bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of a Machine Learning Model Using Limited Features to Predict 6-Month Mortality at Treatment Decision Points for Patients With Advanced Solid Tumors
Authors: Chalkidis George , McPherson Jordan , Beck Anna , Newman Michael , Yui Shuntaro , Staes Catherine 
Published: April 2022

PURPOSE Patients with advanced solid tumors may receive intensive treatments near the end of life. This study aimed to create a machine learning (ML) model using limited features to predict 6-month mortality at treatment decision points (TDPs). METHODS We identified a cohort of adults with advanced solid tumors receiving care at a major cancer center from 2014 to 2020. We identified TDPs for new lines of therapy (LoTs) and confirmed mortality at 6 months after a TDP. Using extreme gradient boosting, ML models were developed, which used or derived features from a limited set of electronic health record data considering the literature, clinical relevance, variability, availability, and predictive importance using Shapley additive explanations scores. We predicted and observed 6-month mortality after a TDP and assessed a risk stratification strategy with different risk thresholds to support communication of chance of survival. RESULTS Four thousand one hundred ninety-two patients were included. Patients had 7,056 TDPs, for which the 6-month mortality increased from 17.9% to 46.7% after starting first to sixth LoT, respectively. On the basis of internal validation, models using both 111 (Full) or 45 (Limited-45) features accurately predicted 6-month mortality (area under the curve ≥ 0.80). Using a 0.3 risk threshold in the Limited-45 model, the observed 6-month survival was 34% (95% CI, 28 to 40) versus 81% (95% CI, 81 to 82) among those classified with low or higher chance of survival, respectively. The positive predictive value of the Limited-45 model was 0.66 (95% CI, 0.60 to 0.72). CONCLUSION We developed and validated a ML model using a limited set of 45 features readily derived from electronic health record data to predict 6-month prognosis in patients with advanced solid tumors. The model output may support shared decision making as patients consider the next LoT.
Integration of Infant Metabolite, Genetic, and Islet Autoimmunity Signatures to Predict Type 1 Diabetes by Age 6 Years
Authors: Webb-Robertson Bobbie-Jo M , Nakayasu Ernesto S , Frohnert Brigitte I , Bramer Lisa M , Akers Sarah M , Norris Jill M , Vehik Kendra , Ziegler Anette-G , Metz Thomas O , Rich Stephen S , Rewers Marian J 
Published: April 2022

Abstract

Context
Biomarkers that can accurately predict risk of type 1 diabetes (T1D) in genetically predisposed children can facilitate interventions to delay or prevent the disease.

Objective
This work aimed to determine if a combination of genetic, immunologic, and metabolic features, measured at infancy, can be used to predict the likelihood that a child will develop T1D by age 6 years.

Methods
Newborns with human leukocyte antigen (HLA) typing were enrolled in the prospective birth cohort of The Environmental Determinants of Diabetes in the Young (TEDDY). TEDDY ascertained children in Finland, Germany, Sweden, and the United States. TEDDY children were either from the general population or from families with T1D with an HLA genotype associated with T1D specific to TEDDY eligibility criteria. From the TEDDY cohort there were 702 children will all data sources measured at ages 3, 6, and 9 months, 11.4% of whom progressed to T1D by age 6 years. The main outcome measure was a diagnosis of T1D as diagnosed by American Diabetes Association criteria.

Results
Machine learning–based feature selection yielded classifiers based on disparate demographic, immunologic, genetic, and metabolite features. The accuracy of the model using all available data evaluated by the area under a receiver operating characteristic curve is 0.84. Reducing to only 3- and 9-month measurements did not reduce the area under the curve significantly. Metabolomics had the largest value when evaluating the accuracy at a low false-positive rate.

Conclusion
The metabolite features identified as important for progression to T1D by age 6 years point to altered sugar metabolism in infancy. Integrating this information with classic risk factors improves prediction of the progression to T1D in early childhood.
Monitoring of inflammation using novel biosensor mouse model reveals tissue- and sex-specific responses to Western diet
Authors: Talley Sarah , Bonomo Raiza , Gavini Chaitanya , Hatahet Jomana , Gornick Emily , Cook Tyler , Chun Byeong Jae , Kekenes-Huskey Pete , Aubert Gregory , Campbell Edward , Mansuy-Aubert Virginie 
Published: April 2022

ABSTRACT
Obesity is an epidemic, and it is characterized by a state of low-grade systemic inflammation. A key component of inflammation is the activation of inflammasomes, multiprotein complexes that form in response to danger signals and that lead to activation of caspase-1. Previous studies have found that a Westernized diet induces activation of inflammasomes and production of inflammatory cytokines. Gut microbiota metabolites, including the short-chain fatty acid butyrate, have received increased attention as underlying some obesogenic features, but the mechanisms of action by which butyrate influences inflammation in obesity remain unclear. We engineered a caspase-1 reporter mouse model to measure spatiotemporal dynamics of inflammation in obese mice. Concurrent with increased capsase-1 activation in vivo, we detected stronger biosensor signal in white adipose and heart tissues of obese mice ex vivo and observed that a short-term butyrate treatment affected some, but not all, of the inflammatory responses induced by Western diet. Through characterization of inflammatory responses and computational analyses, we identified tissue- and sex-specific caspase-1 activation patterns and inflammatory phenotypes in obese mice, offering new mechanistic insights underlying the dynamics of inflammation.
Predicting selection–response gradients of heat tolerance in a widespread reef-building coral
Authors: Weeriyanun Ponchanok , Collins Rachael B. , Macadam Alex , Kiff Hugo , Randle Janna L. , Quigley Kate M. 
Published: April 2022

ABSTRACT
Ocean temperatures continue to rise owing to climate change, but it is unclear whether heat tolerance of marine organisms will keep pace with warming. Understanding how tolerance scales from individuals to species and quantifying adaptive potentials is essential to forecasting responses to warming. We reproductively crossed corals from a globally distributed species (Acropora tenuis) on the Great Barrier Reef (Australia) from three thermally distinct reefs to create 85 offspring lineages. Individuals were experimentally exposed to temperatures (27.5, 31 and 35.5°C) in adult and two critical early life stages (larval and settlement) to assess acquired heat tolerance via outcrossing of offspring phenotypes by comparing five physiological responses (photosynthetic yields, bleaching, necrosis, settlement and survival). Adaptive potentials and physiological reaction norms were calculated across three stages to integrate heat tolerance at different biological scales. Selective breeding improved larval survival to heat by 1.5–2.5× but did not result in substantial enhancement of settlement, although population crosses were significantly different. Under heat stress, adults were less variable compared with larval responses in warmer reefs than in the cooler reef. Adults and offspring also differed in their mean population responses, likely underpinned by heat stress imposing strong divergent selection on adults. These results have implications for downstream selection during reproduction, evidenced by variability in a conserved heat tolerance response across offspring lineages. These results inform our ability to forecast the impacts of climate change on wild populations of corals and will aid in developing novel conservation tools such as the assisted evolution of at-risk species.
Observation on the clinical efficacy of external ventricular drain combined with intraventricular urokinase injection and intravenous piracetam in the treatment of intraventricular hemorrhage
Authors: Cui Jing , Ma Xin-lei , Tong Jian-zhou , Shu Min 
Published: April 2022

Objective: To observe the clinical efficacy of external ventricular drain combined with intraventricular urokinase injection and intravenous piracetam in the treatment of intraventricular hemorrhage.
Methods: A randomized controlled trial was used in this study conducted at Baoding First Central Hospital, China from January 2017 to December 2019. Sixty patients with intraventricular hemorrhage were randomly divided into two groups. Patients in the control group were treated with external ventricular drain, while patients in the experimental group were given intraventricular urokinase injection and intravenous piracetam on the basis of the control group. The incidence of adverse drug reactions, hospitalization time, hematoma elimination time, and drainage tube removal time in two groups were compared and analyzed including the cerebrospinal fluid protein content, changes in GCS score, neurological function recovery (ADL score), and Glasgow outcome scale (GOS) of the two groups after treatment.
Results: The hematoma elimination time, drainage tube removal time and hospitalization time of the experimental group were shorter than those of the control group, with a statistically significant difference (P<0.05). After treatment, compared with the control group, the protein content of cerebrospinal fluid in the experimental group decreased more significantly (P=0.00), the GCS score was higher (P=0.00), the overall good rate of neurological function was higher (P=0.04), while the rate of good prognosis was higher (P=0.03). Within one month of treatment, the incidence of surgical complications in experimental group was significantly lower than that in control group (P=0.04).
Conclusions: External ventricular drain combined with intraventricular urokinase injection and intravenous piracetam is an effective method for the treatment of intraventricular hemorrhage, which is worthy of clinical promotion.
doi: https://doi.org/10.12669/pjms.38.5.4820
How to cite this:Cui J, Ma X, Tong J, Shu M. Observation on the clinical efficacy of external ventricular drain combined with intraventricular urokinase injection and intravenous piracetam in the treatment of intraventricular hemorrhage. Pak J Med Sci. 2022;38(5):---------. doi: https://doi.org/10.12669/pjms.38.5.4820
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Seasonal variation and severity of Diabetic Ketoacidosis in patients at a tertiary care hospital in Pakistan
Authors: Babar Bakht , Aamir Azizul Hasan 
Published: April 2022

Objectives: To asses the seasonal variability in the hospital admissions of Diabetic Ketoacidosis (DKA) patients.
Methods: This two year retrospective analysis was carried out from first November 2018 to 31st OCTOBER 2020, which involved medical chart reviewing of all those patients admitted to the Department of Diabetes, Endocrinology and Metabolic diseases, Hayatabad Medical complex, Peshawar, Pakistan with confirmed DKA. Data related to patient demography, past history, biochemical profile and treatment was collected and analysed using SPSS version 25.
Results: During the above mentioned 24 months, 104 diabetic patients with confirmed DKA were admitted. Fifty-nine (57%) patients were male. Most of the patients had moderate DKA that is 42(40%). Seasonality was observed with majority of the patient admitted in winter season overall 62(60%). In both the years encounter with DKA patient peaked in January. DKA was found to be more severe in female and in age group 10-15 years. DKA severity was found to be significantly associated with age, gender, previous episodes of DKA, length of hospital stay and non compliance plus infection (p<0.05).
Conclusion: We found seasonal variation and peaked cases of DKA in the winter season presenting at a tertiary care hospital in Pakistan. Noncompliance was found to be major contributory factor.
doi: https://doi.org/10.12669/pjms.38.5.5227
How to cite this:Babar B, Aamir AH. Seasonal variation and severity of Diabetic Ketoacidosis in patients at a tertiary care hospital in Pakistan. Pak J Med Sci. 2022;38(5):---------. doi: https://doi.org/10.12669/pjms.38.5.5227
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Variable-Rate Fertigation Control for Hydroponics Using an On-The-Go Transpiration Monitoring System
Authors: Cho Woo-Jae , Kim Hak-Jin , Jung Dae Hyun , Kim Dong-Wook , Yi Yoon-Hong , Jang Gyu-jin 
Published: April 2022

HighlightsAn on-the-go monitoring system was developed for assessing spatial and temporal variations in crop growth.The system was used to realize real-time transpiration estimation for lettuce growth.A variable-rate fertigation system was developed based on on-the-go transpiration monitoring.The variable-rate fertigation system was validated in controlled-environment cultivation of hydroponic lettuce.Abstract. Variable-rate fertigation, as a key component of hydroponic cultivation, ensures the sustainable use of water. However, this fertigation method is challenging to implement because of the difficulty associated with assessing the water needs of plants, which vary with plant growth stage and environmental conditions. In this study, an on-the-go crop growth monitoring system was developed to measure the canopy cover of lettuce plants on a daily basis. The canopy cover during the vegetative growth period could be estimated with an accuracy of 98.5% ±1.7% compared to manual segmentation. A modified Penman-Monteith equation was used to predict the transpiration rate of the lettuce plants. In the first cultivation test, the transpiration rate model exhibited a highly linear relationship with a slope of 0.91, coefficient of determination of &gt;0.9, and standard error of regression of &lt;0.51, compared to the directly measured transpiration rates. In the second cultivation test, an automated system that could variably control the fertigation volume was incorporated with the on-the-go system for monitoring the lettuce transpiration in real time. The proposed system could realize on-the-go mapping of the spatial distribution of the canopy cover of the growing lettuce plants, and the variable fertigation responded to the daily water consumption of the plants with an error of only 7.3%. Moreover, the stable canopy cover growth indicated the higher efficiency of variable fertigation compared to timer-based fertigation systems. The proposed variable-rate fertigation system is a promising and practical approach to implement hydroponics with reduced water and energy consumption. Keywords: Canopy cover, Hydroponic, On-the-go monitoring, Transpiration, Variable fertigation.
Crop Improvement for Circular Bioeconomy Systems
Authors: Messina Carlos D. , van Eeuwijk Fred , Tang Tom , Truong Sandra K. , McCormick Ryan F. , Technow Frank , Powell Owen , Mayor Laura , Gutterson Neal , Jones James W. , Hammer Graeme L. , Cooper Mark 
Published: April 2022

HighlightsWe describe and demonstrate a multidimensional framework to integrate environmental and genomic predictors to enable crop improvement for a circular bioeconomy.A model training procedure based on multiple phenotypes is shown to improve predictive skill.The decision set comprised of model outputs can inform selection for both productivity and circularity metrics.Abstract. Contemporary agricultural systems are poised to transition from linear to circular, adopting concepts of recycling, repurposing, and regeneration. This transition will require changing crop improvement objectives to consider the entire system, and thus provide solutions to improve complex systems for higher productivity, resource use efficiency, and environmental quality. The methods and approaches that underpinned the doubling of yields during the last century may no longer be fully adequate to target crop improvement for circular agricultural systems. Here we propose a multidimensional framework for prediction with outcomes useful to assess both crop performance traits and environmental sustainability of the designed agricultural systems. The study focuses on maize harvestable grain yield and total carbon production, water use, and use efficiency for yield and carbon. The framework builds on the crop growth model whole genome prediction system, which is enabled by advanced phenomics and the integration of symbolic and sub-symbolic artificial intelligence. We demonstrate the approach and prediction accuracy advantages over a standard statistical genomic prediction approach used to breed maize hybrids for yield, flowering time, and kernel set using a dataset comprised of 7004 hybrids, 103 breeding populations, and 62 environments resulting from six years of experimentation in maize drought breeding in the U.S. We propose this framework to motivate a dialogue for how to enable circularity in agriculture through prediction-based systems design. Keywords: Circular bioeconomy, Circular economy, Crop improvement, Crop models, Drought, Gene editing, Genomic prediction, Maize, Plant breeding.
Constructing and expressing acyl-homoserine lactone lactonase (aiiA) gene for enhancing Solanum tuberosum resistance against soft rot disease
Authors: SURYANTI ERMA , RUSMANA IMAN , WAHYUDI ARIS TRI , AKHDIYA ALINA , SUKMADJAJA DEDEN 
Published: April 2022

Abstract. Suryanti E, Rusamana I, Wahyudi AT, Akhdiya A, Sukamdjaja D. 2022. Constructing and expressing acyl-homoserine lactone lactonase (aiiA) gene for enhancing Solanum tuberosum resistance against soft rot disease. Biodiversitas 23: 1780-1787. Expression of the genes associated with pectinase production in soft rot disease of Dickeya spp. are regulated by quorum sensing mechanism using acyl homoserine lactone(AHL). Degradation of AHL using AHL lactonase can be developed to reduce pectinase production in Dickeyaspp.The aiiA gene encodes AHL lactonase from Bacillus spp. This study aims to construct binary vector of inserted aiiA gene (pCAB10) from Bacillus cereus B10 and express the aiiA gene in potato Medians cultivar genome. The aiiAgene was cloned into binary vector and transformed into Agrobacterium tumefaciens LB4404. The Agrobacterium-mediated genetic transformation was conducted with co-cultivation technique.The transgenic plant was confirmed through PCR andselected through kanamycin and soft rot disease resistance to Dickeya dadantii A3. The result showed that aiiA gene was successfully integrated top CAB10 and introduced to A. tumefaciens LB4404. The percentage of pCAB10 transformation was 57.6%, while there generation efficiency was 11.9% with 50 mg/L acetosyringone addition. Four transgenic potato Medians cultivar exhibited significantly higher resistance against soft rot disease than non-transgenic plants. Mahl1 clone had the highest resistance to D. dadantii with soft rot disease incidence as 7.1% and percentage of soft rot disease suppression as 92.85%.
Evaluation of agronomic and fruit quality traits of miraculin transgenic tomato
Authors: CARSONO NONO , DESIANA NIA , NURRIZQI FERI M. , ELFAKHRIANO IQBAL F. , ANAS ANAS , SARI SANTIKA , KUSUMIYATI KUSUMIYATI , OHSAWA RYO , SHIMONO AYAKO , EZURA HIROSHI 
Published: April 2022

Abstract. Carsono N, Desiana N, Nurrizqi FM, Elfakhriano IF, Anas, Sari S, Kusumiyati, Ohsawa R, Shimono A, Ezura H. 2022. Evaluation of agronomic and fruit quality traits of miraculin transgenic tomato. Biodiversitas 23: 2004-2009. Tomato cv. Moneymaker has been inserted with miraculin gene which can modify sour taste becomes sweet in the human tongue and, thus, it has potential as a sweetener. Evaluation of agronomic and fruit quality traits for this special transgenic tomato is a major concern that should be performed as substantial equivalence. The study's objective was to compare agronomic and fruit quality traits of transgenic miraculin tomato with those of its wild-type. The experiment employed a randomized block design, one genotype factor with two levels (transgenic vs. non-transgenic tomato cv. Moneymaker), and each was four replicates. Data were subjected to the Student t-test. The study revealed no significant differences between the transgenic tomato plants cv. Moneymaker and the wild type for important agronomic traits such as plant height, stem diameter, leaf area index, fruit weight, fruit weight per cluster, fruit weight per plant, fruit diameter, number of fruits per cluster, number of fruits per plant, and harvest index of miraculin. Some fruit quality traits such as fruit shelf-life, fruit hardness, total soluble solids, and content of glucose, sucrose, and fructose were equivalent to those of its counterpart, suggesting that miraculin transgene did not affect the expression of the observed traits. The miraculin transgenic tomato traits were more likely identical to those of wild-type except for the existence of the miraculin transgene. This will open the possibility for this special transgenic tomato to undergo further environmental safety assessment in the field test facility as a part of the biosafety assessment of genetically modified organism (GMO).
The composition of fatty acids in several vegetable oils from Indonesia
Authors: RAHMAN HAMIDAH , SITOMPUL JOHNNER P. , TJOKRODININGRAT SURYATI 
Published: April 2022

Abstract. Rahman H, Sitompul JP, Tjokrodiningrat S. 2022. The composition of fatty acids in several vegetable oils from Indonesia. Biodiversitas 23: 2167-2176. Fatty acids are generally incorporated into a triglyceride structure in vegetable oils and this indicates vegetable oils are a source of fatty acids. Fatty acids and triglycerides are fatty groups commonly known to have a detrimental effect on health but have an important role in terms of nutrition, health, and are also a source of industrial raw materials. Therefore, this study was conducted to identify the composition of fatty acids in several edible vegetable oils which are quite widely available in Indonesia such as coconut oil, palm kernel oil, palm oil, nutmeg oil, cinnamon oil, and canarium oil. The fatty acids profile of these vegetable oils was determined using high-performance liquid chromatography while the composition was determined by comparing the peaks in each vegetable oil with the standard fatty acids. It was discovered that all the six vegetable oils contain fatty acids with different compositions, and this signifies the availability of a complete variety of fatty acids in Indonesia. Moreover, the highest fatty acid content in coconut oil and palm kernel oil was found to be lauric acid with a concentration of 49.00% and 49.25% respectively while the contents in palm oil include palmitic acid with 44.00% and oleic acid with 41.00%. The nutmeg oil was dominated by myristic acid with 78.00%, cinnamon oil by stearic acid with 50.16%, and canarium oil by oleic acid with 51.71%. Furthermore, the concentration range for all the vegetable oils includes 14.66-91.20% saturated, 6.30-52.31% monounsaturated, and 1.35-33.03% polyunsaturated fatty acids. These results can be used as a source of information in the process of utilizing fatty acids and triglycerides in vegetable oils, and also provide the data required to estimate the nutritional value of the plant biodiversity originating from Indonesia.