Marker Tracking Research Articles

Six-degrees-of-freedom pelvic bone monitoring on 2D kV intrafraction images to enable multi-target tracking for locally advanced prostate cancer.

Patients with locally advanced prostate cancer require the prostate and pelvic lymph nodes to be irradiated simultaneously during radiation therapy treatment. However, relative motion between treatment targets decreases dosimetric conformity. Current treatment methods mitigate this error by having large treatment margins and often prioritize the prostate at patient setup at the cost of lymph node coverage. Treatment accuracy can be improved through real-time multi-target adaptation which requires simultaneous motion monitoring of both the prostate and lymph node targets. This study developed and evaluated an intrafraction pelvic bone motion monitoring method as a surrogate for pelvic lymph node displacement to be combined with prostate motion monitoring to enable multi-target six-degrees-of-freedom (6DoF) tracking using 2D kV projections acquired during treatment. A method to monitor pelvic bone translation and rotation was developed and retrospectively applied to images from 20 patients treated in the TROG 15.01 Stereotactic Prostate Ablative Radiotherapy with Kilovoltage Intrafraction Monitoring (KIM) trial. The pelvic motion monitoring method performed template matching to calculate the 6DoF position of the pelvis from 2D kV images. The method first generated a library of digitally reconstructed radiographs (DRRs) for a range of imaging angles and pelvic rotations. The normalized 2D cross-correlations were then calculated for each incoming kV image and a subset of DRRs and the DRR with the maximum correlation coefficient was used to estimate the pelvis translation and rotation. Translation of the pelvis in the unresolved direction was calculated using a 3D Gaussian probability estimation method. Prostate motion was measured using the KIM marker tracking method. The pelvic motion monitoring method was compared to the ground truth obtained from a 6DoF rigid registration of the CBCT and CT. The geometric errors of the pelvic motion monitoring method demonstrated sub-mm and sub-degree accuracy and precision in the translational directions ( , , ) and rotational directions ( , , ). The 3D relative displacement between the prostate and pelvic bones exceeded 2, 3, 5, and 7mm for approximately 66%, 44%, 12%, and 7% of the images. Accurate intrafraction pelvic bone motion monitoring in 6DoF was demonstrated on 2D kV images, providing a necessary tool for real-time multi-target motion-adapted treatment.

Computational identification of surface markers for isolating distinct subpopulations from heterogeneous cancer cell populations

Intratumor heterogeneity reduces treatment efficacy and complicates our understanding of tumor progression and there is a pressing need to understand the functions of heterogeneous tumor cell subpopulations within a tumor, yet systems to study these processes in vitro are limited. Single-cell RNA sequencing (scRNA-seq) has revealed that some cancer cell lines include distinct subpopulations. Here, we present clusterCleaver, a computational package that uses metrics of statistical distance to identify candidate surface markers maximally unique to transcriptomic subpopulations in scRNA-seq which may be used for FACS isolation. With clusterCleaver, ESAM and BST2/tetherin were experimentally validated as surface markers which identify and separate major transcriptomic subpopulations within MDA-MB-231 and MDA-MB-436 cells, respectively. clusterCleaver is a computationally efficient and experimentally validated workflow for identification of surface markers for tracking and isolating transcriptomically distinct subpopulations within cell lines. This tool paves the way for studies on coexisting cancer cell subpopulations in well-defined in vitro systems.

Assessing human-source microbial contamination of stormwater in the U.S

Stormwater capture and use (SCU) projects have the potential to provide a significant portion of municipal water demand. However, uncertainty about the degree of microbial contamination in stormwater and the required treatment is a barrier for implementation of SCU projects. Stormwater runoff could become contaminated with human fecal matter in areas with deteriorating infrastructure where raw wastewater exfiltrates from sewer networks to stormwater collection networks, homeless encampments exist, or sanitary sewer overflows (SSOs) occur. Estimation of human fecal contamination can inform selection of stormwater treatment targets. This study investigates stormwater microbial contamination originating from human fecal matter using observed detections and concentrations of human microbial source tracking (MST) markers and potentially human-infectious pathogens (PHIPs). First, a systematic review complied measurements of human MST markers in wet and dry weather stormwater flows and influent wastewater. In addition, measurements of viral pathogens (e.g., adenoviruses, norovirus GI+GII, and enteroviruses) and protozoan pathogens (e.g., Giardia lamblia and Cryptosporidium parvum) in wet weather flows and influent wastewater were assessed. Human MST marker and PHIP data were statistically analyzed and applied to estimate a human fecal contamination analog (HFCA) which is an estimate of the amount of human fecal matter based on relative concentrations of microbial contaminants in stormwater compared to municipal wastewater. Human MST-based HFCAs in wet and dry weather flows ranged from <10−7.0 to 10−1.5 (median = 10−4.5) and 10−12 to 10−2.6 (median = 10−7.0), respectively. PHIP-based HFCAs in wet weather flows ranged from ∼10−8 to 10−0.14. Estimates of human MST-based HFCAs are more reliable than PHIP-based HFCAs because the current PHIP datasets are generally limited by the number of data points, percent detection, variability observed within the statistical distributions, and the geographical span of sampling locations. The use of human MST-based HFCAs is recommended to guide the selection of stormwater treatment process trains that are protective of public health based on the intended end use. Application of HFCA 10−1 (i.e., sewage dilution 10−1) remains a reasonable conservative estimate of human fecal contamination in stormwater to inform selection of pathogen log reduction targets based on the data presently available.

Personalizing the shoulder rhythm in a computational upper body model improves kinematic tracking in high range-of-motion arm movements

Musculoskeletal models of the shoulder are needed to understand the mechanics of overhead motions. Existing models implementing the shoulder rhythm are generic and might not accurately represent an individual’s scapular kinematics. We introduce a method to personalize the shoulder rhythm of a computational model of the upper body that defines the orientations of the clavicle and scapula based on glenohumeral joint angles. During five static calibration poses, we palpate and measure the orientation of the scapula. We explore the importance of representing shoulder elevation by introducing clavicle elevation as a degree of freedom that is independent of the glenohumeral angles. For ten subjects, we record the five calibration poses, ten additional static poses, and dynamic arm raises covering the participants’ full range of motion in each body plane using optical motion capture. We examine the data using a dynamically-constrained inverse kinematics analysis. Shoulder rhythm personalization, independent clavicle elevation, and both in combination reduce the average upper body marker tracking error compared to the generic model in the static poses (26 mm to 17–20 mm) and in the dynamic trials (22 mm to 14–17 mm). Only personalization reduces the average scapula marker error (51 mm to 36–38 mm) and scapula axis-angle error (15° to 10°) compared with the palpated ground truth measurements in the static poses, and in the dynamic trials at instances that best match the static poses (53 mm to 37–40 mm, 15° to 9°). Our results show that personalizing upper body models improves kinematic tracking. We provide our experimental data, model, and methods to allow researchers to reproduce and build upon our results.

Inverse kinematics in cervical spine models: Effects of scaling and model degrees of freedom for extension and flexion movements

Intervertebral kinematics can affect model-predicted loads and strains in the spine; therefore knowledge of expected vertebral kinematics error is important for understanding the limitations of model predictions. This study addressed how different kinematic models of the neck affect the prediction of intervertebral kinematics from markers on the head and trunk. Eight subjects executed head and neck extension-flexion motion with simultaneous motion capture and biplanar dynamic stereo-radiography (DSX) of vertebrae C1-C7. A generic head and neck model in OpenSim was scaled by marker data, and three versions of the model were used with an inverse kinematics solver. The models differed according to the number of independent degrees of freedom (DOF) between the head and trunk: 3 rotational DOF with constraints defining intervertebral kinematics as a function of overall head-trunk motion; 24DOF with 3 independent rotational DOF at each level, skull-T1; 48DOF with 3 rotational and 3 translational DOF at each level. Marker tracking error was lower for scaled models compared to generic models and decreased as model DOF increased. The largest mean absolute error (MAE) was found in extension-flexion angle and anterior-posterior translation at C1-C2, and superior-inferior translation at C2-C3. Model scaling and complexity did not have a statistically significant effect on most error metrics when corrected for multiple comparisons, but ranges of motion were significantly different from DSX in some cases. This study evaluated model kinematics in comparison to gold standard radiographic data and provides important information about intervertebral kinematics error that are foundational to model validity.

Development of a novel crAss-like phage detection method with a broad spectrum for microbial source tracking

CrAssphage has been recognized as the most abundant and human-specific bacteriophage in the human gut. Consequently, crAssphage has been used as a microbial source tracking (MST) marker to monitor human fecal contamination. Many crAss-like phages (CLPs) have been recently discovered, expanding the classification into the new order Crassvirales. This study aims to assess CLP prevalence in South Korea and develop a detection system for MST applications. Thirteen CLPs were identified in six human fecal samples and categorized into seven genera via metagenomic analysis. The major head protein (MHP) displayed increased sequence similarity within each genus. Eight PCR primer candidates, designed from MHP sequences, were evaluated in animal and human feces. CLPs were absent in animal feces except for those from raccoons, which hosted genera VI, VIIa, and VIIb. CLPs were detected in 91.52% (54/59) of humans, with genus VI (38 out of 59) showing the highest prevalence, nearly double that of p-crAssphage in genus I (22 out of 59). This study highlights genus VI as a potent MST marker, broadening the detection range for CLPs. Human-specific and selectively targeted MST markers can significantly impact hygiene regulations, lowering public health costs through their application in screening liver, sewage, wastewater, and various environmental samples.

Nontechnical Skills Assessment in Acute Care Trauma Simulations: A Mixed Methods Approach Using Eye Tracking and Behavioral Marker Systems.

The condition of trauma patients and the urgent need for timely resuscitation present unique challenges to trauma teams. These difficulties are exacerbated for military trauma teams in combat environments. Consequently, there is a need for continued improvement of nontechnical skills (NTS) training for trauma teams. However, current approaches to NTS assessment rely on subjective ratings, which can introduce bias. Accordingly, objective methods of NTS evaluation are needed. Eye-tracking (ET) methods have been applied to studying communication, situation awareness, and leadership in many health care settings, and could be applied to studying physicians' NTS during trauma situations. In this study, we aimed to assess the relationship between trauma team leaders' objective gaze patterns and subjective expert NTS ratings during patient care simulations. After Institutional Review Board approval, 9 trauma teams from first-year post-graduate general surgery and emergency medicine residents were recruited to participate in 1 of 2 trauma simulations (a difficult airway case and a multi-patient trauma). Each scenario lasted approximately 15 minutes. All team leaders wore a mobile ET system to evaluate gaze metrics-time to first fixation (TTFF), average fixation duration (AFD), and total percentage of the scenario (TPS) focused on Areas of Interest (AOI), which included patient, care team, diagnostic equipment, and patient care equipment. Trained faculty raters completed the Non-Technical Skills for Surgeons (NOTSS) assessment tool and the Trauma Non-Technical Skills (T-NOTECHS) scale. One-way analysis of variance, Kruskal-Wallis, and appropriate post-hoc pairwise comparison tests were run to assess differences between ET metrics across AOI groups. Spearman's Rho tests were used to assess correlations between ET and subjective NTS ratings. Compared to other NTS domains, trauma teams scored relatively poorly on communication across both T-NOTECHS (3.29$ \pm $0.61, maximum = 5) and NOTSS (2.87$ \pm $0.66, maximum = 4). We found significant differences in trauma team leaders' TTFF between teammates and the patient (Team: 1.56 vs Patient: 29.82 seconds, P < .001). TTFF on the diagnostic equipment was negatively correlated (P < .05) to multiple measures of subjective NTS assessments. There were no significant differences in AFD between AOIs, and AFD on teammates was positively correlated (P < .05) to communication and teamwork. There were significant differences in TPS across most AOI pairs (P < .05), and the average TPS fixated was highest on the patient (32%). Finally, there were several significant correlations between additional ET and NTS metrics. This study utilized a mixed methods approach to assess trauma team leaders' NTS in simulated acute care trauma simulations. Our results provide several objective insights into trauma team leaders' NTS behaviors during patient care simulations. Such objective insights provide a more comprehensive understanding of NTS behaviors and can be leveraged to guide NTS training of trauma physicians in the future. More studies are needed to apply these methods to capture NTS from a larger sample of teams in both simulated and real trauma environments.

STTAR: Surgical Tool Tracking Using Off-the-Shelf Augmented Reality Head-Mounted Displays.

The use of Augmented Reality (AR) for navigation purposes has shown beneficial in assisting physicians during the performance of surgical procedures. These applications commonly require knowing the pose of surgical tools and patients to provide visual information that surgeons can use during the performance of the task. Existing medical-grade tracking systems use infrared cameras placed inside the Operating Room (OR) to identify retro-reflective markers attached to objects of interest and compute their pose. Some commercially available AR Head-Mounted Displays (HMDs) use similar cameras for self-localization, hand tracking, and estimating the objects' depth. This work presents a framework that uses the built-in cameras of AR HMDs to enable accurate tracking of retro-reflective markers without the need to integrate any additional electronics into the HMD. The proposed framework can simultaneously track multiple tools without having previous knowledge of their geometry and only requires establishing a local network between the headset and a workstation. Our results show that the tracking and detection of the markers can be achieved with an accuracy of 0.09±0.06 mm on lateral translation, 0.42 ±0.32 mm on longitudinal translation and 0.80 ±0.39° for rotations around the vertical axis. Furthermore, to showcase the relevance of the proposed framework, we evaluate the system's performance in the context of surgical procedures. This use case was designed to replicate the scenarios of k-wire insertions in orthopedic procedures. For evaluation, seven surgeons were provided with visual navigation and asked to perform 24 injections using the proposed framework. A second study with ten participants served to investigate the capabilities of the framework in the context of more general scenarios. Results from these studies provided comparable accuracy to those reported in the literature for AR-based navigation procedures.

Nanomaterial-Mediated Immunosensors and Their Performance in Detecting Tumor Markers.

The detection of tumor markers is crucial for assessing the progression of specific cancers. Numerous research studies have shown that immunosensors can convert immune-specific response biosignals into visual signals, enabling the highly sensitive tracking and detection of tumor markers. This offers a promising solution for early cancer diagnosis. However, most tumor markers are inert molecules that are challenging to detect at low concentrations in the early stages of cancer. Therefore, there is a need to develop immunosensor analysis platforms with a higher sensitivity. Nanomaterials, with their advantages of high stability, low cost, and versatility in design, have emerged as ideal candidates for enhancing the performance of immunosensor analysis. In this paper, we review the design ideas of nanomaterials in antibody-based electrochemical, electrochemiluminescent, and photoelectrochemical immunosensors, including electrode interface modification, signaling probes for stimulating sensing signals, and design strategies of modified materials in signaling mechanisms. In addition, we have thoroughly analyzed the performance, advantages and disadvantages of different immunosensors. Therefore, the aim of this paper is to review the recent advances in advanced nanomaterial strategies for different immunosensors and their biomedical applications, and to point out the challenges and prospects of immunosensors in future clinical applications.

Strategic Integration of AI in Higher Education and Industry: The AI8-Point Model

The AI8-Point Model, derived from extensive experience in technology, AI, and higher education administration, addresses the critical need for cost-effective, high-impact strategies tailored to higher education. Despite the transformative potential of AI in enhancing student engagement, optimizing processes, and improving educational outcomes, institutions often struggle with practical implementation. The AI8-Point Model fills this gap by offering strategies that balance cost and impact. Visualized as a circle divided into four quadrants, the model encompasses phases of student engagement and institutional interaction: pre-enrollment beyond institutional control, pre-enrollment within institutional control, post-enrollment within institutional control, and post-enrollment beyond institutional control. Each quadrant contains specific markers for data collection, strategic planning, and outcome tracking, addressing student aptitude, motivation, marketing strategies, enrollment processes, academic support, faculty development, lifelong learning, and employment outcomes. Integrating methodologies from educational research, business strategy, and technology management, the model is grounded in empirical evidence and personal experience, emphasizing a low-cost, high-value approach to AI applications. This comprehensive framework enables institutions to align initiatives with goals, optimize resource allocation, and track progress effectively, fostering a holistic approach to student success and institutional growth. Additionally, the model’s adaptability extends its value to non-profit and corporate organizations, offering a versatile tool for enhancing strategic initiatives across various sectors.

Benefits and Challenges of Applying Bacteriophage Biocontrol in the Consumer Water Cycle.

Bacteria (including disinfection- and antibiotic-resistant bacteria) are abundant in the consumer water cycle, where they may cause disease, and lead to biofouling and infrastructure damage in distributions systems, subsequently resulting in significant economic losses. Bacteriophages and their associated enzymes may then offer a biological control solution for application within the water sector. Lytic bacteriophages are of particular interest as biocontrol agents as their narrow host range can be exploited for the targeted removal of specific bacteria in a designated environment. Bacteriophages can also be used to improve processes such as wastewater treatment, while bacteriophage-derived enzymes can be applied to combat biofouling based on their effectiveness against preformed biofilms. However, the host range, environmental stability, bacteriophage resistance and biosafety risks are some of the factors that need to be considered prior to the large-scale application of these bacterial viruses. Characteristics of bacteriophages that highlight their potential as biocontrol agents are thus outlined in this review, as well as the potential application of bacteriophage biocontrol throughout the consumer water cycle. Additionally, the limitations of bacteriophage biocontrol and corresponding mitigation strategies are outlined, including the use of engineered bacteriophages for improved host ranges, environmental stability and the antimicrobial re-sensitisation of bacteria. Finally, the potential public and environmental risks associated with large-scale bacteriophage biocontrol application are considered, and alternative applications of bacteriophages to enhance the functioning of the consumer water cycle, including their use as water quality or treatment indicators and microbial source tracking markers, are discussed.

Suture Packaging as a Marker for Intraoperative Image Alignment in Augmented Reality on Mobile Devices.

Preoperative vascular imaging has become standard practice in the planning of microsurgical breast reconstruction. Currently, translating perforator locations from radiological findings to a patient's abdomen is often not easy or intuitive. Techniques using three-dimensional printing or patient-specific guides have been introduced to superimpose anatomy onto the abdomen for reference. Augmented and mixed reality is currently actively investigated for perforator mapping by superimposing virtual models directly onto the patient. Most techniques have found only limited adoption due to complexity and price. Additionally, a critical step is aligning virtual models to patients. We propose repurposing suture packaging as an image tracking marker. Tracking markers allow quick and easy alignment of virtual models to the individual patient's anatomy. Current techniques are often complicated or expensive and limit intraoperative use of augmented reality models. Suture packs are sterile, readily available, and can be used to align abdominal models on the patients. Using an iPad, the augmented reality models automatically align in the correct position by using a suture pack as a tracking marker. Given the ubiquity of iPads, the combination of these devices with readily available suture packs will predictably lower the barrier to entry and utilization of this technology. Here, our workflow is presented along with its intraoperative utilization. Additionally, we investigated the accuracy of this technology.

The spatiotemporal richness of hummingbird wing deformations.

Animals exhibit an abundant diversity of forms, and this diversity is even more evident when considering animals that can change shape on demand. The evolution of flexibility contributes to aspects of performance from propulsive efficiency to environmental navigation. It is, however, challenging to quantify and compare body parts that, by their nature, dynamically vary in shape over many time scales. Commonly, body configurations are tracked by labelled markers and quantified parametrically through conventional measures of size and shape (descriptor approach) or non-parametrically through data-driven analyses that broadly capture spatiotemporal deformation patterns (shape variable approach). We developed a weightless marker tracking technique and combined these analytic approaches to study wing morphological flexibility in hoverfeeding Anna's hummingbirds (Calypte anna). Four shape variables explained >95% of typical stroke cycle wing shape variation and were broadly correlated with specific conventional descriptors such as wing twist and area. Moreover, shape variables decomposed wing deformations into pairs of in-plane and out-of-plane components at integer multiples of the stroke frequency. This property allowed us to identify spatiotemporal deformation profiles characteristic of hoverfeeding with experimentally imposed kinematic constraints, including through shape variables explaining <10% of typical shape variation. Hoverfeeding in front of a visual barrier restricted stroke amplitude and elicited increased stroke frequencies together with in-plane and out-of-plane deformations throughout the stroke cycle. Lifting submaximal loads increased stroke amplitudes at similar stroke frequencies together with prominent in-plane deformations during the upstroke and pronation. Our study highlights how spatially and temporally distinct changes in wing shape can contribute to agile fluidic locomotion.

Structural vibration frequency monitoring based on event camera

Compared with traditional cameras, event cameras (ECs) have the significant advantages of high temporal resolution, low data redundancy, and microsecond delay, which are beneficial in structural monitoring to extract the dense response of structures in both spatial and temporal dimensions. In this paper, the vibration frequency detection method based on ECs is studied. This study investigates vibration frequency detection methods based on ECs, and proposes two algorithms for vibration frequency detection based on event streams: marker tracking and event count. Experimental verification is conducted through forced vibration experiments. The results indicate that the event count method achieves high-precision measurement of vibration frequencies in the range of 10–190 Hz for different vibration scales, with a maximum relative error of 1% and an average relative error of 0.673%. The marker tracking method demonstrates a maximum relative error of 1.43% and an average relative error of 0.575% in frequency measurement for large-amplitude vibrations. However, as the amplitude decreases, the frequency measurement error increases. When the amplitude is less than 3 pixels, the frequency measurement error exceeds 30%, rendering the measurement results unreliable. This research provides technical support for high-precision structural vibration frequency monitoring and further expands the application of ECs in structural monitoring.

GaitFormer: Leveraging dual-stream spatial–temporal Vision Transformer via a single low-cost RGB camera for clinical gait analysis

Gait analysis is an essential technique in treating patients with lower limb dysfunctions. Traditional methods often rely on expensive and complex equipment, such as wearable body sensors and a multi-camera with marker tracking system. Aiming for a more cost-effective yet accurate alternative, this paper introduces GaitFormer, a novel approach that leverages Vision Transformer (ViT) for gait analysis using minimal, non-invasive equipment, i.e. a single low-cost RGB camera. Initially, a unique dataset using a multi-camera system with marker tracking, comprising 6 walking patterns gathered from 80 volunteers is developed. The ViT-based GaitFormer is then proposed to automatically recognize human walking patterns through a single RGB camera. GaitFormer comprises hybrid networks for each step, including: (i) a cascaded convolutional 2D human key points estimation network; (ii) a ViT-based dual-stream spatial–temporal network extending the information of human key points into 3D; (iii) leveraging specific lower limb key joints’ angle features for clinical gait analysis, capturing the geometric, kinematic, and physical attributes of human motion; (iv) employing a pure self-attention-based classification network to recognize clinical human walking patterns. The experiments are designed to comprehensively validate each step against various related baseline methods and multi-camera tracking system, with results demonstrating the promising performance of GaitFormer as an affordable, precise, and integrated solution. To the best of our knowledge, GaitFormer is the first hybrid CNN- and ViT-based end-to-end solution via low-cost device for clinically valuable gait analysis.

Estimating 3D kinematics and kinetics from virtual inertial sensor data through musculoskeletal movement simulations.

Portable measurement systems using inertial sensors enable motion capture outside the lab, facilitating longitudinal and large-scale studies in natural environments. However, estimating 3D kinematics and kinetics from inertial data for a comprehensive biomechanical movement analysis is still challenging. Machine learning models or stepwise approaches performing Kalman filtering, inverse kinematics, and inverse dynamics can lead to inconsistencies between kinematics and kinetics. We investigated the reconstruction of 3D kinematics and kinetics of arbitrary running motions from inertial sensor data using optimal control simulations of full-body musculoskeletal models. To evaluate the feasibility of the proposed method, we used marker tracking simulations created from optical motion capture data as a reference and for computing virtual inertial data such that the desired solution was known exactly. We generated the inertial tracking simulations by formulating optimal control problems that tracked virtual acceleration and angular velocity while minimizing effort without requiring a task constraint or an initial state. To evaluate the proposed approach, we reconstructed three trials each of straight running, curved running, and a v-cut of 10 participants. We compared the estimated inertial signals and biomechanical variables of the marker and inertial tracking simulations. The inertial data was tracked closely, resulting in low mean root mean squared deviations for pelvis translation (≤20.2mm), angles (≤1.8 deg), ground reaction forces (≤1.1 BW%), joint moments (≤0.1 BWBH%), and muscle forces (≤5.4 BW%) and high mean coefficients of multiple correlation for all biomechanical variables . Accordingly, our results showed that optimal control simulations tracking 3D inertial data could reconstruct the kinematics and kinetics of individual trials of all running motions. The simulations led to mutually and dynamically consistent kinematics and kinetics, which allows researching causal chains, for example, to analyze anterior cruciate ligament injury prevention. Our work proved the feasibility of the approach using virtual inertial data. When using the approach in the future with measured data, the sensor location and alignment on the segment must be estimated, and soft-tissue artifacts are potential error sources. Nevertheless, we demonstrated that optimal control simulation tracking inertial data is highly promising for estimating 3D kinematics and kinetics for a comprehensive biomechanical analysis.

Scenario-based assessment of fecal pathogen sources affecting bathing water quality: novel treatment options to reduce norovirus and Campylobacter infection risks.

Wastewater discharge and runoff waters are significant sources of human and animal fecal microbes in surface waters. Human-derived fecal contamination of water is generally estimated to pose a greater risk to human health than animal fecal contamination, but animals may serve as reservoirs of zoonotic pathogens. In this study, quantitative microbial risk assessment (QMRA) tools were used to evaluate the hygienic impact of sewage effluents and runoff water from municipalities and animal farms on surface and bathing waters. The human-specific microbial source tracking (MST) marker HF183 was used to evaluate the dilution of fecal pathogens originating from the sewage effluent discharge to the downstream watershed. As novel risk management options, the efficiency of UV-LED disinfection and wetland treatment as well as biochar filtration was tested on-site for the contamination sources. According to the dilution pattern of the MST marker HF183, microbes from wastewater were diluted (2.3-3.7 log10) in the receiving waters. The scenario-based QMRA revealed, that the health risks posed by exposure to human-specific norovirus GII and zoonotic Campylobacter jejuni during the bathing events were evaluated. The risk for gastroenteritis was found to be elevated during wastewater contamination events, where especially norovirus GII infection risk increased (1-15 cases per day among 50 bathers) compared with the business as usual (BAU) situation (1 case per day). The noted C. jejuni infection risk was associated with animal farm contamination (1 case per day, versus 0.2-0.6 cases during BAU). Tertiary treatment of wastewater with wetland treatment and UV-LED disinfection effectively reduced the waterborne gastroenteritis risks associated with bathing. Based on the experiences from this study, a QMRA-based approach for health risk evaluations at bathing sites can be useful and is recommended for bathing site risk assessments in the future. In case of low pathogen numbers at the exposure sites, the MST marker HF183 could be used as a pathogen dilution coefficient for the watershed under evaluation. The full-scale implementation of novel tertiary treatment options at wastewater treatment plants (WWTPs) as well as on-site runoff water treatment options should be considered for infection risk management at locations where scenario-based QMRA implies elevated infection risks.

The PIVOT App: A User Guide

Background: While the pivot shift examination is often regarded as the gold standard test for diagnosis of anterior cruciate ligament (ACL) injury, one of the pitfalls of the pivot shift test is that it lacks standardization among physicians. The PIVOT App is a validated application to quantify the amount of tibial translation during the pivot shift maneuver and improve standardization of clinical measurement. Indications: The PIVOT App can be used in both clinic and operating room settings for patients who sustained injury to the ACL. The PIVOT App may assist in identifying the amount of rotatory knee laxity in patients with ACL deficiency or following ACL reconstruction. Technique Description: The PIVOT App works by quantifying the amount of translation in the lateral tibia relative to a marker on the lateral femoral epicondyle. To use the PIVOT App, 3 yellow circle stickers are placed on the bony prominences of the lateral knee: the lateral epicondyle, Gerdy’s tubercle, and the “pivot point” 3 cm posterior to Gerdy’s tubercle parallel to the joint line. Once placed, the pivot shift flexion maneuver can be recorded in the PIVOT App and analyzed to identify both the distance of spontaneous tibial reduction during the pivot shift maneuver and the time of reduction in seconds. The most common problems encountered while using the application include (1) improper marker placement, (2) interference of marker tracking with yellow color in the background, (3) interference of marker tracking with overhead lighting, and (4) extraneous data collection before and after pivot shift flexion. Results: Previous studies have validated the PIVOT App to accurately distinguish normal, low-grade, and high-grade pivot shifts with resultant increasing tibial translation in the lateral compartment of the knee. The PIVOT App has been used at institutions worldwide to quantify and standardize measurement of the pivot shift. Conclusion: The PIVOT App is a validated application to quantify the amount of lateral tibial translation and reduction during the pivot shift maneuver. Proper use and avoidance of complications while using the application can aid clinicians in accurate diagnosis of rotatory knee laxity in patients following ACL injury. Patient Consent Disclosure Statement: The author(s) attests that consent has been obtained from any patient(s) appearing in this publication. If the individual may be identifiable, the author(s) has included a statement of release or other written form of approval from the patient(s) with this submission for publication.

Is detection of enteropathogens and human or animal faecal markers in the environment associated with subsequent child enteric infections and growth: an individual participant data meta-analysis

Quantifying contributions of environmental faecal contamination to child diarrhoea and growth faltering can illuminate causal mechanisms behind modest health benefits in recent water, sanitation, and hygiene (WASH) trials. We aimed to assess associations between environmental detection of enteropathogens and human or animal microbial source tracking markers (MSTM) and subsequent child health outcomes. In this individual participant data meta-analysis we searched we searched PubMed, Embase, CAB Direct Global Health, Agricultural and Environmental Science Database, Web of Science, and Scopus for WASH intervention studies with a prospective design and concurrent control that measured enteropathogens or MSTM in environmental samples, or both, and subsequently measured enteric infections, diarrhoea, or height-for-age Z-scores (HAZ) in children younger than 5 years. We excluded studies that only measured faecal indicator bacteria. The initial search was done on Jan 19, 2021, and updated on March 22, 2023. One reviewer (AM) screened abstracts, and two independent reviewers (AM and RT) examined the full texts of short-listed articles. All included studies include at least one author that also contributed as an author to the present Article. Our primary outcomes were the 7-day prevalence of caregiver-reported diarrhoea and HAZ in children. For specific enteropathogens in the environment, primary outcomes also included subsequent child infection with the same pathogen ascertained by stool testing. We estimated associations using covariate-adjusted regressions and pooled estimates across studies. Data from nine published reports from five interventions studies, which included 8603 children (4302 girls and 4301 boys), were included in the meta-analysis. Environmental pathogen detection was associated with increased infection prevalence with the same pathogen and lower HAZ (ΔHAZ -0·09 [95% CI -0·17 to -0·01]) but not diarrhoea (prevalence ratio 1·22 [95% CI 0·95 to 1·58]), except during wet seasons. Detection of MSTM was not associated with diarrhoea (no pooled estimate) or HAZ (ΔHAZ -0·01 [-0·13 to 0·11] for human markers and ΔHAZ -0·02 [-0·24 to 0·21] for animal markers). Soil, children's hands, and stored drinking water were major transmission pathways. Our findings support a causal chain from pathogens in the environment to infection to growth faltering, indicating that the lack of WASH intervention effects on child growth might stem from insufficient reductions in environmental pathogen prevalence. Studies measuring enteropathogens in the environment should subsequently measure the same pathogens in stool to further examine theories of change between WASH, faecal contamination, and health. Given that environmental pathogen detection was predictive of infection, programmes targeting specific pathogens (eg, vaccinations and elimination efforts) can environmentally monitor the pathogens of interest for population-level surveillance instead of collecting individual biospecimens. The Bill & Melinda Gates Foundation and the UK Foreign and Commonwealth Development Office.

CrAss-Like Phages: From Discovery in Human Fecal Metagenome to Application as a Microbial Source Tracking Marker.

CrAss-like phages are a diverse group of bacteriophages genetically similar to the prototypical crAssphage (p-crAssphage), which was discovered in the human gut microbiome through a metagenomics approach. It was identified as a ubiquitous and highly abundant bacteriophage group in the gut microbiome. Initial co-occurrence analysis postulated Bacteroides spp. as the prospective bacterial host. Subsequent studies have confirmed multiple host species under Phylum Bacteroidetes and some Firmicutes. Detection of crAss-like phages in sewage-contaminated environmental water and robust correlation with enteric viruses and bacteria has culminated in their adoption as a microbial source tracking (MST) marker. Polymerase chain reaction (PCR) and real-time PCR assays have been developed utilizing the conserved genes in the p-crAssphage genome to detect human fecal contamination of different water sources, with high specificity. Numerous investigations have examined the implications of crAss-like phages in diverse disease conditions, including ulcerative colitis, obesity and metabolic syndrome, autism spectrum disorders, rheumatoid arthritis, atopic eczema, and other autoimmune disorders. These studies have unveiled associations between certain diseases and diminished abundance and diversity of crAss-like phages. This review offers insights into the diverse aspects of research on crAss-like phages, including their discovery, genomic characteristics, structure, taxonomy, isolation, molecular detection, application as an MST marker, and role as a gut microbiome modulator with consequential health implications.