bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison between the effectiveness of three prophylactic drugs for vestibular migraine; cinnarizine, propranolol, and topiramate: prospective study
Authors: Maksoud Nassar Adel Abdel , Emara Tamer Hussien , Hamid Shaimaa Salah Abdel , Galal Eman Mohamed
Published: October 2023

Background

Vestibular migraine (VM) is considered one of the most common causes of episodic vertigo. Acute attacks may interfere or hinder daily activities, and hence decrease the quality of life. Accordingly, this study was designed to evaluate and compare the effectiveness of Cinnarizine, Propranolol, and Topiramate as prophylactic treatment for vestibular migraine, in order to decrease the occurrence of acute attacks. Several medications have been proposed as a prophylactic treatment, but their benefit is still a vast field of study.

Methods

Forty-five subjects were diagnosed with vestibular migraine. They were divided into 3 groups; each group either received Cinnarzine, Propranolol, or Topiramate. All patients were submitted to thorough history taking for headache and vertiginous attacks, Dizziness Handicap Inventory questionnaire (DHI) -Arabic version, visual analog scale, videonystagmography, and computerized dynamic posturography (CDP) before and after receiving the treatment by 3 months.

Results

Topiramate was significantly superior in reducing the frequency and severity of headache attacks. The three drugs showed improvement but with no significant difference as regards duration and frequency of vertiginous attacks, DHI scores, and CDP. Only 5 patients had non-serious temporary side effects.

Conclusions

The three drugs were effective for ameliorating vertiginous attacks in vestibular migraine patients, but Topiramate was better in the 25 mg twice daily dose.
Evaluation of wetting front detector to estimate the dimensions of wetting front in the drip irrigation
Authors: Fattahi Nafchi Rouhallah , Valiyari-Eskandari Milad , Raeisi Vanani Hamid , Ostad-Ali-Askari Kaveh , Bahrami Abbas
Published: October 2023

In order to achieve proper water consumption efficiency in micro-irrigation systems, the space and flow rate of the drippers should match the hydraulic characteristics of the soil and the time and amount of plant irrigation water. As a result, having proper information about the width and depth of the wetted soil (wetting volume) is essential for the design, planning, and proper management of drip irrigation systems. The aim of this study was to obtain a set of semi-empirical relationships for more accurate and easier estimation of the diameter and depth of the wetting front. Field data of drip irrigation systems were collected by wet front detector (WFD) installed in three different conditions in terms of soil texture and flow rates of 4 and 8 L/h. Due to the technical problems and errors in the measurement of saturated hydraulic conductivity, which is the main representative of soil properties, the relationships presented here estimate the dimensions of the wetted soil volume based on the infiltration time and the volume of water stored in the reservoir. No need for hydraulic conductivity of the soil. The equations obtained in this research predict the diameter and depth of the wetted soil volume with a correlation coefficient of 89 and 98%, respectively.
Building Authentic Science Experiences: Students’ Perceptions of Sequential Course-Based Undergraduate Research
Authors: Von der Mehden Bailey M. , Pennino Eric M. , Fajardo Heather L. , Ishikawa Catherine , McDonald Kelly. K.
Published: October 2023

The SIRIUS project integrated scaffolded Course-based Undergraduate Research Experiences (CUREs) across a biology department to provide students with multiple opportunities to engage in authentic research at a primarily undergraduate-serving institution.
Correlates of Skeletal Muscle Mass and Differences Between Novel Subtypes in Recent-Onset Diabetes
Authors: Herder Christian , Maalmi Haifa , Saatmann Nina , Zaharia Oana-Patricia , Strassburger Klaus , Burkart Volker , Norman Kristina , Roden Michael
Published: October 2023

Context

Low skeletal muscle mass (SMM) is associated with long-standing diabetes but little is known about SMM in newly diagnosed diabetes.

Objective

We aimed to identify correlates of SMM in recent-onset diabetes and to compare SMM between novel diabetes subtypes.

Methods

SMM was normalized to body mass index (SMM/BMI) in 842 participants with known diabetes duration of less than 1 year from the German Diabetes Study (GDS). Cross-sectional associations between clinical variables, 79 biomarkers of inflammation, and SMM/BMI were assessed, and differences in SMM/BMI between novel diabetes subtypes were analyzed with different degrees of adjustment for confounders.

Results

Male sex and physical activity were positively associated with SMM/BMI, whereas associations of age, BMI, glycated hemoglobin A1c, homeostatic model assessment for β-cell function, and estimated glomerular filtration rate with SMM/BMI were inverse (all P < .05; model r2 = 0.82). Twenty-three biomarkers of inflammation showed correlations with SMM/BMI after adjustment for sex and multiple testing (all P < .0006), but BMI largely explained these correlations. In a sex-adjusted analysis, individuals with severe autoimmune diabetes had a higher SMM/BMI whereas individuals with severe insulin-resistant diabetes and mild obesity-related diabetes had a lower SMM/BMI than all other subtypes combined. However, differences were attenuated after adjustment for the clustering variables.

Conclusion

SMM/BMI differs between diabetes subtypes and may contribute to subtype differences in disease progression. Of note, clinical variables rather than biomarkers of inflammation explain most of the variation in SMM/BMI.
Freeze-drying of Red Blood Cells Using Ultrafast Cooling by Spraying into a Vacuum
Authors: Konoo Tomoka , Uematsu Sora , Nishihashi Tsutomu , Murakami Hirohiko , Honda Hidemine , Takiuchi Tsuyoshi , Kimura Tadashi
Published: October 2023

Ultrafast cooling inhibits the growth of ice crystals and prevents red blood cells from being damaged by ice crystals. Micro-Powder-Dry (µPD), a novel freeze-drying technique, was applied in this work. Using the µPD approach, we looked at the hemolysis and morphology of frozen/freeze-dried red blood cells. After freezing, the µPD method had a higher recovery rate than the slow freezing method. The recovery of the red blood cells was maintained after freeze-drying.
The genome sequence of a leaf beetle, Cryptocephalus moraei (Linnaeus, 1758)
Authors: Sivell Olga , Sivell Duncan , Mitchell Ryan ,   Natural History Museum Genome Acquisition Lab,   Darwin Tree of Life Barcoding collective,   Wellcome Sanger Institute Tree of Life programme,   Wellcome Sanger Institute Scientific Operations: DNA Pipelines collective,   Tree of Life Core Informatics collective,   Darwin Tree of Life Consortium
Published: October 2023

We present a genome assembly from an individual female Cryptocephalus moraei (a leaf beetle; Arthropoda; Insecta; Coleoptera; Chrysomelidae). The genome sequence is 500.5 megabases in span. Most of the assembly is scaffolded into 15 chromosomal pseudomolecules, including the X sex chromosome. The mitochondrial genome has also been assembled and is 15.68 kilobases in length.
The genome sequence of the black-bellied cluster fly, Pollenia amentaria (Scopoli, 1763)
Authors: Falk Steven , Mitchell Ryan , Sivell Olga ,   University of Oxford and Wytham Woods Genome Acquisition Lab,   Natural History Museum Genome Acquisition Lab,   Darwin Tree of Life Barcoding collective,   Wellcome Sanger Institute Tree of Life programme,   Wellcome Sanger Institute Scientific Operations: DNA Pipelines collective,   Tree of Life Core Informatics collective,   Darwin Tree of Life Consortium
Published: October 2023

We present a genome assembly from an individual female Pollenia amentaria (the black-bellied cluster fly; Arthropoda; Insecta; Diptera; Polleniidae). The genome sequence is 1,270.8 megabases in span. Most of the assembly is scaffolded into 6 chromosomal pseudomolecules, including the X sex chromosome. The mitochondrial genome has also been assembled and is 15.28 kilobases in length. Gene annotation of this assembly on Ensembl identified 12,065 protein coding genes.
The genome sequence of the silverweed cinquefoil, Potentilla anserina L., 1753
Authors: Christenhusz Maarten J. M. , Leitch Ilia J ,   Royal Botanic Gardens Kew Genome Acquisition Lab,   Plant Genome Sizing collective,   Darwin Tree of Life Barcoding collective,   Wellcome Sanger Institute Tree of Life programme,   Wellcome Sanger Institute Scientific Operations: DNA Pipelines collective,   Tree of Life Core Informatics collective,   Darwin Tree of Life Consortium
Published: October 2023

We present a genome assembly from a specimen of Potentilla anserina (the silverweed cinquefoil; Streptophyta; eudicotyledons; Rosales; Potentilleae). The haploid genome sequence is 237 megabases in span. Most of the assembly is scaffolded into seven chromosomal pseudomolecules. The mitochondrial and plastid genomes have also been assembled and are 294.6 and 155.6 kilobases in length respectively.
Development Trajectory of Blockchain Platforms: The Role of Multirole
Authors: Li Tianyi , Zhang Xiaoquan (Michael)
Published: October 2023

Understanding the development trajectory of digital platforms is central to digital platform management. We develop a parametric model that investigates the development trajectories of blockchain platforms, accounting for the feedback between blockchains’ utility change and people’s adoption and abandonment behavior. We consider a typical blockchain participant to simultaneously play three roles on the platform, user, investor, and laborer, each contributing to blockchains’ multi-faceted utility: providing service for transaction/interaction, providing a medium for digital investment, and providing workspace for online labor. The model describes a three-phase development trajectory for blockchain platforms: a chaotic initial stage, a rapid growth stage, and a mature stage of stable market cycles. The model was used to match 112 token price series, demonstrating robust performance across different fitting setups and outperforming existing models. The study identifies two temporal parameters, the time delay in quitting the platform and the holding time of the platform’s token, that significantly differentiate blockchains’ development trajectories. We extend the model to study forking events; results suggest that fork launch time is more important than forking amplitude in influencing the main chain’s subsequent development and that forking can increase the exposure of the forked platform.
The importance of a comprehensive geriatric assessment for older people admitted onto a virtual ward
Authors: Goggins Suzanne
Published: October 2023

A comprehensive geriatric assessment (CGA) provides a holistic assessment for the frail and older person. The CGA considers physical and mental conditions as well as function, environmental and a person's social circumstances. Virtual wards are a new concept within the NHS, and use of virtual wards during the COVID-19 pandemic reduced hospital admissions by 50%. The British Geriatrics Society has set clear guidelines on how virtual wards should be developed within integrated care services via multidisciplinary community rapid response teams to improve patient outcomes. This article considers a logical approach to assessing suitability for admission onto a virtual ward for a patient who required hospital-at-home services. It does this through the use of a theoretical patient case study, in this case involving delirium and urinary tract infection. Frailty and frailty scoring tools are discussed, as are the advantages and disadvantages of a CGA, considering a clear progression through the five domains. It shows how conducting a CGA allows for the development of a problem list to help prioritise the patient's problems and plan accordingly. A critical review of the literature around virtual wards, hospital-at-home services and admission avoidance identified that community rapid response teams were the logical choice to provide a multidisciplinary holistic approach to the older person admitted onto a virtual ward.
The importance of diversity in clinical research
Authors: Adan Carlito
Published: October 2023

Clinical research is a fundamental part of the healthcare system and is critical to improving care, making it safe and effective. Research participants should be diverse as this reduces bias and helps to better understand illness and treatment and how it affects different groups of people. However, due to health inequalities and barriers to research participation, clinical research still lacks diversity. Data from the US Food and Drug Administration showed that 76% of research participants were White and the remaining 24% were from an ethnic minority. In the UK, only 5% of ethnic minorities have ever participated in clinical trials. Recently, with the COVID-19 vaccine trials, out of 270 000 participants, only 11 000 and 1200 participants were from Asian and Black backgrounds, respectively. The research participation of under-represented groups requires co-development with community members. This proactive approach helps establish trust and enhance recruitment strategies that build a positive legacy for under-represented groups.
Martha's Rule and NHS patient safety
Authors: Tingle John , Cattini Amanda
Published: October 2023

John Tingle, Lecturer in Law, Birmingham Law School, University of Birmingham, and Amanda Cattini reflect on the reasons for the introduction of Martha's Rule
Aquacel Ag Advantage/Ag+ Extra and Cutimed Sorbact in the management of hard-to-heal wounds: a cohort study
Authors: Dissemond Joachim , Aare Kristina , Ozer Kerem , Gandhi Divay , Ryan Jessica L , DeKoven Mitch
Published: October 2023

Objective:

To compare Aquacel Ag Advantage/Ag+ Extra (Aquacel Ag+) (Convatec, UK) and Cutimed Sorbact (Sorbact) (Essity, US) dressings indicated for the treatment of patients with venous leg ulcers (VLUs), diabetes foot ulcers (DFUs) and pressure injuries (PIs) for clinical performance and outcomes using real-world evidence in Germany and the US.

Method:

This study was a chart audit review of patients who used either Aquacel Ag+ or Sorbact dressings in the 24 months prior to October 2022. Healthcare providers with access to electronic medical records and charts were asked to capture data via patient record forms. The quantitative data were analysed.

Results:

Findings in Germany were comparable between Aquacel Ag+ and Sorbact with regards to wound description, management and treatment outcomes, including percent area reduction and wound closure. A difference was that a greater proportion of Sorbact patients required surgery (0% versus 11%; p=0.039). In the US, a greater proportion of wounds were worsening before dressing in the Aquacel Ag+ cohort (49% versus 34%; p=0.010). A multinomial logistic regression yielded the result that patients who received Aquacel Ag+ were 3.53 times more likely to have the wound completely healed (p=0.033).

Conclusion:

Both Aquacel Ag+ and Sorbact dressings are widely used in Germany and the US for patients with VLUs, DFUs and PIs. Our study found two important differences: patients who used Aquacel Ag+ were less likely to need further surgery in Germany; and in the US, there were significantly higher odds that wounds would completely heal with Aquacel Ag+ dressings compared to Sorbact.
Compression therapy for NHS inpatients with leg ulcers: a literature review
Authors: Lian Yaping , Anderson Irene , Atkin Leanne , Gohel Manj
Published: October 2023

Objective:

Leg ulcers are common, distressing and painful for patients, and are a significant financial burden to healthcare providers. Compression therapy is the mainstay of treatment for venous leg ulceration. Several studies have evaluated leg ulcer management and compression therapy in the community. However, little is known about the prevalence of leg ulceration and use of compression therapy in acute hospitals. The aim of this study was to explore the published literature on the use of compression therapy for inpatients with leg ulcers in UK National Health Service hospital settings.

Method:

A literature search was undertaken to identify published papers reporting on inpatient leg ulcer populations and the use of compression therapy in hospitals using the following databases: CINAHL, MEDLINE Complete, Embase and PubMed.

Results:

The literature review identified 364 articles, of which three met the eligibility criteria. These studies reported on the prevalence of leg ulceration, the number of Doppler assessments conducted for patients and the use of compression therapy.

Conclusion:

This review confirmed a lack of information on the prevalence of hospital inpatients with leg ulcers, and identified the need to conduct prevalence audits, establish leg ulcer services to streamline inpatient leg ulcer care and provide staff and patient education programmes.
Hyperbaric oxygen therapy restores wound healing in irradiated gingiva to a similar level to that in healthy gingiva
Authors: Kasikasetsiri Juthathip , Apaijai Nattayaporn , Aschaitrakool Yuthakran , Kerdphoo Sasiwan , Sriyaranya Nutchada , Chattipakorn Nipon , Chattipakorn Siriporn C
Published: October 2023

Objective:

This study aimed to investigate the involvement of mitochondrial biogenesis, and determine the extent of fibroblast proliferation and cellular apoptosis, in the gingiva of patients who had undergone head and neck radiation, after receiving hyperbaric oxygen therapy (HBOT), in comparison with normal gingiva.

Method:

A total of 16 patients who had undergone head and neck radiation with HBOT and six healthy subjects were included in the study. After the completion of radiation therapy, patients received HBOT at 2 ATA for 90 minutes per session, and for 20 sessions per patient. Samples of gingival tissues were then taken. The levels of: transforming growth factor beta (TGF-β); phospho-nuclear factor kappa-light-chain-enhancer of activated B cells (p-NFϰB); nuclear factor kappa-light-chain-enhancer of activated B cells (NFϰB); proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α); phospho-dynamin-related protein 1 at ser616 (p-Drp1ser616); dynamin-related protein 1 (Drp1); Bcl-2-associated X-protein (Bax); and B-cell lymphoma 2 (Bcl-2) were determined using a Western blot. Independent t-test and Chi-squared tests were used in the study.

Results:

There were no differences in the levels of TGF-β, p-NFϰB, NFϰB, p-Drp1ser616, Drp1, Bax and Bcl-2 between the two groups. However, the level of PGC-1α was greater in irradiated gingival tissues with HBOT than in the healthy gingiva.

Conclusion:

Radiation-induced impaired wound healing can be improved by HBOT as indicated by levels of apoptosis, mitochondrial dynamics, cell proliferation and inflammation in irradiated gingiva with HBOT to a similar level to normal healthy gingiva. These findings may occur through an increase in mitochondrial biogenesis following HBOT.
Usefulness of analyzing endoscopic features in identifying the colorectal serrated sessile lesions with and without dysplasia
Authors: Wang Rui-Gang , Ren Yu-Tang , Jiang Xuan , Wei Lai , Zhang Xiao-Fei , Liu Hao , Jiang Bo
Published: October 2023

Time series analysis is a valuable tool in epidemiology that complements the classical epidemiological models in two different ways: Prediction and forecast. Prediction is related to explaining past and current data based on various internal and external influences that may or may not have a causative role. Forecasting is an exploration of the possible future values based on the predictive ability of the model and hypothesized future values of the external and/or internal influences. The time series analysis approach has the advantage of being easier to use (in the cases of more straightforward and linear models such as Auto-Regressive Integrated Moving Average). Still, it is limited in forecasting time, unlike the classical models such as Susceptible-Exposed-Infectious-Removed. Its applicability in forecasting comes from its better accuracy for short-term prediction. In its basic form, it does not assume much theoretical knowledge of the mechanisms of spreading and mutating pathogens or the reaction of people and regulatory structures (governments, companies, etc. ). Instead, it estimates from the data directly. Its predictive ability allows testing hypotheses for different factors that positively or negatively contribute to the pandemic spread; be it school closures, emerging variants, etc. It can be used in mortality or hospital risk estimation from new cases, seroprevalence studies, assessing properties of emerging variants, and estimating excess mortality and its relationship with a pandemic.
Roles of biochemistry data, lifestyle, and inflammation in identifying abnormal renal function in old Chinese
Authors: Chen Chao-Hung , Wang Chun-Kai , Wang Chen-Yu , Chang Chun-Feng , Chu Ta-Wei
Published: October 2023

Time series analysis is a valuable tool in epidemiology that complements the classical epidemiological models in two different ways: Prediction and forecast. Prediction is related to explaining past and current data based on various internal and external influences that may or may not have a causative role. Forecasting is an exploration of the possible future values based on the predictive ability of the model and hypothesized future values of the external and/or internal influences. The time series analysis approach has the advantage of being easier to use (in the cases of more straightforward and linear models such as Auto-Regressive Integrated Moving Average). Still, it is limited in forecasting time, unlike the classical models such as Susceptible-Exposed-Infectious-Removed. Its applicability in forecasting comes from its better accuracy for short-term prediction. In its basic form, it does not assume much theoretical knowledge of the mechanisms of spreading and mutating pathogens or the reaction of people and regulatory structures (governments, companies, etc. ). Instead, it estimates from the data directly. Its predictive ability allows testing hypotheses for different factors that positively or negatively contribute to the pandemic spread; be it school closures, emerging variants, etc. It can be used in mortality or hospital risk estimation from new cases, seroprevalence studies, assessing properties of emerging variants, and estimating excess mortality and its relationship with a pandemic.
Primary renal lymphoma presenting as renal failure: A case report and review of literature from 1989
Authors: Lee Seul-Bi , Yoon Young-Min , Hong Ran
Published: October 2023

Time series analysis is a valuable tool in epidemiology that complements the classical epidemiological models in two different ways: Prediction and forecast. Prediction is related to explaining past and current data based on various internal and external influences that may or may not have a causative role. Forecasting is an exploration of the possible future values based on the predictive ability of the model and hypothesized future values of the external and/or internal influences. The time series analysis approach has the advantage of being easier to use (in the cases of more straightforward and linear models such as Auto-Regressive Integrated Moving Average). Still, it is limited in forecasting time, unlike the classical models such as Susceptible-Exposed-Infectious-Removed. Its applicability in forecasting comes from its better accuracy for short-term prediction. In its basic form, it does not assume much theoretical knowledge of the mechanisms of spreading and mutating pathogens or the reaction of people and regulatory structures (governments, companies, etc. ). Instead, it estimates from the data directly. Its predictive ability allows testing hypotheses for different factors that positively or negatively contribute to the pandemic spread; be it school closures, emerging variants, etc. It can be used in mortality or hospital risk estimation from new cases, seroprevalence studies, assessing properties of emerging variants, and estimating excess mortality and its relationship with a pandemic.
Co-infection of Chlamydia psittaci and Tropheryma whipplei: A case report
Authors: Du Zhu-Man , Chen Pei
Published: October 2023

Time series analysis is a valuable tool in epidemiology that complements the classical epidemiological models in two different ways: Prediction and forecast. Prediction is related to explaining past and current data based on various internal and external influences that may or may not have a causative role. Forecasting is an exploration of the possible future values based on the predictive ability of the model and hypothesized future values of the external and/or internal influences. The time series analysis approach has the advantage of being easier to use (in the cases of more straightforward and linear models such as Auto-Regressive Integrated Moving Average). Still, it is limited in forecasting time, unlike the classical models such as Susceptible-Exposed-Infectious-Removed. Its applicability in forecasting comes from its better accuracy for short-term prediction. In its basic form, it does not assume much theoretical knowledge of the mechanisms of spreading and mutating pathogens or the reaction of people and regulatory structures (governments, companies, etc. ). Instead, it estimates from the data directly. Its predictive ability allows testing hypotheses for different factors that positively or negatively contribute to the pandemic spread; be it school closures, emerging variants, etc. It can be used in mortality or hospital risk estimation from new cases, seroprevalence studies, assessing properties of emerging variants, and estimating excess mortality and its relationship with a pandemic.
Surgical treatment of severe anterior capsular organized hard core cataract: A case report
Authors: Wang Li-Wen , Fang Shi-Feng
Published: October 2023

Time series analysis is a valuable tool in epidemiology that complements the classical epidemiological models in two different ways: Prediction and forecast. Prediction is related to explaining past and current data based on various internal and external influences that may or may not have a causative role. Forecasting is an exploration of the possible future values based on the predictive ability of the model and hypothesized future values of the external and/or internal influences. The time series analysis approach has the advantage of being easier to use (in the cases of more straightforward and linear models such as Auto-Regressive Integrated Moving Average). Still, it is limited in forecasting time, unlike the classical models such as Susceptible-Exposed-Infectious-Removed. Its applicability in forecasting comes from its better accuracy for short-term prediction. In its basic form, it does not assume much theoretical knowledge of the mechanisms of spreading and mutating pathogens or the reaction of people and regulatory structures (governments, companies, etc. ). Instead, it estimates from the data directly. Its predictive ability allows testing hypotheses for different factors that positively or negatively contribute to the pandemic spread; be it school closures, emerging variants, etc. It can be used in mortality or hospital risk estimation from new cases, seroprevalence studies, assessing properties of emerging variants, and estimating excess mortality and its relationship with a pandemic.
Rare finding of primary aortoduodenal fistula on single-photon emission computed tomography/computed tomography of gastrointestinal bleeding: A case report
Authors: Kuo Chun-Liang , Chen Ching-Fu , Su Wen-Ko , Yang Rong-Hsin , Chang Yu-Hong
Published: October 2023

Time series analysis is a valuable tool in epidemiology that complements the classical epidemiological models in two different ways: Prediction and forecast. Prediction is related to explaining past and current data based on various internal and external influences that may or may not have a causative role. Forecasting is an exploration of the possible future values based on the predictive ability of the model and hypothesized future values of the external and/or internal influences. The time series analysis approach has the advantage of being easier to use (in the cases of more straightforward and linear models such as Auto-Regressive Integrated Moving Average). Still, it is limited in forecasting time, unlike the classical models such as Susceptible-Exposed-Infectious-Removed. Its applicability in forecasting comes from its better accuracy for short-term prediction. In its basic form, it does not assume much theoretical knowledge of the mechanisms of spreading and mutating pathogens or the reaction of people and regulatory structures (governments, companies, etc. ). Instead, it estimates from the data directly. Its predictive ability allows testing hypotheses for different factors that positively or negatively contribute to the pandemic spread; be it school closures, emerging variants, etc. It can be used in mortality or hospital risk estimation from new cases, seroprevalence studies, assessing properties of emerging variants, and estimating excess mortality and its relationship with a pandemic.
Case of takotsubo cardiomyopathy after surgical treatment of liver hydatid cyst: A case report
Authors: Altaş Yakup , Abdullayeva Ülfet
Published: October 2023

Time series analysis is a valuable tool in epidemiology that complements the classical epidemiological models in two different ways: Prediction and forecast. Prediction is related to explaining past and current data based on various internal and external influences that may or may not have a causative role. Forecasting is an exploration of the possible future values based on the predictive ability of the model and hypothesized future values of the external and/or internal influences. The time series analysis approach has the advantage of being easier to use (in the cases of more straightforward and linear models such as Auto-Regressive Integrated Moving Average). Still, it is limited in forecasting time, unlike the classical models such as Susceptible-Exposed-Infectious-Removed. Its applicability in forecasting comes from its better accuracy for short-term prediction. In its basic form, it does not assume much theoretical knowledge of the mechanisms of spreading and mutating pathogens or the reaction of people and regulatory structures (governments, companies, etc. ). Instead, it estimates from the data directly. Its predictive ability allows testing hypotheses for different factors that positively or negatively contribute to the pandemic spread; be it school closures, emerging variants, etc. It can be used in mortality or hospital risk estimation from new cases, seroprevalence studies, assessing properties of emerging variants, and estimating excess mortality and its relationship with a pandemic.
Emphysematous thrombophlebitis caused by a misplaced central venous catheter: A case report
Authors: Chen Ni , Chen Hua-Jun , Chen Tao , Zhang Wen , Fu Xiao-Yun , Xing Zhou-Xiong
Published: October 2023

Time series analysis is a valuable tool in epidemiology that complements the classical epidemiological models in two different ways: Prediction and forecast. Prediction is related to explaining past and current data based on various internal and external influences that may or may not have a causative role. Forecasting is an exploration of the possible future values based on the predictive ability of the model and hypothesized future values of the external and/or internal influences. The time series analysis approach has the advantage of being easier to use (in the cases of more straightforward and linear models such as Auto-Regressive Integrated Moving Average). Still, it is limited in forecasting time, unlike the classical models such as Susceptible-Exposed-Infectious-Removed. Its applicability in forecasting comes from its better accuracy for short-term prediction. In its basic form, it does not assume much theoretical knowledge of the mechanisms of spreading and mutating pathogens or the reaction of people and regulatory structures (governments, companies, etc. ). Instead, it estimates from the data directly. Its predictive ability allows testing hypotheses for different factors that positively or negatively contribute to the pandemic spread; be it school closures, emerging variants, etc. It can be used in mortality or hospital risk estimation from new cases, seroprevalence studies, assessing properties of emerging variants, and estimating excess mortality and its relationship with a pandemic.
Imaging misdiagnosis and clinical analysis of significant hepatic atrophy after bilioenteric anastomosis: A case report
Authors: Liang Shao-Yong , Lu Jian-Guo , Wang Zong-Ding
Published: October 2023

Time series analysis is a valuable tool in epidemiology that complements the classical epidemiological models in two different ways: Prediction and forecast. Prediction is related to explaining past and current data based on various internal and external influences that may or may not have a causative role. Forecasting is an exploration of the possible future values based on the predictive ability of the model and hypothesized future values of the external and/or internal influences. The time series analysis approach has the advantage of being easier to use (in the cases of more straightforward and linear models such as Auto-Regressive Integrated Moving Average). Still, it is limited in forecasting time, unlike the classical models such as Susceptible-Exposed-Infectious-Removed. Its applicability in forecasting comes from its better accuracy for short-term prediction. In its basic form, it does not assume much theoretical knowledge of the mechanisms of spreading and mutating pathogens or the reaction of people and regulatory structures (governments, companies, etc. ). Instead, it estimates from the data directly. Its predictive ability allows testing hypotheses for different factors that positively or negatively contribute to the pandemic spread; be it school closures, emerging variants, etc. It can be used in mortality or hospital risk estimation from new cases, seroprevalence studies, assessing properties of emerging variants, and estimating excess mortality and its relationship with a pandemic.
Surgical treatment of mixed cervical spondylosis with spontaneous cerebrospinal fluid leakage: A case report
Authors: Yu Zhong , Zhang Hao-Fu-Zi , Wang Yan-Jun
Published: October 2023

Time series analysis is a valuable tool in epidemiology that complements the classical epidemiological models in two different ways: Prediction and forecast. Prediction is related to explaining past and current data based on various internal and external influences that may or may not have a causative role. Forecasting is an exploration of the possible future values based on the predictive ability of the model and hypothesized future values of the external and/or internal influences. The time series analysis approach has the advantage of being easier to use (in the cases of more straightforward and linear models such as Auto-Regressive Integrated Moving Average). Still, it is limited in forecasting time, unlike the classical models such as Susceptible-Exposed-Infectious-Removed. Its applicability in forecasting comes from its better accuracy for short-term prediction. In its basic form, it does not assume much theoretical knowledge of the mechanisms of spreading and mutating pathogens or the reaction of people and regulatory structures (governments, companies, etc. ). Instead, it estimates from the data directly. Its predictive ability allows testing hypotheses for different factors that positively or negatively contribute to the pandemic spread; be it school closures, emerging variants, etc. It can be used in mortality or hospital risk estimation from new cases, seroprevalence studies, assessing properties of emerging variants, and estimating excess mortality and its relationship with a pandemic.
Collecting as Identity Creation and Memory Preservation
Authors: Adams Isabelle
Published: October 2023

Adams considers collecting as tools of memory, storytelling, and individual identity. Through the lens of individual identity, memory preservation, and storytelling, collecting becomes a vital part of the human experience.
No Firearms Allowed On the Premises
Authors: Schrage Jordan
Published: October 2023

Schrage’s project considers the normalization of gun violence in American schools.
Emphasised, feared, despised and hegemonic: images of femininity in the US far-right digital ecosystem on Telegram channels
Authors: Doerr Nicole , Svatoňová Eva
Published: October 2023

In this article, we deliver an empirical analysis of far-right visualisations of womanhood on US Telegram channels. Previous studies show that the far right, which increasingly engages in misogynist, anti-lesbian, gay, bisexual and transgender rhetoric, and opposition to feminism, is marked by the growing involvement of women in the roles of political leaders. Such engagement by women within the far right causes an ‘image problem’, as it makes the traditional gender image of wifely submission less convincing. Our analysis of images of womanhood shared on US far-right Telegram channels shows how far-right images of ‘approved’ performances of womanhood include transgressive gender performances of hegemonic femininity that are in conflict with conservative representations of womanhood in traditional nationalist ideology. Our findings also show how hateful images of liberal, non-binary and minority women serve as a tool for the construction of a variety of ‘approved’ far-right identity images of hegemonic femininity.
Examining Adolescents' Mental Health Before and During the COVID-19 Pandemic
Authors: Yarger Heather A. , Shariq Deena , Hickey Alexandra C. , Giacobbe Elizabeth , Dziura Sarah L. , Redcay Elizabeth
Published: October 2023

Abstract: The current study characterized the impact of the COVID-19 pandemic and stay-at-home orders on adolescents' internalizing symptoms and assessed predictors of adolescents' internalizing symptoms during the pandemic. Seventy-nine adolescents (18 autistic, 61 nonautistic) and their parents who participated in a previous study and were at least 10 years old ( M = 13.8, SD = 1.7) were invited to participate in three online follow-up surveys post-stay-at-home order (May through November 2020). Measures of children's anxiety and depressive symptoms, parenting practices, family togetherness, conflict, financial problems, and parental mental health during the pandemic were collected. Nonautistic adolescents experienced a significant decrease in anxiety symptoms across the beginning of the pandemic and a significant increase in depressive symptoms from pre- to post-stay-at-home order. Permissive parenting and financial problems predicted adolescents' depressive symptoms. Parental mental health difficulties and permissive parenting predicted adolescents' anxiety symptoms. Results underscore the need to support parents and youth.
From Power as Force to Power as Theater: Scenes of Agency in Hegel and Nietzsche
Authors: Vinketa Darko
Published: October 2023

Abstract: This article identifies a tension between two opposing conceptualizations of power within contemporary political theory: the vitalist understanding of power as force, friction, and agonism, and the deconstructivist treatment of power as impressionability, imitation, and theatricality. It situates this divergence within Gilles Deleuze’s employment of Nietzsche against the Hegelian dialectics, and proceeds to excavate a latent shadow of theatricality running through both Hegel’s and Nietzsche’s respective theorizations of power as bondage and as tragedy. This rearticulates the primary operation of power as one that is neither superseded by Reason as in Hegel, nor entirely exhausted by the excesses of materiality over and above identity as in Deleuze’s uptake of the Nietzschean “will-to-power.”
Deep learning based coherence holography reconstruction of 3D objects
Authors: Trieu Quang , Nehmetallah George
Published: October 2023

We propose a reconstruction method for coherence holography using deep neural networks. cGAN and U-NET models were developed to reconstruct 3D complex objects from recorded interferograms. Our proposed methods, dubbed deep coherence holography (DCH), predict the non-diffracted fields or the sub-objects included in the 3D object from the captured interferograms, yielding better reconstructed objects than the traditional analytical imaging methods in terms of accuracy, resolution, and time. The DCH needs one image per sub-object as opposed to N images for the traditional sin-fit algorithm, and hence the total reconstruction time is reduced by N×. Furthermore, with noisy interferograms the DCH amplitude mean square reconstruction error (MSE) is 5×104× and 104× and phase MSE is 102× and 3×103× better than Fourier fringe and sin-fit algorithms, respectively. The amplitude peak signal to noise ratio (PSNR) is 3× and 2× and phase PSNR is 5× and 3× better than Fourier fringe and sin-fit algorithms, respectively. The reconstruction resolution is the same as sin-fit but 2× better than the Fourier fringe analysis technique.
Four-color fiber-coupled mid-infrared laser-absorption sensor for temperature, CO, CO2, and NO at 5  kHz in internal combustion engine vehicle exhaust
Authors: Stiborek Joshua W. , Schwartz Charles J. , Kempema Nathan J. , Szente Joseph J. , Loos Michael J. , Goldenstein Christopher S.
Published: October 2023

A mid-infrared (MIR) laser absorption spectroscopy (LAS) sensor was developed for temperature, CO, NO, and CO2 measurements at 5 kHz in engine-out exhaust. It used fiber-coupled quantum cascade lasers (QCLs) for measuring CO and NO, and an interband cascade laser (ICL) for measuring CO2. Validation tests in a heated gas cell confirmed that the LAS measurements of CO, CO2, NO, and temperature are accurate to within 4.8%, 5.1%, 4.6%, and 3.1%, respectively, at 1–2 atm and 300–1000 K. The LAS sensor was applied to characterize the engine-out exhaust gas of an 8-cylinder gasoline engine in a light-duty truck at operating conditions where commercial instruments lack sufficient time response to quantify important emission dynamics.
Field curvature reduction in miniaturized high numerical aperture and large field-of-view objective lenses with sub 1 µm lateral resolution
Authors: Stark Sophia Laura , Gross Herbert , Reglinski Katharina , Messerschmidt Bernhard , Eggeling Christian
Published: October 2023

In this paper the development of a miniaturized endoscopic objective lens for various biophotonics applications is presented. While limiting the mechanical dimensions to 2.2 mm diameter and 13 mm total length, a numerical aperture of 0.7 in water and a field-of-view (FOV) diameter of 282 µm are achieved. To enable multimodal usage a wavelength range of 488 nm to 632 nm was considered. The performed broad design study aimed for field curvature reduction when maintaining the sub 1 µm resolution over a large FOV. Moreover, the usage of GRadient-INdex (GRIN) lenses was investigated. The resolution, field curvature improvement and chromatic performance of the novel device were validated by means of a confocal laser-scanning-microscope.
1-to-N terahertz integrated switches enabling multi-beam antennas
Authors: Dechwechprasit Panisa , Lees Harrison , Headland Daniel , Fumeaux Christophe , Withayachumnankul Withawat
Published: October 2023

Implementing terahertz circuits and system designs relies on integrating reconfigurable devices such as switches, to fulfill a critical role in controlling and manipulating the flow of terahertz signals on the chip. Although there have been several demonstrations of on–off switching in the terahertz range, there have been no demonstrations of 1-to-N switching, to our knowledge. This pronounced lack of dynamically reconfigurable routing has severely limited the achievable complexity of terahertz systems. To address this, we propose 1-to-N switches made of cascaded disk resonators integrated into a substrateless silicon waveguide platform. A single switch can be controlled via photoexcitation using a low-power 658-nm laser focused onto the disk resonator, turning off the resonance and inhibiting coupling into a crossing port. The measurement results demonstrate that the proposed switch has low insertion loss, which can be attributed to the inherently low dissipation of the platform. The proposed on–off switch achieves a maximum insertion loss of 1.2 dB, and the maximum extinction ratio of the switch is 16.1 dB with 1.5 GHz of bandwidth. Furthermore, a 1-to-3 switch is monolithically integrated together with a Luneburg lens in order to project each of its output ports to a different far-field direction and, thereby, translate the switching operation into a form of reconfigurable beam control for future applications.
Conserved and divergent signals in 5’ splice site sequences across fungi, metazoa and plants
Authors: Beckel Maximiliano S. , Kaufman Bruno , Yanovsky Marcelo , Chernomoretz Ariel
Published: October 2023

In eukaryotic organisms the ensemble of 5’ splice site sequences reflects the balance between natural nucleotide variability and minimal molecular constraints necessary to ensure splicing fidelity. This compromise shapes the underlying statistical patterns in the composition of donor splice site sequences. The scope of this study was to mine conserved and divergent signals in the composition of 5’ splice site sequences. Because 5’ donor sequences are a major cue for proper recognition of splice sites, we reasoned that statistical regularities in their composition could reflect the biological functionality and evolutionary history associated with splicing mechanisms.

Results: We considered a regularized maximum entropy modeling framework to mine for non-trivial two-site correlations in donor sequence datasets corresponding to 30 different eukaryotes. For each analyzed species, we identified minimal sets of two-site coupling patterns that were able to replicate, at a given regularization level, the observed one-site and two-site frequencies in donor sequences. By performing a systematic and comparative analysis of 5’splice sites we showed that lineage information could be traced from joint di-nucleotide probabilities. We were able to identify characteristic two-site coupling patterns for plants and animals, and propose that they may echo differences in splicing regulation previously reported between these groups.
Short-term neuronal and synaptic plasticity act in synergy for deviance detection in spiking networks
Authors: Kern Felix Benjamin , Chao Zenas C.
Published: October 2023

Sensory areas of cortex respond more strongly to infrequent stimuli when these violate previously established regularities, a phenomenon known as deviance detection (DD). Previous modeling work has mainly attempted to explain DD on the basis of synaptic plasticity. However, a large fraction of cortical neurons also exhibit firing rate adaptation, an underexplored potential mechanism. Here, we investigate DD in a spiking neuronal network model with two types of short-term plasticity, fast synaptic short-term depression (STD) and slower threshold adaptation (TA). We probe the model with an oddball stimulation paradigm and assess DD by evaluating the network responses. We find that TA is sufficient to elicit DD. It achieves this by habituating neurons near the stimulation site that respond earliest to the frequently presented standard stimulus (local fatigue), which diminishes the response and promotes the recovery (global fatigue) of the wider network. Further, we find a synergy effect between STD and TA, where they interact with each other to achieve greater DD than the sum of their individual effects. We show that this synergy is caused by the local fatigue added by STD, which inhibits the global response to the frequently presented stimulus, allowing greater recovery of TA-mediated global fatigue and making the network more responsive to the deviant stimulus. Finally, we show that the magnitude of DD strongly depends on the timescale of stimulation. We conclude that highly predictable information can be encoded in strong local fatigue, which allows greater global recovery and subsequent heightened sensitivity for DD.