Natural Language Processing of Computed Tomography Reports to Label Metastatic Phenotypes With Prognostic Significance in Patients With Colorectal Cancer

PURPOSE

Natural language processing (NLP) applied to radiology reports can help identify clinically relevant M1 subcategories of patients with colorectal cancer (CRC). The primary purpose was to compare the overall survival (OS) of CRC according to American Joint Committee on Cancer TNM staging and explore an alternative classification. The secondary objective was to estimate the frequency of metastasis for each organ.

METHODS

Retrospective study of CRC who underwent computed tomography (CT) chest, abdomen, and pelvis between July 1, 2009, and March 26, 2019, at a tertiary cancer center, previously labeled for the presence or absence of metastasis by an NLP prediction model. Patients were classified in M0, M1a, M1b, and M1c (American Joint Committee on Cancer), or an alternative classification on the basis of the metastasis organ number: M1, single; M2, two; M3, three or more organs. Cox regression models were used to estimate hazard ratios; Kaplan-Meier curves were used to visualize survival curves using the two M1 subclassifications.

RESULTS

Nine thousand nine hundred twenty-eight patients with a total of 48,408 CT chest, abdomen, and pelvis reports were included. On the basis of NLP prediction, the median OS of M1a, M1b, and M1c was 4.47, 1.72, and 1.52 years, respectively. The median OS of M1, M2, and M3 was 4.24, 2.05, and 1.04 years, respectively. Metastases occurred most often in liver (35.8%), abdominopelvic lymph nodes (32.9%), lungs (29.3%), peritoneum (22.0%), thoracic nodes (19.9%), bones (9.2%), and pelvic organs (7.5%). Spleen and adrenal metastases occurred in < 5%.

CONCLUSION

NLP applied to a large radiology report database can identify clinically relevant metastatic phenotypes and be used to investigate new M1 substaging for CRC. Patients with three or more metastatic disease organs have the worst prognosis, with an OS of 1 year.

Association between remote monitoring and acute care visits in high-risk patients initiating intravenous antineoplastic therapy

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Background: Acute care visits (emergency department [ED] visits or inpatient admissions) for patients with cancer are growing disproportionately. Traditional oncology care models have not effectively identified and managed at-risk patients to prevent acute care. A next step is to harness advances in technology and mobile applications to enable patients to report symptoms any time, enabling “digital hovering” - intensive monitoring and management of high-risk patients. Our objective was to evaluate a digital platform that identifies and remotely monitors high-risk patients initiating intravenous antineoplastic therapy with the goal of preventing unnecessary acute care visits. Methods: This was a single-institution matched cohort quality improvement study conducted at an NCI-designated cancer center between January 1, 2019 and March 31, 2020. Eligible patients were those initiating intravenous antineoplastic therapy who were identified as high-risk for seeking acute care. Patients were identified as high-risk for an acute care visit by their oncologist with decision support from a web-based machine learning model. Enrolled patients’ symptoms were monitored using a digital platform. The platform is integrated into the EMR and includes: 1) a secure patient portal enabling communication and daily delivery of electronic patient-reported outcomes symptom assessments; 2) clinical alerts for concerning symptoms; and 3) a symptom trending application. A dedicated team of registered nurses and nurse practitioners managed reported symptoms. These clinicians acted as an extension of the primary oncology team, assisting with patient management exclusively through the platform. The primary outcomes evaluated were incidence of ED visits and inpatient admissions within six months of intravenous antineoplastic initiation. Results: Eighty-one high-risk patients from the intervention arm were matched by stage and disease with contemporaneous high-risk control patients. Matched cohorts had similar baseline characteristics, including age, sex, race, and treatment. ED visits and hospitalizations within six months of treatment initiation were analyzed using cumulative incidence analyses with a competing risk of death. The cumulative incidence of an ED visit for the intervention cohort was 0.27 (95% CI: 0.17, 0.37) at six months compared to 0.47 (95% CI: 0.36, 0.58) in the control group (p = 0.01). The cumulative incidence of an inpatient admission was 0.23 (95% CI: 0.14, 0.33) in the intervention group versus 0.41 (95% CI: 0.30, 0.51) in the control group (p = 0.02). Conclusions: The narrow employment of technology solutions to complex care delivery challenges in oncology can improve outcomes and innovate care. This program was a first step in using a digital platform and a remote team to improve symptom care in the home for high-risk patients.

A standardised template for reporting lower limb kinematic waveform movement compensations from a sensor-based portable clinical movement analysis toolkit

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Standardised terminology for the interpretation of movement analysis waveforms is provided, to describe the amount, nature and timing of a compensation strategy.

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A stand-alone application have been created for users to generate a movement analysis report for lower limb joint kinematics.

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A digital, interactive version of the movement analysis report is now being created in the next iteration of the sensor based portable movement analysis toolkit.

Objectives

To develop a standardised template to support physiotherapist reporting of lower limb kinematic waveform data

Design

Within and between user agreement identification of movement compensation strategies.

Setting

University Health Board Physiotherapy Department

Participants

Fourteen individuals with anterior cruciate ligament reconstruction performed overground gait, double-leg squat, and stair ascent wearing body-worn sensors. Six users viewed 252 kinematic waveforms of hip, knee and ankle joint angles in the sagittal and frontal planes.

Main outcome measures

Between and within-user observed agreement and themes from movement analysis reports

Results

Between-user observed agreement for presence of a movement compensation was 0.6–0.9 for the sagittal plane and 0.75–1.0 for the frontal place. Within-user observed agreement was 0.57–1.00 for the sagittal plane and 0.71–1.00 for the frontal plane. Three themes and seven categories were identified from the waveform interpretations: Amount (qualitative and quantitative description), timing (phase, discrete time point, cycle), and nature (peak, range of motion, timing) of the compensation.

Conclusion

There was good agreement between users at identifying the presence of movement compensation from the kinematic waveforms, but there was variation in how movement compensations were described. An interactive report, a standardised template for interpretation of kinematic waveforms, and training to support the clinical application of a movement analysis toolkit are proposed.

Analysis of a Remote Monitoring Program for Symptoms Among Adults With Cancer Receiving Antineoplastic Therapy

IMPORTANCE

Electronic patient-reported outcomes (ePROs) may have the potential to improve cancer care delivery by enhancing patient quality of life, reducing acute care visits, and extending overall survival. However, the optimal cadence of ePRO assessments is unknown.

OBJECTIVE

To determine patient response preferences and the clinical value associated with a daily cadence for ePROs for patients receiving antineoplastic treatment.

DESIGN, SETTING, AND PARTICIPANTS

This quality improvement study of adult patients undergoing antineoplastic treatment assessed a remote monitoring program using ePROs that was developed to manage cancer therapy-related symptoms. ePRO data submitted between October 16, 2018 to February 29, 2020, from a single regional site within the Memorial Sloan Kettering Cancer Center network were included. Data were analyzed from April 2020 to January 2022.

EXPOSURE

While undergoing active treatment, patients received a daily ePRO assessment that, based on patient responses, generated yellow (moderate) or red (severe) symptom alerts that were sent to clinicians.

MAIN OUTCOMES AND MEASURES

The main outcomes assessed included patient response rate, symptom alert frequency, and an analysis of the clinical value of daily ePROs.

RESULTS

A total of 217 patients (median [range] age, 66 [31-92] years; 103 [47.5%] women and 114 [52.5%] men) initiating antineoplastic therapy at high risk for symptoms were monitored for a median (range) of 91 (2-369) days. Most patients had thoracic (59 patients [27.2%]), head and neck (48 patients [22.1%]), or gastrointestinal (43 patients [19.8%]) malignant neoplasms. Of 14 603 unique symptom assessments completed, 7349 (50.3%) generated red or yellow symptom alerts. Symptoms commonly generating alerts included pain (665 assessments [23.0%]) and functional status (465 assessments [16.1%]). Most assessments (8438 assessments [57.8%]) were completed at home during regular clinic hours (ie, 9 am-5 pm), with higher response rates on weekdays (58.4%; 95% CI, 57.5%-59.5%) than on weekend days (51.3%; 95% CI, 49.5%-53.1%). Importantly, 284 of 630 unique red alerts (45.1%) surfaced without a prior yellow alert for the same symptom within the prior 7 days; symptom severity fluctuated over the course of a week, and symptom assessments generating a red alert were followed by an acute care visit within 7 days 8.7% of the time compared with 2.9% for assessments without a red alert.

CONCLUSIONS AND RELEVANCE

These findings suggest that daily ePRO assessments were associated with increased insight into symptom management in patients undergoing antineoplastic treatment and symptom alerts were associated with risk of acute care.

Natural Language Processing of Large-Scale Structured Radiology Reports to Identify Oncologic Patients With or Without Splenomegaly Over a 10-Year Period

PURPOSE

To assess the accuracy of a natural language processing (NLP) model in extracting splenomegaly described in patients with cancer in structured computed tomography radiology reports.

METHODS

In this retrospective study between July 2009 and April 2019, 3,87,359 consecutive structured radiology reports for computed tomography scans of the chest, abdomen, and pelvis from 91,665 patients spanning 30 types of cancer were included. A randomized sample of 2,022 reports from patients with colorectal cancer, hepatobiliary cancer (HB), leukemia, Hodgkin lymphoma (HL), and non-HL patients was manually annotated as positive or negative for splenomegaly. NLP model training/testing was performed on 1,617/405 reports, and a new validation set of 400 reports from all cancer subtypes was used to test NLP model accuracy, precision, and recall. Overall survival was compared between the patient groups (with and without splenomegaly) using Kaplan-Meier curves.

RESULTS

The final cohort included 3,87,359 reports from 91,665 patients (mean age 60.8 years; 51.2% women). In the testing set, the model achieved accuracy of 92.1%, precision of 92.2%, and recall of 92.1% for splenomegaly. In the validation set, accuracy, precision, and recall were 93.8%, 92.9%, and 86.7%, respectively. In the entire cohort, splenomegaly was most frequent in patients with leukemia (32.5%), HB (17.4%), non-HL (9.1%), colorectal cancer (8.5%), and HL (5.6%). A splenomegaly label was associated with an increased risk of mortality in the entire cohort (hazard ratio 2.10; 95% CI, 1.98 to 2.22; P < .001).

CONCLUSION

Automated splenomegaly labeling by NLP of radiology report demonstrates good accuracy, precision, and recall. Splenomegaly is most frequently reported in patients with leukemia, followed by patients with HB.

Patterns of Metastatic Disease in Patients with Cancer Derived from Natural Language Processing of Structured CT Radiology Reports over a 10-year Period

Background Patterns of metastasis in cancer are increasingly relevant to prognostication and treatment planning but have historically been documented by means of autopsy series. Purpose To show the feasibility of using natural language processing (NLP) to gather accurate data from radiology reports for assessing spatial and temporal patterns of metastatic spread in a large patient cohort. Materials and Methods In this retrospective longitudinal study, consecutive patients who underwent CT from July 2009 to April 2019 and whose CT reports followed a departmental structured template were included. Three radiologists manually curated a sample of 2219 reports for the presence or absence of metastases across 13 organs; these manually curated reports were used to develop three NLP models with an 80%-20% split for training and test sets. A separate random sample of 448 manually curated reports was used for validation. Model performance was measured by accuracy, precision, and recall for each organ. The best-performing NLP model was used to generate a final database of metastatic disease across all patients. For each cancer type, statistical descriptive reports were provided by analyzing the frequencies of metastatic disease at the report and patient levels. Results In 91 665 patients (mean age ± standard deviation, 61 years ± 15; 46 939 women), 387 359 reports were labeled. The best-performing NLP model achieved accuracies from 90% to 99% across all organs. Metastases were most frequently reported in abdominopelvic (23.6% of all reports) and thoracic (17.6%) nodes, followed by lungs (14.7%), liver (13.7%), and bones (9.9%). Metastatic disease tropism is distinct among common cancers, with the most common first site being bones in prostate and breast cancers and liver among pancreatic and colorectal cancers. Conclusion Natural language processing may be applied to cancer patients' CT reports to generate a large database of metastatic phenotypes. Such a database could be combined with genomic studies and used to explore prognostic imaging phenotypes with relevance to treatment planning. © RSNA, 2021 Online supplemental material is available for this article.

A Nonproprietary Movement Analysis System (MoJoXlab) Based on Wearable Inertial Measurement Units Applicable to Healthy Participants and Those With Anterior Cruciate Ligament Reconstruction Across a Range of Complex Tasks: Validation Study

Background

Movement analysis in a clinical setting is frequently restricted to observational methods to inform clinical decision making, which has limited accuracy. Fixed-site, optical, expensive movement analysis laboratories provide gold standard kinematic measurements; however, they are rarely accessed for routine clinical use. Wearable inertial measurement units (IMUs) have been demonstrated as comparable, inexpensive, and portable movement analysis toolkits. MoJoXlab has therefore been developed to work with generic wearable IMUs. However, before using MoJoXlab in clinical practice, there is a need to establish its validity in participants with and without knee conditions across a range of tasks with varying complexity.

Objective

This paper aimed to present the validation of MoJoXlab software for using generic wearable IMUs for calculating hip, knee, and ankle joint angle measurements in the sagittal, frontal, and transverse planes for walking, squatting, and jumping in healthy participants and those with anterior cruciate ligament (ACL) reconstruction.

Methods

Movement data were collected from 27 healthy participants and 20 participants with ACL reconstruction. In each case, the participants wore seven MTw2 IMUs (Xsens Technologies) to monitor their movement in walking, jumping, and squatting tasks. The hip, knee, and ankle joint angles were calculated in the sagittal, frontal, and transverse planes using two different software packages: Xsens’ validated proprietary MVN Analyze and MoJoXlab. The results were validated by comparing the generated waveforms, cross-correlation (CC), and normalized root mean square error (NRMSE) values.

Results

Across all joints and activities, for data of both healthy and ACL reconstruction participants, the CC and NRMSE values for the sagittal plane are 0.99 (SD 0.01) and 0.042 (SD 0.025); 0.88 (SD 0.048) and 0.18 (SD 0.078) for the frontal plane; and 0.85 (SD 0.027) and 0.23 (SD 0.065) for the transverse plane (hip and knee joints only). On comparing the results from the two different software systems, the sagittal plane was very highly correlated, with frontal and transverse planes showing strong correlation.

Conclusions

This study demonstrates that nonproprietary software such as MoJoXlab can accurately calculate joint angles for movement analysis applications comparable with proprietary software for walking, squatting, and jumping in healthy individuals and those following ACL reconstruction. MoJoXlab can be used with generic wearable IMUs that can provide clinicians accurate objective data when assessing patients’ movement, even when changes are too small to be observed visually. The availability of easy-to-setup, nonproprietary software for calibration, data collection, and joint angle calculation has the potential to increase the adoption of wearable IMU sensors in clinical practice, as well as in free living conditions, and may provide wider access to accurate, objective assessment of patients’ progress over time.

A framework for building a clinically relevant risk model

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Background: Acute care accounts for half of cancer expenditures and is a measure of poor quality care. Identifying patients at high risk for emergency department (ED) visits enables institutions to target resources to those most likely to benefit. Risk stratification models developed to date have not been meaningfully employed in oncology, and there is a need for clinically relevant models to improve patient care. Methods: We established and applied a predictive framework for clinical use with attention to modeling technique, clinician feedback, and application metrics. The model employs electronic health record data from initial visit to first antineoplastic administration for patients at our institution from January 2014 to June 2017. The binary dependent variable is occurrence of an ED visit within the first 6 months of treatment. The final regularized multivariable logistic regression model was chosen based on clinical and statistical significance. In order to accommodate for the needs to the program, parameter selection and model calibration were optimized to suit the positive predictive value of the top 25% of observations as ranked by model-determined risk. Results: There are 5,752 antineoplastic administration starts in our training set, and 1,457 in our test set. The positive predictive value of this model for the top 25% riskiest new start antineoplastic patients is 0.53. From over 1,400 data features, the model was refined to include 400 clinically relevant ones spanning demographics, pathology, clinician notes, labs, medications, and psychosocial information. At the patient level, specific features determining risk are surfaced in a web application, RiskExplorer, to enable clinician review of individual patient risk. This physician facing application provides the individual risk score for the patient as well as their quartile of risk when compared to the population of new start antineoplastic patients. For the top quartile of patients, the risk for an ED visit within the first 6 months of treatment is greater than or equal to 49%. Conclusions: We have constructed a framework to build a clinically relevant risk model. We are now piloting it to identify those likely to benefit from a home-based, digital symptom management intervention.

Employing electronic health record data to predict risk of ED visits for new patients

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Background: Acute care accounts for half of cancer expenditures and is a measure of poor quality care. Identifying patients at high risk for ED visits enables institutions to target symptom management resources to those most likely to benefit. Risk stratification models developed to date have not been meaningfully employed in oncology, and there is a need for clinically relevant models to improve patient care. Methods: We established a predictive analytics framework for clinical use with attention to the modeling technique, clinician feedback, and application metrics. The model employs EHR data from initial visit to first antineoplastic administration for new patients at our institution from January 2014 to June 2017. The binary dependent variable is occurrence of an ED visit within the first 6 months of treatment. From over 1,400 data features, the model was refined to include 400 clinically relevant ones spanning demographics, pathology, clinician notes, labs, medications, and psychosocial information. Clinician review was performed to confirm EHR data input validity. The final regularized multivariate logistic regression model was chosen based on clinical and statistical significance. Parameter selection and model evaluation utilized the positive predictive value for the top 25% of observations ranked by model-determined risk. The final model was evaluated using a test set containing 20% of randomly held out data. The model was calibrated based on a 5-fold cross-validation scheme over the training set. Results: There are 5,752 antineoplastic starts in our training set, and 1,457 in our test set. The positive predictive value of this model for the top 25% riskiest new start antineoplastic patients is 0.53. The 400 clinically relevant features draw from multiple areas in the EHR. For example, those features found to increase risk include: combination chemotherapy, low albumin, social work needs, and opioid use, whereas those found to decrease risk include stage 1 disease, never smoker status, and oral antineoplastic therapy. Conclusions: We have constructed a framework to build a clinically relevant model. We are now piloting it to identify those likely to benefit from a home-based, digital symptom management intervention.

Employing electronic health record data to predict risk of emergency department visits for new patients

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Background: Acute care accounts for half of cancer expenditures and is a measure of poor quality care. Identifying patients at high risk for ED visits enables institutions to target symptom management resources to those most likely to benefit. Risk stratification models developed to date have not been meaningfully employed in oncology, and there is a need for clinically relevant models to improve patient care. Methods: We established a predictive analytics framework for clinical use with attention to the modeling technique, clinician feedback, and application metrics. The model employs EHR data from initial visit to first antineoplastic administration for new patients at our institution from January 2014 to June 2017. The binary dependent variable is occurrence of an ED visit within the first 6 months of treatment. From over 1,400 data features, the model was refined to include 400 clinically relevant ones spanning demographics, pathology, clinician notes, labs, medications, and psychosocial information. Clinician review was performed to confirm EHR data input validity. The final regularized multivariate logistic regression model was chosen based on clinical and statistical significance. Parameter selection and model evaluation utilized the positive predictive value for the top 25% of observations ranked by model-determined risk. The final model was evaluated using a test set containing 20% of randomly held out data. The model was calibrated based on a 5-fold cross-validation scheme over the training set. Results: There are 5,752 antineoplastic starts in our training set, and 1,457 in our test set. The positive predictive value of this model for the top 25% riskiest new start antineoplastic patients is 0.53. The 400 clinically relevant features draw from multiple areas in the EHR. For example, those features found to increase risk include: combination chemotherapy, low albumin, social work needs, and opioid use, whereas those found to decrease risk include stage 1 disease, never smoker status, and oral antineoplastic therapy. Conclusions: We have constructed a framework to build a clinically relevant model. We are now piloting it to identify those likely to benefit from a home-based, digital symptom management intervention.

Misery Loves Company: Presenting Symptom Clusters to Urgent Care by Patients Receiving Antineoplastic Therapy

PURPOSE

The Centers for Medicare & Medicaid Services (CMS) identifies suboptimal management of treatment toxicities as a care gap and proposes the measurement of hospital performance on the basis of emergency department visits for 10 common symptoms. Current management strategies do not address symptom co-occurrence.

METHODS

We evaluated symptom co-occurrence in three patient cohorts that presented to a cancer hospital urgent care center in 2016. We examined both the CMS-identified symptoms and an expanded clinician-identified set defined as symptoms that could be safely managed in the outpatient setting if identified early and managed proactively. The cohorts included patients who presented with a CMS-defined symptom within 30 days of treatment, patients who presented within 30 days of treatment with a symptom from the expanded set, and patients who presented with a symptom from the expanded set within 30 days of treatment start. Symptom co-occurrence was measured by Jaccard index. A community detection algorithm was used to identify symptom clusters on the basis of a random walk process, and network visualizations were used to illustrate symptom dynamics.

RESULTS

There were 6,429 presentations in the CMS symptom-defined cohort. The network analysis identified two distinct symptom clusters centered around pain and fever. In the expanded symptom cohort, there were 5,731 visits and six symptom clusters centered around fever, emesis/nausea, fatigue, deep vein thrombosis, pain, and ascites. For patients who newly initiated treatment, there were 1,154 visits and four symptom clusters centered around fever, nausea/emesis, fatigue, and deep vein thrombosis.

CONCLUSION

Uncontrolled symptoms are associated with unplanned acute care. Recognition of the complexity of symptom co-occurrence can drive improved management strategies.

Integrating self-management support for knee injuries into routine clinical practice: TRAK intervention design and delivery

BACKGROUND

TRAK is a web-based intervention that provides knee patients with health information, personalised exercise plans and remote clinical support. The aim of this study was to fully define TRAK intervention content, setting and context and develop the training through an implementation study in a physiotherapy out-patient service.

METHODS

A mixed methods study. Phase 1 was a qualitative interview study, whereby fifteen physiotherapists used TRAK for 1 month with a patient of their choice. Interviews explored patient and physiotherapist views of TRAK intervention and training requirements. In Phase 2 seventy-four patients were recruited, all received conventional physiotherapy, a subset of 48 patients used TRAK in addition to conventional Physiotherapy. Aspects of feasibility measured included: uptake and usage of TRAK.

RESULTS

Patients and physiotherapists reported that TRAK was easy to use and highlighted the therapeutic benefit of the exercise videos and personalised exercise plans to remind them of their exercises and the correct technique. Patients reported needing to use TRAK with the guidance of their treating physiotherapist initially. Physiotherapists highlighted appointment time constraints and lack of familiarity with TRAK as factors limiting engagement. In Phase 2, 67% patients accessed TRAK outside of the clinical environment. A total of 91% of patients were given a personalised exercise plan, but these were only updated in 34% of cases.

CONCLUSION

A comprehensive training package for patients and clinicians has been defined. The refined TRAK intervention is reported using the 'Template for Intervention Description and Replication in preparation for a definitive randomised control trial.

CD14 and TLR4 are expressed early in tammar (Macropus eugenii) neonate development

Marsupials are born in a relatively underdeveloped state and develop during a period of intensive maturation in the postnatal period. During this period, the young marsupial lacks a competent immune system, but manages to survive despite the potential of exposure to environmental pathogens. Passive immune transfer via the milk is one well-recognised strategy to compensate the neonate, but there also may be innate immune mechanisms in place. In this study, CD14 and Toll-like receptor 4 (TLR4), integral molecular components of pathogen recognition, were identified and characterised for the first time in a marsupial, the tammar wallaby (Macropus eugenii). Functional motifs of tammar CD14 and the toll/interleukin receptor (TIR) domain of TLR4 were highly conserved. The lipopolysaccharide (LPS) binding residues and the TLR4 interaction site of CD14 were conserved in all marsupials. The TIR signalling domain had 84% identity within marsupials and 77% with eutherians. Stimulation of adult tammar leukocytes resulted in the induction of a biphasic pattern of CD14 and TLR4 expression, and coincided with increased production of the pro-inflammatory cytokine TNF-alpha. Differential patterns of expression of CD14 and TLR4 were observed in tammar pouch young early in development, suggesting that early maturation of the innate immune system in these animals may have developed as an immune survival strategy to protect the marsupial neonate from exposure to microbial pathogens.

Comparative modeling of marsupial MHC class I molecules identifies structural polymorphisms affecting functional motifs

Major histocompatibility complex (MHC) class I molecules are transmembrane glycoproteins that present antigenic peptides to CD8+ T cells and are subsequently important for the initiation of an immune response. In this study novel MHC class I sequences from the tammar wallaby (Macropus eugenii) have been characterized. Analysis and comparative modeling of these and existing marsupial molecules reveals potential functional polymorphisms within peptide-binding grooves, MHC assembly motifs and the T cell receptor recognition interface. In addition, we show that a previously identified marsupial-specific insertion is within a region, which is known as a putative NK cell receptor (Ly49A) binding site in the mouse, suggesting that this site may be functionally active in marsupials. Further, the analysis highlighted differences in structural and sequence based grouping of marsupial MHC class I molecules.

Characterization and expression of Peroxiredoxin 1 in the neonatal tammar wallaby (Macropus eugenii)

Peroxiredoxin 1 (PRDX1) is a ubiquitously expressed antioxidant with vital roles in basal metabolic functions. In addition PRDX1 is involved in cell differentiation and proliferation, apoptosis and innate immunity. In this study, we have characterized PRDX1 from the tammar wallaby (Macropus eugenii). Tammar PRDX1 has high conservation of functional residues and motifs, and demonstrates a close homology with eutherian and vertebrate orthologues. Stimulation of adult tammar leukocytes with lipopolysaccharide and lipoteichoic acid suggests a role for PRDX1 in innate immune defences. PRDX1 expression in the organs of tammar pouch young was mildly elevated early in life possibly reflecting its role in basal metabolic processes. Later increases in PRDX1 expression correlated with functional maturation of several immune organs or with preparation for increased oxidative stress of emergence. The findings of the study are reflections of the complex integrated roles that PRDX1 has in regulation of oxidative stress, apoptosis, cell differentiation and proliferation, and innate immunity.

Analysis of the expression of immunoglobulins throughout lactation suggests two periods of immune transfer in the tammar wallaby (Macropus eugenii)

Marsupial young are born in an under-developed state without mature immune responses. Prior to the maturation of an immune system, marsupial young are heavily reliant upon immune factors secreted in the milk to defend them against potential microbial pathogens in the environment. In this study, we identified and characterized the immunoglobulin heavy chain constant regions, light chains, polymeric Ig receptor (pIgR), J chain, neonatal Fc receptor (alpha chain) (FcRn) and the chemokine CCL28 from the model marsupial species, the tammar wallaby (Macropus eugenii). Low levels of conservation were seen in motifs in C alpha and C gamma associated with receptor binding and or transcytosis, and this may have potential implications for functionality. We evaluated the expression of immunoglobulin genes in the tammar mammary gland throughout lactation and found that two periods of increased expression of immunoglobulin genes occur. These two periods coincide with the birth of the young, and with its first emergence from the pouch. This increased expression may represent a strategy for maternal immunological protection of the pouch young.

A quantitative study of the morphological development and bacterial colonisation of the gut of the tammar wallaby Macropus eugenii eugenii and brushtail possum Trichosurus vulpecula during in-pouch development

We compared the rates of change of various morphological parameters of the stomach, small intestine, caecum and colon of tammar wallabies and brushtail possums with body mass during in-pouch development. These were correlated with changes in the numbers of bacterial species in the various gut segments. In the pouch-young of both species, the wet tissue masses of all gut segments increased with body mass in a positively allometric manner (i.e. with a body mass exponent > 1), suggesting that the mass of each component was disproportionately low at birth, but increased disproportionately rapidly postnatally. However, the lengths of the wallaby stomach and small intestine scaled isometrically with respect to body mass (i.e. with a body mass exponent around 0.33), which may indicate that the shape of these components changes to the adult form during early neonatal development. Conversely, the length of the caecum and colon of both wallabies and possums scaled in a positively allometric manner with respect to body mass, showing area to volume compensation. This may indicate a more general pattern of disproportionately rapid postnatal enlargement in areas that are distal to the principal sites of neonatal digestion (i.e. the stomach). The numbers of bacterial species present in the various gastrointestinal segments of both species were low in animals aged 100 days or less but there was a significant increase in microbial diversity in the caecum of brushtail possums aged over 100 days. The possum caecum also showed the greatest rate of increase in wet tissue mass relative to body mass. It is postulated that caecal development may act as a nidus for establishment of communities of commensal microflora in the developing marsupial.

Cross-fostering inMacropus eugenii leads to increased weight but not accelerated gastrointestinal maturation

Stomach and small intestine development was characterized in tammar wallaby (Macropus eugenii) pouch young (PY) using both morphological and immunohistological criteria. At birth, the stomach is undeveloped in comparison to the well-developed intestinal mucosa. The stomach maintains a uniform morphology in both the forestomach and hindstomach regions until the specialization of cardiac and gastric glands are seen at PY170. Parietal cells, found throughout the mucosa are downregulated in the forestomach as cardiac glandular stomach is developing prior to the transition of the offspring to a diet that includes herbage. In the small intestine, mature-type villi are present at birth but the muscularis externa is immature and undergoes significant development around PY120 onwards. We investigated the effects of changes in maternal milk on gut development in the tammar wallaby using a cross fostering approach that provided younger pouch young with older stage milk. Younger PY (average age 67 days postpartum, n = 5) were transferred onto teats vacated by older stage PY (average age 100 days postpartum, n = 6) for 34 days before gut development was assessed. In addition milk analysis was performed before and after fostering events. Cross-fostered PY animals receiving older stage milk were found to be 31% heavier than controls. There was no difference between carbohydrate and protein concentrations however, fostered PY milk had a higher concentration of lipid than that of controls that may have contributed to heavier fostered PY. No difference was found in stomach or small intestine development between these groups using the criteria employed in this study.

Low grade gliomas treated with adjuvant radiation therapy in the modern imaging era

The purpose of this study is to evaluate tumor control and failure patterns in patients with low grade gliomas treated with surgery and conventional adjuvant radiation therapy. Twenty-eight patients with low grade gliomas (7 grade I, 21 grade II) were retrospectively evaluated. Extent of resection was gross total (3), subtotal (17), and biopsy alone (8). All grade I tumors underwent subtotal resection. Median radiation therapy dose was 54 Gy delivered to localized fields. Tumor control and patterns of failure were determined from follow-up computed tomography and/or magnetic resonance scans. Median follow-up was 86 months (range, 2.4-177 months). Thirteen patients (46%) (four grade I, nine grade II) developed tumor progression. The 5-year actuarial progression-free survival rates for grade I and grade II patients were 86% and 51%, respectively. Corresponding 5-year actuarial survival rates were 100% and 70%. All recurrences were within the treated volume. Our results reveal that conventional adjuvant radiation therapy is associated with high rates of local tumor progression in both grade II and incompletely resected grade I low grade gliomas. Alternative strategies need to be explored in these patients in an effort to improve tumor control and outcome.

Developmentally-regulated expression of a putative protease inhibitor gene in the lactating mammary gland of the tammar wallaby, Macropus eugenii

A novel milk protein, which is secreted only in the early stage of lactation, has been identified in the whey fraction of milk from the tammar wallaby (Macropus eugenii). The amino acid sequence currently available suggests the protein comprises 71 amino acids. The protein migrates at 18 kDa when analysed by SDS polyacrylamide gel electrophoresis but has a calculated molecular weight of 8 kDa. A partial cDNA clone of 153 bp has been isolated by reverse transcriptase PCR. Northern analysis of mammary gland RNA extracted from various stages throughout the entire lactation period showed a messenger RNA transcript of approximately 500 bp present only in the first third of lactation. The protein shares 74.5% similarity at the amino acid level with early lactation protein (ELP) from the brush-tailed possum (Trichosurus vulpecula) and 37% with bovine colostrum trypsin inhibitor, a member of the Kunitz family of protease inhibitors. We hypothesise that the expression of this gene may be controlled by changes in the sucking patterns of the dependent pouch young.

Molecular characterisation and hormone-dependent expression of the porcine whey acidic protein gene

A 17.5 kDa protein was isolated from porcine whey by reverse phase HPLC and identified as a putative whey acidic protein (WAP) homologue by sequencing 35 and 40 amino acid residues of the amino- and carboxy-terminus respectively. Degenerate oligonucleotides to both of these amino acid sequences were designed and used in reverse transcriptase PCR with RNA from lactating porcine mammary gland as a template. A 162 bp PCR fragment was detected and sequenced. Compilation of the deduced and determined amino acid sequence revealed a protein of 111 amino acids, which had approximately 75, 50, 40 and 35% similarity at amino acid level to camel, rabbit, rat and mouse WAP respectively. It also included the four-disulphide core characteristic of all WAP proteins and most Kunitz-type protease inhibitors. This provides the first unequivocal evidence for WAP secretion in the pig. SDS PAGE analysis of the whey fraction showed that WAP is secreted as a major protein in sow's milk from farrowing to weaning. The molecular mass of WAP in SDS PAGE was significantly greater than the 11.7 kDa determined from amino acid sequence, indicating that porcine WAP is possibly glycosylated. Northern analysis detected a single mRNA transcript of approximately 600 bp in porcine RNA from the mammary gland of lactating sows. To examine the hormone-regulated expression of the WAP gene the mammary glands of sows at day 90 of pregnancy were biopsied and explants cultured for 3 days in the presence of various combinations of porcine insulin (I), cortisol (F) and porcine prolactin (P). Northern analysis of RNA extracted from the tissue indicated that WAP gene expression was barely detectable in the mammary gland prior to culture and there was no increment in explants cultured in the presence of I and F. However, a significant increase in the accumulation of WAP mRNA was observed in explants cultured in I, F and P. A similar result was observed for beta-casein and alpha-lactalbumin gene expression.

The tammar wallaby: a model to study putative autocrine-induced changes in milk composition

The marsupial newborn is immature and the mother has the capacity to alter milk composition significantly during lactation, presumably to meet the nutritional requirements of the developing young. Furthermore, macropodid marsupials may practice asynchronous concurrent lactation (ACL)7 whereby the mother provides milk which differs in all the major components from adjacent mammary glands for two young of different ages. This phenomenon suggests that local regulation of mammary function, in addition to endocrine stimuli, is likely to be important for controlling milk composition. This paper explores the possibility that changes in sucking patterns of the young represent the first step in a mechanism to signal the mammary gland for putative autocrine-induced changes in milk composition.

Prolactin-independent induction of alpha-lactalbumin gene expression in mammary gland explants from pregnant Balb/c mice

A four-fold increment of alpha-lactalbumin mRNA was induced in mammary gland explants from mid-pregnant Balb/c mice cultured for 24h in media containing insulin, cortisol and T3, and this response was enhanced by 40% with the addition of prolactin. In contrast, elevated beta-casein gene expression was evident only in explants cultured in media with insulin, cortisol, T3 and prolactin. These results suggest that the induction of the alpha-lactalbumin gene was prolactin-independent and did not result from retention of endogenous prolactin, or its effects, by the mammary explants.

Manual verification of computer analysis of 24-hour esophageal motility

The application of solid-state technology to intraesophageal pressure monitoring over an entire circadian cycle has resulted in large amounts of data that require computer analysis. Recently available commercial software has yet to be validated. The aim of this study was to compare the analysis of ambulatory esophageal manometry by an automated computer program with manual analysis and make the software modifications necessary to validate the automated system for clinical use. Computer-aided analysis of a large number of esophageal contractions recorded during ambulatory esophageal manometry was compared with manual analysis by four experienced physicians. Good correlations were found between manual and computerized measurements of contraction amplitude and duration (r = 0.99 and r = 0.73, respectively). Software modifications resulted in correct identification of 94% of contractions and correct classification of 93.3% of these waves as peristaltic or simultaneous. These results demonstrate that the evaluated program for automated analysis of ambulatory esophageal manometry is accurate and reliable for research and clinical applications.

Molecular characterization and in-vitro hormonal requirements for expression of two casein genes from a marsupial

Two marsupial casein genes have been isolated from a tammar wallaby (Macropus eugenii) mammary gland cDNA library. Comparisons of the tammar alpha- and beta-casein genes with their eutherian homologous reveal extensive divergence at the levels of nucleotide and amino acid sequences. Regions of similarity between the tammar and eutherian Ca(2+)-sensitive caseins are restricted to the major phosphorylation sites and the signal peptides. Quantification of casein mRNA levels in hormone-stimulated mammary gland explants from tammars in late pregnancy suggests that maximal induction of the beta-casein gene is dependent upon prolactin and insulin, while maximal induction of the alpha-casein gene is dependent upon prolactin, insulin and cortisol. These results are in contrast to earlier studies which show that the maximal induction of a putative 19 kDa casein, alpha-lactalbumin and beta-lactoglobulin in the tammar mammary gland is dependent upon prolactin alone. The expression of the latter three genes is not modulated by other hormones known to play a role in the in-vitro initiation of lactation in eutherians.

Detection of Norwalk-like virus and specific antibody by immune-electron microscopy with colloidal gold immune complexes

Direct electron-microscopy (DEM), immune electron microscopy (IEM) and four different procedures of immune electron microscopy with colloidal gold immune complexes were evaluated for the detection of Norwalk-like virus and specific antibody. A solid-phase immune electron microscopy with colloidal gold immune complexes-triple layer method (SPIEMGIC-TLM) is developed for screening patients' specimens for the detection of Norwalk-like virus and its specific antibody. The method demonstrates low non-specific background labelling and is simple, sensitive and easy to perform. A quadruple layer method (SPIEMGIC-QLM), which is a modification of the triple layer method, has been established by adding a cross-linking anti-IgG layer to amplify the reaction and to provide a more sensitive test which is suitable for screening monoclonal antibodies prepared against 32-34-nm Norwalk-like virus isolated in our laboratory.

A marsupial beta-lactoglobulin gene: characterization and prolactin-dependent expression

Analysis of the tammar wallaby beta-lactoglobulin cDNA and inferred amino acid sequences reveal extensive sequence divergence from the eutherian beta-lactoglobulins. Conserved residues include the cysteines and a number of individual amino acids involved in structure and ligand-binding. The only region of extended similarity is a heptapeptide sequence which may impart specificity to its interaction with a receptor protein. Northern analysis of total mammary RNA revealed two transcripts which result from differential utilization of polyadenylation signals. The concentration of beta-lactoglobulin mRNA increased in late lactation and correlates with increases in milk production and levels of milk fat. Quantification of beta-lactoglobulin mRNA levels in hormone-stimulated mammary gland explants from tammars in late pregnancy suggests that maximal induction of the gene is dependent on prolactin alone and that expression is not modulated by other hormones known to play a role in the initiation of lactation in eutherians.

A questionnaire survey of the prevalence of scrapie in sheep in Britain

An anonymous, self-administered questionnaire has been used in two independent surveys to try to determine the prevalence of scrapie in the national sheep flock. The disease was recorded in 35 counties in England and Wales. About a third (26.5 and 37.3 percent) of respondents owning 100 or more sheep indicated that they had seen sheep with scrapie in their flocks. The incidences of clinical cases recorded in affected flocks in the two surveys were 0.5 and 1.1 cases/100 ewes/year. At present there is no control over the disposal of these animals. If as has been suggested, an increase in the prevalence of scrapie was a contributory factor in the emergence of bovine spongiform encephalopathy, it would seem logical that measures should be introduced to monitor the prevalence and incidence of scrapie and to control the disposal of clinical cases.

Cloning, cDNA analysis and prolactin-dependent expression of a marsupial alpha-lactalbumin

The gene for alpha-lactalbumin has been cloned from a tammar wallaby (Macropus eugenii) mammary gland cDNA library. Tammar alpha-lactalbumin has approximately 50 and 30% homology to the alpha-lactalbumins of eutherians at the levels of nucleotide and protein sequence respectively. Comparison of the inferred tammar polypeptide sequence with the sequence of the eutherian proteins reveals extensive divergence at almost all of the non-essential amino acid residues. However, the hydropathy plots of the tammar protein are almost identical to those of eutherian alpha-lactalbumins, suggesting that protein conformation is conserved. The tammar gene encodes a transcript of approximately 975 bases. Northern blot analysis of hormone-stimulated mammary gland explants shows that maximal induction of alpha-lactalbumin mRNA is dependent on prolactin and that expression is not modulated by other hormones that play a role in the initiation of lactation in eutherians.

Molecular cloning and characterization of a novel marsupial milk protein gene

The tammar wallaby (Macropus eugenii) produces two different types of milk; "early" milk for the first 180 days and "late" milk for the remaining 150 days of lactation. We report the cloning of the cDNA of a novel whey protein, Late-Lactation Protein (LLP), which is produced during the late phase of lactation. The cDNA was cloned using an oligonucleotide probe deduced from the published partial protein sequence. The cDNA encodes an open-reading frame of 176 amino acids of which the first 18 residues represent a signal peptide. Northern blot analysis revealed a 1kb transcript in late phase lactation but not in the early phase.

Isolation, partial sequence and asynchronous appearance during lactation of lysozyme and alpha-lactalbumin in the milk of a marsupial, the common ringtail possum (Pseudocheirus peregrinus)

1. Lysozyme and alpha-lactalbumin from the milk of the common ringtail possum have been purified and partially sequenced. 2. The lysozyme had similar enzymic activity to the c-type lysozyme of the domestic hen and 43% homology over the N-terminal 49 residues. 3. alpha-Lactalbumin was present in the milk in two biologically active forms; the more acidic form had 66% sequence homology with the N-terminal 35 residues of red-necked wallaby, 54% with human and 43% with bovine alpha-lactalbumin. 4. SDS polyacrylamide-gel electrophoresis of milk samples showed that alpha-lactalbumin was present in the milk throughout lactation but that lysozyme first appeared only in mid-lactation. The implications of this functional adaptation are discussed.