bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimizing surface roughness of workpieces made of stainless steel 316L with DMLS technology: a Taguchi method approach
Authors: Jakupi Kaltrine , Dukovski Vladimir , Abdullahu Fitore
Published: April 2024

This study employs Direct Metal Laser Sintering (DMLS) technology to investigate surface roughness in stainless steel 316L 3D printing processes. Utilizing the Taguchi method in experimental design, we examine the influence of independent variables—laser power, scan speed, and hatch spacing - on surface roughness quality. Results indicate that laser power has the greatest impact, followed by scan speed and hatch spacing. Notably, both laser power and hatch spacing positively affect surface roughness, while scan speed adversely affects the top surface quality of printed components. This research enhances comprehension of the intricate relationship between process parameters and surface quality in DMLS-based 3D printing, offering insights for optimizing surface roughness in stainless steel 316L applications. The study holds practical significance for enhancing the quality and performance of 3D-printed components across diverse engineering and manufacturing sectors.
Magnetic and optical properties of ZnO nanoparticles and nanorods synthesized by green chemistry
Authors: Reyes-Damián C , Álvarez-Chimal R , Ascencio F , León-Flores J , Arenas-Alatorre J
Published: April 2024

ZnO nanostructures have attracted considerable attention because of their physicochemical properties and applications as antibacterial agents, photocatalytic reactions for pollutant removal, and electronics. Hence, efficient production and knowledge of their properties under different synthesis conditions are essential. Biosynthesis has emerged as an excellent growth-directing method for synthesizing nanomaterials, representing a soft and cleaner alternative for their production. In this study, we synthesized different ZnO nanostructures using a soft chemistry method at different growth temperatures, from 200 to 800 °C every 200 °C. The crystalline structure was estudied by x-ray Diffraction (XRD) and High-Resolution Transmission Electron Microscopy (HRTEM). The shape and size were studied by Field Emission Scanning Electron Microscopy (FESEM) and Transmission Electron Microscopy (TEM), which revealed a ZnO hexagonal phase with two shapes: nanoparticles (NPs) with irregular shapes and nanorods of different sizes. The optical properties were studied by Raman and UV-visible spectroscopy, and optical absorption measurements showed bandgap tuning of the produced nanostructures. Finally, the magnetic characteristics of the samples demonstrated magnetic anisotropy due to the preference for crystalline formation and the size of the nanoparticles. The magnetic interaction between the two types of NPs increased the diamagnetism associated with the nanorods.
Diet choices determine mercury exposure risks for people living in gold mining regions of Peru
Authors: Marchese Melissa J , Gerson Jacqueline R , Berky Axel J , Driscoll Charles , Fernandez Luis E , Hsu-Kim Heileen , Lansdale Kelsey N , Letourneau Eliza , Montesdeoca Mario , Pan William K , Robie Emily , Vega Claudia , Bernhardt Emily S
Published: April 2024

Artisanal and small-scale gold mining (ASGM) is the largest global anthropogenic mercury (Hg) source and is widespread in the Peruvian Amazon. Consuming Hg-laden foods exposes people to this potent neurotoxin. While numerous studies have examined fish Hg content near ASGM, Hg accumulation in other commonly consumed animal-and plant-based foods from terrestrial environments is often overlooked. In this study, we aim to address understudied dietary Hg exposures.

To understand Hg exposure from food staples in the Peruvian Amazon, we measured total and methyl Hg in local crops, fish, chicken meat, chicken feathers, and eggs from ASGM-impacted and upstream (reference) communities. Diet surveys were used to estimate probable weekly Hg intake from each food. Fish and chicken stable carbon and nitrogen isotope signatures were analyzed to evaluate trophic magnification.

Though few crops exceeded food safety recommendations, rice methyl Hg proportions were high (84%). Trophic level was an expected key predictor of fish Hg content. 81% (17 of 21) of local carnivorous fish exceeded WHO and EPA recommendations. Compared to upstream communities, mining-impacted communities demonstrated elevated total Hg in crops (1.55 (interquartile ranges (IQR): 0.60–3.03) μg kg−1 upstream versus 3.38 (IQR: 1.62–11.58) in mining areas), chicken meats (2.69 (IQR: BDL–9.96) μg kg−1 versus 19.68 (IQR: 6.33–48.1)), and feathers (91.20 (IQR: 39.19–216.13) μg kg−1 versus 329.99 (IQR: 173.22–464.99)). Chicken meats from mining areas exhibited over double the methyl Hg concentrations of those upstream. Methyl Hg fractions in chicken muscle tissue averaged 93%. Egg whites and livers exceeded Hg recommendations most frequently. Proximity to mining, but not trophic position, was a predictor of chicken Hg content.

Our results demonstrate that terrestrial and aquatic foods can accumulate Hg from mining activity, introducing additional human Hg exposure routes. However, locally sourced carnivorous fish was the largest contributor to an estimated three-fold exceedance of the provisional tolerable weekly Hg intake.
SPDesign: protein sequence designer based on structural sequence profile using ultrafast shape recognition
Authors: Wang Hui , Liu Dong , Zhao Kailong , Wang Yajun , Zhang Guijun
Published: April 2024

Protein sequence design can provide valuable insights into biopharmaceuticals and disease treatments. Currently, most protein sequence design methods based on deep learning focus on network architecture optimization, while ignoring protein-specific physicochemical features. Inspired by the successful application of structure templates and pre-trained models in the protein structure prediction, we explored whether the representation of structural sequence profile can be used for protein sequence design. In this work, we propose SPDesign, a method for protein sequence design based on structural sequence profile using ultrafast shape recognition. Given an input backbone structure, SPDesign utilizes ultrafast shape recognition vectors to accelerate the search for similar protein structures in our in-house PAcluster80 structure database and then extracts the sequence profile through structure alignment. Combined with structural pre-trained knowledge and geometric features, they are further fed into an enhanced graph neural network for sequence prediction. The results show that SPDesign significantly outperforms the state-of-the-art methods, such as ProteinMPNN, Pifold and LM-Design, leading to 21.89%, 15.54% and 11.4% accuracy gains in sequence recovery rate on CATH 4.2 benchmark, respectively. Encouraging results also have been achieved on orphan and de novo (designed) benchmarks with few homologous sequences. Furthermore, analysis conducted by the PDBench tool suggests that SPDesign performs well in subdivided structures. More interestingly, we found that SPDesign can well reconstruct the sequences of some proteins that have similar structures but different sequences. Finally, the structural modeling verification experiment indicates that the sequences designed by SPDesign can fold into the native structures more accurately.
Improving drug response prediction via integrating gene relationships with deep learning
Authors: Li Pengyong , Jiang Zhengxiang , Liu Tianxiao , Liu Xinyu , Qiao Hui , Yao Xiaojun
Published: April 2024

Predicting the drug response of cancer cell lines is crucial for advancing personalized cancer treatment, yet remains challenging due to tumor heterogeneity and individual diversity. In this study, we present a deep learning-based framework named Deep neural network Integrating Prior Knowledge (DIPK) (DIPK), which adopts self-supervised techniques to integrate multiple valuable information, including gene interaction relationships, gene expression profiles and molecular topologies, to enhance prediction accuracy and robustness. We demonstrated the superior performance of DIPK compared to existing methods on both known and novel cells and drugs, underscoring the importance of gene interaction relationships in drug response prediction. In addition, DIPK extends its applicability to single-cell RNA sequencing data, showcasing its capability for single-cell-level response prediction and cell identification. Further, we assess the applicability of DIPK on clinical data. DIPK accurately predicted a higher response to paclitaxel in the pathological complete response (pCR) group compared to the residual disease group, affirming the better response of the pCR group to the chemotherapy compound. We believe that the integration of DIPK into clinical decision-making processes has the potential to enhance individualized treatment strategies for cancer patients.
TripHLApan: predicting HLA molecules binding peptides based on triple coding matrix and transfer learning
Authors: Wang Meng , Lei Chuqi , Wang Jianxin , Li Yaohang , Li Min
Published: April 2024

Human leukocyte antigen (HLA) recognizes foreign threats and triggers immune responses by presenting peptides to T cells. Computationally modeling the binding patterns between peptide and HLA is very important for the development of tumor vaccines. However, it is still a big challenge to accurately predict HLA molecules binding peptides. In this paper, we develop a new model TripHLApan for predicting HLA molecules binding peptides by integrating triple coding matrix, BiGRU + Attention models, and transfer learning strategy. We have found the main interaction site regions between HLA molecules and peptides, as well as the correlation between HLA encoding and binding motifs. Based on the discovery, we make the preprocessing and coding closer to the natural biological process. Besides, due to the input being based on multiple types of features and the attention module focused on the BiGRU hidden layer, TripHLApan has learned more sequence level binding information. The application of transfer learning strategies ensures the accuracy of prediction results under special lengths (peptides in length 8) and model scalability with the data explosion. Compared with the current optimal models, TripHLApan exhibits strong predictive performance in various prediction environments with different positive and negative sample ratios. In addition, we validate the superiority and scalability of TripHLApan’s predictive performance using additional latest data sets, ablation experiments and binding reconstitution ability in the samples of a melanoma patient. The results show that TripHLApan is a powerful tool for predicting the binding of HLA-I and HLA-II molecular peptides for the synthesis of tumor vaccines. TripHLApan is publicly available at https://github.com/CSUBioGroup/TripHLApan.git.
Coding genomes with gapped pattern graph convolutional network
Authors: Wang Ruo Han , Ng Yen Kaow , Zhang Xianglilan , Wang Jianping , Li Shuai Cheng
Published: April 2024

Motivation

Genome sequencing technologies reveal a huge amount of genomic sequences. Neural network-based methods can be prime candidates for retrieving insights from these sequences because of their applicability to large and diverse datasets. However, the highly variable lengths of genome sequences severely impair the presentation of sequences as input to the neural network. Genetic variations further complicate tasks that involve sequence comparison or alignment.

Results

Inspired by the theory and applications of “spaced seeds,” we propose a graph representation of genome sequences called “gapped pattern graph.” These graphs can be transformed through a Graph Convolutional Network to form lower-dimensional embeddings for downstream tasks. On the basis of the gapped pattern graphs, we implemented a neural network model and demonstrated its performance on diverse tasks involving microbe and mammalian genome data. Our method consistently outperformed all the other state-of-the-art methods across various metrics on all tasks, especially for the sequences with limited homology to the training data. In addition, our model was able to identify distinct gapped pattern signatures from the sequences.

Availability and implementation

The framework is available at https://github.com/deepomicslab/GCNFrame.
DrivR-Base: a feature extraction toolkit for variant effect prediction model construction
Authors: Francis Amy , Campbell Colin , Gaunt Tom R
Published: April 2024

Motivation

Recent advancements in sequencing technologies have led to the discovery of numerous variants in the human genome. However, understanding their precise roles in diseases remains challenging due to their complex functional mechanisms. Various methodologies have emerged to predict the pathogenic significance of these genetic variants. Typically, these methods employ an integrative approach, leveraging diverse data sources that provide important insights into genomic function. Despite the abundance of publicly available data sources and databases, the process of navigating, extracting, and pre-processing features for machine learning models can be highly challenging and time-consuming. Furthermore, researchers often invest substantial effort in feature extraction, only to later discover that these features lack informativeness.

Results

In this article, we introduce DrivR-Base, an innovative resource that efficiently extracts and integrates molecular information (features) related to single nucleotide variants. These features encompass information about the genomic positions and the associated protein positions of a variant. They are derived from a wide array of databases and tools, including structural properties obtained from AlphaFold, regulatory information sourced from ENCODE, and predicted variant consequences from Variant Effect Predictor. DrivR-Base is easily deployable via a Docker container to ensure reproducibility and ease of access across diverse computational environments. The resulting features can be used as input for machine learning models designed to predict the pathogenic impact of human genome variants in disease. Moreover, these feature sets have applications beyond this, including haploinsufficiency prediction and the development of drug repurposing tools. We describe the resource’s development, practical applications, and potential for future expansion and enhancement.

Availability and implementation

DrivR-Base source code is available at https://github.com/amyfrancis97/DrivR-Base.
scDAC: deep adaptive clustering of single-cell transcriptomic data with coupled autoencoder and Dirichlet process mixture model
Authors: An Sijing , Shi Jinhui , Liu Runyan , Chen Yaowen , Wang Jing , Hu Shuofeng , Xia Xinyu , Dong Guohua , Bo Xiaochen , He Zhen , Ying Xiaomin
Published: April 2024

Motivation

Clustering analysis for single-cell RNA sequencing (scRNA-seq) data is an important step in revealing cellular heterogeneity. Many clustering methods have been proposed to discover heterogenous cell types from scRNA-seq data. However, adaptive clustering with accurate cluster number reflecting intrinsic biology nature from large-scale scRNA-seq data remains quite challenging.

Results

Here, we propose a single-cell Deep Adaptive Clustering (scDAC) model by coupling the Autoencoder (AE) and the Dirichlet Process Mixture Model (DPMM). By jointly optimizing the model parameters of AE and DPMM, scDAC achieves adaptive clustering with accurate cluster numbers on scRNA-seq data. We verify the performance of scDAC on five subsampled datasets with different numbers of cell types and compare it with 15 widely used clustering methods across nine scRNA-seq datasets. Our results demonstrate that scDAC can adaptively find accurate numbers of cell types or subtypes and outperforms other methods. Moreover, the performance of scDAC is robust to hyperparameter changes.

Availability and implementation

The scDAC is implemented in Python. The source code is available at https://github.com/labomics/scDAC.
A supervised Bayesian factor model for the identification of multi-omics signatures
Authors: Gygi Jeremy P , Konstorum Anna , Pawar Shrikant , Aron Edel , Kleinstein Steven H , Guan Leying
Published: April 2024

Motivation

Predictive biological signatures provide utility as biomarkers for disease diagnosis and prognosis, as well as prediction of responses to vaccination or therapy. These signatures are identified from high-throughput profiling assays through a combination of dimensionality reduction and machine learning techniques. The genes, proteins, metabolites, and other biological analytes that compose signatures also generate hypotheses on the underlying mechanisms driving biological responses, thus improving biological understanding. Dimensionality reduction is a critical step in signature discovery to address the large number of analytes in omics datasets, especially for multi-omics profiling studies with tens of thousands of measurements. Latent factor models, which can account for the structural heterogeneity across diverse assays, effectively integrate multi-omics data and reduce dimensionality to a small number of factors that capture correlations and associations among measurements. These factors provide biologically interpretable features for predictive modeling. However, multi-omics integration and predictive modeling are generally performed independently in sequential steps, leading to suboptimal factor construction. Combining these steps can yield better multi-omics signatures that are more predictive while still being biologically meaningful.

Results

We developed a supervised variational Bayesian factor model that extracts multi-omics signatures from high-throughput profiling datasets that can span multiple data types. Signature-based multiPle-omics intEgration via lAtent factoRs (SPEAR) adaptively determines factor rank, emphasis on factor structure, data relevance and feature sparsity. The method improves the reconstruction of underlying factors in synthetic examples and prediction accuracy of coronavirus disease 2019 severity and breast cancer tumor subtypes.

Availability and implementation

SPEAR is a publicly available R-package hosted at https://bitbucket.org/kleinstein/SPEAR.
Teaching scientific evidence and critical thinking for policy making
Authors: Pasternak Taschner Natalia , Almeida Paulo
Published: April 2024

While there is worldwide tendency to promote the use of scientific evidence to inform policy making, little has been done to train scientists and policy makers for this interaction. If we want to bridge the gap between academia, scientific knowledge, and policy, we must begin by providing formal training and skill building for actors and stakeholders. Scientists are not trained to communicate and inform policy, and policy makers are not trained to understand scientific process and assess evidence. Building an environment where this collaboration can flourish depends on teaching competencies and abilities specific for decision-making processes. As professors of policy with a background in science, we have started teaching preliminary courses on the use of scientific evidence in policy making. Feedback from students and institutions has been positive, paving the way for similar courses in other schools and institutions and maybe even new career paths. This article is intended to share our experience in designing and teaching courses aimed at training policy makers. Moving forward we plan to include training for science majors, thus encompassing the two main sides of this dialogue and opening new career opportunities for scientists and policy makers.
Tazarotene is as effective and well-tolerated as imiquimod in the treatment of verruca plana: a comparative randomized controlled trial
Authors: Nofal Hagar , Omran Fatma , ElKholy Basma , Nofal Sara , Nofal Ahmad
Published: April 2024

Background

Plane warts, when multiple and recurrent, present a therapeutic challenge acting as a source of reinfection, causing frustration and affecting a patient’s quality of life. For large numbers of lesions in cosmetically significant sites, topical treatment is preferred to avoid potential sequelae.

Objectives

To evaluate and compare the efficacy and tolerability of tazarotene 0.1% gel vs. imiquimod 5% cream for the treatment of plane warts.

Methods

In a parallel three-arm randomized controlled trial, 60 patients were randomized to imiquimod, tazarotene or placebo groups. Patients applied the corresponding treatment once daily at night for a maximum of 12 weeks. Primary outcomes were the percentage of respondents with complete clearance in the three studied groups, and the type and frequency of side-effects in each group.

Results

Both active treatments resulted in significant improvement compared with baseline and the placebo group (P = 0.001). The imiquimod 5% treated group showed complete clearance in 50% (10/20) of patients, partial response in 15% (3/20), and no response in 35% (7/20). Tazarotene 0.1% gel showed complete clearance in 40% (8/20) of patients, partial response in 40% (8/20), and no response in 20% (4/20). No significant difference was detected between the imiquimod and tazarotene groups (P = 0.19).

Conclusions

Compared with imiquimod, tazarotene 0.1% gel for the treatment of plane warts seems to offer an equivalent treatment response, it maintained efficacy without recurrence and had a safer profile regarding dyspigmentation with an advantageous cheaper cost.
Behaviorally meaningful functional networks mediate the effect of Alzheimer’s pathology on cognition
Authors: Ziontz Jacob , Harrison Theresa M , Chen Xi , Giorgio Joseph , Adams Jenna N , Wang Zehao , Jagust William ,   Alzheimer’s Disease Neuroimaging Initiative
Published: April 2024

Tau pathology is associated with cognitive impairment in both aging and Alzheimer’s disease, but the functional and structural bases of this relationship remain unclear. We hypothesized that the integrity of behaviorally meaningful functional networks would help explain the relationship between tau and cognitive performance. Using resting state fMRI, we identified unique networks related to episodic memory and executive function cognitive domains. The episodic memory network was particularly related to tau pathology measured with positron emission tomography in the entorhinal and temporal cortices. Further, episodic memory network strength mediated the relationship between tau pathology and cognitive performance above and beyond neurodegeneration. We replicated the association between these networks and tau pathology in a separate cohort of older adults, including both cognitively unimpaired and mildly impaired individuals. Together, these results suggest that behaviorally meaningful functional brain networks represent a functional mechanism linking tau pathology and cognition.
Aerobic fitness as a moderator of acute aerobic exercise effects on executive function
Authors: Dai Yuan-Fu , Zhong Xiao-Ke , Gao Xiao-Yan , Huang Chen , Leng Wen-Wu , Chen Han-Zhe , Jiang Chang-Hao
Published: April 2024

This study aimed to investigate the moderating role of aerobic fitness on the effect of acute exercise on improving executive function from both behavioral and cerebral aspects. Thirty-four young individuals with motor skills were divided into high- and low-fitness groups based on their maximal oxygen uptake. Both groups completed 30 min of moderate-intensity aerobic exercise on a power bike. Executive function tests (Flanker, N-back, More-odd-shifting) were performed before and after exercise and functional near-infrared spectroscopy was used to monitor prefrontal cerebral blood flow changes during the tasks. The results indicated significant differences between the two groups regarding executive function. Participants with lower aerobic fitness performed better than their higher fitness counterparts in inhibitory control and working memory, but not in cognitive flexibility. This finding suggests that the aerobic fitness may moderate the extent of cognitive benefits gained from acute aerobic exercise. Furthermore, the neuroimaging data indicated negative activation in the frontopolar area and dorsolateral prefrontal cortex in response to three complex tasks. These findings underscore the importance of considering individual aerobic fitness when assessing the cognitive benefits of exercise and could have significant implications for tailoring fitness programs to enhance cognitive performance.
Stress conditions extend maternal care and delay juvenile development in crayfish
Authors: Kaur Davinder , Das Koushik , Kubec Jan , Buřič Miloš
Published: April 2024

Maternal care in crayfish has been extensively studied, but little is known of its response to environmental factors. We studied the duration of maternal care and its association with the juvenile development of marbled crayfish Procambarus virginalis in adverse environmental conditions. We exposed females with developmental stage 3 juveniles to environments of low water volume (LW) with food provided, low water volume with no feed (starvation) (LWS), and low water volume without feeding plus an intruder (red swamp crayfish male) (LWSI). A control group with standard water level/feed conditions was included for comparison. Groups were monitored for up to 90 days. The LWS group showed significantly prolonged maternal care (~65 days) as indicated by an extended attachment phase, delayed moulting of mothers (~53 days), and retarded juvenile development. In the LWSI group, conflict precluded extended maternal care. Low use of shelter and feeding was evident under all stress conditions. The results showed that crayfish females modify maternal care in accordance with conditions, providing a longer period of safety for offspring under adverse circumstances. It is possible that the expression of maternal pheromones can manipulate the developmental rate in juveniles, a topic for future research.
Mid-term outcomes of right ventricular papillary muscle approximation for severe functional tricuspid regurgitation
Authors: Ito Chihiro , Kohno Hiroki , Matsuura Kaoru , Watanabe Michiko , Inui Tomohiko , Matsumiya Goro
Published: April 2024

OBJECTIVES

Recurrence of tricuspid regurgitation (TR) after tricuspid annuloplasty can occur in cases where a dilated right ventricle exists and subsequent leaflet tethering follows. We previously reported a new technique of the right ventricular papillary muscle approximation (RV-PMA) for functional TR associated with leaflet tethering. The objective of this study is to elucidate the mid-term outcomes and evaluate the durability of RV-PMA.

METHODS

Between January 2014 and March 2023, we applied RV-PMA in 20 patients of advanced functional TR with severe leaflet tethering. The indication of the technique was severe TR with leaflet tethering height >8 mm, and/or a right ventricular end-diastolic diameter >45 mm. The patients were followed up with echocardiography before discharge and at annual interval thereafter.

RESULTS

There was no perioperative mortality. In the echocardiography performed before discharge, TR was decreased to mild or less in 85%, and a significant improvement in right ventricular end-diastolic diameter and tethering height were achieved (53–45 mm and 11.1–4.4 mm, respectively). Furthermore, during the median 3-year follow-up period, TR was kept controlled mild or less in 80% of the cases.

CONCLUSIONS

RV-PMA is considered to be a safe, effective and durable technique as an additional approach for tricuspid annuloplasty.
Integrative analysis of the methylome and transcriptome of tomato fruit (Solanum lycopersicum L.) induced by postharvest handling
Authors: Zhou Jiaqi , Zhou Sitian , Chen Bixuan , Sangsoy Kamonwan , Luengwilai Kietsuda , Albornoz Karin , Beckles Diane M
Published: April 2024

Tomato fruit ripening is triggered by the demethylation of key genes, which alters their transcriptional levels thereby initiating and propagating a cascade of physiological events. What is unknown is how these processes are altered when fruit are ripened using postharvest practices to extend shelf-life, as these practices often reduce fruit quality. To address this, postharvest handling-induced changes in the fruit DNA methylome and transcriptome, and how they correlate with ripening speed, and ripening indicators such as ethylene, abscisic acid, and carotenoids, were assessed. This study comprehensively connected changes in physiological events with dynamic molecular changes. Ripening fruit that reached ‘Turning’ (T) after dark storage at 20°C, 12.5°C, or 5°C chilling (followed by 20°C rewarming) were compared to fresh-harvest fruit ‘FHT’. Fruit stored at 12.5°C had the biggest epigenetic marks and alterations in gene expression, exceeding changes induced by postharvest chilling. Fruit physiological and chronological age were uncoupled at 12.5°C, as the time-to-ripening was the longest. Fruit ripening to Turning at 12.5°C was not climacteric; there was no respiratory or ethylene burst, rather, fruit were high in abscisic acid. Clear differentiation between postharvest-ripened and ‘FHT’ was evident in the methylome and transcriptome. Higher expression of photosynthetic genes and chlorophyll levels in ‘FHT’ fruit pointed to light as influencing the molecular changes in fruit ripening. Finally, correlative analyses of the -omics data putatively identified genes regulated by DNA methylation. Collectively, these data improve our interpretation of how tomato fruit ripening patterns are altered by postharvest practices, and long-term are expected to help improve fruit quality.
Experiences from targeted removal of farmed Atlantic salmon from Norwegian rivers
Authors: Skolgund Helge , Kambestad Marius , Normann Eirik Straume , Wiers Tore , Lehmann Gunnar Bekke , Urdal Kurt , Barlaup Bjørn Torgeir , Vollset Knut Wiik
Published: April 2024

Farmed salmon escaping from aquaculture and interbreeding with wild conspecifics pose a significant threat to the genetic integrity of natural salmon populations. Despite advancements in aquaculture security, escape incidents persist, prompting the need for effective mitigation strategies. This study summarizes experiences from efforts to remove escaped farmed salmon over a 12-year period in 63 western Norwegian rivers, using either (1) spearfishing during snorkelling by trained personnel or (2) traditional fishing methods employed by local groups. Recaptured farmed salmon ranged widely in size and included both spawners as well as immature fish, demonstrating that farmed fish entering rivers comprise fish of different ages and escape histories. Traditional fishing by locals recaptured the highest number of farmed fish, while removal during snorkelling in general captured larger and mature fish. On average, 53% of the farmed salmon observed during snorkelling were recaptured. This efficacy was influenced by the number of farmed fish present and the size of the farmed fish. In addition, efficacy increased over time, indicating that the removal team became more efficient. The study underscores that active removal, when executed judiciously, contributes to reducing the ecological risks associated with escaped farmed fish, complementing broader strategies for sustainable aquaculture.
Active and passive smoking and breast cancer in Japan: a pooled analysis of nine population-based cohort studies
Authors: Wada Keiko , Nagata Chisato , Utada Mai , Sakata Ritsu , Kimura Takashi , Tamakoshi Akiko , Sugawara Yumi , Tsuji Ichiro , Sato Ren , Sawada Norie , Tsugane Shoichiro , Oze Isao , Ito Hidemi , Kitamura Tetsuhisa , Koyanagi Yuriko N , Lin Yingsong , Matsuo Keitaro , Abe Sarah K , Inoue Manami ,   for the Research Group for the Development and Evaluation of Cancer Prevention Strategies in Japan, Inoue Manami , Abe Sarah Krull , Sawada Norie , Tanaka Shiori , Kimura Takashi , Sugawara Yumi , Mizoue Tetsuya , Nomura Shuhei , Takimoto Hidemi , Ito Hidemi , Matsuo Keitaro , Lin Yingsong , Wada Keiko , Kitamura Tetsuhisa , Sakata Ritsu , Tanaka Keitaro , Charvat Hadrien , Hidaka Akihisa , Hirabayashi Mayo , Iwasaki Motoki , Kitamura Yuri , Mori Nagisa , Muto Michihiro , Nagata Chisato , Naito Mariko , Nakayama Tomio , Nishino Yoshikazu , Sadakane Atsuko , Saito Eiko , Sasazuki Shizuka , Shimazu Taichi , Shimizu Hiroyuki , Sugiyama Kemmyo , Suzuki Hidekazu , Tamakoshi Akiko , Tsubono Yoshitaka , Tsuji Ichiro , Tsugane Shoichiro , Utada Mai , Wakai Kenji , Yamagiwa Yoko , Yamaji Taiki
Published: April 2024

Background

Epidemiological studies have shown inconsistent results regarding the link between smoking and breast cancer risk, despite the biological plausibility of a positive association.

Methods

Participants were 166 611 women from nine prospective cohort studies in Japan which launched in 1984–1994 and followed for 8–22 years. Information on smoking and secondhand smoke was obtained through self-administered baseline questionnaires. Breast cancer was defined as code C50 according to the International Classification of Diseases for Oncology, 3rd Edition or the International Classification of Diseases, 10th Revision. After adjusting for several potential confounders, relative risks for breast cancer were calculated in the individual studies according to the current or previous status of active and passive smoking using Cox regression, followed by a summary estimate of hazard ratios using random-effects meta-analyses.

Results

Of the 60 441 participants who reported being premenopausal and 106 170 who reported being postmenopausal at baseline, 897 and 1168 developed breast cancer during follow-up, respectively. Compared with never smokers, current smokers had a higher risk of developing breast cancer before the age of 50 years. In addition, ever smokers who started smoking at 30 years of age or younger, or who started smoking before first childbirth, had a higher risk of developing breast cancer before the age of 50 years. No association between adulthood or childhood exposure to secondhand smoke and breast cancer was observed.

Conclusion

Smoking may increase the risk of premenopausal breast cancer, and smoking earlier in life might be especially harmful. The impact of secondhand smoke needs further investigation.
Optimization of combustion strategy for application of sustainable fuels regarding elimination of vehicles emission footprint
Authors: Puškár Michal , Kopas Melichar
Published: April 2024

Nowadays, transport generates a significant portion of greenhouse gas emissions and at the same time it is also one of the dominant polluters within urban agglomerations. However, vehicles with piston combustion engines are still the most popular choice of consumers thanks to the unquestionable advantages of these engines. There are currently several hundred million cars driven by combustion engines in EU-countries, and approximately one-and-a-half billion of worldwide. The only possible way to reduce the emission footprint of automotive transport while at the same time keeping the current fleet of combustion engine vehicles, is the application of synthetic fuels. Of course, hydrogen will have its place in the new green economy. A very promising idea is the low temperature combustion (LTC) technology. This technology combines the high efficiency of modern combustion engines with utilization of climate-neutral fuels. Therefore, the LTC technology can be a suitable solution for the sustainable future of the current vehicle fleet. The presented scientific article is focused on the development of dual-fuel technology, specifically on optimization of combustion conditions as well as on design of a new geometrical shape of the combustion chamber regarding minimization of engine emissions. This article also introduces a unique LTC system, which is characterized by significant achievements in reducing emissions. This innovative system together with design of a new geometrical shape are the subjects of patent protection.
Slow Dissent and Worldmaking beyond Imperial Relations in “Kamer-amère” (Bitter Cameroon)
Authors: Murrey Amber
Published: April 2024

Working in the subfields of postcolonial geographies of responsibility and Black and African Geographies, my analysis centers on Cameroonian political resistance and practices of worldmaking. From January 2016 to August 2023, political activists experienced a set of difficulties: A wariness and oftentimes hostility to France’s continued support for the authoritarian state, dismissals by state representatives that dissenters were “externally supported,” and misappropriations of the anti-imperial mantel by government representatives. Over the preceding several decades, the state fostered a political environment antagonistic toward Cameroonians of the diaspora, and this was instrumentalized in the widespread dismissal of activists as foreign, foreign-backed, or foreign-influenced. Activists were hesitant but sometimes strategically prepared to call upon transnational groups for attention and political action against repression and violence in Cameroon. In the context of the state’s appropriation of an anti-imperialist ideology, I argue that transnational solidarities must be attuned to and integrated with local politics in Cameroon. Making sense of popular debates regarding (anti)imperialism, (anti)intervention, and transnational solidarity in conditions of authoritarianism matters for political debates across the African continent.
Cheap Tweets?: Crisis Signaling in the Age of Twitter
Authors: Harris Benjamin Norwood , Lin-Greenberg Erik
Published: April 2024

World leaders are increasingly turning to social media to engage in crisis signaling. This raises important questions about the effects of emerging communication technologies on international politics. In particular, are threats issued via social media seen as more or less credible than those issued through traditional channels such as government press releases? Using survey experiments fielded both on unique samples of foreign policy experts in the United States, India, and Singapore and on US public samples, we find that threat medium generally generates no significant difference in perceived credibility among national security experts and members of the public. Put differently, tweeted threats are not seen as “cheaper talk” than threats issued through more traditional channels. This project extends work on crisis signaling, elite decision-making, and the domestic politics of international relations by taking into account an increasingly common technology.
Transcriptome data reveal beneficial effects of Rickettsia (Rickettsiales: Rickettsiaceae) on Bemisia tabaci
(Hemiptera: Aleyrodidae) through nutritional factors and defense mechanisms
Authors: Li Yi-Han , Peng Jing , Wu Qing-Jun , Sun Jing-Chen , Zhang Peng-Jun , Qiu Bao-Li
Published: April 2024

Whitefly Bemisia tabaci (Hemiptera: Aleyrodidae) is a destructive insect pest of many crops. Rickettsia infection in different cryptic species of B. tabaci has been observed worldwide. Understanding the interactions between these 2 organisms is critical to developing Rickettsia-based strategies to control B. tabaci and thereby reduce the transmission of related vector-borne viruses. In this study, we investigated the effects of Rickettsia infection on the biological characteristics of the Middle East Asia Minor 1 (MEAM1) strain of B. tabaci through biological analysis of infected and uninfected individuals. The results of this study suggest that Rickettsia may confer fitness benefits. These benefits include increased fertility, improved survival rates, accelerated development, and resulted in female bias. We also investigated the transcriptomics impact of Rickettsia infection on B. tabaci by performing a comparative RNA-seq analysis of nymphs and adult females, both with and without the infection. Our analysis revealed 218 significant differentially expressed genes (DEGs) in infected nymphs compared to uninfected ones and 748 significant DEGs in infected female adults compared to their uninfected whiteflies. Pathway analysis further revealed that Rickettsia can affect many important metabolic pathways in whiteflies. The results suggest that Rickettsia plays an essential role in energy metabolism, and nutrient synthesis in the B. tabaci MEAM1, and depends on metabolites obtained from the host to ensure its survival. Overall, our findings suggest that Rickettsia has beneficial effects on B. tabaci and offered insights into the potential molecular mechanisms governing the interactions between Rickettsia and B. tabaci MEAM1.
Milanese antique dealers and the international market
Authors: Colombi Martina
Published: April 2024

This article provides two concrete examples of the opening of the Milanese art market to the international stage at the time of Gian Giacomo Poldi Pezzoli. The main focus is on the career of Giuseppe Baslini (1817–1887), the most important art dealer in nineteenth-century Milan. A true self-made man, Baslini entertained close relations with the most eminent Milanese collectors of the time, including Poldi Pezzoli and the Bagatti Valsecchi brothers; his success was secured by the international market on three major axes – London, Paris and Berlin. The second example concerns the family company of the Grandi art dealers, during the same years. In 1877 Baslini’s brothers-in-law Carlo (1842–1914) and Antonio (1857–1923) Grandi inherited the company of their father, Antonio (1810–1877), which originally specialized in Old Master drawings and prints, but extended its interests to paintings and objets d’art soon after Baslini’s death. The Grandi correspondence, preserved by the heirs and recently donated to the Fondo per l’Ambiente Italiano, has provided the opportunity to reconstruct their business, which had an international dimension from its inception.
‘Caregivers’ Experiences of a Singing Training Program to Support Person-Centered Dementia Care
Authors: Stuart-Röhm Karyn , Clark Imogen N , Baker Felicity A
Published: April 2024

Music-based interventions are acknowledged to be accessible and beneficial to people living with dementia. As part of an over-arching research project exploring the contributions of person-centered caregiver singing (PCCS) intervention to caregiver’s provision of care, this study aimed to explore caregiver’s experiences of a PCCS training program. 8 caregivers across 2 care homes in South Africa participated in 4 iterative participatory cycles aimed at refining the training protocol. We completed a thematic analysis of semi-structured interviews of caregivers’ experiences of the training. 3 themes emerged: workshop components contributed to positive learning experiences; caregivers’ increased knowledge and insight into dementia, music, and personhood; and caregivers’ enhanced self-efficacy which encompassed their emotional wellbeing, self-awareness, and confidence. Our study highlights caregivers’ self-efficacy, self-hood, and personhood as valuable benefits in person-centered care training. Caregivers experienced training as both professionally and personally beneficial. While PCCS supported a shift toward a person-centered care approach, further research would help establish approaches to support sustainability of PCCS training and use in wider contexts.
Retracted and Replaced: Increasing power in screening trials by testing control-arm specimens: application to multicancer detection screening
Authors: Katki Hormuzd A , Prorok Philip C , Castle Philip E , Minasian Lori M , Pinsky Paul F
Published: April 2024

Background

Cancer screening trials have required large sample sizes and long time-horizons to demonstrate cancer mortality reductions, the primary goal of cancer screening. We examine assumptions and potential power gains from exploiting information from testing control-arm specimens, which we call the “intended effect” (IE) analysis that we explain in detail herein. The IE analysis is particularly suited to tests that can be conducted on stored specimens in the control arm, such as stored blood for multicancer detection (MCD) tests.

Methods

We simulated hypothetical MCD screening trials to compare power and sample size for the standard vs IE analysis. Under two assumptions that we detail herein, we projected the IE analysis for 3 existing screening trials (National Lung Screening Trial [NLST], Minnesota Colon Cancer Control Study [MINN-FOBT-A], and Prostate, Lung, Colorectal, Ovarian Cancer Screening Trial—colorectal component [PLCO-CRC]).

Results

Compared with the standard analysis for the 3 existing trials, the IE design could have reduced cancer-specific mortality P values 5-fold (NLST), 33-fold (MINN-FOBT-A), or 14 160-fold (PLCO-CRC) or, alternately, reduced sample size (90% power) by 26% (NLST), 48% (MINN-FOBT-A), or 59% (PLCO-CRC). For potential MCD trial designs requiring 100 000 subjects per arm to achieve 90% power for multicancer mortality for the standard analysis, the IE analysis achieves 90% power for only 37 500-50 000 per arm, depending on assumptions concerning control-arm test-positives.

Conclusions

Testing stored specimens in the control arm of screening trials to conduct the IE analysis could substantially increase power to reduce sample size or accelerate trials and could provide particularly strong power gains for MCD tests.
Manual rolling load and low back pain among workers in Japan: a cross-sectional study
Authors: Iwakiri Kazuyuki , Sasaki Takeshi , Du Tanghuizi , Miki Keiichi , Oyama Fuyuki
Published: April 2024

Objectives:

Manual rolling of heavy objects remains in the workplace. The Health and Safety Executive (HSE) in the United Kingdom recommends load weights of <400 kg in the rolling task. However, the association of rolling weights <400 kg with work-related low back pain (LBP) has not been sufficiently investigated. This study examined the effect of rolling loads weighing <400 kg on LBP among Japanese workers.

Methods:

A web-based survey gathered information from 15 158 workers in 2022. Among them, 15 035 did not handle loads, whereas 123 handled rolling weights <400 kg. Load weight was categorized into 4 groups: no-handling (0 kg) and rolling weights of ≤20, 20-40, and >40 kg. Multiple logistic regression analysis examined the association between the subdivided rolling weight and LBP.

Results:

No significant differences in odds ratio (OR) of LBP were found for workers handling ≤40 kg rolling weights compared with that for no-handling workers. However, workers handling >40 kg rolling weights had a significantly greater OR of LBP than those not handling loads.

Conclusions:

Rolling weights between 40 and 400 kg could place a high stress on the lower back. Implementation in Japan of the HSE recommendations regarding rolling load should be carefully considered.
Validity and reliability of Japanese version of the MAPO index for assessing manual patient handling in nursing homes
Authors: Tani Naomichi , Ichikawa Fumiko , Oda Susumu , Menoni Olga , Tasso Marco , Iwakiri Kazuyuki , Kumashiro Masaharu , Ebara Takeshi , Tsutsui Yasuhiro
Published: April 2024

Objectives:

Low back pain (LBP) among caregivers in Japanese nursing homes has long been considered an occupational health issue. This study aimed to verify the reliability and validity of our developed Japanese version of the Movement and Assistance for Hospitalized Patients (J-MAPO) index, a risk assessment tool for LBP, in nursing homes.

Methods:

Two inspectors assessed 15 nursing homes using J-MAPO, and deduced 3 LBP risk levels as follows: low, moderate, and high risk. Caregivers in nursing homes responded to a self-administered questionnaire on LBP over the past 12 months. Data from 296 caregivers with no missing data were used. We further used logistic regression models to analyze the association between LBP as a dependent variable, and J-MAPO risk level as an independent variable. We used Cohen kappa coefficient to assess interrater reliability to further assess the agreement between the 2 inspectors.

Results:

The multivariate logistic regression analysis showed that the adjusted odds ratio and 95% CIs for LBP increased progressively with J-MAPO risk level (Low-risk: 1.00; Moderate-risk: 1.70 [0.74-3.91]; High-risk: 2.67 [1.28-5.56]). Furthermore, the J-MAPO risk levels assessed by the 2 inspectors were in perfect agreement (κ = 1) observed for interrater reliability using Cohen kappa coefficient.

Conclusions:

There was high interrater reliability, and J-MAPO risk levels were associated with LBP. Therefore, our results suggest that the J-MAPO is a useful risk assessment tool for LBP in Japanese nursing homes.