bluuebunny/crossref_metadata_2025 huggingface dataset:
Relapse of severe acute malnutrition among children discharged from outpatient therapeutic program in western Ethiopia
Authors: Teshale Endalkachew Befekadu , Nigatu Yakob Desalegn , Delbiso Tefera Darge
Published: September 2023

Background

Children with severe acute malnutrition (SAM) without complication are treated in the outpatient therapeutic program (OTP) and the program has been reported to be effective. However, relapse post-discharge from the program is poorly defined, and scarcely evaluated across programs and research. The objective of this study is to assess the prevalence of SAM among children post-discharge from the OTP and to identify factors associated with SAM relapse in Gambella Region, Western Ethiopia.

Methods

We conducted a facility-based cross-sectional study among 208 children aged 6–59 months who have been discharged from the OTP as cured. Baseline data were collected from caregivers using structured questionnaire. Child anthropometry and oedema was measured. The association between SAM relapse and the risk factors were assessed using bivariate and multivariable logistic regression models.

Results

The prevalence of SAM relapse was 10.1% (95% CI: 5.8–14.0%). The odds of SAM relapse was significantly higher in children with mothers who had no exposure to education and promotion about infant and young child feeding (IYCF) practices (OR = 5.7; 95% CI: 1.3–12.6), children who were not fully immunized for their age (OR = 8.0; 95% CI: 3.8–23.4), and children with mid-upper arm circumference (MUAC) at discharge of < 12.5 cm (OR = 4.4; 95% CI: 2.1–12.8) than their counterparts.

Conclusions

To reduce SAM relapse, the OTP programs should avoid premature discharge and consider provision of supplementary food for children with low MUAC at discharge. Further, the OTP discharge criteria should consider both the anthropometric indicators – weight-for-height/length z-score (WHZ) and MUAC – and the absence of bilateral pitting oedema irrespective of the anthropometric indicator that is used during admission. Promotion of nutrition education and improving child immunization services and coverage would help reduce SAM relapse.
“Pouring their heart out in Sainsbury’s”: qualitative study of young people’s, parents’ and mental health practitioners’ experiences of adapting to remote online mental health appointments during COVID-19
Authors: Biddle Lucy , Derges Jane , Cliffe Bethany , Gooberman-Hill Rachael , Linton Myles-Jay , Moran Paul , Bould Helen
Published: September 2023

Background

During the COVID-19 pandemic, technologies such as videoconferencing were used to deliver mental health appointments remotely online. For many people, this was a change from previous methods of mental healthcare receipt and delivery. We aimed to explore in-depth how practitioners, young people and parents in the UK experienced this transition.

Methods

We used qualitative methods to collect data, triangulating between free-text online survey data (n = 38), focus groups (n = 5) (3 young adult groups (total n = 11); 2 practitioner groups (total n = 7)), and semi-structured interviews (practitioners n = 8; parents n = 4). Data were analysed using reflexive thematic analysis.

Results

Participants held mixed views about remote appointments, which were encompassed within the five themes of: home as clinic; disrupted therapeutic relationships; difficulties with engagement; uncontained risk; and scope of care provision. While appointments at home could be regarded as more comfortable, naturalistic and accessible, it was also recognised that remoteness compromised practitioner control with consequences for their ability to monitor patient engagement, manage risk and ensure confidentiality when others were present in the home. This could create an additional burden for parents as they tried to facilitate appointments but felt unsupported in this role. Relatedly, remoteness was seen to hinder interpersonal communication, formation of trust, communication of empathy and opportunities to observe body language, all of which were deemed important to building and maintaining effective therapeutic relationships. Despite this, others thought the anonymity of a remote exchange may allow earlier disclosure. There was disagreement as to whether remote provision narrowed or expanded the scope of practice.

Conclusions

While some had positive views of remote mental health appointments, others found them challenging. Findings highlight key areas requiring attention and mitigation in future offerings of remote provision, namely: risk management, parental burden, and problematic engagement.
Telemedicine treatment of patients with mental disorders during and after the first COVID-19 pandemic lockdown in Germany – an observational study on feasibility and patient satisfaction
Authors: Link Karsten , Christians Svenja , Hoffmann Wolfgang , Grabe Hans Jörgen , van den Berg Neeltje
Published: September 2023

Introduction

In response to the COVID-19 pandemic, a general lockdown was enacted across Germany in March 2020. As a consequence, patients with mental health conditions received limited or no treatment in day hospitals and outpatient settings. To ensure continuity of care, the necessary technological preparations were made to enable the implementation of telemedical care via telephone or video conferencing, and this option was then used as much as possible. The aim of this study was to investigate the satisfaction and acceptance with telemedical care in a heterogeneous patient group of psychiatric outpatients in Germany during the first COVID-19 lockdown.

Methods

In this observational study, patients in ongoing or newly initiated outpatient psychiatric therapy as well as those who had to be discharged from the day clinic ahead of schedule received telemedical treatment via telephone. Data collection to assess the patients’ and therapists’ satisfaction with and acceptance of the telemedical care was adjusted to the treatment setting.

Results

Of 60 recruited patients, 57 could be included in the analysis. 51.6% of the patients and 52.3% of their therapists reported that the discussion of problems and needs worked just as well over the phone as in face-to-face consultations. In the subgroup of patients who were new to therapy due to being discharged from hospital early, acceptance was higher and telemedicine was rated as equally good in 87.5% of contacts. Both patients and therapists felt that telemedicine care during lockdown was an alternative for usual therapy in the outpatient clinic and that the option of telemedicine care should continue for the duration of the coronavirus pandemic.

Discussion

The results show a clear trend towards satisfaction with and acceptance of telemedicine care in a heterogeneous group of unselected psychiatric patients. Although the number of patients is small, the results indicate that the mostly positive results of telemedicine concepts in research projects can probably be transferred to real healthcare settings.

Conclusions

Telemedicine can be employed in healthcare for psychiatric patients either an alternative treatment option to maintain continuity of care or as a potential addition to regular care.
Excess mortality during the Coronavirus disease pandemic in Korea
Authors: Han Changwoo , Jang Hoyeon , Oh Juhwan
Published: September 2023

Background

Although the ongoing epidemics of Coronavirus disease 2019 (COVID-19) may have affected the mortality trend of the nation, the national level assessment of excess mortality (changes in overall mortality in the entire population) is still scarce in Korea. Therefore, this study evaluated the excess mortality during the COVID-19 pandemic in Korea using the certified mortality data.

Methods

Monthly mortality and population data from January 2013 to June 2022 was obtained from the National Health Insurance Service database and Statistics Korea. A quasi-Poisson interrupted time-series model adjusted for age structure, population, seasonality, and long-term trends was used to estimate the counterfactual projections (expected) of mortality during the COVID-19 pandemic (March 2020 to June 2022). The absolute difference (observed—expected) and ratio (observed / expected) of mortality were calculated. Stratified analysis based on pandemic years (years 2020, 2021, and 2022), sex, and age groups (aged 0–4, 5–19, 20–64, and ≥ 65 years) were conducted.

Results

An 8.7% increase in mortality was observed during the COVID-19 pandemic [absolute difference: 61,277 persons; ratio (95% confidence interval (CI)): 1.087 (1.066, 1.107)]. The gap between observed and estimated mortality became wider with continuation of the pandemic [ratio (95% CI), year 2020: 1.021 (1.003, 1.040); year 2021: 1.060 (1.039, 1.080), year 2022: 1.244 (1.219, 1.270)]. Although excess mortality across sex was similar, the adult [aged 20–64, ratio (95% CI): 1.059 (1.043, 1.076)] and elderly [aged 65-, ratio (95% CI): 1.098 (1.062, 1.135)] population showed increased excess mortality during the pandemic.

Conclusions

Despite Korea's successful quarantine policy response, the continued epidemic has led to an excess mortality. The estimated mortality exceeded the number of deaths from COVID-19 infection. Excess mortality should be monitored to estimate the overall impact of the pandemic on a nation.
Development and validation of a novel nomogram to predict the risk of the prolonged postoperative length of stay for lumbar spinal stenosis patients
Authors: Yasin Parhat , Cai Xiaoyu , Mardan Muradil , Xu Tao , Abulizi Yakefu , Aimaiti Abasi , Yang Huan , Sheng Weibin , Mamat Mardan
Published: September 2023

Background

Lumber spinal stenosis (LSS) is the increasingly reason for spine surgery for elder patients since China is facing the fastest-growing aging population. The aim of this research was to create a model to predict the probabilities of requiring a prolonged postoperative length of stay (PLOS) for lumbar spinal stenosis patients, minimizing the healthcare burden.

Methods

A total of 540 LSS patients were enrolled in this project. The outcome was a prolonged PLOS after spine surgery, defined as hospitalizations ≥ 75th percentile for PLOS, including the day of discharge. The least absolute shrinkage and selection operator (LASSO) was used to identify independent risk variables related to prolonged PLOS. Multivariable logistic regression analysis was utilized to generate a prediction model utilizing the variables employed in the LASSO approach. The receiver operating characteristic (ROC) curve’s area under the curve (AUC) and the calibration curve’s respective curves were used to further validate the model’s calibration with predictability and discriminative capabilities. By using decision curve analysis, the resulting model’s clinical effectiveness was assessed.

Results

Among 540 individuals, 344 had PLOS that was within the usual range of P75 (8 days), according to the interquartile range of PLOS, and 196 had PLOS that was above the normal range of P75 (prolonged PLOS). Four variables were incorporated into the predictive model, named: transfusion, operation duration, blood loss and involved spine segments. A great difference in clinical scores can be found between the two groups (P < 0.001). In the development set, the model’s AUC for predicting prolonged PLOS was 0.812 (95% CI: 0.768–0.859), while in the validation set, it was 0.830 (95% CI: 0.753–0.881). The calibration plots for the probability showed coherence between the expected probability and the actual probability both in the development set and validation set respectively. When intervention was chosen at the potential threshold of 2%, analysis of the decision curve revealed that the model was more clinically effective.

Conclusions

The individualized prediction nomogram incorporating five common clinical features for LSS patients undergoing surgery can be suitably used to smooth early identification and improve screening of patients at higher risk of prolonged PLOS and minimize health care.
Scale development to measure the patient perception of patient-centered care of dentists in primary care settings of Thailand: a measurement invariance test
Authors: Khamnil Yutthana , Kao-iean Surasak , Pisarnturakit Pagaporn Pantuwadee
Published: September 2023

Background

Patient-centered care is essential for providing quality services thoroughly at the primary care level, but it is unclear and lacks measurement. This study aimed to develop a reliable and valid instrument to measure patient perception of patient-centered care in primary dental care in Thailand and test the measurement invariance between large and small community hospitals.

Methods

The initial set of 45 items for the patient perception of Patient-Centered Care of Dentist Scale (PCCDS-P version) was developed using a mixed-method approach, which included a literature review, a content validity test, cognitive interviews, and a pre-test. A multistage sampling strategy was used to recruit dental patients or their parents or caregivers from community hospitals across Thailand. Validity was examined through exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Reliability was assessed using Cronbach's alpha coefficient and the intraclass correlation coefficient. Furthermore, a multi-group analysis was conducted to compare the responses of patients from large and small community hospitals.

Results

Three hundred thirty-six and One thousand one hundred sixty-seven samples were randomized for EFA and CFA, respectively. The final PCCDS-P version consists of 7 factors with satisfactory reliability and validity and is composed of 42 items: dentist-patient relationship, disease-illness, integrated care, communication, shared information and decision-making, holistic, and empathy and anxiety management. The CFA showed the model fit was consistent with the entire sample. The metric invariance analysis showed that the factor loadings were invariant across patient groups. Overall, Cronbach's alpha coefficient and intraclass correlation coefficient were satisfactory.

Conclusions

The newly developed PCCDS-P version is composed of seven domains with 42 items with good reliability and validity, and it indicated measurement invariance across patients in large and small community hospitals.
Association of free-living diet composition with plasma lipoprotein(a) levels in healthy adults
Authors: Matveyenko Anastasiya , Seid Heather , Kim Kyungyeon , Ramakrishnan Rajasekhar , Thomas Tiffany , Matienzo Nelsa , Reyes-Soffer Gissette
Published: September 2023

Background

Lipoprotein (a) [Lp(a)] is an apoB100-containing lipoprotein with high levels being positively associated with atherosclerotic cardiovascular disease. Lp(a) levels are genetically determined. However, previous studies report a negative association between Lp(a) and saturated fatty acid intake. Currently, apoB100 lowering therapies are used to lower Lp(a) levels, and apheresis therapy is FDA approved for patients with extreme elevations of Lp(a). The current study analyzed the association of free-living diet components with plasma Lp(a) levels.

Methods

Dietary composition data was collected during screening visits for enrollment in previously completed lipid and lipoprotein metabolism studies at Columbia University Irving Medical Center via a standardized protocol by registered dietitians using 24 hour recalls. Data were analyzed with the Nutrition Data System for Research (Version 2018). Diet quality was calculated using the Healthy Eating Index (HEI) score. Fasting plasma Lp(a) levels were measured via an isoform-independent ELISA and apo(a) isoforms were measured using gel electrophoresis.

Results

We enrolled 28 subjects [Black (n = 18); Hispanic (n = 7); White (n = 3)]. The mean age was 48.3 ± 12.5 years with 17 males. Median level of Lp(a) was 79.9 nmol/L (34.4–146.0) and it was negatively associated with absolute (grams/day) and relative (percent of total calories) intake of dietary saturated fatty acids (SFA) (R = -0.43,P = 0.02, SFA …(% CAL): R = -0.38,P = 0.04), palmitic acid intake (R = -0.38,P = 0.05), and stearic acid intake (R = -0.40,P = 0.03). Analyses of associations with HEI score when stratified based on Lp(a) levels > or ≤ 100 nmol/L revealed no significant associations with any of the constituent factors.

Conclusions

Using 24 hour recall, we confirm previous findings that Lp(a) levels are negatively associated with dietary saturated fatty acid intake. Additionally, Lp(a) levels are not related to diet quality, as assessed by the HEI score. The mechanisms underlying the relationship of SFA with Lp(a) require further investigation.
Secured delivery of basic fibroblast growth factor using human serum albumin-based protein nanoparticles for enhanced wound healing and regeneration
Authors: Son Boram , Kim Minju , Won Hyosub , Jung Ara , Kim Jihyun , Koo Yonghoe , Lee Na Kyeong , Baek Seung-Ho , Han Uiyoung , Park Chun Gwon , Shin Heungsoo , Gweon Bomi , Joo Jinmyoung , Park Hee Ho
Published: September 2023

Background

Basic fibroblast growth factor (bFGF) is one of the critical components accelerating angiogenesis and tissue regeneration by promoting the migration of dermal fibroblasts and endothelial cells associated with matrix formation and remodeling in wound healing process. However, clinical applications of bFGF are substantially limited by its unstable nature due to rapid decomposition under physiological microenvironment.

Results

In this study, we present the bFGF-loaded human serum albumin nanoparticles (HSA-bFGF NPs) as a means of enhanced stability and sustained release platform during tissue regeneration. Spherical shape of the HSA-bFGF NPs with uniform size distribution (polydispersity index < 0.2) is obtained via a simple desolvation and crosslinking process. The HSA-bFGF NPs securely load and release the intact soluble bFGF proteins, thereby significantly enhancing the proliferation and migration activity of human dermal fibroblasts. Myofibroblast-related genes and proteins were also significantly down-regulated, indicating decrease in risk of scar formation. Furthermore, wound healing is accelerated while achieving a highly organized extracellular matrix and enhanced angiogenesis in vivo.

Conclusion

Consequently, the HSA-bFGF NPs are suggested not only as a delivery vehicle but also as a protein stabilizer for effective wound healing and tissue regeneration.
Integrated machine learning survival framework develops a prognostic model based on inter-crosstalk definition of mitochondrial function and cell death patterns in a large multicenter cohort for lower-grade glioma
Authors: Qin Hu , Abulaiti Aimitaji , Maimaiti Aierpati , Abulaiti Zulihuma , Fan Guofeng , Aili Yirizhati , Ji Wenyu , Wang Zengliang , Wang Yongxin
Published: September 2023

Background

Lower-grade glioma (LGG) is a highly heterogeneous disease that presents challenges in accurately predicting patient prognosis. Mitochondria play a central role in the energy metabolism of eukaryotic cells and can influence cell death mechanisms, which are critical in tumorigenesis and progression. However, the prognostic significance of the interplay between mitochondrial function and cell death in LGG requires further investigation.

Methods

We employed a robust computational framework to investigate the relationship between mitochondrial function and 18 cell death patterns in a cohort of 1467 LGG patients from six multicenter cohorts worldwide. A total of 10 commonly used machine learning algorithms were collected and subsequently combined into 101 unique combinations. Ultimately, we devised the mitochondria-associated programmed cell death index (mtPCDI) using machine learning models that exhibited optimal performance.

Results

The mtPCDI, generated by combining 18 highly influential genes, demonstrated strong predictive performance for prognosis in LGG patients. Biologically, mtPCDI exhibited a significant correlation with immune and metabolic signatures. The high mtPCDI group exhibited enriched metabolic pathways and a heightened immune activity profile. Of particular importance, our mtPCDI maintains its status as the most potent prognostic indicator even following adjustment for potential confounding factors, surpassing established clinical models in predictive strength.

Conclusion

Our utilization of a robust machine learning framework highlights the significant potential of mtPCDI in providing personalized risk assessment and tailored recommendations for metabolic and immunotherapy interventions for individuals diagnosed with LGG. Of particular significance, the signature features highly influential genes that present further prospects for future investigations into the role of PCD within mitochondrial function.
Improved genomic prediction using machine learning with Variational Bayesian sparsity
Authors: Yan Qingsen , Fruzangohar Mario , Taylor Julian , Gong Dong , Walter James , Norman Adam , Shi Javen Qinfeng , Coram Tristan
Published: September 2023

Background

Genomic prediction has become a powerful modelling tool for assessing line performance in plant and livestock breeding programmes. Among the genomic prediction modelling approaches, linear based models have proven to provide accurate predictions even when the number of genetic markers exceeds the number of data samples. However, breeding programmes are now compiling data from large numbers of lines and test environments for analyses, rendering these approaches computationally prohibitive. Machine learning (ML) now offers a solution to this problem through the construction of fully connected deep learning architectures and high parallelisation of the predictive task. However, the fully connected nature of these architectures immediately generates an over-parameterisation of the network that needs addressing for efficient and accurate predictions.

Results

In this research we explore the use of an ML architecture governed by variational Bayesian sparsity in its initial layers that we have called VBS-ML. The use of VBS-ML provides a mechanism for feature selection of important markers linked to the trait, immediately reducing the network over-parameterisation. Selected markers then propagate to the remaining fully connected feed-forward components of the ML network to form the final genomic prediction. We illustrated the approach with four large Australian wheat breeding data sets that range from 2665 lines to 10375 lines genotyped across a large set of markers. For all data sets, the use of the VBS-ML architecture improved genomic prediction accuracy over legacy linear based modelling approaches.

Conclusions

An ML architecture governed under a variational Bayesian paradigm was shown to improve genomic prediction accuracy over legacy modelling approaches. This VBS-ML approach can be used to dramatically decrease the parameter burden on the network and provide a computationally feasible approach for improving genomic prediction conducted with large breeding population numbers and genetic markers.
Personalized medicine: paradigm shift in ALK positive non-small cell lung cancer: a case report
Authors: Barreira João Vasco , Mendes José Leão , Parmanande Anuraj
Published: September 2023

Background

Since the identification of multiple therapeutic targets, as is the case of anaplastic lymphoma kinase (ALK) translocation, the paradigm of treating patients with non-small cell lung cancer (NSCLC) has improved. In order to guarantee the possibility of longer survival outcomes with a better quality of life we must invest in the determination, in suitable time, of the consensual biomarkers and in the availability of the best treatments to our patients.

Case presentation

We present a case of a caucasian male in his fifth decade of life, non-smoker, who highlights the complex journey of ALK-positive patients. This particular case, demonstrates the efficacy and tolerability of the new ALK target therapies, allowing our patients to maintain their routines without compromising the effectiveness of the therapy.

Conclusion

Focusing on the reality of ALK positive patients and the impact that this therapy has on the daily lives of our patients, we can contribute to the awareness of this specific pathology.
Development of a phytoplankton-based index of biotic integrity for ecological health assessment in the Yangtze River
Authors: Gao Wenqi , Xiong Fangyuan , Lu Ying , Qu Xiao , Xin Wei , Chen Yushun
Published: September 2023

Background

The application of index of biotic integrity (IBI) to evaluate river health can be an essential method for river ecosystem management. However, these types of methods were developed in small, low-order streams, and are therefore, infrequently applied to large rivers. To that end, phytoplankton communities and environmental variables were monitored in 30 sampling segments of the middle and lower reaches of the Yangtze River, China during the wet (July–August) and dry (November–December) seasons in 2017–2018. We developed a phytoplankton-based index of biotic integrity (P-IBI) and used the index to assess the ecological health of the Yangtze River. Relationships among P-IBI, its component metrics, and environmental factors were analyzed across different seasons.

Results

Results obtained from the P-IBI indicated that the phytoplankton-based ecological health of the Yangtze River was rated as “good” during both seasons, with an overall better condition in the dry season. During the wet season, there were scattered river segments with P-IBI ratings of “fair” or below. Water quality and land use appeared to shape the patterns of P-IBI. In the wet season, P-IBI negatively correlated with total phosphorus, nitrate, total suspended solids, turbidity, conductivity, and dissolved oxygen. In the dry season, P-IBI positively correlated with total nitrogen, ammonium, and nitrite, and negatively correlated with water temperature.

Conclusions

The ecological health of the Yangtze River as reflected by the P-IBI exhibited spatial and temporal variability, with the effect of water quality being greater than that of local land use. This study indicated the importance of considering seasonal effects in detecting large river ecological health. These findings enhanced our understanding of the ecological health and characterized potential benchmarks for management of the Yangtze River. These findings also may be applicable to other large rivers elsewhere.
Hospitalized patients received furosemide undergoing acute kidney injury: the risk and prediction tool
Authors: Guan Chen , Li Chenyu , Xu Lingyu , Che Lin , Wang Yanfei , Yang Chengyu , Zhang Ningxin , Liu Zengying , Zhao Long , Zhou Bin , Man Xiaofei , Luan Hong , Xu Yan
Published: September 2023

Purpose

Furosemide, a frequently prescribed diuretic for managing congestive heart failure and edema, remains a topic of debate regarding its potential risk of inducing acute kidney injury (AKI) in patients. Consequently, this study aims to examine the occurrence of hospital-acquired AKI (HA-AKI) in hospitalized patients who are administered furosemide and to investigate potential risk factors associated with this outcome.

Methods

This study encompassed a cohort of 22374 hospitalized patients who either received furosemide treatment or not from June 1, 2012, to December 31, 2017. Propensity score matching was employed to establish comparability between the two groups regarding covariates. Subsequently, a nomogram was constructed to predict the probability of AKI occurrence among patients who underwent furosemide treatment.

Results

The regression analysis identified the single-day total dose of furosemide as the most significant factor for AKI, followed by ICU administration, estimated glomerular filtration rate, antibiotic, statin, NSAIDs, β-blockers, proton pump inhibitor, chronic kidney disease, and 7 other indicators. Subgroup analysis revealed a synergistic effect of furosemide with surgical operation, previous treatment with β-blockers, ACEI/ARB and antibiotics, leading to an increased risk of AKI when used in combination. Subsequently, a visually represented prognostic nomogram was developed to predict AKI occurrence in furosemide users. The predictive accuracy of the nomogram was assessed through calibration analyses, demonstrating an excellent agreement between the nomogram predictions and the actual likelihood of AKI, with a probability of 77.40%.

Conclusions

Careful consideration of factors such as dosage, concurrent medication use, and renal function of the patient is necessary for clinical practice when using furosemide. Our practical prognostic model for HA-AKI associated with furosemide use can be utilized to assist clinicians in making informed decisions about patient care and treatment.
Antarctic snow algae: unraveling the processes underlying microbial community assembly during blooms formation
Authors: Soto Daniela F. , Gómez Iván , Huovinen Pirjo
Published: September 2023

Background and aims

At the West Antarctic Peninsula, snow algae blooms are composed of complex microbial communities dominated by green microalgae and bacteria. During their progression, the assembly of these microbial communities occurs under harsh environmental conditions and variable nutrient content due to fast snow melting. To date, it is still unclear what are the ecological mechanisms governing the composition and abundance of microorganisms during the formation of snow algae blooms. In this study, we aim to examine the main ecological mechanisms governing the assembly of snow algae blooms from early stages to colorful stages blooms.

Methods

The composition of the microbial communities within snow algae blooms was recorded in the West Antarctic Peninsula (Isabel Riquelme Islet) during a 35-day period using 16S rRNA and 18S rRNA metabarcoding. In addition, the contribution of different ecological processes to the assembly of the microbial community was quantified using phylogenetic bin-based null model analysis.

Results

Our results showed that alpha diversity indices of the eukaryotic communities displayed a higher variation during the formation of the algae bloom compared with the bacterial community. Additionally, in a macronutrients rich environment, the content of nitrate, ammonium, phosphate, and organic carbon did not play a major role in structuring the community. The quantification of ecological processes showed that the bacterial community assembly was governed by selective processes such as homogenous selection. In contrast, stochastic processes such as dispersal limitation and drift, and to a lesser extent, homogenous selection, regulate the eukaryotic community.

Conclusions

Overall, our study highlights the differences in the microbial assembly between bacteria and eukaryotes in snow algae blooms and proposes a model to integrate both assembly processes.
Effect of age and gender on dietary patterns, mindful eating, body image and confidence
Authors: Jacob Jinsa Sara , Panwar Neeraj
Published: September 2023

The emergence of ‘Diet Culture’ came into existence with the era of pop culture, which emphasized the idea of body improvement by embracing the portrayal of unrealistic beauty standards set by the thin-ideal media. This growing and trending culture gained its popularity in India with the COVID pandemic and the imposed lockdown, wherein the prevalence of obesity and binge eating resulted from counter-regulatory eating behaviors and restrictive food intake to a greater extent of skipping meals to achieve the desired body type. The present empirical investigation focuses on understanding the gender and age-based differences (between the ages 18 to 55) among Indian population on dietary patterns, body image, mindful eating and physical appearance confidence using 2 × 3 factorial design. The tools used were Eating Behavior Pattern Questionnaire (EBPQ) [43], Body Self- image Questionnaire (BSIQ) [40], Mindful Eating Questionnaire (MEQ) [18] and Personal Evaluation Inventory (PEI) [44] were administered on a sample size of 120, selected using convenience sampling technique. The collected data was analyzed using SPSS Version 20.0. Results of the study reveal non-significant age and gender differences for mindful eating and appearance confidence. Significant age- differences were observed for Snacking and convenience F(2,114) = 6.22, p < .05; social dependence F(2,114) = 3.87, p < .05 and height dissatisfaction F(2,114) = 8.79, p < .05. And, significant gender differences were observed for Meal Skipping F(1,114) = 6.46, P < .05; snacking and convenience F(1,114) = 4.19, p < .05; fatness evaluation F(1,114) = 5.94, p < .05 and fitness evaluation F(1,114) = 5.33, p < .05. The only significant interaction effect observed was for social dependence dimension F(2, 114) = 3.96, p < .05. Thus, high exposure to social media and diet-related content contributed significantly to changing dietary patterns, and how they look, feel or perceive their body.
Development of a resilience-enhancing intervention during and after pregnancy: a systematic process informed by the behaviour change wheel framework
Authors: Van Haeken Sarah , Braeken Marijke A.K.A. , Horsch Antje , Oosterman Mirjam , Bogaerts Annick
Published: September 2023

Background

Pregnancy and the transition to parenthood are accompanied by multiple changes and stress exposure. Resilience has the potential to counteract the negative impact of stress and can be a protective factor against mental health problems. To date, the use of a theoretical framework in the development or application of resilience interventions during pregnancy up to one year postpartum is missing. The aim of this study is to develop an intervention to enhance resilience for pregnant women up to one year postpartum.

Methods

A systematic and theory-based approach informed by the Behaviour Change Wheel framework and the theoretical model of perinatal resilience was applied. The development took place in three phases and during the process, the target group, researchers and clinicians were involved.

Results

A combination of resilience-enhancing exercises, group sessions and an online support platform, including follow-up at six and twelve months after delivery, was designed to enhance resilience during pregnancy and up to one year postpartum. This intervention incorporates 5 intervention functions delivered by 18 behaviour change techniques.

Conclusions

This study responds to the need for theory-based intervention programs aiming to enhance resilience to improve the psychological health of pregnant women. We developed a multicomponent resilience-enhancing intervention for pregnant women up to one year postpartum.
MAFSIDS: a reinforcement learning-based intrusion detection model for multi-agent feature selection networks
Authors: Ren Kezhou , Zeng Yifan , Zhong Yuanfu , Sheng Biao , Zhang Yingchao
Published: September 2023

Large unbalanced datasets pose challenges for machine learning models, as redundant and irrelevant features can hinder their effectiveness. Furthermore, the performance of intrusion detection systems (IDS) can be further degraded by the emergence of new network attack types. To address these issues, we propose MAFSIDS (Multi-Agent Feature Selection Intrusion Detection System), a DQL (Deep Q-Learning) based IDS.

MAFSIDS comprises a feature self-selection algorithm and a DRL (Deep Reinforcement Learning) attack detection module. The feature self-selection algorithm leverages a multi-agent reinforcement learning framework, which redefines the feature selection problem by converting the traditional$${2}^{N}$$2Nfeature selection space into$$N$$Nagent representations. This approach reduces model complexity and enhances the search strategy for feature selection. To ensure accurate feature representation and expedite the feature selection process, we have also developed a GCN (Graph Convolutional Network) method that extracts deeper features from the data. The DRL attack detection module utilizes the Mini-Batchs technique to encode the data, allowing reinforcement learning to be applied in a supervised learning context. This integration improves accuracy. Additionally, the policy network in this module is designed to be minimalist, enhancing model efficiency. To evaluate the performance of our model, we conducted comprehensive simulation experiments using Python. We tested the model using the CSE-CIC-IDS2018 and NSL-KDD datasets, achieving impressive accuracy rates of 96.8% and 99.1%, as well as F1-Scores of 96.3% and 99.1%, respectively. The selected feature subset successfully eliminates approximately 80% of redundant features compared to the original feature set. Furthermore, we compared our proposed model with other popular machine-learning models.
Non-canonical two-step biosynthesis of anti-oomycete indole alkaloids in Kickxellales
Authors: Rassbach Johannes , Hilsberg Nathalie , Haensch Veit G. , Dörner Sebastian , Gressler Julia , Sonnabend Robin , Semm Caroline , Voigt Kerstin , Hertweck Christian , Gressler Markus
Published: September 2023

Background

Fungi are prolific producers of bioactive small molecules of pharmaceutical or agricultural interest. The secondary metabolism of higher fungi (Dikarya) has been well-investigated which led to > 39,000 described compounds. However, natural product researchers scarcely drew attention to early-diverging fungi (Mucoro- and Zoopagomycota) as they are considered to rarely produce secondary metabolites. Indeed, only 15 compounds have as yet been isolated from the entire phylum of the Zoopagomycota.

Results

Here, we showcase eight species of the order Kickxellales (phylum Zoopagomycota) as potent producers of the indole-3-acetic acid (IAA)-derived compounds lindolins A and B. The compounds are produced both under laboratory conditions and in the natural soil habitat suggesting a specialized ecological function. Indeed, lindolin A is a selective agent against plant-pathogenic oomycetes such as Phytophthora sp. Lindolin biosynthesis was reconstituted in vitro and relies on the activity of two enzymes of dissimilar evolutionary origin: Whilst the IAA–CoA ligase LinA has evolved from fungal 4-coumaryl-CoA synthetases, the subsequently acting IAA-CoA:anthranilate N-indole-3-acetyltransferase LinB is a unique enzyme across all kingdoms of life.

Conclusions

This is the first report on bioactive secondary metabolites in the subphylum Kickxellomycotina and the first evidence for a non-clustered, two-step biosynthetic route of secondary metabolites in early-diverging fungi. Thus, the generally accepted “gene cluster hypothesis” for natural products needs to be reconsidered for early diverging fungi.
Discrete element modelling of granular materials incorporating realistic particle shapes
Authors: Kodicherla Shiva Prashanth Kumar
Published: September 2023

This paper proposes an approach to generate realistic particle shapes considering the major plane of orientation of particles in discrete element modelling (DEM). The particle generation framework includes capturing high-quality scanning electron microscope (SEM) images, followed by image processing and generation of clumps using a commonly used multi-sphere (MS) approach in particle flow code (PFC3D). A set of experimental direct shear tests (DST) and subsequent DEM simulations were performed by incorporating realistic particle shapes. The simulation results show a good agreement with those obtained in the laboratory. In addition, the normal stress showed a significant effect on the structural anisotropy of the granular materials.
Infectious disease control: from health security strengthening to health systems improvement at global level
Authors: Zhang Xiao-Xi , Jin Yin-Zi , Lu Yi-Han , Huang Lu-Lu , Wu Chuang-Xin , Lv Shan , Chen Zhuo , Xiang Hao , Zhou Xiao-Nong
Published: September 2023

Since the twenty first century, the outbreaks of global infectious diseases have caused several public health emergencies of international concern, imposing an enormous impact on population health, the economy, and social development. The COVID-19 pandemic has once again exposed deficiencies in existing global health systems, emergency management, and disease surveillance, and highlighted the importance of developing effective evaluation tools. This article outlines current challenges emerging from infectious disease control from the perspective of global health, elucidated through influenza, malaria, tuberculosis, and neglected tropical diseases. The discordance among government actors and absent data sharing platforms or tools has led to unfulfilled targets in health system resilience and a capacity gap in infectious disease response. The current situation calls for urgent action to tackle these threats of global infectious diseases with joined forces through more in-depth international cooperation and breaking governance barriers from the purview of global health. Overall, a systematic redesign should be considered to enhance the resilience of health systems, which warrants a great need to sustain capacity-building efforts in emergency preparedness and response and raises an emerging concern of data integration in the concept of One Health that aims to address shared health threats at the human-animal-environment interface.
Typology and working mechanism of a hybrid power router based on power-frequency transformer electromagnetic coupling with converters
Authors: Lai Jinmu , Yin Xin , Yin Xianggen , Hu Jiaxuan , Xiao Fan
Published: September 2023

The power router (PR) is a promising piece of equipment for realizing multi-voltage level interconnection and flexible power control in the future distribution power grid. In this paper, a hybrid PR (HPR) topology based on power-frequency transformer electromagnetic coupling with converters is proposed for the medium distribution power grid. The power-frequency transformer is used to undertake power transmission, voltage conversion, and other main tasks, while the power electronic converters are combined to achieve active control. Equivalent magnetic and electrical circuit models are established to help discuss the operating principle of the proposed HPR. Additionally, the power flow and control principle of the HPR in different operating conditions are analyzed, with the control system design scheme presented. The theoretical analysis results are verified by MATLAB/Simulink + Plecs simulation and a controller hardware-in-the-loop study, as well as a down-scale experimental test, indicating that the proposed HPR is flexible in active voltage support and current control.
Health and well-being of the Portuguese citizens: impacts of the COVID-19
Authors: Ferreira Lara N. , Pereira Luís N. , Ferreira Pedro L.
Published: September 2023

Background

COVID-19 pandemic placed unprecedented pressure on societies and healthcare systems around the world. Over the last years, measures imposed in almost all countries dealing with the pandemic sent the entire world into an extensive crisis and thus into a deep global recession. Since the outbreak began, many European countries have faced three/four waves of pandemic. Portugal has mainly dealt with three waves (March/April’2020; October/November’2020; January/February’2021), the third being the deadliest one. The purpose of this article is to provide evidence on the impact of the COVID-19 on health-related quality of life (HRQol) and well-being (W-B) of Portuguese citizens. It aims to (i) characterize these outcomes during the COVID-19 pandemic; (ii) compare them to pre-COVID-19 Portuguese population; and (iii) identify the social determinants that may affect these outcomes during the COVID-19 pandemic.

Methods

This study used data from a survey that collected data on HRQoL, W-B, satisfaction with life, economic and labour impacts, access to healthcare, mental and physical health, amongst others. The survey was implemented by telephone to a representative random sample of 1,255 respondents from the general adult Portuguese population, stratified by sex, age group and region. Data was collected during the end of the second national lockdown. For comparison purposes, we have also used two other representative databases from the general Portuguese population: (i) data from before the pandemic (n = 1,006); and (ii) data from a survey conducted during the first lockdown, (n = 904).

Results

Looking at health and access to healthcare, 4% of citizens had their surgeries postponed or cancelled because of COVID-19, more than a quarter had medical appointments or complementary exams postponed or cancelled, with 7% over 65 years old with surgeries cancelled or postponed and 32% medical appointments. COVID-19 pandemic also impacted negatively on the HRQoL of citizens, especially in the first lockdown. Half of the respondents reported feeling nervous, anxious, or on edge, about 45% of citizens felt sad or depressed. Sleeping problems were reported for almost 39% of citizens, and loneliness is reported by 29% of citizens. For about 70–85% of citizens, these feelings were more so than before the pandemic. Citizens with fair/strong economic stability were the most economically affected by the pandemic.

Conclusions

We provided evidence on the impact of COVID-19 on health and W-B of Portuguese citizens. Their health was worse than before the pandemic and the access to healthcare was highly affected.
Quantized autoencoder (QAE) intrusion detection system for anomaly detection in resource-constrained IoT devices using RT-IoT2022 dataset
Authors: Sharmila B S , Nagapadma Rohini
Published: September 2023

In recent years, many researchers focused on unsupervised learning for network anomaly detection in edge devices to identify attacks. The deployment of the unsupervised autoencoder model is computationally expensive in resource-constrained edge devices. This study proposes quantized autoencoder (QAE) model for intrusion detection systems to detect anomalies. QAE is an optimization model derived from autoencoders that incorporate pruning, clustering, and integer quantization techniques. Quantized autoencoder uint8 (QAE-u8) and quantized autoencoder float16 (QAE-f16) are two variants of QAE built to deploy computationally expensive AI models into Edge devices. First, we have generated a Real-Time Internet of Things 2022 dataset for normal and attack traffic. The autoencoder model operates on normal traffic during the training phase. The same model is then used to reconstruct anomaly traffic under the assumption that the reconstruction error (RE) of the anomaly will be high, which helps to identify the attacks. Furthermore, we study the performance of the autoencoders, QAE-u8, and QAE-f16 using accuracy, precision, recall, and F1 score through an extensive experimental study. We showed that QAE-u8 outperforms all other models with a reduction of 70.01% in average memory utilization, 92.23% in memory size compression, and 27.94% in peak CPU utilization. Thus, the proposed QAE-u8 model is more suitable for deployment on resource-constrained IoT edge devices.