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It has been almost 18 months since the first outbreak of COVID-19 disease was reported in Wuhan, China. This unexpected devastating phenomenon, raised a great deal of concerns and anxiety among people around the world and imposed a huge economic burden on the nations’ health care systems. Accordingly, clinical scientists, pharmacologists and physicians worldwide felt an urgent demand for a safe, effective therapeutic agent, treatment strategy or vaccine in order to prevent or cure the recently-emerged disease. Initially, due to the lack of specific pharmacological agents and approved vaccines to combat the COVID-19, the disease control in the confirmed cases was limited to supportive care. Accordingly, repositioning or repurposing current drugs and examining their possible therapeutic efficacy received a great deal of attention. Despite revealing promising results in some clinical trials, the overall results are conflicting. For this reason, there is an urgent need to seek and investigate other potential therapeutics. Mesenchymal stem cells (MSC), representing immunomodulatory and regenerative capacity to treat both curable and intractable diseases, have been investigated in COVID-19 clinical trials carried out in different parts of the world. Nevertheless, up to now, none of the MSC-based approaches has been approved in controlling COVID-19 infection. Thanks to the fact that the final solution for defeating the pandemic is developing a safe, effective vaccine, enormous efforts and clinical research have been carried out. In this review, we will concisely discuss the safety and efficacy of the most relevant pharmacological agents, MSC-based approaches and candidate vaccines for treating and preventing COVID-19 infection.

Spinal cord injury (SCI) is a central nervous system (CNS) devastate event that is commonly caused by traumatic or non-traumatic events. The reinnervation of spinal cord axons is hampered through a myriad of devices counting on the damaged myelin, inflammation, glial scar, and defective inhibitory molecules. Unfortunately, an effective treatment to completely repair SCI and improve functional recovery has not been found. In this regard, strategies such as using cells, biomaterials, biomolecules, and drugs have been reported to be effective for SCI recovery. Furthermore, recent advances in combinatorial treatments, which address various aspects of SCI pathophysiology, provide optimistic outcomes for spinal cord regeneration. According to the global importance of SCI, the goal of this article review is to provide an overview of the pathophysiology of SCI, with an emphasis on the latest modes of intervention and current advanced approaches for the treatment of SCI, in conjunction with an assessment of combinatorial approaches in preclinical and clinical trials. So, this article can give scientists and clinicians' clues to help them better understand how to construct preclinical and clinical studies that could lead to a breakthrough in spinal cord regeneration.

The respiratory system is a complex group of organs in the human body, all of which are necessary in breathing. Due to its special anatomy and composition, after exposure to various damaging factors such as micro particles, carbon granules and toxic gases, the respiratory system can be affected by a variety of damage without return to its original state. Currently, the prevalence of lung diseases, including asthma, and chronic obstructive pulmonary diseases, such as emphysema, has increased remarkably. New therapeutic approaches are desperately needed to discover regenerative medicine approaches, especially cell therapy. This review summarizes the recent advances in stem cell treatments and the research efforts conducted through the application of stem cell therapy for respiratory system diseases. In particular, researchers have used animal models to gather data about treating lung injury by stem cell transplantation. This review concentrated on the findings about route, timing and adjustment of cell transplantation dose, optimum stem cell type selection and potency marker of cells as therapeutic agents. These factors are essential subjects for approval and clinical transplantation. The current clinical trials aiming at treatment of lung diseases by stem cells are mentioned and discussed.

Background: The main goal of using statins is to reduce the level of plasma cholesterol, meanwhile they have a wide spectrum of actions. Objectives: To identify the effect of statins on fractional cholesterol esterification (FCE) as well as the complete profile of lipids and (apo)lipoproteins. Design and methods: In an age and sex matched case-control study, 400 subjects who were referred for coronary angiography were divided into two groups according using statins. Results: Total cholesterol was decreased significantly following treatment with statins (165.6 ± 38.0 mg/dL vs. 205.3 ± 48.4, p≤0.001). About 90% of the reduction was occurred in nonHDL and 10% in HDL fraction. Reduction of nonHDL cholesterol (125.2 ± 35.2 mg/dL vs. 162.8 ± 45.2, p≤0.001) occurred on both unesterified (52.4 ± 21.5 mg/dL vs. 65.2 ± 25.5, p≤0.001) and esterified cholesterol (74.7 ± 27.3 mg/dL vs. 96.6 ± 34.1, p≤0.001). But the decrease in HDL cholesterol (40.4 ± 10.0 mg/dL vs. 42.3 ± 9.9, p≤0.079) happened exclusively in unesterified fraction (10.9 ± 3.4 vs. 15.2 ± 5.1, p≤0.001) and was counterbalanced with a significant increase in esterified portion (29.5 ± 8.2 mg/dL vs. 27.2 ± 9.5, p≤0.020). The ratio of esterified- per total- cholesterol in HDL was 67.5 ± 8.1% in the control group and was decreased to 58.0 ± 14.9% (p≤0.01) in diabetes and CAD and increased to 73.5 ± 6.9 (p≤0.01) after using statins. Conclusions: The results suggest that the percent of esterified cholesterol in HDL fraction is decreased in diabetes and CAD patients and increased by using statins.

Skin wound healing, a dynamic physiological process, progresses through coordinated overlapping phases to restore skin integrity. In some pathological conditions such as diabetes, wounds become chronic and hard-to-heal resulting in substantial morbidity and healthcare costs. Despite much advancement in understanding mechanisms of wound healing, chronic and intractable wounds are still a considerable challenge to nations' health care systems. Extracellular matrix (ECM) components play pivotal roles in all phases of wound healing. Therefore, a better understanding of their roles during wound healing can help improve wound care approaches. The ECM provides a 3D structure and forms the stem cell niche to support stem cell adhesion and survival and to regulate stem cell behavior and fate. Also, this dynamic structure reserves growth factors, regulates their bioavailability and provides biological signals. In various diseases, the composition and stiffness of the ECM is altered, which as a result, disrupts bidirectional cell-ECM interactions and tissue regeneration. Hence, due to the impact of ECM changes on stem cell fate during wound healing and the possibility of exploring new strategies to treat chronic wounds through manipulation of these interactions, in this review, we will discuss the importance/impact of ECM in the regulation of stem cell function and behavior to find ideal wound repair and regeneration strategies. We will also shed light on the necessity of using ECM in future wound therapy and highlight the potential roles of various biomimetic and ECM-based scaffolds as functional ECM preparations to mimic the native stem cell niche.

Type 1 diabetes (T1D), a spontaneous autoimmune disease, is associated with destruction of insulin-producing β-cells in the pancreas. Since some heat shock proteins (HSP), such as HSP70 exert a protective effect in both tissues and cells, the present study was conducted to elucidate the effects of carbenoxolone (CBX) as an HSP70 inducer on T1D. The disease was induced in male C57BL/6 mice using streptozotocin (STZ) and subjects were allocated to therapeutic 1 and therapeutic 2 groups, as well as negative and positive control groups. The treated mice (therapeutic 1 and therapeutic 2 groups) received 50 mg/kg CBX intraperitoneally every 24 hours, in the therapeutic 1 group the drug was injected before and after disease induction whereas in the therapeutic 2 group the drug was injected only after disease induction. Serum fasting blood sugar (FBS) level, cytokines production (Interferon-gamma (IFN-γ), Interleukin 10 (IL-10), and IL-17), serum HSP70 level and CD4+CD25+Foxp3+ regulatory T cell (Treg) frequency measurements were outperformed 14 days after the last STZ injection. Our results showed that in the treated groups, serum HSP70, IFN-γ, and IL-17 levels were increased in contrast to the untreated groups. The IL-10 level was markedly decreased in comparison to untreated diabetic mice (p0.05). Our results confirm that CBX might through HSP70 induction, followed by increasing IFN-γ level leads to suppression of IL-10 production in diabetic mice resulted in toxic effects on pancreatic islet beta cells and deteriorating of disease.

Introduction: The risk for cardiovascular disease is increased in all stages of the impairment of renal function. It is proposed that serum creatinine is a marker of diabetes and coronary artery disease (CAD) as well as the kidney function. Aim: to study the association of serum creatinine with the likelihood and severity of CAD. The study population consisted of 262 males and 266 females who were classified as CAD cases and controls according to the results of coronary angiography. Results: Patients with CAD compared with the controls had increased levels of serum urea and creatinine. Serum creatinine showed significant positive correlation with male sex, hypertension and negative correlation with total- and HDL-cholesterol and apoAI. Serum urea, uric acid and potassium were the major determinants of creatinine. All hematological parameters were strong negative correlates of creatinine. None of markers of inflammation had significant correlation with creatinine. Creatinine was associated significantly with the prevalence [odds ratio of 1.79 (1.47-2.20), p

1. The vascular endothelium is injured by blood flow abnormalities exacerbated by different risk factors, including markers of haemoconcentration. The aim of the present study was to assess the association between markers of haemoconcentration and dehydration and the prevalence and severity of coronary artery disease (CAD). 2. Subjects in the present study (189 men and 126 women) were classified as either CAD cases or controls according to the results of coronary angiography. The severity of CAD was scored on the basis of the number and the extent of lesions on coronary arteries. Serum electrolytes, osmolality and haematological parameters were measured. 3. Compared with control subjects, patient with CAD had increased levels of serum osmolality, calculated osmolality, tonicity, sodium, glucose and blood urea nitrogen (BUN). Significant differences were also observed in the haematocrit and haemoglobin concentration, but not in erythrocyte counts and total serum protein. On multiple logistic regression analysis adjusting for major risk factors, serum osmolality, glucose and BUN exhibited significant associations with CAD, but the correlations were lessened by diabetes. Analysis using anova showed a significant correlation between serum osmolality, sodium, glucose and BUN and the severity of CAD. The area under the receiver operating characteristic curves, as a relative measure of the test's efficiency, was the highest and significant for serum osmolality, BUN and glucose. 4. The results indicate that some of the markers of dehydration and haemoconcentration are associated significantly with the prevalence and severity of CAD, but the independence of these correlations is questioned. These markers may play a role in the pathogenesis of atherosclerosis.

The terms osmotic pressure, osmotic coefficient, osmole, osmolarity, osmolality, effective osmolality and delta osmolality are formally defined. Osmole is unit of the amount of substance, one mole of nonionized impermeant solute is one osmole. Assuming an ideal solution, osmotic pressure (π) in mmHg is 19.3 times the osmolarity. Osmolarity is defined as the number of milliosmoles of the solutes per liter of solution. Suitable equations are presented for the rapid calculation of the osmolarity of different solutions. The concentrations of electrolytes are expressed by mEq/L that is, equal to their osmolarity as mOsm/L. If the solute concentration (C) is expressed as mg/L, mg/dL and g%, osmolarity is calculated as: C.n' /MW, C.n' (10)/MW and C.n' (10(4))/MW respectively. Osmolality is milliosmoles of solutes per one kilogram (or liter) of water of solution (plasma) and is calculated by osmolarity divided to plasma water. The osmolal concentration is corrected to osmolal activity by using the osmotic coefficient, φ. The salts of sodium (choloride and bicarbonate) and nonelectrolyte glucose and urea are the major five osmoles of plasma. The equation: Posm =2 [Na(+)]+glucose (mg/dL)/18+BUN (mg/dL)//2.8 is also the simplest and best formula to calculate plasma osmolality. The concentration of only effective osmoles evaluates effective osmolality or tonicity as: Eosm =2 [Na(+)]+glucose/18. The normal range of plasma tonicity is 275-295mOsm/kg of water. The difference between the measured and calculated osmolality is called osmolal gap. It is recommended to withdraw the formula of Dorwart-Chalmers from the textbooks and autoanalyzers and to use the simplest equation of Worthley et al. as the best equation for calculating serum osmolality. Furthermore the normal ranges of osmolal gap also must be corrected to 0±2mOsm/L.

Background The hypothesis is proposed that the atherogenicity of lipoporotein fractions is correlated with the content of unesterified cholesterol. Objectives To evaluate the role and prognostic values of unesterified and esterified cholesterol in lipoprotein fractions for coronary artery disease (CAD). Design and methods The study population consisted of 400 patients who were divided to CAD controls and cases according to the data of coronary angiography. Fractional cholesterol esterification (FCE) as well as the complete profile of lipids and (apo)lipoproteins were determined. Results Total cholesterol was increased significantly in CAD patients (196.3 ± 52.3 mg/dL vs. 185.7 ± 48.0, p≤ 0.049) and the increment occurred totally in unesterified portion (77.2 ± 28.4 mg/dL vs. 71.1 ± 24.4, p≤ 0.031). HDL cholesterol showed a significant decrease in CAD group (39.9 ± 9.5 mg/dL vs. 44.6 ± 10.5, p≤ 0.001), but the decrement occurred wholly in the esterified portion (26.2 ± 9.2 mg/dL vs. 31.1 ± 8.1, p≤ 0.001). NonHDL cholesterol was increased significantly in CAD group (156.8 ± 48.3 mg/dL vs. 140.3 ± 43.6, p≤ 0.001), and the changes occurred in both un- and esterified portions. FCE in HDL was diminished significantly in CAD patients (64.8 ± 13.9% vs. 69.3 ± 7.9, p≤ 0.01). In multivariate logistic regression analysis, unesterified cholesterol in NonHDL (UeNonHDLc) and esterified cholesterol in HDL (EsHDLc) excluded total cholesterol and HDLc respectively from the regression equation. In ROC analysis, the ratio of UeNonHDLc/EsHDLc was the strongest predictor for CAD among cholesterol subfractions. Conclusions The results confirm that UeNonHDLc is atherogenic and EsHDLc is antiatherogenic and are independent risk factors for CAD.

Background Low-density lipoprotein cholesterol (LDLc) can be calculated or measured directly and their accordance is the subject of controversy. Objectives The aim of this study was to identify the independent predictors of LDLc, to formulate the best equation for calculating LDLc and to evaluate the validity of it and the published formulas, including the new method with adjustable coefficient. Methods The profile of serum lipids and (apo)lipoproteins of 310 subjects was used to determine the most accurate formula for calculating serum LDLc. Serum lipids, lipoproteins and apolipoproteins were measured by enzymatic, new homogenous and immunoturbidometric methods, respectively. Results Multiple linear regression analysis indicates that total cholesterol, apoB, HDLc and triglyceride are independent predictors of LDLc. We proposed four new formulas to calculate LDLc. As total cholesterol (TC) is the major determinant of LDLc, it can be estimated simply as 0.545 of total cholesterol. Inclusion of HDLc, triglyceride, apoB and a constant value improved the equation slightly. The equation of: LDLc (mg/dl) = 0.75 TC − 0.5 HDLc − 0.1 TG had the lowest mean and SD of difference among all the methods examined here. LDLc was also calculated by the new modified Friedewald's equation using adjustable factor from Martin's table, but it did not improve the results significantly. LDLc gap was correlated significantly and positively with triglyceride and negatively with cholesterol or its subfractions. Conclusions Our data suggest the simplest formula: LDLc = 0.545 TC or a more detailed: LDLc = 0.75 TC − 0.5 HDLc − 0.1 TG be used for calculating serum LDLc.

It has been shown that microalbuminuria is an independent risk factor for cardiovascular diseases in diabetics, hypertensive patients and in the general population. However, few data has addressed the correlation of microalbuminuria with the severity of coronary artery disease (CAD). The aim of the study was to assess the association of microalbuminuria with the prevalence and severity of CAD.The subjects, 79 men and 74 women aged 45-70 years, were classified as CAD-negative and CAD-positive according to the results of coronary angiography. The severity of CAD was scored on the basis of the number and the extent of lesions within the coronary arteries. Urine albumin excretion was measured in 24 h urine samples by method of nephelometry.Coronary artery disease occurred more frequently in males than in females and in smokers than in non-smokers. There were no significant differences in the prevalence of hypertension and hypercholesterolemia between two groups. Microalbuminuria was more prevalent in CAD-positive patients than in controls (62.9% vs. 8.8%; por = 0.001). Patients with microalbuminuria compared with the controls had increased prevalence of one (15.3% vs. 7.4%, p pound 0.001), two (50% vs. 22.2%, por = 0.001), and three vessel disease (29.2% vs. 19.8%, por = 0.001). Microalbuminuria exhibited a significant correlation with the severity of CAD (r = 0.40; por = 0.001).Patients with microalbuminuria have more severe angiographically detected CAD than those without microalbuminuria. The results indicate that microalbuminuria exhibits a significant association with the presence and severity of CAD.

Background Synergistic interactions between elevated serum lipoprotein(a) [Lp(a)] and other unfavorable risk factors have been proposed to cause very high risk for coronary artery disease (CAD). The aim of this study was to examine the potential interactions between Lp(a) and other risk factors. Methods The profiles of serum (apo)(lipo)proteins, markers of inflammation, indicators of hemoconcentration as well as classical risk factors were determined in 264 clinically stable angiographically documented subjects. Correlation, linear and logistic regression and stratification analyses were performed. Results The frequency and severity of CAD and the prevalence of diabetes mellitus were significantly higher in the 3rd relative to 1st tertile of Lp(a). Subjects with Lp(a) levels in the upper tertile had significantly higher levels of serum glucose, total cholesterol and low-density lipoprotein cholesterol (LDL-C), apolipoprotein B (apoB), calcium, phosphate and their ion product. Bivariate correlation analysis indicated that serum Lp(a) was associated positively with the occurrence and severity of CAD, diabetes mellitus and the levels of serum glucose, cholesterol, LDL-C, apoB, calcium, phosphate and inversely to physical inactivity. In linear regression analysis, LDL-C (or apoB), diabetes, physical inactivity and phosphate were the major independent determinants of Lp(a) values. In multiple logistic regression analysis, after adjusting for major risk factors, Lp(a) showed a significant and independent association with the prevalence of CAD. By constructing dummy combined variables, elevated Lp(a) accompanied with diabetes or high levels of serum glucose, apoB and cholesterol exhibited an amplified high risk for CAD. Conclusions The results indicate that serum Lp(a) does interact multiplicatively with diabetes, apoB and cholesterol. The simultaneous assessment of Lp(a) and interactive risk factors enhances the discriminating value for CAD.

BACKGROUND The ratio of low- to high-density lipoprotein-cholesterol (LDL-C/HDL-C) conventionally represents the balance of proatherogenic and anti-atherogenic lipids. However, growing evidence supports the idea that the ratio of apolipoprotein (apo) B/apoAI is a better index for risk assessment of coronary artery disease (CAD). The aim of this study was to evaluate the efficiency of advanced profile of serum (apo)lipoproteins for predicting stable CAD in secondary prevention. METHODS The study subjects, 138 men and 126 women aged 40-70 years, were classified as CAD cases or controls, according to the results of coronary angiography. The severity of CAD was scored on the basis of the number and extent of lesions in coronary arteries. Serum (apo)lipoproteins were measured by immunoturbidometric and electrophoresis methods. RESULTS Patients with CAD compared with controls had increased serum levels of triglycerides (2.6+/-2.0 vs. 2.0+/-1.2 mmol/L, p< or =0.005), apoB (1.36+/-0.31 vs. 1.19+/-0.24 g/L, p< or =0.0001), lipoprotein(a) [Lp(a)] (0.69+/-0.60 vs. 0.43+/-0.31 g/L, p< or =0.0001) and apoB/apoAI ratio (1.07+/-0.32 vs. 0.87+/-0.18, p< or =0.0001), and decreased serum levels of HDL-C (1.02+/-0.29 vs. 1.11+/-0.34 mmol/L, p< or =0.03), apoAI (1.32+/-0.22 vs. 1.37+/-0.19 g/L, p< or =0.04) and LDL-C/apoB ratio (0.91+/-0.32 vs. 1.02+/-0.25 mmol/g, p< or =0.01). Multiple logistic regression analysis after adjusting for major risk factors showed that the apoB/apoAI ratio, apoB and Lp(a) were among seven significant and independent determinants of CAD. The area under the receiver operating characteristic (ROC) curves (AUC) as a relative measure of test efficiency was highest and significant for the apoB/apoAI ratio (AUC=0.71, p< or =0.0001), apoB (0.67, p< or =0.0001), Lp(a) (0.63, p< or =0.001), the LDL-C/apoB ratio (0.62, p< or =0.006), triglycerides (0.62, p< or =0.004) and apoAI (0.58, p< or =0.05). ANOVA analysis showed significant association for the apoB/apoAI ratio, apoB, Lp(a) and triglycerides, and moderate association for total cholesterol and its subfractions, with the severity of CAD. CONCLUSIONS The results indicate that the apoB/apoAI ratio, apoB and Lp(a) are independent risk factors for CAD and are superior to any of the cholesterol ratios. We suggest using the apoB/apoAI ratio as the best marker of CAD in clinical practice.

Background The role and diagnostic value of markers of inflammation is well recognized in acute coronary syndromes but it is uncertain in patients with stable coronary artery disease (CAD). This study was done to investigate the association of markers of inflammation with the occurrence and severity of CAD and to evaluate their predictive values. Methods Markers of inflammation, electrophoresis serum protein fractions, serum (apo)lipoproteins and classical risk factors were determined in 270 angiographically documented subjects. The subjects were classified as CAD cases and controls according to angiography. The severity of CAD was scored on the basis of the number and extent of lesions. Results The counts of total leukocytes (7.14 ± 1.86 cell/nl vs. 6.58 ± 1.62, p ≤ 0.02), neutrophils (3.95 ± 1.42 vs. 3.59 ± 1.07, p ≤ 0.05) and eosinophils (0.25 ± 0.28 vs. 0.19 ± 0.24, p ≤ 0.03) were increased significantly, whereas the concentrations of high-sensitivity C-reactive protein (hsCRP, 2.03 (0.0−32.0) mg/l vs.1.72 (0.09−11.36), p ≤ 0.07) changed modestly in CAD patients relative to controls. There were no significant differences in the counts of monocytes and lymphocytes and the concentrations of erythrocyte sedimentation rate (ESR) and any five fractions of serum proteins between two groups. The counts of total leukocytes, neutrophils and eosinophils, but not hsCRP and ESR exhibited significant associations with the severity of CAD. In univariate logistic regression analysis, leukocytes count associated significantly (OR = 1.97, p ≤ 0.01) whereas hsCRP modestly (OR = 1.76, p ≤ 0.06) with the occurrence of CAD. The association was lessened by diabetes mellitus in multivariable adjustment. Receiver operating characteristic (ROC) analysis showed that, only total leukocyte and differential counts had significant potency to predict CAD (area under curve, AUC = 0.60 ± 0.04, p ≤ 0.02). Conclusions The total leukocytes count and its subgroups are associated with the presence and severity of CAD, but the associations were not independent. The efficiency was questioned for hsCRP, ESR and five fractioned serum proteins to identify stable CAD.

Background: Plasma high-sensitivity CRP (hsCRP) is a marker of inflammation, and it is reported to link with coronary artery disease (CAD). Interactions between elevated serum hsCRP and other unfavorable risk factors have been proposed to cause high risk for CAD. Objectives: To examine the potential interactions between serum hsCRP and lipids and non-lipidic risk factors. Methods: Markers of inflammation, the profiles of serum (apo)(lipo) proteins as well as classical risk factors were determined in 270 clinically stable angiographically documented subjects. The patients were stratified into tertiles according to hsCRP distribution. Results: The Framingham CAD scores, relative and absolute risk for CAD and the prevalence of diabetes mellitus and hypertension were significantly higher in 3rd relative to 1st tertile of hsCRP. Subjects with hsCRP levels in the upper tertile had significant higher levels of serum glucose, triglyceride, apolipoprotein (apo)B, apoB/apoAI ratio and the counts of total leukocyte and neutrophil and lower levels of HDL-C, albumin and the ratio of albumin/globulins. Analyses by bivariate correlation as well as linear regression showed that serum hsCRP was associated positively with the occurrence of diabetes and hypertension, the counts of total leukocyte and neutrophil and the levels of serum glucose, uric acid, apoB, apoB/apoAI ratio, α1- and α2-globulins and inversely with albumin, albumin/globulin ratio and HDL-C. By constructing dummy combined variables, elevated hsCRP accompanied with male sex, diabetes, hypertension and high levels of serum glucose, apoB, apoB/apoAI ratio and cholesterol exhibited amplified high risk for CAD. Conclusions: The results show that hsCRP does interact multiplicatively with apoB and some variables of metabolic syndrome. The simultaneous assessment of hsCRP and interactive risk factors enhances discriminating value for CAD. It is suggested to use hsCRP in conjunction with apoB or apoB/apoAI ratio instead of cholesterol ratios in global risk assessment.

The associations of serum calcium and phosphorus concentrations as well as other cardiovascular risk factors were investigated in relation to the existence and severity of coronary heart disease (CHD) in 260 clinically stable, angiographically defined CHD patients aged 40-70 years. The subjects were classified as CHD(+) cases if one or more coronary arteries had a significant stenosis (> or =70%) and CHD(-) controls if there was no stenosis (< or =10%) in any artery. The severity of coronary occlusion was scored on the basis of the number and extent of lesions, as normal, mild, moderate or severe. Fasting serum concentrations of electrolytes, lipids and (apo)lipoproteins were determined. The concentrations of serum total calcium (2.41 +/-0.14 vs. 2.33 +/- 0.22 mmol/L, p < or = 0.05), albumin-corrected calcium (2.33 +/- 0.25 vs. 2.23 +/- 0.25 mmol/L, p < or = 0.01), phosphorus (1.32 +/-0.21 vs. 1.25 +/- 0.17 mmol/L, p < or = 0.007) and the ion product of calcium and phosphorus (3.16 +/- 0.58 vs. 2.91 +/- 0.50, p < or =0.0001) were significantly higher in the CHD(+) compared to the CHD(-) group. Patients with CHD compared with controls had increased serum levels of triglyceride, total cholesterol, low-density lipoprotein-cholesterol (LDL-C), apolipoprotein B (apoB), lipoprotein(a) [Lp(a)] and decreased serum levels of high-density lipoprotein (HDL)-C and apoAI. Multiple logistic regression analysis showed strong and significant association between diabetes mellitus (odds ratio, OR = 5.24, p < or = 0.0001), male gender (OR = 8.84, p < or =0.0001), Lp(a) (OR = 1.014, p < or =0.006), hypertension (OR = 2.61, p < or =0.02), apoB (OR = 1.031, p < or =0.001), age (OR = 1.055, p < or =0.003), phosphorus (OR = 2.438, p < or =0.01), albumin-adjusted calcium (OR = 1.532, p < or =0.05), cholesterol (OR = 1.009, p < or =0.05) and the occurrence of CHD. On the basis of bivariate correlation analysis, serum-adjusted calcium was positively correlated with the levels of cholesterol (r = 0.285, p < or =0.0001), LDL-C (r = 0.320, p < or =0.0001), Lp(a) (r = 0.173, p < or = 0.005), apoB (r = 0.237, p < or =0.0001), LDL-C/apoB ratio (r = 0.180, p < or= 0.007), apoAI (r = 0.181, p < or =0.003) and inversely to HDL-C (r = -0.146, p < or =0.02) and HDL-C/apoAI ratio (r = -0.263, p < or =0.0001). Serum phosphorus concentration was a significant correlate of triglyceride (r = 0.199, p < or =0.001) and Lp(a) (r = 0.129, p < or =0.04). The results demonstrated that serum calcium and phosphorus are associated with the prevalence and severity of CHD, probably through correlation with atherogenic lipids and (apo)lipoproteins. Serum calcium and phosphorus and their ion product were also independent risk factors for CHD.

The electrophoretic pattern of serum proteins of 85 patients carrying different types of neoplasia and 85 matched healthy adults were comparatively studied by agarose gel electrophoresis, to find out if there is a specific protein pattern common to different types of cancer. Each protein fraction was analyzed quantitatively by densitometry. Multivariate logistic regression and receiver operating characteristic (ROC) analyses were performed using SPSS software. When total protein and albumin were measured by colorimetric methods, cancer patients, compared to controls, had a decreased concentration of total protein (66.0+/-11.5 g/L vs. 76.4+/-6.8 g/L, p< or =0.0001) and of albumin (39.0+/-8.1 g/L vs. 46.0+/-4.3 g/L, p< or =0.0001). The electrophoretic data of serum proteins showed that the ratio of albumin to globulin (0.92+/-0.30 vs. 1.21+/-0.16, p< or =0.0001), percent of the fractions albumin (46.7+/-8.5% vs. 54.4+/-3.5%, p< or =0.0001) and beta-globulin (11.6+/-4.4% vs. 13.0+/-1.9%, p< or =0.001) were decreased and alpha(1)- (5.3+/-2.5% vs. 2.9+/-0.8%, p< or =0.0001), alpha(2)- (13.5+/-4.8% vs. 11.3+/-2.1%, p< or =0.0001) and gamma-globulins (23.0+/-7.7% vs. 18.3+/-3.1%, p< or =0.0001) were significantly increased in cancer patients relative to controls. Cancer patients also had higher counts of leukocytes (7.98+/-3.11, x10(9) cells/L vs. 6.33+/-1.68 x10(9) cells/L, p< or =0.0001) and erythrocyte sedimentation rate (35.9+/-23.5 mm/h vs. 14.1+/-9.5 mm/h,p< / =0.0001). On the basis of univariate analysis, a protein profile out of the normal ranges was more prevalent in cancer patients than in controls. Analysis of the data using multiple logistic regression indicated that the prevalence of cancer was strongly associated with the serum proteins' profile, and alpha(1)-globulin, erythrocyte sedimentation rate, total protein and the ratio of albumin to globulin were the best parameters to discriminate between malignant and healthy states. The area under the ROC curves were the same for most components of the serum proteins' profile at about 0.75+/-0.09, p< or =0.001. We conclude that the profile of serum proteins indicates high diagnostic values for discriminating between cancer patients and healthy individuals and may be useful as an adjunct diagnosis for detection of malignancy.

BACKGROUND There are several methods for calculating serum osmolality, and their accordance with measured osmolality is the subject of controversy. METHODS The concentrations of sodium, potassium, glucose, blood urea nitrogen (BUN) and osmolalities of 210 serum samples were measured. Two empirical equations were deduced for the calculation of serum osmolality by regression analysis of the data. To choose the best equation, chemical concentrations were also used to calculate osmolalities according to our formulas and 16 different equations were taken from the literature and compared with the measured osmolalities. Correlation and linear regression analyses were performed using Excel and SPSS software. RESULTS Multiple linear regression analysis showed that serum concentrations of sodium (beta = 0.778, p< or = 0.000), BUN (beta = 0.315, p < or = 0.000), glucose (beta = 0.0.089, p < or = 0.007) and potassium (beta = 0.109, p < or = 0.008) are strong predictors of serum osmolality. The data were also analyzed by manual linear regression to yield the equations: osmolality = 1.897[Na + ]+glucose+BUN+13.5, and osmolality = 1.90[Na+ + K+]+glucose+BUN+5.0. The osmotic coefficient for sodium and potassium solutes was deduced to be 0.949 from the slope of the curves of measured osmolality vs. [Na+] and [Na+ + K+], respectively. The inclusion of a BUN value in the equation for osmolality increased the correlation coefficient by approximately 450% and decreased the SD of difference by approximately 35% (p < or = 0.002). Inclusion of the osmotic coefficient for sodium solutes caused an underestimation of measured osmolality and positive osmolal gap unless an appropriate coefficient, constant value and/or the potassium value were included in the equation. The agreement was not improved when molal chemical concentrations were used instead of molar values. The formula presented by Dorwart and Chalmers gave inferior results to those obtained with our formulas. CONCLUSIONS Our data suggest use of the Worthley et al. formula Osm = 2[Na +]+glucose+BUN for rapid mental calculation and the formulas of Bhagat et al. or ours for calculation of serum osmolality by equipment linked to a computer.