bluuebunny/crossref_metadata_2025_split huggingface dataset:
Second Primary Lung Cancer after Breast Cancer: A Case Series
Authors: Sua Luz Fernanda , Osorio Alvaro , Zuñiga-Restrepo Valeria , Castrillón Ana Isabel , Ibarra Ciro , Quintero Natalia , Fernandez-Trujillo Liliana 
Published: March 2023

Abstract
Background: Breast cancer (BC) accounts for approximately 24.2% of all malignant tumours in women. Due to advances in chemotherapeutic agents and targeted treatment, survival of BC patients is increasing. Second primary cancers (SPC) are becoming more common, among which lung cancer (LC) has a latency of approximately ten years and may be related to risk factors such as exposure to BC radiotherapy. We present a case series of nine patients with SPC of the lung after BC (BC-LC), highlighting the clinical and molecular findings in a tertiary care hospital in Colombia.
Case presentation: This is a retrospective case series report describing demographic, diagnostic, therapeutic and molecular profile data of patients with SPC of the lung diagnosed between 2014 and 2019 with a history of BC in a referred tertiary care hospital.
Nine women with BC-LC were included. The mean age at BC diagnosis was 56.2 ± 10.8 years. All cases were ductal carcinoma, seven were triple negative, one was HER2 positive, and one was estrogen and progesterone positive. Adenocarcinoma was the only histological type of LC. All patients had received radiotherapy for BC, and the mean latency between the two diagnoses was 8.1 years.
Conclusion: Our case series provides preliminary data on patients with BC-LC and contributes to the local epidemiology. Histology (ductal BC, adenocarcinoma of the lung) has a role in BC-LC patients and radiotherapy for BC. Adequate histological diagnosis of lung lesions in patients with BC is essential for appropriate approach and treatment.
Investigating the Use of Different Recurrent Neural Networks for Natural Language Inference in Arabic
Authors: Bensghaier Mabrouka , Bakari Wided , Neji Mahmoud 
Published: March 2023

Abstract
Natural language inference (NLI) is a subfield of natural language processing (NLP) that involves determining the logical relationship between two pieces of text, usually a premise and a hypothesis. The goal of an NLI system is to classify the inference relationship between the premise and the hypothesis into one of three categories, namely, entailment, contradiction and neutral. An understanding of this relationship is useful for performing several NLP tasks, such as, summarization, question-answering, information retrieval, etc. Given the potential of neural networks to handle complex natural language tasks, and the absence of prior research on their application to NLI in Arabic. In this context, we propose the investigation of different neural network models for the NLI task in Arabic language. Particularly, we carried out experiments using various types of recurrent neural networks, such as, Simple RNN, LSTM, GRU, Bi-LSTM, and BiGRU to find the one that performs best on the NLI task in Arabic. We performed our experiments using the existing datasets for Arabic NLI namely, ArbTE, XNLI, and ArNLI.
Molecular detection of pathogens from ticks collected from dogs and cats at veterinary clinics in Finland
Authors: Zakham Fathiah , Korhonen Essi M , Puonti Petteri T , Castrén Robert S , Uusitalo Ruut , Smura Teemu , Kant Ravi , Vapalahti Olli , Sironen Tarja , Kinnunen Paula M 
Published: March 2023

Abstract
Background: Ticks carry microbes, some of which are pathogenic for humans and animals. To assess this One Health challenge, 342 ticks were collected from pet dogs and cats at 10 veterinary clinics in Finland as part of the European project “Protect Our Future Too”.
Methods: The tick species were identified and ticks were screened with quantitative PCR (qPCR) for tick-borne pathogens, including Borrelia burgdorferisensu lato, Borrelia miyamotoi, Ehrlichia canis, Anaplasma spp., Candidatus Neoehrlichia mikurensis, tick-borne encephalitis virus (TBEV), and Babesia spp. For comparison, a subset of tick DNAs (20 qPCR positive samples) was analysed with 16S next-generation sequencing (NGS).
Results: Most ticks were Ixodes ricinus (289, 84.5%), followed by I. persulcatus (51, 14.9%). One hybrid tick (I. ricinus/I. persulcatus, 0.3%) and one Rhipicephalus sanguineus tick (0.3%) were identified. We found one or more of the analysed pathogens in 17% (59/342) of the ticks. The most prevalent pathogen was B. burgdorferi s.l. (36, 10.5%), followed by Anaplasma phagocytophilum(12, 3.5%), B. miyamotoi (5, 1.5%), Babesia venatorum(4, 1.2%), and TBEV (1, 0.3%). Ca. N. mikurensis DNA was amplifiable from 3 (0.9%) ticks. Ehrlichia canis was not detected. In the 16S NGS, six samples produced enough reads for the analysis. In these six samples, we confirmed all the positive qPCR findings of Borrelia spp. and Ca. N. mikurensis.
Conclusions: The high prevalence of pathogenic microorganisms in the ticks of this study emphasize the importance of awareness of ticks and tick-borne diseases and prevention. Furthermore, the results show that veterinary surveillance can facilitate early detection of tick-borne pathogens and new tick species and draw attention to possible co-infections that should be considered both in symptomatic humans and animals after tick bites.
Aso volcano, Japan: assessing the 100-year probability of a new caldera-forming eruption based on expert judgements with Bayes Net and Importance Sampling uncertainty analysis
Authors: Aspinall Willy , Sparks R. Stephen J. , Hill Brittain E , Costa Antonio , Connor Charles , Inakura Hirohito , Hasenaka Toshiaki , Miyoshi Masaya , Kiyosugi Koji , Tsuji Tomohiro , Ushioda Masashi 
Published: March 2023

AbstractThe Aso-4 explosive eruption on Kyushu, Japan, 89,500 years ago was one of the biggest eruptions in the last one hundred millennia, with a magnitude of approximately M8. Modern society requires the likelihood of natural events with potentially disastrous consequences to be evaluated, even if probabilities of occurrence are diminishingly small. For some situations, it is not satisfactory to assert an event scenario probability is “negligible” or can be “ignored”. Judicial hearings or litigation may require risk levels to be quantified, in which case, statements of scientific confidence could be decisive. Internationally, e.g. for nuclear site safety evaluations, event likelihoods on order of 10− 7/year are often considered for quantitative assessment. At such hazard levels, this might include evaluating the proposition that a particular volcano can deliver a future super-eruption, a supposition that could be attached to Aso volcano. But, simplistically taking the average recurrence interval between past caldera-forming eruptions at a given volcano is an unreliable guide to the likelihood of a future repeat: each past event represented a unique set of tectonic and magmatic conditions within a continually evolving volcanic system. Such processes are not temporally stationary nor statistically uniform. To evaluate the probability of a new M8 event at Aso, within the next 100 years, we performed a comprehensive stochastic probability uncertainty analysis using a model implemented with advanced computational Bayes Net (BN) software. Our eruption process model is informed by multiple strands of evidence from volcanology, petrology, geochemistry and geophysics, together with estimates of epistemic (knowledge) uncertainty, adduced from reviews of published data, modelling and from expert judgement elicitation. Several lines of evidence characterise the likely structure, magmatic composition and eruptive state of the present-day Aso volcano, which has had numerous smaller eruptions since Aso-4. To calculate the probability of another M8 eruption of Aso, we implemented probabilistic ‘Importance Sampling’ in our model. With this approach, we find the chance of an Aso-4 scale eruption (characterised by mean volume 500 km3DRE and approximate 90% credible interval [210 ‥ 1200] km3DRE) is less than 1–in–1 billion in the next 100 years (i.e., < 10− 9probability). Based on current volcanological understanding and evidence, we believe this probability estimate is secure and robust to better than an order of magnitude. 373 words
Assessment of Trace Elements in Commercially Packaged Forms of Tobacco Using Laser-induced Breakdown Spectroscopy
Authors: A Kripa Adlene Edith , Ongole Ravikiran , K. Unnikrishnan V. , K. Adarsh U. 
Published: March 2023

Abstract

BACKGROUND: Oral cancer is the most common malignancy in many developing countries such as India due to increased consumption of smokeless tobacco. Elemental components in commercially packaged forms of tobacco can play a significant role in the causation of oral cancer.
AIM: Assess trace elements in various types of commercially packaged forms of tobacco using LASER-induced breakdown spectroscopy.
MATERIALS AND METHODS: Two types of ‘Paan masala’ and four types of packaged tobacco were obtained from local ‘paan’ shops. The contents in the packets were made into pellets respectively using a hydraulic press and subjected to elemental analysis using Laser-induced breakdown spectroscopy.
RESULTS: A ten-trial experiment was carried out in all six pellets. The National Institute of Standards and Design (NIST) database was used to assess the emission lines. The elements obtained in both commercially packaged tobacco and ‘paan masala’ were similar. The elements are Calcium, Iron, Aluminium, Nickel, and Chromium.
CONCLUSION:It is known that substances that cause DNA damage and carcinogenesis, are inorganic elements such as nickel and Chromium. It is clear in our study that these carcinogens are present in the commercially packaged form of tobacco and ‘paan masala’ samples.
Bone Ingrowth Simulation within a Novel Microstructure Scaffold
Authors: Wang Yuheng , Wang Luping , Soro Nicolas , Li Zhiyong , Tetsworth Kevin , Erbulut Deniz 
Published: March 2023

Abstract
The utilization of bone scaffold implants represents a promising approach for repairing substantial bone defects. In recent years, various traditional scaffold structures have been developed and, with the advancements in materials biology and computer technology, novel scaffold designs are being evaluated. This study investigated the effects of a novel scaffold unit cell design (Hexnaoid) through a computational framework, comparing its performance to that of four well-known scaffold designs. A finite element analysis (FEA) numerical simulation and mechanical testing were conducted to analyse the dynamic bone ingrowth process and the mechanical strength of the scaffold designs, respectively. The bone formation within the Ti-6Al-4V metal scaffolds was modelled based on the theory of bone remodelling. The results indicated that the novel scaffold design (Hexnaoid) outperforms conventional unit-cell designs, achieving a high final bone occupancy (~27%) and comparable mechanical strength to that of human compact bone tissue. While the design is not optimal in every category, it presents a satisfactory overall performance in both crucial aspects of bone scaffolds among the five scaffold structures evaluated. Although limitations exist in this project, similar methodologies can still be applied in the primary evaluation of new scaffold structures, providing improved efficiency and effectiveness. In future research, the results of this project may be integrated with clinical rehabilitation processes and offering a crucial evaluation and optimization of the novel scaffold unit-cell structure design.
Potential of acetic acid to restore methane production in anaerobic reactors critically intoxicated by ammonia as evidenced by metabolic and microbial monitoring
Authors: Lemaigre Sébastien , Gerin Patrick A. , Adam Gilles , Klimek Dominika , Goux Xavier , Herold Malte , Frkova Zuzana , Calusinska Magdalena , Delfosse Philippe 
Published: March 2023

Abstract
BACKGROUND
Biogas and biomethane production from the on-farm anaerobic digestion (AD) of animal manure and agri-food wastes could play a key role in transforming Europe’s energy system by mitigating its dependence on fossil fuels and tackling the climate crisis. Although ammonia is essential for microbial growth, it inhibits the AD process if present in high concentrations, especially under its free form, thus leading to economic losses. In this study, which includes both metabolic and microbial monitoring, we tested a strategy to restore substrate conversion to methane in AD reactors facing free ammonia critical intoxication.
RESULTS
The AD process of three mesophilic semi-continuous 100L reactors critically intoxicated by free ammonia (> 3.5 g_N L_slurry− 1; interrupted hydrolysis and methanogenesis) was restored by applying a strategy that included pH correction using acetic acid, washing out total ammonia with water, re-inoculation with active microbial flora and the progressive re-introduction of sugar beet pulp, a complex organic substrate. After five weeks, two intoxicated reactors restarted the production of CH4 from the pulp hydrolysis and via hydrogenotrophic methanogenesis. The acetoclastic methanogenesis remained inhibited, probably due to the transient dominance in the slurry of a strictly methylothrophic methanogen of the archaeal genus Candidatus Methanoplasma, to the detriment of a versatile methanogen belonging to the Methanosarcina genus. Concomitantly, the third intoxicated reactor, in which the Methanosarcina members remained permanently dominant, faced transient hydrolysis inhibition but produced CH4 from restored acetoclastic methanogenesis. After eight weeks, the AD process was functional in all formerly intoxicated reactors with a pulp to CH4 conversion ratio of 0.41 ± 0.10 LN_CH4 g_VS− 1, analogous to the pulp biochemical methane potential (0.38 ± 0.03 LN_CH4 g_VS− 1).
CONCLUSIONS
Despite a particularly extreme free ammonia intoxication, the proposed process recovery strategy allowed the hydrolysis and methane production to be restored in three intoxicated reactors within eight weeks, a period during which reinitiating the feedstock supply appeared to be crucial to sustain the process. The initial introduction of acetic acid allowed substantial CH4 production during the recovery period and could enable the agronomic valorization of the effluents produced by full-scale reactors recovering from ammonia intoxication.
Isolation, characterization and In-vitro evaluation of potential probiotic lactic acid bacteria isolated from chicken gut
Authors: Melese Kasech , Alemu Tesfaye , Desalegn Asnake 
Published: March 2023

Abstract
Probiotics are live microorganisms or cultures that can benefit host health, maintain and enhance the production and growth of animals, and prevent and control enteric pathogens when given in sufficient doses. They are also one of the alternatives to antibiotic growth promoters in poultry. The current study was to isolate, characterized and evaluate lactic acid bacteria from chicken gut towards use as potential probiotics. Lactic acid bacteria were isolated from broilers and free range chickens, characterized and evaluated for their probiotic properties including antimicrobial activity against pathogens (Salmonella Typhimurium ATCC 14028, Escherichia coli ATCC 25922, Staphylococcus aureus ATCC 25923, Listeria monocytogenes (clinical isolate) and Enterococus faecalis (clinical isolate), survivability in different acidic environment, tolerance to bile salts, adhesion to chicken intestinal cell, temperature and sodium chloride tolerance. Potential lactic acid bacteria isolated from chickens with outstanding probiotic ability were identified by MALD-TOF mass spectrometer as Lactobacillus reuteri DSM 20016T (B3I13), Pediococcus pentosaccus DSM 20206(B12CA), Lactobacillus reuteri DSM 20016T(B6I3), Lactobacillus reuteri DSM 20016T(F6I8), Lactobacillus reuteri DSM 20016T (B7I05) and Pediococcus pentosaccus DSM 20206(B1I8). The selected strains inhibited all the five pathogens tested with inhibition zone ranging between 11 ± 1 to 20.33 ± 3.055mm, survived in acidic pH and 0.3% bile salt with survival rates of 94.00 to 100.00% and above (100.00%), respectively. The selected lactic acid bacteria were found to have probiotic properties that can be useful in chickens as a supplement for enteric pathogen control and performance improvement.
Association of rheumatoid arthritis with aqueous deficient dry eye development
Authors: Pena-Verdeal Hugo , Garcia-Queiruga Jacobo , Sabucedo-Villamarin Belén , Garcia-Resua Carlos , Giraldez Maria J. , Yebra-Pimentel Eva 
Published: March 2023

Abstract
Purpose: to evaluate rheumatoid arthritis (RA) as a potential risk factor for the development of aqueous deficient dry eye (ADDE) compared to evaporative dry eye (EDE).
Study Design: The study design was observational and cross-sectional.
Methods: Two hundred volunteer participants with dry eye disease (DED) were recruited based on the TFOS DEWS II criteria, which included tear film osmolarity, Fluorescein Break-Up Time, and ocular surface damage assessment. To obtain OSDI scores, demographics, and RA diagnosis by their medical doctor, participants were recruited using QR codes linked to designated mobile Forms. Tear meniscus height and lipid layer pattern were measured in all participants to differentiate between ADDE, EDE, or Mixed dry eye in addition to the DED diagnostic criteria.
Results: after the initial recruitment, a total of 113 eligible participants were included in the final analysis. The ADDE group had a higher likelihood of having RA (OR 5.65, 95% CI 1.20-26.55) compared to the EDE group. Additionally, the number of participants with RA in the ADDE group was statistically higher than those in the EDE group (Fisher's exact test, all p = 0.020). Furthermore, a correlation was obtained between RA and an ADDE differential diagnosis (Cramer's V = 0.227, p = 0.026).
Conclusion: the present study supports the hypothesis that RA could be a risk factor for the development of ADDE over EDE type.
Investigation of time dependent growth of HepG2 cancerous cells using deep learning and shape metrics
Authors: Ronickom Jac Fredo Agastinose 
Published: March 2023

Abstract
Study of growth of Human hepatocellular carcinoma cells (HepG2) cells provide useful information for clinical study of megestrol acetate for the treatment of Hepatocellular carcinoma. In this study, we analyzed the growth of HepG2 liver cancerous cells using image processing methods. Initially, the HepG2 cells were cultured and microscopic images were captured in bright field mode at time of seeding (00 h) followed by 06 h and 18 h. We segmented the cells using Tsallis and deep learning methods and the average size of colonies were calculated using shape metrics. Finally, we correlated the cell density obtained using MTT assay with the average size of colonies calculated from the Tsallis and deep learning segmented images. Results show that deep learning methods were able to segment the cells more precisely than Tsallis method. The average colony area calculated from the deep learning segmented images increases with time and concentration. The cell growth and adhesion pattern measured by deep leaning method showed good consistency with spectroscopic observations. The process pipeline provides a new way to assess cell adhesion and proliferation with capabilities in measuring their occupied surface area. The framework documented can be a promising tool to automate cancerous cell growth by evaluating average colony size for studying normal and pathological conditions.
Iodine-coated implants in prevention and treatment of surgical site infections for compromised hosts: A prospective study.
Authors: Shirai Toshiharu , Tsuchiya Hiroyuki , Terauchi Ryu , Tsuchida Shinji , Shimomura Seiji , Kajino Yoshihito , Takahashi Kenji 
Published: March 2023

Abstract
Background
Surgical site infection (SSI) is a common complication following orthopedic implantation. We developed an iodine coating for titanium implants to reduce implant-related infectionsand conducted a prospective clinical study to evaluate the efficacy and potential drawbacks of iodine-coated implants.
Patients and Methods
Between July 2008 and July 2017, 653 patients (377 male and 27 female patients; mean age, 48.6) with postoperative infection or a compromised status were treated using iodine-loaded titanium implants. The mean follow-up period was 41.7 months. In 477 patients, iodine-supported implants were used to prevent infection and in 176 patients, to treat active infection (one-stage surgery, 89 patients; two-stage surgery,87 patients). In the limbs and pelvis, the primary diagnoses included the following: 161 tumors, 92 deformities/shortening, 47 pseudarthrosis, 42 fractures, 32 infected TKA, 25 osteoarthritis, 21 pyogenic arthritis, 20 infected THA, and 6 osteomyelitis. In the spinal cases, there were 136 cases of tumors, 36 cases of pyogenic spondylitis, and 35 cases of degeneration. Five modes of implant failure were identified and classified as follows: soft tissue failure(type 1), aseptic loosening (type 2), structural failure (type 3), infection (type 4), and tumor progression (type 5).
Results
The overall failure rate in our series was 26.3% (172/653). There were 101 mechanical failures, including 22 type 1, 20 type 2, and 59 type 3 failures. Non-mechanical causes accounted for 71 failures, including 45 type 4 and 26 type 5 failures. The overall incidence of infections was 6.8%. The mean time to the onset of infection after implantation was 9.1 months. The overall infection rate was 3.7% in the prevention cases and 15.3% in the treatment cases. There was no difference between one-stage replacement (14.6%) and two-stage replacement (16.0%). There were 11 cases of treatment for SSI of spine surgery, and the re-infection rate was 0% using iodine-coated instruments.
Conclusions
The five modes of failure of the iodine-coated implant were satisfactory compared with previous reports. In particular, because the infection rate of iodine-coated implants used for compromised hosts is low compared with other methods, postoperative infection is more easily controlled. It can be considered highly effective for spinal infections that require one-stage revision surgery.
Level of Evidence: IV
Trial registration: prospective, observation study
Recommendation with Item Response Theory
Authors: Veldkamp Karel , Grasman Raoul , Molenaar Dylan 
Published: March 2023

Abstract
A popular approach to recommender systems is to factor the ratingmatrix into two low rank matrices. Although this has proven to be agood way to predict ratings, the component scores in these matrix fac-torisation methods don’t serve as estimates of the underlying causesof the ratings. We propose to model the rating matrix using Multidi-mensional Item Response Theory (MIRT). We show that MIRT doesallow for a causal interpretation of the latent scores, and additionally,allows to control the exploration-exploitation trade off using comput-erized adaptive testing (CAT). We adapt MIRT to large proportionsof missing data using elastic net regularisation. Our model is vali-dated in parameter recovery simulations, and is applied to a binarizedversion of the movielens 1M dataset. Results show that parameterscan be recovered accurately for models with up to three dimensions,for various proportions of missing data. Performance on the movielensdataset with a three dimensional MIRT model–performing is on parwith matrix factorisation methods of up to 20 dimensions. In a secondsimulation study, we show how MIRT can be combined with CAT totackle the exploration-exploitation tradeoff, resulting in more accurateitem rankings. We conclude that MIRT can provide both more inter-pretability and more control over the exploration-exploitation tradeoff.We discuss directions for future work on MIRT based recommendation.