bluuebunny/crossref_metadata_2025 huggingface dataset:
Long COVID-19 and longer sick leave: longitudinal study of economically active patients
Authors: Gallo González Virginia , López-Padilla Daniel , Díez Javier de Miguel , Suárez Escudero Sergio , Ojeda Castillejo Elena , Ji Zichen , Puente Maestu Luis
Published: November 2024

Introduction

Sick leave was also part of the numerous consequences of the COVID-19 pandemic. Given the relevance of occupational status for any individual, the aim of the study was to evaluate the impact of persistent symptoms after active infection and determine associated factors with longer sick leaves (LSL).

Methods

Observational study of economically active patients attending a post-COVID outpatient clinic for persistence of symptoms or radiological alterations after active infection. LSL temporal cut off point was defined by the third tertile of total leave days. Median leave time was compared with the optimal sick leave time for any other viral pneumonia, estimated by the local Ministry of Employment. To determine factors associated with LSL, multivariate models were performed.

Results

A total of 248 patients were included. Median sick leave time of all population was 53 days (interquartile range [IQR] 37–126.5), global sum of 30 169 days; median optimal sick leave time was 21.9 days (IQR 19.7–25.9) (p<0.05). Third tertile cut off point for LSL was 83 days, and multivariate analysis showed that dyspnea associated significantly with it (OR 3.26, 95% CI 1.59–6.70, p=0.0001), while physical exercise of at least 10 min a day significantly associated with shorter sick leaves (OR 0.45, 95% CI 0.20–0.98, p=0.04).

Discussion

COVID-19 sick leave was considerably longer than that stipulated for non-SARS-CoV-2 viral pneumonia. LongCOVID syndrome, especially dyspnea, seems to be a very present factor in the inability to work of these patients.
Acute effect of acetazolamide on exercise hemodynamics in patients with pulmonary arterial and chronic thromboembolic pulmonary hypertension: a randomised controlled trial
Authors: Carta Arcangelo F. , Saxer Stéphanie , Mayer Laura , Schneider Simon R. , Furian Michael , Schwarz Esther I. , Swenson Erik R. , Bloch Konrad E. , Lichtblau Mona , Ulrich Silvia
Published: November 2024

Background/Aims

The aim of this study was to investigate the acute effect of acetazolamide on pulmonary hemodynamics during exercise in patients with pulmonary vascular disease (PVD).

Methods

Patients with PVD diagnosed as pulmonary arterial or chronic thromboembolic pulmonary hypertension (PAH/CTEPH) underwent right heart catheterisation with hemodynamic measurements at rest and during stepwise incremental cycling exercise 60 min after intravenous administration of acetazolamide (500 mg) or placebo-saline according to a double-blind, randomised-controlled cross-over design. The main outcomes were the difference between pulmonary vascular resistance (PVR) and its components mean pulmonary artery pressure (mPAP), cardiac output (CO) and pulmonary arterial wedge pressure (PAWP) during exercise assessed by mixed linear regression analysis.

Results

24 patients (7 PAH, 17 CTEPH, 17 male) were included (mean±sdage 59±14 years). Treatment with acetazolamide compared to placebo-saline showed the following average marginal effects during exercise: unchanged end exercise power (mean difference and 95%CI, −0.9 W, −5.7 to 4.1 W, p=0.740), reduced mPAP (−1.7 mmHg, −2.9 to −0.5 mmHg, p=0.007), tendency to reduced CO (−0.3 L·min−1, −0.7 to 0.1 L·min−1, p=0.097), unchanged PVR (−0.1 WU, −0.3 to 0.2 WU, p=0.694), unchanged PAWP (−0.0 mmHg, −0.2 to 0.3 mmHg, p=0.783) and unchanged mPAP/CO-slope (0.5 mL·min−1, −0.7 to 1.6, p=0.431).

Conclusion

Intravenous acetazolamide was well tolerated and resulted in a significant but small decrease of mPAP while CO, PVR and the pressure-flow slope during exercise were unchanged.
Effect of Benralizumab treatment on the airway microbiome in COPD
Authors: Haldar Koirobi , Mistry Vijay , Richardson Mathew , Hamblet Corinne , Jison Maria , Barer Michael R. , McCrae Christopher , Brightling Christopher E.
Published: November 2024

Background

One-third of patients with Chronic obstructive pulmonary disease (COPD) have an eosinophilic inflammatory phenotype. Benralizumab is an afucosylated humanised monoclonal antibody that targets the IL-5 receptor α subunit, leading to rapid and near-complete eosinophil depletionviaantibody-dependent cellular cytotoxicity. We hypothesized that benralizumab targeted immune modulation could have an impact on the airway microbiome in COPD.

Objective

To investigate the effect of Benralizumab treatment on inflammation and the sputum microbiome in COPD.

Methods

Sputum samples from 94 COPD patients enrolled to the GALATHEA trial (NCT02138916) and randomized to receive placebo (33), benralizumab at 100 mg (29) or 30 mg (32) over 52 weeks, were analysed at baseline, week 24 and at end-of-treatment (week 56). Sputum microbiota taxonomic profiles and diversity indices, generated from paired-end Illumina sequencing targeting the 16sRNA gene, were used for comparative analyses. Linear mixed model analyses were applied on blood and sputum cell count and eosinophil mediators for within and between treatment group analysis.

Results

Participants treated with 100 and 30 mg benralizumab respectively, showed a significant reduction from baseline in blood and sputum eosinophil counts (Blood p=1.2E-10 & p=8.8E-10; Sputum p=0.03 & p=0.004) and eosinophil-derived serum mediators (ECP p<3E-09 & p<2E-08; EDN p<8E- 12 & p<2E-09). No significant changes in the composition or diversity of the sputum microbiome were observed.

Conclusions

In this study, the airway microbiome measured in sputum was unaffected by targeted reduction of eosinophilic inflammation with benralizumab treatment.
Mannitol-evoked cough response is reduced by inhaled salbutamol
Authors: Wahab Mustafaa , Cusack Ruth P. , Stevens Caitlin , Howie Karen J. , Schlatman Abbey , Killian Kieran J. , O'Byrne Paul M. , Satia Imran , Gauvreau Gail M.
Published: November 2024

Background

Mannitol inhalation induces bronchoconstriction and coughing in asthmatics. Salbutamol causes smooth muscle relaxation in acute asthma, but its effects on airway nerves are unclear. We conducted mannitol cough challenges in allergic asthmatics (AA) and controls (HC) to determine whether salbutamol would reduce mannitol-evoked coughs independent of changes in airway calibre.

Methods

A double-blind, randomized, placebo-controlled, 2-way crossover study included 20 mild steroid-naïve AA and 20 HC. The maximum number of coughs (Emax) evoked by mannitol was compared between salbutamol and placebo.

Results

HC and AA were matched for age, lung function, and sex. Mannitol-evoked cough dose ratio (CDR) in HC was significantly lower than in AA (5.63 (1.84)versus7.32 (3.67) coughs, p=0.023). Both groups had similar Emax, C2 and C5 (dose causing 2 and 5 coughs, respectively). In AA mannitol decreased FEV1by 8.11±2.32% with placebo, which was attenuated to 3.19±1.16% with salbutamol (p=0.03). In HC, FEV1reduction was not significant. Emax in AA for placebo and salbutamol was 8.90 (8.09–9.80) coughs and 7.07 (6.28–8.00) coughs, respectively (p<0.001) and in HC 8.19 (7.08–9.61) coughs and 4.95 (4.38–5.66) coughs, respectively (p<0.001). The effect of salbutamol on Emax between groups was significantly different (p<0.001). Salbutamol improved CDR, C2 and C5 in AA (p<0.05) but without effect between groups.

Conclusion

Salbutamol reduced mannitol Emax in AA and HC. The reduced mannitol-evoked cough response by salbutamol in HC was independent of changes in airway calibre measured by FEV1, suggesting mechanisms of salbutamol extend beyond smooth muscle relaxation.
Contact Stiffness Identification Method for Joint Surface and the Effect of Contact Stiffness on the Dynamic Response of the Cable Bracket
Authors: Wei Xue , Ren Zunsong , Li Guangquan
Published: November 2024

The cable bracket is one of the crucial components of high-speed Electric Multiple Units (EMUs), which is fixed to the axle box by bolts to support the cable. As an important parameter of the joint surface, contact stiffness significantly affects the dynamic response and service life of the cable bracket. However, it is difficult to directly measure the contact stiffness of the joint surface. As a result, an identification method is proposed in this investigation to identify the contact stiffness. A finite element model incorporating both normal and tangential stiffness parameters is developed. According to the finite element model and modal testing results, an improved particle swarm optimization algorithm is employed to identify the contact stiffness of the joint surface. The effect of the contact stiffness on the vibrations of the cable bracket is investigated. The findings indicate that pre-tightening torque significantly influences the contact stiffness of the cable bracket. The contact stiffness has a great effect on the vibrations of the cable bracket. Optimal contact stiffness notably reduces vibrations of the cable bracket, thereby extending its service life.
Human Gb3/CD77 synthase: a glycosyltransferase at the crossroads of immunohematology, toxicology, and cancer research
Authors: Szymczak-Kulus Katarzyna , Czerwinski Marcin , Kaczmarek Radoslaw
Published: November 2024

Human Gb3/CD77 synthase (α1,4-galactosyltransferase, P1/Pk synthase, UDP-galactose: β-d-galactosyl-β1-R 4-α-d-galactosyltransferase, EC 2.4.1.228) forms Galα1 → 4Gal structures on glycosphingolipids and glycoproteins. These glycans are recognized by bacterial adhesins and toxins. Globotriaosylceramide (Gb3), the major product of Gb3/CD77 synthase, is a glycosphingolipid located predominantly in plasma membrane lipid rafts, where it serves as a main receptor for Shiga toxins released by enterohemorrhagic Escherichia coli and Shigella dysenteriae of serotype 1. On the other hand, accumulation of glycans formed by Gb3/CD77 synthase contributes to the symptoms of Anderson–Fabry disease caused by α-galactosidase A deficiency. Moreover, variation in Gb3/CD77 synthase expression and activity underlies the P1PK histo-blood group system. Glycosphingolipids synthesized by the enzyme are overproduced in colorectal, gastric, pancreatic, and ovarian cancer, and elevated Gb3 biosynthesis is associated with cancer cell chemo- and radioresistance. Furthermore, Gb3/CD77 synthase acts as a key glycosyltransferase modulating ovarian cancer cell plasticity. Here, we describe the role of human Gb3/CD77 synthase and its products in the P1PK histo-blood group system, Anderson–Fabry disease, and bacterial infections. Additionally, we provide an overview of emerging evidence that Gb3/CD77 synthase and its glycosphingolipid products are involved in cancer metastasis and chemoresistance.

Graphical Abstract
Challenges in measurement of adolescent mental health: how are gender patterns affected when level of symptoms is analysed simultaneously with impairment?
Authors: Hagquist Curt
Published: November 2024

Background

Adolescent mental health surveys in public health are sometimes questioned because of their main focus on self-reported symptoms, lacking data on impairment, e.g. the consequences on everyday life of the mental health problems. While public health studies typically reveal higher prevalence rates of internalising problems for girls than boys, there are indications that the gender pattern may change when self-reported data on symptoms are analysed simultaneously with impairment. The purpose is to determine how gender patterns of adolescent mental health solely based on symptoms are affected when level of symptoms is analysed simultaneously with impairment.

Methods

Questionnaire data on adolescent mental health were collected in schools by Statistics Sweden in the autumn of 2009 as part of a national total population study in grades 6 and 9 in Sweden. In this study only data from grade 9 students are used (n = 91 627; response rate = 80 per cent). Psychosomatic symptoms were measured with the Psychosomatic Problems scale including eight items. Impairment was measured with four items included in the SDQ impact supplement. The associations between these key constructs were analysed with logistic regression and contingency tables.

Results

When analysing variables on psychosomatic symptoms and impairment independently, the results are consistent with typical findings of gender patterns in adolescent internalising mental health. Girls report both more psychosomatic symptoms, and more negative consequences in everyday life, than boys. The gender patterns are, however, strongly affected when impairment is conditioned on level of psychosomatic symptoms. Except for the Home Life setting, in the settings of Friendships, Classroom Learning and Leisure Activities, the previously reported gender pattern favoring higher disturbances among girls becomes partly reversed implying that boys report more negative consequences than girls. Hence, while girls report a higher prevalence of psychosomatic symptoms, boys appear to suffer from such symptoms more than, or as much as, girls in three out of four everyday life settings.

Conclusions

The study confirms the insufficiency of solely including data on symptoms in the measurement of adolescent mental health. Regardless of the causes of the complex gender pattern shown in this study, the results highlight the importance of simultaneous inclusion of indicators of impairment as well as symptom counts and frequency in the measurement of adolescent mental health.
Head circumference and intelligence, schooling, employment, and income: a systematic review
Authors: Freire Marina B O , Slater Rebeccah , Santos Thiago M , da Silva Bruna G C , Baxter Luke , Menezes Ana M B
Published: November 2024

Background

No consensus exists about the role of head circumference in identifying children at risk of suboptimal development. The objective of this study was to evaluate the association between head circumference and intelligence, schooling, employment, and income. The review 1) summarizes the overall evidence and 2) restricts the evidence to a subset of articles that met minimum quality criteria.

Methods

PubMed, Web of Science, PsycINFO, LILACS, CINAHL, WHO Institutional Repository for Information Sharing and UNICEF Innocenti were searched to identify published studies. Cohort, case–control or cross-sectional studies which evaluated the associations of interest in the general population, premature babies, babies with low birth weight or small for gestational age were included; head circumference must have been measured before the age of 20 years. Two reviewers independently performed study selection, data extraction and quality assessments.

Results

Of 2521 records identified, 115 were included and 21 met the minimum quality criteria. Ninety studies investigated if early measures of head circumference predict later outcomes and 25 studies measured head circumference and the outcome at the same timepoint; 78 studies adjusted the head circumference for age and sex. We identified large heterogeneity and inconsistency in the effect measures and data reported across studies. Despite the relatively large number of included articles, more than 80% presented serious limitations such as lack of adjustment for confounding and severe selection bias. Considering the subset of articles which met the minimum quality criteria, 12 of 16 articles showed positive association between head circumference and intelligence in the general population. However, in premature babies, 2 of 3 articles showed no clear effect. Head circumference was positively associated with academic performance in all investigated samples (5 of 5 articles). No article which evaluated educational attainment and employment met the minimum quality criteria, but the association between head circumference and these outcomes seems to be positive.

Conclusions

Larger head circumferences are positively associated with higher levels of intelligence and academic performance in the general population, but there is evidence of non-linearity in those associations. Identifying a group of children in higher risk for worse outcomes by a simple and inexpensive tool could provide an opportunity to mitigate these negative effects. Further research is needed for a deeper understanding of the whole distribution of head circumference and its effect in premature babies. Authors should consider the non-linearity of the association in the data analysis.

Trial registration

Association between head circumference and intelligence, educational attainment, employment, and income: A systematic review, CRD42021289998.
Needs assessment for interprofessional education module on prevention and early detection of oral cancer among dental interns: a cross- sectional survey
Authors: Sujir Nanditha , Ahmed Junaid , Ramakrishna Anand , Mohammed Ciraj Ali , Unnikrishnan Bhaskaran , Gilbert John HV
Published: November 2024

Background

The challenges associated with ensuring widespread system changes to enable early diagnosis and prevention of oral cancer could benefit from interprofessional practice. A needs assessment study was conducted to inform the Interprofessional Education and Collaborative Practice (IPECP) course related to oral cancer. The primary objectives of this study were 1) to establish a tool assess the knowledge attitude and practice (KAP) related to prevention and early detection of oral cancer of health professional students, and 2) to assess the same KAP of pre-licensure dental students. Additional objectives were to consider the possibility that dental students would demonstrate good scores related to early detection and prevention of oral cancer thus indicating their readiness for interprofessional learning and collaborative practice.

Methods

Two questionnaires were utilized for this study which included 1) Readiness for interprofessional learning was assessed using the pre- validated tool of Readiness for Interprofessional Learning Scale (RIPLS) 2) A questionnaire to assess the KAP related to early diagnosis and prevention of oral cancer which was developed, validated, and evaluated. Statistical analysis includes, descriptive statistics, Mann–Whitney U test, Ordered logistic regression and Probit analysis. p value was set at < 0.05.

Results

A total of 130 dental students (74.6% female) were included in the study. Mean scores related to KAP were 15.96 ± 1.394, 4.70 + 1.146, 7.02 ± 1.019 respectively. The mean score of RIPLS was 73.15 ± 15.961. The probability of overall samples to have good RIPLS scores was around 0.68 to 0.76 (Male 0.68—0.82 & Female 0.68 -0.74). The percentage of students having good knowledge score was 93.8%, good attitude score was around 54.6% and good practice score was around 90%.

Conclusion

Knowledge and practice related to prevention and early detection of oral cancer were scored highly. Attitude scores were lower in a relatively higher proportion of participants and needed to be addressed in the curriculum. RIPLS score indicates a positive attitude towards interprofessional learning.
Identifying influential factors using machine learning techniques on the intention to receive a COVID-19 booster dose and vaccine fatigue among partially vaccinated individuals
Authors: Bikaki Athina , Luningham Justin M. , Thompson Erika L. , Krenek Brittany , Vishwanatha Jamboor K. , Kakadiaris Ioannis A.
Published: November 2024

This study assesses COVID-19 booster intentions and hesitancy in Texas, a state known for its diversity and libertarian values. A survey was conducted with 274 participants residing in Texas between June and July 2022. The analysis examined sociodemographic and health-related factors, trusted information sources, and preventive behaviors. The survey focused on vaccinated participants and their intention to receive the booster dose, which was categorized into three outcomes: yes, no, and not sure. Machine learning techniques were employed to analyze the survey responses of vaccinated participants to identify the most critical factors. Among the participants, 113 expressed their intention to get the booster (41.2%), 107 did not plan to receive the booster (39.1%), and 54 remained undecided (19.7%). Our findings indicate that the perception of vaccine safety significantly influenced the decision to receive the booster dose. Those who reported trust in social media contacts as reliable information sources were more likely to intend to boost. Additionally, among those hospitalized when diagnosed with COVID-19, the largest proportion were unwilling to receive the booster (47.0%) compared to those who intended to receive the booster (33.3%). In contrast, most of those who believed they would be hospitalized if infected with COVID-19 intended to get the booster. Other factors did not demonstrate a significant association. Our findings are highly transferable and can offer valuable insights, particularly for countries where COVID-19 remains prevalent and are pivotal both presently and in the future for developing strategies to improve booster uptake and shape public health initiatives in epidemic and pandemic outbreaks.
Sport participation levels among New York City’s kids remain low months after the COVID-19 pandemic
Authors: Jeong Yealeen , Salunga Arianne , Karamitopoulos Mara , Carter Cordelia
Published: November 2024

The COVID-19 pandemic resulted in decreased sports participation due to social distancing policies and strict return-to-play protocols. This effect has been felt profoundly in New York City, one of the earliest COVID-19 hotspots, even as restrictions have eased. This study aimed to describe sport participation rates in New York City before and after the COVID-19 pandemic. Using a cross-sectional, online retrospective survey, this study assessed sports participation among children aged 6–17 with musculoskeletal complaints. The survey included parents and guardians of 242 children (123 males, 119 females) who had an average age of 12.5 years. Statistical analyses were performed using McNemar’s test to assess changes in sports participation. The results revealed significant decreases in participation in gym class, pick-up games, basketball, and soccer after the pandemic. Notably, female adolescents were more affected, particularly in gym class. This study underscores a substantial decline in specific sports participation among New York City’s kids post-pandemic. The findings highlight the need for targeted public health strategies to encourage physical activity.
Chronic corticosterone exposure causes anxiety- and depression-related behaviors with altered gut microbial and brain metabolomic profiles in adult male C57BL/6J mice
Authors: Shoji Hirotaka , Maeda Yasuhiro , Miyakawa Tsuyoshi
Published: November 2024

Chronic exposure to glucocorticoids in response to long-term stress is thought to be a risk factor for major depression. Depression is associated with disturbances in the gut microbiota composition and peripheral and central energy metabolism. However, the relationship between chronic glucocorticoid exposure, the gut microbiota, and brain metabolism remains largely unknown. In this study, we first investigated the effects of chronic corticosterone exposure on various domains of behavior in adult male C57BL/6J mice treated with the glucocorticoid corticosterone to evaluate them as an animal model of depression. We then examined the gut microbial composition and brain and plasma metabolome in corticosterone-treated mice. Chronic corticosterone treatment resulted in reduced locomotor activity, increased anxiety-like and depression-related behaviors, decreased rotarod latency, reduced acoustic startle response, decreased social behavior, working memory deficits, impaired contextual fear memory, and enhanced cued fear memory. Chronic corticosterone treatment also altered the composition of gut microbiota, which has been reported to be associated with depression, such as increased abundance of Bifidobacterium, Turicibacter, and Corynebacterium and decreased abundance of Barnesiella. Metabolomic data revealed that long-term exposure to corticosterone led to a decrease in brain neurotransmitter metabolites, such as serotonin, 5-hydroxyindoleacetic acid, acetylcholine, and gamma-aminobutyric acid, as well as changes in betaine and methionine metabolism, as indicated by decreased levels of adenosine, dimethylglycine, choline, and methionine in the brain. These results indicate that mice treated with corticosterone have good face and construct validity as an animal model for studying anxiety and depression with altered gut microbial composition and brain metabolism, offering new insights into the neurobiological basis of depression arising from gut-brain axis dysfunction caused by prolonged exposure to excessive glucocorticoids.
Combining microscale ATR-FTIR and chemometrics to interpret degradation characteristics of earlywood, latewood, and compression wood in waterlogged archaeological pine wood
Authors: Li Ren , Zhang Zhiguo , Jiao Lichao , Yin Yafang , Tie Fude , Sun Manli
Published: November 2024

Interpreting the degradation characteristics of waterlogged archaeological wood (WAW) is crucial for the conservation of wooden cultural heritage. Generally, multidisciplinary diagnostic methods, including physical, micromorphological, and chemical approaches, are employed to evaluate the preservation state of WAW. However, primarily focused on the sample level, this methodology limits the understanding of the variability in degradation from a detailed perspective. In this paper, we adopted the in-situ microscale attenuated total reflectance Fourier transform infrared (ATR-FTIR) method to investigate the degradation variability in waterlogged archaeological Masson pine (Pinus massoniana) wood excavated from the ancient Chinese shipwreck Nanhai No. 1. Specifically, spectra of earlywood (EW), latewood (LW), and compression wood (CW) were extracted and combined with chemometrics to achieve rapid classification of their degradation levels. The micromorphological features of wood cell walls in conjunction with the ratios of lignin (A1509) and carbohydrate (A1370) peak areas were used to estimate the degradation levels. Unlike recent wood, moderate degradation in CW and severe degradation in EW and LW were classified in archaeological samples. The degradation levels were effectively determined through principal component analysis (PCA) and sparse partial least squares discriminant analysis (sPLSDA). The results suggest that chemometric analysis is a promising method to discern the variable degradation levels of archaeological wood at the tissue level. The methodologies developed in this study provide detailed insights into the degradation characteristics in WAW and improve the accuracy of evaluating the preservation state.
Accurate acoustic classification research of visually similar monochrome porcelain fragments
Authors: Jin Xiaoxue , Wang Xiufeng , Zhang Xiaoyu , Xue Chaohua
Published: November 2024

Exploring a non-destructive and rapid evaluation method for precious ancient ceramic relics is of significant importance. Currently, there are countless monochrome porcelain fragments awaiting measurement and categorization. Various instruments such as XRF, XRD, SEM, OM, and thermoluminescence dating have been extensively utilized by numerous researchers to study ancient ceramics. However, these techniques pose challenges in reliably identifying monochrome porcelain fragments from the same kiln with similar appearance, content, and microstructure due to their limitations. To address this issue, this study presents an acoustic measurement system that utilizes audible frequencies to non-destructively evaluate monochrome porcelain fragments. The proposed method enables the extraction of parameters related to time domain analysis (e.g., group delay), frequency domain analysis (e.g., resonance), and sound loss characteristics of these fragments. This non-destructive and efficient technology for detecting acoustic characteristics of monochrome porcelain fragments presented in this work clarifies the fundamental principles governing the interaction between sound waves and ancient ceramic fragments while providing a completely non-destructive and highly efficient method for classifying and restoring valuable solid cultural heritages like stone, jade, bronze etc. Moreover, this approach can also be applied for non-destructive testing of elastic modulus in advanced ceramic devices including detecting small cracks, deterioration effects due to aging as well as other defects.
Study on the prehistoric decorated spindle whorls in Haidai region of China
Authors: Tao Yuan , Wang Qicai
Published: November 2024

Spindle whorls are a kind of spinning tools of crucially important in prehistoric period. Haidai region is one of the main historical and cultural areas of prehistoric China, and had a relatively developed textile handicraft production, where a large number of spindle whorls were unearthed, including many decorated ones. In order to make clear the uses of the decorated spindle whorls and the meanings of the patterns on them, the data of prehistoric decorated spindle whorls unearthed in archaeological sites of the period from Beixin Culture to Yueshi Culture in Haidai region of China were collected and analyzed, and the morphological data (dimension and shapes) of them were compared with that of undecorated ones. The patterns on the decorated spindle whorls were analyzed and classified, and the characteristics of the patterns in different cultural periods were studied, and based on this, the purpose of making decorated spindle whorls and the function and meanings of the patterns were discussed. The results showed that the range of morphological data of the decorated spindle whorls in Haidai region is consistent with that of undecorated ones belonging to the same period and unearthed in the same site, while compared with undecorated spindle whorls, decorated ones are more affected by regional culture and thus show different features from the ones unearthed in other archaeological sites belonging to the same cultural period. It is concluded that the most basic function of the decorated spindle whorls should be as practical tools for normal spinning production, and the patterns on them should have multiple meanings such as practical, decorative, distinctive and symbolic. The study of decorated spindle whorls can help us understand the prehistoric regional culture in Haidai region.
Advances in ECG and PCG-based cardiovascular disease classification: a review of deep learning and machine learning methods
Authors: Ameen Asmaa , Fattoh Ibrahim Eldesouky , Abd El-Hafeez Tarek , Ahmed Kareem
Published: November 2024

Cardiovascular diseases (CVD) have been found to be prevalent in society, frequently ending in death. According to the findings of a recent survey, the mortality rate is increasing due to the prevalence of adult cigarette consumption, elevated blood pressure, high cholesterol levels, and obesity. The previously mentioned causes are exacerbating the severity of the condition. A pressing necessity exists for a study on the variability of these factors and their impact on cardiovascular disease (CVD). This involves the use of advanced tools to detect the disease early on and aid in the reduction of fatality rates. With their extensive methodologies that would help in the early CVD prediction and recognition of behavioral patterns in large amounts of data, artificial intelligence, and data mining disciplines offer a broad study potential. The results of these predictions will help physicians make decisions and early diagnoses, decreasing the risk of patient death. This work compares and reports the classification, machine learning, and deep learning algorithms that predict cardiovascular illnesses. For this study, articles from 2012 to 2023 were considered; after filtering, 82 articles were chosen for primary research. Future researchers will benefit from this review on cardiovascular disorders by better understanding the Deep Learning and Machine Learning models now in the healthcare sector. The review encompasses commonly employed methodologies such as support vector machine, decision tree, random forest, and convolutional neural networks (CNNs). Additionally, this survey aggregates and presents information on the performance metrics used to report accuracy. It also goes over the most popular datasets used by various diagnostic models (ECG and PCG signals datasets). In addition, it emphasizes prominent publishers, journals, and conferences that serve as platforms for the evaluation of scholarly works. Additionally, it will facilitate their understanding of the unresolved challenges or hurdles experienced by past researchers. A lack of more extensive and consistent datasets was the most common issue, followed by the need to improve existing models.
Low-level turbulence risk assessment and visualization using temporal rate of change of headwind of an aircraft
Authors: Ito Koji , Ohba Haruka , Mizuno Shinya
Published: November 2024

In this study, we focused on the temporal rate of change of headwind, which is one of the recorded parameters in the aircraft’s in-flight quick access recorder data. We selected the Laplace distribution and utilized the scaling parameter to construct a low-level turbulence risk assessment model. Using this model, we calculated the risk of low-level turbulence occurrence at five airports in Japan based on the month, time of day, and wind speed. We visualized how the geographical conditions at each airport influenced risk in relation to airport wind speeds. We developed a low-level turbulence visualization site linked to weather conditions using these results to enable pilots to easily verify low-level turbulence risk and incorporate this information into their flight routines. These findings are anticipated to significantly enhance aircraft safety.
Exploring the application of ChatGPT in ESL/EFL education and related research issues: a systematic review of empirical studies
Authors: Lo Chung Kwan , Yu Philip Leung Ho , Xu Simin , Ng Davy Tsz Kit , Jong Morris Siu-yung
Published: November 2024

ChatGPT, a sophisticated artificial intelligence (AI) chatbot capable of providing personalised responses to users’ inquiries, recently has had a substantial impact on education. Many studies have explored the use of ChatGPT in English as a second language (ESL) and English as a foreign language (EFL) education since its release on 30 November 2022. However, there has been a lack of systematic reviews summarising both the current knowledge and the gaps in this research area. This systematic review analyses 70 empirical studies related to the use of ChatGPT in ESL/EFL education within a 1.5-year period following its release. Using the Technology-based Learning Model, we provide a comprehensive overview of the domains in which ChatGPT has been applied, the methodological approaches, and associated research issues. The included studies collectively provide solid evidence regarding the affordances (e.g., increased learning opportunities, personalised learning, and teacher support) and potential drawbacks (e.g., incorrect information, privacy leakage, and academic dishonesty) of ChatGPT use in ESL/EFL education. However, our findings indicate that the majority of studies have focused on students’ use of this AI tool in writing, while few studies have quantitatively examined its effects on students’ performance and motivation. In addition, the impact of ChatGPT on other language skills, such as reading, speaking, and listening, remains under-researched. Therefore, we recommend that longer-term studies with rigorous research designs (e.g., quasi-experimental designs) and objective data sources (e.g., standardised tests) be conducted to provide more robust evidence regarding the influence of ChatGPT on students’ English language acquisition.
Organ-specific SPECT activity calibration using 3D printed phantoms for molecular radiotherapy dosimetry
Authors: Robinson Andrew P. , Tipping Jill , Cullen David M. , Hamilton David , Brown Richard , Flynn Alex , Oldfield Christopher , Page Emma , Price Emlyn , Smith Andrew , Snee Richard
Published: November 2024

Background

Patient-specific absorbed dose calculations for molecular radiotherapy require accurate activity quantification. This is commonly derived from Single-Photon Emission Computed Tomography (SPECT) imaging using a calibration factor relating detected counts to known activity in a phantom insert.

Methods

A series of phantom inserts, based on the mathematical models underlying many clinical dosimetry calculations, have been produced using 3D printing techniques. SPECT/CT data for the phantom inserts has been used to calculate new organ-specific calibration factors for 99m
Tc and 177Lu. The measured calibration factors are compared to predicted values from calculations using a Gaussian kernel.

Results

Measured SPECT calibration factors for 3D printed organs display a clear dependence on organ shape for 99m
Tc and 177Lu. The observed variation in calibration factor is reproduced using Gaussian kernel-based calculation over two orders of magnitude change in insert volume for 99m
Tc and 177Lu. These new organ-specific calibration factors show a 24, 11 and 8 % reduction in absorbed dose for the liver, spleen and kidneys, respectively.

Conclusions

Non-spherical calibration factors from 3D printed phantom inserts can significantly improve the accuracy of whole organ activity quantification for molecular radiotherapy, providing a crucial step towards individualised activity quantification and patient-specific dosimetry. 3D printed inserts are found to provide a cost effective and efficient way for clinical centres to access more realistic phantom data.
Advances in genomic tools for plant breeding: harnessing DNA molecular markers, genomic selection, and genome editing
Authors: Kumar Rahul , Das Sankar Prasad , Choudhury Burhan Uddin , Kumar Amit , Prakash Nitish Ranjan , Verma Ramlakhan , Chakraborti Mridul , Devi Ayam Gangarani , Bhattacharjee Bijoya , Das Rekha , Das Bapi , Devi H. Lembisana , Das Biswajit , Rawat Santoshi , Mishra Vinay Kumar
Published: November 2024

Conventional pre-genomics breeding methodologies have significantly improved crop yields since the mid-twentieth century. Genomics provides breeders with advanced tools for whole-genome study, enabling a direct genotype–phenotype analysis. This shift has led to precise and efficient crop development through genomics-based approaches, including molecular markers, genomic selection, and genome editing. Molecular markers, such as SNPs, are crucial for identifying genomic regions linked to important traits, enhancing breeding accuracy and efficiency. Genomic resources viz. genetic markers, reference genomes, sequence and protein databases, transcriptomes, and gene expression profiles, are vital in plant breeding and aid in the identification of key traits, understanding genetic diversity, assist in genomic mapping, support marker-assisted selection and speeding up breeding programs. Advanced techniques like CRISPR/Cas9 allow precise gene modification, accelerating breeding processes. Key techniques like Genome-Wide Association study (GWAS), Marker-Assisted Selection (MAS), and Genomic Selection (GS) enable precise trait selection and prediction of breeding outcomes, improving crop yield, disease resistance, and stress tolerance. These tools are handy for complex traits influenced by multiple genes and environmental factors. This paper explores new genomic technologies like molecular markers, genomic selection, and genome editing for plant breeding showcasing their impact on developing new plant varieties.
Enhancing the diagnostic capacity of [18F]PSMA-1007 PET/MRI in primary prostate cancer staging with artificial intelligence and semi-quantitative DCE: an exploratory study
Authors: Glemser Philip Alexander , Freitag Martin , Kovacs Balint , Netzer Nils , Dimitrakopoulou-Strauss Antonia , Haberkorn Uwe , Maier-Hein Klaus , Schwab Constantin , Duensing Stefan , Beuthien-Baumann Bettina , Schlemmer Heinz-Peter , Bonekamp David , Giesel Frederik , Sachpekidis Christos
Published: November 2024

Background

To investigate the ability of artificial intelligence (AI)-based and semi-quantitative dynamic contrast enhanced (DCE) multiparametric MRI (mpMRI), performed within [18F]-PSMA-1007 PET/MRI, in differentiating benign from malignant prostate tissues in patients with primary prostate cancer (PC).

Results

A total of seven patients underwent whole-body [18F]-PSMA-1007 PET/MRI examinations including a pelvic mpMRI protocol with T2w, diffusion weighted imaging (DWI) and DCE image series. Conventional analysis included visual reading of PET/MRI images and Prostate Imaging Reporting & Data System (PI-RADS) scoring of the prostate. On the prostate level, we performed manual segmentations for time-intensity curve parameter formation and semi-quantitative analysis based on DCE segmentation data of PC-suspicious lesions. Moreover, we applied a recently introduced deep learning (DL) pipeline previously trained on 1010 independent MRI examinations with systematic biopsy-enhanced histopathological targeted biopsy lesion ground truth in order to perform AI-based lesion detection, prostate segmentation and derivation of a deep learning PI-RADS score. DICE coefficients between manual and automatic DL-acquired segmentations were compared. On patient-based analysis, PET/MRI revealed PC-suspicious lesions in the prostate gland in 6/7 patients (Gleason Score-GS ≥ 7b) that were histologically confirmed. Four of these patients also showed lymph node metastases, while two of them had bone metastases. One patient with GS 6 showed no PC-suspicious lesions. Based on DCE segmentations, a distinction between PC-suspicious and normal appearing tissue was feasible with the parameters fitted maximum contrast ratio (FMCR) and wash-in-slope. DICE coefficients (manual vs. deep learning) were comparable with literature values at a mean of 0.44. Further, the DL pipeline could identify the intraprostatic PC-suspicious lesions in all six patients with clinically significant PC.

Conclusion

Firstly, semi-quantitative DCE analysis based on manual segmentations of time-intensity curves was able to distinguish benign from malignant tissues. Moreover, DL analysis of the MRI data could detect clinically significant PC in all cases, demonstrating the feasibility of AI-supported approaches in increasing diagnostic certainty of PSMA-radioligand PET/MRI.
Decolonising our minds: what UK psychiatry needs to (un)learn
Authors: Satram Venkatalakshmi
Published: November 2024

The dominance of Western orthodox models of psychiatry has led to colonisation of the mind and marginalisation of diverse cultural conceptualisations of distress and forms of caring. Compounded by a crisis of care and chronic underfunding, this has also diminished our practice here in the UK. This article probes the biases that UK psychiatry must unlearn and what lessons it can learn from decolonising praxes originating in the Global South. This is a call to action. We must transform our mindsets and advocate for contextualised, collective, integrative and socially just mental healthcare in the UK.
Successful Multimodal Treatment of Locally Advanced Parathyroid Carcinoma
Authors: Kim Na Hyun , Kim Chae A , Chung Sae Rom , Chung Ki-Wook , Kim Won Gu , Jeon Min Ji
Published: November 2024

Parathyroid carcinoma is a rare endocrine malignancy for which the primary treatment is surgery; however, 50% of the patients develop local recurrence or distant metastases. No consensus exists on the standard treatment for metastatic parathyroid cancer. Here we report a case of a 41-year-old male with inoperable locally advanced parathyroid carcinoma who was successfully treated with multimodal therapy including radiofrequency ablation (RFA), external beam radiation therapy (EBRT) to the neck, and sorafenib. Eleven months after initiating sorafenib, serum calcium levels were normal, and both the intact PTH level and the size of metastatic lesion remained stable; thus, we decided to discontinue sorafenib. After discontinuation, the disease remained stable for 18 months and continues to be so. Hence, clinicians can consider multimodal treatment with RFA, EBRT, and sorafenib as a treatment option for locally advanced parathyroid carcinoma.
Comprehensive Morphometric Analysis to Identify Key Neuroimaging Biomarkers for the Diagnosis of Adult Hydrocephalus Using Artificial Intelligence
Authors: Gholampour Seifollah , Rosen Jacob Benjamin , Pagan Michelangelo , Chen Sonja , Gomaa Ibrahim , Dehghan Arshia , Waterstraat Mark Graham
Published: November 2024

BACKGROUND AND OBJECTIVES:

Hydrocephalus involves abnormal cerebrospinal fluid accumulation in brain ventricles. Early and accurate diagnosis is crucial for timely intervention and preventing progressive neurological deterioration. The aim of this study was to identify key neuroimaging biomarkers for the diagnosis of hydrocephalus using artificial intelligence to develop practical and accurate diagnostic tools for neurosurgeons.

METHODS:

Fifteen 1-dimensional (1-D) neuroimaging parameters and ventricular volume of adult patients with non-normal pressure hydrocephalus and healthy subjects were measured using manual image processing, and 10 morphometric indices were also calculated. The data set was analyzed using 8 machine, ensemble, and deep learning classifiers to predict hydrocephalus. SHapley Additive exPlanations (SHAP) feature importance analysis identified key neuroimaging diagnostic biomarkers.

RESULTS:

Gradient Boosting achieved the highest performance, with an accuracy of 0.94 and an area under the curve of 0.97. SHAP analysis identified ventricular volume as the most important parameter. Given the challenges of measuring volume for clinicians, we identified key 1-D morphometric biomarkers that are easily measurable yet provide similar classifier performance. The results showed that the frontal-temporal horn ratio, modified Evan index, modified cella media index, sagittal maximum lateral ventricle height, and coronal posterior callosal angle are key 1-D diagnostic biomarkers. Notably, higher modified Evan index, modified cella media index, and sagittal maximum lateral ventricle height, and lower frontal-temporal horn ratio and coronal posterior callosal angle values were associated with hydrocephalus prediction. The results also elucidated the relationships between these key 1-D morphometric parameters and ventricular volume, providing potential diagnostic insights.

CONCLUSION:

This study highlights the importance of a multifaceted diagnostic approach incorporating 5 easily measurable 1-D neuroimaging biomarkers for neurosurgeons to differentiate non-normal pressure hydrocephalus from healthy subjects. Incorporating our artificial intelligence model, interpreted through SHAP analysis, into routine clinical workflows may transform the diagnostic landscape for hydrocephalus by standardizing diagnosis and overcoming the limitations of visual evaluations, particularly in early stages and challenging cases.