bluuebunny/crossref_metadata_2025 huggingface dataset:
Chemical engineering of zein with polyethylene glycol and Angiopep-2 to manufacture a brain-targeted docetaxel nanomedicine for glioblastoma treatment
Authors: Awad Seem , Araújo Marco , Faria Paulo , Sarmento Bruno , Martins Cláudia
Published: July 2024

Glioblastoma (GBM) is the deadliest adult brain cancer. The current standard-of-care chemotherapy using orally administered temozolomide (TMZ) presents poor improvement in patient survival, emphasizing the compelling need for new therapies. A possible chemotherapeutic alternative is docetaxel (DTX), which possesses higher tumoricidal potency against GBM cells. However, its limited blood-brain barrier (BBB) permeability poses a constraint on its application. Nonetheless, nanomedicine offers promising avenues for overcoming this challenge. Angiopep-2 (ANG2) is a peptide that targets the BBB-overexpressed low-density lipoprotein receptor (LDLR). In this work, we managed, for the first time, to employ a pioneering approach of covalently linking zein protein with polyethylene glycol (PEG) and ANG2 prior to its formulation into nanoparticles (ZNPs) with enhanced stability and LDLR-mediated brain targetability, respectively. Carbodiimide and click chemistry approaches were optimized, resulting in functional modification of zein with around 25% PEG, followed by functional modification of PEG with nearly 100% ANG2. DTX-loaded ZNPs presented 100 nm average size, indicating high suitability for BBB crossing through receptor-mediated transcytosis. ZNPs maintained the cytotoxic effect of the loaded DTX against GBM cells, while demonstrating a safe matrix against BBB cells. Importantly, these brain-targeted ZNPs showcased up to fourfold enhancement in blood-to-brain permeability in a BBB in vitro model, highlighting the potential of this novel approach of BBB targeting in significantly improving therapeutic outcomes for GBM patients. The versatility of the system and the possibility of significantly increasing drug concentration in the brain open the door to its future application in a wide range of other brain-related diseases.

Graphical abstract
Biodynamers: applications of dynamic covalent chemistry in single-chain polymer nanoparticles
Authors: Zeroug-Metz Lena , Lee Sangeun
Published: July 2024

Dynamic Covalent Chemistry (DCC) enables the development of responsive molecular systems through the integration of reversible bonds at the molecular level. These systems are thermodynamically stable and capable of undergoing various molecular assemblies and transformations, allowing them to adapt to changes in environmental conditions like temperature and pH. Introducing DCC into the field of polymer science has led to the design of Single-Chain Nanoparticles (SCNPs), which are formed by self-folding via intramolecular crosslinking mechanisms. Defined by their adaptability, SCNPs mimic biopolymers in size and functionality. Biodynamers, a subclass of SCNPs, are specifically designed for their stimuli-responsive and tunable, dynamic properties. Mimicking complex biological structures, their scope of application includes target-specific and pH-responsive drug delivery, enhanced cellular uptake and endosomal escape. In this manuscript, we discuss the integration of DCC for the design of SCNPs, focusing particularly on the characteristics of biodynamers and their biomedical and pharmaceutical applications. By underlining their potential, we highlight the factors driving the growing interest in SCNPs, providing an overview of recent developments and future perspectives in this research field.

Graphical Abstract
Nutrition Module: Addressing the Nutrition Education Gap in Undergraduate Medical Curricula via a Novel Approach
Authors: Chen Pinyu , Alexander Seth McKenzie , Baute Penry Vanessa
Published: July 2024

Introduction

Despite the known importance of nutrition on health outcomes, most medical curricula do not dedicate sufficient time to nutrition topics. Many barriers prevent the successful integration of nutrition education into existing curricula.

Methods

We created an online nutrition module to educate students about foundational nutritional topics. To assess the efficacy of the module and improve integration of knowledge, students were asked to take a pre-assessment and a post-assessment immediately before and after completion of the module. Two months after completion, students were asked to take a follow-up assessment to assess long-term retention of the information covered in the module.

Results

A total of 15 medical students completed all the requirements of the nutrition module (including pre-, post-, and follow-up assessments). The mean percent correct on the pre-, post-, and follow-up assessments were 67.5%, 87.0%, and 83.5%, respectively. The absolute difference between the pre- and post-module scores was 3.8 points (19.0%, t = 9.2, p < 0.0001). The absolute difference between the mean post- and follow-up scores was − 0.93 points (4.7%, t =  − 1.7, p = 0.1154).

Discussion

Most medical students do not feel adequately prepared to counsel patients on nutrition. Development of an accessible, online nutrition module was effective in teaching medical students about nutritional topics and in retaining the information over time. Advantages of the module include flexibility for students to choose when to complete the learning, brief (< 1 h) concise material, and the ability for educators to quickly update the module content.
Regional Assessment of Groundwater Contamination Risk from Crude Oil Spillages in the Niger Delta: A Novel Application of the Source-Pathway-Receptor Model
Authors: Oyebamiji Ajibola R. , Hoque Mohammad A. , Whitworth Malcolm
Published: July 2024

Onshore oil spills are known for their disastrous environmental impacts and potential to cause lasting damage to underlying groundwater. The Niger Delta is particularly vulnerable to widespread spillages linked to extensive oil exploration, transportation, and theft-related incidents. This research employed a geospatial approach in formulating risk equations, based on the source-pathway-receptor (S-P-R) model using multiple openly available data sets, to assess groundwater contamination risk in the Niger Delta Region (NDR), Nigeria. To develop the overall risk equation, the study combined fourteen thematic data layers including the volume of oil spilled, type of spill, slope, elevation, proximity to spill site, pipeline, oil wells and streams, drainage density, mean annual precipitation and population density. These layers were integrated into source potency, pathway transmissivity, and receptor susceptibility. The NDR was systematically categorized into low, moderate, and high groundwater risk zones. The delineation revealed that high-risk zones predominantly span the central areas, extending from southeast to northwest, effectively encircled by regions of low to medium risk located in both the northern and southern extents of the delta. The efficacy of the risk model was corroborated by existing knowledge. Moderate to high-risk zones were found to be in about 16% of the NDR, revealing previously unknown areas of risk. This spatial configuration underscores a significant gradient in contamination risk across the NDR, with the central corridor emerging as a critical focus for groundwater protection and remediation efforts. In line with UN Sustainable Development Goal (SDG) #6, this study recommends targeted strategies to ensure clean water provision in these identified high-risk areas. By leveraging the S-P-R model within this complex and sensitive ecological area, this research both advances environmental risk assessment and sets a precedent for future large-scale environmental risk assessments utilizing open-source data.
Analysis of preschool children’s outdoor play behaviours
Authors: Cakan Ayse , Acer Dilek
Published: July 2024

This research aimed to observe preschoolers' outdoor play behaviours, gather their opinions about the outdoors and examine their drawings related to outdoor activities. Methodology: Using a mixed methods approach, children aged 60 to 69 months were studied over a 4-week period in a preschool setting. Observation, interviews, and drawing tasks were used as data sources, ensuring triangulation. The children's outdoor play behaviours were video-recorded, and their opinions were taken through one-on-one interviews. The children were asked to draw pictures of the materials they wanted to see in the playground. This study explored how the outdoor environment impacts children's play behaviour. Research Findings: Using content analysis and frequency distribution, we found that the most frequently played in the schoolyard was functional play, and they most often played alone and solitarily. Physical conditions, such as the schoolyard grounds, material diversity, and material types within the play environment, affected children's outdoor play behaviours. The schoolyard setting led children to consider alternative play types and toys. The children stated that they mostly preferred to play in the park area and playhouse within the schoolyard. The children also stated that they wanted to see fixed park components, sports, dramatic play, arts, entertainment, and natural areas. In addition, the observed play behaviours and children's views regarding the schoolyard supported one another. Practice and Policy: These results support the theory that the environment impacts behaviour and show that outdoor spaces tailored to children's wishes and needs are an effective way to encourage quality play behaviours.
How AI Works: Reconfiguring Lifelong Learning
Authors: Palenski Ted , Hills Libby , Unnikrishnan Sagarika , Eynon Rebecca
Published: July 2024

Lifelong learning is a current policy focus in many countries, with AI technologies promoted as both the motivation for the need for lifelong learning (due to its assumed role in social change) and as an important way to ‘deliver’ learning across the life course. Such policies tend to be instrumental and technologically deterministic, and there is a need to properly theorize the relationships between AI and lifelong learning to better inform policy and practice. In this paper, we examine the ways that academic communities conceptualize AI and lifelong learning, based on a thematic analysis of existing academic literature in contexts beyond formal education. We identify three groups of research, which vary according to their engagement with theories of learning and AI technology and how AI ‘works’. In group 1 (working AI), AI is assumed to contribute to increased efficiency of humans and learning; in group 2 (working with AI), AI is implemented and conceptualized as a peer or colleague; and in group 3 (reconfiguring AI), AI is viewed as part of a wider reconfiguration of humans and their contexts. This latter group, though least well represented in the literature, holds promise in advancing a postdigital research agenda that focuses not solely on how AI works to increase efficiency, but how people are increasingly working, learning, and living with AI, thus moving beyond exclusively instrumental, economic, and technologically deterministic concerns.
A hyperparameter study for quantum kernel methods
Authors: Egginger Sebastian , Sakhnenko Alona , Lorenz Jeanette Miriam
Published: July 2024

Quantum kernel methods are a promising method in quantum machine learning thanks to the guarantees connected to them. Their accessibility for analytic considerations also opens up the possibility of prescreening datasets based on their potential for a quantum advantage. To do so, earlier works developed the geometric difference, which can be understood as a closeness measure between two kernel-based machine learning approaches, most importantly between a quantum kernel and a classical kernel. This metric links the quantum and classical model complexities, and it was developed to bound generalization error. Therefore, it raises the question of how this metric behaves in an empirical setting. In this work, we investigate the effects of hyperparameter choice on the model performance and the generalization gap between classical and quantum kernels. The importance of hyperparameters is well known also for classical machine learning. Of special interest are hyperparameters associated with the quantum Hamiltonian evolution feature map, as well as the number of qubits to trace out before computing a projected quantum kernel. We conduct a thorough investigation of the hyperparameters across 11 datasets, and we identify certain aspects that can be exploited. Analyzing the effects of certain hyperparameter settings on the empirical performance, as measured by cross validation accuracy, and generalization ability, as measured by geometric difference described above, brings us one step closer to understanding the potential of quantum kernel methods on classical datasets.
Hybrid genetic optimization for quantum feature map design
Authors: Pellow-Jarman Rowan , Pillay Anban , Sinayskiy Ilya , Petruccione Francesco
Published: July 2024

Kernel methods are an import class of techniques in machine learning. To be effective, good feature maps are crucial for mapping non-linearly separable input data into a higher dimensional (feature) space, thus allowing the data to be linearly separable in feature space. Previous work has shown that quantum feature map design can be automated for a given dataset using NSGA-II, a genetic algorithm, while both minimizing circuit size and maximizing classification accuracy. However, the evaluation of the accuracy achieved by a candidate feature map is costly. In this work, we demonstrate the suitability of kernel-target alignment as a substitute for accuracy in genetic algorithm-based quantum feature map design. Kernel-target alignment is faster to evaluate than accuracy and does not require some data points to be reserved for its evaluation. To further accelerate the evaluation of genetic fitness, we provide a method to approximate kernel-target alignment. To improve kernel-target alignment and root mean squared error, the final trainable parameters of the generated circuits are further trained using COBYLA to determine whether a hybrid approach applying conventional circuit parameter training can easily complement the genetic structure optimization approach. A total of eight new approaches are compared to the original across nine varied binary classification problems from the UCI machine learning repository, showing that kernel-target alignment and its approximation produce feature map circuits enabling comparable accuracy to the previous work but with larger margins on training data (in excess of 20% larger) that improve further with circuit parameter training.
Durability and Functionality of Conventional Polymeric Packaging Materials in Reusable Packaging Systems
Authors: Tenhunen-Lunkka Anna , Parikka Risto , Korostavyi Artur , Palola Sarianna , Ronkainen Helena
Published: July 2024

Reusable packaging is increasingly recognised as a sustainable solution to address issues related to increasing packaging waste generation and harmful environmental impacts. The packaging sector consumes a significant portion of Europe’s plastic production, which is mostly single-use packaging. There is a sense of urgency to develop sustainable reusable alternatives. Unlike single-use packaging, the longevity of reusable plastic packaging is paramount, necessitating material durability and functionality. This study examines the durability of conventional polymeric packaging materials (polyethylene terephthalate (PET), polypropylene, high-density polyethylene) and investigates the effectiveness of scratch resistance additives. A specialised test set-up was created to evaluate the performance of various polymers in reusable takeaway food packaging scenarios. The research included scratch testing, wear analysis and wash cycles to assess the reuse potential of these materials. Qualitative measures were employed to compare material characteristics. Results indicated that polymer type significantly affects hardness and scratch performance, while additives had minimal impact on hardness and modulus. Although current scratch resistance additives do not effectively mitigate wear in reusable packaging in the experimental scenarios, tailored additives could present potential in increasing the durability and longevity of reusable packaging. PET demonstrated notable recovery post-washing, suggesting that washing conditions could influence material resilience. This study emphasises the need for further research to optimise scratch resistance additives and understand the impact of washing conditions on different polymers, aiming to enhance the design and longevity of reusable packaging systems.
Epithelial to Mesenchymal Transition in Neuroblastoma: Mechanisms and Therapeutic Considerations
Authors: Jahangiri Leila
Published: July 2024

Purpose of Review

Neuroblastoma (NB) is a solid tumour of the extracranial region in children, and it originates from the developing sympathetic nervous system. Metastasis is present in circa 70% of NB cases at the time of diagnosis and may be accompanied by poor prognosis and resistance to treatment. As such, metastasis is an important step in NB progression and is the main cause of fatality in this cancer. Furthermore, metastasis is linked to epithelial to mesenchymal transition (EMT).

Recent Findings

EMT is characterised by the loss of the stationary compact epithelial cell arrangement and increased motility and invasion of these cells and may also be associated with patient outcomes, including treatment resistance, recurrence, and poor survival.

This study aims to gain mechanistic insight into EMT and review signalling pathways, proteins, non-coding RNA, and microenvironmental factors that may contribute to this process in NB. Further, drug compounds that affect EMT in NB, and proteins and non-coding RNA that impact EMT and treatment resistance will be reviewed. A better comprehension of EMT in NB will deepen our understanding of this cancer and provide new avenues for clinical interventions and therapeutic gain.
Evaluation of weather generator tools to estimate climate conditions in different agro ecological zones of North Shewa, Ethiopia
Authors: Ayele Biruk Getaneh , Mengistu Tsegaye Getachew , Woldemariam Ayele Desalegn
Published: July 2024

The information on climatic condition is difficult to obtain, expensive, and time-consuming so as to make timely decision on agricultural activities. As a scientific effort, this study was conducted to assess the temporal changes and trends of rainfall and temperature, to know the performance of weather generator (WG) tools in capturing the temporal and spatial distribution of rainfall, maximum temperature (Tmax) and minimum temperature (Tmin) and to evaluate the performance of WG in simulating the observed rainfall, Tmax and Tmin by using statistical methods. Mann–Kendall's trend analysis revealed that rainfall had non-significant (P < 0.05) decreasing trends, while Tmax and Tmin had an increasing significant (P < 0.05) trends at all stations. NASA POWER data followed by NewlocClim exactly capture the temporal changes of rainfall, Tmax, and Tmin in all stations except Debre Birhan and Mehal Meda. NewlocClim well captures rainfall at Alem ketema, while NASA well simulates rainfall at Debre Birhan and Majete stations. However Had-GEM2-ES, MRI-CGCM3, and CSIRO-Mk3.6.0 were not handling the spatial variability of observed rainfall at all stations. Similarly, some WGs showed moderate to good performance in capturing the spatial distributions of Tmax and Tmin. The smallest RMSE and CV, the highest R and d values were observed in NASA POWER and NewlocClim for rainfall, Tmax and Tmin. Therefore, NASA and NewlocClim are more accurate with goodness of fit to estimate rainfall, Tmax and Tmin in most of the stations to access weather data for ungagged stations for timely and reasonable decision-making on agriculture.
Ethics and the use of generative AI in professional editing
Authors: Otmar Renée , Michael Rose , Mullins Sharon , Day Katherine
Published: July 2024

Generative artificial intelligence (GnAI) has garnered significant attention worldwide across diverse industries, including in book publishing. To date, more attention has been paid to its potential in creative collaboration and less to the editorial possibilities of its application. Interest has accelerated since the breakthrough of a new Large Language Model in late 2022. This paper engages with the ethical and industrial implications of using GnAI in a creative context, namely literary publishing. It raises crucial questions about intellectual property, trust, the author–editor relationship and publishing professionals’ evolving roles in shaping quality literature. Using a published story as a test case, we compare edits using GnAI with those by professional editors over multiple drafts and at different stages of editorial development. We consider the potential ethical implications of the use of GnAI in literary fiction editing, highlighting the principles and practices that underpin professional editing to consider how these may or may not translate in the use of GnAI. This is followed by a discussion of the risks and opportunities in using GnAI in editing literary texts in the trade publishing context.
Understanding the explosion risk presented by ammonium nitrate and aluminium home-made explosives detonated as surface charges in hexahedral main charge containers
Authors: Collett Gareth , Akhavan Jacqueline , Critchley Richard
Published: July 2024

Ammonium nitrate and aluminium (AN–Al) has been used as a typical homemade explosive (HME) by non-state actors since the turn of the century. Despite the regulation applied to ammonium nitrate above 16% nitrogen content and an aluminium particle size below 200 µm, their use has been widespread in Afghanistan, Columbia, Iraq, Syria and Yemen. Containers used to utilise AN–Al as a man-portable improvised explosive device (IED) are typically hexahedral in shape, not the spherical or hemispherical geometries used to theorise risk mitigation. This is particularly important in post-blast investigation where explosives of a non-ideal nature are often used in non-spherical containers.

Given the breadth of HME available to criminals, the explosion performance of forty hexahedral containers filled with AN–Al of unknown manufacture is examined. Performance of the AN–Al is determined through the surface detonation of these containers on alluvial soil, with apparent crater volume compared to theoretical calculations for spherical charges of TNT detonated in that same medium. A conversion factor for hexahedral main charges to spherical charges is then established to achieve more accurate predictions of the explosion risk using Kingery-Bulmash and Bowen curves. The paper provides worked examples for practical application and a methodology by which predictions of charge mass in other mediums such as asphalt can be determined.
A Class of Polynomial Recurrences Resulting in $$({\text {n}}/{\text {log}}\,\,{\text {n}}, {\text {n}}/{\text {log}}^2{\text {n}})$$–Asymptotic Normality
Authors: Hitczenko Paweł
Published: July 2024

We consider sequences of polynomials that satisfy differential–difference recurrences. Polynomials satisfying such recurrences frequently appear as generating polynomials of integer valued random variables that are of interest in discrete mathematics. It is, therefore, of interest to understand the properties of such polynomials and their probabilistic consequences. We identify a class of polynomial recurrences that lead to a normal law with the expected value and the variance proportional to $$n/\log ~n$$

n
/
log

n

and $$n/\log ^2n$$

n
/

log
2

n

, respectively. Examples include Stirling numbers of the second kind and other polynomials concerning set partitions as well as polynomials related to Whitney numbers of Dowling lattices.
Differences in the clinical management of shoulder pain by physician specialty: data from the 2007–2019 National Ambulatory Medical Care Survey
Authors: Liu Yujian , Lu Jian , Liu Guangwu
Published: July 2024

Objectives

The aim of this study was to identify the differences in the clinical management of shoulder pain by primary care physicians (PCPs) and non-primary care physicians (non-PCPs) from the National Ambulatory Medical Care Survey (NAMCS) dataset.

Methods

This cross-sectional study included ambulatory care visits for shoulder pain by using NAMCS data from 2007 to 2019. Descriptive statistics were presented to assess patient-level and visit-level characteristics of the sampled visits. By controlling for patient-level and visit-level covariates, we conducted a multivariable logistic regression to evaluate the influence of primary care physician status on the utilization of health services (pain medications, PT referral, health education/counseling, and diagnostic imaging) for shoulder pain.

Results

There were 74.43 million ambulatory care visits by adults with shoulder pain during the study period, and nearly one-third of these shoulder visits were made to PCPs. As compared with non-PCPs, PCPs had higher adjusted odds of prescribing narcotic analgesics (adjusted odds ratio [OR] = 1.62, 95% confidence interval [CI]: 1.04–2.51), skeletal muscle relaxants (adjusted OR = 2.71, 95% CI: 1.65–4.45), other pain medications (adjusted OR = 1.87, 95% CI: 1.13–3.07), and lower odds of prescribing PT (adjusted OR = 0.34, 95% CI: 0.21–0.55) and MRI (adjusted OR = 0.46, 95% CI: 0.25–0.84).

Conclusion

We observed significant differences in the services ordered or provided by PCPs versus non-PCPs for shoulder pain in ambulatory care settings. These results may reveal the higher reliance of pharmacological approaches, coupled with the potential under-utilization of PT during the ambulatory shoulder care provided by PCPs compared to non-PCPs in the United States.
Using economic analysis to inform health resource allocation: lessons from Malawi
Authors: Rao Megha , Nkhoma Dominic , Mohan Sakshi , Twea Pakwanja , Chilima Benson , Mfutso-Bengo Joseph , Ochalek Jessica , Hallett Timothy B. , Phillips Andrew N. , McGuire Finn , Woods Beth , Walker Simon , Sculpher Mark , Revill Paul
Published: July 2024

Despite making remarkable strides in improving health outcomes, Malawi faces concerns about sustaining the progress achieved due to limited fiscal space and donor dependency. The imperative for efficient health spending becomes evident, necessitating strategic allocation of resources to areas with the greatest impact on mortality and morbidity. Health benefits packages hold promise in supporting efficient resource allocation. However, despite defining these packages over the last two decades, their development and implementation have posed significant challenges for Malawi. In response, the Malawian government, in collaboration with the Thanzi la Onse Programme, has developed a set of tools and frameworks, primarily based on cost-effectiveness analysis, to guide the design of health benefits packages likely to achieve national health objectives. This review provides an overview of these tools and frameworks, accompanied by other related analyses, aiming to better align health financing with health benefits package prioritization. The paper is organized around five key policy questions facing decision-makers: (i) What interventions should the health system deliver? (ii) How should resources be allocated geographically? (iii) How should investments in health system inputs be prioritized? (iv) How should equity considerations be incorporated into resource allocation decisions? and (v) How should evidence generation be prioritized to support resource allocation decisions (guiding research)? The tools and frameworks presented here are intended to be compatible for use in diverse and often complex healthcare systems across Africa, supporting the health resource allocation process as countries pursue Universal Health Coverage.
Investigation of lawsuit process duration using machine learning and process mining
Authors: Vercosa Luiz , Silva Vinicius , Cruz Jaqueline , Bastos-Filho Carmelo , Bezerra Byron L. D.
Published: July 2024

Delays in legal proceedings significantly impact both corporate finances and individual livelihoods. Traditional methods for managing these delays typically rely on subjective assessments of what constitutes a reasonable process duration. This study explores a more precise approach by integrating machine learning and process mining techniques to enhance prediction of legal proceedings’ overall time. Diverging from previous works that either utilized machine learning analysis or process mining in isolation, this research synergizes these approaches. We applied process mining clustering techniques to over 60,000 cases from Brazilian labor courts to segment cases based on their procedural movements, creating clusters. These clusters, along with other procedural characteristics, such as case subject, class, and digital status, were then incorporated into a feature set for regression modelling. We employed linear regression, support vector regressor, and gradient boosting based methods to develop models that predicted case duration. The gradient boosting model demonstrated the best performance with an $$R^2$$

R
2

-score of 0.87. Furthermore, our analysis identifies time bands where the model performs better and employs explainable AI techniques to elucidate key features influencing case durations. The clustering features emerged among the most significant for the task. The proposed combined approach offers a comprehensive method for analyzing and forecasting legal case timelines and also shows the potential of process mining clustering techniques to improve the analysis.
Use of multivariate techniques to regionalize rainfall patterns in semiarid Botswana
Authors: Nkoni Godiraone , Mphale Kgakgamatso , Mbangiwa Nicholas , Samuel Sydney , Molosiwa Rejoice
Published: July 2024

Monthly precipitation data from 58 synoptic stations throughout Botswana, spanning 1981–2016, were used in this study. The data were examined using multivariate analysis to determine regions exhibiting distinct precipitation variability patterns and regimes. To accomplish this, the T-mode of principal component analysis was applied to the correlation matrix of the data. Based on the maximum loading values of the rotational principal component scores, the T-mode indicated three separate subregions with varying precipitation patterns over time. Four clusters with distinct rainfall patterns were identified when cluster analysis was performed on the principal component scores. An assessment of the homogeneity of the clusters was performed using L-moment’s heterogeneity measure (H). Statistical analysis was employed to model annual rainfall data using five commonly used rainfall analysis probability distribution functions: normal, lognormal, gamma, Weibull, and Gumbel. The probability distributions with the greatest fit were determined based on the maximum overall score, which was calculated by adding the individual point scores of three chosen goodness-of-fit tests. Each cluster exhibited distinct probability distribution functions, with the gamma, Gumbel, lognormal, and Weibull distributions providing the most accurate descriptions.
First record of two species of brachyuran crab (Crustacea: Decapoda) Austruca albimana (Kossmann, 1877) and Tirmilyra concinnus (Ghani and Tirmizi, 1995) from India
Authors: Dudiya Deep D. , Pandya Pranav J. , Goswami Mansi S. , Naderloo Reza
Published: July 2024

This study reports the first record of two brachyuran crab species, Austruca albimana Kossmann, [21] and Tirmilyra concinnus Ghani and Tirmizi [18], from the western Indian coast. Their identification, taxonomic observations, and geographic distribution are provided. The species belong to the families Ocypodidae and Leucosiidae, respectively. This is the first report from Indian waters, as the species are so far reported from Oman, Iran and Persian Gulf. These records emphasize the need for research and conservation efforts in the region to explore the diversity and distribution of brachyuran crabs in Indian waters.
Targeting oncogene-induced cellular plasticity for tumor therapy
Authors: Li Bin , Zheng Lingling , Yang Jianhua , Qu Lianghu
Published: July 2024

Cellular plasticity, the remarkable adaptability of cancer cells to survive under various stress conditions, is a fundamental hallmark that significantly contributes to treatment resistance, tumor metastasis, and disease recurrence. Oncogenes, the driver genes that promote uncontrolled cell proliferation, have long been recognized as key drivers of cellular transformation and tumorigenesis. Paradoxically, accumulating evidence demonstrates that targeting certain oncogenes to inhibit tumor cell proliferation can unexpectedly induce processes like epithelial-to-mesenchymal transition (EMT), conferring enhanced invasive and metastatic capabilities. In this review, we summarize the latest models elucidating the biology of oncogenes that concurrently promote cell proliferation while inhibiting metastasis. We suggest that the complexity of oncogene-induced cellular plasticity, involving the participation of multiple signaling pathways and mechanisms, necessitates a multifaceted approach, prompting a shift towards precision targeting strategies that can effectively target oncogenes without exacerbating metastatic potential.
The role of religion in the evolution of peace
Authors: Kiper Jordan , Sosis Richard
Published: July 2024

Glowacki's account overlooks the role of religion in the regulation of cooperation, tolerance, and peace values. We interrogate three premises of Glowacki's argument and suggest that approaching religion as an adaptive system reveals how religious commitments and practices likely had a more substantial impact on the evolution of peace and conflict than currently presumed.
Rethinking peace from a bonobo perspective
Authors: Samuni Liran , Wessling Erin G. , Surbeck Martin
Published: July 2024

Reconstructing pathways to human peace can be hampered by superficial evaluations of similar processes in nonhuman species. A deeper understanding of bonobo social systems allows us to reevaluate the preconditions for peace to gain a greater insight on the evolutionary timescale of peace emergence.
Peace as prerequisite rather than consequence of cooperation
Authors: Romano Angelo , Gross Jörg , De Dreu Carsten K. W.
Published: July 2024

We take issue with Glowacki's assumption that intergroup relations are characterized by positive-sum interactions and suggest to include negative-sum interactions, and between-group independence. As such, peace may be better defined as the absence of negative-sum interactions. Rather than being a consequence of cooperation, peace emerges as a necessary but not sufficient prerequisite for positive (in)direct reciprocity between groups that, in turn, is key to social identities and cultural complexity.
Whole genome sequencing refines stratification and therapy of patients with clear cell renal cell carcinoma
Authors: Culliford Richard , Lawrence Samuel E. D. , Mills Charlie , Tippu Zayd , Chubb Daniel , Cornish Alex J. , Browning Lisa , Kinnersley Ben , Bentham Robert , Sud Amit , Pallikonda Husayn ,   The Renal Cancer Genomics England Consortium, Afshar Mehran , Akala Oyeyemi , Brown Janet , Faust Guy , Fife Kate , Foy Victoria , Germanou Styliani , Giles Megan , Grieco Charlotte , Grummet Simon , Jain Ankit , Kanwar Anuradha , Protheroe Andrew , Raza Iwan , Rehan Ahmed , Rudman Sarah , Santiapillai Joseph , Sarwar Naveed , Seeva Pavetha , Strong Amy , Toki Maria , Tran Maxine , Tutika Rippie , Waddell Tom , Wheater Matthew , Frangou Anna , Gruber Andreas J. , Litchfield Kevin , Wedge David , Larkin James , Turajlic Samra , Houlston Richard S.
Published: July 2024

Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer, but a comprehensive description of its genomic landscape is lacking. We report the whole genome sequencing of 778 ccRCC patients enrolled in the 100,000 Genomes Project, providing for a detailed description of the somatic mutational landscape of ccRCC. We identify candidate driver genes, which as well as emphasising the major role of epigenetic regulation in ccRCC highlight additional biological pathways extending opportunities for therapeutic interventions. Genomic characterisation identified patients with divergent clinical outcome; higher number of structural copy number alterations associated with poorer prognosis, whereas VHL mutations were independently associated with a better prognosis. The observations that higher T-cell infiltration is associated with better overall survival and that genetically predicted immune evasion is not common supports the rationale for immunotherapy. These findings should inform personalised surveillance and treatment strategies for ccRCC patients.
The occurrence and human health risk assessment of total and aflatoxin B1 in selected food commodities in Bhutan
Authors: Monger Adeep , Mongar Pooja , Dorji Tshering , Chhetri Vishal
Published: July 2024

Aflatoxins are mycotoxins that contaminate staple foods globally and pose a significant health risk. To the best of our knowledge, information on the occurrence of aflatoxins in Bhutanese diets is scarce. This study aimed to estimate the aflatoxin levels in selected foodstuffs in Bhutan and determine the health risk associated with aflatoxin exposure. Ten different types of food commodities were randomly collected from farmers’ markets, shelves of supermarkets, and wholesale and retail shops from 20 districts of the country. The samples were subjected to analysis by an enzyme-linked immunosorbent assay for both total aflatoxins (B1, B2, G1 and G2) and aflatoxin B1. Among the 315 samples included, 48.81% and 79.35% were positive for total aflatoxins and aflatoxin B1, respectively. The overall mean total aflatoxin concentration was 11.49 ± 12.83 µg/kg, and that for B1 was 17.62 ± 23.99 µg/kg. The most prevalent food commodity with the highest aflatoxin contamination was chili products. In addition, the estimated daily intake and margin of exposure to aflatoxin B1 via the consumption of chili products ranged from 0.98 to 5.34 ng kg−1 bw day−1 and from 74.90 to 408.10, indicating a risk for public health. The liver cancer risk was estimated to be 0.01 and 0.007 cancers per year per 100,000 population resulting from the consumption of chili products. The present findings revealed the presence of total aflatoxins and aflatoxin B1 in the selected samples. The margin of exposure values was exorbitant, demanding a stringent public health measure. Notably, these results suggest the need for routine monitoring of aflatoxin contamination in the region and stress rigorous safety management strategies to reduce exposure.
Carbapenem-resistant Enterobacteriaceae in the livestock, humans and environmental samples around the globe: a systematic review and meta-analysis
Authors: Tuhamize Barbra , Bazira Joel
Published: July 2024

Carbapenem-resistant Enterobacteriaceae (CRE) have diminished treatment options causing serious morbidities and mortalities. This systematic review and meta-analysis assessed the prevalence and associated factors of Enterobacteriaceae infections in clinical, livestock and environmental settings globally. The population intervention comparison and outcome strategy was used to enroll studies using the preferred reporting system for systematic review and meta-analysis to include only cross-sectional studies. Search engines used to retrieve articles included journal author name estimator, PubMed, Google Scholar and African Journals Online (AJOL). The Newcastle–Ottawa scale was used to assess the quality of studies. Sixteen articles from 2013 to 2023 in Africa, Asia, Europe and South America were studied. The pooled prevalence of CRE was 43.06% (95% CI 21.57–66.03). Klebsiella pneumoniae (49.40%), Escherichia coli (26.42%), and Enterobacter cloacae (14.24%) were predominant. Klebsiella pneumoniae had the highest resistance with the blaKPC-2 in addition to blaNDM, blaOXA-48, blaIMP and blaVIM. The blaKPC-2 genes occurrence was associated with environmental (P-value < 0.0001) and South American studies (P-value < 0.0001), but there was no difference in the trends over time (P-value = 0.745). This study highlights the high rates of CRE infections, particularly within blaKPC production. Monitoring and surveillance programs, research and infection control measures should be strengthened. Additionally, further studies are needed to explore the mechanisms driving the predominance of specific bacterial species and the distribution of resistance genes within this bacterial family.
Epidemiological characteristics of common respiratory pathogens in children
Authors: Lv Guojian , Shi Limei , Liu Yi , Sun Xuecheng , Mu Kai
Published: July 2024

Children's respiratory tract infection is a common disease affecting children's health, our purpose is to describe the epidemiological characteristics of common pathogens of children's respiratory tract infection in central Shandong, China, and compare them with those in other parts of world, so as to summarize the rules of children's respiratory tract infection in central Shandong, and provide scientific basis for health departments to prevent and treat local children's respiratory tract infection. Sputum, tracheal aspirate, alveolar lavage fluid and other samples of 4804 children admitted to wards of Zibo Maternal and Child Health Hospital for treatment of respiratory tract infection from June 2019 to December 2022 were collected, and 12 common respiratory tract pathogens were detected by PCR capillary electrophoresis fragment analysis, two bacteria (Streptococcus pneumoniae, Haemophilus influenzae), two atypical pathogens (Mycoplasma Pneumoniae, Chlamydia Pneumoniae) and eight viruses (Human rhinovirus, Respiratory Syncytial Virus, Influenza A Virus, Parainfluenza Virus, Human metapneumovirus, Human boca virus, Human coronavirus, Influenza B virus) were included, the positive detection rate of single pathogen, the proportion of each type of respiratory tract mixed infection and the positive detection rate of single pathogen in different ages and seasons were analyzed statistically. (1)Among 4804 children with respiratory tract infection, the total positive rate was 77.87% (3741/4804), the positive rate of single pathogen was 43.40% (1656/4804), Streptococcus pneumoniae, Rhinovirus and Respiratory syncytial virus were the highest, there were 2085 cases of mixed infection with two or more pathogens, the positive rate was 43.40%. (2) The positive rates of infection in infant group (0–1 years old), infant group (1–3 years old), preschool group and school age group (3 years old-) were roughly the same, the infection rates of Streptococcus pneumoniae, Respiratory syncytial virus and Parainfluenza virus in infant group, Rhinovirus in infant group, Influenza A virus, Chlamydia pneumoniae, Mycoplasma pneumoniae and Haemophilus influenzae in school age group were higher than those in other groups, the difference was statistically significant (P < 0.05). (3) The positive detection rates of spring, summer, autumn and winter groups were 43.58%, 38.64%, 33.73% and 29.27%, respectively, the positive rates of Streptococcus pneumoniae and Haemophilus influenzae in spring group, Mycoplasma pneumoniae in summer group, Rhinovirus, Respiratory syncytial virus and Influenza A virus in autumn group, Chlamydia pneumoniae, Boca virus and Influenza B virus in winter group were higher than those in other seasons, and the differences were statistically significant (P < 0.05). The pathogen detection rate of children varies with age and season, and the prevention and treatment of a certain respiratory pathogen infection must be combined with its raging season and age rule.
Climate change triggered planktonic cyanobacterial blooms in a regulated temperate river
Authors: Kleinteich Julia , Frassl Marieke A. , Schulz Manoj , Fischer Helmut
Published: July 2024

Harmful algae blooms are a rare phenomenon in rivers but seem to increase with climate change and river regulation. To understand the controlling factors of cyanobacteria blooms that occurred between 2017 and 2020 over long stretches (> 250 km) of the regulated Moselle River in Western Europe, we measured physico-chemical and biological variables and compared those with a long-term dataset (1997–2016). Cyanobacteria (Microcystis) dominated the phytoplankton community in the late summers of 2017–2020 (cyano-period) with up to 110 µg Chlorophyll-a/L, but had not been observed in the river in the previous 20 years. From June to September, the average discharge in the Moselle was reduced to 69–76% and water temperature was 0.9–1.8 °C higher compared to the reference period. Nitrogen (N), phosphorus (P) and silica (Si) declined since 1997, albeit total nutrient concentrations remained above limiting conditions in the study period. Cyanobacterial blooms correlated best with low discharge, high water temperature and low nitrate. We conclude that the recent cyanobacteria blooms have been caused by dry and warm weather resulting in low flow conditions and warm water temperature in the regulated Moselle. Under current climate projections, the Moselle may serve as an example for the future of regulated temperate rivers.
Optimization of passive micromixers: effects of pillar configuration and gaps on mixing efficiency
Authors: Kheirkhah Barzoki Ali
Published: July 2024

Chemical bioreactions play a significant role in many of the microfluidic devices, and their applications in biomedical science have seen substantial growth. Given that effective mixing is vital for initiating biochemical reactions in many applications, micromixers have become increasingly prevalent for high-throughput assays. In this research, a numerical study using the finite element method was conducted to examine the fluid flow and mass transfer characteristics in novel micromixers featuring an array of pillars. The study utilized two-dimensional geometries. The impact of pillar configuration on mixing performance was evaluated using concentration distribution and mixing index as key metrics. The study explores the effects of pillar array design on mixing performance and pressure drop, drawing from principles such as contraction–expansion and split-recombine. Two configurations of pillar arrays, slanted and arrowhead, are introduced, each undergoing investigation regarding parameters such as pillar diameter, gap size between pillar groups, distance between pillars, and vertical shift in pillar groups. Subsequently, optimal micromixers are identified, exhibiting mixing efficiency exceeding 99.7% at moderate Reynolds number (Re = 1), a level typically challenging for micromixers to attain high mixing efficiency. Notably, the pressure drop remains low at 1102 Pa. Furthermore, the variations in mixing index over time and across different positions along the channel are examined. Both configurations demonstrate short mixing lengths and times. At a distance of 4300 μm from the inlet, the slanted and arrowhead configurations yielded mixing indices of 97.2% and 98.9%, respectively. The micromixers could provide a mixing index of 99.5% at the channel’s end within 8 s. Additionally, both configurations exceeded 90% mixing indices by the 3 s. The combination of rapid mixing, low pressure drop, and short mixing length positions the novel micromixers as highly promising for microfluidic applications.