bluuebunny/crossref_metadata_2025_split huggingface dataset:
Repetitive Negative Thinking in Adolescents Who Stutter
Authors: Tichenor Seth E. , Gerwin Katelyn L. , Walsh Bridget 
Published: July 2023

Purpose:
Repetitive negative thinking (RNT) is the process of engaging in negatively valenced and habitual thought patterns. RNT is strongly associated with mental health conditions and often affects quality of life. This study explored RNT in older school-age children and adolescents who stutter to quantify the relationship between RNT and self-reported anxiety characteristics. An additional aim was to describe how individual differences in an adolescent's goal when speaking influences the frequency they engage in RNT.

Method:
Ninety-nine children and adolescents who stutter aged 9–18 years completed a measurement of the frequency/severity of RNT, a screener of anxiety characteristics, and a measure of adverse impact related to stuttering. Children aged 10 years and above also answered questions about their goal when speaking.

Results:
Individual differences in RNT significantly predicted Overall Assessment of the Speaker's Experience of Stuttering (OASES) Total Scores more so than a child or adolescent's age. Higher generalized or social anxiety scores were significantly correlated with more frequent RNT and higher OASES Total Scores. Individual differences in goal when speaking (i.e., whether or not to stutter openly) were found to predict RNT. Finally, 22 children and adolescents (22.2%) also screened positive for generalized anxiety disorder and 32 (32.3%) screened positive for social anxiety disorder.

Discussion:
These data provide strong evidence that (a) many children and adolescents who stutter engage in RNT; (b) children and adolescents who engage more frequently in RNT or who have higher OASES Total Scores may be at increased risk for more characteristics of generalized or social anxiety; and (c) individual differences in goal when speaking can predict the degree to which an adolescent engages in RNT.

Supplemental Material:

https://doi.org/10.23641/asha.23713296
Auswirkungen der COVID-19-Pandemie auf die Versorgung von Menschen mit Diabetes mellitus in Deutschland: ein Scoping Review-Update
Authors: Friedrichs Paula , Schmidt Kerstin , Hauner Hans 
Published: July 2023

ZusammenfassungBei der vorliegenden Arbeit handelt es sich um ein Scoping Review-Update zu den Auswirkungen der COVID-19-Pandemie auf die Versorgung von Menschen mit Diabetes in Deutschland. Dazu wurde eine systematische Literaturrecherche in Literatur- und Forschungsdatenbanken (BELIT, LIVIVO, DNB, CORDIS, MediaTUM, GEPRIS und PubMed), sowie mit Google und Google Scholar durchgeführt. Auf diese Weise konnten 30 Studien zur Versorgung von Menschen mit Diabetes im Verlauf der COVID-19-Pandemie identifiziert und in die Datenextraktion eingeschlossen werden. Die eingeschlossenen Studien wurden hinsichtlich ihrer methodischen Qualität bewertet. Thematisch bezogen sich die identifizierten Studien auf die folgenden Versorgungsbereiche: ambulante Versorgung, stationäre Versorgung, Arzneimittelversorgung, Psychosoziales, Disease-Management-Programme, Qualität der Diabeteseinstellung, Diabetes-Schulung, Telemedizin und Mortalität. Die Beobachtungszeiträume fast aller Studien umfassten mindestens die Anfangsphase der Pandemie (März bis Mai 2020) und gingen nicht über das Ende der 2. Welle hinaus (April 2021).Der Großteil der Studien zeigte keine gravierenden bzw. lediglich kurzfristige Effekte der COVID-19-Pandemie auf die Versorgung von Menschen mit Diabetes. Es gab vor allem in der Anfangsphase der Pandemie weniger Diabetes-Diagnosen im ambulanten und stationären Bereich. Weiter fand sich ein zeitweiser Anstieg diabetischer Ketoazidosen bei der Erstmanifestation von Kindern und Jugendlichen mit Typ-1-Diabetes und es gab Anhaltspunkte für eine höhere Rate von Majoramputationen bei Personen mit Typ-2-Diabetes.Zusammenfassend legen die hier gefundenen Studien mit deutlich besserer Datenlage nahe, dass die Mehrzahl der Menschen mit Diabetes während der COVID-19-Pandemie medizinisch adäquat versorgt war. Einen wichtigen Beitrag dazu leistete wahrscheinlich der Einsatz der Telemedizin. So wurden Telefon- oder Videokonsultationen häufig genutzt, um die medizinische Versorgung zu gewährleisten, ohne dass ein persönlicher Kontakt nötig war. Diese Erfahrungen sollten genutzt werden, um telemedizinische Ansätze auch zukünftig in der Versorgung von Menschen mit Diabetes stärker einzusetzen.
Management of Brachial Plexus Birth Injuries at British Columbia Children's Hospital
Authors: Verchere Cynthia , Durlacher Kim , Bellows Doria 
Published: July 2023

AbstractA multidisciplinary team at BC Children's Hospital provides brachial plexus birth injury management for our provincial catchment area. Although compared with many centers we service a relatively small clinic population, we have the benefit of universal health care, province-wide reach, and accessible research infrastructure. In 2008, we created the Sup-ER protocol, which includes an orthosis that passively positions the neonatal shoulder into more idealized glenohumeral contact during early growth. We have since shown that our Sup-ER patients have better shoulder outcomes, require less brachial plexus surgery, and need fewer shoulder tendon transfers than those patients treated in our clinic prior to 2008. We have also found that the rate and degree of elbow flexion contractures are reduced compared with results reported in the literature.
Detection of Antibiotic Resistance and Biofilm- Producing Ability of Staphylococcus Species in Clinical Isolates
Authors: Singh Shila Kumari , Bhattacharjee Minakshi , Unni Balagopalan , Kashyap Rajpal Singh 
Published: July 2023

Background
Staphylococci are responsible for life-threatening infections in hospitals and community. Their ability to produce multiple virulence factors and antibiotic resistance is an important reason of high mortality in staphylococcal infections. Biofilm production by these organisms makes it difficult to treat. Most of the treating antibiotics are failing and making it a matter of concern.

Aims
This study aims to detect the increased antibiotic resistance in biofilm-producing Staphylococcus and to compare the performance of three potential methods of detection.

Methods
A total of 81 isolates of staphylococci including coagulase negative staphylococci (CoNs), methicillin resistant S. aureus (MRSA), and methicillin sensitive S. aureus (MSSA) are included in this study. After the identification, an antibiotic sensitivity test was performed. Biofilm detection was done by three different methods: Congo red agar method, tube adherence method, and microtiter plate method.

Result
Out of the 81 samples, 37 CoNs, 17 MRSA, and 27 MSSA were identified. Out of them we got 43 (53%) biofilm producers by Congo red agar method, 40 (49%) by tube adherence method, and 52 (64%) producers by tissue culture plate/microtiter plate method. Most of the biofilm producers showed multiple drug resistance.

Conclusion
We found out that the microtiter plate method is sensitive and reliable as compared with the other two methods. Antibiotic resistance was found to be very common in biofilm producers. This was due to the resistance developed as a result of the matrix that does not let the antibiotic bind with the organisms. This can make the treatment of Staphylococcus very difficult in the future as the rate of drug resistance is faster as compared with newly emerging antibiotics.
Novel applications of generative adversarial networks (GANs) in the analysis of ultrafast electron diffraction (UED) images
Authors: Daoud Hazem , Sirohi Dhruv , Mjeku Endri , Feng John , Oghbaey Saeed , Miller R. J. Dwayne 
Published: July 2023

Inferring transient molecular structural dynamics from diffraction data is an ambiguous task that often requires different approximation methods. In this paper, we present an attempt to tackle this problem using machine learning. Although most recent applications of machine learning for the analysis of diffraction images apply only a single neural network to an experimental dataset and train it on the task of prediction, our approach utilizes an additional generator network trained on both synthetic and experimental data. Our network converts experimental data into idealized diffraction patterns from which information is extracted via a convolutional neural network trained on synthetic data only. We validate this approach on ultrafast electron diffraction data of bismuth samples undergoing thermalization upon excitation via 800 nm laser pulses. The network was able to predict transient temperatures with a deviation of less than 6% from analytically estimated values. Notably, this performance was achieved on a dataset of 408 images only. We believe that employing this network in experimental settings where high volumes of visual data are collected, such as beam lines, could provide insights into the structural dynamics of different samples.
A fault detection method for induction motors with sliding mode observers based on stochastic resonance and the Teager energy operator
Authors: Zhong Guanglin , Yu Wenxin , Wang Junnian 
Published: July 2023

Abstract
To accurately and sensitively track the stator current of an induction motor (IM) and detect faults, stochastic resonance (SR) and the Teager energy operator (TEO) are combined to detect a fault in the residual stator current of a sliding mode observer (SMO) under strong noise interference and complex weak fault conditions. First, a new reaching law is constructed to establish an SMO for better state tracking. Second, SR is used to absorb noise and amplify the detection residuals of the SMO, and the output results are estimated by the TEO in the time domain to achieve fault detection. Finally, the detection results of the IM stator and rotor winding faults and sensor intermittent faults are presented. The experimental results show that the SMO has higher state tracking accuracy and a faster rate of convergence. Moreover, the residual of the stator current is processed by SR and the TEO, and the effectiveness of fault detection is enhanced.
Sparse random similarity feature decomposition and its application in gear fault diagnosis
Authors: Liu Feng , Cheng Junsheng , Hu Niaoqing , Cheng Zhe , Yang Yu 
Published: July 2023

Abstract
As a new signal decomposition method, sparse random mode decomposition (SRMD) does not depend on the signal sampling process and has good anti-mode aliasing performance. However, SRMD needs preset decomposition parameters and cannot perform accurate decomposition for strong noise interference signals. Thus, this paper proposes a sparse random similarity feature decomposition (SRSFD) method to overcome the problems of SRMD. Firstly, SRSFD utilizes the windowed sinusoidal function to randomly generate time–frequency features. Then, by solving sparse optimization problem, the sparse random feature approximation of the input signal can be obtained and its corresponding time–frequency features can be applied to reconstruct the initial signal components. Finally, the initial signal components are regrouped by using periodic similarity to obtain the final components. The analytical results of simulation and actual gear fault signals show that SRSFD can effectively achieve adaptive signal decomposition and has better decomposition performance and noise robustness compared with existing methods.
A comprehensive review on recent developments of natural fiber composites synthesis, processing, properties, and characterization
Authors: Shebaz Ahmed J P , Satyasree Karedla , Rohith Kumar R , Meenakshisundaram Omkumar , Shanmugavel Sudarsan 
Published: July 2023

AbstractThe escalation of ecological awareness and sustainability has motivated many researchers to foster bio-composite studies and advancement in employing natural fibers and resin. During the last few decades, composites have emerged with various environmental impacts such as degradation, incineration, and toxicity. The credence is that bio-composite materials will downsize the need for environmentally and economically synthetic polymers. To enhance the degradability to the maximum extent, natural resin and natural fiber must be acquired from natural resources. A sequence of treatments must be followed throughout the resin synthesis process to obtain a usable and effective form of natural resin. Natural fibers are becoming more and more dominant over synthetic fibers because of their superior strength, stiffness, durability, and lack of toxicity. In comparison to synthetic fibers, biocomposites have the potential to diminish material expenses while improving mechanical properties. The processing techniques of compression molding, injection molding, and extrusion are frequently employed for biopolymer composite preparations. The ultimate properties of the composite are determined by the degree of adhesion between the matrix and fiber. To assess the mechanical and thermal properties of biocomposites, tests such as tensile, flexural, impact, thermogravimetric analysis, and dynamic mechanical analyzer are conducted. Many applications of bio-composites have created new opportunities for research and business ventures. Bio-composites are non-abrasive, degradable, and used for various purposes like packaging, medicine, agriculture, and the automotive industry. The undesirable factors like degradation, incineration, and recycling problem of non-biodegradable composite have induced the research and evolution of bio-composite. This decisive review would manifest a summary concerning the framework of natural resins, natural fibers, and bio-composites, the factors affecting the characteristics of bio-composites, and the future prospects for this field.
CAMEL NANOBODIES NEUTRALIZE SARS-COV-2 VARIANTS
Authors: Hong Jessica , Kwon Hyung Joon , Cachau Raul , Butay Kevin John , Duan Zhijian , Li Dan , Ren Hua , Hsieh Chao-Ming , Dandey Venkata P , Borgnia Mario J , Xie Hang , Ho Mitchell 
Published: July 2023

Abstract

Background and Significance
With the emergence of SARS-CoV-2 variants during the global pandemic from 2020 to 2023, there is need for broadly neutralizing antibodies. Due to their small size and unique conformations, nanobodies can recognize protein cavities that are not accessible to conventional antibodies.

Methods and Results
Here, we used phage display libraries built from dromedary camels to isolate two VHH nanobodies (7A3 and 8A2), which have high affinity for the receptor-binding domain (RBD) of the SARS-CoV-2 spike. Cryo-EM complex structures revealed that 8A2 binds the RBD in its up mode and 7A3 targets a conserved and deeply buried site in the spike regardless of the conformational state of the RBD. At a dose of ≥5 mg/kg, nanobody 7A3 efficiently protected K18-hACE2 transgenic mice from the lethal challenge of SARS-CoV-2 variants B.1.351 or B.1.617. With the addition of omicron variant, a new VHH nanobody (J1B4) was isolated to target the S2 subunit of the SARS-CoV-2 spike that can bind across many variants including omicron. Trispecific nanobodies were made using 7A3, 8A2, and J1B4 which had increased binding signals compared to the nanobodies alone. Using this method, we hope to create a therapeutic that is able to broadly neutralize not only all pre-existing variants of SARS-CoV-2, but also be effective towards future SARS-CoV related variants.

Conclusions and Future Directions
By combining nanobodies targeting the RBD of the S1 subunit (7A3+8A2) with a nanobody targeting the S2 subunit (J1B4), we can increase the chance of protection against all SARS-CoV-2 infections. Due to the increased protein binding of the trispecific compared to individual nanobodies alone, it shows great promise that the trispecific may be able to enhance its activity across all variants. Nanobody-based therapeutics may be developed as a nasal spray which can be self-administered and inhaled directly to the lungs to treat the infection at its source.
DEVELOPMENT OF A SELECTIVE CD16A-BASED NK CELL ENGAGER UTILIZING ANTIBODIES TARGETING A SINGLE AMINO ACID VARIATION
Authors: Liao Wuxiang , Tumanut Christine , Li Lin , Corper Adam , Challa Dilip , Chang Alex , Begum Hydari , Farokhi Elinaz , Woods Catherine , Fan Xiaomin 
Published: July 2023

Abstract

Background and Significance
Natural killer (NK) cells play a vital role in the human innate immune system and are being explored as a promising approach for cancer immunotherapy. Of particular interest are NK cell engagers that can target and activate NK cells to attack cancer cells. In this study, we developed novel NK cell engagers by targeting the NK cell activating receptor CD16a using antibodies that selectively distinguish between CD16a on NK cells and CD16b on granulocytes, which are highly homologous to each other.

Methods and Results
To generate antibodies with high developability, we employed a rational design approach to construct large yeast display libraries of human antibodies. This approach was based on the analysis of a deep sequencing dataset of human antibodies from over 500 individuals, which allowed us to determine the natural amino acid usage patterns of human antibody CDRs and mimic human antibody repertoires.
Through screening these libraries, we discovered two classes of antibody clones that selectively recognize CD16a without cross-reactivity to CD16b. Epitope mapping revealed that a single amino acid difference confers over 10,000-fold selectivity for one class of antibody clones, while for the other class a second unique epitope on CD16a was identified.
To evaluate the activity of these antibody clones, we produced bispecific antibody clones with one arm targeting CD16a and the other arm targeting a tumor-associated antigen (TAA). Our results demonstrated potent tumor cell-dependent activation of NK cells and effective killing of tumor cells. Several of these antibodies had greatly enhanced resistance to human IgG inhibition in killing target cells. Significantly, our anti-CD16a antibody clones exhibited superior performance compared to leading reference anti-CD16a clones in two distinct NK cell engager formats. This included higher affinity for CD16a, higher thermostability, and more potent killing activity both in the absence and presence of 10 mg/mL human IgGs as competitors.

Conclusion
Our findings indicate that anti-CD16a antibody-based NK cell engagers have significant potential for cancer immunotherapies.
TARGETING TREG CELLS BY TNFR2 ANTIBODY INDUCES TUMOR REGRESSION IN VIVO
Authors: Yi Zuoan David , He Chong , Hso Yueh-Mei , Strainic Michael , Yin Yong , Zhai Wenwu 
Published: July 2023

Abstract

Background
Tumor necrosis factor receptor 2 (TNFR2) is considered an appealing target due to its low-level expression on immune cells, but it could be upregulated on regulatory T cells (Tregs) in the tumor microenvironment which plays key roles in Treg proliferation and function. It has been demonstrated that Tregs with high TNFR2 expression were the most suppressive subsets among all Treg populations in the tumor. While early studies showed that TNFR2 co-stimulates naïve T cells, it has been revealed later that TNFR2 also limits CD8+ T-cell-mediated viral clearance and anti-tumor immunity by inducing rapid contraction of CD8+ T cells. Consistent with these findings, several publications reported that anti-TNFR2 antibody treatment exhibited robust antitumor efficacy. In short, TNFR2 signaling is critical in regulating immune response in different diseases. In the current study, the anti-human TNFR2 antibody SBT-1901 was developed and the anti-tumor activity was evaluated.

Materials and methods
SBT-1901 was generated through hybridoma and humanization technologies. The binding affinity and specificity were tested by ELISA, FACS, and OCTET. The function of SBT-1901 was tested in TNFR2-Fas overexpressing Ramos cells and in Treg proliferation assay. The in vivo anti-tumor activity and pharmacokinetics of SBT-1901 were evaluated in the human TNFR2 transgenic mouse model (Biocytogen) bearing MC38 tumor.

Results
SBT-1901 binds to the extracellular domain of human and cynomolgus TNFR2 with the affinity of single digit-nanomolar. It competes with TNFα for binding to TNFR2 receptor and inhibits TNFα-induced TNFR2-Fas overexpressing RAMOS cell death. SBT-1901 also blocks TNFα induced Treg proliferation in human PBMC. In addition, SBT-1901 significantly inhibits MC38 tumor growth in a dose-dependent manner as a monotherapy and enhances anti-tumor efficacy of mPD-1 antibody in a combination study in human TNFR2 transgenic mouse model. SBT-1901 is currently under preclinical development.

Conclusions
Our studies show that SBT-1901 exhibits a very potent anti-tumor efficacy in vivo as a single agent or the combination. Therefore, it is highly valuable to further develop SBT-1901 for human cancer treatment.
ESTABLISHMENT OF AN ULTRA HIGH-THROUGHPUT PROTEIN PRODUCTION PLATFORM (ULTRA 96) FOR EARLY STAGE IN VITRO STUDIES
Authors: Jiang Kai , Li Huishuai , Tang Chuanlong , Zhang Dawei , Zhang Xuejian , Zhang Ying , Zhao Zhengyang , Zhou Jun , Lu Mengjie , Xiao Yongsheng , Feng Zhumei , Wu Jiansheng 
Published: July 2023

Abstract
Proteins are known as the building blocks of life which play many critical roles in the body. In early stage drug discovery, numerous μg to mg scale high quality proteins need to be produced for in vitro functional studies and therapeutic evaluation, including antigens, monoclonal antibodies (mAb), bispecific antibodies (bsAbs) as well as other Fc fusion proteins. High-throughput production (HTP) of various proteins with high quality in very short time is a big challenge in industry. Here we present how WuXi Biologics has created a powerful ultra HTP protein production platform (termed as “Ultra 96”) that can automatically produce proteins within 3 weeks with one step purification at 1~3mL expression scale by using 96 and 24 well DWP. High titer of expression, high quality of products, short timeline as well as low cost make “Ultra 96” a robust platform which can empower our clients and dramatically accelerate their early stage drug discovery projects.