bluuebunny/crossref_metadata_2025 huggingface dataset:
Development Of Electronic Data Analytics For Public Health Surveillance And Epidemiology
Authors: Deshmukh Dr. Shailesh Madhavrao , Salwadkar Mrunal
Published: September 2024

The process of assessing patient data that is taken from various medical devices is known as health care analytics. The patient's condition is projected by the analytics, which helps the physician support the diagnosis. The data created are referred to as Electronic Health Records (EHR) / Electronic Medical Records (EMR). Large volumes of electronic health and medical records being produced, giving rise to the idea of medical big data. Medical data may be in its early stages of development or fully developed and organised. The data research community now has a new way to experiment with medical data and access the results of intelligent algorithms through testing or historical experiences. The vast amount of medical big data used in this study project served as the impetus for an attempt to handle the data using supervised classifiers and predictors from clever machine learning techniques.  In healthcare, this analytical model is used to forecast illnesses. The goal of this project is to develop an intelligent framework for mining large amounts of medical data in order to assess public health issues and forecast illness occurrences.
Electrical Engineering Solutions for Personalized Public Health Monitoring Based on Activities and Vital Parameters
Authors: Deshmukh Dr. Shailesh Madhavrao , Shrirao Nisha Milind
Published: September 2024

The present paper proposes personalised remote healthcare based on soft computing. The primary goal of the thesis is to develop an intelligent, personalised RHM that uses personalised monitoring to create alerts in almost real-time settings and detect abnormalities in the status of human wellness. Since the activities have a significant impact on the vital sign values, the range of linguistic severity class labels in this research work is fixed based on the same, which results in a good level of personalisation of health data. The suggested study project can be very helpful to those under home quarantine or in specially designated quarantine areas, such as hotels, etc. Soft computing techniques offer a chance to create a RHM that can reliably detect changes in the population health state and accurately monitor many or all metrics of interest.
Electrical Safety in Public Healthcare Facilities and Medical Devices Management
Authors: Biradar Dr. Vijayalaxmi , Khemraj Ikhar Avinash
Published: September 2024

In hospitals, electrical hazards pose a serious risk that needs to be continuously assessed and improved. Medical surveillance systems and workplace assessments are frequently disregarded, and workers do not follow workplace instructions on safety precautions. The events are linked to a lack of understanding about the significance of electrical dangers and workplace safety and public health. Ignoring these evaluations could have negative effects on one's health, the quality of one's work, handicap, and impairment. The perspective of occupational safety and health on electrical dangers in hospital settings is described in this paper. Additional preventive actions were suggested in order to provide a list of workable and realistic actions that would create a safer and healthier workplace.
Enhancing Health Data Assessment Performance: A Multi-Sensor Focused Study for Public Health
Authors: Soni Palvi , Tandan Gajendra
Published: September 2024

The term health data assessment performance described the process of assessing efficacy of acquiring and reporting health data. Multi sensor approach for predicting diabetes in public health scenarios, multi sensor for public health assimilates assorted data source and addresses community health challenges widely and efficiently. In this study, we proposed a Horse Herd Fused Discriminant Generative Adversarial Network (HHF-DGAN) algorithm for diabetes prediction. Sensor-based diabetes data is gathered from kaggle, and then data preprocessing using z-score normalization is inaccurate records from a dataset. To extract feature from the pre-processed data, Short-Time Fourier Transform (STFT) is used for dimensionality reduction. HHF-DGAN is a public health technique that addresses diabetes prevention and management while also including multi sensor assessment data. The proposed methods are to evaluate F1-score (86%), precision (92%), recall (93%), and accuracy (93%). The effectiveness of the suggested strategy in improving prediction reliability for diabetes detection in public health circumstances has been established by comparing it with existing methods. The study concludes field of healthcare assessments with a robust framework for leveraging multi sensor data and deep learning methods in disease prediction.
Evaluation of Health Science Examination of Pharmacy Students Using Critical Thinking Ability
Authors: Gupta Khushboo , Sahu Kishor Kumar
Published: September 2024

This research aims to find a link between how well pharmacy students did on the Health Science Examination (HSE) and how well they did on a task that tests their critical thinking skills (package insert). Pharmacy students in their first year were given the HSE as part of a spring term task to help them think critically.  The box insert project was finished as part of a pharmacokinetics course in the same semester. The correlation analysis was used to check for a link between HSE scores and project grades. A weak but significant link existed between the learners' grades on the task and their overall HSE rating. Team-Based Learning (TBL) is a way of teaching that gets students to learn by doing and by getting them to think critically about how to solve problems. Given a weak but meaningful link with HSE scores, this study showed that a package insert task could be used to test pharmacy students' critical thinking skills.
Evaluation of patient's quality of counselling in the context of diabetes treatment by community pharmacists for Public Health
Authors: Sao Dr. Rupali Bharti , Chandrakar Kunal
Published: September 2024

Providing Patient Counseling (PC) may be beneficial in enhancing disease treatment results, especially for chronic illnesses like Diabetes Mellitus (DbM), which is prevalent in underdeveloped countries. This research aims to examine the counseling and contentment levels of patients who visit diabetes clinics in Community Pharmacies (CP), intending to contribute to the field of Public Health (PH). This research aimed to evaluate the efficacy of PC services offered to individuals with DbM. In this cross-sectional research, a patient simulation technique was used with an organized survey of 560 CPs chosen to offer primary healthcare. The survey has been split into three sections: demographics, PC methods used during prescription collection, and satisfaction assessment of the services rendered. The results revealed that PC was offered for taking medication among patients with type 1 DbM, but it was lacking for patients with type 2 DbM. Patients were provided with insufficient counseling on the potential adverse effects and the need to adopt a healthier lifestyle. The degree of satisfaction was a mere 20.2%, suggesting that there may be a deficiency in PC services. The investigation has shown inadequate PC procedures and low levels of contentment in the services offered by CP to patients with DbM. Given the rising occurrence of DbM and the presence of other medical conditions, it is crucial to provide PCs with DbM.
Integration of digital twins to simulate community health scenarios and evaluate the effectiveness of public health interventions led by pharmacists
Authors: Kumar Dr. Sanjay , Ikhar Sharyu Bhushan
Published: September 2024

Public health emergencies such as the 2019 coronavirus disease (COVID-19) have increased the focus on digital technology. A digital twin (DT) is a cybernetic representation of a physical object (e.g., a person or a community) that helps us comprehend the complexity of the real thing and makes it easier to foresee, avoid, track, and improve its actual performance. To prepare for a new age of reliable and precise public health and medical care, DT technology can propel a much-needed radical transformation of conventional electronic health and medical records, which centre on individuals and their aggregates covering populations. Hence, this paper presents the Digital Twin-based Public Health Intervention Model (DT-PHIM) to simulate community health led by pharmacists. The use of digital twins in healthcare has the potential to revolutionize workflow analysis and resource allocation, ultimately resulting in better patient care and more efficient operations. In addition, healthcare providers may hone their abilities and rehearse intricate treatments in a secure and realistic environment with the help of digital twins. There is great promise for digital twin technology to revolutionize healthcare by boosting innovation, patient safety, and overall patient outcomes. On top of that, DTs may help doctors and other medical staff, such as hospital pharmacists, make decisions by simulating how therapy would affect these patients. The experimental outcomes demonstrate that the suggested DT-PHIM model increases the patient data access ratio by 97.4%, the monitoring efficiency ratio by 96.2% and the decision-making ratio by 98.2% compared to other existing models.
Mechanical Engineering Solutions For Healthcare Accessibility And Affordability In Public Health
Authors: Tamrakar Dr. Gaurav , Ahlawat Dr. Amit
Published: September 2024

The commercial outlook for the healthcare industry is bright these days, both globally and in India. The need for prosthetics, implants, and surgical equipment, among other specialised or customised medical devices, is growing daily. Investigating personalised medical gadgets is crucial to take advantage of upcoming business prospects. In order to expand this commercial opportunity in terms of customised medical devices, additive manufacturing, or AM, can be extremely important. Further investigation into the public healthcare system revealed that the laparoscopic surgical method necessitates the use of specially made, ergonomic surgical instruments. Because laparoscopic surgery is done by staring at a monitor rather than making direct touch with the organs like open surgery does, surgeons doing this sort of procedure often lack hand-eye coordination. Surgical mistakes were discovered with this surgical method. The laparoscopic surgical instrument is the only interface device, and it must be designed to improve coordination and feel responsive during the procedure.
Next-Gen Public Healthcare: Modeling an Advanced Framework for Diabetes Management
Authors: Yadav Kamlesh Kumar , Kirit Dhablia Dharmesh
Published: September 2024

Advancements in biotechnology and public health technologies have significantly increased public health data, aiding early disease detection and prevention, particularly in diabetes, which can lead to serious public health issues. In this study, we propose a novel crow search-driven dynamic random forest for (CS-DRF) for diabetes management reorganization. The goal of this integrated strategy is to enhance diabetes treatment results and diagnosis. The Pima Indian Diabetes (PID) dataset is gathered from open-source Kaggle website for diabetes management. We implement our recommended evaluation technique using Python software. The findings showed that the CS-DRF performed more effectively than the others regarding F1-score-93.25%, accuracy-95.46%, specificity-92.38 %, sensitivity-92.22%, and precision-93.28%. The study's validation results demonstrate how advanced the structure model based on machine learning is in detecting diabetes management.
Pharmacists Impact on Promoting the Public Health
Authors: Pal Dr. Tarun , Dash Smruti Ranjan
Published: September 2024

Because they can guarantee that patients receive safe and effective medications, pharmacists are essential members of the healthcare team. In an effort to maximize patient results, they work in tandem with other medical specialists to evaluate pharmacological therapy, dispense medication, counsel patients on drug interactions and side effects, and monitor medication schedules. Pharmacists also give patients advice on managing illnesses, changing lifestyles, and adhering to medication regimens. The range of work that pharmacists do has expanded with the emergence of numerous global health issues. Safe and efficient drug usage by community and clinical pharmacists is necessary to provide the best possible patient outcomes. The public is still ignorant about the pharmacist's contribution to national and international health, nevertheless. They also perform drug use assessments, act as drug information specialists, and offer advice on the proper choice and dosage of medications. Pharmacists play a critical role in healthcare organizations as they strive to reduce prescription errors, enhance patient safety, and manage costs. The pharmacist can improve public health in a beneficial way. Thus far, the rise in the importance of pharmacists has been more influenced by the expansion of patient services than by a population-based approach to health. Pharmacists may find that integrating the five public health core competencies—social and behavioral science, health policy and administration, epidemiology, biostatistics, and environmental health sciences—into their pharmacy practice increases their efficacy and influence.
Promoting the Public Health by Medical Image Analysis and Disease Diagnosis
Authors: Biswas Debarghya , Tiwari Ankita
Published: September 2024

Public health has improved as a result of data analysis tools since they make disease identification early and simple. In the absence of data analysis methods, medical professionals' judgement is the only means of identifying the illness. This could be problematic in places without access to skilled medical professionals, which could ultimately result in the illness patient's death. Data analysis techniques are currently being applied in numerous medical disease detection situations in order to address the aforementioned challenges. The methods for detecting blood disorders are presented in this article. This model detects blood disorder disease using a blood smear in addition to a clinical report. The sick patients are classified using an ML classifier after an ML model extracts information from blood smear images and combines them with clinical features.
Public Health Initiative: Enhancing Stress Evaluation using EEG Data
Authors: Sharma Nikita , Ramesh Hajare Hirendra
Published: September 2024

Study proposes an innovative public health that uses EEG data processing to improve stress assessment. Stress is a widespread health issue that affects people in a variety of demographics. Stress evaluation techniques based on traditional self-reporting are biased and subjective. EEG records patterns of brain activity linked to stress reactions and offers an objective measurement. In this study, we proposed Social Spider Advanced Bidirectional Long ShortTerm Memory (SS-ABiLSTM), an innovative method for improving stress evaluation by integration of EEG data. Initially, EEG data is gathered, and then preprocessed the EEG data using min-max normalization to remove inaccurate records from a dataset. To extract features from the preprocessed data using the Discrete Wavelet Transform (DWT), this reliably extracts frequency-domain information from the data. The most discriminative characteristics for stress assessment to select feature using Recursive Feature Elimination (RFE). By combining these methods, stress assessment models that utilize EEG data have high accuracy. Utilizing the application of SS-ABiLSTM, that addresses stress prevention and management while also improving the ability to interpret EEG data in public health. The proposed methods are to evaluate F1-score (90.1%), precision (88.2%), recall (91.8%), and accuracy (98.97%). The accuracy of the proposed technique is superior to the existing techniques. Finally by using EEG data for stress evaluation in public health shows potential for more individualized care and better mental health results.
Relationship of TSH and FT3 Levels to The Incidence of Hashimoto's Thyroiditis in Autoimmune Patients
Authors: Anggraini Rahayu , Kamilah Benta Habibah E. , Ramasamy Rajesh , Samsudin Intan Nureslyna , Thambiah Subashini C.
Published: September 2024

Hashimoto's thyroiditis is portrayed by the presence of thyroid autoantibodies. Pathogenetic systems, a few cytokine networks have been recognized to be engaged with thyroid cells in a progression of proinflammatory impacts, like the statement of provocative parts, and a progression of imperfections in administrative Lymphocytes that control the deficiency of resistance to thyroid autoantigens, subsequently assuming an immediate part in the autoimmune cycle causing a few diligent side effects. The point of this review was to assess the connection between 36 autoimmune patients matured 14 to 52 years with responsive ANA test results. Then, Thyroid-Animate Hormone (TSH) and free Triiodothyronine (fT3) levels were analyzed utilizing the Enzyme-linked immunosorbent assay (ELISA) technique. The consequences of the review showed that the quantity of ladies was more prominent than men, 32 individuals (88.9%) and 10 individuals matured between 20-25 years. The typical TSH level was 9.65uIU/mL and the free T3 level was 1.64pg/ml. The consequences of the Spearman connection test among TSH and free T3 levels got a worth of p = 0.029 (p<0.05), implying that the connection between TSH levels and the free T3 test had an adequate relationship of - 0.364 (0.260-0.500), however was negative and not in a similar heading, so that when the levels TSH expands, fT3 levels will diminish. All in all, in autoimmune sufferers essential hypothyroidism happens, when the thyroid organ creates low Free T3, causing the deficiency of negative criticism restraint on the front pituitary, bringing about expanded creation of the TSH hormone which causes Hashimoto's thyroiditis.
Revolutionizing WBAN communication for public health: Effective Optimization strategy-driven health assessment
Authors: Sawlani Chandni , Sharma Pooja
Published: September 2024

This study explores the optimization procedures that are critical to enhancing WBAN communication efficacy in an environment of public health initiatives. In order to observe someone's physiological characteristics continuously and non-invasively, wireless body area networks (WBANs), are an essential piece of innovation for distant health observation. The WBAN individual nodes, yet, might relocate and lose reception from a distant base station over time. Thus, an effective inter-WBAN interaction approach is required to address this issue. In order to lower cost associated with networks and maximize cluster lifespan towards the network's effectiveness, this research develops a clustering-driven routing approach that uses cluster head serving as a gateway. For efficient cluster head selection, a novel customized chicken swarm optimization (CCSO) technique was introduced. Various parameter adjustments are made in multiple trials to verify the suggested approach effectiveness. The research conduct comprehensive comparison analysis of suggested and existing algorithms, several tests are conducted. The results show that the approach technique can increase the effectiveness of WBAN engagement and create clusters more quickly than the other methods in the framework of public health initiatives.
Self-analysis in Pharmacy and Health Science practices: A case study of pharmacy institutions
Authors: Shrivastava Pranjul , Ali Syed Sajid Ali Syed Sabir
Published: September 2024

Self-assessment (SA) is essential for a healthcare professional's ongoing growth and development, starting from their time as a student pharmacist and continuing throughout their professional career. The study examines the existing body of research on SA among students and practitioners and investigates the potential for enhancing this capacity in Pharmacy and Health Science. Despite the potential for improvement, learners and professionals still need help accurately assessing themselves. Until SA procedures improve, experts' evaluation of learners continues to be the primary method of testing abilities and knowledge. Although SA is crucial for lifelong learning, external evaluation is as critical for practitioners' ongoing professional growth.
Transforming Public Health Data Management in IoMT Networks Based on Innovative Offloading Scheme
Authors: Bharti Gopesh Kumar , Jaikumar Deshmukh Vaishnavi
Published: September 2024

Healthcare platform monitoring IoT-oriented technologies constitute the idea of Internet of Medical Things (IoMT) in public health and medical services. The amount and quality of created data have a substantial influence on data management and privacy compute offloading solutions are unable to keep up with the growing needs of the health industry, especially when fast and dependable communication was needed. The study suggests a unique approach called Mutated Barnacles Mating Optimization (MBMO) for assisting the data management issues in IoMT systems. The suggested MBMO framework successfully addresses problems that are common in the medical industry by using a data offloading technique. To overcome the issues of discrete tasks and resource allocation, guarantees the needs of dependable and efficient communication. We implemented Java software. The evaluation of the performance step encompasses several measures, such as energy consumption (J/ms) and Time delay (ms)model to assess the efficiency of the suggested forecasting algorithm. We performed an assessment of comparison with other established approaches results indicate that the suggested model produces superior results for assisting the data management issues in IoMT systems.
Building a Talent Portfolio: A Modern Approach to Career Development
Authors: Westover Jonathan
Published: September 2024

In today's disruptive business environment where entire job categories are emerging and transforming rapidly, traditional career path models centered on predefined vertical progression no longer adequately equip organizations with the workforce mobility and strategic resilience needed to dynamically deploy talent as work evolves. This article explores how progressive companies like global banking giant HSBC and humanitarian relief leader World Vision have overcome these challenges through transitioning to career portfolio-based talent systems that empower employees to curate diverse experiences through roles, projects, assignments and skills development opportunities. A shift from narrow career paths to emphasis on capability and experience building strengthens organizational agility through a multi-skilled workforce while providing strategic benefits to talent retention, succession planning and futureproofing the business in uncertainty. Perhaps most importantly, the career portfolio approach also empowers individual contributors with the versatility and lifelong learning critical for navigating today's fluid labor market landscape - futureproofing both their employability and work fulfillment in the new world of work.
Strength Underutilization: Why Talented People Don't Use Their Strengths
Authors: Westover Jonathan
Published: September 2024

This article explores why talented individuals frequently fail to fully utilize their innate strengths in their work despite years spent developing skills and abilities. Several reasons for strengths underutilization are examined based on research evidence. A key factor is the paradox between skills, which can be expanded through training and experience, versus immutable strengths that energize individuals. Additionally, rigid job descriptions and misalignment between individual strengths and organizational cultures that reward other attributes over talents hinder strengths application. Barriers like the difficulty of strengths development and lack of a shared strengths language are also discussed. Practical recommendations are provided for activating strengths through individual reflection, leadership support, and building an organizational strengths culture. The article aims to spark meaningful changes enabling every person to optimize their inborn talents daily through a concerted, multi-level strengths focus.
Next-level health: Aging at home – can our parents be techy?
Authors: Haller Andrew
Published: September 2024

Technology and our parents, it’s a tale as old as time; from the lady who thought her computer came with a cup holder (remember CD-ROMs?) to my dad trying to find the “any” button on his keyboard. In a world where nursing homes are becoming more expensive and more isolating for our loved ones, some people are turning to technology to keep them safer and closer to us.
WNKs regulate mouse behavior and alter central nervous system glucose uptake and insulin signaling
Authors: Jaykumar Ankita B , Binns Derk , Taylor Clinton A , Anselmo Anthony , Birnbaum Shari G , Huber Kimberly M , Cobb Melanie H
Published: September 2024

Certain areas of the brain involved in episodic memory and behavior, such as the hippocampus, express high levels of insulin receptors and glucose transporter-4 (GLUT4) and are responsive to insulin. Insulin and neuronal glucose metabolism improve cognitive functions and regulate mood in humans. Insulin-dependent GLUT4 trafficking has been extensively studied in muscle and adipose tissue, but little work has demonstrated either how it is controlled in insulin-responsive brain regions or its mechanistic connection to cognitive functions. In this study, we demonstrate that inhibition of WNK (With-No-lysine (K)) kinases improves learning and memory in mice. Neuronal inhibition of WNK enhances
in vivo
hippocampal glucose uptake. Inhibition of WNK enhances insulin signaling output and insulin-dependent GLUT4 trafficking to the plasma membrane in mice primary neuronal cultures and hippocampal slices. Therefore, we propose that the extent of neuronal WNK kinase activity has an important influence on learning, memory and anxiety-related behaviors, in part, by modulation of neuronal insulin signaling.
A mathematical model for ketosis-prone diabetes suggests the existence of multiple pancreatic β-cell inactivation mechanisms
Authors: Ridout Sean A , Vellanki Priyathama , Nemenman Ilya
Published: September 2024

Ketosis-prone diabetes mellitus (KPD) is a subtype of type 2 diabetes, which presents much like type 1 diabetes, with dramatic hyperglycemia and ketoacidosis. Although KPD patients are initially insulin-dependent, after a few months of insulin treatment, ∼ 70% undergo near-normoglycemia remission and can maintain blood glucose without insulin, as in early type 2 diabetes or prediabetes. Here, we propose that these phenomena can be explained by the existence of a fast, reversible glucotoxicity process, which may exist in all people but be more pronounced in those susceptible to KPD. We develop a simple mathematical model of the pathogenesis of KPD, which incorporates this assumption, and show that it reproduces the phenomenology of KPD, including variations in the ability for patients to achieve and sustain remission. These results suggest that a variation of our model may be able to quantitatively describe variations in the course of remission among individuals with KPD.
I-Spin live: An open-source software based on blind-source separation for real-time decoding of motor unit activity in humans
Authors: Rossato Julien , Hug François , Tucker Kylie , Gibbs Ciara , Lacourpaille Lilian , Farina Dario , Avrillon Simon
Published: September 2024

Decoding the activity of individual neural cells during natural behaviours allows neuroscientists to study how the nervous system generates and controls movements. Contrary to other neural cells, the activity of spinal motor neurons can be determined non-invasively (or minimally invasively) from the decomposition of electromyographic (EMG) signals into motor unit firing activities. For some interfacing and neuro-feedback investigations, EMG decomposition needs to be performed in real-time. Here, we introduce an open-source software that performs real-time decoding of motor neurons using a blind-source separation approach for multichannel EMG signal processing. Separation vectors (motor unit filters) are optimised for each motor unit from baseline contractions and then re-applied in real-time during test contractions. In this way, the firing activity of multiple motor neurons can be provided through different forms of visual feedback. We provide a complete framework with guidelines and examples of recordings to guide researchers who aim to study movement control at the motor neuron level. We first validated the software with synthetic EMG signals generated during a range of isometric contraction patterns. We then tested the software on data collected using either surface or intramuscular electrode arrays from five lower limb muscles (gastrocnemius lateralis and medialis, vastus lateralis and medialis, and tibialis anterior). We assessed how the muscle or variation of contraction intensity between the baseline contraction and the test contraction impacted the accuracy of the real-time decomposition. This open-source software provides a set of tools for neuroscientists to design experimental paradigms where participants can receive real-time feedback on the output of the spinal cord circuits.
CausalXtract: a flexible pipeline to extract causal effects from live-cell time-lapse imaging data
Authors: Simon Franck , Comes Maria Colomba , Tocci Tiziana , Dupuis Louise , Cabeli Vincent , Lagrange Nikita , Mencattini Arianna , Parrini Maria Carla , Martinelli Eugenio , Isambert Hervé
Published: September 2024

Live-cell microscopy routinely provides massive amount of time-lapse images of complex cellular systems under various physiological or therapeutic conditions. However, this wealth of data remains difficult to interpret in terms of causal effects. Here, we describe CausalXtract, a flexible computational pipeline that discovers causal and possibly time-lagged effects from morphodynamic features and cell-cell interactions in live-cell imaging data. CausalXtract methodology combines network-based and information-based frameworks, which is shown to discover causal effects overlooked by classical Granger and Schreiber causality approaches. We showcase the use of CausalXtract to uncover novel causal effects in a tumor-on-chip cellular ecosystem under therapeutically relevant conditions. In particular, we find that cancer associated fibroblasts directly inhibit cancer cell apoptosis, independently from anti-cancer treatment. CausalXtract uncovers also multiple antagonistic effects at different time delays. Hence, CausalXtract provides a unique computational tool to interpret live-cell imaging data for a range of fundamental and translational research applications.
Reproducible, data-driven characterization of sleep based on brain dynamics and transitions from whole-night fMRI
Authors: Yang Fan Nils , Picchioni Dante , de Zwart Jacco A , Wang Yicun , van Gelderen Peter , Duyn Jeff H
Published: September 2024

Understanding the function of sleep requires studying the dynamics of brain activity across whole-night sleep and their transitions. However, current gold standard polysomnography (PSG) has limited spatial resolution to track brain activity. Additionally, previous fMRI studies were too short to capture full sleep stages and their cycling. To study whole-brain dynamics and transitions across whole-night sleep, we used an unsupervised learning approach, the Hidden Markov model (HMM), on two-night, 16-hour fMRI recordings of 12 non-sleep-deprived participants who reached all PSG-based sleep stages. This method identified 21 recurring brain states and their transition probabilities, beyond PSG-defined sleep stages. The HMM trained on one night accurately predicted the other, demonstrating unprecedented reproducibility. We also found functionally relevant subdivisions within rapid eye movement (REM) and within non-REM 2 stages. This study provides new insights into brain dynamics and transitions during sleep, aiding our understanding of sleep disorders that impact sleep transitions.
Genome-wide mapping of native co-localized G4s and R-loops in living cells
Authors: Liu Ting , Shen Xing , Ren Yijia , Lu Hongyu , Liu Yu , Chen Chong , Yu Lin , Xue Zhihong
Published: September 2024

The non-B DNA structures can act as dynamic functional genomic elements regulating gene expression. Among them, G4s and R-loops are two of the best studied. The interplay between R-loops and G4s are emerging in regulating DNA repair, replication and transcription. A comprehensive picture of native co-localized G4s and R-loops in living cells is currently lacking. Here, we describe the development of HepG4-seq and an optimized HBD-seq methods, which robustly capture native G4s and R-loops, respectively, in living cells. We successfully employed these methods to establish comprehensive maps of native co-localized G4s and R-loops in human HEK293 cells and mouse embryonic stem cells (mESCs). We discovered that co-localized G4s and R-loops are dynamically altered in a cell type-dependent manner and are largely localized at active promoters and enhancers of transcriptional active genes. We further demonstrated the helicase Dhx9 as a direct and major regulator that modulates the formation and resolution of co-localized G4s and R-loops. Depletion of Dhx9 impaired the self-renewal and differentiation capacities of mESCs by altering the transcription of co-localized G4s and R-loops - associated genes. Taken together, our work established that the endogenous co-localized G4s and R-loops are prevalently persisted in the regulatory regions of active genes and are involved in the transcriptional regulation of their linked genes, opening the door for exploring broader roles of co-localized G4s and R-loops in development and disease.
Soil organic carbon stabilization by iron in permafrost regions of the Qinghai‐Tibet Plateau
Authors: Mu C. C. , Zhang T. J. , Zhao Q. , Guo H. , Zhong W. , Su H. , Wu Q. B.
Published: September 2016

A close relationship exists between soil organic carbon (SOC) and reactive iron; however, little is known about the role of iron in SOC preservation in permafrost regions. We determined the amount of SOC associated with reactive iron phases (OC‐Fe) in the permafrost regions of the Qinghai‐Tibetan Plateau (QTP). The results showed that the percentage of OC‐Fe ranged between 0.9% and 59.5% in the upper 30 cm of soil and that the OC‐Fe represented 19.5 ± 12.3% of the total SOC pool. No clear vertical distribution pattern in OC‐Fe was present in the upper 1 m of soil. Throughout the year, the OC‐Fe accounted for relatively stable proportions of the total SOC pool. This study suggests that approximately 20% of SOC is a potential rusty OC pool in the permafrost regions of the QTP. Biogeochemical processes related to the reaction of iron may play important roles in soil carbon cycles in permafrost regions.
Automated identification of discrete, lightning‐generated, multiple‐dispersed whistler waves in C/NOFS‐VEFI very low frequency observations
Authors: Jacobson Abram R. , Holzworth Robert H. , Pfaff Robert , Heelis Roderick
Published: September 2016

Automated wave feature detection is required to efficiently analyze large archives of very low frequency broadband recordings for discrete whistler identification and feature extraction. We describe a new method to do this, even in the presence of simultaneous, multiple whistler phase dispersions. Previous techniques of whistler identification were unable to deal with simultaneous, multiple phase dispersions. We demonstrate the new method with data from the Vector Electric Field Investigation (VEFI) payload on the Communication/Navigation Outage Forecast System (C/NOFS) satellite, from the mission years 2008–2014.
Time‐lapse gravity data for monitoring and modeling artificial recharge through a thick unsaturated zone
Authors: Kennedy Jeffrey , Ferré Ty P. A. , Creutzfeldt Benjamin
Published: September 2016

Groundwater‐level measurements in monitoring wells or piezometers are the most common, and often the only, hydrologic measurements made at artificial recharge facilities. Measurements of gravity change over time provide an additional source of information about changes in groundwater storage, infiltration, and for model calibration. We demonstrate that for an artificial recharge facility with a deep groundwater table, gravity data are more sensitive to movement of water through the unsaturated zone than are groundwater levels. Groundwater levels have a delayed response to infiltration, change in a similar manner at many potential monitoring locations, and are heavily influenced by high‐frequency noise induced by pumping; in contrast, gravity changes start immediately at the onset of infiltration and are sensitive to water in the unsaturated zone. Continuous gravity data can determine infiltration rate, and the estimate is only minimally affected by uncertainty in water‐content change. Gravity data are also useful for constraining parameters in a coupled groundwater‐unsaturated zone model (Modflow‐NWT model with the Unsaturated Zone Flow (UZF) package).
Examining the reactive proactive questionnaire in adults in forensic and non‐forensic settings: A variable‐ and person‐based approach
Authors: Brugman Suzanne , Cornet Liza J. M. , Smeijers Danique , Smeets Kirsten , Oostermeijer Sanne , Buitelaar Jan K. , Verkes Robbert‐Jan , Lobbestael Jill , de Kogel Catharina H. , Jansen Lucres M. C.
Published: September 2016

The Reactive Proactive Questionnaire (RPQ) was originally developed to assess reactive and proactive aggressive behavior in children. Nevertheless, some studies have used the RPQ in adults. This study examines the reliability of the RPQ within an adult sample by investigating whether reactive and proactive aggression can be distinguished at a variable‐ and person‐based level. Male adults from forensic samples (N = 237) and from the general population (N = 278) completed the RPQ questionnaire. Variable‐based approaches, including factor analyses, were conducted to verify the two‐factor model of the RPQ and to examine alternative factor solutions of the 23 items. Subsequently, a person‐based approach, i.e., Latent Class Analysis (LCA), was executed to identify homogeneous classes of subjects with similar profiles of aggression in the observed data. The RPQ proved to have sufficient internal consistency. Multiple‐factor models were examined, but the original two‐factor model was statistically and theoretically considered as most solid and in line with previous research. The multi‐level LCA identified three different classes of aggression severity (class 1 showed low aggressive behavior; class 2 subjects displayed modest aggression levels; and class 3 exhibited the highest level of aggressive behavior). In addition, class 1 and 2 showed more reactive than proactive aggression, whereas class 3 displayed comparable levels of reactive/proactive aggression. The RPQ appears to have clinical relevance for adult populations in the way that it can distinguish severity levels of aggression. Before the RPQ is implemented in adult populations, norm scores need to be developed. Aggr. Behav. 43:155–162, 2017. © 2016 Wiley Periodicals, Inc.
αCAR IGF‐1 vector targeting of motor neurons ameliorates disease progression in ALS mice
Authors: Eleftheriadou Ioanna , Manolaras Ioannis , Irvine Elaine E. , Dieringer Michael , Trabalza Antonio , Mazarakis Nicholas D.
Published: September 2016

Objective

We have previously described the generation of coxsackievirus and adenovirus receptor (αCAR)‐targeted vector, and shown that intramuscular delivery in mouse leg muscles resulted in specific retrograde transduction of lumbar‐motor neurons (MNs). Here, we utilized the αCAR‐targeted vector to investigate the in vivo neuroprotective effects of lentivirally expressed IGF‐1 for inducing neuronal survival and ameliorating the neuropathology and behavioral phenotypes of the SOD1G93A mouse model of ALS.

Methods

We produced cell factories of IGF‐1 expressing lentiviral vectors (LVs) bearing αCAR or Vesicular Stomatitis Virus glycoprotein (VSV‐G) on their surface so as to compare neuroprotection from MN transduced versus muscle transduced cells. We performed intramuscular delivery of either αCAR IGF‐1 or VSVG IGF‐1 LVs into key muscles of SOD1G93A mice prior to disease onset at day 28. Motor performance, coordination and gait analysis were assessed weekly.

Results

We observed substantial therapeutic efficacy only with the αCAR IGF‐1 LV pretreatment with up to 50% extension of survival compared to controls. αCAR IGF‐1 LV‐treated animals retained muscle tone and had better motor performance during their prolonged survival. Histological analysis of spinal cord samples at end‐stage further confirmed that αCAR IGF‐1 LV treatment delays disease onset by increasing MN survival compared with age‐matched controls. Intrastriatal injection of αCAR eGFP LV in rats leads to transduction of neurons and glia locally and neurons in olfactory bulb distally.

Interpretation

Our data are indicative of the efficacy of the αCAR IGF‐1 LV in this model and support its candidacy for early noninvasive neuroprotective therapy in ALS.
Spin‐Structured Multilayers: A New Class of Materials for Precision Spintronics
Authors: Schlage Kai , Bocklage Lars , Erb Denise , Comfort Jade , Wille Hans‐Christian , Röhlsberger Ralf
Published: September 2016

Magnetoelectronic multilayer devices are widely used in today's information and sensor technology. Their functionality, however, is limited by the inherent properties of magnetic exchange or dipolar coupling which constrain possible spin configurations to collinear or perpendicular alignments of adjacent layers. Here, a deposition procedure is introduced that allows for a new class of layered materials in which complex spin structures can be accurately designed to result in a multitude of new and precisely adjustable spintronic and magnetoresistive properties. The magnetization direction and coercivity of each individual layer are determined by the deposition process in oblique incidence geometry and can be completely decoupled from neighboring layers. This applies for layers of any ferromagnetic material down to layer thicknesses of a few nm and lateral dimensions of a few 100 nm, enabling the design of efficient and compact magnetoelectronic devices, encompassing precision magnetoresistive sensors as well as layer systems with multiple addressable remanent states for magnetic memory applications.
Bioinspired Nanoparticles with NIR‐Controlled Drug Release for Synergetic Chemophotothermal Therapy of Metastatic Breast Cancer
Authors: Su Jinghan , Sun Huiping , Meng Qingshuo , Yin Qi , Zhang Pengcheng , Zhang Zhiwen , Yu Haijun , Li Yaping
Published: September 2016

Optimal nanosized drug delivery systems (NDDS) require long blood circulation and controlled drug release at target lesions for efficient anticancer therapy. Red blood cell (RBC) membrane‐camouflaged nanoparticles (NPs) can integrate flexibility of synergetic materials and highly functionality of RBC membrane, endowed with many unique advantages for drug delivery. Here, new near‐infrared (NIR)‐responsive RBC membrane‐mimetic NPs with NIR‐activated cellular uptake and controlled drug release for treating metastatic breast cancer are reported. An NIR dye is inserted in RBC membrane shells, and the thermoresponsive lipid is employed to the paclitaxel (PTX)‐loaded polymeric cores to fabricate the RBC‐inspired NPs. The fluorescence of dye in the NPs can be used for in vivo tumor imaging with an elongated circulating halftime that is 12.3‐folder higher than that of the free dye. Under the NIR laser stimuli, the tumor cellular uptake of NPs is significantly enhanced to 2.1‐fold higher than that without irradiation. The structure of the RBC‐mimetic NPs can be destroyed by the light‐induced hyperthermia, triggered rapid PTX release (45% in 30 min). These RBC‐mimetic NPs provide a synergetic chemophotothermal therapy, completely inhibited the growth of the primary tumor, and suppress over 98% of lung metastasis in vivo, suggesting it to be an ideal NDDS to fight against metastatic breast cancer.
Discovery of a Novel Sn(II)‐Based Oxide β‐SnMoO4 for Daylight‐Driven Photocatalysis
Authors: Hayashi Hiroyuki , Katayama Shota , Komura Takahiro , Hinuma Yoyo , Yokoyama Tomoyasu , Mibu Ko , Oba Fumiyasu , Tanaka Isao
Published: September 2016

Daylight‐driven photocatalysts have attracted much attention in the context of “green” technology. Although various active materials have been reported and their applications are rapidly increasing, many are discovered after enormous experimental efforts. Herein the discovery of a novel oxide photocatalyst, β‐SnMoO4, is demonstrated via a rational search of 3483 known and hypothetical compounds with various compositions and structures over the whole range of SnO‐MOq/2 (M: Ti, Zr, and Hf (q = 4); V, Nb, and Ta (q = 5); Cr, Mo, and W (q = 6)) pseudobinary systems. Screening using thermodynamic stability, band gap, and band‐edge positions by density functional theory calculations identifies β‐SnMoO4 as a potential target. Then a low temperature route is used to successfully synthesize the novel crystal, which is confirmed by X‐ray powder diffraction and Mössbauer spectroscopy. β‐SnMoO4 is active for the photocatalytic decomposition of a methylene blue solution under daylight and its activity is comparable to a known photocatalyst, β‐SnWO4.
Genetic variation of FOXE1 and risk for orofacial clefts in a California population
Authors: Lammer Edward J. , Mohammed Nebil , Iovannisci David M. , Ma Chen , Lidral Andrew C. , Shaw Gary M.
Published: September 2016

We investigated whether orofacial clefts are associated with polymorphic variation within and around FOXE1. This California population‐based case control study focused on white Hispanic and white nonHispanic infants among which there were 262 infants with cleft lip with or without cleft palate (CL/P), 103 with cleft palate only (CPO), and 382 unaffected controls. These cases and controls were genotyped for 13 SNPs across 220 Kb at the FOXE1 Locus. We observed associations with multiple FOXE1 SNPs for CL/P and for CPO, especially for the Hispanic study population. Increased risks were associated with the more common allele for all SNPs tested. Our results implicate FOXE1 as an important locus whose polymorphic variation increases risks for all types of isolated clefts, and opens a new biological pathway to investigate in efforts to understand genetic factors underlying human clefting. © 2016 Wiley Periodicals, Inc.
Tietz/Waardenburg type 2A syndrome associated with posterior microphthalmos in two unrelated patients with novel MITF gene mutations
Authors: Cortés‐González Vianney , Zenteno Juan Carlos , Guzmán‐Sánchez Martín , Giordano‐Herrera Verónica , Guadarrama‐Vallejo Dalia , Ruíz‐Quintero Narlly , Villanueva‐Mendoza Cristina
Published: September 2016

Tietz syndrome and Waardenburg syndrome type 2A are allelic conditions caused by MITF mutations. Tietz syndrome is inherited in an autosomal dominant pattern and is characterized by congenital deafness and generalized skin, hair, and eye hypopigmentation, while Waardenburg syndrome type 2A typically includes variable degrees of sensorineural hearing loss and patches of de‐pigmented skin, hair, and irides. In this paper, we report two unrelated families with MITF mutations. The first family showed an autosomal dominant pattern and variable expressivity. The second patient was isolated. MITF gene analysis in the first family demonstrated a c.648A>C heterozygous mutation in exon 8 c.648A>C; p. (R216S), while in the isolated patient, an apparently de novo heterozygous c.1183_1184insG truncating mutation was demonstrated in exon 10. All patients except one had bilateral reduced ocular anteroposterior axial length and a high hyperopic refractive error corresponding to posterior microphthalmos, features that have not been described as part of the disease. Our results suggest that posterior microphthalmos might be part of the clinical characteristics of Tietz/Waardenburg syndrome type 2A and expand both the clinical and molecular spectrum of the disease. © 2016 Wiley Periodicals, Inc.