bluuebunny/crossref_metadata_2025 huggingface dataset:
‘People Like Us Would Have No Clue If the Information Is Online’: Exploring Understanding and Sources of Hepatitis B Information Among Vietnamese Australians
Authors: Brener Loren , Vu Hoang Minh Khoi , Horwitz Robyn , Cama Elena , Martin Kacey , Rance Jake , Okeke Sylvester , Bryant Joanne
Published: June 2024

Socio-cultural and behavioural factors are often not adequately considered in designing health promotion programs for culturally and linguistically diverse communities in Australia. Given that people of Vietnamese background are disproportionately impacted by hepatitis B, the aim of this research was to better understand these factors to inform hepatitis B health promotion messages for the Vietnamese community. Twenty participants (four living with hepatitis B) were interviewed by a Vietnamese-speaking researcher. The interview sessions explored beliefs about health, the body and liver; knowledge and attitudes about hepatitis B vaccines, testing, clinical management and stigma; and sources of health information and value given to information on social media. Participants had a range of understandings of health and hepatitis B which informed their responses to health education and intervention. Participants appeared to have limited knowledge and misconceptions about transmission, prevention, treatment, and management of hepatitis B. Stigma surrounding hepatitis B was apparent, with over half the participants reporting that they distanced themselves from people living with hepatitis B. Participants preferred online information resources for younger people and traditional media in the Vietnamese language for older people. By understanding what Vietnamese people know about hepatitis B and how they access health information, these findings can be used to inform health promotion campaigns using print, media, and radio to ensure wide reach. Knowledge of community specific information is key to reducing the burden of hepatitis B among culturally and linguistically diverse communities and ensuring they are able to access healthcare services for testing, monitoring, and care.
Disparities in Cancer Mortality among Disaggregated Asian American Subpopulations, 2018–2021
Authors: Zhu David T. , Lai Alan , Park Andrew , Zhong Anthony , Tamang Suzanne
Published: June 2024

Federal, state, and institutional data collection practices and analyses involving Asian Americans as a single, aggregated group obscure critical health disparities among the vast diversity of Asian American subpopulations. Using from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) Underlying Causes of Death database, we conducted a cross-sectional study using data on disaggregated Asian American subgroups (Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, other Asians) between 2018 and 2021. We examine deaths from 22 cancer types and in situ, benign neoplasms, identified using ICD-10 codes C00-C97 and D00-D48. Overall, our study comprised 327,311 Asian American decedents, with a mean age of death at 70.57 years (SD=2.79), wherein females accounted for approximately half of the sample (n=36,596/73,207; 49.99%). Notably, compared to the aggregated Asian American reference group, we found higher proportions of deaths from total cancers among Chinese (25.99% vs. 22.37% [ref]), Korean (25.29% vs. 22.37% [ref]), and Vietnamese (24.98% vs. 22.37% [ref]) subgroups. In contrast, total cancer deaths were less prevalent among Asian Indians (17.49% vs. 22.37% [ref]), Japanese (18.90% vs. 22.37% [ref]), and other Asians (20.37% vs. 22.37% [ref]). We identified further disparities by cancer type, sex, and age. Disaggregated data collection and analyses are imperative to understanding differences in cancer mortality among Asian American subgroups, illustrating at-risk populations with greater granularity. Future studies should aim to describe the association between these trends and social, demographic, and environmental risk factors.
Trends in mortality related to kidney failure and diabetes mellitus in the United States: a 1999–2020 analysis
Authors: Rashid Ahmed Mustafa , Jamil Adeena , Khan Zoha , Shakoor Muteia , Kamal Usama Hussain , Khan Iqra Israr , Akram Abdullah , Shahabi Mariam , Yamani Naser , Ali Soha , Fatima Kanza , Kamdi Aamna , Junaid Muhammad , Khan Ayesha Mazhar , Mattumpuram Jishanth , Perswani Prinka
Published: June 2024

Background

Kidney failure ranks as the tenth leading cause of mortality in the United States (US), frequently arising as a complication associated with diabetes mellitus (DM).

Methods

Trends in DM and kidney failure mortality were assessed using a cross-sectional analysis of death certificates from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) database. Crude and age-adjusted mortality rates (AAMR) per 100,000 people and annual percent change (APC) in age-adjusted mortality rate with 95% CI were obtained and measured across different demographic and geographic subgroups.

Results

Between 1999 and 2020, a total of 325,515 deaths occurred related to kidney failure and DM. The overall age-adjusted mortality rate showed no significant change between 1999 and 2012, after which it declined until 2015 − 64.8 (95% CI − 75.6 to − 44.8) and has been steadily increasing since. Men had consistently higher age-adjusted mortality rates than women throughout the study duration (overall age-adjusted mortality rate men: 8.1 vs. women: 5.9). Non-Hispanic (NH) Black or African American individuals had the highest overall age-adjusted mortality rate (13.9), followed by non-Hispanic American Indian or Alaskan Native (13.7), Hispanic or Latino (10.3), non-Hispanic Asian or Pacific Islander (6.1), and non-Hispanic White (6.0). Age-adjusted mortality rate also varied by region (overall age-adjusted mortality rate: West:7.5; Midwest: 7.1; South: 6.8; Northeast: 5.8), and non metropolitan areas had higher overall age-adjusted mortality rate (7.5) than small/medium (7.2) and large metropolitan areas (6.4).

Conclusion

After an initial decline, mortality rose across all the demographic groups from 2015 to 2020, revealing notable disparities in gender, race, and region.

Graphical Abstract
Sustainability Assessment in Mining: A CSR-Based Analysis Model for Social and Environmental Impact
Authors: Bascompta Marc , Yousefian M. , Vintró Carla , Sanmiquel Lluís , Rodríguez Rafael , Yubero María Teresa
Published: June 2024

A simple approach is proposed to study the main factors related to the mining activity’s impact on society, through a corporate social responsibility (CSR) qualitative analysis based on the type of raw materials extracted, either by mine site or firm. A CSR index is defined by 30 environmental and socioeconomic elements and, subsequently, it is weighted by three primary factors; the recycling rate, the transition to green energy, and geographical conditions. The proposed method is adaptable to any change in raw material needs over time and, depending on the analyzed country or region, is applicable to any type of mineral resource. The system can be used to drive engagement with the different stakeholders, add value to a project, and establish a CSR continuous improvement system.
Numerical simulation of adsorption process of O2/H2O mixed gas in coal porous media
Authors: Guo Huiyan , Zhou Hongxiang , Guo Chang , Nie Rongshan , Liang Xiaoyu
Published: June 2024

It is of great significance for coal mining and utilization to study the adsorption process of mixed gas in coal. In this paper, the Monte Carlo method (MC) is employed to study the competitive saturation adsorption of oxygen and water vapor inside coal particles, and then the convection, diffusion and adsorption inside and between particles are studied by lattice Boltzmann method (LBM). In addition, this study examines the impacts of porosity, average particle size, and gas concentration on the process of adsorption in coal porous media. The research results show that oxygen and water vapor present in the mixed gas experience increased permeability, diffusion rate, and saturated adsorption capacity as the porosity and average particle size of the coal porous medium increase. However, the time required to achieve saturated adsorption decreases. Under the condition of maintaining the proportion of gas components and altering the initial gas concentrations from 4.087 to 53.131 mol/m3, saturated adsorption capacity of both gases remains nearly unchanged. Yet, the effective diffusivity of gases declines with increasing initial concentration. Additionally, it is also found that water vapor diffuses more quickly than oxygen in the mixed gas and achieves adsorption saturation faster.
Enhancing the Photosensitivity of Hypocrellin A by Perylene Diimide Metallacage-Based Host–Guest Complexation for Photodynamic Therapy
Authors: Li Rongrong , Yang Tianfeng , Peng Xiuhong , Feng Qian , Hou Yali , Zhu Jiao , Chu Dake , Duan Xianglong , Zhang Yanming , Zhang Mingming
Published: June 2024

The development of supramolecular hosts which can efficiently encapsulate photosensitizers to improve the photodynamic efficacy holds great promise for cancer therapy. Here, we report two perylene diimide-based metallacages that can form stable host–guest complexes with planar conjugated molecules including polycyclic aromatic hydrocarbons and photosensitizers (hypocrellin A). Such host–guest complexation not only prevents the aggregation of photosensitizers in aqueous environments, but also offers fluorescence resonance energy transfer (FRET) from the metallacage to the photosensitizers to further improve the singlet oxygen generation (ΦΔ = 0.66). The complexes are further assembled with amphiphilic polymers, forming nanoparticles with improved stability for anticancer study. Both in vitro and in vivo studies indicate that the nanoparticles display excellent anticancer activities upon light irradiation, showing great potential for cancer photodynamic therapy. This study provides a straightforward and effective approach for enhancing the photosensitivity of conventional photosensitizers via host–guest complexation-based FRET, which will open a new avenue for host–guest chemistry-based supramolecular theranostics.
A Review of Biocarbon Substitutes in Electrodes and Refractories for the Metallurgical Industries
Authors: White Jesse Franklin , Renau Luis Miguel López , Glaser Björn
Published: June 2024

The chemical and thermophysical properties of carbon make it essentially irreplaceable for non-reductant uses in many high-temperature metallurgical processes. At present, biocarbon substitutes are not technically feasible for large-scale application in electrode and refractory materials that are such vital consumables in the steel, aluminum, and non-ferrous metal industries. Carbon electrodes of all types, including Söderberg, prebaked, and anodes/cathodes for Al, graphite electrodes, as well as carbon lining pastes are all similar in that they are comprised of a granular carbon aggregate bonded in a carbon-based binder matrix. Similarly, refractories such as MgO–C utilize both natural (mined) graphite and carbon-based binders. Replacement of fossil carbon materials with biocarbon substitutes has the potential to dramatically reduce the carbon footprints of these products. However, there are considerable materials engineering challenges that must be surmounted. The technological demands for these applications and potential for substitution with biogenic carbon are explored.

Graphical Abstract
Implementation of extended kalman filter for localization of ambulance robot
Authors: Yang Chan-Yun , Samani Hooman , Tang Zirong , Li Chunxu
Published: June 2024

This paper focuses on the implementation of the Extended Kalman Filter for indoor localization of a semi-autonomous Ambulance Robot system named Ambubot. The system is designed to reduce the response time for lay rescuers to locate an Automated External Defibrillator (AED) during sudden cardiac arrest events. To achieve this objective, the robot is equipped with an AED, and the Extended Kalman Filter is utilized for optimal indoor localization. The filter is implemented using data from the robot’s Inertial Measurement Unit, which comprises 9 Degrees of Freedom. The paper provides an explicit description of the performance of the Extended Kalman Filter in estimating the position of Ambubot, and demonstrates that the proposed approach is effective in accurately determining and estimating the robot’s position in unknown indoor environments. The results suggest that the proposed method is a promising solution for improving survival rates in cardiac arrest cases, and may have potential applications in other fields where accurate indoor localization is required.
On the cost of risk misspecification in insurance pricing
Authors: Finger D. , Albrecher H. , Wilhelmy L.
Published: June 2024

In the non-life insurance industry, pricing is often done relative to individual criteria of policyholders. Various classification algorithms are in use to categorize policyholders into risk classes defined by the insurer, but classification errors may result from this process. In the light of recent automatic classification practices, it becomes important to assess the risks caused by such errors. In this paper we examine the impact of risk class misspecifications for a simple situation with two risk types. We provide a mean-variance framework for quantitatively studying the insurer’s optimization problem of specifying premiums and we analyze the tradeoff of costs and benefits when classification error probabilities are known.
Sustainable energy efficient workflow classification and scheduling in geo distributed cloud datacenter
Authors: Sharma Anu Priya , Singh Jaspreet , Gulzar Yonis , Gupta Deepali , Kumar Mukesh
Published: June 2024

Data centers are a major source of carbon emissions and are subsequently contributing to global carbon footprints. Keeping in view of providing a sustainable solution to society, we have analyzed various factors that can help to achieve carbon neutrality and maximum sustainability. Our study pointed towards the need to follow a sustainable approach for incoming workflow throughout the life-cycle of Data centers. We analyzed that workloads need to be segregated before assigning them to the data centers so that energy-efficient resource allocation could be done. This paper demonstrates unsupervised learning techniques to cluster the incoming cloud workloads. The heterogeneous workloads were characterized using machine learning approaches and appropriate clusters were crafted. For analysis, Google Cluster Dataset is used. In order to improve the accuracy, data were normalized, and random samples of data were selected for clustering. The machine learning algorithms applied were able to successfully determine the appropriate clusters that can further be used for energy-efficient resource scheduling.
Development of a simultaneous LC–MS/MS analytical method for plasma: 16 antipsychotics approved in Japan and 4 drug metabolites
Authors: Maekawa Masamitsu , Yokota Maki , Sato Toshihiro , Sato Yu , Kumondai Masaki , Sato Yuji , Suzuka Masato , Kobayashi Daisuke , Sakamoto Kotaro , Matsuura Masaki , Kikuchi Masafumi , Komatsu Hiroshi , Fujii Kumiko , Ozeki Yuji , Tomita Hiroaki , Mano Nariyasu
Published: June 2024

The increased risk of adverse drug reactions due to the concomitant use of antipsychotics is problematic in the treatment of schizophrenia. Therefore, the simultaneous analysis of their plasma concentrations is required. In this study, we developed a simultaneous liquid chromatography/tandem mass spectrometry (LC–MS/MS) method for analyzing plasma antipsychotics approved in Japan for therapeutic drug monitoring (TDM) applications. First, we counted the prescriptions for 16 antipsychotics and concomitant drugs used at the Tohoku University Hospital. LC–MS/MS was used for the simultaneous analysis of 16 antipsychotics and four drug metabolites. This analysis was conducted using a combination of selected reaction monitoring mode and reversed-phase chromatography. Following the examination of the MS/MS and LC conditions, an analytical method validation test was conducted. The developed method was used to analyze plasma antipsychotic levels in patients with schizophrenia. One-third of the patients received treatment with multiple antipsychotics. Under LC–MS/MS conditions, LC separation was performed using a combination of a C18 column and ammonium formate-based mobile phases with a gradient flow. The calibration curves were optimized by adjusting the ion abundance, and 11 compounds met the criteria for intra- and inter-day reproducibility tests. Some stability test results did not meet these criteria; therefore, further investigation is required. The developed method permitted the measurement of all the plasma parameters, including concentrations above the therapeutic range. Therefore, this method may be useful in the daily TDM practice of antipsychotics.

Graphical abstract
Topologically optimised facade brackets: an embodied carbon, structural and residual stress analysis
Authors: Grigoriadis Kostas , Bouchard John , Herrmann Michael
Published: June 2024

The research investigates the topological optimisation of the metal brackets that connect curtain wall panelling to the floor slabs of a building. As is typically the case with standard building components, the brackets are overdesigned with higher load margins than real applied loads. Optimising them results in reduced mass and a more evenly spread stress distribution. Correspondingly, the question that the project asks is whether the optimised designs have a comparable structural performance to the standard bracketry used in construction, and a lower embodied carbon. To answer this, several optimisations of a standard facade bracket are performed, resulting in a total of six converged design options, with three of them progressed for fabrication. The manufactured designs are then horizontal and vertical load and residual stress tested to assess their performance, and an embodied carbon analysis is performed to calculate the corresponding emissions for raw material extraction, processing, and component fabrication. The results indicate the presence of compressive yield magnitude residual stresses, and that structural performance is comparable to a standard bracket, but embodied carbon is in most cases higher. The paper concludes with a discussion of the findings, and possible next steps in the optimisation, structural testing, and embodied carbon analysis workflow.
A survey on deep clustering: from the prior perspective
Authors: Lu Yiding , Li Haobin , Li Yunfan , Lin Yijie , Peng Xi
Published: June 2024

Facilitated by the powerful feature extraction ability of neural networks, deep clustering has achieved great success in analyzing high-dimensional and complex real-world data. The performance of deep clustering methods is affected by various factors such as network structures and learning objectives. However, as pointed out in this survey, the essence of deep clustering lies in the incorporation and utilization of prior knowledge, which is largely ignored by existing works. From pioneering deep clustering methods based on data structure assumptions to recent contrastive clustering methods based on data augmentation invariances, the development of deep clustering intrinsically corresponds to the evolution of prior knowledge. In this survey, we provide a comprehensive review of deep clustering methods by categorizing them into six types of prior knowledge. We find that in general the prior innovation follows two trends, namely, i) from mining to constructing, and ii) from internal to external. Besides, we provide a benchmark on five widely-used datasets and analyze the performance of methods with diverse priors. By providing a novel prior knowledge perspective, we hope this survey could provide some novel insights and inspire future research in the deep clustering community.
Multi-dimensional classification: paradigm, algorithms and beyond
Authors: Jia Bin-Bin , Zhang Min-Ling
Published: June 2024

Multi-dimensional classification (MDC) aims at learning from objects where each of them is represented by a single instance while associated with multiple class variables. In recent years, this practical learning paradigm has attracted increasing attentions in machine learning community. In this paper, a timely review on this topic is provided with emphasis on representative algorithms. Firstly, the MDC learning framework, commonly used evaluation metrics and publicly available MDC datasets are given. Then, eight state-of-the-art MDC algorithms are scrutinized as the representatives of three categories. After that, several related learning settings are briefly summarized. Finally, this paper is concluded with discussing some open problems to be studied in the future.
Traditional health care systems and immunity boosting: exploring plant based indigenous knowledge systems amidst the COVID-19 pandemic
Authors: Maikhuri Rakesh Kumar , Maletha Ajay , Singh Ravindra , Bhatt Girish , Agarwal Sunil , Dhyani Shalini , Nautiyal Sunil , Phondani Prakash Chandra , Rawat Lakhpat Singh , Badoni Priyanka , Kandari Laxman Singh , Srivastava Abhishek , Maikhuri Rama , Chamola Bhagwati Prasad , Semwal Rajeev Lochan , Purohit Vijay Kant , Singh Shankar
Published: June 2024

The COVID-19 outbreak has highlighted the importance of utilizing traditional Ecological knowledge (TEK) to address the health risks linked to the pandemic. Mountain communities have traditionally relied on wild plant species and indigenous crops to enhance their immune system and maintain nutritional security. Recognizing the significance of indigenous knowledge systems this study was undertaken to explore plant-based traditional healthcare systems to revitalize immunity against COVID-19. A comprehensive survey and interviews of 195 local healers (Vaidyas) and residents were carried out using structured and semi-structured questionnaires following the convenience sampling method. The survey identified 40 plant species traditionally used for treating various ailments and augmenting immune functions. This study revealed a strong interest (over 80%) among the local population in plant-based remedies to enhance immunity for COVID-19. This study underscores the necessity of revitalizing and integrating diminishing traditional knowledge into mainstream healthcare practices, emphasizing the significance of region-specific approaches aligned with local resources and requirements. Therefore, there is an urgent need for exploration and recognition of the value of traditional knowledge and indigenous foods, alongside rigorous clinical trials to ascertain their role in fortifying health resilience against COVID-19.
The Transfer of Solar Wind Energy to the Venusian Ionosphere Through Magnetic Pumping: Evidence From Pioneer Venus Orbiter Observations
Authors: Fowler C. M. , Frost A. , Agapitov O. , Frahm R. , Xu S.
Published: June 2024

The collisionless nature of planetary magnetospheres means that electromagnetic forces are fundamental in controlling the flow of energy and momentum through these systems. We use Pioneer Venus Orbiter (PVO) observations to demonstrate that the magnetic pumping process can be active at Venus, in analogy to its recent discovery at Mars. The presented case study demonstrates the framework for how the process can work at Venus, and the results of a statistical analysis show that the ambient plasma conditions support the process being active. Magnetic pumping enables low frequency magnetosonic waves to heat ambient ionospheric electrons and provides a mechanism that couples the solar wind to the Venusian ionosphere. This is the first time the magnetic pumping process has been discussed at Venus.
Nonlinear and Non‐Gaussian Ensemble Assimilation of MOPITT CO
Authors: Gaubert Benjamin , Anderson Jeffrey L. , Trudeau Michael , Smith Nadia , McKain Kathryn , Pétron Gabrielle , Raeder Kevin , Arellano Avelino F. , Granier Claire , Emmons Louisa K. , Ortega Ivan , Hannigan James W. , Tang Wenfu , Worden Helen M. , Ziskin Daniel , Edwards David P.
Published: June 2024

Satellite retrievals of carbon monoxide (CO) are routinely assimilated in atmospheric chemistry models to improve air quality forecasts, produce reanalyzes and to estimate emissions. This study applies the quantile‐conserving ensemble filter framework, a novel assimilation algorithm that can deal with non‐Gaussian and modestly nonlinear distributions. Instead of assuming normal distributions like the Ensemble Adjustments Kalman Filter (EAKF), we now apply a bounded normal rank histogram (BNRH) distribution for the prior. The goal is to efficiently estimate bounded quantities such as CO atmospheric mixing ratios and emission fluxes while maintaining the good performance achieved by the EAKF. We contrast assimilating meteorological and MOPITT (Measurement of Pollution in the Troposphere) observations for May 2018. We evaluate the results with the fourth deployment of the NASA Atmospheric Tomography Mission (ATom‐4) airborne field campaign. We also compare simulations with CO tropospheric columns from the network for the detection of atmospheric composition change and surface in‐situ observations from NOAA carbon cycle greenhouse gases. While the differences remain small, the BNRH approach clearly works better than the EAKF in comparison to all observation data sets.
Pioneer Venus Orbiter Observations of Solar Wind Driven Magnetosonic Waves Interacting With the Dayside Venusian Ionosphere
Authors: Fowler C. M. , Ledvina S. , Chaston C. C. , Persson M. , Ramstad R. , Luhmann J.
Published: June 2024

We use in situ plasma observations made by the Pioneer Venus Orbiter spacecraft to show for the first time that magnetosonic waves can couple the solar wind to the upper ionosphere and deposit energy there. The waves are generated upstream of Venus, are advected into the shock and propagate across the draped magnetic field, through the magnetosheath and into the dayside upper ionosphere. The magnetosonic waves damp in the upper ionosphere in a region where physical collisions are rare, and electromagnetic forces must control this damping. The waves damp when the ionospheric heavy ion density is a few thousand cm−3 and wave‐particle interactions with the dominant O+ ions are postulated as the damping mechanism. Estimates of ion heating rates show that 1%–5% of the O+ ion distribution function could be heated to escape energy in 10–40 s.
Two-stage strategy using denoising autoencoders for robust reference-free genotype imputation with missing input genotypes
Authors: Kojima Kaname , Tadaka Shu , Okamura Yasunobu , Kinoshita Kengo
Published: June 2024

Widely used genotype imputation methods are based on the Li and Stephens model, which assumes that new haplotypes can be represented by modifying existing haplotypes in a reference panel through mutations and recombinations. These methods use genotypes from SNP arrays as inputs to estimate haplotypes that align with the input genotypes by analyzing recombination patterns within a reference panel, and then infer unobserved variants. While these methods require reference panels in an identifiable form, their public use is limited due to privacy and consent concerns. One strategy to overcome these limitations is to use de-identified haplotype information, such as summary statistics or model parameters. Advances in deep learning (DL) offer the potential to develop imputation methods that use haplotype information in a reference-free manner by handling it as model parameters, while maintaining comparable imputation accuracy to methods based on the Li and Stephens model. Here, we provide a brief introduction to DL-based reference-free genotype imputation methods, including RNN-IMP, developed by our research group. We then evaluate the performance of RNN-IMP against widely-used Li and Stephens model-based imputation methods in terms of accuracy (R2), using the 1000 Genomes Project Phase 3 dataset and corresponding simulated Omni2.5 SNP genotype data. Although RNN-IMP is sensitive to missing values in input genotypes, we propose a two-stage imputation strategy: missing genotypes are first imputed using denoising autoencoders; RNN-IMP then processes these imputed genotypes. This approach restores the imputation accuracy that is degraded by missing values, enhancing the practical use of RNN-IMP.
How risky is a second allogeneic stem cell transplantation?
Authors: Penack Olaf , Abouqateb Mouad , Peczynski Christophe , Boreland William , Kröger Nicolaus , Zeiser Robert , Ciceri Fabio , Schroeder Thomas , Dreger Peter , Passweg Jakob , Schetelig Johannes , Stelljes Matthias , Blau Igor Wolfgang , Franke Georg-Nikolaus , Riesner Katarina , Schoemans Hélène , Moiseev Ivan , Peric Zinaida
Published: June 2024

There is no consensus on second allogeneic stem cell transplantation (alloSCT) indications in patients with hematologic malignancies relapsing after a first alloSCT. In historic publications, a very high non-relapse mortality (NRM) has been described, arguing against performing a second alloSCT. We analysed the outcome of 3356 second alloSCTs performed 2011–21 following a hematologic malignancy relapse. Outcomes at two years after second alloSCT were: NRM 22%, relapse incidence 50%, overall survival 38%, and progression-free survival 28%. Key risk factors for increased NRM were: older age, low performance score, high disease-risk-index, early relapse after the first alloSCT, unrelated/haploidentical donor, and GVHD before second alloSCT. Any type of GVHD after first alloSCT was also important risk factor for acute GVHD and chronic GVHD after second alloSCT. There was a preferential use of a different donor (80%) at second alloSCT from first alloSCT. However, in multivariate analysis, the use of the same alloSCT donor for second alloSCT vs. a different donor was not associated with any of the survival or GVHD endpoints. We show considerably improved outcome as compared to historic reports. These current data support a wider use of second alloSCT and provide risk factors for NRM that need to be considered.
Elasto-inertial focusing and particle migration in high aspect ratio microchannels for high-throughput separation
Authors: Tanriverdi Selim , Cruz Javier , Habibi Shahriar , Amini Kasra , Costa Martim , Lundell Fredrik , Mårtensson Gustaf , Brandt Luca , Tammisola Outi , Russom Aman
Published: June 2024

The combination of flow elasticity and inertia has emerged as a viable tool for focusing and manipulating particles using microfluidics. Although there is considerable interest in the field of elasto-inertial microfluidics owing to its potential applications, research on particle focusing has been mostly limited to low Reynolds numbers (Re<1), and particle migration toward equilibrium positions has not been extensively examined. In this work, we thoroughly studied particle focusing on the dynamic range of flow rates and particle migration using straight microchannels with a single inlet high aspect ratio. We initially explored several parameters that had an impact on particle focusing, such as the particle size, channel dimensions, concentration of viscoelastic fluid, and flow rate. Our experimental work covered a wide range of dimensionless numbers (0.05 < Reynolds number < 85, 1.5 < Weissenberg number < 3800, 5 < Elasticity number < 470) using 3, 5, 7, and 10 µm particles. Our results showed that the particle size played a dominant role, and by tuning the parameters, particle focusing could be achieved at Reynolds numbers ranging from 0.2 (1 µL/min) to 85 (250 µL/min). Furthermore, we numerically and experimentally studied particle migration and reported differential particle migration for high-resolution separations of 5 µm, 7 µm and 10 µm particles in a sheathless flow at a throughput of 150 µL/min. Our work elucidates the complex particle transport in elasto-inertial flows and has great potential for the development of high-throughput and high-resolution particle separation for biomedical and environmental applications.
Dexmedetomidine improves the circulatory dysfunction of the glymphatic system induced by sevoflurane through the PI3K/AKT/ΔFosB/AQP4 pathway in young mice
Authors: Wang Shuying , Yu Xiaojin , Cheng Lili , Ren Weishu , Wen Gehua , Wu Xue , Lou Haoyang , Ren Xinghua , Lu Lei , Hermenean Anca , Yao Jun , Li Baoman , Lu Yan , Wu Xu
Published: June 2024

Multiple sevoflurane exposures may damage the developing brain. The neuroprotective function of dexmedetomidine has been widely confirmed in animal experiments and human studies. However, the effect of dexmedetomidine on the glymphatic system has not been clearly studied. We hypothesized that dexmedetomidine could alleviate sevoflurane-induced circulatory dysfunction of the glymphatic system in young mice. Six-day-old C57BL/6 mice were exposed to 3% sevoflurane for 2 h daily, continuously for 3 days. Intraperitoneal injection of either normal saline or dexmedetomidine was administered before every anaesthesia. Meanwhile the circulatory function of glymphatic system was detected by tracer injection at P8 and P32. On P30-P32, behavior tests including open field test, novel object recognition test, and Y-maze test were conducted. Primary astrocyte cultures were established and treated with the PI3K activator 740Y-P, dexmedetomidine, and small interfering RNA (siRNA) to silence ΔFosB. We propose for the first time that multiple exposure to sevoflurane induces circulatory dysfunction of the glymphatic system in young mice. Dexmedetomidine improves the circulatory capacity of the glymphatic system in young mice following repeated exposure to sevoflurane through the PI3K/AKT/ΔFosB/AQP4 signaling pathway, and enhances their long-term learning and working memory abilities.
Innate and adaptive immune responses that control lymph-borne viruses in the draining lymph node
Authors: Melo-Silva Carolina R. , Sigal Luis J.
Published: June 2024

The interstitial fluids in tissues are constantly drained into the lymph nodes (LNs) as lymph through afferent lymphatic vessels and from LNs into the blood through efferent lymphatics. LNs are strategically positioned and have the appropriate cellular composition to serve as sites of adaptive immune initiation against invading pathogens. However, for lymph-borne viruses, which disseminate from the entry site to other tissues through the lymphatic system, immune cells in the draining LN (dLN) also play critical roles in curbing systemic viral dissemination during primary and secondary infections. Lymph-borne viruses in tissues can be transported to dLNs as free virions in the lymph or within infected cells. Regardless of the entry mechanism, infected myeloid antigen-presenting cells, including various subtypes of dendritic cells, inflammatory monocytes, and macrophages, play a critical role in initiating the innate immune response within the dLN. This innate immune response involves cellular crosstalk between infected and bystander innate immune cells that ultimately produce type I interferons (IFN-Is) and other cytokines and recruit inflammatory monocytes and natural killer (NK) cells. IFN-I and NK cell cytotoxicity can restrict systemic viral spread during primary infections and prevent serious disease. Additionally, the memory CD8+ T-cells that reside or rapidly migrate to the dLN can contribute to disease prevention during secondary viral infections. This review explores the intricate innate immune responses orchestrated within dLNs that contain primary viral infections and the role of memory CD8+ T-cells following secondary infection or CD8+ T-cell vaccination.
Targeting the intestinal circadian clock by meal timing ameliorates gastrointestinal inflammation
Authors: Niu Yunhui , Heddes Marjolein , Altaha Baraa , Birkner Michael , Kleigrewe Karin , Meng Chen , Haller Dirk , Kiessling Silke
Published: June 2024

The expression of clock genes has been observed to be impaired in biopsies from patients with inflammatory bowel disease (IBD). Disruption of circadian rhythms, which occurs in shift workers, has been linked to an increased risk of gastrointestinal diseases, including IBD. The peripheral circadian clock in intestinal epithelial cells (IECs) was previously shown to balance gastrointestinal homeostasis by regulating the microbiome. Here, we demonstrated that the intestinal clock is disrupted in an IBD-relevant mouse model (IL-10−/−). A lack of the intestinal clock gene (Bmal1) in intestinal epithelial cells (IECs) in a chemically and a novel genetically induced colitis model (DSS, Bmal1IEC−/−xIL-10−/−) promoted colitis and dramatically reduced survival rates. Germ-free Bmal1IEC−/− mice colonized with disease-associated microbiota from IL-10−/− mice exhibited increased inflammatory responses, highlighting the importance of the local intestinal clock for microbiota-induced IBD development. Targeting the intestinal clock directly by timed restricted feeding (RF) in IL-10−/− mice restored intestinal clock functions, including immune cell recruitment and microbial rhythmicity; improved inflammatory responses; dramatically enhanced survival rates and rescued the histopathological phenotype. In contrast, RF failed to improve IBD symptoms in Bmal1IEC−/−xIL-10−/− mice, demonstrating the significance of the intestinal clock in determining the beneficial effect of RF. Overall, we provide evidence that intestinal clock dysfunction triggers host immune imbalance and promotes the development and progression of IBD-like colitis. Enhancing intestinal clock function by RF modulates the pathogenesis of IBD and thus could become a novel strategy to ameliorate symptoms in IBD patients.
Landscape features support natural pest control and farm income when pesticide application is reduced
Authors: Klinnert Ana , Barbosa Ana Luisa , Catarino Rui , Fellmann Thomas , Baldoni Edoardo , Beber Caetano , Hristov Jordan , Paracchini Maria Luisa , Rega Carlo , Weiss Franz , Witzke Peter , Rodriguez-Cerezo Emilio
Published: June 2024

Future trajectories of agricultural productivity need to incorporate environmental targets, including the reduction of pesticides use. Landscape features supporting natural pest control (LF-NPC) offer a nature-based solution that can serve as a partial substitute for synthetic pesticides, thereby supporting future productivity levels. Here, we introduce a novel approach to quantify the contribution of LF-NPC to agricultural yields and its associated economic value to crop production in a broad-scale context. Using the European Union as case study, we combine granular farm-level data, a spatially explicit map of LF-NPC potential, and a regional agro-economic supply and market model. The results reveal that farms located in areas characterized by higher LF-NPC potential experience lower productivity losses in a context of reduced synthetic pesticides use. Our analysis suggests that LF-NPC reduces yield gaps on average by four percentage points, and increases income by a similar magnitude. These results highlight the significance of LF-NPC for agricultural production and income, and provide a valuable reference point for farmers and policymakers aiming to successfully invest in landscape features to achieve pesticides reduction targets.
Ferroelectric freestanding hafnia membranes with metastable rhombohedral structure down to 1-nm-thick
Authors: Shen Yufan , Ooe Kousuke , Yuan Xueyou , Yamada Tomoaki , Kobayashi Shunsuke , Haruta Mitsutaka , Kan Daisuke , Shimakawa Yuichi
Published: June 2024

Two-dimensional freestanding membranes of materials, which can be transferred onto and make interfaces with any material, have attracted attention in the search for functional properties that can be utilized for next-generation nanoscale devices. We fabricated stable 1-nm-thick hafnia membranes exhibiting the metastable rhombohedral structure and out-of-plane ferroelectric polarizations as large as 13 μC/cm2. We also found that the rhombohedral phase transforms into another metastable orthorhombic phase without the ferroelectricity deteriorating as the thickness increases. Our results reveal the key role of the rhombohedral phase in the scale-free ferroelectricity in hafnia and also provide critical insights into the formation mechanism and phase stability of the metastable hafnia. Moreover, ultrathin hafnia membranes enable heterointerfaces and devices to be fabricated from structurally dissimilar materials beyond structural constrictions in conventional film-growth techniques.
A trans-oceanic flight of over 4,200 km by painted lady butterflies
Authors: Suchan Tomasz , Bataille Clément P. , Reich Megan S. , Toro-Delgado Eric , Vila Roger , Pierce Naomi E. , Talavera Gerard
Published: June 2024

The extent of aerial flows of insects circulating around the planet and their impact on ecosystems and biogeography remain enigmatic because of methodological challenges. Here we report a transatlantic crossing by Vanessa cardui butterflies spanning at least 4200 km, from West Africa to South America (French Guiana) and lasting between 5 and 8 days. Even more, we infer a likely natal origin for these individuals in Western Europe, and the journey Europe-Africa-South America could expand to 7000 km or more. This discovery was possible through an integrative approach, including coastal field surveys, wind trajectory modelling, genomics, pollen metabarcoding, ecological niche modelling, and multi-isotope geolocation of natal origins. The overall journey, which was energetically feasible only if assisted by winds, is among the longest documented for individual insects, and potentially the first verified transatlantic crossing. Our findings suggest that we may be underestimating transoceanic dispersal in insects and highlight the importance of aerial highways connecting continents by trade winds.
Production of constrained L-cyclo-tetrapeptides by epimerization-resistant direct aminolysis
Authors: Chen Huan , Zhang Yuchen , Wen Yuming , Fan Xinhao , Sciolino Nicholas , Lin Yanyun , Breindel Leonard , Dai Yuanwei , Shekhtman Alexander , Xue Xiao-Song , Zhang Qiang
Published: June 2024

The synthesis of constrained 12-membered rings is notably difficult. The main challenges result from constraints during the linear peptide cyclization. Attempts to overcome constraints through excessive activation frequently cause peptidyl epimerization, while insufficient activation of the C-terminus hampers cyclization and promotes intermolecular oligomer formation. We present a β-thiolactone framework that enables the synthesis of cyclo-tetrapeptides via direct aminolysis. This tactic utilizes a mechanism that restricts C-terminal carbonyl rotation while maintaining high reactivity, thereby enabling efficient head-to-tail amidation, reducing oligomerization, and preventing epimerization. A broad range of challenging cyclo-tetrapeptides ( > 20 examples) are synthesized in buffer and exhibits excellent tolerance toward nearly all proteinogenic amino acids. Previously unattainable macrocycles, such as cyclo-L-(Pro-Tyr-Pro-Val), have been produced and identified as μ-opioid receptor (MOR) agonists, with an EC50 value of 2.5 nM. Non-epimerizable direct aminolysis offers a practical solution for constrained peptide cyclization, and the discovery of MOR agonist activity highlights the importance of overcoming synthetic challenges for therapeutic development.
Tandem dehydrogenation-olefination-decarboxylation of cycloalkyl carboxylic acids via multifold C–H activation
Authors: Pal Tanay , Ghosh Premananda , Islam Minhajul , Guin Srimanta , Maji Suman , Dutta Suparna , Das Jayabrata , Ge Haibo , Maiti Debabrata
Published: June 2024

Dehydrogenation chemistry has long been established as a fundamental aspect of organic synthesis, commonly encountered in carbonyl compounds. Transition metal catalysis revolutionized it, with strategies like transfer-dehydrogenation, single electron transfer and C–H activation. These approaches, extended to multiple dehydrogenations, can lead to aromatization. Dehydrogenative transformations of aliphatic carboxylic acids pose challenges, yet engineered ligands and metal catalysis can initiate dehydrogenation via C–H activation, though outcomes vary based on substrate structures. Herein, we have developed a catalytic system enabling cyclohexane carboxylic acids to undergo multifold C–H activation to furnish olefinated arenes, bypassing lactone formation. This showcases unique reactivity in aliphatic carboxylic acids, involving tandem dehydrogenation-olefination-decarboxylation-aromatization sequences, validated by control experiments and key intermediate isolation. For cyclopentane carboxylic acids, reluctant to aromatization, the catalytic system facilitates controlled dehydrogenation, providing difunctionalized cyclopentenes through tandem dehydrogenation-olefination-decarboxylation-allylic acyloxylation sequences. This transformation expands carboxylic acids into diverse molecular entities with wide applications, underscoring its importance.
Battery electronification: intracell actuation and thermal management
Authors: Longchamps Ryan S. , Ge Shanhai , Trdinich Zachary J. , Liao Jie , Wang Chao-Yang
Published: June 2024

Electrochemical batteries – essential to vehicle electrification and renewable energy storage – have ever-present reaction interfaces that require compromise among power, energy, lifetime, and safety. Here we report a chip-in-cell battery by integrating an ultrathin foil heater and a microswitch into the layer-by-layer architecture of a battery cell to harness intracell actuation and mutual thermal management between the heat-generating switch and heat-absorbing battery materials. The result is a two-terminal, drop-in ready battery with no bulky heat sinks or heavy wiring needed for an external high-power switch. We demonstrate rapid self-heating (∼ 60 °C min−1), low energy consumption (0.138% °C−1 of battery energy), and excellent durability (> 2000 cycles) of the greatly simplified chip-in-cell structure. The battery electronification platform unveiled here opens doors to include integrated-circuit chips inside energy storage cells for sensing, control, actuating, and wireless communications such that performance, lifetime, and safety of electrochemical energy storage devices can be internally regulated.
3D architecture and complex behavior along the simple central San Andreas fault
Authors: Cheng Yifang , Bürgmann Roland , Allen Richard M.
Published: June 2024

The central San Andreas Fault (CSAF) exhibits a simple linear large-scale fault geometry, yet seismic and aseismic deformation features vary in a complex way along the fault. Here we investigate fault zone behaviors using geodetic observation, seismicity and microearthquake focal mechanisms. We employ an improved focal-mechanism characterization method using relative earthquake radiation patterns on 75,164 Ml ≥ 1 earthquakes along a 2-km-wide, 190-km-long segment of the CSAF, from 1984 to 2015. The data reveal the 3D fine-scale structure and interseismic kinematics of the CSAF. Our findings indicate that the first-order spatial variations in interseismic fault creep rate, creep direction, and the fault zone stress field can be explained by a simple fault coupling model. The inferred 3D mechanical properties of a mechanically weak and poorly coupled fault zone provide a unified understanding of the complex fine-scale kinematics, indicating distributed slip deficits facilitating small-to-moderate earthquakes, localized stress heterogeneities, and complex multi-scale ruptures along the fault. Through this detailed mapping, we aim to relate the fine-scale fault architecture to potential future faulting behavior along the CSAF.