. Here, we examined energy status in neurons and astrocytes using mixed hippocampal cultures and PercevalHR, an ATP:ADP nanosensor. We assessed exposures of several compounds including KCl, glutamate, FCCP, insulin, and glucose. A mitochondrial stress test was performed, and PercevalHR’s fluorescence was corrected for pH using pHrodo. Results demonstrate that PercevalHR can reliably report on the energetic status of two cell types that communicate in a mixed-culture setting. While KCl, glutamate, and FCCP showed clear changes in PercevalHR fluorescence, insulin and glucose responses were found to be more subtle and sensitive to extracellular glucose. These results may highlight mechanisms that mediate insulin sensitivity in the brain.

Variable sensitivity of clinical Candida auris strains to Biocides: implications for infection control in Healthcare Settings

PurposeCandida auris, a multidrug-resistant yeast, poses significant challenges in healthcare settings due to its ability to form biofilms and resistance to common disinfectants. Understanding its susceptibility to biocides used in hospital disinfection practices is crucial for infection control. We investigated the biocide sensitivity of eight clinical C. auris strains from different patients and one reference strain (CDC B11903) using the biocide activity tests.MethodsSpecies identification was confirmed through MALDI-TOF MS, while clade differentiation and phylogenetic classification were determined via whole-genome sequencing. Biofilm formation was assessed using the MTT assay. Antifungal susceptibilities were tested according to CLSI standards. The effectiveness of biocides, including chlorine, chlorhexidine, and benzalkonium chloride, was evaluated through broth microdilution following CLSI standards and quantitative suspension and carrier tests, following EN standards.ResultsAll clinical strains were identified as clade 1, and the reference strain as clade 4, with all exhibiting biofilm formation. Clade 1 strains showed resistance to fluconazole, with MIC values ranging from 8 to 32 µg/ml, while being susceptible to other antifungals. Broth microdilution MIC assays for biocides demonstrated that all strains exhibited resistance to benzalkonium chloride. Chlorine and chlorhexidine showed variable efficacy, dependent on concentration and environmental cleanliness. Alcohol-based hand sanitizers demonstrated effectiveness against C. auris from the first minute of application.ConclusionThe study highlights the variable susceptibility of C.auris to different biocides, underscoring the challenge in eradicating this pathogen from healthcare environments. Our findings advocate for the careful selection of disinfectants in hospital settings, emphasizing the need for high-concentration chlorine and chlorhexidine solutions to combat C. auris, even in especially clean environments.

Sensitivity analysis of damage extent in naval ship compartments due to internal airborne explosions

The objective of this paper is to identify the design variables of the compartment that are most influential in determining the extent of damage due to in-compartment airborne explosions (INCEX). From a comparison of numerical simulation results using the CONventional Weapons Effects Program (CONWEP) with results from airborne blast experiments, CONWEP generated blast pressures with reasonable accuracy. From a comparison of numerical simulation results using the Horsford-Coulomb and local necking hybrid fracture model (HC-LN model) with results from indentation experiments, HC-LN model accurately predicts steel fractures. The engine compartment was selected for the damage variable sensitivity analyses in terms of the probabilities of being hit, flooded, and incapacitated. When three TNT masses, two stand-off distances, and eight engine room dimensions with six levels of each dimension were considered, more than 10 million INCEX cases were required. The Latin hypercube sampling technique was adopted to reduce the number of INCEX simulations to 5,000. The element-based and image-based methods were applied to evaluate the damage extents. The element-based method underestimated and overestimated the damage area and damage perimeter more than the image-based method, respectively. The most influential design variables on the damage extent were bulkhead thickness and curtain plate height, respectively.

Bacterial Co-Infections and Antibiotic Resistance in Urinary Tract Infection of Covid-19 Patients in Erbil City

The COVID-19 pandemic has raised concerns over secondary infections because it has limited treatment options and empiric antimicrobial treatment poses serious risks of aggravating antimicrobial resistance. Many studies have shown that COVID-19 patients are predisposed to developing secondary infections. The prevalence of urinary tract infections (UTI) was evaluated in 248 patients admitted to different hospitals in Erbil city, Iraq. Results showed 138 (55.65%) patients were positive for bacterial growth, of which 72 isolates of Gram-negative and 66 isolates of Gram-positive bacteria were isolated and identified from the urine of COVID-19 patients depending on the 16S rRNA gene using PCR. The predominant obtained bacteria were Staphylococci species, of which isolates belong to 6 species, and the predominant Gram-negative species was Pseudomonas spp. which belongs to 4 species. Also, their susceptibility to 15 antibiotics was tested and it was found that most of the Gram-negative isolates were highly resistant to ampicillin 66(91.66%), amoxicillin 60(83.33%), cephalexin 52(72.22%) and cefixime 50(69.44%). While the most effective antibiotic was imipenem, and with percentage of 26(36.11%), it also showed variable sensitivity to other antibiotics. For Gram-positive bacteria, the highest resistance was against cefixime 40(60.60%), ampicillin 28(42.42%), and 18(27.27%) for both amoxicillin and ciprofloxacin, while the most effective antibiotic was gentamicin, which showed effectiveness against all the Gram-positive isolates. Another part of the study concerned with detection of the existence of ESBLs genes responsible for antibiotic resistance. The results revealed that all the isolates possessed the 16S rRNA gene, whereas blaTEM and blaCTX-M were found to be the most possessed genes in all the isolates, with a percentage of (88.33%).

Routine application of cardiac magnetic resonance imaging in patients with suspected myocarditis from immune checkpoint inhibitor therapy

Abstract Background Cardiovascular adverse events including myocarditis associated with immune checkpoint inhibitor (ICI) therapy remain a challenge in clinical practice. Diagnostic assessment of ICI-related myocarditis (ICI-M) is challenging due to a variable phenotype, confounding effects and limited sensitivity of diagnostic tools. Cardiac magnetic resonance imaging (CMR) is used to diagnose non-ICI myocarditis, but evidence on diagnostic sensitivity is low, particularly in patients with a discrete phenotype. Here, we aim to assess the impact of CMR in patients with suspected ICI-related myocarditis and relate to final diagnosis including endomyocardial biopsy findings. Methods All consecutive patients receiving CMR for suspected ICI-M between September 2019 and January 2024 were included and retrospectively analysed. CMR parameters were correlated with clinical, laboratory and echocardiographic parameters and stratified for presence or absence of myocarditis as per final diagnosis. Results A total of 55 patients who received CMR for suspected ICI-related myocarditis were analysed, including 25 patients with confirmed ICI-M as per final diagnosis and 30 patients with cardiotoxicity other than myocarditis or no cardiotoxicity (ICI-O). The mean age (ICI-M versus ICI-O) was 65.7±13.6 versus (vs.) 67.3±9.9 (p=0.61) years, 32.0% vs. 26.7% (p=0.67) were female, and 40.0% vs. 26.7% (p=0.29) had pre-existing coronary heart disease. Cardiac biomarkers and echocardiographic data did not differ between the groups. In CMR analysis, presence of late gadolinium enhancement (LGE) was associated with ICI-M (56.0% vs. 26.7%, p=0.027). Myocardial oedema was generally rare and not associated with ICI-M. Endomyocardial biopsy (EMB) was used in 6 out of 55 patients (10.9%) with suspected ICI-M. In 4 of these 6 patients (66.7%) EMB confirmed ICI-M diagnosis. Of note, only 2/4 patients with EMB-confirmed myocarditis showed abnormal CMR findings. Conclusion The diagnostic assessment of ICI-M is challenged by low sensitivity of common diagnostic measures, often requiring a multimodal approach. Presence of LGE in CMR was associated with ICI-M, but sensitivity and specificity are low. Our data emphasize the high value of EMB in patients with clinically suspected ICI-M despite inconspicuous CMR. Prospective data to improve diagnostic criteria are needed.

Correction: On Non-Penalization SEMDOT Using Discrete Variable Sensitivities

Correction: On Non-Penalization SEMDOT Using Discrete Variable Sensitivities

Data-Driven Sparse Sensor Placement Optimization on Wings for Flight-By-Feel: Bioinspired Approach and Application.

Flight-by-feel (FBF) is an approach to flight control that uses dispersed sensors on the wings of aircraft to detect flight state. While biological FBF systems, such as the wings of insects, often contain hundreds of strain and flow sensors, artificial systems are highly constrained by size, weight, and power (SWaP) considerations, especially for small aircraft. An optimization approach is needed to determine how many sensors are required and where they should be placed on the wing. Airflow fields can be highly nonlinear, and many local minima exist for sensor placement, meaning conventional optimization techniques are unreliable for this application. The Sparse Sensor Placement Optimization for Prediction (SSPOP) algorithm extracts information from a dense array of flow data using singular value decomposition and linear discriminant analysis, thereby identifying the most information-rich sparse subset of sensor locations. In this research, the SSPOP algorithm is evaluated for the placement of artificial hair sensors on a 3D delta wing model with a 45° sweep angle and a blunt leading edge. The sensor placement solution, or design point (DP), is shown to rank within the top one percent of all possible solutions by root mean square error in angle of attack prediction. This research is the first to evaluate SSPOP on a 3D model and the first to include variable length hairs for variable velocity sensitivity. A comparison of SSPOP against conventional greedy search and gradient-based optimization shows that SSPOP DP ranks nearest to optimal in over 90 percent of models and is far more robust to model variation. The successful application of SSPOP in complex 3D flows paves the way for experimental sensor placement optimization for artificial hair-cell airflow sensors and is a major step toward biomimetic flight-by-feel.

Approach for multi-valued integer programming in multi-material topology optimization: Random discrete steepest descent (RDSD) algorithm

The present study models the multi-material topology optimization problems as the multi-valued integer programming (MVIP) or named as combinatorial optimization. By extending classical convex analysis and convex programming to discrete point-set functions, the discrete convex analysis and discrete steepest descent (DSD) algorithm are introduced. To overcome combinatorial complexity of the DSD algorithm, we employ the sequential approximate integer programming (SAIP) to explicitly and linearly approximate the implicit objective and constraint functions. Considering the multiple potential changed directions for multi-valued design variables, the random discrete steepest descent (RDSD) algorithm is proposed, where a random strategy is implemented to select a definitive direction of change. To analytically calculate multi-material discrete variable sensitivities, topological derivatives with material contrast is applied. In all, the MVIP is finally transferred as the linear 0–1 programming that can be efficiently solved by the canonical relaxation algorithm (CRA). Explicit nonlinear examples demonstrate that the RDSD algorithm owns nearly three orders of magnitude improvement compared with the commercial software (GUROBI). The proposed approach, without using any continuous variable relaxation and interpolation penalization schemes, successfully solves the minimum compliance problem, strength-related problem, and frequency-related optimization problems. Given the algorithm efficiency, mathematical generality and merits over other algorithms, the proposed RDSD algorithm is meaningful for other structural and topology optimization problems involving multi-valued discrete design variables.

No Evidence for Endocannabinoid-Induced G Protein Subtype Selectivity at Human and Rodent Cannabinoid CB1 Receptors.

Introduction: The endocannabinoid system (ECS) is a widespread neurotransmitter system. A key characteristic of the ECS is that there are multiple endogenous ligands (endocannabinoids). Of these, the most extensively studied are arachidonoyl ethanolamide (AEA) and 2-arachidonoyl-glycerol (2-AG), both act as agonists at the cannabinoid CB1 receptor. In humans, three CB1 variants have been identified: hCB1, considered the most abundant G protein-coupled receptor in the brain, alongside the less abundant and studied variants, hCB1a and hCB1b. CB1 exhibits a preference for coupling with inhibitory Gi/o proteins, although its interactions with specific members of the Gi/o family remain poorly characterized. This study aimed to compare the AEA and 2-AG-induced activation of various G protein subtypes at CB1. Furthermore, we compared the response of human CB1 (hCB1, hCB1a, hCB1b) and explored species differences by examining rodent receptors (mCB1, rCB1). Materials and Methods: Activation of individual G protein subtypes in HEK293 cells transiently expressing CB1 was measured with G protein dissociation assay utilizing TRUPATH biosensors. The performance of the TRUPATH biosensors was evaluated using Z-factor analysis. Pathway potencies and efficacies were analyzed using the operational analysis of bias to determine G protein subtype selectivity for AEA and 2-AG. Results: Initial screening of TRUPATH biosensors performance revealed variable sensitivities within our system. Based on the biosensor performance, the G protein subtypes pursued for further characterization were Gi1, Gi3, GoA, GoB, GZ, G12, and G13. Across all pathways, AEA demonstrated partial agonism, whereas 2-AG exhibited full or high-efficacy agonism. Notably, we provide direct evidence that the hCB1 receptor couples to G12 and G13 proteins. Our findings do not indicate any evidence of G protein subtype selectivity. Similar observations were made across the human receptor variants (hCB1, hCB1a, hCB1b), as well as at mCB1 and rCB1. Discussion: There was no evidence suggesting G protein subtype selectivity for AEA and 2-AG at CB1, and this finding remained consistent across human receptor variants and different species.

HcGAN: Harmonic conditional generative adversarial network for efficiently generating high-quality IHC images from H&E

Generating high quality histopathology images like immunohistochemistry (IHC) stained images is essential for precise diagnosis and the advancement of computer-aided diagnostic (CAD) systems. Producing IHC images in laboratory is quite expensive and time consuming. Recently, some attempts have been made based on artificial intelligence techniques (particularly, deep learning) to generate IHC images. Existing IHC stained image generation methods, still have a limited performance due to the complex structures and variations in cells shapes, potential nonspecific staining and variable antibody sensitivity. This paper proposes a novel technique known as harmonic conditional generative adversarial network (HcGAN) for generating high quality IHC-stained images. To generate the IHC images, the HcGAN model is fed with the widely available hematoxylin and eosin (H&E) images that contain cellular and morphological underlying structures of diverse cancer tissues. Such approach helps generate high quality IHC images mimicking the real ones that highlight the positive cells. The proposed HcGAN model is based generative adversarial learning with generator and discriminator networks. In HcGAN, harmonic convolution based on discrete cosine transform filter banks is employed in the generator and discriminator networks instead of the standard convolution in order to improve visual quality of the generated images and address the issue of overfitting. Our qualitative and quantitative results demonstrate that the proposed HcGAN achieved the highest performance over state-of-the-art methods using two publicly available datasets.

[Translated article] Diagnosis of Onychomycosis: Utility of an Immunochromatography Strip Test Compared with Conventional Culture

BackgroundRingworm is highly prevalent in our setting and is frequently observed in our routine clinical practice. Diagnostic confirmation depends on techniques that are not always accessible (PCR), with highly variable sensitivity depending on the observer (direct microscopy) or delayed results (culture, histopathology). Recently, an immunochromatography-based rapid test (Diafactory®) for the antigenic detection of dermatophytes has been developed. This diagnostic tool can help diagnose ringworm, allowing early initiation of treatment and fewer consultation visits. ObjectiveTo determine the sensitivity and specificity of the rapid antigen detection test compared to conventional culture. Material and methodsFor a full year, 333 nail samples were collected from patients with suspected onychomycosis. The rapid test and the conventional culture were simultaneously performed on each sample. Those with a positive antigenic test result began treatment early. The remaining patients had appointments for serial cultures and subsequent medical consultation to evaluate the results. ResultsCompared to conventional culture, the sensitivity and specificity rates of the rapid antigen detection test are 97.2% and 80.7%, respectively. ConclusionThe effectiveness of the rapid antigen detection test is similar to that of conventional culture for the detection of dermatophytes in nail samples. It is a quick and simple diagnostic technique that reduces the number of patient visits to the hospital, and allows early treatment start.

Monocentric evaluation of the Novaplex dermatophyte multiplex qPCR assay in the diagnosis of dermatophytoses.

Superficial fungal infections caused by dermatophytes are a prevalent global health concern. Rapid and accurate diagnosis of these pathogens through molecular tools would offer a substantial advantage for early detection and effective treatment. The conventional fungal culture presents inherent limitations, including extended result delivery delay and variable sensitivity. This study aimed to evaluate the performance of the multiplex real-time PCR Novaplex dermatophyte assay (Seegene) in comparison to traditional mycological methods including direct examination and culture. A total of 312 nail, skin, and scalp samples collected from patients with suspected superficial fungal infections for mycological diagnosis were retrospectively subjected to the Novaplex dermatophyte assay. Overall, 170 (54.6%) and 186 (59.6%) samples tested positive for dermatophyte culture and dermatophyte PCR, respectively. The concordance between PCR and culture for dermatophyte detection was 87.2%. There were 158 culture-positive/PCR-positive samples, 12 culture-positive/PCR-negative samples, and 28 culture-negative/PCR-positive samples. The sensitivity of PCR against culture varied according to the dermatophyte target, ranging from 90.5% (Trichophyton mentagrophytes/interdigitale/benhamiae), 91.2% (Trichophyton rubrum), to 100% (Microsporum spp. and Trichophyton tonsurans). When considering the final diagnosis using composite criteria, the sensitivity and specificity for the diagnosis of dermatophytosis were 92.9% and 96.6% for PCR, 86.7% and 100% for culture, and 95.4% and 92.2% for direct examination and culture combined, respectively. The Seegene Novaplex dermatophyte assay is an easy-to-use automated one-step extraction-PCR system that offers satisfactory performance for routine diagnosis of dermatophytoses in clinical laboratories, particularly in non-specialized centers. However, it cannot fully replace conventional mycology due to its inability to detect mold infections and to identify dermatophytes at the species level.

Comparison of urine and serum IgG detection ELISA for tegumentary leishmaniasis diagnosis and prognosis

Laboratorial diagnosis of tegumentary leishmaniasis (TL) is hampered by variable sensitivity and/or specificity of the tests, which are still hampered by blood́ invasive collection. In this context, in the present study, we develop a serum- and urine-based ELISA to TL diagnoses. A recombinant protein (rLiHyA), which was previously showed to be antigenic for the disease, as well as a B-cell epitope produced as synthetic peptide and a Leishmania antigenic extract (SLA), were used as antigens. A total of paired 205 urine and serum samples were used, which were comprised by samples from cutaneous (n = 30) and mucosal (n = 30) leishmaniasis patients, as well as from healthy individuals living in endemic region of disease (n = 45), of patients with Chagas disease (n = 30), leprosy (n = 35), malaria (n = 15) or HIV-infected (n = 20). Results showed that serum-based ELISA presented sensitivity of 24.0 %, 100 % and 41.0 %, when SLA, rLiHyA and synthetic peptide were used as antigens, and specificity of 98.4 %, 98.4 % and 98.4 %, respectively. The area under the curve (AUC) was calculated and results were 0.74, 1.0, and 0.71, respectively, when SLA, rLiHyA and synthetic peptide were used as antigens. Performing an urine-based ELISA, sensitivity was 28.0 %, 100 % and 75.0 %, respectively, when SLA, rLiHyA, and synthetic peptide were used, while specificity values were of 98.4 %, 98.4 % and 98.4 %, respectively. In addition, the AUC values were 0.82, 1.0, and 0.94, respectively. A significant drop in specific antibodies levels in both patientś serum and urine samples was found six months after treatment, suggesting a prognostic role of rLiHyA for TL. In conclusion, preliminary data suggest the potential of use patient urine to TL diagnoses.

Match Point: Nuclear Medicine Imaging for Recurrent Thyroid Cancer in TENIS Syndrome-Systematic Review and Meta-Analysis.

Background/Objectives: Disease recurrence and resistance to radioiodine (RAI) therapy are major challenges in the management of differentiated thyroid cancer (DTC). In particular, the TENIS (Thyroglobulin Elevated Negative Iodine Scintigraphy) syndrome, characterised by elevated thyroglobulin (Tg) serum levels in addition to a negative radioiodine whole body scan (WBS), complicates disease monitoring and treatment decisions. Conventional imaging techniques often fail to detect disease in WBS-negative patients with rising Tg levels, leading to limitations in therapeutic intervention. This systematic review and meta-analysis aims to evaluate the diagnostic accuracy of nuclear imaging modalities in detecting disease recurrence in patients with the TENIS syndrome and to provide insights to guide therapeutic approaches in this complex clinical scenario. Methods: A comprehensive search of PubMed/MEDLINE and EMBASE databases up to March 2024 was performed according to PRISMA guidelines. Eligible studies were selected, and quality assessment was performed with the QUADAS-2 tool. For each study, relevant data were extracted and synthesised. A meta-analysis of the diagnostic accuracy of [18F]FDG PET/CT was performed, and patient-based pooled sensitivity and specificity were calculated using a random-effects model. Statistical heterogeneity between studies was assessed using the I2 statistic. Results: Of the 538 studies initially identified, 22 were included in the systematic review, of which 18 were eligible for meta-analysis. The eligible studies, mainly focused on [18F]FDG PET/CT, showed variable sensitivity and specificity for the detection of RAI-refractory thyroid cancer lesions. For [18F]FDG PET/CT, pooled estimates displayed a sensitivity of 0.87 (95% CI: 0.82-0.90) and a specificity of 0.76 (95% CI: 0.61-0.86), with moderate heterogeneity between studies. Conclusions: [18F]FDG PET/CT remains central in the detection of disease recurrence in patients with the TENIS syndrome. The emergence of novel radiopharmaceuticals with specific molecular targets is a promising way to overcome the limitations of [18F]FDG in these patients and to open new theranostics perspectives. This review highlights the great potential of nuclear medicine in guiding therapeutic strategies for RAI-refractory thyroid cancer.

Tunable soft pressure sensors based on magnetic coupling mediated by hyperelastic materials

Recent advances in pressure sensors have garnered significant interest due to their promising applications in healthcare, robotics and wearable technology. In these fields, there is an ever-increasing demand for soft sensors that can conform to complex surfaces, such as the human body. However, current sensors often face limitations in measurable pressure ranges and customization involves complex manufacturing processes. In this study, we introduce an innovative solution for producing soft pressure sensors with varying maximum detection pressures. By utilizing a magnetic transduction mechanism and different hyperelastic materials, we have developed sensors that can adapt to irregular surfaces. These sensors measure a wide range of pressures, from ultra-low to medium, and offer variable stiffness, sensitivity, and measurement ranges. The sensors we manufactured exhibit a detection range from 6.8 to 77.4 kPa, a sensitivity range between -5.1 × 10-2 and -0.4 × 10-2 kPa-1, a short recovery time of 0.4 s, low hysteresis values during repeated loading/unloading cycles, and stable response over thousands of pressure cycle. Proof-of-concept experiments validated the sensors’ suitability for breathing monitoring and finger tap detection, highlighting their potential in medical and robotic applications. The results demonstrate a robust strategy for controlling the performance of soft pressure sensors, positioning them as promising candidates for diverse pressure sensing applications.

New BB0108, BB0126, BB0298, BB0323, and BB0689 Chromosomally Encoded Recombinant Proteins of Borrelia burgdorferi sensu lato for Serodiagnosis of Lyme Disease.

Five chromosomally encoded proteins, BB0108, BB0126, BB0298, BB0323, and BB0689, from Borrelia burgdorferi sensu lato (s.l.), were obtained in three variants each, representing the most common genospecies found in Europe (Borrelia afzelii, Borrelia burgdorferi sensu stricto (s.s.), and Borrelia garinii). The reactivity of these recombinant proteins with the IgM and IgG antibodies present in human serum was assessed using Western blot (WB) and the ELISA. In IgG-WB, the proteins exhibited varying reactivity, peaking at approximately 40-50% for BB0108 and BB0689. However, none of these proteins were recognized by specific antibodies in the IgM-WB. The sensitivity of IgG-ELISA based on three variants of BB0108 and BB0323 ranged from 71% to 82% and from 62% to 72%, respectively. Conversely, the specificity of both tested proteins was consistently above 82%. Tests utilizing single variants of BB0323 did not yield any diagnostic value in detecting IgM antibodies. However, BB0108 demonstrated recognition by antibodies present in 52% to 63% of the tested sera. These antigens appear advantageous due to the consistent reactivity observed across their variants. This observation suggests that appropriate selection of antigens conserved within B. burgdorferi s.l. could offer a solution to the issue of variable sensitivity encountered in serodiagnostic tests across Europe.

Regression prediction model for shear strength of cold joint in concrete

The shear resistance of cold joint in concrete is influenced by various design parameters. Traditional mechanical models typically consider only a limited number of parameters to predict the shear strength of cold joints. This research aims to explore the complex nonlinear relationship between design parameters and cold joint shear strength using statistical method and machine learning technology. The goal is to develop a more accurate, reliable, and engineering applicable regression model for predicting shear strength. A dataset of 546 Z-shaped shear specimens characterizing cold joint in concrete was constructed, involving a total of 16 variables that may affect shear performance. Correlation analysis and recursive elimination were adopted to eliminate correlated and insignificant variables based on their importance. Multiple linear regression (MLR), random forest regression (RFR), and support vector machine regression (SVR) prediction models for cold joint shear strength were established based on rigorously screened variables and comprehensively evaluated using multiple methods. It was found that the most significant factors influencing the shear strength of cold joints are concrete strength, interface shear key, product of interface reinforcement strength and its reinforcement ratio, normal stress, fiber length of new concrete, casting method of the new concrete, and product of the fiber length and its tensile strength of old concrete. The MLR, SVR, and RFR models all exhibited superior performance relative to traditional mechanics-based models with regard to shear strength prediction of cold joints. The RFR model is recommended for predicting the shear strength of cold joints due to its superior evaluation indexes in comparison to the MLR and SVR models, and variable sensitivity analysis shows that it does not yield common-sense errors.

XENTURION is a population-level multidimensional resource of xenografts and tumoroids from metastatic colorectal cancer patients

The breadth and depth at which cancer models are interrogated contribute to the successful clinical translation of drug discovery efforts. In colorectal cancer (CRC), model availability is limited by a dearth of large-scale collections of patient-derived xenografts (PDXs) and paired tumoroids from metastatic disease, where experimental therapies are typically tested. Here we introduce XENTURION, an open-science resource offering a platform of 128 PDX models from patients with metastatic CRC, along with matched PDX-derived tumoroids. Multidimensional omics analyses indicate that tumoroids retain extensive molecular fidelity with parental PDXs. A tumoroid-based trial with the anti-EGFR antibody cetuximab reveals variable sensitivities that are consistent with clinical response biomarkers, mirror tumor growth changes in matched PDXs, and recapitulate EGFR genetic deletion outcomes. Inhibition of adaptive signals upregulated by EGFR blockade increases the magnitude of cetuximab response. These findings illustrate the potential of large living biobanks, providing avenues for molecularly informed preclinical research in oncology.

Long-distance electron transport in multicellular freshwater cable bacteria.

Filamentous multicellular cable bacteria perform centimeter-scale electron transport in a process that couples oxidation of an electron donor (sulfide) in deeper sediment to the reduction of an electron acceptor (oxygen or nitrate) near the surface. While this electric metabolism is prevalent in both marine and freshwater sediments, detailed electronic measurements of the conductivity previously focused on the marine cable bacteria (Candidatus Electrothrix), rather than freshwater cable bacteria, which form a separate genus (Candidatus Electronema) and contribute essential geochemical roles in freshwater sediments. Here, we characterize the electron transport characteristics of Ca. Electronema cable bacteria from Southern California freshwater sediments. Current-voltage measurements of intact cable filaments bridging interdigitated electrodes confirmed their persistent conductivity under a controlled atmosphere and the variable sensitivity of this conduction to air exposure. Electrostatic and conductive atomic force microscopies mapped out the characteristics of the cell envelope's nanofiber network, implicating it as the conductive pathway in a manner consistent with previous findings in marine cable bacteria. Four-probe measurements of microelectrodes addressing intact cables demonstrated nanoampere currents up to 200 μm lengths at modest driving voltages, allowing us to quantify the nanofiber conductivity at 0.1 S/cm for freshwater cable bacteria filaments under our measurement conditions. Such a high conductivity can support the remarkable sulfide-to-oxygen electrical currents mediated by cable bacteria in sediments. These measurements expand the knowledgebase of long-distance electron transport to the freshwater niche while shedding light on the underlying conductive network of cable bacteria.

Systematic literature review to inform the EULAR recommendations for the use of imaging in crystal-induced arthropathies in clinical practice

ObjectiveTo summarise current data regarding the use of imaging in crystal-induced arthropathies (CiAs) informing a European Alliance of Associations for Rheumatology task force.MethodsWe performed four systematic searches in Embase, Medline...