bluuebunny/crossref_metadata_2025 huggingface dataset:
Utilizing Neural Networks to Assist in the Assessment and Predictive Measurement of Developmental Hip Dysplasia Radiographs
Authors: Perry Sheridan , Folkman Matthew , O’Brien Takara , Wilson Lauren , Coyle Eric , Liu Raymond W. , Price Charles T. , Huayamave Victor
Published: February 2024

Developmental dysplasia of the hip (DDH) is a condition in which the acetabular socket inadequately contains the femoral head. If left untreated, DDH can result in degenerative changes in the hip joint. Several imaging techniques are used for DDH assessment. In radiographs, the acetabular index, center-edge angle, Sharp’s angle, and migration percentage metrics are used to assess DDH. Determining these metrics is time-consuming and repetitive. This study uses a convolutional neural network (CNN) to identify physical metrics on radiographs and improve traditional methods of identifying DDH. The dataset consisted of 60 subject radiographs rotated along the craniocaudal and mediolateral axes 25 times, generating 1500 images. A CNN detection algorithm was used to identify DDH metrics. The algorithm was able to detect the metrics with reasonable accuracy in comparison to the blank metrics. The CNN performed well on images with high contrast margins between bone and soft tissues. In comparison, the CNN was not able to identify some critical points for metric calculation on a select few images that had poor definition due to low contrast between bone and soft tissues. This study shows that CNNs can efficiently measure clinical parameters to assess DDH on radiographs with high contrast margins between bone and soft tissues with purposeful rotation away from an ideal image. Results from this study could help inform and broaden the existing bank of information on using CNNs for radiographic measurement and medical condition prediction.
Flexible Surface Acoustic Wave (SAW) Sensors for Cryogenic Sensing Application
Authors: Kohler Michael , Zhang Andy , Moore Christopher , Voiculescu Ioana , Li Fang
Published: February 2024

Real-time monitoring of temperature and pressure, particularly in harsh environments such as extreme temperature and high electromagnetic radiation environments, has wide-ranging applications in the aerospace, civil infrastructure, and motor industries. Surface acoustic wave (SAW) technology has gained significant attention for harsh environment applications due to its ability to enable self-powered and wireless sensor devices that can operate in harsh environments. Our previous studies have demonstrated the effectiveness of 128° YX-cut LiNbO3-based SAW sensors for cryogenic sensing applications with no degradation in sensor signals at cryogenic temperatures of 80K. However, the high value of the temperature coefficient of delay (TCD) presents a major challenge in developing wireless SAW pressure sensors, as even small changes in temperature can induce significant changes in the signal, which may be greater than that due to the pressure change of interest. Therefore, there is a need to improve the thermal stability and pressure sensitivity of the 128° YX-cut LiNbO3-based SAW device. This paper reports on our simulation study of improving the thermal stability of the LiNbO3-based SAW sensor by applying an overlayer to compensate for the temperature effects. Additionally, we present our experimental study to develop a single crystalline thin-film-based SAW sensor, which has the potential to improve pressure sensitivity.
Development and Integration of Continuous Load and Position Measurement for Quasi-Steady Flows
Authors: Cockrell Quintin J. , Hiremath Nandeesh
Published: February 2024

Obtaining aerodynamic forces and moments about all three orthogonal axes for arbitrary shapes at arbitrary orientations in a fast manner via a measurement technique specific to Cal Poly’s low-speed wind tunnel to continually obtain the forces and moments under quasi-steady conditions is explored. A Continuous Rotation Technique (CR) uses a 6-DOF load cell and stepper motor to rotate an object about an axis for a complete rotation. The forces and moments acting upon the object pass through the stepper motor and interface plates and recorded by the load cell as the object is rotated continuously a finite number of rotations. An optical encoder installation tracks the progress of a rotation serving indicator between the subsequent rotations to determine starting angles and body slippage. Average loading of measurements at each timestep along the average time for rotation is found. This dataset along the average time is placed in 1-degree bins and averaged to a final dataset of load measurements at 1-degree intervals for a complete 360-degree load map. Testing of this technique is performed on aspect ratio 1 circular cylinder. This paper showcases the repeatability of the results in a different and smaller wind tunnel with improved certainty on angle measurements.
Design and Experiments Involving a Mechanism-Based Artificial Tongue Prosthesis
Authors: Holod Ace , Singh Nadia , Curney Xavier , Radhakrishnan Pradeep , Pahlavan Kaveh
Published: February 2024

Oral cancer can result in the loss of tongue through total glossectomy, and patients have difficulty with speech, deglutition, and mastication. Current tongue prostheses lack the ability to move for mastication and deglutition and are mainly for cosmetic purposes. The goal of this research was to investigate and develop a self-contained prosthetic tongue that could aid in deglutition by moving bolus from the front of the mouth to the back. A review of existing designs and alternatives led to the development of a linkage system mounted in a silicone cast to move the bolus. The development of this new prosthetic tongue design entailed creating silicone molds, 3D printing linkage systems and jaws, and developing new circuits. The circuit used a TinyDuino microcontroller and MOSFET. A functional mandibular Hawley retainer was added to hold the tongue to increase ease of use. The final circuit used an EMG sensor to trigger actuation and a single servo motor with a gear train to actuate the tongue. The prosthetic tongue succeeded in moving bolus from the front of the mouth to the back when lying at a 5-degree angle and actuating between 1.8–2.31cm in height. The paper will describe the development process, challenges, and future work.
Numerical Investigation of Broken V-Ribbed Turbulators in a Multi-Pass Turbine Channel Under Rotating Conditions
Authors: Thirumalai Madhusudan Pallikaranai , Ekkad Srinath V.
Published: February 2024

Rotation induces Coriolis and centrifugal forces resulting in a significant non-uniformity of heat transfer distribution on the pressure and suction side walls of turbine blade internal cooling channels. This nonuniformity in cooling creates asymmetric cooling resulting in significant thermal stresses and potential failure of the airfoil. In order to minimize this non-uniform distribution of heat flux, this study proposes a novel multi-pass channel configuration with a 45-deg angled V-Broken ribs. Numerical simulations were conducted under stationary and rotation conditions to calculate detailed heat transfer coefficients on the internal walls of these channels. Results indicate that the heat transfer characteristics on the pressure and suction side internal walls were very similar under both stationary and rotating conditions. The new design with the broken rib configuration does not significantly affect the pressure drop while providing the added benefit of heat transfer enhancement.
Performance Characteristics of Small-Scale Horizontal Axis Three Bladed Ocean Current Turbine: Computational Fluid Dynamics Investigation
Authors: Sadeqi Setare , Xiros Nikolaos I. , Rouhi Shahab , Ioup Juliette W.
Published: February 2024

The fundamental research described in this paper is a comprehensive numerical simulation (Blade Element Momentum Theory) for developing a small-scale three bladed horizontal axis underwater ocean current turbine (OCT), to be tested in a laboratory towing tank located at the University of New Orleans. A precise numerical simulation has been developed to generate hydrokinetic loads such as torque and power for the OCT based on the geometry and design characteristics of the small-scaled blades. Each blade is divided into 25 different cross sections from the FX77-W airfoil family based on the real size OCT. This method is an in-house blade element momentum theory (BEM) algorithm which considers each cross section of the blade as a two-dimensional hydrofoil to calculate the local drag and lift coefficients for each sub-section to obtain the maximum generated power of the OCT. Many different generated power estimates based on these simulations have been conducted for different in-coming flow speeds in the range of few cm/s to as much as 2 m/s, along with constant turbine circular speeds. The results of this numerical study are used as one of the main sources of initial information for ongoing research which is the design and implementation of an experimental small scale experimental underwater ocean current turbine. Also, the results of the numerical study are compared to the results of the experimental research. The aim of this research is to provide an accurate prediction of the nominal rotor speed for a given incoming flow current to optimize the capability of the small-scale OCT performance. The paper also highlights the need to develop new and reliable technologies to harness ocean currents and extract the maximum hydrokinetic energy from the ocean in order to convert it into reliable and usable energy.
Optimizing Material Properties for 3D Printing: A Study on Compressive Strength of Mixed Clear and Tough Resins
Authors: Javvaji Vijay K. , Angadi Santosh , Piovesan Davide
Published: February 2024

Most published review papers primarily discuss 3D printing techniques, the printing of pure materials and incorporating nano particles, but never looked at the possibility of mixing different resins with different mechanical properties to develop hybrid material. The main objective of the experiment was to explore the potential of mixing different resin materials and creating a hybrid material. The goal was to optimize the properties of the resin material by combining different components. By experimenting with different ratios and compositions, the aim was to achieve a hybrid material with enhanced characteristics, such as improved strength, durability, or other desirable properties. The experiment aimed to determine the feasibility of creating such hybrid materials and to optimize their properties for various applications in 3D printing or other fields.

Clear and tough resins provided by Anycubic were used for this experiment. The Clear is a multipurpose resin for 3D printing with good rigidity, low shrinkage, high success rates, and excellent detail performance. The Tough resin can withstand both compression and bending and is suitable for sections requiring durability. The two materials were mixed at different volume ratios to create three different samples. The samples were printed using the PRUSA SL1 speed printer and washed in isopropyl alcohol.

Samples were tested before and after post-processing to identify their compressive strength using the ASTM D695-15 standards. The results showed that mixed resin is stronger than regular resin and increasing the amount of clear resin in the mixture increases strength.

Overall, this experiment provides valuable insights into the properties of mixed Clear and Tough resins, and their potential uses in 3D printing applications where both resistance to creep and toughness are required. Along with pointing out the possibility of mixing materials it also points out that the hybrid material can withstand more compression load when compared to the standard materials which increases the use cases and potential of implementing in different industries and labs.
Soft Sensor Digital Twin Implementation of a Pick-and-Place Operation
Authors: Schrader Brandon , Guerra-Zubiaga David , McMichael Grayson
Published: February 2024

This research paper proposes the use of a modular soft sensor positioned around the end effector of an industrial robotic arm to optimize human-machine interaction and safety. The smart sensor is designed to detect collisions with external objects and alert a control center through an Industrial Internet of Things (IIoT) device connected to the cloud. This innovative solution aims to improve safety in collaborative scenarios where humans work with industrial robots, reducing the risk of injuries and accidents. This research explores the integration of soft robotics, IIoT, and cloud manufacturing to obtain next-generation automation systems with digital manufacturing tools. The research is focused on developing a cost-effective and efficient solution that can be easily integrated with existing collaborative industrial robots. Simulations performed in Siemens’ Process Simulate Tecnomatix show the efficacy and usefulness of this sensor in a digital twin format. The results of this study show the possibility of using Industry 4.0 technology to improve safety conditions in factory settings and will contribute to the advancement of human-robot collaboration and the integration of IoT technology in the manufacturing industry.
A Finite Element Model for Analyzing the Shear Wave Propagation in Soft Biomaterials
Authors: Wang Jianing , Li Runze , Zhou Qifa , Gu Linxia , Dong Pengfei
Published: February 2024

The elastography method has been widely used to estimate the stiffness of biomaterials based on the shear wave speed. The wave propagation excited by a single indent on the surface of the biomaterials is not always an ideal shear wave. The distance from the interested region to the indent, or different algorithms for elastography may affect the calculation of stiffness. This paper aims to analyze the shear wave propagation in soft biomaterials with a finite element model. The finite element model was constructed based on the setup of our previous in-vitro experiments on the elastography of gelatin. Briefly, a shear wave propagation was induced by a single indent with a frequency of 1 kHz. Following simulation, the displacements along a path line, at three depths were extracted for analyzing the shear wave propagation. The influence of the damping behavior and three different elastography algorithms were also investigated with our data. Results have shown that the finite element simulation agreed well with the previous in-vitro experiments. The estimated stiffness increased by more than 10% as the depth increased from 1 mm to 7 mm. This increase was even larger for the material with larger damping behavior (viscoelasticity). The precise estimation was related to the distance between the interested region and the indent for the material with a larger damping behavior. The feasibility of three algorithms: wavefront slope, cross-correlation algorithm, and finite differencing method (FDM), were investigated with our model. The FDM proposed in this work can determine the shear wave speed based on local spatial and temporal data, while high-frequency data are required. The understanding from this work may provide valuable information for optimizing the performance of elastography.
Uncertainty of Thermodynamic-Entropy-Based Reliability and Remaining Useful Life Predictions Under Variable Amplitude Fatigue
Authors: Curtis Lance R. , Ayyub Bilal M.
Published: February 2024

Traditionally, engineers have used empirical relationships such as the modified Goodman relation and the Basquin equation to design for fatigue and Miner’s Rule to calculate reliability and to predict the remaining useful life (RUL) of structures subjected to fatigue. Research has shown the viability of using thermodynamic entropy as an alternative to traditional empirical relationships for fatigue-related design, reliability estimation, and RUL prediction. This entropy-based approach relies upon fatigue fracture entropy, a material property shown empirically to be connected with an entropy-based Miner’s Rule.

Practical application of any approach, however, demands an accounting for uncertainty; otherwise, any predictions inherently carry a higher level of risk. Entropy-based formulations observed in the literature provide no such accounting. This work provides an analytically derived formulation for uncertainty in both entropy-centered and empirically based physics-of-failure-centered (PoF-centered) approaches to estimating reliability. For both the PoF- and entropy-centered approaches, Monte Carlo simulation data of an AISI 304 stainless steel rod subjected to variable amplitude fatigue produced estimates of both cycle-based and time-based reliability using both entropy-centered and PoF-centered formulations.

This procedure includes non-parametric as well as parametric approaches. The entropy-based calculations compare well with their traditional counterparts above 80% reliability. More investigation to improve the simulation as well as comparing against empirical fatigue tests are recommended.
Utilizing Relative Frequency Shift for Defect Detection and Localization in Additively Manufactured Parts: An Analytical Methodology
Authors: Howell Quin I. , Davis Joshua I. , Perez Ennio M. , Mitchell Joseph B. , Lamon Stewart , O’Connor Dennis M.
Published: February 2024

Metal 3D printing techniques have become the primary additive manufacturing method for intricate and detailed designs, surpassing traditional techniques. These innovative methods allow for the use of novel fabrication techniques that enable greater intricacy, resolution, and detail compared to previous methods. In the aerospace industry, this printing technique is being developed to manufacture lightweight parts with complex designs. Similarly, in the biomedical engineering industry, metal 3D printing is used to manufacture implants and prosthetics that require precise designs and high-quality finishes. While research in conventional manufacturing has made advancements in the understanding of crack and defect propagation, there has been relatively less attention given to the dynamic attributes of metal 3D printed parts. If these parts are to be used in engineering applications, it is essential to have strict quality control and inspection in place to detect defects. To address this issue, this investigation proposes the use of the relative frequency shift (RFS) method, a non-destructive and efficient method for detecting and localizing internal voids in metal 3D printed parts. This study examines the vibration of an additively manufactured metal cantilever beam with a purposely placed square void, using analytical and Finite Element Methods (FEM). By considering a segmented and continuous beam, the relative frequency shifts were determined analytically. The location of voids with respect to modes and antinodes was observed to impact the magnitude of shift in each mode. To gather an array of frequency responses, void location along the beam was varied. Using an analytical transfer matrix method, a parametric map was created to display the frequency response of higher modes with respect to void location. This map is utilized to detect and locate internal voids along the length of the beam by comparing the observed shifts to those in the map and drawing inferences. This parametric map was validated using FEM. Through this investigation, it was discovered that every void location in 3D printed metal parts has a distinct dynamic “fingerprint” that can be utilized to precisely identify and localize defects. The effectiveness of the RFS method in detecting and localizing such defects is successfully demonstrated by this study. These findings have significant implications for the quality control and design optimization of metal 3D printed parts in various industries, including aerospace and biomedical engineering. By providing a non-destructive and efficient method for detecting defects, the RFS method can help to ensure the safety and reliability of 3D printed metal parts used in critical applications.
Study on Molecular Dynamics Simulation With Boiling Water and Copper for Different Nanostructured Surfaces
Authors: Afreen Tanjee , Gebre Fisseha L. , Xu JiaJun
Published: February 2024

This study utilized molecular dynamics simulation to investigate how boiling a liquid water film on a hot copper plate generates distinctive features of nanostructured surfaces. This study aims to explore the impact of nanostructured surfaces on boiling water and observe heat flow for microelectronic systems. The molecular system comprises a solid copper wall, liquid water, and water vapor. LAMMPS (open-source large-scale atomic/molecular massively parallel simulator) was used to conduct the simulations and OVITO was used to visualize the results.

This study compared the results for hot plain surfaces with different concave surfaces. The purpose is to observe how the nanostructured surface reacts to bubble formation in contrast to the smooth surfaces. The result shows that boiling initiates faster on the largest concave nanostructured surface than on the plain surface. The effect of nanostructured surface on the boiling liquid film has extensive applications in Engineering and nanotechnology. Furthermore, different studies show that at a macroscopic level, smooth surfaces can have nanoscale and microscale structures. Therefore, understanding the boiling process on different surfaces is essential to gain insights into these physical phenomena.
Real-World Deep Reinforcement Learning for Position Tracking of a Pendulum Driven by a Series Elastic Actuator
Authors: Sambhus Ruturaj , Gokce Aydin , Welch Stephen , Leonessa Alexander
Published: February 2024

In this study, deep reinforcement learning (DRL) is employed to train a policy for position trajectory tracking of a pendulum driven by a series elastic actuator (SEA) on hardware. SEAs are commonly used in various robotics applications, but often exhibit non-linearities, motivating a model-free control approach. Real-time learning of DRL policies is conducted using the Proximal Policy Optimization (PPO) algorithm for tracking position trajectories within a 0.05–0.5 Hz frequency interval and 0.12 rad amplitude. The impact of an additional velocity-tracking reward term on position-tracking performance is also explored. The SEA in this work is controlled by a low-level controller, with learning performed on a high-level PC. The environment trains on target sinusoidal trajectories sampled randomly from 0.05 to 0.5 Hz with safety measures, including a physical emergency stop, low-level position safety bounds, and input current limits. The modified reward function investigates the effect of including a term proportional to the negative square of velocity error for smoother tracking. The performance is characterized by metrics of episode mean square position error for tracking accuracy and episode mean absolute acceleration for smoothness. This research demonstrates real-time learning of DRL policy for position tracking of a pendulum driven by a SEA with non-linearities using freely available software tools.
Air-Aluminum Foam Applications for Cooling Systems With Heat Generation
Authors: Carbajal Gerardo
Published: February 2024

The present numerical study provides valuable information about air-aluminum foams for cooling systems with heat generation. Different aluminum foam porosities, permeabilities, and air mass flow rates were conducted. This study focuses on increasing the effective thermal conductivity by using air-aluminum foam. The numerical simulations include cylindrical and rectangular samples distributed in one array consisting of two rows and 10 columns. The pressure and the speed of the fluid along the center line of the cylindrical samples experienced a harmonic pressure and speed response. In the case of the rectangular samples, the air-aluminum foam was tested on three air passage configurations: I, Z, and U. The numerical results showed that the hot spot temperature for the heat source is evenly spread in the system. The results show that the air-aluminum foam significantly reduces the hot spot temperature of the modules. For the same heat generation, the cylindrical modules performed better than the rectangular modules due to better flow interaction between the fluid and the solid surface of the cylindrical samples compared with the sharp corners of the rectangular modules. Like the air-cooling system, the I-combination resulted in less pressure drop than the U and Z configurations. The pressure drops for air-aluminum foam increased was inversely proportional to the porosity.
Predicting Pressure Gradient in Aortic Coarctation Based on Geometrical Features Using Design of Experiments and Machine Learning Models
Authors: Asadbeygi Alireza , Abazari Mohammad Amin , Alimohammadi Mona
Published: February 2024

Aortic coarctation is the term used for narrowing of the aorta that can result in a range of cardiovascular complications, such as hypertension and heart failure, making it a condition that warrants timely diagnosis and management. Although surgical and catheter-based interventions have progressed, the treatment of aortic coarctation remains a challenge, especially in patients with complex anatomy or comorbidities. The current risk assessment routines for aortic coarctation are based on pressure gradient and narrowing diameter measurements. In This study, predictive models of pressure gradient in aortic coarctation are developed based on geometrical parameters using machine learning algorithms. Parametric idealized geometry of aortic coarctation is developed, and multiple coarctation cases were generated based on central composite design of experiment (CCD). Transient computational fluid dynamics (CFD) simulations were performed on the generated geometries. Three different pressure gradient indices were defined based on the cardiac time point and extracted from the CFD results. These indices were then used as the training dataset. Finally, linear quadratic, SVM, RIDGE and MARS regression models were developed for pressure gradient indices and the performance of the models were determined. Based on the obtained results, the RIDGE and MARS models outperformed the others to predict the pressure gradient indices with RSME values of 1.26 Pa and 1.94 Pa, respectively.
Pathogenic
Rickettsia
spp. as emerging models for bacterial biology
Authors: Sit Brandon , Lamason Rebecca L.
Published: February 2024

Our understanding of free-living bacterial models like
Escherichia coli
far outpaces that of obligate intracellular bacteria, which cannot be cultured axenically. All obligate intracellular bacteria are host-associated, and many cause serious human diseases. Their constant exposure to the distinct biochemical niche of the host has driven the evolution of numerous specialized bacteriological and genetic adaptations, as well as innovative molecular mechanisms of infection. Here, we review the history and use of pathogenic
Rickettsia
species, which cause an array of vector-borne vascular illnesses, as model systems to probe microbial biology. Although many challenges remain in our studies of these organisms, the rich pathogenic and biological diversity of
Rickettsia
spp. constitutes a unique backdrop to investigate how microbes survive and thrive in host and vector cells. We take a bacterial-focused perspective and highlight emerging insights that relate to new host–pathogen interactions, bacterial physiology, and evolution. The transformation of
Rickettsia
spp. from pathogens to models demonstrates how recalcitrant microbes may be leveraged in the lab to tap unmined bacterial diversity for new discoveries.
Rickettsia
spp. hold great promise as model systems not only to understand other obligate intracellular pathogens but also to discover new biology across and beyond bacteria.
The end of the reign of a “master regulator’’? A defect in function of the LasR quorum sensing regulator is a common feature of
Pseudomonas aeruginosa
isolates
Authors: Trottier Mylène C. , de Oliveira Pereira Thays , Groleau Marie-Christine , Hoffman Lucas R. , Dandekar Ajai A. , Déziel Eric
Published: February 2024

Pseudomonas aeruginosa
, a bacterium causing infections in immunocompromised individuals, regulates several of its virulence functions using three interlinked quorum sensing (QS) systems (
las
,
rhl
, and
pqs
). Despite its presumed importance in regulating virulence, dysfunction of the
las
system regulator LasR occurs frequently in strains isolated from various environments, including clinical infections. This newfound abundance of LasR-defective strains calls into question existing hypotheses regarding their selection. Indeed, current assumptions concerning factors driving the emergence of LasR-deficient isolates and the role of LasR in the QS hierarchy must be reconsidered. Here, we propose that LasR is not the primary master regulator of QS in all
P. aeruginosa
genetic backgrounds, even though it remains ecologically significant. We also revisit and complement current knowledge on the ecology of LasR-dependent QS in
P. aeruginosa
, discuss the hypotheses explaining the putative adaptive benefits of selecting against LasR function, and consider the implications of this renewed understanding.
mSphere of Influence: Compartmentalized cAMP signals in American trypanosomes
Authors: Lander Noelia
Published: February 2024

Noelia Lander works on cell signaling in American trypanosomes and studies the role of cyclic adenosine monophosphate (cAMP) microdomains in environmental sensing and differentiation. In this mSphere of Influence, Dr. Lander reflects on three research articles in different eukaryotic models that had impacted on the way she thinks about the regulation of cAMP signals in
Trypanosoma cruzi
, the etiologic agent of Chagas disease. The articles “FRET biosensor uncovers cAMP nano-domains at β-adrenergic targets that dictate precise tuning of cardiac contractility” (N. C. Surdo, M. Berrera, A. Koschinski, M. Brescia, et al., Nat Commun 8:15031, 2017,
https://doi.org/10.1038/ncomms15031
), “Cyclic AMP signaling and glucose metabolism mediate pH taxis by African trypanosomes” (S. Shaw, S. Knüsel, D. Abbühl, A. Naguleswaran, et al., Nat Commun 13:603, 2022,
https://doi.org/10.1038/s41467-022-28293-w
), and “Encystation stimuli sensing is mediated by adenylate cyclase AC2-dependent cAMP signaling in
Giardia
” (H. W. Shih, G. C. M. Alas, and A. R. Paredez, Nat Commun 14:7245, 2023,
https://doi.org/10.1038/s41467-023-43028-1
) influenced her current hypothesis that cAMP signals are generated in response to environmental cues leading to changes in membrane fluidity at the flagellar tip and the contractile vacuole complex of
T. cruzi
, structures where cAMP mediates key cellular processes for developmental progression.
Identification of a microbial sub-community from the feral chicken gut that reduces
Salmonella
colonization and improves gut health in a gnotobiotic chicken model
Authors: Wongkuna Supapit , Ambat Achuthan , Ghimire Sudeep , Mattiello Samara Paula , Maji Abhijit , Kumar Roshan , Antony Linto , Chankhamhaengdecha Surang , Janvilisri Tavan , Nelson Eric , Doerner Kinchel C. , More Sunil , Behr Melissa , Scaria Joy
Published: February 2024

A complex microbial community in the gut may prevent the colonization of enteric pathogens such as
Salmonella
. Some individual or a combination of species in the gut may confer colonization resistance against
Salmonella
. To gain a better understanding of the colonization resistance against
Salmonella enterica
, we isolated a library of 1,300 bacterial strains from feral chicken gut microbiota which represented a total of 51 species. Using a co-culture assay, we screened the representative species from this library and identified 30 species that inhibited
Salmonella enterica
subspecies enterica serovar Typhimurium
in vitro
. To improve the
Salmonella
inhibition capacity, from a pool of fast-growing species, we formulated 66 bacterial blends, each of which composed of 10 species. Bacterial blends were more efficient in inhibiting
Salmonella
as compared to individual species. The blend that showed maximum inhibition (Mix10) also inhibited other serotypes of
Salmonella
frequently found in poultry. The
in vivo
effect of Mix10 was examined in a gnotobiotic and conventional chicken model. The Mix10 consortium significantly reduced
Salmonella
load at day 2 post-infection in gnotobiotic chicken model and decreased intestinal tissue damage and inflammation in both models. Cell-free supernatant of Mix10 did not show
Salmonella
inhibition, indicating that Mix10 inhibits
Salmonella
through either nutritional competition, competitive exclusion, or through reinforcement of host immunity. Out of 10 species, 3 species in Mix10 did not colonize, while 3 species constituted more than 70% of the community. Two of these species were previously uncultured bacteria. Our approach could be used as a high-throughput screening system to identify additional bacterial sub-communities that confer colonization resistance against enteric pathogens and its effect on the host.

IMPORTANCE

Salmonella
colonization in chicken and human infections originating from
Salmonella-
contaminated poultry is a significant problem. Poultry has been identified as the most common food linked to enteric pathogen outbreaks in the United States. Since multi-drug-resistant
Salmonella
often colonize chicken and cause human infections, methods to control
Salmonella
colonization in poultry are needed. The method we describe here could form the basis of developing gut microbiota-derived bacterial blends as a microbial ecosystem therapeutic against
Salmonella
.
Genetic diversity and recombination of bovine enterovirus strains in China
Authors: Chang Xiaoran , Zhang Zhiyuan , Cui Xuyuan , Zhang Qun , Lin Qian , Hu Junying , Guo Yidi , Wang Xinping
Published: February 2024

Bovine enterovirus (BEV) consisting of enterovirus species E (EV-E) and F (EV-F) is the causative agent associated with respiratory and gastrointestinal diseases in cattle. Here, we reported the characterization, genetic diversity, and recombination of novel BEV strains isolated from the major cattle-raising regions in China during 2012–2018. Twenty-seven BEV strains were successfully isolated and characterized. Molecular characterization demonstrated that the majority of these novel BEV strains (24/27) were EV-E, while only few strains (3/27) were EV-F. Sequence analysis revealed the diversity of the circulating BEV strains such as species and subtypes where different species or subtype coinfections were detected in the same regions and even in the same cattle herds. For the EV-E, two novel subtypes, designated as EV-E6 and EV-E7, were revealed in addition to the currently reported EV-E1–EV-E5. Comparative genomic analysis revealed the intraspecies and interspecies genetic exchanges among BEV isolates. The representative strain HeN-B62 was probably from AN12 (EV-F7) and PS-87-Belfast (EV-F3) strains. The interspecies recombination between EV-E and EV-F was also discovered, where the EV-F7-AN12 might be from EV-E5 and EV-F1, and EV-E5-MexKSU/5 may be recombined from EV-F7 and EV-E1. The aforementioned results revealed the genetic diversity and recombination of novel BEV strains and unveiled the different BEV species or subtype infections in the same cattle herd, which will broaden the understanding of enterovirus genetic diversity, recombination, pathogenesis, and prevention of disease outbreaks.

IMPORTANCE

Bovine enterovirus (BEV) infection is an emerging disease in China that is characterized by digestive, respiratory, and reproductive disorders. In this study, we first reported two novel EV-E subtypes detected in cattle herds in China, unveiled the coinfection of two enterovirus species (EV-E/EV-F) and different subtypes (EV-E2/EV-E7, EV-E1/EV-E7, and EV-E3/EV-E6) in the same cattle herds, and revealed the enterovirus genetic exchange in intraspecies and interspecies recombination. These results provide an important update of enterovirus prevalence and epidemiological aspects and contribute to a better understanding of enterovirus genetic diversity, evolution, and pathogenesis.
Klebsiella pneumoniae
ST147 harboring
bla
NDM-1
, multidrug resistance and hypervirulence plasmids
Authors: Ofosu-Appiah Frederick , Acquah Ezra E. , Mohammed Jibril , Sakyi Addo Comfort , Agbodzi Bright , Ofosu Dorcas A. S. , Myers Charles J. , Mohktar Quaneeta , Ampomah Opoku-Ware , Ablordey Anthony , Amissah Nana Ama
Published: February 2024

The spread of hypervirulent (hv) and carbapenem-/multidrug-resistant
Klebsiella pneumoniae
is an emerging problem in healthcare settings. The New Delhi metallo-β-lactamase-1 (
bla
NDM-1
) is found in Enterobacteriaceae including
K. pneumoniae.
The
bla
NDM-1
is capable of hydrolyzing β-lactam antibiotics which are used for treatment of severe infections caused by multidrug-resistant Gram-negative bacteria. This is associated with the unacceptably high mortality rate in immunocompromised burn injury patients. This study reports on the characterization of
bla
NDM-1
gene and virulence factors in hv carbapenem-/multidrug-resistant
K. pneumoniae
ST147 in the burns unit of a tertiary teaching hospital during routine surveillance. Two
K. pneumoniae
strains were obtained from wounds of burn-infected patients from May 2020 to July 2021. The hypervirulence genes and genetic context of the
bla
NDM-1
gene and mobile genetic elements potentially involved in the transposition of the gene were analyzed. We identified a conserved genetic background and an IS
26
and open reading frame flanking the
bla
NDM-1
gene that could suggest its involvement in the mobilization of the gene. The plasmid harbored additional antibiotic resistance predicted regions that were responsible for resistance to almost all the routinely used antibiotics. To ensure the identification of potential outbreak strains during routine surveillance, investigations on resistance genes and their environment in relation to evolution are necessary for molecular epidemiology.

IMPORTANCE

Data obtained from this study will aid in the prompt identification of disease outbreaks including evolving resistance and virulence of the outbreak bacteria. This will help establish and implement antimicrobial stewardship programs and infection prevention protocols in fragile health systems in countries with limited resources. Integration of molecular surveillance and translation of whole-genome sequencing in routine diagnosis will provide valuable data for control of infection. This study reports for the first time a high-risk clone
K. pneumoniae
ST147 with hypervirulence and multidrug-resistance features in Ghana.
A high-throughput target-based screening approach for the identification and assessment of
Mycobacterium tuberculosis
mycothione reductase inhibitors
Authors: Smiejkowska Natalia , Oorts Lauren , Van Calster Kevin , De Vooght Linda , Geens Rob , Mattelaer Henri-Philippe , Augustyns Koen , Strelkov Sergei V. , Lamprecht Dirk , Temmerman Koen , Sterckx Yann G.-J. , Cappoen Davie , Cos Paul
Published: February 2024

The World Health Organization’s goal to combat tuberculosis (TB) is hindered by the emergence of anti-microbial resistance, therefore necessitating the exploration of new drug targets. Multidrug regimens are indispensable in TB therapy as they provide synergetic bactericidal effects, shorten treatment duration, and reduce the risk of resistance development. The research within our European RespiriTB consortium explores
Mycobacterium tuberculosis
energy metabolism to identify new drug candidates that synergize with bedaquiline, with the aim of discovering more efficient combination drug regimens. In this study, we describe the development and validation of a luminescence-coupled, target-based assay for the identification of novel compounds inhibiting
Mycobacterium tuberculosis
mycothione reductase (Mtr
Mtb
), an enzyme with a role in the protection against oxidative stress. Recombinant Mtr
Mtb
was employed for the development of a highly sensitive, robust high-throughput screening (HTS) assay by coupling enzyme activity to a bioluminescent readout. Its application in a semi-automated setting resulted in the screening of a diverse library of ~130,000 compounds, from which 19 hits were retained after an assessment of their potency, selectivity, and specificity. The selected hits formed two clusters and four fragment molecules, which were further evaluated in whole-cell and intracellular infection assays. The established HTS discovery pipeline offers an opportunity to deliver novel Mtr
Mtb
inhibitors and lays the foundation for future efforts in developing robust biochemical assays for the identification and triaging of inhibitors from high-throughput library screens.

IMPORTANCE

The growing anti-microbial resistance poses a global public health threat, impeding progress toward eradicating tuberculosis. Despite decades of active research, there is still a dire need for the discovery of drugs with novel modes of action and exploration of combination drug regimens. Within the European RespiriTB consortium, we explore
Mycobacterium tuberculosis
energy metabolism to identify new drug candidates that synergize with bedaquiline, with the aim of discovering more efficient combination drug regimens. In this study, we present the development of a high-throughput screening pipeline that led to the identification of
M. tuberculosis
mycothione reductase inhibitors.
Place of birth and postnatal transfers in infants with congenital diaphragmatic hernia in England and Wales: a descriptive observational cohort study
Authors: Nezafat Maldonado Behrouz , Lanoue Julia , Allin Benjamin , Hargreaves Dougal , Knight Marian , Gale Chris , Battersby Cheryl
Published: February 2024

Objective

To describe clinical pathways for infants with congenital diaphragmatic hernia (CDH) and short-term outcomes.

Design

Retrospective observational cohort study using the UK National Neonatal Research Database (NNRD).

Patients

Babies with a diagnosis of CDH admitted to a neonatal unit in England and Wales between 2012 and 2020.

Main outcome measures

Clinical pathways defined by place of birth (with or without colocated neonatal and surgical facilities), transfers, clinical interventions, length of hospital stay and discharge outcome.

Results

There were 1319 babies with a diagnosis of CDH cared for in four clinical pathways: born in maternity units with (1) colocated tertiary neonatal and surgical units (‘neonatal surgical units’), 50% (660/1319); (2) designated tertiary neonatal unit and transfer to stand-alone surgical centre (‘tertiary designated’), 25% (337/1319); (3) non-designated tertiary neonatal unit (‘tertiary non-designated’), 7% (89/1319); or (4) non-tertiary unit (‘non-tertiary’), 18% (233/1319)—the latter three needing postnatal transfers. Infant characteristics were similar for infants born inneonatal surgicalandtertiary designatedunits. Excluding 149 infants with minimal data due to early transfer (median (IQR) 2.2 (0.4–4.5) days) to other settings, survival to neonatal discharge was 73% (851/1170), with a median (IQR) stay of 26 (16–44) days.

Conclusions

We found that half of the babies with CDH were born in hospitals that did not have on-site surgical services and required postnatal transfer. Similar characteristics between infants born in neonatal surgical units and tertiary designated units suggest that organisation rather than infant factors influence place of birth. Future work linking the NNRD to other datasets will enable comparisons between care pathways.
Prediction of retinopathy progression using deep learning on retinal images within the Scottish screening programme
Authors: Mellor Joseph , Jiang Wenhua , Fleming Alan , McGurnaghan Stuart J , Blackbourn Luke A K , Styles Caroline , Storkey Amos , McKeigue Paul M , Colhoun Helen M
Published: February 2024

Background/aims

National guidelines of many countries set screening intervals for diabetic retinopathy (DR) based on grading of the last screening retinal images. We explore the potential of deep learning (DL) on images to predict progression to referable DR beyond DR grading, and the potential impact on assigned screening intervals, within the Scottish screening programme.

Methods

We consider 21 346 and 247 233 people with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM), respectively, each contributing on average 4.8 and 4.4 screening intervals of which 1339 and 4675 intervals concluded with a referable screening episode. Information extracted from fundus images using DL was used to predict referable status at the end of interval and its predictive value in comparison to screening-assigned DR grade was assessed.

Results

The DL predictor increased the area under the receiver operating characteristic curve in comparison to a predictor using current DR grades from 0.809 to 0.87 for T1DM and from 0.825 to 0.87 for T2DM. Expected sojourn time—the time from becoming referable to being rescreened—was found to be 3.4 (T1DM) and 2.7 (T2DM) weeks less for a DL-derived policy compared with the current recall policy.

Conclusions

We showed that, compared with using the current retinopathy grade, DL of fundus images significantly improves the prediction of incident referable retinopathy before the next screening episode. This can impact screening recall interval policy positively, for example, by reducing the expected time with referable disease for a fixed workload—which we show as an exemplar. Additionally, it could be used to optimise workload for a fixed sojourn time.
Responsiveness of services rendered at primary healthcare facilities of Bharatpur, Nepal: a cross-sectional study
Authors: Adhikari Anup , Paneru Damaru Prasad , Pokhrel Amshu
Published: February 2024

Introduction

Responsiveness of services refers to the way healthcare systems and providers interact with patients and how well they meet patients’ non-clinical expectations and needs. The responsiveness is a crucial aspect of a well-functioning health system while primary healthcare is considered as its foundational cornerstone. However, in low and middle-income countries, there are numerous obstacles to its efficient operation and a very limited understanding of the concept of service responsiveness. This study aimed to assess the responsiveness of services and identify associated factors at primary healthcare facilities of Bharatpur, Nepal.

Methods

A facility-based cross-sectional study was carried out among 358 patients visiting outpatient department (OPD) of primary healthcare facilities of Bharatpur. A pretested structured interview schedule was used to conduct a face-to-face interview to obtain the information per the study’s objective. Univariate as well as bivariable and multivariable logistic regressions were carried out to obtain the result per our objectives.

Results

The overall performance of the responsiveness of services was 74.6% (95% CI 70.1 to 78.8), dignity being the highest performing domain (97.2%) and choice being the lowest (22.6%). Respondents aged more than or equal to 50 (adjusted OR (AOR)=4.107, 95% CI 1.28 to 13.14), those who are satisfied with the service (AOR=7.02, 95% CI 3.21 to 15.36), those who perceive high quality of care (AOR=5.69, 95% CI 2.54 to 12.73) and those who did not have to pay for transportation (AOR=4.63, 95% CI 2.20 to 9.72) showed higher responsiveness.

Conclusion

The primary healthcare facilities of Bharatpur, Nepal demonstrated nearly three-quarters of the respondents reporting good responsiveness of services at OPD. To further enhance the level of responsiveness, strengthening the referral networks, empowering patients in decision-making and prioritising patient satisfaction and quality of services can help.