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Glioblastoma (GBM) is the most aggressive primary brain tumor in adults, with a universally lethal prognosis despite maximal standard therapies. Here, we present a consensus treatment protocol based on the metabolic requirements of GBM cells for the two major fermentable fuels: glucose and glutamine. Glucose is a source of carbon and ATP synthesis for tumor growth through glycolysis, while glutamine provides nitrogen, carbon, and ATP synthesis through glutaminolysis. As no tumor can grow without anabolic substrates or energy, the simultaneous targeting of glycolysis and glutaminolysis is expected to reduce the proliferation of most if not all GBM cells. Ketogenic metabolic therapy (KMT) leverages diet-drug combinations that inhibit glycolysis, glutaminolysis, and growth signaling while shifting energy metabolism to therapeutic ketosis. The glucose-ketone index (GKI) is a standardized biomarker for assessing biological compliance, ideally via real-time monitoring. KMT aims to increase substrate competition and normalize the tumor microenvironment through GKI-adjusted ketogenic diets, calorie restriction, and fasting, while also targeting glycolytic and glutaminolytic flux using specific metabolic inhibitors. Non-fermentable fuels, such as ketone bodies, fatty acids, or lactate, are comparatively less efficient in supporting the long-term bioenergetic and biosynthetic demands of cancer cell proliferation. The proposed strategy may be implemented as a synergistic metabolic priming baseline in GBM as well as other tumors driven by glycolysis and glutaminolysis, regardless of their residual mitochondrial function. Suggested best practices are provided to guide future KMT research in metabolic oncology, offering a shared, evidence-driven framework for observational and interventional studies., Competing Interests: Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: A.P. is an owner of Poff Medical Consulting and Communications, LLC, which performs consulting and public speaking services related to ketogenic metabolic therapy. A.P. is a scientific advisor to Pruvit Ventures, LLC, which sells exogenous ketone products. A.P. is an owner of Metabolic Health Initiative, LLC which is a medical education company in the field of metabolic health and metabolism-based therapies. A.P. is an inventor on and receives royalties from the following patent: “Targeting Cancer with Metabolic Therapy and Hyperbaric Oxygen” (Patent Number: 9801903). D.P.D. is an inventor of patents on the use of exogenous ketones, advisor for Levels Health, and co-owner of Ketone Technologies LLC, which does consulting and public speaking events. C.E.C. receives royalties from books, consulting, and lectures on nutrition and exercise, and serves on the scientific advisory board of Simply Good Foods/Atkins. M.K. is employed by Dietary Therapies LLC. The other authors declare no competing interests., (© 2024. The Author(s).)

Frontiers requested research on how a systems approach can explore the mechanisms of cardiovascular complications in Covid-19. The focus of this paper will thus be on these detailed mechanisms. It will elucidate the integrated pathogenic pathways based on an extensive review of literature. Many severe Covid-19 cases and deaths occur in patients with chronic cardiovascular comorbidities. To help understand all the mechanisms of this interaction, Covid-19 complications were integrated into a pre-existing systems-based coronary heart disease (CHD) model. Such a complete model could not be found in literature. A fully integrative view could be valuable in identifying new pharmaceutical interventions , help understand how health factors influence Covid-19 severity and give a fully integrated explanation for the Covid-19 death spiral phenomenon seen in some patients. Covid-19 data showed that CHD hallmarks namely, Hypercoagulability, Hypercholesterolemia, Hyperglycemia/Hyperinsulinemia, Inflammation and Hypertension have an important effect on disease severity. The pathogenic pathways that Covid-19 activate in CHD were integrated into the CHD model. This fully integrated model presents a visual explanation of the mechanism of interaction between CHD and Covid-19 complications. This includes a detailed integrated explanation of the death spiral as a result of interactions between Inflammation , endothelial cell injury, Hypercoagulability and hypoxia. Additionally, the model presents the aggravation of this death spiral through the other CHD hallmarks namely, Hyperglycemia/Hyperinsulinemia, Hypercholesterolemia , and/or Hypertension . The resulting model further suggests systematically how the pathogenesis of nine health factors (stress, exercise, smoking, etc.) and seven pharmaceutical interventions (statins, salicylates, thrombin inhibitors, etc.) may either aggravate or suppress Covid-19 severity. A strong association between CHD and Covid-19 for all the investigated health factors and pharmaceutical interventions , except for β-blockers, was found. It is further discussed how the proposed model can be extended in future to do computational analysis to help assess the risk of Covid-19 in cardiovascular disease. With insight gained from this study, recommendations are made for future research in potential new pharmacotherapeutics. These recommendations could also be beneficial for cardiovascular disease, which killed five times more people in the past year than Covid-19., Competing Interests: This study received funding from HumanSim (Pty) Ltd. The funder was not involved in the study design, collection, analysis,interpretation of data, the writing of this article or the decision to submit it for publication. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Meyer, Mathews, Gous and Mathews.)

Objective: Although metabolic treatment of highly glycolytic cancers and metastases is becoming an important research field, the effects of such treatments are not fully quantified yet. In this article we attempt to quantify the effect of long-term glucose deprivation (similar to ketogenic diets) on cancer cells using in vitro tests., Methods: Two tumorigenic cell lines were used, namely a metastatic breast and a cervical cancer cell line. The non-tumorigenic control cell line was an immortalized breast cell line. All the cell lines were stabilized at a typical average human blood glucose level of 6 mmol/L. The cell lines were then exposed to the therapeutic blood glucose level of 3 mmol/L for 90 d., Results: The tests indicated that glucose deprivation restricted the different cancer cell lines' growth more than that of non-tumorigenic cells. The different cell lines were also differentially affected, which suggests that long-term glucose deprivation will not be equally effective for different types of cancer. The highly glycolytic breast cancer cell line was most adversely affected, with cell growth decreasing to 30% after 26 d. Cell growth was stable at this level for up to 22 d. Furthermore, all of the other cancer cell lines were similarly affected., Conclusions: This in vitro data could help to direct future human in vivo tests to find the most therapeutic time (cancer cells at their most vulnerable) for additional short-term adjuvant therapies. Partial recovery of proliferation occurred after 90 d. Therefore, as expected, the results also indicated that without an adjuvant treatment, full extinction cannot be reached with the proposed long-term metabolic treatment. The need for more clinical data on long-term glucose deprivation treatments for cancer is well described in the literature. This paper attempts to add to the available pool of knowledge., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Most proliferating cancer cells and cancer-associated tumor stroma have an upregulated glucose energy demand in relation to normal cells. Cancer cells are further less metabolically flexible than normal cells. They can therefore not survive metabolic stress as well as normal cells can. Metabolic deprivation thus provides a potential therapeutic window. Unfortunately, current glucose blockers have toxicity problems. An alternative way to reduce a cancer patient's blood glucose (BG), for a short-term period to very low levels, without the concomitant toxicity, is hypothesized in this paper. In vitro tests have shown that short-term BG deprivation to 2 mmol/L for 180 min is an effective cancer treatment. This level of hypoglycaemia can be maintained in vivo with a combination of very low-dose insulin and the suppression of the glucose counter-regulation system. Such suppression can be safely achieved by the infusion of somatostatin and a combination of both α and β-blockers. The proposed short-term in vivo method, was shown to be non-toxic and safe for non-cancer patients. The next step is to test the effect of the proposed method on cancer patients. It is also suggested to incorporate well-known, long-term BG deprivation treatments to achieve maximum effect., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Background: Moderate exercise is associated with a lower risk for coronary heart disease (CHD). A suitable integrated model of the CHD pathogenetic pathways relevant to moderate exercise may help to elucidate this association. Such a model is currently not available in the literature., Methods: An integrated model of CHD was developed and used to investigate pathogenetic pathways of importance between exercise and CHD. Using biomarker relative-risk data, the pathogenetic effects are representable as measurable effects based on changes in biomarkers., Results: The integrated model provides insight into higherorder interactions underlying the associations between CHD and moderate exercise. A novel 'connection graph' was developed, which simplifies these interactions. It quantitatively illustrates the relationship between moderate exercise and various serological biomarkers of CHD. The connection graph of moderate exercise elucidates all the possible integrated actions through which risk reduction may occur., Conclusion: An integrated model of CHD provides a summary of the effects of moderate exercise on CHD. It also shows the importance of each CHD pathway that moderate exercise influences. The CHD risk-reducing effects of exercise appear to be primarily driven by decreased inflammation and altered metabolism.

Background: It is well documented that there is some correlation between poor oral health in the form of periodontal disease and coronary heart disease (CHD). It is unclear whether this correlation is due to a causal relationship or shared underlying disorder such as inflammation. A suitable integrated model of the CHD pathogenetic pathways relevant to periodontal disease may help to elucidate the association. Such a model is currently not available in literature., Methods: A previously developed integrated model of CHD was used to investigate potential pathogenetic pathways linking periodontal disease to CHD biomarkers., Results: The integrated model was created to provide insight into possible higher-order biological interactions underlying CHD and periodontal disease. In order to simplify these interactions a novel 'connection graph' was developed. It quantitatively illustrates the relationship between periodontal disease and various serological biomarkers of CHD. The pathogenesis of periodontitis shows various possible pathways which could link periodontitis to CHD pathogenesis., Conclusion: An integrated model of CHD was developed which provides a summary of the potential CHD effects of periodontal disease. Further research must refine and validate the model.

Background: Depression is known to increase the risk for coronary heart disease (CHD) likely through various pathogenetic actions. Understanding the links between depression and CHD and the effects of mediating these links may prove beneficial in CHD prevention., Methods: An integrated model of CHD was used to elucidate pathogenetic pathways of importance between depression and CHD. Using biomarker relative risk data the pathogenetic effects are representable as measurable effects based on changes in biomarkers., Results: A 'connection graph' presents interactions by illustrating the relationship between depression and the biomarkers of CHD. The use of selective serotonin reuptake inhibitors (SSRIs) is postulated to have potential to decrease CHD risk. Comparing the 'connection graph' of SSRI's to that of depression elucidates the possible actions through which risk reduction may occur., Conclusions: The CHD effects of depression appear to be driven by increased inflammation and altered metabolism. These effects might be mediated with the use of SSRI's.

Background: Due to their high proliferative requirements, tumorigenic cells possess altered metabolic systems whereby cells utilize higher quantities of glutamine and glucose. These altered metabolic requirements make it of interest to investigate the effects of physiological non-tumorigenic concentrations of glucose and glutamine on tumorigenic cells since deprivation of either results in a canonical amino acid response in mammalian cell., Methods: The influence of short-term exposure of tumorigenic cells to correlating decreasing glutamine- and glucose quantities were demonstrated in a highly glycolytic metastatic breast cell line and a cervical carcinoma cell line. Thereafter, cells were propagated in medium containing typical physiological concentrations of 1 mM glutamine and 6 mM glucose for 7 days. The effects on morphology were investigated by means of polarization-optical transmitted light differential interference contrast. Flow cytometry was used to demonstrate the effects of glutamine-and glucose starvation on cell cycle progression and apoptosis induction. Fluorometrics were also conducted to investigate the effects on intrinsic apoptosis induction (mitocapture), reactive oxygen species production (2,7-dichlorofluorescein diacetate) and acidic vesicle formation (acridine orange)., Results: Morphological data suggests that glutamine-and glucose deprivation resulted in reduced cell density and rounded cells. Glutamine-and glucose starvation also resulted in an increase in the G2M phase and a sub-G1 peak. Complete starvation of glutamine and glucose resulted in the reduction of the mitochondrial membrane potential in both cell lines with MDA-MB-231 cells more prominently affected when compared to HeLa cells. Further, starved cells could not be rescued sufficiently by propagating since cells possessed an increase in reactive oxygen species, acidic compartments and vacuole formation., Conclusion: Starvation from glutamine and glucose for short periods resulted in decreased cell density, rounded cells and apoptosis induction by means of reactive oxygen species generation and mitochondrial dysfunction. In addition, the metastatic cell line reacted more prominently to glutamine-and glucose starvation due to their highly glycolytic nature. Satisfactory cellular rescue was not possible as cells demonstrated oxidative stress and depolarized mitochondrial membrane potential. This study contributes to the knowledge regarding the in vitro effects and signal transduction of glucose and/or l-glutamine deprivation in tumorigenic cell lines.

Background: Moderate alcohol consumption is associated with a lower risk for coronary heart disease (CHD). A suitably integrated view of the CHD pathogenesis pathway will help to elucidate how moderate alcohol consumption could reduce CHD risk., Methods: A comprehensive literature review was conducted focusing on the pathogenesis of CHD. Biomarker data were further systematically analysed from 294 cohort studies, comprising 1 161 560 subjects. From the above a suitably integrated CHD pathogenetic system for the purpose of this study was developed., Results: The resulting integrated system now provides insight into the integrated higher-order interactions underlying CHD and moderate alcohol consumption. A novel 'connection graph' further simplifies these interactions by illustrating the relationship between moderate alcohol consumption and the relative risks (RR) attributed to various measureable CHD serological biomarkers. Thus, the possible reasons for the reduced RR for CHD with moderate alcohol consumption become clear at a glance., Conclusions: An integrated high-level model of CHD, its pathogenesis, biomarkers, and moderate alcohol consumption provides a summary of the evidence that a causal relationship between CHD risk and moderate alcohol consumption may exist. It also shows the importance of each CHD pathway that moderate alcohol consumption influences.

Background: Diet has a significant relationship with the risk of coronary heart disease (CHD). Traditionally the effect of diet on CHD was measured with the biomarker for low-density lipoprotein (LDL) cholesterol. However, LDL is not the only or even the most important biomarker for CHD risk. A suitably integrated view of the mechanism by which diet influences the detailed CHD pathogenetic pathways is therefore needed in order to better understand CHD risk factors and help with better holistic CHD prevention and treatment decisions., Methods: A systematic review of the existing literature was conducted. From this an integrated CHD pathogenetic pathway system was constructed. CHD biomarkers, which are found on these pathways, are the only measurable data to link diet with these CHD pathways. They were thus used to simplify the link between diet and the CHD mechanism. Data were systematically analysed from 294 cohort studies of CHD biomarkers constituting 1 187 350 patients., Results and Discussion: The resulting integrated analysis provides insight into the higher-order interactions underlying CHD and high-glycemic load (HGL) diets. A novel "connection graph" illustrates the measurable relationship between HGL diets and the relative risks attributed to the important CHD serological biomarkers. The "connection graph" vividly shows that HGL diets not only influence the lipid and metabolic biomarkers, but also the inflammation, coagulation and vascular function biomarkers in an important way., Conclusion: A focus primarily on the low density lipoprotein cholesterol biomarker for CHD risk has led to the traditional guidelines of CHD dietary recommendations. This has however inadvertently led to HGL diets. The influence of HGL diets on the other CHD biomarkers is not always fully appreciated. Thus, new diets or other interventions which address the full integrated CHD impact, as shown in this paper, are required.

Objective: Most glucose (and glutamine)-deprivation studies of cancer cell cultures focus on total depletion, and are conducted over at least 24 h. It is difficult to extrapolate findings from such experiments to practical anti-glycolytic treatments, such as with insulin-inhibiting diets (with 10%-50% carbohydrate dietary restriction) or with isolated limb perfusion therapy (which usually lasts about 90 min). The aim of this study was to obtain experimental data on the effect of partial deprivation of d-glucose and l-glutamine (to typical physiological concentrations) during 0 to 6-h exposures of HeLa cells., Methods: HeLa cells were treated for 0 to 6 h with 6 mM d-glucose and 1 mM l-glutamine (normal in vivo conditions), 3 mM d-glucose and 0.5 mM l-glutamine (severe hypoglycemic conditions), and 0 mM d-glucose and 0 mM l-glutamine ("starvation"). Polarization-optical differential interference contrast and phase-contrast light microscopy were employed to investigate morphologic changes., Results: Reduction of glucose levels from 6 to 3 mM (and glutamine levels from 1 to 0.5 mM) brings about cancer cell survival of 73% after 2-h exposure and 63% after 4-h exposure. Reducing glucose levels from 6 to 0 mM (and glutamine levels from 1 to 0 mM) for 4 h resulted in 53% cell survival., Conclusion: These data reveal that glucose (and glutamine) deprivation to typical physiological concentrations result in significant cancer cell killing after as little as 2 h. This supports the possibility of combining anti-glycolytic treatment, such as a carbohydrate-restricted diet, with chemotherapeutics for enhanced cancer cell killing., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Blood glucose (BG) is the primary metabolic fuel for, among others, cancer cell progression, cardiovascular disease and inflammation. Stress is an important contributor to the amount of BG produced especially by the liver. In this paper, we attempt to quantify the BG production due to chronic (in the order of weeks) high-level psychological stress in a manner that a lay person will understand. Three independent approaches were used. The first approach was based on a literature survey of stress hormone data from healthy individuals and its subsequent mathematical manipulation. The next approach was a deductive process where BG levels could be deduced from published stress data of large cardiovascular clinical trials. The third approach used empirical BG data and a BG simulation model. The three different methods produced an average BG increase of 2.2-fold above basal for high levels of stress over a period of more than a day. The standard deviation normalized to the average value was 4.5%., (Copyright © 2011 John Wiley & Sons, Ltd.)

Background: Previous work derived a theoretically rigorous bolus insulin model. It was shown that the new model predicts insulin response of subjects without diabetes substantially better than the carbohydrate counting method (CHOcm). As most individuals with type 1 diabetes use the CHOcm, this article investigates if the new model can be applied to them., Methods: Equations are derived to characterize a person with type 1 diabetes. These are implemented on a cell phone that calculates bolus insulin dosages. In a small feasibility study the cell phone was used by 11 patients. Basal insulin remained unchanged. The subjects were experienced in the CHOcm and were using it at the start of the study. Continuous glucose monitoring data were recorded to capture blood glucose (BG) control elements such as average BG and tightness of control, as well as hypoglycemic and hyperglycemic events. A new rating method was proposed to estimate BG control. It (or a derivative thereof ) may in the future become a valuable measure of total glycemic control. We used the status quo ante versus status quo approach to find indicative results. BG control for the same group when using CHOcm (status quo ante) was compared with BG control when using the new application (status quo)., Results: Patients found the new application on the cell phone practical. Indicative results also showed BG control improvements, although the subjects were more experienced in the CHOcm. Depending on the weights assigned to the underlying control elements an improvement of between 26% and 64% was found., Conclusion: An indicative study (status quo ante vs. status quo) on 11 patients with type 1 diabetes showed that the new method can be practically and successfully applied on a cell phone. Glycemic control even improved. A new BG rating method was proposed. We believe there is enough preliminary indication to warrant a more detailed clinical trial in future by an institution with adequate funds and access to more patients.

Many difficult-to-treat solid cancer tumours and metastases have high-glucose uptake, usually under hypoxic conditions. Hypoxic tumours suppress the immune system and are insensitive to traditional chemoradiotherapies. The only therapy usually available is surgical resection. However, with widespread metastases, surgery often becomes unviable. Surgery in itself can also result in metastasis. The need for investigating adjuvant treatments is obvious. Here we investigate whether the high-glucose uptake of hypoxic tumours could lead to such a treatment. Before any treatment can be hypothesised, it is crucial to understand how this glycolytic cancer phenotype fits in with the normal body's blood glucose cycle. The brain creates the healthy body's largest demand for blood glucose (BG) and ensures a very high level of control on in vivo supply. It is hypothesised that, through somatic evolution, high-glycolytic cancer cells opportunistically tap into this very stable energy environment. It is shown that therapies which target the glycolytic cancers' high BG needs cannot be developed without addressing the brain's energy needs. Based on this knowledge, and to initiate thinking on potential BG therapies, a first attempt is made at hypotheses for potential control of the in vivo brain demand as well as the available in vivo BG. The aim is to adversely affect primary as well as metastatic tumours without damaging brain and innocent bystander cells., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

Background: Patients with type 1 diabetes usually use the carbohydrate (CHO) counting method to establish their bolus insulin need. However, most still struggle with blood glucose control. We believe that for good control their insulin requirements should strive to mimic the insulin secretion of those without diabetes. The objective here is to develop, from first principles, a better model than the CHO counting model for calculating the bolus insulin need of subjects without diabetes. Such a model may also provide better blood glucose control for patients with type 1 diabetes. This will be investigated in a future article., Methods: Equations for metabolism of CHO and for insulin response were derived from first principles. Clinical trials were used to verify these models. The final results--namely, the new bolus insulin requirement equations--were verified using clinical trials by other researchers (Wolever and co-workers). Their methods used are described in their articles given in the list of references., Results: The postprandial insulin secretion relationships resulted in an average Pearson R(2) of 0.807 (for the new method) versus the old method's R(2) of 0.562 (CHO counting)., Conclusions: The newly derived equation provides a better approximation than the CHO counting method of insulin secretion due to metabolized blood glucose energy from ingested carbohydrates for those without diabetes. We believe that insulin dosage requirements for a patient with type 1 diabetes should mimic the insulin secretion of those without diabetes. If this is true, it means that the new equation should also estimate bolus insulin need for a patient with type 1 diabetes more accurately than before. This will be investigated in a future article.