Discrepancies between self-reported medication in adherence and indirect measurement adherence among patients undergoing antiretroviral therapy: a systematic review.

BACKGROUND: Given the critical importance of medication adherence in HIV/AIDS treatment, this study aims to compare medication adherence measured by self-report (SR) and indirect measurement among antiretroviral therapy (ART) patients, exploring the differences of adherence results measured by different tools. METHODS: We systematically searched PubMed, Embase, and the Cochrane Library to identify all relevant literature published up to November 22, 2023, without language restrictions, reporting adherence to ART measured by both SR and indirect measurement methods, while also analyzing individual and group adherence separately. Discrepancies between SR and indirect measurement results were assessed using the Mann-Whitney U test or Wilcoxon signed-rank test, with correlations evaluated using the Pearson correlation coefficient. Following one-to-one comparisons, meta-epidemiological one-step analysis was conducted, and network meta-analysis techniques were applied to compare results obtained through specific adherence assessment tools reported in the identified articles. RESULTS: The analysis encompassed 65 original studies involving 13,667 HIV/AIDS patients, leading to 112 one-to-one comparisons between SR and indirect measurement tools. Statistically significant differences were observed between SR and indirect measurement tools regarding both individual and group adherence (P < 0.05), with Pearson correlation coefficients of 0.843 for individual adherence and 0.684 for group adherence. During meta-epidemiological one-step analysis, SR-measured adherence was determined to be 3.94% (95% CI: -4.48-13.44%) higher for individual adherence and 16.14% (95% CI: 0.81-18.84%) higher for group adherence compared to indirectly measured results. Subgroup analysis indicated that factors such as the year of reporting and geographic region appeared to influence the discrepancies between SR and indirect measurements. Furthermore, network meta-analysis revealed that for both individual and group adherence, the results obtained from most SR and indirect measurement tools were higher than those from electronic monitoring devices, with some demonstrating statistical significance (P < 0.05). CONCLUSIONS: The findings underscored the complexity of accurately measuring medication adherence among ART patients. Significant variability was observed across studies, with self-report methods showing a significant tendency towards overestimation. Year of reporting, geographic region, and adherence measurement tools appeared to influence the differences between SR and indirect measurements. Future research should focus on developing and validating integrated adherence measurements that can combine SR data with indirect measures to achieve a more comprehensive understanding of adherence behaviors.

Association between TB delay and TB treatment outcomes in HIV-TB co-infected patients: a study based on the multilevel propensity score method.

BACKGROUND: HIV-tuberculosis (HIV-TB) co-infection is a significant public health concern worldwide. TB delay, consisting of patient delay, diagnostic delay, treatment delay, increases the risk of adverse anti-TB treatment (ATT) outcomes. Except for individual level variables, differences in regional levels have been shown to impact the ATT outcomes. However, few studies appropriately considered possible individual and regional level confounding variables. In this study, we aimed to assess the association of TB delay on treatment outcomes in HIV-TB co-infected patients in Liangshan Yi Autonomous Prefecture (Liangshan Prefecture) of China, using a causal inference framework while taking into account individual and regional level factors. METHODS: We conducted a study to analyze data from 2068 patients with HIV-TB co-infection in Liangshan Prefecture from 2019 to 2022. To address potential confounding bias, we used a causal directed acyclic graph (DAG) to select appropriate confounding variables. Further, we controlled for these confounders through multilevel propensity score and inverse probability weighting (IPW). RESULTS: The successful rate of ATT for patients with HIV-TB co-infection in Liangshan Prefecture was 91.2%. Total delay (OR = 1.411, 95% CI: 1.015, 1.962), diagnostic delay (OR = 1.778, 95% CI: 1.261, 2.508), treatment delay (OR = 1.749, 95% CI: 1.146, 2.668) and health system delay (OR = 1.480 95% CI: (1.035, 2.118) were identified as risk factors for successful ATT outcome. Sensitivity analysis demonstrated the robustness of these findings. CONCLUSIONS: HIV-TB co-infection prevention and control policy in Liangshan Prefecture should prioritize early treatment for diagnosed HIV-TB co-infected patients. It is urgent to improve the health system in Liangshan Prefecture to reduce delays in diagnosis and treatment.

Long-term complete remission and peripheral biomarkers in Hodgkin lymphoma patients after decitabine-plus-camrelizumab epi-immunotherapy and treatment cessation.

Patients with relapsed/refractory classical Hodgkin lymphoma (cHL) achieve complete response (CR) after decitabine-plus-camrelizumab therapy, while long-term outcome especially after treatment discontinuation remains unclear. We present a retrospective analysis of 87 relapsed/refractory cHL patients who acquired CR after decitabine-plus-camrelizumab. Patients were divided into two groups and received consolidation treatment every 3-4 or 6-12 weeks, and 1-year of continuous CR was guaranteed for treatment cessation. At a median follow-up of 5.3 years, the median relapse-free survival (RFS) after achieving CR with decitabine-plus-camrelizumab therapy was 4.5 years, and patients underwent consolidation per 3-4 weeks might have longer RFS. The baseline percentage of peripheral central memory T cells was not associated with RFS, while patients with higher pretreatment serum levels of interleukin-6 (IL-6) and lactate dehydrogenase (LDH) had significantly shorter RFS and increased risk for disease recurrence. Fifty-seven patients completed and discontinued decitabine-plus-camrelizumab, and their median RFS had not been reached. The 2-year RFS rate after treatment cessation was 78% (95% CI, 67-90%). Patients in the high-risk subgroup with higher pretreatment IL-6 and LDH levels showed poor treatment-free remission. Moreover, decitabine-plus-camrelizumab therapy was safe and cost-effective. In conclusion, patients who obtained CR with decitabine-plus-camrelizumab and received consolidation per 3-4 weeks can achieve long-term remission after treatment discontinuation.

Multi-Optimization of Injection Parameters Affecting Emissions in a Diesel Engine Fueled with Fischer-Tropsch Fuel Based on NSGA-II.

In this paper, an electronically controlled diesel engine fueled with Fischer-Tropsch fuel was selected to optimize soot and NOx emissions. First, the effects of injection parameters on exhaust performance and combustion properties were studied on an engine test bench and then a prediction model based on a support vector machine (SVM) was established according to the test results. On this basis, a decision analysis of soot and NOx solutions assigned with different weights was performed based on the TOPSIS analysis method. It turned out that the "trade-off" relation between soot and NOx emission was improved effectively. As a matter of fact, the Pareto front selected by this method showed a significant decline compared with the original operating points, in which soot declined by 3.7-7.1% and NOx declined by 1.2-2.6%. Finally, the experiments were used to confirm the validity of the results, which indicated that the Pareto front corresponded well with the test value. The maximum relative error between the soot Pareto front and the measured value is 8% while it is 5% for NOx emission, and the R2 values of soot and NOx under various conditions are more than 0.9. This instance proved that research on diesel engine emission optimization based on the SVM and NSGA-II is feasible and valid.

Effect of endogenous sodium and potassium ions in plants on the quality of alfalfa silage and bacterial community stability during fermentation.

This study investigated the impact of endogenous sodium and potassium ions in plants on the quality of alfalfa silage, as well as the stability of bacterial communities during fermentation. Silage was produced from the fermented alfalfa, and the chemical composition, fermentation characteristics, and microbiome were analyzed to understand their interplay and impact on silage fermentation quality. The alfalfa was cultivated under salt stress with the following: (a) soil content of <1‰ (CK); (b) 1‰-2‰ (LP); (c) 2‰-3‰ (MP); (d) 3‰-4‰ (HP). The results revealed that the pH of silage was negatively correlated with the lactic acid content. With the increase of lactic acid (LA) content increased (26.3-51.0 g/kg DM), the pH value decreased (4.9-5.3). With the increase of salt stress, the content of Na+ in silage increased (2.2-5.4 g/kg DM). The presence of endogenous Na+ and K+ ions in plants significantly affected the quality of alfalfa silage and the dynamics of bacterial communities during fermentation. Increased salt stress led to changes in microbial composition, with Lactococcus and Pantoea showing a gradual increase in abundance, especially under high salt stress. Low pH inhibited the growth of certain bacterial genera, such as Pantoea and Pediococcus. The abundance of Escherichia-Shigella and Comamonas negatively correlated with crude protein (CP) content, while Enterococcus and Lactococcus exhibited a positive correlation. Furthermore, the accumulation of endogenous Na+ in alfalfa under salt stress suppressed bacterial proliferation, thereby reducing protein degradation during fermentation. The pH of the silage was high, and the LA content was also high. Silages from alfalfa under higher salt stress had higher Na+ content. The alpha diversity of bacterial communities in alfalfa silages showed distinct patterns. Desirable genera like Lactococcus and Lactobacillus predominated in silages produced from alfalfa under salt stress, resulting in better fermentation quality.

Energy-Saving and Pollution-Reduction Potential Analysis for Diesel Engines Fueled with Fischer-Tropsch Fuel.

Alternative fuels have attracted wide attention owing to the increasing energy consumption and environmental pollution problems, which are caused by the extensive application of diesel engines for various occasions. The Fischer-Tropsch (F-T) diesel synthesized from coal is considered as one kind of ideal alternative fuel for diesel engines; however, its combustion and exhaust emission characteristics are different from those of national diesel owing to its special fuel properties. Therefore, the combustion and emission characteristics of F-T diesel and 0# diesel, which meet the China stage VI were compared in a common rail direct injection (CRDI) diesel engine. Moreover, energy-saving and pollution-reduction potential were analyzed in one CRDI diesel engine fueled with F-T diesel. The results showed that F-T diesel had an earlier ignition point, shorter ignition delay, lower cylinder pressure, and heat release rate compared with those of 0# diesel at the same operating conditions. Meanwhile, the amplitude, oscillation level, and energy of cylinder pressure were decreased to some extent, with the maximum drops of 0.98 bar, 16.4 dB, and 1.01 × 1012 Pa, respectively. Additionally, under external characteristic conditions, maximum break thermal efficiency (BTE) and break-specific fuel consumption (BSFC) of F-T diesel were reduced by 1.1 and 2.1% on average compared with those of 0# diesel. In addition, CO, HC, NOx, and SOOT emissions of F-T diesel were found to be lower than those of 0# diesel, which were decreased by an average of 8, 3.7, 2.1, and 1.3%, respectively.

Bioinformatics analysis of differentially expressed genes and identification of an miRNA-mRNA network associated with entorhinal cortex and hippocampus in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is a fatal neurodegenerative disorder, and the lesions originate in the entorhinal cortex (EC) and hippocampus (HIP) at the early stage of AD progression. Gaining insight into the molecular mechanisms underlying AD is critical for the diagnosis and treatment of this disorder. Recent discoveries have uncovered the essential roles of microRNAs (miRNAs) in aging and have identified the potential of miRNAs serving as biomarkers in AD diagnosis. METHODS: We sought to apply bioinformatics tools to investigate microarray profiles and characterize differentially expressed genes (DEGs) in both EC and HIP and identify specific candidate genes and pathways that might be implicated in AD for further analysis. Furthermore, we considered that DEGs might be dysregulated by miRNAs. Therefore, we investigated patients with AD and healthy controls by studying the gene profiling of their brain and blood samples to identify AD-related DEGs, differentially expressed miRNAs (DEmiRNAs), along with gene ontology (GO) analysis, KEGG pathway analysis, and construction of an AD-specific miRNA-mRNA interaction network. RESULTS: Our analysis identified 10 key hub genes in the EC and HIP of patients with AD, and these hub genes were focused on energy metabolism, suggesting that metabolic dyshomeostasis contributed to the progression of the early AD pathology. Moreover, after the construction of an miRNA-mRNA network, we identified 9 blood-related DEmiRNAs, which regulated 10 target genes in the KEGG pathway. CONCLUSIONS: Our findings indicated these DEmiRNAs having the potential to act as diagnostic biomarkers at an early stage of AD.

Progress: Targeted Therapy, Immunotherapy, and New Chemotherapy Strategies in Advanced Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is one of the most aggressive subtypes of breast cancer, accounting for approximately 15% of cases, and is defined by the lack of expression of hormone receptors (estrogen and progesterone receptors) and lack of amplification or overexpression of human epidermal growth receptor 2 (HER2). Due to the lack of targets of hormone receptors and HER2, treatment of TNBC or advanced TNBC relies on conventional chemotherapeutic agents, but their efficacy and prognosis are poor. In patients with advanced TNBC, poorer outcomes are observed. Recently, with the launch of clinical trials and advancements in molecular studies, targeted therapy for signaling transduction pathways, immunotherapy for immune checkpoints, and new chemotherapy strategies have provided feasible or potential therapeutic options for advanced TNBC. This review aimed to summarize recent progress in targeted therapy, immunotherapy, and chemotherapy for advanced TNBC.

Gene expression changes induced by valproate in the process of rat hippocampal neural stem cells differentiation.

Valproate (VPA), an effective clinical approved anti-epileptic drug and mood stabilizer, has been believed to induce neuronal differentiation at the expense of inhibiting astrocytic and oligodendrocytic differentiation. Nevertheless, the involving mechanisms of it remain unclear yet. In the present study, we explored the global gene expression changes of fetus rat hippocampal neural stem cells following VPA treatment by high-throughput microarray. We obtained 874 significantly upregulated genes and 258 obviously downregulated genes (fold change > 2 and P < 0.05). Then, we performed gene ontology and pathway analyses of these differentially expressed genes and chose several genes associated with nervous system according to gene ontology analysis to conduct expression analysis to validate the reliability of the array results as well as reveal possible mechanisms of VPA. To get a better comprehension of the differentially regulated genes by VPA, we conducted protein-protein association analysis of these genes, which offered a source for further studies. In addition, we made the overlap between the VPA-downregulated genes and the predicted target genes of VPA-upregulated microRNAs (miRNAs), which were previously demonstrated. These overlapped genes may provide a source to find functional VPA/miRNA/mRNA axes during neuronal differentiation. This study first constructed a comprehensive potential downstream gene map of VPA in the process of neuronal differentiation.

Antimicrobial resistance genetic factor identification from whole-genome sequence data using deep feature selection.

BACKGROUND: Antimicrobial resistance (AMR) is a major threat to global public health because it makes standard treatments ineffective and contributes to the spread of infections. It is important to understand AMR's biological mechanisms for the development of new drugs and more rapid and accurate clinical diagnostics. The increasing availability of whole-genome SNP (single nucleotide polymorphism) information, obtained from whole-genome sequence data, along with AMR profiles provides an opportunity to use feature selection in machine learning to find AMR-associated mutations. This work describes the use of a supervised feature selection approach using deep neural networks to detect AMR-associated genetic factors from whole-genome SNP data. RESULTS: The proposed method, DNP-AAP (deep neural pursuit - average activation potential), was tested on a Neisseria gonorrhoeae dataset with paired whole-genome sequence data and resistance profiles to five commonly used antibiotics including penicillin, tetracycline, azithromycin, ciprofloxacin, and cefixime. The results show that DNP-AAP can effectively identify known AMR-associated genes in N. gonorrhoeae, and also provide a list of candidate genomic features (SNPs) that might lead to the discovery of novel AMR determinants. Logistic regression classifiers were built with the identified SNPs and the prediction AUCs (area under the curve) for penicillin, tetracycline, azithromycin, ciprofloxacin, and cefixime were 0.974, 0.969, 0.949, 0.994, and 0.976, respectively. CONCLUSIONS: DNP-AAP can effectively identify known AMR-associated genes in N. gonorrhoeae. It also provides a list of candidate genes and intergenic regions that might lead to novel AMR factor discovery. More generally, DNP-AAP can be applied to AMR analysis of any bacterial species with genomic variants and phenotype data. It can serve as a useful screening tool for microbiologists to generate genetic candidates for further lab experiments.

MicroRNA expression profiles of neural stem cells following valproate inducement.

Neural stem cells (NSCs) possess self-renewal and multilineage differentiation ability, thus are considered to be a potential source for cell replacement therapy of many nervous system diseases, such as neurodegenerative diseases. Valproate (VPA), a member of histone deacetylase inhibitor family, is an epigenetic regulator and can promote NSCs to differentiate into neurons, nevertheless, the underlying mechanisms of the process remain unclear. MicroRNAs (miRNAs) exert a crucial part in the posttranscriptional regulation of gene expression. Epigenetic mechanisms involve in the regulation of miRNAs expression. Therefore we speculated that miRNAs may be important factors during the promotion of neuronal differentiation by VPA. Here, after selecting appropriate concentration and treatment time of VPA, we conducted microRNA arrays at 24 h on the treatment of 1 mM VPA or vehicle. After validation, we obtained 5 significantly upregulated miRNAs (miR-29a-5p, miR-674-5p, miR-155-5p, miR-652-3p, and miR-210-3p) in VPA group compared with control. We predicted the target genes of these miRNAs on the website. Through gene ontology (GO) and pathway analyses, we obtained preliminary comprehension of the function of these genes. The bioinformatics analyses indicated the involvement of them during neurogenesis. In addition, we observed high expression of miR-210-3p, miR-29a-5p, and miR-674-5p in central nervous system, which suggested that they were likely to play crucial roles in neuronal differentiation. We then defined the upregulation of Map2 by transfecting mimic of miR-674-5p, which indicated the promotion of miR-674-5p on NSCs differentiation. The present study explored the miRNAs potentially mediated the function of VPA on promoting NSCs to differentiate into neurons.

Brain lipid binding protein mediates the proliferation of human glioblastoma cells by regulating ERK1/2 signaling pathway in vitro.

Brain lipid binding protein (BLBP) is highly expressed in the radial glial cells (RGCs) of the central nervous system (CNS), in glioblastomas, and, in vitro, in U251 cells. In this report, we have demonstrated that increased BLBP expression in glioblastoma is associated with poor survival and used a double-vector CRISPR/Cas9 lentiviral system to deplete endogenous BLBP from U251 cells, we found that loss of BLBP induced cell growth inhibition and S-phase arrest. Moreover, an increase in P53 and a decrease in p-ERK1/2 were observed after BLBP depletion, suggesting a potential mechanism by which loss of BLBP results in growth inhibition.

Overexpression of Lhx8 inhibits cell proliferation and induces cell cycle arrest in PC12 cell line.

LIM-homeobox genes play a pivotal function in tissue patterning and differentiation, Lhx8 is a member of LIM-homeobox gene family, and it is selectively expressed in embryonic basal forebrain and is a key factor for the determination of cholinergic cells fate. However, besides cholinergic differentiation, little is known about the potential role of Lhx8 in cell biology. In this study, we transfected Lhx8 complementary DNA (cDNA) into PC12 cell line using lentiviral vectors to acquire the cells which stably expressed high level of Lhx8, and we provide the experimental evidence that overexpression of Lhx8 inhibits cell proliferation and induces cell cycle arrest but not apoptosis in vitro. In conclusion, besides cholinergic differentiation, our results suggest that Lhx8 also plays as a suppressor gene of proliferation in cell biology.

Therapeutic effect of human umbilical cord mesenchymal stem cells on neonatal rat hypoxic-ischemic encephalopathy.

The therapeutic potential of umbilical cord blood mesenchymal stem cells has been studied in several diseases. However, the possibility that human umbilical cord Wharton's jelly-derived mesenchymal stem cells (hUCMSCs) can be used to treat neonatal hypoxic-ischemic encephalopathy (HIE) has not yet been investigated. This study focuses on the potential therapeutic effect of hUCMSC transplantation in a rat model of HIE. Dermal fibroblasts served as cell controls. HIE was induced in neonatal rats aged 7 days. hUCMSCs labeled with Dil were then transplanted into the models 24 hr or 72 hr post-HIE through the peritoneal cavity or the jugular vein. Behavioral testing revealed that hUCMSC transplantation but not the dermal fibroblast improved significantly the locomotor function vs. vehicle controls. Animals receiving cell grafts 24 hr after surgery showed a more significant improvement than at 72 hr. More hUCMSCs homed to the ischemic frontal cortex following intravenous administration than after intraperitoneal injection. Differentiation of engrafted cells into neurons was observed in and around the infarct region. Gliosis in ischemic regions was significantly reduced after hUCMSC transplantation. Administration of ganglioside (GM1) enhanced the behavioral recovery on the base of hUCMSC treatment. These results demonstrate that intravenous transplantation of hUCMSCs at an early stage after HIE can improve the behavior of hypoxic-ischemic rats and decrease gliosis. Ganglioside treatment further enhanced the recovery of neurological function following hUCMSC transplantation.

Upregulation of Lhx8 increase VAChT expression and ACh release in neuronal cell line SHSY5Y.

Lhx8 is a transcription factor for cholinergic differentiation. Our previous experiments found upregulation of Lhx8 promoted cholinergic neuronal differentiation of hippocampal neural stem/progenitor cells or hippocampal newborn neurons in vitro. However, the role of Lhx8 in VAChT expression and ACh release is still less understood. In this report, we transfected Lhx8 cDNA into neuronal cell line SHSY5Y by lentiviral vectors to acquire the cells which stably expressed high level of Lhx8. Using this cell model, we provided experimental evidence that increasing Lhx8 upregulated the expression of ChAT and VAChT, and also increased the ACh release in culture medium. We suggested that Lhx8 overexpression is a useful strategy to increase the release of ACh and maybe of therapeutic value to neurodegenerative diseases.

Cortical endogenic neural regeneration of adult rat after traumatic brain injury.

Focal and diffuse neuronal loss happened after traumatic brain injury (TBI). With little in the way of effective repair, recent interest has focused on endogenic neural progenitor cells (NPCs) as a potential method for regeneration. Whether endogenic neural regeneration happened in the cortex of adult rat after TBI remains to be determined. In this study, rats were divided into a sham group and a TBI group, and the rat model of medium TBI was induced by controlled cortical impact. Rats were injected with BrdU at 1 to 7 days post-injury (dpi) to allow identification of differentiated cells and sacrificed at 1, 3, 7, 14 and 28 dpi for immunofluorescence. Results showed nestin(+)/sox-2(+) NPCs and GFAP(+)/sox-2(+) radial glial (RG)-like cells emerged in peri-injured cortex at 1, 3, 7, 14 dpi and peaked at 3 dpi. The number of GFAP(+)/sox-2(+) cells was less than that of nestin(+)/sox-2(+) cells. Nestin(+)/sox-2(+) cells from posterior periventricle (pPV) immigrated into peri-injured cortex through corpus callosum (CC) were found. DCX(+)/BrdU(+) newborn immature neurons in peri-injured cortex were found only at 3, 7, 14 dpi. A few MAP-2(+)/BrdU(+) newborn neurons in peri-injured cortex were found only at 7 and 14 dpi. NeuN(+)/BrdU(+) mature neurons were not found in peri-injured cortex at 1, 3, 7, 14 and 28 dpi. While GFAP(+)/BrdU(+) astrocytes emerged in peri-injured cortex at 1, 3, 7, 14, 28 dpi and peaked at 7 dpi then kept in a stable state. In the corresponding time point, the percentage of GFAP(+)/BrdU(+) astrocytes in BrdU(+) cells was more than that of NPCs or newborn neurons. No CNP(+)/BrdU(+) oligodendrocytes were found in peri-injured cortex. These findings suggest that NPCs from pPV and reactive RG-like cells emerge in peri-injured cortex of adult rats after TBI. It can differentiate into immature neurons and astrocytes, but the former fail to grow up to mature neurons.

Unifying protein inference and peptide identification with feedback to update consistency between peptides.

We first propose a new method to process peptide identification reports from databases search engines. Then via it we develop a method for unifying protein inference and peptide identification by adding a feedback from protein inference to peptide identification. The feedback information is a list of high-confidence proteins, which is used to update an adjacency matrix between peptides. The adjacency matrix is used in the regularization of peptide scores. Logistic regression (LR) is used to compute the probability of peptide identification with the regularized scores. Protein scores are then calculated with the LR probability of peptides. Instead of selecting the best peptide match for each MS/MS, we select multiple peptides. By testing on two datasets, the results have shown that the proposed method can robustly assign accurate probabilities to peptides, and have a higher discrimination power than PeptideProphet to distinguish correct and incorrect identified peptides. Additionally, not only can our method infer more true positive proteins but also infer less false positive proteins than ProteinProphet at the same false positive rate. The coverage of inferred proteins is also significantly increased due to the selection of multiple peptides for each MS/MS and the improvement of their scores by the feedback from the inferred proteins.

Identifying protein complexes in protein-protein interaction networks by using clique seeds and graph entropy.

The identification of protein complexes plays a key role in understanding major cellular processes and biological functions. Various computational algorithms have been proposed to identify protein complexes from protein-protein interaction (PPI) networks. In this paper, we first introduce a new seed-selection strategy for seed-growth style algorithms. Cliques rather than individual vertices are employed as initial seeds. After that, a result-modification approach is proposed based on this seed-selection strategy. Predictions generated by higher order clique seeds are employed to modify results that are generated by lower order ones. The performance of this seed-selection strategy and the result-modification approach are tested by using the entropy-based algorithm, which is currently the best seed-growth style algorithm to detect protein complexes from PPI networks. In addition, we investigate four pairs of strategies for this algorithm in order to improve its accuracy. The numerical experiments are conducted on a Saccharomyces cerevisiae PPI network. The group of best predictions consists of 1711 clusters, with the average f-score at 0.68 after removing all similar and redundant clusters. We conclude that higher order clique seeds can generate predictions with higher accuracy and that our improved entropy-based algorithm outputs more reasonable predictions than the original one.

A feedback framework for protein inference with peptides identified from tandem mass spectra.

BACKGROUND: Protein inference is an important computational step in proteomics. There exists a natural nest relationship between protein inference and peptide identification, but these two steps are usually performed separately in existing methods. We believe that both peptide identification and protein inference can be improved by exploring such nest relationship. RESULTS: In this study, a feedback framework is proposed to process peptide identification reports from search engines, and an iterative method is implemented to exemplify the processing of Sequest peptide identification reports according to the framework. The iterative method is verified on two datasets with known validity of proteins and peptides, and compared with ProteinProphet and PeptideProphet. The results have shown that not only can the iterative method infer more true positive and less false positive proteins than ProteinProphet, but also identify more true positive and less false positive peptides than PeptideProphet. CONCLUSIONS: The proposed iterative method implemented according to the feedback framework can unify and improve the results of peptide identification and protein inference.