bluuebunny/crossref_metadata_2025_split huggingface dataset:
Corneal in vivo confocal microscopy to detect belantamab mafodotin-induced ocular toxicity early and adjust the dose accordingly: a case report
Authors: Marquant Kevin , Quinquenel Anne , Arndt Carl , Denoyer Alexandre 
Published: October 2021

Abstract
Background
New targeted antibody–drug conjugates (ADCs) against multiple myeloma are known to induce adverse effects that may lead to treatment discontinuation. Preclinical studies reported early severe ocular damage related to the use of belantamab mafodotin (belamaf), including ocular surface inflammation, severe dry eye, and a specific toxicity to the cornea, namely microcystic keratopathy. While belamaf-induced ocular changes have not been prospectively studied, a better understanding of mechanisms involved as well as kinetics may aid in anticipating dose adjustment rather than stopping the treatment once clinical ocular damage is too severe.

Case presentation
A 61-year-old woman scheduled for belamaf as a fifth-line treatment against multiple myeloma was prospectively included. Clinical examinations were performed before and every 3 weeks afterward, together with in vivo confocal microscopy (IVCM) of the cornea. Visual acuity, symptoms, slit-lamp examination, and ultrastructural changes of the cornea were recorded according to the received dose of belamaf. More precisely, kinetics, shape, density, and location of the toxic corneal lesions have been followed and analyzed using IVCM. Also, specific lesions at the sub-basal nerve plexus layer were detected and characterized for the first time. This advanced approach allowed a better understanding of the belamaf-induced toxicity, further balancing the dose to maintain good vision and eye health while continuing the treatment.

Conclusions
Systematic ultrastructural analysis and follow-up of the corneal state during ADCs treatment for multiple myeloma may open new avenues in the therapeutic approach. Early preclinical detection of ocular damage may accurately contribute to finding the correct dose for each patient and not stopping the treatment due to severe ocular adverse effects.
Deep-learning model for screening sepsis using electrocardiography
Authors: Kwon Joon-myoung , Lee Ye Rang , Jung Min-Seung , Lee Yoon-Ji , Jo Yong-Yeon , Kang Da-Young , Lee Soo Youn , Cho Yong-Hyeon , Shin Jae-Hyun , Ban Jang-Hyeon , Kim Kyung-Hee 
Published: October 2021

Abstract
Background
Sepsis is a life-threatening organ dysfunction and a major healthcare burden worldwide. Although sepsis is a medical emergency that requires immediate management, screening for the occurrence of sepsis is difficult. Herein, we propose a deep learning-based model (DLM) for screening sepsis using electrocardiography (ECG).

Methods
This retrospective cohort study included 46,017 patients who were admitted to two hospitals. A total of 1,548 and 639 patients had sepsis and septic shock, respectively. The DLM was developed using 73,727 ECGs from 18,142 patients, and internal validation was conducted using 7774 ECGs from 7,774 patients. Furthermore, we conducted an external validation with 20,101 ECGs from 20,101 patients from another hospital to verify the applicability of the DLM across centers.

Results
During the internal and external validations, the area under the receiver operating characteristic curve (AUC) of the DLM using 12-lead ECG was 0.901 (95% confidence interval, 0.882–0.920) and 0.863 (0.846–0.879), respectively, for screening sepsis and 0.906 (95% confidence interval (CI), 0.877–0.936) and 0.899 (95% CI, 0.872–0.925), respectively, for detecting septic shock. The AUC of the DLM for detecting sepsis using 6-lead and single-lead ECGs was 0.845–0.882. A sensitivity map revealed that the QRS complex and T waves were associated with sepsis. Subgroup analysis was conducted using ECGs from 4,609 patients who were admitted with an infectious disease, and the AUC of the DLM for predicting in-hospital mortality was 0.817 (0.793–0.840). There was a significant difference in the prediction score of DLM using ECG according to the presence of infection in the validation dataset (0.277 vs. 0.574, p < 0.001), including severe acute respiratory syndrome coronavirus 2 (0.260 vs. 0.725, p = 0.018).

Conclusions
The DLM delivered reasonable performance for sepsis screening using 12-, 6-, and single-lead ECGs. The results suggest that sepsis can be screened using not only conventional ECG devices but also diverse life-type ECG machines employing the DLM, thereby preventing irreversible disease progression and mortality.
Application of ensemble clustering and survival tree analysis for identifying prognostic clinicogenomic features in patients with colorectal cancer from the 100,000 Genomes Project
Authors: Wei Yuguo , Papachristou Nikolaos , Mueller Stefanie ,   Genomics England Research Consortium, Ambrose J. C. , Arumugam P. , Bleda M. , Boardman-Pretty F. , Boustred C. R. , Brittain H. , Caulfield M. J. , Chan G. C. , Fowler T. , Giess A. , Hamblin A. , Henderson S. , Hubbard T. J. P. , Jackson R. , Jones L. J. , Kasperaviciute D. , Kayikci M. , Kousathanas A. , Lahnstein L. , Leigh S. E. A. , Leong I. U. S. , Lopez F. J. , Maleady-Crowe F. , Moutsianas L. , Mueller M. , Murugaesu N. , Need A. C. , O’Donovan P. , Odhams C. A. , Patch C. , Perez-Gil D. , Pereira M. B. , Pullinger J. , Rahim T. , Rendon A. , Rogers T. , Savage K. , Sawant K. , Scott R. H. , Siddiq A. , Sieghart A. , Smith S. C. , Sosinsky A. , Stuckey A. , Tanguy M. , Thomas E. R. A. , Thompson S. R. , Tucci A. , Walsh E. , Welland M. J. , Williams E. , Witkowska K. , Wood S. M. , Chang Wai Hoong , Lai Alvina G. 
Published: October 2021

Abstract
Objective
The objective of this study was to employ ensemble clustering and tree-based risk model approaches to identify interactions between clinicogenomic features for colorectal cancer using the 100,000 Genomes Project.

Results
Among the 2211 patients with colorectal cancer (mean age of diagnosis: 67.7; 59.7% male), 16.3%, 36.3%, 39.0% and 8.4% had stage 1, 2, 3 and 4 cancers, respectively. Almost every patient had surgery (99.7%), 47.4% had chemotherapy, 7.6% had radiotherapy and 1.4% had immunotherapy. On average, tumour mutational burden (TMB) was 18 mutations/Mb and 34.4%, 31.3% and 25.7% of patients had structural or copy number mutations in KRAS, BRAF and NRAS, respectively. In the fully adjusted Cox model, patients with advanced cancer [stage 3 hazard ratio (HR)  =  3.2; p  <  0.001; stage 4 HR  =  10.2; p  <  0.001] and those who had immunotherapy (HR  =  1.8; p  <  0.04) or radiotherapy (HR  =  1.5; p  <  0.02) treatment had a higher risk of dying. The ensemble clustering approach generated four distinct clusters where patients in cluster 2 had the best survival outcomes (1-year: 98.7%; 2-year: 96.7%; 3-year: 93.0%) while patients in cluster 3 (1-year: 87.9; 2-year: 70.0%; 3-year: 53.1%) had the worst outcomes. Kaplan–Meier analysis and log rank test revealed that the clusters were separated into distinct prognostic groups (p  <  0.0001). Survival tree or recursive partitioning analyses were performed to further explore risk groups within each cluster. Among patients in cluster 2, for example, interactions between cancer stage, grade, radiotherapy, TMB, BRAF mutation status were identified. Patients with stage 4 cancer and TMB  ≥  1.6 mutations/Mb had 4 times higher risk of dying relative to the baseline hazard in that cluster.
An exploration of the sociodemographic and health conditions associated with self-rated wellbeing for Aboriginal and Torres Strait Islander adults
Authors: Gall A. , Diaz A. , Garvey G. , Anderson K. , Lindsay D. , Howard K. 
Published: October 2021

Abstract
Objective
To identify sociodemographic factors and health conditions associated with self-rated wellbeing for Aboriginal and Torres Strait Islander adults. Participants were recruited via investigator networks and an online panel provider with an established nationwide panel of Aboriginal and Torres Strait Islander adults. Those interested were invited to complete a survey that included an assessment of wellbeing using a visual analogue scale. Data was collected from October–November 2019 and August–September 2020. Exploratory analyses were conducted to ascertain factors associated with self-rated wellbeing for Aboriginal and Torres Strait Islander adults.

Results
Having more than enough money to last until next pay day, full-time employment, completion of grade 12, having a partner, and living with others were significantly associated with higher wellbeing among Aboriginal and Torres Strait Islander adults. A self-reported history of depression, anxiety, other mental health conditions, heart disease, or disability were associated with lower self-rated wellbeing scores. Our findings indicate a need for further investigation among these socioeconomic and patient groups to identify how to improve and support the wellbeing of Aboriginal and Torres Strait Islander adults.
DNA methylation profiling identifies two distinct subgroups in breast cancers with low hormone receptor expression, mainly associated with HER2 amplification status
Authors: Jurmeister Philipp , Weber Karsten , Villegas Sonia , Karn Thomas , Untch Michael , Thieme Anne , Müller Volkmar , Taube Eliane , Fasching Peter , Schmitt Wolfgang D. , Marmé Frederik , Stickeler Elmar , Sinn Bruno V. , Jank Paul , Schem Christian , Klauschen Frederick , van Mackelenbergh Marion , Denkert Carsten , Loibl Sibylle , Capper David 
Published: October 2021

Abstract
Background
Current clinical guidelines suggest that breast cancers with low hormone receptor expression (LowHR) in 1–10% of tumor cells should be regarded as hormone receptor positive. However, clinical data show that these patients have worse outcome compared to patients with hormone receptor expression above 10%. We performed DNA methylation profiling on 23 LowHR breast cancer specimens, including 13 samples with HER2 amplification and compared our results with a reference breast cancer cohort from The Cancer Genome Atlas to clarify the status for this infrequent but important patient subgroup.

Results
In unsupervised clustering and dimensionality reduction, breast cancers with low hormone receptor expression that lacked HER2 amplification usually clustered with triple negative breast cancer (TNBC) reference samples (8/10; “LowHR TNBC-like”). In contrast, most specimens with low hormone receptor expression and HER2 amplification grouped with hormone receptor positive cancers (11/13; “LowHR HRpos-like”). We observed highly similar DNA methylation patterns of LowHR TNBC-like samples and true TNBCs. Furthermore, the Ki67 proliferation index of LowHR TNBC-like samples and clinical outcome parameters were more similar to TNBCs and differed from LowHR HRpos-like cases.

Conclusions
We here demonstrate that LowHR breast cancer comprises two epigenetically distinct groups. Our data strongly suggest that LowHR TNBC-like samples are molecularly, histologically and clinically closely related to TNBC, while LowHR HRpos-like specimens are closely related to hormone receptor positive tumors.
Automated fragment formula annotation for electron ionisation, high resolution mass spectrometry: application to atmospheric measurements of halocarbons
Authors: Guillevic Myriam , Guillevic Aurore , Vollmer Martin K. , Schlauri Paul , Hill Matthias , Emmenegger Lukas , Reimann Stefan 
Published: October 2021

AbstractBackgroundNon-target screening consists in searching a sample for all present substances, suspected or unknown, with very little prior knowledge about the sample. This approach has been introduced more than a decade ago in the field of water analysis, together with dedicated compound identification tools, but is still very scarce for indoor and atmospheric trace gas measurements, despite the clear need for a better understanding of the atmospheric trace gas composition. For a systematic detection of emerging trace gases in the atmosphere, a new and powerful analytical method is gas chromatography (GC) of preconcentrated samples, followed by electron ionisation, high resolution mass spectrometry (EI-HRMS). In this work, we present data analysis tools to enable automated fragment formula annotation for unknown compounds measured by GC-EI-HRMS.ResultsBased on co-eluting mass/charge fragments, we developed an innovative data analysis method to reliably reconstruct the chemical formulae of the fragments, using efficient combinatorics and graph theory. The method does not require the presence of the molecular ion, which is absent in$$\sim$$∼40% of EI spectra. Our method has been trained and validated on >50 halocarbons and hydrocarbons, with 3–20 atoms and molar masses of 30–330 g mol$$^{-1}$$-1, measured with a mass resolution of approx. 3500. For >90% of the compounds, more than 90% of the annotated fragment formulae are correct. Cases of wrong identification can be attributed to the scarcity of detected fragments per compound or the lack of isotopic constraint (no minor isotopocule detected).ConclusionsOur method enables to reconstruct most probable chemical formulae independently from spectral databases. Therefore, it demonstrates the suitability of EI-HRMS data for non-target analysis and paves the way for the identification of substances for which no EI mass spectrum is registered in databases. We illustrate the performances of our method for atmospheric trace gases and suggest that it may be well suited for many other types of samples. The L-GPL licenced Python code is released under the name ALPINAC for ALgorithmic Process for Identification of Non-targeted Atmospheric Compounds.
Automated liver lesion detection in 68Ga DOTATATE PET/CT using a deep fully convolutional neural network
Authors: Wehrend Jonathan , Silosky Michael , Xing Fuyong , Chin Bennett B. 
Published: October 2021

Abstract
Background
Gastroenteropancreatic neuroendocrine tumors most commonly metastasize to the liver; however, high normal background 68Ga-DOTATATE activity and high image noise make metastatic lesions difficult to detect. The purpose of this study is to develop a rapid, automated and highly specific method to identify 68Ga-DOTATATE PET/CT hepatic lesions using a 2D U-Net convolutional neural network.

Methods
A retrospective study of 68Ga-DOTATATE PET/CT patient studies (n = 125; 57 with 68Ga-DOTATATE hepatic lesions and 68 without) was evaluated. The dataset was randomly divided into 75 studies for the training set (36 abnormal, 39 normal), 25 for the validation set (11 abnormal, 14 normal) and 25 for the testing set (11 abnormal, 14 normal). Hepatic lesions were physician annotated using a modified PERCIST threshold, and boundary definition by gradient edge detection. The 2D U-Net was trained independently five times for 100,000 iterations using a linear combination of binary cross-entropy and dice losses with a stochastic gradient descent algorithm. Performance metrics included: positive predictive value (PPV), sensitivity, F1 score and area under the precision–recall curve (PR-AUC). Five different pixel area thresholds were used to filter noisy predictions.

Results
A total of 233 lesions were annotated with each abnormal study containing a mean of 4 ± 2.75 lesions. A pixel filter of 20 produced the highest mean PPV 0.94 ± 0.01. A pixel filter of 5 produced the highest mean sensitivity 0.74 ± 0.02. The highest mean F1 score 0.79 ± 0.01 was produced with a 20 pixel filter. The highest mean PR-AUC 0.73 ± 0.03 was produced with a 15 pixel filter.

Conclusion
Deep neural networks can automatically detect hepatic lesions in 68Ga-DOTATATE PET. Ongoing improvements in data annotation methods, increasing sample sizes and training methods are anticipated to further improve detection performance.
A blockchain index structure based on subchain query
Authors: Xing Xiaogang , Chen Yuling , Li Tao , Xin Yang , Sun Hongwei 
Published: October 2021

AbstractBlockchain technology has the characteristics of decentralization and tamper resistance, which can store data safely and reduce the cost of trust effectively. However, the existing blockchain system has weak performance in data management, and only supports traversal queries with transaction hashes as keywords. The query method based on the account transaction trace chain (ATTC) improves the query efficiency of historical transactions of the account. However, the efficiency of querying accounts with longer transaction chains has not been effectively improved. Given the inefficiency and single method of the ATTC index in the query, we propose a subchain-based account transaction chain (SCATC) index structure. First, the account transaction chain is divided into subchains, and the last block of each subchain is connected by a hash pointer. The block-by-block query mode in ATTC is converted to the subchain-by-subchain query mode, which shortens the query path. Multiple transactions of the same account in the same block are merged and stored, which simplifies the construction cost of the index and saves storage resources. then, the construction algorithm and query algorithm is given for the SCATC index structure. Simulation analysis shows that the SCATC index structure significantly improves query efficiency.
Biosynthesis of ethyl caffeate via caffeoyl-CoA acyltransferase expression in Escherichia coli
Authors: Lee Shin-Won , Kim Han , Ahn Joong-Hoon 
Published: October 2021

AbstractHydroxycinnamic acids (HCs) are natural compounds that form conjugates with diverse compounds in nature. Ethyl caffeate (EC) is a conjugate of caffeic acid (an HC) and ethanol. It has been found in several plants, including Prunus yedoensis, Polygonum amplexicaule, and Ligularia fischeri. Although it exhibits anticancer, anti-inflammatory, and antifibrotic activities, its biosynthetic pathway in plants still remains unknown. This study aimed to design an EC synthesis pathway and clone genes relevant to the same. Genes involved in the caffeic acid synthesis pathway (tyrosine ammonia-lyase (TAL) and p-coumaric acid hydroxylase (HpaBC)) were introduced into Escherichia coli along with 4-coumaroyl CoA ligase (4CL) and acyltransferases (AtCAT) cloned from Arabidopsis thaliana. In presence of ethanol, E. coli harboring the above genes successfully synthesized EC. Providing more tyrosine through the overexpression of shikimate-pathway gene-module construct and using E. coli mutant enhanced EC yield; approximately 116.7 mg/L EC could be synthesized in the process. Synthesis of four more alkyl caffeates was confirmed in this study; these might potentially possess novel biological properties, which would require further investigation.
Exome sequencing implicates a novel heterozygous missense variant in DSTYK in autosomal dominant lower urinary tract dysfunction and mild hereditary spastic paraparesis
Authors: Vidic Clara , Zaniew Marcin , Jurga Szymon , Thiele Holger , Reutter Heiko , Hilger Alina C. 
Published: October 2021

Abstract
Introduction
DSTYK encodes dual serine/threonine and tyrosine protein kinase. DSTYK has been associated with autosomal-dominant congenital anomalies of the kidney and urinary tract and with autosomal-recessive hereditary spastic paraplegia type 23. Here, we report a father and his two dizygotic twin sons carrying a novel heterozygous missense variant in DSTYK, presenting with early onset lower urinary tract dysfunction due to dysfunctional voiding. Moreover, in the later course of the disease, both sons presented with bilateral spasticity in their lower limbs, brisk reflexes, and absence seizures.

Materials and methods
Exome sequencing in the affected father and his affected sons was performed. The sons presented clinically with urinary hesitancy, dysfunctional voiding, and night incontinence till adolescence, while the father reported difficulty in voiding. In the sons, cystoscopy excluded urethral valves and revealed hypertrophy of the bladder neck and trabeculated bladder. Additionally, both sons were diagnosed with absence epilepsy in early childhood. Filtering of exome data focused on rare (MAF < 0.01%), autosomal-dominant variants, predicted to be deleterious, residing in highly conserved regions of the exome.

Results
Exome analysis identified a novel, heterozygous missense variant (c.271C>A (p.Leu91Met)) in DSTYK segregating with the disease. In silico prediction analyses uniformly rated the variant to be deleterious suggesting the variant to be disease-causing in the family.

Conclusion
To the best of our knowledge, this is the first report of early onset dysfunctional voiding, seizures, and bilateral spasticity of the lower limbs associated with a novel heterozygous dominant missense variant in DSTYK.
Perceived quality of life and associated factors among patients with severe mental illness in Ethiopia: a cross-sectional study
Authors: Shumye Seid , Amare Tadele , Derajew Habtamu , Endris Merdia , Molla Wondwosen , Mengistu Nebiyu 
Published: October 2021

Abstract
Background
Severe mental illness is strongly associated with an impaired quality of life. This intern can affect the treatment adherence and outcomes of the illness. However, there are insufficient studies in the literature pertaining to the quality of life of patients with severe mental illness in Ethiopia. Therefore, assessing the quality of life of patients with severe mental illness and its correlates is a yardstick measure of the effectiveness of the mental health service.

Methods
An institutional based cross-sectional study was conducted from May 1 to 16, 2019 at Amanuel Mental Specialized Hospital. A systematic random sampling technique was used to get a total number of 387 samples. Data were collected using interview-administered questionnaires; World Health Organization Quality of Life Brief Version, Morisky Medication Adherence Screening Tool, Oslo Social Support Scale, and Jacoby Stigma Scale. Simple and multiple linear regression analysis were used to assess the contributing factors of quality of life in the participants and B coefficient with 95% CI confidence interval was used. The statistical significance was accepted at p value < 0.05.

Results
The result showed that the Mean quality of life score of patients with severe mental illness for each domain (mean ± SD) was 41.3 ± 7.5, 42.8 ± 8.2, 38.9 ± 8.9, and 41.8 ± 6.5 for physical, psychological, social and environmental, respectively. Multiple regression analysis showed that age of participants was strongly positively correlated with all domains of quality of life. It predicts above 45% of the variability in each domain. Social support is also another strong predictor which was negatively correlated with all domains of quality of life, except physical.

Conclusion
This study revealed that the mean score quality of life of patients with severe mental illness in each domain was low. This demonstrates a need for improving the quality of life of people with severe mental illness by integration of a positive mental health approach and bio-psychosocial view with biological treatment of severe mental illness. Moreover, in Collaboration with medical professionals, people with severe mental illness should screen and managed for any comorbid medical conditions.