bluuebunny/crossref_metadata_2025_split huggingface dataset:
1041 Recurrent Retropharyngeal Ganglioneuroma in a Pediatric Patient
Authors: Thanawala Mitali , Revana Amee 
Published: May 2023

Abstract

Introduction
Ganglioneuroma is a rare benign subtype of peripheral neuroblastic tumor that arises from sympathetic ganglion cells. Fewer than 10% of these cases occur in the head and neck and are rarely seen in pediatric patients. Clinical symptoms and treatment are dependent on mass location and extension. The authors present a case of recurrent retropharyngeal ganglioneuroma in a pediatric patient.

Report of case(s)
Patient is a 2-year-old previously healthy female who presented with progressive snoring and found to have retropharyngeal lymphadenopathy during tonsillectomy. Differential diagnosis included retropharyngeal abscess; however, after no improvement with antibiotics, malignancy was suspected. Pathology results from a needle biopsy confirmed the diagnosis of ganglioneuroma. CT imaging showed extension of mass to bilateral retropharyngeal, posterior mediastinal and paraspinal, and retroperitoneal spaces. Given concerns for significant morbidity with complete resection, patient underwent partial resection of mass, followed by chemotherapy to decrease tumor burden. Patient initially did well, then developed nine-month progressive snoring, positional apnea, persistent stertor, and dysphagia. Sleep study showed severe obstructive sleep apnea (OSA) with apnea hypopnea index (AHI) 74, oxygen nadir 66%, and maximum transcutaneous carbon dioxide (CO2) level of 58 mmHg. Repeat CT imaging showed regrowth of the tumor with large right-sided retropharyngeal mass, mass effect on right oropharynx and associated vasculature, and moderate narrowing of airway. Supplemental oxygen via nasal cannula was initiated as inpatient, due to concerns that noninvasive positive pressure support would further compromise the critical airway. Urgent repeat debulking of the tumor with partial pharyngectomy was completed. Post-operatively, patient's oxygen dependence, stertor, and positional apnea resolved within 24 hours. Repeat sleep study showed considerable improvement with mild OSA, AHI 1.4, oxygen nadir 89%, and maximum transcutaneous CO2 level of 47 mmHg. Her dysphagia and residual mild intermittent snoring are improving with no signs of recurrence of the mass.

Conclusion
Upper airway obstruction secondary to neck mass in pediatric patients is rare and even less commonly found to be recurrent ganglioneuroma. This case offers further understanding of the complexities of diagnosing and treating insidiously growing retropharyngeal tumors and the prompt management of critically obstructed airways.

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1042 Cognitive Behavioral Therapy for Insomnia (CBT-I) in Patient with Neurological Symptoms of Unclear Etiology
Authors: Tiani Alaina , Roth Alicia , Drerup Michelle , Kane Alexa 
Published: May 2023

Abstract

Introduction
For those experiencing neurological symptoms and being evaluated for multiple sclerosis (MS), it is important to assess whether sleep disturbance is primary or secondary to neurological disease. In this case, CBT-I was initiated to rule out a sleep disorder as an underlying cause of neurological symptoms.

Report of case(s)
The patient is a 61-year-old, White, female with chronic insomnia, excessive daytime sleepiness, and mild OSA comorbid with abnormal brain MRI (significant non-specific lesions). Patient is followed by neuroimmunology for management of neurological symptoms with unclear etiology (fatigue, paresthesia, neuropathic pain, and impaired cognition). She was referred to sleep medicine by her neurologist who suspected severe fatigue and sleepiness may be contributing to complex medical presentation. Patient endorsed a history of sleep-maintenance insomnia associated with drowsy driving (1 MVA and 3 near-misses). Of note, patient discontinued CPAP use for mild OSA in spring 2022 due to device recall. Her sleep physician recommended CBT-I to increase TST prior to OSA re-evaluation. Patient presented as anxious and distressed regarding safety while driving. She initiated CBT-I and engaged in stimulus control, cognitive restructuring, sleep diaries, relaxation, motivational interviewing, and supportive therapy. Baseline sleep diaries showed average WASO=146 minutes, SE=58%, and TST=4.1 hours. At week 7, average WASO=60 minutes, SE=86%, and TST=6.0 hours. Though no baseline measure was obtained, sleep disturbance (PROMIS Sleep T Score) was WNL (T=54) at week 7. Depression, anxiety, and pain-related disability decreased: PHQ-9 (11-moderate to 8-mild), GAD-7 (6-moderate to 4-mild), PDI (41 to 33). Measures of daytime sleepiness remained in the severe range (ESS 20 to 18), suggesting the need for OSA re-evaluation. Although sleep quality improved, patient reported new and worsening neurological symptoms including dysphagia and falls at home. CBT-I treatment is ongoing.

Conclusion
As individuals diagnosed with MS and other neurological disorders are more likely to experience insomnia than the general population, assessment of sleep disorders and evidenced-based treatments should be part of comprehensive neurological evaluation. In this case, the patient’s sleep parameters improved with CBT-I, but neurological symptoms persisted and worsened, suggesting the need for continued assessment and follow-up with neurology and sleep physicians.

Support (if any)
None.
Prospective Evaluation of a Dynamic Acuity Score for Regularly Assessing a Critically Ill Patient’s Risk of Mortality
Authors: Kramer Andrew A. , Krinsley James F. , Lissauer Matthew 
Published: May 2023

OBJECTIVE:
Predictive models developed for use in ICUs have been based on retrospectively collected data, which does not take into account the challenges associated with live, clinical data. This study sought to determine if a previously constructed predictive model of ICU mortality (ViSIG) is robust when using data collected prospectively in near real-time.

DESIGN:
Prospectively collected data were aggregated and transformed to evaluate a previously developed rolling predictor of ICU mortality.

SETTING:
Five adult ICUs at Robert Wood Johnson-Barnabas University Hospital and one adult ICU at Stamford Hospital.

PATIENTS:
One thousand eight hundred and ten admissions from August to December 2020.

MEASUREMENTS AND MAIN RESULTS:
The ViSIG Score, comprised of severity weights for heart rate, respiratory rate, oxygen saturation, mean arterial pressure, mechanical ventilation, and values for OBS Medical’s Visensia Index. This information was collected prospectively, whereas data on discharge disposition was collected retrospectively to measure the ViSIG Score’s accuracy. The distribution of patients’ maximum ViSIG Score was compared with ICU mortality rate, and cut points determined where changes in mortality probability were greatest. The ViSIG Score was validated on new admissions. The ViSIG Score was able to stratify patients into three groups: 0–37 (low risk), 38–58 (moderate risk), and 59–100 (high risk), with mortality of 1.7%, 12.0%, and 39.8%, respectively (p < 0.001). The sensitivity and specificity of the model to predict mortality for the high-risk group were 51% and 91%. Performance on the validation dataset remained high. There were similar increases across risk groups for length of stay, estimated costs, and readmission.

CONCLUSIONS:
Using prospectively collected data, the ViSIG Score produced risk groups for mortality with good sensitivity and excellent specificity. A future study will evaluate making the ViSIG Score visible to clinicians to determine whether this metric can influence clinician behavior to reduce adverse outcomes.
Prediction values of tertiary lymphoid structures in the prognosis of patients with left- and right-sided colon cancer: a multicenter propensity score-matched study
Authors: Mao Yonghuan , Wang Xingzhou , Xi Ling , Dong Meng , Song Peng , Miao Ji , Lu Cheng , Sun Sizheng , Li Qiang , Yu Chunzhao , Shen Xiaofei 
Published: May 2023

Background:
Tertiary lymphoid structures (TLS) are the lymphocyte aggregates that play a key role in the vast majority of solid tumors including colon cancer, displaying an anti-tumor effect under most circumstances. The heterogeneity between left- and right-sided colon cancer (LCC and RCC) encompasses various aspects, such as clinical manifestations, pathological features, and immune responses. However, the function and prognostic significance of TLS within LCC and RCC have yet to be fully understood.

Methods:
A retrospective analysis was performed on 2612 patients who underwent radical resection for LCC or RCC without distant metastasis in multiple medical centers. Utilizing propensity score matching, 121 patients with LCC and 121 patients with RCC were selected for the training set. An external validation set including 64 patients with LCC and 64 patients with RCC were also employed. Hematoxylin-eosin (H&E) and immunohistochemical (IHC) staining were used to assess TLS and the proportion of various immune cells. Clinical characteristics and prognostic values of TLS in patients with LCC and RCC were analyzed. Nomograms were constructed for LCC and RCC to predict 3-year and 5-year overall survival (OS), respectively.

Results:
For LCC and RCC patients, TLS was located in the interstitial region or outside the tumor tissue and mainly consisted of B cells and T cells. The TLS quantity and density in RCC were higher than those of LCC. In multivariate Cox regression analysis, TLS density (P=0.014), vascular invasion (P=0.019) and AJCC stage (P=0.026) were independent prognostic factors for 5-year OS of RCC. For LCC patients, AJCC stage (P=0.024), tumor differentiation (P=0.001), and tumor budding (P=0.040) emerged as independent prognostic factors for 5-year OS. Similar results were obtained in the external verification set. Separate nomograms for RCC and LCC were developed, displaying improved prediction performance compared to AJCC 8th edition TNM staging system.

Conclusions:
Differences in TLS quantity and density were observed between LCC and RCC, suggesting that a nomogram based on TLS density could more effectively predict survival for RCC patients. Furthermore, a nomogram based on tumor budding was recommended for better prediction of LCC patient survival. Taken together, these results suggested that the immune and clinical characteristics of colon cancer at left and right side were substantially different, which may lead to the use of different prediction model and the development of individual treatment strategy.
A framework for the detection and attribution of biodiversity change
Authors: Gonzalez Andrew , Chase Jonathan M. , O'Connor Mary I. 
Published: May 2023

The causes of biodiversity change are of great scientific interest and central to policy efforts aimed at meeting biodiversity targets. Changes in species diversity and high rates of compositional turnover have been reported worldwide. In many cases, trends in biodiversity are detected, but these trends are rarely causally attributed to possible drivers. A formal framework and guidelines for the detection and attribution of biodiversity change is needed. We propose an inferential framework to guide detection and attribution analyses, which identifies five steps—causal modelling, observation, estimation, detection and attribution—for robust attribution. This workflow provides evidence of biodiversity change in relation to hypothesized impacts of multiple potential drivers and can eliminate putative drivers from contention. The framework encourages a formal and reproducible statement of confidence about the role of drivers after robust methods for trend detection and attribution have been deployed. Confidence in trend attribution requires that data and analyses used in all steps of the framework follow best practices reducing uncertainty at each step. We illustrate these steps with examples. This framework could strengthen the bridge between biodiversity science and policy and support effective actions to halt biodiversity loss and the impacts this has on ecosystems.This article is part of the theme issue ‘Detecting and attributing the causes of biodiversity change: needs, gaps and solutions’.
Theory and application of an improved species richness estimator
Authors: Tekwa Eden W. , Whalen Matthew A. , Martone Patrick T. , O'Connor Mary I. 
Published: May 2023

Species richness is an essential biodiversity variable indicative of ecosystem states and rates of invasion, speciation and extinction both contemporarily and in fossil records. However, limited sampling effort and spatial aggregation of organisms mean that biodiversity surveys rarely observe every species in the survey area. Here we present a non-parametric, asymptotic and bias-minimized richness estimator,Ωby modelling how spatial abundance characteristics affect observation of species richness. Improved asymptotic estimators are critical when both absolute richness and difference detection are important. We conduct simulation tests and appliedΩto a tree census and a seaweed survey.Ωconsistently outperforms other estimators in balancing bias, precision and difference detection accuracy. However, small difference detection is poor with any asymptotic estimator. An R-package,Richness, performs the proposed richness estimations along with other asymptotic estimators and bootstrapped precisions. Our results explain how natural and observer-induced variations affect species observation, how these factors can be used to correct observed richness using the estimatorΩon a variety of data, and why further improvements are critical for biodiversity assessments.This article is part of the theme issue ‘Detecting and attributing the causes of biodiversity change: needs, gaps and solutions’.
Perspective: sustainability challenges, opportunities and solutions for long-term ecosystem observations
Authors: Mori Akira S. , Suzuki Kureha F. , Hori Masakazu , Kadoya Taku , Okano Kotaro , Uraguchi Aya , Muraoka Hiroyuki , Sato Tamotsu , Shibata Hideaki , Suzuki-Ohno Yukari , Koba Keisuke , Toda Mariko , Nakano Shin-ichi , Kondoh Michio , Kitajima Kaoru , Nakamura Masahiro 
Published: May 2023

As interest in natural capital grows and society increasingly recognizes the value of biodiversity, we must discuss how ecosystem observations to detect changes in biodiversity can be sustained through collaboration across regions and sectors. However, there are many barriers to establishing and sustaining large-scale, fine-resolution ecosystem observations. First, comprehensive monitoring data on both biodiversity and possible anthropogenic factors are lacking. Second, somein situecosystem observations cannot be systematically established and maintained across locations. Third, equitable solutions across sectors and countries are needed to build a global network. Here, by examining individual cases and emerging frameworks, mainly from (but not limited to) Japan, we illustrate how ecological science relies on long-term data and how neglecting basic monitoring of our home planet further reduces our chances of overcoming the environmental crisis. We also discuss emerging techniques and opportunities, such as environmental DNA and citizen science as well as using the existing and forgotten sites of monitoring, that can help overcome some of the difficulties in establishing and sustaining ecosystem observations at a large scale with fine resolution. Overall, this paper presents a call to action for joint monitoring of biodiversity and anthropogenic factors, the systematic establishment and maintenance ofin situobservations, and equitable solutions across sectors and countries to build a global network, beyond cultures, languages, and economic status. We hope that our proposed framework and the examples from Japan can serve as a starting point for further discussions and collaborations among stakeholders across multiple sectors of society. It is time to take the next step in detecting changes in socio-ecological systems, and if monitoring and observation can be made more equitable and feasible, they will play an even more important role in ensuring global sustainability for future generations.This article is part of the theme issue ‘Detecting and attributing the causes of biodiversity change: needs, gaps and solutions’.
Demography–environment relationships improve mechanistic understanding of range dynamics under climate change
Authors: Malchow A.-K. , Hartig F. , Reeg J. , Kéry M. , Zurell D. 
Published: May 2023

Species respond to climate change with range and abundance dynamics. To better explain and predict them, we need a mechanistic understanding of how the underlying demographic processes are shaped by climatic conditions. Here, we aim to infer demography–climate relationships from distribution and abundance data. For this, we developed spatially explicit, process-based models for eight Swiss breeding bird populations. These jointly consider dispersal, population dynamics and the climate-dependence of three demographic processes—juvenile survival, adult survival and fecundity. The models were calibrated to 267 nationwide abundance time series in a Bayesian framework. The fitted models showed moderate to excellent goodness-of-fit and discriminatory power. The most influential climatic predictors for population performance were the mean breeding-season temperature and the total winter precipitation. Contemporary climate change benefitted the population trends of typical mountain birds leading to lower population losses or even slight increases, whereas lowland birds were adversely affected. Our results emphasize that generic process-based models embedded in a robust statistical framework can improve our predictions of range dynamics and may allow disentangling of the underlying processes. For future research, we advocate a stronger integration of experimental and empirical studies in order to gain more precise insights into the mechanisms by which climate affects populations.This article is part of the theme issue ‘Detecting and attributing the causes of biodiversity change: needs, gaps and solutions’.
Bridging adaptive management and reinforcement learning for more robust decisions
Authors: Chapman Melissa , Xu Lily , Lapeyrolerie Marcus , Boettiger Carl 
Published: May 2023

From out-competing grandmasters in chess to informing high-stakes healthcare decisions, emerging methods from artificial intelligence are increasingly capable of making complex and strategic decisions in diverse, high-dimensional and uncertain situations. But can these methods help us devise robust strategies for managing environmental systems under great uncertainty? Here we explore how reinforcement learning (RL), a subfield of artificial intelligence, approaches decision problems through a lens similar to adaptive environmental management: learning through experience to gradually improve decisions with updated knowledge. We review where RL holds promise for improving evidence-informed adaptive management decisions even when classical optimization methods are intractable and discuss technical and social issues that arise when applying RL to adaptive management problems in the environmental domain. Our synthesis suggests that environmental management and computer science can learn from one another about the practices, promises and perils of experience-based decision-making.
This article is part of the theme issue ‘Detecting and attributing the causes of biodiversity change: needs, gaps and solutions’.
Economic factors underlying biodiversity loss
Authors: Dasgupta Partha , Levin Simon 
Published: May 2023

Contemporary economic thinking does not acknowledge that the human economy is embedded in Nature; it instead treats humanity as a customer that draws on Nature. In this paper, we present a grammar for economic reasoning that is not built on that error. The grammar is based on a comparison between our demand for Nature's maintenance and regulating services and her ability to supply them on a sustainable basis. The comparison is then used to show that for measuring economic well-being, national statistical offices should estimate an inclusive measure of their economies' wealth and its distribution, not GDP and its distribution. The concept of ‘inclusive wealth’ is then used to identify policy instruments that ought to be used to manage such global public goods as the open seas and tropical rainforests. Trade liberalization without heed paid to the fate of local ecosystems from which primary products are drawn and exported by developing countries leads to a transfer of inclusive wealth from there to rich importing countries. Humanity's embeddedness in Nature has far-reaching implications for the way we should view human activities—in households, communities, nations and the world.This article is part of the theme issue ‘Detecting and attributing the causes of biodiversity change: needs, gaps and solutions’.
Looking back on biodiversity change: lessons for the road ahead
Authors: Dornelas Maria , Chase Jonathan M. , Gotelli Nicholas J , Magurran Anne E , McGill Brian J , Antão Laura H. , Blowes Shane A. , Daskalova Gergana N. , Leung Brian , Martins Inês S. , Moyes Faye , Myers-Smith Isla H. , Thomas Chris D , Vellend Mark 
Published: May 2023

Estimating biodiversity change across the planet in the context of widespread human modification is a critical challenge. Here, we review how biodiversity has changed in recent decades across scales and taxonomic groups, focusing on four diversity metrics: species richness, temporal turnover, spatial beta-diversity and abundance. At local scales, change across all metrics includes many examples of both increases and declines and tends to be centred around zero, but with higher prevalence of declining trends in beta-diversity (increasing similarity in composition across space or biotic homogenization) and abundance. The exception to this pattern is temporal turnover, with changes in species composition through time observed in most local assemblages. Less is known about change at regional scales, although several studies suggest that increases in richness are more prevalent than declines. Change at the global scale is the hardest to estimate accurately, but most studies suggest extinction rates are probably outpacing speciation rates, although both are elevated. Recognizing this variability is essential to accurately portray how biodiversity change is unfolding, and highlights how much remains unknown about the magnitude and direction of multiple biodiversity metrics at different scales. Reducing these blind spots is essential to allow appropriate management actions to be deployed.
This article is part of the theme issue ‘Detecting and attributing the causes of biodiversity change: needs, gaps and solutions’.