bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recent Trends on the Development of Machine Learning Approaches
for the Prediction of Lysine Acetylation Sites
Authors: Basith Shaherin , Chang Hye Jin , Nithiyanandam Saraswathy , Shin Tae Hwan , Manavalan Balachandran , Lee Gwang 
Published: September 2021

:
Acetylation on lysine residues is considered one of the most potent protein
post-translational modifications, owing to its crucial role in cellular metabolism and regulatory
processes. Recent advances in experimental techniques have unraveled several lysine
acetylation substrates and sites. However, owing to its cost-ineffectiveness, cumbersome
process, time-consumption, and labor-intensiveness, several efforts have been
geared towards the development of computational tools. In particular, machine learning
(ML)-based approaches hold great promise in the rapid discovery of lysine acetylation
modification sites, which could be witnessed by the growing number of prediction tools.
Recently, several ML methods have been developed for the prediction of lysine acetylation
sites, owing to their time- and cost-effectiveness. In this review, we present a complete
survey of the state-of-the-art ML predictors for lysine acetylation. We discuss a variety
of key aspects for developing a successful predictor, including operating ML algorithms,
feature selection methods, validation techniques, and software utility. Initially, we
review lysine acetylation site databases, current ML approaches, working principles, and
their performances. Lastly, we discuss the shortcomings and future directions of ML approaches
in the prediction of lysine acetylation sites. This review may act as a useful
guide for the experimentalists in choosing the right ML tool for their research. Moreover,
it may help bioinformaticians in the development of more accurate and advanced MLbased
predictors in protein research.
Maslinic Acid Inhibits Cervical Intraepithelial Neoplasia by Suppressing Interleukin-
6 and Enhancing Apoptosis in a Mouse Model
Authors: Chen Jiuwei , Wang Lin 
Published: September 2021

Background:
Cervical intraepithelial neoplasia (CIN) directly precedes cervical cancer, and elevated proinflammatory
cytokine interleukins (IL)-6 is implicated in CIN.

Objective:
As maslinic acid exhibits anti-IL-6 property, the present study sought to determine the effect of maslinic
acid on CIN in vitro and in vivo using cell cultures and mouse CIN models, respectively.

Methods:
The dose-effect of maslinic acid on HeLa cells, a human cervical cancer cell line, was first evaluated, including
cytotoxicity, IL-6 secretion, IL-6 receptor (IL-6R) expression, proliferation potential and apoptosis status. A mouse
model of CIN was also established, which was then subjected to increasing doses of maslinic acid treatment, followed
by assessment of serum IL-6 level, cervical expression of IL-6R, and the proliferation potential and apoptosis of cervical
tissues.

Results:
Maslinic acid dose-dependently inhibited cell growth and proliferation potential, reduced IL-6 secretion, cervical
expression of IL-6R and induced apoptosis of HeLa cells in vitro. In the CIN mouse model, serum IL-6 level and
cervical expression of IL-6R were elevated, which could be repressed by maslinic acid administration dosedependently.
Additionally, maslinic acid treatment in the CIN mice could also restore the otherwise increased proliferation
potential and reduced apoptosis in the cervical tissues.

Conclusion:
Maslinic acid exhibits potent anti-IL-6 property in the CIN mouse model, and alleviates the diseaserelated
abnormality in proliferation potential and apoptosis state of the cervical tissue cells, demonstrating its usefulness
as a promising agent in treating CIN.
Targeted Delivery of Montelukast for the Treatment of Alzheimer’s
Disease
Authors: Datusalia Ashok K. , Singh Gurpreet , Yadav Nikita , Gaun Sachin , Manik Moumita , Singh Rakesh K. 
Published: September 2021

:
Alzheimer’s Disease (AD) is one of the most common neurodegenerative diseases,
which affects millions of people worldwide. Accumulation of amyloid-β plaques and hyperphosphorylated
neurofibrillary tangles are the key mechanisms involved in the etiopathogenesis of AD,
characterized by memory loss and behavioural changes. Effective therapies targeting AD pathogenesis
are limited, making it the largest unmet clinical need. Unfortunately, the available drugs provide
symptomatic relief and primary care, with no substantial impact on the disease pathology.
However, in recent years researchers are working hard on several potential therapeutic targets to
combat disease pathogenesis, and few drugs have also reached clinical trials. In addition, drugs are
being repurposed both in the preclinical and clinical studies for the treatment of AD. For instance,
montelukast is the most commonly used leukotriene receptor antagonist for treating asthma and seasonal
allergy. Its leukotriene antagonistic action can also be beneficial for the reduction of detrimental
effects of leukotriene against neuro-inflammation, a hallmark feature of AD. The available
marketed formulations of montelukast present challenges such as poor bioavailability and reduced
uptake, reflecting the lack of effectiveness of its desired action in the CNS. While on the other side,
targeted drug delivery is a satisfactory approach to surpass the challenges associated with the therapeutic
agents. This review will discuss the enhancement of montelukast treatment efficacy and its
access to CNS by using new approaches like nano-formulation, nasal gel, solid lipid formulation,
nano-structure lipid carrier (NSLC), highlighting lessons learned to target AD pathologies and hurdles
that persist.
Liquid Chromatographic Analysis of Methotrexate and Minocycline-relevance to the Determination in Plasma/Nanoparticulate Formulations
Authors: Janakiraman Kumar , Krishnaswami Venkateshwaran , Sethuraman Vaidevi , Rajendran Vijaya , Kandasamy Ruckmani 
Published: September 2021

Aim:
To develop RP-HPLC method for the simultaneous estimation of methotrexate
(MTX) and minocycline (MNC).

Background:
Different HPLC methods were reported for the estimation of MTX/MNC individually,
but there is no report for the simultaneous estimation of both MTX and MNC in a simple
method.

Objective:
The objective of the developed method is to utilize the method for the estimation of
MTX/MNC in different pharmaceutical formulations and in biological fluids

Methods:
An HPLC method for the estimation of Methotrexate (MTX) and Minocycline (MNC)
relevance to the evaluation of nanoparticulate formulations has been developed and validated. Chromatographic
estimation was achieved using the mobile phase composition of sodium acetate buffer
and acetonitrile (70:30% v/v) at pH 4.0 at a flow rate of 0.2 mL/min at 307 nm.

Results:
The calibration curve for MTX and MNC was found to be linear at nanogram (5 to 25
ng.mL-1) and microgram (5 to 25 μg.mL-1) levels at correlation coefficient range of 0.98 to 0.99
for both MTX/MNC. The lower limit of detection and limit of quantification were found to be
0.026 ng.mL-1 and 0.079 ng.mL-1 for MTX and MNC, respectively. The percentage relative standard
deviation for validation parameters of both drugs was found to be less than 6.5%. The amount
of MTX and MNC present within the nanoparticles was found to be MTX (0.84 mg/mL) and MNC
(0.61 mg/mL). The in vitro release showed an immediate release pattern for MTX (64.95±2.08%)
and MNC (90.90±1.78%) within 12 h.

Conclusion:
The developed analytical method for the simultaneous estimation of MTX and MNC
was found to be simple, affordable, dynamic, low cost, rapid and easy to perform with good repeatability.
This method is also time consuming, since the peaks were obtained within a moderate
analysis time.
Health Impacts and Characteristics of Deprescribing Interventions in Older Adults: Protocol for a Systematic Review and Meta-analysis
Authors: Tremblay Zoë , Mumbere David , Laurin Danielle , Sirois Caroline , Furrer Daniela , Poisblaud Lise , Carmichael Pierre-Hugues , Farrell Barbara , Tourigny André , Giguere Anik , Vedel Isabelle , Morais José , Kröger Edeltraut 
Published: September 2021

Background
Deprescribing, a relatively recent concept, has been proposed as a promising solution to the growing issues of polypharmacy and use of medications of questionable benefit among older adults. However, little is known about the health outcomes of deprescribing interventions.

Objective
This paper presents the protocol of a study that aims to contribute to the knowledge on deprescribing by addressing two specific objectives: (1) describe the impact of deprescribing in adults ≥60 years on health outcomes or quality of life; and (2) determine the characteristics of effective interventions in deprescribing.

Methods
Primary studies targeting three concepts (older adults, deprescribing, and health or quality of life outcomes) will be included in the review. The search will be performed using key international databases (MEDLINE, EMBASE, CINAHL, Ageline, PsycInfo), and a special effort will be made to identify gray literature. Two reviewers will independently screen the articles, extract the information, and evaluate the quality of the selected studies. If methodologically feasible, meta-analyses will be performed for groups of intervention studies reporting on deprescribing interventions for similar medications, used for similar or identical indications, and reporting on similar outcomes (eg, benzodiazepines used against insomnia and studies reporting on quality of sleep or quality of life). Alternatively, the results will be presented in bottom-line statements (objective 1) and a matrix outlining effective interventions (objective 2).

Results
The knowledge synthesis may be limited by the availability of high-quality clinical trials on deprescribing and their outcomes in older adults. Additionally, analyses will likely be affected by studies on the deprescribing of different types of molecules within the same indication (eg, different pharmacological classes and medications to treat hypertension) and different measures of health and quality of life outcomes for the same indication. Nevertheless, we expect the review to identify which deprescribing interventions lead to improved health outcomes among seniors and which of their characteristics contribute to these outcomes.

Conclusions
This systematic review will contribute to a better understanding of the health outcomes of deprescribing interventions among seniors.

Trial Registration
PROSPERO International Prospective Register of Systematic Reviews CRD42015020866; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42015020866

International Registered Report Identifier (IRRID)
PRR1-10.2196/25200
Detecting Tonic-Clonic Seizures in Multimodal Biosignal Data From Wearables: Methodology Design and Validation
Authors: Böttcher Sebastian , Bruno Elisa , Manyakov Nikolay V , Epitashvili Nino , Claes Kasper , Glasstetter Martin , Thorpe Sarah , Lees Simon , Dümpelmann Matthias , Van Laerhoven Kristof , Richardson Mark P , Schulze-Bonhage Andreas ,   The RADAR-CNS Consortium
Published: September 2021

Background
Video electroencephalography recordings, routinely used in epilepsy monitoring units, are the gold standard for monitoring epileptic seizures. However, monitoring is also needed in the day-to-day lives of people with epilepsy, where video electroencephalography is not feasible. Wearables could fill this gap by providing patients with an accurate log of their seizures.

Objective
Although there are already systems available that provide promising results for the detection of tonic-clonic seizures (TCSs), research in this area is often limited to detection from 1 biosignal modality or only during the night when the patient is in bed. The aim of this study is to provide evidence that supervised machine learning can detect TCSs from multimodal data in a new data set during daytime and nighttime.

Methods
An extensive data set of biosignals from a multimodal watch worn by people with epilepsy was recorded during their stay in the epilepsy monitoring unit at 2 European clinical sites. From a larger data set of 243 enrolled participants, those who had data recorded during TCSs were selected, amounting to 10 participants with 21 TCSs. Accelerometry and electrodermal activity recorded by the wearable device were used for analysis, and seizure manifestation was annotated in detail by clinical experts. Ten accelerometry and 3 electrodermal activity features were calculated for sliding windows of variable size across the data. A gradient tree boosting algorithm was used for seizure detection, and the optimal parameter combination was determined in a leave-one-participant-out cross-validation on a training set of 10 seizures from 8 participants. The model was then evaluated on an out-of-sample test set of 11 seizures from the remaining 2 participants. To assess specificity, we additionally analyzed data from up to 29 participants without TCSs during the model evaluation.

Results
In the leave-one-participant-out cross-validation, the model optimized for sensitivity could detect all 10 seizures with a false alarm rate of 0.46 per day in 17.3 days of data. In a test set of 11 out-of-sample TCSs, amounting to 8.3 days of data, the model could detect 10 seizures and produced no false positives. Increasing the test set to include data from 28 more participants without additional TCSs resulted in a false alarm rate of 0.19 per day in 78 days of wearable data.

Conclusions
We show that a gradient tree boosting machine can robustly detect TCSs from multimodal wearable data in an original data set and that even with very limited training data, supervised machine learning can achieve a high sensitivity and low false-positive rate. This methodology may offer a promising way to approach wearable-based nonconvulsive seizure detection.
Optimizing Coaching During Web-Based Relationship Education for Low-Income Couples: Protocol for Precision Medicine Research
Authors: Hatch S Gabe , Lobaina Diana , Doss Brian D 
Published: September 2021

Background
In-person relationship education classes funded by the federal government tend to experience relatively high attrition rates and have only a limited effect on relationships. In contrast, low-income couples tend to report meaningful gains from web-based relationship education when provided with individualized coach contact. However, little is known about the method and intensity of practitioner contact that a couple requires to complete the web-based program and receive the intended benefit.

Objective
The aim of this study is to use within-group models to create an algorithm to assign future couples to different programs and levels of coach contact, identify the most powerful predictors of treatment adherence and gains in relationship satisfaction within 3 different levels of coaching, and examine the most powerful predictors of treatment adherence and gains in relationship satisfaction among the 3 levels of coach contact.

Methods
To accomplish these goals, this project intends to use data from a web-based Sequential Multiple Assignment Randomized Trial of the OurRelationship and web-based Prevention and Relationship Enhancement programs, in which the method and type of coach contact were randomly varied across 1248 couples (2496 individuals), with the hope of advancing theory in this area and generating accurate predictions. This study was funded by the US Department of Health and Human Services, Administration for Children and Families (grant number 90PD0309).

Results
Data collection from the Sequential Multiple Assignment Randomized Trial of the OurRelationship and web-based Prevention and Relationship Enhancement Program was completed in October of 2020.

Conclusions
Some of the direct benefits of this study include benefits to social services program administrators, tailoring of more effective relationship education, and effective delivery of evidence- and web-based relationship health interventions.

International Registered Report Identifier (IRRID)
DERR1-10.2196/33047
An Advanced Nursing Directive for Children With Suspected Appendicitis: Protocol for a Quality Improvement Feasibility Study
Authors: Chaudhari Hanu , Schneeweiss Michelle , Rebinsky Reid , Rullo Enrico , Eltorki Mohamed 
Published: September 2021

BackgroundPediatric appendicitis accounts for an estimated 7% to 10% of abdominal pain cases in the emergency department (ED). The diagnosis is time-consuming, and the investigative process depends on physician assessment, resulting in delays in diagnosis and therapeutic management. The utility of an advanced nursing directive (AND) to expedite this process is unclear and needs further exploration.ObjectiveThis study aims to describe key components of ED flow in patients with suspected appendicitis seen at a pediatric ED and pilot a directive that allows ED nurses to perform an order set that includes blood work, urine tests, analgesics, fluids, and an abdominal-pelvis ultrasound prior to physician assessment.MethodsThis study involves conducting a retrospective chart review alongside a quality improvement initiative to compare key ED flow metrics before and after AND implementation. Primary outcome measures include median time from ED triage assessment to ultrasound completion, analgesia administration, blood work results, and time to disposition (consult or discharge), alongside other key ED flow metrics for suspected appendicitis. Secondary outcomes will involve patient and caretaker satisfaction surveys. Descriptive statistics will be used to summarize the data. For differences in proportions, a chi-square test will be used. The Student t test will be used for continuous variables. A variable-controlled run chart will be performed to assess impact on ED flow metrics. Patient and family satisfaction surveys are administered immediately after the directive encounter and 7 days afterward.ResultsThere are currently 3900 patients who have been screened, 344 patients who have been enrolled, and 90 patients who have received the medical directive since implementation in June 2020. Interim results on reduction of time to diagnostic and therapeutic ED flow parameters and satisfaction surveys are expected to be published in February 2022. The final study endpoint will be in June 2022.ConclusionsThis study proposes a novel protocol for improving the diagnosis and treatment of suspected pediatric appendicitis through implementation of an evidence-based AND. This model may provide a standardized, international pathway for management of common pediatric and adult emergencies.International Registered Report Identifier (IRRID)RR1-10.2196/33158
Co-Infección por Cryptococcus neoformans en paciente trasplantado renal con COVID-19. Reporte de caso.
Authors: Torrez Serrano Rodolfo Eduardo , Rosselli San Martin Carlos , Olivares  Algarin Orlando , Agudelo Gonzalez Stefany , Carrillo Ayerbe María Paula , Coral Zuñiga Victoria Elena 
Published: September 2021

La infección por el síndrome respiratorio agudo severo por coronavirus 2 (SARS-CoV-2), causante de la enfermedad COVID-19, representa una de las emergencias sanitarias más deletéreas de las últimas dos décadas; de la que aún existen innumerables incógnitas acerca del curso y manejo de presentaciones atípicas. Por lo anterior, resulta importante publicar casos clínicos de interés en población especial como lo son los pacientes receptores de trasplante renal quienes pueden tener un mayor riesgo de contraer la enfermedad por el estado de inmunosupresión y por el contacto frecuente con el sistema de atención médica.
La coinfección con otros virus respiratorios no es infrecuente en población trasplantada con COVID-19, y la asociación con gérmenes oportunistas como Micobacterias, Citomegalovirus, Pneumocystis jirovecii y hongos, tal como el Cryptococcus neoformans es desconocida, pero es posible que dicha asociación podría empeorar la severidad del compromiso sistémico y pulmonar.
Se presenta el caso de un hombre de 45 años que ingresó al servicio de urgencias del Hospital de San José, con antecedente de trasplante renal de donante cadavérico, el presentó SINDROME DE DIFICULTAD RSEPIRATORIA AGUDA (SDRA) y falla ventilatoria por infección por SARS-CoV-2, además se confirmó infección sistémica por Cryptococcus neoformans sin compromiso del sistema nervioso central. Se inició manejo con ventilación mecánica invasiva, glucocorticoide, anfotericina B liposomal y fallece a los 12 días de su ingreso.
Wealthy Watches Inc.: The Substantive Testing of Accounts Receivable in the Evolving Audit Environment
Authors: Andiola Lindsay M. , Downey Denise Hanes , Earley Christine E. , Jefferson Devon 
Published: September 2021

ABSTRACT
Substantive testing of accounts receivable through confirmations is an established and required audit procedure. However, the technology used to perform portions of this work is evolving. This case exposes students to the testing of accounts receivable while introducing them to audit-related technologies (such as Interactive Data Extraction and Analysis [IDEA] software and robotic process automation [RPA]) used in practice. In this case, students (1) evaluate a client-provided data file, (2) select a sample of customer invoices using IDEA, (3) obtain audit evidence from their firm's RPA software and evaluate the evidence for the identification of exceptions, (4) project any misstatements from the sample to the population, and (5) document their conclusions. This case helps students develop a greater awareness of technologies used in audit practice. The case also allows students to practice skepticism, apply professional judgment, and hone their business writing skills by documenting their results in a professional memo.
The Impact of Tax Policy Uncertainty on Forecasting
Authors: Brown Jennifer L. , Lin K. C. , Moore Jared A. , Wellman Laura A. 
Published: September 2021

ABSTRACT
This study examines the impact of tax policy uncertainty (TPU) on analysts' forecasts and managers' interim estimates of effective tax rates (ETRs). We adopt a broad definition of TPU that encompasses both the legislative and regulatory processes and perform tests to validate a news-based measure of TPU consistent with our definition. We document that (1) analysts' implied ETR forecasts are less accurate and more disperse during periods of high TPU, (2) managers' ETR estimates are less accurate during periods of high TPU, and (3) the presence of relatively inaccurate management ETR estimates strengthens the effects of TPU on analysts' ETR forecasts. We further find that firm-level tax-related complexity exacerbates the effects of TPU on analysts' and managers' ETR predictions. Overall, our results are consistent with uncertainty surrounding tax policy impairing analysts' and managers' ability to assess and predict future tax-related fundamentals, thus imposing real costs on managers and market participants.
JEL Classifications: H25; G17; M41; D72; D81.