bluuebunny/crossref_metadata_2025 huggingface dataset:
Synthesis of site‐specific Fab‐drug conjugates using ADP‐ribosyl cyclases
Authors: Kim Hyo Sun , Hariri Kimia , Zhang Xiao‐Nan , Chen Liang‐Chieh , Katz Benjamin B. , Pei Hua , Louie Stan G. , Zhang Yong
Published: March 2024

Targeted delivery of small‐molecule drugs via covalent attachments to monoclonal antibodies has proved successful in clinic. For this purpose, full‐length antibodies are mainly used as drug‐carrying vehicles. Despite their flexible conjugation sites and versatile biological activities, intact immunoglobulins with conjugated drugs, which feature relatively large molecular weights, tend to have restricted tissue distribution and penetration and low fractions of payloads. Linking small‐molecule therapeutics to other formats of antibody may lead to conjugates with optimal properties. Here, we designed and synthesized ADP‐ribosyl cyclase‐enabled fragment antigen‐binding (Fab) drug conjugates (ARC‐FDCs) by utilizing CD38 catalytic activity. Through rapidly forming a stable covalent bond with a nicotinamide adenine dinucleotide (NAD+)‐based drug linker at its active site, CD38 genetically fused with Fab mediates robust site‐specific drug conjugations via enzymatic reactions. Generated ARC‐FDCs with defined drug‐to‐Fab ratios display potent and antigen‐dependent cytotoxicity against breast cancer cells. This work demonstrates a new strategy for developing site‐specific FDCs. It may be applicable to different antibody scaffolds for therapeutic conjugations, leading to novel targeted agents.
Engineering diaryl alcohol dehydrogenase KpADH reveals importance of retaining hydration shell in organic solvent tolerance
Authors: Zhang Lu , Dai Wei , Rong Shuo , Schwaneberg Ulrich , Xu Guochao , Ni Ye
Published: March 2024

Alcohol dehydrogenases (ADHs) are synthetically important biocatalysts for the asymmetric synthesis of chiral alcohols. The catalytic performance of ADHs in the presence of organic solvents is often important since most prochiral ketones are highly hydrophobic. Here, the organic solvent tolerance of KpADH from Kluyveromyces polyspora was semi‐rationally evolved. Using tolerant variants obtained, meticulous experiments and computational studies were conducted to explore properties including stability, activity and kinetics in the presence of various organic solvents. Compared with WT, variant V231D exhibited 1.9‐fold improvement in ethanol tolerance, while S237G showed a 6‐fold increase in catalytic efficiency, a higher , as well as 15% higher tolerance in 7.5% (v/v) ethanol. Based on 3 × 100 ns MD simulations, the increased tolerance of V231D and S237G against ethanol may be ascribed to their enhanced ability in retaining water molecules and repelling ethanol molecules. Moreover, 6.3‐fold decreased KM value of V231D toward hydrophilic ketone substrate confirmed its capability of retaining hydration shell. Our results suggest that retaining hydration shell surrounding KpADH is critical for its tolerance to organic solvents, as well as catalytic performance. This study provides useful guidance for engineering organic solvent tolerance of KpADH and other ADHs.
Assessing the mechanism of fast‐cycling cancer‐associated mutations of Rac1 small Rho GTPase
Authors: Parise Angela , Magistrato Alessandra
Published: March 2024

Rho‐GTPases proteins function as molecular switches alternating from an active to an inactive state upon Guanosine triphosphate (GTP) binding and hydrolysis to Guanosine diphosphate (GDP). Among them, Rac subfamily regulates cell dynamics, being overexpressed in distinct cancer types. Notably, these proteins are object of frequent cancer‐associated mutations at Pro29 (P29S, P29L, and P29Q). To assess the impact of these mutations on Rac1 structure and function, we performed extensive all‐atom molecular dynamics simulations on wild‐type (wt) and oncogenic isoforms of this protein in GDP‐ and GTP‐bound states. Our results unprecedentedly elucidate that P29Q/S‐induced structural and dynamical perturbations of Rac1 core domain weaken the binding of the catalytic site Mg2+ ion, and reduce the GDP residence time within protein, enhancing the GDP/GTP exchange rate and Rac1 activity. This broadens our knowledge of the role of cancer‐associated mutations on small GTPases mechanism supplying valuable information for future drug discovery efforts targeting specific Rac1 isoforms.
Construction of a versatile fusion protein for targeted therapy and immunotherapy
Authors: Huang Xiu‐Song , Yang Li‐Ting , Yang Ke , Zhou Hang , Abudureheman Tuersunayi , Zheng Wei‐Wei , Chen Kai‐Ming , Duan Cai‐Wen
Published: March 2024

Antibody (Ab)‐based drugs have been widely used in targeted therapies and immunotherapies, leading to significant improvements in tumor therapy. However, the failure of Ab therapy due to the loss of target antigens or Ab modifications that affect its function limits its application. In this study, we expanded the application of antibodies (Abs) by constructing a fusion protein as a versatile tool for Ab‐based target cell detection, delivery, and therapy. We first constructed a SpaC Catcher (SpaCC for short) fusion protein that included the C domains of Staphylococcal protein A (SpaC) and the SpyCatcher. SpaCC conjugated with SpyTag‐X (S‐X) to form the SpaCC‐S‐X complex, which binds non‐covalently to an Ab to form the Ab‐SpaCC‐S‐X protein complex. The “X” can be a variety of small molecules such as fluoresceins, cell‐penetrating peptide TAT, Monomethyl auristatin E (MMAE), and DNA. We found that Ab‐SpaCC‐S‐FITC(−TAT) could be used for target cell detection and delivery. Besides, we synthesized the Ab‐SpaCC‐SN3‐MMAE complex by linking Ab with MMAE by SpaCC, which improved the cytotoxicity of small molecule toxins. Moreover, we constructed an Ab‐DNA complex by conjugating SpaCC with the aptamer (Ap) and found that Ab‐SpaCC‐SN3‐Ap boosted the tumor‐killing function of T‐cells by retargeting tumor cells. Thus, we developed a multifunctional tool that could be used for targeted therapies and immunotherapies, providing a cheap and convenient novel drug development strategy.
Structural dynamics and functional cooperativity of human NQO1 by ambient temperature serial crystallography and simulations
Authors: Grieco Alice , Boneta Sergio , Gavira José A. , Pey Angel L. , Basu Shibom , Orlans Julien , Sanctis Daniele de , Medina Milagros , Martin‐Garcia Jose Manuel
Published: March 2024

The human NQO1 (hNQO1) is a flavin adenine nucleotide (FAD)‐dependent oxidoreductase that catalyzes the two‐electron reduction of quinones to hydroquinones, being essential for the antioxidant defense system, stabilization of tumor suppressors, and activation of quinone‐based chemotherapeutics. Moreover, it is overexpressed in several tumors, which makes it an attractive cancer drug target. To decipher new structural insights into the flavin reductive half‐reaction of the catalytic mechanism of hNQO1, we have carried serial crystallography experiments at new ID29 beamline of the ESRF to determine, to the best of our knowledge, the first structure of the hNQO1 in complex with NADH. We have also performed molecular dynamics simulations of free hNQO1 and in complex with NADH. This is the first structural evidence that the hNQO1 functional cooperativity is driven by structural communication between the active sites through long‐range propagation of cooperative effects across the hNQO1 structure. Both structural results and MD simulations have supported that the binding of NADH significantly decreases protein dynamics and stabilizes hNQO1 especially at the dimer core and interface. Altogether, these results pave the way for future time‐resolved studies, both at x‐ray free‐electron lasers and synchrotrons, of the dynamics of hNQO1 upon binding to NADH as well as during the FAD cofactor reductive half‐reaction. This knowledge will allow us to reveal unprecedented structural information of the relevance of the dynamics during the catalytic function of hNQO1.
Reengineering of a flavin‐binding fluorescent protein using ProteinMPNN
Authors: Nikolaev Andrey , Kuzmin Alexander , Markeeva Elena , Kuznetsova Elizaveta , Ryzhykau Yury L. , Semenov Oleg , Anuchina Arina , Remeeva Alina , Gushchin Ivan
Published: March 2024

Recent advances in machine learning techniques have led to development of a number of protein design and engineering approaches. One of them, ProteinMPNN, predicts an amino acid sequence that would fold and match user‐defined backbone structure. Its performance was previously tested for proteins composed of standard amino acids, as well as for peptide‐ and protein‐binding proteins. In this short report, we test whether ProteinMPNN can be used to reengineer a non‐proteinaceous ligand‐binding protein, flavin‐based fluorescent protein CagFbFP. We fixed the native backbone conformation and the identity of 20 amino acids interacting with the chromophore (flavin mononucleotide, FMN) while letting ProteinMPNN predict the rest of the sequence. The software package suggested replacing 36–48 out of the remaining 86 amino acids so that the resulting sequences are 55%–66% identical to the original one. The three designs that we tested experimentally displayed different expression levels, yet all were able to bind FMN and displayed fluorescence, thermal stability, and other properties similar to those of CagFbFP. Our results demonstrate that ProteinMPNN can be used to generate diverging unnatural variants of fluorescent proteins, and, more generally, to reengineer proteins without losing their ligand‐binding capabilities.
A guide to prescribing valproate medicines safely
Authors: Molloy Aisling
Published: March 2024

New regulatory changes were introduced in January further restricting the prescription of valproate medicines in patients under 55 years of age due to the significant reproductive risks. This article discusses these changes as well as the other issues to consider to ensure valproate prescribing is as safe as possible, including monitoring for adverse effects and avoiding interactions.
Prescribing in prisons and other secure settings
Authors: Bicknell Marcus , Glover Catherine , Wright Nat
Published: March 2024

Prescribers in prisons and other secure settings play a key role in supporting the well‐being of prisoners. As part of our series on medicines optimisation in people with additional needs, this article discusses the issues healthcare professionals should consider to ensure safe, optimised prescribing for people who are imprisoned.
Voice recognition software and medication errors
Authors: Thompson Angus
Published: March 2024

Voice recognition software is a useful tool for transcribing medical notes but inaccuracies are common, especially when interpreting drug names. Without the outputs being reviewed by a human familiar with drug names, there is an increased risk of confusion and whilst medication errors are never a laughing matter, the outputs can sometimes be a source of mirth.
Supercharged coiled‐coil protein with N‐terminal decahistidine tag boosts siRNA complexation and delivery efficiency of a lipoproteoplex
Authors: Sun Jonathan W. , Thomas Joseph S. , Monkovic Julia M. , Gibson Halle , Nagapurkar Akash , Frezzo Joseph A. , Katyal Priya , Punia Kamia , Mahmoudinobar Farbod , Renfrew P. Douglas , Montclare Jin Kim
Published: March 2024

Short interfering RNA (siRNA) therapeutics have soared in popularity due to their highly selective and potent targeting of faulty genes, providing a non‐palliative approach to address diseases. Despite their potential, effective transfection of siRNA into cells requires the assistance of an accompanying vector. Vectors constructed from non‐viral materials, while offering safer and non‐cytotoxic profiles, often grapple with lackluster loading and delivery efficiencies, necessitating substantial milligram quantities of expensive siRNA to confer the desired downstream effects. We detail the recombinant synthesis of a diverse series of coiled‐coil supercharged protein (CSP) biomaterials systematically designed to investigate the impact of two arginine point mutations (Q39R and N61R) and decahistidine tags on liposomal siRNA delivery. The most efficacious variant, N8, exhibits a twofold increase in its affinity to siRNA and achieves a twofold enhancement in transfection activity with minimal cytotoxicity in vitro. Subsequent analysis unveils the destabilizing effect of the Q39R and N61R supercharging mutations and the incorporation of C‐terminal decahistidine tags on α‐helical secondary structure. Cross‐correlational regression analyses reveal that the amount of helical character in these mutants is key in N8's enhanced siRNA complexation and downstream delivery efficiency.
True‐Red InGaN Light‐Emitting Diodes for Display Applications
Authors: Armitage Robert , Ren Zhongmin , Holmes Mark , Flemish Joseph
Published: March 2024

Red InGaN has attracted much attention recently for micro‐light‐emitting diode (microLED) display applications. However, the consequences of spectral broadening are often overlooked and many of the published spectra do not meet display gamut requirements. Herein, maximizing the red InGaN radiance with a spectrum capable of meeting the digital cinema initiatives‐protocol 3 standard (dominant wavelength of ≈615 nm) is focused on. The maximum radiance for LEDs meeting said requirement is obtained at 20 A cm−2 and corresponds to 4% wall‐plug efficiency (WPE) in large‐area encapsulated devices. The WPE can be increased to 12.5% using epitaxy of lower In concentration driven at 2 A cm−2. Also, data for microLEDs fabricated from similar red InGaN epitaxy are reported. No size dependence of the internal quantum efficiency or spectra is observed down to the smallest sizes studied (≈2 μm). Herein, expertise with red InGaN and nitride tunnel junctions is further leveraged to demonstrate polychromatic microLEDs with independent control of red, green, and blue emission within single pixels of 9 × 12 μm dimensions. These devices are grown in a single growth run on the same sapphire substrate wafer using methods proven in high‐volume epitaxy manufacturing.
Meat consumption and obesity: A climate‐friendly way to reduce health inequalities
Authors: Sares‐Jäske Laura , Tapanainen Heli , Valsta Liisa , Haario Peppi , Männistö Satu , Vaalavuo Maria
Published: March 2024

Background

Climate change, health inequalities and obesity are considerable public health challenges of the 21st century. Red and processed meat (RPM) consumption is associated with an increased risk of obesity and with higher climate impact. At the same time, educational inequalities exist not only in RPM consumption and obesity but also in other health behaviours. Thus, we investigated whether educational inequalities exist in the association between RPM consumption and obesity, while also considering health behaviours (physical activity, vegetable, legume and fruit consumption, alcohol consumption and smoking) as potential confounding and effect modifying factors.

Methods

The FinHealth 2017 Study data, including 4494 participants aged 18–74 years, were used. A validated food frequency questionnaire was employed to determine dietary intake. Height and weight were measured by trained study nurses. Linear and logistic regression models were used.

Results

Odds of obesity increased along with RPM consumption in women (p < 0.001) and men (p < 0.001) and in each educational group regardless of other unfavourable health behaviours. Only in men with basic education were the differences between RPM consumption categories not statistically significant. Compared to those with high education and the lowest RPM consumption, those with basic education and the highest RPM consumption had multiple odds of obesity (odds ratio (95% confidence interval) among women: 7.5 (2.7–20.4); among men: 5.3 (2.5–11.1)).

Conclusion

High RPM consumption appears to be associated with obesity independently of other unfavourable health behaviours or education, yet the odds are higher with basic education. Targeting unhealthy dietary patterns with heavy ecological burden could help reduce both health inequalities and mitigate climate change.
Indirect effects of latent heat of condensation on the simulation of the 2021 catastrophic Henan rainfall event in central China
Authors: Xu Hongxiong , Zhao Dajun , Gao Wenhua , Duan Yihong , Yin Jinfang , Li Ying , Zhou Lingli
Published: March 2024

Cloud‐related latent heat is critical to the development and maintenance of atmospheric circulation. However, it is unclear how sensitive the key large‐scale weather systems of an extreme rainfall event could be to the variation in cloud‐related latent heat. In a companion study, by investigating the indirect effects of different microphysics schemes, we hypothesized that the latent heat of condensation (CT) would play a role in the ability to simulate the extreme rainfall event that took place in Henan Province, central China, on July 19–21, 2021. To examine the proposed hypothesis, the impacts of varying the CT and the collection of cloud water by rainwater (ACW) in the Thompson, WDM6, and Morrison microphysics schemes on the simulation of the southerly flow and its indirect effect on this extreme rainfall case were studied using the Advanced Research Weather Research and Forecasting (ARW‐WRF) model. It was found that directly changing the CT and ACW had significant effects on the southerly flow and precipitation. An increase in CT generally led to a reduced temperature gradient, a smaller pressure gradient, a stronger southerly flow, and a precipitation surge of 32%–50%. Similar outcomes resulted from increasing ACW in the WDM6 scheme, which effectively diminished the cloud mixing ratio, generated higher CT, and consequently intensified the southerly flow and precipitation by 31%. This study confirmed that the accurate simulation of microphysical processes, along with latent heating, is desirable for more realistically reproducing the key weather systems in the simulation of extreme rainfall.
Photonic Non‐Markovianity Identification by Quantum Process Capabilities of Non‐CP Processes
Authors: Hsu Chan , Kao Yu‐Chien , Chen Hong‐Bin , Chen Shih‐Hsuan , Li Che‐Ming
Published: March 2024

A Markovian quantum process can be arbitrarily divided into two or more legitimate completely‐positive (CP) subprocesses. When at least one non‐CP process exists among the divided processes, the dynamics is considered non‐Markovian. However, how to utilize minimum experimental efforts, without examining all process input states and using entanglement resources, to identify or measure non‐Markovianity is still being determined. Herein, a method is proposed to quantify non‐CP processes for identifying and measuring non‐Markovianity without the burden of state optimization and entanglement. This relies on the non‐CP processes as new quantum process capabilities and can be systematically implemented by quantum process tomography. Additionally, an approach for witnessing non‐Markovianity by analyzing at least four system states without process tomography is provided. It is faithfully demonstrated that this method can be explicitly implemented using all‐optical setups and applied to identify the non‐Markovianity of single‐photon and two‐photon dynamics in birefringent crystals. The results also can be used to explore non‐Markovianity in other dynamical systems where process or state tomography is implementable.
Bevacizumab‐induced pulmonary cystic disease
Authors: McNierney Dakota , Owda Fahed , Salim Hamza A. , Mallah Shatha M. A. , Azar Jehad
Published: March 2024

The use of Bevacizumab has significantly advanced the treatment of various malignancies. Bevacizumab's inhibition of angiogenesis is a known mechanism that impedes tumour growth and facilitates chemotherapy delivery; however, its association with the development of cystic lung disease is not fully understood. We report a unique case of a 73‐year‐old woman with a past medical history of metastatic endometrial adenocarcinoma status post‐chemotherapy with bevacizumab that presented with worsening respiratory symptoms. A follow‐up chest CT scan post chemotherapy showed the transformation of the metastatic lesions into cystic formations. After further extensive evaluation, she was diagnosed with pulmonary cystic disease secondary to bevacizumab. This case illustrates a rare presentation of secondary pulmonary cystic disease following Bevacizumab therapy in a patient with metastatic endometrial adenocarcinoma. It highlights the importance of recognizing uncommon side effects of targeted immunotherapy and underscores the need for ongoing research to understand the underlying mechanisms and manage such complications effectively.
Ferritin: Significance in viral infections
Authors: Zhao Xia , Zhou Yuntao , Zhang Yong , Zhang Yan
Published: March 2024

As an indispensable trace element, iron is essential for many biological processes. Increasing evidence has shown that virus infection can perturb iron metabolism and play a role in the occurrence and development of viral infection‐related diseases. Ferritin plays a crucial role in maintaining the body's iron homoeostasis. It is an important protein to stabilise the iron balance in cells. Ferritin is a 24‐mer hollow iron storage protein composed of two subunits: ferritin heavy chain and ferritin light chain. It was reported that ferritin is not only an intra‐cellular iron storage protein, but also a pathogenic mediator that enhances the inflammatory process and stimulates the further inflammatory pathway, which is a key member of the vicious pathogenic cycle to perpetuate. Ferritin exerts immuno‐suppressive and pro‐inflammatory functions during viral infection. In this review, we describe in detail the basic information of ferritin in the first section, including its structural features, the regulation of ferritin. In the second part, we focus on the role of ferritin in viral infection‐related diseases and the molecular mechanisms by which viral infection regulates ferritin. The last section briefly outlines the potential of ferritin in antiviral therapy. Given the importance of iron and viral infection, understanding the role of ferritin during viral infection helps us understand the relationship between iron metabolic dysfunction and viral infection, which provides a new direction for the development of antiviral therapeutic drugs.
Analyzing natural bed‐level dynamics to mitigate the morphological impact of river interventions
Authors: van Denderen R. Pepijn , Schielen Ralph M. J. , Paarlberg Andries J. , Reneerkens Michiel , Augustijn Denie C. M.
Published: March 2024

Local river interventions, such as channel narrowing or side channels, are often necessary to maintain safety, ecology, or navigation. Such interventions have different effects on the river's bed morphology during periods of high‐ and low‐discharge events. Mapping the bed‐level variations for different discharge levels and understanding these effects can provide new opportunities for the design of interventions in multifunctional rivers. At any moment, the local bed level in a river is composed of bed‐level changes that occur at various spatial and temporal scales. These changes consist of bed aggradation/degradation trends on a large scale, on an intermediate scale bed‐level variations as a result of discharge fluctuations, and on small‐scale moving river bed forms like dunes. Using the river Waal in the Netherlands as a case study, we analyze the intermediate‐term bed‐level changes resulting from discharge fluctuations (dynamic component) and propose adaptations to the design of floodplain interventions such that possible negative impact on the local bed‐level changes is minimized. Time series of bed levels along two 10 km stretches of the case study are considered for a period of 16 years (2005–2020). Using a wavelet transform, we isolate bed‐level variations resulting from discharge events. These bed‐level variations are presented based on the magnitude of the discharge event and are compiled in an interactive atlas of river morphodynamics, allowing us to mitigate the impact of interventions. This will help river managers in the design of interventions and lead to improved management, operation, and maintenance of multifunctional rivers.
Advancement in Sustainable Wastewater Treatment: A Multifaceted Approach to Textile Dye Removal through Physical, Biological and Chemical Techniques
Authors: N Lotha Tsenbeni , Sorhie Viphrezolie , Bharali Pranjal , Jamir Latonglila
Published: March 2024

The global manufacturing sector heavily relies on the textile industry, yet the widespread utilization of synthetic dyes within this sector has raised serious environmental apprehensions, notably regarding wastewater contamination. The release of untreated wastewater containing residual dyes poses a significant risk to both aquatic ecosystems and human well‐being. In reaction to this issue, considerable efforts have been made to develop efficient and sustainable methods for the removal of textile dyes from wastewater. This comprehensive review paper furnishes in‐depth literature information covering various aspects of dyes, including their classification, toxicity effects, and evaluation of recent advancements in dye removal technology, emphasizing their advantages, limitations, and future potential. Various strategies are covered, including physical, chemical, and biological methods. Physical techniques like adsorption, filtration, and membrane technologies are contrasted with chemical approaches such as coagulation, precipitation, and advanced oxidation processes. Biological methods include the utilization of micro‐organisms, fungi, and enzymes to break down or metabolize dye compounds. Key considerations in the critical analysis include the efficiency, cost‐effectiveness, and scalability of each method. This review focuses on enzyme breakdown (biological) and adsorption (physical) color removal procedures, which are currently considered the most effective. It also proposes the utilization of a composite adsorbent, anticipating enhanced efficiency and faster removal of dyes through this technique.
Preparation of Metal‐Containing Zwitterionic Fe3O4@SiO2−βPDMA Composite Systems and Catalytic Activity Studies
Authors: Tuncer Cansel , Yurdakul Cagdas
Published: March 2024

In response to the current challenges in the field, this study will contribute to the development of a highly versatile magnetic core/shell nanocomposite by addressing issues in the synthesis and functionalization of Fe3O4 nanoparticles through the presentation of innovative solutions. Firstly, Fe3O4 nanoparticles were synthesized. Tetraethyl orthosilicate was used as a silicon source and Fe3O4@SiO2 magnetic nanoparticles were synthesized. The outer surface of Fe3O4@SiO2 nanoparticles were modified and converted into Fe3O4@SiO2−NH2 structure. These modified particles were then functionalized with alkyl bromide to be used as an ATRP initiator and Fe3O4@SiO2−Br structure was obtained. The polymerization of 2‐(dimethylamino)ethyl methacrylate (DMA) monomer on the particle surface was achieved by the SI‐ATRP method. In the last step, betainization of Fe3O4@SiO2−PDMA composite was worked, and the salts of gold and silver were added to composite systems. The dispersions of the metal loaded Fe3O4@SiO2−βPDMA composite was obtained and used as catalysts in the reduction reaction of p‐nitrophenol to p‐aminophenol. Consequently, Fe3O4@SiO2−βPDMA composite system with magnetic properties in the range of 145–160 nm was prepared. The structure of synthesized magnetic nanoparticle was characterized by PXRD, TEM, TG‐DTA and the catalyst activity in the reduction reaction of p‐nitrophenol to p‐aminophenol was examined by UV‐vis spectrophotometer.
Precise Control of Metal Active Sites of Metal–Organic Framework Nanozymes for Achieving Excellent Enzyme‐Like Activity and Efficient Pancreatitis Therapy
Authors: Zhang Jie , Guo Meilin , He Qikuan , Zhang Zhisen , Wu Boda , Wu Hongji , Li Rizhao , Zhang Qiyu , Tang Yonghua , Lin Youhui , Jin Yuepeng
Published: March 2024

Acute pancreatitis (AP) is a potentially life‐threatening inflammatory disease that can lead to the development of systemic inflammatory response syndrome and its progression to severe acute pancreatitis. Hence, there is an urgent need for the rational design of highly efficient antioxidants to treat AP. Herein, an optimized Cu‐based metal–organic framework (MOF) nanozyme with exceptional antioxidant activity is introduced, designed to effectively alleviate AP, by engineering the metal coordination centers in MN2Cl2 (M = Co, Ni, Cu). Specifically, the Cu MOF, which benefits from a Cu active center similar to that of natural superoxide dismutase (SOD), exhibited at least four times higher SOD‐like activity than the Ni/Co MOF. Theoretical analyses further demonstrate that the CuN2Cl2 site not only has a moderate adsorption effect on the substrate molecule •OOH but also reduces the dissociation energy of the product H2O2. Additionally, the Cu MOF nanozyme possesses the excellent catalase‐like activity and •OH removal ability. Consequently, the Cu MOF with broad‐spectrum antioxidant activity can efficiently scavenge reactive oxygen species to alleviate arginine‐induced AP. More importantly, it can also mitigate apoptosis and necrosis of acinar cells by activating the PINK1/PARK2‐mediated mitophagy pathway. This study highlights the distinctive functions of tunable MOF nanozymes and their potential bio‐applications.
Doping Regulation Stabilizing δ‐MnO2 Cathode for High‐Performance Aqueous Aluminium‐ion Batteries
Authors: Chen Shuimei , Kong Yueqi , Tang Cheng , Gadelhak Nashaat Ahmed , Nanjundan Ashok Kumar , Du Aijun , Yu Chengzhong , Huang Xiaodan
Published: March 2024

δ‐MnO2 is a promising cathode material for aqueous aluminium‐ion batteries (AAIBs) for its layered crystalline structure with large interlayer spacing. However, the excellent Al ion storage performance of δ‐MnO2 cathode remains elusive due to the frustrating structural collapse during the intercalation of high ionic potential Al ion species. Here, it is discovered that introducing heterogeneous metal dopants with high bond dissociation energy when bonded to oxygen can significantly reinforce the structural stability of δ‐MnO2 frameworks. This reinforcement translates to stable cycling properties and high specific capacity in AAIBs. Vanadium‐doped δ‐MnO2 (V‐δ‐MnO2) can deliver a high specific capacity of 518 mAh g−1 at 200 mA g−1 with remarkable cycling stability for 400 cycles and improved rate capabilities (468, 339, and 285 mAh g−1 at 0.5, 1, and 2 A g−1, respectively), outperforming other doped δ‐MnO2 materials and the reported AAIB cathodes. Theoretical and experimental studies indicate that V doping can substantially improve the cohesive energy of δ‐MnO2 lattices, enhance their interaction with Al ion species, and increase electrical conductivity, collectively contributing to high ion storage performance. These findings provide inspiration for the development of high‐performance cathodes for battery applications.
Advances of Layered Double Hydroxide‐Based Materials for Tumor Imaging and Therapy
Authors: Ma Ke , Chen Ke‐Zheng , Qiao Sheng‐Lin
Published: March 2024

Layered double hydroxides (LDH) are a class of functional anionic clays that typically consist of orthorhombic arrays of metal hydroxides with anions sandwiched between the layers. Due to their unique properties, including high chemical stability, good biocompatibility, controlled drug loading, and enhanced drug bioavailability, LDHs have many potential applications in the medical field. Especially in the fields of bioimaging and tumor therapy. This paper reviews the research progress of LDHs and their nanocomposites in the field of tumor imaging and therapy. First, the structure and advantages of LDH are discussed. Then, several commonly used methods for the preparation of LDH are presented, including co‐precipitation, hydrothermal and ion exchange methods. Subsequently, recent advances in layered hydroxides and their nanocomposites for cancer imaging and therapy are highlighted. Finally, based on current research, we summaries the prospects and challenges of layered hydroxides and nanocomposites for cancer diagnosis and therapy.
Multi‐Task Residential Short‐Term Load Prediction Based on Contrastive Learning
Authors: Zhang Wuqing , Li Jianbin , Wu Sixing , Guo Yiguo
Published: March 2024

Load forecasting is crucial for the operation and planning of electricity generation, transmission, and distribution. In the context of short‐term electricity load prediction for residential users, single‐task learning methods fail to consider the relationship among multiple residential users and have limited feature extraction capabilities for residential load data. It is challenging to obtain sufficient information from individual residential user load predictions, resulting in poor prediction performance. To address these issues, we propose a framework for multi‐task residential short‐term load prediction based on contrastive learning. Firstly, clustering techniques are used to select residential users with similar electricity consumption patterns. Secondly, contrastive learning is employed for pre‐training, extracting trend and seasonal feature representations of load sequences, thereby enhancing the feature extraction capability for residential load Feature. Lastly, a multi‐task learning prediction framework is utilized to learn shared information among multiple residential users' loads, enabling short‐term load prediction for multiple residences. The proposed load prediction framework has been implemented on two real‐world load data sets, and the experimental results demonstrate that it effectively reduces the prediction errors for residential load prediction. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.
Johnny Duncan Alston
Authors: Winstone Jamie
Published: March 2024

Unconventional and independent, he was a larger‐than‐life character at the heart of the veterinary family who raised a smile in everyone he met.
Reflections on wellbeing and what it looks like in our practice
Authors: Merton Blue Cross
Published: March 2024

BVA held its inaugural Wellbeing Awards at the end of last year and, here, members of one of the winning teams, Blue Cross Merton animal hospital in London, share their experiences of wellbeing initiatives that have had a positive impact.
The development of gait and mobility: Form and function in infant locomotion
Authors: Hospodar Christina M. , Adolph Karen E.
Published: March 2024

The development of locomotion can be described by its form (i.e., gait) and its function (i.e., mobility). Both aspects of locomotion improve with experience. Traditional treatises on infant locomotion focus on form by describing an orderly progression of postural and locomotor milestones en route to characteristic patterns of crawling and walking gait. We provide a traditional treatment of gait by describing developmental antecedents of and improvements in characteristic gait patterns, but we highlight important misconceptions inherent in the notion of “milestones”. Most critically, we argue that the prevailing focus on gait and milestones fails to capture the true essence of locomotion—functional mobility to engage with the world. Thus, we also describe the development of mobility, including the use of mobility aids for support and propulsion. We illustrate how infants find individual solutions for mobility and how the ability to move cascades into other domains of development. Finally, we show how an integration of gait and mobility provides insights into the psychological processes that make locomotion functional.

This article is categorized under:

Psychology > Motor Skill and Performance

Psychology > Development and Aging
Magnetic modulation of lysosomes for cancer therapy
Authors: Li Yingze , Lv Cheng , Li Zhenguang , Chen Chang , Cheng Yu
Published: March 2024

Lysosomes play a central role in biochemical signal transduction and oxidative stress in cells. Inducing lysosome membrane penetration (LMP) to cause lysosomal‐dependent cell death (LCD) in tumor cells is an effective strategy for cancer therapy. Chemical drugs can destroy the stability of lysosomes by neutralizing protons within the lysosomes or enhancing the fragility of the lysosomal membranes. However, there remain several unsolved problems of traditional drugs in LMP induction due to insufficient lysosomal targeting, fast metabolism, and toxicity in normal cells. With the development of nanotechnology, magnetic nanoparticles have been demonstrated to target lysosomes naturally, providing a versatile tool for lysosomal modulation. Combined with excellent tissue penetration and spatiotemporal manipulability of magnetic fields, magnetic modulation of lysosomes progresses rapidly in inducing LMP and LCD for cancer therapy. This review comprehensively discussed the strategies of magnetic modulation of lysosomes for cancer therapy. The intrinsic mechanisms of LMP‐induced LCD were first introduced. Then, the modulation of lysosomes by diverse physical outputs of magnetic fields was emphatically discussed. Looking forward, this review will shed the light on the prospect of magnetic modulation of lysosomes, inspiring future research of magnetic modulation strategy in cancer therapy.

This article is categorized under:

Therapeutic Approaches and Drug Discovery > Emerging Technologies

Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease

Nanotechnology Approaches to Biology > Nanoscale Systems in Biology
Reducing the Gap Between Theory and Applications in Algorithmic Bayesian Persuasion
Authors: Castiglioni Matteo
Published: March 2024

This work focuses on the following question: is it possible to influence the behavior of self-interested agents through the strategic provision of information? This ‘sweet talk’ is ubiquitous among all sorts of economics and non-economics activities. In this work, we model these multi-agent systems as games between an informed sender and one or multiple receivers. We study the computational problem faced by an informed sender that wants to use his information advantage to influence rational receivers with the partial disclosure of information. In particular, the sender faces an information structure design problem that amounts to deciding ‘who gets to know what’. Bayesian persuasion provides a formal framework to model these settings as asymmetric-information games. In recent years, much attention has been given to Bayesian persuasion in the economics and artificial intelligence communities due also to the applicability of this framework to a large class of scenarios like online advertising, voting, traffic routing, recommendation systems, security, and product marketing. However, there is still a large gap between the theoretical study of information in games and its applications in real-world scenarios. This work contributes to close this gap along two directions. First, we study the persuasion problem in real-world scenarios, focusing on voting, routing, and auctions. While the Bayesian persuasion framework can be applied to all these settings, the algorithmic problem of designing optimal information disclosure polices introduces computational challenges related to the specific problem under study. Our goal is to settle the complexity of computing optimal sender’s strategies, showing when an optimal strategy can be implemented efficiently. Then, we relax stringent assumptions that limit the applicability of the Bayesian persuasion framework in practice. In particular, the classical model assumes that the sender has perfect knowledge of the receiver’s utility. We remove this assumption initiating the study of an online version of the persuasion problem. This is the first step in designing adaptive information disclosure policies that deal with the uncertainty intrinsic in all real-world applications.
Modern High-Level Synthesis: Improving Productivity with a Multi-level Approach
Authors: Curzel Serena
Published: March 2024

High-Level Synthesis (HLS) tools simplify the design of hardware accelerators by automatically generating Verilog/VHDL code starting from a general-purpose software programming language. Because of the mismatch between the requirements of hardware descriptions and the characteristics of input languages, HLS tools still require hardware design knowledge and non-trivial design space exploration, which might be an obstacle for domain scientists seeking to accelerate applications written, for example, in Python-based programming frameworks. This research proposes a modern approach based on multi-level compiler technologies to bridge the gap between HLS and high-level frameworks, and to use domain-specific abstractions to solve domain-specific problems. The key enabling technology is the Multi-Level Intermediate Representation (MLIR), a framework that supports building reusable compiler infrastructure. The proposed approach uses MLIR to introduce new optimizations at appropriate levels of abstraction outside the HLS tool while still relying on years of HLS research in the low-level hardware generation steps; users and developers of HLS tools can thus increase their productivity, obtain accelerators with higher performance, and not be limited by the features of a specific (possibly closed-source) backend. The presented tools and techniques were designed, implemented, and tested to synthesize machine learning algorithms, but they are broadly applicable to any input specification written in a language that has a translation to MLIR. Generated accelerators can be deployed on Field Programmable Gate Arrays or Application-Specific Integrated Circuits, and they can reach high energy efficiency without any manual optimization of the code.
Social Innovation and Co-design for Climate Neutrality: The NetZeroCities Project
Authors: Bresciani Sabrina , Rizzo Francesca , Mureddu Francesco
Published: March 2024

The complex and urgent challenge of reaching carbon neutrality requires systemic changes of our current systems. Starting from the acknowledgment that technological solutions alone are not enough to reach climate neutrality at the required speed, social innovation becomes a crucial lever for accelerating systemic transformation. Several projects and scientific evidence outline the benefits of a people-centred and co-design approaches to transitions. Yet, public administrators, policy makers and urban transition teams have limited guidance on how to embed social innovations in their cities’ action plans, and on how to assess the progresses, outcomes and impacts of social innovation initiatives at urban level. Based on the work developed within the EU-funded project NetZeroCities, the book presents a framework for categorization of social innovation solutions for climate neutrality at city level, and a clustered catalogue of indicators, which can be utilized by cities’ public administrators to monitor and evaluate social innovation action plans to support people-centred, collaborative solutions to lower carbon emissions.
Introduction: Studying the Relationship Between Parties and Democracy
Authors: Fink-Hafner Danica
Published: March 2024

In the current world, there are many empirical challenges to both parties and democracy. A long-term simplistic view of the party–democracy relationship helps neither in understanding the current challenges nor in the context-sensitive analysis of parties and party systems and their relationship with democracy. This book critically assesses early liberal political thought and the trends in political thought since the 1970s. The main thesis, the research questions and the methodological approach are presented using several puzzles from the real world and from political science on the relationship between parties, party systems and democracy, and the novel ideas of the book are explained.
An eikonal-inspired approach to the gravitational scattering waveform
Authors: Georgoudis Alessandro , Heissenberg Carlo , Russo Rodolfo
Published: March 2024

Abstract

We revisit the amplitude-based derivation of gravitational waveform for the scattering of two scalar black holes at subleading post-Minkowskian (PM) order. We take an eikonal-inspired approach to the two-massive-particle cut needed in the KMOC framework, as highlighted in [1], and show that its effect is to implement a simple change of frame. This clarifies one of the points raised in [2] when comparing with the post-Newtonian (PN) results. We then provide an explicit PM expression for the waveform in the soft limit, ω → 0, including the first non-universal, ω log ω, contribution. Focusing on this regime, we show that the small-velocity limit of our result agrees with the soft limit of the PN waveform of [2], provided that the two quantities are written in the same asymptotic frame. Performing the BMS supertranslation that, as discussed in [3], is responsible for the $$\mathcal{O}$$(G) static contribution to the asymptotic field employed in the PN literature, we find agreement between the amplitude-based and the PN soft waveform up to and including G3/c5 order.
Weak chaos and mixed dynamics in the string S-matrix
Authors: Savić Nikola , Čubrović Mihailo
Published: March 2024

Abstract

We investigate chaotic dynamics in tree-level S-matrices describing the scattering of tachyons, photons and gravitons on highly excited open and closed bosonic strings, motivated by the string/black hole complementarity. The eigenphase spacing distribution and other indicators of quantum chaotic scattering suggest that the dynamics is only weakly chaotic, consisting of both regular/Poisson and chaotic/Wigner-Dyson processes. Only for special values of momenta and (for photon scattering) scattering angles do we find strong chaos of random matrix type. These special values correspond to a crossover between two regimes of scattering, dominated by short versus long partitions of the total occupation number of the highly excited string; they also maximize the information entropy of the S-matrix. The lack of strong chaos suggests that perturbative dynamics of highly excited strings can never describe the universal properties and maximal chaos of black hole horizons.
The NADase CD38 is a central regulator in gouty inflammation and a novel druggable therapeutic target
Authors: Alabarse Paulo Gil , Oliveira Patricia , Qin Huaping , Yan Tiffany , Migaud Marie , Terkeltaub Robert , Liu-Bryan Ru
Published: March 2024

Objectives

Cellular NAD+ declines in inflammatory states associated with increased activity of the leukocyte-expressed NADase CD38. In this study, we tested the potential role of therapeutically targeting CD38 and NAD+ in gout.

Methods

We studied cultured mouse wild type and CD38 knockout (KO) murine bone marrow derived macrophages (BMDMs) stimulated by monosodium urate (MSU) crystals and used the air pouch gouty inflammation model.

Results

MSU crystals induced CD38 in BMDMs in vitro, associated with NAD+ depletion, and IL-1β and CXCL1 release, effects reversed by pharmacologic CD38 inhibitors (apigenin, 78c). Mouse air pouch inflammatory responses to MSU crystals were blunted by CD38 KO and apigenin. Pharmacologic CD38 inhibition suppressed MSU crystal-induced NLRP3 inflammasome activation and increased anti-inflammatory SIRT3–SOD2 activity in macrophages. BMDM RNA-seq analysis of differentially expressed genes (DEGs) revealed CD38 to control multiple MSU crystal-modulated inflammation pathways. Top DEGs included the circadian rhythm modulator GRP176, and the metalloreductase STEAP4 that mediates iron homeostasis, and promotes oxidative stress and NF-κB activation when it is overexpressed.

Conclusions

CD38 and NAD+ depletion are druggable targets controlling the MSU crystal- induced inflammation program. Targeting CD38 and NAD+ are potentially novel selective molecular approaches to limit gouty arthritis.