Use of a glycomics array to establish the anti-carbohydrate antibody repertoire in type 1 diabetes.

Type 1 diabetes (T1D) is an autoimmune disease, characterized by the presence of autoantibodies to protein and non-protein antigens. Here we report the identification of specific anti-carbohydrate antibodies (ACAs) that are associated with pathogenesis and progression to T1D. We compare circulatory levels of ACAs against 202 glycans in a cross-sectional cohort of T1D patients (n = 278) and healthy controls (n = 298), as well as in a longitudinal cohort (n = 112). We identify 11 clusters of ACAs associated with glycan function class. Clusters enriched for aminoglycosides, blood group A and B antigens, glycolipids, ganglio-series, and O-linked glycans are associated with progression to T1D. ACAs against gentamicin and its related structures, G418 and sisomicin, are also associated with islet autoimmunity. ACAs improve discrimination of T1D status of individuals over a model with only clinical variables and are potential biomarkers for T1D.

Diagnostic and Prognostic Biomarkers in Renal Clear Cell Carcinoma.

Renal clear cell carcinoma (ccRCC) comprises over 75% of all renal tumors and arises in the epithelial cells of the proximal convoluted tubule. Molecularly ccRCC is characterized by copy number alterations (CNAs) such as the loss of chromosome 3p and VHL inactivation. Additional driver mutations (SETD2, PBRM1, BAP1, and others) promote genomic instability and tumor cell metastasis through the dysregulation of various metabolic and immune-response pathways. Many researchers identified mutation, gene expression, and proteomic signatures for early diagnosis and prognostics for ccRCC. Despite a tremendous influx of data regarding DNA alterations, gene expression, and protein expression, the incorporation of these analyses for diagnosis and prognosis of RCC into the clinical application has not been implemented yet. In this review, we focused on the molecular changes associated with ccRCC development, along with gene expression and protein signatures, to emphasize the utilization of these molecular profiles in clinical practice. These findings, in the context of machine learning and precision medicine, may help to overcome some of the barriers encountered for implementing molecular profiles of tumors into the diagnosis and treatment of ccRCC.

Oncocytoma-Related Gene Signature to Differentiate Chromophobe Renal Cancer and Oncocytoma Using Machine Learning.

Publicly available gene expression datasets were analyzed to develop a chromophobe and oncocytoma related gene signature (COGS) to distinguish chRCC from RO. The datasets GSE11151, GSE19982, GSE2109, GSE8271 and GSE11024 were combined into a discovery dataset. The transcriptomic differences were identified with unsupervised learning in the discovery dataset (97.8% accuracy) with density based UMAP (DBU). The top 30 genes were identified by univariate gene expression analysis and ROC analysis, to create a gene signature called COGS. COGS, combined with DBU, was able to differentiate chRCC from RO in the discovery dataset with an accuracy of 97.8%. The classification accuracy of COGS was validated in an independent meta-dataset consisting of TCGA-KICH and GSE12090, where COGS could differentiate chRCC from RO with 100% accuracy. The differentially expressed genes were involved in carbohydrate metabolism, transcriptomic regulation by TP53, beta-catenin-dependent Wnt signaling, and cytokine (IL-4 and IL-13) signaling highly active in cancer cells. Using multiple datasets and machine learning, we constructed and validated COGS as a tool that can differentiate chRCC from RO and complement histology in routine clinical practice to distinguish these two tumors.

T1DMicro: A Clinical Risk Calculator for Type 1 Diabetes Related Microvascular Complications.

Development of complications in type 1 diabetes patients can be reduced by modifying risk factors. We used a cross-sectional cohort of 1646 patients diagnosed with type 1 diabetes (T1D) to develop a clinical risk score for diabetic peripheral neuropathy (DPN), autonomic neuropathy (AN), retinopathy (DR), and nephropathy (DN). Of these patients, 199 (12.1%) had DPN, 63 (3.8%) had AN, 244 (14.9%) had DR, and 88 (5.4%) had DN. We selected five variables to include in each of the four microvascular complications risk models: age, age of T1D diagnosis, duration of T1D, and average systolic blood pressure and HbA1C over the last three clinic visits. These variables were selected for their strong evidence of association with diabetic complications in the literature and because they are modifiable risk factors. We found the optimism-corrected R2 and Harrell's C statistic were 0.39 and 0.87 for DPN, 0.24 and 0.86 for AN, 0.49 and 0.91 for DR, and 0.22 and 0.83 for DN, respectively. This tool was built to help inform patients of their current risk of microvascular complications and to motivate patients to control their HbA1c and systolic blood pressure in order to reduce their risk of these complications.

Applying Artificial Intelligence to Gynecologic Oncology: A Review.

IMPORTANCE: Artificial intelligence (AI) will play an increasing role in health care. In gynecologic oncology, it can advance tailored screening, precision surgery, and personalized targeted therapies. OBJECTIVE: The aim of this study was to review the role of AI in gynecologic oncology. EVIDENCE ACQUISITION: Artificial intelligence publications in gynecologic oncology were identified by searching "gynecologic oncology AND artificial intelligence" in the PubMed database. A review of the literature was performed on the history of AI, its fundamentals, and current applications as related to diagnosis and treatment of cervical, uterine, and ovarian cancers. RESULTS: A PubMed literature search since the year 2000 showed a significant increase in oncology publications related to AI and oncology. Early studies focused on using AI to interrogate electronic health records in order to improve clinical outcome and facilitate clinical research. In cervical cancer, AI algorithms can enhance image analysis of cytology and visual inspection with acetic acid or colposcopy. In uterine cancers, AI can improve the diagnostic accuracies of radiologic imaging and predictive/prognostic capabilities of clinicopathologic characteristics. Artificial intelligence has also been used to better detect early-stage ovarian cancer and predict surgical outcomes and treatment response. CONCLUSIONS AND RELEVANCE: Artificial intelligence has been shown to enhance diagnosis, refine clinical decision making, and advance personalized therapies in gynecologic cancers. The rapid adoption of AI in gynecologic oncology will depend on overcoming the challenges related to data transparency, quality, and interpretation. Artificial intelligence is rapidly transforming health care. However, many physicians are unaware that this technology is being used in their practices and could benefit from a better understanding of the statistics and computer science behind these algorithms. This review provides a summary of AI, its applicability, and its limitations in gynecologic oncology.

Serum Levels of Inflammatory Proteins Are Associated With Peripheral Neuropathy in a Cross-Sectional Type-1 Diabetes Cohort.

Chronic low-grade inflammation is involved in the pathogenesis of type-1 diabetes (T1D) and its complications. In this cross-section study design, we investigated association between serum levels of soluble cytokine receptors with presence of peripheral neuropathy in 694 type-1 diabetes patients. Sex, age, blood pressure, smoking, alcohol intake, HbA1c and lipid profile, presence of DPN (peripheral and autonomic), retinopathy and nephropathy was obtained from patient's chart. Measurement of soluble cytokine receptors, markers of systemic and vascular inflammation was done using multiplex immunoassays. Serum levels were elevated in in DPN patients, independent of gender, age and duration of diabetes. Crude odds ratios were significantly associated with presence of DPN for 15/22 proteins. The Odds ratio (OR) remained unchanged for sTNFRI (1.72, p=0.00001), sTNFRII (1.45, p=0.0027), sIL2Rα (1.40, p=0.0023), IGFBP6 (1.51, p=0.0032) and CRP (1.47, p=0.0046) after adjusting for confounding variables, HbA1C, hypertension and dyslipidemia. Further we showed risk of DPN is associated with increase in serum levels of sTNFRI (OR=11.2, p<10), sIL2Rα (8.69, p<10-15), sNTFRII (4.8, p<10-8) and MMP2 (4.5, p<10-5). We combined the serum concentration using ridge regression, into a composite score, which can stratify the DPN patients into low, medium and high-risk groups. Our results here show activation of inflammatory pathway in DPN patients, and could be a potential clinical tool to identify T1D patients for therapeutic intervention of anti-inflammatory therapies.

Tumor-intrinsic and -extrinsic (immune) gene signatures robustly predict overall survival and treatment response in high grade serous ovarian cancer patients.

In the present study, we developed a transcriptomic signature capable of predicting prognosis and response to primary therapy in high grade serous ovarian cancer (HGSOC). Proportional hazard analysis was performed on individual genes in the TCGA RNAseq data set containing 229 HGSOC patients. Ridge regression analysis was performed to select genes and develop multigenic models. Survival analysis identified 120 genes whose expression levels were associated with overall survival (OS) (HR = 1.49-2.46 or HR = 0.48-0.63). Ridge regression modeling selected 38 of the 120 genes for development of the final Ridge regression models. The consensus model based on plurality voting by 68 individual Ridge regression models classified 102 (45%) as low, 23 (10%) as moderate and 104 patients (45%) as high risk. The median OS was 31 months (HR = 7.63, 95% CI = 4.85-12.0, P < 1.0-10) and 77 months (HR = ref) in the high and low risk groups, respectively. The gene signature had two components: intrinsic (proliferation, metastasis, autophagy) and extrinsic (immune evasion). Moderate/high risk patients had more partial and non-responses to primary therapy than low risk patients (odds ratio = 4.54, P < 0.001). We concluded that the overall survival and response to primary therapy in ovarian cancer is best assessed using a combination of gene signatures. A combination of genes which combines both tumor intrinsic and extrinsic functions has the best prediction. Validation studies are warranted in the future.

Retrospective Validation of a 168-Gene Expression Signature for Glioma Classification on a Single Molecule Counting Platform.

Gene expression profiling has been shown to be comparable to other molecular methods for glioma classification. We sought to validate a gene-expression based glioma classification method. Formalin-fixed paraffin embedded tissue and flash frozen tissue collected at the Augusta University (AU) Pathology Department between 2000-2019 were identified and 2 mm cores were taken. The RNA was extracted from these cores after deparaffinization and bead homogenization. One hundred sixty-eight genes were evaluated in the RNA samples on the nCounter instrument. Forty-eight gliomas were classified using a supervised learning algorithm trained by using data from The Cancer Genome Atlas. An ensemble of 1000 linear support vector models classified 30 glioma samples into TP1 with classification confidence of 0.99. Glioma patients in TP1 group have a poorer survival (HR (95% CI) = 4.5 (1.3-15.4), p = 0.005) with median survival time of 12.1 months, compared to non-TP1 groups. Network analysis revealed that cell cycle genes play an important role in distinguishing TP1 from non-TP1 cases and that these genes may play an important role in glioma survival. This could be a good clinical pipeline for molecular classification of gliomas.

Are There Survival Differences Between Women with Equivalent Residual Disease After Interval Cytoreductive Surgery Compared with Primary Cytoreductive Surgery for Advanced Ovarian and Peritoneal Cancer?

OBJECTIVE: The aim of this study was to investigate survival differences between equivalent residual disease [complete gross resection (CGR), minimal residual disease (MRD), suboptimal] at the time of primary debulking surgery (PDS) and interval debulking surgery (IDS). METHODS: The National Cancer Database was used to identify patients from 2010 to 2015 with stage IIIC/IV primary peritoneal or ovarian cancer who had residual disease recorded. Propensity score matching (PSM) was used to correct for differences in characteristics between the PDS and IDS groups. RESULTS: Of 8683 patients with advanced ovarian cancer, 4493 (52%), 2546 (29%), and 1644 (19%) had CGR, MRD, or suboptimal resection, respectively. From 2010 to 2015, the number of patients undergoing IDS increased 27% (ptrend < 0.001), and there was an 18% increase in CGRs (ptrend = 0.005). The increased use of IDS from 2010 to 2015 was associated with increased CGRs (ptrend = 0.02) and decreased MRD (ptrend = 0.001), but not with decreased suboptimal resections (ptrend = 0.18). IDS, even after PSM, was associated with inferior overall survival [OS; hazard ratio (HR) 1.12, 95% confidence interval (CI) 1.03-1.22, p = 0.008]. A CGR at PDS had prolonged median OS compared with a CGR at IDS (51 vs. 44 months, p < 0.001). Additionally, MRD at PDS had worse median OS compared with a CGR at IDS (41 vs. 44 months, p = 0.03), but improved median OS compared with MRD at IDS (median OS 35 months, p = 0.05). CONCLUSION: The use of IDS continues to rise in the US, and is associated with improved surgical outcomes but not necessarily similar oncologic outcomes. There should be continued efforts to improve cytoreductive outcomes in women with advanced ovarian and peritoneal malignancies.

Comparative analysis of transcriptomic profile, histology, and IDH mutation for classification of gliomas.

Gliomas are currently classified through integration of histology and mutation information, with new developments in DNA methylation classification. However, discrepancies exist amongst the major classification methods. This study sought to compare transcriptome-based classification to the established methods. RNAseq and microarray data were obtained for 1032 gliomas from the TCGA and 395 gliomas from REMBRANDT. Data were analyzed using unsupervised and supervised learning and other statistical methods. Global transcriptomic profiles defined four transcriptomic glioma subgroups with 91.4% concordance with the WHO-defined mutation subtypes. Using these subgroups, 168 genes were selected for the development of 1000 linear support vector classifiers (LSVC). Based on plurality voting of 1000 LSVC, the final ensemble classifier confidently classified all but 17 TCGA gliomas to one of the four transcriptomic profile (TP) groups. The classifier was validated using a gene expression microarray dataset. TP1 cases include IDHwt, glioblastoma high immune infiltration and cellular proliferation and poor survival prognosis. TP2a is characterized as IDHmut-codel, oligodendrogliomas with high tumor purity. TP2b tissue is mostly composed of neurons and few infiltrating malignant cells. TP3 exhibit increased NOTCH signaling, are astrocytoma and IDHmut-non-codel. TP groups are highly concordant with both WHO integrated histology and mutation classification as well as methylation-based classification of gliomas. Transcriptomic profiling provides a robust and objective method to classify gliomas with high agreement to the current WHO guidelines and may provide additional survival prediction to the current methods.

Senescence-Associated Secretory Phenotype Determines Survival and Therapeutic Response in Cervical Cancer.

Molecular biomarkers that can predict survival and therapeutic outcome are still lacking for cervical cancer. Here we measured a panel of 19 serum proteins in sera from 565 patients with stage II or III cervical cancer and identified 10 proteins that have an impact on disease specific survival (DSS) (Hazzard's ratio; HR = 1.51-2.1). Surprisingly, all ten proteins are implicated in senescence-associated secreted phenotype (SASP), a hallmark of cellular senescence. Machine learning using Ridge regression of these SASP proteins can robustly stratify patients with high SASP, which is associated with poor survival, and patients with low SASP associated with good survival (HR = 3.09-4.52). Furthermore, brachytherapy, an effective therapy for cervical cancer, greatly improves survival in SASP-high patients (HR = 3.3, p < 5 × 10-5) but has little impact on survival of SASP-low patients (HR = 1.5, p = 0.31). These results demonstrate that cellular senescence is a major determining factor for survival and therapeutic response in cervical cancer and suggest that senescence reduction therapy may be an efficacious strategy to improve the therapeutic outcome of cervical cancer.

Identification of a transcriptomic signature with excellent survival prediction for squamous cell carcinoma of the cervix.

Survival for patients with newly diagnosed cervical cancer has not significantly improved over the past several decades. We sought to identify a clinically relevant set of prognostic genes for squamous cell carcinoma of the cervix (SCCC), the most common cervical cancer subtype. Using RNA-sequencing data and survival data from 203 patients in The Cancer Genome Atlas (TCGA), we conducted a series of analyses using different decile cutoffs for gene expression to identify genes that could indicate large and consistent survival differences across different decile cutoffs of gene expression. Those analyses identified 42 high-risk genes. A patient's survivability could be estimated by simply counting the number of high-risk genes with extremely high expression (above the 90th percentile) or estimating a transcriptomic risk score (TRS) using a machine learning algorithm with 9 of the 42 genes. On multivariate analysis, the significant predictors of mortality included high TRS (HR = 44.8), stage IV (HR = 28.1), intermediate TRS (HR = 4.75), and positive lymph node status (HR = 2.92). Approximately 18% of earlier-stage patients were identified as a poor-prognosis subgroup with high TRS. In patients with SCCC, transcriptomic risk appears to better predict survival than clinical prognostic factors, including stage.

A 73-gene proliferative transcriptomic signature predicts uterine serous carcinoma patient survival and response to primary therapy.

OBJECTIVES: To develop a transcriptomic signature capable of predicting overall survival (OS) for uterine serous carcinoma (USC). METHODS: RNAseq data for 58 USC patients were obtained from TCGA. Expression of 73 candidate genes was measured for 67 Augusta University (AU) samples using NanoString technology. RESULTS: Analysis of the TCGA RNAseq data identified 73 genes that individually predict prognosis for USC patients and an elastic net model with all 73 genes (USC73) distinguishes a good OS group with low USC73 score from a poor OS group with high USC73 score (5-year OS = 83.3% and 13.3% respectively, HR = 40.1; p = 3 × 10-8). This finding was validated in the independent AU cohort (HR = 4.3; p = 0.0004). The poor prognosis group with high USC73 score consists of 37.9% and 32.8% of patients in the TCGA and AU cohort respectively. USC73 score and pathologic stage independently contribute to OS and together provide the best prognostic value. Early stage, low USC73 patients have the best prognosis (5-year OS = 85.1% in the combined dataset), while advanced stage, high USC73 patients have the worst prognosis (5-year OS = 6.4%, HR = 30.5, p = 1.2 × 10-12). Consistent with the observed poor survival, primary cell cultures from high USC73 patients had higher proliferation rate and cell cycle progression; and high USC73 patients had lower rates of complete response to standard therapy. CONCLUSIONS: The USC73 transcriptomic signature and stage independently predict OS of USC patients and the best prediction is achieved using USC73 and stage. USC73 may also serve as a therapeutic biomarker to guide patient care.

Better survival is observed in cervical cancer patients positive for specific anti-glycan antibodies and receiving brachytherapy.

OBJECTIVE: To measure anti-glycan antibodies (AGA) in cervical cancer (CC) patient sera and assess their effect on therapeutic outcome. PATIENTS AND METHODS: Serum AGA was measured in 276 stage II and 292 stage III Peruvian CC patients using a high content and throughput Luminex multiplex glycan array (LMGA) containing 177 glycans. Association with disease-specific survival (DSS) and progression free survival (PFS) were analyzed using Cox regression. RESULTS: AGAs were detected against 50 (28.3%) of the 177 glycans assayed. Of the 568 patients, 84.5% received external beam radiation therapy (EBRT) plus brachytherapy (BT), while 15.5% only received EBRT. For stage-matched patients (Stage III), receiving EBRT alone was significantly associated with worse survival (HR 6.4, p < 0.001). Stage III patients have significantly worse survival than Stage II patients after matching for treatment (HR = 2.8 in EBRT+BT treatment group). Furthermore, better PFS and DSS were observed in patients positive for AGA against multiple glycans belonging to the blood group H, Lewis, Ganglio, Isoglobo, lacto and sialylated tetrarose antigens (best HR = 0.49, best p = 0.0008). CONCLUSIONS: Better PFS and DSS are observed in cervical cancer patients that are positive for specific antiglycan antibodies and received brachytherapy.

Binding of Campylobacter jejuni FliW Adjacent to the CsrA RNA-Binding Pockets Modulates CsrA Regulatory Activity.

Campylobacter jejuni CsrA is an mRNA-binding, post-transcriptional regulator that controls many metabolic- and virulence-related characteristics of this important pathogen. In contrast to E. coli CsrA, whose activity is modulated by binding to small non-coding RNAs (sRNAs), C. jejuni CsrA activity is controlled by binding to the CsrA antagonist FliW. In this study, we identified the FliW binding site on CsrA. Deletion of the C-terminus of C. jejuni CsrA, which is extended relative to sRNA-binding CsrA proteins, abrogated FliW binding. Bacterial two-hybrid experiments were used to assess the interaction of FliW with wild-type CsrA and mutants thereof, in which every amino acid was individually mutated. Two CsrA mutations (V51A and N55A) resulted in a significant decrease in FliW binding. The V51A and N55A mutants also showed a decrease in CsrA-FliW complex formation, as assessed by size-exclusion chromatography and surface plasmon resonance. These residues were highly conserved in bacterial species containing CsrA orthologs whose activities are predicted to be regulated by FliW. The location of FliW binding was immediately adjacent to the two RNA-binding sites of the CsrA homodimer, suggesting the model that FliW binding to CsrA modulates its ability to bind to its mRNA targets either by steric hindrance, electrostatic repulsion, or by altering the overall structure of the RNA-binding sites.

A combined score of clinical factors and serum proteins can predict time to recurrence in high grade serous ovarian cancer.

OBJECTIVE: To investigate the utility of a combined panel of protein biomarkers and clinical factors to predict recurrence in serous ovarian cancer patients. METHODS: Women at Augusta University diagnosed with ovarian cancer were enrolled between 2005 and 2015 (n = 71). Blood was drawn at enrollment and follow-up visits. Patient serum collected at remission was analyzed using the SOMAscan array (n = 35) to measure levels of 1129 proteins. The best 26 proteins were confirmed using Luminex assays in the same 35 patients and in an additional 36 patients (ntotal = 71) as orthogonal validation. The data from these 26 proteins was combined with clinical factors using an elastic net multivariate model to find an optimized combination predictive of progression-free survival (PFS). RESULTS: Of the 26 proteins, Brain Derived Neurotrophic Factor and Platelet Derived Growth Factor molecules were significant for predicting PFS on both univariate and multivariate analyses. All 26 proteins were combined with clinical factors using the elastic net algorithm. Ten components were determined to predict PFS (HR of 6.55, p-value 1.12 × 10-6, CI 2.57-16.71). This model was named the serous high grade ovarian cancer (SHOC) score. CONCLUSION: The SHOC score can predict patient prognosis in remission. This tool will hopefully lead to early intervention and consolidation therapy strategies in remission patients destined to recur.

Uptake of human papillomavirus (HPV) vaccination in Hong Kong: Facilitators and barriers among adolescent girls and their parents.

The present study is aimed at assessing the feasibility of delivering the HPV (human papillomavirus) vaccine to girls through a school-based program in Hong Kong, as well as to examine the facilitators and barriers associated with their participation. We approached 1,229 eligible girls aged 9 to 14 at eight schools in Hong Kong to join the program and then delivered the bivalent HPV vaccine at 0 and 6 months over the course of one school year. The students and their parents completed separate questionnaires to indicate their decision on whether or not to participate, and to assess their knowledge of cervical cancer and the HPV vaccine. The overall vaccine uptake was 81.4% (1,000/1,229) for the first dose and 80.8% (993/1,229) for the second dose. Parents and students were given separate questionnaires and asked whether or not they would like to participate in the vaccination program. 87.1% (1,010/1,160) of parents and 84.9% (974/1,147) of students indicated that they would join the program. The reasons associated with parents' decision not to vaccinate their daughters primarily included concerns around side effects and safety. Multivariate regression analysis showed that parents who thought that the vaccine would protect their daughter from getting cervical cancer (OR = 3.16, 95% CI = 1.39-7.15, p < .01), and those who reported having a doctor's recommendation (OR = 4.54, 95% CI = 1.05-19.57, p < .05) were more likely to join the program. In contrast, parents who had never heard of the vaccine (OR = .15, 95% CI = .03-.71, p < .02), those who were willing to pay more than HK$2,000 for the vaccine (OR = .39, 95% CI = .19-.81, p < .05), or had a preference to access it through a private clinic (OR = .44, 95% CI = .26-.75, p < .01) were significantly less likely to allow their daughter to join the program. Delivery of the HPV vaccine with high uptake rate in a school setting is feasible in Hong Kong. Engaging key stakeholders including school administrators, teachers and community physicians, and providing relevant information on safety and vaccine effectiveness to parents were important to the success of the program.

A lost tribe in the city: health status and needs of African asylum seekers and refugees in Hong Kong.

BACKGROUND: Hong Kong's resistance to be a signatory of the 1951 Geneva Convention and lack of domestic policies in this area has resulted in restrictions on access to healthcare amongst asylum seekers and refugees (ASRs). Using social determinants of health framework this study sought to identify health practices, problems and needs of African ASRs in Hong Kong. METHODS: A cross-sectional survey comprising of six domains including health status, health-seeking behaviour and social experience targeted at adult African ASRs in Hong Kong was conducted through three local non-governmental organisations between February and April 2013. Outpatient care and inpatient care in the past 12 months were used as proxy measures of general and severe ill health respectively. Associations between the determinants of health factors with general or severe health was explored through logistic regressions. RESULTS: Majority of 374 participants were young, single, educated males having been in Hong Kong for over 5 years. A third of ARS (36.1 %) screened positive for depression. Most reported problems related to basic necessities (64.7-78.6 %) and access to health services (72.2 %). ASRs with relatively less education, health awareness or higher risk behaviours were less likely to have obtained outpatient or inpatient services. African ASRs reporting problems with case officers (aOR = 2.80; 95 % CI = 1.35-5.79) or illness in the past 30 days (aOR = 6.00; 95 % CI = 2.94-12.25) were more likely to report general ill health. Similarly, problems with the case officers (aOR = 3.76; 95 % CI = 1.97-7.18) and self-reported illness in the past 30 days (a​OR = 3.32; 95 % CI= 1.68-6.57) were also significantly associated with severe ill health. At the health system level, those who reported experiencing difficulties accessing the medical services in Hong Kong are 3.29 (95 % CI = 1.48-7.31) and 4.12 (95 % CI = 1.73-9.79) times as likely to report general and severe ill health respectively. CONCLUSION: The host government should have moral and ethical obligations to attend to the health needs of ASRs. Evidently a number of structural and health system factors have significantly impacted the health of African ASRs in Hong Kong. Changes to current policies regarding how African ASRs are handled whilst in Hong Kong but, more immediately, improvements in healthcare access are needed.

Psychological health and HIV transmission among female sex workers: a systematic review and meta-analysis.

Current HIV prevention interventions for female sex workers (FSWs) have tended to target the cognitive factors in changing their behaviors, yet little attention has been paid to the psychological factors that influence the behavior of women in sex work. This review aimed to explore the associations between the psychological health of FSWs and HIV risk. A total of eight studies published in English before July 2013 were identified and reviewed. FSWs had reported psychological issues, including depression, suicidal thoughts as well as lower quality of life, and the pooled prevalence of probable depression was as high as 62.4%. The majority of studies showed that higher scores in psychological health problems were associated with increased HIV risk behavior, in particular inconsistent condom use, or sexually transmitted infections. Among the five studies which measured symptoms of depression, four documented that higher depression scores were significantly associated with inconsistent condom use among FSWs with their clients and/or partners. Meta-analysis using a fixed-effects model was performed to examine the association between depression and inconsistent condom use and found that higher scores in depression were significantly associated with inconsistent condom use (odds ratio = 2.57, p < .001). This review contends that future HIV preventive interventions should take psychological health of FSWs into consideration.

Bacterial diversity and Clostridia abundance decrease with increasing severity of necrotizing enterocolitis.

BACKGROUND: Necrotizing enterocolitis (NEC) is a devastating neonatal gastrointestinal disease that primarily affects premature infants. It is characterized by bowel inflammation and necrosis. In spite of extensive research, there has been little progress in decreasing the incidence or mortality of NEC over the past three decades. The exact etiology of NEC has not been identified. However, it is believed to result from an inappropriate immune response to gut microbiota. Using 454-pyrosequencing analyses of 16S rRNA genes that were PCR-amplified from stool DNA specimens, we compared the gut microbiota of infants with NEC to matched controls without NEC. The infants with NEC were then categorized into three subgroups based on severity: mild, severe, and lethal. We compared the microbiota among these subgroups and between each severity group and appropriate controls. RESULTS: Bacterial diversity and the relative abundance of Actinobacteria and Clostridia were significantly lower in NEC specimens compared to controls. The absence of Clostridia was significantly associated with NEC. Microbial diversity and Clostridia abundance and prevalence decreased with increasing severity of NEC. CONCLUSIONS: Low bacterial diversity in stool specimens may be indicative of NEC and the severity of NEC. The low bacterial diversity, and the lack of Clostridia in lethal specimens, could indicate that the presence of a diverse bacterial population in the gut as well as the presence of taxa such as Clostridia may play a role in attenuating inflammation leading to NEC.