Four phenotypes of obstructive sleep apnea hypopnea syndrome (OSAHS) have been identified. Only one of these is anatomical. As such, anatomically based treatments for OSAHS may not fully resolve the condition. Equally, compliance and uptake of gold-standard treatments is inadequate. This has led to interest in novel therapies that provide the basis for personalized treatment protocols. This review examines each of the four phenotypes of OSAHS and explores how these could be targeted using breathing re-education from three dimensions of functional breathing: biochemical, biomechanical and resonant frequency. Breathing re-education and myofunctional therapy may be helpful for patients across all four phenotypes of OSAHS. More research is urgently needed to investigate the therapeutic benefits of restoring nasal breathing and functional breathing patterns across all three dimensions in order to provide a treatment approach that is tailored to the individual patient. Obstructive sleep apnea hypopnea syndrome (OSAHS) is a chronic sleep-related breathing disorder that is increasingly widespread and represents a significant cost to health ,2. In re2) pressure. If poor breathing patterns during wakefulness can be addressed, it is likely that this may provide a mechanism whereby sleep-disordered breathing can also benefit.Dysfunctional breathing patterns affect 9.5% of the general population , increasBreathing re-education (BRE) focuses on the patient’s breathing pattern, as dysfunctional breathing, such as chronic hyperventilation, is known to contribute to hypocapnia and related physical and mental problems, e.g., asthma and anxiety or panic disorders . The ButEstablishing full-time nasal breathing during wakefulness and sleep.Correcting the resting posture of the tongue.Slowing the respiratory rate.2.Using breath-hold time (BHT) to establish chemosensitivity to CORestoring diaphragm function and the lateral expansion of the lower ribs.2.Reducing the minute volume towards normal to regulate levels of COBRE is a therapeutic intervention based on the following fundamentals :EstablisThe key to treating dysfunctional breathing lies in viewing breathing pattern disorders from a three-dimensional perspective . DysfuncTake a normal breath in and out through your nose;Pinch your nose with your fingers to hold your breath;As you hold your breath, move your body or gently nod your head up and down;Hold your breath for as long as you can—until you feel a strong air hunger;Let go of your nose and breathe through it as calmly as possible.To decongest the nose, instruct the student to perform the following:Repeat 6 times with a 30–60 s rest between each repetition.BRE is of considerable interest to people with asthma and is recommended in evidence-based guidelines as possible adjuvant treatment for patients whose symptoms are not adequately controlled by pharmacological treatment. The current evidence base for BRE in asthma has been assessed as convincing by some systematic reviews, and the most recent Cochrane review has reported encouraging trends . The BREThe purpose of this review is to evaluate the possible application of BRE to OSAHS, and the effect that BRE might have in the four phenotypes that are currently described in OSAHS patients.Sleep-disordered breathing is a widespread condition with significant public health outcomes  and it iThere is a lack of enthusiasm for existing treatment options, and this contributes to poor treatment uptake. The gold standard treatment for OSAHS is continuous positive airway pressure (CPAP). but many factors can play a role in non-adherence. Claustrophobia, nasal obstruction and poor social support can all negatively impact CPAP use . Mouth lIn recent years, there has been an uptake in the use of mandibular advancement devices (MAD) in treating OSAHS . MADs prA further concern is that primary care physicians may fail to sufficiently explore the avenue of early OSAHS diagnosis, especially if the patient does not present with daytime fatigue and a high body mass index . As manyThe field of sleep medicine has changed radically in the last seven years with the recognition that OSAHS is not simply an anatomical issue. Upper airway collapsibility and craniofacial anatomy remain fundamentally important in the development of OSAHS . HoweverThe four phenotypes, as defined in 2013 research by Eckert et al., are pharyngeal critical closing pressure (Pcrit), loop gain, upper airway recruitment and arousal threshold . This coTreatment outcomes for the patient are strongly influenced by whether or not treatment is tailored to the phenotypes of the individual. For instance, a patient with high loop gain will not respond favorably to MAD . The impPhenotyping of OSAHS will have an important use for the sleep specialist, promoting the development of precision medicine and personalized management. A correct concept of phenotypes and endotypes of OSAHS is thus needed to understand the role that BRE should play in the multidisciplinary management of this disease ,38,39,40Pcrit is the gold standard of OSAHS assessment in terms of functional anatomy. It is used to measure the collapsibility of the airway in sleep-disordered breathing conditions from snoring to OSAHS ,41. PcriFactors that contribute to high Pcrit include deposits of fat around the pharynx and torso. Abdominal obesity compresses the abdomen and thoracic cavities causing an anatomical reduction in lung volume. This reduces tracheal tension and thus impairs the function of the upper airway dilator muscles. The same effect occurs during rostral fluid shift in patients with congestive heart failure. Rostral fluid shift involves fluid that has collected in the legs during the day migrating to the neck during sleep, restricting the function of the upper airway . Abdomin2. Patients with high loop gain have an exaggerated response to minimal changes in CO2. Messineo et al. assessed loop gain using breath holding and found that high loop gain is directly related to low breath-hold time (BHT) [Loop gain is a measure of the stability of ventilatory chemoreflex control. In other words, it reflects chemosensitivity to COme (BHT) . If loop2 is unable to leave the body via the lungs and so builds up in the bloodstream. The respiratory process is controlled by the levels of oxygen, CO2 and hydrogen ions in the arterial blood. Of the three, CO2 provides the most significant ventilatory stimulus. Rassovsky et al. state that an increase in pCO2 of just 2–5 mmHg can increase ventilation more than twofold [When the breathing stops during an apnea, CO twofold .2 and the switch from hypercapnia to hypocapnia. When the level of blood CO2 is too low, the brain is unable to send appropriate signals to breathe, and this can result in a central apnea [When breathing resumes after an apnea, individuals with high loop gain demonstrate exaggerated ventilation in response to minimal increases in carbon dioxide . A fast al apnea . Buterbaal apnea . At the al apnea .High loop gain can lead to a vicious cycle in which breathing resumes with such exaggerated force that the respiratory signals are inhibited. This can cause a central apnea to occur. At the same time, increased collapsibility of the throat produces an obstructive apnea. For this reason, high loop gain contributes to perpetuating apneas. This is supported by evidence that loop gain predicts apnea-hypopnea index (AHI) scores .Messineo et al. tested 20 patients in an overnight study using breath-hold time during wakefulness to determine the loop gain during sleep. The study tested maximal breath-hold duration and ventilatory response in the first two breaths following a 20 s breath hold—a duration that it was expected all participants could tolerate. Higher loop gain during sleep correlated with both a shorter maximal breath-hold time and a larger ventilatory response to a 20 s breath hold during wakefulness .The human pharynx is unique in that it lacks rigid, bony support . DependiOsman et al. state that there are more than 20 muscles in the upper airway. These are involved in both respiratory and non-respiratory functions, including breathing, chewing, speech and swallowing. In healthy people, activation of the upper airway muscles effectively opposes the negative suction pressure created during inhalation. This is also the case in patients with OSAHS during wakefulness. However, during sleep, reduced activity of these dilator muscles combined with a narrow airway can prompt airway collapse . Upper aIn the simplest of terms, arousal threshold refers to whether the patient is a light sleeper or a deep sleeper. The propensity to wake frequently from sleep correlates with insomnia, another sleep disorder that is commonly linked to autonomic imbalance . Insomni2 required to trigger arousal [Arousal threshold is defined by the level of intra-esophageal pressure and the amount of change in the concentration in arterial CO arousal . Patient arousal . Butler  arousal .If the upper airway dilator muscles are not functioning properly, sleep that is too deep can also present a problem. If the arousal threshold is so high that the patient fails to arouse during an apnea, the breathing can stop for a long time, leading to greater oxygen desaturation. High arousal threshold has, for instance, been implicated in sudden infant death syndrome .2 can drop by up to 25%. Stress can further increase hyperventilation when CO2 is already low [Breathing pattern disorders and chronic hyperventilation are more prevalent in women than men. This may be due to hormonal influences. Progesterone stimulates the respiratory rate in the luteal phase of the menstrual cycle (the phase after ovulation and prior to menstruation). During this time, levels of COeady low .Women have a later onset of OSAHS, and AHI severity did not increase until age 50 years and older. These gender differences decreased with age. Studies have suggested that hormonal changes experienced by women during menopause may be responsible for an increased AHI in women of menopausal age ,59,60.It has been proven that OSAHS and sleep-disordered breathing (SDB) increase in postmenopausal women. LoMauro and Aliverti suggest that sex hormones play a protective role in airway health in women . The litChanges in body-fat distribution are likely to contribute to OSAHS in postmenopausal women . After mOSAHS is caused by the interaction of several key traits of upper airway anatomy and neuromuscular control . These cThere is currently limited research into the relationship between breathing pattern disorders and the phenotypes of sleep apnea. Equally, the application of BRE for OSAHS has not been studied. It is known, however, that mouth breathing during sleep increases the severity of OSAHS , and tec2 and high loop gain during sleep maintain these characteristics during wakefulness [In a review of 14 articles, Courtney describes an interest in treatments that address the four phenotypes of OSAHS, emphasizing the bi-directional relationship between breathing during the day and breathing at night [efulness  . There is an argument for taping the mouth during sleep regardless of whether breathing is through the mouth, nose or oro-nasally. Meurice et al. found that just opening the mouth increases the collapsibility of the upper airway independently of any nasal obstruction and without changes in the breathing route [Our own empirical evidence indicates that the only way to ensure nasal breathing during sleep is to use supports such as paper tape across the lips, chin up strips or MyoTapeng route . This isng route .2 can be estimated by measuring breath-hold time (BHT) [Chemosensitivity to COme (BHT) ,96. One me (BHT) . Short bme (BHT) ,102,103.2. Since chemosensitivity to CO2 and BHT are both predictors of loop gain, BRE may reduce the loop gain by increasing BHT and lowering chemosensitivity to CO2.Keisel et al.  proposedIt is apparent that treatment of loop gain is important in the treatment of OSAHS, especially in patients who do not respond to MAD and surgery ,104. MADNasal breathing harnesses the gas nitric oxide, which plays a role in the maintenance of muscle tone and regulation of neuromuscular pathways in the pharyngeal muscles . IndividIt has been found that individuals with OSAHS have reduced respiratory muscle strength compared with individuals of the same age and gender without OSAHS . AccordiBRE includes exercises to improve the strength and function of the inspiratory muscles, in particular, the diaphragm. Because of the small size of the nostrils relative to the mouth, breathing through the nose during wakefulness imparts a resistance to airflow that is at least 50% greater than the resistance from mouth breathing . It may The resting posture of the tongue is relevant in OSAHS. The genioglossus muscle in the tongue plays a key role in maintaining an adequate airway ,111. IndWishney et al. state that MT offers a potential way to increase tone in the upper airway muscles and restore nasal breathing, and that it can provide a successful adjunct therapy for OSAHS in adults and children . The deb2 before and after MT of 4.19% [In a review of the relevant literature, Camacho et al. concluded that MT yields a reduction in AHI of around 50% in adults and 62% in children . The revof 4.19% . The man2, sleepiness and snoring all improved in adults as a result of MT and that the therapy could provide a useful adjunct to other forms of OSAHS treatment [Therefore, more research is needed to identify the pathophysiology and mechanisms whereby MT is effective for some patients with OSAHS. The review recommends that future studies utilize the standardized exercises that have been developed and used by Guimaraes et al. , who havreatment .® have been developed [p < 0.001). The tongue pressure increased from 39.83 (35.32–45.2) to 59.06 (54.74–64.00) kPa (p < 0.001). The AHI correlated significantly with the tongue pressure. There was an adherence rate of 90% in the intervention group [The main problem with MT is the proper selection of the patient to the therapy. O’Connor et al. suggest that patients with an absence of nasal obstruction, no restriction in tongue movement and low airway muscle tone ) are the best candidates for MT . It is aeveloped . In a raon group .p = 0.03), while tongue pressure significantly increased from 35.9 to 45.6 kPa (p < 0.01). Seven patients (22%), including six of the 12 patients with moderate OSAHS (50%), experienced successful CPAP discontinuation.Suzuki et al.  recentlyIn 2019, Huang et al. published the first study to indicate that MT can restore nasal breathing during sleep . All-nigDiaféria et al.  studied A review from de Felício et al. showed that MT is successful in reducing snoring and OSAHS and improving quality of life in adults. It is also effective in treating children with residual apnea, and it improves CPAP compliance and adherence. Only a limited number of clinical studies currently exist into MT, and it is necessary to analyze the long-term effects of treatment to discover whether it contributes to changes in the musculature .During nose breathing, sleep is deeper. In 1991, Smith et al. identified a neural circuit within the brainstem called the preBötzinger complex (preBötC) . This neLow arousal threshold and insomnia often go hand in hand . Both arLow arousal threshold represents perhaps the greatest risk for OSAHS patients of all the phenotypes. The risk of all-cause mortality is inversely proportional to the duration of apneic events . Butler Slow, nasal breathing activates the parasympathetic nervous system via the vagus nerve . Mouth b®, does not cover the mouth. Instead, it surrounds the mouth, bringing the lips together with light elastic tension to help ensure nasal breathing. If at any time, the user needs to open their mouth, they can do so easily . The median AHI score was significantly decreased by using a POP from 12.0 per hour before treatment to 7.8 per hour during treatment . Taping o easily .It is important to examine OSAHS with an awareness of all four phenotypes/endotypes. This is not just an anatomical issue. Even in terms of Pcrit, the speed and volume of airflow are as relevant as the collapsibility of the airway. It is necessary to open the airway in order to help the anatomy. Equally, it is necessary to reduce breathing rate and flow to minimize airway turbulence during sleep , as propAn interesting point to note in terms of research history is that when Evans and Lum began examining hyperventilation syndrome in the mid-1970s, their work roused considerable resistance and even hostility. It was suggested that they had misdiagnosed asthma, allergies and “non-disease” . This un2 . This involves:For individuals with sleep apnea, the goal should be to reach a comfortable breath-hold time after an exhalation of 25 s. While mouth taping is effective, merely taping the mouth during sleep is not enough. Nor is it sufficient to target only one dimension of breathing. BRE needs a tailored approach to the individual. Managed in this way, it could offer substantial therapeutic intervention across all four phenotypes of sleep apnea. It would seem much of the groundwork has been done. It is time to follow the research to its logical conclusion.


Giardia duodenalis is a zoonotic enteric parasite that can infect humans and a number of animal species including rabbits with a worldwide distribution. Infection with G. duodenalis can cause serious public health problems and significant economic losses to animal husbandry. So accurate understanding of the prevalence and genotype distribution of G. duodenalis in rabbits is necessary. In the present study, a total of 616 fecal samples were collected from rabbits in Shandong province, eastern China, and examined in G. duodenalis prevalence and genotypes by nested PCR amplification of β-giardin (bg), glutamate dehydrogenase (gdh), and triosephosphate isomerase (tpi) gene loci of G. duodenalis. Sixty-nine (11.2%) of the examined rabbit fecal samples were G. duodenalis-positive. Of them, the prevalence of G. duodenalis is 8.4% (41/490) in Rizhao city and 22.2% (28/126) in Weihai city. Breeds, region, and feeding modes were highly correlated with G. duodenalis infection in rabbits. Moreover, three genotypes  were identified in rabbits at three gene loci, and the assemblage E was the dominant genotype, while the assemblage A was reported in rabbits in China for the first time. It is noticeable that two rabbits were found to be infected with two different G. duodenalis assemblages . These findings enrich the genotype distribution of G. duodenalis in rabbits and provide baseline data for preventing and controlling G. duodenalis infection in rabbits in eastern China. Giardia duodenalis  is a common gastrointestinal protozoon that causes enteric disease in a variety of animal species and humans [G. duodenalis over the world [G. duodenalis cysts [G. duodenalis also has been recognized as an important zoonotic disease for both public and animal health [d humans –4. More he world , 5. Humais cysts . The cliis cysts , 6, 7. Gl health , 7, 8.G. duodenalis, including assemblages A–H [Eight assemblages have been identified in ages A–H , 5. The ages A–H . Among aages A–H , while tages A–H , 11.G. duodenalis [G. duodenalis prevalence in rabbits in China [G. duodenalis in rabbits in Shandong province, eastern China.Rabbits are one of the most important economic animals in China, and the consumption of meat and fur accounts for a large part of China's economy . Howeverodenalis –20, whicin China , 18–20; A total of 616 rabbit fecal samples  were collected from Shandong province, eastern China. The fecal samples were composed of 207 New Zealand white rabbits, 188 long-haired rabbits, and 221 Tolai hares. Each fresh fecal sample was collected with gloves and placed into a box with ice, then marked with the breed, age, and region, respectively, and transported to the laboratory. All of the fecal samples were stored at −20°C for further DNA extraction.g for 5 min in a centrifuge, the filtrate was discarded, and the precipitate was retained; then approximately 300 mg of each precipitate of fecal sample was used to extract genomic DNA using the commercial E.Z.N.A.R® Stool DNA Kit , following the manufacturer's recommendations. The extracted genomic DNA was stored at −20°C for further PCR amplification.Each rabbit fecal sample was washed with distilled water, uniformly stirred, and the residue was filtered through a 60-mesh sieve (0.23 × 0.23 mm). The filtrate was centrifuged at 4000G. duodenalis were examined by nested PCR amplification of the bg, gdh, and tpi gene loci as described previously [The prevalence and genotypes of eviously , 15. Thehttp://www.ncbi.nlm.nih.gov/BLAST/) and edited using computer Clustal X 1.83 [https://www.megasoftware.net/), the Kimura 2-parameter model was selected, and 1,000 bootstrap replicates were calculated.All of the positive secondary PCR products were sent to Tsingke Biotechnology Technology Company  for two-directional sequencing. The obtained sequences were compared with reference sequences in GenBank database  test. The 95% confidence intervals (CIs) and odds ratios (ORs) were estimated by SPSS version 24.0 . If the statistical resultP < 0.05, the difference was considered statistically significant.The relationship between the G. duodenalis by nested PCR amplification of the bg, gdh, and tpi loci . Moreover, the G. duodenalis prevalence in rabbits from Rizhao city  was significantly lower than that from Weihai city  . Rabbits raised outdoors had a significantly higher G. duodenalis prevalence (23.1%) than that raised indoors (4.6%)   than rabbits of more than 6 months old   (95% CI: 7.70–15.33) was slightly higher  than that in female rabbits (11.0%) (95% CI: 7.67–14.22)  of the examined 616 rabbit fecal samples were positive for tpi loci . Among d < 0.01) . Rabbits7–16.27) . The G. 7–14.22) .G. duodenalis prevalence in rabbits was 11.2% (69/616), which was higher than that in rabbits in Henan province  [G. duodenalis prevalence in rabbits may be caused by many factors such as geographical ecological environment, detection methods, sample size, and individual health status [In the present study, the overall  80/955) , Jilin p 80/955) , Heilong 80/955) , Xinjian 80/955)  in China1.2% 69/6, which w 80/955) , but low 80/955) . The difh status .G. duodenalis assemblages (assemblages B and E) have been reported in rabbits in China [G. duodenalis genotypes by nested PCR targeting the bg, gdh, and tpi genes. The results showed that 53 bg-positive samples and 39 gdh-positive samples were identified as assemblage E; two  tpi-positive samples and one  tpi-positive sample were identified as assemblage B and assemblage A, respectively. Interestingly, the assemblage E  was the dominant genotype in rabbits in the present study, which was different from the previous studies [G. duodenalis assemblages  were identified in rabbits, and the assemblage A was firstly detected in rabbits in China in the present study. The G. duodenalis assemblage A was also reported in humans [G. duodenalis.Two in China , 18–20.  studies . Moreoven humans . This fiG. duodenalis assemblages in rabbits, we aligned the obtained sequences with reference sequences in GenBank by Clustal X 1.83, which were used for phylogenetic analyses  existed in bg sequences and gdh sequences in this study . Three G. duodenalis assemblages  were identified in rabbits, assemblage A was reported in rabbits in China for the first time, while assemblage E was the dominant assemblage. These findings not only enriched the genotype distribution of G. duodenalis in rabbits but also have an implication for better control of G. duodenalis in rabbits. Further studies are necessary to examine the infection status and genotype distribution of G. duodenalis in rabbits in other areas of the country.The present study revealed a higher (11.2%)


The reproductive status of dairy cows remains a challenge for dairy farmers worldwide, with impaired fertility linked to a significant reduction in herd profitability, due in part to impaired immunity, increased metabolic pressure, and longer postpartum anestrous interval (PPAI). Exosomes are nanovesicles released from a variety of cell types and end up in circulation, and carry proteins, bioactive peptides, lipids, and nucleic acids specific to the place of origin. As such, their role in health and disease has been investigated in humans and animals. This review discusses research into exosomes in the context of reproduction in dairy herds and introduces recent advances in mass-spectrometry (MS) based proteomics that have a potential to advance quantitative profiling of exosomal protein cargo in a search for early biomarkers of cattle fertility. Dairy cow fertility has been in decline for the past 20 years ,2,3. SelAlthough it is widely accepted that increased metabolic pressure due to increased milk production is associated with poor reproductive outcomes, average producing cows may also experience reproductive challenges . There aHeifers can be separated into high- and low-fertility groups based on their genetic merit and other measurable physical traits . HoweverExosomes, nanovesicles of ≈30–150 nm in diameter, can be isolated from the bodily fluids of dairy cows , and present a unique opportunity to studying the molecular cues that underlie poor reproductive performance . ExosomeWithin the cell there is a complex protein synthesis and sorting pathway, whereby protein folding and glycosylation begin in the endoplasmic reticulum (ER). Mature and proproteins are further modified as they pass through the Golgi apparatus, and following this are transported via transport vesicles to early endosomes  and prostaglandin F2α (PGF2α) in cell culture media supernatant compared to controls , ,40, 2 anactivity . A recenactivity . UnfortuThe transition period is a demanding phase in the life of dairy cows and challenging from the farm management perspective. It is typically defined as the period ranging from 3 weeks before and after calving  and repr2α produced by cells treated with exosomes derived from the infected cows [2α in disrupting normal reproductive processes and offers a potential target for improving outcomes in these animals. Despite this, the transition period still proves to be a challenging time for dairy farmers and their herds, and further research is required to better identify at-risk cows in hopes of preventing postpartum infection and maintaining reproductive efficiency.Numerous studies have focused on the link between BCS, NEB, and feed-intake during the transition period as a method of immunomodulation, in hopes of improving management of the transition dairy cow ,65,66,67ted cows . This suThus far, partly due to the ethical nature of conducting in vivo experiments, studies have steered towards in vitro modeling of bovine uterine infection. However, this may not be representative of the full spectrum of physiological mechanisms involved in, and leading to, high- or low-fertility and susceptibility to reproductive disruption in early life and during the transition or postpartum period. Bodily fluid samples obtained from cattle with and without disease may already be compromised regarding differences in molecular content, as it would be expected that inflammatory/disease markers would be present in affected animals at the time of disease occurrence. A more useful and predictive method of testing for differences would require sampling at the baseline stage, long before cattle experience reproductive and immune challenges. For example, sampling may occur around the time of puberty or earlier in order to establish a predictive model of reproductive performance and predisposition for disease in the early stages of reproductive life. Currently, Fertility Breeding Value (FBV) and BCS are the only tools available to dairy farmers to assist in the herd selection process, which does not consider the individual genetics or physiology of animals, but merely relies on physical attributes and genetic lineage as predictors ,69. EarlEpigenetic regulation of gene expression has been well studied with regards to mammalian development ,72,73,74Bovine blood sera and exosomes have been subjected to miRNA profiling, and while 282 shared miRNAs were identified, 12 miRNAs were found to be differentially expressed between sera and exosomes . CirculaMass spectrometry (MS) is the technique of choice for determining the abundance of hundreds to thousands of proteins and continues to evolve through advancements in instrumentation, data acquisition modes and data analysis software. Its utility in protein analysis has a long history and has been extensively reviewed elsewhere ,92,93,94In relation to dairy cow reproduction, MS has been utilized to perform thorough and reproducible analyses of bovine plasma, milk, follicular fluid, and uterine flushings ,102,103.DDA and targeted methods of MS, while effective, can be costly and/or only applicable to a limited number of samples. More recently, techniques such as sequential window acquisition of all theoretical mass spectra (SWATH-MS), termed next-generation proteomics, have emerged that allow the analysis of a greater number of samples with greater quantitative precision and impressive proteome coverage ,117,118.First described by Gillet et al. (2012), SWATH-MS is a variant of DIA that has already been applied to a large number of proteomic studies, including the analysis of exosomal protein cargo ,120,121.Compared to other quantitative proteomics methods, the ease at which data is acquired is also a significant advantage, as once the precursor isolation scheme is set and method optimized for a particular sample type, analysis of different samples of the same type can be performed using the same method. A collaborative study looking at reproducibility and accuracy of SWATH-MS data detected and quantified >4000 proteins from Human embryonic kidney 293 (HEK293) cells in a 2-h run, and this was reproducible across multiple laboratories . This alIrrespective of MS approach employed, the analysis will largely depend on sample processing prior to MS. Highly abundant exosome proteins could compromise quantitation of low abundant cargo proteins of reproductive tissue origin and thus of biomarker potential. Enrichment of exosome populations of interest are therefore key to a successful outcome. The current methods of exosome purification involve sequential centrifugation, ultrafiltration, and size-exclusion chromatography, although there is currently no ‘gold-standard’ for exosome isolation ,129,130.Suboptimal fertility in dairy cows has been attributed to acquired conditions such as poor uterine health, the adaptation to the transition period, and maternal-embryonic crosstalk in early pregnancy. Fertility status in dairy cows may also be determined at a much earlier timepoint due to factors stemming from genetic variants, which manifests in vivo as alterations to signaling pathways related to reproduction. Whether the fertility is a result of an acquired condition or inherited, the body responds in-kind by releasing exosomes that contain bioactive cargo that may provide a clue to cattle fertility ,50,51. E


N = 1,472,813). To study the direct effect of birth order on fertility, sibling comparison models are applied, while to analyse the joint effect of number of siblings and birth order, the sample was stratified by birth order. Results show that higher birth order has a negative effect on completed fertility for women; hence, earlier-born women show overall higher fertility than later-born women. Parity transitions indicate that later-born women are less likely to have two or more children, while no overall gradient for men can be found. The number of siblings is more positively associated with completed fertility for firstborn than for later-born individuals. We conclude that the position in the family of origin can be seen as an additional factor that influences fertility, although effect sizes are rather small.This study examines how the sibling constellation in childhood is associated with later fertility behaviour of men and women in Sweden. Administrative register data are used to investigate how birth order affects completed fertility, how the number of siblings and birth order jointly affect completed fertility, and in both cases if there are gender differences in these relationships. Our data consist of all fully biologically related siblings in Sweden whose mothers were born between 1915 and 1935 (the younger generation is born primarily in the 1940s, 1950s and 1960s;  Research consistently found that the family background has important implications for future childbearing patterns. Both the family composition during childhood and the values acquired from parents have been linked to subsequent fertility behaviour and attitudes Barber . Such faThus, structural factors in the family of upbringing—such as number of siblings and the position among them—may have important implications later in life Kolk , due to In this study, we focus on how the sibling composition in the family of origin affects their future fertility, focusing on both an individual’s order in the sibling set, and how the birth order interacts with the number of siblings in the family. Birth order research on outcomes such as education and IQ has a long history going back to the 1930s  is associated with high fertility among their children. Theories on birth order and childhood development suggest that the relative role of parents’ impact on preferences will vary across birth orders, which was one of the central concerns in research on intergenerational transmission of fertility in the 1960s and 1970s  are also important determinants for fertility outcomes, but this relationship varies substantively across context. For Sweden, it has been shown that education is only weakly related to completed fertility , while processes such as socialization may be affected by birth order. If parents treat and socialize firstborn children different from later-born children, this would imply different conditions during upbringing. Individual childbearing behaviour and preferences are, amongst others, results of socialization. However, little research has focused on the structural characteristics, such as if the number of siblings and birth order affects socialization of fertility preferences   is associated with completed fertility and how the effect varies according to the birth order of the child. Number of siblings is a strong and influential predictor of fertility Kolk . Hence, In the 1960s and 1970s, research on intergenerational transmission of fertility used birth order as one of the key explanatory variables  and own fertility is shown. This was chosen as second-born siblings will always have one older sibling, but we are interested in how an increase in family size affects them. We present such results with separate models for each birth order, where the slope in the graph represents the strength of the relationship between number of siblings and own fertility. Ordinary least square (OLS) regression analysis has been used for both research questions, in which number of children of the younger generation is our dependent variable.We use administrative population registers for the complete population of Sweden. Individuals are connected by means of a personal identity number, allowing accurate linkages across generations inside Sweden. The analysis population consist of all Swedish-born individuals with a mother born between 1915 and 1935 . Whereas the younger generation is born between 1932 and 1988  and is observed in 2012, thus prior to applying our sample selection criteria, the data include completed fertility for virtually all members of the younger generation. Although both our older and younger cohorts cover very different historical times, effects would not reflect cohort effects as the cohort fertility rate in Sweden was very stable over these periods (“Appendix”, Fig. In general, very young maternal age is associated with negative child outcomes in education, cognitive abilities and health Conley , which iIn order to investigate how birth order affects fertility, we run sibling fixed-effects models. Firstly, Fig. In a next step, the analysis was extended to examine transitions to different parities by birth order. Focusing on each parity transition enables us to show nonlinear relationships between a person’s birth order and the distribution of their eventual number of children. Figure Figure The combined effect of both number of siblings and birth order on fertility is examined in the second part of the analysis. Theoretical approaches and research suggest that the influence of parental characteristics, such as number of siblings, on their children might be larger for early-born siblings. Our results are consistent with the previous research, showing that intergenerational transmission of completed fertility exists in Sweden Dahlberg . A positTo identify whether the fertility of firstborn individuals is stronger related to the number of siblings, than the fertility of later-born individuals, we stratify our population by birth order and examine subsequent siblings born after the index person, which means younger siblings. Figures Overall, we find evidence that firstborn men and women show higher intergenerational transmission of fertility, with lower levels for higher birth orders. Our results therefore largely conform to theories of firstborn being more affected by parental behaviour, and potentially more compliant than later-born siblings, and this suggests that intergenerational transmission is linked to the number of younger siblings, rather than just siblings per se. Our birth order differences are most clear when contrasting the firstborn with everyone else, rather than finding a gradual decrease in the effect of parental behaviour at each subsequent birth order. The results presented in Figs. We have examined two aspects of how birth order is affecting fertility outcomes; firstly, we examined the direct effect of birth order on fertility, and secondly, the interplay of birth order and number of siblings on fertility. By applying sibling comparison models, we are able to control for all shared factors between siblings including unobserved heterogeneity and the fact that higher birth order siblings come from bigger families. These sibling fixed-effects OLS models show a negative effect of increasing birth order on completed fertility for women, while no substantive association can be found for men, though all effects are rather small. Birth order effects on parity transitions show that for women higher birth order has a negative effect on the second, third, and fourth parity transitions. Hence, later-born women are less likely to have two or more children compared to their firstborn sisters. Being a later-born sibling for man is associated with a lower likelihood to have three or more children, but effects are much smaller. Overall, these results indicate that firstborn men and women are less likely to have only one child and more likely to have a higher number of children compared to their brothers and sisters. For women, this translates into lower completed fertility of later-born sisters. The largest effect sizes are found for parity progression ratios for later-born women, who typically are up to 5 more percentage points less likely to have higher order births than firstborn women. Nevertheless, comparing the effect sizes to other well-known fertility predictors, birth order seems to be a less important factor.Theoretically, the resource dilution hypothesis as well as the confluence hypothesis led to the assumption that earlier-born individuals may have higher completed fertility, given the positive association between status and fertility in Sweden. On the other hand, previous studies from psychological research on personality and birth order would suggest a negative effect of being earlier born on fertility outcomes. Our results for women show that the effect of birth order on total family size is consistent with explanations of lower socio-economic status with higher birth order, which may lead to lower fertility. However, we do not find such a pattern for men, which is not consistent with a socioeconomic status based explanation, especially when socioeconomic indicators are more strongly linked to fertility for men in Sweden (Boschini et al. What role does the number of siblings play in combination with birth order? Intergenerational transmission of family size has previously been shown, but does the importance of the number of siblings differ by birth order? Birth order and socialization theory suggest a stronger intergenerational resemblance for firstborn children, but previous studies did yield mixed results. Stratifying the population by birth order identifies different effects of number of siblings on earlier- and later-born individuals. We find that firstborn men and women show higher levels of fertility, as well as increasing fertility with higher numbers of siblings. Few significant differences can be found among second or higher birth orders, except for their lower transmission compared to firstborn. Accordingly, our results are consistent with previous research on intergenerational transmission of fertility that has found firstborns to show higher fertility (Booth and Kee Overall, this shows that firstborn siblings show a higher fertility within their family, as well as with increasing number of siblings. Finding a negative relationship between increasing birth order and fertility for women complements other research that has recently found birth order effects for various later life outcomes (Barclay and Myrskylä


Mycobacterium sp. exploits macrophage proteins such as Coronin 1, Calcineurin, LRG47, SOCS1, CISH, Gbp5 etc. and secretes virulence proteins such as PknG, PtpA, SapM, Eis etc. to hijack these intra-macrophage, signaling cascades and thereby develop its own niche. Coronin 1, being a cortical protein is transiently recruited to all mycobacteria containing phagosomes, but only pathogenic mycobacteria can retain it on the phagosome, to hinder its maturation. Additionally, mycobacterial infection linked secretion of virulence factor Protein Kinase G through its phosphorylation, manipulates several macrophage signaling pathways and thus promotes pathogenesis at various stages, form early infection to latency to granuloma formation. Here we discuss the present status of mycobacteria engaged Coronin 1-dependent signaling cascades and secreted PknG related sequence of events promoting mycobacterial pathogenesis. Current knowledge about these two proteins in context of macrophage signaling manipulation encompassing diverse mechanisms like calcium-calcineurin signaling, reduced proinflamtory cytokine secretion, cytoskeletal changes, and adaptation in acidic environment, which ultimately converge toward mycobacterial survival inside the macrophages has been discussed.Macrophages being the connecting link between innate and adaptive immune system plays a crucial role in microbial antigen presentation and orchestrates the subsequent clearance of microorganisms. Microbial invasion of macrophages trigger a plethora of signaling cascades, which interact among them to generate a dynamically altered hostile environment, that ultimately leads to disruption of microbial pathogenesis. Paradoxically,  Mycobacteria sp. which are the causative agent of pulmonary and extra-pulmonary tuberculosis, leprosy, skin abscess etc. are one of those notorious intracellular pathogens. On average 10 million people contract tuberculosis every year with a mortality being close to 1.5 million. Additionally latent TB infection globally is 1.7 billion of which more than 10% progress to active disease  plays a primary role and these together enables it to survive within the macrophage as well as generate an anti-inflammatory milieu. Here we discuss different approaches taken by several groups to understand the role of Coronin 1 and PknG in mycobacterial pathogenesis.Mycobacterium sp hijacks several host factors. Coronin 1 is one such factor that helps mycobacteria to prevent phagosome maturation and thereby aids in mycobacterial survival inside the macrophages  is one (Cole et al., in vitro and upon infection with mycobacteria (Wu et al., PknG gets transphosphorylated on N-terminal threonine residues prior to activation of the kinase domain for phosphorylation events and thereby accentuate mycobacterial survival inside macrophages (Scherr et al., The interplay of host factors and secreted virulence factors culminating in immunesubversion ultimately enables successful mycobacterial pathogenesis. Owing to the emergence of chemoresistant mycobacterial species and the success of host-directed immunomodulatory therapeutics in oncotherapy, such approaches are being envisioned against tuberculosis and leprosy. Targeting of Coronin 1 trimerization through peptidomimetics could induce maturation of mycobacterial phagosomes thus leading to lysosomal transfer and elimination. PknG being a secreted kinase can be targeted in the macrophage cytosol so as to prevent phosphorylation of host substrates key to mycobacterial pathogenesis and thereby induce its elimination. Therefore, host-directed therapeutics would emanate as an efficient strategy to combat the global tuberculosis and leprosy menace.SS wrote the manuscript. SB reviewed the manuscript and provided critical inputs. PD checked for format and typographical errors. All authors contributed to the article and approved the submitted version.The authors declare that this mini review was prepared in the absence of any commercial or financial relationships that could be interpreted as a potential conflict of interest.


Cardiac fibrosis describes the inappropriate proliferation of cardiac fibroblasts (CFs), leading to accumulation of extracellular matrix (ECM) proteins in the cardiac muscle, which is found in many pathophysiological heart conditions. A range of molecular components and cellular pathways, have been implicated in its pathogenesis. In this review, we focus on the TGF-β and WNT signaling pathways, and their mutual interaction, which have emerged as important factors involved in cardiac pathophysiology. The molecular and cellular processes involved in the initiation and progression of cardiac fibrosis are summarized. We focus on TGF-β and WNT signaling in cardiac fibrosis, ECM production, and myofibroblast transformation. Non-coding RNAs (ncRNAs) are one of the main players in the regulation of multiple pathways and cellular processes. MicroRNAs, long non-coding RNAs, and circular long non-coding RNAs can all interact with the TGF-β/WNT signaling axis to affect cardiac fibrosis. A better understanding of these processes may lead to new approaches for diagnosis and treatment of many cardiac conditions.Video Abstract Cardiac fibrosis and abnormal tissue remodeling are pathological findings in many cardiac disorders, such as myocardial infarction, hypertension, myocarditis, cardiac hypertrophy, and dilated cardiomyopathy. These conditions are associated with considerable morbidity and mortality –3. The p−/− and Smad3+/+ mice revealed that TGF-β did not induce any transcription in Smad3−/− fibroblasts [−/−) were not viable during embryogenesis, suggesting that Smad2 is required for normal development [A growing body of evidence indicates that members of the TGF-β family can play a major role in a wide range of processes related to cardiac pathophysiology, including cardiac repair, hypertrophy, fibrotic remodeling, fibroblast activation, and extracellular matrix deposition –23. The roblasts . Intriguelopment . Two inhelopment . After celopment , 44.In addition, TGF-β can also result in direct activation of a non-canonical response via three different pathways, namely the PI3K/Akt, RhoA-ROCK axis and MAPK cascades. In the PI3K/Akt pathway, activated TGF-β type I receptor stimulates a signaling cascade involving phosphatidylinositol-3-kinase (PI3K) and protein kinase B . In this pathway, PI3K activation mediates phosphorylation and activation of Akt kinase, which in turn modulates several downstream effectors, such as the mammalian target of rapamycin (mTOR), glycogen synthase kinase-3β (GSK-3β) and many others , 46. TheSeveral publications have indicated the importance of the WNT signaling cascade in normal development and the pathogenesis of many diseases –56. WNT In the WNT/β-catenin signaling pathway, the activated Fz/LRP complex activates the Dishevelled (DVL) protein, which interacts with a “destruction complex” comprised of axin, adenomatous polyposis coli (APC), glycogen synthase kinase 3 (GSK3), casein kinase 1 (CK1), plus the ubiquitin ligase, β-TrCP. This destruction complex normally causes the ubiquitination and consequent destruction of β-catenin –61. When2 + −sensitive enzyme activated by Ca2+ release which results in elevated nuclear levels of the AP-1/c-Jun transcription factor [In the β-catenin-independent signaling pathway, WNT4, WNT5a or WNT11 ligands can stimulate the Fz receptor to trigger gene transcription, by activating the planar cell polarity pathway, and a calcium-dependent pathway. Signal transduction through the WNT/calcium cell polarity pathway typically consists of protein kinase C (PKC), calmodulin kinase II and calcineurin. Calcineurin is a Can factor , 65. In n factor .Endogenous WNT antagonists, such as the Dikkopf (DKK) and secreted frizzled-related protein (sFRP) families can regulate WNT signaling –69. Manyact-induced fibrosis) enhanced the stability and nuclear accumulation of β-catenin in primary cultured fibroblasts. These results showed that TGF-β activated the canonical WNT pathway through a decrease in Dkk-1 via MAPKp38, and this could be a major molecular mechanism for the activation of the canonical WNT pathway [Recent studies have highlighted the extensive cross-talk between the TGF-β and WNT pathways, which could be responsible for the transcription of pro-fibrotic genes. These pathways could create a positive feedback loop or a negative feedback loop that impacts on the transcriptional activity of other signaling cascades. For instance, loss of the WNT co-receptor LRP5, in bleomycin-induced lung fibrosis decreased the expression of TGF-β1, and attenuated the induction of fibrosis . Consist pathway . In addi pathway . In addi pathway . Another pathway .Furthermore, the microRNA, miR-29 inhibited the synthesis of ECM caused by TGFβ1, through inhibition of WNT3a/β-catenin signaling pathway in human orbital fibroblasts . Yeast tCardiac fibrosis is characterized by the increased activity of cardiac fibroblasts, resulting in the accumulation of ECM proteins (e.g. collagen I and III), which produce increased myocardial stiffness, and thereby increase the risk of heart failure and sudden cardiac death . CardiacFinding an effective treatment for myocardial fibrosis is a major clinical challenge, which may dramatically improve the survival rate and the quality of life in patients. Cardiac magnetic resonance (CMR) imaging has been used to evaluate the extent of diffuse myocardial fibrosis, and for monitoring patients with cardiac fibrosis –95. In oand Table Myofibroblasts expressing expressed α-SMA (smooth muscle actin) are mainly involved in the excessive synthesis and degradation of collagen in cardiac fibrosis , 101. Fo1ncRNAs play important roles in many cellular processes. Based on nucleotide length, they are classified into: small miRNAs (22 nucleotides) and lncRNAs (> 200 nucleotides) , 139. CiThe role of ncRNAs  has been shown in many studies –152. TheCircRNAs are another type of single-stranded RNA molecules, which are involved in many normal physiological processes, as well as the pathogenesis of cardiovascular disease , 157. FoThe relationship between ncRNAs and TGFβ and/or WNT signaling has been demonstrated in studies, and could affect many pathogenic conditions. Colorectal cancer patients with high expression of certain lncRNAs had a shorter overall survival and a worse response to chemotherapy. It was found that these lncRNAs promoted CRC progression by activating Wnt/ β -catenin pathway through activator protein 2 α. Furthermore, lncRNA can induce multidrug resistance through activating Wnt/ β-catenin signaling by up-regulating MDR1/P-gp expression .Wu et al. showed that down-regulation of lncRNA CCAT2 reduced the expression of TGF-β, Smad2 and α-SMA in breast cancer patients. CCAT2 promoted growth and metastasis of breast cancer by regulating the TGF-β signaling pathway .Shan et al. found that over-expression of lncRNA Linc00675 inhibited the proliferation and migration of colorectal cancer cells. Furthermore, they found that the expression of miR-942 in clinical colorectal cancer tissues was higher than in normal tissue. More importantly, the inhibitory effect of Linc00675 was also attenuated by a miR-942 mimetic, suggesting that down-regulation of miR-942 represented one of the mechanisms by which Linc00675 inhibited the proliferation and metastasis of colorectal cancer. They demonstrated the inhibition of Wnt/β-catenin signaling in the Linc00675/miR-942 regulated pathway in colorectal cancer cells .LncTCF7 is a lncRNA which required for liver cancer stem cell self-renewal and tumor progression. lncTCF7 recruited the SWI/SNF complex to the promoter of TCF7 to regulate its expression, leading to activation of Wnt signaling. lncTCF7-mediated Wnt signaling primes liver cancer stem cell self-renewal and tumor propagation [Yoan et al. found that over-expression of lncRNA CTD903 inhibited invasion and migration of colorectal cancer cells by repressing Wnt/β-catenin signaling and predicts favorable prognosis . LncTCF7pagation .In addition to lncRNAs, microRNAs have important roles in TGFβ and/or WNT signaling. Yu et al. found that microRNA-21 induces stemness by down-regulating TGF-β receptor 2 (TGFβR2) in colon cancer cells . Tan et In another study, salvianolic acid B  treatment induced the inactivation of the Wnt/β-catenin pathway, with an increase in phosphorylated-β-catenin and Wnt inhibitory factor 1. It was found that miR-17-5p was reduced in vivo and in vitro after Sal B treatment. As confirmed by luciferase activity assays, WIF1 was a direct target of miR-17-5p. Importantly, the suppression of HSCs induced by Sal B was almost completely inhibited by miR-17-5p mimetics. Therefore, miR-17-5p activates Wnt/β-catenin pathway to result in HSC activation through inhibiting WIF1 expression .Many studies have provided evidence for cross-talk between fibrosis development and miRNA deregulation, via the TGFβ and WNT signaling pathways Fig. . Some ofFor example, researchers found that TGF-β1 and miR-21 expression were up-regulated in the border zone of mouse heart after myocardial infarction, whereas TGF-β receptor type III was down-regulated. TGFβRIII is a negative regulator of the TGF-β pathway. Over-expression of miR-21 attenuated TGFβRIII expression in cardiac fibroblasts, thereby potentially contributing to excessive ECM production via the TGF-β pathway . HoweverSeo et al. showed that miR-384-5p was a key mediator in the formation of a transactivation circuit between the TGF-β and WNT signaling pathways in cardiac fibrosis. This function might be related to the modulation of different receptors, such as Fzd1, Fzd2, TGFβR1, and LRP6. The expression of miR-384-5p was significantly decreased in CFs at 3 and 7 days after ischemia/reperfusion (I/R) injury, and 24 h after TGF-β treatment. Moreover, the over-expression of miR-384-5p significantly attenuated cardiac fibrosis and decreased the fibrotic area in the rat I/R injury model. These findings suggested that miR-384-5p might be able to control cardiac fibrosis . A recenThe relentless progression of fibrosis is well known to be a pathological finding in many cardiac conditions. The mechanisms responsible for this process are rather complex, and involve multiple pathways. Therefore, a better understanding of the functional characteristics and molecular profiles of these fibrotic processes could provide solutions for the prevention and treatment of fibrotic lesions in the heart. Accumulating evidence points to the cross-talk between the TGF-β and WNT signaling pathways in the pathogenesis of cardiac fibrosis. Although the cell biology of the TGF-β and WNT pathways has been well-described in cellular development and in the pathophysiology of many diseases, the mechanisms of these pro-fibrotic pathways in cardiac pathologies is less well-understood. As discussed in this review, canonical WNT signaling and TGF-β signaling can combine together to regulate fibrotic processes in the heart, and is likely to play a key role in switching on the genetic machinery for the pro-fibrotic changes. ncRNAs have increasingly been recognized to play possible roles in strategies for combating CVDs, as described above. Recent studies in the ncRNA field that are described in this review, also indicate the important function of ncRNAs in the regulation of cell signaling pathways, especially TGFB and WNT signaling. Information gathered from these experiments, and identification of the signaling pathways of the ncRNAs involved with cardiac fibrosis, may lead to a new target for treatment strategies for cardiac fibrosis. Additional research is needed to identify the exact details of the mechanism by which the ncRNA network affects cardiac fibrosis through TGFβ/WNT signaling. Moreover, the possible clinical importance of these TGFβ/WNT related ncRNAs, such as the use of microRNAs as therapeutic tools, and circRNAs as diagnostic/prognostic biomarkers for cardiac fibrosis should be examined in additional animal and clinical trials.


Unstable angina (UA) is a form of the acute coronary syndrome (ACS) that affects more than a third of the population before age 70. Due to the limitations of diagnostic tests, appropriate identification of UA is difficult. In this study, we proceeded to investigate metabolite profiling in UA patients compared with controls to determine potential candidate biomarkers. Ninety-four plasma samples from UA and 32 samples from controls were analyzed based on 1H NMR spectroscopy. The raw data were processed, analyzed, and subjected to partial least squares-discrimination analysis (PLS-DA), a supervised classification method with a good separation of control and UA patients was observed. The most important variables (VIP) ≥1 were selected and submitted to MetaboAnalyst pathway enrichment to identify the most important ones. We identified 17 disturbed metabolites in UA patients in comparison with the controls. These metabolites are involved in various biochemical pathways such as steroid hormone biosynthesis, aminoacyl-tRNA biosynthesis, and lysine degradation. Some of the metabolites were deoxycorticosterone, 17-hydroxyprogesterone, androstenedione, androstanedione, etiocholanolone, estradiol, 2-hydroxyestradiol, 2-hydroxyestrone, 2-methoxyestradiol, and 2-methoxyestrone. In order to determine test applicability in diagnosing UA, a diagnostic model was further created using the receiver operator characteristic (ROC) curve. The areas under the curve (AUC), sensitivity, specificity, and precision were 0.87, 90%, 65%, and 91%, respectively, for diagnosing of UA.These metabolites could not only be useful for the diagnosis of UA patients but also provide more information for further deciphering of the biological processes of UA.  Acute coronary syndrome (ACS) is a type of coronary artery disease (CAD) that refers to a range of conditions compatible with acute myocardial ischemia and/or infarction due to a sudden reduction in coronary blood flow . ACS is 1H NMR), which has functions for analysis of urine and plasma specimens. Some of the benefits of NMR include no need for degradation and chemical manipulation of specimens and also providing accurate information from the molecular concentrations and structures of metabolites , Left Circumflex Artery (LCX), and Right Coronary Artery (RCA). From the patients with UA symptoms who were a candidate for coronary artery bypass grafting (CABG) and percutaneous coronary intervention (PCI), we selected 94 UA patients based on having an obstruction in any of the coronary arteries, and also 32 controls that did not have any obstruction in their coronary arteries. The demographic data for the patients with UA and the controls are shown in Ethics, consent, and permissionsDiagnosis criteria of UA refer to the ‘‘2014 AHA/ACC guideline for the management of patients with Non–ST-Elevation Acute Coronary Syndromes’’. All stages were carried out in accordance with the Helsinki Declaration. The study was ethically approved by the ethics committee of the Zanjan University of Medical Science . Informed consent was taken from all patients before their inclusion in the study.Inclusion, exclusion, and rejection criteriaAll selected UA and the controls were diagnosed by physical examination, cardiac biomarkers, and confirmed by coronary angiography. Patients with obstruction over 75% in one of the three main coronary arteries  were included in the UA group. Also, patients who were accepted as UA patients but in angiography did not have any obstruction in coronary arteries were included in the control group. The exclusion criteria include a history of heart, liver, or metabolic disease, diabetes, rheumatism, cancer, hematopoietic system, pulmonary embolism, autoimmune disorders, severe infectious diseases, trauma, and a recent surgical procedure. Also, patient samples whose files were not available or lacked clinical information were excluded from the study. Sample collection, preparation, and NMR spectroscopy°C until NMR analysis. The 1H NMR data were acquired at room temperature on a Bruker 400 NMR spectrometer using Carr–Purcell–Meiboom–Gill (CPMG) pulse program  was applied as the internal reference in NMR tubes.Five-milliliter blood samples were taken from patients with UA symptoms and placed in tubes containing EDTA as an anticoagulant and immediately centrifuged  at 3500 rpm for 10 min to separate plasma. The plasma samples were stored at -80  program . In briePre-processing and Multivariate statistical analysis of 1H NMR spectra1H NMR spectrum from plasma was segmented into equal widths (0.003 ppm), corresponding to regions 0–9 ppm. 1H NMR spectra of all samples. Then the spectral data were mean-centered and scaled according to the Pareto scaling method (All NMR data in the FID time domain were imported into the MestReNova software package (version 6.0.2-5475) for data processing. The FID data were subjected to Fourier transform to obtain the spectra in the frequency domain. Then data were phased and baseline-corrected and exported as an ASCII file and imported into MATLAB  for further analysis. To eliminate water resonance, the spectral regions from 4.7 to 5 ppm were removed. In the next step, each g method , 29. A home-written program in MATLAB was used for multivariate statistical analysis. After pre-processing of data, principal component analysis (PCA) was applied to data as an unsupervised classification method. Since the separation of groups was not good (data not shown), PLS-DA as a supervised classification method was applied. The corresponding loading plot from PLS-DA was obtained, and the important variables were selected according to VIP≥1 . The proximity of patient and control profiles can be a good reason for some patients to overlap in the PCA analysis, which probably indicates that the metabolic profile of these patients is close to the metabolic profile of the controls. The loading plot is shown in Identification of metabolites and pathwaysP-values less than or equal to 0.05  was used to obtain metabolites based on the chemical shifts of class separation . Selecte to 0.05 .Clinical characteristics and demographic informationPatients were selected based on UA symptoms and lack of cardiac biomarkers and coronary angiography, a golden standard method for detecting atherosclerotic plaques verified the percentage of stenosis in each of LAD, LCX, and RCA. Obstruction over 75% was considered as significant, and patients with at least one blockage were enrolled in the UA group. Patients without any significant obstruction were included in the control group. For patients with UA and control, a data collection form was completed that included clinical characterizations and demographic information of each patient and control. In the next stage, the informed consent form was completed for patients. In our study, NMR spectrometry was carried out for the 204 plasma samples of UA patients and 56 from controls. Some patients in case and control groups were rejected from our study because of incomplete information and having special diseases. Also, diabetic patients in cases and controls were rejected from the study. Therefore, we removed their NMR information from the study. Hence, 94 cases and 32 control samples remained in the study. The detailed demographics and clinical data of the study’s subjects are indicated in Metabolite identificationP-value less than or about 0.05. We applied multivariate analysis to the obtained raw data from NMR spectroscopy to find best chemical shifts. The information about all analysis presented in -arginine, L-methionine, L-tryptophan, L-tyrosine, aminoadipic acid, N6-acetyl-L-lysine, L-pipecolic acid. 10 metabolites were altered in the steroid hormone biosynthesis pathway included deoxycorticosterone, 17-hydroxyprogesterone, androstenedione, androstanedione, etiocholanolone, estradiol, 2-hydroxyestradiol, 2-hydroxyestrone, 2-methoxyestradiol, 2-methoxyestrone. 4 metabolites were altered in aminoacyl-tRNA biosynthesis pathway included L-arginine, L-methionine, L-tryptophan, L-tyrosine. 3 metabolites were altered in the lysine degradation pathway included aminoadipic acid, N6-acetyl-L-lysine, and L-pipecolic acid. Also, two metabolites L-tyrosine and L-tryptophan were altered in another biochemical pathway called phenylalanine, tyrosine and tryptophan biosynthesis pathway.The important altered biochemical pathways were steroid hormone biosynthesis, aminoacyl-tRNA biosynthesis, lysine degradation, phenylalanine, tyrosine, and tryptophan biosynthesis. The most important metabolites associated with the most important biochemical pathways were deoxycorticosterone, 17-hydroxyprogesterone, androstenedione, androstanedione, etiocholanolone, estradiol, 2-hydroxyestradiol, 2-hydroxyestrone, 2-methoxyestradiol, 2-methoxyestrone, LAmong 17 selected metabolites, 12 metabolites had decreased levels, and 5 metabolites had increased levels in UA patients in comparison to the control group . -arginine, L-tryptophan, L-tyrosine, aminoadipic acid, N6-acetyl-L-lysine, and L-pipecolic acid. The significant altered biochemical pathways are shown in As shown in P-values less than or equal to 0.05. The significant altered metabolic pathways are shown in To validate the PLS-DA model and test and also its applicability in diagnosing UA, the ROC curve analysis was carried out to determine the clinical efficacy of these potential biomarkers. Accordingly, the sensitivity and specificity were determined for the test. The areas under the curve (AUC) for UA were 0.99. The sensitivity, specificity, and precision of the test were 0.87, 90%, 65%, and 91%, respectively, for diagnosing UA .1H NMR metabolomics approach was applied to investigate the novel candidate metabolites in UA patients. We identified some of the disturbed important metabolic pathways in UA patients, which include steroid hormone biosynthesis, aminoacyl-tRNA biosynthesis, lysine degradation, and phenylalanine, tyrosine, and tryptophan biosynthesis pathway. Because UA can lead to MI, it is important that the disease is diagnosed as soon as symptoms appear, and urgent proceedings are taken to prevent MI. The first altered pathway in our study was steroid hormone biosynthesis. The affected metabolites in this pathway were in the group of mineralocorticoid and sex hormones. We identified 10 metabolites in the pathway of steroid hormone biosynthesis including one metabolite from mineralocorticoid group, a class of corticosteroids, and 9 metabolites from the sex hormone group. In mineralocorticoid group, deoxycorticosterone and in sex hormone group 17-hydroxyprogesterone, androstenedione, androstanedione, etiocholanolone, estradiol, 2-hydroxyestradiol, 2-hydroxyestrone, 2-methoxyestradiol, and 2-methoxyestrone were detected compared to the controls. Mineralocorticoids are produced in the adrenal cortex and affect electrolyte and fluid balance, such as salt and water. Deoxycorticosterone is a precursor to aldosterone, which is the primary mineralocorticoid. Corticosterone, the main glucocorticoid, is produced from deoxycorticosterone involved in the regulation of energy, immune reactions, and stress responses. Glucocorticoids are steroid hormones that have inflammatory and immunosuppressive effects on a wide variety of cells. One of the effects of glucocorticoids is to reduce the expression of pro-inflammatory genes . TherefoAldosterone binds to mineralocorticoid receptors (MR) and regulates gene expression involved in sodium retention, potassium secretion, and water reabsorption, all of these actions may result in increased blood pressure. Moreover, MR is expressed in a variety of other tissues, and its activation could lead to tissue injury. Indeed, it has been shown that MR activation in the cardiovascular system promotes hypertension, fibrosis, and inflammation. Confirming this issue, the use of MR antagonists is helpful for patients with heart failure (HF) and prevents mortality and morbidity . In addition, an increasing number of clinical and experimental evidence suggests that MR is involved in a wide range of diseases, especially CVDs. MR activation is involved under different pathophysiologic conditions of the cardiovascular system, such as high blood pressure, HF, and MI . SeveralThe other metabolite in the pathway of steroid hormone biosynthesis were sex hormones. Some of the studies mentioned sex steroids have immunomodulating actions, but their roles in inflammation are complex. Understanding the interplay of atherosclerosis and sex steroid hormones and their receptors on the vessel wall has great importance for clinical practice. Atherosclerosis is caused by a chronic inflammatory condition in the vessel wall, which leads to vasoconstriction or obstruction and is associated with vascular dysfunction . Other i-arginine, L-methionine, L-tryptophan, and L-tyrosine. Aminoacyl-tRNA synthetases include an old family of enzymes that harbor all cells and exist in three major kingdoms of life. Aminoacyl-tRNA synthetases are necessary and ubiquitous ‘house-keeping’ enzymes responsible for charging amino acids to their cognate tRNAs and giving the substrates to synthesize proteins. They perform the esterification reactions that connect amino acids with their tRNAs bearing the correct anticodon to protect the perfect transfer of information directed by the genetic code. Generally, the aminoacylation reaction includes a two-step process: first activation of amino acids by ATP and creating an intermediate aminoacyl adenylate, and then transfer to the 3′-end of tRNA to form the aminoacyl-tRNA end-product. Recent studies have shown several roles for aminoacyl-tRNA synthetases in diseases and their application as pharmacological targets and therapeutic reagents. In addition to the canonical functions of aminoacyl-tRNA synthetases, including aminoacylation and editing, they have the noncanonical activities that are unrelated to aminoacylation, consisting of translation control, transcription regulation, signal transduction, immune cell migration, endothelial cell detachment, stimulation of endothelial cell migration, angiogenesis, inflammation, and tumorigenesis (-arginine, L-tryptophan, and L-tyrosine decreased in UA patients, but L-methionine increased.One of the affected pathways in UA patients was the aminoacyl-tRNA biosynthesis pathway, which consists of four metabolites Ligenesis , 42. Chaigenesis . In thisin vitro data also indicate that L-arginine may have antiaggregatory, anticoagulant, and profibrinolytic effects (L-arginine is the only substrate of NO production that affects the cardiovascular system. Many studies have clearly shown a beneficial effect of L-arginine on endothelium hypofunction and thus reduced NO synthesis. Additionally, experiments on animals have been performed and  effects . -Argini effects . Product effects . In our  effects . Also, i effects . High do effects . It is k effects . L-tryptophan is an essential amino acid and a major component of protein synthesis in humans and animals. Research has displayed that the -kynurenine pathway has a key role related to the pathological regulation in both innate and adaptive immune systems . The actsaccharopine. Lysine catabolism occurs through one of several pathways, the most common of which is the saccharopine pathway. Aminoadipic acid may be used as a precursor to the downstream enzyme for tryptophan metabolism. It has also been shown that aminoadipic acid inhibits the production of kynurenic acid (Aminoadipic acid is an intermediate metabolite in the degradation of lysine and nic acid . As a re It is known that aminoadipic acid, as an atherogen, is produced by oxidation of lysine in proteins into the atherosclerotic plaques at high levels . The rolWe conducted the first study on the metabolome profile of UA patients in the Iranian population based on NMR-based spectroscopy. The patients with diabetes were excluded from our research in order to eliminate interferences. In our study, some of the altered pathways and metabolites in the UA patients were reported for the first time. We identified two new important disturbed pathways including steroid hormone biosynthesis, phenylalanine, tyrosine, and tryptophan biosynthesis in UA patients. Also, we have reported the aminoacyl-tRNA biosynthesis pathway and lysine degradation that agree with a previous study about UA patients . The ide


Cellular responses to environmental changes are encoded in the complex temporal patterns of signaling proteins. However, quantifying the accumulation of information over time to direct cellular decision-making remains an unsolved challenge. This is, in part, due to the combinatorial explosion of possible configurations that need to be evaluated for information in time-course measurements. Here, we develop a quantitative framework, based on inferred trajectory probabilities, to calculate the mutual information encoded in signaling dynamics while accounting for cell-cell variability. We use it to understand NFκB transcriptional dynamics in response to different immune threats, and reveal that some threats are distinguished faster than others. Our analyses also suggest specific temporal phases during which information distinguishing threats becomes available to immune response genes; one specific phase could be mapped to the functionality of the IκBα negative feedback circuit. The framework is generally applicable to single-cell time series measurements, and enables understanding how temporal regulatory codes transmit information over time. Understanding how cells discriminate between stimuli is an ongoing challenge. Here, the authors propose a mathematical framework for inferring the mutual information encoded in temporal signaling dynamics and use it to study how information is transmitted over time in response to different stimuli in NFκB, MAPK and p53 signaling pathways. These signaling pathways respond to perturbations in the presence of nutrients, pathogens, cytokines, growth factors, toxins, or radiation that may function as stimuli or signaling inputs. Prior work has established that the temporal patterns (dynamics) of signaling molecular abundance within these pathways play a crucial role in determining the cellular response specific to each stimulus8. Moreover, signaling typically occurs over a timescale of hours, as it involves de novo protein synthesis and degradation. Regulatory circuits that control cellular core functions must interpret signaling dynamics when information about the identity and dose of the stimulus becomes available. Therefore, quantifying the temporal accumulation of information for stimuli-discrimination is essential to revealing how cells adapt to environmental changes and make cell fate decisions in real time.Cells have the capacity to sense, respond, and adapt to their environment through biochemical signaling pathways10 that may diminish its reliability as different individual cells of the same cell type receiving the same stimulus respond differently. To quantify information transmitted through noisy biochemical pathways, information-theoretic approaches have been adapted to analyze single-cell measurements of signaling molecules17. The mutual information (MI) between the stimulus conditions and the single-cell signaling responses is an estimate on the amount of information about the stimulus identity and dose that are encoded in the signaling molecular activity18. However, it remains an outstanding challenge to quantify the MI encoded in the dynamics of signaling and further to uncover how information accumulates over time, as cells react to environmental changes in real time with the information available at a certain timepoint22. That is because the possible configurations of response trajectories increase combinatorially with the number of timepoints, and this combinatorial explosion hinders an exact estimation on trajectory probabilities and MI.Signaling through biochemical pathways is affected by the stochastic nature of molecular interactions26, none estimates the MI from an entire trajectory. One recently developed approach27 allows estimates for several timepoints. However, it does not extract the information encoded in the dynamical patterns of responses, because it is not sensitive to the sequence of timepoints and does not distinguish between differentially permuted timepoints. Another method28 analyzed the MI in dynamic signals using a machine learning decoder. However, such an analysis only provides a lower bound as it is unclear how much information might be lost in training the classifier. For example, classifiers employing linear principal components29 may be inadequate to discriminate oscillatory and non-oscillatory trajectories.Though several information measures consider two consecutive timepoints30 or a hidden Markov model32. We then present a general workflow to identify the appropriate model and the optimal number of parameters for calculating the trajectory probability. This forms the basis for the dynamical mutual information (dMI), a measure we propose to quantify MI in the trajectory space.Here, we address the complexity challenge of quantifying information accumulation from the trajectories with combinatorially increasing configurations. We employ a modeling approach to learn the ensemble of complex response trajectories using a time-inhomogeneous Markov model33. For our data of NFκB signaling in macrophages, we show that a hidden Markov model is superior to a Markov model and gives a posterior trajectory probability for each response trajectory. Then, the dMI framework reveals the capacity of cells to discriminate different stimulus conditions, and is capable of quantifying information accumulation with high temporal resolution unlike the previous methods. Specifically, the present method could reveal the timing of recognizing certain immune threats, and identify molecular mechanisms for specific temporal phases of information gain.We demonstrate the workflow by applying it to the signaling dynamics of the pathogen-response transcription factor NFκB, which shows complex oscillatory and non-oscillatory trajectories and determines the expression of immune response genes27. For example, M different stimulus conditions. The rate or temporal profile with which cells acquire the information to discriminate specific stimulus conditions remains largely unexplored.Cellular signaling molecules often encode information about the biological condition via the temporal trajectories, or dynamics, of their activities Fig. , upper. 18 considered the data of single-cell signaling activity at a single timepoint as a distribution across cells (timepoint method), and calculated the MI among the distributions under various stimulus conditions -divergence) between the measured trajectory ensemble under each stimulus condition and the simulated trajectory ensemble from the trained model (see the next section and Methods). Overfitting is guarded against by identifying the number of states that would result in misclassification of the heterogeneity within each condition.p(yn1:), where yn1: denotes a trajectory from timepoint 1 to n, can be obtained32 by sampling from the inferred transition matrix and emission matrix. Then, the trajectory entropy for each single trajectory is given by37:When an appropriate model has been generated, the next step is to infer the probability of each trajectory and its corresponding trajectory entropy. Specifically, given a trained Markov or hidden Markov model under each stimulus condition, every trajectory’s probability 32, such as a colloidal particle in a viscous fluid. Here, the trajectory entropy is calculated by inferring a stochastic model, e.g., a hidden Markov model, from the data of biochemical signaling responses.Note that the trajectory entropy is for a single trajectory, rather than the average on the trajectory ensemble. The trajectory entropy was originally formulated for mesoscopic non-equilibrium systemsM conditions of stimuli set (S) and the signaling responses set (Rn1:) is27 by revealing the information encoded in dynamical patterns.As detailed in Methods and Supplementary Note M stimulus conditions M stimulus conditions cumulatively up to that timepoint. A computational optimization over the distribution of stimulus conditions can be different from the genuine optimization conducted by the cell, because cells might not weight the distribution of stimuli as in the computation. Thus, n.Considering the probability distribution of the M distinct conditions were employed, perfectly transmitted information would result in The proposed workflow estimates the maximum dMI, of which the value depends on the stimulus conditions under consideration. It approximates to the channel capacity of the signaling channel if an exhaustive number of perturbing conditions (stimuli) were employed experimentally. In practice, one can only sample a finite number of stimulus conditions in the continuous-concentration space, resulting in the maximum dMI that can be gleaned from the available datasets. In other words, if 7 which responds with diverse dynamics to different immune threats. We obtained a dataset of NFκB trajectories from macrophages exposed to the cytokine TNF and four different pathogen-associated molecular patterns, namely the bacterial cell wall components LPS and Pam3CSK, and the nucleic acids CpG and polyIC38. Responses to each were tracked for 12 h. Various concentrations were used for the stimuli with responses dependent on concentrations . The measures indicate that with a sufficient number of states the model can approximately reproduce the ensembles of single-cell NFκB trajectories. For example, the relative KL-divergence measuring the relative accuracy of the model reaches below 0.1 and the false k-nearest neighbor probability approaches 0.4, close to the optimal mixing probability 0.5. For the hidden Markov model, we explored how the numbers of hidden and emission states affect the training performance  have distinct responses in the first hour, where only TNF leads to a peak of activity, and give similar responses in an intermediate phase leading to a decrease in MI. Third, CpG and poly(I:C) are different only in the late phase Fig. . UndertaTo investigate the robustness of dMI calculations, we used the replicate data to replace one of the two in each pairwise conditions in Fig. 41 in the same conditions (cells and stimuli) measured at 1, 3, and 8 h. From the calculated correlation between the dMI values and the absolute difference of gene expression fold change between the pairwise stimuli in Fig. 19 that may avoid the co-activation of other factors involved in gene expression control.To explore how the information of the NFκB signaling can be decoded by the responsive genes, we analyzed the data of NFκB-responsive genes42, that operate at different timescales  in control and mutant cells deficient in IκBα-feedback (IκB-mutant). Both control and mutant cells showed a rapid increase of the dMI in the first hour, but then diverged during the second hour in which mutant cells showed a diminished increase of the dMI than control cells; after that, both cell types showed a slow but steady information gain for the duration of the 12-h timecourse , the dMI increases at around 1 h when the negative feedback produces an oscillatory pattern. For the perturbation on the sustained features (modifying the stimulus lifetime), the dMI increases after about 2 h, indicating the information gain derives from signaling duration and integral. The analysis supports the hypothesis in Fig. We further investigated the temporal phases of dMI accumulation by generating NFκB response data with a mathematical model of the NFκB signaling network formulated byWe have developed a quantitative framework to estimate the information accumulation encoded in the dynamics of biochemical signaling molecule. Specifically, we have used time-inhomogeneous Markov and hidden Markov models to learn such dynamics, which enabled the calculation of dMI to reveal the temporal profile of how information for distinguishing stimulus conditions becomes available. We demonstrated the workflow by applying it to NFκB signaling responses, where we found that some immune threats are recognized by cells more rapidly than others.The ideal measurement of signaling responses for information-theoretic analysis would involve the same set of cells responding to different inputs, such that the potential differences between cell populations can be avoided. In practice, this is not possible as the response to one stimulus will affect the cells to the second stimulus. Therefore, in order to compare signaling responses of naïve cells, we split the single population of cells into physically separated compartments stimulated with a single stimulus. It is possible that the physical separation causes the subpopulations to be distinct. This is mitigated if the stimulations are done at the same time in parallel on the same microscope run, with the microscope objective gathering the data from compartment to compartment for each timepoint. To address the scenario when experiments cannot be done in parallel, we have investigated replicates produced at different times  is consistent with how responsive gene expression is determinedThe Methods section briefly outlines the model training, the performance evaluation, and the calculation on the dMI. More descriptions of methods are given in l to lth column element in the count matrix t specifies the timepoint. The transition matrix is obtained by normalizing the count matrix by each column: Given an ensemble of the trajectories, we can extract a set of transition matrices as follows. We first binned the observed data points into discrete states. For every two consecutive timepoints, we counted the number of the data points with 48 was used to infer one transition matrix between hidden states, and one emission matrix between hidden states and emission states. It derives a maximum likelihood estimation on the parameters of the hidden Markov model given time series data. There are two numbers of states, i.e., of hidden states and emission states. In most analyses the ratio between the numbers of hidden states and emission states was fixed to 2:1 .The Baum–Welch algorithmThe KL-divergence at each timepoint is the relative entropy between the sampled trajectories and the true data distribution. The ratio of the KL-divergence and the entropy of the data distribution, termed as the “relative KL-divergence,” was calculated : E is the emission matrix, and T is the transition matrix for the hidden states xn. The emission and transition matrices were inferred by the Baum–Welch algorithm for the given trajectory ensemble. The trajectory probability for an observed time series is given by summing over the K hidden states: We employed the hidden Markov model to demonstrate the procedure. The forward algorithm of the hidden Markov model27 to estimate the conditional and unconditional trajectory entropy. Specifically, For the set of mi trajectories ith stimulus, where j is the index for a trajectory, the conditional trajectory entropy for the ith stimulus is estimated with the probability distribution of observing the trajectories27:Then, applying Eq.  led to tM stimuli:Given the probability of different stimulus The unconditional trajectory probabilities are obtained by weighting the conditional trajectory probabilities with the stimulus probability distribution:The total unconditional trajectory entropy is given by:27, the present framework quantifies the information transmission encoded in dynamics of the trajectory space. More details about the calculations are in The dMI is calculated by Eqs. , 5), an, an5), a38, WT and IκB-mutant mice were produced (https://github.com/Adewunmi91/MACKtrack). It resulted in the datasets used here.Using an mVenus-RelA endogenously-tagged mouse lineproduced , V.A. BoThe UCLA Institutional Animal Care and Use Committee approved the protocol for animal research per guidance from the American Veterinary Medical Association.Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary