IP Library › Granted Patent US 12,517,141
Granted Patent B2
US 12,517,141 · App. 17/207,020 · Granted Jan 6, 2026

Methods of estimating blood glucose and related systems

Inventors: Roy Malka (Binyamina, IL); John M. Higgins (Cambridge, MA); David M. Nathan (West Newton, MA)
Assignee: The General Hospital Corporation
G01N33/723G01N33/555G01N33/726A61B5/14532G01N2800/042
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Quick Facts
Patent No.
US 12,517,141
App. No.
17/207,020
Granted
Jan 6, 2026
Kind
B2
Abstract

A method includes estimating a value of a parameter indicative of an age or lifespan of a population of red blood cells of a subject, estimating a value of average glucose (AG) of the subject based on (i) the value of the parameter and (ii) a value indicative of an amount of glycated hemoglobin (HbA1c) of the subject, and providing information for treatment or diagnosis of a hyperglycemia condition of the subject based on the estimated value of AG.

Claims (38)

1 . A glucose monitoring device comprising:

a glucose sensor configured to measure one or more values indicative of blood glucose concentration of a subject when the glucose monitoring device is worn by the subject, the one or more values indicative of blood glucose concentration being further indicative of an estimated value of a parameter indicative of an average age or lifespan of a population of red blood cells of the subject;

a user terminal configured to provide information to the subject or a healthcare provider; and

a controller configured to execute instructions to perform one or more operations comprising:

estimating the value of the parameter, wherein estimating the value of the parameter comprises determining a linear relationship between the one or more values indicative of blood glucose concentration and one or more values indicative of an amount of glycated hemoglobin (HbA1c) of the subject, wherein the parameter defines a slope of the linear relationship;

estimating a value of average glucose (AG) based on (i) the estimated value of the parameter and (ii) a value of the one or more values indicative of an amount of HbA1c of the subject, and

providing, via the user terminal, an amount of insulin or insulin analog to be administered to the subject to treat a hyperglycemia condition of the subject, the amount of the insulin or insulin analog being a function of the estimated value of AG.

2 . The glucose monitoring device of claim 1 , wherein the glucose sensor is implantable under a skin of the subject.

3 . The glucose monitoring device of claim 2 , wherein the controller is worn externally on the subject.

4 . The glucose monitoring device of claim 3 , further comprising a user output device configured to provide to the subject, information related to the hyperglycemia condition.

5 . The glucose monitoring device of claim 4 , wherein the user output device is a display.

6 . The glucose monitoring device of claim 1 , wherein the one or more operations further comprise:

before estimating the value of AG, receiving, from a hemoglobin testing system, the value of the one or more values indicative of the amount of HbA1c.

7 . The glucose monitoring device of claim 1 , wherein the glucose sensor is configured to measure the value of the one or more values indicative of blood glucose concentration by collecting a plurality of measurements over a period of time of at least 7 days.

8 . The glucose monitoring device of claim 1 , wherein the parameter is estimated based on a weighted average of multiple values indicative of blood glucose concentration of the subject.

9 . The glucose monitoring device of claim 8 , wherein:

the value indicative of the amount of HbA1c is a second value of the one or more values indicative of the amount of HbA1c,

the value of the parameter is estimated based on a first value of the one or more values indicative of the amount of HbA1c, and

the weighted average is determined based on times at which the one or more values indicative of blood glucose concentration are measured relative to a time at which the first value of the one or more values indicative of the amount of HbA1c is measured.

10 . The glucose monitoring device of claim 1 , wherein the one or more operations further comprise determining a diagnostic threshold for the hyperglycemia condition based on the parameter and the estimated value of AG, administering the amount of insulin or insulin analog to the subject to treat a hyperglycemia condition of the subject includes administering the amount of insulin or insulin analog to the subject when the value indicative of the amount of HbA1c is above the diagnostic threshold.

11 . The glucose monitoring device of claim 1 , wherein the one or more operations further comprise estimating, based on the value indicative of blood glucose concentration, the value of the parameter indicative of the average age or lifespan of the population of red blood cells of the subject.

12 . The glucose monitoring device of claim 11 , wherein the value of the one or more values indicative of the amount of HbA1c is a second value of the one or more values indicative of the amount of HbA1c, and the value of the parameter is estimated based on a first value of the one or more values indicative of the amount of HbA1c and the value of the one or more values indicative of blood glucose concentration of the subject.

13 . The glucose monitoring device of claim 12 , wherein the first value of the one or more values indicative of the amount of HbA1c is measured at a first time after a time period in which the value of the one or more values indicative of blood glucose concentration of the subject is measured.

14 . The glucose monitoring device of claim 13 , wherein the first time is earlier than a second time at which the second value of the one or more values indicative of the amount of HbA1c is measured.

15 . The glucose monitoring device of claim 1 , wherein the value of the parameter is indicative of at least one of an average red blood cell age (MRBC), a half-life of a red blood cell population, or an average red blood cell lifespan.

16 . A glucose monitoring device comprising:

a glucose sensor configured to measure a value indicative of blood glucose concentration of a subject when the glucose monitoring device is worn by the subject, the value indicative of blood glucose concentration being further indicative of an estimated value of a parameter indicative of an average age or lifespan of a population of red blood cells of the subject;

a user terminal configured to provide information to the subject or a healthcare provider; and

a controller configured to execute instructions to perform one or more operations comprising:

receiving a value of AG estimated based on (i) the value indicative of blood glucose concentration and (ii) a value indicative of HbA1c, wherein estimating the AG comprises estimating the value of the parameter, comprising determining a linear relationship between one or more values indicative of blood glucose concentration and one or more values indicative of an amount of HbA1c of the subject, wherein the parameter defines a slope of the linear relationship, and

providing, via the user terminal, an amount of insulin or insulin analog to be administered the subject to treat a hyperglycemia condition of the subject, the amount of the insulin or insulin analog being a function of the estimated value of AG.

17 . A glucose monitoring device comprising:

a glucose sensor configured to measure a value indicative of blood glucose concentration of a subject when the glucose monitoring device is worn by the subject, the value indicative of blood glucose concentration being further indicative of an estimated value of a parameter indicative of an age or lifespan of a population of red blood cells of the subject;

a user terminal configured to provide information to the subject or a healthcare provider; and

a controller configured to execute instructions to perform one or more operations comprising:

determining a subject-specific relationship between values indicative of blood glucose concentration and values indicative of an amount of HbA1c for the subject based on the parameter, wherein the subject-specific relationship is a linear relationship between the values indicative of AG and the values indicative of the amount of HbA1c, wherein the parameter defines a slope of the linear relationship; and

providing, via the user terminal, an amount of insulin or insulin analog to be administered to the subject to treat a hyperglycemia condition of the subject, the amount of insulin or insulin analog being a function of the subject-specific relationship.

18 . The glucose monitoring device of claim 17 , wherein the subject-specific relationship is defined by at least one of a value of a glycation rate constant or a value of a reticulocyte HbA1c amount.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 24, 2021
From: MALKA, ROY; HIGGINS, JOHN M.; NATHAN, DAVID M.
To: THE GENERAL HOSPITAL CORPORATION
Reel/Frame 056324/0784 →
Continuity (4)
Continuation 16061951
Provisional Application 62379942 · Aug 26, 2016
Provisional Application 62267588 · Dec 15, 2015
Related Publication 20210208167A1 · Jul 8, 2021
References Cited (274)
US 5017497A · Gerard de Grooth et al. · 1991 [cited by applicant]
US 5266269A · Niiyama et al. · 1993 [cited by applicant]
US 5369014A · Brugnara et al. · 1994 [cited by applicant]
US 5378633A · von Behrens et al. · 1995 [cited by applicant]
US 5631165A · Chupp et al. · 1997 [cited by applicant]
US 5812419A · Chupp et al. · 1998 [cited by applicant]
US 5822715A · Worthington et al. · 1998 [cited by applicant]
US 6030838A · Telmissani · 2000 [cited by applicant]
US 6228652B1 · Rodriguez et al. · 2001 [cited by applicant]
US 6320656B1 · Ferrante et al. · 2001 [cited by applicant]
US 6524858B1 · Zelmanovic et al. · 2003 [cited by applicant]
US 7324194B2 · Roche et al. · 2008 [cited by applicant]
US 7981681B2 · Champseix et al. · 2011 [cited by applicant]
US 8481323B2 · Tyvoll et al. · 2013 [cited by applicant]
US 8792693B2 · Satish et al. · 2014 [cited by applicant]
US 10509024B2 · Zelmanovic et al. · 2019 [cited by applicant]
US 11293852B2 · Higgins et al. · 2022 [cited by applicant]
US 20040152199A1 · Kendall et al. · 2004 [cited by applicant]
US 20060203226A1 · Roche et al. · 2006 [cited by applicant]
US 20070099301A1 · Tyvoll · 2007 [cited by examiner]
US 20070172956A1 · Magari et al. · 2007 [cited by applicant]
US 20080153170A1 · Garrett et al. · 2008 [cited by applicant]
US 20080158561A1 · Vacca et al. · 2008 [cited by applicant]
US 20080268494A1 · Linssen · 2008 [cited by applicant]
US 20100198142A1 · Sloan · 2010 [cited by examiner]
US 20110070210A1 · Andrijauskas · 2011 [cited by applicant]
US 20110070606A1 · Winkelman et al. · 2011 [cited by applicant]
US 20110077871A1 · Fukuma et al. · 2011 [cited by applicant]
US 20110149061A1 · Wardlaw et al. · 2011 [cited by applicant]
US 20110164803A1 · Wang et al. · 2011 [cited by applicant]
US 20110178716A1 · Krockenberger et al. · 2011 [cited by applicant]
US 20110190143A1 · Payen de la Garanderie et al. · 2011 [cited by applicant]
US 20120263369A1 · Xie et al. · 2012 [cited by applicant]
US 20130236566A1 · Higgins · 2013 [cited by applicant]
US 20140030729A1 · Basiji et al. · 2014 [cited by applicant]
US 20140187887A1 · Dunn et al. · 2014 [cited by applicant]
US 20150160188A1 · Krockenberger et al. · 2015 [cited by applicant]
US 20150330963A1 · Vidal et al. · 2015 [cited by applicant]
US 20160259884A1 · Han · 2016 [cited by applicant]
US 20160364544A1 · Das et al. · 2016 [cited by applicant]
US 20170108487A1 · Higgins · 2017 [cited by applicant]
US 20170228507A1 · Bottinger et al. · 2017 [cited by applicant]
US 20180187235A1 · Higgins · 2018 [cited by applicant]
US 20180364262A1 · Malka et al. · 2018 [cited by applicant]
US 20190066843A1 · Carlson · 2019 [cited by applicant]
US 20190113438A1 · Higgins et al. · 2019 [cited by applicant]
US 20190336085A1 · Kayser et al. · 2019 [cited by applicant]
US 20220293210A1 · Higgins et al. · 2022 [cited by applicant]
JP 1995105166 · 1995 [cited by applicant]
JP 1999326315 · 1999 [cited by applicant]
JP A2005503559 · 2005 [cited by applicant]
JP 2006516735 · 2006 [cited by applicant]
JP 2006527199 · 2006 [cited by applicant]
JP 200936587 · 2009 [cited by applicant]
JP 2009510402 · 2009 [cited by applicant]
JP 2009524068 · 2009 [cited by applicant]
JP 2009524069 · 2009 [cited by applicant]
JP 2010526873 · 2010 [cited by applicant]
WO WO2001077140 · 2001 [cited by applicant]
WO WO2003025583 · 2003 [cited by applicant]
WO WO2004108121 · 2004 [cited by applicant]
WO WO20070084977 · 2007 [cited by applicant]
WO WO2011057744 · 2011 [cited by applicant]
WO WO2012037524 · 2012 [cited by applicant]
WO WO2014074889 · 2014 [cited by applicant]
WO WO2021034770 · 2021 [cited by applicant]
WO WO2022266654 · 2022 [cited by applicant]
Hemoglobin Glycation Rate Constant in Non-diabetic Individuals Piotr Ladyzynski, Jan M. Wojcicki, Marianna I. Bak, Stanisawa Sabalinska, Jerzy Kawiak, Pitor Foltynski, Janusz Krzymien, Waldemar Karnafel Annals of Biomed… [cited by examiner]
[No Author Listed], “How to read complete blood count,” JIM, 2006, 16: 792-795 (with English abstract). [cited by applicant]
Adams et al., “Cardiac troponin I. A marker with high specificity for cardiac injury,” Circulation, 1993, 88: 101-106. [cited by applicant]
Ali et al., “H2RM: A Hybrid Rough Set Reasoning Model for Prediction and Management of Diabetes Mellitus,” Sensors, Jul. 2015, 15: 15921-15951. [cited by applicant]
Allen et al., “Validation and Potential 10 Mechanisms of Red Cell Distribution Width as a Prognostic Marker in Heart Failure,” J Card Fail, Mar. 2010, 16:230-238. [cited by applicant]
Altenbaugh, “Suitability and Utility of Computational Analysis Tools: characterization of Erythrocyte Parameter Variation,” Pacific Symposium on Biocomputing, 2003, 8: 104-115. [cited by applicant]
American Diabetes Association, “Standards of medical care in diabetes—2010,” Diabetes Care, 2010, 33: S11-S61. [cited by applicant]
Anderson et al, “Usefulness of a complete blood count-derived risk score to predict incident mortality in patients with suspected cardiovascular disease,” Am J Cardiol, 2007, 99: 169-174. [cited by applicant]
Apple et al., “Analytical Characteristics of High-Sensitivity Cardiac Troponin Assays,” Clin. Chem, 2011, 58: 54-61. [cited by applicant]
Athens et al., “Leukokinetic Studies. IV. The Total Blood, Circulating And Marginal Granulocyte Pools And The Granulocyte Turnover Rate In Normal Subjects,” J. Clin. Invest, 1961, 40: 989-995. [cited by applicant]
Bainton et al., “Developmental Biology of Neutrophils and Eosinophils,” Inflammation: Basic Principles and Clinical Correlates, Chapter 2, 1999, 13-34. [cited by applicant]
Barua et al,, “The relationship between fasting plasma glucose and HbA(1c) during intensive periods of glucose control in antidiabetic therapy,” J. Theor. Biol, Dec. 2014, 363: 158-163. [cited by applicant]
Beach, “A theoretical model to predict the behavior of glycosylated hemoglobin levels,” Journal of Theoretical Biology, 1979, 81: 547-561. [cited by applicant]
Bergman, “Toward Physiological Understanding of Glucose-Tolerance—Minimal-Model Approach,” Diabetes, 1989, 38: 1512-1527. [cited by applicant]
Bergman, et al., “Physiologic Evaluation Of Factors Controlling Glucose-Tolerance in Man—Measurement of Insulin Sensitivity and Beta-Cell Glucose Sensitivity from the Response to Intravenous Glucose,” Journal of Clinica… [cited by applicant]
Beutler and Waalen, “The definition of anemia: what is the lower limit of normal of the blood hemoglobin concentration?,” Blood, 2006, 107: 1747-1750. [cited by applicant]
Bunn et al., “The biosynthesis of human hemoglobin A1c. Slow glycosylation of hemoglobin in vivo,” Journal of Clinical Investigation, 1976, 57: 1652-1659. [cited by applicant]
Bunn et al., “The glycosylation of hemoglobin: relevance to diabetes mellitus,” Science, Apr. 1978, 200:21-27. [cited by applicant]
Carstairs, “The Human Small Lymphocyte: Its Possible Pluripotential Quality,” Lancet, 1962, 279: 829-832. [cited by applicant]
Casanova-Acebes et al., “Rhythmic Modulation of the Hematopoietic Niche through Neutrophil Clearance,” Cell, 2017, 153: 1025-1035. [cited by applicant]
Cohen et al., “Red cell life span heterogeneity in hematologically normal people is sufficient to alter HbA1 c,” Blood, Nov. 2008, 112:4284-4291. [cited by applicant]
Cohen et al., “Discordance between HbA(1c) and fructosamine—Evidence for a glycosylation gap and its relation to diabetic nephropathy,” Diabetes Care, Jan. 2003, 26: 163-167. [cited by applicant]
Cohen et al., “Is poor glycemic control associated with reduced red blood cell lifespan?,” Diabetes Care, 2004, 27: 1013-1014. [cited by applicant]
Cook, “Diagnosis and management of iron-deficiency anaemia,” Best Practice & Research Clinical Haematology, vol. 18, p. 319-332, 2005. [cited by applicant]
Cornbleet, “Clinical utility of the band count,” Clin. Lab. Med, 2002, 22: 101-136. [cited by applicant]
Crane et al., “Glucose levels and risk of dementia,” New England Journal of Medicine, 2013, 369: 540-548. [cited by applicant]
Cronkite and Vincent, “Granulocytopoiesis,” Series Haematologica, 1969, II: 3-43. [cited by applicant]
D'Onofrio et al., “Simultaneous Measurement of Reticulocyte and Red-Blood-Cell Indexes in Healthy-Subjects and Patients with Microcytic Anemia,” Blood, 1995, 85(3):818-823. [cited by applicant]
Damiano et al., “A comparative effectiveness analysis of three continuous glucose monitors: the Navigator, G4 Platinum, and Enlite,” Journal of Diabetes Science and Technology, Jul. 2014, 8: 699-708. [cited by applicant]
Daubert and Jeremias, The utility of troponin measurement to detect myocardial infarction: review of the current findings, Vasc. Health Risk Manag, 2010, 6: 691-699. [cited by applicant]
DCCT Research Group, “The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus,” N Engl J Med, 1993, 329: 977-986. [cited by applicant]
De Smet et al., “Use of the Cell-Dyn Sapphire Hematology Analyzer for Automated Counting of Blood Cells in Body Fluids,” Am. J. Clin. Pathol, 2010, 133: 291-299. [cited by applicant]
Eliaz et al., “Modeling failure of metallic glasses due to hydrogen embrittlement in the absence of external loads,” Acta Materialia, Jan. 2004, 52: 93-105. [cited by applicant]
El-Khatib et al., “A Bihormonal Closed-Loop Artificial Pancreas for Type 1 Diabetes,” Science Translational Medicine, Apr. 2010, 2: 27ra27, 17 pages. [cited by applicant]
Engstrom et al, “Red cell distribution width, haemoglobin A1e and incidence of diabetes mellitus,” Journal of Internal Medicine, Aug. 2014, 276: 174-183. [cited by applicant]
EP Office Action in European Application No. 11826059, dated Jan. 29, 2016, 8 pages. [cited by applicant]
EP Office Action in European Application No. 15803598.0, dated Oct. 16, 2018, 7 pages. [cited by applicant]
EP Office Action in European Appln. No. 17160801, dated Apr. 2, 2020, 5 pages. [cited by applicant]
EP Search Report in Application No. 15803598.0, dated Nov. 27, 2017, 10 pages. [cited by applicant]
EP Search Report in Application No. 17160801.1, dated Jan. 16, 2018, 14 pages. [cited by applicant]
EP Search Report in Application No. 1716081.1, dated Sep. 25, 2017. [cited by applicant]
EP Supplementary European Search Report issued in EP 11826059 dated Feb. 21, 2014, 18 pages. [cited by applicant]
Felker et al, “Red cell distribution width as a novel prognostic marker in heart failure—Data from the CHARM program and the Duke Databank,” J Am Coll Cardiol, 2007, 50:40-47. [cited by applicant]
Franco et al., “Changes in the properties of normal human red blood cells during in vivo aging,” Am J Hematol, Jan. 2013, 88:44-51. [cited by applicant]
Franco, “The measurement and importance of red cell survival,” Am J Hematol, Feb. 2009, 84:109-114. [cited by applicant]
Gardner and Benz Jr., “Anemia of chronic diseases.” In: Hoffman et al., eds. Hematology: Basic Principles and Practice. 5th ed. Philadelphia, Pa: Elsevier Churchill Livingstone; 2008:chap 37, 8 pages. [cited by applicant]
Garner et al., “Genetic influences on F cells and other hematologic variables: a twin heritability study,” Blood, 2000, 95(1):342-346. [cited by applicant]
Georga et al., “Evaluation of short-term predictors of glucose concentration in type 1 diabetes combining feature ranking with regression models,” Medical & Biological Engineering & Computing, Dec. 2015, 53: 1305-1318. [cited by applicant]
George, “Malignant or Benign Leukocytosis,” American Society of Hematology, 2012, 475-484. [cited by applicant]
Gifford et al., “A detailed study of time-dependent changes in human red blood cells: from reticulocyte maturation to erythrocyte senescence,” Br J Haematol., 2006, 135(3):395-404. [cited by applicant]
Gijsberts et al., “Hematological Parameters Improve Prediction of Mortality and Secondary Adverse Events in Coronary Angiography Patients: A Longitudinal Cohort Study,” Medicine (Baltimore), Nov. 2015, 94: e1992, 10 pag… [cited by applicant]
Given et al., “Measurement error in estimated average glucose: a novel approach,” Clinical Chemistry and Laboratoiy Medicine, Jul. 2014, 52: E147-E150. [cited by applicant]
Golub et al., “Developmental plasticity of red blood cell homeostasis,” Am J. Hematol, May 2014, 89: 459-466. [cited by applicant]
Gould et al., “Investigation of the mechanism underlying the variability of glycated haemoglobin in non-diabetic subjects not related to glycaemia,” Clin. Chim. Acta, Apr. 1997, 260: 49-64. [cited by applicant]
Gram-Hansen et al, “Glycosylated Hemoglobin (HbA1c) as an Index of the Age of the Erythrocyte Population in NonDiabetic Patients,” Eur J Haematol, 1990, 44:201-203. [cited by applicant]
Harrington et al., “Iron Deficiency Anemia, β-Thalassemia Minor, and Anemia of Chronic Disease: A Morphologic Reappraisal,” Am J Clin Pathol., Dec. 2008, 129:466-471. [cited by applicant]
Hempe et al., “High and low hemoglobin glycation phenotypes in type 1 diabetes: a challenge for interpretation of glycemic control,” Journal of Diabetes and Its Complications, 2002, 16: 313-320. [cited by applicant]
Higgins and Bunn, “Kinetic analysis of the nonenzymatic glycosylation of hemoglobin,” Journal of Biological Chemistry, 1981, 256: 5204-5208. [cited by applicant]
Higgins and Mahadevan, “Physiological and Pathological Population Dynamics of Circulating Human Red Blood Cells,” PNAS, Nov. 2010, 107(47):20587-20595. [cited by applicant]
Hoelzel et al., “IFCC reference system for measurement of hemoglobin A1c in human blood and the national standardization schemes in the United States, Japan, and Sweden: a method-comparison study,” Clinical Chemistiy, 2… [cited by applicant]
Hoffstein et al., “Degranulation, membrane addition, and shape change during chemotactic factor-induced aggregation of human neutrophils,” J. Cell Biol, 1982, 95: 234-241. [cited by applicant]
Horne et al., “Which White Blood Cell Subtypes Predict Increased Cardiovascular Risk?,” J. Am. Coll. Cardiol, 2005, 45: 1638-1643. [cited by applicant]
Horne, “A Changing Focus on the Red Cell Distribution Width: Why Does It Predict Mortality and Other Adverse Medical Outcomes?,” Cardiology, 2012, 122:213-215. [cited by applicant]
Horne, “The Red Cell Distribution Width: What Is Its Value for Risk Prognostication and for Understanding Disease Pathophysiology?,” Cardiology, 2011, 119:140-141. [cited by applicant]
Huang et al., “Using Hemoglobin A1C as a Predicting Model for Time Interval from Pre-Diabetes Progressing to Diabetes,” Plos One, Aug. 2014, 9(8):e104263, 7 pages. [cited by applicant]
IDF Diabetes Altas, Seventh Edition, International Diabetes Federation, 2015, 140 pages. [cited by applicant]
IL Office Action in Israel Application No. 225275, dated Dec. 13, 2015, 7 pages (with English translation). [cited by applicant]
IL Office Action in Israeli Application No. 225275, dated Jan. 8, 2017, 4 pages, with English translation. [cited by applicant]
International Preliminary Report on Patentability in International Application No. PCT/US2011/052038, dated Mar. 19, 2013, 7 pages. [cited by applicant]
International Preliminary Report on Patentability in International Application No. PCT/US2015/034508, dated Dec. 6, 2016, 9 pages. [cited by applicant]
International Preliminary Report on Patentability in International Application No. PCT/US2016/066860, dated Jun. 9, 2018. [cited by applicant]
International Preliminary Report on Patentability in International Application No. PCT/US2017/026695, dated Oct. 18, 2018. [cited by applicant]
International Search Report and Written Opinion in International Application No. PCT/US2016/066860, dated Mar. 2, 2017, 12 pages. [cited by applicant]
International Search Report and Written Opinion issued in PCT/US2011/052038 dated May 2, 2012, 11 pages. [cited by applicant]
International Search Report and Written Opinion dated Aug. 27, 2015 in International application No. PCT/US2015/034508, 13 pages. [cited by applicant]
International Search Report and Written Opinion dated Jun. 27, 2017 in International Application No. PCT/US2017/026695, 18 pgs. [cited by applicant]
International Search Report and Written Opinion dated Mar. 2, 2017 in international application No. PCT/US2016/066860, 12 pgs. [cited by applicant]
Jansen et al, “Determinants of HbA1c in nondiabetic Dutch adults: genetic loci and clinical and lifestyle parameters, and their interactions in the lifelines cohort study,” Journal of Internal Medicine, 2013, 273:283-29… [cited by applicant]
Jelkmann and Lundby, “Blood doping and its detection,” Blood, Sep. 2011, 118(9):2395-2404. [cited by applicant]
Jopang et al., “False Positive Rates of Thalassemia Screening in Rural Clinical Setting: 10-Year Experience in Thailand,” Southeast Asian J Trop. Med. Public Health, 2009, 40(3):576-580. [cited by applicant]
JP Office Action in Application No. 2017-144114, dated May 15, 2018, 9 pages (with English translation). [cited by applicant]
JP Office Action in Japanese Application No. 2015-189343, dated Sep. 6, 2016, 15 pages (with English translation). [cited by applicant]
JP Office Action issued in JP2013-529382 dated May 26, 2015, 9 pages (with English translation). [cited by applicant]
Kakkar and Makkar, “Red Cell Cytograms Generated by an AD VIA 120 Automated Hematology Analyzer: Characteristic Patterns in Common Hematological Conditions,” LabMedicine, 2009, 40: 549-555. [cited by applicant]
Kawaguchi et al., “Band neutrophil count and the presence and severity of coronary atherosclerosis,” Am. Heart J, 1996, 132: 9-12. [cited by applicant]
Khera et al., “Use of an oral stable isotope label to confirm variation in red blood cell mean age that influences HbA1c interpretation,” Am. J. Hematol, 2015, 90: 50-55. [cited by applicant]
Kim et al., “Association Between Iron Deficiency and A1C Levels Among Adults Without Diabetes in the National Health and Nutrition Examination Survey, 1999-2006,” Diabetes Care, Jan. 2010, 33: 780-785. [cited by applicant]
Kitcharoen et al., “A New Screening Program for Thalassemias in Thailand Based on the Complete Blood Count,” Medical Online, 1994, 17: 178-183. [cited by applicant]
Kleophas, “Dose tailoring strategies in haemodialysis patients: a discussion of case histories,” Nephrol Dial Transplant, vol. 20 [Suppl 6], p. vi31-vi36, 2005. [cited by applicant]
Kochanek et al., “Mortality in the United States, 2013,” NCHS Data Brief, No. 178. Hyattsville, MD: National Center for Health Statistics, 2014, 8 pages. [cited by applicant]
Koren-Morag et al., “White blood cell count and the incidence of ischemic stroke in coronary heart disease patients,” Am. J. Med, 2005, 118: 1004-1009. [cited by applicant]
Kovatchev et al., “Accuracy and Robustness of Dynamical Tracking of Average Glycemia (A1c) to Provide Real-Time Estimation of Hemoglobin A1c Using Routine Self-Monitored Blood Glucose Data,” Diabetes Technol. Ther, May … [cited by applicant]
Ladyzynski et al, “Hemoglobin Glycation Rate Constant in Non-diabetic Individuals,” Ann Biomed Eng, 2011, 39:2721-2734. [cited by applicant]
Ladyzynski et al, “Validation of hemoglobin glycation models using glycemia monitoring in vivo and culturing of erythrocytes in vitro,” Ann Biomed Eng, 2008, 36: 1188-1202. [cited by applicant]
Lang et al., “Mechanisms of suicidal erythrocyte death,” Cell Physiol Biochem., 2005, 15(5):195-202. [cited by applicant]
Lenters-Westra and Slingerland, “Six of Eight Hemoglobin A(1c) Point-of-Care Instruments Do Not Meet the General Accepted Analytical Performance Criteria,” Clinical Chemistry, Jan. 2010, 56:44-52. [cited by applicant]
Leslie and Cohen, “Biologic variability in plasma glucose, hemoglobin A1e, and advanced glycation end products associated with diabetes complications,” Journal of Diabetes Science and Technology, Jul. 2009, 3:635-643. [cited by applicant]
Lew et al., “Generation of Normal Human Red-Cell Volume, Hemoglobin Content, and Membrane Area Distributions by “Birth” or Regulation,” Blood, 1995, 86(1):334-341. [cited by applicant]
Lippi et al., “Stability of blood cell counts, hematologic parameters and reticulocytes indexes on the Advia A120 hematologic analyzer,” J Lab. Clin. Med., 2005, 146(6):333-340. [cited by applicant]
Lledó-García et al., “A semi-mechanistic model of the relationship between average glucose and HbA1c in healthy and diabetic subjects.” Journal of Pharmacokinetics and Pharmacodynamics, 2013,14 pages. [cited by applicant]
Lozoff et al., “Long-Term Developmental Outcome of Infants with Iron-Deficiency,” N Engl J Med, Sep. 1991, 325:687-694. [cited by applicant]
Lundby, “Erythropoietin treatment elevates haemoglobin concentration by increasing red cell volume and depressing plasma volume,” J Physiol, 578, Jan. 2007, 309-314. [cited by applicant]
Mackay, “Homing of naive, memory and effector lymphocytes,” Curr. Opin. Immunol, 1993, 5: 423-427. [cited by applicant]
Madjid et al., “Leukocyte count and coronary heart disease,” J. Am. Coll. Cardiol, 2004, 44: 1945-1956. [cited by applicant]
Malka et al., “In vivo volume and hemoglobin dynamics of human red blood cells,” PLoS Comput. Biol, 2014, 10: e1003839, 12 pages. [cited by applicant]
Matthews et al., “Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man,” Diabetologia, Jul. 1985, 28: 412-419. [cited by applicant]
Menezes et al., “Targeted clinical control of trauma patient coagulation through a thrombin dynamics model,” Sci. Transl. Med, 2017, 9: eaaf5045, 11 pages. [cited by applicant]
Menon et al., “Leukocytosis and adverse hospital outcomes after acute myocardial infarction,” Am. J. Cardiol, 2003, 92: 368-372. [cited by applicant]
Milbrandt et al., “Predicting late anemia in critical illness,” Crit. Care, 2006, 10(1), 8 pages. [cited by applicant]
Mock et al., “Measurement of Posttransfusion Red Cell Survival With the Biotin Label,” Transf Med Rev, Jul. 2014, 28: 114-125. [cited by applicant]
Mortensen et al., “Glucosylation of human haemoglobin a. dynamic variation in HbA 1c described by a biokinetic model,” Clinica Chimica Acta, 1984, 136: 75-81. [cited by applicant]
Mosior et al., “Critical cell volume and shape of bovine erythrocytes,” General Physiology and Biophysics, Oct. 1992, 499-506. [cited by applicant]
Nathan et al., “Translating the A1C assay into estimated average glucose values,” Diabetes Care, 2008, 31: 1-6. [cited by applicant]
Neumann and Nurse, “Nuclear size control in fission yeast,” J. Cell Biol, 2007, 179: 593-600. [cited by applicant]
Ntaios et al., “Discrimination indices as screening tests for beta-thalassemic Trait,” Ann. Hematol., 2007, 86(7):487-491. [cited by applicant]
Office Action in U.S. Appl. No. 13/823,338, dated Apr. 7, 2017, 17 pages. [cited by applicant]
Osterman-Golkar and Vesper, “Assessment of the relationship between glucose and A1c using kinetic modeling,” Journal of Diabetes and its Complications, 2006, 20: 285-294. [cited by applicant]
Pande et al., “The sweep constant concept in phase coarsening,” Metallurgical and Materials Transactions, Sep. 1998, 29: 2395-2398. [cited by applicant]
Pascual-Figal et al., “Red blood cell distribution width predicts new-onset anemia in heart failure patients,” Int J Cardiol, 2012, 160: 196-200. [cited by applicant]
Patel et al., “Modulation of red blood cell population dynamics is a fundamental homeostatic response to disease : Modulation of red blood cell population dynamics,” American Journal of Hematology, May 2015, 90:422-428. [cited by applicant]
Patel et al., “Red Blood Cell Distribution Width and the Risk of Death in Middle-aged and Older Adults,” Arch Intern Med, Mar. 2009, 169:515-523. [cited by applicant]
Perlstein et al., “Red Blood Cell Distribution 30 Width and Mortality Risk in a Community-Based Prospective Cohort,” Arch Intern Med, Mar. 2009, 169:588-594. [cited by applicant]
Piva et al., “Automated reticulocyte counting: state of the art and clinical applications in the evaluation of erythropoiesis,” Clinical Chemistiy and Laboratoiy Medicine, Oct. 2010, 48: 1369-1380. [cited by applicant]
Prommer, “Total Hemoglobin Mass—A New Parameter to Detect Blood Doping,” Medicine & Science in Sports & Exercise, vol. 40, p. 2112-2118, 2008. [cited by applicant]
Rockey and Cello, “Evaluation of the Gastrointestinal Tract in Patients With Iron-Deficiency Anemia,” New Engl J Med., Dec. 1992, 329(23):1691-1695. [cited by applicant]
Rohlfing et al., “Biological variation of glycohemoglobin,” Clinical Chemistry, Jul. 2002, 48: 1116-1118. [cited by applicant]
Sacks, “Hemoglobin A1c in diabetes: panacea or pointless?,” Diabetes, 2013, 62: 41-43. [cited by applicant]
Segura et al., “Current strategic approaches for the detection of blood doping practices,” Forensic Sci Int., 2011, 42-48. [cited by applicant]
Sens and Gov, “Force balance and membrane shedding at the red blood-cell surface,” Phys Rev Lett., 2007, 98(018102):1-4. [cited by applicant]
Shiga et al., “Laboratory Diagnosis of Anemia and Related Diseases Using Multivariate Analysis,” American Journal of Hematology, 1997, 54: 108-117. [cited by applicant]
Spell et al., “The value of a complete blood 5 count in predicting cancer of the colon,” Cancer Detect Prev, 2004, 28:37-42. [cited by applicant]
Statland et al., “Evaluation of Biologic Sources of Variation of Leukocyte Counts and Other Hematologic Quantities Using Very Precise Automated Analyzers,” Am. J. Clin. Pathol, 1978, 69: 48-54. [cited by applicant]
Tahara and Shima, “Kinetics of HbA(1c), glycated albumin, and fructosamine and analysis of their weight-functions against preceding plasma-glucose level,” Diabetes Care, Apr. 1995, 18: 440-447. [cited by applicant]
Tamhane et al., “Association Between Admission Neutrophil to Lymphocyte Ratio and Outcomes in Patients With Acute Coronary Syndrome,” Am. J. Cardiol, 2008, 102: 653-657. [cited by applicant]
Thompson et al., “Size-dependent B lymphocyte subpopulations: relationship of cell volume to surface phenotype, cell cycle, proliferative response, and requirements for antibody production to TNP-Ficoll and TNP-BA,” J. … [cited by applicant]
Tzur et al., “Cell Growth and Size Homeostasis in Proliferating Animal Cells,” Science, 2009, 325: 167-171. [cited by applicant]
UK Prospective Diabetes Study (UKPDS) Group, “Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33),” T… [cited by applicant]
Veeranna et al., “The Association of Red Cell Distribution Width with Glycated Hemoglobin among Healthy Adults without Diabetes Mellitus,” Cardiology, 2012, 122:129-132. [cited by applicant]
Wang et al., “Closed-Loop Control of Artificial Pancreatic beta-Cell in Type 1 Diabetes Mellitus Using Model Predictive Iterative Learning Control,” IEEE Trans. Biomed. Eng, Febmary 2010, 57: 211-219. [cited by applicant]
Wang et al., “Heterogeneity of human blood monocyte: two subpopulations with different sizes, phenotypes and functions,” Immunology, 1992, 77: 298-303. [cited by applicant]
Waugh et al., “Rheologic properties of senescent erythrocytes: loss of surface area and volume with red blood cell age,” Blood, 1992, 79(5):1351-1358. [cited by applicant]
Webster et al., “Sizing up the nucleus: nuclear shape, size and nuclear-envelope assembly,” J. Cell Sci, 2009, 122: 1477-1486. [cited by applicant]
Wilkinson and Grand, “Comparison of amino acid sequence of troponin I from different striated muscles,” Nature, 1978, 271: 31-35. [cited by applicant]
Willekens et al., “Erythrocyte vesiculation: a self-protective mechanism?,” Br J Haematol, Apr. 2008, 141:549-556. [cited by applicant]
Willekens et al., “Hemoglobin loss from erythrocytes in vivo results from spleen-facilitated vesiculation,” Blood, 2003, 101(2):747-751. [cited by applicant]
Willekens et al., “Liver Kupffer cells rapidly remove red blood cell-derived vesicles from the circulation by scavenger receptors,” Blood, 2005, 105(5):2141-2145. [cited by applicant]
Yudkin et al., “Unexplained Variability of Glycated Hemoglobin in Nondiabetic Subjects Not Related to Glycemia,” Diabetologia, Apr. 1990, 33: 208-215. [cited by applicant]
Yunoki et al., “MCH is useful for early diagnosis of thalassemia,” 2003, 44: 771 PS-1-169 (with English Abstract). [cited by applicant]
Zecchin et al., “Jump Neural Network for Real-Time Prediction of Glucose Concentration,” in Artificial Neural Networks, 2nd Edition, 2015, 1260: 245-259. [cited by applicant]
Zenker et al., “From inverse problems in mathematical physiology to quantitative differential diagnoses,” PLoS Comput. Biol., 2007, 3(11):2072-2086. [cited by applicant]
Baron et al., “Single-cell transcriptomics reveal the dynamic of haematopoietic stem cell production in the aorta,” Nat Commun, Jun. 2018, 9(1):2517, 15 pages. [cited by applicant]
Baumann and Gauldie, “The acute phase response,” Immunol Today, Feb. 1994, 15(2):74-80. [cited by applicant]
Borghans et al., “Current best estimates for the average lifespans of mouse and human leukocytes: reviewing two decades of deuterium-labeling experiments,” Immunol Rev, Sep. 2018, 285(1):233-248. [cited by applicant]
Bosman et al., “Erythrocyte ageing in vivo and in vitro: structural aspects and implications for transfusion,” Transfus Med, Dec. 2008, 18(6):335-347. [cited by applicant]
Bunn, “Erythropoietin,” Cold Spring Harb Perspect Med, 2013, 3:a011619, 21 pages. [cited by applicant]
Cabitza et al., “Unintended consequences of machine learning in medicine,” JAMA, Aug. 2017, 318(6):517-518, 2 pages. [cited by applicant]
CDC.Gov [online], “Clinical Growth Charts,” Jun. 16, 2017, retrieved on Jun. 5, 2021, retrieved from URL<https://www.cdc.gov/growthcharts/clinical_charts.htm#Set1>, 5 pages. [cited by applicant]
Chaturvedi et al., “Evaluation of multiplexed cytokine and inflammation marker measurements: a methodologic study,” Cancer Epidemiol Biomarkers Prev, 2011, 20(9):1902-1911. [cited by applicant]
Chaudhury et al., “Single-cell modeling of routine clinical blood tests reveals transient dynamics of human response to blood loss,” eLife, Dec. 2019, 8:e48590, 12 pages. [cited by applicant]
Chaudhury et al., “White blood cell population dynamics for risk stratification of acute coronary syndrome,” Proc Natl Acad Sci, Nov. 2017, 114(46):12344-12349. [cited by applicant]
Chen and Asch, “Machine learning and prediction in medicine—beyond the peak of inflated expectations,” N Engl J Med, Jun. 2017, 376(26):2507-2509. [cited by applicant]
Dijkstra et al., “Whole blood donation affects the interpretation of hemoglobin A1c,” PLoS One, Jan. 2017, 12(1):e0170802, 12 pages. [cited by applicant]
Dornhorst, “Analytical Review: The Interpretation of Red Cell Survival Curves,” Blood, Dec. 1951, 6(12):1284-1292. [cited by applicant]
Foy et al., “Human acute inflammatory recovery is defined by co-regulatory dynamics of white blood cell and platelet populations,” Nat Commun, Aug. 2022, 13(1):4705, 10 pages. [cited by applicant]
Gabay and Kushner, “Acute-phase proteins and other systemic responses to inflammation,” N Engl J Med, Feb. 1999, 340(6):448-454, 8 pages. [cited by applicant]
Giustacchini et al., “Single-cell transcriptomics uncovers distinct molecular signatures of stem cells in chronic myeloid leukemia,” Nat Med, Jun. 2017, 23(6):692-702, 14 pages. [cited by applicant]
Head et al., “The extent and consequences of p-hacking in science,” PLoS Biol, Mar. 2015, 13(3):e1002106, 15 pages. [cited by applicant]
Hoda et al., “Robbins and Cotran Pathologic Basis of Disease,” Am J Clin Pathol, Dec. 2020, 154(6):869. [cited by applicant]
International Preliminary Report on Patentability in International Appln. No. PCT/US2020/047173, dated Mar. 3, 2022, 9 pages. [cited by applicant]
International Search Report and Written Opinion in International Appln. No. PCT/US2020/047173, dated Jan. 21, 2021, 12 pages. [cited by applicant]
Invitation to Pay Additional Fees And, Where Applicable, Protest Fee in International Appln. No. PCT/US2020/047173, dated Nov. 3, 2020, 2 pages. [cited by applicant]
Johnson et al., “Machine learning and decision support in critical care,” Proceedings of the IEEE Inst Electr Electron Eng, Feb. 2016, 104(2):444-466. [cited by applicant]
Khera et al., “Abstract: Measurement Of Erythrocyte Survival In Vivo using a Stable Isotope Label In Sickle Cell Anemia,” Blood, Nov. 2013, 122(21):2223, 3 pages (Abstract only). [cited by applicant]
Kim and Ornstein, “Isovolumetric sphering of erythrocytes for more accurate and precise cell volume measurement by flow cytometry,” Cytometry, May 1983, 3(6):419-427. [cited by applicant]
Kotas and Medzhitov, “Homeostasis, inflammation, and disease susceptibility,” Cell, Feb. 2015, 160(5):816-827. [cited by applicant]
Kuczmarski et al., “CDC growth charts: United States,” Adv Data, Jun. 2000, 314:1-27, 28 pages. [cited by applicant]
Leuschner et al., “Rapid monocyte kinetics in acute myocardial infarction are sustained by extramedullary monocytopoiesis,” J Exp Med, Jan. 2012, 209(1):123-37. [cited by applicant]
Liu et al., “Statistical significance of clustering for high-dimension, low-sample size data,” J Am Stat Assoc, Sep. 2008, 103(483):1281-1293. [cited by applicant]
Malka et al., “Mechanistic modeling of hemoglobin glycation and red blood cell kinetics enables personalized diabetes monitoring,” Sci Transl Med, Oct. 2016, 8(359):359ra130, 9 pages. [cited by applicant]
Medzhitov, “Origin and physiological roles of inflammation,” Nature, Jul. 2008, 454(7203):428-435. [cited by applicant]
Mohandas et al., “Accurate and independent measurement of volume and hemoglobin concentration of individual red cells by laser light scattering,” Blood, Aug. 1986, 68(2):506-513. [cited by applicant]
Obermeyer and Emanuel, “Predicting the future—big data, machine learning, and clinical medicine,” N Engl J Med, Sep. 2016, 375(13):1216-9. [cited by applicant]
O'Brien et al. “The Society of Thoracic Surgeons 2008 Cardiac Surgery Risk Models: Part 2—Isolated Valve Surgery,” Ann Thorac Surg, Jul. 2009, 88(1 Suppl):S23-42. [cited by applicant]
O'Brien et al. “The Society of Thoracic Surgeons 2008 Cardiac Surgery Risk Models: Part 2—Statistical Methods and Results,” Ann Thorac Surg, May 2018, 105(5):1419-1428. [cited by applicant]
Özcan et al., “Red cell distribution width and inflammation in patients with non-dipper hypertension,” Blood Press, Apr. 2013, 22(2):80-5. [cited by applicant]
Pechenizkiy et al., “PCA-based feature transformation for classification: issues in medical diagnostics,” Paper, Presented at Proceedings of the IEEE Symposium on Computer-Based Medical Systems, Bethesda, MD, Jun. 23-25… [cited by applicant]
Piva et al., “Clinical Utility of Reticulocyte Parameters,” Clin Lab Med, 2015, 35:133-163. [cited by applicant]
Shahian et al., “The Society of Thoracic Surgeons 2008 Cardiac Surgery Risk Models: Part 1—Background, Design Considerations, and Model Development,” Ann Thorac Surg, 2018, 105:1411-8. [cited by applicant]
Shahian et al., “The Society of Thoracic Surgeons 2008 Cardiac Surgery Risk Models: Part 1—Coronary Artery Bypass Grafting Surgery,” Ann Thorac Surg, Jul. 2009, 88(1 Suppl):S2-22. [cited by applicant]
Shalek et al., “Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells,” Nature, Jun. 2013, 498(7453):236-40, 13 pages. [cited by applicant]
Shameer et al., “Machine learning in cardiovascular medicine: Are we there yet?,” Heart, Jul. 2018, 104(14):1156-1164. [cited by applicant]
Shrestha et al., “Models for the red blood cell lifespan,” J Pharmacokinet Pharmacodyn., Jun. 2016, 43(3):259-74, 16 pages. [cited by applicant]
Tibble et al., “Use of surrogate markers of inflammation and Rome criteria to distinguish organic from nonorganic intestinal disease,” Gastroenterology, Aug. 2002, 123(2):450-60. [cited by applicant]
Tusi et al., “Population snapshots predict early haematopoietic and erythroid hierarchies,” Nature, Mar. 2018, 555(7694):54-60, 31 pages. [cited by applicant]
UpToDate.com [online], “Regulation of erythropoiesis,” Sep. 2022, retrieved on Oct. 3, 2022, retrieved from URL<https://www.uptodate.com/contents/regulation-of-erythropoiesis#!>, 9 pages. [cited by applicant]
Wikipedia.org [online], “Hematology analyzer,” Jul. 14, 2019, retrieved on Oct. 23, 2020, retrieved from URL<https://en.wikipedia.org/w/index.phptitle=Hernatology_analyzer&oldid=906172508>, 3 pages. [cited by applicant]
Alashwal et al., “The Application of Unsupervised Clustering Methods to Alzheimer's Disease,” Frontiers in Computational Neuroscience, May 2019, 13:31, 9 pages. [cited by applicant]
Chen et al., “Inflammatory responses and inflammation associated diseases in organs,” Oncotarget, Dec. 2017, 9(6):7204-7218. [cited by applicant]
Fahey et al., “Development and validation of clinical prediction models for mortality, functional outcome and cognitive impairment after stroke: a study protocol,” BMJ Open, Aug. 2017, 7(8):e014607, 5 pages. [cited by applicant]
International Search Report and Written Opinion in International Appln. No. PCT/US2022/072988, mailed Sep. 23, 2022, 13 pages. [cited by applicant]
Lou et al., “Clinical usefulness of measuring red blood cell distribution width in patients with hepatitis B,” PLoS One, 2012, 7(5):e37644, 6 pages. [cited by applicant]
Mori et al., “Protocol for project recovery after cardiac surgery: a single-center cohort study leveraging digital platform to characterise longitudinal patient-reported postoperative recovery patterns,” BMJ Open, Sep. … [cited by applicant]
Santimone et al., “White blood cell count, sex and age are major determinants of heterogeneity of platelet indices in an adult general population: results from the MOLI-SANI project,” Haematologica, Aug. 2018, 96(8):118… [cited by applicant]
Ultsch and Lötsch, “Machine-learned cluster identification in high-dimensional data,” J Biomed Inform., Feb. 2017, 66:95-104. [cited by applicant]
Visweswaran et al., “Patient-Specific Models for Predicting the Outcomes of Patients with Community Acquired Pneumonia,” AMIA Annu Symp Proc., 2005, 2005:759-63. [cited by applicant]
Zhang et al., “Platelet-to-white blood cell ratio: A novel and promising prognostic marker for HBV-associated decompensated cirrhosis,” J Clin Lab Anal., Dec. 2020, 34(12):e23556, 6 pages. [cited by applicant]
International Preliminary Report on Patentability in International Appln. No. PCT/US2022/072988, mailed Dec. 28, 2023, 11 pages. [cited by applicant]