After writing: Judged erroneous, not amrit, coz extension of telomeres does not reduce age! BUT Katcher E5, under tests, amazed the greats by actually reducing age, hence real amrit when a product.
Research Paper Volume 12, Issue 22 pp 22445—22456
Hyperbaric oxygen therapy increases telomere length and decreases immunosenescence in isolated blood cells: a prospective trial
Arun Arya comments are so.
zArun Arya stuff is like this.Introduction
Aging can be characterized by the progressive loss of physiological integrity, resulting in impaired functions and susceptibility for diseases and death. This biological deterioration is considered a major risk factor for cancer, cardiovascular diseases, diabetes and Alzheimer’s disease among others.
That is why it is health span, not life span for me. Unlike eligible patients of the study, cardiovascular diseases, diabetes and Alzheimer’s, osteoarthritis and essential tremors affect me, passed on by my father, affect me. He succumbed at 88. There is no cure for them in mm. He successfully battled the disabilities to end by diet, exercise and mm treatments. His exercise was lifelong yoga. I don’t consider yoga as efficient as long fast energetic walks and gym machines. I ape him for diet and mm treatment (two specialist doctors and earlier advice re cardiovascular). Unlike mother, I consider Ayurveda as iffy treatment, dangerous of all heavy metals. Some parts are very good, but which?
At the cellular level, there are two key hallmarks of the aging process: shortening of telomere length and cellular senescence [1].
Telomeres are tandem nucleotide repeats located at the end of the chromosomes which maintain genomic stability. Telomeres shorten during replication (mitosis) due to the inherent inability to fully replicate the end part of the lagging DNA strand [2]. Telomere length (TL), measuring between 4 to 15 kilobases, gradually shorten by ~20-40 bases per year and is associated with different diseases, low physical performance and cortical thinning of the brain [3–5]. When TL reaches a critical length, cells cannot replicate and progress to senescence or programmed cell death [6]. Goglin et al. demonstrated that adults with shorter TLs have increased mortality rates [7].
Programmed cell death is an important theory, to the extent that there are no evolutionary advantages for survival over reproduction. Our natural advantages arise from slow detiorations of evolutionary advantages. Long life is a certain evolutionary trait. Real aging is a consequence of many genetic factors, two identified so far, the shortening of telomere to Hayflick limit and error correction failure. These are cellular. Others will be identified of organ aging but can be fixed by higher level methods derived from mRNA, Yamanaka factors and blood rejuvenation.
Shortened TLs can be a direct inherited trait, but several environmental factors have also been associated with shortening TL including stress, lack of physical endurance activity, excess body mass index, smoking, chronic inflammation, vitamins deficiency and oxidative stress [2, 8, 9].
Factors identified by black box medicine without identifying the cellular causes are important for life style modifications. Stress is an essential part of computer science profession, all greats have had very poor life-size records. I escaped with TBI after my accident bat 35. It explains to me the several year failure to build unbuggy software, despite it works mostly and only person on earth able to solve multi bit Cocks IBE problem. The lack of physical endurance activity was fixed 10 years ago by 2km walk per day and gym. The excess body mass index problem went away with mostly vegetarian diet. The smoking was ended 30 years ago. The chronic inflammation is not there. A vitamins deficiency can not happen with daily a-z. Any oxidative stress should fix with Liposome NMN and resveratrol.
Cellular senescence is an arrest of the cell cycle which can be caused by telomere shortening [10], as well as other aging associated stimuli independent of TL such as non-telomeric DNA damage [1]. The primary purpose of senescence is to prevent propagation of damaged cells by triggering their elimination via the immune system. The accumulation of senescent cells with aging reflects either an increase in the generation of these cells and/or a decrease in their clearance, which in turn aggravates the damage and contributes to aging [1].
I have strongly asserted that NAD+ incrementation must be tied to senescent cell claring by senolytic like Quertecin. Great if HBOT adds to it.
A growing body of research has found several pharmacological agents that can reduce the telomere shortening rate [11, 12]. Several lifestyle interventions including endurance training, diets and supplements targeting cell metabolism and oxidative stress have reported relatively small effects (2-5%) on TL3, [2, 8, 9].
Hyperbaric oxygen therapy (HBOT) utilizes 100% oxygen in an environmental pressure higher than one absolute atmospheres (ATA) to enhance the amount of oxygen dissolved in body’s tissues. Repeated intermittent hyperoxic exposures, using certain HBOT protocols, can induce physiological effects which normally occur during hypoxia in a hyperoxic environment, the so called hyperoxic-hypoxic paradox [13–16]. In addition, it was recently demonstrated that HBOT can induce cognitive enhancements in healthy aging adults via mechanisms involving regional changes in cerebral blood flow [17]. On the cellular level, it was demonstrated that HBOT can induce the expression of hypoxia induced factor (HIF), vascular endothelial growth factor (VEGF) and sirtuin (SIRT), stem cell proliferation, mitochondrial biogenesis, angiogenesis and neurogenesis [18]. However, no study to date has examined HBOT’s effects on TL and senescent cell accumulation.
The aim of the current study was to evaluate whether HBOT affects TL and senescence-like T-cells population in aging adults.
Results
Thirty-five individuals were assigned to HBOT. Five patients did not complete baseline assessments and were excluded. All 30 patients who completed baseline evaluations completed the interventions. Due to the low quality of blood samples (low number of cells or technician error), four patients were excluded from the telomere analysis and 10 patients from senescent cell analysis (Figure 1). The baseline characteristics and comparison of the cohorts following exclusion of the patients are provided in Table 1. There were no significant differences between the three groups (Table 1).
Figure 1. Patient flowchart.
Table 1. Baseline characteristics.
HBOT | Telomere analysis | Senescent analysis | P-value | ||
N | 30 | 25 (83.3%) | 20 (66.6%) | ||
Age (years) | 68.41±13.2 | 67.56±14.35 | 66.70±16.00 | 0.917 | |
BMI | 26.77±3.20 | 26.89±3.34 | 27.14±3.81 | 0.946 | |
Males | 16 (53.3%) | 13 (52.0%) | 10 (50.0%) | 0.987 | |
Females | 14 (47.7%) | 12 (48.0%) | 10 (50.0%) | 0.987 | |
Complete blood count | |||||
Hemoglobin | 6.33±1.25 | 6.57±1.15 | 6.58±1.29 | 0.707 | |
White blood cells | 14.02±1.40 | 13.92±1.35 | 13.97±1.49 | 0.969 | |
%PBMC | 39.96±6.75 | 39.25±6.64 | 38.59±6.63 | 0.774 | |
Platelets | 239.87±1.39 | 244.08±43.0 | 254.05±41.4 | 0.559 | |
Chronic medical conditions | |||||
Atrial fibrillation | 4 (13.3%) | 4 (16.0%) | 2 (10.0%) | 0.841 | |
Hypothyroidism | 4 (13.3%) | 4 (16.0%) | 3 (15.8%) | 0.956 | |
Obstructive sleep apnea | 4 (13.3%) | 4 (16.0%) | 3 (15.0%) | 0.961 | |
Asthma | 1 (3.3%) | 1 (4.0%) | 0 | 0.680 | |
BPH | 7 (23.3%) | 5 (20.0%) | 6 (30.0%) | 0.733 | |
GERD | 3 (10%) | 2 (8.0%) | 2 (10.0%) | 0.961 | |
Osteoporosis | 5 (16.7%) | 5 (20.0%) | 4 (20.0%) | 0.936 | |
Rheumatic arthritis | 1 (3.3%) | 0 | 1 (5.0%) | 0.561 | |
Osteoarthritis | 7 (23.3%) | 4 (16.0%) | 5 (25.0%) | 0.755 | |
Diabetes mellitus | 3 (10%) | 3 (12.0%) | 2 (10.0%) | 0.966 | |
Hypertension | 7 (23.3%) | 5 (20.0%) | 5 (25.0%) | 0.918 | |
Dyslipidemia | 16 (53.3%) | 14 (56.0%) | 12 (60.0%) | 0.897 | |
Ischemic heart disease | 2 (6.7%) | 1 (4.0%) | 2 (10.0%) | 0.725 | |
History of smoking | 10 (33.3%) | 8 (32.0%) | 7 (35.0%) | 0.978 | |
Chronic medications | |||||
Anti-aggregation | 8 (26.7%) | 6 (24.0%) | 5 (25.0%) | 0.974 | |
ACE-Inhibitors/ARB blockers | 6 (20%) | 6 (24.0%) | 6 (30.0%) | 0.720 | |
Beta blockers | 5 (16.7%) | 5 (20.0%) | 3 (15.0%) | 0.901 | |
Calcium blockers | 3 (10%) | 3 (12.0%) | 2 (10.0%) | 0.966 | |
Alpha blockers | 7 (23.3%) | 5 (20.0%) | 6 (30.0%) | 0.733 | |
Diuretics | 2 (6.7%) | 1 (4.0%) | 1 (5.0%) | 0.906 | |
Statins | 10 (33.3%) | 9 (36.0%) | 7 (35.0%) | 0.978 | |
Oral hypoglycemic | 1 (3.3%) | 1 (4.0%) | 1 (5.0%) | 0.958 | |
Bisphosphonates | 1 (3.3%) | 1 (4.0%) | 1 (5.0%) | 0.958 | |
Proton pump inhibitors | 3 (10%) | 3 (12.0%) | 3 (15.0%) | 0.726 | |
Hormones | 3 (10%) | 3 (12.0%) | 2 (10.0%) | 0.966 | |
Benzodiazepines | 3 (10%) | 2 (8.0%) | 1 (5.0%) | 0.816 | |
SSRI | 5 (16.7%) | 5 (20.0%) | 3 (15.0%) | 0.990 |
Telomere length
Compared to the baseline, the T-helper telomere lengths were significantly increased at the 30th session and post-HBOT by 21.70±40.05 (p=0.042), 23.69%±39.54 (p=0.012) and 29.30±38.51 (p=0.005), respectively (Figure 2). However, repeated measures analysis shows a non-significant trend (F=4.663, p=0.06, Table 2 and Figure 2).
Figure 2. Telomere length changes with HBOT. Mean+SEM *p<0.05, **p<0.01, ***p<0.001.
Table 2. Telomere length and senescent cell changes post-HBOT.
Absolute changes | Relative changes (%) | Repeated measures F (p) | |||||||
PBMC | Baseline | 30thSession | 60thSession | Post HBOT | 30th session | 60thsession | Post-HBOT | ||
PBMC ((N=25) | 2.55±0.53 | -0.15±0.40 | -4.91±16.70 | 1.987 (t) 0.09 | |||||
PBMC (N=20) | 2.50±0.53 | -0.13±0.31 | -4.21±11.99 | 1.810 (t) 0.07 | |||||
Relative telomeres length (N=25) | |||||||||
Natural killer | 9.27±1.91 | 11.77±5.14 (0.045) | 10.73±2.73 (0.013) | 11.75±4.22 (0.06) | 25.02±51.42 | 20.56±33.35 | 22.16±44.81 | 0.812 (0.391) | |
B-cells | 8.36±2.02 | 10.22±3.04 (0.007) | 11.23±3.58 (0.0001) | 11.17±2.98 (0.007) | 25.68±40.42 | 29.39±23.39 | 37.63±52.73 | 7.390 (0.017) | |
T Helper | 8.04±1.82 | 9.92±3.68 (0.042) | 9.63±2.17 (0.012) | 10.20±2.77 (0.005) | 21.70±40.05 | 23.69±39.54 | 29.30±38.51 | 4.663 (0.063) | |
T Cytotoxic | 8.26±1.54 | 9.83±4.08 (0.11) | 10.08±3.33 (0.019) | 10.15±2.74 (0.023) | 18.29±45.62 | 24.13±40.88 | 19.59±33.98 | 1.159 (0.310) | |
Senescent cells (% of T cells) (N=20) | |||||||||
T Helper | 10.29±5.42 | 7.84±7.09 (0.09) | 8.51±7.45 (0.20) | 6.22±4.88 (<0.0001) | -19.66±80.03 | -11.67±94.30 | -37.30±33.04 | 8.548 (0.01) | |
T Cytotoxic | 52.19±21.07 | 45.53±19.91 (<0.0001) | 45.45±18.81 (0.002) | 46.59±21.91 (0.0004) | -12.21±8.74 | -9.81±9.50 | -10.96±12.59 | 6.916 (0.018) | |
P-values shown in () compared to baseline. | |||||||||
P-values in bold <0.05. | |||||||||
Compared to baseline, telomere lengths of B cells increased significantly at the 30th session, 60th session and post-HBOT by 25.68%±40.42 (p=0.007), 29.39%±23.39 (p=0.0001) and 37.63%±52.73 (p=0.007), respectively (Figure 2). Repeated measures analysis shows a significant within-group effect (F=0.390, p=0.017, Table 2 and Figure 2).
Compared to baseline, natural killer cells telomer lengths significantly increased at the 30th session (p=0.045) and at the 60th session by 20.56% ±33.35 (p=0.013). Post-HBOT, telomere lengths increased by 22.16%±44.81 post-HBOT (p=0.06, Table 2 and Figure 2). Repeated measures analysis indicates that there was no additional significant effect after the 30th session (F=0.812, p=0.391).
Compared to baseline, cytotoxic T-cells had a non-significant increase at the 30th session by 18.29%±45.62 (p=0.11), followed by a significant increase of 24.13%±40.88 at the 60th session (p=0.0019) and 19.59%±33.98 post-HBOT (p=0.023). Repeated measures analysis indicates that there was no additional significant effect after the 30th session (F=1.159, p=0.310, Table 2 and Figure 2).
Excellent for part 1. Clearly will supplement NMN mix in orthogonal ways.
Senescent cells
There was a non-significant decrease in the number of senescent T-helpers at the 30th session and 60thsession by -19.66%±80.03 (p=0.09) and -11.67%±94.30 (p=0.20) respectively. However, there was a significant drop in the number of senescent T helpers by -37.30%±33.04 post-HBOT (P<0.0001, Figure 3). Repeated measures analysis showed a significant continuous effect even after the 30th session, with a within-group effect (F=8.547, p=0.01, Table 2 and Figure 3).
Figure 3. Senescent cell changes with HBOT. Mean+SEM *p<0.05, **p<0.01, ***p<0.001.
T-cytotoxic senescent cell percentages decreased significantly by -12.21%±8.74 (P<0.0001) at the 30th HBOT session, -9.81%±9.50 at the 60th HBOT session (0.002) and -10.96%±12.59 (p=0.0004) post-HBOT (Table 2and Figure 3). Repeated measures analysis shows a significant continuous effect even after the 30th session, with a within-group effect (F=6.916, p=0.018, Table 2).
Excellent for part 2. Clearly will supplement Quertecin in orthogonal ways.
HIF-1alpha
HIF-1alpha levels were increased from 10.54±3.39 to 19.71±3.39 at the 60th session (p=0.006) where 2 weeks post HBOT levels of 16.81±7.65 were not significantly different from baseline (p=0.16).
Excellent for part HIF-1alpha. Has no evil effect.
