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Article: Utility of NICaS Non-Invasive Hemodynamic Monitoring in Critically Ill Patients with COVID-19.

Zabeeda, Wisam / Cohen, Jonah Benjamin / Reiner Benaim, Anat / Zarour, Shiri / Lichter, Yael / Matot, Idit / Goren, Or

2024 Volume 13, Issue 7

Abstract: 1) ...

Abstract	(1)
Language	English
Publishing date	2024-04-03
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662592-1
ISSN	2077-0383
ISSN	2077-0383
DOI	10.3390/jcm13072072
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Response by Szekely et al to Letters Regarding Article, "Spectrum of Cardiac Manifestations in COVID-19: A Systematic Echocardiographic Study".

Szekely, Yishay / Lichter, Yael / Topilsky, Yan

Circulation

2021 Volume 143, Issue 9, Page(s) e753–e754

MeSH term(s)	COVID-19 ; Echocardiography ; Heart ; Humans ; SARS-CoV-2
Language	English
Publishing date	2021-03-01
Publishing country	United States
Document type	Letter ; Comment
ZDB-ID	80099-5
ISSN	1524-4539 ; 0009-7322 ; 0069-4193 ; 0065-8499
ISSN (online)	1524-4539
ISSN	0009-7322 ; 0069-4193 ; 0065-8499
DOI	10.1161/CIRCULATIONAHA.120.051635
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Article ; Online: Temperature interruptions harm the quality of stored 'Rustenburg' navel oranges and development of dynamic shelf-life prediction models

Owoyemi, Abiola / Holder, Tamar / Porat, Ron / Lichter, Amnon / Koenigstein, Noam / Salzer, Yael

Postharvest Biology and Technology. 2023 Oct., v. 204 p.112458-

2023

Abstract: The optimal temperature for postharvest storage of 'Rustenburg' navel oranges is 5 ºC, and any deviations from this temperature may harm fruit quality. The goals of the current study were to examine the effects of different temperature interruptions on ... ...

Abstract	The optimal temperature for postharvest storage of 'Rustenburg' navel oranges is 5 ºC, and any deviations from this temperature may harm fruit quality. The goals of the current study were to examine the effects of different temperature interruptions on the quality of stored 'Rustenburg' navel oranges, and to develop a dynamic fruit-quality prediction model that takes into account any deviations from the optimal storage temperature. The temperature interruptions included exposures to a temperature of 22 ºC for different lengths of time (1, 3 or 7 d) at different time points during the cold-storage period (after 4, 8 or 12 w). The experiment included 126 cartons of 30 fruit each, which were stored under different temperature-interruption regimes. Quality evaluations were conducted every 4 w during a prolonged storage period of up to 24 w. Storage time appeared to be the most important feature affecting fruit quality, followed by the length and the timing of the temperature interruptions. Statistical analysis revealed that storage time significantly affected most of the examined quality parameters; whereas the duration and timing of the temperature interruptions significantly affected fruit weight loss, firmness, internal dryness, shriveling, flavor and quality-acceptance scores. Overall, the longer the temperature interruptions and the later during storage they were applied, the more harmful they were for fruit quality. The collected data was further used to develop dynamic quality-prediction models. It was found that an extreme gradient boosting (XGBoost) model allowed the prediction of fruit acceptance score on a scale of 1–5 with a root mean square error (RMSE) of 0.233 and R² of 0.876. The XGBoost model also effectively predicted fruit quality at various fictive data points within and outside the tested data set, including different durations and timings of temperature interruptions during the cold-storage period. Dynamic quality-prediction models that consider storage interruptions will assist in assuring produce quality and reducing food losses.
Keywords	Biological Sciences ; cold storage ; data collection ; firmness ; flavor ; fruit quality ; fruit weight ; fruits ; models ; postharvest storage ; prediction ; shelf life ; statistical analysis ; storage temperature ; storage time ; weight loss ; Cold chain ; Modelling ; Orange ; Postharvest ; Temperature interruptions ; XGBoost
Language	English
Dates of publication	2023-10
Publishing place	Elsevier B.V.
Document type	Article ; Online
ZDB-ID	1082798-5
ISSN	1873-2356 ; 0925-5214
ISSN (online)	1873-2356
ISSN	0925-5214
DOI	10.1016/j.postharvbio.2023.112458
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Article: Sour rot in the vineyard is an indicator of Botrytis rot in grapes after storage

Owoyemi, Abiola / Lapidot, Or / Kochanek, Bettina / Zahavi, Tirtza / Salzer, Yael / Porat, Ron / Lichter, Amnon

Postharvest biology and technology. 2022 Sept., v. 191

2022

Abstract: At harvest, table grape clusters may seem intact but can suffer from unacceptable levels of decay by Botrytis cinerea after storage. Sour rot is a disease complex that initiates from cracked or injured berries in which yeast and acetic acid bacteria ... ...

Abstract	At harvest, table grape clusters may seem intact but can suffer from unacceptable levels of decay by Botrytis cinerea after storage. Sour rot is a disease complex that initiates from cracked or injured berries in which yeast and acetic acid bacteria develop, and the disease is propagated by Drosophila flies. Initial results from storage of grapes with and without microcracks showed that the latter had a low level of postharvest decay. Evaluation of the incidence of sour rot in nine Vitis vinifera cv. Scarlotta vineyards showed a range of 2–41% after veraison and 27–83% on day of harvest. Clusters from those vineyards that were free of sour rot symptoms were stored for 9 weeks with SO₂ sheets followed by 3 d of shelf life. Decay levels after storage ranged from 3% to 15%, with the highest incidence of decay encountered in grapes from vineyards with the highest level of sour rot at harvest. The correlation coefficient between the sour rot index and Botrytis decay after storage was 0.32 and 0.25 for the evaluations at veraison and harvest, respectively, with significant P values. Further strengthening of these results was obtained by sampling of two vineyards with low and high incidence of sour rot that displayed a 10-fold reduction in Botrytis decay after storage. These results suggest that sour rot in the vineyard can be an important indicator for decay development during storage.
Keywords	Botrytis cinerea ; Drosophila ; Vitis vinifera ; acetic acid ; postharvest diseases ; ripening ; shelf life ; table grapes ; technology ; vineyards ; yeasts
Language	English
Dates of publication	2022-09
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	1082798-5
ISSN	1873-2356 ; 0925-5214
ISSN (online)	1873-2356
ISSN	0925-5214
DOI	10.1016/j.postharvbio.2022.111980
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Article: Large-Scale, High-Throughput Phenotyping of the Postharvest Storage Performance of 'Rustenburg' Navel Oranges and the Development of Shelf-Life Prediction Models.

Owoyemi, Abiola / Porat, Ron / Lichter, Amnon / Doron-Faigenboim, Adi / Jovani, Omri / Koenigstein, Noam / Salzer, Yael

Foods (Basel, Switzerland)

2022 Volume 11, Issue 13

Abstract: We conducted a large-scale, high-throughput phenotyping analysis of the effects of various pre-harvest and postharvest features on the quality of ‘Rustenburg’ navel oranges, in order to develop shelf-life prediction models to enable the use of the First ... ...

Abstract	We conducted a large-scale, high-throughput phenotyping analysis of the effects of various pre-harvest and postharvest features on the quality of ‘Rustenburg’ navel oranges, in order to develop shelf-life prediction models to enable the use of the First Expired, First Out logistics strategy. The examined pre-harvest features included harvest time and yield, and the examined postharvest features included storage temperature, relative humidity during storage and duration of storage. All together, we evaluated 12,000 oranges (~4 tons) from six different orchards and conducted 170,576 measurements of 14 quality parameters. Storage time was found to be the most important feature affecting fruit quality, followed by storage temperature, harvest time, yield and humidity. The examined features significantly affected (p < 0.001) fruit weight loss, firmness, decay, color, peel damage, chilling injury, internal dryness, acidity, vitamin C and ethanol levels, and flavor and acceptance scores. Four regression models were evaluated for their ability to predict fruit quality based on pre-harvest and postharvest features. Extreme gradient boosting (XGBoost) combined with a duplication approach was found to be the most effective approach. It allowed for the prediction of fruit-acceptance scores among the full data set, with a root mean square error (RMSE) of 0.217 and an R2 of 0.891.
Language	English
Publishing date	2022-06-22
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2704223-6
ISSN	2304-8158
ISSN	2304-8158
DOI	10.3390/foods11131840
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Article ; Online: Chloroquine-induced torsades de pointes in a patient with coronavirus disease 2019.

Szekely, Yishay / Lichter, Yael / Shrkihe, Bander Abu / Bruck, Hila / Oster, Howard S / Viskin, Sami

Heart rhythm

2020 Volume 17, Issue 9, Page(s) 1452–1455

MeSH term(s)	Aged, 80 and over ; Antimalarials/adverse effects ; Betacoronavirus ; COVID-19 ; Chloroquine/adverse effects ; Coronavirus Infections/complications ; Coronavirus Infections/diagnosis ; Coronavirus Infections/drug therapy ; Female ; Humans ; Pandemics ; Pneumonia, Viral/complications ; Pneumonia, Viral/diagnosis ; Pneumonia, Viral/drug therapy ; SARS-CoV-2 ; Torsades de Pointes/chemically induced ; Torsades de Pointes/diagnosis
Chemical Substances	Antimalarials ; Chloroquine (886U3H6UFF)
Keywords	covid19
Language	English
Publishing date	2020-05-05
Publishing country	United States
Document type	Case Reports ; Journal Article
ZDB-ID	2229357-7
ISSN	1556-3871 ; 1547-5271
ISSN (online)	1556-3871
ISSN	1547-5271
DOI	10.1016/j.hrthm.2020.04.046
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Article ; Online: Kinetics of C-reactive protein during extracorporeal membrane oxygenation.

Lichter, Yael / Gal Oz, Amir / Carmi, Uri / Adi, Nimrod / Nini, Asaph / Angel, Yoel / Nevo, Andrey / Aviram, Daniel / Moshkovits, Itay / Goder, Noam / Stavi, Dekel

The International journal of artificial organs

2023 Volume 47, Issue 1, Page(s) 41–48

Abstract: Background: The exposure of blood to the artificial circuit during extracorporeal membrane oxygenation (ECMO) can induce an inflammatory response. C-reactive protein (CRP) is a commonly used biomarker of systemic inflammation.: Methods: In this ... ...

Abstract	Background: The exposure of blood to the artificial circuit during extracorporeal membrane oxygenation (ECMO) can induce an inflammatory response. C-reactive protein (CRP) is a commonly used biomarker of systemic inflammation. Methods: In this retrospective observational study, we analyzed results of daily plasma CRP measurements in 110 critically ill patients, treated with ECMO. We compared CRP levels during the first 5 days of ECMO operation, between different groups of patients according to ECMO configurations, Coronavirus disease 2019 (COVID-19) status, and mechanical ventilation parameters. Results: There was a statistically significant decrease in CRP levels during the first 5 days of veno-venous (VV) ECMO (173 ± 111 mg/L, 154 ± 107 mg/L, 127 ± 97 mg/L, 114 ± 100 mg/L and 118 ± 90 mg/L for days 1-5 respectively, Conclusions: We observed a significant decrease in CRP levels during the first 5 days of VV ECMO support, and suggest that the concomitant reduction in ventilatory MP may have mitigated the degree of alveolar stress and strain that could have contributed to a decrease in the systemic inflammatory process.
MeSH term(s)	Humans ; Extracorporeal Membrane Oxygenation/adverse effects ; Extracorporeal Membrane Oxygenation/methods ; C-Reactive Protein ; COVID-19 ; Inflammation/etiology ; Retrospective Studies
Chemical Substances	C-Reactive Protein (9007-41-4)
Language	English
Publishing date	2023-11-29
Publishing country	United States
Document type	Observational Study ; Journal Article
ZDB-ID	80456-3
ISSN	1724-6040 ; 0391-3988
ISSN (online)	1724-6040
ISSN	0391-3988
DOI	10.1177/03913988231213511
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Article ; Online: Two-hour indirect calorimetry measurement as a predictor of 24-hour energy expenditure in critically ill surgical patients: A longitudinal study.

Lichter, Yael / Sold, Oded / Angel, Yoel / Nizri, Eran / Gerstenhaber, Fabian / Gal Oz, Amir / Stavi, Dekel / Nini, Asaph / Singer, Pierre / Goder, Noam

JPEN. Journal of parenteral and enteral nutrition

2023 Volume 47, Issue 7, Page(s) 896–903

Abstract: Background: Measuring energy expenditure (EE) by indirect calorimetry (IC) has become the gold standard tool for critically ill patients to define energy targets and tailor nutrition. Debate remains as to the optimal duration of measurements or the ... ...

Abstract	Background: Measuring energy expenditure (EE) by indirect calorimetry (IC) has become the gold standard tool for critically ill patients to define energy targets and tailor nutrition. Debate remains as to the optimal duration of measurements or the optimal time of day in which to perform IC. Methods: In this retrospective longitudinal study, we analyzed results of daily continuous IC in 270 mechanically ventilated, critically ill patients admitted to the surgical intensive care unit in a tertiary medical center and compared measurements performed at different hours of the day. Results: A total of 51,448 IC hours was recorded, with an average 24-h EE of 1523 ± 443 kcal/day. Night shift (00:00-8:00) was found to have significantly lower EE measurements (mean, 1499 ± 439 kcal/day) than afternoon (16:00-00:00; mean, 1526 ± 435 kcal/day) and morning (8:00-16:00; mean, 1539 ± 462 kcal/day) measurements (P < 0.001 for all). The bi-hourly time frame that most closely resembled the daily mean was 18:00-19:59, with a mean of 1521 ± 433 kcal/day. Daily EE measurements of the continuous IC at days 3-7 of admission showed a trend toward a daily increase in 24-h EE, but the difference was not statistically significant (P = 0.081). Conclusions: Periodic measurements of EE can differ slightly when performed at various hours of the day, but the error range is small and may not necessarily have a clinical impact. When continuous IC is not available, a 2-h EE measurement between 18:00 and 19:59 can serve as a reasonable alternative.
MeSH term(s)	Humans ; Longitudinal Studies ; Retrospective Studies ; Calorimetry, Indirect/methods ; Critical Illness ; Respiration, Artificial ; Energy Metabolism
Language	English
Publishing date	2023-07-18
Publishing country	United States
Document type	Journal Article
ZDB-ID	800861-9
ISSN	1941-2444 ; 0148-6071
ISSN (online)	1941-2444
ISSN	0148-6071
DOI	10.1002/jpen.2545
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Article: Large-Scale, High-Throughput Phenotyping of the Postharvest Storage Performance of ‘Rustenburg’ Navel Oranges and the Development of Shelf-Life Prediction Models

Owoyemi, Abiola / Porat, Ron / Lichter, Amnon / Doron-Faigenboim, Adi / Jovani, Omri / Koenigstein, Noam / Salzer, Yael

Foods. 2022 June 22, v. 11, no. 13

2022

Abstract	We conducted a large-scale, high-throughput phenotyping analysis of the effects of various pre-harvest and postharvest features on the quality of ‘Rustenburg’ navel oranges, in order to develop shelf-life prediction models to enable the use of the First Expired, First Out logistics strategy. The examined pre-harvest features included harvest time and yield, and the examined postharvest features included storage temperature, relative humidity during storage and duration of storage. All together, we evaluated 12,000 oranges (~4 tons) from six different orchards and conducted 170,576 measurements of 14 quality parameters. Storage time was found to be the most important feature affecting fruit quality, followed by storage temperature, harvest time, yield and humidity. The examined features significantly affected (p < 0.001) fruit weight loss, firmness, decay, color, peel damage, chilling injury, internal dryness, acidity, vitamin C and ethanol levels, and flavor and acceptance scores. Four regression models were evaluated for their ability to predict fruit quality based on pre-harvest and postharvest features. Extreme gradient boosting (XGBoost) combined with a duplication approach was found to be the most effective approach. It allowed for the prediction of fruit-acceptance scores among the full data set, with a root mean square error (RMSE) of 0.217 and an R² of 0.891.
Keywords	acidity ; ascorbic acid ; color ; data collection ; ethanol ; firmness ; flavor ; fruit quality ; fruit weight ; harvest date ; phenotype ; postharvest storage ; prediction ; relative humidity ; shelf life ; storage temperature ; storage time ; weight loss
Language	English
Dates of publication	2022-0622
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2704223-6
ISSN	2304-8158
ISSN	2304-8158
DOI	10.3390/foods11131840
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Article: Evaluation of the Storage Performance of ‘Valencia’ Oranges and Generation of Shelf-Life Prediction Models

Owoyemi, Abiola / Porat, Ron / Lichter, Amnon / Doron-Faigenboim, Adi / Jovani, Omri / Koenigstein, Noam / Salzer, Yael

Horticulturae. 2022 June 22, v. 8, no. 7

2022

Abstract: We conducted a large-scale, high-throughput phenotyping analysis of the effects of various preharvest and postharvest features on the quality of ‘Valencia’ oranges in order to develop shelf-life prediction models. Altogether, we evaluated 10,800 oranges ( ...

Abstract	We conducted a large-scale, high-throughput phenotyping analysis of the effects of various preharvest and postharvest features on the quality of ‘Valencia’ oranges in order to develop shelf-life prediction models. Altogether, we evaluated 10,800 oranges (~3.6 tons) harvested from three orchards at different periods and conducted 151,200 measurements of 14 quality parameters. The storage time was the most important feature affecting fruit quality, followed by the yield, storage temperature, humidity, and harvest time. The storage time and temperature features significantly affected (p < 0.001) all or most of the tested quality parameters, whereas the harvest time, yield, and humidity conditions significantly affected several particular quality parameters, and the selection of rootstocks had no significant effect at all. Five regression models were evaluated for their ability to predict fruit quality based on preharvest and postharvest features. Non-linear Support Vector Regression (SVR) combined with a data-balancing approach was found to be the most effective approach. It allowed the prediction of fruit-acceptance scores among the full data set, with a root mean square error (RMSE) of 0.195 and an R² of 0.884. The obtained data and models should assist in determining the potential storage times of different batches of fruit.
Keywords	data collection ; fruit quality ; fruits ; harvest date ; humidity ; phenotype ; prediction ; regression analysis ; shelf life ; storage temperature ; storage time
Language	English
Dates of publication	2022-0622
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2813983-5
ISSN	2311-7524
ISSN	2311-7524
DOI	10.3390/horticulturae8070570
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