Predicted Protein Research Articles

Genome-Wide Identification and Expression Analysis of the Aux/IAA and Auxin Response Factor Gene Family in Medicago truncatula.

Aux/IAA and auxin response transcription factor (ARF) genes are key regulators of auxin responses in plants. A total of 25 MtIAA and 40 MtARF genes were identified based on the latest updated Medicago truncatula reference genome sequence. They were clustered into 10 and 8 major groups, respectively. The homologs among M. truncatula, soybean, and Arabidopsis thaliana shared close relationships based on phylogenetic analysis. Gene structure analysis revealed that MtIAA and MtARF genes contained one to four concern motifs and they are localized to eight chromosomes, except chromosome 6 without MtARFs. In addition, some MtIAA and MtARF genes were expressed in all tissues, while others were specifically expressed in specific tissues. Analysis of cis-acting elements in promoter region and expression profiles revealed the potential response of MtIAA and MtARF genes to hormones and abiotic stresses. The prediction protein–protein interaction network showed that some ARF proteins could interact with multiple Aux/IAA proteins, and the reverse is also true. The investigation provides valuable, basic information for further studies on the biological functions of MtIAA and MtARF genes in the regulation of auxin-related pathways in M. truncatula.

Evaluation of Total Female and Male Aedes aegypti Proteomes Reveals Significant Predictive Protein-Protein Interactions, Functional Ontologies, and Differentially Abundant Proteins.

Simple SummaryAedes aegypti is a significant vector for flavivirus diseases. Only the female mosquito transmits pathogens, while the male plays a vital role in mating and species continuity. In this study, female and male Ae. aegypti proteins were analysed using a mass analyser. Then, we identified proteins for the examination of protein-protein interactions, functional enrichment, and differential protein abundance analysis. This study identified 422 and 682 proteins exclusive to male and female Ae. aegypti, respectively, with 608 proteins found in both sexes. The most significant protein-protein interaction clusters and functional enrichments were observed in the biological process, molecular function, and cellular component for the proteins of both sexes. The abundance of the proteins differed, with one protein showing an increase (elongation factor 1 α, EF1α) and two showing reductions (actin family) in females versus males. The study highlights the protein differences in male and female Ae. aegypti, and future research could further investigate their roles in mosquito–viral interactions for blocking disease transmission.Aedes aegypti is a significant vector for many tropical and subtropical flavivirus diseases. Only the female mosquito transmits pathogens, while the male plays a vital role in mating and species continuity. This study explored the total proteomes of females and males based on the physiological and genetic differences of female and male mosquitoes. Protein extracts from mosquitoes were analysed using LC–ESI–MS/MS for protein identification, protein interaction network analysis, functional ontology enrichment, and differential protein abundance analyses. Protein identification revealed 422 and 682 proteins exclusive to males and females, respectively, with 608 common proteins found in both sexes. The most significant PPIs (<1.0 × 10−16) were for common proteins, followed by proteins exclusive to females (<1.0 × 10−16) and males (1.58 × 10−12). Significant functional enrichments were observed in the biological process, molecular function, and cellular component for the male and female proteins. The abundance of the proteins differed, with one protein showing an increase (elongation factor 1 α, EF1α) and two showing reductions (actin family) in females versus males. Overall, the study verified the total proteomes differences between male and female Ae. aegypti based on protein identification and interactions, functional ontologies, and differentially abundant proteins. Some of the identified proteins merit further investigation to elucidate their roles in blocking viral transmission.

Systemic inflammation and nutritional insufficiency in palliative cancer patients

Aim. To study the relationship between the symptoms of nutritional insufficiency and systemic inflammation in cancer palliative patients.&#x0D; Methods. 106 palliative cancer patients were examined at Chelyabinsk Regional Clinical Center of Oncology and Nuclear Medicine: 54 (50.9%) men and 52 (49.1%) women aged 61 [54; 67] years. All patients underwent laboratory and instrumental examination within the approved standards of specialized medical care. Systemic inflammation was assessed by the levels of acute phase proteins (C-reactive protein, fibrinogen). The study of integrated clinical and laboratory, somatometric parameters was carried out. The nutritional risk index was assessed.&#x0D; Results. Palliative cancer patients showed a statistically significant decrease in the concentration of hemoglobin, lymphocytes, and albumin. The activation of systemic inflammation that manifested by hyperfibrinogenemia and an increase in the level of C-reactive protein was revealed. The study of somatometric parameters revealed a statistically significant decrease in body mass index, shoulder circumference, subscapular skinfold thickness, and a tendency to reduce lean body mass. The nutritional risk index assessment showed mild nutritional insufficiency in 22 (20.8%) of the examined patients and severe nutritional insufficiency in 28 (26.4%) patients. The maximum diagnostic significance of the level of C-reactive protein for prediction the nutritional insufficiency was achieved at 80.4% sensitivity and 52.7% specificity (AUC=0.671, 95% confidence interval [0.573; 0.759], p=0.001), which corresponded to a C-reactive protein threshold of 31 mg/l.&#x0D; Conclusion. 50 (47.2%) of the examined patients showed signs of nutritional insufficiency, a statistically significant decrease in hemoglobin and albumin concentration, as well as lymphocyte count, activation of systemic inflammation, manifested by hyperfibrinogenemia, and an increase in the level of C-reactive protein; it was revealed a statistically significant relationship between C-reactive protein level and malnutrition.

Protein structure prediction using deep learning distance and hydrogen-bonding restraints in CASP14.

In this article, we report 3D structure prediction results by two of our best server groups ("Zhang-Server" and "QUARK") in CASP14. These two servers were built based on the D-I-TASSER and D-QUARK algorithms, which integrated four newly developed components into the classical protein folding pipelines, I-TASSER and QUARK, respectively. The new components include: (a) a new multiple sequence alignment (MSA) collection tool, DeepMSA2, which is extended from the DeepMSA program; (b) a contact-based domain boundary prediction algorithm, FUpred, to detect protein domain boundaries; (c) a residual convolutional neural network-based method, DeepPotential, to predict multiple spatial restraints by co-evolutionary features derived from the MSA; and (d) optimized spatial restraint energy potentials to guide the structure assembly simulations. For 37 FM targets, the average TM-scores of the first models produced by D-I-TASSER and D-QUARK were 96% and 112% higher than those constructed by I-TASSER and QUARK, respectively. The data analysis indicates noticeable improvements produced by each of the four new components, especially for the newly added spatial restraints from DeepPotential and the well-tuned force field that combines spatial restraints, threading templates, and generic knowledge-based potentials. However, challenges still exist in the current pipelines. These include difficulties in modeling multi-domain proteins due to low accuracy in inter-domain distance prediction and modeling protein domains from oligomer complexes, as the co-evolutionary analysis cannot distinguish inter-chain and intra-chain distances. Specifically tuning the deep learning-based predictors for multi-domain targets and protein complexes may be helpful to address these issues.

Biochemical and molecular features of Chinese patients with glutaric acidemia type 1 detected through newborn screening

BackgroundGlutaric acidemia type 1 (GA1) is a treatable disorder affecting cerebral organic acid metabolism caused by a defective glutaryl-CoA dehydrogenase (GCDH) gene. GA1 diagnosis reports following newborn screening (NBS) are scarce in the Chinese population. This study aimed to assess the acylcarnitine profiles and genetic characteristics of patients with GA1 identified through NBS.Results From January 2014 to September 2020, 517,484 newborns were screened by tandem mass spectrometry, 102 newborns with elevated glutarylcarnitine (C5DC) levels were called back. Thirteen patients were diagnosed with GA1, including 11 neonatal GA1 and two maternal GA1 patients. The incidence of GA1 in the Quanzhou region was estimated at 1 in 47,044 newborns. The initial NBS results showed that all but one of the patients had moderate to markedly increased C5DC levels. Notably, one neonatal patient with low free carnitine (C0) level suggest primary carnitine deficiency (PCD) but was ultimately diagnosed as GA1. Nine neonatal GA1 patients underwent urinary organic acid analyses: eight had elevated GA and 3HGA levels, and one was reported to be within the normal range. Ten distinct GCDH variants were identified. Eight were previously reported, and two were newly identified. In silico prediction tools and protein modeling analyses suggested that the newly identified variants were potentially pathogenic. The most common variant was c.1244-2 A>C, which had an allelic frequency of 54.55% (12/22), followed by c.1261G>A (p.Ala421Thr) at 9.09% (2/22).ConclusionsNeonatal GA1 patients with increased C5DC levels can be identified through NBS. Maternal GA1 patients can also be detected using NBS due to the low C0 levels in their infants. Few neonatal GA1 patients may have atypical acylcarnitine profiles that are easy to miss during NBS; therefore, multigene panel testing should be performed in newborns with low C0 levels. This study indicates that the GCDH variant spectra were heterogeneous in this southern Chinese cohort.

Predictive protein markers for depression severity in mood disorders: A preliminary trans-diagnostic approach study

Depression is a common symptom of many mental disorders, especially major depressive disorder (MDD) and bipolar disorder (BD). Previous studies have reported that these diseases share common pathophysiological pathways; therefore, this study elucidated whether the plasma levels of protein markers related to common depressive symptoms differed between patients with BD and those with MDD. Plasma samples of 71 patients with mood disorders and clinical manifestations were analyzed in this study. After depleting the abundant proteins, liquid chromatography–tandem mass spectrometry and label-free quantification were performed. Five proteins, viz., cholesteryl ester transfer protein (CETP), apolipoprotein D (APOD), mannan-binding lectin serine protease 2 (MASP2), Ig lambda chain V-II region BO (IGLV2-8) and Ig kappa chain V-III region NG9 (IGKV3-20) were negatively associated with the total scores of the Hamilton depression rating scale (HAM-D), after adjusting for the covariates. CETP and APOD also showed significant negative correlations with the anhedonia/retardation and guilt/agitation scores of the HAM-D. Four proteins, namely, Ig kappa chain V-II region TEW (IGKC; IGKV2D-28), Ig lambda variable 5–45 (IGLV5-45), complement factor H (CFH) and attractin (ATRN), showed significant associations with anhedonia/retardation after adjusting for covariates. Proteins that significantly correlated with the symptoms could predict the remission state of depression (area under the curve [AUC], 0.83) and anhedonia/retardation (AUC, 0.80). Bioinformatics analysis revealed that complement activation, immune response, and lipid metabolism were significantly enriched pathways. Although our study design was cross-sectional and no controls were included, protein markers identified in this preliminary study will be further investigated in our subsequent longitudinal study.

Validation of Potential Protein Markers Predicting Chemoradioresistance in Early Cervical Cancer by Immunohistochemistry.

BackgroundIn a previous study, a proteomic panel consisting of BCL-2, HER2, CD133, CAIX, and ERCC1 significantly predicted survival in patients with locally advanced cervical cancer. However, the prognostic significance of these proteins has not been assessed in early cervical cancer. The present study investigated the clinical significance and chemoradioresistance prediction power of these proteins in patients with early-stage cervical cancer.Materials and MethodsBCL-2, HER2, CD133, CAIX, and ERCC1 expression was determined by the immunohistochemical staining of 336 cervical cancer tissue microarrays. The associations of these proteins with clinicopathologic characteristics and disease progression were assessed.ResultsThere was a trend of low CAIX expression (p=0.082) and high ERCC1 expression (p=0.059) in patients with a favorable response to adjuvant radiation. High HER2 expression was significantly associated with shorter disease-free survival (DFS) in the total group (5-year DFS of 80.1% vs. 92.2%, p=0.004). A prognostic significance remained in multivariate analysis (Hazard ratio, HR=2.10, p=0.029). In the adjuvant radiation group, low CAIX and high ERCC1 expression indicated significantly unfavorable DFS (75.0% vs. 89.0%, p=0.026 and 76.8% vs. 88.6%, p=0.022, respectively). Low CAIX expression remained an independent prognostic marker in multivariate analysis (HR=0.45, p=0.037). The combined molecular-clinical model using random survival forest method predicted DFS with improved power compared with that of the clinical variable model (C-index 0.77 vs. 0.71, p=0.006).ConclusionHER2, CAIX, and ERCC1 expression can be predictive protein markers for clinical outcomes in early cervical cancer patients treated primarily with radical surgery with or without adjuvant radiation.

Oxidative Stress Level as a Predictor of Anastomotic Leakage after Rectal Surgery.

Background Early diagnosis of anastomotic leakage (AL) after rectal surgery can reduce the adverse effects of AL, thereby reducing morbidity and mortality. Currently, there are no accepted indicators or effective scoring systems that can clearly identify patients at risk of anastomotic leakage. Methods A prospective study with assessment of the diagnostic accuracy of oxidative stress level (CAT, SOD, MDA) in serum and drain fluid compared to white blood cell count (WBC), C-reactive protein (CRP), and neutrophil percentage (NEUT) in prediction of AL in patients undergoing elective rectal surgery with anastomosis. Results Most of the oxidative stress indicators we detected are of considerable significance in the diagnosis of anastomotic leakage. The level of MDA on postoperative day (POD)3 (areas under the curve (AUC): 0.831) and POD5 (AUC: 0.837) in the serum and on POD3 (AUC: 0.845) in the drain fluid showed the same excellent diagnostic accuracy as the level of CRP on the POD3 (AUC: 0.847) and POD5 (AUC: 0.896). Conclusions The overall level of oxidative stress in serum and drain fluid is a reliable indicator for the early diagnosis of anastomotic leakage after rectal surgery. More specifically, among the redox indicators analyzed, MDA has almost the same predictive value as CRP, which provides another useful biomarker for the early diagnosis of anastomotic leakage.

Next generation proteomics with drug sensitivity screening identifies sub-clones informing therapeutic and drug development strategies for multiple myeloma patients

With the introduction of novel therapeutic agents, survival in Multiple Myeloma (MM) has increased in recent years. However, drug-resistant clones inevitably arise and lead to disease progression and death. The current International Myeloma Working Group response criteria are broad and make it difficult to clearly designate resistant and responsive patients thereby hampering proteo-genomic analysis for informative biomarkers for sensitivity. In this proof-of-concept study we addressed these challenges by combining an ex-vivo drug sensitivity testing platform with state-of-the-art proteomics analysis. 35 CD138-purified MM samples were taken from patients with newly diagnosed or relapsed MM and exposed to therapeutic agents from five therapeutic drug classes including Bortezomib, Quizinostat, Lenalidomide, Navitoclax and PF-04691502. Comparative proteomic analysis using liquid chromatography-mass spectrometry objectively determined the most and least sensitive patient groups. Using this approach several proteins of biological significance were identified in each drug class. In three of the five classes focal adhesion-related proteins predicted low sensitivity, suggesting that targeting this pathway could modulate cell adhesion mediated drug resistance. Using Receiver Operating Characteristic curve analysis, strong predictive power for the specificity and sensitivity of these potential biomarkers was identified. This approach has the potential to yield predictive theranostic protein panels that can inform therapeutic decision making.

C-reactive protein and haemoglobin level in acute kidney injury among preterm newborns.

Aim To explore the possibility of C-reactive protein (CRP) and haemoglobin (Hb) in prediction and risk assessment of acute kidney injury (AKI) among preterm newborns. This is believed to be closely related to the incidences of AKI, and could be the most affordable in early detection of AKI. Methods A case control study was carried out at Dr Hasan Sadikin Hospital in Bandung with a total of 112 preterms divided into two groups: with and without AKI based on the neonatal KDIGO (Kidney Disease: Improving Global Outcomes). CRP and creatinine serum were measured within 6 hours and at 72-96 hours after birth. The routine blood count included haemoglobin, haematocrit, leucocyte, and thrombocyte in the first 24 hours of life. Results CRP increase was the most influential factor for AKI with sensitivity of 80.6% and specificity of 60.2%. An increase in CRP >0.04 had an aOR (95% CI) of 5.64 (1.89-16.84). Haemoglobin <14.5 g/dL had slightly increased aOR (95% CI) of 1.65 (1.05- 8.63) Conclusion CRP increases >0.04 and level Hb <14.5 g/dL showed acceptable as an early warning for AKI in preterm newborns.

Genome Features of Asaia sp. W12 Isolated from the Mosquito Anopheles stephensi Reveal Symbiotic Traits.

Asaia bacteria commonly comprise part of the microbiome of many mosquito species in the genera Anopheles and Aedes, including important vectors of infectious agents. Their close association with multiple organs and tissues of their mosquito hosts enhances the potential for paratransgenesis for the delivery of antimalaria or antivirus effectors. The molecular mechanisms involved in the interactions between Asaia and mosquito hosts, as well as Asaia and other bacterial members of the mosquito microbiome, remain underexplored. Here, we determined the genome sequence of Asaia strain W12 isolated from Anopheles stephensi mosquitoes, compared it to other Asaia species associated with plants or insects, and investigated the properties of the bacteria relevant to their symbiosis with mosquitoes. The assembled genome of strain W12 had a size of 3.94 MB, the largest among Asaia spp. studied so far. At least 3585 coding sequences were predicted. Insect-associated Asaia carried more glycoside hydrolase (GH)-encoding genes than those isolated from plants, showing their high plant biomass-degrading capacity in the insect gut. W12 had the most predicted regulatory protein components comparatively among the selected Asaia, indicating its capacity to adapt to frequent environmental changes in the mosquito gut. Two complete operons encoding cytochrome bo3-type ubiquinol terminal oxidases (cyoABCD-1 and cyoABCD-2) were found in most Asaia genomes, possibly offering alternative terminal oxidases and allowing the flexible transition of respiratory pathways. Genes involved in the production of 2,3-butandiol and inositol have been found in Asaia sp. W12, possibly contributing to biofilm formation and stress tolerance.

Quantitative Multiplexed Proteomics Could Assist Therapeutic Decision Making in Non-Small Cell Lung Cancer Patients with Ambiguous ALK Test Results.

Simple SummaryTherapeutic guidance in non-small cell lung cancer (NSCLC) patients with discordant anaplastic lymphoma kinase (ALK) fluorescent in situ hybridization (+) where immunohistochemistry (IHC) (−) results are challenging. Selected reaction monitoring (SRM) quantitative multiplexed proteomics could detect ALK protein in NSCLC samples with delayed fixation where a conventional IHC method failed. ALK protein detection by the SRM method was associated with good responses on ALK inhibitors. It also could detect various predictive proteins for conventional chemotherapy at the same time, and combined results were related to clinical outcomes in this population. The SRM may provide additional information for therapeutic decision making in NSCLC patients with ambiguous ALK test results.Therapeutic guidance in non-small cell lung cancer (NSCLC) tumors that are positive for anaplastic lymphoma kinase (ALK) fluorescent in situ hybridization (FISH), but negative for ALK immunohistochemistry, is still challenging. Parallel routine screening of 4588 NSCLC cases identified 22 discordant cases. We rechecked these samples using ALK antibodies and selected reaction monitoring (SRM) quantitative multiplexed proteomics screening multiple protein targets, including ALK and MET for the ALK tyrosine kinase inhibitor (TKI), and FR-alpha, hENT1, RRM1, TUBB3, ERCC1, and XRCC1 for chemotherapy. The presence of ALK (31.8%), MET (36.4%), FR-alpha (72.7%), hENT1 (18.2%), RRM1 (31.8%), TUBB3 (72.9%), ERCC1 (4.5%), and a low level of XRCC1 (54.4%) correlated with clinical outcomes. SRM was more sensitive than the ALK D5F3 assay. Among the eight cases receiving ALK TKI, four cases with ALK or MET detected by SRM had complete or partial responses, whereas four cases without ALK or MET showed progression. Twenty-seven treatment outcomes from 20 cases were assessed and cases expressing more than half of the specific predictive proteins were sensitive to matching therapeutic agents and showed longer progression-free survival than the other cases (p < 0.001). SRM showed a potential role in therapeutic decision making in NSCLC patients with ambiguous ALK test results.

End-to-end learning for compound activity prediction based on binding pocket information

BackgroundRecently, machine learning-based ligand activity prediction methods have been greatly improved. However, if known active compounds of a target protein are unavailable, the machine learning-based method cannot be applied. In such cases, docking simulation is generally applied because it only requires a tertiary structure of the target protein. However, the conformation search and the evaluation of binding energy of docking simulation are computationally heavy and thus docking simulation needs huge computational resources. Thus, if we can apply a machine learning-based activity prediction method for a novel target protein, such methods would be highly useful. Recently, Tsubaki et al. proposed an end-to-end learning method to predict the activity of compounds for novel target proteins. However, the prediction accuracy of the method was still insufficient because it only used amino acid sequence information of a protein as the input.ResultsIn this research, we proposed an end-to-end learning-based compound activity prediction using structure information of a binding pocket of a target protein. The proposed method learns the important features by end-to-end learning using a graph neural network both for a compound structure and a protein binding pocket structure. As a result of the evaluation experiments, the proposed method has shown higher accuracy than an existing method using amino acid sequence information.ConclusionsThe proposed method achieved equivalent accuracy to docking simulation using AutoDock Vina with much shorter computing time. This indicated that a machine learning-based approach would be promising even for novel target proteins in activity prediction.

Phenotypic and genotypic spectrum of CTSK variants in a cohort of twenty-five Indian patients with pycnodysostosis

BackgroundPycnodysostosis is an autosomal recessive skeletal dysplasia with easily recognizable clinical features and marked molecular heterogeneity. In this study, we explored the clinical and molecular spectrum of 25 Indian patients with pycnodysostosis from 20 families. MethodsClinical information was collected on a predesigned clinical proforma. Sanger method was employed to sequence all the exons and exon/intron boundaries of the CTSK gene. Novel variants were systematically assessed by prediction softwares and protein modelling. The pathogenicity of variant was established based on ACMG-AMP criteria. An attempt was also made to establish a genotype-phenotype correlation and devise a diagnostic scoring system based on clinical and radiological findings. ResultsConsanguinity and positive family history were present in 65% (13/20) and 45% (9/20) of the families respectively. Short stature and fractures were the predominant presenting complaints and was evident in 96% (24/25) and 32% (8/25) of affected individuals respectively. Gestalt facial phenotype and acro-osteolysis were present in 76% (19/25) and 82.6% (19/23) of the individuals respectively. Hepatosplenomegaly was present in 15% (3/20) of the individuals with one of them having severe anaemia. Causative sequence variations were identified in all of them. A total of 19 variants were identified from 20 families amongst which 10 were novel. Homozygous variants were identified in 90% (18/20) families. Amongst the novel variants, there was a considerable proportion (40%) of frameshift variants (4/10). No significant genotype-phenotype correlation was noted. Scoring based on clinical and radiological findings led to the proposal that a minimum of 2 scores in each category is required in addition to high bone density to diagnose pycnodysostosis with certainty. ConclusionThis study delineated the genotypic and phenotypic characterisation of Indian patients with pycnodysostosis with identification of 10 novel variants. We also attempted to develop a clinically useful diagnostic scoring system which requires further validation.

Characteristics of hatching enzymes and egg envelope in cross progenies from crucian carp (Carassius auratus var.) and zebrafish (Barchydanio rerio var.)

In distant hybridization of fishes, there is a low hatching rate of hybrid progenies. To further understand the causes of low hatchability, in this article, cross-breeding between zebrafish (ZF) and crucian carp (CC) are generated, in which the hatching rate of cross progenies (ZF♀ × CC♂, ZC) is 35.67%, while that of reciprocal cross progenies (CC♀ × ZF♂, CZ) is about zero. The structures and SDS-PAGE protein pattern of egg envelopes in hybrid early embryos are like their maternal fish, however, during the process of embryo development, some differences are detected between the CZ and CC. The hatching enzyme gene 1 (he1) nucleotide sequences from ZF and CC were 85.1% identity, while that of 99.6% identity was between the ZF and ZC, and 98.4% from CC and hybrid of CZ. There are differences in predictive protein physicochemical properties of he1 between CZ and CC, but no significant change in he1 mRNA levels during embryonic development. Our data furtherly verify that the characteristics of egg envelope and hatching enzyme in hybrid progenies are inherited from maternal fish. Moreover, there are obvious differences between CZ and maternal parent in both egg envelope and hatching enzyme during embryonic development, which are considered to be related to its low hatching rate.

The Impact of C Reactive Protein in Prediction of the Outcome in Infective Endocarditis

Infective endocarditis (IE), among the most common life-threatening infection, is a serious disease causing substantial morbidity and mortality. Determining at-risk patients and following them up closely with appropriate interventions are necessary to decrease complications and mortality. Treatment response to infective endocarditis is followed up with the combination of relief of symptoms, blood cultures, echocardiographic investigations and laboratory tests. A simple and widely available test

A meta-analysis of the activity, stability, and mutational characteristics of temperature-adapted enzymes.

Understanding the characteristics that define temperature-adapted enzymes has been a major goal of extremophile enzymology in recent decades. In the present study, we explore these characteristics by comparing psychrophilic, mesophilic, and thermophilic enzymes. Through a meta-analysis of existing data, we show that psychrophilic enzymes exhibit a significantly larger gap (Tg) between their optimum and melting temperatures compared with mesophilic and thermophilic enzymes. These results suggest that Tg may be a useful indicator as to whether an enzyme is psychrophilic or not and that models of psychrophilic enzyme catalysis need to account for this gap. Additionally, by using predictive protein stability software, HoTMuSiC and PoPMuSiC, we show that the deleterious nature of amino acid substitutions to protein stability increases from psychrophiles to thermophiles. How this ultimately affects the mutational tolerance and evolutionary rate of temperature adapted organisms is currently unknown.

Novel Murine Biomarkers of Radiation Exposure Using An Aptamer-Based Proteomic Technology.

Purpose: There is a need to identify new biomarkers of radiation exposure both for use in the development of biodosimetry blood diagnostics for radiation exposure and for clinical use as markers of radiation injury. In the current study, a novel high-throughput proteomics screening approach was used to identify proteomic markers of radiation exposure in the plasma of total body irradiated mice. A subset panel of significantly altered proteins was selected to build predictive models of radiation exposure and received radiation dose useful for population screening in a future radiological or nuclear event. Methods: Female C57BL6 Mice of 8–14 weeks of age received a single total body irradiation (TBI) dose of 2, 3.5, 8 Gy or sham radiation and plasma was collected by cardiac puncture at days 1, 3, and 7 post-exposure. Plasma was then screened using the aptamer-based SOMAscan proteomic assay technology, for changes in expression of 1,310 protein analytes. A subset panel of protein biomarkers which demonstrated significant changes (p < 0.05) in expression following radiation exposure were used to build predictive models of radiation exposure and radiation dose. Results: Detectable values were obtained for all 1,310 proteins included in the SOMAscan assay. For the Control vs. Radiation model, the top predictive proteins were immunoglobulin heavy constant mu (IGHM), mitogen-activated protein kinase 14 (MAPK14), ectodysplasin A2 receptor (EDA2R) and solute carrier family 25 member 18 (SLC25A18). For the Control vs. Dose model, the top predictive proteins were cyclin dependent kinase 2/cyclin A2 (CDK2. CCNA2), E-selectin (SELE), BCL2 associated agonist of cell death (BAD) and SLC25A18. Following model validation with a training set of samples, both models tested with a new sample cohort had overall predictive accuracies of 85% and 73% for the Control vs. Radiation and Control vs. Dose models respectively. Conclusion: The SOMAscan proteomics platform is a useful screening tool to evaluate changes in biomarker expression. In our study we were able to identify a novel panel of radiation responsive proteins useful for predicting whether an animal had received a radiation exposure and to what dose they had received. Such diagnostic tools are needed for future medical management of radiation exposures.

Maternal Serum C-Reactive Protein for Prediction of Maternal and Perinatal Morbidity in Premature Rupture of Membranes

Background: Premature rupture of membranes (PROM) is defined as spontaneous rupture of membranes before the onset of uterine contraction. If the rupture of the membranes occurs after 28 weeks but before 37 weeks of gestation it is termed as PPROM (Preterm Premature Rupture of Membranes). Objective: To assess the role of the C- reactive protein (CRP) as a reliable predictor of chorioamnionitis in premature rupture of membranes (PROM). Patients and methods: This is an observational prospective study that was conducted on 120 pregnant women admitted to Menoufia University Hospitals and Shebin EL-Kom Teaching Hospital during the period from October 2019 till December 2020. Results: CRP level has sensitivity and specificity of (87.5% and 88.7%) respectively, at cutoff value >13 with area under curve of 0.915 with accuracy of 76.3% as the diagnostic tool in PPROM cases with histological chorioamnionitis (HCA). Also, C-reactive protein was significantly positively correlated with placental examination HCA, offensive discharge, ESR at 2nd hour, and TLC (p 0.05). Conclusion: CRP has a role for detection of maternal and perinatal morbidity with accuracy about 76% and can be used as an early predictor for morbidity in pregnant women with PPROM. Pregnant women with PPROM who had CRP level ≤13 mg/l should have expectant management if there are no other contraindications and those have CRP level >13 mg/l; termination of pregnancy should be taken in consideration in presence of signs of clinical chorioamnionitis.

Methodological considerations for identifying multiple plasma proteins associated with all-cause mortality in a population-based prospective cohort

Novel methods to characterize the plasma proteome has made it possible to examine a wide range of proteins in large longitudinal cohort studies, but the complexity of the human proteome makes it difficult to identify robust protein-disease associations. Nevertheless, identification of individuals at high risk of early mortality is a central issue in clinical decision making and novel biomarkers may be useful to improve risk stratification. With adjustment for established risk factors, we examined the associations between 138 plasma proteins measured using two proximity extension assays and long-term risk of all-cause mortality in 3,918 participants of the population-based Malmö Diet and Cancer Study. To examine the reproducibility of protein-mortality associations we used a two-step random-split approach to simulate a discovery and replication cohort and conducted analyses using four different methods: Cox regression, stepwise Cox regression, Lasso-Cox regression, and random survival forest (RSF). In the total study population, we identified eight proteins that associated with all-cause mortality after adjustment for established risk factors and with Bonferroni correction for multiple testing. In the two-step analyses, the number of proteins selected for model inclusion in both random samples ranged from 6 to 21 depending on the method used. However, only three proteins were consistently included in both samples across all four methods (growth/differentiation factor-15 (GDF-15), N-terminal pro-B-type natriuretic peptide, and epididymal secretory protein E4). Using the total study population, the C-statistic for a model including established risk factors was 0.7222 and increased to 0.7284 with inclusion of the most predictive protein (GDF-15; P < 0.0001). All multiple protein models showed additional improvement in the C-statistic compared to the single protein model (all P < 0.0001). We identified several plasma proteins associated with increased risk of all-cause mortality independently of established risk factors. Further investigation into the putatively causal role of these proteins for longevity is needed. In addition, the examined methods for identifying multiple proteins showed tendencies for overfitting by including several putatively false positive findings. Thus, the reproducibility of findings using such approaches may be limited.