bluuebunny/crossref_metadata_2025 huggingface dataset:
One‐Pot N‐Alkylation of Amines over Ni(II) Embedded Reusable Porous Organic Polymer via Borrowing Hydrogen Strategy
Authors: Pathak Debabrat , Kumar Kalita Bikash , Sharma Himanshu , Biswakarma Nishant , Deka Ramesh Ch. , Sarma Bipul
Published: January 2024

The first‐of‐its‐kind, one‐pot N‐alkylation reaction of amines over Ni(II) impregnated porous organic polymer of highly dense N‐rich skeleton is reported. The primeval Ni(II) decorated hollow spherical porous polymer is synthesized and employed in a series of catalytic reactions involving C−N bond formation. The catalytic reactions are optimised to yield the desired product highlighting the role of different substituents present on the reactants towards the overall selectivity and efficiency. The detailed reaction mechanism is corroborated with computation validating a three‐step arrow formalism viz. dehydrogenation of the alcohol, condensation with amines to generate the imine as intermediate followed by hydrogenation by a borrowing strategy to yield the final product. The role of the bare support material in the first step and that of the Ni(II) centres of the support material in the third step is marked as pivotal for the forward reaction to proceed with enriching sustainability and feasibility.
Regio‐ and Enantioselective Synthesis of 1,2‐Diamines by Formal Hydroamination of Enamines: Scope, Mechanism, and Asymmetric Synthesis of Orthogonally Protected Bis‐Piperazines as a Privileged Scaffold
Authors: Mohiti Maziar , Lu Yu , He Hui , Ni Shao‐Fei , Somfai Peter
Published: January 2024

We have previously reported the first formal hydroamination of enamines for the synthesis of chiral 1,2‐diamines. Here, we describe: (i) the discovery, optimization, and substrate expansion of this reaction; (ii) a novel and straightforward protocol for the “click‐type” synthesis of enamines in quantitative yield utilizing sodium sulfate in a dual role as an ancillary and dehydrating agent without the need for workup or purification; (iii) the application of this methodology to the first enantioselective synthesis of orthogonally protected 1,1′‐(1‐(4‐fluorophenyl)ethane‐1,2‐diyl) piperazines, a scaffold for rapid lead optimization in drug discovery; (iv) a computational investigation into the mechanism and rationalization of the enantioselectivities of the reaction.
Hexagonal Prismatic Siloxanes Functionalized with Organosilyl Groups as Building Blocks of Nanoporous Materials
Authors: Hayashi Taiki , Kikuchi Miharu , Murase Nanako , Matsuno Takamichi , Sugimura Natsuhiko , Kuroda Kazuyuki , Shimojima Atsushi
Published: January 2024

Utilization of well‐defined siloxane molecules allows for the construction of functional siloxane‐based nanoporous materials based on the molecular design. Herein, a novel class of siloxane‐based porous materials is synthesized via cross‐linking of dimethylsilyl‐ and dimethylvinylsilyl‐functionalized cage siloxanes with double‐6‐ring (D6R) geometry. Compared with the conventional double‐4‐ring cage siloxane, this study highlights the characteristics of D6R siloxanes as building blocks, demonstrating their high surface area and chemical stability. Furthermore, density functional theory calculations show their unique cation encapsulation ability.
A new control method of hybrid energy storage system for DC microgrid application
Authors: Taye Biks Alebachew , Choudhury Nalin Behari Dev
Published: January 2024

Energy storage system play a crucial role in safeguarding the reliability and steady voltage supply within microgrids. While batteries are the prevalent choice for energy storage in such applications, their limitation in handling high‐frequency discharging and charging necessitates the incorporation of high‐energy density and high‐power density storage devices to enhance power quality, maintain power balance, and reduce fluctuations. In this study, we introduce a hybrid energy storage system (HESS) solution, combining a battery and a supercapacitor, to address intermittent power supply challenges. The effective management of this HESS is pivotal for constant DC voltage and sustaining microgrid stability. To achieve this, we propose an innovative control strategy called the Adaptive Filter‐Based Method (AFBM) for DC microgrid operation, which prioritizes stable and smooth performance while addressing safety and degradation concerns related to the storage devices. Our control strategy determines the distribution of charging and discharging currents for each storage device within the DC microgrid based on their state of charge. We conducted simulations in MATLAB/Simulink, comparing the proposed AFBM method with the conventional filter‐based approach using identical configurations, parameters, and operational modes. The results demonstrate the superior performance of our proposed system, showcasing improved voltage stability, more equitable load distribution, and efficient charging and discharging of storage devices compared to the traditional method. This research contributes to the advancement of microgrid energy storage solutions, enhancing their reliability and performance.
What affects how Chinese patients wish to be involved in health care delivery? Perspectives of the Chinese policy and institutional contexts
Authors: Zhu Jingyan , Sui Ping
Published: January 2024

Introduction

The benefits of involving patients and carers include improving health outcomes and safety, reducing costs and enhancing an open, accountable and equitable relationship between service providers and users. However, the willingness for involvement and participation is largely affected by a range of factors, including those at the micro, meso and macro levels. As the previous studies have given much attention to the factors at the individual level, it is worthwhile to explore the factors at the broader levels of the policy and institutional contexts. The objective of the research is to understand how the policy and institutional contexts in China affect how patients wish to be involved in their health care delivery.

Methods

An abductive research strategy was used to generate emergent hypotheses in the first stage of data construction. In the second stage of fieldwork, hypotheses were tested using the deductive approach. Three local hospitals in Shandong Province, China, were selected. The case study method was designed with qualitative methods of policy documents and interviews. Interviews included health professionals, health board managers, local administrators and service users. Thematic analysis and framework analysis were conducted.

Results

Four policy and institutional contexts were identified: insufficient policy support, the current institutional design of involving users, the heterogeneity of organisational autonomy and resources, as well as the demography of the population of service users.

Conclusions

As a policy strategy at the state level, there is a lack of policy support for patient involvement and participation in the Chinese health system. The heterogeneity of the institutional context of health facilities plays a key role in affecting how patients wish to be involved in health care delivery.
Linc‐ROR inhibits NK cell‐killing activity by promoting RXRA ubiquitination and reducing MICB expression in gastric cancer patients
Authors: Niu Qingbin , Li Zongrui , Jiang He , Hu Baoguang
Published: January 2024

Linc‐ROR plays an important role in gastric cancer (GC) development and progression. This study sought to determine how the aberrant expression of Linc‐ROR impacts GC progression and immune evasion, and to identify new targets for GC therapy. GC cells overexpressing Linc‐ROR and GSAGS cells were cocultured with NK‐92 cells, respectively, and Linc‐ROR expression was determined using reverse transcription polymerase chain reaction. Linc‐ROR overexpression experiments were used to measure the expression of MICB, a tumor protein that is recognized by natural killer (NK) cells. Bioinformatics analysis identified retinoid X receptor α (RXRA) and YY1 as MICB‐specific transcription factors. Cotransfection and ubiquitinated drug experiments found that Linc‐ROR promoted the ubiquitination and degradation of RXRA. Linc‐ROR was upregulated in GC tissue and high expression was associated with tumor escape from NK‐92 cell‐mediated immunity. Linc‐ROR overexpression inhibited the expression of MICB on the cell surface by degrading RXRA. These findings indicate that Linc‐ROR promotes the binding of RXRA and E3 ligase UBE4B, reducing RXRA and MICB expression, and limiting NK cell‐killing activity. Linc‐ROR is a critical long noncoding RNA with a tumor‐promoting function in GC and thus may serve as a potential therapeutic target.
Dental student application of artificial intelligence technology in detecting proximal caries lesions
Authors: Ayan Enes , Bayraktar Yusuf , Çelik Çiğdem , Ayhan Baturalp
Published: January 2024

Objectives

This study aimed to investigate the caries diagnosis performances of dental students after training with an artificial intelligence (AI) application utilizing deep learning techniques, a type of artificial neural network.

Methods

A total of 1200 bitewing radiographs were obtained from the institution's database and two specialist dentists labeled the caries lesions in the images. Randomly selected 1000 images were used for training purposes and the remaining 200 radiographs were used to evaluate the caries diagnostic performance of the AI. Then, a convolutional neural network, a deep learning algorithm commonly employed to analyze visual imagery problems, called “You Only Look Once,” was modified and trained to detect enamel and dentin caries lesions in the radiographs. Forty dental students were selected voluntarily and randomly divided into two groups. The pre‐test results of dental caries diagnosis performances of both groups were recorded. After 1 week, group 2 students were trained using an AI application. Then, the post‐test results of both groups were recorded. The labeling duration of the students was also measured and analyzed.

Results

When both groups’ pre‐test and post‐test results were evaluated, a statistically significant improvement was found for all parameters examined except precision score (p < 0.05). However, the trained group's accuracy, sensitivity, specificity, and F1 scores were significantly higher than the non‐trained group in terms of post‐test scores (p < 0.05). In group 2 (trained group), the post‐test labeling time was considerably increased (p < 0.05).

Conclusions

The students trained by AI showed promising results in detecting caries lesions. The use of AI can also contribute to the clinical education of dental students.
Altered Iron and Microstructure in Huntington's Disease Subcortical Nuclei: Insight From 7T MRI
Authors: Yao Jingwen , Morrison Melanie A. , Jakary Angela , Avadiappan Sivakami , Rowley Paul , Glueck Julia , Driscoll Theresa , Geschwind Michael D. , Nelson Alexandra B. , Possin Kathrine L. , Xu Duan , Hess Christopher P. , Lupo Janine M.
Published: January 2024

Background

Pathophysiological changes of Huntington's disease (HD) can precede symptom onset by decades. Robust imaging biomarkers are needed to monitor HD progression, especially before the clinical onset.

Purpose

To investigate iron dysregulation and microstructure alterations in subcortical regions as HD imaging biomarkers, and to associate such alterations with motor and cognitive impairments.

Study Type

Prospective.

Population

Fourteen individuals with premanifest HD (38.0 ± 11.0 years, 9 females; far‐from‐onset N = 6, near‐onset N = 8), 21 manifest HD patients (49.1 ± 12.1 years, 11 females), and 33 age‐matched healthy controls (43.9 ± 12.2 years, 17 females).

Field Strength/Sequence

7 T, T1‐weighted imaging, quantitative susceptibility mapping, and diffusion tensor imaging.

Assessment

Volume, susceptibility, fractional anisotropy (FA), and mean diffusivity (MD) within subcortical brain structures were compared across groups, used to establish HD classification models, and correlated to clinical measures and cognitive assessments.

Statistical Tests

Generalized linear model, multivariate logistic regression, receiver operating characteristics with the area under the curve (AUC), and likelihood ratio test comparing a volumetric model to one that also includes susceptibility and diffusion metrics, Wilcoxon paired signed‐rank test, and Pearson's correlation. A P‐value <0.05 after Benjamini–Hochberg correction was considered statistically significant.

Results

Significantly higher striatal susceptibility and FA were found in premanifest and manifest HD preceding atrophy, even in far‐from‐onset premanifest HD compared to controls (putamen susceptibility: 0.027 ± 0.022 vs. 0.018 ± 0.013 ppm; FA: 0.358 ± 0.048 vs. 0.313 ± 0.039). The model with additional susceptibility, FA, and MD features showed higher AUC compared to volume features alone when differentiating premanifest HD from HC (0.83 vs. 0.66), and manifest from premanifest HD (0.94 vs. 0.83). Higher striatal susceptibility significantly correlated with cognitive deterioration in HD (executive function: r = −0.600; socioemotional function: r = −0.486).

Data Conclusion

7 T MRI revealed iron dysregulation and microstructure alterations with HD progression, which could precede volume loss, provide added value to HD differentiation, and might be associated with cognitive changes.

Evidence Level

2

Technical Efficacy

Stage 2
Comparison of Myocardial Blood Flow Quantification Models for Double ECG Gating Arterial Spin Labeling MRI: Reproducibility Assessment
Authors: Aramendía‐Vidaurreta Verónica , Solís‐Barquero Sergio M. , Vidorreta Marta , Ezponda Ana , Echeverria‐Chasco Rebeca , Bastarrika Gorka , Fernández‐Seara María A.
Published: January 2024

Background

Arterial spin labeling (ASL) allows non‐invasive quantification of myocardial blood flow (MBF). Double‐ECG gating (DG) ASL is more robust to heart rate variability than single‐ECG gating (SG), but its reproducibility requires further investigation. Moreover, the existence of multiple quantification models hinders its application. Frequency‐offset‐corrected‐inversion (FOCI) pulses provide sharper edge profiles than hyperbolic‐secant (HS), which could benefit myocardial ASL.

Purpose

To assess the performance of MBF quantification models for DG compared to SG ASL, to evaluate their reproducibility and to compare the effects of HS and FOCI pulses.

Study Type

Prospective.

Subjects

Sixteen subjects (27 ± 8 years).

Field Strength/Sequence

1.5 T/DG and SG flow‐sensitive alternating inversion recovery ASL.

Assessment

Three models for DG MBF quantification were compared using Monte Carlo simulations and in vivo experiments. Two models used a fitting approach (one using only a single label and control image pair per fit, the other using all available image pairs), while the third model used a T1 correction approach. Slice profile simulations were conducted for HS and FOCI pulses with varying B0 and B1. Temporal signal‐to‐noise ratio (tSNR) was computed for different acquisition/quantification strategies and inversion pulses. The number of images that minimized MBF error was investigated in the model with highest tSNR. Intra and intersession reproducibility were assessed in 10 subjects.

Statistical Tests

Within‐subject coefficient of variation, analysis of variance. P‐value <0.05 was considered significant.

Results

MBF was not different across acquisition/quantification strategies (P = 0.27) nor pulses (P = 0.9). DG MBF quantification models exhibited significantly higher tSNR and superior reproducibility, particularly for the fitting model using multiple images (tSNR was 3.46 ± 2.18 in vivo and 3.32 ± 1.16 in simulations, respectively; wsCV = 16%). Reducing the number of ASL pairs to 13/15 did not increase MBF error (minimum = 0.22 mL/g/min).

Data Conclusion

Reproducibility of MBF was better for DG than SG acquisitions, especially when employing a fitting model.

Level of Evidence

2

Technical Efficacy

Stage 1
Special cases of the minimum spanning tree problem under explorable edge and vertex uncertainty
Authors: Mathwieser Corinna , Çela Eranda
Published: January 2024

This article studies the Minimum Spanning Tree Problem under Explorable Uncertainty as well as a related vertex uncertainty version of the problem. We particularly consider special instance types, including cactus graphs, for which we provide randomized algorithms. We introduce the problem of finding a minimum weight spanning star under uncertainty for which we show that no algorithm can achieve constant competitive ratio.
Predictors of rewarded caregiving for family caregivers of person with dementia: A longitudinal study
Authors: Liu Hsin‐Yun , Kuo Li‐Min , Shyu Yea‐Ing L. , Hsu Wen‐Chuin
Published: January 2024

The purpose of this study was to explore variables associated with rewarded caregiving for family caregivers of persons living with dementia over a 2‐year follow‐up. This correlational longitudinal study was comprised of 200 family caregivers of persons living with dementia from neurological clinics of a medical center was conducted. Dichotomous scoring of the Rewards of Caregiving Scale of the Family Caregiving Inventory resulted in 61 (30.5%) caregivers being assigned to the well‐rewarded group and 139 (69.5%) to the poorly reward group at baseline. Variables included characteristics of family caregivers and their care receivers and assessments with validated scales of caregivers' social support and dyadic relational variables of mutuality, preparedness, and balance. Analysis at baseline showed significant predictors of well‐rewarded family caregivers were being an adult child of the care receiver, having a high perceived level mutuality and having a high perceived level of preparedness. These three variables remained as significant predictors at the 1‐ and 2‐year follow‐up. Caregivers with high levels of perceived mutuality and preparedness at 2‐years were seven times more likely to perceive themselves as well‐rewarded. Based on the findings, developing clinical interventions that focus on promoting mutuality and preparedness for family caregivers of persons with dementia could allow caregivers to perceive their role as rewarding. Attention should also be paid to the relationship between the caregiver and care receiver to enhance the family caregiver's feelings of mutuality and preparedness.
Factors influencing older women's decision‐making related to treatment of operable breast cancer: A qualitative systematic review
Authors: Malcolm Francesca Ligori , Howard Penny , Klukowska Anita Maria , Minhas Nikita , Parks Ruth Mary , Cheung Kwok Leung
Published: January 2024

Objective

There is variation in practice in the treatment of older women with breast cancer. International guidelines highlight the importance of patient autonomy in treatment decision‐making. The aim of this study is to identify factors which influence decision‐making in older women with operable breast cancer, which will enable us to further understand how to support these patients.

Methods

Systematic review in accordance with the PRISMA guidelines was performed to identify factors which influence treatment decision‐making in older women with operable breast cancer. Medline, Web of Science and SCOPUS were searched.

Results

The search yielded 5840 results; 13 articles met the inclusion criteria and reported on a total of 1118 women. Thematic analysis identified three key themes in which decision‐making factors could be categorised. These were healthcare‐related factors, patient‐related factors and impact of treatment. Healthcare‐related factors included communication with clinicians and provision of information. Patient‐related factors were age, pre‐existing knowledge, preconceptions of breast cancer and treatment, decision‐making style and co‐morbidities. The impact of treatment considerations included body image and effect on quality of life. Decision‐making style was frequently reported; older women did not demonstrate one preferred style.

Conclusions

The findings have highlighted the complex interplay of factors which influence how older women make breast cancer treatment‐decisions. Clinicians should have an awareness of the factors highlighted to maximise their ability to provide support and personalised care to older women with breast cancer whilst treatment decisions are made.
Recent Advances in Interface Engineering for Enhanced Open‐Circuit Voltage Regulation in Perovskite Solar Cells
Authors: Zhang Siqi , Ren Fumeng , Sun Zhenxing , Liu Xiaoxuan , Tan Zhengtian , Liu Wenguang , Chen Rui , Liu Zonghao , Chen Wei
Published: January 2024

In recent years, perovskite solar cells (PSCs) have attracted significant attention due to their excellent photoelectric properties. However, several key performance parameters of these devices still fall short of their theoretical limits. Among these parameters, the regulation of open‐circuit voltage (VOC) has been a focal point of intensive research efforts, playing a pivotal role in advancing the efficiency of PSCs. This review first provides an overview of the generation and loss mechanism of VOC. It then discusses the significance of interface engineering in VOC regulation. Recent developments in high‐efficiency PSCs realized via interface engineering have been summarized and categorized into three key areas: surface modification, interface structure optimization, and surface dimensional engineering. Finally, a comprehensive summary of past research in this domain and offered insights into the future prospects of enhancing VOC in PSCs is provided.
Markedly Enhanced Analysis of Mass Spectrometry Images Using Weakly Supervised Machine Learning
Authors: Gardner Wil , Winkler David A. , Bamford Sarah E. , Muir Benjamin W. , Pigram Paul J.
Published: January 2024

Supervised and unsupervised machine learning algorithms are routinely applied to time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) imaging data and, more broadly, to mass spectrometry imaging (MSI). These algorithms have accelerated large‐scale, single‐pixel analysis, classification, and regression. However, there is relatively little research on methods suited for so‐called weakly supervised problems, where ground‐truth class labels exist at the image level, but not at the individual pixel level. Unsupervised learning methods are usually applied to these problems. However, these methods cannot make use of available labels. Here a novel method specifically designed for weakly supervised MSI data is presented. A dual‐stream multiple instance learning (MIL) approach is adapted from computational pathology that reveals the spatial‐spectral characteristics distinguishing different classes of MSI images. The method uses an information entropy‐regularized attention mechanism to identify characteristic class pixels that are then used to extract characteristic mass spectra. This work provides a proof‐of‐concept exemplification using printed ink samples imaged by ToF‐SIMS. A second application‐oriented study is also presented, focusing on the analysis of a mixed powder sample type. Results demonstrate the potential of the MIL method for broader application in MSI, with implications for understanding subtle spatial‐spectral characteristics in various applications and contexts.
Automatic detection of building surface cracks using UAV and deep learning‐combined approach
Authors: Wang Jiehui , Wang Pujin , Qu Lei , Pei Zheng , Ueda Tamon
Published: January 2024

Concrete cracking is one of the most significant damage types in reinforced concrete structures due to its potential to adversely affect durability, safety, and serviceability and even reduce the bearing capacity during operation. Thus, damage inspection of damage caused by concrete cracking is important for management, maintenance, and structural assessment for both damaged and undamaged existing buildings but with concrete cracking after a long time of use that needs reconstruction or renovation. This study provides an improved building damage inspection approach by applying Unmanned Aerial Vehicles (UAVs) and state‐of‐the‐art deep learning algorithms to detect concrete cracks on building surfaces. Two distinct architectures for Convolutional Neural Networks (CNNs), namely ResNet50 and YOLOv8 based on classification, and object detection approaches to create a total of 11 models are established, trained, and compared. The classification models attained accuracy levels exceeding 99%, whereas the object detection models achieved approximately 85%. All models effectively identified and accurately located concrete cracks on building surfaces. Besides, the CNN models' capacity to detect cracks is influenced by a variety of model hyperparameters, encompassing factors such as model architecture, the number of network layers, different training dataset sizes, and the quantity of trainable parameters necessary to learn the specific features of detection targets during the training process. The results of this study ultimately demonstrate that the proposed approach can yield accurate detection results and holds high potential for application in crack inspection to advance automatic damage inspection in building structures to a greater extent. In addition, it is important to note that a universal rule cannot be established rule as a larger and more complex model, or an increased number of trainable parameters, necessarily leads to improved detection performance. Models that are trained from scratch using local datasets might not necessarily result in enhanced performance in comparison to the improvements gained through fine‐tuning via transfer learning. Therefore, an appropriate training type, dataset size, task complexity, computational resources, and time demands to achieve a balance between accuracy and efficiency should be considered for specific application scenarios.
Maximal D = 2 supergravities from higher dimensions
Authors: Bossard Guillaume , Ciceri Franz , Inverso Gianluca , Kleinschmidt Axel
Published: January 2024

Abstract

We develop in detail the general framework of consistent Kaluza-Klein truncations from D=11 and type II supergravities to gauged maximal supergravities in two dimensions. In particular, we unveil the complete bosonic dynamics of all gauged maximal supergravities that admit a geometric uplift. Our construction relies on generalised Scherk-Schwarz reductions of E9 exceptional field theory. The application to the reduction of D=11 supergravity on S8 × S1 to SO(9) gauged supergravity is presented in a companion paper.
Testing complex singlet scalar cosmology at the Large Hadron Collider
Authors: Zhang Wenxing , Cai Yizhou , Ramsey-Musolf Michael J. , Zhang Lei
Published: January 2024

Abstract

The Standard Model extended with a complex singlet scalar (cxSM) can admit a strong first order electroweak phase transition (SFOEWPT) as needed for electroweak baryogenesis and provide a dark matter (DM) candidate. The presence of both a DM candidate and a singlet-like scalar that mixes with the Standard Model Higgs boson leads to the possibility of a $$ b\overline{b} $$
b

b
¯

+ MET final state in pp collisions. Focusing on this channel, we analyze the prospective reach at the Large Hadron Collider (LHC) for a heavy singlet-like scalar in regions of cxSM parameter space compatible with a SFOEWPT and DM phenomenology. We identify this parameter space while implementing current constraints from electroweak precision observable and Higgs boson property measurements as well as those implied by LHC heavy resonance searches. Implementing a proposed search strategy, we find that the heavy scalar and DM candidate can be probed up to 1 TeV and 450 GeV at 2σ level respectively.
Food safety knowledge, attitudes, and practices of food vendors participating in Nigeria’s school feeding program
Authors: Barnabas Bulus , Bavorova Miroslava , Madaki Mustapha Yakubu , Kächele Harald
Published: January 2024

This study aimed to measure the food safety knowledge, attitude, and practices among food vendors engaged in Nigeria’s ongoing Home-grown School Feeding Program. A cross-sectional survey was conducted in face-to-face interviews with 240 food vendors from 3 states in northeast Nigeria involved in the school feeding program using a structured questionnaire. Multiple linear regression results revealed that increased education and access to information through radio, television, and food inspection institutions increased food safety knowledge. Food safety attitudes score increased with more years of vending experience and accessing food safety information via radio, food inspection institutions, and the Internet. An increase in household size and food safety information from friends and colleagues negatively affected food safety attitude scores. As a result, we emphasize the need for dissemination of improved food safety information via radio, television and food safety inspection institutes. Food vendors in the SFP should be selected after passing a food safety training and gaining food handling experience. Higher education should be a priority criterion in the hiring process.
The Whittaker Functional Is a Shifted Microstalk
Authors: Nadler David , Taylor Jeremy
Published: January 2024

For a smooth projective curve X and reductive group G, the Whittaker functional on nilpotent sheaves on $$Bun _G(X)$$

B
u

n
G

(
X
)

is expected to correspond to global sections of coherent sheaves on the spectral side of Betti geometric Langlands. We prove that the Whittaker functional calculates the shifted microstalk of nilpotent sheaves at the point in the Hitchin moduli where the Kostant section intersects the global nilpotent cone. In particular, the shifted Whittaker functional is exact for the perverse t-structure and commutes with Verdier duality. Our proof is topological and depends on the intrinsic local hyperbolic symmetry of $$Bun _G(X)$$

B
u

n
G

(
X
)

. It is an application of a general result relating vanishing cycles to the composition of restriction to an attracting locus followed by vanishing cycles.
Enhanced efficiency of MS/MS all-ion fragmentation for non-targeted analysis of trace contaminants in surface water using multivariate curve resolution and data fusion
Authors: Vosough Maryam , Salemi Amir , Rockel Sarah , Schmidt Torsten C.
Published: January 2024

Data-independent acquisition–all-ion fragmentation (DIA-AIF) mode of mass spectrometry can facilitate wide-scope non-target analysis of contaminants in surface water due to comprehensive spectral identification. However, because of the complexity of the resulting MS2 AIF spectra, identifying unknown pollutants remains a significant challenge, with a significant bottleneck in translating non-targeted chemical signatures into environmental impacts. The present study proposes to process fused MS1 and MS2 data sets obtained from LC-HRMS/MS measurements in non-targeted AIF workflows on surface water samples using multivariate curve resolution-alternating least squares (MCR-ALS). This enables straightforward assignment between precursor ions obtained from resolved MS1 spectra and their corresponding MS2 spectra. The method was evaluated for two sets of tap water and surface water contaminated with 14 target chemicals as a proof of concept. The data set of surface water samples consisting of 3506 MS1 and 2170 MS2 AIF mass spectral features was reduced to 81 components via a fused MS1-MS2 MCR model that describes at least 98.8% of the data. Each component summarizes the distinct chromatographic elution of components together with their corresponding MS1 and MS2 spectra. MS2 spectral similarity of more than 82% was obtained for most target chemicals. This highlights the potential of this method for unraveling the composition of MS/MS complex data in a water environment. Ultimately, the developed approach was applied to the retrospective non-target analysis of an independent set of surface water samples.

Graphical abstract
Vivaria housing conditions expose sex differences in brain oxidation, microglial activation, and immune system states in aged hAPOE4 mice
Authors: Reyes-Reyes E. M. , Brown J. , Trial M. D. , Chinnasamy D. , Wiegand J. P. , Bradford D. , Brinton R. D. , Rodgers K. E.
Published: January 2024

Apolipoprotein E ε4 allele (APOE4) is the predominant genetic risk factor for late-onset Alzheimer’s disease (AD). APOE4 mouse models have provided advances in the understanding of disease pathogenesis, but unaccounted variables like rodent housing status may hinder translational outcomes. Non-sterile aspects like food and bedding can be major sources of changes in rodent microflora. Alterations in intestinal microbial ecology can cause mucosal barrier impairment and increase pro-inflammatory signals. The present study examined the role of sterile and non-sterile food and housing on redox indicators and the immune status of humanized-APOE4 knock-in mice (hAPOe4). hAPOE4 mice were housed under sterile conditions until 22 months of age, followed by the transfer of a cohort of mice to non-sterile housing for 2 months. At 24 months of age, the redox/immunologic status was evaluated by flow cytometry/ELISA. hAPOE4 females housed under non-sterile conditions exhibited: (1) higher neuronal and microglial oxygen radical production and (2) lower CD68+ microglia (brain) and CD8+ T cells (periphery) compared to sterile-housed mice. In contrast, hAPOE4 males in non-sterile housing exhibited: (1) higher MHCII+ microglia and CD11b+CD4+ T cells (brain) and (2) higher CD11b+CD4+ T cells and levels of lipopolysaccharide-binding protein and inflammatory cytokines in the periphery relative to sterile-housed mice. This study demonstrated that sterile vs. non-sterile housing conditions are associated with the activation of redox and immune responses in the brain and periphery in a sex-dependent manner. Therefore, housing status may contribute to variable outcomes in both the brain and periphery.
Metabolic control analysis enabled the improvement of the L-cysteine production process with Escherichia coli
Authors: Caballero Cerbon Daniel Alejandro , Widmann Jeremias , Weuster-Botz Dirk
Published: January 2024

L-cysteine is an amino acid with relevance to the pharmaceutical, food, feed, and cosmetic industry. The environmental and societal impact of its chemical production has led to the development of more sustainable fermentative L-cysteine production processes with engineered E. coli based on glucose and thiosulfate as sulphur source. Still, most of the published processes show low yields. For the identification of further metabolic engineering targets, engineered E. coli cells were withdrawn from a fed-batch production process, followed by in vivo metabolic control analysis (MCA) based on the data of short-term perturbation experiments, metabolomics (LC–MS), and thermodynamic flux analysis (TFA). In vivo MCA indicated that the activities of the L-cysteine synthases of the cells withdrawn from the production process might be limiting, and we hypothesised that the L-cysteine precursor O-acetylserine (OAS) might be exported from the cells faster than it took to transform OAS into L-cysteine. By increasing the expression of the L-cysteine synthases, either sulfocysteine synthase or L-cysteine synthase, which transform OAS into L-cysteine, an improvement of up to 70% in specific L-cysteine productivity and up to 47% in the final L-cysteine concentration was achieved in standardised fed-batch processes thereby increasing the yield on glucose by more than 85 to 9.2% (w/w).

Key points

• Metabolic control analysis was applied to analyse L-cysteine production with E. coli

• OAS export was faster than its transformation to L-cysteine

• Overexpression of L-cysteine synthases improved L-cysteine productivity and yield
Tuning plasmid DNA amounts for cost-effective transfections of mammalian cells: when less is more
Authors: Carreño Aida , Guerrero-Yagüe Rubén , Casal Enriqueta , Mendoza Rosa , Corchero José Luis
Published: January 2024

Transient gene expression (TGE) in mammalian cells is a well-known approach to the fast expression of recombinant proteins. The human cell line HEK (human embryonic kidney) 293F is widely used in this field, due to its adaptability to grow in suspension to high cell densities in serum-free media, amenability to transfection, and production of recombinant proteins in satisfactory quantities for functional and structural analysis. Amounts of plasmid DNA (pDNA) required in transfections for TGE remain high (usually 1 µg pDNA/mL, or even higher), representing a noticeable proportion of the overall cost. Thus, there is an economic need to reduce amounts of coding pDNA in TGE processes. In this work, amounts of both pDNA and transfecting agent used for TGE in HEK 293F cells have been explored in order to reduce them without compromising (or even improving) the productivity of the process in terms of protein yield. In our hands, minimal polyethyleneimine (PEI) cytotoxicity and optimum protein yields were obtained when transfecting at 0.5 µg pDNA/mL (equal to 0.5 µg pDNA/million cells) and a DNA-to-PEI ratio of 1:3, a trend confirmed for several unrelated recombinant proteins. Thus, carefully tuning pDNA and transfecting agent amounts not only reduces the economic costs but also results in higher recombinant protein yields. These results surely have a direct application and interest for the biopharmaceutical industry, always concerned in increasing productivity while decreasing economic costs.

Key points

• Mammalian cells are widely used to produce recombinant proteins in short times.

• Tuning DNA and transfecting agent are of great interest to optimize economic costs.

• Reducing DNA and transfecting agent amounts result in higher protein yields.

Graphical Abstract
Phase I study of the anti-TIGIT antibody tiragolumab in combination with atezolizumab in Japanese patients with advanced or metastatic solid tumors
Authors: Yamamoto Noboru , Koyama Takafumi , Sato Jun , Yoshida Tatsuya , Sudo Kazuki , Iwasa Satoru , Kondo Shunsuke , Yonemori Kan , Kawasaki Atsuko , Satake Kyoko , Shibata Shoyo , Shimizu Toshio
Published: January 2024

Purpose

Tiragolumab is a monoclonal antibody that binds to the inhibitory immune checkpoint TIGIT (T-cell immunoreceptor with Ig and ITIM domains). In early phase clinical trials, tiragolumab in combination with the programmed death-ligand 1-inhibitor atezolizumab was well tolerated and has demonstrated preliminary anti-tumor activity in patients with advanced/metastatic solid tumors. We report the results of a phase I study of tiragolumab plus atezolizumab in Japanese patients (jRCT2080224926).

Methods

Japanese patients ≥ 20 years old received tiragolumab (600 mg) and atezolizumab (1200 mg) intravenously every 21 days until unacceptable toxicity or disease progression. Primary endpoints were safety and pharmacokinetic (PK) parameters of tiragolumab plus atezolizumab. Secondary endpoints were anti-tumor activity.

Results

Three patients were enrolled with diagnoses of non-small cell lung cancer, pancreatic cancer, and cholangiocarcinoma. No dose-limiting toxicities were observed. Two patients experienced treatment-related adverse events (AEs) of any grade. There were no grade ≥ 3 AEs, serious AEs, AEs leading to discontinuation, modification or withdrawal of any study drug, or AEs leading to death. At cycle 1, mean PK parameters of tiragolumab were as follows: Cmax 217 μg/mL; Cmin 54.9 μg/mL; area under the concentration–time curve from 0 to the last measurable concentration, 2000 μg·day/mL; t1/2, 17.6 days. Best overall response was stable disease in two patients.

Conclusion

Tiragolumab plus atezolizumab was well tolerated in Japanese patients with advanced/metastatic solid tumors, and no differences in tiragolumab PK characteristics were noted between Japanese patients enrolled in this study, and non-Japanese patients enrolled in a global phase Ia/Ib study. These results may support the inclusion of Japanese patients in ongoing global phase III clinical trials.

Trial registration number

jRCT2080224926.
CSF and venous blood flow from childhood to adulthood studied by real-time phase-contrast MRI
Authors: Sahoo Prativa , Kollmeier Jost M. , Wenkel Nora , Badura Simon , Gärtner Jutta , Frahm Jens , Dreha-Kulaczewski Steffi
Published: January 2024

Purpose

In vivo measurements of CSF and venous flow using real-time phase-contrast (RT-PC) MRI facilitate new insights into the dynamics and physiology of both fluid systems. In clinical practice, however, use of RT-PC MRI is still limited. Because many forms of hydrocephalus manifest in infancy and childhood, it is a prerequisite to investigate normal flow parameters during this period to assess pathologies of CSF circulation. This study aims to establish reference values of CSF and venous flow in healthy subjects using RT-PC MRI and to determine their age dependency.

Methods

RT-PC MRI was performed in 44 healthy volunteers (20 females, age 5–40 years). CSF flow was quantified at the aqueduct (Aqd), cervical (C3) and lumbar (L3) spinal levels. Venous flow measurements comprised epidural veins, internal jugular veins and inferior vena cava. Parameters analyzed were peak velocity, net flow, pulsatility, and area of region of interest (ROI). Statistical tests: linear regression, student's t-test and analysis of variance (ANOVA).

Results

In adults volunteers, no significant changes in flow parameters were observed. In contrast, pediatric subjects exhibited a significant age-dependent decrease of CSF net flow and pulsatility in Aqd, C3 and L3. Several venous flow parameters decreased significantly over age at C3 and changed more variably at L3.

Conclusion

Flow parameters varies depending on anatomical location and age. We established changes of brain and spinal fluid dynamics over an age range from 5–40 years. The application of RT-PC MRI in clinical care may improve our understanding of CSF flow pathology in individual patients.
Dysphagia Management in the Emergency Department: Using Concept Mapping to Identify Actionable Change to Improve Services
Authors: Lal Pranika B. , Ward Elizabeth C. , Wishart Laurelie R. , Foley Jasmine , Schwarz Maria , Seabrook Marnie , O’Donnell Carolann , Coccetti Anne
Published: January 2024

Background

Integrated speech-language pathology (SLP) services within the emergency department (ED) may facilitate timely dysphagia management. However, there are multiple patient and logistical factors specific to the ED that challenge the delivery of optimal dysphagia referral and management practices within this setting. The aim of the current study was to engage a stakeholder group to identify prioritised, actionable goals that could help enhance dysphagia management within the ED.

Methods and Procedures

Applying concept mapping methodology, 16 ED stakeholders from SLP, medical, nursing, and leadership participated in semi-structured interviews to develop action statements which were sorted and ranked for importance and changeability. Multidimensional scaling and hierarchical cluster analysis were used to organise data in clusters with unifying themes before statements were ranked by importance and changeability.

Outcomes and Results

Stakeholders identified 53 unique statements, grouped into 8 clusters. Review of the 8 clusters identified 3 overarching aspects for change: (a) Improving processes related to identification and referral of patients as well as communication; (b) Teamwork and collaboration amongst the ED multidisciplinary team and SLP; and (c) Improving staffing and access to training resources for SLP and nursing teams.

Seventeen statements were within the Go-zone rated highest for importance and changeability) with the highest rated statement being: Clear documentation by SLP re: recommendations.

Conclusion

The current data identified multiple aspects of service provision that require change to facilitate improved dysphagia referral and management services in the ED. Collaborative actions are required by both SLP and the ED multidisciplinary team to help optimise dysphagia services.
Enhancing crop recommendation systems with explainable artificial intelligence: a study on agricultural decision-making
Authors: Shams Mahmoud Y. , Gamel Samah A. , Talaat Fatma M.
Published: January 2024

Crop Recommendation Systems are invaluable tools for farmers, assisting them in making informed decisions about crop selection to optimize yields. These systems leverage a wealth of data, including soil characteristics, historical crop performance, and prevailing weather patterns, to provide personalized recommendations. In response to the growing demand for transparency and interpretability in agricultural decision-making, this study introduces XAI-CROP an innovative algorithm that harnesses eXplainable artificial intelligence (XAI) principles. The fundamental objective of XAI-CROP is to empower farmers with comprehensible insights into the recommendation process, surpassing the opaque nature of conventional machine learning models. The study rigorously compares XAI-CROP with prominent machine learning models, including Gradient Boosting (GB), Decision Tree (DT), Random Forest (RF), Gaussian Naïve Bayes (GNB), and Multimodal Naïve Bayes (MNB). Performance evaluation employs three essential metrics: Mean Squared Error (MSE), Mean Absolute Error (MAE), and R-squared (R2). The empirical results unequivocally establish the superior performance of XAI-CROP. It achieves an impressively low MSE of 0.9412, indicating highly accurate crop yield predictions. Moreover, with an MAE of 0.9874, XAI-CROP consistently maintains errors below the critical threshold of 1, reinforcing its reliability. The robust R2 value of 0.94152 underscores XAI-CROP's ability to explain 94.15% of the data's variability, highlighting its interpretability and explanatory power.
MXene-based electrochemical devices applied for healthcare applications
Authors: Lorencova Lenka , Kasak Peter , Kosutova Natalia , Jerigova Monika , Noskovicova Eva , Vikartovska Alica , Barath Marek , Farkas Pavol , Tkac Jan
Published: January 2024

The initial part of the review provides an extensive overview about MXenes as novel and exciting 2D nanomaterials describing their basic physico-chemical features, methods of their synthesis, and possible interfacial modifications and techniques, which could be applied to the characterization of MXenes. Unique physico-chemical parameters of MXenes make them attractive for many practical applications, which are shortly discussed. Use of MXenes for healthcare applications is a hot scientific discipline which is discussed in detail. The article focuses on determination of low molecular weight analytes (metabolites), high molecular weight analytes (DNA/RNA and proteins), or even cells, exosomes, and viruses detected using electrochemical sensors and biosensors. Separate chapters are provided to show the potential of MXene-based devices for determination of cancer biomarkers and as wearable sensors and biosensors for monitoring of a wide range of human activities.

Graphical Abstract