Cost prediction for ischemic heart disease hospitalization: Interpretable feature extraction using network analysis.

OBJECTIVES: Ischemic heart disease (IHD) is a significant contributor to global mortality and disability, imposing a substantial social and economic burden on individuals and healthcare systems. To enhance the efficient allocation of medical resources and ultimately benefit a larger population, accurate prediction of healthcare costs is crucial. METHODS: We developed an interpretable IHD hospitalization cost prediction model that integrates network analysis with machine learning. Specifically, our network-enhanced model extracts explainable features by leveraging a diagnosis-procedure concurrence network and advanced graph kernel techniques, facilitating the capture of intricate relationships between medical codes. RESULTS: The proposed model achieved an R2 of 0.804 ± 0.008 and a root mean square error (RMSE) of 17,076 ± 420 CNY on the temporal validation dataset, demonstrating comparable performance to the model employing less interpretable code embedding features (R2: 0.800 ± 0.008; RMSE: 17,279 ± 437 CNY) and the hybrid graph isomorphism network (R2: 0.802 ± 0.007; RMSE: 17,249 ± 387 CNY). The interpretation of the network-enhanced model assisted in pinpointing specific diagnoses and procedures associated with higher hospitalization costs, including acute kidney injury, permanent atrial fibrillation, intra-aortic balloon bump, and temporary pacemaker placement, among others. CONCLUSION: Our analysis results demonstrate that the proposed model strikes a balance between predictive accuracy and interpretability. It aids in identifying specific diagnoses and procedures associated with higher hospitalization costs, underscoring its potential to support intelligent management of IHD.

A dynamic sequential decision-making model on MRI real-time scheduling with simulation-based optimization.

Magnetic resonance imaging (MRI) is widely used in diagnostic medicine and contributes significantly to US health care spending. Scheduling MRI jobs involves uncertainties (e.g., patient arrival time, scanning time, and preparation time) that can lead to excessive delays and high costs in MRI operations. This study addresses real-time decision making in use of MRI scanners based on job assignment and sequencing decisions that override the appointment schedule. The decisions are made using real-time information of the waiting patients, the utilization status of the MRI scanners, and the partially revealed uncertainties of scanning times of current patients. A sequential decision-making framework and a simulation-based solution method are proposed to utilize massive real-time information and match the use of MRI rescheduling in practice. The results are then compared with a real case in a large midwestern academic medical center in the US. This study illustrates that the proposed method reduces patient waiting time by 21.7% and improves utilization of MRI scanners by 23.0%. An optimality gap of 13.6% is provided when compared to off line scheduling methods based on a mixed integer programming (MIP) model. The number of simulation replications in this approach uses the ranking and selection method, which not only reduces solution time, but also provides solution quality guarantees wherein the probability of errors in the proposed method for one day is less than 0.1%. In 100 randomly generated workday experiments, all of the scheduling decisions given by the proposed method perform better than current policy, with an average reduction of 17.93 minutes in each patient's waiting time and an improvement of scanner utilization by 7.20%.

Fabrication of Bioresource-Derived Porous Carbon-Supported Iron as an Efficient Oxidase Mimic for Dual-Channel Biosensing.

Herein, we designed a new strategy for fabricating a renewable bioresource-derived N-doped hierarchical porous carbon-supported iron (Fe/NPC)-based oxidase mimic. The obtained results suggested that Fe/NPC possessed a large specific surface area (1144 m2/g) and pore volume (0.62 cm3/g) to afford extensive Fe-Nx active sites. Taking advantages of the remarkable oxidase-mimicking activity, outstanding stability, and reusability of Fe/NPC, a novel dual-channel biosensing system was strategically fabricated for sensitively determining acetylcholinesterase (AChE) through the integration of Fe/NPC and fluorescent silver nanoclusters (AgNCs) for the first time. The limits of detection for AChE can achieve as low as 0.0032 and 0.0073 U/L by the outputting fluorometric and colorimetric dual signals, respectively. Additionally, this dual-signal system was applied to analyze human erythrocyte AChE and its inhibitor with robust analytical performance. This work provides one sustainable and effective avenue to apply a bioresource for fabricating an Fe/NPC-based oxidase mimic with high catalytic performance and also gives new impetuses for developing novel biosensors by applying Fe/NPC-based enzyme mimics as substitutes for the natural enzyme.

Fe-N-C single-atom nanozymes with peroxidase-like activity for the detection of alkaline phosphatase.

Single-atom nanozymes have drawn wide attention in bio-sensing for their remarkable merits such as low cost, high stability, and maximum atom utilization. Herein, a colorimetric strategy based on Fe-N-C single-atom nanozymes (Fe/NC-SAs) was established for the detection of alkaline phosphatase (ALP) activity. The Fe/NC-SAs prepared by pyrolysis have excellent peroxidase-like activity and can oxidize 3,3',5,5'-tetramethylbenzidine (TMB) to a blue color product in the presence of hydrogen peroxide (H2O2). When ascorbic acid (AA) is added to the system, the blue color fades, and the absorbance has a linear relationship with the concentration of AA. Alkaline phosphatase (ALP) can catalyze the hydrolysis of ascorbic acid 2-phosphate (AAP) to produce AA. Thus, a strategy based on Fe/NC-SAs for the detection of ALP activity was established, which provided a linear range of 0.1-1.5 U L-1 and a limit of detection as low as 0.05 U L-1. Besides, Fe/NC-SAs showed high stability under harsh conditions. Moreover, an Fe/NC-SA-based assay was successfully validated using human serum samples for ALP determination with satisfactory results, and has broad prospects in the field of biosensing.

A prediction and interpretation framework of acute kidney injury in critical care.

Acute kidney injury (AKI) is a common clinical condition with high mortality and resource consumption. Early identification of high-risk patients to achieve an appropriate allocation of limited clinical resources and timely interventions is of significant importance, which has attracted substantial research to develop prediction models for AKI risk stratification. However, most available AKI prediction models have moderate performance and lack of interpretability, which limits their applicability in supporting care intervention. In this paper, a machine learning-based framework for AKI prediction and interpretation in critical care is presented. First, an ensemble model is developed to predict a patient's risk of AKI within 72 h of admission to the intensive care units. Next, the model is interpreted both globally and locally. For the global interpretation, the important predictors are pinpointed and the detailed relationships between AKI risk and these predictors are illustrated. For the local interpretation, patient-specific analysis is presented to provide a visualized explanation for each individual prediction. Experimental results show that such a prediction and interpretation framework can lead to good prediction and interpretation performance, which has the potential to provide effective clinical decision support.

[Experience and lessons on guiding and governing clinical applications of chromosome microarray analysis in the United States].

Chromosome microarray analysis (CMA) has become the first-tier testing for chromosomal abnormalities and copy number variations (CNV). This review described the clinical validation of CMA, the development and updating of technical standards and guidelines and their diagnostic impacts. The main focuses were on the development and updating of expert consensus, practice resources, and a series of technical standards and guidelines through systematic review of case series with CMA application in the literature. Expert consensus and practice resource supported the use of CMA as the first-tier testing for detecting chromosomal abnormalities and CNV in developmental and intellectual disabilities, multiple congenital anomalies and autism. The standards and guidelines have been applied to pre- and postnatal testing for constitutional CNV and tumor testing for acquired CNV. CMA has significantly improved the diagnostic yields but still needs to overcome its technical limitations and face challenges of new technologies. Guiding and governing CMA through expert consensus, practice resource, standards and guidelines in the United States has provided effective and safe diagnostic services to patients and their families, reliable diagnosis on related genetic diseases for clinical database and basic research, and references for clinical translation of new technologies.

[A review of consensus statements, practice resources, standards and guidelines for clinical applications of next-generation sequencing technologies in the United States].

The use of whole exome sequencing (WES) for the detection of disease-causing variants of genetic diseases and for non-invasive prenatal screening (NIPS) of fetal aneuploidies are two major clinical applications of next generation sequencing (NGS). This article has summarized the official documents developed and updated by the American College of Medical Genetics and Genomics (ACMG) on governing WES and NIPS. These include the development of expert consensus policies and position statements on an ongoing basis to guide clinical application of NGS technology and variant analysis, establish evidence-based practical resources, as well as standards and guidelines to govern diagnosis and screening. These ACMG documents are valuable references to Chinese geneticists, but direct adoption of these standards and guidelines may not be practical due to the differences in disease-associated variant frequencies in Chinese population, socioeconomic status, and medical practice between the two countries. It is hoped that this review could facilitate the development of NGS and NIPS standards and guidelines that are consistent with international standards and concordant with medical genetics practice in China to provide high-quality, efficient and safe clinical services for patients and their families with genetic diseases.

Cisplatin in Combination with MDM2 Inhibition Downregulates Rad51 Recombinase in a Bimodal Manner to Inhibit Homologous Recombination and Augment Tumor Cell Kill.

Dysfunction of p53 and resistance to cancer drugs can arise through mutually exclusive overexpression of MDM2 or MDM4. Cisplatin-resistant cells, however, can demonstrate increased binding of both MDM2 and MDM4 to p53 but in absence of cellular overexpression. Whether MDM2 inhibitors alone can activate p53 in these resistant cells was investigated with the goal to establish the mechanism for potential synergy with cisplatin. Thus, growth inhibition by individual drugs and combinations was assessed by a colorimetric assay. Drug-treated parental A2780 and resistant tumor cells were also examined for protein expression using immunoblot and reverse phase protein array (RPPA) and then subjected to Ingenuity Pathway Analysis (IPA). Gene expression was assessed by real-time polymerase chain reaction, DNA damage by confocal microscopy, cell cycle by flow cytometry, and homologous recombination (HR) by a GFP reporter assay. Our results demonstrate that Nutlin-3 but not RITA (reactivation of p53 and induction of tumor cell apoptosis) effectively disrupted the p53-MDM2-MDM4 complex to activate p53, which increased robustly with cisplatin/Nutlin-3 combination and enhanced antitumor effects more than either agent alone. RPPA, IPA, and confocal microscopy provided evidence for an "apparent" increase in DNA damage resulting from HR inhibition by cisplatin/Nutlin-3. Molecularly, the specific HR protein Rad51 was severely downregulated by the combination via two mechanisms: p53-dependent transrepression and p53/MDM2-mediated proteasomal degradation. In conclusion, Nutlin-3 fully destabilizes the p53-MDM2-MDM4 complex and synergizes with cisplatin to intensify p53 function, which then downregulates Rad51 through a bimodal mechanism. As a result, HR is inhibited and antitumor activity enhanced in otherwise HR-proficient sensitive and resistant tumor cells. SIGNIFICANCE STATEMENT: Rad51 downregulation by the combination of cisplatin and Nutlin-3 inhibits homologous recombination (HR), which leads to persistence in DNA damage but not an increase. Thus, inhibition of HR enhances antitumor activity in otherwise HR-proficient sensitive and resistant tumor cells.

Investigating the suitability of high-resolution mass spectrometry for newborn screening: identification of hemoglobinopathies and ß-thalassemias in dried blood spots.

A fast and reliable method for the determination of hemoglobinopathies and thalassemias by high-resolution accurate mass spectrometry (HRAM/MS) is presented. The established method was verified in a prospective clinical study (HRAM/MS vs. high-pressure liquid chromatography [HPLC]) of 5335 de-identified newborn samples from the Hamburg area. The analytical method is based on a dual strategy using intact protein ratios for thalassemias and tryptic digest fragments for the diagnosis of hemoglobinopathies. Due to the minimal sample preparation and the use of flow injection, the assay can be considered as a high-throughput screening approach for newborn screening programs (2 min/sample). Using a simple dried blood spot (DBS) extraction (tryptic digest buffer), the following results were obtained: (1) a carrier incidence of 1:100 newborns (35 FAS, nine FAC, eight FAD and two FAE), and (2) no homozygous affected patient was detected. Using the HRAM/MS protocol, an unknown Hb mutation was identified and confirmed by genetic testing. In addition to greater specificity toward rare mutations and ß-thalassemia, the low price/sample (1-2€) as well as an automated data processing represent the major benefits of the described HRAM/MS method.

Identification of chicken FSHR gene promoter and the correlations between polymorphisms and egg production in Chinese native hens.

Egg production is an important economic trait in poultry, and it is of great significance to study the key genes and functional SNPs that affect egg laying performance. Follicle-stimulating hormone (FSH) plays an important physiological role in the reproductive performance of humans and animals by binding to its receptor (FSHR). Studies have shown that there are many transcriptional regulatory elements in the 5' flanking region of the FSHR gene that interact with transcription factors to regulate FSHR transcription. In this study, DNA sequencing was used to identify SNPs in the FSHR promoter sequence in both Dongxiang and Suken chickens. To detect the activity of the chicken FSHR gene promoter, we analysed the characteristics of the sequence and constructed three deletion vectors. We confirmed that the region (-18/-544) was the core promoter. Furthermore, five polymorphisms, including a 200-bp indel at -869, C-1684T, C-1608T, G-368A and T-238A, were detected in both the Dongxiang and Suken chickens. The age at first egg (AFE) for different genotype of -869 indel in Suken chicken was significantly different (p < 0.01). For SNP C-1684T in Dongxiang chickens, the CC genotype had higher egg number at 43 weeks of age (E43) than that of the TC genotype (p < 0.05). For SNP C-1684T in Suken chickens, the TC genotype had higher AFE than that of the CC genotype (p < 0.05). For SNP C-1608T in Suken chickens, the CC genotype had higher AFE than that of the TC genotype (p < 0.05). For SNP G-368A in Suken chickens, the AG genotype had higher AFE than that of the GG genotype (p < 0.05).

Cost-effectiveness analysis of intensive hypertension control in China.

China has the largest population of adults with hypertension in the world. Recent clinical trials have shown that intensive hypertension control can help patients achieve lower blood pressure and reduce the incidence of major cardiovascular disease (CVD) events, but this level of hypertension control also incurs additional costs to patients and society and may result in a substantial increase in adverse events. The objective of this study is to assess the cost-effectiveness of intensive hypertension control to inform health policymakers and health care delivery systems in China in their decision-making regarding hypertension treatment strategies. We developed a Markov based simulation model of hypertension to assess the impact of intensive and standard hypertension control strategies for the Chinese population who are diagnosed with hypertension. Model parameters were estimated based on the best available data and the literature. We projected that intensive hypertension control would avert about 2.2 million coronary heart disease events and 4.4 million stroke events for all hypertensive patients in China in 10 years compared to standard hypertension control. The incremental cost-effectiveness ratio (ICER) for intensive hypertension control was estimated at 7876 CNY per quality-adjusted life year (QALY) compared to standard hypertension control. Intensive hypertension control would be more cost-effective than standard hypertension control in China. Our findings indicated that China should consider expanding intensive hypertension control among hypertensive patients given its great potential in preventing CVD.

A rapid method to identify Salmonella enterica serovar Gallinarum biovar Pullorum using a specific target gene ipaJ.

Salmonella enterica serovar Gallinarum biovar Pullorum (S. Pullorum) is the pathogen of pullorum disease, which leads to severe economic losses in many developing countries. Traditional methods to identify S. enterica have relied on biochemical reactions and serotyping, which are time-consuming with accurate identification if properly carried out. In this study, we developed a rapid polymerase chain reaction (PCR) method targeting the specific gene ipaJ to detect S. Pullorum. Among the 650 S. Pullorum strains isolated from 1962 to 2016 all over China, 644 strains were identified to harbour ipaJ gene in the plasmid pSPI12, accounting for a detection rate of 99.08%. Six strains were ipaJ negative because pSPI12 was not found in these strains according to whole genome sequencing results. There was no cross-reaction with other Salmonella serotypes, including Salmonella enterica serovar Gallinarum biovar Gallinarum (S. Gallinarum), which show a close genetic relationship with S. Pullorum. This shows that the PCR method could distinguish S. Gallinarum from S. Pullorum in one-step PCR without complicated biochemical identification. The limit of detection of this PCR method was as low as 90 fg/µl or 102 CFU, which shows a high sensitivity. Moreover, this method was applied to identify Salmonella isolated from the chicken farm and the results were consistent with what we obtained from biochemical reactions and serotyping. Together, all the results demonstrated that this one-step PCR method is simple and feasible to efficiently identify S. Pullorum.

Prediction task guided representation learning of medical codes in EHR.

There have been rapidly growing applications using machine learning models for predictive analytics in Electronic Health Records (EHR) to improve the quality of hospital services and the efficiency of healthcare resource utilization. A fundamental and crucial step in developing such models is to convert medical codes in EHR to feature vectors. These medical codes are used to represent diagnoses or procedures. Their vector representations have a tremendous impact on the performance of machine learning models. Recently, some researchers have utilized representation learning methods from Natural Language Processing (NLP) to learn vector representations of medical codes. However, most previous approaches are unsupervised, i.e. the generation of medical code vectors is independent from prediction tasks. Thus, the obtained feature vectors may be inappropriate for a specific prediction task. Moreover, unsupervised methods often require a lot of samples to obtain reliable results, but most practical problems have very limited patient samples. In this paper, we develop a new method called Prediction Task Guided Health Record Aggregation (PTGHRA), which aggregates health records guided by prediction tasks, to construct training corpus for various representation learning models. Compared with unsupervised approaches, representation learning models integrated with PTGHRA yield a significant improvement in predictive capability of generated medical code vectors, especially for limited training samples.

Influence of Salmonella enterica serovar Pullorum pathogenicity island 2 on type III secretion system effector gene expression in chicken macrophage HD11 cells.

Salmonella pathogenicity island 2 (SPI2) can encode type III secretion system 2 (T3SS2) which plays an important role in systemic disease development through delivering different effector proteins into host cells. Here, the influence of Salmonella Pullorum pathogenicity island 2 on T3SS2 effector gene expression was studied using qRT-PCR in chicken macrophage HD11 cells. Our results showed that all the detected genes (including pseudogenes sifB, sspH2 and steC) can express in HD11 cells of S. Pullorum infection; deletion of SPI2 of S. Pullorum did not significantly affect the expression of genes cigR, gtgA, slrP, sopD, sseK1, steB and steC, but had a significant effect on the expression of genes pipB2, sifB, sopD2, sseJ, sseL, sspH2, steD, sifA, pipB and steA at different degrees. These results suggest that SPI2 can significantly affect the expression of some T3SS2 effector genes. Some effectors may have secretion pathways other than T3SS2 and pseudogenes may play roles in the process of S. Pullorum infection.

Contributing factors of elective surgical case cancellation: a retrospective cross-sectional study at a single-site hospital.

BACKGROUND: Case cancellation (CC) has significant impact on the efficiency of operating room (OR) management, which can be mitigated by taking preventive measures. In this study, using the data of the West China Hospital (WCH), we identified the effect of contributing factors and recommended hospital interventions to facilitate CC prevention. METHOD: We conducted a retrospective review of 11,331 elective surgical cases from January 1 to December 31, 2014. CC reasons were grouped into six categories. The methods of descriptive statistics and hypothesis test were used to identify the effect of factors. RESULTS: CC reasons (746) were divided into six broad categories: workup related (preoperative diagnostic assessment issues or sudden medical condition changes) (25.8%), non-specified reasons (25.8%), coordination issues (15.1%), patient related (13.0%), support system issues (11.8%), and doctor related (8.5%). The types of the most frequently performed operations are identified, as well as their CRs. The cancellation rate (CR) of males was lower than that of females (16.7% to 18.3%). A large difference in the CRs existed among doctors. The CR on Monday was significantly higher than the other four weekdays. CONCLUSIONS: Workup related issues, the types of procedures, the menstrual cycle of females, highly imbalanced CRs among doctors, and tendency of cancellation on Monday are the major identified factors, which account for a significant amount of preventable cancellations. It is suggested that corresponding hospital interventions can reduce CR and improve OR efficiency, including maintaining effective coordination, good communication and well-designed preoperative assessment processes, focusing on the type of procedures which are more time-consuming and complex, paying special attention to the physiology of females during surgery planning, taking measures to reduce CR of top eight doctors, and improving surgery scheduling on Monday.

A Novel Transient Fault Current Sensor Based on the PCB Rogowski Coil for Overhead Transmission Lines.

The accurate detection of high-frequency transient fault currents in overhead transmission lines is the basis of malfunction detection and diagnosis. This paper proposes a novel differential winding printed circuit board (PCB) Rogowski coil for the detection of transient fault currents in overhead transmission lines. The interference mechanism of the sensor surrounding the overhead transmission line is analyzed and the guideline for the interference elimination is obtained, and then a differential winding printed circuit board (PCB) Rogowski coil is proposed, where the branch and return line of the PCB coil were designed to be strictly symmetrical by using a joining structure of two semi-rings and collinear twisted pair differential windings in each semi-ring. A serial test is conducted, including the frequency response, linearity, and anti-interference performance as well as a comparison with commercial sensors. Results show that a PCB Rogowski coil has good linearity and resistance to various external magnetic field interferences, thus enabling it to be widely applied in fault-current-collecting devices.

[Effects of Freezing and Thawing Treatments on Beef Protein Secondary Structure Analyzed with ATR-FTIR].

In order to further clarify the influence mechanism of different freezing temperature on meat quality in meat industry. The effects of freezing at -18, -23 and -38 ℃ on the stability of protein secondary structures of beef were studied. The attenuated total reflectance Fourier transfer infrared spectroscopy(ATR-FTIR)technique and automatic deconvolution, curve fitting and other calculation and analysis methods were used to analyze the changes of beef myofibrillar protein infrared spectra and secondary structures during -18, -23 and -38 ℃ freezing-thawing processes. ATR-FTIR results showed that the peak high and peak area of infrared spectra of beef myofibrillar protein in the freezing-thawing processes were changed, and the red shift or blue shift of wavenumbers occurred. The intensities of the absorption peak of 3 500~3 300 cm-1 in the infrared spectra of the frozen-thawed beef were reduced or even disappeared. This indicated that the intramolecular and intermolecular hydrogen bonding interactions, which formed by the bound water O­H group and the amino acid CO group, in thawed beef myofibrillar protein were broken. In other words, freezing can result in the destruction of beef myofibrillar protein secondary structures and protein advanced structures unfolded. Once the beef is thawed, the unfolded protein would reaggregation, and protein renaturation. Freezing could affect the stability of beef myofibrillar protein, the relative content of α-helix, ß-sheet, and ß-turn of beef myofibrillar protein were decreased, and the α-helix and ordered structures changed to the randon coil and disordered structures. After thawing, the increase of ß-sheet relative content of beef myofibrillar protein at -38 ℃ was greater than that of -23 and -18 ℃. The stability of -38 ℃ frozen beef myofibrillar protein was the best, and the protein renaturation was also the best after thawing. That is, the lower the freezing temperature, the lower the measure of freezing denaturation of beef myofibrillar protein, and the better the secondary structures stability of beef myofibrillar protein. The experimental study based on the actual production condition of the meat industry. And the effect of freezing temperatures on beef protein denaturation and the possible mechanism were revealed at the micro-aspect. It can be seen that the ATR-FTIR technology can reflect the changes of protein secondary structures in the process of freezing-thawing of beef, and reveal the regularity of beef protein denaturation, which can be used to identify and evaluate the quality of frozen meat. The experimental results provide a reference for the freezing preservation process and a method for the quality evaluation of meat.

INT-1B3, an LNP formulated miR-193a-3p mimic, promotes anti-tumor immunity by enhancing T cell mediated immune responses via modulation of the tumor microenvironment and induction of immunogenic cell death.

microRNAs (miRNAs) are small, non-coding RNAs that regulate expression of multiple genes. MiR-193a-3p functions as a tumor suppressor in many cancer types, but its effect on inducing specific anti-tumor immune responses is unclear. Therefore, we examined the effect of our lipid nanoparticle (LNP) formulated, chemically modified, synthetic miR-193a-3p mimic (INT-1B3) on anti-tumor immunity. INT-1B3 inhibited distant tumor metastasis and significantly prolonged survival. INT-1B3-treated animals were fully protected against challenge with autologous tumor cells even in absence of treatment indicating long-term immunization. Protection against autologous tumor cell challenge was hampered upon T cell depletion and adoptive T cell transfer abrogated tumor growth. Transfection of tumor cells with our miR-193a-3p mimic (1B3) resulted in tumor cell death and apoptosis accompanied by increased expression of DAMPs. Co-culture of 1B3-transfected tumor cells and immature DC led to DC maturation and these mature DC were able to stimulate production of type 1 cytokines by CD4+ and CD8+ T cells. CD4-CD8- T cells also produced type 1 cytokines, even in response to 1B3-transfected tumor cells directly. Live cell imaging demonstrated PBMC-mediated cytotoxicity against 1B3-transfected tumor cells. These data demonstrate for the first time that miR-193a-3p induces long-term immunity against tumor development via modulation of the tumor microenvironment and induction of immunogenic cell death.

Altered expression of sialylated glycoproteins in ovarian cancer sera using lectin-based ELISA assay and quantitative glycoproteomics analysis.

Herein, we identify and confirm differentially expressed sialoglycoproteins in the serum of patients with ovarian cancer. On the basis of Sambucus nigra (SNA) lectin enrichment and on an isobaric chemical labeling quantitative strategy, clusterin (CLUS), leucine-rich alpha-2-glycoprotein (LRG1), hemopexin (HEMO), vitamin D-binding protein (VDB), and complement factor H (CFH) were found to be differentially expressed in the serum of patients with ovarian cancer compared to benign diseases. The abnormal sialylation levels of CLUS, CFH, and HEMO in serum of ovarian cancer patients were verified by a lectin-based ELISA assay. ELISA assays were further applied to measure total protein level changes of these glycoproteins. Protein levels of CLUS were found to be down-regulated in the serum of ovarian cancer patients, while protein levels of LRG1 were increased. The combination of CLUS and LRG1 (AUC = 0.837) showed improved performance for distinguishing stage III ovarian cancer from benign diseases compared to CA125 alone (AUC = 0.811). In differentiating early stage ovarian cancer from benign diseases or healthy controls, LRG1 showed comparable performance to CA125. An independent sample set was further used to confirm the ability of these candidate markers to detect patients with ovarian cancer. Our study provides a comprehensive strategy for the identification of candidate biomarkers that show the potential for diagnosis of ovarian cancer. Further studies using a large number of samples are necessary to validate the utility of this panel of proteins.

Isolation and characterization of a novel PDR-type ABC transporter gene PgPDR3 from Panax ginseng C.A. Meyer induced by methyl jasmonate.

In order to screen novel genes involved in the biosynthesis and accumulation of ginsenosides in ginseng for investigating the molecular mechanism of ginsenosides accumulation, the differential expression analysis was performed by cDNA-amplified fragment length polymorphism (cDNA-AFLP) in methyl jasmonate (MeJA) treated ginseng suspension cells and untreated controls. Twenty-five transcript-derived-fragments (TDFs) were obtained and 14 of them was involved in secondary metabolite biosynthesis, transportation, signal transduction and stress response. PgTDF3 (JK974248) was detected in MeJA-treated ginseng cells and its full-length cDNA was subsequently isolated. The gene designated PgPDR3 (GenBank accession number KC013238) has 4515 bp in length containing a 4137 bp open reading frame (ORF). The deduced amino acid sequence of PgPDR3 shares high similarity to other plant pleiotropic drug resistance (PDR) transporters and have the characteristic domain of plant PDR transporter Walker A, Walker B and ABC signature both at the N- and C-terminal ends respectively. RT-PCR and quantitative real-time PCR (qRT-PCR) analysis indicated that PgPDR3 was expressed at a high level in the roots and adventitious roots compared to leaves, seeds and buds, and the expression was induced strongly by MeJA in a time-dependent manner, as it is well known MeJA is a signaling molecule that mediates the biosynthesis and accumulation of secondary metabolites. These results demonstrate a potential role of the PgPDR3 gene in the accumulation of secondary metabolites in MeJA-induced ginseng.