bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of Decision Support System Platform for Daily Dietary Plan
Authors: Javadi Bagher , Kooptiwoot Suwimon 
Published: March 2022

Background:
Solving health issues needs accurate and significant information regarding
food consumption. Recently, data analysis and communication have provided outstanding
and robust approaches to fulfill the necessity of scientific information and help in decisionmaking
in many fields. Many evidence has reported that with little information, better decisions
could be achieved.

Objective:
This research aimed to develop the Decision Support System (DSS) for the daily dietary
plan to practically help users in food consumption and health care.

Methods:
The system consists of 1,940 cuisine items, including Thai and English menus. In this
system, the user can set the daily dietary plan by selecting menu items with food-specific and total
calories. Overall calories of selected menu items would be calculated automatically. The user
can see the normal range of calories required based on gender with the help of the baseline (normal
office person).

Results:
This system can help users to become familiar with a better daily dietary plan, food calories,
and health care easily. Furthermore, experts (doctors) can improve their learning experiences
by formulating and adjusting the Decision Support System (DSS) for patients in special
need. The easiness and usefulness of this system are evaluated by 119 users using a Likert scale
(1=least, 5=most). The result, on average, is noted to be 4.58.

Conclusion:
The Decision Support System (DSS) is developed for the daily dietary plan. The accessibility
to the system is via personal computer (PC), smartphone, and tablet with an internet
connection. For future work, this DSS can improve by connecting the platform with health care
providers via sharing the data for more online support.
Isolation and Characterization of An Allergic Dimer Impurity in Cefmenoxime Hydrochloride by NMR and HR-MS Method
Authors: Xu Ming-Zhe , Li Jin , Yao Shang-Chen , Yin Li-hui , Hu Chang-Qin 
Published: March 2022

Background:
We systematically characterized an allergic dimer impurity in
cefmenoxime hydrochloride raw material by UV, IR, HR-MS, 1D, and 2D NMR for the first
time.

Methods:
The dimer stock solution of cefmenoxime hydrochloride was obtained by the degradation
method. The target dimer impurity in the stock solution was separated by preparative
RP-HPLC and purified by the freeze-drying method. By comparing the dimer to cefmenoxime
hydrochloride, the functional groups corresponding to the characteristic peaks of UV and IR
spectra were identified, and the molecular formula and mass fragmentation pattern were determined
using HR-MS.

Results:
Then, based on the full assignment of 1H and 13C NMR signals， the dimerized position
was confirmed and its absolute configuration was identified by 1D and 2D NMR.

Conclusion:
This study provided a structural basis for the allergic study of dimer impurities in
cephalosporin drugs.
iATC-NFMLP: Identifying Classes of Anatomical Therapeutic Chemicals
Based on Drug Networks, Fingerprints, and Multilayer Perceptron
Authors: Tang Shunrong , Chen Lei 
Published: March 2022

Background:
The Anatomical Therapeutic Chemicals (ATC) classification system is a
widely accepted drug classification system. It classifies drugs according to the organ or system in
which they can operate and their therapeutic, pharmacological, and chemical properties. Assigning
drugs into 14 classes in the first level of the system is an essential step to understanding drug properties. Several multi-label classifiers have been proposed to identify drug classes. Although their performance was good, most classifiers directly only adopted drug relationships or the features derived from
these relationships, but the essential properties of drugs were not directly employed. Thus, classifiers
still have a space for improvement.

Objective:
The aim of this study was to build a novel and powerful multilabel classifier for identifying
classes in the first level of the ATC classification system for given drugs

Methods:
A powerful multi-label classifier, namely, iATC-NFMLP, was proposed. Two feature types
were adopted to encode each drug. The first type was derived from drug relationships via a network
embedding algorithm, whereas the second one represented the fingerprints of drugs. Multilayer perceptron using sigmoid as the activating function was used to learn these features for the construction of the
classifier.

Results:
The 10-fold cross-validation results indicated that a combination of the two feature types could
improve the performance of the classifier. The jackknife test on the benchmark dataset with 3883 drugs
showed that the accuracy and absolute true were 82.76% and 79.27%, respectively.

Results:
The 10-fold cross-validation results indicated that a combination of the two feature types could
improve the performance of the classifier. The jackknife test on the benchmark dataset with 3883 drugs
showed that the accuracy and absolute true were 82.76% and 79.27%, respectively.

Conclusion:
The performance of iATC-NFMLP was best compared with all previous classifiers
Overview of Key Technologies for Torque Ripple Suppression in Four-
Wheel In-Wheel Motor Drive Electric Vehicles
Authors: Wang Pan , Fan Xiaobin , Zhu Shuaiwei 
Published: March 2022

Aims and Objectives:
The stability control of the four-wheel hub motor-driven electric
vehicle is of great significance to the safety of the driver during the driving process, and the
torque fluctuation is an important factor that affects the stability control of the vehicle. Therefore,
this paper reviews the key technologies and difficulties of torque ripple suppression for in-wheel
motor-driven electric vehicles from two aspects: rational design of the in-wheel motor structure to
suppress the torque fluctuation of the motor and the in-wheel motor torque control distribution
strategy.

Methods:
Through the analysis of the structural characteristics of the motor, the structural optimization
design of the pole slot, cogging, core shape, and magnetic pole shape is used to suppress
the torque fluctuation of the motor, and the methods of previous scholars are unified and explained;
From the motor control strategy, summed up the scholars in the motor torque ripple suppression
method strategy; From the perspective of motor torque control allocation strategy, a series
of related strategies are elaborated. The previous researchers proposed the neural network
PID electronic differential speed torque comprehensive control strategies, electronic differential
control algorithms based on sliding mode control, automotive electronic stability program control
algorithms based on hierarchical coordinated control strategies, and other control strategies and
algorithms.

Results:
Based on the theoretical model, the theoretical model is verified and tested through software
simulation or test platform. The errors of all simulation and test results in the literature and
the theoretical model are within the acceptable range.

Conclusion:
The theoretical model has been verified on the software simulation or test platform,
which proves the feasibility and effectiveness of the theoretical model, thereby suppressing torque
fluctuations and improving the stability of the vehicle. Finally, the development direction of the
key technology of torque ripple suppression for four-wheel in-wheel motor-driven electric vehicles
has been prospected.
Understanding the Molecular Mechanisms of Betel miRNAs on Human
Health
Authors: Manvar Toral , Mangukia Naman , Patel Saumya , Rawal Rakesh 
Published: March 2022

Background:
Since ancient times, "betel leaf" (Piper betle) has been revered for its reli-gious, cultural, and medicinal properties. Phytochemicals from the Piper betle are effective in a variety of conditions, including cancer. To date, however, no genomic study or evidence has been found to elucidate the regulatory mechanism that underpins its therapeutic properties. This is the first study of its kind to predict Piper betle miRNAs and also the first genomics source representation of Piper betle. According to previous research, miRNAs from the plants we eat can regulate gene expression. In line with this, our in-silico study revealed that Piper betle and human cross-kingdom control occurs.

Method:
This study demonstrates the prediction and in-silico validation of Piper betle miRNAs from NGS-derived transcript sequences. The cross-kingdom regulation, which can also be understood as in-ter-species RNA regulation, was studied to identify human mRNA targets controlled by Piper betle miRNAs. Functional annotation and gene-disease association of human targets were performed to un-derstand the role of Piper betle miRNAs in human health and disease. The protein-protein interaction and expression study of targets was further carried out to decipher their role in cancer development.

Results:
Identified six Piper betle miRNAs belonging to miR156, miR164, miR172, and miR535 fami-lies were discovered to target 198 human mRNAs involved in various metabolic and disease processes. Angiogenesis and the cell surface signaling pathway were the most enriched gene ontology correlated with targets, both of which play a critical role in disease mechanisms, especially in the case of carci-noma. In an analysis of gene-disease interactions, 40 genes were found to be related to cancer. Accord-ing to a protein-protein interaction, the CDK6 gene, which is thought to be a central regulator of cell cycle progression, was found as a hub protein, affecting the roles of CBFB, SAMD9, MDM4, AXIN2, and NOTCH2 oncogenes. Further investigation revealed that pbe-miRNA164a can be used as a regula-tor to minimise disease severity in Acute Myeloid Leukemia, where CDK6 expression is highest com-pared to normal cells.

Conclusion:
The predicted pbe-miRNA164a in this study can be a promising suppressor of CDK6 gene involved in tumour angiogenesis. In vivo validation of the pbe-miRNA164a mimic could pave the way for new opportunities to fight cancer and leverage the potential of Piper betle in the healthcare sector.
Therapeutic Effects of Gut Microbiota on Metabolic Syndrome: A Patent
Review
Authors: Singhal Shivani , Rani Vibha 
Published: March 2022

Background:
The balanced composition of the gut microbiota is essential for human
health. The dysbiotic condition may develop various complex diseases. A metabolic syndrome is
a group of biochemical and physiological abnormalities that can increase the risk of cardiovascular
diseases, diabetes, and inflammatory diseases. It has become a serious concern worldwide because
there is no acceptable medication to overcome this problem.

Objective:
This review aims to evaluate the relationship between gut microbiota and metabolic
syndrome. The balance of gut microbiota relates to human health as well as diseases. Patents related
to significant findings on probiotics, prebiotics, synbiotics, and fecal microbiota transplantation
signify the importance of the proposed theme and provide promising therapeutic strategies
to modulate the dysbiotic condition and reoccurrence of beneficial microbial species during metabolic
syndromes. Screening of patents-related databases can be worth full to track new technology.
Therefore, some selected recent patents related to gut microbiota and associated therapies
have been discussed in the present manuscript.

Conclusion:
Under the existing situation, the role of gastrointestinal microbiota as a therapeutic
agent is becoming more utilized for treating human health issues and various metabolic syndromes
including obesity, diabetes, and cardiovascular diseases. Understanding gut dysbiosis
and associated complex interactions between microbes and hosts would be effective for designing
future therapeutic interventions for metabolic syndrome. Our detailed patent analysis reflects
that gut dysbiosis has a prominent role in metabolic syndromes and dietary therapeutic strategies
can improve health by modulating the human microbiota, their metabolites ad stability.
Development of a Connected Sensor System in Colorectal Surgery: User-Centered Design Case Study
Authors: Schwartz-Lasfargues Christel , Roux-Gendron Camille , Edomskis Pim , Marque Isabelle , Bayon Yves , Lange Johan F , Faucheron Jean Luc , Trilling Bertrand 
Published: March 2022

Background
A successful innovative medical device is not only technically challenging to develop but must also be readily usable to be integrated into health care professionals’ daily practice. Through a user-centered design (UCD) approach, usability can be improved. However, this type of approach is not widely implemented from the early stages of medical device development.

Objective
The case study presented here shows how UCD may be applied at the very early stage of the design of a disruptive medical device used in a complex hospital environment, while no functional device is available yet. The device under study is a connected sensor system to detect colorectal anastomotic leakage, the most detrimental complication following colorectal surgery, which has a high medical cost. We also aimed to provide usability guidelines for the initial design of other innovative medical devices.

Methods
UCD was implemented by actively involving health care professionals and all the industrial partners of the project. The methodology was conducted in 2 European hospitals: Grenoble-Alpes University Hospital (France) and Erasmus Medical Center Rotterdam (the Netherlands). A total of 6 elective colorectal procedures and 5 ward shifts were observed. In total, 4 workshops were conducted with project partners and clinicians. A formative evaluation was performed based on 5 usability tests using nonfunctional prototype systems. The case study was completed within 12 months.

Results
Functional specifications were defined for the various components of the medical device: device weight, size, design, device attachment, and display module. These specifications consider the future integration of the medical device into current clinical practice (for use in an operating room and patient follow-up inside the hospital) and interactions between surgeons, nurses, nurse assistants, and patients. By avoiding irrelevant technical development, this approach helps to promote cost-effective design.

Conclusions
This paper presents the successful deployment over 12 months of a UCD methodology for the design of an innovative medical device during its early development phase. To help in reusing this methodology to design other innovative medical devices, we suggested best practices based on this case.
Mechanism of Impact of Big Data Resources on Medical Collaborative Networks From the Perspective of Transaction Efficiency of Medical Services: Survey Study
Authors: Yuan Junyi , Wang Sufen , Pan Changqing 
Published: March 2022

Background
The application of big data resources and the development of medical collaborative networks (MCNs) boost each other. However, MCNs are often assumed to be exogenous. How big data resources affect the emergence, development, and evolution of endogenous MCNs has not been well explained.

Objective
This study aimed to explore and understand the influence of the mechanism of a wide range of shared and private big data resources on the transaction efficiency of medical services to reveal the impact of big data resources on the emergence and development of endogenous MCNs.

Methods
This study was conducted by administering a survey questionnaire to information technology staff and medical staff from 132 medical institutions in China. Data from information technology staff and medical staff were integrated. Structural equation modeling was used to test the direct impact of big data resources on transaction efficiency of medical services. For those big data resources that had no direct impact, we analyzed their indirect impact.

Results
Sharing of diagnosis and treatment data (β=.222; P=.03) and sharing of medical research data (β=.289; P=.04) at the network level (as big data itself) positively directly affected the transaction efficiency of medical services. Network protection of the external link systems (β=.271; P=.008) at the level of medical institutions (as big data technology) positively directly affected the transaction efficiency of medical services. Encryption security of web-based data (as big data technology) at the level of medical institutions, medical service capacity available for external use, real-time data of diagnosis and treatment services (as big data itself) at the level of medical institutions, and policies and regulations at the network level indirectly affected the transaction efficiency through network protection of the external link systems at the level of medical institutions.

Conclusions
This study found that big data technology, big data itself, and policy at the network and organizational levels interact with, and influence, each other to form the transaction efficiency of medical services. On the basis of the theory of neoclassical economics, the study highlighted the implications of big data resources for the emergence and development of endogenous MCNs.
Delivery of a Mental Health Intervention for Chronic Pain Through an Artificial Intelligence–Enabled App (Wysa): Protocol for a Prospective Pilot Study
Authors: Gupta Megha , Malik Tanya , Sinha Chaitali 
Published: March 2022

Background
Patients with chronic pain often experience coexisting, long-term and debilitating mental health comorbidities such as depression and anxiety. Artificial intelligence–supported cognitive behavioral therapy (AI-CBT) interventions could offer cost-effective, accessible, and potentially effective resources to address this problem. However, there is not enough research conducted about the efficacy of AI-CBT interventions for chronic pain.

Objective
This prospective cohort study aims to examine the efficacy and use of an AI-CBT intervention for chronic pain (Wysa for Chronic Pain app, Wysa Inc) using a conversational agent (with no human intervention). To the best of our knowledge, this is the first such study for chronic pain using a fully-automated, free-text–based conversational agent.

Methods
Participants with self-reported chronic pain (n=500) will be recruited online on a rolling basis from April 2022 through posts on US-based internet communities within this prospective cohort. Informed consent is received from participants within the app, and the Wysa for Chronic Pain intervention is delivered remotely for 8 weeks. Outcome measures including a numeric pain rating scale and Patient-Reported Outcomes Measurement Information System–Pain Interference, Generalized Anxiety Disorder–7, and Patient Health Questionnaire–9 questionnaires administered to test the effectiveness of the intervention on reducing levels of pain interference, depression, and anxiety. The therapeutic alliance created with the conversational agent will be assessed through the Working Alliance Inventory–Short Revised instrument. Retention and use statistics will be observed for adherence and engagement.

Results
The study will open for recruitment in April 2022, and data collection is expected to be completed by August 2022. The results for the primary outcomes are expected to be published by late 2022.

Conclusions
Mental health conversational agents driven by artificial intelligence could be effective in helping patients with chronic pain learn to self-manage their pain and common comorbidities like depression and anxiety. The Wysa for Chronic Pain app is one such digital intervention that can potentially serve as a solution to the problems of affordability and scalability associated with interventions that include a human therapist. This prospective study examines the efficacy of the app as a treatment solution for chronic pain. It aims to inform future practices and digital mental health interventions for individuals with chronic pain.

International Registered Report Identifier (IRRID)
PRR1-10.2196/36910
The Pattern of Hypertension Drug Utilization in Public Health Center in the Medan City
Authors: Wahyuni Sri , K Khairunnisa , U Harahap 
Published: March 2022

Background: Hypertension is a disease thatcan causes death as much as 12.8% worldwide. Hypertension is a silent killer that causes complications in Hypertension patients. Complications can be prevented by using anti-hypertension drugs. The aimed of this study was to describe the pattern of drug utilization in several Public health centers in Medan.
Method: This non-experimental study involved 109 hypertension patients using cross-sectional methods. Samples were collected at several health centers in August and September 2020 using convenience sampling techniques.
Result: The results showed that the single drug type that was most widely used in this study was the Calcium Channel Blocker (CaCB) group (57.8%). The most widely used combination antihypertension drugs were Calcium Channel Blocker (CaCB) and Angiotensin 2 Recep`tor Blocker (ARB) (15.6%).
Conclusion: Based on the study results, it can be concluded that the pharmacologic management of antihypertension uses a single anti-hypertension drug (monotherapy) is more than the use of combination drugs (polytherapy).
Anti Inflammatory Potential of Euphoria Hirta L. Leaves In Jaipur Region
Authors: Verma Gunjan , Sharma Vandana , Pareek Ramesh 
Published: March 2022

Introduction: Euphorbia hirta Linn. (E.hirta L.) is a medicinal herb belonging to the family Euphorbiaceae. It is commomly known as Asthma plant, Duddhi, Bara duddhi. It has been claimed for the various medicinal properties such as inflammation, diarrhoea, bronchitis, kidney stones, peptic ulcer, menstrual problems etc.
Objective: the goal of our research work is to assessing the anti inflammatory activity of E.hirta L. leaves in regards to phytochemical studies.
Methods: The method carragennan induced paw edema in rats was used to assess the anti inflammatory activity of aqueous extract of E.hirta L. leaves. The extract was obtained by maceration method and the analysis of phytochemicals was carried out by performing different chemical test in laboratory. Crude aqueous extract was given orally at different doses of 100mg/kg, 300mg/kg and 500mg/kg in wistar albino rats 30mins before carragennan injection. Ibuprofen (50mg/kg) was taken as reference drug. The volume of paw edema was measured by using plethysmometer at 1, 2 and 3 hr after carragennan administration.
Results: The preliminary phytochemical study reveals the availibility of flavonoids, terpenoids, sterols, glycosides, tannins etc in different solvents of crude drug extract. The anti inflammatory effect of crude drug extract was exhibited a remarkable dose dependent reduction in paw edema volume. The inhibitory effect was highest at 500mg/kg dose of drug. Extract and ibuprofen showed 52% and 66% inhibition of paw edema respectively, at 3hr after carragennan administration.
Conclusion: E.hirta L. leaves aqueous extract has a strong anti inflammatory activity. These consequences help in the traditional uses of the plants and in the development of new treatments.