bluuebunny/crossref_metadata_2025_split huggingface dataset:
Network meta‐analysis of the analgesic effectiveness of regional anaesthesia techniques for anterior cruciate ligament reconstruction
Authors: Hussain N. , Brull R. , Vannabouathong C. , Speer J. , Lagnese C. , McCartney C. J. L. , Abdallah F. W. 
Published: November 2022

SummaryAnterior cruciate ligament reconstruction can cause moderate to severe acute postoperative pain. Despite advances in our understanding of knee innervation, consensus regarding the most effective regional anaesthesia techniques for this surgical population is lacking. This network meta‐analysis compared effectiveness of regional anaesthesia techniques used to provide analgesia for anterior cruciate ligament reconstruction. Randomised trials examining regional anaesthesia techniques for analgesia following anterior cruciate ligament reconstruction were sought. The primary outcome was opioid consumption during the first 24 h postoperatively. Secondary outcomes were: rest pain at 0, 6, 12 and 24 h; area under the curve of pain over 24 h; and opioid‐related adverse effects and functional recovery. Network meta‐analysis was conducted using a frequentist approach. A total of 57 trials (4069 patients) investigating femoral nerve block, sciatic nerve block, adductor canal block, local anaesthetic infiltration, graft‐donor site infiltration and systemic analgesia alone (control) were included. For opioid consumption, all regional anaesthesia techniques were superior to systemic analgesia alone, but differences between regional techniques were not significant. Single‐injection femoral nerve block combined with sciatic nerve block had the highest p value probability for reducing postoperative opioid consumption and area under the curve for pain severity over 24 h (78% and 90%, respectively). Continuous femoral nerve block had the highest probability (87%) of reducing opioid‐related adverse effects, while local infiltration analgesia had the highest probability (88%) of optimising functional recovery. In contrast, systemic analgesia, local infiltration analgesia and adductor canal block were each poor performers across all analgesic outcomes. Regional anaesthesia techniques that target both the femoral and sciatic nerve distributions, namely a combination of single‐injection nerve blocks, provide the most consistent analgesic benefits for anterior cruciate ligament reconstruction compared with all other techniques but will most likely impair postoperative function. Importantly, adductor canal block, local infiltration analgesia and systemic analgesia alone each perform poorly for acute pain management following anterior cruciate ligament reconstruction.
The impact of preservation and recovery of renal function on survival after veno‐arterial extracorporeal life support: A retrospective cohort study
Authors: Prasad Amit , Brehm Christoph , Singbartl Kai 
Published: November 2022

AbstractBackgroundVeno‐arterial extracorporeal life support (V‐A ECLS) has become a cornerstone in the management of critical cardiogenic shock, but it can also precipitate organ injury, e.g., acute kidney injury (AKI). Available studies highlight the effect of non‐cardiac organ injury on patient outcomes. Only very little is known about the impact of non‐cardiac organ recovery on patient survival. AKI occurs frequently during cardiogenic shock and carries a poor prognosis. We have developed descriptive models to hypothesize on the role of AKI severity versus that of recovery of renal function for patient survival.MethodsRetrospective, observational study including 175 patients who were successfully decannulated from V‐A ECLS. We assessed AKI severity using the “Kidney Disease: Improving Global Outcomes” (KDIGO) criteria. We defined recovered or preserved renal function (RPRF) prior to decannulation from V‐A ECLS as 0 (AKI with no improvement) or 1 (no AKI or AKI with improvement). We classified patient outcomes as alive or dead at hospital discharge.Results78% (n = 138) of all patients survived hospital discharge of which 38% (n = 67) never developed AKI. After adjusting for shock severity and non‐renal organ injury, RPRF emerged as an independent predictor of survival in both the overall cohort [OR (95% CI) – 4.11 (1.72–9.79)] and the AKI‐only sub‐cohort [OR (95% CI) – 5.18 (1.8–14.92)]. Neither maximum KDIGO stage nor KDIGO stage at the end of V‐A ECLS was independently associated with survival.ConclusionsOur model identifies RPRF, but not AKI severity, as an independent predictor of hospital survival in patients undergoing V‐A ECLS for cardiogenic shock. We hypothesize that recovered or preserved non‐cardiac organ function during V‐A ECLS is crucial for patient survival.
Changes in dental and medical visits before and during the COVID‐19 pandemic among U.S. children aged 1–17 years
Authors: Karande Sharvari , Chong Gabriel Tse Feng , Megally Hayam , Parmar Digvijaysinh , Taylor George W. , Obadan‐Udoh Enihomo Mary , Agaku Israel Terungwa 
Published: November 2022

AbstractObjectivesThe COVID‐19 pandemic has tremendously impacted the U.S. healthcare system, but no study has examined the impact of the pandemic on utilization of dental care among U.S. children. Changes in past‐year dental versus medical visits and perceived unmet health needs between 2019 and 2020 among U.S. children aged 1–17 years were examined.MethodsNational and state representative, cross‐sectional data from the National Survey of Children's Health conducted during June 2019–January 2020 (i.e. pre‐pandemic, n = 28 500) and July 2020–January 2021 (i.e. intra‐pandemic, n = 41 380) were analysed. Any past‐year visit and perceived unmet needs (i.e. delay or inability to receive needed care) were reported by the parent proxy. Weighted prevalence estimates were compared using two‐tailed chi‐squared tests at p < .05. Poisson regression analyses were used to explore the relationship between having dental and/or medical unmet needs during the pandemic and indicators of poor health and social wellbeing.ResultsBetween 2019 and 2020, a significantly reduced prevalence of past‐year medical (87.2%–81.3%) and dental visits (82.6%–78.2%) among U.S. children aged 1–17 years (all p < .05) were observed. Correspondingly, perceived unmet needs increased by half for dental care (from 2.9% in 2019 to 4.4% in 2020) and almost one‐third for medical care (from 3.2% to 4.2% in 2020). Subgroups with the highest prevalence of unmet dental need included those with low socio‐economic status, living with their grandparents, uninsured and living with a smoker.ConclusionsUnmet health needs increased in general but increased more for dental than for medical care among U.S. children aged 1–17 years. Enhanced and sustained efforts will be needed to deliver targeted services towards disadvantaged segments of the population to narrow existing disparities.
First‐in‐human study of deucravacitinib: A selective, potent, allosteric small‐molecule inhibitor of tyrosine kinase 2
Authors: Catlett Ian M. , Aras Urvi , Hansen Lars , Liu Yali , Bei Di , Girgis Ihab G. , Murthy Bindu 
Published: November 2022

AbstractThis randomized, double‐blind, single‐ and multiple‐ascending dose study assessed the pharmacokinetics (PKs), pharmacodynamics, and safety of deucravacitinib (Sotyktu™), a selective and potent small‐molecule inhibitor of tyrosine kinase 2, in 100 (75 active, 25 placebo) healthy volunteers (NCT02534636). Deucravacitinib was rapidly absorbed, with a half‐life of 8–15 h, and 1.4–1.9‐fold accumulation after multiple dosing. Deucravacitinib inhibited interleukin (IL)‐12/IL‐18‐induced interferon (IFN)γ production ex vivo in a dose‐ and concentration‐dependent manner. Following in vivo challenge with IFNα‐2a, deucravacitinib demonstrated dose‐dependent inhibition of lymphocyte count decreases and expression of 53 IFN‐regulated genes. There were no serious adverse events (AEs); the overall frequency of AEs was similar in the deucravacitinib (64%) and placebo (68%) groups. In this first‐in‐human study, deucravacitinib inhibited IL‐12/IL‐23 and type I IFN pathways in healthy volunteers, with favorable PK and safety profiles. Deucravacitinib is a promising therapeutic option for immune‐mediated diseases, including Crohn's disease, psoriasis, psoriatic arthritis, and systemic lupus erythematosus.
A novel method to assess copy number variation in melanoma: Droplet digital PCR for precise quantitation of the RREB1 gene in formalin‐fixed, paraffin‐embedded melanocytic neoplasms, a proof‐of‐concept study
Authors: O'Hern Keegan , Barney Rachael , Chambers Meagan , Baker Catherine , Stevanovic Mirjana , Tsongalis Gregory J. , Hughes Edward , Sriharan Aravindhan 
Published: November 2022

AbstractBackgroundMelanocytic neoplasms can be challenging to diagnose. One well‐established diagnostic aid is the detection of copy number variation (CNV) in a few key genetic loci using conventional methods such as fluorescence in situ hybridization (FISH) and chromosomal microarray (CMA). Droplet digital polymerase chain reaction (ddPCR) is a novel, cost‐effective, rapid, and automated method to detect CNV.MethodsWe perform the first investigation of ddPCR to assay Ras‐responsive element‐binding protein‐1 (RREB1), the most common CNV in melanoma using formalin‐fixed, paraffin‐embedded (FFPE) melanocytic lesion samples; CMA data are used as the gold standard. Archival samples from 2013 to 2021 were analyzed, including 153 data points from 39 FFPE samples representing 34 patients. Benign, borderline, malignant, and metastatic melanocytic neoplasms were examined.ResultsddPCR showed a sensitivity and specificity of 93.8% and 95.7% using one reference gene, and 87.5% and 100% using a different reference gene for RREB1 gain detection.ConclusionsHere we show that ddPCR can provide inexpensive, rapid, and robust data on the commonest copy number alteration in melanoma. Future development and validation could provide a useful ancillary tool in the diagnosis of challenging melanocytic lesions.
Revisiting the hymenopteran diploid male vortex: a review of avoidance mechanisms and incidence
Authors: Leung Kelley , van der Meulen Henk 
Published: November 2022

AbstractAll hymenopterans (bees, ants, wasps, and sawflies) have haplodiploid sex determination. Generally, this involves haploid males developing from unfertilized eggs and diploid females developing from fertilized eggs, but diploid male production (DMP) frequently occurs. Some species have complementary sex determination (CSD), in which heterozygotes of a csd locus or loci are diploid females, hemizygotes are haploid males, and homozygotes are typically sterile diploid males. These diploid males underlie the diploid male vortex (DMV), the phenomenon of inbreeding reducing csd allelic diversity and causing increasingly higher production of sterile diploid males until the population dies out. The DMV has been cited as an extinction risk for many species across the order and a danger to both human‐controlled and natural hymenopteran populations important in biological control, pollination, and endangered species conservation. However, it has been unclear how frequently it occurs. We review the known mechanisms for DMV avoidance. Many of these mechanisms are linked to lifestyle, and so we structure our investigation around eusocial lifestyle and non‐eusocial (solitary or gregarious) species. We also review documented DMV incidence to make an inference about its prevalence. There are many means to avoid inbreeding or diploid male production, including eusocial‐exclusive polygyny, polyandry, and diploid queen execution. For both eusocial and non‐eusocial species these include biological mechanisms such as multi‐locus CSD or non‐CSD sex determination, diploid male inviability or brood removal, partial diploid male fecundity, and mating avoidance of kin or diploid males; or population genetic mechanisms such as gene flow and dispersal, balancing selection of csd alleles (with some being more prominent in eusocial vs. non‐eusocial species). Documented cases of DMV are uncommon, and incidence is often tied to exacerbatory conditions such as habitat fragmentation and host declines. With this review we suggest that due to numerous avoidance mechanisms, DMV risk may not be as high as previously believed, and requires specific circumstances. In doing so we aim to better inform hymenopteran breeding and conservation efforts.
Determining the potential use of biosurfactants in preventing endodontic infections
Authors: Hashim Zahraa Amer , Maillard Jean‐Yves , Wilson Melanie Jay , Waddington Rachel Jane 
Published: November 2022

AbstractMicrobial biofilms play a dominant role in the failure of endodontic therapies. Bacterial adhesion is the first step in the establishment of biofilms, activating the host immune response leading to tissue damage. Biosurfactants are microbe‐derived tensioactive molecules with latent anti‐adhesive and anti‐microbial activity. This study reports the extraction and characterization of a biosurfactant from Lactobacillus (L.) plantarum (Lp‐BS) and investigates its anti‐microbial and anti‐adhesive properties compared to rhamnolipid, a commercially available biosurfactant. Lp‐BS, extracted from L. plantarum during the growth phase, was characterized as a glycoprotein, able to reduce surface tension and emulsify non‐polar liquids. Proteomic analysis of Lp‐BS identified three bacterial adhesin‐like proteins, suggesting roles in hindering bacterial adhesion. Lp‐BS did not show significant anti‐microbial activity against endodontic pathogens from the Streptococcus (Strep.) anginosus group or Enterococcus (Ent.) faecalis at 50 mg/ml. However, anti‐adhesive activity on abiotic surfaces was observed against both Strep. anginosus and Strep. intermedius. Rhamnolipid exhibited strong anti‐microbial activity, with minimum inhibitory concentrations of 0.097 mg/ml against Strep. anginosus, and 0.048 mg/ml against Strep. constellatus and Strep. intermedius, in addition to a marked anti‐adhesive activity. These findings offer preliminary evidence for the potential application of biosurfactants as an anti‐microbial and/or anti‐adhesive pharmacotherapy in endodontics.
Limited gains in native parasitoid performance on an invasive host beyond three generations of selection
Authors: Linder Shelley , Jarrett Benjamin J. M. , Fanning Philip , Isaacs Rufus , Szűcs Marianna 
Published: November 2022

AbstractCo‐evolved natural enemies provide sustainable and long‐term control of numerous invasive insect pests, but the introduction of such enemies has declined sharply due to increasing regulations. In the absence of co‐evolved natural enemies, native species may attack exotic invasive pests; however, they usually lack adaptations to control novel hosts effectively. We investigated the potential of two native pupal parasitoids,Pachycrepoideus vindemmiaeandTrichopria drosophilae, to increase their developmental success on the invasiveDrosophila suzukii. Replicated populations of the two parasitoids were subjected to 10 generations of laboratory selection onD. suzukiiwithDrosophila melanogasterserving as the co‐evolved host. We assessed developmental success of selected and control lines in generations 0, 3, and 10. Changes in host preference, sex ratio, development time, and body size were measured to evaluate correlated responses with adaptation. Both parasitoid species responded rapidly to selection by significantly increasing their developmental success on the novel host within three generations, which remained constant for seven additional generations without further improvement. The generalist parasitoid speciesP. vindemmiaewas able to reach similar developmental success as the control populations, while the performance of the more specialized parasitoidT. drosophilaeremained lower on the novel than on the co‐evolved host. There was no increase in preference towards the novel host over 10 generations of selection nor were there changes in development time or body size associated with adaptation in either parasitoid species. The sex ratio became less female‐biased for both parasitoids after three generations of selection but rebounded inP. vindemmiaeby generation 10. These results suggest that a few generations of selection may be sufficient to improve the performance of native parasitoids on invasive hosts, but with limits to the degree of improvement for managing invasive pests when exotic co‐evolved natural enemies are not available.
Enhancement of clustering techniques by coupling clustering tree and neural network: Application to brain tumour segmentation
Authors: Osadebey Michael , Pedersen Marius , Kalra Meeta , Waaler Dag , Bouguila Nizar 
Published: November 2022

AbstractCurrently, no classical clustering algorithm is efficient on its own. The predefined number of clusters required for their operation does not consistently produce satisfactory segmentation results. They exhibit cluster instability, are vulnerable to the local optimum trap, and are sensitive to noise and imaging artefacts. Most contributions designed to overcome these drawbacks incorporate prior knowledge such as cluster label information and statistic measures that demand minimal labelled training data. Although these approaches improve the segmentation accuracy, they tend to diminish the advantages of clustering algorithms over the supervised learning methods. This study proposes a shift from the use of a predefined number of clusters to a clustering tree‐based method for performance enhancement of classical clustering algorithms. The proposed method is a three‐stage algorithm. It begins with the extraction of low‐level features from a clustering tree. Clustering trees are sets of labelled clusters of an image at multiple clustering resolutions. The second stage extracts high‐level features by coupling the clustering tree to a single‐layer feedforward neural network. The third stage is the classification stage, where the basic model of a neural network extracts the tumour from a high‐level feature map. Because neither of the neural networks requires training, the proposed method is both fully unsupervised and fully automated and retains all its advantages over supervised methods. A performance evaluation using FLAIR MRI images of brain tumour patients from the BRATS2015 and BRATS2020 databases demonstrates significant performance enhancement over four classical clustering algorithms and two of the four proposed techniques were comparable to deep learning methods.
COVID‐19 detection based on pre‐trained deep networks and LSTM model using X‐ray images enhanced contrast with artificial bee colony algorithm
Authors: Er Mehmet Bilal 
Published: November 2022

AbstractCoronavirus (COVID‐19) is an infectious disease that has spread across the world within a short period of time and is causing rapid casualties. The main symptoms of this virus are shortness of breath, fever, cough, and a sore throat. The virus is detected through samples, such as throat swabs and sputum, taken from people who meet the possible case definition and the results are usually obtained within a few hours or a day. The development of test kits to detect the COVID‐19 virus is still an open research topic, and automated and faster diagnostic tools are needed. Recent studies have shown that biomedical images can be used for COVID‐19 testing. This study proposes the hybrid use of pre‐trained deep networks and the long short‐term memory (LSTM) for the classification of COVID‐19 from contrast‐enhanced chest X‐rays. In the proposed system, a transformation function is applied to X‐ray images first. Then, the artificial bee colony (ABC) algorithm is used to optimize the parameters obtained from the transformation function. The pre‐trained deep network models and LSTM are preferred to extract features from the contrast‐enhanced chest X‐rays. At the final stage, COVID‐19, normal (healthy), and pneumonia chest X‐ray are classified using softmax. To evaluate the performance of the proposed method, the “COVID‐19 radiography” dataset, which is widely used in the literature, is preferred. From the proposed model, 98.97% accuracy, 98.80% precision, and 98.70% sensitivity rates are obtained. Experimental results reveal that the proposed model provides efficient results compared to other methods. Thanks to the application of ABC‐based image enhancement, increased classification of 2.5% has been achieved against other state‐of‐the‐art models.
RETRACTED: Adoption of blockchain + Internet of Things in demand forecasting of farm supply chain
Authors: Wang Hao , Liu Tao , Yu Zhongyang 
Published: November 2022

AbstractIt aims to improve the application efficiency of modern science and technology in farm operation, enhance the prediction effect of machine learning and blockchain technology on farm supply and demand issues, and help enterprise managers to better manage and operate enterprise projects. First, the agricultural super business model under the blockchain + Internet of Things (IoT) is analysed, and the farm management system of the IoT + blockchain is constructed. Then, the demand forecasting model of agricultural products is established. Autoregressive Integrated Moving Average model (ARIMA) and Support Vector Machine (SVM) models are used to predict demand. Finally, the characteristics of the two models in prediction are discussed. The results show that the ARIMA model can reach 99.2% in the application efficiency evaluation of farm operation. Moreover, in the case of proper selection of model indicators, the prediction result is close to the actual value, the prediction error fluctuation is small, and the maximum error value is 0.4318. The local error of SVM model in predicting the demand of farm supply chain is slightly larger, and the maximum error value is 8.5430. By comparing the error results of the two models, the prediction accuracy of ARIMA model is higher than that of SVM model. The ARIMA model designed in this work can provide effective product demand prediction for farm operation and provide a strong technical reference for farm operation. The research not only provides technical support for machine learning and blockchain technology to predict farm supply and demand, but also contributes to the integrated management and sustainable development of enterprises.