bluuebunny/crossref_metadata_2025_split huggingface dataset:
Detection and characterization of colorectal cancer by autofluorescence lifetime imaging: a preliminary study on surgical specimens
Authors: Herrando Alberto Ignacio , Fernández Laura M. , Azevedo José , Vieira Pedro , Domingos Hugo , Galzerano Antonio , Shcheslavskiy Vladislav , Heald Richard J. , Parvaiz Amjad , Silva Pedro Garcia da , Castillo-Martin Mireia , Lagarto João L. 
Published: May 2024

Abstract

Colorectal cancer (CRC) ranks among the most prevalent malignancies worldwide, driving a quest for comprehensive characterization methods. We report a characterization of the ex vivo autofluorescence lifetime fingerprint of colorectal tissues obtained from 73 patients that underwent surgical resection. We specifically target the autofluorescence characteristics of collagens, reduced nicotine adenine (phosphate) dinucleotide (NAD(P)H), and flavins employing a fiber-based dual excitation (375 nm and 445 nm) optical imaging system. Autofluorescence-derived parameters obtained from normal tissues, adenomatous lesions, and adenocarcinomas were analyzed considering the underlying clinicopathological features. Our results indicate that differences between tissues are primarily driven by collagen and flavins autofluorescence parameters. We also report changes in the autofluorescence parameters associated with NAD(P)H that we tentatively attribute to intratumoral heterogeneity, potentially associated to the presence of distinct metabolic subpopulations. Changes in autofluorescence signatures of tumors were also observed with lymphatic and venous invasion, differentiation grade, and microsatellite instability. Finally, we characterized the impact of radiative treatment in the autofluorescence fingerprints of rectal tissues and observed a generalized increase in the mean lifetime of radiated tumors, which is suggestive of altered metabolism and structural remodeling. Overall, our preliminary findings indicate that multiparametric autofluorescence lifetime measurements have the potential to significantly enhance clinical decision-making in CRC, spanning from initial diagnosis to ongoing management. We believe that our results will provide a foundational framework for future investigations to further understand and combat CRC exploiting autofluorescence measurements.
Association of sleep traits, physical activity and leisure sedentary behavior with women’s reproductive health: a two-sample Mendelian randomization analysis
Authors: Zhang Jiaxin , Wang Tao , Yang Pusheng , Miao Yaxin , Ge Beilei , Sun Jing 
Published: May 2024

Abstract

Background: Living habits affect women's endocrine and fertility over time with aging and in certain circumstances, according to which we can promote women's reproductive health by adjusting living habits.
Methods: We utilized two-sampleMendelian randomization (TSMR) analysis with summary datasets from genome-wide association study (GWAS) to investigate the causal relationship between sleep traits, leisure sedentary behavior, physical activity and women’s reproductive health-related traits. Exposure genetic instruments were used as variants significantly related to traits. The inverse-variance weighted (IVW) method was used as the main analysis approach, and we also performed MR-Egger and weighted median to supplement the sensitivity test. Then, the horizontal pleiotropy was detected by using MRE intercept and MR-PRESSO methods, and the heterogeneity was assessed using Cochran’s Q statistics by IVW and MR-Egger.
Results: We found evidence that insomnia showed a significant inverse causal association with the endometriosis [OR (95% CI) IVW = 1.80 (1.16, 2.80), P = 0.009], and with the abnormal menstruation [OR (95% CI) IVW = 2.37 (1.34, 4.20), P = 0.003]. What else the sleep duration has the negative relation menopause age (beta IVW = −0.034, P = 0.001), the long sleep duration might be the protective factor of endometriosis [OR (95% CI) IVW = 0.07 (0.01, 0.72), P = 0.024], strenuous sports were also negatively correlated with the female infertility[OR (95% CI) IVW = 0.10 (0.02, 0.68), P = 0.019]. In sensitivity analysis, we observed no sign of horizontal pleiotropy or heterogeneity.
Conclusion: Our finding suggested insomnia was an adverse factor of endometriosis and abnormal menstruation, long sleep duration was a protective factor with endometriosis. Therefore, adequate sleep and regular schedule might decrease the risk of endometriosis and abnormal menstruation to guarantee the women reproductive health.
Medical Laboratory Technology (MLT) study criteria, and training drawbacks in Pakistani institutions a web-based survey
Authors: Shoukani Hussan Ibne , Kubra Khudija tul 
Published: May 2024

Abstract

Background
Medical Laboratory Technology (MLT) is an allied health profession, that performs diagnostic tests by using different tools and analyzes the biological samples for the diagnosis of diseases to monitor the patient's health, after that the physician decides his medical opinion based on lab investigation. Sometimes patients suffer from death or life conditions, at that time accurate lab investigations can facilitate the physician to make the best decision which can help to save the patient's life. This needs a well-settled teaching lab which should be attached to a teaching hospital, to produce qualified medical lab professionals.
Objective
This study aimed to define the required professional criteria for medical lab technology and the evolution of training drawbacks in Pakistani institutions.
Methods
Study data summarized from different verified sources such as institutional websites, course and training curriculums of MLT offering institutions. They were defined in different grades according to the fulfillment of professional requirements. Out of n = 185 institutions (offering MLT courses and degrees), only n = 18 (9.72%) are in A-Grade level institutes which are fulfilling all requirements of MLT qualification, n = 17 (9.18%) are situated in B-Grade, n = 84 (45.40%) are part of C-Grade, and n = 66(36.67%) ranked in D-Grade institutions.
Conclusion
Based on standard MLT qualification requirements this study showed that most institutions offering MLT without any proper job training facilitation of clinical lab departments, and no proper affiliation with any clinical teaching lab.
Rapid Resolution of Newly Formed Carotid Free-Floating Thrombus Through Anticoagulation Therapy
Authors: Xie Fuli , Liang Lili , Wang Yuzhou 
Published: May 2024

Abstract

Background
Carotid free-floating thrombus (CFFT) are rare but carry significant risks of ischemic strokes. While the predominant treatment modality typically involves vascular intervention, in this case study, we highlight the feasibility of alternative options, specifically short-term anticoagulation therapy guided by extensive radiological evaluation.
Case presentation:
We admitted a patient with acute ischemic stroke due to middle cerebral artery (MCA) occlusion, and the National Institutes of Health Stroke Score (NIHSS) was 15. The patient was satisfactorily revascularized by prompt intravenous alteplase thrombolysis, but a rare occurrence of carotid free-floating thrombus was found, which was the culprit for the occlusion of the MCA. Instead of surgical treatment, we performed extensive radiological evaluations for the thrombus, including high-resolution magnetic resonance and serial ultrasonic scans. The intramural thrombus is highly suspected to be newly formed, so we hypothesized it might respond to anticoagulant therapy. As expected, after short-term anticoagulant therapy of enoxaparin injection, CFFT significantly dissolved.
Conclusions
This case illustrates the efficacy of anticoagulation for newly formed CFFT and introduces a novel treatment protocol guided by extensive radiological evaluation.
Honokiol inhibits arsenic trioxide-induced cardiomyopathy by modulating ferroptosis via SIRT3 signaling pathway
Authors: Wei Qing-qing , Huang An-Liang , Liu Ning-xi , Zhang Yi-ran , Yang Fan 
Published: May 2024

Abstract

Background Our previous studies have confirmed that Honokiol exerts protective effect on cardiomyocytes and cardiac tissue against ATO-induced cardiotoxicity, which is attributed to inhibiting cardiomyocyte apoptosis via reduced oxidative stress.Objectives This research aimed to explore the entire mechanism by which Honokiol provides protection against arsenic trioxide-induced cardiotoxicity.Materials and methods 129S1/SvImJ male wild type (WT) mice and SIRT3-knockout (SIRT3−/−) mice with 129S1 background were applied to verify the pathway of Honokiol on myocardial toxicity of arsenic trioxide; MitoSox, carboxy-DCFDA and Amplex Red were used to detect oxidative stress; ferroptosis-associated markers (MDA, GSH, tissue iron, GPX4 and 4-HNE expression) were tested by test kit or immunohistochemistry; autophagic flux was analyzed by western blot.Results SIRT3 knockout abolishes protective effects of HKL in ATO-induced myocardial injury and hypertrophy; Honokiol protects myocardium from ATO-induced oxidative stress through SIRT3/SOD2 pathway; Honokiol inhibited ATO-induced ferroptosis via the SIRT3 pathway in myocardial tissues; Honokiol improve autophagic flux in cardiomyocytes exposed to ATO treatment. Autophagic flux plays a critical role in protective effect of Honokiol on ATO-induced ferroptosis. The present study confirmed that Honokiol inhibits oxidative stress injury and ferroptosis in cardiomyocytes by promoting the autophagic flux in cardiomyocytes through the activation of SIRT3.
Accurate, Scalable and Cross-platform Cell Identification for High-resolution Spatial Transcriptomics
Authors: Wang Chenfei , Sun Dongqing , Zhang Lele , Han Tong , Wu Qiu , Zhang Peng 
Published: May 2024

Abstract

Recent advances in spatial transcriptomics (ST) have brought unparalleled opportunities to unravel cellular diversity and cell-cell interactions within their spatial context. High-resolution ST techniques, including barcoding-based and imaging-based platforms, have achieved remarkable sub-cellular resolution. However, the precise segmentation of cells remains a significant challenge and hampers effective single-cell spatial analysis. Existing methods targeting specific techniques lack compatibility across different high-resolution ST platforms, and many of them cannot scale well to ST data with large fields of view. Here, we introduce Cellist, a novel multi-modal cell-segmentation method that synergistically combines image and expression information, enabling comprehensive investigations at the cell level. Employing Cellist on mouse brain Stereo-seq data, we showcased its superiority in yielding heightened within-cell homogeneity over existing methods. Furthermore, Cellist facilitated accurate spatial domain identification and cell-type annotation. Importantly, Cellist is suitable for various ST techniques including Seq-Scope, seqFISH+, STARmap, and 10x Xenium, exhibiting exceptional accuracy across diverse high-resolution ST platforms and biological systems, all while maintaining high computational efficiency. Finally, we applied Cellist to post-neoadjuvant immunotherapy non-small cell lung cancer (NSCLC) samples. Our analyses revealed the spatial heterogeneity of tumor clones and identified therapy response-related myeloid subtypes and structures. These findings highlight the immense potential of Cellist in enhancing the power of high-resolution ST techniques for characterizing the spatial organization of cells and unraveling intricate tissue architectures. Cellist is publicly available at https://github.com/wanglabtongji/Cellist.
Assessing Microbial Diversity in Open-Pit Mining: Metabarcoding Analysis of Soil and Pit Microbiota Across Operational and Restoration Stages
Authors: Reto Priscila Heredia , Rogel Rosita Castillo , Lucano Gabriela Palomino , Fallen Jean Louis , Vidaurre Karina Zapata , Febre Marisol Saavedra , Calle Gabriel Reyes , Rosell Juan Zingg , Perez Jimmy Lopez , Rosillo José Morán , Mialhe Eric , Diringer Benoit 
Published: May 2024

Abstract

Mine closure operations aim to restore the ecosystem close to its original state. Microorganisms are key components of the soil equilibrium and therefore essential to the restoration process. We used metabarcoding techniques to characterize the bacterial and fungal composition in pristine soils, stockpiled soils (topsoils), enriched stockpiled soils (technosoils), enriched and revegetated soils (revegetated technosoils), and visually distinct pits in an open pit gold mine. Comparative analysis indicated that pristine and topsoils exhibited the highest levels of richness, followed by technosoils and pits. Taxonomic analysis identified dominant microbes’ communities. For both bacteria and fungi, the dominant genera differed between pristine/topsoils and technosoils. Ecological similarity indices showed that topsoil microbial communities were separated from pristine soil. Revegetated technosoil showed more similarity to pristine/topsoil than freshly prepared technosoil, indicating an ongoing process of microbial restoration. All pit samples differed greatly in their microbial composition, with the presence of moisture and rock composition being the main axes of dissimilarity. It is concluded that the greater community complexity in soils is related to the availability of nutrients, physicochemical variations and the possibility of interaction with other microbes, while pits could be considered as extreme ecosystems that limit the growth of most microorganisms.
Thermostable fungal xylanase as a potential supplemental additive for commercial cellulase cocktails
Authors: Estevão Carlos Junior de Assis , Almeida Lucas Filipe , Arruda Luiz Vinícius de Souza , de Souza João Batista , Guimarães Valéria , Alfenas Rafael Ferreira , Maitan-Alfenas Gabriela 
Published: May 2024

Abstract

Enzymes are crucial in acquiring valuable biotechnological products, such as fermentable sugars, from alternative carbon sources. Lignocellulosic biomass, often derived from agro-industrial waste, serves as a renewable source for second-generation (2G) ethanol production employing cellulolytic and hemicellulolytic enzymes in the saccharification process, releasing glucose for alcoholic fermentation. Thus, there is a growing demand for novel catalysts that act in biomasses depolymerization, while remaining environmentally friendly. This study aimed to induce xylanase production by Ceratocystis fimbriata using barley, corn cob, and wheat bran as substrates. Additionally, the study evaluated the supplementation of a commercial cellulase cocktail with the partially purified fungal xylanase. The biomass substrates exhibited the highest xylanolytic activity after 8 days of cultivation, with barley yielding 21.20 U/mg. After partial purification through ion exchange chromatography, the xylanase produced in barley demonstrated activity of 67.34 U/mg, resulting in a purification factor of 3.2 and a yield of 56.9 %. The xylanase displayed optimal activity in the pH range of 2.0 to 8.0, retaining more than 50 % of its relative activity. Moreover, the enzyme displayed an optimal temperature of 55 °C and retained over 50 % of its activity after 72 hours at 50 °C. The supplemented Multifect® CL cocktail retained xylanase activity above 50 % for 72 hours, unlike the unsupplemented one. These findings unveiled the thermostability of C. fimbriata xylanase. Finally, the supplementation resulted in hydrolysis enhancement of pretreated sugarcane bagasse, leading to an increase of over 40 and 80 % in glucose and xylose production, respectively.
Structural basis for antibiotic transport and inhibition in PepT2, the mammalian proton-coupled peptide transporter.
Authors: Newstead Simon , Parker Joanne , Deme Justin , Lichtinger Simon , Kuteyi Gabriel , Biggin Philip , Lea Susan 
Published: May 2024

Abstract

The uptake and elimination of beta-lactam antibiotics in the human body are facilitated by the proton-coupled peptide transporters PepT1 (SLC15A1) and PepT2 (SLC15A2). The mechanism by which SLC15 family transporters recognize and discriminate between different drug classes and dietary peptides remains unclear, hampering efforts to improve antibiotic pharmacokinetics through targeted drug design and delivery. Here, we present cryo-EM structures of the mammalian proton-coupled peptide transporter, PepT2, in complex with the widely used beta-lactam antibiotics cefadroxil, amoxicillin and cloxacillin. Our structures, combined with pharmacophore mapping, molecular dynamics simulations and biochemical assays, establish the mechanism of antibiotic recognition and the important role of protonation in drug binding and transport.
Exploring the host compound dynamics of 1,4-phenylene-bis(di-p-fluorophenylmethanol) in mixed pyridines
Authors: Barton Benita , Vorgers Jarryd A. , Hosten Eric C. 
Published: May 2024

Abstract

In this investigation, the wheel-and-axle host compound, 1,4-phenylene-bis(di-p-fluorophenylmethanol) H, was demonstrated to have inclusion ability for each of PYR, 2MP, 3MP and 4MP (1:1, 1:2, 1:2 and 1:2 were the H:G ratios). In the equimolar guest competition experiments, H was observed to have an overwhelming affinity for PYR and 4MP relative to 2MP and 3MP. In fact, selectivity coefficients calculated from the non-equimolar binary guest competition experiments suggested that this host compound would be an efficient candidate for the separation of all PYR/2MP mixtures and a 40:60 4MP/3MP solution through host-guest chemistry strategies. SCXRD analyses established the preferred guests (PYR and 4MP) to be involved in significantly shorter stabilizing classical hydrogen bonding interactions with H, explaining the selectivity behaviour of this host compound in the guest mixtures. Additionally, Hirshfeld surface considerations also explained this behaviour, but only for PYR. Additionally, thermal analyses were used to ascertain the relative thermal stabilities of the four complexes and, satisfyingly, the PYR- and 4MP-containing complexes possessed the greater thermal stabilities compared with H·2(2MP) and H·2(3MP), as was demonstrated by a comparison of their guest release onset temperatures.
Large Language Model Based Mutations in Genetic Improvement
Authors: Brownlee Alexander Edward Ian , Callan James , Even-Mendoza Karine , Geiger Alina , Hanna Carol , Petke Justyna , Sarro Federica , Sobania Dominik 
Published: May 2024

Abstract

Ever since the first large language models (LLMs) have become available, both academics and practitioners have used them to aid software engineering tasks. However, little research as yet has been done in combining search-based software engineering (SBSE) and LLMs. In this paper, we evaluate the use of LLMs as mutation operators for genetic improvement (GI), an SBSE approach, to improve the GI search process. In a preliminary work, we explored the feasibility of combining the Gin Java GI toolkit with OpenAI LLMs in order to generate an edit for the JCodec tool. Here we extend this investigation involving three LLMs and three types of prompt, and five real-world software projects. We sample the edits at random, as well as using local search. Our results show that, compared with conventional statement GI edits, LLMs produce fewer unique edits, but these compile and pass tests more often, with the OpenAI model finding test-passing edits 77% of the time. The OpenAI and Mistral LLMs were roughly equal in finding the best run-time improvements. Simpler prompts were more successful than those providing more context and examples. Qualitative analysis revealed a wide variety of areas where LLMs typically failed to produce valid edits: commonly including inconsistent formatting, generating non-Java syntax, or refusing to provide a solution.
Distribution-Aware Prompt Generator for Long-Tailed Vision Recognition
Authors: Liao Walter , Fang Pengfei , Ge Zongyuan , Harandi Mehrtash 
Published: May 2024

Abstract

We present a prompt learning framework designed to enhance the performance in computer vision task considering a particular use case where the training image dataset is confronted with highly imbalanced categorical distributions. By formulating the prompt learning as a variational problem, our model is capable of generating multiple prompts to describe a semantic (i.e, class). The motivation behind generating multiple prompts originates from the heuristic that the voting ensemble establishes a more robust aggregated learning algorithm which potentially benefits learning the tail classes where the number of the training sample is scarce. Unlike previous prompt learning techniques, which are often restricted by using a fixed set of prompts during the training and the test phase, we propose to learn the prompt distribution from which an arbitrary number of prompts can be sampled whenever required, and we named our method as “Prompt Distribution Learning (PDL)”. We will discuss and contrast various ways to formulate the variation model and thoroughly compare their performances against state-of-the-art solutions for long-tailed visual recognition. Our empirical study suggests that the proposed prompt-learning framework is beneficial for transferring a pre-trained vision-language model to long-tailed downstream visual recognition tasks while being sufficiently flexible in accommodating different designs of prompt-generating functions. Our code is publicly available at https: //github.com/Walter-pixel/Prompt-Distribution-of-CLIP-Long-Tailed-Data.
Black-box Dehazing Network via Joint Loss Function
Authors: Zhang Jian , Zhao Guang , Song Wanjuan , Xu Zhiyan 
Published: May 2024

Abstract

Single image dehazing is a notoriously challenging task in image processing due to the numerous unknown factors involved. Most existing dehazing methods are based on physical models of the haze formation process. However, real-world haze scenes cannot be accurately mathematically modeled due to the existence of various unquantifiable factors in the scene. Therefore, the dehazing methods based on physical models often perform poorly in complex haze scenes. In this paper, we propose a novel black-box dehazing equation. In this equation, the haze is modelled as an additional image interference layer, without explicitly reasoning about the physical model of haze formation. The dehazing process is modelled as removing this image interference layer. Based on this equation, we propose a novel network architecture called the Black-box Dehazing Network (BDN). Moreover, we propose a joint loss function for training this network. The joint loss function not only evaluates pixel-level differences between the dehazed image and the haze-free image, but also measures differences in texture, color, and structure between the hazy image and its corresponding dehazed version as well as those between the hazy image and its haze-free version. In training, BDNet is only fed pairs of haze-free images and their corresponding hazy images. The corresponding hazy patches are generated on-the-fly during network training. Experimental results demonstrate that the proposed method has the advantage of universality and outperforms existing state-of-the-art dehazing methods.