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Abstract The immune system undergoes progressive functional remodeling from neonatal stages to old age. Therefore, understanding how aging shapes immune cell function is vital for precise treatment of patients at different life stages. Here, we constructed the first transcriptomic atlas of immune cells encompassing human lifespan, ranging from newborns to supercentenarians, and comprehensively examined gene expression signatures involving cell signaling, metabolism, differentiation, and functions in all cell types to investigate immune aging changes. By comparing immune cell composition among different age groups, HLA highly expressing NK cells and CD83 positive B cells were identified with high percentages exclusively in the teenager (Tg) group, whereas unknown_T cells were exclusively enriched in the supercentenarian (Sc) group. Notably, we found that the biological age (BA) of pediatric COVID-19 patients with multisystem inflammatory syndrome accelerated aging according to their chronological age (CA). Besides, we proved that inflammatory shift- myeloid abundance and signature correlate with the progression of complications in Kawasaki disease (KD). The shift- myeloid signature was also found to be associated with KD treatment resistance, and effective therapies improve treatment outcomes by reducing this signaling. Finally, based on those age-related immune cell compositions, we developed a novel BA prediction model PHARE ( https://xiazlab.org/phare/ ), which can apply to both scRNA-seq and bulk RNA-seq data. Using this model, we found patients with coronary artery disease (CAD) also exhibit accelerated aging compared to healthy individuals. Overall, our study revealed changes in immune cell proportions and function associated with aging, both in health and disease, and provided a novel tool for successfully capturing features that accelerate or delay aging.

Reproductive strategies of sexually dimorphic plants vary in response to the environment. Here, we ask whether the sexual systems of Fagopyrum species (i.e., selfing homostylous and out-crossing distylous) represent distinct adaptive strategies to increase reproductive success in changing alpine environments. To answer this question, we determined how spatial and temporal factors (e.g., elevation and peak flowering time) affect reproductive success (i.e., stigmatic pollen load) in nine wild Fagopyrum species (seven distylous and two homostylous) among 28 populations along an elevation gradient of 1299–3315 m in the Hengduan Mountains, southwestern China. We also observed pollinators and conducted hundreds of hand pollinations to investigate inter/intra-morph compatibility, self-compatibility and pollen limitation in four Fagopyrum species (two distylous and two homostylous). We found that Fagopyrum species at higher elevation generally had bigger flowers and more stigmatic pollen loads; late-flowering individuals had smaller flowers and lower pollen deposition. Stigmatic pollen deposition was more variable in distylous species than in homostylous species. Although seed set was not pollen-limited in all species, we found that fruit set was much lower in distylous species, which rely on frequent pollinator visits, than in homostylous species capable of autonomous self-pollination. Our findings that pollination success increases at high elevations and decreases during the flowering season suggest that distylous and homostylous species have spatially and temporally distinct reproductive strategies related to environment-dependent pollinator activity.

Abstract Background In the field of biology and medicine, the interpretability and accuracy are both important when designing predictive models. The interpretability of many machine learning models such as neural networks is still a challenge. Recently, many researchers utilized prior information such as biological pathways to develop neural networks-based methods, so as to provide some insights and interpretability for the models. However, the prior biological knowledge may be incomplete and there still exists some unknown information to be explored. Results We proposed a novel method, named PathExpSurv, to gain an insight into the black-box model of neural network for cancer survival analysis. We demonstrated that PathExpSurv could not only incorporate the known prior information into the model, but also explore the unknown possible expansion to the existing pathways. We performed downstream analyses based on the expanded pathways and successfully identified some key genes associated with the diseases and original pathways. Conclusions Our proposed PathExpSurv is a novel, effective and interpretable method for survival analysis. It has great utility and value in medical diagnosis and offers a promising framework for biological research.

Abstract Background The phagocytosis and homeostasis of microglia play an important role in promoting blood clearance and improving prognosis after subarachnoid hemorrhage (SAH). LC3-assocaited phagocytosis (LAP) contributes to the microglial phagocytosis and homeostasis via autophagy-related components. With RNA-seq sequencing, we found potential signal pathways and genes which were important for the LAP of microglia. Methods We used an in vitro model of oxyhemoglobin exposure as SAH model in the study. RNA-seq sequencing was performed to seek critical signal pathways and genes in regulating LAP. Bioparticles were used to access the phagocytic ability of microglia. Western blot (WB), immunoprecipitation, quantitative polymerase chain reaction (qPCR) and immunofluorescence were performed to detect the expression change of LAP-related components and investigate the potential mechanisms. Results In vitro SAH model, there were increased inflammation and decreased phagocytosis in microglia. At the same time, we found that the LAP of microglia was inhibited in all stages. RNA-seq sequencing revealed the importance of P38 MAPK signal pathway and DAPK1 in regulating microglial LAP. P38 was found to regulate the expression of DAPK1, and P38-DAPK1 axis was identified to regulate the LAP and homeostasis of microglia after SAH. Finally, we found that P38-DAPK1 axis regulated expression of BECN1, which indicated the potential mechanism of P38-DAPK1 axis regulating microglial LAP. Conclusion P38-DAPK1 axis regulated the LAP of microglia via BECN1, affecting the phagocytosis and homeostasis of microglia in vitro SAH model. Video Abstract

Abstract Background Aucubin (Au), an iridoid glycoside from natural plants, has antioxidative and anti-inflammatory bioactivities; however, its effects on a traumatic brain injury (TBI) model remain unknown. We explored the potential role of Au in an H2O2-induced oxidant damage in primary cortical neurons and weight-drop induced-TBI in a mouse model. Methods In vitro experiments, the various concentrations of Au (50 μg/ml, 100 μg/ml, or 200 μg/ml) were added in culture medium at 0 h and 6 h after neurons stimulated by H2O2 (100 μM). After exposed for 12 h, neurons were collected for western blot (WB), immunofluorescence, and M29,79-dichlorodihydrofluorescein diacetate (DCFH-DA) staining. In vivo experiments, Au (20 mg/kg or 40 mg/kg) was administrated intraperitoneally at 30 min, 12 h, 24 h, and 48 h after modeling. Brain water content, neurological deficits, and cognitive functions were measured at specific time, respectively. Cortical tissue around focal trauma was collected for WB, TdT-mediated dUTP Nick-End Labeling (TUNEL) staining, Nissl staining, quantitative real time polymerase chain reaction (q-PCR), immunofluorescence/immunohistochemistry, and enzyme linked immunosorbent assay (ELISA) at 72 h after TBI. RNA interference experiments were performed to determine the effects of nuclear factor erythroid-2 related factor 2 (Nrf2) on TBI mice with Au (40 mg/kg) treatment. Mice were intracerebroventricularly administrated with lentivirus at 72 h before TBI establishment. The cortex was obtained at 72 h after TBI and used for WB and q-PCR. Results Au enhanced the translocation of Nrf2 into the nucleus, activated antioxidant enzymes, suppressed excessive generation of reactive oxygen species (ROS), and reduced cell apoptosis both in vitro and vivo experiments. In the mice model of TBI, Au markedly attenuated brain edema, histological damages, and improved neurological and cognitive deficits. Au significantly suppressed high mobility group box 1 (HMGB1)-mediated aseptic inflammation. Nrf2 knockdown in TBI mice blunted the antioxidant and anti-inflammatory neuroprotective effects of the Au. Conclusions Taken together, our data suggest that Au provides a neuroprotective effect in TBI mice model by inhibiting oxidative stress and inflammatory responses; the mechanisms involve triggering Nrf2-induced antioxidant system.

Mounting evidence has suggested that modulating microglia polarization from pro-inflammatory M1 phenotype to anti-inflammatory M2 state might be a potential therapeutic approach in the treatment of subarachnoid hemorrhage (SAH) injury. Our previous study has indicated that sirtuin 1 (SIRT1) could ameliorate early brain injury (EBI) in SAH by reducing oxidative damage and neuroinflammation. However, the effects of SIRT1 on microglial polarization and the underlying molecular mechanisms after SAH have not been fully illustrated. In the present study, we first observed that EX527, a potent selective SIRT1 inhibitor, enhanced microglial M1 polarization and nod-like receptor pyrin domain-containing 3 (NLRP3) inflammasome activation in microglia after SAH. Administration of SRT1720, an agonist of SIRT1, significantly enhanced SIRT1 expression, improved functional recovery, and ameliorated brain edema and neuronal death after SAH. Moreover, SRT1720 modulated the microglia polarization shift from the M1 phenotype and skewed toward the M2 phenotype. Additionally, SRT1720 significantly decreased acetylation of forkhead box protein O1, inhibited the overproduction of reactive oxygen species (ROS) and suppressed NLRP3 inflammasome signaling. In contrast, EX527 abated the upregulation of SIRT1 and reversed the inhibitory effects of SRT1720 on ROS-NLRP3 inflammasome activation and EBI. Similarly, in vitro, SRT1720 suppressed inflammatory response, oxidative damage, and neuronal degeneration, and improved cell viability in neurons and microglia co-culture system. These effects were associated with the suppression of ROS-NLRP3 inflammasome and stimulation of SIRT1 signaling, which could be abated by EX527. Altogether, these findings indicate that SRT1720, an SIRT1 agonist, can ameliorate EBI after SAH by shifting the microglial phenotype toward M2 via modulation of ROS-mediated NLRP3 inflammasome signaling.

Abstract High‐throughput biological data has created an unprecedented opportunity for illuminating the mechanisms of tumor emergence and evolution. An important and challenging problem in deciphering cancers is to investigate the commonalities of driver genes and pathways and the associations between cancers. Aiming at this problem, a tool ComCovEx is developed to identify common cancer driver gene modules between two cancers by searching for the candidates in local signaling networks using an exclusivity‐coverage iteration strategy and outputting those with significant coverage and exclusivity for both cancers. The associations of the cancer pairs are further evaluated by Fisher's exact test. Being applied to 11 TCGA cancer datasets, ComCovEx identifies 13 significantly associated cancer pairs with plenty of biologically significant common gene modules. The novel results of cancer relationship and common gene modules reveal the relevant pathological basis of different cancer types and provide new clues to diagnosis and drug treatment in associated cancers.

Abstract Background Microglia are resident immune cells in the central nervous system and central to the innate immune system. Excessive activation of microglia after subarachnoid haemorrhage (SAH) contributes greatly to early brain injury, which is responsible for poor outcomes. Dehydroepiandrosterone (DHEA), a steroid hormone enriched in the brain, has recently been found to regulate microglial activation. The purpose of this study was to address the role of DHEA in SAH. Methods We used in vivo models of endovascular perforation and in vitro models of haemoglobin exposure to illustrate the effects of DHEA on microglia in SAH. Results In experimental SAH mice, exogenous DHEA administration increased DHEA levels in the brain and modulated microglial activation. Ameliorated neuronal damage and improved neurological outcomes were also observed in the SAH mice pretreated with DHEA, suggesting neuronal protective effects of DHEA. In cultured microglia, DHEA elevated the mRNA and protein levels of Jumonji d3 (JMJD3, histone 3 demethylase) after haemoglobin exposure, downregulated the H3K27me3 level, and inhibited the transcription of proinflammatory genes. The devastating proinflammatory microglia-mediated effects on primary neurons were also attenuated by DHEA; however, specific inhibition of JMJD3 abolished the protective effects of DHEA. We next verified that DHEA-induced JMJD3 expression, at least in part, through the tropomyosin-related kinase A (TrkA)/Akt signalling pathway. Conclusions DHEA has a neuroprotective effect after SAH. Moreover, DHEA increases microglial JMJD3 expression to regulate proinflammatory/anti-inflammatory microglial activation after haemoglobin exposure, thereby suppressing inflammation.

Despite the improvements in prognostication of the revised International Prognostic Scoring System (IPSS-R) in myelodysplastic syndrome (MDS), there remain a portion of patients with lower risk (low/intermediate risk, LR) but poor prognostics. This study aimed to evaluate the relative contribution of mutational status when added to the IPSS-R, for estimating overall survival (OS) and progression-free survival (PFS) in patients with LR-MDS. We retrospectively analyzed clinical and laboratory variables of 328 patients diagnosed with MDS according to the FAB criteria. Twenty-nine-gene NGS assay was applied to bone marrow samples obtained at diagnosis. 233 (71.04%) patients were classified as LR-MDS. Univariate analysis showed association between inferior outcome (OS and PFS) and presence of JAK2 (p = 0.0177, p = 0.0002), RUNX1 (p = 0.0250, p = 0.0387), and U2AF1 (p = 0.0227, p = 0.7995) mutations. Multivariable survival analysis revealed JAK2 (p < 0.0001) and RUNX1 (p = 0.0215) mutations were independently prognostic for PFS in LR-MDS. Interestingly, bone marrow blast >1.5% could further predict disease progression of patients with LR-MDS (HR 8.06, 95%CI 2.95–22.04, p < 0.0001). Incorporation of JAK2, RUNX1 mutation and bone marrow blast in the IPSS-R can improve risk stratification in patients with LR-MDS. In summary, our result provided new risk factors for LR-MDS prognostics to identify candidates for early therapeutic intervention.

Blockchain technology gains more and more attention in the past decades and has been applied in many areas. The main bottleneck for the development and application of blockchain is its limited scalability. Blockchain with directed acyclic graph structure (BlockDAG) is proposed in order to alleviate the scalability problem. One of the key technical problems in BlockDAG is the identification of honest blocks which are very important for establishing a stable and invulnerable total order of all the blocks. The stability and security of BlockDAG largely depends on the precision of honest block identification. This paper presents a novel universal framework based on graph theory, called MaxCord, for identifying the honest blocks in BlockDAG. By introducing the concept of discord, the honest block identification is modelled as a generalized maximum independent set problem. Several algorithms are developed, including exact, greedy and iterative filtering algorithms. The extensive comparisons between proposed algorithms and the existing method were conducted on the simulated BlockDAG data to show that the proposed iterative filtering algorithm identifies the honest blocks both efficiently and effectively. The proposed MaxCord framework and algorithms can set the solid foundation for the BlockDAG technology.

Abstract Background Peroxiredoxin (Prx) protein family have been reported as important damage-associated molecular patterns (DAMPs) in ischemic stroke. Since peroxiredoxin 2 (Prx2) is the third most abundant protein in erythrocytes and the second most protein in the cerebrospinal fluid in traumatic brain injury and subarachnoid hemorrhage (SAH) patients, we assessed the role of extracellular Prx2 in the context of SAH. Methods We introduced a co-culture system of primary neurons and microglia. Prx2 was added to culture medium with oxyhemoglobin (OxyHb) to mimic SAH in vitro. Neuronal cell viability was assessed by lactate dehydrogenase (LDH) assay, and neuronal apoptosis was determined by TUNEL staining. Inflammatory factors in culture medium were measured by ELISA, and their mRNA levels in microglia were determined by qPCR. Toll-like receptor 4 knockout (TLR4-KO) mice were used to provide TLR4-KO microglia; ST-2825 was used to inhibit MyD88, and pyrrolidine dithiocarbamate (PDTC) was used to inhibit NF-κB. Related cellular signals were analyzed by Western blot. Furthermore, we detected the level of Prx2 in aneurysmal SAH patients’ cerebrospinal fluids (CSF) and compared its relationship with Hunt-Hess grades. Results Prx2 interacted with TLR4 on microglia after SAH and then activated microglia through TLR4/MyD88/NF-κB signaling pathway. Pro-inflammatory factors were expressed and released, eventually caused neuronal apoptosis. The levels of Prx2 in SAH patients positively correlated with Hunt-Hess grades. Conclusions Extracellular Prx2 in CSF after SAH is a DAMP which resulted in microglial activation via TLR4/MyD88/NF-κB pathway and then neuronal apoptosis. Prx2 in patients’ CSF may be a potential indicator of brain injury and prognosis.

Inflammatory injury and neuronal apoptosis participate in the period of early brain injury (EBI) after subarachnoid hemorrhage (SAH). Suppression of inflammation has recently been shown to reduce neuronal death and neurobehavioral dysfunction post SAH. Biochanin A (BCA), a natural bioactive isoflavonoid, has been confirmed to emerge the anti-inflammatory pharmacological function. This original study was aimed at evaluating and identifying the neuroprotective role of BCA and the underlying molecular mechanism in an experimental Sprague-Dawley rat SAH model. Neurobehavioral function was evaluated via the modified water maze test and modified Garcia neurologic score system. Thus, we confirmed that BCA markedly decreased the activated level of TLRs/TIRAP/MyD88/NF-κB pathway and the production of cytokines. BCA also significantly ameliorated neuronal apoptosis which correlated with the improvement of neurobehavioral dysfunction post SAH. These results indicated that BCA may provide neuroprotection against EBI through the inhibition of inflammatory injury and neuronal apoptosis partially via the TLRs/TIRAP/MyD88/NF-κB signal pathway.

Background: Accumulating evidence suggests that neuroinflammation plays a critical role in early brain injury after subarachnoid hemorrhage (SAH). Pannexin-1 channels, as a member of gap junction proteins located on the plasma membrane, releases ATP, ions, second messengers, neurotransmitters, and molecules up to 1 kD into the extracellular space, when activated. Previous studies identified that the opening of Pannexin-1 channels is essential for cellular migration, apoptosis and especially inflammation, but its effects on inflammatory response in SAH model have not been explored yet.Methods: Adult male Sprague-Dawley rats were divided into six groups: sham group (n = 20), SAH group (n = 20), SAH + LV-Scramble-ShRNA group (n = 20), SAH + LV-ShRNA-Panx1 group (n = 20), SAH + LV-NC group (n = 20), and SAH + LV-Panx1-EGFP group (n = 20). The rat SAH model was induced by injection of 0.3 ml fresh arterial, non-heparinized blood into the prechiasmatic cistern in 20 s. In SAH + LV-ShRNA-Panx1 group and SAH + LV-Panx1-EGFP group, lentivirus was administered via intracerebroventricular injection (i.c.v.) at 72 h before the induction of SAH. The Quantitative real-time polymerase chain reaction, electrophoretic mobility shift assay, enzyme-linked immunosorbent assay, immunofluorescence staining, and western blotting were performed to explore the potential interactive mechanism between Pannexin-1 channels and TLR2/TLR4/NF-κB-mediated signaling pathway. Cognitive and memory changes were investigated by the Morris water maze test.Results: Administration with LV-ShRNA-Panx1 markedly decreased the expression levels of TLR2/4/NF-κB pathway-related agents in the brain cortex and significantly ameliorated neurological cognitive and memory deficits in this SAH model. On the contrary, administration of LV-Panx1-EGFP elevated the expressions of TLR2/4/NF-κB pathway-related agents, which correlated with augmented neuronal apoptosis.Conclusion: Pannexin-1 channels may contribute to inflammatory response and neurobehavioral dysfunction through the TLR2/TLR4/NF-κB-mediated pathway signaling after SAH, suggesting a potential role of Pannexin-1 channels could be a potential therapeutic target for the treatment of SAH.

Cysteine S-sulfenylation is an important post-translational modification (PTM) in proteins, and provides redox regulation of protein functions. Bioinformatics and structural analyses indicated that S-sulfenylation could impact many biological and functional categories and had distinct structural features. However, major limitations for identifying cysteine S-sulfenylation were expensive and low-throughout. In view of this situation, the establishment of a useful computational method and the development of an efficient predictor are highly desired. In this study, a predictor iSulf-Cys which incorporated 14 kinds of physicochemical properties of amino acids was proposed. With the 10-fold cross-validation, the value of area under the curve (AUC) was 0.7155 ± 0.0085, MCC 0.3122 ± 0.0144 on the training dataset for 20 times. iSulf-Cys also showed satisfying performance in the independent testing dataset with AUC 0.7343 and MCC 0.3315. Features which were constructed from physicochemical properties and position were carefully analyzed. Meanwhile, a user-friendly web-server for iSulf-Cys is accessible at http://app.aporc.org/iSulf-Cys/.

The Minimum Error Correction (MEC) is an important model for haplotype reconstruction from SNP fragments. However, this model is effective only when the error rate of SNP fragments is low. In this paper, we propose a new computational model called Minimum Conflict Individual Haplotyping (MCIH) as an extension to MEC. In contrast to the conventional approaches, the new model employs SNP fragment information and also related genotype information, thereby a high accurate inference can be expected. We first prove the MCIH problem to be NP-hard. To evaluate the practicality of the new model we design an exact algorithm (a dynamic programming procedure) to implement MCIH on a special data structure. The numerical experience indicates that it is fairly effective to use MCIH at the cost of related genotype information, especially in the case of SNP fragments with a high error rate. Moreover, we present a feed-forward neural network algorithm to solve MCIH for general data structure and large size instances. Numerical results on real biological data and simulation data show that the algorithm works well and MCIH is a potential alternative in individual haplotyping.

Abnormal immunophenotypes of hematopoietic cells can be detected by flow cytometry (FCM) to assist the diagnosis of myelodysplastic syndromes (MDS). We previously established a FCM scoring system for the diagnosis of low-grade MDS. In this study, additional valuable antigens were involved in an updated FCM scoring system (u-FCMSS) for all MDS subtypes. The u-FCMSS showed better sensitivity and specificity (89.4% and 96.5%) in distinguishing MDS from non-clonal cytopenia diseases. Validation analysis of u-FCMSS exhibited comparable sensitivity and specificity (86.7% and 93.3%) and high agreement rate (88.9%) of FCM diagnosis with morphological diagnosis at optimal cut-off (score 3). The distribution of FCM scores in different disease stages was also analyzed. The results suggested that early scoring from abnormal expression of mature myeloid/lymphoid antigens and advanced scoring from abnormal expression of stem/progenitor antigens expression constituted the majority of FCM scores of low-grade and high-grade MDS, respectively. High early scoring was generally accompanied by low IPSS-R score and superior survival, whereas high advanced scoring was accompanied by high IPSS-R score and inferior survival. In addition, the low-risk MDS patients with high early scoring and low advanced scoring were revealed as candidates for immunosuppressive therapy, whereas those with high advanced scoring and low early scoring may be more suitable for decitabine treatment. In conclusion, the u-FCMSS is a useful tool for diagnosis, prognosis and treatment selection in MDS. Differences in classes of antigens expressed and in distribution of FCM scores may reflect distinctive stage characteristics of MDS during disease progression.

Nitrotyrosine is one of the post-translational modifications (PTMs) in proteins that occurs when their tyrosine residue is nitrated. Compared with healthy people, a remarkably increased level of nitrotyrosine is detected in those suffering from rheumatoid arthritis, septic shock, and coeliac disease. Given an uncharacterized protein sequence that contains many tyrosine residues, which one of them can be nitrated and which one cannot? This is a challenging problem, not only directly related to in-depth understanding the PTM's mechanism but also to the nitrotyrosine-based drug development. Particularly, with the avalanche of protein sequences generated in the postgenomic age, it is highly desired to develop a high throughput tool in this regard. Here, a new predictor called "iNitro-Tyr" was developed by incorporating the position-specific dipeptide propensity into the general pseudo amino acid composition for discriminating the nitrotyrosine sites from non-nitrotyrosine sites in proteins. It was demonstrated via the rigorous jackknife tests that the new predictor not only can yield higher success rate but also is much more stable and less noisy. A web-server for iNitro-Tyr is accessible to the public at http://app.aporc.org/iNitro-Tyr/. For the convenience of most experimental scientists, we have further provided a protocol of step-by-step guide, by which users can easily get their desired results without the need to follow the complicated mathematics that were presented in this paper just for the integrity of its development process. It has not escaped our notice that the approach presented here can be also used to deal with the other PTM sites in proteins.

As one of the most important and universal posttranslational modifications (PTMs) of proteins, S-nitrosylation (SNO) plays crucial roles in a variety of biological processes, including the regulation of cellular dynamics and many signaling events. Knowledge of SNO sites in proteins is very useful for drug development and basic research as well. Unfortunately, it is both time-consuming and costly to determine the SNO sites purely based on biological experiments. Facing the explosive protein sequence data generated in the post-genomic era, we are challenged to develop automated vehicles for timely and effectively determining the SNO sites for uncharacterized proteins. To address the challenge, a new predictor called iSNO-AAPair was developed by taking into account the coupling effects for all the pairs formed by the nearest residues and the pairs by the next nearest residues along protein chains. The cross-validation results on a state-of-the-art benchmark have shown that the new predictor outperformed the existing predictors. The same was true when tested by the independent proteins whose experimental SNO sites were known. A user-friendly web-server for iSNO-AAPair was established at http://app.aporc.org/iSNO-AAPair/, by which users can easily obtain their desired results without the need to follow the mathematical equations involved during its development.

Posttranslational modifications (PTMs) of proteins are responsible for sensing and transducing signals to regulate various cellular functions and signaling events. S-nitrosylation (SNO) is one of the most important and universal PTMs. With the avalanche of protein sequences generated in the post-genomic age, it is highly desired to develop computational methods for timely identifying the exact SNO sites in proteins because this kind of information is very useful for both basic research and drug development. Here, a new predictor, called iSNO-PseAAC, was developed for identifying the SNO sites in proteins by incorporating the position-specific amino acid propensity (PSAAP) into the general form of pseudo amino acid composition (PseAAC). The predictor was implemented using the conditional random field (CRF) algorithm. As a demonstration, a benchmark dataset was constructed that contains 731 SNO sites and 810 non-SNO sites. To reduce the homology bias, none of these sites were derived from the proteins that had [Formula: see text] pairwise sequence identity to any other. It was observed that the overall cross-validation success rate achieved by iSNO-PseAAC in identifying nitrosylated proteins on an independent dataset was over 90%, indicating that the new predictor is quite promising. Furthermore, a user-friendly web-server for iSNO-PseAAC was established at http://app.aporc.org/iSNO-PseAAC/, by which users can easily obtain the desired results without the need to follow the mathematical equations involved during the process of developing the prediction method. It is anticipated that iSNO-PseAAC may become a useful high throughput tool for identifying the SNO sites, or at the very least play a complementary role to the existing methods in this area.

Myelodysplastic syndromes (MDS) mainly occur in elderly individuals in Western countries. However, MDS is commonly found in young individuals (

Toll-like receptor 4 (TLR4) has been proven to play a critical role in neuroinflammation and to represent an important therapeutic target following subarachnoid hemorrhage (SAH). Resveratrol (RSV), a natural occurring polyphenolic compound, has a powerful anti-inflammatory property. However, the underlying molecular mechanisms of RSV in protecting against early brain injury (EBI) after SAH remain obscure. The purpose of this study was to investigate the effects of RSV on the TLR4-related inflammatory signaling pathway and EBI in rats after SAH. A prechiasmatic cistern SAH model was used in our experiment. The expressions of TLR4, high-mobility group box 1 (HMGB1), myeloid differentiation factor 88 (MyD88), and nuclear factor-κB (NF-κB) were evaluated by Western blot and immunohistochemistry. The expressions of Iba-1 and pro-inflammatory cytokines in brain cortex were determined by Western blot, immunofluorescence staining, or enzyme-linked immunosorbent assay. Neural apoptosis, brain edema, and neurological function were further evaluated to investigate the development of EBI. We found that post-SAH treatment with RSV could markedly inhibit the expressions of TLR4, HMGB1, MyD88, and NF-κB. Meanwhile, RSV significantly reduced microglia activation, as well as inflammatory cytokines leading to the amelioration of neural apoptosis, brain edema, and neurological behavior impairment at 24 h after SAH. However, RSV treatment failed to alleviate brain edema and neurological deficits at 72 h after SAH. These results indicated that RSV treatment could alleviate EBI after SAH, at least in part, via inhibition of TLR4-mediated inflammatory signaling pathway.

The Minimum Error Correction (MEC) is an important model for haplotype reconstruction from SNP fragments. However, this model is effective only when the error rate of SNP fragments is low. In this paper, we propose a new computational model called Minimum Conflict Individual Haplotyping (MCIH) as an extension to MEC. In contrast to the conventional approaches, the new model employs SNP fragment information and also related genotype information, thereby a high accurate inference can be expected. We first prove the MCIH problem to be NP-hard. To evaluate the practicality of the new model we design an exact algorithm (a dynamic programming procedure) to implement MCIH on a special data structure. The numerical experience indicates that it is fairly effective to use MCIH at the cost of related genotype information, especially in the case of SNP fragments with a high error rate. Moreover, we present a feed-forward neural network algorithm to solve MCIH for general data structure and large size instances. Numerical results on real biological data and simulation data show that the algorithm works well and MCIH is a potential alternative in individual haplotyping.