bluuebunny/crossref_metadata_2025 huggingface dataset:
Dairy fortification as a good option for dietary nutrition status improvement of 676 preschool children in China: A simulation study based on a cross-sectional diet survey (2018–2019)
Authors: Ding Ye , Han Fei , Xie Zhencheng , Li Genyuan , Zhuang Yiding , Yin Jia , Fu Mingxian , You Jialu , Wang Zhixu
Published: December 2022

Background

Chinese children are deficient in several essential nutrients due to poor dietary choices. Dairy products are a source of many under-consumed nutrients, but preschool children in China consume dairy products significantly less than the recommended level.

Methods

From the cross-sectional dietary intake survey of infants and young children aged 0–6 years in China (2018–2019), preschool children (age: 3–6 years) (n = 676) were selected. The four-day dietary data (including 2 working days and 2 weekends) collected through an online diary with reference to the food atlas were used for analysis and simulation. In scenario 1, individual intake of liquid milk equivalents was substituted at a corresponding volume by soymilk, cow’s milk, or formulated milk powder for preschool children (FMP-PSC). In scenario 2, the amount of cow’s milk or FMP-PSC increased to ensure each child’s dairy intake reached the recommended amount (350 g/day). In both scenarios, the simulated nutrient intakes and nutritional inadequacy or surplus were compared to the survey’s actual baseline data.

Results

It was suggested suggested that replacing dairy foods with FMP-PSC at matching volume is better than replacing them with soymilk or cow’s milk to increase the intake of DHA, calcium, iron, zinc, iodine, vitamin A, vitamin B1, vitamin B3, vitamin B12, vitamin C and vitamin D. Moreover, our results suggested that adding FMP-PSC to bring each child’s dairy intake to the recommended amount can bring the intakes of dietary fiber, DHA, calcium, iron, zinc, iodine, vitamin A, vitamin B1, vitamin B3, vitamin B9, vitamin B12, vitamin C and vitamin D more in line with the recommendations when compared with cow’s milk.

Conclusion

Accurate nutrition information should be provided to the parents of preschool children so as to guide their scientific consumption of dairy products and the usage and addition of fortified dairy products can be encouraged as needed.
Associations between serum soluble transferrin receptor and the prevalence of cancers
Authors: Zhang Yuzhuo , Xue Nianci , Jia Wenyu , Chen Xikang , Chen Xuezhang , Li Hongliang , Wang Bin , Guo Yi , Chen Ju , Tian Huaqin
Published: December 2022

Background

As increasing experimental evidence suggests that iron metabolism play crucial roles in cancer and non-cancer conditions, there is a lack of data on serum soluble transferrin receptor (sTfR), a promising marker representing unmet cellular iron demands, between cancer risk from epidemiological studies. Here, we aimed to evaluate the predictive value of sTfR and cancer prevalence.

Materials and methods

We analyzed on 5,480 adult participants from 2015 to 2018 National Health and Nutrition Examination Survey (NHANES). Spearman correlation analysis was performed to investigate the correlations between sTfR and other characteristics. To identify the associations between sTfR and the prevalence of cancers, stratified multivariable logistic regression models, subgroup and sensitivity analyses were also performed.

Results

In tertile analyses, participants in the highest level of sTfR were significantly associated with increased prevalence of total cancers [odds ratio (OR) = 1.53, 95% confidence interval (CI): 1.15-2.02] as compared with those at the lowest tertile. Each unit increment in ln-transformed sTfR concentration was shown to be associated with 39% increased risks of total cancers. Similar associations were found in males rather than females. Further subgroup and sensitivity analyses indicated that, in continuous and tertile analyses, sTfR was more closely associated with male- and female-specific cancers of prostate and testis (2.35: 1.03-5.40; 2.03: 1.00-4.09; respectively), and breast, cervix, ovary and uterus (1.92: 1.11-3.35; 1.66: 1.02-2.69; respectively).

Conclusions

Our findings suggested that elevated level of sTfR was associated with the prevalence of cancers, especially in sex-specific cancers. In order to better determine them, further research in humans will be required.
Durable effect of pyrotinib plus capecitabine in HER-2+ breast cancer patient undergoing peritoneal dialysis: A case report and literature review
Authors: Jin Xiangting , Yan Min , Li Fanfan
Published: December 2022

For patients with end-stage renal disease (ESRD), peritoneal dialysis (PD) and hemodialysis (HD) are important renal replacement treatments. Patients on dialysis usually have a high incidence rate of malignant tumors. In 2020, breast cancer has become the malignant tumor with the highest incidence rate in the world. Human epidermal growth factor receptor-2-positive (HER-2+) breast cancer accounts for 20%-30% of the total breast cancer patients. It is highly invasive and has a poor prognosis. Anti-HER-2 treatment is an important therapy for this type of cancer. There are few case reports of anti-HER2-targeted therapy in dialysis patients. We report a 56-year-old Chinese woman with breast cancer (cT3N1MX, Her-2+/HR-). She underwent peritoneal dialysis for 11 years since she had suffered end-stage renal disease. The clinician prescribed the regimen (pyrotinib 320mg qd + capecitabine 1g bid D1-D14 Q3W). The tumor was significantly reduced after 1 month of single administration of pyrotinib, and partially relieved after 2 months of pyrotinib + capecitabine. The main side effects were grade II hand foot syndrome and grade II diarrhea. This case shows that the combination of pyrotinib and capecitabine has potential therapeutic benefits in HER-2+ breast cancer patients with end-stage renal disease.
Case report: Clinical and single-cell transcriptome sequencing analysis of a mixed gangliocytoma-adenoma presenting as acromegaly
Authors: Li Chao , Feng Daqin , Zhou Dabiao
Published: December 2022

Background

Mixed gangliocytoma-adenoma (MGA) is a rare tumor of pituitary gland. It’s difficult to distinguish it from pituitary adenoma by clinical manifestations, imaging features or serological testing. Thus, the histopathological examination is still the golden standard for diagnosis. Besides, studies on molecular level are still lacking.

Case information

In this case report, we described a 28-year-old male with MGA presenting as acromegaly, who suffered staging operation and post-operation gamma knife radiosurgery, but finally died of secondary hyperglycemic hyperosmolar collapse. A complete data including clinical, histopathological, ultrastructural and single-cell transcriptome level information were collected and analyzed.

Conclusion

This case report detailed the only clinical and molecular report of MGA following operation and radiotherapy. Complete clinical data enhanced the understanding of the diagnosis and treatment of this disease. Besides, the single-cell transcriptome sequencing analysis further disclosed the intra-tumoral heterogeneity and provided support for subsequent basic research.
Incorporation of a machine learning pathological diagnosis algorithm into the thyroid ultrasound imaging data improves the diagnosis risk of malignant thyroid nodules
Authors: Li Wanying , Hong Tao , Fang Jianqiang , Liu Wencai , Liu Yuwen , He Cunyu , Li Xinxin , Xu Chan , Wang Bing , Chen Yuanyuan , Sun Chenyu , Li Wenle , Kang Wei , Yin Chengliang
Published: December 2022

Objective

This study aimed at establishing a new model to predict malignant thyroid nodules using machine learning algorithms.

Methods

A retrospective study was performed on 274 patients with thyroid nodules who underwent fine-needle aspiration (FNA) cytology or surgery from October 2018 to 2020 in Xianyang Central Hospital. The least absolute shrinkage and selection operator (lasso) regression analysis and logistic analysis were applied to screen and identified variables. Six machine learning algorithms, including Decision Tree (DT), Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), Naive Bayes Classifier (NBC), Random Forest (RF), and Logistic Regression (LR), were employed and compared in constructing the predictive model, coupled with preoperative clinical characteristics and ultrasound features. Internal validation was performed by using 10-fold cross-validation. The performance of the model was measured by the area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, F1 score, Shapley additive explanations (SHAP) plot, feature importance, and correlation of features. The best cutoff value for risk stratification was identified by probability density function (PDF) and clinical utility curve (CUC).

Results

The malignant rate of thyroid nodules in the study cohort was 53.2%. The predictive models are constructed by age, margin, shape, echogenic foci, echogenicity, and lymph nodes. The XGBoost model was significantly superior to any one of the machine learning models, with an AUC value of 0.829. According to the PDF and CUC, we recommended that 51% probability be used as a threshold for determining the risk stratification of malignant nodules, where about 85.6% of patients with malignant nodules could be detected. Meanwhile, approximately 89.8% of unnecessary biopsy procedures would be saved. Finally, an online web risk calculator has been built to estimate the personal likelihood of malignant thyroid nodules based on the best-performing ML-ed model of XGBoost.

Conclusions

Combining clinical characteristics and features of ultrasound images, ML algorithms can achieve reliable prediction of malignant thyroid nodules. The online web risk calculator based on the XGBoost model can easily identify in real-time the probability of malignant thyroid nodules, which can assist clinicians to formulate individualized management strategies for patients.
Hepatocellular carcinoma complicated with huge posterior pancreas head lymph node metastasis and primary renal carcinoma: A case report
Authors: Chen Jun , Zhou Zhiyi , Chen Wenyan , Khan Abid Ali , Liu Zhikun , Wang Kai , Yang Fan , Xu Xiao
Published: December 2022

The incidence of hepatocellular carcinoma (HCC) associated with extrahepatic primary malignancy (EHPM) is extremely rare, especially for those that involve primary renal cell carcinoma (PRC). Here we present a case of a 66-year-old male who was diagnosed with HCC complicated with lymph node metastasis at posterior pancreas head and PRC. Biopsy results of the liver and the lymph node confirmed the diagnosis of HCC. The disease progressions of both HCC and PRC are controlled effectively following the initiation of comprehensive therapy including pembrolizumab, lenvatinib, radiotherapy, and transcatheter arterial chemo-embolization (TACE). Ultimately, the patient had successfully access to surgery and complete response (CR) of all the tumors were achieved after surgery.
Clustering and molecular states in neutron rich nuclei
Authors: Gnoffo B. , Pirrone S. , Politi G. , Cardella G. , De Filippo E. , Geraci E. , Maiolino C. , Martorana N. S. , Pagano A. , Pagano E. V. , Papa M. , Risitano F. , Rizzo F. , Russotto P. , Trimarchi M.
Published: December 2022

An investigation plan of different clustering and molecular states in neutron rich isotopes of Lithium, Beryllium, Boron and Carbon, in the context of an experimental campaign at INFN-Laboratori Nazionali del Sud, is presented. High statistics and new information on known states and study on new states will be possible thanks to the high intensities available for the exotic beams, delivered by the FRAISE facility and thanks to the opportunity of using very performing experimental apparatus, as well as the detectors CHIMERA, FARCOS, and NArCOS. Among these, the new hodoscope NArCOS, by detecting with high efficiency neutrons and providing high energy and angular resolutions, will allow also a precise study of reaction channels characterized by neutron emission.
An established protocol for generating transgenic wheat for wheat functional genomics via particle bombardment
Authors: Wang Yaqiong , Zeng Jian , Su Peipei , Zhao Hongyan , Li Li , Xie Xiaoxue , Zhang Qian , Wu Ya’nan , Wang Ruibin , Zhang Yufan , Yu Boju , Chen Mingjie , Wang Yuesheng , Yang Guangxiao , He Guangyuan , Chang Junli , Li Yin
Published: December 2022

Wheat is one of the most important food crops in the world and is considered one of the top targets in crop biotechnology. With the high-quality reference genomes of wheat and its relative species and the recent burst of genomic resources in Triticeae, demands to perform gene functional studies in wheat and genetic improvement have been rapidly increasing, requiring that production of transgenic wheat should become a routine technique. While established for more than 20 years, the particle bombardment-mediated wheat transformation has not become routine yet, with only a handful of labs being proficient in this technique. This could be due to, at least partly, the low transformation efficiency and the technical difficulties. Here, we describe the current version of this method through adaptation and optimization. We report the detailed protocol of producing transgenic wheat by the particle gun, including several critical steps, from the selection of appropriate explants (i.e., immature scutella), the preparation of DNA-coated gold particles, and several established strategies of tissue culture. More importantly, with over 20 years of experience in wheat transformation in our lab, we share the many technical details and recommendations and emphasize that the particle bombardment-mediated approach has fewer limitations in genotype dependency and vector construction when compared with the Agrobacterium-mediated methods. The particle bombardment-mediated method has been successful for over 30 wheat genotypes, from the tetraploid durum wheat to the hexaploid common wheat, from modern elite varieties to landraces. In conclusion, the particle bombardment-mediated wheat transformation has demonstrated its potential and wide applications, and the full set of protocol, experience, and successful reports in many wheat genotypes described here will further its impacts, making it a routine and robust technique in crop research labs worldwide.
Creation and validation of the Chinese regulatory focus in relationships scale across multiple relationships context
Authors: Li WeiWei , He XiaoQi , Wang Yun , Zeng XiHua
Published: December 2022

A regulatory focus in relationships motivates individuals to be concerned about the presence/absence of positives (promotion focus)/negatives (prevention focus) in social interactions. How to capture the regulatory focus in relationships remains unclear. Based on regulatory focus theory, we created a regulatory focus in relationships scale (RFRS) with a sample of Chinese undergraduates. The RFRS included four subscales of interpersonal relationships (parent–child, teacher-student, friend, classmate), each of which consists of a model of promotion-prevention focus. With a series of interviews and tests, we found that the RFRS had acceptable validation and reliability. And promotion-prevention focus in relationships is context-dependent: Chinese undergraduates hold high promotion and low prevention focus for parents, friends, and classmates, while they hold high prevention focus and low promotion focus for teachers. The regulatory focus in relationships newly created can be used for future studies to test relational motivation in the specific interpersonal context.
Analysis of the impact of social insurance on farmers in China: A study exploring subjective perceptions of well-being and the mechanisms of common prosperity
Authors: Cheng Yongsheng , Zhang Deyuan
Published: December 2022

Objective

Exploring common prosperity in China, this study focuses on the impact of social pension insurance on the well-being of rural communities. It explores the direct beneficiaries and policy effects of the Rural Social Pension Insurance system (RSPI), which was piloted in 2009 and achieved full coverage in 2012. It summarizes the performance and implementation of social pension insurance and the development of the rural social pension system.

Methods

The article uses microdata from the four most recent periods of China Family Panel Studies (CFPS), which were undertaken in 2012, 2014, 2016, and 2018, and uses the Order Probit model to analyze the effects of participating in insurance on rural residents in terms of their subjective well-being. The study identifies diverse effects on farmers from different age groups, genders, and regions, with a focus on subjective well-being. The article also tests the mediating effects of health status and self-rated social status on farmers’ subjective well-being and their mechanisms of action.

Results

Findings reveal that participating in the insurance system significantly improved the subjective well-being of rural residents. Its biggest beneficiaries were groups of rural residents with poor health status, living in good overall conditions. Taking into account the most recent aims of this policy, to promote rural revitalization and common prosperity, further optimization of the rural pension insurance system should improve the living standards of low-income groups, enabling more comprehensive coverage, and potentially helping to mitigate the risk of returning to poverty due to illness.

Conclusion

Developments in basic social security and the rural basic pension system could effectively guarantee the basic standards of living of rural residents. Future development of the system should take into account the heterogeneous characteristics of rural residents and implement social pension protection policies in accordance with local conditions.
Influence of family cohesion on Chinese adolescents’ engagement in school bullying: A moderated mediation model
Authors: Chen Xin , Jiang Jiarui , Li Zuoshan , Gong Yue , Du Jiangli
Published: December 2022

In this study, a total number of 1,026 Chinese adolescents were surveyed using the cohesion sub-scale of the Family Environment Scale, the Self-control Scale, the Parental Monitoring Questionnaire, and the revised Olweus Bully/Victim Questionnaire to explore the effects of family cohesion on adolescents’ engagement in school bullying and the mechanisms of self-control and parental monitoring in the relationship between them. The results showed that: (1) family cohesion, self-control, and parental monitoring were significantly and negatively related to school bullying; (2) family cohesion directly influenced school bullying and also indirectly influenced school bullying through a mediating effect – self-control; (3) parental monitoring played a moderating role in the path of self-control affecting school bullying. Therefore, to reduce the occurrence of school bullying, it is necessary to strengthen the self-control ability of adolescents and improve the family cohesion environment and maintain a moderate level of parental monitoring. The results of this study revealed the effect of family cohesion on adolescents’ engagement in school bullying and its mechanism of action, which can provide a theoretical basis for preventing and reducing the occurrence of school bullying incidents.
A configurational analysis on career success of scientific and technological innovation talents in universities
Authors: Qu Guoli , Sun Bingyue , He Dan , Guo Xingxing
Published: December 2022

Introduction

Increasing the career success of scientific and technological innovation talents has become an important means of keeping and using talents in countries around the world. However, the problem has not been solved effectively.

Methods

Thirty-five cases were chosen in this study. The combined effects of human capital, psychological capital, micro-social capital, team social capital, and macro-social capital on the career success of scientific and technological innovation talents, as well as relevant influencing mechanisms, were discussed using qualitative comparative analysis (QCA).

Results

Results demonstrate that: (a) while a single factor cannot be the only condition for the high career success of scientific and technological innovation talents in universities, increasing macro-social capital plays a relatively universal role in a high career success rate. (b) There are three paths driving the high career success of scientific and technological innovation talents in universities. (c) There are two paths driving the non-high career success of scientific and technological innovation. Both have characteristics of absent psychological capital and micro-social capital. Moreover, the driving mechanism of high career success has an asymmetrical causal relationship.

Discussion

Research conclusions are not only conducive to expanding the research perspectives of social capital theory and career success, but also provide valuable insight into how to stimulate the career success of scientific and technological innovation talents in universities.
Facilitating factors for seeking help for mental health problems among Norwegian adolescent males: A focus group interview study
Authors: Slotte Sebastian , Ramsøy-Halle Hege , Melby Line , Kaasbøll Jannike
Published: December 2022

Background

Young males are overrepresented in suicide statistics and underrepresented in statistics of help-seeking and receiving help from formal health services compared with young females. Few studies have examined facilitating factors for help-seeking among adolescent males with no previous experience seeking mental health help. This study aimed to explore thoughts, attitudes, and experiences regarding facilitating factors toward formal help-seeking for mental health problems among Norwegian adolescent males.

Method

Three focus group interviews were conducted, each including four adolescent males with no experience with help-seeking or receiving help from a help service for mental health problems. The interviews addressed topics such as barriers and facilitating factors for help-seeking and preferences regarding structural factors and modes of delivery of help. Data were analyzed according to the systematic text condensation method.

Results

The analysis revealed three main categories of facilitating factors: (1) transparent information and available help services, (2) proactive and outreaching help services, and (3) the possibility for discreet help-seeking.

Conclusions

Improving help-seeking is integral to accessing care and improving mental health. Help services can be more accessible and approachable for male adolescents if they offer discretion, the possibility to remain anonymous, the option to receive help in a convenient context, and outreach services.
Individual strategies in the rat gambling task are related to voluntary alcohol intake, but not sexual behavior, and can be modulated by naltrexone
Authors: Tjernström Nikita , Roman Erika
Published: December 2022

Introduction

Gambling disorder (GD) is the first non-substance or behavioral addiction to be included in substance-related and addictive disorders in DSM-5. Since GD is a younger phenomenon relative to alcohol and substance use disorders, little is known about potential unique features in GD and to what extent characteristics are shared with alcohol and substance use disorders. The rat gambling task (rGT) is used to study decision-making in rats. This study aimed to identify individual differences in rGT strategies and explore the stability of these strategies over time. Moreover, motor impulsivity, sexual behavior, and voluntary alcohol intake were examined in rats with different rGT strategies. Finally, the response to naltrexone on performance in rats with different rGT strategies was investigated.

Methods

Male Lister hooded rats (n = 40) underwent repeated testing in the rGT, repeated copulatory behavioral tests, and 7 weeks of voluntary alcohol intake through a modified intermittent two-bottle free-choice paradigm. Finally, rats were treated with naltrexone prior to testing in the rGT.

Results

The results revealed individual choice strategies in the rGT that were stable over time, even after multiple interruptions and other behavioral testing. The rats with a risky choice strategy displayed higher motor impulsivity and voluntary alcohol intake than the other groups. No difference in sexual behavior was found between the different rGT groups. Finally, in all rats irrespectively of rGT strategy, treatment with naltrexone decreased the number of completed trials and premature responses, and increased omissions, which indicates an overall lowered motivation.

Discussion

In conclusion, rats with risky rGT strategies had higher voluntary alcohol intake but not elevated sexual behavior, indicating shared underlying mechanisms between rGT strategies and alcohol intake but not natural rewards in terms of sexual behavior. Finally, naltrexone treatment resulted in an overall lowered motivation in the rGT.
Assessing the impact of stigma reduction interventions in Iran: A qualitative study from the perspective of mental health stakeholders
Authors: Hajebi Ahmad , Hashemian Seyed Sepehr , Abolhassani Moussa , Hajebi Amirali , Alizadeh Kamyab , Rahnejat Amir Mohsen , Khademi Mojgan , Taghva Arsia
Published: December 2022

Introduction

The fear and embarrassment associated with stigmas discourage patients from help seeking behavior, which may explain why even the patients' loved ones advise them to discontinue treatment to avoid being labeled. In addition, stigmas can lead to personal and family issues, causing patients to disregard their illness. As such, their disease may develop into a chronic condition. This being said, the present study aims to investigate the challenges, solutions, and successes associated with stigmatization in Iran from the perspective of mental health stakeholders.

Method

A qualitative study was conducted in the summer of 2022. Purposive sampling was utilized to recruit participants. The primary data collection method involved a focus group interview that lasted 110 min. The project manager monitored the interviews, and all research team members attended the meetings, took notes, and made the necessary preparations. After explaining the study's purpose and ensuring the data's confidentiality, the interviewer led a focus group discussion. The interviews were recorded with the participants' consent. A focus group was used to conduct interviews with 13 individuals until data saturation was reached.

Findings

Ten psychologists, psychiatrists, and managers responsible for mental health, two patients, and one patient's family member participated in the current study as eligible participants. Repeated readings led to the emergence of three main classes under the headings of challenges, solutions, and successes of stigma management in Iran, each containing subclasses.

Conclusion

The majority of the proposed solutions in this study centered on raising awareness and training diverse individuals and groups to lessen stigmas. The most crucial de-stigmatization measure is to offer training that will cause the current stereotypes to change. This must be taken by patients and their families as well as therapists, leaders, policymakers, the general public, and the media. Ideally, younger members of the target groups should be considered for these pieces of training, which must be based on research and derived from cultural and localized needs.
Scaling up community-delivered mental health support and care: A landscape analysis
Authors: Siddiqui Saher , Morris Angelika , Ikeda Daniel J. , Balsari Satchit , Blanke Laura , Pearsall Miriam , Rodriguez Roxanna , Saxena Shekhar , Miller Benjamin F. , Patel Vikram , Naslund John A.
Published: December 2022

Introduction

The mental health crisis has caused widespread suffering and has been further exacerbated by the COVID-19 pandemic. Marginalized groups are especially affected, with many concerns rooted in social determinants of mental health. To stem this tide of suffering, consideration of approaches outside the traditional biomedical model will be necessary. Drawing from task-sharing models of mental health care that have been pioneered in low-resource settings, community-initiated care (CIC) represents a potentially promising collection of approaches. This landscape analysis seeks to identify examples of CIC that have been implemented outside of the research context, with the aim of identifying barriers and facilitators of scale up.

Methods

A narrative review approach was used for this landscape analysis in which the PubMed database was searched and further supplemented with Google Scholar. Promising programs were then discussed over multiple rounds of meetings with the research team, consisting of collaborators with varied experiences in mental health. Using the selection criteria and feedback derived from group meetings, a final list of programs was identified and summarized according to common characteristics and features.

Results

The initial PubMed search yielded 16 results, supplemented by review of the first 100 entries in Google Scholar. Through 5 follow-up meetings among team members, consensus was reached on a final list of 9 programs, which were grouped into three categories based on similar themes and topics: (1) approaches for the delivery of psychosocial interventions; (2) public health and integrative approaches to mental health; and (3) approaches for addressing youth mental health. Key facilitators to scale up included the importance of sustainable financing and human resources, addressing social determinants and stigma, engaging diverse stakeholders, leveraging existing health infrastructure, using sustainable training models, ensuring cultural relevance and appropriateness, and leveraging digital technologies.

Discussion

This landscape analysis, though not an exhaustive summary of the literature, describes promising examples of efforts to scale up CIC outside of the research context. Going forward, it will be necessary to mobilize stakeholders at the community, health system, and government levels to effectively promote CIC.
Physical ability, cervical function, and walking plantar pressure in frail and pre-frail older adults: An attentional focus approach
Authors: Pinloche Laurianne , Zhang Qingshan , Berthouze Sophie E. , Monteil Karine , Hautier Christophe
Published: December 2022

Aging and increased vulnerability define the clinical condition of frailty. However, while the cervical function is recognized as a determinant of balance and walking performance, no study simultaneously physical ability, cervical function, balance, and plantar pressure distribution in walking in nursing house population. Thus, the present study aimed to compare these parameters between Frail and Pre-Frail aged people. Thirty-one (12 men and 19 women) institutionalized participants (age: 89.45 ± 5.27 years, weight: 61.54 ± 9.99 kg, height: 160.34 ± 7.93 cm) were recruited and divided into Pre-Frail and Frail groups according to SPPB (Short Physical Performance Battery) score (Frail <6, Pre–Frail ≥6). Participants performed the Timed Up and Go Test (TUGT) and a static balance evaluation. The cervical range of motion (COM), knee extensor strength, and walking plantar pressure distribution have been measured. The Pre-Frail group showed a higher gait speed (ES = 0.78, p ≤ 0.001) and a better TUGT, as well as higher knee extensor strength (ES = 0.4, p = 0.04). Furthermore, the Pre-Frail group presented a center of pressure (COP) displacement velocity on the sagittal axis (ES = 0.43, p = 0.02) and a more COP projection on this axis (ES = 0.43, p = 0.02). No significant difference has been observed between the two groups concerning the total contact time and most of the plantar pressure parameters except for the rear foot relative contact time which was lower in the Pre-Frail group. The Pre-Frail group also showed better cervical tilt mobility (ES = 0.35, p = 0.04). This study highlights the influence of some new parameters on frailty in older people, such as cervical mobility and plantar pressure distribution in walking.
Voices of the Costa Rican scientific diaspora: Policy lessons from a decade of experiences from our scientists abroad
Authors: Jarquin-Solis Maria Esteli , Lin-Shiao Enrique , Guerra Melania , Calderón Zúñiga Karlissa , Mora Solórzano Dayana , Gutiérrez José María
Published: December 2022

Scientific diasporas have been identified as valuable resources to strengthen science, technology, and innovation in their countries of origin. In this context, our paper seeks to contribute by addressing the following research questions: What are the main features of the Costa Rican scientific diaspora, and what policy lessons can be extracted from their experiences abroad? Toward this goal, we analyzed ten years of diaspora perspectives as collected by TicoTal, an online database and network of Costa Rican scientists studying and working abroad created by the National Academy of Sciences (ANC) in 2010. Our study reveals the main features of the Costa Rican scientific diaspora using 121 interviews published over a ten-year period: we identified the academic areas in which the diaspora has specialized, the countries where they were trained, their current location, the most frequent funding mechanisms and sources that enabled professional opportunities abroad, the level of engagement and collaboration they maintain with the Costa Rican STI ecosystem, along with the incentives they consider important to support and harness the potential of this community to advance STI goals in the country. Results from this analysis can inform national policies and investment strategies in R&D infrastructure and resources, by providing a roadmap to engage with scientific diasporas and benefit from their training and talent, as well as guide future scholarship and exchange programs.
Towards reliable retrievals of cloud droplet number for non-precipitating planetary boundary layer clouds and their susceptibility to aerosol
Authors: Foskinis Romanos , Nenes Athanasios , Papayannis Alexandros , Georgakaki Paraskevi , Eleftheriadis Konstantinos , Vratolis Stergios , Gini Maria I. , Komppula Mika , Vakkari Ville , Kokkalis Panos
Published: December 2022

Remote sensing has been a key resource for developing extensive and detailed datasets for studying and constraining aerosol-cloud-climate interactions. However, aerosol-cloud collocation challenges, algorithm limitations, as well as difficulties in unraveling dynamic from aerosol-related effects on cloud microphysics, have long challenged precise retrievals of cloud droplet number concentrations. By combining a series of remote sensing techniques and in situ measurements at ground level, we developed a semi-automated approach that can address several retrieval issues for a robust estimation of cloud droplet number for non-precipitating Planetary Boundary Layer (PBL) clouds. The approach is based on satellite retrievals of the PBL cloud droplet number (Ndsat) using the geostationary meteorological satellite data of the Optimal Cloud Analysis (OCA) product, which is obtained by the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). The parameters of the retrieval are optimized through closure with droplet number obtained from a combination of ground-based remote sensing data and in situ observations at ground level. More specifically, the remote sensing data are used to retrieve cloud-scale vertical velocity, and the in situ aerosol measurements at ground level were used constrain as input to a state-of-the-art droplet activation parameterization to predict the respective Cloud Condensation Nuclei (CCN) spectra, cloud maximum supersaturation and droplet number concentration (Nd), accounting for the effects of vertical velocity distribution and lateral entrainment. Closure studies between collocated Nd and Ndsat are then used to evaluate exising droplet spectral width parameters used for the retrieval of droplet number, and determine the optimal values for retrieval. This methodology, used to study aerosol-cloud interactions for non-precipitating clouds formed over the Athens Metropolitan Area (AMA), Greece, during the springtime period from March to May 2020, shows that droplet closure can be achieved to within ±33.4%, comparable to the level of closure obtained in many in situ studies. Given this, the ease of applying this approach with satellite data obtained from SEVIRI with high temporal (15 min) and spatial resolution (3.6 km × 4.6 km), opens the possibility of continuous and reliable Ndsat, giving rise to high value datasets for aerosol-cloud-climate interaction studies.
A perspective on the Langmuir adsorption model applied to molecular liquid crystals containing ions and nanoparticles
Authors: Garbovskiy Yuriy
Published: December 2022

Electrical properties of molecular liquid crystals doped with nanomaterials have been extensively studied over the past two decades. In general, nanoparticles in liquid crystals can play a dual role acting as either ion capturing agents or ion generating objects. An interplay between ions and nanomaterials in liquid crystals can result in a great variety of nontrivial ionic effects. This perspective discusses the Langmuir adsorption model applied to describe ionic phenomena in molecular liquid crystals doped with nanoparticles. The applicability and limitations of this model are emphasized. Within a range of its applicability, the Langmuir adsorption model can be used to obtain a wealth of information about nanoparticle-induced ionic effects in molecular liquid crystals. In addition, this model also offers important improvements to standard experimental procedures for evaluation of electrical properties of advanced liquid crystal materials.
Seasonal prediction of Horn of Africa long rains using machine learning: The pitfalls of preselecting correlated predictors
Authors: Deman Victoria M. H. , Koppa Akash , Waegeman Willem , MacLeod David A. , Bliss Singer Michael , Miralles Diego G.
Published: December 2022

The Horn of Africa is highly vulnerable to droughts and floods, and reliable long-term forecasting is a key part of building resilience. However, the prediction of the “long rains” season (March–May) is particularly challenging for dynamical climate prediction models. Meanwhile, the potential for machine learning to improve seasonal precipitation forecasts in the region has yet to be uncovered. Here, we implement and evaluate four data-driven models for prediction of long rains rainfall: ridge and lasso linear regressions, random forests and a single-layer neural network. Predictors are based on SSTs, zonal winds, land state, and climate indices, and the target variables are precipitation totals for each separate month (March, April, and May) in the Horn of Africa drylands, with separate predictions made for lead-times of 1–3 months. Results reveal a tendency for overfitting when predictors are preselected based on correlations to the target variable over the entire historical period, a frequent practice in machine learning-based seasonal forecasting. Using this conventional approach, the data-driven methods—and particularly the lasso and ridge regressions—often outperform dynamical seasonal hindcasts. However, when the selection of predictors is done independently of both the train and test data, by performing this predictor selection within the cross-validation loop, the performance of all four data-driven models is poorer than that of the dynamical hindcasts. These findings should not discourage future applications of machine learning for rainfall forecasting in the region. Yet, they should be seen as a note of caution to prevent optimistically biased results that are not indicative of the true power in operational forecast systems.
Ergogenic effects of caffeine are mediated by myokines
Authors: Takada Shingo , Fumoto Yoshizuki , Kinugawa Shintaro
Published: December 2022

Exercise has long been known to effectively improve and enhance skeletal muscle function and performance. The favorable effects of exercise on remote organs other than skeletal muscle are well known, but the underlying mechanism has remained elusive. Recent studies have indicated that skeletal muscle not only enables body movement, but also contributes to body homeostasis and the systemic stress response via the expression and/or secretion of cytokines (so-called myokines). Not only the induction of muscle contraction itself, but also changes in intracellular calcium concentration ([Ca2+]i) have been suggested to be involved in myokine production and secretion. Caffeine is widely known as a Ca2+ ionophore, which improves skeletal muscle function and exercise performance (i.e., an “ergogenic aid”). Interestingly, some studies reported that caffeine or an increase in [Ca2+]i enhances the expression and/or secretion of myokines. In this review, we discuss the association between caffeine as an ergogenic aid and myokine regulation.
Landscape or local? Distinct responses of flower visitor diversity and interaction networks to different land use scales in agricultural tropical highlands
Authors: Escobedo-Kenefic Natalia , Casiá-Ajché Quebin Bosbely , Cardona Edson , Escobar-González Denisse , Mejía-Coroy Alfredo , Enríquez Eunice , Landaverde-González Patricia
Published: December 2022

Land use change has been identified as a cause for biodiversity loss and has significant effects on pollinators and their interactions with plants. Interaction network analyses complement diversity estimators by providing information on the stability and functionality of the plant-pollinator community in an ecosystem. However, how land use changes affect insect diversity, and the structure of their plant-insect interaction networks, could depend on the intensity of the disturbance but also may be a matter of scale. Our study was carried out in a tropical highland landscape dominated by intense, yet diverse, small-scale agriculture. We studied the effects of land use, at a landscape scale, and local cover and plant ecological descriptors, at a local scale; on diversity descriptors of insect pollinator communities, the abundance of the most frequent flower visitors, and their interaction networks. Seminatural vegetation favored insect flower visitors at both scales. At the landscape scale, human settlements positively influenced bee diversity, and seminatural areas favored the abundance of frequent hoverfly and bumblebee species. At the local scale, bare soil cover negatively influenced honeybee abundance while flower-rich covers positively related to bumblebee abundance. Only local scale variables had influence on network metrics. Bare soil cover was related to higher network specialization, probably due to a low rate of honeybee interactions. Flower-rich covers negatively influenced network connectance but favored modularity. These results suggest that flower resources, provided by weed areas and flowering crops, promote a high rate of interactions between trophic levels and a non-random structure in the interaction networks that may be helping to sustain network stability. Our results highlight the role of seminatural vegetation, at both scales, in maintaining stable insect pollinator communities and interactions in heterogeneous agricultural landscapes of the tropics.
A Momentum-Based Local Face Adversarial Example Generation Algorithm
Authors: Lang Dapeng , Chen Deyun , Huang Jinjie , Li Sizhao
Published: December 2022

Small perturbations can make deep models fail. Since deep models are widely used in face recognition systems (FRS) such as surveillance and access control, adversarial examples may introduce more subtle threats to face recognition systems. In this paper, we propose a practical white-box adversarial attack method. The method can automatically form a local area with key semantics on the face. The shape of the local area generated by the algorithm varies according to the environment and light of the character. Since these regions contain major facial features, we generated patch-like adversarial examples based on this region, which can effectively deceive FRS. The algorithm introduced the momentum parameter to stabilize the optimization directions. We accelerated the generation process by increasing the learning rate in segments. Compared with the traditional adversarial algorithm, our algorithms are very inconspicuous, which is very suitable for application in real scenes. The attack was verified on the CASIA WebFace and LFW datasets which were also proved to have good transferability.
Estimation of Clinch Joint Characteristics Based on Limited Input Data Using Pre-Trained Metamodels
Authors: Zirngibl Christoph , Schleich Benjamin , Wartzack Sandro
Published: December 2022

Given strict emission targets and legal requirements, especially in the automotive industry, environmentally friendly and simultaneously versatile applicable production technologies are gaining importance. In this regard, the use of mechanical joining processes, such as clinching, enable assembly sheet metals to achieve strength properties similar to those of established thermal joining technologies. However, to guarantee a high reliability of the generated joint connection, the selection of a best-fitting joining technology as well as the meaningful description of individual joint properties is essential. In the context of clinching, few contributions have to date investigated the metamodel-based estimation and optimization of joint characteristics, such as neck or interlock thickness, by applying machine learning and genetic algorithms. Therefore, several regression models have been trained on varying databases and amounts of input parameters. However, if product engineers can only provide limited data for a new joining task, such as incomplete information on applied joining tool dimensions, previously trained metamodels often reach their limits. This often results in a significant loss of prediction quality and leads to increasing uncertainties and inaccuracies within the metamodel-based design of a clinch joint connection. Motivated by this, the presented contribution investigates different machine learning algorithms regarding their ability to achieve a satisfying estimation accuracy on limited input data applying a statistically based feature selection method. Through this, it is possible to identify which regression models are suitable to predict clinch joint characteristics considering only a minimum set of required input features. Thus, in addition to the opportunity to decrease the training effort as well as the model complexity, the subsequent formulation of design equations can pave the way to a more versatile application and reuse of pretrained metamodels on varying tool configurations for a given clinch joining task.