bluuebunny/crossref_metadata_2025 huggingface dataset:
A Resonating B, N Covalent Bond and Coordination Bond in Aromatic Compounds and Conjugated Polymers
Authors: Shao Xingxin , Liu Mengyu , Liu Jun , Wang Lixiang
Published: June 2022

We herein report an organoboron compound (SBN‐1) based on N−B←N units with a balanced resonance hybrid of B, N single bond (B−N) and B, N coordination bond (B←N). Despite the different chemical environments of the two nitrogen atoms in the N−B←N unit, the single‐crystal structure reveals that the two B, N bonds have similar bond lengths of ca. 1.55 Å and are almost equivalent. The resonance nature of the two B, N bonds contributes to the excellent chemical stability and photostability ofSBN‐1. The N−B←N units inSBN‐1show a strong electron‐withdrawing capability and large dipole, resulting in a red‐shifted absorption spectrum, downshifted LUMO/HOMO energy levels, and drastically altered molecular packing behaviors in solid state.SBN‐1can be used as a building block to construct small band gap conjugated polymers. The resonance of B, N bonds discovered in this work provides new insight into the design of stable organoboron small molecules and polymers for practical applications.
Direct Enantioselective Addition of Alkynes to Imines by a Highly Efficient Palladacycle Catalyst
Authors: Pfeffer Camilla , Probst Patrick , Wannenmacher Nick , Frey Wolfgang , Peters René
Published: June 2022

Enantiopure propargylic amines are highly valuable synthetic building blocks. Much effort has been devoted to develop methods for their preparation. The arguably most important strategy is the 1,2‐addition of alkynes to imines. Despite remarkable progress, the known methods using Zn and Cu catalysts suffer from the need for high catalyst loadings, typically ranging from 2–60 mol % for neutral aldimine substrates. Here we report a planar chiral Pd complex acting as very efficient catalyst for direct asymmetric alkyne additions to imines, requiring very low catalyst loadings. Turnover numbers of up to 8700 were accomplished. Our investigation suggests that a Pd‐acetylide complex is generated as a catalytically relevant intermediate by the aid of an acac ligand acting as internal catalytic base. It is shown that the catalyst is quite stable under the reaction conditions and that product inhibition is not an issue. A total of 39 examples is shown which all yielded almost enantiopure products.
Input‐to‐state stability for discrete‐time time‐varying impulsive switched delayed systems with asynchronous phenomena
Authors: Fu Zhiwen , Peng Shiguo
Published: June 2022

This paper studies the input‐to‐state stability (ISS) for a class of discrete‐time time‐varying impulsive switched delayed systems, in which the asynchronous phenomena are considered. Asynchronous phenomena here include two implications: asynchronous impulses and switches and asynchronous switching. The former means that the events, that is, impulses and switches, are not necessary to occur simultaneously, while the latter indicates that the actual switching modes and related controllers or specified modes do not coincide. Applying the mode‐dependent concept to impulses and switches, both the improved Krasovskii‐type and Razumikhin‐type ISS criteria are provided. The time differences of Lyapunov functionals or functions here are sign‐changing and time‐varying, releasing from the traditional assumption that always requires negative definiteness. Meanwhile, in this paper, ISS or non‐ISS subsystems and stabilizing or destabilizing impulses are taken into account. Finally, three numerical examples are given to illustrate the effectiveness of the proposed results.
Development and validation of a leukocyte‐associated immunoglobulin‐like receptor‐1 prognostic signature for lower‐grade gliomas
Authors: Fang Zhansheng , Lin Li , Tu Zewei , Zhu Xingen , Li Jingying , Luo Pengxiang , Huang Kai , Wu Lei
Published: June 2022

Objective

Leukocyte‐associated immunoglobulin‐like receptor‐1 (LAIR‐1), is an immunosuppressive receptor, widely expressed by immune cells, but the part of LAIR‐1 in glioma progression remains unclear. The purpose of this study was to explore the relationship between LAIR‐1 expression and the development of lower‐grade glioma (LGG) using publicly available data sets.

Methods

We took advantage of The Cancer Genome Atlas (TCGA) to analyze the expression of LAIR‐1 in patients with LGG. Second, Kaplan‐Meier methods and univariate and multivariate Cox regression analyses were used to examine the clinical significance of LAIR‐1 expression in combination with CGGA databases, and then receiver operating characteristic curve analysis was used to verify the prognostic utility of LAIR‐1. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis (GSEA) were used to explore the function of LAIR‐1. Analysis of the correlation with immune infiltration was conducted using the ESTIMATE algorithm and single sample gene set enrichment analysis.

Results

Our results showed that LAIR‐1 expression to be positively correlated with malignant clinicopathologic features of LGG. Univariate analysis and multivariate analysis revealed that overexpression of LAIR‐1 was correlated with a worse prognosis in patients. A nomogram model combining LAIR‐1 was more useful in guiding clinical diagnosis, and functional enrichment analysis showed that malignant development of glioma was closely affiliated with the tumor immune microenvironment.

Conclusion

These results indicate that LAIR 1 is a latent marker for determining the prognosis of LGG patients. LAIR 1 may also participate a critical part in TIME of LGG by regulating the infiltration of immune cells, suggesting that LAIR 1 might be used as a therapeutic target to regulate the antitumor immune response.
Oral brush biopsy using liquid‐based cytology is a reliable tool for oral cancer screening: A cost‐utility analysis
Authors: Idrees Majdy , Farah Camile S. , Sloan Philip , Kujan Omar
Published: June 2022

Background

This study aimed to assess the diagnostic utility and associated cost of oral liquid‐based brush cytology (OLBC) in the diagnosis of oral cancer and oral potentially malignant disorders (OPMDs).

Methods

A total of 284 patients with oral mucosal lesions were included. OLBC samples were collected from all patients immediately before undergoing surgical biopsies. A liquid‐based cytology slide was prepared from each OLBC sample for cytological evaluation using the modified 2014 Bethesda cytology system. The results and the cost were compared with the histopathological outcomes.

Results

The level of agreement between the two approaches was very good (weighted kappa = 0.824). The accuracy of OLBC in differentiating between the different diagnostic groups was 91.69%, whereas the associated sensitivity and specificity were 79.23% and 94.81%, respectively. The estimated cost of each OLBC sample was at least 26% less than the cost of a single biopsy and more than 42% less in cases of multiple biopsied lesions.

Conclusions

The proposed modifications of the Bethesda system can be adopted as a standardized system for oral cytological assessment. Our findings support OLBC as a reliable adjunct to surgical biopsy in the diagnosis of OPMDs. This tool has potential for oral cancer–finding and surveillance programs.
Weather parameters forecasting with time series using deep hybrid neural networks
Authors: Yalçın Sercan
Published: June 2022

Weather forecasting has recently gained great importance in terms of predicting potential disasters, taking precautions, and increasing the quality of life around the world. Researchers apply optimization and artificial intelligence techniques to make weather forecasts based on various nature parameters. In this study, it is proposed a weather condition forecasting scheme with time series using deep hybrid neural networks. In the proposed scheme, the essential parameters for weather forecasting, namely, relative humidity, temperature, atmospheric pressure, and wind speed are trained and predicted with long short‐term memory (LSTM)‐convolutional neural networks (CNNs) models in a hybrid way. The values represented by the input neurons are first passed through the CNN layers for a clearer and more accurate estimation of the data. Then, after fine‐tuning, the results are sent to the LSTM block. The proposed hybrid deep method has been compared with both machine learning and deep learning methods According to the results, running the proposed method, the RMSE, MADE, and MAPE values are 1.82, 1.64, 1.21 for temperature, 7.12, 6.58, and 4.63 for relative humidity, 2.61, 2.36, and 1.86 for atmospheric pressure, and 1.06, 0.85, and 0.52 for wind speed, respectively.
Using seabird and whale distribution models to estimate spatial consumption of krill to inform fishery management
Authors: Warwick‐Evans V. , Kelly N. , Dalla Rosa L. , Friedlaender A. , Hinke J. T. , Kim J. H. , Kokubun N. , Santora J. A. , Secchi E. R. , Seyboth E. , Trathan P. N.
Published: June 2022

Ecosystem dynamics at the northwest Antarctic Peninsula are driven by interactions between physical and biological processes. For example, baleen whale populations are recovering from commercial harvesting against the backdrop of rapid climate change, including reduced sea ice extent and changing ecosystem composition. Concurrently, the commercial harvesting of Antarctic krill is increasing, with the potential to increase the likelihood for competition with and between krill predators and the fishery. However, understanding the ecology, abundance, and spatial distribution of krill predators is often limited, outdated, or at spatial scales that do not match those desired for effective fisheries management. We update current knowledge of predator dependence on krill by integrating telemetry‐based data, at‐sea observational surveys, estimates of predator abundance, and physiological data to estimate the spatial distribution of krill consumption during the austral summer by three species ofPygoscelispenguin, 11 species of flying seabirds, one species of pinniped, and two species of baleen whale. Our models show that the majority of important areas for krill predator foraging are close to penguin breeding colonies in nearshore areas where humpback whales also regularly feed, and along the shelf‐break, though we caution that not all known krill predators are included in these analyses. We show that krill consumption is highly variable across the region, and often concentrated at fine spatial scales, emphasizing the need for the management of the local krill fishery at relevant temporal and spatial scales. We also note that krill consumption by recovering populations of krill predators provides further evidence in support of the krill surplus hypothesis, and highlight that despite less than comprehensive data, cetaceans are likely to consume a significant proportion of the krill consumed by natural predators but are not currently considered directly in the management of the krill fishery. If management of the krill fishery is to be precautionary and operate in a way that minimizes the risks to krill predator populations, it will be necessary in future analyses, to include up‐to‐date and precise abundance and consumption estimates for pack‐ice seals, finfish, squid, and other baleen whale species not currently considered.
A Steroidal Molecular Rotor with Fast Solid‐State Dynamics Obtained by Crystal Engineering: Role of the Polarity of the Stator
Authors: Labra‐Vázquez Pablo , Ochoa María E. , Alfonso‐Herrera Luis A. , Vera Marco A. , Farfán Norberto , Santillan Rosa
Published: June 2022

A set of Steroidal Molecular Rotors (SMRs) were synthesized and characterized employing a Sonogashira cross‐coupling reaction as the key synthetic step. The static dipole moment (μ0) of the stator was examined as a crystal engineering criterium that could determine the easiness with which the rotator participates in the high energy supramolecular interactions that frequently preclude rotation in this class of molecular machines. The strategy is critically evaluated through theoretical/experimental analyses, featuring SXRD experiments and QM/MM computations of the rotational activation energy (Ea), allowing us to propose, within the systems studied, a potential correlation between the use of stators with lower μ0and a lowering of theEavalue. Results from solid‐state NMR revealed that one of the most promising compounds indeed hosts fast rotational motion (above 25–30 kHz), standing as a rare example of a SMR with fast rotation within a crowded crystallographic environment.
Molecular Iodine Mediated Oxidation of Arylated α‐Carbonyl Sulfoxonium Ylides to 1,2‐Dicarbonyl‐Containing Compounds
Authors: Echemendía Radell , De Jesus Matheus P. , Furniel Lucas G. , Day David Philip , Burtoloso Antonio C. B.
Published: June 2022

Sulfoxonium ylides in recent years have proved to be versatile building blocks and have found applications in the synthesis of structurally diverse organic molecules. In this work, we report a new oxidative, molecular iodine‐mediated transformation on sterically encumbered arylated sulfoxonium ylides, which give access to 1,2‐dicarbonyl containing compounds. Twenty‐six examples have been realized (47–92 % yields), with structural diversity modified at two key sites on the sulfoxonium ylide reactants. Furthermore, the protocol benefits from the use of inexpensive molecular iodine to mediate the oxidation and, from a sustainability viewpoint, short reaction times (30 minutes), ambient temperature, and ethyl acetate as a greener reaction solvent. Experimental studies also gave insight to the mechanism of the reaction, involving DMSO as an oxygen source.
Problematic eating behaviours of autistic women—A scoping review
Authors: Schröder Sabrina S. , Danner Unna N. , Spek Annelies A. , van Elburg Annemarie A.
Published: June 2022

Aim

Eating and feeding behaviours of autistic individuals and related consequences have been mainly investigated in autistic children or in autistic adults with intellectual disabilities. Behaviours such as food selectivity or food neophobia have been shown to persist into adolescence and adulthood and are associated with aversive consequences. However, much less is known about the eating behaviours of autistic adults without intellectual disabilities, especially those of women. By means of a scoping review, we aim to assess the extent of the scientific literature on what is known about the eating behaviours of these women and the possible consequences of such eating behaviour.

Method

Medline, Cochrane, PubMed and PsycInfo databases were searched according to Preferred Reporting Items for Systematic reviews and Meta‐Analyses (PRISMA) guidelines.

Results

Five studies met the eligibility criteria and were included in this review. Autistic women not only reported high levels of eating behaviour frequently seen in autism spectrum disorders (ASD), but also high levels of disordered eating behaviour, similar to that of women with eating disorders.

Conclusions

Autistic women seem to exhibit high levels of eating behaviour frequently seen in ASD as well as disordered eating behaviour. Future research needs to shed light on what underlies these problematic eating behaviours, in order to help to adapt current treatment modalities to meet the unique needs of these women.
Experimental investigation for the impact of chlorite dissolution on CO2 mineral trapping in a sandstone‐brine‐CO2 system
Authors: Cheng Jianmei , Yu Hui , Liu Ning , Yu Ying , Ahmat Kaisar , Zhao Ruirui
Published: June 2022

The mineral trapping of CO2 in geological formation is the most promising and safe mechanism for permanent carbon storage. The chlorite shows a great influence on the form and capacity of carbon storage in sandstone reservoirs due to its wide distribution and strong chemical activity. In this paper, to better understand the dissolution process of chlorite after the injection of CO2 and its potential impacts on carbon mineral trapping patterns, two sets of hydrothermal batch reactions toward chlorite and CO2 fluid are conducted at elevated temperature‐pressure conditions (120 °C/180 °C, 18 MPa), considering the effects of extra calcite addition and the initial concentration of Ca2+ in solution. During reactions, the changes in water chemistry and mineral surface morphology are monitored through effluent sampling and scanning electron microscope (SEM) observation, respectively and they are further analyzed in PHREEQC by the method of mineral saturation index. It is found that the simultaneous dissolution of chlorite and calcite in CO2 saturated solutions will lead to a competition for H+, and the formation of massive surface complex CaHCO3– by Ca2+ in the initial solutions will lead to the consumption of H+. These inhibit the proton‐promoted dissolution of chlorite. But when the concentration of Ca2+ is increased to meet the requirements for ankerite precipitation, the demand of ankerite precipitation for elements Fe and Mg will conversely promote the chlorite dissolution. Besides, the concentration of Ca2+ required for the precipitation of ankerite is relatively low, which implies that the injected CO2 can be mineralized and trapped by the chlorite dissolution process easily. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd.
An examination of machine learning to map non‐preference based patient reported outcome measures to health state utility values
Authors: Aghdaee Mona , Parkinson Bonny , Sinha Kompal , Gu Yuanyuan , Sharma Rajan , Olin Emma , Cutler Henry
Published: June 2022

Non‐preference‐based patient‐reported outcome measures (PROMs) are popular in health outcomes research. These measures, however, cannot be used to estimate health state utilities, limiting their usefulness for economic evaluations. Mapping PROMs to a multi‐attribute utility instrument is one solution. While mapping is commonly conducted using econometric techniques, failing to specify the complex interactions between variables may lead to inaccurate prediction of utilities, resulting in inaccurate estimates of cost‐effectiveness and suboptimal funding decisions. These issues can be addressed using machine learning. This paper evaluates the use of machine learning as a mapping tool. We adopt a comprehensive approach to compare six machine learning techniques with eight econometric techniques to map the Patient‐Reported Outcomes Measurement Information System Global Health 10 (PROMIS‐GH10) to the EuroQol five dimensions (EQ‐5D‐5L). Using data collected from 2015 Australians, we find the least absolute shrinkage and selection operator (LASSO) model out‐performed all machine learning techniques and the adjusted limited dependent variable mixture model (ALDVMM) out‐performed all econometric techniques, with the LASSO performing better than ALDVMM. The variable selection feature of LASSO was then used to enhance the performance of the ALDVMM in a hybrid model. Our analysis identifies the potential benefits and challenges of using machine learning techniques for mapping and offers important insights for future research.
Decellularization of porcine esophageal tissue at three diameters and the bioscaffold modification with EETs‐ECM gel
Authors: Orozco‐Vega Adriana , Montes‐Rodríguez Metzeri I. , Luévano‐Colmenero Guadalupe H. , Barros‐Gómez Jimena , Muñoz‐González Pedro U. , Flores‐Moreno Mauricio , Delgadillo‐Holtfort Isabel , Vega‐González Arturo , Rojo Francisco J. , Guinea Gustavo V. , Mendoza‐Novelo Birzabith
Published: June 2022

Damaged complex modular organs repair is a current clinical challenge in which one of the primary goals is to keep their biological response. An interesting case of study it is the porcine esophagus since it is a tubular muscular tissue selected as raw material for tissue engineering. The design of esophageal constructs can draw on properties of the processed homologous extracellular matrix (ECM). In this work, we report the decellularization of multilayered esophagus tissue from 1‐, 21‐ and 45‐days old piglets through the combination of reversible alkaline swelling and detergent perfusion. The bioscaffolds were characterized in terms of their residual composition and tensile mechanical properties. The biological response to esophageal submucosal derived bioscaffolds modified with ECM gel containing epoxyeicosatrienoic acids (EETs) was then evaluated. Results suggest that the composition (laminin, fibronectin, and sulphated glycosaminoglycans/sGAG) depends on the donor age: a better efficiency of the decellularization process combined with a higher retention of sGAG and fibronectin is observed in piglet esophageal scaffolds. The heterogeneity of this esophageal ECM is maintained, which implied the preservation of anisotropic tensile properties. Coating of bioscaffolds with ECM gel is suitable for carrying esophageal epithelial cells and EETs. Bioactivity of EETs‐ECM gel modified esophageal submucosal bioscaffolds is observed to promote neovascularization and antiinflammatory after rabbit full‐thickness esophageal defect replacement.
A semiparametric approach for meta‐analysis of diagnostic accuracy studies with multiple cut‐offs
Authors: Frömke Cornelia , Kirstein Mathia , Zapf Antonia
Published: June 2022

The accuracy of a diagnostic test is often expressed using a pair of measures: sensitivity (proportion of test positives among all individuals with target condition) and specificity (proportion of test negatives among all individuals without target condition). If the outcome of a diagnostic test is binary, results from different studies can easily be summarized in a meta‐analysis. However, if the diagnostic test is based on a discrete or continuous measure (e.g., a biomarker), several cut‐offs within one study as well as among different studies are published. Instead of taking all information of the cut‐offs into account in the meta‐analysis, a single cut‐off per study is often selected arbitrarily for the analysis, even though there are statistical methods for the incorporation of several cut‐offs. For these methods, distributional assumptions have to be met and/or the models may not converge when specific data structures occur. We propose a semiparametric approach to overcome both problems. Our simulation study shows that the diagnostic accuracy is under‐estimated, although this underestimation in sensitivity and specificity is relatively small. The comparative approach of Steinhauser et al. is better in terms of coverage probability, but may lead to convergence problems. In addition to the simulation results, we illustrate the application of the semiparametric approach using a published meta‐analysis for a diagnostic test differentiating between bacterial and viral meningitis in children.
Lessons learnt: Undertaking rapid reviews on public health and social measures during a global pandemic
Authors: Rehfuess Eva A. , Burns Jacob B. , Pfadenhauer Lisa M. , Krishnaratne Shari , Littlecott Hannah , Meerpohl Joerg J. , Movsisyan Ani
Published: June 2022

Public health and social measures (PHSM) have been central to the COVID‐19 response. Consequently, there has been much pressure on decision‐makers to make evidence‐informed decisions and on researchers to synthesize the evidence regarding these measures. This article describes our experiences, responses and lessons learnt regarding key challenges when planning and conducting rapid reviews of PHSM during the COVID‐19 pandemic. Stakeholder consultations and scoping reviews to obtain an overview of the evidence inform the scope of reviews that are policy‐relevant and feasible. Multiple complementary reviews serve to examine the benefits and harms of PHSM across different populations and contexts. Conceiving reviews of effectiveness as adaptable living reviews helps to respond to evolving evidence needs and an expanding evidence base. An appropriately skilled review team and good planning, coordination and communication ensures smooth and rigorous processes and efficient use of resources. Scientific rigor, the practical implications of PHSM‐related complexity and likely time savings should be carefully weighed in deciding on methodological shortcuts. Making the best possible use of modeling studies represents a particular challenge, and methods should be carefully chosen, piloted and implemented. Our experience raises questions regarding the nature of rapid reviews and regarding how different types of evidence should be considered in making decisions about PHSM during a global pandemic. We highlight the need for readily available protocols for conducting studies on the effectiveness, unintended consequences and implementation of PHSM in a timely manner, as well as the need for rapid review standards tailored to “rapid” versus “emergency” mode reviewing.
Dietary fiber ameliorates lead‐induced gut microbiota disturbance and alleviates neuroinflammation
Authors: Yao Mei , Shao Xingfeng , Wei Yingying , Zhang Xin , Wang Hongfei , Xu Feng
Published: June 2022

Dietary fiber (DF) is a carbohydrate from the edible part of plants and has the functions of promoting gastrointestinal motility, regulating gut microbiota (GM) and improving health. Lead is a non‐essential toxic heavy metal that can accumulate in the environment over time and enter the body through the respiratory tract, skin and gastrointestinal tract. Lead not only causes disturbances in GM but also leads to loss of homeostasis of immune functions, causes neuronal damage and results in neuroinflammation. The scientific literature has reported that DF had anti‐inflammatory activity as a natural product. This review highlights the role of DF and its metabolic products in alleviating lead‐induced neuroinflammation by inducing changes in the species and quantity of GM and regulating the immune system, providing a potential dietary protective strategy for lead‐induced disease. © 2022 Society of Chemical Industry.
Clinical detection of “extremely low‐risk” follicular thyroid carcinoma: A population‐based study of 7304 patients
Authors: Le Minh‐Khang , Odate Toru , Vuong Huy Gia , Mochizuki Kunio , Kondo Tetsuo
Published: June 2022

Background

Previous studies have not been consistent in the risk of metastasis in follicular thyroid carcinoma (FTC). Therefore, we conducted a large population study to stratify the risk of distant metastasis in FTC patients using only clinical parameters.

Methods

We extracted FTC patients from The Surveillance, Epidemiology, and End Results (SEER) database and divided them into training and validation cohorts.

Results

The two cohorts consisted of 4913 and 2391 patients, respectively. We developed a nomogram and risk table based on a logistic regression model using algorithm‐selected variables. Receiver Operating Characteristic (ROC) analyses showed high discriminatory power in the training and validation cohorts (Area under the curve [AUC] of 0.85 and 0.84, respectively). Extremely low, low, intermediate, and high‐risk groups had 0.3%, 1%, 3.5%, and 16.7% risk of distant metastasis, respectively.

Conclusions

Our risk scoring table can separates patients into four risk groups and efficiently detect patients with almost no risk of metastasis.
Targeted protein quantitation in human body fluids by mass spectrometry
Authors: Chen Yi‐Ting , Liao Wan‐Rou , Wang Hsueh‐Ting , Chen Hsiao‐Wei , Chen Sung‐Fang
Published: June 2022

Human body fluids (biofluids) contain various proteins, some of which reflect individuals' physiological conditions or predict diseases. Therefore, the analysis of biofluids can provide substantial information on novel biomarkers for clinical diagnosis and prognosis. In the past decades, mass spectrometry (MS)‐based technologies have been developed as proteomic strategies not only for the identification of protein biomarkers but also for biomarker verification/validation in body fluids for clinical applications. The main advantage of targeted MS‐based methodologies is the accurate and specific simultaneous quantitation of multiple biomarkers with high sensitivity. Here, we review MS‐based methodologies that are currently used for the targeted quantitation of protein components in human body fluids, especially in plasma, urine, cerebrospinal fluid, and saliva. In addition, the currently used MS‐based methodologies are summarized with a specific focus on applicable clinical sample types, MS configurations, and acquisition modes.
Exploring the characteristics and most bothersome symptoms in MECP2 duplication syndrome to pave the path toward developing parent‐oriented outcome measures
Authors: Ak Muharrem , Suter Bernhard , Akturk Zekeriya , Harris Holly , Bowyer Kristina , Mignon Laurence , Pasupuleti Sasidhar , Glaze Daniel G. , Pehlivan Davut
Published: June 2022

Background

MECP2 Duplication Syndrome (MDS), resulting from the duplication of Xq28 region, including MECP2, is a rare disorder with a nascent understanding in clinical features and severity. Studies using antisense oligonucleotides revealed a broad phenotypic rescue in transgenic mice. With human clinical trials on the horizon, there is a need to develop clinical outcome measures for MDS.

Methods

We surveyed caregivers of MDS individuals to explore the frequency and severity of MDS clinical features, and identify the most meaningful symptoms/domains that need to be included in the outcome measure scales.

Results

A total of 101 responses were eligible for the survey. The top six most meaningful symptoms to caregivers in descending order included epilepsy, gross motor, fine motor, communication, infection, and constipation problems. Epilepsy was present in 58.4% of the subjects and 75% were drug‐resistant, Furthermore, ~12% required intensive care unit (ICU) admission. Infections were present in 55% of the subjects, and one‐fourth of them required ICU admission. Constipation was present in ~85% of the subjects and one‐third required enemas/suppositories.

Conclusion

Our study is one of the largest cohorts conducted on MDS individuals characterizing the frequency and severity of MDS symptoms. Additionally, these study results will contribute to establishing a foundation to develop parent‐reported outcomes in MDS.
Recent Advances in the Applications of Water‐soluble Resorcinarene‐based Deep Cavitands
Authors: Zhu Yu‐Jie , Zhao Ming‐Kai , Rebek Julius , Yu Yang
Published: June 2022

We review here the use of container molecules known as cavitands for performing organic reactions in water. Central to these endeavors are binding forces found in water, and among the strongest of these is the hydrophobic effect. We describe how the hydrophobic effect can be used to drive organic molecule guests into the confined space of cavitand hosts. Other forces participating in guest binding include cation−π interactions, chalcogen bonding and even hydrogen bonding to water involved in the host structure. The reactions of guests take advantage of their contortions in the limited space of the cavitands which enhance macrocyclic and site‐selective processes. The cavitands are applied to the removal of organic pollutants from water and to the separation of isomeric guests. Progress is described on maneuvering the containers from stoichiometric participation to roles as catalysts.
Physicochemical insights into the rational designing of new acceptor molecules by donor bridge modifications for efficient solar cells: In silico chemistry
Authors: Haroon Muhammad , Fatima Wajiha , Janjua Muhammad Ramzan Saeed Ashraf
Published: June 2022

In small‐molecule organic solar cells (SM‐OSCs), it remains a big challenge to obtain favorable bulk heterojunction morphology by acceptor material design. In this report, efforts are being made to design efficient acceptor molecules for the active layer of the organic solar cell. Donor bridge modifications have been made by using effective donor units, and thus, four new molecules (KSD1–KSD4) have been designed and examined theoretically. Density functional theory (DFT) and time‐dependent density functional theory (TD‐DFT) have been employed for the calculation of various geometric and structural parameters. Transition density matrix, open‐circuit voltage, reorganizational energy of hole and electron, and photovoltaic characteristics of newly designed molecules have been examined through quantum chemical techniques. Additionally, the frontier molecular orbital analysis along with excitation and binding energies has been performed for these molecules. A narrow bandgap with a redshift in absorption spectrum is observed for KSD1–KSD4 molecules. Results of different analyses have recommended that the designed molecules are effective contributors for organic solar cell applications.
The challenges of the low birth rate in China
Authors: Lucero‐Prisno Don Eliseo , Kouwenhoven M. B. N. , Vicerra Paolo Miguel Manalang , Ma Zheng Feei , Méndez María José González , Gacutno‐Evardone Angelica Joyce Abordo , Manirambona Emery , Gyeltshen Dawa , Musa Shuaibu Saidu
Published: June 2022

Introduction

The population growth rate of China has been steadily declining owing to the low birth rate of the country. The Chinese census also indicates that the population is also rapidly ageing because of increasing life expectancy in conjunction with the low birth rate.

Method

We performed a commentary to point out the challenges of the low birth rate in China. A comprehensive data search was performed in data bases such as Google Scholar and PubMed using predetermined search term.

Results

The decline in birth rate is due to societal changes including increasing standard of living. Although the Chinese government has recently allowed couples to have up to three children in a major policy shift, many couples remain unwilling to have more than one child due to the high cost. An increasing fraction of Chinese women, particularly among the highly‐educated urban dwellers, no longer regard marriage and parenthood as essential aspects of life.

Conclusion

If not addressed urgently, the declining young population will impact China's future socio‐economic situation, as there will be a smaller workforce relative to an increasing dependent older population. The repercussions may cascade to other spheres of China's status, including socioeconomic, security and global influence, if not addressed decisively. It is imperative that the country develops policies, strategies, and approaches to tackle this issue, including human capital development and the use of technology and innovations.
Revisiting the issue of access to medicines in Africa: Challenges and recommendations
Authors: Adebisi Yusuff Adebayo , Nwogu Ifechukwu Benedict , Alaran Aishat Jumoke , Badmos Abubakar Olaitan , Bamgboye Adeboye Olakunle , Rufai Basirat Oluwadamilola , Okonji Osaretin Christabel , Malik Malik O. , Teibo John Oluwafemi , Abdalla Samah Faisal , Lucero‐Prisno Don Eliseo , Samai Mohamed , Akande‐Sholabi Wuraola
Published: June 2022

Background

Access to safe, effective, affordable, and quality medicines is an essential component of the right to health and is also one of the targets in the global development agenda. In this review article, we extensively discuss the challenges and issues surrounding access to medicines in the African region as well as provides recommendations for ensuring medicines security on the continent.

Methods

We conducted narrative review with the use of data reported in published literature, reports, and grey literature available in African countries on topics pertaining access to medicines. The authors also snowballed further data to gather information for this review and narrative synthesis was conducted.

Results

Africa faces a double burden of infectious and non‐communicable diseases and the need for effective universal access to medicines cannot be deemphasized. However, access to medicines on the continent is not without issues and challenges. Some of which are the high burden of infectious diseases and non‐infectious diseases, limited pharmaceutical industries and high costs of raw materials, overdependence on countries abroad for medicines, poor supply chain systems, lack of government investment in the pharmaceutical sector, unfavourable manufacturing conditions, limited health workforce, lack of sustainable health financing mechanisms, lack of infrastructures and technical know‐how, low investment on research and development, and circulation of fake and counterfeit medicines among others.

Conclusion

This review reifies that access to medicines in Africa faces numerous challenges and it emphasizes the urgent need to address these issues as the continent geared towards strengthening its health systems for universal health coverage.
Impact of abnormal karyotype on reproductive outcome in premature ovarian insufficiency
Authors: Grin Leonti , Ishizuka Bunpei , Onimaru Asami , Furuya Masataka , Kawamura Kazuhiro
Published: June 2022

Purpose

This study evaluated the reproductive potential of premature ovarian insufficiency (POI) patients with abnormal karyotypes undergoing infertility treatments.

Methods

A retrospective analysis of infertility treatments in POI patients with an abnormal karyotype treatment. Clinical and laboratory data were analyzed.

Results

The study group was forty‐nine POI patients. Follicular growth was achieved in 29% (89/307) controlled ovarian stimulation (COS) cycles in 57% (28/49) of patients. Oocyte retrieval was attempted in 47% (23/49) of patients with a proportion of successful oocyte retrieval per oocyte pick‐up (OPU) of 59.4% (41/69). The average number of retrieved oocytes was 2.4 ± 2.7 per patient and fertilization rate was 70.7% (29/41). Embryo transfer (ET) performed in eight patients with a total of nine ET attempts, resulting in 33.3% (3/9) of live birth rate per ET. Three patients delivered a healthy baby (6.1% (3/49) of live birth rate per patient). Mosaic Turner syndrome patients had a longer duration of amenorrhea and lower chances of successful follicular growth with OPU in 35.7% (5/14) of patients, whereas 47XXX had shorter duration of amenorrhea and COS with follicle growth with OPU in 83.3% (5/6).

Conclusion

COS might provide an opportunity for POI women with abnormal karyotypes to conceive a biological offspring.
Anticorrosive Performance of Wild Lycium ferocissimum Miers Fruit Extract on Carbon Steel in an Acidic Medium
Authors: Fadhil Hajer , Mraihi Farouk , Ayadi Pr. Malika Trabelsi , Cherif Pr. Jamila Kalthoum
Published: June 2022

In the last decade, the increasing environmental awareness among scientists brought out green innovations and adequate exploitation of natural resources in corrosion inhibition technology. Herein, the phenolic extract of the Lycium ferocissimum Miers fruit plant was prepared and tested at various stages of maturity as a corrosion inhibitor on commercial carbon steel in an acidic medium (HCl,1 M). The main components of L. ferocissimum extracts were identified by high‐performance liquid chromatography‐electrospray ionization mass spectrometry (HPLC‐MS/ESI). Nine phenolic compounds were found in the extract and the richness in polyphenol content was found in the first stage of maturity. The inhibition performance and mechanism were investigated using potentiodynamic polarization (PDP), electrochemical impedance spectroscopy (EIS), and weight loss measurements. Assay results revealed similar values in inhibition percentages, around 80 % at an extract concentration of 100 ppm. The inhibition efficiency was critically dependent on the stage of maturity and extractive solvent. Both electrochemical and loss measurements demonstrated that the first stage of maturity displays the highest corrosion inhibition effectiveness and the ethanolic extract presents the strongest active properties.
High Efficient Catalyst of N‐doped Carbon Modified Copper Containing Rich Cu−N−C Active Sites for Electrocatalytic CO2 Reduction
Authors: Sun Yingxin , Jing Haiyan , Wu Zongdeng , Yu Jia , Gao Haiwen , Zhang Yuehua , He Guangyu , Lei Wu , Hao Qingli
Published: June 2022

The synthesis of multi‐carbon products through electrochemical CO2 reduction reactions has attracted great interest from researchers. Herein, nitrogen‐ and carbon‐doped copper nanocatalyst (NC−Cu) containing abundant Cu−N−C active sites was prepared by thermal decomposition of the complexes containing copper and melamine. The NC−Cu catalyst exhibited an ideal current density of 22 mA cm−2 at −0.93 V versus reversible hydrogen electrode (vs. RHE) in CO2‐saturated 0.5 M KHCO3 medium, with ethanol as the predominant product at −0.93 V (vs. RHE) and a maximum Faraday efficiency of 31 %. The current density of the catalyst remained almost unchanged after 20 h of electrolysis, indicating its excellent stability. The excellent catalytic ability is attributed to the abundant Cu−N−C active sites of NC−Cu with 3D porous microstructure.
Azobenzene Photoswitches in Proteolysis Targeting Chimeras: Photochemical Control Strategies and Therapeutic Benefits
Authors: Negi Arvind , Kieffer Charline , Voisin‐Chiret Anne Sophie
Published: June 2022

The photoswitchable‐PROTACs have photoswitches that work as an actual ON/OFF switch for any particular bioactivity. In reported studies, the ON/OFF activity correlates with the photostationary state and quantum yield of a specific isomer under a definite wavelength of light, providing a spatiotemporal control over protein degradation (an example of photochemistry‐based precision medicine). The studies reported the role of azobenzenes as photoswitches (ortho‐tetramethoxybenzenes, ortho‐tetraflurobenzenes as push‐pull and push‐push) to develop light‐controlled PROTACs. This paper discussed the photophysical properties of photoswitchable‐PROTACs (such as photoisomerization, quantum yield, and thermal relaxation states) and correlated their photochemical‐based structural bioactivity relationships. The proteins studied under photoswitchable‐PROTACs are kinase proteins: BCR‐ABL fusion protein, ABL; Bromodomain proteins: BRD2, 3, 4; Immunophilins: FKBP12.
Recent progress in MXene layers materials for supercapacitors: High‐performance electrodes
Authors: Wang Yitong , Wang Yuhua
Published: June 2022

In 2011, Gogotsi et al. discovered a new type of two‐dimensional transition metal carbides and nitrides, called MXenes, which have become a dazzling new star in the energy storage industry. MXenes are endowed with a series of fascinating properties due to their unique structures and tunable surface chemical functional groups. The application of MXenes in electrochemical energy storage has attracted special attention, especially showing great potential in supercapacitor applications. Compared with other materials, MXenes have high mechanical flexibility, high energy density, and good electrochemical performance, so they are especially suitable as electrode materials for supercapacitors. However, similar to other 2D materials, due to the strong van der Waals forces, MXene layers inevitably undergo stacking agglomeration, resulting in severe loss of electrochemically active sites. If the self‐stacking of MXenes layers can be effectively suppressed, their electrochemical performance will be enhanced. Structural optimization of MXenes and composite doping of MXenes with other materials are two strategies with significant effects. This review summarizes recent advances in MXene synthesis, fundamental properties, and composite materials, focusing on the latest electrochemical performance of MXene‐based electrodes/devices, and puts forward the challenges and new opportunities that MXenes face in this emerging energy storage field.
Minimax optimal high‐dimensional classification using deep neural networks
Authors: Wang Shuoyang , Shang Zuofeng
Published: June 2022

High‐dimensional classification is a fundamentally important research problem in high‐dimensional data analysis. In this paper, we derive a nonasymptotic rate for the minimax excess misclassification risk when feature dimension exponentially diverges with the sample size and the Bayes classifier possesses a complicated modular structure. We also show that classifiers based on deep neural networks can attain the above rate, hence, are minimax optimal.
Erving Goffman on Misinformation and Information Control: The Conduct of Contemporary Russian Information Operations
Authors: Innes Martin , Dawson Andrew
Published: June 2022

Misinformation is a social problem increasingly, and routinely, commanding significant political and public attention. Less well known is that Erving Goffman was writing about misinformation as early as 1953 in his PhD thesis. Subsequent to which, he wrote repeatedly about the social organization and conduct of “information control” across several of his most influential publications. This article distils his ideas about these concepts to explore how they illuminate the contemporary phenomena of misinformation. To do this, empirical data are introduced from a large‐scale research program exploring the causes, communication, and consequences of digital information operations and campaigns, with a particular focus upon the Internet Research Agency and Instagram. The analysis attends in particular to sequences of “revealing moves” and “concealing moves” performed by the social media account operators. The dialogue between the data and Goffman's concepts outlines the precepts of a sociologically inflected, interactionist position on misinformation.
Advancements in Three Dimensional In‐Vitro Cell Culture Models
Authors: De Shreemoyee , Singh Neetu
Published: June 2022

The scientific field is observing a gradual shift from monolayer cultures to three‐dimensional (3D) models, as they give a more relevant data in pre‐clinical stages. This review summarizes the major techniques and materials used to develop 3D platforms, especially for cancer. It also discusses the challenges and some unresolved issues of the field and highlights some techniques that have made it to the market.
Curb Detection Using a Novel Deep Learning Framework Based on YOLO‐v2
Authors: Zou Min , Kageyama Yoichi , Akashi Takuya
Published: June 2022

Curb detection with a monocular camera is important to assist driving by detecting curbs to avoid accidents. However, various road scenes and curb shapes make it difficult to detect curbs based on a single image. In this study, a novel image‐based curb detection method that is highly efficient, inexpensive, and less complex than LiDAR‐based solutions was developed. A deep learning framework was used to detect curbs from road images automatically. A custom convolutional neural network (CNN) model was built, and another seven pretrained models were fine‐tuned for curb patch classification. The evaluation metrics, such as accuracy, F1‐score, area under curve, and prediction time, were considered comprehensively to select the optimal CNN architecture. Three promising CNN architectures were employed as classification networks and embedded into the YOLO‐v2 framework to construct curb detectors. The detection performance was evaluated in terms of the average precision on an urban road image dataset. By configuring parameters for the optimal CNN architecture, the best detector achieved an average precision of 99.16%, which verifies the effectiveness of the proposed method. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.