bluuebunny/crossref_metadata_2025 huggingface dataset:
Silent Speech Interface: An Inversion Problem
Authors: Abirami S , Anirudh L , Vijayalakshmi P
Published: September 2022

When conventional acoustic-verbal communication is neither possible or desirable, silent speech interfaces (SSI) rely on biosignals, non-acoustic signals created by the human body during speech production, to facilitate communication. Despite considerable advances in sensing techniques that can be employed to capture these biosignals, majority of them are used under controlled scenarios in laboratories. One such example is Electromagnetic Articulograph (EMA), which monitors articulatory motion. It is expensive with inconvenient wiring and practically not portable in real world. Since articulator measurement is difficult, articulatory parameters may be estimated from acoustics through inversion. Acoustic-to-articulatory inversion (AAI) is a technique for determining articulatory parameters using acoustic input. Automatic voice recognition, text-to- speech synthesis, and speech accent conversion can all benefit from this. However, for speakers with no articulatory data, inversion is required in many practical applications. Articulatory reconstruction is more useful when the inversion is speaker independent. Initially, we analysed positional data to better understand the relationship between sensor data and uttered speech. Following the analysis, we built a speaker independent articulatory reconstruction system that uses a Bi- LSTM model. Additionally, we evaluated the trained model using standard evaluation measures.
Biomechanical Characterization of Human GAIT Using EMG Parameters
Authors: Das Chitra M , Nagarajan S , Poonguzhali S , Mohanavelu K
Published: September 2022

Predicting and analysing individual muscle forces during walking can give a good perspective of anatomical, physiological, and neurological characteristics of human movement. It can help analyse neuromuscular impairments of skeletal system and provide an understanding on how lower limb assistive devices affect wearer’s body, as these assistive devices are vital to assist people with disabilities to carry their daily activities with ease. Estimating force from EMG allows us to assess the contribution of an individual muscle to the over-all force applied by a group of muscles. This finding helps in understanding muscle dynamics during walking, which can serve as input for assistive devices. Thus, electromyography signals (EMG) can be an excellent choice for force estimation in kinesiological studies. This study aims to predict individual muscle force from EMG during walking. The right gastrocnemius lateralis muscle of a 23-year-old-male subject with no neurological/muscular disorder was analysed at normal walking. Two approaches were used to predict forces from EMG using MATLAB. The forces obtained were compared with force predicted using OpenSim. The main parameters used for prediction were muscle length, muscle velocity, pennation angle, and isometric force, along with EMG.
Automatic Seizure Detection Using Modified CNN Architecture and Activation Layer
Authors: Khan Izhar Dad , Farooq Omar , Khan Yusuf Uzzaman
Published: September 2022

An epileptology expert must visually inspect the EEG to identify abnormal neural activity, which is time-consuming and subject to human errors. The capability of convolution neural networks (CNN) to extract visuospatial features and learn from these discriminative features makes them useful for this task. This paper presents seizure classification based on long-term EEGs using CNN. After filtering, the scalogram is plotted using a 1-second window each. A recently published dataset (TUSZ v1.5.2) was used for the performance evaluation of various CNN-based deep neural networks. The best accuracy obtained for GoogLeNet and AlexNet is 95.88%, and 95.79% respectively with 50 epochs and 32 mini-batch sizes by using the SWISH activation function. The proposed hybrid architecture (AG86) for epoch 50 with mini-batch size 32 has shown the best testing results in terms of accuracy (94.98%) as compared to the SqueezeNet (93.19%), GoogLeNet (92.65%), and AlexNet (94.44%). Similar performance was observed using metrics specificity, sensitivity, Mathew correlation coefficient (MCC), and F1 score. A general inference based on evaluation can be drawn as the proposed hybrid architecture (AG86) showed better test results compared to pre-trained CNN models. Moreover, by replacing ReLU with the SWISH activation function, the performance of AlexNet and GoogLeNet improved.
Dose Response Curve Using Chemically Induced PCC Assay in Peripheral Cells Irradiated In-vitro to 5 MeV Alpha Particles Emitted From Radon Source
Authors: Meenakshi C , Chandrasekaran S , Rajesh N P , Venkatraman B
Published: September 2022

Bio-dosimetry is defined as estimation of dose received by individuals based on biological end points induced by ionizing radiation. By using cytogenetic assay, it is possible to quantify the absorbed dose. High linear energy transfer (LET) radiation produces dense ionizations along their path and causes more clustered DNA damage compared to low LET. Radon is a natural radioactive element present in the atmosphere mainly produced during decay of uranium. The main objective of the present study is to construct dose response curve by using Premature Chromosome Condensation (PCC) techniques in blood cells exposed in-vitro to radon exposure. Blood samples were drawn from healthy non-smokers (n=4), aged between 28 to 42 years and exposed to twenty doses of radon ranged between 0 to 5.5 mGy. A total of about 24000 metaphase spreads were counted to find the DNA damages include ring chromosomes (RC), dicentric chromosomes (DC) and acentric fragments (AF). As the dose increases gradual increase was observed in RC, DC and AF with the slope of 0.001, 0.005 and 0.064 respectively. So far, no calibration reference curve was generated for low dose radon using chemically induced PCC assay and hence this study is considered as first of its kind.
Design of a mobile application for the vaccination registry of children under 5 years
Authors: Chaupi Alvarez Miriam Senaida , Loja Ponce Erick Arturo , Auccahuasi Wilver
Published: September 2022

Information and Communication Technologies are allowing to improve the development of certain processes optimizing the management of information for users, as in the case of the vaccination control process to digitize the use of the vaccination card, being very important for the registration of the administration of vaccines to the child during his five years. This information should be easily accessible and available to parents and health personnel during each stage of vaccination. In the present work we developed a mobile application called Children’s Vaccine, with the purpose of registering and storing vaccine data (type, date and place of vaccination), as well as relevant information for the management of vaccines, the prototype developed was implemented in the health Center: Juan Pablo II Maternal and Child Center located in the District of Villa el Salvador, in Lima, Peru, in order to improve the quality of the service of attention. We present the results as performance tests to measure the influence of the application, this evaluation was carried out through an observation sheet with the comparison of records before and after the use of the application called “pre-test” and “post-test”. This application is applicable and scalable for various health centers.
Hardware Implementation Of ECG Signal Compression Using SPIHT
Authors: Shanmuga sundari M , Loganathan S , Sujatha C.M
Published: September 2022

Cardiovascular disorder is a primary cause of mortality throughout the world in both developed and underdeveloped countries. Continuous cardiac monitoring enables clinicians to identify arrhythmias and other heart conditions. Tele-cardiology introduces remote monitoring devices for tracking the cardiac activity of the patients. The large volume of Electrocardiogram (ECG) data needs to be stored, processed and transmitted by these portable health care devices. The implementation of ECG compression in hardware platform is crucial for continuous health monitoring applications. The aim of this work is to implement field programmable gate array based set partitioning in hierarchical trees-based electrocardiogram compression. Discrete wavelet transform method is employed to break up the signal into sub bands. The transformed coefficients after discrete wavelet transform are passed through dead zone quantization which rejects low magnitude values of transformed coefficients lying around zero. These quantized coefficients are then encoded by lossless set partitioning used in hierarchical trees compression approach. The introduction of dead zone quantization in the proposed technique is found to be effective and yields an increased compression ratio of 10.33 with decreased distortion value of 1.04 percent for ECG record 117 of MIT-BIH arrhythmia database.
Effect of grounding on electromyogram and hand grip strength in healthy young adults
Authors: Anusha  , Dwivedi Anjana
Published: September 2022

Handgrip strength has often used as a tool to measure upper body conditions including neuromuscular performance, frailty, and cardiovascular health. Grounding has been a way of living in past and presently have been demonstrated by researchers to speed wound healing, reduce inflammation, and balance excessive free radical charge in the body. Grounding is hypothesized to work in two ways-one by discharging the static field developed in the body by exposure to electrical devices and by neutralizing the excess free radicals generated in the body due to improper lifestyle. This study aims to analyze the change in handgrip strength and EMG signals in young adults pre-and post- grounding. The participants are students aged 22-28 having maximum exposure to mobile phones and laptop radiation especially due to the current pandemic situation for the necessity of taking online classes. We are trying to relate grounding and muscular performance (in terms of handgrip strength, fatigue time, electromyogram) to understand how grounding for few hours a day can make change in a person’s life. Grounding can be used as an effective lifestyle intervention for improving strength and hence quality of life. Even after only one hour of earthing, handgrip strength, EMG, and fatigue time were improved.
Inducement of Artificial Sleep using Low Strength Magnetic Waves
Authors: Sudhakar T. , Hari Krishnan G. , Prem Kumar J. , Divakaran Sindu , Janney Bethanney , Mohandass G. , Devanesan Pavithra S , Shalini S.
Published: September 2022

Every human need eight to ten hours sleep every day for healthy and good functioning of brain and body. Proposed system induces sleep using low frequency, low strength magnetic waves produced by using coil circuitry. Majority of age people, people with anxiety, stress, depressed feel difficulty to get sleep due to few unknown factors. Our proposed system will induce sleep without drugs, meditation and other chemical-based methods having huge side effects.
Methodology for the multichannel recording of upper limb muscle activity
Authors: Ovalle Christian , Cordova-Buiza Franklin , Herrera Lucas , Auccahuasi Aly , Echevarría Martha Romero , Rojas Karin , Urbano Kitty , Loza Ana Barrera , Revilla Jorge Figueroa , Herrera Salazar José Luis
Published: September 2022

In the study of the functioning of the muscle, the study standard is to be able to analyze its behavior or functioning, this behavior is represented by a continuous signal where the muscle signal can be recorded and visualized, to perform this registration a designed circuit is required For the capture of electromyography signals, there are many options of these circuits in the market, depending on the application, the part of the body that is required to be analyzed, the best option can be chosen, in this work, we present a methodology for recording in Simultaneous 8 signals, for the characteristic use of the arm muscles, due to its special shape, which allows it to be placed in the form of a bracelet, the signals that are acquired simultaneously and individually, can be used in many applications depending on the problem and challenge, recommending for use on the arm and providing a clean signal allowing Being used in the design of detection mechanisms for some pathologies related to the arm muscles and in the design of control mechanisms for the design of prostheses.
Effective minutiae extraction and template creation in fingerprints
Authors: Karuppathal E , Kalpana R , Thilagavathy B , Baghavathi Priya S , Rajamanogaran M
Published: September 2022

Despite years of research in using the fingerprint as a biometric entity, there remains a niche to improve the underlying accuracy, specifically on enhancement, feature extraction and classification consideration. Attempted in this paper is a ridge compensation filtering technique for enhancement, followed by minutiae extraction and false minutiae removal and eventually a procedure for template creation. The extracted features are evaluated using metrics like accuracy, error rate and goodness index. These values were found to be better when compared with the results of some state-of-art algorithms, which endorse the effectiveness of the first two stages. Mahalanobis distance (MD) is used to recognise the fingerprints through the generated features that resulted in accuracy above 92%. Finally, convolution neural network (CNN) is used to cross-examine the recognition capacity. Though CNN also able to give a similar accuracy, the proposed algorithm is simple and robust and hence easily embedded in hand-held devices.
Deep ensemble of texture maps for false positive reduction in mammograms
Authors: Srinivashini N , Raveenthini M , Lavanya R
Published: September 2022

Worldwide, breast cancer is a life-threatening disease attributing to increased mortality rates among women. Mammograms are commonly used for screening breast cancer in asymptomatic stages. However, the subtle nature of abnormalities in early stages makes mammogram analysis a cumbersome task. A computer aided diagnosis (CAD) system can complement subjective diagnosis of physicians with its objective assessment. Mass detection is the most important task in breast cancer diagnosis, as masses are the prominent indicators of the disease. Nevertheless, it is the most challenging task due to the ambiguity between masses and the surrounding normal tissues, especially in dense breasts. Though CAD systems are effective in detecting masses with high sensitivity, the price paid is usually high false positive rates (FPR). Texture analysis is normally employed to reduce the FPR in mass detection, where texture features extracted from suspicious regions are used to build a classifier model to discriminate between actual masses and false positives. Deep learning (DL) is a data-driven model that is gaining increased importance in diverse fields, including medical diagnosis, that involve voluminous amounts of data. In particular, convolutional neural network (CNN) plays an important role in image analysis in various applications, including mammogram analysis. Converting raw images to texture maps can enhance the performance of CNN for false positive reduction. In this work, textural image maps based on Hilbert curve, forest fire model, Radon transform, discrete wavelet transform (DWT) and curvelet transform are analysed using CNN. More specifically, an ensemble of CNNs based on these individual textural image representations is constructed. The proposed work is validated on CBIS-DDSM, a publicly available benchmark dataset, demonstrating 100% accuracy for mass detection with 0% FPR.
Computer aided diagnosis system for breast density classification in mammograms
Authors: Shrinithi S , Vijayan Devi , Lavanya R
Published: September 2022

Breast cancer is a deadly disease affecting women around the globe. Mass detection in the breast tissue at an early stage can lessen the mortality rate occurring due to breast cancer. Through mammograms, the presence of masses can be detected at an early stage, however, it’s sensitivity and specificity are limited in the case of dense tissues. Identification of the breast density type prior to the detection of mass can lessen the chance of misclassifying a breast tissue as normal or abnormal, which eventually decreases the false negative and false positive rate. The proposed system classifies breast density on the basis of Breast Imaging Reporting and Data System (BI-RADS). The proposed method has explored the effect of local descriptors on breast density classification and various feature-classifier combinations have also been explored for the classification. The proposed method validated on 624 mammograms from the Image Retrieval in Medical Applications (IRMA) version of the Digital Database for Screening Mammography (DDSM) database has produced an accuracy of 73% for multi-class breast density classification using the speeded-up robust features (SURF) and support vector machine (SVM) classifier.
Transfer learning approaches in deep learning for Indian sign language classification
Authors: Abraham Tuhina Sheryl , Sachin Raj S P , Yaamini A , Divya B
Published: September 2022

Speech is the major way of human communication, but when it is limited, humans move to tactile kinaesthetic communication. People with speech-hearing impairments use sign language as an example of such adaptations. The deaf community uses Indian sign language (ISL) throughout India. In India, 250 licensed sign language interpreters are serving a deaf population of 1.8 to 7 million individuals. ISL interpreters are badly needed at institutes and places where persons with hearing impairments communicate. An Indian sign language picture database for English alphabets is established in this project. To prepare it for training, several pre-processing techniques were used. The effectiveness of deep learning neural networks is frequently influenced by the quantity of data available. As a result, data augmentation, a strategy for adding more and diverse samples to train datasets, was used to boost the effectiveness and outcomes of machine learning models. Our model is trained in CNN models utilizing transfer learning methodologies, with an accuracy of 95% for vgg16 and an accuracy of 92% for the inception model. More study on this research, as well as real-time implementation, has the potential to better connect people with hearing loss to society.
Methodology for muscle recovery, through motor imagery techniques applying virtual reality
Authors: Ovalle Christian , Cordova-Buiza Franklin , Linares Oscar , Auccahuasi Aly , Echevarría Martha Romero , Meza Sandra , Urbano Kitty , Loza Ana Barrera , Revilla Jorge Figueroa , Bernardo Grisi
Published: September 2022

Recovery of movement is a long and hard process for patients. One of the most common problems that occurs is the so-called “phantom limb", which induces the body to feel strange due to the failure to use the injured limb. This process is due to the lack of use of the leg that in most cases is fractured and the long recovery time, so the use of crutches makes the body in conjunction with the brain understand that normal movement of the body is with the leg suspended and always with the help of crutches. In the present work a technique for the retraining of the brain is presented by means of which the brain is taught through the presentation of images if it corresponds to the right and left side of the arms and legs. This retraining makes it possible for the brain to understand the coordinated movement between the arms and legs. In addition to the use of virtual reality, through the OCULUS GEST II lenses, allowing maximum concentration, the results allow to improve the recovery time of patients, the technique can be used both in rehabilitation centers and in the patient’s own home patient.
Active contour-based segmentation of normal and fetal spina bifida ultrasound images
Authors: Ajitha R , Punitha N
Published: September 2022

Fetal spina bifida is a neurological disorder which occurs due to improper closure of the spinal column. Fetus identified with spina bifida suffers from various paralytic disorders throughout their lifespan. Early diagnosis of spina bifida aids in timely medical interventions. The ultrasound imaging is widely preferred for fetal monitoring. This study involves segmentation of the normal and abnormal fetal spine from ultrasound images using active contour algorithm. The images for analysis are collected from a diagnostic centre. The noise present in the images is removed using Wiener filter and anisotropic diffusion (AD) filter. The denoised images are evaluated with the metrics such as signal to noise ratio (SNR), peak signal to noise ratio (PSNR), structural similarity index measure (SSIM) and mean square error (MSE). The contrast enhancement is performed by histogram equalization (HE) and adaptive histogram equalization (AHE) techniques. The contrast enhanced images are validated by measures namely entropy and adaptive mean brightness error (AMBE). From the pre-processed image, the spine region is segmented using the active contour method. The results demonstrate that the AD filter with optimal parameters performs better than the Wiener filter for denoising. For the contrast enhancement, the AHE technique shows better performance compared to HE. The active contour technique is able to segment the spine regions in both the normal and spina bifida images. As early diagnosis of spina bifida is essential, this approach could be clinically significant.
Metal halide perovskites-based white light-emitting diodes
Authors: Yao Jisong , Xu Leimeng , Wang Shalong , Song Jizhong
Published: September 2022

White light-emitting diodes (WLEDs) serve as a replacement for traditional incandescent light due to their excellent characteristics, such as high brightness, efficiency in energy consumption, and long lifetime. The high-efficiency and low-cost white-emitting materials and light-emitting diode devices has always been the goal pursued in the field of lighting technology. Recently, metal halide perovskites are emerging as one of the most promising luminescent materials for next-generation WLEDs due to their facile synthesis and excellent optoelectronic properties, such as high photoluminescence quantum yields, widely tunable bandgap, and high charge-carrier mobility. Although the luminescence efficiency of perovskite emitters and WLED devices has increased rapidly over the past several years, achieving high-efficiency and stable WLEDs remains great challenges. In this review, we focus on the recent progresses of WLEDs based on metal halide perovskites including color-conversion WLEDs, tandem structure of WLEDs, double-emissive-layer of WLEDs, and single-emissive-layer of WLEDs. Importantly, we highlight the WLEDs based on a single emissive layer that show white electroluminescence directly from the perovskite emitters. Finally, we will give an outlook of future research avenues on how to reach the goal of efficient and stable perovskite-based WLEDs.
The Efficacy and Duration of Onabotulinum Toxin A in Improving Upper Facial Expression Lines With 64-Unit Dose Optimization: A Systematic Review and Meta-Analysis With Trial Sequential Analysis of the Randomized Controlled Trials
Authors: Rahman Eqram , Mosahebi Afshin , Carruthers Jean D A , Carruthers Alastair
Published: September 2022

Background

Onabotulinumtoxin A (Onabot A) was the first treatment to be approved for aesthetic indications, namely glabellar lines (GLs), crow's feet lines (CFLs), and forehead lines (FHLs), with a cumulative dose of 64 U.

Objectives

The aim of this study was to conduct a meta-analysis to combine the available data for approved doses for GLs, CFLs, and FHLs to explore the effect and duration of simultaneous treatment with Onabot A.

Methods

PubMed/MEDLINE, Embase, and other national clinical trial registries were searched for randomized controlled trials from January 2010 to July 2022. The meta-analysis, trial sequential analysis, and investigator-assessed time to return to nonresponder status in GLs, CFLs, and FHLs following Onabot A were plotted to elicit a cumulative dose-adjusted response curve based on Kaplan-Meier analysis with a log-rank test.

Results

Fourteen randomized controlled trials were eligible for quantitative analysis. A total of 8369 subjects were recruited across the trials. The meta-analysis results show that Onabot A is very effective in reducing moderate to severe GLs, CFLs, and FHLs. The cumulative Z-curve for GLs, CFLs, and FHLs also exceeds the required information size (RIS). Kaplan-Meier analysis with a log-rank test demonstrated that simultaneous treatment of GLs, CFLs, and FHLs requires 182 days (95% CI = 179, 215 days) (P < 0.00002) to return to nonresponder status.

Conclusions

Treatment of the upper facial expression lines with Onabot A is effective, and the approved cumulative dose of 64 U gives longer-lasting effects.

Level of Evidence: 1
The Relationship between Workplace Support and Turnover intention amongst Chinese Social Workers: A Moderated Mediation Model
Authors: Li Hongfei , Mo Jian
Published: September 2022

The workplace support, job burnout and income are powerful predictors of turnover intention, yet the potential mechanisms remain not fully understood amongst social workers in China. Framing the job demands-resources model, this study established a moderated mediation model to test the role of job burnout in mediating the association between workplace support and turnover intention, as well as the role of income in moderating the above mediating process. A survey was distributed to social workers from the China Social Work Longitudinal Study in 2019 to investigate their demographic information, Maslach’s Burnout Inventory, workplace support and turnover intention, and 4,704 respondents were included in the final analyses. The results showed that workplace support of social workers was negatively associated with turnover intention. Moderated mediation analyses revealed that monthly income buffered the negative association amongst the triad of workplace support, job burnout and turnover intention. The findings suggest that the government and social service agencies need to provide workplace support and offer a satisfying salary to reduce job burnout and turnover intention of social workers.
LC–MS/MS Method Assay for Simultaneous Determination of the Apixaban and Metformin in Rat Plasma: Assessment of Pharmacokinetic Drug–Drug Interaction Study
Authors: Wang Libin , Shang Kun , Feng Tian , Dong Wei , Wang Fang , Shen Xin
Published: September 2022

A simple, sensitive and accurate LC–MS/MS method was developed and validated for the simultaneous quantification of apixaban (APB) and metformin (MET) in rat plasma using rivaroxaban as internal standard (IS). An Inertsil ODS3 C18 column (150 × 4.6 mm, 5 μm) was used for chromatographic separation with isocratic elution. Multiple reaction monitoring (MRM) using positive-ion ESI mode to monitor ion transitions of m/z 459.8 → 442.8 for APB, m/z 130.2 → 71.2 for MET, m/z 436.8 → 144.9 for IS. The procedure of method validation included selectivity, linearity, precision, accuracy, matrix effect, extraction recovery and stability were conducted according to the guidelines of EMA and FDA. The method was validated over the concentration range of 0.5–250 ng/mL for APB and 8–8000 ng/mL for MET. The intra- and inter-day precision and accuracy of the quality control samples exhibited relative standard deviations (RSD) < 12.5% and the accuracy values ranged from −8.6 to 12.4%. Recovery and matrix effect values variations were all less than 15%. After oral administration APB and MET to rats, the comparison of pharmacokinetic parameters of APB in the single and co-administrated groups showed significant difference in AUC(0-t) from 730.71 ± 121.31 to 573.07 ± 90.13 ng/mL·h, t1/2 from 5.86 ± 3.21 to 4.24 ± 1.15 h and Cmax from113.54 ± 24.04 to 159.42 ± 54.6 ng/mL. The comparison of pharmacokinetic parameters of MET in the single and co-administrated groups showed significant difference in t1/2 from 2.83 ± 1.81 to 3.97 ± 0.57 h and Cmax from 4015.76 ± 873.23 to 3153.6 ± 1012.51 ng/mL. The results indicated that drug–drug interactions (DDI) occurred might be owing to APB affect one or all of OCTs, MATE1, MATE2-K.
Pathogens Identified by Minimally Invasive Tissue Sampling in India and Pakistan From Preterm Neonatal Deaths: The PURPOSE Study
Authors: Ghanchi Najia Karim , Ahmed Imran , Kim Jean , Harakuni Sheetal , Somannavar Manjunath S , Zafar Afia , Tikmani Shiyam Sunder , Saleem Sarah , Goudar Shivaprasad S , Dhaded Sangappa M , Guruprasad Gowdar , Yogeshkumar S , Hwang Kay , Aceituno Anna , Silver Robert M , McClure Elizabeth M , Goldenberg Robert L
Published: September 2022

Background

We identified pathogens found in internal organs and placentas of deceased preterm infants cared for in hospitals in India and Pakistan.

Methods

Prospective, observational study conducted in delivery units and neonatal intensive care units. Tissue samples from deceased neonates obtained by minimally invasive tissue sampling and placentas were examined for 73 different pathogens using multiplex polymerase chain reaction (PCR).

Results

Tissue for pathogen PCR was obtained from liver, lung, brain, blood, cerebrospinal fluid, and placentas from 377 deceased preterm infants. Between 17.6% and 34.1% of each type of tissue had at least 1 organism identified. Organism detection was highest in blood (34.1%), followed by lung (31.1%), liver (23.3%), cerebrospinal fluid (22.3%), and brain (17.6%). A total of 49.7% of the deceased infants had at least 1 organism. Acinetobacter baumannii was in 28.4% of the neonates compared with 14.6% for Klebsiella pneumoniae, 11.9% for Escherichia coli/Shigella, and 11.1% for Haemophilus influenzae. Group B streptococcus was identified in only 1.3% of the neonatal deaths. A. baumannii was rarely found in the placenta and was found more commonly in the internal organs of neonates who died later in the neonatal period. The most common organism found in placentas was Ureaplasma urealyticum in 34% of the samples, with no other organism found in >4% of samples.

Conclusions

In organ samples from deceased infants in India and Pakistan, evaluated with multiplex pathogen PCR, A. baumannii was the most commonly identified organism. Group B streptococcus was rarely found. A. baumannii was rarely found in the placentas of these deceased neonates.
3D chromatin structure in chondrocytes identifies putative osteoarthritis risk genes
Authors: Thulson Eliza , Davis Eric S , D’Costa Susan , Coryell Philip R , Kramer Nicole E , Mohlke Karen L , Loeser Richard F , Diekman Brian O , Phanstiel Douglas H
Published: September 2022

Genome-wide association studies have identified over 100 loci associated with osteoarthritis risk, but the majority of osteoarthritis risk variants are noncoding, making it difficult to identify the impacted genes for further study and therapeutic development. To address this need, we used a multiomic approach and genome editing to identify and functionally characterize potential osteoarthritis risk genes. Computational analysis of genome-wide association studies and ChIP-seq data revealed that chondrocyte regulatory loci are enriched for osteoarthritis risk variants. We constructed a chondrocyte-specific regulatory network by mapping 3D chromatin structure and active enhancers in human chondrocytes. We then intersected these data with our previously collected RNA-seq dataset of chondrocytes responding to fibronectin fragment, a known osteoarthritis trigger. Integration of the 3 genomic datasets with recently reported osteoarthritis genome-wide association study variants revealed a refined set of putative causal osteoarthritis variants and their potential target genes. One of the putative target genes identified was SOCS2, which was connected to a putative causal variant by a 170-kb loop and is differentially regulated in response to fibronectin fragment. CRISPR-Cas9-mediated deletion of SOCS2 in primary human chondrocytes from 3 independent donors led to heightened expression of inflammatory markers after fibronectin fragment treatment. These data suggest that SOCS2 plays a role in resolving inflammation in response to cartilage matrix damage and provides a possible mechanistic explanation for its influence on osteoarthritis risk. In total, we identified 56 unique putative osteoarthritis risk genes for further research and potential therapeutic development.
Scaling-up through piloting: dual-track provider payment reforms in China’s health system
Authors: He Alex Jingwei
Published: September 2022

Gaining wide prominence in the global health arena, scaling-up increases the coverage of health innovations emerging from pilots and experimental projects to a larger scale. However, scaling-up in the health sector should not follow a linear ‘pilot-diffusion’ pathway in order to better facilitate local adaptation and policy refinement. This paper puts forth ‘scaling-up through piloting’ as a distinctive pathway for the strategic management of scaling-up in the health sector. It analyses the recent development of provider payment reforms in China, focusing particularly on the ongoing pilot programmes, namely diagnosis-related groups (DRGs) and diagnosis-intervention packet (DIP), that are being piloted in a dual-track fashion since 2020. Data were drawn from extensive documentary analysis and 20 in-depth interviews with key stakeholders, including decision-makers and implementers. This paper finds that scaling-up through piloting helps Chinese policymakers minimize the vast uncertainties associated with complex payment reforms and maximize the local adaptability of provider payment innovations. This pathway has forged a phased implementation process, allowing new payment models to be tested, evaluated, compared and adjusted in a full spectrum of local contexts before national rollout. The phased implementation creates a ‘slower is faster’ effect, helping reduce long-term negative consequences arising from improperly managed scaling-up in a complex system. Error detection and correction and recalibration of new policy tools can support national-level policy refinement in a more robust and dynamic fashion. Several key factors have been identified as crucial for strategic scaling-up: necessary central steering, a pragmatic piloting design, strong technical capacity and effective policy learning mechanisms
Humoral Immunogenicity After Vaccination Against SARS-CoV-2 Infection in Inflammatory Bowel Disease Patients Under Immunosuppressive Therapy: Should We Prioritize an Additional Booster Injection?
Authors: Macedo Silva Vítor , Lima Capela Tiago , Freitas Marta , Cúrdia Gonçalves Tiago , Boal Carvalho Pedro , Dias de Castro Francisca , João Moreira Maria , Cotter José
Published: September 2022

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may lead to the development of the novel coronavirus disease (coronavirus disease 2019 [COVID-19]). Scarce data are available regarding safety and efficacy of SARS-CoV-2 vaccination in inflammatory bowel disease (IBD) patients, which may present differences between subgroups. Lower humoral immunological response could require additional booster injections.

Methods

This is a prospective study including adult patients with IBD after complete vaccination against SARS-CoV-2 infection with BioNTech vaccine. Patients with previous SARS-CoV-2 infection were excluded. A control group with healthy individuals matched for age and sex was also analyzed. Blood samples were collected 30 days after complete vaccination to quantify immunoglobulin G (IgG) antibody titers against SARS-CoV-2 in both groups.

Results

The final sample included 81 IBD and 32 non-IBD patients, 55 (48.7%) of them women, with a mean age of 40.2 ± 13.0 years. From IBD patients, 58 (71.6%) had Crohn’s disease and 23 (28.4%) had ulcerative colitis. IBD patients had significantly lower median anti-SARS-CoV-2 IgG levels when compared with the control group (6479 [interquartile range (IQR) 1830-11883, 10 053] AU/mL vs 13 061 [IQR 2826-21427, 15 539] AU/mL; P = .003). Regarding IBD medication, significant lower levels of SARS-CoV-2 IgG antibodies when compared with control subjects were observed in patients treated with thiopurines (5423 [IQR 3109-13369, 10 260] AU/mL; P = .011), methotrexate (834 [IQR 507-3467, 4155] AU/mL; P = .002), anti-tumor necrosis factor α agents (5065 [IQR 1033-11669, 10 636] AU/mL; P = .001), and corticosteroids (548 AU/mL; P = .001). The incidence of SARS-CoV-2 infection after vaccination was also significantly higher in patients treated with these agents.

Conclusions

IBD patients treated with immunomodulators, anti-tumor necrosis factor α agents and corticosteroids presented significantly lower anti-SARS-CoV-2 IgG levels following complete vaccination when compared with healthy control subjects. These findings support the benefit of additional booster injections in this population.
Orally administered antigen can reduce or exacerbate pathology in an animal model of inflammatory arthritis dependent upon the timing of administration
Authors: Meehan Gavin R , Scales Hannah E , McInnes Iain B , Brewer James M , Garside Paul
Published: September 2022

Currently, treatments for rheumatoid arthritis (RA) are focussed on management of disease symptoms rather than addressing the cause of disease, which could lead to remission and cure. Central to disease development is the induction of autoimmunity through a breach of self-tolerance. Developing approaches to re-establish antigen specific tolerance is therefore an important emerging area of RA research. A crucial step in this research is to employ appropriate animal models to test prospective antigen specific immunotherapies. In this short communication, we evaluate our previously developed model of antigen specific inflammatory arthritis in which ovalbumin-specific T cell receptor transgenic T cells drive breach of tolerance to endogenous antigens to determine the impact that the timing of therapy administration has upon disease progression. Using antigen feeding to induce tolerance we demonstrate that administration prior to articular challenge results in a reduced disease score as evidenced by pathology and serum antibody responses. By contrast, feeding antigen after initiation of disease had the opposite effect and resulted in the exacerbation of pathology. These preliminary data suggest that the timing of antigen administration may be key to the success of tolerogenic immunotherapies. This has important implications for the timing of potential tolerogenic therapies in patients.
Prognostic health management of the robotic strain wave gear reducer based on variable speed of operation: a data-driven via deep learning approach
Authors: Raouf Izaz , Lee Hyewon , Noh Yeong Rim , Youn Byeng Dong , Kim Heung Soo
Published: September 2022

The robotic reducer is prone to failure because of its unique characteristics. Data from vibration and acoustic emission sensors have been used for the prognostics of the reducer. However, various issues are associated with such traditional techniques. Hence, our research group proposes a novel approach to utilize the embedded setup of the electrical current to detect the mechanical fault of the robotic reducer in the actual industrial robot. Previously, a comprehensive approach of feature engineering was proposed to classify the mechanical fault for the robotic reducer. However, handcraft-based feature extraction is quite a tedious task, and computationally expensive. These features require a well-designed feature extractor, and the features need to be manually optimized before feeding into classifiers. In addition, the handcrafted features are problem-specific, and are complicated to generalize. To resolve these challenges, deep features are extracted to classify the fault and generalize for two different motion profiles under different working conditions. In the proposed research work, the fault characteristic is generalized for variable speed of operations considering various kinds of scenarios. In this research work, the generalization capability of the proposed approach is comprehensively evaluated. For that purpose, the data under different working conditions such as of lower speeds, higher speeds, and speed sequestration are used as unseen data to validate the model. The authenticity of the presented approach can be supported by the performance evaluation for fault classification of the different motion profiles and speed of operations.
Lamin A/C impairments cause mitochondrial dysfunction by attenuating PGC1α and the NAMPT-NAD+ pathway
Authors: Maynard Scott , Hall Arnaldur , Galanos Panagiotis , Rizza Salvatore , Yamamoto Tatsuro , Gram Helena Hagner , Munk Sebastian H N , Shoaib Muhammad , Sørensen Claus Storgaard , Bohr Vilhelm A , Lerdrup Mads , Maya-Mendoza Apolinar , Bartek Jiri
Published: September 2022

Mutations in the lamin A/C gene (LMNA) cause laminopathies such as the premature aging Hutchinson Gilford progeria syndrome (HGPS) and altered lamin A/C levels are found in diverse malignancies. The underlying lamin-associated mechanisms remain poorly understood. Here we report that lamin A/C-null mouse embryo fibroblasts (Lmna−/− MEFs) and human progerin-expressing HGPS fibroblasts both display reduced NAD+ levels, unstable mitochondrial DNA and attenuated bioenergetics. This mitochondrial dysfunction is associated with reduced chromatin recruitment (Lmna−/− MEFs) or low levels (HGPS) of PGC1α, the key transcription factor for mitochondrial homeostasis. Lmna−/− MEFs showed reduced expression of the NAD+-biosynthesis enzyme NAMPT and attenuated activity of the NAD+-dependent deacetylase SIRT1. We find high PARylation in lamin A/C-aberrant cells, further decreasing the NAD+ pool and consistent with impaired DNA base excision repair in both cell models, a condition that fuels DNA damage-induced PARylation under oxidative stress. Further, ATAC-sequencing revealed a substantially altered chromatin landscape in Lmna−/− MEFs, including aberrantly reduced accessibility at the Nampt gene promoter. Thus, we identified a new role of lamin A/C as a key modulator of mitochondrial function through impairments of PGC1α and the NAMPT-NAD+ pathway, with broader implications for the aging process.
Effect of the phosphate binder sucroferric oxyhydroxide in dialysis patients on endogenous calciprotein particles, inflammation, and vascular cells
Authors: Thiem Ursula , Hewitson Tim D , Toussaint Nigel D , Holt Stephen G , Haller Maria C , Pasch Andreas , Cejka Daniel , Smith Edward R
Published: September 2022

Background

Calciprotein particles (CPPs), colloidal mineral-protein nanoparticles, have emerged as potential mediators of phosphate toxicity in dialysis patients, with putative links to vascular calcification, endothelial dysfunction and inflammation. We hypothesized that phosphate binder therapy with sucroferric oxyhydroxide (SO) would reduce endogenous CPP levels and attenuate pro-calcific and pro-inflammatory effects of patient serum towards human vascular cells in vitro.

Methods

This secondary analysis of a randomised controlled crossover study compared the effect of 2-week phosphate binder washout with high-dose (2000 mg/day) and low-dose (250 mg/day) SO therapy in 28 haemodialysis patients on serum CPP levels, inflammatory cytokine/chemokine arrays and human aortic smooth muscle cell (HASMC) and coronary artery endothelial cell (HCAEC) bioassays.

Results

In our cohort (75% male, 62 ± 12 years) high-dose SO reduced primary (amorphous) and secondary (crystalline) CPP levels {−62% [95% confidence interval (CI) −76 to −44], P < .0001 and −38% [−62 to −0.14], P < .001, respectively} compared with washout. Nine of 14 plasma cytokines/chemokines significantly decreased with high-dose SO, with consistent reductions in interleukin-6 (IL-6) and IL-8. Exposure of HASMC and HCAEC cultures to serum of SO-treated patients reduced calcification and markers of activation (IL-6, IL-8 and vascular cell adhesion protein 1) compared with washout. Serum-induced HASMC calcification and HCAEC activation was ameliorated by removal of the CPP-containing fraction from patient sera. Effects of CPP removal were confirmed in an independent cohort of chronic kidney disease patients.

Conclusions

High-dose SO reduced endogenous CPP formation in dialysis patients and yielded serum with attenuated pro-calcific and inflammatory effects in vitro.
Artificial neural networks predict the need for permanent cerebrospinal fluid diversion following posterior fossa tumor resection
Authors: Bray David P , Saad Hassan , Douglas James Miller , Grogan Dayton , Dawoud Reem A , Chow Jocelyn , Deibert Christopher , Pradilla Gustavo , Nduom Edjah K , Olson Jeffrey J , Alawieh Ali M , Hoang Kimberly B
Published: September 2022

Background

Resection of posterior fossa tumors (PFTs) can result in hydrocephalus that requires permanent cerebrospinal fluid (CSF) diversion. Our goal was to prospectively validate a machine-learning model to predict postoperative hydrocephalus after PFT surgery requiring permanent CSF diversion.

Methods

We collected preoperative and postoperative variables on 518 patients that underwent PFT surgery at our center in a retrospective fashion to train several statistical classifiers to predict the need for permanent CSF diversion as a binary class. A total of 62 classifiers relevant to our data structure were surveyed, including regression models, decision trees, Bayesian models, and multilayer perceptron artificial neural networks (ANN). Models were trained using the (N = 518) retrospective data using 10-fold cross-validation to obtain accuracy metrics. Given the low incidence of our positive outcome (12%), we used the positive predictive value along with the area under the receiver operating characteristic curve (AUC) to compare models. The best performing model was then prospectively validated on a set of 90 patients.

Results

Twelve percent of patients required permanent CSF diversion after PFT surgery. Of the trained models, 8 classifiers had an AUC greater than 0.5 on prospective testing. ANNs demonstrated the highest AUC of 0.902 with a positive predictive value of 83.3%. Despite comparable AUC, the remaining classifiers had a true positive rate below 35% (compared to ANN, P < .0001). The negative predictive value of the ANN model was 98.8%.

Conclusions

ANN-based models can reliably predict the need for ventriculoperitoneal shunt after PFT surgery.
Breaking the Tie: Benacerraf’s Identification Argument Revisited
Authors: Avron Arnon , Grabmayr Balthasar
Published: September 2022

Most philosophers take Benacerraf’s argument in ‘What numbers could not be’ to rebut successfully the reductionist view that numbers are sets. This philosophical consensus jars with mathematical practice, in which reductionism continues to thrive. In this note, we develop a new challenge to Benacerraf’s argument by contesting a central premise which is almost unanimously accepted in the literature. Namely, we argue that — contra orthodoxy — there are metaphysically relevant reasons to prefer von Neumann ordinals over other set-theoretic reductions of arithmetic. In doing so, we provide set-theoretical facts which, we believe, are crucial for informed assessment of reductionism.