bluuebunny/crossref_metadata_2025_split huggingface dataset:
A New Treatment Program: Focused Integrated Team-based Treatment Program for Bipolar Disorder (FITT-BD)
Authors: Sylvia Louisa G. , Tovey Roberta E. , Katz Douglas , Boccagno Chelsea , Stromberg Audrey R. , Peters Amy T. , Temes Christina M. , Gold Alexandra K. , Mow Jessica , Puvanich Nicha , Albury Evan A. , Stephan Nicole J. , Faria Caylin M. , Nierenberg Andrew A. , Kamali Masoud P. 
Published: April 2023

Objective:
Bipolar disorder (BD) is complicated by a dynamic, chronic course along with multiple comorbid psychiatric and medical conditions, making it challenging for clinicians to treat and patients to thrive. To efficiently manage the complexity of BD and help patients recover, we developed a Focused Integrated Team-based Treatment Program for Bipolar Disorder (FITT-BD). The purpose of this paper is to describe how we developed this clinic and the lessons we learned.

Methods:
We developed FITT-BD by integrating strategies from stepped care, collaborative care, and learning health care systems. We describe the rationale, details, and lessons learned in developing FITT-BD.

Results:
By integrating stepped care, collaborative care, and a learning health care system approach, FITT-BD aims to reduce barriers to care, leverage the expertise of a multidisciplinary treatment team, ensure patient-centeredness, and use assessments to inform and continuously improve outcomes in real time. We learned that there are challenges in the creation of a web-based application that tracks the treatment of patients within a network of hospitals.

Conclusions:
The success of FITT-BD will be determined by the degree to which it can increase treatment access, improve treatment adherence, and help individuals with BD achieve their treatment goals. We expect that FITT-BD will improve outcomes in the context of ongoing clinical care.

Public Health Significance:
The treatment of BD is challenging and complex. We propose a new treatment model for BD: FITT-BD. We expect that this program will be a patient-centered approach that improves outcomes in the context of ongoing clinical care for patients with BD.
Recent Advances in the Treatment of Brachial Plexus Birth Injury
Authors: Zuo Kevin J. , Ho Emily S. , Hopyan Sevan , Clarke Howard M. , Davidge Kristen M. 
Published: April 2023

Learning Objectives:
After studying this article, the participant should be able to: 1. Describe methods of clinical evaluation for neurologic recovery in brachial plexus birth injury. 2. Understand the role of different diagnostic imaging modalities to evaluate the upper limb. 3. List nonsurgical strategies and surgical procedures to manage shoulder abnormality. 4. Explain the advantages and disadvantages of microsurgical nerve reconstruction and distal nerve transfers in brachial plexus birth injury. 5. Recognize the prevalence of pain in this population and the need for greater sensory outcomes evaluation.

Summary:
Brachial plexus birth injury (BPBI) results from closed traction injury to the brachial plexus in the neck during an infant’s vertex passage through the birth canal. Although spontaneous upper limb recovery occurs in most instances of BPBI, some infants do not demonstrate adequate motor recovery within an acceptable timeline and require surgical intervention to restore upper limb function. This article reviews major advances in the management of BPBI in the past decade that include improved understanding of shoulder pathology and its impact on observed motor recovery, novel surgical techniques, new insights in sensory function and pain, and global efforts to develop standardized outcomes assessment scales.
Effects of cannabis legalization on the use of cannabis and other substances
Authors: Assanangkornchai Sawitri , Kalayasiri Rasmon , Ratta-apha Woraphat , Tanaree Athip 
Published: April 2023

Purpose of review
As more jurisdictions legalize cannabis for non-medical use, the evidence on how legalization policies affect cannabis use and the use of other substances remains inconclusive and contradictory. This review aims to summarize recent research findings on the impact of recreational cannabis legalization (RCL) on cannabis and other substance use among different population groups, such as youth and adults.

Recent findings
Recent literature reports mixed findings regarding changes in the prevalence of cannabis use after the adoption of RCL. Most studies found no significant association between RCL and changes in cannabis use among youth in European countries, Uruguay, the US, and Canada. However, some studies have reported increases in cannabis use among youth and adults in the US and Canada, although these increases seem to predate RCL. Additionally, there has been a marked increase in unintentional pediatric ingestion of cannabis edibles postlegalization, and an association between RCL and increased alcohol, vaping, and e-cigarette use among adolescents and young adults.

Summary
Overall, the effects of cannabis legalization on cannabis use appear to be mixed. Further monitoring and evaluation research is needed to provide longer-term evidence and a more comprehensive understanding of the effects of RCL.
Rapid opioid overdose response system technologies
Authors: Tay Wee Teck Joseph , Oteo Alberto , Baldacchino Alexander 
Published: April 2023

Purpose of review
Opioid overdose events are a time sensitive medical emergency, which is often reversible with naloxone administration if detected in time. Many countries are facing rising opioid overdose deaths and have been implementing rapid opioid overdose response Systems (ROORS). We describe how technology is increasingly being used in ROORS design, implementation and delivery.

Recent findings
Technology can contribute in significant ways to ROORS design, implementation, and delivery. Artificial intelligence-based modelling and simulations alongside wastewater-based epidemiology can be used to inform policy decisions around naloxone access laws and effective naloxone distribution strategies. Data linkage and machine learning projects can support service delivery organizations to mobilize and distribute community resources in support of ROORS. Digital phenotyping is an advancement in data linkage and machine learning projects, potentially leading to precision overdose responses. At the coalface, opioid overdose detection devices through fixed location or wearable sensors, improved connectivity, smartphone applications and drone-based emergency naloxone delivery all have a role in improving outcomes from opioid overdose. Data driven technologies also have an important role in empowering community responses to opioid overdose.

Summary
This review highlights the importance of technology applied to every aspect of ROORS. Key areas of development include the need to protect marginalized groups from algorithmic bias, a better understanding of individual overdose trajectories and new reversal agents and improved drug delivery methods.
Generalized higher-order Freud weights
Authors: Clarkson Peter A. , Jordaan Kerstin , Loureiro Ana 
Published: April 2023

We discuss polynomials orthogonal with respect to a semi-classical generalized higher-order Freud weight

ω
(
x
;
t
,
λ
)
=

|

x

|

2
λ
+
1

exp
⁡
(
t

x
2

−

x

2
m

)
,

x
∈

R

,

with parameters

λ
>
−
1

,

t
∈

R

and

m
=
2
,
3
,
…

. The sequence of generalized higher-order Freud weights for

m
=
2
,
3
,
…

, forms a hierarchy of weights, with associated hierarchies for the first moment and the recurrence coefficient. We prove that the first moment can be written as a finite partition sum of generalized hypergeometric

1

F
m

functions and show that the recurrence coefficients satisfy difference equations which are members of the first discrete Painlevé hierarchy. We analyse the asymptotic behaviour of the recurrence coefficients and the limiting distribution of the zeros as

n
→
∞

. We also investigate structure and other mixed recurrence relations satisfied by the polynomials and related properties.
Diagnostic performance of plasma Aβ1-42, Aβ1-40and pTau181in the LUMIPULSE automated platform for the detection of Alzheimer disease
Authors: Arranz Javier , Zhu Nuole , Rubio-Guerra Sara , Rodríguez-Baz íñigo , Carmona-Iragui María , Barroeta Isabel , Illán-Gala Ignacio , Santos-Santos Miguel , Fortea Juan , Lleó Alberto , Tondo Mireia , Alcolea Daniel 
Published: April 2023

AbstractBACKGROUNDRecently-developed blood markers for Alzheimer’s (AD) detection have high accuracy but usually require ultra-sensitive analytic tools not commonly available in clinical laboratories.METHODSWe analyzed plasma samples from 367 consecutive participants in the SPIN cohort, comprising 302 euploid participants (67 cognitively unimpaired, 136 participants with mild cognitive impairment, and 99 with dementia) and 65 with Down Syndrome (46 non-demented and 19 with AD dementia). Participants were classified according to CSF biomarkers status using the AT(N) system. Plasma Aβ1–42, Aβ1–40and pTau181were measured in the fully-automated LUMIPULSE platform. We used ANOVA to compare plasma biomarkers concentrations between AT(N) groups, evaluated Spearman’s correlation between plasma and CSF and performed ROC analyses to assess their diagnostic accuracy to detect AD.RESULTSPlasma pTau181concentration was higher in A+T+ than A+T- and A-T-, and in A+T- and A-T+ than A-T-. The plasma Aβ1–42/Aβ1–40ratio was lower in A+T+ and A+T- compared to A-T-. pTau181and the Aβ1–42/Aβ1–40ratio showed moderate correlation between plasma and CSF (Rho=0.66 and 0.65, respectively). The areas under the ROC curve (AUC) to discriminate A+T+ from A-T- participants were 0.91 for pTau181and 0.86 for Aβ1–42/Aβ1–40. The combination of both measures yielded an AUC=0.94. Chronic kidney disease (CKD) was related to increased plasma biomarker concentrations, but ratios were not significantly affected.CONCLUSIONThe feasibility and performance of plasma-based biomarker measurements on an automated platform showed high diagnostic accuracy and hold great promise for the diagnostic process of AD.What is already known on this topicBlood biomarkers have shown high accuracy to detect AD pathophysiology. The feasibility of those biomarkers in different platforms and the influence of comorbidities in their concentrations needs to be studied.What this study addsWe analyze the feasibility and diagnostic performance of AD biomarkers measured in a fully-automated platform and assess how comorbidities affect their concentrations.How this study might affect research, practice, or policyThe measurement of plasma AD biomarkers in an automated platform yields high accuracy to detect AD pathophysiology and would be easy to implement. Plasma AD biomarker concentrations are increased in chronic kidney disease, and in this context, the use of ratios would be more reliable.
Suboptimal Sleep Duration is Associated with Poorer Neuroimaging Brain Health Profiles
Authors: Clocchiatti-Tuozzo Santiago , Rivier Cyprien , Renedo Daniela , Torres Lopez Victor M , Geer Jacqueline , Miner Brienne , Yaggi Henry , de Havenon Adam , Payabvash Sam , Sheth Kevin N , Gill Thomas M , Falcone Guido J 
Published: April 2023

AbstractBackgroundCardiovascular health optimization during middle age benefits brain health. The American Heart Association’s Life’s Simple 7 recently added sleep duration as a key determinant of cardiovascular health becoming the Life’s Essential 8. We tested the hypothesis that suboptimal sleep duration is associated with poorer neuroimaging brain health profiles in asymptomatic middle-aged adults.MethodsWe conducted a prospective MRI neuroimaging study in middle-aged persons without stroke, dementia, or multiple sclerosis enrolled in the UK Biobank. Self-reported sleep duration was categorized as short (<7 hours), optimal (7-<9 hours), or long (≥9 hours). Evaluated neuroimaging markers of brain health included white matter hyperintensities (presence and volume) and diffusion tensor imaging metrics (fractional anisotropy and mean diffusivity) evaluated in 48 distinct neuroanatomical regions. We used multivariable logistic and linear regression models, as appropriate, to test for association between sleep duration and neuroimaging markers of brain health.ResultsWe evaluated 39,502 middle-aged persons (mean age 55, 53% female). Of these, 28,712 (72.7%) had optimal, 8,422 (21.3%) short, and 2,368 (6%) long sleep. Compared to optimal sleep, short sleep was associated with higher risk (OR 1.11; 95% CI 1.05-1.17; P<0.001) and larger volume (beta=0.06, SE=0.01; P<0.001) of white matter hyperintensities, while long sleep was associated with higher volume (beta=0.04, SE=0.02; P=0.01) but not higher risk (P>0.05) of white matter hyperintensities. Short (beta=0.03, SE=0.01; P=0.004) and long sleep (beta=0.07, SE=0.02; P<0.001) were associated with worse fractional anisotropy, while only long sleep associated with worse mean diffusivity (beta=0.05, SE=0.02; P=0.005).ConclusionsAmong middle-aged adults without clinically observed neurological disease, suboptimal sleep duration is associated with poorer neuroimaging brain health profiles. Because the evaluated neuroimaging markers precede stroke and dementia by several years, our findings support early interventions aimed at correcting this modifiable risk factor.
A study of gene expression in the living human brain
Authors: Liharska Lora E. , Park You Jeong , Ziafat Kimia , Wilkins Lillian , Silk Hannah , Linares Lisa M. , Thompson Ryan C. , Vornholt Eric , Sullivan Brendan , Cohen Vanessa , Kota Prashant , Feng Claudia , Cheng Esther , Johnson Jessica S. , Rieder Marysia-Kolbe , Huang Jia , Scarpa Joseph , Polanco Jairo , Moya Emily , Hashemi Alice , Levin Matthew A. , Nadkarni Girish N. , Sebra Robert , Crary John , Schadt Eric E. , Beckmann Noam D. , Kopell Brian H. , Charney Alexander W. 
Published: April 2023

SummaryA goal of medical research is to determine the molecular basis of human brain health and illness. One way to achieve this goal is through observational studies of gene expression in human brain tissue. Due to the unavailability of brain tissue from living people, most such studies are performed using tissue from postmortem brain donors. An assumption underlying this practice is that gene expression in the postmortem human brain is an accurate representation of gene expression in the living human brain. Here, this assumption – which, until now, had not been adequately tested – is tested by comparing human prefrontal cortex gene expression between 275 living samples and 243 postmortem samples. Expression levels differed significantly for nearly 80% of genes, and a systematic examination of alternative explanations for this observation determined that these differences are not a consequence of cell type composition, RNA quality, postmortem interval, age, medication, morbidity, symptom severity, tissue pathology, sample handling, batch effects, or computational methods utilized. Analyses integrating the data generated for this study with data from earlier landmark studies that used tissue from postmortem brain donors showed that postmortem brain gene expression signatures of neurological and mental illnesses, as well as of normal traits such as aging, may not be accurate representations of these gene expression signatures in the living brain. By using tissue from large cohorts living people, future observational studies of human brain biology have the potential to (1) determine the medical research questions that can be addressed using postmortem tissue as a proxy for living tissue and (2) expand the scope of medical research to include questions about the molecular basis of human brain health and illness that can only be addressed in living people (e.g., “What happens at the molecular level in the brain as a person experiences an emotion?”).
A generalizable functional connectivity signature characterizes brain dysfunction and links to rTMS treatment response in cocaine use disorder
Authors: Zhao Kanhao , Fonzo Gregory A. , Xie Hua , Oathes Desmond J. , Keller Corey J. , Carlisle Nancy , Etkin Amit , Garza-Villarreal Eduardo A , Zhang Yu 
Published: April 2023

ABSTRACTCocaine use disorder (CUD) is a prevalent substance abuse disorder, and repetitive transcranial magnetic stimulation (rTMS) has shown potential in reducing cocaine cravings. However, a robust and replicable biomarker for CUD phenotyping is lacking, and the association between CUD brain phenotypes and treatment response remains unclear. Our study successfully established a cross-validated functional connectivity signature for accurate CUD phenotyping, using resting-state functional magnetic resonance imaging from a discovery cohort, and demonstrated its generalizability in an independent replication cohort. We identified phenotyping FCs involving increased connectivity between the visual network and dorsal attention network, and between the frontoparietal control network and ventral attention network, as well as decreased connectivity between the default mode network and limbic network in CUD patients compared to healthy controls. These abnormal connections correlated significantly with other drug use history and cognitive dysfunctions, e.g., non-planning impulsivity. We further confirmed the prognostic potential of the identified discriminative FCs for rTMS treatment response in CUD patients and found that the treatment-predictive FCs mainly involved the frontoparietal control and default mode networks. Our findings provide new insights into the neurobiological mechanisms of CUD and the association between CUD phenotypes and rTMS treatment response, offering promising targets for future therapeutic development.
A novel multimodal approach to improve upper extremity function after moderate-to-severe stroke
Authors: Sethi Amit , Pascual-leone Alvaro , Santarnecchi Emiliano , Almalki Ghaleb , Krishnan Chandramouli 
Published: April 2023

AbstractBackgroundInterventions to recover upper extremity (UE) function after moderate-to-severe stroke are limited. Transcranial random noise stimulation (tRNS) is an emerging non-invasive technique to improve neuronal plasticity and may potentially augment functional outcomes when combined with existing interventions, such as functional electrical stimulation (FES).ObjectiveThe objective of this study was to investigate the feasibility and preliminary efficacy of combined tRNS and FES-facilitated task practice to improve UE impairment and function after moderate-to-severe stroke.MethodsFourteen individuals with UE weakness were randomized into one of two groups: 1) tRNS with FES-facilitated task practice, or 2) sham-tRNS with FES-facilitated task practice. Both groups involved 18 intervention sessions (3 per week for 6 weeks). We evaluated number of sessions completed, adverse effects, participant satisfaction, and intervention fidelity between two therapists. UE impairment (Fugl-Meyer Upper Extremity, FMUE), function (Wolf Motor Function Test, WMFT), participation (Stroke Impact Scale hand score, SIS-H), and grip strength were assessed at baseline, within 1 week and 3 months after completing the intervention.ResultsAll participants completed the 18 intervention sessions. Participants reported minimal adverse effects (mild tingling in head). The two trained therapists demonstrated 93% adherence and 96% competency with the intervention protocol. FMUE and SIS-H improved significantly more in the tRNS group than in the sham-tRNS group at both timepoints (p≤0.05), and the differences observed exceeded the clinically meaningful differences for these scores. The WMFT and paretic hand grip strength improved in both groups after the intervention (p≤0.05), with no significant between group differences.ConclusionOur findings show for the first time that combining tRNS and FES-facilitated task practice is a feasible and promising approach to improve UE impairment and function after moderate-to-severe stroke.
Anxiety due to Long COVID is partially driven by activation of the tryptophan catabolite (TRYCAT) pathway
Authors: Al-Hakeim Hussein Kadhem , Abed Anwar Khairi , Almulla Abbas F. , Moustafa Shatha Rouf , Maes Michael 
Published: April 2023

AbstractThis study examines whether activation of the tryptophan catabolite (TRYCAT) pathway is associated with anxiety symptoms due to Long COVID. We selected 90 participants, 60 Long COVID patients and 30 individuals without any symptoms following acute CIVID-19 infection. Using cluster analysis and the Hamilton Anxiety Rating scale (HAMA) score, the pure HAMA anxiety score, serum tryptophan (TRP) and kynurenine (KYN), the KYN/TRP ratio (all measured during Long COVID), and oxygen saturation (SpO2) (measured during the acute phase of COVID-19), we were able to classify Long COVID patients into two distinct clusters with an adequate silhouette cohesion and separation index (0.58): cluster 1 (n=61) and cluster 2 (n=29). Cluster 2 patients had lower SpO2 and TRP levels, as well as higher KYN, KYN/TRP ratio, and HAMA scores than cluster 1. Regression analysis revealed that the KYN/TRP ratio explained 14.4% of the variance in the HAMA score (F=14.81, df=1/88, p=0.001). In addition, regression analysis revealed that SpO2 partially explained the variance in serum TRP (r=0.396, p=0.005), KYN/TRP ratio (r=-0.248, p=0.018), and the HAMA score (r=-0.279, p=0.008). The current data imply that decreased SpO2 during the acute phase of COVID-19 infection is predictive of anxiety caused by Long COVID. Our data reveal that around 32% of Long COVID patients have elevated IDO activity in association with elevated anxiety.
Transformer based deep learning denoising of single and multi-delay 3D Arterial Spin Labeling
Authors: Shou Qinyang , Zhao Chenyang , Shao Xingfeng , Jann Kay , Helmer Karl G. , Lu Hanzhang , Wang Danny JJ 
Published: April 2023

AbstractPurposeTo present a Swin Transformer-based deep learning (DL) model for denoising of single-delay and multi-delay 3D arterial spin labeling (ASL) and compare its performance with convolutional neural network (CNN) methods.MethodsSwin Transformer and CNN-based spatial denoising models were developed for single-delay ASL. The models were trained on 59 subjects (104 scans) and tested on 44 subjects (57 scans) from 3 different vendors. Spatiotemporal denoising models were developed using another dataset (6 subjects, 10 scans) of multi-delay ASL. A range of input conditions was tested for denoising single and multi-delay ASL respectively. The performance was evaluated using similarity metrics, spatial signal-to-noise ratio (SNR) and quantification accuracy of cerebral blood flow (CBF) and arterial transit time (ATT).ResultsSwin Transformer outperformed CNN-based networks, whereas pseudo-3D models showed better performance than 2D models for denoising single-delay ASL. The similarity metrics and image quality (SNR) improved with more slices in pseudo-3D models, and further improved when using M0 as input but introduced greater biases for CBF quantification. Pseudo-3D models with 3 slices as input achieved optimal balance between SNR and accuracy, which can be generalized to different vendors. For multi-delay, spatiotemporal denoising models had better performance than spatial-only models with reduced biases in fitted CBF and ATT maps.ConclusionsSwin Transformer DL models provided better performance than CNN methods for denoising both single and multi-delay 3D ASL data. The proposed model offers flexibility to improve image quality and/or reduce scan time for 3D ASL to facilitate its clinical use.