bluuebunny/crossref_metadata_2025 huggingface dataset:
A review on layerless 3D printing: challenges and applications
Authors: Moayedi Siavash , Zamani Jamal , Salehi Mohammad
Published: October 2024

Purpose

This paper aims to provide a full introduction, new classification, comparison and investigation of the challenges as well as applications of layerless 3D printing, which is one of the industry 4.0 pioneers.

Design/methodology/approach

Given the significance and novelty of uniform 3D printing, more than 250 publications were collected and reviewed in an unbiased and clear manner.

Findings

As a result, the majority of uniform parts printed in polymer form are known up to this point. In a novel division for better researchers’ comprehension, uniform printing systems were classified into three categories: oxygen inhibition (OI), liquid lubrication (LL) and photon penetration (PP), and each was thoroughly investigated. Furthermore, these three approaches were evaluated in terms of printing speed, precision and accuracy, manufacturing scale and cost.

Originality/value

The parameters of each approach were compared independently, and then a practical comparison was conducted among these three approaches. Finally, a variety of technologies, opportunities, challenges and advantages of each significant method, as well as a future outlook for layerless rapid prototyping, are presented.
Nexus between intellectual capital and innovation performance: the mediating role of firm’s attractiveness and knowledge sharing
Authors: Kumar Jitender , Rani Vinki , Rani Manju , Rani Garima
Published: October 2024

Purpose

Intellectual capital has recently gained significant attention for achieving a competitive advantage for firms. Accordingly, this study aims to examines the impact of intellectual capital on small and medium enterprises (SMEs) innovation performance. Additionally, it also examines the mediating role of firm’s attractiveness (FATR) and knowledge sharing (KS) in small enterprises of India’s National Capital Region (NCR).

Design/methodology/approach

Data was gathered from 395 owners and managers of the NCR region through a self-administered survey questionnaire. The author applied a “variance-based structural equation modeling” to examine the outcomes.

Findings

The outcomes exhibited that relational capital (RC) significantly influences the FATR, while human capital (HC) and structural capital (SC) insignificantly influences the FATR. Furthermore, HC, RC and SC substantially influence KS. Interestingly, the outcomes also reveal that a FATR and KS substantially influence innovation performance.

Research limitations/implications

This research provides valuable opportunities to expand the study of intellectual capital and innovation performance in SMEs across different countries, paving the way for future comparative analyses in diverse international contexts.

Practical implications

The results assist policymakers and practitioners in assessing an organization’s ability to transform data into intellectual capital within the context of “Industrial Revolution 4.0” to strengthen its sustainability and innovation performance.

Originality/value

The current paper delivers a more affluent and novel understanding of Indian SMEs by examining the interplay between intellectual capital and innovation performance mediating by a FATR and KS behavior. Furthermore, the proposed model has not been previously addressed in the academic literature, which signifies advancement in scientific knowledge.
Staff shortages in hospitality and tourism industries: how technology influences?
Authors: Birdir Kemal , Sahilli Birdir Sevda
Published: October 2024

Purpose

This paper offers an introduction and sets the stage for the theme issue. It describes the methodology used and highlights the articles that address the strategic question of how hospitality and tourism industries can minimize the effects of labor shortages by embracing advanced technologies.

Design/methodology/approach

This special issue explores the potential of automation, artificial intelligence, robotics and advanced data analytics in mitigating staff shortages. Automation streamlines operations, AI enhances customer interactions, robotics reimagines service delivery and data analytics informs strategic decisions. The study addresses a strategic question by combining literature reviews, data analysis, expert insights from practitioners and practical solution recommendations.

Findings

The theme issue presents research that explores how advanced technologies can be effectively utilized to mitigate labor shortages in the hospitality and tourism industries. Automation streamlines operations, AI enhances customer interactions, robotics reimagines service delivery and data analytics informs strategic decisions. However, successful integration of technology requires careful planning, training and ongoing maintenance to ensure a balance between technology and human interaction. By embracing these technologies, businesses can better cope with staffing deficits and position themselves for long-term success in a rapidly evolving environment.

Originality/value

This special issue explores the ways in which advanced technologies, such as automation, AI and robotics, can be leveraged to alleviate the labor shortage crisis faced by the hospitality and tourism industries worldwide. From developed to developing countries, these industries are grappling with severe labor shortages, particularly in terms of skilled workers. The articles presented in this issue offer valuable insights and strategies for addressing this pressing issue.
Detecting and evaluating surface defects in additive manufacturing composite materials via image processing technique
Authors: Nawafleh Nashat , AL-Oqla Faris M.
Published: October 2024

Purpose

This study aims to offer an image-based robust edge detection system that can estimate, identify, locate and label surface flaws during manufacturing for real-time surface issue diagnostics. Of great concern, this methodology extrapolates surface defect information from scanning electron microscopy (SEM) images of composite fracture surfaces. This study predicts changes in topological intensity of composite fracture surfaces and display them as real-time surface intensity values for the first time.

Design/methodology/approach

This work, however, introduces a novel robust edge detection method – based image processing – as it is shown to be effective in locating defects, as measured by SEM images of composite fracture surfaces created using additive manufacturing (AM). SEM images, obtained in this study, are related to previous study considering the fracture surfaces of reinforced thermoset composites created via the AM method. These SEM images are of two types: fracture surface of AM of carbon fiber reinforced thermoset composites and fracture surface of AM of syntactic foam reinforced thermoset composites. Initially, MATLAB environment is used for analyzing the SEM images; the technique used, as well as the validity are explained more in the methodology section.

Findings

The robust surface defect inspection approach used herein is found to be capable of predicting, identifying, localizing and labeling surface defects during production, allowing for real-time surface issue diagnosis. Further, this work makes it possible to use image processing and analysis of these surfaces to anticipate fluctuations in the topological intensity of the fracture surfaces of composites and represent them as values of surface intensity in real time.

Originality/value

Rising worldwide company rivalry requires a fast, accurate component failure diagnostic method. To create an efficient feature set, a surface defect inspection system must identify product flaws in real time. Thus, this study proposed an image-based robust edge detection system – based on MATLAB environment – that is capable of estimating, identifying, locating and labeling surface faults during production. This paves the way for an extensive set of high-quality tools for dealing with a wide range of problems associated with digital image processing in composites. As a result, the ability to define methodologies and rapidly prototype prospective solutions typically minimizes the cost and time required to implement a successful system during the design phase of an image processing system.
Gross saponins of Tribulus terrestris attenuate rheumatoid arthritis by promoting apoptosis of fibroblast‐like synoviocytes and reducing inflammation by inhibiting MAPK signalling pathway
Authors: Cheng Xinghai , Su Yuantao , Dong Ningzheng , Liu Meng , Wang Mengting , Zhou Tiantian , Zhou Haibin
Published: October 2024

Among the numerous treatment options for rheumatoid arthritis (RA), the promotion of synoviocyte apoptosis and inhibition of inflammation are considered the most effective. However, the potential pro‐apoptotic effects of gross saponins of Tribulus terrestris (GSTT), which are natural saponins derived from the herb Tribulus terrestris L., on rheumatoid arthritis fibroblast‐like synoviocytes (RA‐FLSs) and their essential molecular mechanisms remain unclear. The aim of the present study was to investigate the influence of different concentrations of GSTT on RA‐FLSs using various assays, including cell counting kit‐8 (CCK‐8), reverse transcription polymerase chain reaction (RT‐PCR), enzyme‐linked immunosorbent assay (ELISA), flow cytometry, terminal deoxynucleotidyl transferase dUTP nick end labelling (TUNEL) and western blot analysis. These assessments were conducted to evaluate the cell viability, changes in the levels of inflammatory cytokines, apoptosis rates and alterations in protein expression related to this process. In vivo, arthritis clinical score, haematoxylin and eosin (HE) staining and ELISA were used to assess paw inflammation, histopathology and serum inflammatory cytokine changes. Our findings demonstrated that GSTT substantially promotes the apoptosis of RA‐FLSs and reduces pro‐inflammatory cytokine levels. GSTT also reduced the Bcl‐2/Bax ratio and inhibited JNK and p38 phosphorylation. Furthermore, GSTT exhibits positive effects on RA by improving clinical scores, reducing synovial inflammatory infiltration and lowering serum pro‐inflammatory cytokine levels. Therefore, by promoting the apoptosis of RA‐FLSs and suppressing inflammation through the inhibition of the MAPK signalling pathway, GSTT is a promising therapeutic intervention for RA.
First‐Trimester Prediction Models Based on Maternal Characteristics for Adverse Pregnancy Outcomes: A Systematic Review and Meta‐Analysis
Authors: van Eekhout Jacintha C. A. , Becking Ellis C. , Scheffer Peter G. , Koutsoliakos Ioannis , Bax Caroline J. , Henneman Lidewij , Bekker Mireille N. , Schuit Ewoud
Published: October 2024

Background

Early risk stratification can facilitate timely interventions for adverse pregnancy outcomes, including preeclampsia (PE), small‐for‐gestational‐age neonates (SGA), spontaneous preterm birth (sPTB) and gestational diabetes mellitus (GDM).

Objectives

To perform a systematic review and meta‐analysis of first‐trimester prediction models for adverse pregnancy outcomes.

Search Strategy

The PubMed database was searched until 6 June 2024.

Selection Criteria

First‐trimester prediction models based on maternal characteristics were included. Articles reporting on prediction models that comprised biochemical or ultrasound markers were excluded.

Data Collection and Analysis

Two authors identified articles, extracted data and assessed risk of bias and applicability using PROBAST.

Main results

A total of 77 articles were included, comprising 30 developed models for PE, 15 for SGA, 11 for sPTB and 35 for GDM. Discriminatory performance in terms of median area under the curve (AUC) of these models was 0.75 [IQR 0.69–0.78] for PE models, 0.62 [0.60–0.71] for SGA models of nulliparous women, 0.74 [0.72–0.74] for SGA models of multiparous women, 0.65 [0.61–0.67] for sPTB models of nulliparous women, 0.71 [0.68–0.74] for sPTB models of multiparous women and 0.71 [0.67–0.76] for GDM models. Internal validation was performed in 40/91 (43.9%) of the models. Model calibration was reported in 21/91 (23.1%) models. External validation was performed a total of 96 times in 45/91 (49.5%) of the models. High risk of bias was observed in 94.5% of the developed models and in 58.3% of the external validations.

Conclusions

Multiple first‐trimester prediction models are available, but almost all suffer from high risk of bias, and internal and external validations were often not performed. Hence, methodological quality improvement and assessment of the clinical utility are needed.
Racing toward attaining sustainable development in India: Probing the asymmetric effect of country risk and coal energy
Authors: Wei Yanfeng , Ramzan Muhammad , Awosusi Abraham Ayobamiji , Uzun Berna , Khudoykulov Khurshid
Published: October 2024

The pursuit of a sustainable environment is a common goal for many nations; however, achieving this has become increasingly difficult due to country‐specific risks, often referred to as country risk. Despite its importance, the relationship between country risk and environmental outcomes is still in its early stages of exploration. This study aims to bridge this gap by examining the influence of country risk on India's ecological footprint within an asymmetric empirical framework, while accounting for economic growth and coal energy consumption. Utilizing the nonlinear autoregressive distributed lag (NARDL) estimator, the analysis covers data from 1984 to 2018. The findings reveal that positive changes in economic and financial risk contribute to environmental improvement by significantly reducing the ecological footprint, whereas negative changes in these risks lead to an increase in ecological footprint. Additionally, positive changes in political risk, economic growth, and coal energy usage exacerbate the ecological footprint, while reductions in coal energy use and political risk lead to environmental benefits. Based on these outcomes, policymakers are encouraged to establish a clear risk benchmark and reduce the ecological footprint by fostering economic growth in a sustainable manner. Governments should also prioritize strong support for green technology investments and ensure stability across political, economic, and financial sectors to promote long‐term environmental sustainability.
Adoption of agronomic practices and their impact on crop yield and income: An analysis for black gram and green gram in India
Authors: Varma Poornima , Manda Julius
Published: October 2024

Black gram and green gram are important pulse crops in India, but their production has faced fluctuations and stagnancy in yields over the last few decades. The Government of India has implemented several measures to enhance crop yield, including recommending and promoting the adoption of crop‐specific agronomic practices. However, there is limited empirical evidence on the determinants of the adoption of these practices and their impact on yield and income. In this context, this study analyses the determinants of the adoption of climate and plant management practices among black gram and green gram farmers and their impact on yield, crop revenue and net income across four major crop‐producing Indian states using a multinomial endogenous treatment effects model. Our analysis shows that information, contact with government extension services and access to off‐farm activities are crucial in adopting climate and plant management practices. The results strengthen the view that the adoption of knowledge‐intensive practices happens via formal information sources and plot‐level demonstrations. In addition, the results indicate that farmers who experience frequent crop loss exhibit an aversion towards adopting climate and plant management practices. While adopting these practices had a positive impact on crop yield and crop revenue, the impact on net income was observed only in the case of climate management.
Neuronal cathepsin S increases neuroinflammation and causes cognitive decline via CX3CL1‐CX3CR1 axis and JAK2‐STAT3 pathway in aging and Alzheimer's disease
Authors: Liu Pei‐Pei , Liu Xiao‐Hui , Ren Ming‐Jing , Liu Xiao‐Tong , Shi Xiao‐Qing , Li Ming‐Li , Li Shu‐Ang , Yang Yang , Wang Dian‐Dian , Wu Yue , Yin Fan‐Xiang , Guo Yan‐Hong , Yang Run‐Zhou , Cheng Meng , Xin Yong‐Juan , Kang Jian‐Sheng , Huang Bing , Ren Kai‐Di
Published: October 2024

Aging is an intricate process involving interactions among multiple factors, which is one of the main risks for chronic diseases, including Alzheimer's disease (AD). As a member of cysteine protease, cathepsin S (CTSS) has been implicated in inflammation across various diseases. Here, we investigated the role of neuronal CTSS in aging and AD started by examining CTSS expression in hippocampus neurons of aging mice and identified a significant increase, which was negatively correlated with recognition abilities. Concurrently, we observed an elevation of CTSS concentration in the serum of elderly people. Transcriptome and fluorescence‐activated cell sorting (FACS) results revealed that CTSS overexpression in neurons aggravated brain inflammatory milieu with microglia activation to M1 pro‐inflammatory phenotype, activation of chemokine C‐X3‐C‐motif ligand 1 (CX3CL1)—chemokine C‐X3‐C‐motif receptor 1 (CX3CR1) axis and janus kinase 2 (JAK2)—signal transducer and activator of transcription 3 (STAT3) pathway. As CX3CL1 is secreted by neurons and acts on the CX3CR1 in microglia, our results revealed for the first time the role of neuron CTSS in neuron–microglia “crosstalk.” Besides, we observed elevated CTSS expression in multiple brain regions of AD patients, including the hippocampus. Utilizing CTSS selective inhibitor, LY3000328, rescued AD‐related pathological features in APP/PS1 mice. We further noticed that neuronal CTSS overexpression increased cathepsin B (CTSB) activity, but decreased cathepsin L (CTSL) activity in microglia. Overall, we provide evidence that CTSS can be used as an aging biomarker and plays regulatory roles through modulating neuroinflammation and recognition in aging and AD process.
Real‐world data on the efficacy and safety of hedgehog pathway inhibitors in patients with basal cell carcinoma: Experience of a tertiary Australian centre
Authors: Truong K. , Peera M. , Liu R. , Wijaya M. , Jones‐Caballero M. , Araujo R. Ruiz , Fernandez‐Penas P.
Published: October 2024

Background

Basal cell carcinomas (BCCs) are the most common cancers worldwide. Although most BCCs are amenable to local treatment, there are limited therapeutic options for surgically unresectable locally advanced and metastatic BCCs. Activation of the sonic hedgehog signalling pathway plays a significant role in the development of most BCCs. Hedgehog pathway inhibitors (HPIs) can be used to inhibit this pathway. Efficacy and safety data on HPI use in Australia is scarce.

Objectives

This study aims to present the effectiveness and safety of HPI at a tertiary dermatology referral centre.

Methods

We conducted a retrospective analysis of the clinical charts of all patients with BCC treated with an HPI at a tertiary Dermatology referral centre in New South Wales, Australia from 1 January 2016 to 1 July 2023.

Results

Twenty‐three patients with BCCs were treated with an HPI; 11 locally advanced, 8 multiple, 3 basal cell naevus syndrome and 1 metastatic. All patients were of Caucasian background, with a median age of 56. Across 41 treatment cycles, the median treatment duration was 4 months. The overall response rate (ORR) was 20/23 (87%) and complete response (CR) rate was 9/23 (39%); patients treated with sonidegib achieved an ORR of 11/12 (92%) and CR of 4/12 (33%), and vismodegib‐treated patients achieved an ORR of 9/11 (82%) and CR of 5/11 (45%). Patients who responded to HPI treatment also responded to a subsequent HPI rechallenge. Common treatment emergent adverse events (TEAEs) included muscle spasms, dysgeusia and alopecia. Dysgeusia was more frequent with vismodegib than sonidegib (p = 0.0001). There was no evidence to suggest a difference in other TEAEs between the two HPIs. Four treatment cycles were stopped due to grade 3 muscle spasm.

Conclusions

In our cohort of 23 patients being treated with HPI, the ORR was 87% and CR was 39%. All patients who experienced TEAEs and had a drug holiday successfully responded to HPI rechallenge. TEAEs, particularly muscle spasms, are common reasons for treatment cessation. Clinicians should implement strategies to mitigate TEAE to improve drug survivability.
Long‐term efficacy and safety of stapokibart for moderate‐to‐severe atopic dermatitis: 52‐week results from a phase 3 trial
Authors: Zhao Yan , Zhang Litao , Wu Liming , Yang Bin , Wang Jinyan , Li Yumei , Li Jingyi , Diao Qingchun , Sun Qing , Zhu Xiaohong , Man Xiaoyong , Wang Lihua , Li Linfeng , Feng Yanyan , Zeng Huiming , Cai Tao , Ren Hong , Lu Jianyun , Lu Qianjin , Tao Xiaohua , Xiao Rong , Ji Chao , Li Fuqiu , Zhang Jianzhong
Published: October 2024

Background

Management of moderate‐to‐severe atopic dermatitis (AD) needs long‐term therapy. Stapokibart is a humanized monoclonal antibody targeting interleukin‐4 receptor α subunit (IL‐4Rα), a shared receptor for IL‐4 and IL‐13 which are key pathogenic drivers of AD. In a pivotal phase 3 trial (NCT05265923), significant higher proportions of adult AD patients receiving stapokibart than placebo achieved ≥75% improvement from baseline in Eczema Area and Severity Index (EASI‐75; 66.9% vs. 25.8%) and Investigator's Global Assessment (IGA) score of 0/1 with ≥2‐point reduction (44.2% vs. 16.1%) at Week 16. Herein, we report long‐term (52 weeks) efficacy and safety of stapokibart from this trial.

Methods

After 16‐week double‐blind treatment completed, patients in both stapokibart and placebo groups entered a 36‐week maintenance treatment period and received stapokibart 300 mg every 2 weeks. Concomitant use of topical medications for AD was permitted throughout the maintenance period.

Results

Of 476 patients entering maintenance period, 430 completed the treatment. At Week 52, EASI‐75 was achieved in 92.5% of patients continuing stapokibart and 88.7% of those switching from placebo to stapokibart, respectively; an IGA score of 0 or 1 with a ≥2‐point reduction was achieved in 67.3% and 64.2% of patients, respectively; a ≥4‐point reduction in weekly average of daily Peak Pruritus Numerical Rating Scale (PP‐NRS) was achieved in 67.3% and 60.5% of patients, respectively. Over the 52‐week treatment period, 88.1% of patients reported treatment‐emergent adverse events, most were mild or moderate.

Conclusion

Long‐term treatment with stapokibart demonstrated a sustained efficacy and favorable safety profile in adults with moderate‐to‐severe AD.
Biotronik Implantable Cardioverter Defibrillator for Measurement of Intrathoracic Impedance: A Report of Two Cases
Authors: Ying Xuqing , Yu Xinyue , Cai Weixun , Chen Xiaomin , Wang Lihua , Wang Qingcheng , Pang Jie
Published: October 2024

Objectives

Two patients were received ICDs (Biotronic Iforia7 VR‐TDX). Holter analysis revealed pacing spikes, which occurred regularly at 100 ms intervals following QRS complexes, with consecutive 1024 test pulses at hourly intervals during a specific time, and the VP was 0%.

Methods

By analyzing the dynamic electrocardiogram and consulting relevant literature, it was found that this is a feature of the ICD that measures thoracic impedance.

Results

This phenomenon is a special function for the purpose of transthoracic impedance measurement, which can monitor the heart failure.

Conclusions

This phenomenon should not be regarded as an interference signal or an abnormal sign of pacemaker malfunction.
Prediction de‐correlated inference: A safe approach for post‐prediction inference
Authors: Gan Feng , Liang Wanfeng , Zou Changliang
Published: October 2024

In modern data analysis, it is common to use machine learning methods to predict outcomes on unlabelled datasets and then use these pseudo‐outcomes in subsequent statistical inference. Inference in this setting is often called post‐prediction inference. We propose a novel assumption‐lean framework for statistical inference under post‐prediction setting, called prediction de‐correlated inference (PDC). Our approach is safe, in the sense that PDC can automatically adapt to any black‐box machine‐learning model and consistently outperform the supervised counterparts. The PDC framework also offers easy extensibility for accommodating multiple predictive models. Both numerical results and real‐world data analysis demonstrate the superiority of PDC over the state‐of‐the‐art methods.
The prevalence of overweight among 4‐year‐olds during and after the COVID‐19 pandemic was associated with socioeconomic burden
Authors: Nylander Charlotte , Nowicka Paulina , Derwig Mariette
Published: October 2024

Aim

To assess the prevalence of overweight among Swedish 4 year olds in 2018, 2020 and 2022, taking socioeconomic variables into account.

Methods

Aggregated regional data on children's body mass index were collected. The socioeconomic Care Need Index (CNI), foreign background, low education, being a single parent, low income and childhood poverty, were assessed. The differences in overweight, including obesity, were tested for Sweden and for regions.

Results

Data were available for 303 843 children, representing 87% of children born in 2014, 2016 and 2018. Overweight or obesity were found in 11 177 (11.4%) of children in 2022, decreasing from 2020 (13.3%, p < 0.001) but at the same level as in 2018. Regional low CNI, low level of foreign background, education and income as well as being a single parent were associated with a higher prevalence of overweight or obesity in all cohorts (p < 0.001). In regions with high levels of childhood poverty, overweight or obesity were more prevalent during (p = 0.009) and after the pandemic (p < 0.001).

Conclusion

Three national cohorts demonstrate that the increase in overweight during the COVID‐19 pandemic has returned to pre‐pandemic levels, but the inequalities in health associated with socioeconomic vulnerability of the regions remained.
Incidence and trend of cardiac events among children and young adults exposed to psychopharmacological treatment (2006–2018): A nationwide register‐based study
Authors: Elmowafi Howaida , Kindblom Jenny M. , Halldner Linda , Gyllenberg David , Naumburg Estelle
Published: October 2024

Aims

The aim of this study was to assess cardiac event incidence and trends by sex and age in young patients on psychopharmacological treatment in Sweden.

Methods

This nationwide incidence study encompassed data from Swedish registers (2006–2018). Patients aged 5–30 years were exposed to one or more psychotropic medications (attention deficit hyperactivity disorder medications, antihistamines, selective serotonin reuptake inhibitors, other antidepressants, anxiolytics, antipsychotics, hypnotics/sedatives). Annual incidences, trends and mean incidences of cardiac events (cardiac arrest, arrhythmias, fainting/collapse, sudden death) and recurrent events were calculated.

Results

Among those exposed (n = 875 430, 2 647 957 patient‐years, 55% female), 26 750 cardiac events were identified. The mean annual incidence of cardiac events and first‐ever events were 0.99% and 0.80%, respectively, showing significant upward annual trends of 4.26% and 2.48%, respectively (P < .001). The highest incidences were among females aged 15–19 years (1.50%) and those exposed to polypharmacy (1.63%), anxiolytics (1.53%) or antihistamines (1.27%). The mean annual incidences of cardiac arrest and arrythmias, for both sexes, were 0.01% and 0.51%, respectively. Fainting/collapse accounted for about half of all events, occurring more often in females. The pattern of rising annual incidence remained after excluding fainting/collapse. In all, 21.1% of events were recurrent. Death, including sudden death, occurred in 13 patients.

Conclusions

The mean annual incidence of cardiac events among young patients receiving psychopharmacological treatment was low, 0.99%, with an upward trend of 4.26% annually. Incidence was highest in adolescent females and patients exposed to polypharmacy. Our study highlights the need for more knowledge regarding the possible association between exposure to psychopharmacological treatment and cardiac events.
Primary retroperitoneal lymph node dissection in stage II testicular seminoma: a systematic review
Authors: Liu Jianliang , Hiwase Mrunal , Woon Dixon T.S. , Thomas Benjamin , Tran Ben , Lawrentschuk Nathan
Published: October 2024

Objective

To conduct a systematic review of the current literature to determine the current role of primary retroperitoneal lymph node dissection (RPLND) in stage II testicular seminoma and its associated oncological, functional and peri‐operative outcomes.

Materials and Methods

A comprehensive literature search was conducted in Medline, Embase, and Scopus for publications from inception until November 2023. The systematic review was registered on PROSPERO (ID CRD42023449781), was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines and utilised the Methodological Index for Non‐Randomised Studies (MINORS) tool.

Results

Six studies involving 385 patients were analysed, with 48.5% clinical stage IIA and 51.5% stage IIB seminomas. The patients’ mean (range) age was 37 (20–64) years. The median operation time was 187 min, median estimated blood loss was 150 mL and median length of hospital stay was 4 days. In all, 6.1% of patients developed complications that were greater or equal to Clavien–Dindo grade 3. Only four studies reported on anejaculation rate (median: 4.9%). Only one study had long‐term data, demonstrating a 92% 5‐year overall survival for stage IIA/B disease treated with RPLND. The remaining five studies had a median follow‐up of between 18.5 and 37 months and reported a mean recurrence rate of 15.6%. Most recurrences (78%) were not within the field of RPLND. Recurrence was associated with higher clinical and pathological lymph node stage, and metachronous or delayed development of retroperitoneal lymphadenopathy (initially stage I disease, as opposed to de novo stage IIA/B disease).

Discussion

Primary RPLND, performed by experienced surgeons, has good peri‐operative outcomes. Recurrence is more common than with standard treatment, but long‐term survival and functional data are limited, although promising.
Relationship between renal pelvis pressure and post‐ureteroscopy infection in a live swine model
Authors: Hinojosa‐Gonzalez David , Kottooran Christina , Saunders Jennifer , Chaussee Erin L. , Budrewicz Jay , Eisner Brian H.
Published: October 2024

Objective

To evaluate the relationship between renal pelvis pressure and infection after ureteroscopy, using a live swine model.

Materials and Methods

In anaesthetised pigs, a 1‐h ureteroscopy was performed using a pressure‐sensing guidewire, with renal pelvis pressure maintained at either 37 mmHg or 75 mmHg for the entire procedure and infusion with saline alone or with a standardised concentration of uropathogenic Escherichia coli strain CFT073 (1.5 × 107 colony‐forming units [CFU]/mL). Venous blood sampling was performed during and after the procedure. Vital signs, inflammatory biomarkers, and renal tissue and blood cultures were assessed.

Results

In 21 pig kidneys, study groups were: 37 mmHg with saline irrigation (n = 3); 75 mmHg with saline irrigation (n = 4); 37 mmHg with saline irrigation with 1.5 × 107 CFU/mL E. coli (n = 7); and 75 mmHg with saline irrigation with 1.5 × 107 CFU/mL E. coli (n = 7). Statistically significant changes in inflammatory biomarkers were most pronounced in the group with 75 mmHg saline irrigation + E. coli and were significantly elevated compared with the control group and the group receiving E. coli irrigation at 37 mmHg. Positive blood cultures were noted in 5/7 animals treated with E. coli at 75 mmHg; no others developed bacteraemia.

Conclusion

In this swine model of ureteroscopy, irrigation with saline + E. coli at a renal pelvis pressure of 75 mmHg resulted in bacteraemia and inflammatory biomarker elevations significantly greater than both E. coli irrigation with renal pelvis pressure maintained at 37 mmHg and the control.
Evidence for an active ice margin during the last deglaciation: the Vimmerby Moraine, South Swedish Uplands
Authors: Watts Hannah , Reinardy Benedict T. I. , Lukas Sven
Published: October 2024

The Vimmerby Moraine is the only significant ice‐marginal moraine on the eastern side of southern Sweden, but no detailed studies exist on its formation during the final deglaciation of the Fennoscandian Ice Sheet. Through ground‐penetrating radar surveys and detailed sediment logging, we provide evidence for an active, oscillating ice margin during the formation of the Vimmerby Moraine, suggesting that the deglaciation of the South Swedish Uplands was, at least in some regions, dynamic. Ground‐penetrating radar surveys enabled imaging of internal sediment and delineation of the bedrock surface. These were complemented by common mid‐point surveys and sediment logging, as well as lithofacies analysis at three exposures in agravel pit. This approach revealed multiple subglacial till units partially separated by intercalated glacifluvial deposits. The glacifluvial sediments exhibit evidence of glaciotectonism, suggesting active overriding by the last ice sheet. Further evidence of an active ice margin is provided by the ground‐penetrating radar profiles collected perpendicular to the moraine crest. These contain a series of northerly dipping reflectors, which we interpret as evidence of repeated basal freeze‐on and melt‐out of sediment slabs during ice margin oscillations, as has been observed at contemporary glacier margins in Iceland, Norway, and the Alps. The data presented here demonstrate that the last Fennoscandian Ice Sheet remained active around the time of the Vimmerby Moraine formation. This work highlights the benefits of including detailed sediment logging and near‐surface geophysical surveys in the interpretation of deglaciation dynamics.
Point‐AGM : Attention Guided Masked Auto‐Encoder for Joint Self‐supervised Learning on Point Clouds
Authors: Liu Jie , Yang Mengna , Tian Yu , Li Yancui , Song Da , Li Kang , Cao Xin
Published: October 2024

Masked point modeling (MPM) has gained considerable attention in self‐supervised learning for 3D point clouds. While existing self‐supervised methods have progressed in learning from point clouds, we aim to address their limitation of capturing high‐level semantics through our novel attention‐guided masking framework, Point‐AGM. Our approach introduces an attention‐guided masking mechanism that selectively masks low‐attended regions, enabling the model to concentrate on reconstructing more critical areas and addressing the limitations of random and block masking strategies. Furthermore, we exploit the inherent advantages of the teacher‐student network to enable cross‐view contrastive learning on augmented dual‐view point clouds, enforcing consistency between complete and partially masked views of the same 3D shape in the feature space. This unified framework leverages the complementary strengths of masked point modeling, attention‐guided masking, and contrastive learning for robust representation learning. Extensive experiments have shown the effectiveness of our approach and its well‐transferable performance across various downstream tasks. Specifically, our model achieves an accuracy of 94.12% on ModelNet40 and 87.16% on the PB‐T50‐RS setting of ScanObjectNN, outperforming other self‐supervised learning methods.
Frequency‐Aware Facial Image Shadow Removal through Skin Color and Texture Learning
Authors: Zhang Ling , Xie Wenyang , Xiao Chunxia
Published: October 2024

Existing facial image shadow removal methods predominantly rely on pre‐extracted facial features. However, these methods often fail to capitalize on the full potential of these features, resorting to simplified utilization. Furthermore, they tend to overlook the importance of low‐frequency information during the extraction of prior features, which can be easily compromised by noises. In our work, we propose a frequency‐aware shadow removal network (FSRNet) for facial image shadow removal, which utilizes the skin color and texture information in the face to help recover illumination in shadow regions. Our FSRNet uses a frequency‐domain image decomposition network to extract the low‐frequency skin color map and high‐frequency texture map from the face images, and applies a color‐texture guided shadow removal network to produce final shadow removal result. Concretely, the designed fourier sparse attention block (FSABlock) can transform images from the spatial domain to the frequency domain and help the network focus on the key information. We also introduce a skin color fusion module (CFModule) and a texture fusion module (TFModule) to enhance the understanding and utilization of color and texture features, promoting high‐quality result without color distortion and detail blurring. Extensive experiments demonstrate the superiority of the proposed method. The code is available at https://github.com/laoxie521/FSRNet.
A Hybrid Parametrization Method for B‐Spline Curve Interpolation via Supervised Learning
Authors: Song Tianyu , Shen Tong , Ge Linlin , Feng Jieqing
Published: October 2024

B‐spline curve interpolation is a fundamental algorithm in computer‐aided geometric design. Determining suitable parameters based on data points distribution has always been an important issue for high‐quality interpolation curves generation. Various parameterization methods have been proposed. However, there is no universally satisfactory method that is applicable to data points with diverse distributions. In this work, a hybrid parametrization method is proposed to overcome the problem. For a given set of data points, a classifier via supervised learning identifies an optimal local parameterization method based on the local geometric distribution of four adjacent data points, and the optimal local parameters are computed using the selected optimal local parameterization method for the four adjacent data points. Then a merging method is employed to calculate global parameters which align closely with the local parameters. Experiments demonstrate that the proposed hybrid parameterization method well adapts the different distributions of data points statistically. The proposed method has a flexible and scalable framework, which can includes current and potential new parameterization methods as its components.
Quantifying public support for culling crown‐of‐thorns starfish (Acanthaster spp.) on the Great Barrier Reef
Authors: Lockie Stewart , Bartelet Henry A. , Ritchie Brent W. , Sie Lintje , Paxton Gillian
Published: October 2024

Population surges of crown‐of‐thorns starfish (COTS) (Acanthaster spp.) are a leading cause of coral cover loss on Australia's Great Barrier Reef (GBR). While COTS culling has been undertaken since 2012 little is known about how the public perceive COTS culling or how perceptions vary among social groups. Drawing on survey data collected in 2018 and 2022 we test the relative influence of demographic variables, social and institutional variables, and beliefs concerning the risks and benefits of culling, on public acceptance for the culling of COTS on the GBR. In contrast with previous research suggesting a polarization of views, we found limited opposition to culling (12% in 2018 and 8% in 2022). Remaining respondents, however, were almost equally divided between those who agreed or strongly agreed with culling and those who were neutral or only slightly in agreement. The strongest predictors of support, in terms of standardized mean odds ratios, were the perceived social, environmental, and ethical responsibility of culling (1.57), the manageability of culling risks (1.46), the personal importance of the GBR to the respondent (1.33), trust in science to deliver solutions (1.30), confidence in management of the GBR (1.26), and how much of a threat respondents believed COTS posed to the Reef (1.25). These findings suggest public communications about COTS culling might usefully focus on how scientific understanding, ongoing research, ecosystem monitoring, and partnerships with Reef Traditional Owners and stakeholders guide operations.
Immunohistochemical Expression of Immune Regulatory Proteins in Interface Dermatoses
Authors: McAlpine Sarah Grace , Culton Donna , Duplisea Michael , Liu Zhi , Lim Si On , Googe Paul
Published: October 2024

Cutaneous immune‐related adverse events (irAEs) of immunotherapies, such as anti‐programmed cell death protein‐1 (PD‐1), suggest that immune checkpoint factors may contribute to the pathobiology of lichenoid interface dermatitis in immunotherapy‐naïve patients. Our study aimed to describe innate and adaptive immune markers via immunohistochemical (IHC) staining of lichenoid interface dermatoses. We studied the staining patterns of PD‐L1, STING, IL‐36 gamma, CD8, PD‐1, and LAG‐3 in five interface dermatoses: oral lichen planus (LP) (n = 10), cutaneous LP (n = 10), chronic cutaneous lupus erythematosus (CLE) (n = 11), erythema multiforme (EM) (n = 11), and toxic epidermal necrolysis (TEN) (n = 13), by immunohistochemistry (IHC) analysis. Expression was evaluated semi‐quantitively according to the percentage of keratinocytes and dermal lymphocytes stained compared to keratinocytes and resident pericapillary lymphocytes in normal human skin. All interface dermatoses evaluated showed increased expression of PD‐L1 on keratinocytes and LAG‐3 in lymphocytes. STING was increased on the keratinocytes of most specimens. Expression of IL‐36 gamma, in basal layer keratinocytes was more extensive in oral LP and cutaneous LP and varied in CLE, EM, and TEN. Lymphocytic infiltration expressing PD‐1 was elevated in oral LP, cutaneous LP, and CLE. Current thinking is that interface dermatitis is the result of a cell‐mediated immune reaction involving cytotoxic CD8+ T‐cell‐mediated apoptosis of keratinocytes. The findings of this study suggest that in addition to cell‐mediated immunity, innate immune factors may contribute to pathobiology.
Water pressure method endoscopic submucosal dissection with clip traction for early gastric cancer with submucosal fibrosis
Authors: Ikeda Ryosuke , Kaneko Hiroaki , Maeda Shin
Published: October 2024

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Endoscopic transpapillary gallbladder drainage using a novel cholangioscope
Authors: Hamamura Ryosuke , Kobayashi Masanori , Okamoto Ryuichi
Published: October 2024

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Chemogenetic neuronal silencing decouples c‐Jun activation from cell death in the temporal cortex
Authors: Wood Caleb A. , Somasundaram Preethi , Dundee Jacob M. , Rudy Melissa A. , Watkins Trent A. , Jankowsky Joanna L.
Published: October 2024

Initial symptoms of neurodegenerative diseases are often defined by the loss of the most vulnerable neural populations specific to each disorder. In the early stages of Alzheimer's disease, vulnerable circuits in the temporal lobe exhibit diminished activity prior to overt degeneration. It remains unclear whether these functional changes contribute to regional vulnerability or are simply a consequence of pathology. We previously found that entorhinal neurons in the temporal cortex undergo cell death following transient suppression of electrical activity, suggesting a causal role for activity disruption in neurodegeneration. Here we demonstrate that electrical arrest of this circuit stimulates the injury‐response transcription factor c‐Jun. Entorhinal silencing induces transcriptional changes consistent with c‐Jun activation that share characteristics of gene signatures in other neuronal populations vulnerable to Alzheimer's disease. Despite its established role in the neuronal injury response, inhibiting c‐Jun failed to ameliorate entorhinal degeneration following activity disruption. Finally, we present preliminary evidence of integrated stress response activity that may serve as an alternative hypothesis to what drives entorhinal degeneration after silencing. Our data demonstrate that c‐Jun is activated in response to neuronal silencing in the entorhinal cortex but is decoupled from subsequent neurodegeneration.
Arctic Tundra Plant Dieback Can Alter Surface N2O Fluxes and Interact With Summer Warming to Increase Soil Nitrogen Retention
Authors: Xu Wenyi , Elberling Bo , Li Dan , Ambus Per Lennart
Published: October 2024

In recent years, the arctic tundra has been subject to more frequent stochastic biotic or extreme weather events (causing plant dieback) and warmer summer air temperatures. However, the combined effects of these perturbations on the tundra ecosystem remain uninvestigated. We experimentally simulated plant dieback by cutting vegetation and increased summer air temperatures (ca. +2°C) by using open‐top chambers (OTCs) in an arctic heath tundra, West Greenland. We quantified surface greenhouse gas fluxes, measured soil gross N transformation rates, and investigated all ecosystem compartments (plants, soils, microbial biomass) to utilize or retain nitrogen (N) upon application of stable N‐15 isotope tracer. Measurements from three growing seasons showed an immediate increase in surface CH4 and N2O uptake after the plant dieback. With time, surface N2O fluxes alternated between emission and uptake, and rates in both directions were occasionally affected, which was primarily driven by soil temperatures and soil moisture conditions. Four years after plant dieback, deciduous shrubs recovered their biomass but retained significantly lower amounts of 15N, suggesting the reduced capacity of deciduous shrubs to utilize and retain N. Among four plant functional groups, summer warming only increased the biomass of deciduous shrubs and their 15N retention, while following plant dieback deciduous shrubs showed no response to warming. This suggests that deciduous shrubs may not always benefit from climate warming over other functional groups when considering plant dieback events. Soil gross N mineralization (~ −50%) and nitrification rates (~ −70%) significantly decreased under both ambient and warmed conditions, while only under warmed conditions immobilization of NO3− significantly increased (~ +1900%). This explains that plant dieback enhanced N retention in microbial biomass and thus bulk soils under warmed conditions. This study underscores the need to consider plant dieback events alongside summer warming to better predict future ecosystem‐climate feedback.