bluuebunny/crossref_metadata_2025 huggingface dataset:
Autonomous self-burying seed carriers for aerial seeding
Authors: Luo Danli , Maheshwari Aditi , Danielescu Andreea , Li Jiaji , Yang Yue , Tao Ye , Sun Lingyun , Patel Dinesh K. , Wang Guanyun , Yang Shu , Zhang Teng , Yao Lining
Published: May 2024

Aerial seeding can quickly cover large and physically inaccessible areas to improve soil quality and scavenge residual nitrogen in agriculture, and for postfire reforestation and wildland restoration. However, it suffers from low germination rates, due to the direct exposure of unburied seeds to harsh sunlight, wind and granivorous birds, as well as undesirable air humidity and temperature. Here, inspired by Erodium seeds, we design and fabricate self-drilling seed carriers, turning wood veneer into highly stiff (about 4.9 GPa when dry, and about 1.3 GPa when wet) and hygromorphic bending or coiling actuators with an extremely large bending curvature (1,854 m-1), 45 times larger than the values in the literature. Our three-tailed carrier has an 80% drilling success rate on flat land after two triggering cycles, due to the beneficial resting angle (25°–30°) of its tail anchoring, whereas the natural Erodium seed’s success rate is 0%. Our carriers can carry payloads of various sizes and contents including biofertilizers and plant seeds as large as those of whitebark pine, which are about 11 mm in length and about 72 mg. We compare data from experiments and numerical simulation to elucidate the curvature transformation and actuation mechanisms to guide the design and optimization of the seed carriers. Our system will improve the effectiveness of aerial seeding to relieve agricultural and environmental stresses, and has potential applications in energy harvesting, soft robotics and sustainable buildings.
Oxidative release of glycans from carbohydrate-conjugated vaccine
Authors: Wang Szu-Wen
Published: May 2024

This protocol provides a oxidative method to release glycans from glycoconjugates which was conjugated using p-nitrophenyl ester homobifunctional linker. The advantages of this protocol are its low costs and easy way to purified glycans from complicated samples, such as cell lysate, for glycomic analyses by LC-MS/MS.
A systematic review of pharmacogenetic guided opioid therapy for pain.
Authors: Jethwa Sneha
Published: May 2024

Title
A systematic review of pharmacogenetic guided opioid therapy for pain.
Authors
Sneha Jethwa
Contact:
Sj648@cam.ac.uk
University of Cambridge
Contributions
Dr Kenneth Langlands
Rationale
Genetic polymorphisms have been shown to have a role in the variability in response to analgesics. Clinical Pharmacogenetics Implementation Consortium (CPIC) has issued guidelines that support pharmacogenetic testing for opioid therapy, including the CYP2D6, OPRM1, and COMT genes (Crews et al., 2021). There is a need to determine if pharmacogenetic-guided opioid prescribing leads to improved clinical outcomes using data from clinical trials and whether healthcare providers could benefit from using these tests as part of routine care.
Objectives
1) Determine if pharmacogenetic guided opioid prescribing improves clinical outcomes.
2) Determine if pharmacogenetic tests reduce adverse effects when prescribing opioid therapy.
3) Identify gaps in research and provide recommendations for future research.
Method
A systematic literature review was carried in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines 2020. The following databases were searched: Embase, MEDLINE, Cochrane Central Register of Controlled Trials and Web of Science. The search results were reported in accordance with the PRISMA-S checklist
1D-CNN-based Audio Tampering Detection Using ENF Signals
Authors: Shen Xingfa
Published: May 2024

The extensive adoption of digital audio recording has revolutionized its application in digital forensics, particularly in civil litigation and criminal prosecution. Electric Network Frequency (ENF) has emerged as a reliable technique in the field of audio forensics. However, the absence of comprehensive ENF reference datasets limits current ENF-based methods. To address this, this study introduces ATD, a blind audio forensics framework based on a One-Dimensional Convolutional Neural Network (1D-CNN) model. ATD can identify phase mutations and waveform discontinuities within the tampered ENF signal, without relying on an ENF reference database. To enhance feature extraction, the framework incorporates characteristics of the fundamental harmonics of ENF signals. In addition, a denoising method termed ENF Noise Reduction (ENR) based on the Variational Mode Decomposition (VMD) and Robust Filtering Algorithm (RFA) is proposed to reduce the impact of external noise on embedded Electric Network Frequency signals. This study investigates three distinct types of audio tampering—deletion, insertion, and replacement—culminating in the design of binary-class tampering detection scenarios and four-class tampering detection scenarios tailored to these tampering types. ATD achieves a tampering detection accuracy of over 93% in the four-class scenario and exceeds 96% in the binary-class scenario. The effectiveness, efficiency, adaptability, and robustness of ATD in the two and four classification scenarios have been confirmed by extensive experiments.
Population structure analysis of emmer wheat (Triticum dicoccum Schrank) germplasm conserved in National Genebank of India using SSR markers
Authors: Tanwar Jatin , Tyagi Sandhya , Sharma Shivani , Jakhar Preeti , Kumar Gaurav , Jacob Sherry R , Singh Amit Kumar , Jha Shailendra K , Kumari Jyoti
Published: May 2024

Knowledge of genetic diversity of crop germplasm is essential for their utilization in breeding programme. Emmer wheat germplasm received less attention for exploring its genetic diversity towards enhancing utilization. Agro-morphological characterization was done for 192 emmer wheat accessions during rabi season 2019-20 and subsequently, 96 accessions were selected for morphological and molecular diversity analysis during 2020-21. We estimated genetic diversity and population structure of 96 diverse dicoccum genotypes conserved in national genebank of India using 56 microsatellite (SSR) markers. The number of alleles per locus ranged from 1 to 6 with an average of 1.68 alleles. A total of 93 alleles were detected with the highest PIC value (0.9912) observed for Xcfd20 marker. Based on ‘STRUCTURE’ analysis, 96 dicoccum accession were divided into two sub-populations. The analysis of molecular variance (AMOVA) revealed that genetic differentiation among subpopulations was low and within subpopulations was high. A cluster analysis based on the Jaccard’s dissimilarity index identified two clusters which was in congruence with population structure. Indigenous and exotic collections were categorized into distinct sub-clusters within the same cluster with some overlapping suggesting limited genomic differentiation between these collections from different geographical regions. Based on the allelic information and cluster analysis, cultivated emmer wheat showed low genetic diversity and narrow genetic base. The low genetic diversity in emmer wheat accessions may be due to limited cultivation in small pockets that emphasized a need to broaden the genetic base of emmer wheat genetic resources for enhancing its utilization.
AutoML Platform for Comparative Analysis of Machine Learning Models
Authors: Vinod Pal Sonam , Balasaheb Wagh Shraddha , Pandurang Yadav Mandar , Ravindra Yadgude Samrudhi , Sayyad S F
Published: May 2024

Automated Machine Learning (AutoML) platforms have emerged as indispensable tools in facilitating efficient algorithm selection for diverse machine learning tasks. In this study, we introduce a novel AutoML platform designed to empower users with seamless comparative analysis of machine learning algorithms. Our platform offers a user-friendly interface, guiding users through the process of uploading datasets, selecting algorithms, and evaluating performance metrics. Leveraging automation and in-depth analysis, users can effortlessly compare the performance of two selected algorithms, gaining insights into their data-driven projects. Through visualization tools and explainability mechanisms, our platform aids users in making informed decisions for optimal algorithm selection. By addressing the complexities of algorithm selection and enhancing accessibility, our AutoML platform contributes to advancing data-driven decision-making across various domains.
Psychometric Properties of the Coercion Experience Scale in Patients with Mental Disorders in Iran
Authors: Karimi Kimia , Gardashkhani Sevda , Belil Fatemeh Ebrahimi
Published: May 2024

Background
People with mental disorders are a vulnerable part of society, and it is essential to defend the rights of these patients. The use of threats and coercion s in mental care is a controversial and important issue for research. Therefore, there is a need for a tool that health workers can also use to measure the experience of coercion in mental patients. The present study was conducted with the aim of investigating the psychometric properties of the Coercion Experience Scale among patients admitted to psychiatric departments in Iran.
Methods
This study is a methodological study that examines the psychometric properties of the Coercion Experience Scale in 264 psychiatric patients in psychiatric departments. The instrument's psychometric properties were examined to determine content validity, construct validity (factor analysis), and internal consistency.
Results
The results showed the confirmation of the 34-item and 7-factor model of The Coercion Experience Scale in mentally ill patients in Iran, which explained 63.71% of the total variance. The overall reliability of the tool was also obtained with the internal consistency method of 0.92.
Conclusion
The appropriate model of the Coercion Experience Scale in Iranian society is a scale with 34 items and 7 factors with the best conditions in terms of factorial structure and internal consistency, and it can be used as a screening tool for mental patients in Iran who need support after coercive and threatening interventions to avoid the consequences of traumatic experiences.
RETRACTED: Secondary traumatic stress and vicarious posttraumatic growth in oncology nurses: the mediating role of empathy
Authors: Cai Yitong , Liu Ming , Li Yifei , Li Juan , Geng Jie , Liu Xiaoying , Zhang Jingping
Published: May 2024

The authors have requested that this preprint be removed from Research Square.
Expression and prognosis of NR3C1 in uterine corpus endometrial carcinoma based on multiple datasets
Authors: Shen Yahui , Lu Yanping
Published: May 2024

Uterine corpus endometrial carcinoma (UCEC), a prevalent malignancy in the female reproductive system, has witnessed a 30% increase in recent year. Recognizing the significance of early treatment in reducing patient mortality, the identification of potential biomarkers for UCEC plays a crucial role in early diagnosis. This study was to identify key genes associated with UCEC utilizing the Gene Expression Omnibus (GEO) database, followed by validating their prognostic value across multiple databases. Analysis of four UCEC databases (GSE17025, GSE36389, GSE63678, GSE115810) yielded 72 co-expressed genes. KEGG and GO enrichment analyses revealed their involvement in physiological processes such as transcriptional misregulation in cancer. Constructing a Protein-Protein Interaction (PPI) network for these 72 genes, the top 10 genes with significant interactions were identified. Survival regression analysis highlighted NR3C1 as the gene with a substantial impact on UCEC prognostic outcomes. Differential expression analysis indicated lower expression of NR3C1 in UCEC compared to normal endometrial tissue. Cox regression analysis, performed on clinical datasets of UCEC patients, identified clinical stage III, clinical stage IV, age, and NR3C1 as independent prognostic factors influencing UCEC outcomes. The LinkedOmics online database revealed the top 50 positively and negatively correlated genes with NR3C1 in UCEC. Subsequent investigations into the relationship between NR3C1 and tumor-infiltrating immune cells were conducted using R software. Gene set enrichment analysis (GSEA) provided insights into NR3C1-related genes, showing enrichment in processes such as Ribosome, Oxidative phosphorylation in UCEC. Collectively, these comprehensive analyses suggest that NR3C1 may serve as a potential biomarker indicating the prognosis of UCEC.
Traffic Aware Dynamic Beamforming Antenna Design For 5G Communication
Authors: Imon Hasibul Islam , Rahman Md. Asikur , Reza Md. Mahfuz , Karmaker Amit , Hossain Md. Abir
Published: May 2024

Dynamic beamforming is a wireless communication technique that enhances signal transmission and reception using multiple antennas to focus radio frequency energy towards specific directions or devices. Dynamic beamforming faces several challenges as mobility, signal interference, beam misalignment, beam training overhead, and signal traffic management. In this research work, an Advanced Optimized Algorithm (AOA) for beam-forming is proposed after a comprehensive analysis of the performance exhibited by the least mean square (LMS) and the Adaptive gradient algorithm. The weights of the antenna array are initiated and updated by the Advanced optimized algorithm, which involves moving in the direction of the negative gradient of the error signal. This optimization method significantly improves the array factor and the weighted value compared to the LMS and Ada-Grad algorithm, which reduce the processor burden and power consumption during the beamforming process. The outcomes of the experiments and analysis reveal that the proposed Advanced Optimized Algorithm is effective in enhancing the overall performance of beamforming patterns in the desired direction and can be used to resolve the issues of signal interference by employing complex weights for 5G antenna design. The proposed method demonstrates the suitability for high-speed, reliable real-time data communication, along with superiority for signal strength over the LMS and Ada-Grad algorithms.
The notable outcomes of modified thiotepa-based conditioning followed by autologous stem cell transplantation in primary central nervous system lymphomas: A real-life pilot study
Authors: Li Yan , Li Sen , Bao Fang , Ma Lan , Zhao Wei , Yang Ping , Dong Fei , Wang Jijun , Jing Hongmei
Published: May 2024

High-dose chemotherapy followed by autologous stem cell transplantation (HDC–ASCT) is a promising approach for patients with primary central nervous system lymphoma (PCNSL). Encouraging results have been reported with thiotepa-based conditioning; however, there is currently no consensus on the optimal conditioning regimens. To improve the tolerance and efficacy of ASCT with thiotepa-based conditioning, this retrospective, single-arm, pilot study was conducted, including 12 PCNSL patients who received ASCT with modified thiotepa-based conditioning regimens. It was found that 6 patients received ASCT as a first-line consolidation in complete response (CR)/partial response (PR) state, and 6 cases underwent salvage treatment. Among the patients, 7 (58.3%) received the mTBC conditioning regimen, 4 (33.3%) received TT-Bu, and one patient was incorporated with chimeric antigen receptor T-cell (CAR-T) cell infusion with the TT-Cy regimen. All patients achieved sustained neutrophil recovery within a median of 9 (range, 7–12) days and platelet engraftment within a median of 10 (range, 6–12) days. Furthermore, all patients were in CR status at the initial efficacy evaluation following ASCT. The main complications during hospitalization were febrile neutropenia (83.3%) and diarrhea grade 3 (50.0%). No transplantation- related mortality occurred. Maintenance therapy post-ASCT was administered in 11 cases, demonstrating its effectiveness and favorable tolerability. The estimated 1- and 3-year progression-free survival (PFS) following ASCT were 80.0% and 53.3%, respectively, while the estimated 1-and 3-year overall survival (OS) were both 100%. This study presented the modified thiotepa-based conditioning regimens and confirmed their safety and efficacy with ASCT for PCNSL patients.
A lipid metabolism and immune-related gene signature for predicting the prognosis of human gliomas
Authors: Liang Shanwen , Zhang Xinin , Zhu Zhansheng , Hong Yu , Qi Yangzhi , Ye Liguo , Chen Qianxue
Published: May 2024

Lipid metabolism reprogramming is critical in various biological processes and is considered a hallmark in cancers. The expression data of mRNA and corresponding follow-up information were obtained from TCGA used as a training set and the CGGA used as a validating set. Based on the expression of genes involved in lipid metabolism, 550 glioma samples of the training set were clustered by unsupervised classification method. Then, we construct a lipid metabolism-related risk signature based on the Lasso regression algorithm. The biological mechanism related to risk score was investigated by gene sets enrichment analysis (GSEA). 67 lipid metabolism- and immune-related genes were identified. Two robust groups were yielded by consensus clustering of the 550 samples. Subgroup2 correlated with a significantly better clinical outcome compared with Subgroup1. A 16-genes risk signature was constructed, and the overall survival of patients is dramatically better in the low-risk than the high-risk group. Consistently, the 16-gene signature showed pretty prognostically predicting ability by the receiver operating characteristic curve with areas under curve more than 0.8 in both TCGA and CGGA. Furthermore, the risk score was identified as an independent prognostic factor for glioma. Moreover, samples with a high-risk score were correlated with a higher level of immune infiltration and associated with a higher expression of immune checkpoints, which indicated an inhibitory tumor immune microenvironment. Our study demonstrated a new sight of lipid metabolism-related and immune-associated genes and constructed a 16-gene risk signature to predict prognosis and immunotherapy for glioma patients.
Reinforcement Learning Approach for Traffic Congestion Prediction Empowered with Explainable Artificial Intelligence (XAI)
Authors: Waqas Muhammad , Abbas Sagheer , Farooq Umer , Khan Muhammad Adnan , Alharbi Meshal , Asiff Muhammad
Published: May 2024

Traffic congestion in urban areas is an insistent challenge, increasing pollution levels and economic inefficiencies while reducing quality of life. Traditional traffic management systems, largely static and based on rules of thumb, struggle to dynamically adapt to ever-changing to solve the urban traffic problems. This work introduces a novel predictive framework using Reinforcement Learning enhanced with Explainable Artificial Intelligence techniques to boost both the interpretability and effectiveness of the model. A key hurdle involves securely transmitting data between the machine learning model and cloud servers, facilitated via Blockchain based smart contracts. The proposed RL approach augmented with RL-XAI represents the solution to strengthen security, privacy, and accuracy when detecting traffic jams. By using BC and RL and then evaluating outcomes through XAI, this approach achieves significantly more precise predictions and a reduced missing data rate relative to conventional Machine Learning methods and enhances security, reliability, and overall accuracy by a remarkable 5% compared to another approach.
Altered expression spectrum and target gene prediction of tRNA-derived small RNAs in clear cell renal cell carcinoma
Authors: Xu Yunfei , Dong Yunze , Nueraihemaiti Yimingniyizi , Gao Yuchen , Zhan Xiangcheng , Chen Yanhua , Zhou Hongmin , Chen Bowen , Liu Ding , Chen Hao , Xu Xiao , Xie Tiancheng
Published: May 2024

Background
Dysregulation of tRNA-derived small RNAs (tsRNAs) in various cancers has been indicated to play vital roles in tumorigenesis, but few reported in clear cell renal cell carcinoma (ccRCC). Here, we determined to elucidate the role of tsRNAs in ccRCC and their potential as new tumor biomarkers.
Methods
We obtained the tsRNA expression spectrum of ccRCC by a small RNA microarray sequence. Eight dysregulated tsRNAs were selected and validated by reverse transcription-quantitative real-time PCR (RT-qPCR). We identified these tsRNAs’ potential target genes. The biological functions of tsRNAs were identified by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) assay.
Results
The microarray sequence showed statistically significant 433 upregulated tsRNAs and 798 downregulated tsRNAs in ccRCC. Then, eight tsRNAs were validated by RT-qPCR, and the target genes of the validated tsRNAs were predicted using TargetScan and miRanda databases. GO annotation and KEGG pathway enrichment analyses show potential biological functions and signaling pathways of the predicted target genes of tsRNAs in ccRCC. External database validation results suggest that tRF5-23-ValAAC-2 may be a key biomarker for ccRCC development.
Conclusions
In this study, we identified the tsRNA spectrum in ccRCC tissues and found that dysregulated tsRNAs may be novel biomarkers and possible therapeutic targets for ccRCC.
Relationship between sleep, stress and psychological distress in internally displaced persons – does the length of displacement matter?
Authors: Basishvili Tamar , Eliozishvili Marine , Lortkipanidze Nani , Tsuladze Tengiz , Oniani Nikoloz , Darchia Nato
Published: May 2024

In recent years, the number of refugees and internally displaced persons (IDPs) has dramatically grown worldwide. We aimed to examine psychological distress and its association with sleep and stress in two groups of IDPs with different lengths of displacement in comparison with the general population. Forty-five individuals displaced in 2008, 2.5 months before this study (2008 IDPs), 67 respondents displaced in 1993 (1993 IDPs), and 53 individuals from Tbilisi general population were assessed. All study participants completed the Insomnia Severity Index (ISI), Perceived Stress Scale (PSS) and Brief Symptom Inventory (BSI). Sociodemographic information such as age, sex, education level and marital status was collected. The groups differed significantly on age, education, marital status, ISI, PSS, and Global Severity Index (GSI). The highest ISI and PSS scores were found for the 2008 IDPs, while the highest GSI score - in 1993 IDPs. The GSI and PSS scores did not differ between the two groups of IDPs. The proportion of people with a GSI T score ≥63 was 47.2% in the general population, 71.6% in the 1993 IDPs, and 64.4% in the 2008 IDPs. The ISI and PSS were significant predictors of the GSI in all groups. The PSS exhibited the highest predictive power for 2008 IDPs (β=0.429), while the ISI - in 1993 IDPs (β=0.417). Psychological distress persists over time in IDPs. Although both stress and insomnia are strongly associated with psychological distress, stress has a stronger impact in the early resettlement period, while sleep has a stronger impact later, years after displacement. Therefore, sleep health in displaced population, and on a broader scale in individuals subjected to traumatic events, warrant attention in long-term perspective for implementing targeted interventions and effectively addressing well-being of affected individuals.
Stability evaluation of goaf in closed mining area: a case study of Sanhejian closed mining area in Jiangsu Province, China
Authors: Shi Zhanghao , Zhang Weiqiang , Zhang Fengming , Luo Yue , Chen Shangbin , Zhu Shuyun , Wu Yun
Published: May 2024

The stability of goaf is one of the decisive conditions for the redevelopment and utilization of underground spaces after mine closure. Taking the Sanhejian closed mine area as an example, this study comprehensively evaluates the stability of the goaf using numerical simulation, Analytic Hierarchy Process (AHP), and Vulnerability Index (VI). Firstly, the numerical model of the goaf was built using FLAC3D software to obtain the stress field, displacement field, and characteristics of plastic zone development. Based on the simulation results, stability evaluation criteria for the goaf were formulated, and stability levels were determined. Secondly, a vulnerability assessment model was established using AHP, selecting geological factors, mining factors, and hydrological factors as primary indicators and further determining eight secondary indicators, including geological structural complexity, roof lithology and thickness, geostress, stop mining time, depth-to-coal ratio, goaf width, goaf area, and water volume in goaf. The weights of each indicator were determined, and the indicators were quantified to calculate the VI value of the vulnerability assessment model. The stability zoning threshold of the goaf was obtained using a natural breakpoint classification method and verified against the numerical simulation results to enhance the accuracy of stability evaluation. By integrating the results of both methods and adhering to a conservative risk assessment principle, the stability level of the goaf was ultimately determined, providing reference for the stability evaluation of related underground spaces.
Residential greenness, respiratory symptoms and lung function in children, adolescents and adults with asthma: a cross-sectional study.
Authors: Guinossi Raissa , Mingotti Cintia Bertagni , Burch Monique Olivia , Soares Luciana , Castanha Natalia , Mamoni Ronei Luciano , Marchi Evaldo , Ponte Eduardo
Published: May 2024

We hypothesize that green areas within cities affect the respiratory symptoms of individuals with asthma, but this effect may not be the same for all age groups, because the immunopathology of asthma in children-adolescents is different from the immunopathology of asthma in adults. The objective of this study is to evaluate whether there is an association between the percentage of green area close to the residence and asthma outcomes, stratified by age group. We included individuals with asthma over the age of ten years. Two independent trained researchers measured, in satellite images, the extent of green area around the residence. The primary outcome of the study was the severity of respiratory symptoms measured by the Asthma Control Test. The secondary outcome was the presence of airway obstruction in the spirometry test carried out on the day of the study visit. Binary logistic regression analyzes evaluated whether the percentage of green area close to the residence was associated with asthma outcomes. In children-adolescents, greater density of green area was associated with a greater frequency of uncontrolled asthma symptoms. In adults, greater density of green area was associated with a lower frequency of uncontrolled asthma symptoms and a lower frequency of airway obstruction. We conclude that the extent of green areas close to the residence is associated with asthma morbidity. The expansion of green areas within cities should favor species that do not disseminate pollen with allergenic potential, especially in regions close to schools and daycare centers.
Neutron Spectroscopy of Plutonium using a Handheld Detection System
Authors: Clarke S. D. , Lopez R. , Mozin V. , Kerr P. , Hutchinson J. , Marleau P. , Pozzi S. A.
Published: May 2024

The ability to distinguish multiple forms of plutonium from one another, such as oxide and metal, is paramount to areas of nuclear nonproliferation and international safeguards. In its metal form, plutonium can be readily used in a nuclear weapon, while oxide forms are associated with nuclear reactor fuel. Oxide-based plutonium forms emit neutrons with an energy spectrum that is significantly different from the fission neutrons that are emitted from plutonium metal. Organic scintillation detectors output pulses that are proportional to the neutron energy deposited, and therefore present a means of distinguishing these plutonium forms based on their energy spectra. In this work, metal and oxide forms of plutonium were measured using a handheld detection system based on an organic glass scintillator. Monte Carlo modeling of these experiments was performed to provide insight into the origin of the features in the observed light output spectra. Through analysis of multiple regions of these spectra, in a matter of minutes we were able to unambiguously discriminate oxide and metal plutonium forms from one another and from a plutonium-beryllium neutron source, which was considered for comparison because these sources are commonly used in industrial applications. The ability to discriminate weapons-usable material from nuclear reactor fuel has applications in nuclear treaty verification and safeguards.
Effects of Depth, Distractor Transparency, Chromaticity, and Object type in Feature Search of Transparent Real-World Objects
Authors: Nguyen Rachel T. T. , Peterson Matthew S. , Helton William S.
Published: May 2024

Nguyen et al. (2024) found strong evidence for more efficient orientation searches when semi-transparent, simple objects were in front of distractors, especially when the distractors were more opaque. This study investigates if there is strong evidence for depth effects for orientation search of complex, real-world objects and whether there are differences between orientation search for simple and complex objects. Participants searched for semi-transparent, vertical Hershey bars or Remote controllers amongst horizontal bars. These stimuli were either in front of or behind diagonal bars of 0%, 25%, 50%, 75%, or 100% opacity. Stimuli were also normally colored (chromatic) in Experiment 1 and grayscale in Experiment 2 to investigate whether complex object chromaticity affects orientation search. Search was more efficient when targets were in front of distractor diagonal bars, and there were differences in search efficiency between simple and complex, real-world objects when targets were occluded by distractors. In addition, chromaticity aids search for complex, real-world objects when targets were behind a diagonal of opacity 75% or greater. Overall, when occlusion was present (whether the target is occluded or occludes distractors), search was more efficient when targets were perceived closer to the viewer, and this study additionally yields decisive evidence that orientation search for real-world objects (chromatic or achromatic) yielded larger search slopes than orientation search for simple objects when the target is behind an occluder.
Peripheral Blood Lymphocyte Subsets and Long-Term Clinical Outcomes in Prostate Cancer Patients: An Eight- Year Follow-up Study
Authors: Chen Jiayi , Hao Wenke , Li Guanglan , He Ganyuan , Yu Qixing , Hu Wenxue , Yu Feng
Published: May 2024

Background: The clinical outcomes of prostate cancer (PC) may be influenced by changes in immune profiles. However, the precise correlation between the long-term prognosis of PC and circulating lymphocytes remains uncertain. Therefore, our study aimed to characterize circulating lymphocyte subsets and investigate their relationship with the long-term clinical outcomes in PC patients.
Materials: The prospective cohort study included patients with a pathological diagnosis of PC and Gleason Grades ranging from 5 to 10. Lymphocyte counts were assessed in peripheral blood using flow cytometry. The prognostic value of various lymphocytes was analyzed in the entire cohort, with survival curves generated using the Kaplan-Meier method and multivariate analysis performed using Cox regression models.
Results: Between January 2001 and June 2021, a total of 94 eligible patients with prostate cancer were prospectively enrolled. The median follow-up duration for the study was 98 months. Non-survivors exhibited lower levels of CD4(+)/CD8(+) ratio, CD19(+), and CD19(+)CD5(−) B lymphocytes compared to survivors. Grouping by each cutoff point of the lymphocytes respectively, the lower level of total CD3(+) T cells, CD3(+)CD4(+) T cells, the CD4(+)/CD8(+) ratio, total CD19(+) B cells, CD19(+)CD5(+) B cells, CD19(+)CD5(-) B cells showed poor survival. Multivariate Cox regression analysis confirmed the worse prognosis associated with higher PSA (HR=2.493, 95%CI: 1.356-4.584, P=0.003), lower CD3(+)CD4(+) T lymphocytes (HR=0.379, 95%CI: 0.170-0.843, P=0.017), lower total CD19(+) B cell (HR=0.398, 95%CI:0.187-0.845, P=0.016) and higher CD3(-)CD16(+)CD56(+) NK cells(HR=2.355, 95%CI: 1.175-4.723, P=0.016).
Conclusion: Our findings revealed that a reduced level of CD4(+) T lymphocytes, diminished CD19(+) B cells, and an elevated level of NK cells were associated with poor survival. This suggests potential involvement of B lymphocytes, CD4(+) T lymphocytes, and NK cells in prostate cancer, with implications for the long-term prognosis of these elderly patients.
Revisiting carbon cycling in the Laurentian Great Lakes following dreissenid mussel invasion
Authors: Smith Erin D , McGaughey Leigh J , Marty Jerome , Kirkwood Andrea E , Ridal Jeff
Published: May 2024

Since the active role of inland waters in cycling carbon (C) has been revealed, there has been a renewed interest in calculating C budgets for inland waters to understand their role with respect to global climate change. There is a lack of knowledge regarding C cycling in the Laurentian Great Lakes, the worlds largest freshwater reservoir, with current estimates neglecting the role of invasive species. For one of the most pervasive invaders, dreissenid (zebra and quagga) mussels, research has focused on filter feeding impacts on phosphorus dynamics, but there is a lack of knowledge regarding their role in C cycling, specifically, the impact of the C stored in their slowly degrading shells. As such, we set out to estimate the mass of empty shells and C stored in those shells. We calculated an estimated 1.19 E10 tonnes of empty shell mass currently sitting at the bottom of these lakes, which store approximately 1.43 E9 tonnes of C. This scale of inorganic C storage is comparable to rates of organic C storage in nature-based climate solutions. This work demonstrates the importance of a previously unexplored pathway that dreissenid mussels are altering C cycling in the Laurentian Great Lakes and the thousands of other invaded lakes and rivers.
A Measurement Model for Aquatic Animals Based on Instance Segmentation and 3D Point Cloud
Authors: He Zhiqian , xu Xiaoqing , Luo Jialu , Chen Ziwen , Song Weibo , cao Lijie , Huo Zhongming
Published: May 2024

Traditional computer vision measurement methods often encounter challenges such as scale and dynamic changes and feature extraction difficulties when confronted with aquatic animals images, making measuring aquatic animals' morphology complex and restricted. As a result, most of the current models for measuring aquatic animals’ dimensions focus on length and width information. This paper establishes a Point Cloud Measurement Model to overcome the problems caused by image scale changes and difficulty in feature extraction in aquatic animals’ measurement models. The proposed model integrates neural network instance segmentation, 3D point cloud, and depth camera. First, a convolutional neural network is employed to extract and segment the features of aquatic animals to output Mask and Box coordinates, which can be employed to acquire the depth value of the identified aquatic animals. Then, the Point Cloud Measurement Model reconstructs the 3D point cloud of the aquatic animals and processes the Mask. Finally, the height of the vertex of the aquatic animals from the plane is determined by fitting the point cloud to the plane, and the edge detection is applied to the Mask to obtain the length and width, thus acquiring a collection of boundary points for processing. The self-produced aquatic animals’ segmentation dataset and the public Underwater Robotics Professional Competition (URPC) dataset were tested in different network models to evaluate the effectiveness of the proposed model. The experimental results indicate that the mAP@0.5:0.95 of the improved YOLOv8n model is 97.5% on the self-produced dataset, while the mAP@0.5 is 84.6% on the URPC dataset. The absolute errors of length, width, and height are all within 5 mm. The clams’ absolute height error is 0.89 mm. These results demonstrate the generality and accuracy of the proposed point cloud measurement model.
Targeted TGF-βR2 Knockdown in the Retrotrapezoid Nucleus Mitigates Respiratory Dysfunction and Cognitive Decline in a Mouse Model of Cerebral Amyloid Angiopathy with and without Stroke
Authors: Hamamy Ahmad El , Iqbal Zahid , Le Ngoc Mai , Ranjan Arya , Zhang YuXing , Lin Hung Wen , Tan Chunfeng , Patrizz Anthony , McCullough Louise D. , Li Jun
Published: May 2024

Introduction: Cerebral amyloid angiopathy (CAA) is characterized by the deposition of amyloid-beta peptides within cerebral blood vessels, leading to neurovascular complications. Ischemic strokes result from acute disruptions in cerebral blood flow, triggering metabolic disturbances and neurodegeneration. Both conditions often co-occur and are associated with respiratory dysfunctions. The retrotrapezoid nucleus (RTN), which is crucial for CO2 sensing and breathing regulation in the brainstem, may play a key role in breathing disorders seen in these conditions. This study aims to investigate the role of Transforming Growth Factor Beta (TGF-β) signaling in the RTN on respiratory and cognitive functions in CAA, both with and without concurrent ischemic stroke.
Methods: Adult male Tg-SwDI (CAA model) mice and C57BL/6 wild-type controls underwent stereotaxic injections of lentivirus targeting TGF-βR2 in the RTN. Stroke was induced by middle cerebral artery occlusion using a monofilament. Respiratory functions were assessed using whole-body plethysmography, while cognitive functions were evaluated through the Barnes Maze and Novel Object Recognition Test (NORT). Immunohistochemical analysis was conducted to measure TGF-βR2 and GFAP expressions in the RTN.
Results: CAA mice exhibited significant respiratory dysfunctions, including reduced respiratory rates and increased apnea frequency, as well as impaired cognitive performance. TGF-βR2 knockdown in the RTN improved respiratory functions and cognitive outcomes in CAA mice. In CAA mice with concurrent stroke, TGF-βR2 knockdown similarly enhanced respiratory and cognitive functions. Immunohistochemistry confirmed reduced TGF-βR2 and GFAP expressions in the RTN following knockdown.
Conclusions: Our findings demonstrate that increased TGF-β signaling and gliosis in the RTN contribute to respiratory and cognitive dysfunctions in CAA and CAA with stroke. Targeting TGF-βR2 signaling in the RTN offers a promising therapeutic strategy to mitigate these impairments. This study is the first to report a causal link between brainstem gliosis and both respiratory and cognitive dysfunctions in CAA and stroke models.
The lubricity of gases
Authors: Zhang Jie , Wong Janet , Spikes Hugh
Published: May 2024

A sealed reciprocating tribometer has been used to study the influence of different gaseous environments on the friction and wear properties of AISI52100 bearing steel at atmospheric pressure and 25°C. Helium, argon, hydrogen, carbon dioxide and nitrogen all give high friction and wear, suggestive of very little, if any tribofilm formation under the conditions studied. Dry air and oxygen also give high friction, slightly lower than the inert gases, but produce extremely high wear, much higher than the inert gases. This is characteristic of the phenomenon of “oxidational wear”. The two gases ammonia and carbon monoxide give relatively low friction and wear, and XPS analysis indicates that this is due to the formation of adsorbed ammonia/nitride and carbonate films respectively.
For the hydrocarbon gases studied, two factors appear to control friction and wear, degree of unsaturation and molecular weight. For the saturated hydrocarbons, methane and ethane give high friction and wear but propane and butane give low friction after a period of rubbing that decreases with molecular weight. The unsaturated hydrocarbons all give an immediate reduction in friction with correspondingly low wear. Raman analysis shows that all the hydrocarbons that reduce friction and wear form a carbonaceous tribofilm of the rubbed surfaces.
Meta-path-based drug efficacy prediction model for active natural compound discovery from Traditional Chinese medicine
Authors: Li Yingcan , Shen Yu , Cai Yezi , Gao Jiahui , Huang Lei , Si Weinuo , Zhou Kai , Gao Shan , Luo Qichao
Published: May 2024

Identifying the active nature compounds remains a challenge for drug discovery, and new algorithms need to be developed to predict active ingredients from complex natural products. Here, we proposed Meta-DEP, a Meta-paths-based Drug Efficacy Prediction based on drug-protein-disease heterogeneity network, where Meta-paths contains all the shortest paths between drug targets and disease-related proteins in the network and drug efficacy is measured by a predictive score according to drug disease network proximity. Experiments show that Meta-DEP performs better than traditional network topology analysis on drug-disease interaction prediction task. Further investigations demonstrate that the key targets identified by Meta-DEP for drug efficacy are consistent with clinical pharmacological evidence. To prove that Meta-DEP can be used to discover active nature compounds, we apply it to predict the relationship between the monomeric components of traditional Chinese medicine included in the TCMSP database and diseases. Results indicate that Meta-DEP can accurately predict most of the drug-disease pairs included in the TCMSP database. In addition, biological experiments are directly used to demonstrate that the natural compound mined by Meta-DEP from traditional Chinese medicine has a protective effect against myocardial ischemia. Overall, the model developed in this study provides new impetus for driving the nature compound into innovative lead molecule. Code and data are available at https://github.com/t9lex/Meta-DEP.
Gaps in the usage and reporting of multiple imputation for incomplete data: Findings from a scoping review of observational studies addressing causal questions
Authors: Mainzer Rheanna M , Moreno-Betancur Margarita , Nguyen Cattram D , Simpson Julie A , Carlin John B. , Lee Katherine J
Published: May 2024

Background
Missing data are common in observational studies and often occur in several of the variables required when estimating a causal effect, i.e. the exposure, outcome and/or variables used to control for confounding. Analyses involving multiple incomplete variables are not as straightforward as analyses with a single incomplete variable. For example, in the context of multivariable missingness, the standard missing data assumptions (“missing completely at random”, “missing at random” [MAR], “missing not at random”) are difficult to interpret and assess. It is not clear how the complexities that arise due to multivariable missingness are being addressed in practice. The aim of this study was to review how missing data are managed and reported in observational studies that use multiple imputation (MI) for causal effect estimation, with a particular focus on missing data summaries, missing data assumptions, primary and sensitivity analyses, and MI implementation.
Methods
We searched five top general epidemiology journals for observational studies that aimed to answer a causal research question and used MI, published between January 2019 and December 2021. Article screening and data extraction were performed systematically.
Results
Of the 130 studies included in this review, 108 (83%) derived an analysis sample by excluding individuals with missing data in specific variables (e.g., outcome) and 114 (88%) had multivariable missingness within the analysis sample. Forty-four (34%) studies provided a statement about missing data assumptions, 35 of which stated the MAR assumption, but only 11/44 (25%) studies provided a justification for these assumptions. The number of imputations, MI method and MI software were generally well-reported (71%, 75% and 88% of studies, respectively), while aspects of the imputation model specification were not clear for more than half of the studies. A secondary analysis that used a different approach to handle the missing data was conducted in 69/130 (53%) studies. Of these 69 studies, 68 (99%) lacked a clear justification for the secondary analysis.
Conclusion
Effort is needed to clarify the rationale for and improve the reporting of MI for estimation of causal effects from observational data. We encourage greater transparency in making and reporting analytical decisions related to missing data.
Peritoneal De-differentiated Liposarcoma: A Rare Case Report
Authors: Hardas Gauri Vinod , Lad Lalit , Bora Harshwardhan , Prasad Saurabh
Published: May 2024

Peritoneal de-differentiated liposarcoma is a rare malignancy with a poor prognosis. Our patient, 67 years/Male presented with complaints of constipation & distension of abdomen for one month. Initially based on histology, diagnosis of Gastrointestinal Stromal Tumor (GIST) was thought. On PET scan, he had multiple peritoneal deposits & serosal deposits along recto-sigmoid colon and ileal loop which on immunohistochemistry (IHC) proved to be de-differentiated liposarcoma. The patient was given chemotherapy. Patient responded well to treatment. Such peritoneal tumors pose a challenge to the pathologist as only morphology is not of much help & IHC becomes necessity.
Varicella Zoster Complicated By Disseminated Intravascular Coagulation: Clinico-Pathological Correlation Of A Rare Clinical Manifestation Of A Benign Disease
Authors: Balraam KV Vinu , Taneja Nitin Sagar , Sharma Seema , Jadhav Toyaja M , Sen Alok D
Published: May 2024

Varicella Zoster Virus (VZV) infections are considered to be mild and ubiquitous infections predominantly affecting the pediatric population. However, in adults and immunocompromised patients, this apparently benign self-limiting course can have protean complications with a rapidly downhill course. We present a rare case report of a young individual with a probably compromised immune system who had a fulminant VZV infection complicated with disseminated intravascular coagulation (DIC) resulting in death.
Frequency of Immunofluorescence Antinuclear Antibody Patterns: In A Local Population from North India
Authors: Deepak Rani , Agrawal Charu , Kapoor Sunita , Kanotra Ritesh
Published: May 2024

Background
Autoimmune disorders in India have seen rise in recent times. The first-line test in diagnostic workup of autoimmune disorders is ANA indirect Immunofluorescence (IIF). A positive Antinuclear antibodies (ANA) result in conjunction with clinical findings aids in predicting the diagnosis. ANA test is not widely available in India, probably due to the cost and requirement of technical expertise. In view of rising incidence of autoimmune disorders in India and due to scarcity of data, this study aimed at determining prevalence of ANA positivity, study ANA patterns and their frequency and estimate disease burden in patients among local population of Northern India.
Methods
The study was performed on 2000 suspected autoimmune disorder patients during a period of 01 year (January 2023 till January 2024). Assessment of ANA patterns and titres were carried out by ANA-IIF technique.
Result
Of the 2000 participants, 30.8% were found to be ANA-positive. Nuclear speckled pattern was observed to be the most common, among others.  Among mixed ANA patterns, mix of speckled and homogenous patterns were common. Females showed predominance over males in all age groups in ratio of 3:1.
Conclusion:
The study is a preliminary, retrospective study providing overview of ANA positivity and autoimmunity status in Northern India, where despite the heavy disease burden, data is still scarce. Further studies in Indian population are essential to determine relationship of ANA with various etiologic and biochemical factors and association between ANA patterns and specific antibodies in serum for diagnosis of specific autoimmune diseases.