bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prognostic factors associated with development of infected necrosis in patients with acute necrotizing or severe pancreatitis—A systematic review and meta-analysis
Authors: Tran Alexandre , Fernando Shannon M. , Rochwerg Bram , Inaba Kenji , Bertens Kimberly A. , Engels Paul T. , Balaa Fady K. , Kubelik Dalibor , Matar Maher , Lenet Tori I. , Martel Guillaume 
Published: December 2021

PURPOSE
Acute pancreatitis is a potentially life-threatening condition with a wide spectrum of clinical presentation and illness severity. An infection of pancreatic necrosis (IPN) results in a more than twofold increase in mortality risk as compared with patients with sterile necrosis. We sought to identify prognostic factors for the development of IPN among adult patients with severe or necrotizing pancreatitis.

METHODS
We conducted this prognostic review in accordance with systematic review methodology guidelines. We searched six databases from inception through March 21, 2021. We included English language studies describing prognostic factors associated with the development of IPN. We pooled unadjusted odds ratio (uOR) and adjusted odds ratios (aOR) for prognostic factors using a random-effects model. We assessed risk of bias using the Quality in Prognosis Studies tool and certainty of evidence using the GRADE approach.

RESULTS
We included 31 observational studies involving 5,210 patients. Factors with moderate or higher certainty of association with increased IPN risk include older age (uOR, 2.19; 95% confidence interval [CI], 1.39–3.45, moderate certainty), gallstone etiology (aOR, 2.35; 95% CI, 1.36–4.04, high certainty), greater than 50% necrosis of the pancreas (aOR, 3.61; 95% CI, 2.15–6.04, high certainty), delayed enteral nutrition (aOR, 2.09; 95% CI, 1.26–3.47, moderate certainty), multiple or persistent organ failure (aOR, 11.71; 95% CI, 4.97–27.56, high certainty), and invasive mechanical ventilation (uOR, 12.24; 95% CI, 2.28–65.67, high certainty).

CONCLUSION
This meta-analysis confirms the association between several clinical early prognostic factors and the risk of IPN development among patients with severe or necrotizing pancreatitis. These findings provide the foundation for the development of an IPN risk stratification tool to guide more targeted clinical trials for prevention or early intervention strategies.

LEVEL OF EVIDENCE
Systematic review and meta-analysis, Level IV.
Integrated Proteomic and Metabolomic Analyses of the Mitochondrial Neurodegenerative Disease MELAS
Authors: Li Haorong , Uittenbogaard Martine , Navarro Ryan , Ahmed Mustafa , Gropman Andrea , Chiaramello Anne , Hao Ling 
Published: December 2021

ABSTRACTMELAS (mitochondrial encephalomyopathy, lactic acidosis, stroke-like episodes) is a progressive neurodegenerative disease caused by pathogenic mitochondrial DNA variants. The pathogenic mechanism of MELAS remains enigmatic due to the exceptional clinical heterogeneity and the obscure genotype-phenotype correlation among MELAS patients. To gain insights into the pathogenic signature of MELAS, we designed a comprehensive strategy integrating proteomics and metabolomics in patient-derived dermal fibroblasts harboring the ultra-rare MELAS pathogenic variant m.14453G>A, specifically affecting the mitochondrial respiratory Complex I. Global proteomics was achieved by data-dependent acquisition (DDA) and verified by data-independent acquisition (DIA) using both Spectronaut and the recently launched MaxDIA platforms. Comprehensive metabolite coverage was achieved for both polar and nonpolar metabolites in both reverse phase and HILIC LC-MS/MS analyses. Our proof-of-principle MELAS study with multi-omics integration revealed OXPHOS dysregulation with a predominant deficiency of Complex I subunits, as well as alterations in key bioenergetic pathways, glycolysis, tricarboxylic acid cycle, and fatty acid β-oxidation. The most clinically relevant discovery is the downregulation of the arginine biosynthesis pathway, likely due to blocked argininosuccinate synthase, which is congruent with the MELAS cardinal symptom of stroke-like episodes and its current treatment by arginine infusion. In conclusion, we demonstrated an integrated proteomic and metabolomic strategy for patient-derived fibroblasts, which has great clinical potential to discover therapeutic targets and design personalized interventions after validation with a larger patient cohort in the future.Abstract FigureGraphic Abstract:Integrated proteomics and metabolomics of patient fibroblasts revealed dysregulations in arginine biosynthesis, OXPHOS complexes, and bioenergetic pathways in MELAS, a mitochondrial neurodegenerative disease caused by mitochondrial DNA mutations.
Pattern similarity in the frontoparietal control network reflects an “off-veridical” template that optimizes target-match decisions during visual search
Authors: Yu Xinger , Geng Joy J. 
Published: December 2021

AbstractTheories of attention hypothesize the existence of an “attentional” or “target” template that contains task-relevant information in memory when searching for an object. The target template contributes to visual search by directing visual attention towards potential targets and serving as a decisional boundary for target identification. However, debate still exists regarding how template information is stored in the human brain. Here, we conducted a pattern-based fMRI study to assess how template information is encoded to optimize target-match decisions during visual search. To ensure that match decisions reflect visual search demands, we used a visual search paradigm in which all distractors were linearly separable but highly similar to the target and were known to shift the target representation away from the distractor features (Yu & Geng, 2019). In a separate match-to-sample probe task, we measured the target representation used for match decisions across two resting state networks that have long been hypothesized to maintain and control target information: the frontoparietal control network (FPCN) and the visual network (VisN). Our results showed that lateral prefrontal cortex in FPCN maintained the context-dependent “off-veridical” template; in contrast, VisN encoded a veridical copy of the target feature during match decisions. By using behavioral drift diffusion modeling, we verified that the decision criterion during visual search and the probe task relied on a common biased target template. Taken together, our results suggest that sensory-veridical information is transformed in lateral prefrontal cortex into an adaptive code of target-relevant information that optimizes decision processes during visual search.
Evaluating a communication aid for return of genetic results in families with hypertrophic cardiomyopathy: A randomized controlled trial
Authors: Burns Charlotte , Yeates Laura , Sweeting Joanna , Semsarian Christopher , Ingles Jodie 
Published: December 2021

ABSTRACTIntroductionGenetic testing for hypertrophic cardiomyopathy (HCM) is considered a key aspect of management. Communication of genetic test results to the proband and their family members, can be a barrier to effective uptake. We hypothesized that a communication aid would facilitate effective communication, and sought to evaluate knowledge and communication of HCM risk to at-risk relatives.MethodsThis was a prospective randomized controlled trial. Consecutive HCM patients attending a specialized clinic, who agreed to participate, were randomized to the intervention or current clinical practice. The intervention consisted of a genetic counselorled appointment, separate to their clinical cardiology review, and guided by a communication booklet which could be written in and taken home. Current clinical practice was defined as the return of the genetic result by a genetic counselor and cardiologist, often as part of a clinical cardiology review. The primary outcome was the ability and confidence of the individual to communicate genetic results to at-risk relatives.ResultsThe a priori outcome of improved communication amongst HCM families did not show statistically significant differences between the control and intervention group, though the majority of probands in the intervention group achieved fair communication (n=13/22) and had higher genetic knowledge scores than those in the control group (7 ± 3 versus 6 ± 3). A total of 29% of at-risk relatives were not informed of a genetic result in their family.ConclusionCommunication amongst HCM families remains challenging, with nearly a third of at-risk relatives not informed of a genetic result. We show a significant gap in the current approach to supporting family communication about genetics.Australian New Zealand Clinical Trials Registry: ACTRN12617000706370What is known about this topicCommunication between family members regarding genetic testing can be a barrier to effective uptake.What this paper adds to the topicCommunication is a challenge in HCM families, with nearly a third of at-risk relatives not informed of a genetic result. There is a significant gap in the current approaches to supporting family communication about genetics.
Real-world clinical outcomes of treatment with casirivimab-imdevimab among patients with mild-to-moderate coronavirus disease 2019 during the Delta variant pandemic
Authors: Suzuki Yasuhito , Shibata Yoko , Minemura Hiroyuki , Nikaido Takefumi , Tanino Yoshinori , Fukuhara Atsuro , Kanno Ryuzo , Saito Hiroyuki , Suzuki Shuzo , Ishii Taeko , Inokoshi Yayoi , Sando Eiichiro , Sakuma Hirofumi , Kobayashi Tatsuho , Kume Hiroaki , Kamimoto Masahiro , Aoki Hideko , Takama Akira , Kamiyama Takamichi , Nakayama Masaru , Saito Kiyoshi , Tanigawa Koichi , Sato Masahiko , Kanbe Toshiyuki , Kanzaki Norio , Azuma Teruhisa , Sakamoto Keiji , Nakamura Yuichi , Otani Hiroshi , Waragai Mitsuru , Maeda Shinsaku , Ishida Tokiya , Sugino Keishi , Tsukada Yasuhiko , Yamada Ryuki , Sato Riko , Omuna Takumi , Tomita Hikaru , Saito Mikako , Watanabe Natsumi , Rikimaru Mami , Kawamata Takaya , Umeda Takashi , Morimoto Julia , Togawa Ryuichi , Sato Yuki , Saito Junpei , Kanazawa Kenya , Iseki Ken 
Published: December 2021

AbstractBackgroundMutations of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may reduce the efficacy of neutralizing monoclonal antibody therapy against coronavirus disease 2019 (COVID-19). We here evaluated the efficacy of casirivimab-imdevimab in patients with mild-to-moderate COVID-19 during the Delta variant surge in Fukushima Prefecture, Japan.MethodsWe enrolled 949 patients with mild-to-moderate COVID-19 who were admitted to hospital between July 24, 2021 and September 30, 2021. Clinical deterioration after admission was compared between casirivimab-imdevimab users (n = 314) and non-users (n = 635).ResultsThe casirivimab-imdevimab users were older (P < 0.0001), had higher body temperature (≥ 38°C) (P < 0.0001) and greater rates of history of cigarette smoking (P = 0.0068), hypertension (P = 0.0004), obesity (P < 0.0001), and dyslipidemia (P < 0.0001) than the non-users. Multivariate logistic regression analysis demonstrated that receiving casirivimab-imdevimab was an independent factor for preventing deterioration (odds ratio 0.448; 95% confidence interval 0.263–0.763; P = 0.0023). Furthermore, in 222 patients who were selected from each group after matching on the propensity score, deterioration was significantly lower among those receiving casirivimab-imdevimab compared to those not receiving casirivimab-imdevimab (7.66% vs 14.0%; p = 0.021).ConclusionThis real-world study demonstrates that casirivimab-imdevimab contributes to the prevention of deterioration in COVID-19 patients after hospitalization during a Delta variant surge.SummaryThis real-world retrospective study demonstrates the contribution of treatment with casirivimab-imdevimab to the prevention of deterioration in patients with mild-to-moderate coronavirus disease 2019 (COVID-19) even during the Delta variant pandemic.
Photothermal Dye-based Subcellular-sized Heat Spot Enabling the Modulation of Local Cellular Activities
Authors: Ferdinandus  , Suzuki Madoka , Harada Yoshie , Sarker Satya Ranjan , Ishiwata Shin’ichi , Kitaguchi Tetsuya , Arai Satoshi 
Published: December 2021

AbstractThermal engineering at microscale such as the control and measurement of temperature is a key technology in basic biological research and biomaterials development, which remains challenge yet. Here, we engineered the polymeric nanoparticle, in which a fluorescent temperature sensory dye and a photothermal dye were embedded in its polymer matrices, termed nanoHT. When a near infrared laser at 808 nm is illuminated to the particle, it enables to create the subcellular-sized heat spot in a live cell, where fluorescence thermometry allows the read out of the temperature increment concurrently at individual heat spots. Owing to the controlled local heating, we found that the cell death of HeLa cells was induced at the certain temperature at rate of a few seconds. It should be also noted that the cell death was triggered from the very local heat spot at subcellular level. Furthermore, nanoHT was applied for the induction of muscle contraction of the C2C12 myotube by heat. We successfully showed that the heat-induced contraction took place at the limited area of a single myotube according to the alteration of protein-protein interactions related to the contraction event. These studies demonstrated that even a single heat spot provided by a photothermal material could be very effective in altering cellular functions, paving the way for novel photothermal therapies.
A Parameter-free Deep Embedded Clustering Method for Single-cell RNA-seq Data
Authors: Zeng Yuansong , Wei Zhuoyi , Zhong Fengqi , Pan Zixiang , Lu Yutong , Yang Yuedong 
Published: December 2021

ABSTRACTClustering analysis is widely utilized in single-cell RNA-sequencing (scRNA-seq) data to discover cell heterogeneity and cell states. While many clustering methods have been developed for scRNA-seq analysis, most of these methods require to provide the number of clusters. However, it is not easy to know the exact number of cell types in advance, and experienced determination is not always reliable. Here, we have developed ADClust, an automatic deep embedding clustering method for scRNA-seq data, which can accurately cluster cells without requiring a predefined number of clusters. Specifically, ADClust first obtains low-dimensional representation through pre-trained autoencoder, and uses the representations to cluster cells into initial micro-clusters. The clusters are then compared in between by a statistical test, and similar micro-clusters are merged into larger clusters. According to the clustering, cell representations are updated so that each cell will be pulled toward centres of its assigned cluster and similar clusters, while cells are separated to keep distances between clusters. This is accomplished through jointly optimizing the carefully designed clustering and autoencoder loss functions. This merging process continues until convergence. ADClust was tested on eleven real scRNA-seq datasets, and shown to outperform existing methods in terms of both clustering performance and the accuracy on the number of the determined clusters. More importantly, our model provides high speed and scalability for large datasets.
Dynamic collateral sensitivity profiles highlight challenges and opportunities for optimizing antibiotic sequences
Authors: Maltas Jeff , Huynh Anh , Wood Kevin B. 
Published: December 2021

AbstractAs failure rates for traditional antimicrobial therapies escalate, recent focus has shifted to evolution-based therapies to slow resistance. Collateral sensitivity–the increased susceptibility to one drug associated with evolved resistance to a different drug–offers a potentially exploitable evolutionary constraint, but the manner in which collateral effects emerge over time is not well understood. Here, we use laboratory evolution in the opportunistic pathogen E. faecalis to phenotypically characterize collateral profiles through evolutionary time. Specifically, we measure collateral profiles for 400 strain-antibiotic combinations over the course of 4 evolutionary time points as strains are selected in increasing concentrations of antibiotic. We find that at a global level–when results from all drugs are combined–collateral resistance dominates during early phases of adaptation, when resistance to the selecting drug is lower, while collateral sensitivity becomes increasingly likely with further selection. At the level of individual populations, however, the trends are idiosyncratic; for example, the frequency of collateral sensitivity to ceftriaxone increases over time in isolates selected by linezolid but decreases is isolates selected by ciprofloxacin. Finally, we show experimentally how dynamic collateral sensitivity relationships can lead to time-dependent dosing windows that depend on finely timed switching between drugs.
Simultaneous CUT&Tag profiling of the accessible and silenced regulome in single cells
Authors: Janssens Derek H. , Otto Dominik J. , Meers Michael P. , Setty Manu , Ahmad Kami , Henikoff Steven 
Published: December 2021

SummaryCleavage Under Targets & Tagmentation (CUT&Tag) is an antibody-directed transposase tethering strategy for in situ chromatin profiling in small samples and single cells. We describe a modified CUT&Tag protocol using a mixture of an antibody to the initiation form of RNA Polymerase II (Pol2 Serine-5 phosphate) and an antibody to repressive Polycomb domains (H3K27me3) followed by computational signal deconvolution to produce high-resolution maps of both the active and repressive regulomes in single cells. The ability to seamlessly map active promoters, enhancers and repressive regulatory elements using a single workflow provides a complete regulome profiling strategy suitable for high-throughput single-cell platforms.
IL-23 signaling prevents ferroptosis-driven renal immunopathology during candidiasis
Authors: Millet Nicolas , Solis Norma V. , Aguilar Diane , Lionakis Michail S. , Wheeler Robert T. , Jendzjowsky Nicholas , Swidergall Marc 
Published: December 2021

AbstractDuring infection the host relies on pattern-recognition receptors to sense invading fungal pathogens to launch immune defense mechanisms. While fungal recognition and immune effector responses are organ and cell type specific, during disseminated candidiasis myeloid cells exacerbate collateral tissue damage. However, the complex interplay between protective antifungal immunity and immunopathology remains incompletely understood. The β-glucan receptor ephrin type-A 2 receptor (EphA2) is required to initiate mucosal inflammatory responses during oralCandidainfection. Here we report that Epha2 promotes renal immunopathology during disseminated candidiasis. EphA2 deficiency leads to reduced renal inflammation and injury. Comprehensive analyses reveal that EphA2 limits IL-23 secretion in dendritic cells, while IL-23 signaling prevents ferroptotic myeloid cell death during infection. Further, ferroptosis aggravates inflammation during infection, while at the same time reducing the fungal killing capacity of macrophages. Thus, we identify ferroptotic cell death as a critical pathway ofCandida-mediated renal immunopathology that opens a new avenue to tackleCandidainfection and inflammation.
Scellseg: a style-aware cell instance segmentation tool with pre-training and contrastive fine-tuning
Authors: Xun Dejin , Chen Deheng , Zhou Yitian , Lauschke Volker M. , Wang Rui , Wang Yi 
Published: December 2021

AbstractDeep learning-based cell segmentation is increasingly utilized in cell biology and molecular pathology, due to massive accumulation of diverse large-scale datasets and excellent progress in cell representation. However, the development of specialized algorithms has long been hampered by a paucity of annotated training data, whereas the performance of generalist algorithm was limited without experiment-specific calibration. Here, we present a deep learning-based tool called Scellseg consisted of novel pre-trained network architecture and contrastive fine-tuning strategy. In comparison to four commonly used algorithms, Scellseg outperformed others in average precision and Aggregated Jaccard Index on three disparate datasets. Interestingly, we found that eight images are sufficient for model tuning to achieve satisfied performance based on a shot data scale experiment. We also developed a graphical user interface integrated with functions of annotation, fine-tuning and inference, that allows biologists to easily specialize their self-adaptive segmentation model for analyzing images at the single-cell level.
Soil organic carbon fractionation and metagenomics pipeline to link carbon content and stability with microbial composition – First results investigating fungal endophytes
Authors: Buss Wolfram , Sharma Raghvendra , Ferguson Scott , Borevitz Justin 
Published: December 2021

AbstractSociety needs to capture gigatons of carbon dioxide from the atmosphere annually and then store it long-term to limit and ultimately reverse the effects of climate change. Bringing lost carbon back into agricultural soils should be a priority as it brings the added benefit of improving soil properties. Linking soil organic carbon (SOC) fractions of different stability with soil microbial composition can help understand and subsequently manage SOC storage. Here we develop a pipeline for evaluating the effects of microbial management on SOC content using rapid and low-cost SOC fractionation and metagenomics approaches. We tested the methods in a wheat pot trial inoculated with 17 individual endophytic fungal isolates. Two fungi increased total SOC in the area under the plant stem by ~15%. The fractionation assay showed that the medium stability soil aggregate carbon fraction (AggC) was increased by one of these fungi (+21%) and the chemically recalcitrant proportion (bleach oxidation) of AggC by the other (+35%). Both fungi increased mineral-associated organic carbon (MAOC), the long-term SOC storage, by ~10%. We used rapid, portable, low-cost, whole metagenome long read sequencing to detect a shift in the microbial composition for one of the fungi-inoculated treatments. This treatment showed a more diverse microbial community and a higher quantity of DNA in soil. The results emphasise the link between composition and abundance of soil microorganisms with soil carbon formation. Our dual carbon fractional and metagenomic analysis pipeline can be used to further test the effects of microbial management and ultimately to model the soil factors that influence SOC storage, such as nutrient and water availability, starting SOC content, soil texture and aggregation.