bluuebunny/crossref_metadata_2025_split huggingface dataset:
States should use Medicaid to support violence intervention efforts
Authors: Zavala Claudia , Buggs Shani A. , Fischer Kyle R. 
Published: November 2021

ABSTRACT
In recent years, calls to address gun violence through public health approaches have increased. However, securing funding for health-based community violence intervention models has remained a challenge. New actions suggest that this may be shifting. Upon taking office, the Biden administration announced a series of funding opportunities for these programs, which ranged from competitive grant programs to a proposed 8-year, $5 billion plan. Less publicized, but just as important, is the administration's announcement that Medicaid can be used to reimburse this work, specifically noting the eligibility of hospital-based violence intervention and prevention programs. For these programs, this creates a predictable and reliable funding source that has not existed to date. This integration of violence prevention programming in the traditional health care and financing systems represents a critical inflection point in the United States' shifting response to community violence. However, the decision to use this optional benefit lies with each state. States should strongly consider harnessing Medicaid as a wise investment to address the United States' gun violence epidemic.

LEVEL OF EVIDENCE
Economic and value-based evaluation, level IV.
Experimental study to assess the impact of vasopressors administered during maintenance of the brain-dead donation in the quality of the intestinal graft
Authors: Vecchio Dezillio Leandro Emmanuel , Romanin David Emmanuel , Ivanoff Marinoff Ivana Mariel , Vernengo Julieta , Abate Zárate Juan Cruz , Machuca Mariana Alejandra , Gondolesi Gabriel Eduardo , Lausada Natalia Raquel , Stringa Pablo Luis , Rumbo Martín 
Published: November 2021

BACKGROUND
The hemodynamic maintenance of brain-dead donors will influence the quality of the organs procured for transplantation, including the intestine. Although norepinephrine (NE) and dopamine (DA) are commonly used to sustain mean arterial pressure in humans, there are no standardized protocols for their use during maintenance of brain-dead donors. Our aim was to compare the effects of each drug, in the intestinal graft quality using a rat brain-dead donation model.

METHODS
Wistar rats (N = 17) underwent brain death (BD) for 2 hours with NE (NE group) or with DA (DA group) administration; the control group was mechanically ventilated for 2 hours without BD. Jejunum biopsies were obtained at the end of the maintenance period. Histological damage was evaluated using Park-Chiu scale. Villi/crypt ratio, mucosal thickness, Goblet cell count, and villi density were evaluated using ImageJ software (US National Institutes of Health, Bethesda, MD). Barrier damage was assessed by bacterial translocation culture counting on liver samples. The inflammatory status of the intestine was evaluated by CD3+ counting by immunohistochemistry and gene expression analysis of interleukin (IL)-6, IL-22, and CXCL10.

RESULTS
Norepinephrine-treated donors had higher focal ischemic injury in the intestinal mucosa without a substantial modification of morphometrical parameters compared with DA-treated donors. CD3+ mucosal infiltration was greater in intestines procured from brain-dead donors, being highest in NE (p ˂ 0.001). Local inflammatory mediators were affected in BD: DA and NE groups showed a trend to lower expression of IL-22, whereas CXCL10 expression was higher in NE versus control group. Brain death promoted intestinal bacterial translocation, but the use of NE resulted in the highest bacterial counting in the liver (p ˂ 0.01).

CONCLUSION
Our results favor the use of DA instead of NE as main vasoactive drug to manage BD-associated hemodynamic instability. Dopamine may contribute to improve the quality of the intestinal graft, by better preserving barrier function and lowering immune cell infiltration.
Clinical assessment and screening of stroke patients with aphasia: a best practice implementation project
Authors: Wang Run , Wei Wei , Zhou Jungui , Yu Mei , Zhang Xiaomei , Luo Yansi , Yang Lixiao , Ye Xiaoling , Wu Yanni , Zhou Chunlan 
Published: November 2021

ABSTRACT

Introduction and aims:
As a critical form of stroke damage, aphasia negatively impacts stroke patients’ return to society. Speech and language intervention has been found to assist in optimizing poststroke aphasia patient outcomes; consequently, early identification and diagnosis are vital for poststroke aphasia to ensure that patients receive the rehabilitation they require. This project aimed to promote evidence-based practice (EBP) in the assessment and screening of stroke patients with aphasia and to improve the clinical outcomes of patients who suffer from poststroke aphasia in a large tertiary hospital.

Methods:
The current evidence implementation project was conducted in the neurology and rehabilitation departments of a tertiary hospital in China. Six audit criteria were developed for the baseline and follow-up audits. The project used the JBI PACES software, as well as JBI's Getting Research into Practice audit and feedback tool, to foster evidence-based healthcare in practice.

Results:
Although the performance of all evidence-based criteria during the baseline audit was poor, barriers were identified through baseline, and the project team carried out and implemented developed strategies following Getting Research into Practice resources. All the criteria improved from baseline after the follow-up cycle, with four out of six criteria achieving a compliance rate of 100%, and two evidence-based criteria recorded at 73 and 80% compliance, respectively.

Conclusion:
The current project successfully increased EBP for the assessment and screening of stroke patients with aphasia. Further studies are needed to ensure the project's long-term sustainability.
Gattaca: Base pair resolution mutation tracking for somatic evolution studies using agent-based models
Authors: Schenck Ryan O , Brosula Gabriel , West Jeffrey , Leedham Simon , Shibata Darryl , Anderson Alexander RA 
Published: November 2021

ABSTRACTGattaca provides the first base-pair resolution artificial genomes for tracking somatic mutations within agent based modeling. Through the incorporation of human reference genomes, mutational context, sequence coverage/error information Gattaca is able to realistically provide comparable sequence data for in-silico comparative evolution studies with human somatic evolution studies. This user-friendly method, incorporated into each in-silico cell, allows us to fully capture somatic mutation spectra and evolution.
Altered brain criticality in Schizophrenia: New insights from MEG
Authors: Alamian Golnoush , Lajnef Tarek , Pascarella Annalisa , Lina Jean-Marc , Knight Laura , Walters James , Singh Krish D , Jerbi Karim 
Published: November 2021

AbstractSchizophrenia has a complex etiology and symptomatology that is difficult to untangle. After decades of research, important advancements towards a central biomarker are still lacking. One of the missing pieces is a better understanding of how non-linear neural dynamics are altered in this patient population. In this study, the resting-state neuromagnetic signals of schizophrenia patients and healthy controls were analyzed in the framework of criticality. When biological systems like the brain are in a state of criticality, they are thought to be functioning at maximum efficiency (e.g., optimal communication and storage of information) and with maximum adaptability to incoming information. Here, we assessed the self-similarity and multifractality of resting-state brain signals recorded with magnetoencephalography in patients with schizophrenia patients and in matched controls. Our analysis showed a clear ascending, rostral to caudal gradient of self-similarity values in healthy controls, and an opposite gradient for multifractality (descending values, rostral to caudal). Schizophrenia patients had similar, although attenuated, gradients of self-similarity and multifractality values. Statistical tests showed that patients had higher values of self-similarity than controls in fronto-temporal regions, indicative of more regularity and memory in the signal. In contrast, patients had less multifractality than controls in the parietal and occipital regions, indicative of less diverse singularities and reduced variability in the signal. In addition, supervised machine-learning, based on logistic regression, successfully discriminated the two groups using measures of self-similarity and multifractality as features. Our results provide new insights into the baseline cognitive functioning of schizophrenia patients by identifying key alterations of criticality properties in their resting-state brain data.
Regulatory T cells suppress the formation of potent KLRK1 and IL-7R expressing effector CD8 T cells by limiting IL-2
Authors: Tsyklauri Oksana , Chadimova Tereza , Niederlova Veronika , Kovarova Jirina , Michalik Juraj , Malatova Iva , Janusova Sarka , Ivashchenko Olha , Rossez Helene , Drobek Ales , Vecerova Hana , Galati Virginie , Kovar Marek , Stepanek Ondrej 
Published: November 2021

AbstractRegulatory T cells (Tregs) are indispensable for maintaining self-tolerance by suppressing conventional T cells. On the other hand, Tregs promote tumor growth by inhibiting anti-cancer immunity. In this study, we identified that Tregs increase the quorum of self-reactive CD8+T cells required for the induction of experimental autoimmune diabetes. Their major suppression mechanism is limiting available IL-2, an essential T-cell cytokine. Specifically, Tregs inhibit the formation of a previously uncharacterized subset of antigen-stimulated KLRK1+IL7R+(KILR) CD8+effector T cells, which are distinct from conventional effector CD8+T cells. KILR CD8+T cells show a superior cell killing abilities in vivo. The administration of agonistic IL-2 immunocomplexes phenocopies the absence of Tregs, i.e., it induces KILR CD8+T cells, promotes autoimmunity, and enhances anti-tumor responses. Counterparts of KILR CD8+T cells were found in the human blood, revealing them as a potential target for immunotherapy.
Three-dimensional Shear Wave Elastography Using a 2D Row Column Addressing (RCA) Array
Authors: Dong Zhijie , Kim Jihun , Huang Chengwu , Lowerison Matthew R. , Chen Shigao , Song Pengfei 
Published: November 2021

AbstractObjectiveTo develop a 3D shear wave elastography (SWE) technique using a 2D row column addressing (RCA) array, with either external vibration or acoustic radiation force (ARF) as the shear wave source.Impact StatementThe proposed method paves the way for clinical translation of 3D-SWE based on the 2D RCA, providing a low-cost and high volume-rate solution that is compatible with existing clinical systems.IntroductionSWE is an established ultrasound imaging modality that provides a direct and quantitative assessment of tissue stiffness, which is significant for a wide range of clinical applications including cancer and liver fibrosis. SWE requires high frame-rate imaging for robust shear wave tracking. Due to the technical challenges associated with high volume-rate imaging in 3D, current SWE techniques are typically confined to 2D. Advancing SWE from 2D to 3D is significant because of the heterogeneous nature of tissue, which demands 3D imaging for accurate and comprehensive evaluation.MethodsA 3D SWE method using a 2D RCA array was developed with a volume-rate up to 2000 Hz. The performance of the proposed method was systematically evaluated on tissue-mimicking elasticity phantoms.Results3D shear wave motion induced by either external vibration or ARF was successfully detected with the proposed method. Robust 3D shear wave speed maps were reconstructed for both homogeneous and heterogeneous phantoms with inclusions.ConclusionThe high volume-rate 3D imaging provided by the 2D RCA array provides a robust and practical solution for 3D SWE with a clear pathway for future clinical translation.
Cerebral blood flow predicts multiple demand network activity and fluid intelligence across the lifespan
Authors: Wu Shuyi , Tyler Lorraine K. , Henson Richard N.A. , Rowe James B. ,   Cam-Can, Tsvetanov Kamen A. 
Published: November 2021

AbstractThe preservation of cognitive function into old age is a public health priority. Cerebral hypoperfusion is a hallmark of dementia but its impact on maintaining cognitive ability across the lifespan is less clear. We investigated the relationship between baseline cerebral blood flow (CBF) and blood oxygenation level-dependent (BOLD) response during a fluid reasoning task in a population-based adult lifespan cohort (N=227, age 18-88 years). As age differences in baseline CBF could lead to non-neuronal contributions to the BOLD signal, we introduced commonality analysis to neuroimaging, in order to dissociate performance-related CBF effects from the physiological confounding effects of CBF on the BOLD response. Accounting for CBF, we confirmed that performance- and age-related differences in BOLD responses in the multiple-demand network (MDN) implicated in fluid reasoning. Differences in baseline CBF across the lifespan explained not only performance-related BOLD responses, but also performance-independent BOLD responses. Our results suggest that baseline CBF is important for maintaining cognitive function, while its non-neuronal contributions to BOLD signals reflect an age-related confound. Maintaining perfusion into old age may serve to support brain function with behavioural advantage, regulating brain health.
Real-time alerts from AI-enabled camera traps using the Iridium satellite network: a case-study in Gabon, Central Africa
Authors: Whytock Robin C. , Suijten Thijs , van Deursen Tim , Świeżewski Jędrzej , Mermiaghe Hervé , Madamba Nazaire , Moukoumou Narcys , Zwerts Joeri A. , Koumba Pambo Aurélie Flore , Bahaa-el-din Laila , Brittain Stephanie , Cardoso Anabelle W. , Henschel Philipp , Lehmann David , Momboua Brice Roxan , Makaga Loïc , Orbell Christopher , White Lee J.T. , Iponga Donald Midoko , Abernethy Katharine A. 
Published: November 2021

AbstractEfforts to preserve, protect, and restore ecosystems are hindered by long delays between data collection and analysis. Threats to ecosystems can go undetected for years or decades as a result. Real-time data can help solve this issue but significant technical barriers exist. For example, automated camera traps are widely used for ecosystem monitoring but it is challenging to transmit images for real-time analysis where there is no reliable cellular or WiFi connectivity. Here, we present our design for a camera trap with integrated artificial intelligence that can send real-time information from anywhere in the world to end-users.We modified an off-the-shelf camera trap (Bushnell™) and customised existing open-source hardware to rapidly create a ‘smart’ camera trap system. Images captured by the camera trap are instantly labelled by an artificial intelligence model and an ‘alert’ containing the image label and other metadata is then delivered to the end-user within minutes over the Iridium satellite network. We present results from testing in the Netherlands, Europe, and from a pilot test in a closed-canopy forest in Gabon, Central Africa.Results show the system can operate for a minimum of three months without intervention when capturing a median of 17.23 images per day. The median time-difference between image capture and receiving an alert was 7.35 minutes. We show that simple approaches such as excluding ‘uncertain’ labels and labelling consecutive series of images with the most frequent class (vote counting) can be used to improve accuracy and interpretation of alerts.We anticipate significant developments in this field over the next five years and hope that the solutions presented here, and the lessons learned, can be used to inform future advances. New artificial intelligence models and the addition of other sensors such as microphones will expand the system’s potential for other, real-time use cases. Potential applications include, but are not limited to, wildlife tourism, real-time biodiversity monitoring, wild resource management and detecting illegal human activities in protected areas.
Secure federated Boolean count queries using fully-homomorphic cryptography
Authors: Leighton Alexander T. , Yu Yun William 
Published: November 2021

AbstractBiomedical data is often distributed between a network of custodians, causing challenges for researchers wishing to securely compute aggregate statistics on those data without centralizing everything—the prototypical ‘count query’ asks how many patients match some multifaceted set of conditions across a network of hospitals. Difficulty arises from two sources: (1) the need to deduplicate patients who may be present in the records of multiple hospitals and (2) the need to unify partial records for the same patient which may be split across hospitals. Although cryptographic tools for secure computation promise to enable collaborative studies with formal privacy guarantees, existing approaches either are computationally impractical or support only simplified analysis pipelines. To the best of our knowledge, no existing practical secure method addresses both of these difficulties simultaneously.Here, we introduce secure federated Boolean count queries using a novel 2-stage probabilistic sketching and sampling protocol that can be efficiently implemented in off-the-shelf federated homomorphic encryption libraries (Palisade and Lattigo), provably ensuring data security. To this end, we needed several key technological innovations, including re-encoding the LogLog union-cardinality sketch and designing an appropriate sampling for intersection cardinalities. Our benchmarking shows that we can answer federated Boolean count queries in less than 2 CPU-minutes with absolute errors in the range of 6% of the total number of touched records, while revealing only the final answer and the total number of touched records. With modern core-parallelism, we can thus answer queries on the order of seconds. Our study demonstrates that by computing on compressed and encrypted data, it is possible to securely answer federated Boolean count queries in real-time.
Real-time Image Denoising of Mixed Poisson-Gaussian Noise in Fluorescence Microscopy Images using ImageJ
Authors: Mannam Varun , Zhang Yide , Zhu Yinhao , Nichols Evan , Wang Qingfei , Sundaresan Vignesh , Zhang Siyuan , Smith Cody , Bohn Paul W , Howard Scott 
Published: November 2021

AbstractFluorescence microscopy imaging speed is fundamentally limited by the measurement signal-to-noise ratio (SNR). To improve image SNR for a given image acquisition rate, computational denoising techniques can be used to suppress noise. However, common techniques to estimate a denoised image from a single frame are either computationally expensive or rely on simple noise statistical models. These models assume Poisson or Gaussian noise statistics, which are not appropriate for many fluorescence microscopy applications that contain quantum shot noise and electronic Johnson–Nyquist noise, therefore a mixture of Poisson and Gaussian noise. In this paper, we show convolutional neural networks (CNNs) trained on mixed Poisson and Gaussian noise images to overcome the limitations of existing image denoising methods. The trained CNN is presented as an open-source ImageJ plugin that performs real-time image denoising (within tens of milliseconds) with superior performance (SNR improvement) compared to the conventional fluorescence microscopy denoising methods. The method is validated on external datasets with out-of-distribution noise, contrast, structure, and imaging modalities from the training data and consistently achieves high performance (> 8 dB) denoising in less time than other fluorescence microscopy denoising methods.
Phylogenetic diversity of two commonTrypanosoma cruzilineages in the Southwestern United States
Authors: Flores-López Carlos A. , Mitchell Elizabeth A. , Reisenman Carolina E. , Sarkar Sahotra , Williamson Philip C. , Machado Carlos A. 
Published: November 2021

AbstractTrypanosoma cruziis the causative agent of Chagas disease, a devastating parasitic disease endemic to Central and South America, Mexico, and the USA. We characterized the genetic diversity ofT. cruzicirculating in five triatomine species (Triatoma gerstaeckeri, T. lecticularia, T. indictiva, T. sanguisugaandT. recurva) collected in Texas and Southern Arizona using nucleotide sequences from four single-copy loci (COII-ND1, MSH2, DHFR-TS, TcCLB.506529.310). AllT. cruzivariants fall in two main genetic lineages: 75% of the samples corresponded toT. cruziDiscrete Typing Unit (DTU) I (TcI), and 25% to a North American specific lineage previously labelled TcIV-USA. Phylogenetic and sequence divergence analyses of our new data plus all previously published sequence data from those 4 genes collected in the USA, show that TcIV-USA is significantly different from any other previously definedT. cruziDTUs. The significant level of genetic divergence between TcIV-USA and otherT. cruzilineages should lead to an increased focus on understanding the epidemiological importance of this lineage, as well as its geographical range and pathogenicity in humans and domestic animals. Our findings further corroborate the fact that there is a high genetic diversity of the parasite in North America and emphasize the need for appropriate surveillance and vector control programs for Chagas disease in southern USA and Mexico.
Molecular, anatomical, and functional organization of lung interoceptors
Authors: Liu Yin , Diaz de Arce Alex J. , Krasnow Mark A. 
Published: November 2021

ABSTRACTInteroceptors, sensory neurons that monitor internal organs and states, are essential for physiological homeostasis and generating internal perceptions. Here we describe a comprehensive transcriptomic atlas of interoceptors of the mouse lung, defining 10 molecular subtypes that differ in developmental origin, myelination, receptive fields, terminal morphologies, and cell contacts. Each subtype expresses a unique but overlapping combination of sensory receptors that detect diverse physiological and pathological stimuli, and each can signal to distinct sets of lung cells including immune cells, forming a local neuroimmune interaction network. Functional interrogation of two mechanosensory subtypes reveals exquisitely-specific homeostatic roles in breathing, one regulating inspiratory time and the other inspiratory flow. The results suggest that lung interoceptors encode diverse and dynamic sensory information rivaling that of canonical exteroceptors, and this information is used to drive myriad local cellular interactions and enable precision control of breathing, while providing only vague perceptions of organ states.