bluuebunny/crossref_metadata_2025 huggingface dataset:
In vitro antimicrobial and antibiofilm activity of phage cocktail against Mammaliicoccus sciuri, a causative agent of bovine mastitis
Authors: Shahana Shirin Puthiya Maliyekkal , Chandran Archana , Surabhi Pathiyarathvalappill Subrahmanian , Rathish Ramachandran Latha , Rahila Mundakka Paramban
Published: August 2024

In this research paper the in vitro antimicrobial and antibiofilm activity of phage cocktail against the coagulase negative Mammaliicoccus sciuri was investigated. Three M. sciuri isolates obtained from clinical bovine mastitis samples were characterized and identified by 16S rRNA gene sequencing. Bacteriophages with lytic activity against M. sciuri isolates were isolated from dairy farm effluents. Two typical phages were isolated using standard enrichment and plaque assay techniques, purified by polyethylene glycol precipitation, and morphologically characterized based on shape and size using transmission electron microscopy. This was followed by determination of host range using spot tests and stability to varying temperature, pH and UV treatment. The phage cocktail suppressed bacterial activity within 30 min of exposure. Crystal violet assay showed that the tested phages and their cocktail significantly reduced the biofilm biomass of all three M. sciuri strains compared to the untreated control in vitro within 24 h with a single dosing. Transmission electron micrography of the purified phage particle revealed an icosahedral head and a rigid contractile tail, characteristic of the class Caudoviricetes. The findings open new avenues in phage-based antimicrobial approaches for controlling contagious and teat skin opportunistic bacteria causing bovine mastitis.
Christian Humanitarianism, Violence and the Debate over Empire
Authors: STANLEY BRIAN
Published: August 2024

It may appear odd to write a review article focused on two books that are fundamentally different in intention and scope. The first is a self-conscious attempt by a moral theologian of conservative inclinations to contribute a Christian ethical perspective to the culture wars currently raging on both sides of the Atlantic on empire, race, and slavery. Its author, Nigel Biggar, is the Emeritus Professor of Moral and Pastoral Theology at the University of Oxford. The second book is a collection of papers by imperial and mission historians given at a workshop at the Victoria University of Wellington, New Zealand, in July 2018. Its brief is more limited, namely to explore the professed commitment of nineteenth-century Christian missions to bringing a gospel of peace into contexts that were frequently sites of violence, not least between indigenous peoples and European settlers and other colonial actors. Its geographical remit is limited to Africa and the Pacific. Biggar's book has provoked a predictable storm of criticism, both within the historical academy and beyond it. The Journal of Imperial and Commonwealth History, for example, rapidly published a 15,000–word rebuttal of Biggar's arguments by Alan Lester, Professor of Historical Geography at the University of Sussex, together with an almost equally lengthy reply by Biggar.1 In contrast, Geoffrey Troughton's edited volume, extremely valuable though it undoubtedly is, seems unlikely to attract notice beyond the limited constituencies of professional historians and scholars of mission studies. Although obviously differing in character, these two books, when set in juxtaposition, bring into focus some of the most pertinent issues raised for Christianity by the imperial past and the ambiguous role played within it by Christian missions.
Identity Politics within Kentucky’s Civil Service and the Growth of the Bureaucratic State
Authors: Hood James Larry
Published: August 2024

For five decades now the various levels of government in the United States, through the use of affirmative action and diversity policies, have sought a more racially and gender-wise equitable society with respect to equal employment opportunity. Governments established hiring goals for women and racial minorities. Goals became quotas as state and local governments (and private employers) that were dependent on federal money made certain that goals produced desired results by preferring people based on their race or gender. This article is a case study of how the Commonwealth’s welfare cabinet over two decades ago used long-standing civil service regulations and policies to pursue preferential employment practices while conterminously pursuing greater societal equity by reducing governmental oversight of welfare programs. All this foreshadowed President Biden’s iteration of affirmative action—federal equity directives regarding employment preferences and greater conditions of equality. After the events described herein, Democratic Kentucky transformed itself into a Republican state.
Learning and Knowledge Loss: Returning Antiquities from Fordham University to Italy
Authors: Gill David W. J.
Published: August 2024

In May 2021 a group of 96 classical antiquities was seized from Fordham University where they had formed part of their museum collection. The seizure was directly linked to the investigation by US authorities of objects that had been handled by the dealer Edoardo Almagià. The Fordham material was dominated by objects derived from Italy: Apulian, Campanian, and Paestan figure-decorated pottery; red-on-white ware associated with Crustumerium in Lazio; and Etruscan pottery, architectural terracottas, and terracotta votives. The objects were all donated to Fordham by William D. Walsh and had largely been acquired at auctions or through a narrow group of Manhattan galleries.
A feasibility study on the implementation of head and neck adaptive radiotherapy. A single centre’s experience
Authors: Avgousti Raphaela , Antypas Christos , Armpilia Christina , Simopoulou Foteini , Liakouli Zoi , Karaiskos Pantelis , Kouloulias Vasileios , Zygogianni Anna
Published: August 2024

Introduction:

The purpose of the study is to measure anatomical and dosimetric changes experienced by patients with head and neck cancer undergoing intensity-modulated radiation therapy and evaluate the need for adaptive radiotherapy using predefined relative thresholds as benchmarks.

Methods:

This study involved 31 consecutive patients. Two computed tomography (CT) scans were utilized for initial treatment planning and a midpoint assessment. The study employed rigid registration and contour transfer techniques to apply primary dose calculation to midpoint CT, generating a hybrid plan, and an adaptive plan was generated on the midpoint CT.

Results:

The results revealed statistically significant volume reductions mainly in PTV70, PTV60 and PTV54 volumes. The volume of the parotid glands exhibited volumetric reductions in most of the patients. Hybrid plans demonstrated inferior dose coverage of the tumour regions, and comparisons between hybrid and adaptive plans showed significant variations in the maximum doses.

Conclusions:

Anatomical deviations necessitating a repeat CT scan, along with the application of a new immobilization mask, emerged as a primary rationale for replanning. Indicators that could potentially encompass a breach of 95% dose coverage for 95% of the tumour volume, maximum doses surpassing 50 Gy in the spinal cord and 59 Gy in the brainstem<>, as well as lateral neck displacement exceeding 1cm from the initial position act as benchmarks before implementing a replan.
Seamless Hourly Estimation of Negative Air Ion Concentrations: Integrating Hybrid Stacked Machine Learning Models With Kriging Spatiotemporal Augmentation
Authors: Liang Zhehao , Zeng Zhaoliang , Kada Martin , Luo Yanqing , Kaufhold Lilli , Xu LinSen , Gui Ke , Zhao Yan , Wang Yaqiang
Published: August 2024

Negative Air Ions (NAIs), essential for environmental and human health, facilitate air purification and offer antimicrobial benefits. Our study achieves hourly estimations of NAIs using a machine learning framework, developed from a multi‐layer selection pipeline of over 200 variables, to identify the key determinants critical for adapting to high‐resolution NAIs dynamics. Addressing site sparsity and NAIs volatility, we introduced a hybrid stacking incorporating pseudo sites generated from Kriging Spatiotemporal Augmentation (KSTA) to mitigate spatial overfitting. Our approach, validated in Zhejiang, China, demonstrates exceptional accuracy, achieving R2 values of 0.90 (sample‐based), 0.85 (temporal‐based), and 0.79 (site‐based). This work not only sheds light on NAIs behavior in relation to diurnal shifts, land use, and environmental events, but also integrates a health grading system, enhancing public health strategies through precise air quality assessment.
Light People: Prof. Juejun Hu, exploring the light
Authors: Sun Tingting
Published: August 2024

Editorial

Professor Juejun Hu was admitted by Tsinghua University as top scorer in the science college entrance examination of Fujian Province. After graduating, he went to MIT to pursue further studies, where he continued to excel and became a faculty member. Each step of his journey has been marked by extraordinary achievements, setting a standard that few can match. Today, Prof. Hu is recognized as a leading expert in integrated photonics and optical materials. His pioneering research has not only advanced the frontiers of academia but also made significant impacts on industrial applications. In this interview, we invite you to delve into Prof. Hu’s research world, exploring his unique insights into technological innovation and how he uses the power of science to shape the future.
Perinatal arterial ischemic stroke diagnosed in infants receiving therapeutic hypothermia for hypoxic-ischemic encephalopathy
Authors: Gonzalez Fernando F. , Monsell Sarah E. , Cornet Marie-Coralie , Glass Hannah , Wisnowski Jessica , Mathur Amit , McKinstry Robert , Li Yi , Wu Tai-Wei , Mayock Dennis E. , Heagerty Patrick J. , Juul Sandra E. , Wu Yvonne W.
Published: August 2024

Background

Both perinatal arterial ischemic stroke (PAIS) and hypoxic-ischemic encephalopathy (HIE) can present with neonatal encephalopathy. We hypothesized that among infants undergoing therapeutic hypothermia, presence of PAIS is associated with a higher risk of seizures and a lower risk of persistent encephalopathy after rewarming.

Methods

We studied 473 infants with moderate or severe HIE enrolled in the HEAL Trial who received a brain MRI. We defined PAIS as focal ischemic infarct(s) within an arterial distribution, and HIE pattern of brain injury as central gray, peripheral watershed, or global injury. We compared the risk of seizures (clinically suspected or electrographic), and of an abnormal 5-day Sarnat exam, in infants with and without PAIS.

Results

PAIS was diagnosed in 21(4%) infants, most of whom (16/21, 76%) also had concurrent HIE pattern of brain injury. Infants with PAIS were more likely to have seizures (RR 2.4, CI 2.8–3.3) and persistent moderate or severe encephalopathy on 5-day Sarnat exam (RR 2.5, 95% CI 1.9–3.4).

Conclusion

Among infants undergoing therapeutic hypothermia, PAIS typically occurs with concurrent HIE pattern brain injury. The higher rate of encephalopathy after rewarming in infants with PAIS may be due to the frequent co-existence of PAIS and HIE patterns of injury.
Longitudinal assessment of established risk stratification models in patients with monoclonal gammopathy of undetermined significance
Authors: Zuern Kosima , Hielscher Thomas , Werly Annika , Breitkreutz Iris , Sauer Sandra , Raab Marc S. , Müller-Tidow Carsten , Goldschmidt Hartmut , Mai Elias K.
Published: August 2024

Risk of progression of monoclonal gammopathy of undetermined significance (MGUS) into multiple myeloma and related plasma cell disorders can be determined by three major risk stratification models, namely Mayo2005, Sweden2014, and NCI2019. This retrospective study of 427 patients with MGUS diagnosed according to the 2014 International Myeloma Working Group criteria aimed to describe and analyze the longitudinal applicability of these risk models. In all three models, the majority of patients remained at their baseline risk group, whereas small numbers of patients migrated to a different risk group. Proportions of patients among risk groups remained stable over time (e.g. Mayo2005 model, low-risk group, at baseline: 43%, after 1, 2, 3, 4, 5, and 8 years: 40%, 37%, 37%, 43%, 44%, and 43%). All three risk models reliably distinguished risk of progression at baseline, upon yearly reassessment (e.g. 1 year from diagnosis) and in time-dependent analyses. Upstaging to a high-risk category was associated with an increased risk of progression in all three models (Mayo2005: hazard ratio [HR] = 5.43, 95% confidence interval [95% CI] 1.21–24.39, p = 0.027; Sweden2014: HR = 13.02, 95% CI 5.25–32.28, p < 0.001; NCI2019: HR = 5.85, 95% CI 2.49–13.74, p < 0.001). Our study shows that MGUS risk stratification models can be applied longitudinally to repeatedly determine and improve individual risk of progression. Patient migration to higher risk categories during follow up should prompt more frequent monitoring in clinical routine.
SREBP2 restricts osteoclast differentiation and activity by regulating IRF7 and limits inflammatory bone erosion
Authors: Kim Haemin , Choi In Ah , Umemoto Akio , Bae Seyeon , Kaneko Kaichi , Mizuno Masataka , Giannopoulou Eugenia , Pannellini Tania , Deng Liang , Park-Min Kyung-Hyun
Published: August 2024

Osteoclasts are multinucleated bone-resorbing cells, and their formation is tightly regulated to prevent excessive bone loss. However, the mechanisms by which osteoclast formation is restricted remain incompletely determined. Here, we found that sterol regulatory element binding protein 2 (SREBP2) functions as a negative regulator of osteoclast formation and inflammatory bone loss. Cholesterols and SREBP2, a key transcription factor for cholesterol biosynthesis, increased in the late phase of osteoclastogenesis. The ablation of SREBP2 in myeloid cells resulted in increased in vivo and in vitro osteoclastogenesis, leading to low bone mass. Moreover, deletion of SREBP2 accelerated inflammatory bone destruction in murine inflammatory osteolysis and arthritis models. SREBP2-mediated regulation of osteoclastogenesis is independent of its canonical function in cholesterol biosynthesis but is mediated, in part, by its downstream target, interferon regulatory factor 7 (IRF7). Taken together, our study highlights a previously undescribed role of the SREBP2-IRF7 regulatory circuit as a negative feedback loop in osteoclast differentiation and represents a novel mechanism to restrain pathological bone destruction.
Community assessment of methods to deconvolve cellular composition from bulk gene expression
Authors: White Brian S. , de Reyniès Aurélien , Newman Aaron M. , Waterfall Joshua J. , Lamb Andrew , Petitprez Florent , Lin Yating , Yu Rongshan , Guerrero-Gimenez Martin E. , Domanskyi Sergii , Monaco Gianni , Chung Verena , Banerjee Jineta , Derrick Daniel , Valdeolivas Alberto , Li Haojun , Xiao Xu , Wang Shun , Zheng Frank , Yang Wenxian , Catania Carlos A. , Lang Benjamin J. , Bertus Thomas J. , Piermarocchi Carlo , Caruso Francesca P. , Ceccarelli Michele , Yu Thomas , Guo Xindi , Bletz Julie , Coller John , Maecker Holden , Duault Caroline , Shokoohi Vida , Patel Shailja , Liliental Joanna E. , Simon Stockard ,   Tumor Deconvolution DREAM Challenge consortium, de Reyniès Aurélien , Jain Aashi , Mishra Shreya , Kumar Vibhor , Peng Jiajie , Han Lu , Otazu Gonzalo H. , Meadows Austin , Danaher Patrick J. , Jaakkola Maria K. , Elo Laura L. , Racle Julien , Gfeller David , Livne Dani , Efroni Sol , Snir Tom , Cast Oliver M. , Miller Martin L. , Couturier Dominique-Laurent , Chang Wennan , Cao Sha , Zhang Chi , Otto Dominik J. , Reiche Kristin , Kämpf Christoph , Rade Michael , Schimmelpfennig Carolin , Kreuz Markus , Scholz Alexander , Saez-Rodriguez Julio , Heiser Laura M. , Guinney Justin , Gentles Andrew J.
Published: August 2024

We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.
Certified algorithms for equilibrium states of local quantum Hamiltonians
Authors: Fawzi Hamza , Fawzi Omar , Scalet Samuel O.
Published: August 2024

Predicting observables in equilibrium states is a central yet notoriously hard question in quantum many-body systems. In the physically relevant thermodynamic limit, certain mathematical formulations of this task have even been shown to result in undecidable problems. Using a finite-size scaling of algorithms devised for finite systems often fails due to the lack of certified convergence bounds for this limit. In this work, we design certified algorithms for computing expectation values of observables in the equilibrium states of local quantum Hamiltonians, both at zero and positive temperature. Importantly, our algorithms output rigorous lower and upper bounds on these values. This allows us to show that expectation values of local observables can be approximated in finite time, contrasting related undecidability results. When the Hamiltonian is commuting on a 2-dimensional lattice, we prove fast convergence of the hierarchy at high temperature and as a result for a desired precision ε, local observables can be approximated by a convex optimization program of quasi-polynomial size in 1/ε.
Damage-programmable design of metamaterials achieving crack-resisting mechanisms seen in nature
Authors: Gao Zhenyang , Zhang Xiaolin , Wu Yi , Pham Minh-Son , Lu Yang , Xia Cunjuan , Wang Haowei , Wang Hongze
Published: August 2024

The fracture behaviour of artificial metamaterials often leads to catastrophic failures with limited resistance to crack propagation. In contrast, natural materials such as bones and ceramics possess microstructures that give rise to spatially controllable crack path and toughened material resistance to crack advances. This study presents an approach that is inspired by nature’s strengthening mechanisms to develop a systematic design method enabling damage-programmable metamaterials with engineerable microfibers in the cells that can spatially program the micro-scale crack behaviour. Machine learning is applied to provide an effective design engine that accelerate the generation of damage-programmable cells that offer advanced toughening functionality such as crack bowing, crack deflection, and shielding seen in natural materials; and are optimised for a given programming of crack path. This paper shows that such toughening features effectively enable crack-resisting mechanisms on the basis of the crack tip interactions, crack shielding, crack bridging and synergistic combinations of these mechanisms, increasing up to 1,235% absorbed fracture energy in comparison to conventional metamaterials. The proposed approach can have broad implications in the design of damage-tolerant materials, and lightweight engineering systems where significant fracture resistances or highly programmable damages for high performances are sought after.
Why East Asian monsoon anomalies are more robust in post El Niño than in post La Niña summers
Authors: Zhang Pengcheng , Xie Shang-Ping , Kosaka Yu , Lutsko Nicholas J. , Okumura Yuko M. , Miyamoto Ayumu
Published: August 2024

The East Asian summer monsoon (EASM) supplies vital rainfall for over one billion people. El Niño-Southern Oscillation (ENSO) markedly affects the EASM, but its impacts are more robust following El Niño than La Niña. Here, we show that this asymmetry arises from the asymmetry in ENSO evolution: though most El Niño events last for one year, La Niña events often persist for 2-3 years. In the summers between consecutive La Niña events, the concurrent La Niña opposes the delayed effect of the preceding winter La Niña on the EASM, causing a reduction in the magnitude and coherence of climate anomalies. Results from a large ensemble climate model experiment corroborate and strengthen the observational analysis with an order of magnitude increase in sample size. The apparent asymmetry in the impacts of the ENSO on the EASM can be reduced by considering the concurrent ENSO, in addition to the ENSO state in the preceding winter. This has important implications for seasonal climate forecasts.
Pharmacological investigation of new niclosamide-based isatin hybrids as antiproliferative, antioxidant, and apoptosis inducers
Authors: Omran Mervat M. , Kamal Mona M. , Ammar Yousry A. , Abusaif Moustafa S. , Ismail Magda M. F. , Mansour Heba H.
Published: August 2024

A group of Niclosamide-linked isatin hybrids (Xo, X1, and X2) was created and examined using IR, 1HNMR, 13C NMR, and mass spectrometry. These hybrids' cytotoxicity, antioxidant, cell cycle analysis, and apoptosis-inducing capabilities were identified. Using the SRB assay, their cytotoxicity against the human HCT-116, MCF-7, and HEPG-2 cancer cell lines, as well as VERO (African Green Monkey Kidney), was evaluated. Compound X1 was the most effective compound. In HCT-116 cells, compound X1 produced cell cycle arrest in the G1 phase, promoted cell death, and induced apoptosis through mitochondrial membrane potential breakdown in comparison to niclosamide and the control. Niclosamide and compound X1 reduced reactive oxygen species generation and modulated the gene expression of BAX, Bcl-2, Bcl-xL, and PAR-4 in comparison to the control. Docking modeling indicated their probable binding modalities with the XIAP BIR2 domain, which selectively binds caspase-3/7, and highlighted their structural drivers of activity for further optimization investigations. Computational in silico modeling of the new hybrids revealed that they presented acceptable physicochemical values as well as drug-like characteristics, which may introduce them as drug-like candidates. The study proved that compound X1 might be a novel candidate for the development of anticancer agents as it presents antiproliferative activity mediated by apoptosis.
Copper supported Dowex50WX8 resin utilized for the elimination of ammonia and its sustainable application for the degradation of dyes in wastewater
Authors: Khamis Mohamed M. , Elsherbiny Abeer S. , Salem Ibrahim A. , El-Ghobashy Marwa A.
Published: August 2024

To obtain high efficient elimination of ammonia (NH4+) from wastewater, Cu(II), Ni(II), and Co(II)) were loaded on Dowex-50WX8 resin (D-H) and studied their removal efficiency towards NH4+ from aqueous solutions. The adsorption capacity of Cu(II)-loaded on D-H (D-Cu2+) towards NH4+ (qe = 95.58 mg/g) was the highest one compared with that of D-Ni2+ (qe = 57.29 mg/g) and D-Co2+ (qe = 43.43 mg/g). Detailed studies focused on the removal of NH4+ utilizing D-Cu2+ were accomplished under various experimental conditions. The pseudo-second-order kinetic model fitted well the adsorption data of NH4+ on D-Cu2+. The non-linear Langmuir model was the best model for the adsorption process, producing a maximum equilibrium adsorption capacity (qmax = 280.9 mg/g) at pH = 8.4, and 303 K in less than 20 min. The adsorption of NH4+ onto D-Cu2+ was an exothermic and spontaneous process. In a sustainable step, the resulting D-Cu(II)-ammine composite from the NH4+ adsorption process displayed excellent catalytic activity for the degradation of aniline blue (AB) and methyl violet 2B (MV 2B) dyes utilizing H2O2 as an eco-friendly oxidant.
Formulation of a stable diesel microemulsion using eco-friendly ionic liquids and investigation of particle size and fuel properties as an alternative fuel
Authors: El Nagy H. A. , Abd El-Aziz Mohamed Mahmoud
Published: August 2024

Ecofriendly ionic liquids (ILs) were synthesized through amidation of ricinoleic acid, the main fatty acid in castor oil, followed by a quaternization reaction to solubilize ethanol in IL/diesel blends at different ratios. As a result, stable and highly renewable, low viscous microemulsion biofuels with high oxygen content were prepared. The prepared fuel samples combine the advantages of green ionic liquids and microemulsion properties. The chemical structures of ILs were confirmed with the aid of NMR and FTIR spectroscopy. DLS analysis revealed that the ethanol particles ranged in size from 8 to 18.1 nm in all samples. As ILs ratios decrease in microemulsion from 37 to 69%, the ethanol particle sizes increase from 10 to 25%. Ethanol shows good solubilization in diesel and IL-1 is more effective than IL-2 in ethanol solubilization at low percentages of ethanol due to more oxygen atoms besides three hydroxyl groups. The ternary phase diagram indicated that the microemulsion area in the case of using IL-1 is larger than that of IL-2. The fuel properties of the prepared microemulsions are nearly close to those of neat diesel and fall within the permitted range of ASTM D975. The viscosity and density values at low ratios of ILs are found to be very close to the values of the neat diesel at different temperatures. The prepared samples show a slight decrease in cetane number and heating value compared to diesel. However, they have improved flash points, cloud points, sulfur content, and acid value. The particle sizes were checked every week and the prepared samples showed high stability with the aid of the synthesized ILs. Moreover, the prepared microemulsions stayed in a transparent appearance for more than a year and no phase separation was observed.
Adaptively triggered comparisons enhance perceptual category learning: evidence from face learning
Authors: Jacoby Victoria L. , Massey Christine M. , Kellman Philip J.
Published: August 2024

Categorical learning is important and often challenging in both specialized domains, such as medical image interpretation, and commonplace ones, such as face recognition. Research has shown that comparing items from different categories can enhance the learning of perceptual classifications, particularly when those categories appear highly similar. Here, we developed and tested novel adaptively triggered comparisons (ATCs), in which errors produced during interactive learning dynamically prompted the presentation of active comparison trials. In a facial identity paradigm, undergraduate participants learned to recognize and name varying views of 22 unknown people. In Experiment 1, single-item classification trials were compared to a condition in which ATC trials were generated whenever a participant repeatedly confused two faces. Comparison trials required discrimination between simultaneously presented exemplars from the confused categories. In Experiment 2, an ATC condition was compared to a non-adaptive comparison condition. Participants learned to accuracy and speed criteria, and completed immediate and delayed posttests. ATCs substantially enhanced learning efficiency in both experiments. These studies, using a novel adaptive procedure guided by each learner’s performance, show that adaptively triggered comparisons improve category learning.
Accurate low and high grade glioma classification using free water eliminated diffusion tensor metrics and ensemble machine learning
Authors: Vidyadharan Sreejith , Rao B. V. V. S. N. Prabhakar , Yogeeswari P. , Kesavadas C. , Rajagopalan Venkateswaran
Published: August 2024

Glioma, a predominant type of brain tumor, can be fatal. This necessitates an early diagnosis and effective treatment strategies. Current diagnosis is based on biopsy, prompting the need for non invasive neuroimaging alternatives. Diffusion tensor imaging (DTI) is a promising method for studying the pathophysiological impact of tumors on white matter (WM) tissue. Single-shell DTI studies in brain glioma patients have not accounted for free water (FW) contamination due to tumors. This study aimed to (a) assess the efficacy of a two-compartment DTI model that accounts for FW contamination and (b) identify DTI-based biomarkers to classify low-grade glioma (LGG) and high-grade glioma (HGG) patients. DTI data from 86 patients (LGG n = 39, HGG n = 47) were obtained using a routine clinical imaging protocol. DTI metrics of tumorous regions and normal-appearing white matter (NAWM) were evaluated. Advanced stacked-based ensemble learning was employed to classify LGG and HGG patients using both single- and two-compartment DTI model measures. The DTI metrics of the two-compartment model outperformed those of the standard single-compartment DTI model in terms of sensitivity, specificity, and area under the curve of receiver operating characteristic (AUC-ROC) score in classifying LGG and HGG patients. Four features (out of 16 features), namely fractional anisotropy (FA) of the edema and core region and FA and mean diffusivity of the NAWM region, showed superior performance (sensitivity = 92%, specificity = 90%, and AUC-ROC = 90%) in classifying LGG and HGG. This demonstrates that both tumorous and NAWM regions may be differentially affected in LGG and HGG patients. Our results demonstrate the significance of using a two-compartment DTI model that accounts for FW contamination by improving diagnostic accuracy. This improvement may eventually aid in planning treatment strategies for glioma patients.
How users make online privacy decisions in work and personal contexts of use
Authors: Klütsch Jennifer , Böffel Christian , Abraham Lukas , Mooser Janina , Thüs Dominik , Tawanger Parwana , von Salm-Hoogstraeten Sophia , Schlittmeier Sabine J.
Published: August 2024

With the rising usage of contactless work options since COVID-19, users increasingly share their personal data in digital tools at work. Using an experimental online vignette study (N = 93), we examined users’ willingness to use a video conferencing tool, while systematically varying the context of use (personal vs. low trustworthiness work vs. high trustworthiness work) and the type of information shared (low vs. medium vs. high sensitivity). We also assessed users’ perceived responsibility in work and personal contexts of use and their self-assessed digital competence. Our results highlight employer trustworthiness as an important factor in the willingness to use a third-party video conferencing tool, with increased willingness to use these tools in work contexts of use with high trustworthiness compared to those with low trustworthiness. This effect seems to be reduced when the data to be shared is of high sensitivity, compared to medium and low sensitivity data. Furthermore, despite reduced responsibility for data protection in work compared to personal contexts of use, the willingness to use a video conferencing tool did not decrease between trustworthy work and personal contexts of use. We discuss our findings and their methodological implications for future research and derive implications for privacy decisions at work.
Active learning-based machine learning approach for enhancing environmental sustainability in green building energy consumption
Authors: Mahmood Shahid , Sun Huaping , Ali Alhussan Amel , Iqbal Asifa , El-kenawy El-Sayed M.
Published: August 2024

Green building (GB) techniques are essential for reducing energy waste in the construction sector, which accounts for almost 40% of global energy consumption. Despite their importance, challenges such as occupant behavior and energy management gaps often result in GBs consuming up to 2.5 times more energy than intended. To address this, Building Automation Systems (BAS) play a crucial role in enhancing energy efficiency. This research develops a predictive model for GB design using machine learning to minimize energy consumption and improve indoor sustainability. The dataset is utilized to predict cooling and heating individually, with data visualization by graphically illustrating dataset features and preprocessing through Z-Score normalization and dataset splitting. The proposed model, based on active learning and utilizing ML regressors such as Random Forest (RF), Decision Tree (DT), Gradient Boosting (GB), Extreme Gradient Boosting (XGBoost), CatBoost (CB), Light Gradient Boosting Machine (LGBM), K-Nearest Neighbor (KNN), and Logistic Regressor (LR), shows significant performance improvements. The CBR-AL model achieves impressive results with values of 0.9975 for cooling (Y1) and 0.9883 for heating (Y2), indicating a high level of accuracy. The model’s success in reducing energy consumption and improving sustainability has potential ripple effects, including substantial cost savings, reduced carbon footprints, and improved operational efficiency in green buildings. This approach not only enhances environmental sustainability but also sets a benchmark for future advancements in predictive modelling for energy management.
COVID-19 severity detection using chest X-ray segmentation and deep learning
Authors: Singh Tinku , Mishra Suryanshi , Kalra Riya , Satakshi  , Kumar Manish , Kim Taehong
Published: August 2024

COVID-19 has resulted in a significant global impact on health, the economy, education, and daily life. The disease can range from mild to severe, with individuals over 65 or those with underlying medical conditions being more susceptible to severe illness. Early testing and isolation are vital due to the virus’s variable incubation period. Chest radiographs (CXR) have gained importance as a diagnostic tool due to their efficiency and reduced radiation exposure compared to CT scans. However, the sensitivity of CXR in detecting COVID-19 may be lower. This paper introduces a deep learning framework for accurate COVID-19 classification and severity prediction using CXR images. U-Net is used for lung segmentation, achieving a precision of 0.9924. Classification is performed using a Convulation-capsule network, with high true positive rates of 86% for COVID-19, 93% for pneumonia, and 85% for normal cases. Severity assessment employs ResNet50, VGG-16, and DenseNet201, with DenseNet201 showing superior accuracy. Empirical results, validated with 95% confidence intervals, confirm the framework’s reliability and robustness. This integration of advanced deep learning techniques with radiological imaging enhances early detection and severity assessment, improving patient management and resource allocation in clinical settings.
Low frequency ultrasound elicits broad cortical responses inhibited by ketamine in mice
Authors: Shi Linli , Mastracchio Christina , Saytashev Ilyas , Ye Meijun
Published: August 2024

The neuromodulatory effects of >250 kHz ultrasound have been well-demonstrated, but the impact of lower-frequency ultrasound, which can transmit better through air and the skull, on the brain is unclear. This study investigates the biological impact of 40 kHz pulsed ultrasound on the brain using calcium imaging and electrophysiology in mice. Our findings reveal burst duration-dependent neural responses in somatosensory and auditory cortices, resembling responses to 12 kHz audible tone, in vivo. In vitro brain slice experiments show no neural responses to 300 kPa 40 kHz ultrasound, implying indirect network effects. Ketamine fully blocks neural responses to ultrasound in both cortices but only partially affects 12 kHz audible tone responses in the somatosensory cortex and has no impact on auditory cortex 12 kHz responses. This suggests that low-frequency ultrasound’s cortical effects rely heavily on NMDA receptors and may involve mechanisms beyond indirect auditory cortex activation. This research uncovers potential low-frequency ultrasound effects and mechanisms in the brain, offering a path for future neuromodulation.
Charting sustainable urban development through a systematic review of SDG11 research
Authors: Almulhim Abdulaziz I. , Sharifi Ayyoob , Aina Yusuf A. , Ahmad Shakil , Mora Luca , Filho Walter Leal , Abubakar Ismaila Rimi
Published: August 2024

The Sustainable Development Goal (SDG) 11 underscores the imperative of creating inclusive, safe, resilient and sustainable cities and communities by 2030. Here we employ bibliometric techniques to assess the evolving landscape of SDG11 research. Using a comprehensive dataset of over 21,000 scholarly publications, we investigate publication trends, thematic focus areas, authorship patterns, keyword co-occurrences and citation networks related to SDG11 research. The results reveal a consistent increase in research output, reflecting the growing global interest in urban sustainability studies. We identify influential authors, organizations and countries shaping the research landscape, highlighting existing global collaborative networks and emerging research hubs. Core thematic areas emphasize critical topics and interdisciplinary connections. Citation networks underscore the impacts of disseminating research outputs, including seminal works. This study offers insights for policymakers, academics and practitioners to align their collective efforts toward sustainable, inclusive and climate-resilient urban development. Moreover, it advances SDG11 by noting opportunities for further research, knowledge dissemination and international collaboration.
STIC2 selectively binds ribosome-nascent chain complexes in the cotranslational sorting of Arabidopsis thylakoid proteins
Authors: Stolle Dominique S , Osterhoff Lena , Treimer Paul , Lambertz Jan , Karstens Marie , Keller Jakob-Maximilian , Gerlach Ines , Bischoff Annika , Dünschede Beatrix , Rödiger Anja , Herrmann Christian , Baginsky Sacha , Hofmann Eckhard , Zoschke Reimo , Armbruster Ute , Nowaczyk Marc M , Schünemann Danja
Published: August 2024

Chloroplast-encoded multi-span thylakoid membrane proteins are crucial for photosynthetic complexes, yet the coordination of their biogenesis remains poorly understood. To identify factors that specifically support the cotranslational biogenesis of the reaction center protein D1 of photosystem (PS) II, we generated and affinity-purified stalled ribosome-nascent chain complexes (RNCs) bearing D1 nascent chains. Stalled RNCs translating the soluble ribosomal subunit uS2c were used for comparison. Quantitative tandem-mass spectrometry of the purified RNCs identified around 140 proteins specifically associated with D1 RNCs, mainly involved in protein and cofactor biogenesis, including chlorophyll biosynthesis, and other metabolic pathways. Functional analysis of STIC2, a newly identified D1 RNC interactor, revealed its cooperation with chloroplast protein SRP54 in the de novo biogenesis and repair of D1, and potentially other cotranslationally-targeted reaction center subunits of PSII and PSI. The primary binding interface between STIC2 and the thylakoid insertase Alb3 and its homolog Alb4 was mapped to STIC2’s β-sheet region, and the conserved Motif III in the C-terminal regions of Alb3/4.
Protein- and Lipid-based Bioactive Compounds
Authors: Shinali Tharushi S. , Yu Jie , Qu Ruijing , Shang Nan
Published: August 2024

Natural bioactive compounds have emerged as important biomolecules that promote good health. Much attention to scientific research has recently been paid to developing food-based formulations to manage and prevent chronic diseases. In this context, protein- and lipid-based biomolecules play a key role. The roles of these bioactive protein and lipid components include antimicrobial, anticancer, anti-inflammatory, and many other specific biological activities. Despite the health-promoting properties, these compounds could be used in many other fields due to their diverse functionalities. Significant aspects of bioactive protein and lipid materials, including their primary sources, production technologies, different biofunctionalities toward their applications, and various applications in food, packaging, biotechnological, and biomedical sectors, will be discussed in this chapter.
Functional Protein-based Biomaterials
Authors: Ali M. Azam , Gould Maree , Bhowmik Shuva
Published: August 2024

Functional protein-based biomaterials have been gaining more attention in recent years due to their biophysical and biochemical attributes over synthetic materials, including tunability, biocompatibility, modifications and purifications, scalability, biodegradability, low immunogenicity, and nontoxicity or minimal toxicity. Activities of most of the protein and/or protein-derived biomaterials depend on their structure, including tertiary structure or above, functions, and properties. Additionally, protein-based biomaterials are also limited by their poor chemical and physical properties; therefore, tailoring or modifications of biomaterials from functional proteins are necessary. In this regard, introducing chemical motifs, composite materials, and crosslinking techniques has been shown to enhance the functional properties of protein biomaterials, resulting in the generation of macro-to-nano constructs, including film, sponge, fibre, scaffold, nanoparticles, and hydrogel. These improved biomaterials are used in effective drug delivery systems, tissue repair and regeneration, sustainable crop production in agriculture sectors, functional food fortification, and biodegradable food packaging. This book chapter addresses an update on information on the multi-hierarchical structure of functional proteins, types of proteins (animal-, dairy-, plant-, and marine-sourced protein biomaterials), modification methods, protein derivatives, nanostructure, and their sustainable applications in different industrial sectors.
Advances in Protein- and Lipid-based Materials for Cosmetic Applications
Authors: Iqbal Muniba , Farooq Sadia , Hussain Ajaz
Published: August 2024

Proteins and lipids are very large natural molecules that possess many attributes for skin care and hair growth. Therefore, these molecules and the materials derived from them play a potential role in the aesthetic aspects of our society. In this context, the present chapter focuses on the role that protein- and lipid-based materials play in the field of cosmetics. The sources of lipids and proteins used in cosmetics have also been highlighted, keeping in view the role of nanoscale protein/lipid materials in the field of cosmetics. Moreover, recent advancements in the field have also been shown, which may be equally beneficial for readers who love to use natural materials as beauty ingredients and for people associated with the cosmetic industry.
Quantification and visual inspection of adipic dihydrazide in textile using a xanthylium-based ratiometric fluorescent probe
Authors: Wang Sifan , Wu Weijie , Lv Jiaqi , Li Zicheng , Huang Wencai
Published: August 2024

The visual inspection of ADH residue in textile was easily achieved by spraying a solution of probe SH-Py in DMSO.
Novel point-of-care rapid detection of monkeypox virus
Authors: Chen Hui , Guan Yuhong , Zhang Xinyu , Chen Yuting , Li Song , Deng Yan , Wu Yanqi
Published: August 2024

Monkeypox, a viral zoonotic disease caused by MPXV, has emerged as a significant global health concern since the first outbreak outside Africa in 2003.
Improved ZnWO4@NiCo2O4 core–shell nanosheet arrays with regulatory interfaces and electronic redistribution
Authors: Xu Song-Lin , Wang Shi-Rong , Ma Dongmei , Li Rui-Yu , Xiang Jun , Zhao Rong-Da , Wu Fu-Fa
Published: August 2024

ZnWO4@NiCo2O4 core-shell nanosheet array composites are synthesized on nickel foam via a two-step hydrothermal method. The samples show a specific capacitance of 875 C g−1 at 1 A g−1, and also maintain 81.1% capacitance after 10 000 cycles.
Substituted fullerenes as a promising capping ligand towards stabilization of exohedral Dy(iii) based single-ion magnets: a theoretical study
Authors: Kumari Kusum , Singh Saurabh Kumar
Published: August 2024

Using state-of-the-art computational methods, we have thoroughly investigated the coordination ability of substituted fullerene {C55X5}− (X = CCH3/B/N) towards stabilizing novel Dy(iii) exohedral complexes showcasing giant barrier height >2200 K.
Nickel(ii) complexes with 14-membered bis-thiosemicarbazide and bis-isothiosemicarbazide ligands: synthesis, characterization and catalysis of oxygen evolution reaction
Authors: Besleaga Iuliana , Fesenko Anastasia A. , Paul Anup , Šljukić Biljana , Rapta Peter , Pombeiro Armando J. L. , Shutalev Anatoly D. , Arion Vladimir B.
Published: August 2024

The Ni(ii) complexes reported in this work show high performance for OER and are suggested as promising candidates for alkaline water electrolysis.
Triggering the electronic microenvironment of extraordinary nitrogen-bridged atomic iron coordinated with in-plane nitrogen by manipulating phase-reconfigured 2D vanadium nitride MXenes toward invigorated lithium–sulfur batteries
Authors: Zhang Xinlu , Bai Xuexiu , Wei Chuanliang , Wang Zhengran , Xi Baojuan , Xiong Shenglin , Feng Jinkui
Published: August 2024

The electronic microenvironment of isolated Fe in FeN4-O-NC-VN was modulated by axial-bridged nitrogen-doped carbon for bidirectional lithium–sulfur batteries.
Neltuma nigracotyledon and seed flour: nutritional, phytochemical, and techno-functional characterization and nutraceutic potential of polyphenolic enriched extract
Authors: Cattaneo Florencia , Rodríguez Ivana Fabiola , Zampini Iris Catiana , Burgos-Edwards Alberto , Schmeda-Hirschmann Guillermo , Isla María Inés
Published: August 2024

Neltuma nigraseed and cotyledon flours were prepared and characterized.
Raw and heat-treated quinoa protein protects against glucose metabolism disorders in high-fat diet (HFD)-induced mice by reshaping gut microbiota and fecal metabolic profiles
Authors: Dai Zijian , Wang Han , Shen Qun , Hu Yichen , Xue Yong
Published: August 2024

Quinoa protein improved glucose metabolism and protected against alterations in gut microbiota induced by a chronic HFD. In addition, it increased the abundance of beneficial bacteria, followed by an increase in potentially beneficial metabolites.
High-throughput discovery of umami peptides from pork bone and elucidation of their molecular mechanism for umami taste perception
Authors: Gu Yuxiang , Niu Yajie , Zhang Jingcheng , Sun Baoguo , Liu Zunying , Mao Xiangzhao , Zhang Yuyu
Published: August 2024

This study endeavored to high-throughput identify umami peptides from pork bone.
Pioneering the design of S-scheme SnS2/g-C3N4nanocompositesviasonochemical and physical mixing methods for solar degradation of cationic rhodamine B dye
Authors: Alsalme Ali , Hesham Mustafa , Soltan Ayman , Mohammed Nagy N. , Nejm A. Qassim , Messih M. F. Abdel , Hussein Islam A. , Ahmed M. A.
Published: August 2024

A novel S-scheme SnS2/g-C3N4heterojunction with superior charge separation and transport was synthesized sonochemically for the photocatalytic degradation of rhodamine B dye.
Bio-based poly(benzimidazole-co-amide)-derived N, O co-doped carbons as fast-charging anodes for lithium-ion batteries
Authors: Patnaik Kottisa Sumala , Mantripragada Bharat Srimitra , Badam Rajashekar , Higashimine Koichi , Zhong Xianzhu , Kaneko Tatsuo , Matsumi Noriyoshi
Published: August 2024

This works presents a nitrogen and oxygen co-doped carbon obtained from a bio-based polymer as anode active material for fast charging in lithium-ion batteries.
Liposome biodistribution mapping with in vivo X-ray fluorescence imaging
Authors: Saladino Giovanni Marco , Chao Po-Han , Brodin Bertha , Li Shyh-Dar , Hertz Hans Martin
Published: August 2024

X-ray fluorescence imaging tracks liposomes with high resolution and penetration depth. The encapsulated ruthenium(ii) polypyridyl dye enables dual mode imaging.
Catalyst-free reactions of anilines with β-chloroenones: synthesis of α-chloroenaminones and 1,4-benzodiazepines
Authors: Suresh Sundaram , Palla Sowndarya , Chung Dai-Ru , Chien Hung-Sheng , Du Bo-Xun , Shinde Jivan , Kavala Veerababurao , Yao Ching-Fa
Published: August 2024

The direct synthesis of α-chloroenaminones has been described via one-pot atom-economical reactions. The reactions involving o-phenylenediamines delivered 1,4-benzodiazepines as products.