Vulnerability analysis and modeling false data injection attack against voltage source converter in renewable generation power system.

With the increasing penetration of renewable resources, more power electronic devices that need communication with control centers may bring a novel risk of cyber attacks. This paper investigates the vulnerability of the hierarchical control and proposes a false data injection attack (FDIA) constructing algorithm against voltage source converters. The attack can be accomplished via a physical attack generator or falsification via attacking supervisory control and data acquisition system. By developing the FDIA model against state estimation, the proposed attack model can circumvent bad data detection in the secondary control loop. The tests are carried out on a single converter infinite bus benchmark and an IEEE 34-bus system. The results show that the proposed attack model can mislead the system to produce threatening oscillation.

Causal associations between thyroid cancer and IgA nephropathy: a Mendelian randomization study.

BACKGROUND: The incidence of kidney disease caused by thyroid cancer is rising worldwide. Observational studies cannot recognize whether thyroid cancer is independently associated with kidney disease. We performed the Mendelian randomization (MR) approach to genetically investigate the causality of thyroid cancer on immunoglobulin A nephropathy (IgAN). METHODS AND RESULTS: We explored the causal effect of thyroid cancer on IgAN by MR analysis. Fifty-two genetic loci and single nucleotide polymorphisms were related to thyroid cancer. The primary approach in this MR analysis was the inverse variance weighted (IVW) method, and MR‒Egger was the secondary method. Weighted mode and penalized weighted median were used to analyze the sensitivity. In this study, the random-effect IVW models showed the causal impact of genetically predicted thyroid cancer across the IgAN risk (OR, 1.191; 95% CI, 1.131-1.253, P < 0.001). Similar results were also obtained in the weighted mode method (OR, 1.048; 95% CI, 0.980-1.120, P = 0.179) and penalized weighted median (OR, 1.185; 95% CI, 1.110-1.264, P < 0.001). However, the MR‒Egger method revealed that thyroid cancer decreased the risk of IgAN, but this difference was not significant (OR, 0.948; 95% CI, 0.855-1.051, P = 0.316). The leave-one-out sensitivity analysis did not reveal the driving influence of any individual SNP on the association between thyroid cancer and IgAN. CONCLUSION: The IVW model indicated a significant causality of thyroid cancer with IgAN. However, MR‒Egger had a point estimation in the opposite direction. According to the MR principle, the evidence of this study did not support a stable significant causal association between thyroid cancer and IgAN. The results still need to be confirmed by future studies.

Patient-specific iPSC-derived cardiomyocytes reveal aberrant activation of Wnt/ß-catenin signaling in SCN5A-related Brugada syndrome.

BACKGROUND: Mutations in the cardiac sodium channel gene SCN5A cause Brugada syndrome (BrS), an arrhythmic disorder that is a leading cause of sudden death and lacks effective treatment. An association between SCN5A and Wnt/ß-catenin signaling has been recently established. However, the role of Wnt/ß-catenin signaling in BrS and underlying mechanisms remains unknown. METHODS: Three healthy control subjects and one BrS patient carrying a novel frameshift mutation (T1788fs) in the SCN5A gene were recruited in this study. Control and BrS patient-specific induced pluripotent stem cells (iPSCs) were generated from skin fibroblasts using nonintegrated Sendai virus. All iPSCs were differentiated into cardiomyocytes using monolayer-based differentiation protocol. Action potentials and sodium currents were recorded from control and BrS iPSC-derived cardiomyocytes (iPSC-CMs) by single-cell patch clamp. RESULTS: BrS iPSC-CMs exhibited increased burden of arrhythmias and abnormal action potential profile featured by slower depolarization, decreased action potential amplitude, and increased beating interval variation. Moreover, BrS iPSC-CMs showed cardiac sodium channel (Nav1.5) loss-of-function as compared to control iPSC-CMs. Interestingly, the electrophysiological abnormalities and Nav1.5 loss-of-function observed in BrS iPSC-CMs were accompanied by aberrant activation of Wnt/ß-catenin signaling. Notably, inhibition of Wnt/ß-catenin significantly rescued Nav1.5 defects and arrhythmic phenotype in BrS iPSC-CMs. Mechanistically, SCN5A-encoded Nav1.5 interacts with ß-catenin, and reduced expression of Nav1.5 leads to re-localization of ß-catenin in BrS iPSC-CMs, which aberrantly activates Wnt/ß-catenin signaling to suppress SCN5A transcription. CONCLUSIONS: Our findings suggest that aberrant activation of Wnt/ß-catenin signaling contributes to the pathogenesis of SCN5A-related BrS and point to Wnt/ß-catenin as a potential therapeutic target.

Patient-specific iPSC-derived cardiomyocytes reveal variable phenotypic severity of Brugada syndrome.

BACKGROUND: Brugada syndrome (BrS) is a cardiac channelopathy that can result in sudden cardiac death (SCD). SCN5A is the most frequent gene linked to BrS, but the genotype-phenotype correlations are not completely matched. Clinical phenotypes of a particular SCN5A variant may range from asymptomatic to SCD. Here, we used comparison of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) derived from a SCN5A mutation-positive (D356Y) BrS family with severely affected proband, asymptomatic mutation carriers (AMCs) and healthy controls to investigate this variation. METHODS: 26 iPSC lines were generated from skin fibroblasts using nonintegrated Sendai virus. The generated iPSCs were differentiated into cardiomyocytes using a monolayer-based differentiation protocol. FINDINGS: D356Y iPSC-CMs exhibited increased beat interval variability, slower depolarization, cardiac arrhythmias, defects of Na+ channel function and irregular Ca2+ signaling, when compared to controls. Importantly, the phenotype severity observed in AMC iPSC-CMs was milder than that of proband iPSC-CMs, an observation exacerbated by flecainide. Interestingly, the iPSC-CMs of the proband exhibited markedly decreased Ca2+ currents in comparison with control and AMC iPSC-CMs. CRISPR/Cas9-mediated genome editing to correct D356Y in proband iPSC-CMs effectively rescued the arrhythmic phenotype and restored Na+ and Ca2+ currents. Moreover, drug screening using established BrS iPSC-CM models demonstrated that quinidine and sotalol possessed antiarrhythmic effects in an individual-dependent manner. Clinically, venous and oral administration of calcium partially reduced the malignant arrhythmic events of the proband in mid-term follow-up. INTERPRETATION: Patient-specific and genome-edited iPSC-CMs can recapitulate the varying phenotypic severity of BrS. Our findings suggest that preservation of the Ca2+ currents might be a compensatory mechanism to resist arrhythmogenesis in BrS AMCs. FUNDING: National Key R&D Program of China (2017YFA0103700), National Natural Science Foundation of China (81922006, 81870175), Natural Science Foundation of Zhejiang Province (LD21H020001, LR15H020001), National Natural Science Foundation of China (81970269), Key Research and Development Program of Zhejiang Province (2019C03022) and Natural Science Foundation of Zhejiang Province (LY16H020002).

Juxtaposing Sub-Sahara Africa's energy poverty and renewable energy potential.

Recently, the International Energy Agency (IEA) released a comprehensive roadmap for the global energy sector to achieve net-zero emission by 2050. Considering the sizeable share of (Sub-Sahara) Africa in the global population, the attainment of global energy sector net-zero emission is practically impossible without a commitment from African countries. Therefore, it is important to study and analyze feasible/sustainable ways to solve the energy/electricity poverty in Africa. In this paper, the energy poverty in Africa and the high renewable energy (RE) potential are reviewed. Beyond this, the generation of electricity from the abundant RE potential in this region is analyzed in hourly timestep. This study is novel as it proposes a Sub-Sahara Africa (SSA) central grid as one of the fastest/feasible solutions to the energy poverty problem in this region. The integration of a sizeable share of electric vehicles with the proposed central grid is also analyzed. This study aims to determine the RE electricity generation capacities, economic costs, and supply strategies required to balance the projected future electricity demand in SSA. The analysis presented in this study is done considering 2030 and 2040 as the targeted years of implementation. EnergyPLAN simulation program is used to simulate/analyze the generation of electricity for the central grid. The review of the energy poverty in SSA showed that the electricity access of all the countries in this region is less than 100%. The analysis of the proposed central RE grid system is a viable and sustainable option, however, it requires strategic financial planning for its implementation. The cheapest investment cost from all the case scenarios in this study is $298 billion. Considering the use of a single RE technology, wind power systems implementation by 2030 and 2040 are the most feasible options as they have the least economic costs. Overall, the integration of the existing/fossil-fueled power systems with RE technologies for the proposed central grid will be the cheapest/easiest pathway as it requires the least economic costs. While this does not require the integration of storage systems, it will help the SSA countries reduce their electricity sector carbon emission by 56.6% and 61.8% by 2030 and 2040 respectively.

Deep learning framework for rapid and accurate respiratory COVID-19 prediction using chest X-ray images.

COVID-19 is a contagious disease that affects the human respiratory system. Infected individuals may develop serious illnesses, and complications may result in death. Using medical images to detect COVID-19 from essentially identical thoracic anomalies is challenging because it is time-consuming, laborious, and prone to human error. This study proposes an end-to-end deep-learning framework based on deep feature concatenation and a Multi-head Self-attention network. Feature concatenation involves fine-tuning the pre-trained backbone models of DenseNet, VGG-16, and InceptionV3, which are trained on a large-scale ImageNet, whereas a Multi-head Self-attention network is adopted for performance gain. End-to-end training and evaluation procedures are conducted using the COVID-19_Radiography_Dataset for binary and multi-classification scenarios. The proposed model achieved overall accuracies (96.33% and 98.67%) and F1_scores (92.68% and 98.67%) for multi and binary classification scenarios, respectively. In addition, this study highlights the difference in accuracy (98.0% vs. 96.33%) and F_1 score (97.34% vs. 95.10%) when compared with feature concatenation against the highest individual model performance. Furthermore, a virtual representation of the saliency maps of the employed attention mechanism focusing on the abnormal regions is presented using explainable artificial intelligence (XAI) technology. The proposed framework provided better COVID-19 prediction results outperforming other recent deep learning models using the same dataset.

Short sleep duration and atrial fibrillation risk: A comprehensive analysis of observational cohort studies and genetic study.

BACKGROUND: Previous observational studies are inconclusive on whether an association exists between short sleep duration and the high risk of developing atrial fibrillation (AF). Understanding their potential association would be of great clinical significance. Thus, in this study, we aimed to explore their causal relationship. METHODS AND RESULTS: We meta-analyzed the association between short sleep duration and the risk of developing AF by including six observational studies. Based on genetic susceptibility analysis using the mendelian randomization (MR) method, we identified 16 genetic loci that might link short sleep duration and the high risk of developing AF. Meta-analysis showed a significant association between short sleep duration and a higher risk of developing AF (RR = 1.06, 95% CI 1.02-1.11, P = 0.005). However, the fixed-effect and random-effect inverse variance weighted (IVW) models using the MR method showed a non-obvious effect of short sleep duration on the risk of developing AF (OR, 0.979; 95% CI, 0.880-1.089, P = 0.693; OR, 0.979; 95% CI, 0.857-1.117, P = 0.750, respectively). Other models, also showed no statistical difference. No heterogeneity or asymmetry was observed, as Cochran's Q test showed. The leave-one-out sensitivity analysis demonstrated good robust results, which were not subject to directional pleiotropy. CONCLUSION: Meta-analysis and MR analysis demonstrated inconsistent results on the relationship between short sleep duration and a high risk of developing AF. Specifically, while meta-analysis confirmed that short sleep duration increases the risk of developing AF, MR analysis did not support a causal association between genetically determined short sleep and risk of AF.

No causal association between tea consumption and 7 cardiovascular disorders: A two-sample Mendelian randomization study.

Background: Previous studies have reported inconsistent results on the causal association between habitual tea consumption and the risk of cardiovascular disease (CVD). This study is aim to determine the association between habitual tea intake and CVD using two-sample Mendelian randomization (MR) analysis. Methods: The genetically predicted causation between tea consumption and 7 common cardiovascular diseases (atrial fibrillation, hypertension, acute myocardial infarction, coronary atherosclerosis, peripheral vascular disease, angina, and heart failure) was evaluated using MR analysis model. We performed a total of 9 MR analysis methods to analyze the final results. The IVW methods was used as the primary outcome. The other MR analysis method (simple mode, weighted mode, simple median, weighted median, penalized weighted median, MR Egger, and MR-Egger (bootstrap)) were performed as the complement to IVW. Also, the robustness of the MR analysis results was assessed using a leave-one-out analysis. Results: The IVW analysis methods indicated that there is no causal association between tea consumption and risk of CVD (AF: OR, 0.997, 95% CI, 0.992-1.0001, p = 0.142; hypertension: OR, 0.976, 95% CI, 0.937-1.017, p = 0.242; AMI: OR, 0.996, 95% CI, 0.991-1.000, p = 0.077; CA: OR, 1.001, 95% CI, 0.993-1.009, p = 0.854; PVD: OR, 1.002, 95% CI, 1.000-1.005, p = 0.096; angina: OR, 0.999, 95% CI, 0.993-1.006, p = 0.818; HF: OR, 0.999, 95% CI, 0.996-1.002, p = 0.338). The other MR analysis method and further leave-one-out sensitivity analysis suggested the results were robust. Conclusion: This MR study indicated that there was no genetically predicted causal association between habitual tea intake and risk of CVD.

Comprehensive assessment, review, and comparison of AI models for solar irradiance prediction based on different time/estimation intervals.

Solar energy-based technologies have developed rapidly in recent years, however, the inability to appropriately estimate solar energy resources is still a major drawback for these technologies. In this study, eight different artificial intelligence (AI) models namely; convolutional neural network (CNN), artificial neural network (ANN), long short-term memory recurrent model (LSTM), eXtreme gradient boost algorithm (XG Boost), multiple linear regression (MLR), polynomial regression (PLR), decision tree regression (DTR), and random forest regression (RFR) are designed and compared for solar irradiance prediction. Additionally, two hybrid deep neural network models (ANN-CNN and CNN-LSTM-ANN) are developed in this study for the same task. This study is novel as each of the AI models developed was used to estimate solar irradiance considering different timesteps (hourly, every minute, and daily average). Also, different solar irradiance datasets (from six countries in Africa) measured with various instruments were used to train/test the AI models. With the aim to check if there is a universal AI model for solar irradiance estimation in developing countries, the results of this study show that various AI models are suitable for different solar irradiance estimation tasks. However, XG boost has a consistently high performance for all the case studies and is the best model for 10 of the 13 case studies considered in this paper. The result of this study also shows that the prediction of hourly solar irradiance is more accurate for the models when compared to daily average and minutes timestep. The specific performance of each model for all the case studies is explicated in the paper.

The hypothalamus for whole-body physiology: from metabolism to aging.

Obesity and aging are two important epidemic factors for metabolic syndrome and many other health issues, which contribute to devastating diseases such as cardiovascular diseases, stroke and cancers. The brain plays a central role in controlling metabolic physiology in that it integrates information from other metabolic organs, sends regulatory projections and orchestrates the whole-body function. Emerging studies suggest that brain dysfunction in sensing various internal cues or processing external cues may have profound effects on metabolic and other physiological functions. This review highlights brain dysfunction linked to genetic mutations, sex, brain inflammation, microbiota, stress as causes for whole-body pathophysiology, arguing brain dysfunction as a root cause for the epidemic of aging and obesity-related disorders. We also speculate key issues that need to be addressed on how to reveal relevant brain dysfunction that underlines the development of these disorders and diseases in order to develop new treatment strategies against these health problems.

Exosomes/microvesicles target SARS-CoV-2 via innate and RNA-induced immunity with PIWI-piRNA system.

Murine neural stem cells (NSCs) were recently shown to release piRNA-containing exosomes/microvesicles (Ex/Mv) for exerting antiviral immunity, but it remains unknown if these Ex/Mv could target SARS-CoV-2 and whether the PIWI-piRNA system is important for these antiviral actions. Here, using in vitro infection models, we show that hypothalamic NSCs (htNSCs) Ex/Mv provided an innate immunity protection against SARS-CoV-2. Importantly, enhanced antiviral actions were achieved by using induced Ex/Mv that were derived from induced htNSCs through twice being exposed to several RNA fragments of SARS-CoV-2 genome, a process that was designed not to involve protein translation of these RNA fragments. The increased antiviral effects of these induced Ex/Mv were associated with increased expression of piRNA species some of which could predictably target SARS-CoV-2 genome. Knockout of piRNA-interacting protein PIWIL2 in htNSCs led to reductions in both innate and induced antiviral effects of Ex/Mv in targeting SARS-CoV-2. Taken together, this study demonstrates a case suggesting Ex/Mv from certain cell types have innate and adaptive immunity against SARS-CoV-2, and the PIWI-piRNA system is important for these antiviral actions.

Estimated plasma volume status (ePVS) is a predictor for acute myocardial infarction in-hospital mortality: analysis based on MIMIC-III database.

BACKGROUND: Estimated plasma volume status (ePVS) has been reported that associated with poor prognosis in heart failure patients. However, no researchinvestigated the association of ePVS and prognosis in patients with acute myocardial infarction (AMI). Therefore, we aimed to determine the association between ePVS and in-hospital mortality in AMI patients. METHODS AND RESULTS: We extracted AMI patients data from MIMIC-III database. A generalized additive model and logistic regression model were used to demonstrate the association between ePVS levels and in-hospital mortality in AMI patients. Kaplan-Meier survival analysis was used to pooled the in-hospital mortality between the various group. ROC curve analysis were used to assessed the discrimination of ePVS for predicting in-hospital mortality. 1534 eligible subjects (1004 males and 530 females) with an average age of 67.36 ± 0.36 years old were included in our study finally. 136 patients (73 males and 63 females) died in hospital, with the prevalence of in-hospital mortality was 8.9%. The result of the Kaplan-Meier analysis showed that the high-ePVS group (ePVS ≥ 5.28 mL/g) had significant lower survival possibility in-hospital admission compared with the low-ePVS group (ePVS < 5.28 mL/g). In the unadjusted model, high-level of ePVS was associated with higher OR (1.09; 95% CI 1.06-1.12; P < 0.001) compared with low-level of ePVS. After adjusted the vital signs data, laboratory data, and treatment, high-level of ePVS were also associated with increased OR of in-hospital mortality, 1.06 (95% CI 1.03-1.09; P < 0.001), 1.05 (95% CI 1.01-1.08; P = 0.009), 1.04 (95% CI 1.01-1.07; P = 0.023), respectively. The ROC curve indicated that ePVS has acceptable discrimination for predicting in-hospital mortality. The AUC value was found to be 0.667 (95% CI 0.653-0.681). CONCLUSION: Higher ePVS values, calculated simply from Duarte's formula (based on hemoglobin/hematocrit) was associated with poor prognosis in AMI patients. EPVS is a predictor for predicting in-hospital mortality of AMI, and could help refine risk stratification.

Hypothalamic microinflammation.

Over the past decade, hypothalamic microinflammation has been studied and appreciated as a core mechanism involved in the advancement of metabolic syndrome and aging. Accumulating evidence suggests that atypical microinflammatory insults disturb hypothalamic regulation resulting in metabolic imbalance and aging progression, establishing a common causality for these two pathophysiologic statuses. Studies have causally linked these changes to activation of key proinflammatory pathways, especially NF-κB signaling within the hypothalamus, which leads to hypothalamic neuronal dysregulation, astrogliosis, microgliosis, and loss of adult hypothalamic neural stem/progenitor cells. While hypothalamic microinflammation is a complex, multifaceted process, initial work has been done to reveal how it contributes to the pathogenesis of metabolic syndrome and aging, and studies inhibiting hypothalamic microinflammation through targeting proinflammatory signaling pathways have shown to be beneficial against these disorders and diseases. In this chapter, we provide a broad overview on hypothalamic microinflammation, focusing on its features, inducers, and shared pathogenic roles in metabolic syndrome and aging.

GnRH pulse frequency and irregularity play a role in male aging.

Gonadotropin-releasing hormone (GnRH) has a role in hypothalamic control of aging, but the underlying patterns and relationship with downstream reproductive hormones are still unclear. Here we report that hypothalamic GnRH pulse frequency and irregularity increase before GnRH pulse amplitude slowly decreases during aging. GnRH is inhibited by nuclear factor (NF)-κB, and GnRH pulses were controlled by oscillations in the transcriptional activity of NF-κB. Exposure to testosterone under pro-inflammatory conditions stimulated both NF-κB oscillations and GnRH pulses. While castration of middle-aged mice induced short-term anti-aging effects, preventing elevation of luteinizing hormone (LH) levels after castration led to long-term anti-aging effects and lifespan extension, indicating that high-frequency GnRH pulses and high-magnitude LH levels coordinately mediate aging. Reprogramming the endogenous GnRH pulses of middle-aged male mice via an optogenetic approach revealed that increasing GnRH pulses frequency causes LH excess and aging acceleration, while lowering the frequency of and stabilizing GnRH pulses can slow down aging. In conclusion, GnRH pulses are important for aging in male mice.

Motion Capture Data Analysis in the Instantaneous Frequency-Domain Using Hilbert-Huang Transform.

Motion capture data are widely used in different research fields such as medical, entertainment, and industry. However, most motion researches using motion capture data are carried out in the time-domain. To understand human motion complexities, it is necessary to analyze motion data in the frequency-domain. In this paper, to analyze human motions, we present a framework to transform motions into the instantaneous frequency-domain using the Hilbert-Huang transform (HHT). The empirical mode decomposition (EMD) that is a part of HHT decomposes nonstationary and nonlinear signals captured from the real-world experiments into pseudo monochromatic signals, so-called intrinsic mode function (IMF). Our research reveals that the multivariate EMD can decompose complicated human motions into a finite number of nonlinear modes (IMFs) corresponding to distinct motion primitives. Analyzing these decomposed motions in Hilbert spectrum, motion characteristics can be extracted and visualized in instantaneous frequency-domain. For example, we apply our framework to (1) a jump motion, (2) a foot-injured gait, and (3) a golf swing motion.

Innate and Adaptive Immunity of Murine Neural Stem Cell-Derived piRNA Exosomes/Microvesicles against Pseudotyped SARS-CoV-2 and HIV-Based Lentivirus.

By testing pseudotyped SARS-CoV-2 and HIV-based lentivirus, this study reports that exosomes/microvesicles (Ex/Mv) isolated from murine hypothalamic neural stem/progenitor cells (htNSC) or subtype htNSCPGHM as well as hippocampal NSC have innate immunity-like actions against these RNA viruses. These extracellular vesicles also have a cell-free innate antiviral action by attacking and degrading viruses. We further generated the induced versions of Ex/Mv through prior viral exposure to NSCs and found that these induced Ex/Mv were stronger than basal Ex/Mv in reducing the infection of these viruses, suggesting the involvement of an adaptive immunity-like antiviral function. These NSC Ex/Mv were found to be characterized by producing large libraries of P element-induced wimpy testis (PIWI)-interacting RNAs (piRNAs) against genomes of various viruses, and some of these piRNAs were enriched during the adaptive immunity-like reaction, possibly contributing to the antiviral effects of these Ex/Mv. In conclusion, NSC Ex/Mv have antiviral immunity and could potentially be developed to combat against various viruses.

Control of lifespan and survival by Drosophila NF-κB signaling through neuroendocrine cells and neuroblasts.

We report a comparative analysis of the effects of immune activation in the fly nervous system using genetic activation models to target Drosophila NF-κB within Toll versus Imd pathways. Genetic gain-of-function models for either pathway pan-neuronally as well as in discrete subsets of neural cells including neuroendocrine insulin-producing cells (IPCs) or neuroblasts reduce fly lifespan, however, these phenotypes in IPCs and neuroblasts are stronger with Toll activation than Imd activation. Of note, while aging is influenced more by Toll/NF-κB activation in IPCs during adulthood, neuroblasts influence aging more substantially during development. The study then focused on Toll/NF-κB inhibition, revealing that IPCs or neuroblasts are important for the effects of lifespan and healthspan extension but in a life stage-dependent manner while some of these effects display sexual dimorphism. Importantly, co-inhibition of Toll/NF-κB pathway in IPCs and neuroblasts increased fly lifespan greater than either cell population, suggesting that independent mechanisms might exist. Toll/NF-κB inhibition in IPCs was also sufficient to enhance survival under various fatal stresses, supporting the additional benefits to fly healthspan. In conclusion, IPCs and neuroblasts are important for Drosophila NF-κB for controlling lifespan.

Brain is an endocrine organ through secretion and nuclear transfer of parathymosin.

This study reports that parathymosin (PTMS) is secreted by hypothalamic stem/progenitor cells (htNSC) to inhibit senescence of recipient cells such as fibroblasts. Upon release, PTMS is rapidly transferred into the nuclei of various cell types, including neuronal GT1-7 cells and different peripheral cells, and it is effectively transferred into neuronal nuclei in various brain regions in vivo. Notably, brain neurons also produce and release PTMS, and because neuronal populations are large, they are important for maintaining PTMS in the cerebrospinal fluid which is further transferable into the blood. Compared with several other brain regions, the hypothalamus is stronger for long-distance PTMS transfer, supporting a key hypothalamic role in this function. In physiology, aging is associated with declines in PTMS production and transfer in the brain, and ptms knockdown in the hypothalamus versus hippocampus were studied showing different contributions to neurobehavioral physiology. In conclusion, the brain is an endocrine organ through secretion and nuclear transfer of PTMS, and the hypothalamus-brain orchestration of this function is protective in physiology and counteractive against aging-related disorders.