bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep Reinforcement Learning based Path Planning with Dynamic Trust Region Optimization for Automotive Application
Authors: Arumugam Vengatesan , Alagumalai Vasudevan , Sriniva Venkataramanan 
Published: September 2024

Abstract

Graphical abstract
Abstract
Multi-robot path planning must adapt to difficult situations, allowing autonomous navigation in both static and dynamic barriers in complicated environments. However, defining the best planning strategies for certain applications remains unsolved. This study focused at three methods for learning complex robotic decision-making principles such as Trust Region Policy Optimization (TRPO), Proximal Policy Optimization (PPO), and Deep Reinforcement Learning (DRL). Furthermore, proposed a novel technique for obstacle avoidance and autonomous navigation called Dynamic Improvement Trust Region Policy Optimization with Covariance Grid Adaptation (DITRPO-CGA). Initially, created the Dynamic Improvement Proximal Policy Optimization with Covariance Grid Adaptation (DIPPO-CGA) based on PPO to assure collision-free policies. Next, developed a DRL technique that integrates DIPPO-CGA, resulting in the DITRPO-CGA algorithm, which improved the flexibility of multi-robot systems in different situations. During training process, DIPPO-CGA is utilized to optimize the multi-robot multi-task policies, ensuring least distance obstacle avoidance and target completion. The proposed DIPPO-CGA algorithm reaches the target within minimum distance. The findings showed that when compared to PPO, TRPO, and DIPPO-CGA, the proposed DITRPO-CGA algorithm achieves a higher convergence rate, faster target achievement and reaches the positions more quickly.
Ion Sequential Therapy Aligned With Pathological Changes Enhances Cardiac Function After Myocardial Infarction
Authors: Ye Xiaofeng , Zhong Yiming , Zhang Zhaowenbin , Huang Shixing , Shen Ao , Qian Bei , Long Qiang , Qi Zhaoxi , He Xiaojun , Zhang Yecen , Chang Lan , Hai Wangxi , Wang Xinming , You Zhengwei , Zhao Qiang , Chang Jiang 
Published: September 2024

Abstract

Myocardial infarction can induce a microenvironmental imbalance of trace element ions within the human body. This study initially investigated the change patterns of zinc (Zn) and copper (Cu) ions throughout the natural course of myocardial infarction. Our results uncovered temporal and spatial shifts in the levels of Zn and Cu ions. Leveraging these observed time-based ion variation patterns, we devised a Zn-Cu ion sequential therapy tailored to address the phased requirements of body for these trace elements after myocardial infarction. Zn-Cu ion sequential therapy exhibited significant efficacy in a rat model of myocardial infarction, effectively restoring cardiac function while enhancing cardiomyocyte metabolic activity. Its efficacy hinges on the capacity of Zn-Cu ion sequencing to precisely regulate the Period circadian protein homolog 2 (Per2), which is strikingly linked to the circadian rhythm. By sequentially administering Zn and Cu ions during different phases of myocardial infarction, we maintained elevated Per2 protein levels, fostering a more conducive environment for the repair of damaged cardiomyocytes. Based on the observed change patterns of Zn and Cu ion in the infarcted region, we subsequently introduced an in-situ Zn-Cu ion sequential therapy for myocardial infarction. Utilizing a perfusable multifunctional epicardial device (PerMed), we established a stable ion microenvironment "reservoir" within the infarcted zone. This design enables precise spatiotemporal regulation of ion concentration and balance, thereby optimizing cardiomyocyte repair and regeneration. In conclusion, this study presents an ion sequential therapy strategy that aligns with pathological changes arising from the altered microenvironment post-myocardial infarction. Furthermore, it offers a therapeutic concept for precise ion supplement to address ion imbalances arising from various other diseases.
Buyer Beware: confounding factors and biases abound when predicting omics-based biomarkers from histological images
Authors: Dawood Muhammad , Branson Kim , Tejpar Sabine , Rajpoot Nasir , Minhas Fayyaz 
Published: September 2024

Abstract

Recent advances in computational pathology have introduced deep learning methods to predict molecular biomarkers from routine histology whole slide images (WSIs). In this work, we identify and report some key limitations of these approaches, including the oversight of biomarkers interdependencies during model training and inference. Through statistical analysis, we first demonstrate significant interdependencies among molecular factors, revealing both pathobiologically driven associations and potential spurious correlations that vary across datasets. Subsequently, through permutation testing and stratification analysis, we showed that the predictive performance of WSI-based predictors for a certain biomarker is contingent on the status of other biomarkers, particularly those exhibiting mutually exclusive or co-occurring patterns. For instance, models trained using standard approaches to predict progesterone receptor status in breast tumours perform no better than random guessing (area under the receiver operating characteristic curve of 0.50) in cases with CDH1 mutations. This suggests that due to significant interdependencies among molecular factors in the training data, these models capture aggregated influences rather than predicting individual biomarker status independently. Additionally, we found that the predictive accuracy of WSI-based models varies across patient subgroups with different histological grades or mutational loads. Furthermore, we demonstrate that for certain biomarkers, predictions from deep learning models offer little advantage over simpler models based on pathologist-assigned grade information. Our findings over a large multi-institutional dataset of patients (n = 8,221) suggest revisiting model training protocols to consider biomarker interdependencies at all stages, from problem definition to usage guidelines. This includes selecting diverse datasets to reflect clinical heterogeneity, defining prediction variables or grouping patients based on co-dependencies, designing models to disentangle complex relationships, and stringent stratification testing. Clinically, failing to recognise such model errors can lead to suboptimal decisions, necessitating appropriate usage guidelines for predictive models.
Metagenomic analysis of a glacial ice core record from the contiguous United States
Authors: Kvitko Brian , Wallace Jason , Desai Hanish Vasudev , Lavender Heather F. , Mijatovic Jovana , Techtmann Stephen , Christner Brent C. , Smith Amy 
Published: September 2024

Abstract

Glacial ice preserves time-sequenced records of preserved microbes, offering access to historic pre-anthropic metagenomes. As proof-of-concept, we three tested methods to recover ancient DNA from a ~250-year ice core from Wyoming's Upper Fremont Glacier for metagenomic sequencing. Direct amplification of filter-concentrated melt water (eDNA) was a simple and effective method for metagenomics. We observed higher microbial diversity, enriched nitrogen-cycling genes, and higher abundance of Nitrosopira, Rhodanobacter and Polaromonas sequences in 1790 CE samples compared to 1900-1961 CE samples. The documented microbial variation may be attributable to changes in climate and land use over the last two centuries.
In Vivo Models of Steroid-Induced Intraocular Hypertension
Authors: Tang Wanyu , Dang Yalong 
Published: September 2024

:
Corticosteroids are widely utilized for their anti-inflammatory and immunosuppressive
properties but often lead to ocular complications, including ocular hypertension. If untreated, ocular
hypertension can progress to optic nerve atrophy and eventually result in steroid-induced glaucoma,
which poses a risk of irreversible visual damage. Approximately 40% of individuals experience
increased intraocular pressure after steroid use, and around 6% develop glaucoma. Although
steroid-induced glaucoma is usually temporary and reversible if the treatment duration is under a
year, prolonged exposure can cause permanent vision impairment. The pathogenesis of steroid-induced
glaucoma is suggested to arise from increased outflow resistance of aqueous humor, primarily
due to decreased expression of matrix metalloproteinases. This deficiency promotes the deposition
of extracellular matrix and the dysfunction of trabecular meshwork cells. Additionally, modifications
in the actin cytoskeleton increase the stiffness and alter the morphology of trabecular meshwork,
further impeding aqueous humor outflow. Molecular changes, such as elevated expression
of the MYOC gene, have also been implicated in restricting aqueous outflow. Various animal models,
including rats, mice, primates, rabbits, cattle, sheep, cats, and dogs, have been developed to
study steroid-induced glaucoma. These models exhibit pathological, pathophysiological, and
molecular similarities to human disease, making them valuable for research. This review aims to
summarize common animal models of steroid-induced ocular hypertension, discussing their advantages
and limitations. The goal is to help researchers select appropriate models for future studies,
thereby advancing the understanding of disease mechanisms and developing preventive strategies.
Exploring Tryptophan-based Short Peptides: Promising Candidate for Anticancer and Antimicrobial Therapies
Authors: Rai Neha , Tiwari Richa Tripathy , Sahu Adarsh , Verma Ekta , Rathore Swati , Patil Shailendra , Patil Asmita Gajbhiye 
Published: September 2024

Background:
Ultra-short peptides are essential therapeutic agents due to their heightened selectivity
and reduced toxicity. Scientific literature documents the utilization of dipeptides, tripeptides, and tetrapeptides as
promising agents for combating cancer. We have created a range of tryptophan-based peptides derived from
literature sources in order to assess their potential as anticancer drugs.

Methods:
We present the results of our study on the antibacterial and anticancer effectiveness of 10 ultra-short
peptides that were produced utilizing microwave-assisted solid phase peptide synthesis. The synthesized peptides
underwent screening for in vitro antibacterial activity using the agar dilution method.

Results:
HPLC, LC-MS, 1H NMR, and 13C NMR spectroscopy were used to analyze the synthesized peptides. In
tests using the HeLa and MCF-7 cell lines, the synthesized peptides' anticancer efficacy was assessed. The study
found that two peptides showed potential median inhibitory concentration (IC50) values of 3.9±0.13 μM and
1.8±0.09 μM, respectively, and showed more activity than the reference medication doxorubicin.

Conclusion:
The antibacterial activity of synthesized peptides 3b and 4b was found to be better than the other
synthetic peptides. MIC value of roughly 5–50 μg/mL for peptides 3a, 4c, and 4d showed strong antifungal activity
against Candida albicans. The synthesized peptides were also evaluated for their anticancer activity against
HeLa and MCF-7 cell lines, and found that peptides 3e and 4e were more potent than other peptides against doxorubicin.
Sedimentation Analysis Study in Lake Tondano Due to the Development of the Surrounding Area
Authors: Hendratta Liany Amelia , Laurentia Susilawati Cicilia , KOH Deuk Koo , Monica La’la , Ratu Yosua Aditya 
Published: September 2024

Background
Population growth has increased the need for food, putting great pressure on the environment. This has triggered economic development and land use alternation, which have a major impact on the hydrological cycle. Natural and human factors have impacted the water catchment area of uncontrolled land cover changes in Lake Tondano, which is shallow from a depth of 36 meters to 14 meters due to soil erosion.

Objective
This research emphasizes the assessment of the lake, considering the efforts of conservation and analyzing its influence on the erosion rate and shallowing of the lake. The impact of land use dynamics on sedimentation is essential in providing alternative efforts for land conservation and, subsequently, optimum utilization.

Methods
The analyzing process requires rainfall data and land use maps, including soil type maps and land slope data, while the process itself is assisted by spreadsheets and GIS. In addition, the Universal Soil Loss Equation (USLE) and Sediment Delivery Ratio (SDR) model deliver the expected result of the total sediment production entering the lake.

Results
The calculated total value of actual sediment production governs the thickness of sediment deposition at the bottom of the lake.

Conclusion
The research concludes that the thickness of sediment deposition at lake bottom can be resolved by the total value of actual sediment production, whereas the value is analyzed from the USLE and SDR models previously correlated to bathymetry measurement.
Investigating the Relationship between the General Health of Mothers and their Maternal Performance following Vaginal Childbirth
Authors: Izaddoost Niloufar , Parsaie Sahar , Choobdarnezhad Masoumeh , Pezaro Sally , Amiri-Farahani Leila 
Published: September 2024

Background
Birthing parents need to use specialized skills as the first caregivers of the newborn. Several factors may affect maternal performance, the general health of the birthing parent (e.g., mother) being one of them. Yet, there is a paucity of research in this area, particularly in Iran, and evidence remains inconsistent. Consequently, this study aimed to determine any correlations between maternal performance and the general health of mothers following vaginal childbirth in the context of Iran.

Methods
This cross-sectional study was conducted with people identifying as mothers (n = 450) who had given birth (< two months) and been referred for the vaccination of their newborn. The multi-stage sampling method was carried out from April 2022 to February 2023. Participants who met the inclusion criteria completed a demographic and obstetric information questionnaire, along with the Barkin maternal performance and general health questionnaire. To investigate the relationship between maternal performance and the general health of the mothers, an independent t-test analysis was conducted . The level of statistical significance was set at p < 0.05.

Results
The mean age of participants was 26.78, and the mean total score of maternal performance was 91.04 (0 - 120). The highest and lowest scores related to the ‘maternal competence’ and the ‘maternal needs’ domains, respectively. Overall, 76.89% of participants had a favorable general health condition (a score of less than 3.5 is considered favorable). There was no statistically significant difference identified in terms of maternal performance scores between those with a favorable and those with an unfavorable general health status.

Conclusion
Although the results of the present study did not show a significant relationship between the general health of mothers and maternal performance, this research builds on a growing body of evidence in the context of Iran. Despite recording high maternal performance scores in this sample, it will be important to enhance and maintain good mental health in all childbearing people, particularly following vaginal childbirth, as it is this which will enhance care and outcomes overall.
‘Unlearning this Desire to Vanish': Rape, Illness, and the Politics of Testimony in Lucia Osborne-Crowley’s I Choose Elena and Amy Berkowitz’s Tender Points
Authors: Marqués-López Isabel 
Published: September 2024

In recent years, life writing by survivors of sexual violence has attempted to contest the stigma of shame traditionally attached to women’s testimony. Among these authors, disabled and chronically ill survivors find themselves doubly marginalized by the patriarchal discourses prevalent in culture and medical spaces. For this reason, in their writing, they vindicate political and ethical approaches to their condition, based on emphasizing their bodily experience against the silencing of culture and institutions. This essay looks at Lucia Osborne Crowley’s I Choose Elena (2019) and Amy Berkowitz’s Tender Points (2015) as two examples of memoirs exploring the intersections between sexual trauma and chronic illnesses like endometriosis and fibromyalgia, as well as the possibilities for writing to contest stigma and move towards an ethical audience, inside and outside medical spaces. In their memoirs, these authors expose the physical, socioeconomic, and institutional boundaries that they encounter while vindicating political and engaged ways to live in their bodies.
Investigating Older Adults' Use of a Socially Assistive Robot via Time Series Clustering and User Profiling: Descriptive Analysis Study
Authors: Yoo In-jin , Park Do-Hyung , Lee Othelia EunKyoung , Park Albert 
Published: September 2024

Background
The aging population and the shortage of geriatric care workers are major global concerns. Socially assistive robots (SARs) have the potential to address these issues, but developing SARs for various types of users is still in its infancy.

Objective
This study aims to examine the characteristics and use patterns of SARs.

Methods
This study analyzed log data from 64 older adults who used a SAR called Hyodol for 60 days to understand use patterns and their relationship with user characteristics. Data on user interactions, robot-assisted content use, demographics, physical and mental health, and lifestyle were collected. Time series clustering was used to group users based on use patterns, followed by profiling analysis to relate these patterns to user characteristics.

Results
Overall, 4 time series clusters were created based on use patterns: helpers, friends, short-term users, and long-term users. Time series and profiling analyses revealed distinct patterns for each group. We found that older adults use SARs differently based on factors beyond demographics and health. This study demonstrates a data-driven approach to understanding user needs, and the findings can help tailor SAR interventions for specific user groups.

Conclusions
This study extends our understanding of the factors associated with the long-term use of SARs for geriatric care and makes methodological contributions.
Methodology for Biological Sample Collection, Processing, and Storage in the Newcastle 1000 Pregnancy Cohort: Protocol for a Longitudinal, Prospective Population-Based Study in Australia
Authors: Fisher Joshua J , Grace Tegan , Castles Nathan A , Jones Elizabeth A , Delforce Sarah J , Peters Alexandra E , Crombie Gabrielle K , Hoedt Emily C , Warren Kirby E , Kahl Richard GS , Hirst Jonathan J , Pringle Kirsty G , Pennell Craig E 
Published: September 2024

Background
Research in the developmental origins of health and disease provides compelling evidence that adverse events during the first 1000 days of life from conception can impact life course health. Despite many decades of research, we still lack a complete understanding of the mechanisms underlying some of these associations. The Newcastle 1000 Study (NEW1000) is a comprehensive, prospective population-based pregnancy cohort study based in Newcastle, New South Wales, Australia, that will recruit pregnant women and their partners at 11-14 weeks’ gestation, with assessments at 20, 28, and 36 weeks; birth; 6 weeks; and 6 months, in order to provide detailed data about the first 1000 days of life to investigate the developmental origins of noncommunicable diseases.

Objective
The study aims to provide a longitudinal multisystem approach to phenotyping, supported by robust clinical data and collection of biological samples in NEW1000.

Methods
This manuscript describes in detail the large variety of samples collected in the study and the method of collection, storage, and utility of the samples in the biobank, with a particular focus on incorporation of the samples into emerging and novel large-scale “-omics” platforms, including the genome, microbiome, epigenome, transcriptome, fragmentome, metabolome, proteome, exposome, and cell-free DNA and RNA. Specifically, this manuscript details the methods used to collect, process, and store biological samples, including maternal, paternal, and fetal blood, microbiome (stool, skin, vaginal, oral), urine, saliva, hair, toenail, placenta, colostrum, and breastmilk.

Results
Recruitment for the study began in March 2021. As of July 2024, 1040 women and 684 partners were enrolled, with 922 infants born. The NEW1000 biobank contains 24,357 plasma aliquots from ethylenediaminetetraacetic acid (EDTA) tubes, 5284 buffy coat aliquots, 4000 plasma aliquots from lithium heparin tubes, 15,884 blood serum aliquots, 2977 PAX RNA tubes, 26,595 urine sample aliquots, 2280 fecal swabs, 17,687 microbiome swabs, 2356 saliva sample aliquots, 1195 breastmilk sample aliquots, 4007 placental tissue aliquots, 2680 hair samples, and 2193 nail samples.

Conclusions
NEW1000 will generate a multigenerational, deeply phenotyped cohort with a comprehensive biobank of samples relevant to a large variety of analyses, including multiple -omics platforms.

International Registered Report Identifier (IRRID)
DERR1-10.2196/63562
Social Media Use in Adolescents: Bans, Benefits, and Emotion Regulation Behaviors
Authors: McAlister Kelsey L , Beatty Clare C , Smith-Caswell Jacqueline E , Yourell Jacqlyn L , Huberty Jennifer L 
Published: September 2024

Abstract
Social media is an integral part of adolescents’ daily lives, but the significant time they invest in social media has raised concerns about the effect on their mental health. Bans and severe restrictions on social media use are quickly emerging as an attempt to regulate social media use; however, evidence supporting their effectiveness is limited. Adolescents experience several benefits from social media, including increased social connection, reduced loneliness, and a safe space for marginalized groups (eg, LGBTQ+) to interact. Rather than enforcing bans and severe restrictions, emotion regulation should be leveraged to help adolescents navigate the digital social environment. This viewpoint paper proposes a nuanced approach toward regulating adolescent social media use by (1) discontinuing the use of ineffective bans, (2) recognizing the benefits social media use can have, and (3) fostering emotion regulation skills in adolescents to encourage the development of self-regulation.
Analisis Komunikasi Pemasaran Wisata Palembang Melalui Media Sosial
Authors: Dianthi Martha Heriniazwi 
Published: September 2024

Promosi media online saat ini menjadi sebuah cara baru dalam memproduksikan suatu produk atau barang. Cara ini dinilai cukup efektif daripada cara konvensional. Dampak yang dirasakan dari kegiatan promosi. Salah satunya yang dilakukan oleh pemerintah kota Palembang yang melakukan promosi destinasi wisata melalui media online seperti website dan instagram.Kedua media ini memiliki ciri dan dampak masing-masing yang dapat dirasakan guna mengembangkan pariwisata di Kota Palembang tersebut. Seperti halnya kemudahan dalam memberikan informasi atau mengetahui berita terbaru yang ada di Kota Palembang tersebut. Maka dari itu, penelitian ini akan menganalisis bagaimana promosi komunikasi pemasaran yang dilakukan oleh pemerintahan Kota Palembang melalui media sosial Dalam penelitian ini akan menggunakan metode penelitian kualitatif dengan melakukan wawa cara mendalam terhadap key informan. Key informa tersebut terdiri dari dua orang yang merupakan pengurus serta admi dari media sosial Pemerintah Kota Palembang